Advances in Agronomy, Volume 28

AD VANCES IN

AGRONOMY VOLUME 28

CONTRIBUTORS TO THIS VOLUME

RODNEY J. ARKLEY A.

v. BARKER

JOHN

E. BEGG

J. M. BREMNER

C.M. DONALD L. T. EVANS E. A. N. GREENWOOD J. HAMBLIN

R. D . HAUCK D . N . MAYNARD

P. L. MINOTTI N.

H. PECK

G . C.M.SAGE NEILC. TURNER INDRA

K.VASIL

I. F. WARDLAW

ADVANCES IN

AGRONOMY Prepared under the Auspices of the

AMERICANSOCIETY OF AGRONOMY

VOLUME 28 Edited by N. C . BRADY International Rice Research Institute Manila, Philippines

ADVISORY BOARD

w. L COLVILLE, CHAIRMAN G. W. KUNZE D. G. BAKER D. E WEIBEL G. R DUTT H J. GORZ M, STELLY, EX OFFICIO, ASA Headquarters 1976

ACADEMIC PRESS 0 New York

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ISBN 0-12-000728-2 PRINTED IN THE UNITED STATES OF AMERICA

CONTENTS

............................ PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CONTRIBUTORS TO VOLUME 28

ix xi

NITROGEN STRESS IN PLANTS

E . A. N . Greenwood

I . Introduction .......................................... 1 Quantitative Concepts of Nutrient Deficiency . . . . . . . . . . . . . . . . . 2 Nitrogen Stress ........................................ 7 Factors Affecting Nitrogen Stress .......................... 14 Alternative Evaluators of Nitrogen Stress .................... 18 Applications .......................................... 28 Conclusions and Aspirations .............................. 34 References ............................................ 34

I1. 111. IV . V. VI . VII .

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

Rodney J . Arkley

I . Introduction: Objectives and Problems of Soil Classification

.....

I1. Numerical Taxonomy or Cluster Analysis of Soils .............. I11. Ordination of Soils .....................................

IV. Soil as an Anisotropic Entity .............................. V . Statistical Methods for Comparing Classification ............... VI . Conclusions and Evaluation ............................... References ............................................

37 39 54 59 63 64 68

NITRATE ACCUMULATION IN VEGETABLES

D. N . Maynard. A. V. Barker. P . L.Minotti. and N . H .Peck I . Introduction .......................................... 71 I1. Hazards of Nitrate and Nitrite to Human Health ............... 72 I11. Factors Affecting Nitrate Accumulation ..................... 77

IV. Nitrate Concentrations in Vegetables ....................... V . Conclusions ........................................... References ............................................ V

99 113 114

vi

CONTENTS

THE PROGRESS. PROBLEMS. AND PROSPECTS O F PLANT PROTOPLAST RESEARCH

Indra K . Vasil I. I1. 111. IV. V.

Introduction .......................................... Isolation of Protoplasts .................................. Culture of Protoplasts ................................... Protoplasts and the Genetic Modification of Plants ............. TheFuture ........................................... References ............................................

119 120 126 135 152 153

CROP WATER DEFICITS

John E . Begg and Neil C.Turner

.......................................... ..................................... Measurement of Crop Water Status ......................... Effects of Water Deficits on Crop Growth and Development ..... Adaptation to Water Deficits .............................. Effects of Water Deficits on Yield .......................... Water Use Efficiency ....................................

I . Introduction

I1. Evapotranspiration

.

111

161 163 167 170 182 188 195

IV. V. VI . VII . VIII. Difference in Response of Plants Grown Under Controlled Conditions and in the Field ............................... 202 205 IX. Summary and Conclusions ............................... References ............................................ 207

USE OF TRACERS FOR SO1 L AND FERTILIZER NITROGEN RESEARCH

R . D. Hauck and J .M . Bremner I . Introduction .......................................... I1. Assumptions .......................................... 111. Advantages and Disadvantages of Nitrogen Tracer Techniques .... IV . Determination of Nitrogen Isotopes ........................ V. Sources and Cost of Nitrogen Tracer Materials ................ VI . Use of Nitrogen Tracer Materials ........................... VII . Perspective ........................................... References ............................................

219 223 225 226 239 242 260 261

CONTENTS

vii

NUCLEO-CYTOPLASM IC RELATIONSHIPS IN WHEAT

. .

G. C M Sage 1. Introduction

.......................................... I1. Cytoplasmic Variation in Wheat ........................... 111. The Genetics of Fertility Restoration ....................... IV . Cytoplasmic Effects Other than Male Sterility ................ V . The Biological Basis of Nucleo-cytoplasmic Interactions ......... VI . Cytoplasmic Variation in the Absence of Male Sterility ......... VII . Conclusion ........................................... References ............................................

267 268 274 286 290 295 296 297

ASPECTS OF THE COMPARATIVE PHYSIOLOGY OF GRAIN YIELD IN CEREALS

. .

L T Evans and I . F.Wardlaw

I . Introduction .......................................... I1. Origins and Adaptation .................................. 111. Reproductive Development ............................... IV. Root Growth and Nutrient Use ............................ V . Canopy Growth ........................................ VI . Leaf Photosynthesis .................................... VII . Canopy Photosynthesis .................................. VIII . Translocation ......................................... IX . GrainGrowth ......................................... X . Limiting Stages in the Life Cycle ........................... XI . Conclusion ........................................... References ............................................

301 303 305 310 315 317 323 329 335 340 349 350

THE BIOLOGICAL YIELD AND HARVEST INDEX OF CEREALS AS AGRONOMIC AND PLANT BREEDING CRITERIA

C. M . Donald and J . Hamblin

I . Introduction .......................................... 361 I1. The Relationship of Biological Yield. Grain Yield. and Harvest Index to Each Other and to Other Plant Characteristics ......... 364

viii

CONTENTS

111. The Influence of Environmental Factors ..................... IV. Biological Yield and Harvest Index as Criteria in Cereal Breeding . . V . Concluding Comments .................................. References ............................................ SUBJECTINDEX

.......................................

375 390 402 404 407

CONTRIBUTORS Numbers in parentheses indicate the pages on which the authors’ contributionsbegin.

RODNEY J. ARKLEY (37), Department of Soils and Plant Nutrition, College of Natural Resources, University of California,Berkeley, California A. V . BARKER (71), Department of Plant and Soil Sciences, University of Massachusetts, Amherst, Massachusetts JOHN E. BEGG (161), CSIRO Division of Plant Industry, anbema, A.C.T., Australia J . M. BREMNER (219), Department of Agronomy, Iowa State University, Ames, Iowa C. M. DONALD (361), Waite Agricultural Research Institute, University of Adelaide, South Australia, and Department of Applied Biology. University of Cambridge, England L. T. EVANS (301), Division of Plant Industry, CSIRO, Canbema, A.C. T.,Australia E. A. N . GREENWOOD (l), Division of Land Resources Management, CSIRO, Floreat Park, Western Australia J. HAMBLIN* (361), Waite Agricultural Research Institute, University of Adelaide, South Australia, and Department of Applied Biology, University of Cambridge, England R. D. HAUCK (219), Division of Agricultural Development, Tennessee Valley Authority, Muscle Shoals, Alabama D. N. MAYNARD (71), Department of Plant and Soil Sciences, University of Massachusetts, Amherst, Massachusetts P. L. MINOTTI (7 l), Department of Vegetable Crops, Cornell University,Zthaca, New York N. H. PECK (71), Department of Seed and Vegetable Sciences, New York State Agricultural Experiment Station, Geneva, New York G. C. M. SAGE (2671, Plant Breeding Institute, Cambridge, England NEIL C. TURNER (161), CSIRO Division of Plant Industry, Canbema, A.C.T., Australia INDRA K. VASIL (119), Department of Botany, University of Florida, Gainesville, Florida I. F . WARDLAW (301), Division of Plant Industry, CSIRO, Canberra, A.C.T.. Australia

*Present address: Department of Agriculture, Perth, Western Australia.

ix

This Page Intentionally Left Blank

PREFACE During 1976, an event occurred which is of great significance to all mankind. At some location, probably in one of the developing countries where population growth is high, a child was born, the world’s four billionth human being. T h ~ s event, which was easily predictable considering national birth and death rates, calls our attention to the ever-present race between population and food supplies. It gives reason for the increased focus of the world’s scientific community on food production and it justifies the attention that has been given by crop and soil scientists to this important human problem. Rising costs of energy are a second area of worldwide human concern, an area that has marked effects on man’s ability to feed himself. Modern agricultural technology, developed over a long period of relatively low energy costs, is generally high in its energy requirements. Sudden increases in energy costs have caused a reexamination of the high energy demanding concepts of modern agriculture and have accelerated attempts to obtain high food production rates using practices with modest energy requirements. This volume contains reviews of the research contributions of crop and soil scientists to the solution of each of these worldwide problems. Attention is given to nitrogen, an element essential for crop production and an element whose supply is markedly affected by energy costs. Nitrogen is supplied either through biological fixation in the field or by commercial fertilizers. In either case, there is need for research findings on this element, its efficiency of utilization and its influence on crop production and crop physiological processes. Three review articles on nitrogen are found in this volume. One deals with nitrogen stress in plants, one with the use of tracers in nitrogen research, and a third with nitrate accumulation in plants. Cereal crops are carrying and will likely continue to carry a major share of the burden of food supply, especially in the developing countries. Three articles in this volume focus on the cereals. Emphasis is given to contributions relating t o their genetic improvement and to their physiology. A review of statistical techniques used in soil classification is very timely and should be useful in studies to integrate soil and crop performance information. Likewise, the article on crop-water relations summarizes work on moisture stress in plants and provides background information for draught-alleviating practices. Lastly, the review article on protoplasts calls attention to an exciting new area of research which will likely be pursued as we attempt to increase the yield potential of crop plants.

xi

xii

PREFACE

Volume 28 continues the tradition of the past in that it calls upon scientists from different national and disciplinary backgrounds and it covers a variety of topics of interest to crop and soil scientists.

NITROGEN STRESS IN PLANTS E.A.N. Greenwood Division of Land Resources Management. CSIRO. Floreat Park. Western Australia

..................................................

I . Introduction I1. Quantitative Concepts of Nutrient Deficiency ......................... A . Classic Approach to Nutrient Response ........................... B . Nutrientstress .............................................. 111. Nitrogen Stress ................................................ A . Definition .................................................. B . Measurement ............................................... IV. Factors Affecting Nitrogen Stress .................................. A Supply .................................................... B . Demand ................................................... V . Alternative Evaluators of Nitrogen Stress ............................. A . LeafNitrogenFractions ....................................... B . LeafElongation ............................................. C. LeafArea .................................................. D. Carbon Dioxide Exchange Rate ................................. E . Conclusions ................................................ VI . Applications ................................................... A . AgronomyandEcology ....................................... B . Stress Physiology ............................................ C. Modeling ................................................... VII . Conclusions and Aspirations ...................................... References ....................................................

.

1 2 3 6 7 7

a

14 14 16 18 18 21 25 27 28 28 29 32 33 34 34

I . Introduction

This article is about the quantitative measurement of nitrogen deficiency in plants . It is not a general review of the extensive field of nitrogen nutrition . It must occur to many agronomists to ask why water stress can appear to be so precisely measurable. whereas for nutrient stress we are limited to such broad terms as clinical. subclinical. severe. and mild Our dependence on these qualitative terms reflects an extraordinary weakness within the discipline of plant nutrition in quantifying nutrient deficit You will say at once that there are valid reasons why water deficit must be easier than nutrient deficit to determine And I will agree My criticism is not directed to the greater challenge. but to the meager evolution within the discipline to deal with it . To some extent the cause may be historical This

.

.

.

.

.

1

2

E. A. N. GREENWOOD

century has seen classic plant nutrition engrossed in the search for essential elements, the physiological role, availability in the soil, the clinical symptoms of deficiency and toxicity, and the response of plants to the quantity and chemical composition of nutrient supply. Plant water research was, of course, not concerned with essentiality and diagnostic critera. Whatever the reason, water deficit is commonly defined in terms of the physical stress of the water, whereas nutrient deficiency has come to be defined in terms of the plant’s response to the added nutrient. Consider the succinct definition proposed by Goodall and Gregory (1947): “a plant is deficient in a certain element if supplying that element to the plant in a suitable form causes an increase in yieM [my italics] , this effect being specific to the element in question.” It follows from this definition that in order to quantify the degree of deficiency one can measure the magnitude of the response of the plant. Hence the universal methods by which agronomists seek an estimate of nutrient deficit are based on plant response. If the increase in yield itself after application of fertilizer is not measured, then the soil or plant tissue might be analyzed in order to predict the response, the predictor having been previously calibrated against a response curve. Although the term nutrient stress has been in limited use for a number of years, I am not aware of any exposition of definitions and philosophy. Thus, an attempt is made in Section I1 to state in agronomic terms some basic considerations that agronomists may well accept as axiomatic in the field of water stress, but which have been ignored in the field of nutrient stress. They are my current, personal viewpoints and all of them are arguable (by author as well as reader). Regardless of whether you agree, your constructive participation will certainly assist the advancement of this aspect of agronomy.

II. Quantitative Concepts of Nutrient Deficiency

The term “stress” as used in plant science needs some clarification. It is a broad term that can be defined from more than one point of view; that is, as the status of the stress factor or as the effect of that status on the growth of the plant. For example, Taylor (1968) considered water stress to be the physiological condition of water in the plant, although a plant is often said to be under water stress whenever the conditions of water are unfavorable to plant growth. Because of this ambivalence of meaning, Taylor considered water stress too broad a term to quantify numerically. Hsiao (1973) confines the meaning of water stress to deficit, which is clearly separate from the plant responses which it induces. Central to the issue of evaluating nutrient stress, then, is to decide whether it is to be defined as deficit or as induced response. My current attitude (I have not always held this view) is that nutrient stress should remain a quantitative concept of nutrient deficiency-like growth, it is not measurable. Our efforts, as with water stress, should be directed toward

NITROGEN STRESS IN PLANTS

3

developing measurable parameters of stress which can be used for its evaluation. It would be no departure from convention to call such evaluations “nutrient stress,” for we do not hesitate to invest increments in biomass with the name of “growth rate.” A vital rule must be to indicate which evaluator of nutrient stress is being used. If we allow these first steps to be taken, some difficult problems in estimating nutrient stress can be resolved. But, as these steps are only preliminary, they can be readily retraced should the ground rules be found unacceptable. If the evaluation of nutrient stress is to be analogous to water stress, then we would have to measure such parameters as relative nutrient content and the chemical potential of the nutrient in the plant in some way. Assuming, for the argument, that it is feasible to do this, it would seem that the situation is rather different to what it is for water stress. We take for granted that the upper limit to the water content of a plant cell (full turgor) closely coincides with the water contents at which zero water potential and optimum plant growth occur. But, as is evident from the ability of plants to take upluxury and toxic quantities of nutrients, the upper limit to the nutrient content of a plant cell is well above that required for optimum plant growth. While the lack of a reference point is a major constraint to the concept of relative nutrient content, it is not an objection to the use of chemical potential. It simply implies that the relationship between plant performance and chemical potential would not be so simple, or perhaps as general, as it is in the special case for water stress. The main barrier to the use of chemical potential for estimation of nutrient stress seems to be that it is not yet a feasible proposition to obtain a meaningful measurement of activity of specific ions in plant tissue. And so, for the present, it becomes necessary to fall back to suitable parameters of current plant response. How appropriate to this specific purpose are the classic approaches to the evaluation of nutrient response, viz., nutrient response curves and critical concentrations?

A. CLASSIC APPROACH TO NUTRIENT RESPONSE

This section starts with response curves because the concept dominates the thinking of agronomists about the severity of nutrient deficiency. The only critical criterion of the severity of a deficiency which can be derived from a response curve is the magnitude of the reduction in yield below the maximum, This implies that, for the evaluation of a deficiency, it is unnecessary to know the form of the response curve. The practical significance of this point will be taken up again later in this section. With respect to our present purpose, the main weakness of the nutrient response curve is that it fails to deal with changes in response which inevitably occur in the field with time. The curve is the resultant of all the curves that might have been constructed between sowing and harvesting. Maybe an agron-

4

E. A. N.GREENWOOD

omist does not always want to know more than the final outcome. But sometimes he does need to know what has happened in order to understand how the final response developed-particularly if the results were unexpected. A moment’s consideration shows that responses do vary with time, even to the point of changing sign. These variations in response arise from changes in the supply of the nutrient and the demand for it by the plant. The nutrient supply to the plant may change with time because of uptake by the plant, or as a result of gaseous or leaching losses, chemical reactions, or microbial activity. When fluctuations in nutrient supply are large, the original levels of fertilizer applied inaccurately represent nutrient supply. Further, efficient uptake of fertilizer by the plant implies that the supply of applied fertilizer must approach zero with time, and so response might be expected to decline with this depreciation in treatment strength. The demand by the plant for a given nutrient also changes with time since it is influenced by the changes in all other environmental factors that control plant growth-other nutrients, water, radiation, etc. For example, the amount of nitrogen required by a plant now may be quite large if the environment is favorable for growth, whereas it may be small if, say, the temperature or the supply of available phosphorus is low. In addition to these influences on demand there is the compensating effect of plant size. Plants that response positively to the higher initial levels of the nutrient will, because they are bigger sinks, make larger demands on other nutrients or water. These may in turn become limiting, thereby curtailing the initial response. More certainly, the large plants will intercept so much light that the lower leaves will receive suboptimal illumination. Another important influence on the response of deficient plants is age. The responsivity of plants to a deficient nutrient declines with ontogenetic drift, particuarly in annuals where response approaches zero with maturity. Two conclusions follow from these remarks: nutrient response curves give very little information about the current intensity of deficiency, and in some cases they may also be quite misleading. From the foregoing discussion it is clear there will have to be some integration of supply and demand. A familiar approach has been to determine the concentration of the nutrient in the plant, arguing that the plant itself is the actual integrator of supply and demand. The graphic expression of this approach is to plot yield against nutrient concentration in the tissue (Fig. 1). Refinements are made by selecting the yield of a specific product and the chemical determination may be of some sensitive compound in sensitive tissue. In Fig. la the yield is beet weight, the compound determined is nitrate nitrogen, and the tissue is petiole. A frequent, but not universal, characteristic of the relationship between yield and chemical composition is that, for severe deficiency, yield increases linearly with increase in concentration with a well-defined steep slope, whereas at sufficiency, the curve flattens and becomes poorly defined (Fig. 1). If the change

"Mature" Petioles

A A

A

0

i 20

-

N0.25

I

I

0

I

1

1

16,000

8.000

I

1

1

24,000

Nitrate Nitrogen (ppm) b

100

'

0

128

0

8

8 256

A 80

A 96

0

A

B

0512 88

A

8

0

0

~4 L ~ l l l ~ ~ 1

0

0

2,500

1 .m

5,000

7,500

1

1

1

1

1 0 , ~12,500 15,000 17,500 20,OOO

Nitrate-N In Blade 1 (ppm)

FIG. 1. Relation of yield and nitrate nitrogen in plant tissue. (a) Weight of sugar beet and nitrate in petioles (after Ulrich, 1950). (b) Dry weight of Italian ryegrass and nitrate in leaf blade 1. dy/dx = 1 at approximately 1000 ppm nitrate-N. After Hylton etal. (1964).

6

NITROGEN STRESS IN PLANTS

in slope is abrupt, a “critical concentration” is discernible at the discontinuity, above which there is little increase in yield and below which yield is greatly reduced. It is not always easy to locate the critical point because of the variability of the data or because the curve may be broad and continuous. In the latter case, a numerical definition of the critical concentration can be based on the slope of the curve. For example in Fig. l b a slope of dy/dx = 1 has been adopted by Hylton et al. (1964) as critical. It is a step toward numerically quantifying the degree of deficiency, for a continuous change in slope can provide a continuous numerical scale. There are two serious weaknesses in the use of the slope of the yield concentration curve as a continuous indicator of the intensity of deficiency, as distinct from a single critical point. First, as seen in Fig. 1, the deficient arm of the curve shows little change in slope. Second, it is well known that the critical concentration declines with age and that in annuals this decline is precipitous after flowering. As for the response curve, a whole suite of curves like Fig. l a can be obtained for successive ages. Nevertheless it can be a most useful technique for estimating deficiencies in highly standardized crops (e.g., Ulrich, 1950). The critical concentrations of nutrients in plants is the main form of reference to nutrient status to be found in the literature. Extensive use is made of the reference tables compiled by Chapman (1966). For more specific information, agronomists turn to their colleagues in plant nutrition for interpretation of “spot” chemical analyses. The persistent attraction of such information lies in the certainty that below an accepted concentration in the plant a nutrient will be severely limiting, and that usually there is no better information available. It seems paradoxical to make such a claim in face of the vast literature on the use of plant analyses as a tool for assessing the nutritional status of plants. The problem is that although the concepts seem simple, the results must be qualified, as with response curves, by strong interactions with time. This aspect is discussed by Smith (1962) in his comprehensive and lucid review of tissue analysis.

B. NUTRIENT STRESS

It is evident that response curves and tissue analyses will not provide a satisfactory basis for using plant response as an indicator of nutrient status. We ought now to return to the definition of deficiency proposed by Goodall and Gregory (see Section I), and develop a proposition for nutrient stress. For it seems reasonable to argue that if it is acceptable to base a definition of nutrient deficiency on the yield response to a dose of the nutrient, then a quantification of this response should provide an acceptable basis for nutrient stress. Goodall and Gregory used yield (presumably of dry matter) as the criterion of response. But other criteria can be envisaged such as size (e.g., height, leaf area), or a

E. A. N. GREENWOOD

7

process (e.g., carbon dioxide exchange rate), or any other partial expression of plant growth which can be measured readily. The problem with this choice is that each parameter of growth has its own functional relationship with deficiency which would in turn give different estimates of nutrient stress. The use of the full expression of growth itself for these purposes is not possible since growth is not’ measurable, as pointed out by Arnott et al. (1974) in their introduction on the measurements of “growth.” Setting aside the choice of growth parameter until Section V, let me show what can be done with dry weight. The first task will have to be the development of a reference point to represent zero stress. It is implicit in the nutrient response curve and in the tissue concentration curve that the highest yield obtained under the circumstances represents the complete absence of the deficiency. This circumstantial maximum is the standard against which the degree of deficiency at lesser yields is judged. It was pointed out in Section 11, A that one does not need to know the form of the response curve in order to evalute a deficiency. What is required is the relationship of the yield of the deficient plant to the yield of the plant at the circumstantial maximum. It is necessary also to establish that maximum yield has been obtained. In other words, a numerical value for deficiency can be derived from the shortfall in yield relative to the circumstantial maximum yield. This is the crucial point on which the whole of the remainder of this article is based. There is a further point to recall from the criticism of yield response curves in Section 11, A-an inability to indicate current response. This shortcoming can be easily dealt with by measuring current growth rate instead of the accumulated yield of dry matter. If all these considerations are adopted, the current intensity of deficiency of a nutrient-nutrient stress-can be evaluated as the proportion by which the growth rate of the plant or crop is limited by that nutrient under the prevailing conditions. This definition needs to be qualified by the parameter of growth rate used-in this case, dry weight. The transformation of these ideas into a workable technique will be the objective of Section I11 which will be confined to the specific case of nitrogen stress. At this point also there will be a change in emphasis from a critique to a review of the subject. I l l . Nitrogen Stress

A. DEFINITION

Nitrogen stress is a quantitative estimate of the intensity of current nitrogen deficiency in a plant or crop. It can be evaluated as the proportion by which the growth rate of the plant falls short of maximum growth rate attained with a

8

E. A. N.GREENWOOD

nonlimiting supply of nitrogen over the period when stress is being measured. For this representation of nitrogen stress, Greenwood, Goodall, and Titrnanis (1965) used the symbol SN when it was made on a biomass basis. The relative shortfall can be expressed as a percentage, i.e., (prowth rate at maximum N response)-(growth rate at deficiency) SN = 100

growth rate at maximum N response

(1)

For example, if the growth rate of the deficient crop is 7 g/m2/day and 10 g/m2/day when it is given a nonlimiting dose of nitrogen, then nitrogen stress would be 100[(10-7)/10] = 30%. SN has some broad similarities with relative water content, for which the weight of a leaf deficient in water is compared with its weight after it has been brought to a standard, nonlimiting water content. In order to put this expression into practice, it is necessary to decide precisely what is meant by growth rate and how to find the current limitation of it by nitrogen.

B. MEASUREMENT The split-plot technique is basic to all methods so far devised for estimating

SN. At the time SN is to be measured, one subplot is left untreated and the other is given sufficient nitrogen to make nitrogen nonlimiting. Current growth rate is then measured in the untreated subplot, and the maximum growth rate that can be attained by adding nitrogen is measured in the other subplot. 1. Growth Response There are two conventional ways of expressing growth rate on a dry weight basis. Symbol Crop growth rate

C

1 dW Relative growth rate - Wdt

R

Working formula

In W2-ln W 1 t2 - t 1

Units

g/g/day

where W1 and W 2 are the dry weights at time tl and t 2 , respectively. The numerical value of SN obtained may be influenced by which expression is used. Broadly speaking, C is appropriate for crops or swards with a closed canopy and R is appropriate for spaced plants. In order to distinguish which form of growth rate has been used for estimating SN,the appropriate symbol can be used as a

NITROGEN STRESS IN PLANTS

9

subscript, i.e., SNC or SNR. The expressions for SN then become: SNC =

100 [(cM-C)/cMl

SNR = 100 [ ( R M - R ) / ~ V I

(2) (3)

where C or R is the growth rate in the control subplot and CM or RM is the growth rate in the subplot to which nitrogen has been added. Equation (3), the one originally proposed by Greenwood et LIZ. (1969, has been used consistently in publications on nitrogen stress. Nevertheless, as indicated above, it is not necessarily the most appropriate equation. Relative growth rates were originally adopted as a compromise in the interests of general application. The problem, briefly, is the exponential character of plant growth in unclosed canopies. Under steady conditions, the daily increment in weight increases with plant size, with the implication that the magnitude of the response to nitrogen is confounded with the weight of the plant. More specifically, when one wishes to compare the responsivity of two plants of different size due to different treatments or age, a bias is introduced. The bigger plant will have the bigger potential response in absolute terms. If the exponent of growth were constant then the bias could be exactly overcome by using relative growth rate. Although R does change less than C over the life of a crop by an order of magnitude, its change is appreciable. Operationally there is no difference between using SNC and SNR,for they both require the same primary data, W 1and W2.The real dilemma is that both C and R are nonideal over the whole life of the crop. And there seems no way of deciding which of them is to be preferred, for young crops behave as a community of spaced plants until the canopy is closed. Even if a working rule is adopted such that R is appropriate for crops with LA1 < 1 and C for crops with LA1 > 1 (LA1 = leaf area index), we would be well aware of a very broad transition zone in which neither R nor C would be fully appropriate. We must conclude that the approach to plant stress through dry weight response cannot be taken without some bias. The importance of the bias can be gauged by comparing SNC and SNR derived from the same dry weight data. This can be seen in Fig. 2c for a situation supposedly favoring SNR. The difference between the two curves is small at the extremes but large in the middle portion. In the case of wheat, the real situation does not seem to be as bad as it sounds from these considerations. In Fig. 3, SNR is plotted against SNC from two sets of data. One is the pot data used for Fig. 2c. The other is a reworking of the field data of Halse etal. (1969) in which SN was estimated at four stages from 4 to 16 weeks (ear emergence) with LAI ranging from about 0.1 to 2.5. The one curve fits both sets of data (R2 = 0.995). Three important points follow: age or LA1 has not affected the relationship between SNR and SNC;SNR is neither more nor less appropriate than SNC ;and it is a simple matter to convert SNRto SNC or vice versa. It can be seen from Fig. 3 that because the intercept is close

u

0

2

4

6

N Supply (mM1

8

1

0

.02 0

2

4

6

N Supply (mM)

8

10

0

2

4

6 N Supply (mM1

8

10

FIG. 2. Four expressions of response by wheat to nitrogen supply between the third and fiith week after emergence. (a) Yield of dry matter; (b) relative growth rate ( R ) and crop growth rate (0;(c) nitrogen stress based on R and on C. Data are from Greenwood (1966).

NITROGEN STRESS IN PLANTS

11

80

40

20

0 0

20

60

40

80

100

sNC(%)

FIG. 3. Relationship of nitrogen stress in wheat based on relative growth rate, Sm, to nitrogen stress based on crop growth rate, SNC. Points denoted as are from Fig. 2(c). Other points are derived from Halse et 01. (1969)from a field crop sampled between 4 and 7 weeks (A), 6 and 9 weeks (A), 10 and 13 weeks (+) and 13 and 16 weeks (x) after sowing. ~ derived from all points and accounts for The curve y = 3.55 + 0.25% + 0 . 0 0 6 0 6 ~was 99.5% of the variance.

to zero, and, for subclinical levels of nitrogen deficiency only, the quadratic term can be ignored, the relationship of SNR to SNCcan be simplified to SNR = 0 . 7 5 ~ These ~ . remarks apply to wheat; they may not hold for other species, particularly dicotyledons. A useful reference point is the value of SN at which nitrogen deficiency symptoms begin to develop. In all published work with grasses and cereals this Point Occurs at SNR = 40% (SNC = 60%). This section has dealt with growth response only in terms of dry weight. Other parameters of growth rate are considered in Section V.

2. Response Interval Ideally, growth rates on the control and the plus-nitrogen subplots should be measured as quickly as possible after the plants have responded to the addition of nitrogen. This is because current response is required and SN may be changing rapidly. In practice there is a lag period between application of the nonlimiting dose of nitrogen and its entry into the roots and leaves even in solution culture

12

E. A. N. GREENWOOD

where immediate uptake of nitrogen is ensured. Bouma (1970a) measuring both leaf area and carbon dioxide exchange rate (CER) on subterranean clover at 2-day intervals could clearly detect a nitrogen response after 2 days. Wolf and Greenwood (unpublished data) used a much shorter time interval and measured the leaf elongation rate (L), and CER of expanding and mature leaves of wheat seedlings in light and in the dark. They found that dark respiration responded to added nitrogen in 2-7 hours but the response was small and insensitive. The CER of mature and expanding leaves responded after 22 hours, and a similar time lag was taken by L for elongating leaves. Full response by AL occurred after 48 hours, whereas CER required more than 72 hours. There was no evidence of any temporary toxicity when the nitrogen supply (as ammonium nitrate) was raised from 1 'to 20 mEq N/liter. An example of one of the several response runs is given in Fig. 4. From the foregoing evidence, it seems that at least 2-3 days should elapse between applying nitrogen and commencing to measure the response. In practice, as agronomists will appreciate, it is difficult to get accurate estimates of dry weight increments in less than a week. This is because field sampling is imprecise and because the variance of the increment W2-W, is about twice the variance of a single dry weight measurement. In addition to this we are measuring differences between increments on one subplot and increments on another. Thus the variance of SN is high. 80

0 0

-8

I

60

f

G e

40

8

2 20

t

i Dark

0

20

Dark I

I

0

40

1

60

1

80

Hours

FIG. 4. Apparent change in nitrogen stress in deficient wheat seedlings immediately after the nonlimiting dose of nitrogen was given to alternate matched plants. Successive values of rates of elongation (L)and carbon dioxide exchange rate Q of the emerging second leaf were substituted into Eqs. (4) and (6) in the text. Developing response is indicateli by rising slopes and the attainment of full response by flat slopes. Replication was X 4 . From unpublished data by Wolf and Greenwood.

NITROGEN STRESS IN PLANTS

13

My experience is that a growth interval of at least 10-14 days is required to get meaningful and reliable differences between growth rates on the subplots when these are expressed as dry weights. This is far from being instantaneous. If SN is changing rapidly, only an average value over the time interval can be used. Rapid changes in SN do occur naturally. Power (1971) reported an increase in SNR from 4 to 73% in bromegrass within 3 weeks. On the other hand, there is an advantage in the field in having a fairly long time interval over which SN is being estimated, for it helps to integrate the day-to-day variations in weather which may be of little interest in themselves. Of course, where one wishes to establish relationships between stress and the environment a short-term response would be welcomed. Alternative, short-term, nondestructive methods for estimating stress are described and evaluated in Section V.

3. The Nonlimiting Supply of Nitrogen

SN can be estimated without invoking any assumptions as to the form of the response surface. It requires only the values for the actual growth rate and the growth rate with nitrogen nonlimiting. Since the response curve (i.e., the section of the response surface at prevailing levels of factors other than nitrogen supply) generally has an extensive plateau around the optimum, high precision in the choice of nonlimiting nitrogen levels is not necessary. In cases where there is adequate information available (Power, 1971), one estimate of a nonlimiting nitrogen supply level is sufficient. Otherwise, at least two different levels should be used in order to judge whether the deficiency has been completely removed and whether toxicity has been avoided. The following working rules are useful: when the two “nonlimiting” levels of nitrogen do not produce growth increments that are significantly different from each other, then the increments are averaged to give a best estimate of growth rate with nitrogen nonlimiting; when the difference between them is significant but small, the larger value is taken for nitrogen nonlimiting; when the difference between them is large, then the data are abandoned. Significant growth differences for the two levels of nitrogen selected can be easily avoided provided that some precautions are taken. These precautions can be generalized: very young seedlings and heavily defoliated plants require much lower levels of nitrogen for maximum response than do older and intact plants; for the former, temporary toxicity may occur, particularly if nitrogen is supplied in the ammonium form. 4. Operational Procedures For the estimate of SN by destructive dry weight harvest, a multi-split-plot technique is required. A quartet of matching subplots or quadrat areas is selected. Each of the four subplots is assigned at random to one of the following

14

E. A. N. GREENWOOD

procedures. Dry weight, W1,

is determined at the beginning of the test interval tl and, similarly, W z is obtained at the end of the interval tz . The actual growth increment of the crop is computed from these two values. Meanwhile, at r ,each of the remaining two subplots is given a different “nonlimiting” application of nitrogen and is harvested at tz . From the two dry weights for these subplots the value for W M is obtained. The growth increment of the crop with nitrogen nonlimiting is obtained from W land W M . In the field, if the soil is wet throughout the root zone, the nonlimiting dose of nitrogen can be applied in solution using the equivalent of say only 2 mm of artifical rain in order to avoid disturbing the water regime. A similar amount of nitrogen-free water must also be added to the W z subplot. Where the surface of the soil is dry due to a short and perhaps unimportant absence of rain, then a decision must be made either to wait for rain or to add sufficient water with the nitrogen to simulate rain which could be expected to fall. Again, if water is added it should include Wz.In either case the value for SN would apply to situations where water is not an important limiting factor. In cases where it is realized that water is an important limiting factor, albeit unevaluated, but where rain falls during the growing season, another technique is available. Since it is unlikely that in these circumstances an argonomist would want to know the importance of nitrogen as a limiting factor without similar information for water (though few have sought it), the technique used by Power (1971) can be most effectively employed. This involves the use of supplementary water as well as nitrogen, and it will be discussed in Section VI. IV. Factors Affecting Nitrogen Stress

Nitrogen stress can be considered as a concept that integrates the rate of nitrogen supply with all the other factors essential to growth: genetic, ontogenetic, nutritional, environmental, symbiotic, and other factors. It follows that a change in nitrogen stress may be brought about through variation in either the supply of nitrogen or in any of these other determinants of growth. The following is a review of the limited experimental evidence on factors affecting nitrogen stress. A. SUPPLY

Curves relating SNR and SNC to nitrogen supply for wheat between weeks 3 and 5 are given in Fig. 2c. In this example, both curves lead to a credible

NITROGEN STRESS IN PLANTS

15

extrapolation to 100%stress (no net increment in dry weight) at zero introgen supply, and, of course, they both reach zero stress (no response to nitrogen) as the nitrogen supply approaches the nonlimiting level. In nutrient culture work, it is usual to make some attempt to keep the concentration of nitrogen in the solution fairly steady by periodic or by continuous replacement. But where only a single application is given, say at the beginning of a pot experiment, the progressive depletion of the applied nitrogen must result in an increase in SN ,other factors being held unchanged. In the field, marked fluctuations in nitrogen supply in both directions may occur. On the one hand, these may be leaching and gaseous losses and, on the other hand, all those factors such as temperature and wetting and drying which may control the rate of microbial production of available nitrogen in the soil. Some practical perspective is given by the work of Halse et ul. (1969) who grew a wheat crop in a nitrogen-deficient sandy soil (average annual rainfall, 390 mm) and applied nitrogen at three rates at sowing: nil, 56 kg/ha, and 112 kg/ha, the last also receiving two further applications of 112 kg/ha. These treatments gave grain yields of 900, 1800, and 3000 kg/ha, respectively. SNR was determined on the nil and 56 kg/ha treatments. On the nil treatment SNR remained at 48% for several weeks and then fell to 14% at the late boot stage. The application of 56 kg (kglha) almost eliminated stress during the first few weeks, but by floral initiation it had reached 23%before falling to 5% (Table I). These results were obtained in the Mediterranean climatic zone of southern Australia during the growing seasons of autumn, winter, and spring.

TABLE I Effect of Nitrogen Fertilizer and Plant Age on Nitrogen Stress (SNR) in a Wlieat Crop' Nitrogen applied Weeks after sowing

Nil

56 kg/ha %i

4-7 6-9 10-13 13-16

48i1 47il 26i5 14i7

SE

6i2 23i3 11i4 5i8

'Adapted from Hake e l al. (1969).

16

E. A. N. GREENWOOD

B. DEMAND The age and ontogeny of a plant can greatly influence the magnitude of SN. Greenwood and Titmanis (1968) found that for annual ryegrass grown on a constant nitrogen concentration of 1 mM, S N increased ~ from 10% at 2 weeks after emergence to 11% at week 3, to 17% at week 4, and to 32% at week 5. The explanation could be that, as the daily increment in dry weight increases with age, the demand for nitrogen must increase. If the supply is fixed in concentration and inadequate, the shortfall in supply, whence stress, must also increase. At a much later stage, individual axes of the plant produce flowers and become less capable of response to nitrogen in the sense of net increment of dry weight-at least in more determinate species. This implies, particularly for annuals, that SN must approach zero as the plant approaches maturity. These trends are evident in Tables I and 111. Light will increase SN provided that light intensities are below the optimum for plant growth. Table I1 records some unpublished results for wheat seedlings. When the potential growth rate of a plant is limited by other nutrients as well as nitrogen, then an increase in the supply of those nutrients ought to increase SN. A very clear demonstration of this point with respect to sulfur and phosphorus can be inferred from the data of Bouma and Dowling (1967). They showed increasing responses (whence stress) of leaf area to nitrogen in TrifoZium subferraneum. For example, on a very low supply of inorganic nitrogen, values of stress are 25%, SO%, and 70% for sulfur supplies of 0.125,1.0, and 8.0 ppm. In computing these values, I have taken the highest supply of nitrogen as being nonlimiting, which is good enough for this exercise.

TABLE I1 Effect of Shading on Nitrogen Stress (SNC) at lS"/lO"C in Wheat

N fllpply (mM)

Unshaded

Shaded

2 4 6

42 17

31 11 4

13

NOTE: Plants were grown in a naturally lit glasshouse with noon light intensities of 45,000 (unshaded) and 18,000 lx (shaded). Replication was X 7.

17

NITROGEN STRESS IN PLANTS

Power (1971) studied the interaction between wafer sfress and nitrogen stress on bromegrass in the northern Great Plains of the United States. He found, over a range of conditions, that the plant stress caused by each of these two limiting factors was roughly additive. To give one instance, the value of nitrogen stress (SNR)as obtained by making nitrogen nonlimiting was 24%.The value of water stress (SWR) as obtained by making water nonlimiting was 32%. But when nitrogen and water were both made nonlimiting, the value of plant stress obtained was 54%. This implies that as water becomes more limiting the value of SN declines. Further results are displayed in Table VI. Defoliation, whether by cutting or by grazing, might be expected to reduce SN at low values of LAI when a reduction in photosynthetic area might be expected to limit potential growth during the recovery period. Greenwood and Titmanis (1968) established this point experimentally with young swards of annual ryegrass in pots with clipping, and in the field with sheep. The particular defoliation regimes used reduced SNR from 32 to 19% in the pot experiment and from 11 to 3%in the grazing experiment. These examples probably underestimate the immediate effect of defoliation on SN since the latter was, of necessity, estimated during the ungrazed recovery period. One of the general, and important, effects of cultivation is to increase the supply of available nitrogen to a crop. This should result in a reduction of stress provided that there is a deficiency of nitrogen and that cultivation does not affect other limiting factors. The situation is likely to vary with soil type and other circumstances. The integration of all these factors by the crop can be expressed, with reference to nitrogen, as SN. Table I11 shows that the effect of cultivating sandy loam was to reduce the subsequent values of SNR in a wheat crop. This will be discussed further in Section VI,A.

TABLE 111 Effect of Age and Cultivation on Nitrogen Stress (SNR) in Wheata Nitrogen stress (%) Cultivation treatment

Wk after emergence: 3-6 13

Nil Conventional

6-9 26,

9-12 13

*

***

ns.

5

17

10

Adapted from Greenwood e?al. (1970).

18

E. A. N. GREENWOOD V. Alternative Evaluators of Nitrogen Stress

The evaluation of nitrogen stress by dry weight increment (SN)as described in Section IV is a simple procedure, but it has three important disadvantages in that it requires destructive sampling, a high replication for precision, and a lengthy period for the response to manifest. Obviously it would be a great advantage if nondestructive or more rapid methods could be found. Alternatives are available and they fall into two classes: parameters of plant nitrogen status which are used as indices of SN, and parameters of plant growth which are used as direct alternatives to dry weight.

A. LEAF NITROGEN FRACTIONS

When attempting to relate leaf nitrogen to nitrogen stress, similar specifications to those which usually apply to the establishment of “critical levels” in tissue analysis must be considered. Decisions must be made as to the choice of nitrogen fraction to determine, organ or tissue to sample, and the time of sampling. Insight into these aspects can be gained first from reference tables such as in Goodall and Gregory (1947) and Chapman (1966) as well as individual research papers. For example, Ulrich (1950) gives critical values of nitrate nitrogen for leaves and for petioles at three physiological ages and at different dates of sampling of Beta vulguns; Hylton et al. (1964) give the value of nitrate nitrogen in several plant parts at which dy/& = 1 for Lolium multijlorum; and Rauschkolb el al. (1974a, b) evaluate the nitrogen status of maize and sorghum in terms of the total nitrogen and nitrate-nitrogen concentrations in the whole leaf, midrib, and basal section of the stem. We have examined the relationship of SN to the concentration of total nitrogen and of ninhydrin (mainly a-amino) nitrogen in the youngest fully expanded leaf of the tillers of annual ryegrass (Lolium rigidum) and in several genotypes of wheat. We used the youngest fully expanded leaf on the tiller at the time of sampling because its physiological age is constant and because it is easy to identify and sample. Total nitrogen was chosen because of its common use. Nitrate nitrogen was rejected, mainly because it does not accumulate in measurable quantities over the whole range of deficiency (e.g., Hylton et al., 1964), but also because it is highly variable in concentration, and it is sensitive to the form of nitrogen supplied and to time of day (Allen et al., 1961). Ninhydrin nitrogen was chosen as being intermediate between nitrate (unmetabolized) nitrogen, and total (mainly protein and therefore historic) nitrogen. Typical curves for total nitrogen and ninhydrin nitrogen in the youngest fully expanded leaves of wheat tillers are given in Fig. 5 .

19

NITROGEN STRESS IN PLANTS

K

z

*.

a

b

lJY

i .-

80

:\ 0 60 - \o 40

1

60

Total Nitrogen

\o

40

\

0

b

20

20

0 2

1

I

I

3

4

5

0 6

7

0.3

0.2

0.1

Leaf Nitrogen (%I FIG. 5 . The relation between nitrogen stress (SNR) and the concentration of nitrogen in the youngest expanded leaf of wheat between the third and fgth week after emergence. After Greenwood (1966).

To test the general applicability of leaf nitrogen fractions as estimators of S N , the constancy of the relationship must be investigated under a range of conditions. The results of some investigations are reviewed below. A direct comparison of the relationship of SN to leaf nitrogen was made between four commercial genotypes of wheat between the third and fifth week after emergence. Whereas some genotypes had similar calibration curves others differed (Titmanis and Greenwood, 1969), which leads to the conclusion that, in practice, it would be necessary to calibrate each genotype separately regardless of whether total nitrogen or ninhydrin nitrogen was to be used. Table IV gives the predicted value of SNR for a given value of the estimator in each of the four TABLE IV Comparison of Estimates of Nitrogen Stress (SNR) Given by Set Values of Leaf Nitrogen Fractions in Several Genotypes of Wheat' Nitrogen stress (%) Value of estimator Total N 4% 5% Ninhydrin N 1200 ppm 1500 ppm

Mendos

Gamenya

Emblem

Olympic

Gab0

25 8

25 9

30 -

45 17

21 9

23 10

23 10

20 -

35 11

33 20

'Adapted from Titmanis and Greenwood (1969) and Greenwood (1966).

0.4

20

E. A. N.GREENWOOD

genotypes, and also for Gabo at the same age but from another experiment (Greenwood, 1966). Since the relationship between SNR and leaf nitrogen vanes between close genotypes of the one species, it can also be expected to vary between closely related species. This certainly holds for the two species that have been investigated-annual ryegrass and wheat. At 28 days after seedling emergence the predicted value of SNR at 4% N content is 46% for ryegrass (cf. Fig. 6), which is a much higher value than four out of the five wheat genotypes at the same age just mentioned (Table IV). Work on the effect of age was conducted in two separate experiments by Greenwood and Titmanis (1966); the results have been brought together and reexpressed in Fig. 6. Over the first 5 weeks after emergence, a given concentration of total nitrogen in the youngest fully expanded leaf of the tiller gives a fairly constant estimate of SNR. Thereafter the predicted value of stress falls. For ninhydrin nitrogen, the two experiments gave inconclusive results.

60

0-0-0

50

-

40

-

-ap

3.5%N

-0

Total Nitrogen

\

-

-

6.MN

0-0-0-

10

DO

1

Spring Experiment

0 ,

I

1

0

I

Winter Experiment I

1

I

1

NITROGEN STRESS IN PLANTS

21

Insofar as one can generalize from two species, the period over which the concentration of total nitrogen in the youngest fully expanded leaf of the tiller can be used as a stable estimator of SN is short, i.e., 5-6 weeks at the most. No precise work has been recorded on the effects of either the composition of the nitrogen source or the relative supply of other nutrients on the regression of SN on leaf nitrogen. In experiments with young annual ryegrass, we examined the effects of defoliation on the relation of SN to leaf nitrogen (Greenwood and Titmanis, 1968). The various defoliation treatments used had very little effect on the relationship except at high concentrations of plant nitrogen (cf. Fig. 6). Total nitrogen and ninhydrin nitrogen performed simiiarly as estimators of stress. Light exerted a marked effect on the relationship between SNC and the total nitrogen concentration in the youngest fully expanded leaf of wheat tillers in an unpublished experiment by Greenwood. The treatments were full daylight and shading. Average noon light intensities for the unshaded and shaded treatments were 45,000 and 18,000 lx, respectively. Figure 7 and the accompanying statistics show that the estimation of SNC by total leaf nitrogen was good (R2> 0.98) and that the effect of shading was to produce greater slopes and intercepts than the unshaded treatments. If leaf nitrogen is to be used, then which fraction of nitrogen is to be preferred? There is usually little to choose between total nitrogen and ninhydrin nitrogen. The former is easier to deal with in the field and this may be the deciding factor. Nitrate nitrogen is unsatisfactory because it is not present in detectable amounts in severely deficient plants and because it shows diurnal and other variations. My own conclusion now is that any fraction of leaf nitrogen is rather unsatisfactory for general use as a quantitative estimator of SN.

B. LEAF ELONGATION The use of the rate of leaf or tiller elongation as an estimator of current growth rate in Gramineae has been briefly reviewed by Williams and Biddiscombe (1965). This reference also includes an excellent photograph of both continuous-recording and multi-point auxanometers, which are instruments used for the automatic measurement of tiller elongation rate. Leaf elongation has turned out to be the most useful of the estimators of SN so far evaluated for Gramineae. Leaf elongation rate is sensitive to nitrogen stress and, because of the morphology and pattern of leaf development in Gramineae it is simple and cheap to measure. Under steady conditions the daily rate of elongation of a given leaf of a Gramineae is constant from its first appearance until just before its full expansion. Since the latter coincides with the emergence of the next leaf this period approximates the leaf appearnce interval. Leaf elongation is obtained as

22

E. A. N. GREENWOOD 70

X

60

50

--8

40

0

z

v)

R2=0.995)

30

20

Unshaded R2=O!

10

\X I

0 2

I

1

3

I

4

1

1

5

Leaf Nitrogen(%)

FIG. 7. Effect of shading on the estimation of nitrogen stress (SNC) by total nitrogen in the leaf.

the difference between successive measurements of leaf length (in Gramineae this can be from the base of the ligule of the older leaf to the tip of the emerging leaf). Tiller elongation can be measured from a bench mark on the ground to the tip with a rule, or by an awanometer attached to the emerging leaf tip. More elaborate devices may be used for measuring elongation, such as the one used by Hsiao el al. (1970) for maize. The use of leaf elongation rate as an estimator of SN has not been evaluated in dicotyledons. It may well be suitable, for Wadleigh and Gauch (1948), for example, found leaf elongation to be a sensitive estimator of water stress in cotton plants. Leaf elongation rate, L (cm/day), can be used to estimate SN by substituting L for R or Cin the nitrogen stress equation SNL = 100 [(LM-L)/LM]

(4)

The ability of SNL to estimate SN in Lolium is seen in Fig. 8. For subclinical

NITROGEN STRESS IN PLANTS

23

100 28-42 Days 0 44-58Days

SNR

A

A

sNC

80

28-42 Days ~-58Dayr

60

-s?z v)

40

20

0 0

20

40

60

80

100

SNL(%)

FIG. 8. Linear regressionsof SNR on SNL and of SNC on SNL in Lolium rigidum. Points derived from Greenwood and Titmanis (1966) for plants between 2 8 4 2 days and 44-56 days after emergence. Values from plants with symptoms are not included in the regression.

levels of nitrogen deficiency, over 97%of variation in either SNR or SNC can be accounted for by SNL.Where deficiency symptoms are present there is a marked increase in slope. This seems to be caused by a rapid recycling of nitrogen from the older leaves to the emerging leaf. Consequently, even when SN approaches 100%(zero growth on a dry weight basis), leaf elongation continues. Unfortunately, annual ryegrass is the only species to have been studied with respect to leaf elongation and nitrogen stress. Some unpublished data of Power show that leaf elongation is sensitive to the effect of nitrogen supply on certain growth rate in a wide range of grasses from May to July in North Dakota (Table V) and therefore might also be useful as an estimator of stress. Power compared leaf elongation rate in swards that received either no nitrogen fertilizer or 220 kg Nlha in early spring. It is tempting to calculate SNL values from this array but to do so would be far from rigorous. This is because at each time of comparison,

24

E. A. N. GREENWOOD TABLE V Rate of Leaf Extension of Various Grass Species Prior to Inflorescence as Affected by Nitrogen Fertilization (Values Are Means of 6 Tiller@ Date

Species

N rate (kdha)

5/27

6/2

6/9

6/17

Average SE (%of mean)

17.8 22.0 7.2 11.3 10.5 25.6 11.3 32.3 6.0 2.7 6.7 12.5 9.0 32.2 9.7 9.5

10 12 17 24 18 19 15 20 26 27 17 18 14 17 14 19

mm/day Reed canary grass Smooth brome Western wheatgrass Russian wild

we Crested wheatgrass Green needle grass Garrison creeping foxtail Intermediate wheatgrass

0 180 0 180 0 180 0 180 0 180 0 180 0 180 0 180

8.7 14.0 10.1 8.2 7.2 8.1 4.8 8.5 7.0 3.8 5.2 4.4 5.5 2.5 10.6 8.5

13.5 18.2 7.8 14.5 9.7 12.5 7.3 18.2 11.0 20.0 9.0 10.0 6.8 21.5 12.3 19.2

14.0 25.3 7.5 18.2 9.3 21.2 10.2 25.0 7.6 10.7 8.4 16.0 6.3 36.2 11.3 18.8

‘Unpublished data of J. F. Power.

the No and Nzzo plots were not at all comparable, the latter having responded extensively to nitrogen applied in early April; consequently a split-plot design that is required for SN did not apply. The data have been presented here because of the rare insight they give into the sensitivity of leaf elongation under a variety of seasonal conditions. For example, soil water measurements showed that the fertilized plots contained 2-8 cm less water in the root zone in late May than did the check plots. This could account for the negative response to nitrogen obtained at that period. The dry matter responses obtained (to be published by Power elsewhere) reflected the variation in leaf elongation rates. The day-to-day change in temperature also produced a noticeable effect on elongation (Power, personal communication), an observation that supports the elegant results with Phalaris tuberosa L., P. arundinacea L., and Festuca arundinacea Schreb. obtained by Williams and Biddiscombe (1965). The standard errors in Table V give some idea of the adequacy of the fourfold replication used by Power. More comprehensive information on the number of

NITROGEN STRESS IN PLANTS

25

replicates required for a given level of precision in L is provided by Scott (1961) for tussock grasses. At the present stage of evaluation it appears that leaf elongation is a simply measured and promising estimator of SN, and its use should be encouraged. Accordingly, it would be profitable to investigate its performance early in any program where it might be applicable. Even in the case of annual ryegrass it has been shown that the relation of SNL and SNC does not hold indefinitely. From Fig. 8 it can be seen that a steady relationship holds at least for the first 8 weeks. But Greenwood et al. (1965) have shown that values of SNR begin to rise in relation to SNL shortly after 8 weeks. The application of leaf elongation is taken up again in Section VI, A.

C . LEAFAREA

Since leaf elongation rate is sensitive to nitrogen status, it follows that the rate of increase in leaf area should also reflect accurately the influence of deficiency on growth. Furthermore, lead area is both an expression of size and a partial expression of photosynthetic potential. In this context leaf area is taken to be total leaf area present either per plant or per unit ground area (LAI) as distinct from that of a selected expanding leaf as is used for leaf length. Nutrition can influence photosynthesis (whence growth) through affecting leaf area itself or through changes in photosynthetic rate per unit leaf area (net assimilation rate). These aspects of crop nutrition have been reviewed by Watson (1963) who concluded that, for nitrogen, the main effect on growth is through leaf area rather than through net assimilation rate. More specific evidence of the close relationship between leaf area and the influence of nitrogen on growth can be derived from the data of Bouma and Dowling (1966) and of Halse et al. (1969). Bouma and Dowling measured the dry weight and leaf area response of subterranean clover to nitrogen supply in water culture. I have computed the linear regression of the dry weight data on the leaf area data for each nitrogen level. It shows that 98% of the variation in dry weight is accounted for by the regression on leaf area. Halse measured photosynthetic area (green leaf plus stem area) and SNR in a wheat crop grown at three levels of nitrogen fertilizer: nil, 56 kg N/ha at sowing, and 336 kg N/ha split over three applications. Figure 9 shows my plotting of the change in leaf area against SNR for each period when stress was measured. The exercise shows a close relation between LA1 and nitrogen stress and a strong interaction with time. What is required for the estimation of stress is a set of leaf area data (derived from appropriate plots split for nitrogen) from a range of nitrogen levels and

26

E. A. N. GREENWOOD 2.5

-

2.0

4-7Weeks

-

1.5

0 6-9Weeks

-

A 10-13Weeks

4 C

X

i

-ic?l

1.0

-

0.5

.

0 -

1

1

L

0

10

20

13-16W~ks

I

I

30

40

00,

50

SN R (%I

FIG. 9. Relationship between increase in leaf area index (LAI) and nitrogen stress (Sm) in a crop of wheat over successive 3-weekly intervals. Nitrogen fertilizer treatments were nil, 56 kg N/ha at sowing, and 112 kg N/ha applied at sowing at 5 and at 10 weeks (taken here as producing zero stress). Data are derived from Halse et al. (1969).

which can be substituted into the expression SNA = 100 [(AM-A)/AMI

(5)

where A is the change in leaf area of the deficient plant over a given time interval and A M is the corresponding change in leaf area for a plant given a nonlimiting dose of nitrogen at the beginning of the interval. The adequacy of leaf area as an estimator of SN could then be tested by plotting SNA against SNC which would be derived from the corresponding dry weight values. The author is not aware of any set of data that completely fulfill these requirements other than a fragment from Bouma (1970a). In this instance, subterranean clover was grown in sterile culture solutions containing 4, 16, or 64 ppm N for 27 days. Among other treatments the 16 ppm plants were split into two groups: (1) the nitrogen level remained at 16 ppm; (2) the nitrogen level was raised to 64 ppm (assumed by me to be nonlimiting). Leaf area was estimated frequently. From Bouma’s Fig. 1 , at day 36, leaf area was 34.5 cm for 16 ppm

NITROGEN STRESS IN PLANTS

27

and 55.9 cm for 66 ppm. Substituting into Eq. (9,SNA = 38%. This value is very close to that for wheat at the same age and nitrogen supply (Greenwood, 1966) as also is the value of 59% derived by my extensive extrapolation from Bouma’s Fig. 1 for plants on 4 ppm N raised to 64 ppm. The technique for assessing the nutrient status of plants used extensively by Bouma in Canberra over the last decade has all the essentials of the split-plot approach for estimating nutrient stress. It is unfortunate for this review that most of his research has been concerned with nutrients other than nitrogen, for it has led to a more specific understanding of the physiology of nutrient response. Because of the importance of the work to the field of nutrient stress, the essence of the technique and results will be given. Bouma’s procedure is to grow subterranean clover seedlings in a nutrient solution containing all essential elements except the nutrient to be studied. The latter is provided as a pretreatment over a range of deficient levels. At a certain time some of the plants on each pretreatment are transferred to complete solutions, this time containing the previously deficient nutrient at a nonlimiting level. The treatment for the remainder is unchanged. On several occasions the leaf area of each plant is estimated using the photographic standards of Williams et al. (1964), and the carbon dioxide exchange rate (CER) is measured under standard conditions with an infrared gas analyzer. The results demonstrate the speed of response of leaf area and CER, and the relative importance of the contribution of leaf area and net assimilation rate. With these and other measurements, Bouma has studied what might be called the physiology of recovery from nutrient deficiencies such as nitrogen (Bouma, 1970a, b), phosphorus (Bouma, 1967a, b, 1969a, 1971, 1975; Bouma and Dowling, 1969a, b), sulfur (Bouma, 1967a, c, 1970c, 1971; Bouma et al., 1972), potassium and magnesium (Bouma 1970c), and boron (Bouma, 1969b). For most of these references it would be possible to compute nutrient stress in terms of leaf area, CER, and dry weight. With the advent of bench and portable photometric devices the measurement of leaf area has become a rapid operation. If the area of intact leaves is measured, by either photographic standards or, better, electronic scanner, then it is feasible to consider using the expansion rate of selected individual leaves. This would be much quicker than measuring all leaves. In conclusion, leaf area increment must rank as one of the simplest and most meaningful parameters of growth for estimating nitrogen stress of plants.

D. CARBON DIOXIDE EXCHANGE RATE (CER)

Photosynthesis being the major process for accumulation of dry matter in the plant, its rate is likely to be closely correlated with growth rate as controlled by nutritional deficiencies. The rate of CER may be considered as the most

28

E. A. N. GREENWOOD

comprehensive single measurement that can be taken to indicate instantaneous growth rate of the plant. So it would seem to be an ideal way of obtaining a rapid assessment of nitrogen stress, or any other nutritional stress. In practice it has some limitations. First, the initial cost of the apparatus for determining carbon dioxide concentration (infrared gas analyzer) is great, its use in the field is a little cumbersome, and it has a high maintenance requirement. Second, the rate of CER varies diurnally and between days and seasons. Hence, a near instantaneous determination of CER is not integrated over these variations and will give a biased result. Of course, a more representative result can be obtained by taking several CER readings but this is tedious. If the value of CER of the deficient plant is E , and the corresponding value for a plant given a nonlimiting dose of nitrogen is E M ,then the expression for nitrogen stress becomes

SNE = 100 [(EM-~IEMI

(6) It seems to me that the use of CER in studying nutritional stress has its greatest application in laboratory or controlled environment studies when CER for a large number of treatments can be compared under a standard environment. Bouma (Section V, C) has made great use of this approach. Wolf and Greenwood (unpublished) found that CER measurements in the laboratory gave very satisfactory results in the estimation of nitrogen stress in wheat seedlings. The application of these techniques to physiological studies in the laboratory is taken further in Section VI. E. CONCLUSIONS

Five plant parameters have been proposed for estimating nitrogen stress-leaf nitrogen, dry weight, leaf elongation, leaf area, and CER. What are the criteria for choosing which one of these parameters (or any other which might be proposed) should be used? It has been argued that it is not feasible to measure nitrogen stress in a way similar to water stress, e.g., chemical potential, and that there is no single measurement that can be made which can be called “growth.” Therefore, for the present, practical considerations should be given high priority. The following criteria are helpful: (1) the parameter that has the greatest meaning for the objectives of the project (what measurements are being made irrespective of the measurement of stress); (2) the equipment and expertise that are available; and (3) the measurement that uses the least resources. VI. Applications

It might be said of agronomists in general that they tend to apply treatments, obtain an end result, and then speculate as to how the measured outcome

NITROGEN STRESS IN PLANTS

29

occurred. Those who rigorously examine processes and their interactions come to be called crop physiologists! The foregoing remarks are indeed an oversimplification and are not intended as a criticism insofar as there are obvious and compelling reasons why agricultural research does concentrate on yield of products. But it must also be said that there is an aversion to studying the processes underlying yield, which is largely due to the daunting complexities and the lack of practical techniques to resolve them. The previous sections of this article have been directed to developing concepts and techniques that promise some easing of these constraints with respect to nutritional aspects of agronomy. This section deals with their practical application with the aim of suggesting the easiest way of doing the job in a variety of circumstances.

A. AGRONOMY AND ECOLOGY

Consider the basic operation of cultivation. Let us say that in certain situations it has been found to improve crop yield. And let us suppose that appropriate research showed that cultivation controlled weeds, thereby reducing competition for light, water, nitrogen, and other nutrients. On the other hand, the supply of available nitrogen and other nutrients was increased through microbial activity and through greater root exploration, . . ,and so on. In the event, how much of the response to cultivation can be ascribed to the nitrogen status of the plant during successive stages of growth? And from this, what deductions can be made about the mechanism and the timing of the nitrogen effect on final yield? Could we avoid cultivation by substituting an appropriately timed application of nitrogen and weedicide, and, if so, which would be the better solution? A comprehensive way of obtaining answers to such questions would be to have a large number of plots allocated to cultivation treatments and rates and times of application of nitrogen fertilizer. A shortcut to answering some of the questions posed, though certainly not all of them, would be to restrict the experiment to the two cultivation treatments upon which SN would be determined over successive periods. If, in addition to nitrogen stress, one were to determine other stresses such as water and phosphorus, then the agronomist would be in a strong position not only to answer some of the questions about nitrogen but also to comment on the importance of nitrogen vis-A-vis phosphorus and water stress. Cultivation has been chosen as an example because data already presented (Table 111) as a partial illustration can be used. A knowledge of nitrogen stress of a crop at a particular time does not provide a direct and accurate answer to the practical question: How much fertilizer is required to reduce stress to an acceptable level? This is the price to be paid for avoiding the response curve. Naturally it provides a partial answer; that is, whether the amount of fertilizer required is zero, a little, or a lot. In most cases

.

30

E. A. N.GREENWOOD

this may be good enough unless the agronomist has available an integrating model that qualifies the current biological requirement by economic and marketing factors and also accounts for change in requirement with time. A decade ago most agronomists worked exclusively in agricultural ecosystems. They could rely on a strong background of research literature and unpublished knowledge on which to base their future research policies. In the seventies, with increasing emphasis on nonagricultural ecology many agronomists have been assigned to work on ecosystems with which they are unfamiliar and for which little “hard” data exist. When one is confronted with a new ecosystem to be studied, the first questions to be asked are, What are the important limiting factors? How do they interact? The answers provide such penetrating insight into an ecosystem that they are almost a prerequisite for rationalizing research priorities. For example, there seems little point in embarking early, if at all, on a research program of plant nutrition or nutrient cycling in an ecosystem if it can be shown that nutrients are not important limiting factors. Similarly, if nutrition is limiting plant growth then which element is the most limiting? The technique of evaluating nutrient stress is an efficient way of rating nutrients as limiting factors. The techniques described here for estimating nitrogen stress can also be adapted for other nutrients (e.g., Bouma er al., 1969), for temperature (Greenwood er aL, 1976), and for water (Power, 1971). The most elegant example of this approach is the study by Power (1971) on the northern Great Plains of the United States. In these grassland ecosystems both nitrogen and water were known to be limiting plant growth. Since rainfall declined to the west it was considered that water stress would increase in that direction and that nitrogen stress would increase to the east. Further, as soil water declined during the growing season, water stress was expected to increase. At any one location and at any one time, what were the respective limitations to plant growth by the two factors? Power estimated SNR by using nitrogen fertilizer. Concurrently, he estimated water stress, SWR (Sw in his article), by a comparable technique in which water stress was removed by irrigation. An extract of the results is given in Table VI. There was a strong interaction with time, but the two stresses were, in general, additive. It became clear that, for the particular situation studied, nitrogen was more limiting than water. The dry weight approach to stress used by Power is obviously appropriate for the arable grasslands of North Dakota. It would not be satisfactory for arid rangelands where the spatial distribution of plants is exceedingly variable and sparse. Here it would seem better to use a nondestructive method such as SNL , which has the real advantage for remote areas that there is no equipment to break down. M. A. Ross and M. Friedel (personal communication) are currently evaluating leaf elongation rate of grasses in arid rangelands of Central Australia with a view to estimating SN and S, as did Power. Ross is studying the selection of

31

NITROGEN STRESS IN PLANTS

TABLE VI Percent Stress on Top Growth of Bromegrass Due to Nitrogen and Water Deficiencies' Sampling interval Stress due to

4/28 to 5/22

5/22 to 6/10

6/10 to 6/30

6/30 to 7/22

56 stress A. Low basal N (0-N) N Water N + Water

73

4 1

57 83

8

61 22 73

104 61 103

B. Medium b a d N (9@N) N Water N + Water

-1 2 4

3 32 49

24 32 54

35 10 58

C. High basal N (270-N)

N

0

Water N + Water LSD (0.5)

4 5

-7 31 23

ns.

18

7 24 33 17

13 32 59 25

'Reproduced from Power (1971).

suitable tillers relating leaf elongation rate to dry weight increments, and developing meaningful ways of applying nutrients and water in remote and a n d locations. He has observed an initial surge in elongation rate for a few days following a subsurface application of water to plants under long-term water stress. A similar study of leaf area increment is envisaged for dicotyledons. If these techniques are successful they will be used to estimate the changes in SN and S, which occur after effective rainfall. A technique for estimating phosphorus status using the dry weight response of detached leaves when placed in solutions with and without the element, has been developed by Bouma and Dowling (1976). It should be adaptable to evaluating nitrogen stress. The approach seems appropriate to those situations where water is nonlimiting and where the standard conditions of response imposed match the cultural conditions of the plant, as in the laboratory. In the field the technique would be most useful where the nutrient in question is the major limiting factor, otherwise some bias in the magnitude of response may develop. Further work on the development of this technique is proceeding (Bouma, personal communication).

32

E. A. N.GREENWOOD B. STRESS PHYSIOLOGY

If functional relationships between nutrient deficiency and specific plant processes are to be established, then two conditions must be met. First, the deficiency must be expressed in terms that arise from the plant itself as distinct from some external supply term. Second, the stress must be expressed numerically. The general failure of nutritional physiologists to meet these two conditions has led to a crippling weakness in research in, and also an avoidance of, this field. It is indicative that the abstracting journal Current Advances in Plant Science cites very few papers dealing with nutrient stress in Section 21 on Stress physiology. It must be admitted that some of the techniques of estimating nitrogen stress, as have been reviewed here, are barely adequate to meet the precision and speed often required by physiologists, particularly in the laboratory. Three suggestions follow. The most suitable technique for physiologists so far discussed is that by Bouma for the determination of CER using the infrared gas analyzer. Either the whole plant or a selected leaf can be used. CER determinations are made in the deficient plant and on a comparable plant for which nitrogen stress has been removed by an adequate addition to the nitrogen supply about 2 days prior to the measurements. The major requirements are a controlled environment chamber, an infrared gas analyzer, and an air-sealed photosynthesis chamber of appropriate geometry (Wolf et aL, 1969). Wolf and Greenwood (unpublished) have designed an extremely simple and sensitive arrangement for determining SNE in grasses and cereals on a relatively large scale. In this system the whole controlled environment chamber becomes the equivalent of the mixing chamber of the above-mentioned air-sealed device in which pots can be placed. The air in the large chamber is homogenized with one or more fans. The leaf is inserted in a glass tube through which the homogenized air is continuously drawn. Reference air is similarly sampled and both streams are led to the external analyzer which determines CER by the difference method. A large battery of plants can be harnessed prior to a run and the tubes may be left on the leaves indefinitely, provided that the leaf does not expand beyond the dimensions of the tube. Speed and precision can be obtained with this arrangement. A manifold of 2-way taps is installed outside the growth chamber so that when the air from a particular leaf is not being analyzed it will still be drawn over the leaf by another pump at the same rate. This reduces equilibration time within the tubing almost to zero and allows successive determinations of CER t o be made at about 2-minute intervals. Some simple precautions must be taken to isolate the air inside the growth chamber from the massive fluctuations in carbon dioxide which may occur outside. The resolution

33

NITROGEN STRESS IN PLANTS

and precision of this technique is demonstrated indirectly in Fig. 4,and, of course, it is nondestructive. Wolf and Greenwood used the technique only for one type of situation, but it seems capable of wide adaptation within a controlled environment. A further nondestructive laboratory technique is available for obtaining shortterm weight changes such as would be required by whole-plant physiologists. This is the weighmg technique of Amott et al. (1974), which permits separate live weighings of tops and roots of plants to be made at frequent intervals and with changes in nitrogen supply. Very good estimates of SN on a fresh weight basis can be obtained with this device while the plants themselves are available for other physiological measurements. Two units would be required for each estimate of stress.

C . MODELING

The concepts of nutrient stress can be of direct use to modelers of plant growth in at least two ways. First, a prior knowledge of the stress values for several nutrients allows the modeler to rank the elements in order of importance. He can then filter out the unimportant elements. Second, if the model first generates a potential growth rate which in turn is successively reduced according to the constraints from each important element, then the stress values themselves will be appropriate terms to govern the magnitude of those reductions without necessarily calling on a nutrient supply subroutine. Where the supply of the nutrient, say nitrogen, is also being generated then stress can be estimated through the following steps.

F;-iG J , ,T , , , -( _ty/ {-iziq = supply

controller

increment

CO, ,etc.

I Actual increment

Nitrogen demand is estimated by computing the product of the potential dry matter increment and the nitrogen concentration in the plant. The concentration is derived from a curve of the time course of nitrogen for a plant grown on a nonlimiting supply of nitrogen. This information requires minimal experimentation. The supply of nitrogen is generated by the supply subroutine. The final step is to reduce the potential dry matter increment by a proportion given by the ratio N supply/N demand, which is, of course, a term similar to nitrogen stress.

34

E. A. N. GREENWOOD VII. Conclusions and Aspirations

In this article the opinion has been expressed that the discipline of plant nutrition has badly neglected the quantification of deficiency. It has been suggested that the conventional approaches to deficiency through response curves and tissue analyses are inadequate bases on which to quantify deficiency rigorously except in special circumstances. By analogy with water stress, an attempt has been made to establish the basic requirements for a concept of nutrient stress and a proposal has been offered on how they might be put into practice. But the latter has proved too difficult to accomplish without some compromise and there has been insufficient experimentation to evaluate fully the several techniques available. It is hoped that this article will stimulate the evolution of plant nutrition whether it be through the development of the ideas presented or through more fruitful ideas arising from them.

ACKNOWLEDGMENTS The author is grateful to Dr.J. F. Power, Dr. M. A. Ross, and Dr. D. D. Wolf for supplying unpublished data and to Dr. N. J. Barrow, Dr. D. Bouma, and Mr.G. B. Taylor for their help with the manuscript. The use of leaf elongation was suggested by Dr. R. F. Williams. The work with Dr. Wolf was done while the author was a guest of Virginia Polytechnic Institute. Special thanks go to Dr.R. C. Rossiter for the many enjoyable arguments over the concepts of nutrient stress.

REFERENCES Allen, R. S., Worthington, R. E., Could, N. R., Jacobson, N. L., and Freeman, A. E. 1961. J. Agr. Food G e m . 9,406-408. Amott, R. A., Brockington, N. R., and Spedding, C. R. W. 1974. J. Exp. Bot. 25, 1124-1 136. Bouma, D. 1967a. Aust. J. Biol. Sci. 20, 51-66. Bouma, D. 1967b.Aust. J. Biol. Sci. 20,601-612. Bouma, D. 1967c. Aust. J. Biol. Sci. 20,613-621. Bouma, D. 1969a. Aust. J. Agric. Res. 20,435-445. Bouma, D. 1969b. Aust. J. Biol. Sci. 22,523-533. Bouma, D. 1970a. Ann. Bot. 34,1131-1142. Bouma, D. 1970b. Ann. Bot. 34,1143-1153. Bouma, D. 1970c. Proc. Int. Grassl. Congr., 11th. 1970 pp. 347-350. Bouma, D. 1971. Aust. J. Agric. Res. 22,723-730. Bourn, D. 1975. J. EXP.Bot. 26,42-59. Bouma, D., and Dowling. E J. 1966. Aust. J. Agric. Res. 17,647-655. Bouma, D., and Dowling, E. J. 1967. Aust. J. Agric. Res. 18,223-233. Bouma, D., and Dowling, E. J. 1969a. Aust. J. Biol. Sci. 22,505-514. Bouma, D., and Dowling, E. J. 1969b. Aust. J. Biol. Sci. 22,515-521.

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Bouma, D., and Dowling, E. J. 1976.Aust. J. Agric. Res. 27,5342. Bouma, D., Spencer, K., and Dowling, E. J. 1969.Aust. J. Exp. Agric. Anirn. Husb. 9,

329-340. Bouma, D., Greenwood, E. A. N., and Dowling, E. J. 1972. Aust. J. Biol. Sci. 25,

1147-1 156. Chapman, H . D., ed. 1966. “Diagnostic Criteria for Plants and Soils.” Div. of Agric. Sci., Univ. of California. Goodall, D. W., and Gregory, F. G. 1947. Cornrn. Bur. Hort. Plant. Crop (G. B.) Tech. Cornmun. 17. Greenwood, E. A. N. 1966.Plant Soil 24,279-288. Greenwood, E. A. N., and Titmanis, Z. V. 1966.Plant Soil 24,379-389. Greenwood, E.A. N., and Titmanis, Z. V. 1968.Aust. J. Agric. Res. 19,9-14. Greenwood, E. A. N., Goodall, D. W.,and Titmanis, Z.V. 1965.Plant Soil 23,97-116. Greenwood, E. A. N., Boyd, W. J. R., Wiitchead, J. A., and Titmanis, Z. V. 1970.Ausf. J. Exp. Agric. Anirn. Husb. 10,763-767. Greenwood, E. A. N., Carbon, B. A., Rossiter, R. C., and Beresford, J. D. 1976.Aust. J. A g r k Res. (in press). Hake, N. J., Greenwood, E. A. N., Lapins, P., and Boundy, C. A. P. 1969. Aust. J. Agric. Res. 20, 987-998. Hsiao, T. C. 1973.Annu. Rev. Plant Physiol. 24,519-570. Hsiao, T. C., Acevedo, E.,and Henderson, D. W. 1970.Science 168,590-591. Hylton, L. O., Jr., Williams, D. E., Ulrich, A., and Cornelius, D. R. 1964. Crop Sci. 4,

16-19. Power, J. F. 1971.Crop Sci. 63,726-728. Rauschkolb, R. S., Brown, A. L., Quick, J., Prato, J. D., Pelton, R. E., and Kegel, F. R. 1974a. Calif: Agric. 28, 10-12. Rauschkolb, R. S., Brown, A. L., Sailsbury, R. L., Quick, J., Prato, J. D., and Pelton, R. E. 1974b.Calif:Agrk. 28, 12-13. Scott, D. 1961.N.Z.J. Agric. Res. 4,282-285. Smith, P. F. 1962.Ann. Rev. Plant Physiol. 13,81-108. Taylor 1968. In “Water Deficits and Plant Growth” (T. T. Kozlowski, ed.), Vol. 1, pp. 49-72. Academic Press, New York. Titmanis, Z. V., and Greenwood, E. A. N. 1969.Field Stn. Rec. 8,9-16. Ulrich, A. 1950.Soil Sci. 69,291-309. Wadleigh, C. H.,and Gauch, H.G. 1948.Plant Pfiysiol. 23,485-495. Watson, D. J. 1963.Proc. Easter Sch. Agric Sci., 10th pp. 233-247. Williams, C. N., and Biddiscombe, E. F. 1965.Aust. J. Agric. Res. 16,14-22. Williams, R. F.,Evans, L.T., and Ludwig, J. 1964.Aust. J. Agric. Res. 15,231-233. Wolf, D. D., Peace, R. B., Carbon, G.E., and Lee, D. R. 1969.Crop Sci. 9,24-27.

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STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

.

Rodney J Arkley Department of Soils and Plant Nutrition. College of Natural Resources. University of California. Berkeley. California

............. ..................... ..............................................

I . Introduction: Objectives and Problems of Soil Classification

11. Numerical Taxonomy or Cluster Analysis of Soils

A. GeneralTheory B. Dataselection .............................................. C. Weighting and Standardization of Variables ........................ D. Measures of Similarity or Difference .............................. E Sorting Strategies ............................................ F . Presentation of Results of Sorting Procedures ...................... 111. Ordination of Soils .............................................. A . Q-TypeOrdination ........................................... B. R-Typeordination ........................................... C. Presentation of Results of Ordination ............................. IV . Soil as an Anisotropic Entity ...................................... A . Soil Profile as an Array of Soil Properties .......................... B Soil Data by Layers or Horizons ................................. C. Soil Profile as an Array of Depth Functions ........................ V . Statistical Methods for Comparing Classifications ...................... A . Cophenetic Correlation ........................................ B Coefficient of Association ..................................... C. Wilk's Criterion .............................................. VI . Conclusions and Evaluation ....................................... A The Choice of Methods ........................................ B. A Suggested Procedure for General Soil Classification ................ References ....................................................

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37 39 39 40 41 45 47 52 54 55 56 58 59 60 61 63 63 64 64 64 64 65 67 68

I . Introduction: Objectives and Problems of Soil Classification

The purpose of classification is to organize the members of a large population of objects into groups or classes of objects so that the nature of. and relationships between. the objects can be more easily understood . This purpose may be limited to understanding related to a specific purpose such as the irrigability of soils and based upon only those attributes relevant to the purpose; or the purpose may be to develop a more general classification based upon as many 37

38

RODNEY J. ARKLEY

attributes as possible and useful for a wide range of purposes. Most of the research reported herein is of the latter kind with a few exceptions. Prior to 1955 when Hughes and Lindley first used a statistical procedure to reclassify members of six soil series, soil classification was based primarily on subjective judgment. That is not to say that the judgment applied has not been good; some of the best minds in soil science have been focused on soil classification. Nevertheless, both the selection of criterion variables for classification, their effective weighting by application at different categorical levels in a hierarchical classification, and of boundary values for separations have all been made primarily on the basis of fallible human judgment. Although some statistical analysis was carried out on soil data prior to 1955, the amount was limited primarily by the tedium of statistical analysis and the hand sorting of data. However, with the development of the electronic computer this tedium has been removed, and the application of numerical and statistical methods to soil classification has developed rapidly as indicated by the number of references cited in this paper, most of which deal directly with soil classification. To be both comprehensible and most effective, the differentiating characteristics or criterion variables used to form classes should contain the maximum possible information. That is, they should be those which have the most predictive value for the nature and behavior of the soil when subject to external influences. These criterion variables then should be those which are covariant with other properties (accessory characteristics) not used as criterion variables. The number of soil characteristics that might be used for soil classification is very large, and the selection of criterion variables from this list is very likely to be suboptimal by subjective methods. However, the covariance among all variables can readily be examined with the use of the computer by calculating the product-moment correlation coefficient between all pairs of variables and with direct examination or analysis of the resulting correlation matrix. On this basis an optimal set of differentiating characteristics can be chosen. Gibbons (1968) effectively argued the importance of covariance to the usefulness of soil classification. The extent to which soil properties are covariant will be discussed later in this paper. Soil classification in the past has been primarily hierarchical in nature, with one or more criteria used at each categorical level to divide soils into mutually exclusive classes. Such a classification is helpful in the understanding of relationships among soils, but some relationships may be seriously distorted. This occurs when a group of soils which is relatively similar in all other respects, is subdivided into two groups at all lower categorical levels by small differences in a particular differentiating characteristic. This is a general problem of hierarchical classification, in that it is a divisive procedure and the divisions are dichotomous; that is, they either have or have not a certain property or the value of a certain measured property is above or below a specified level. Avery (1968)

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

39

points out that a successful hierarchical classification can be made only if the differentiating criteria can be ordered in accordance with the number of other attributes (accessory characteristics) associated with them. He points out further that soil variation is not of this character, presumably because soil characteristics result from the interaction of several factors. This is the crux of a major problem in soil classification. Are soils to be considered as made up of discrete natural individuals, or do the individual soil profiles represent points in a multivariate continuum, which considered as a whole contains no distinct boundaries for purposes of classification? Experience has shown that soils may occur as discrete, relatively homogeneous bodies when considered only within a local area. But as investigations extend to broader areas more and more soils of intermediate character are encountered which bridge the gaps between the original discrete soil bodies. This leads to problems in soil correlation. The recognition and identification of soil classes, such as soil series in the field, in the face of this kind of soil variation is the bane of the soil surveyor’s existnece. His decisions must be made primarily on the basis of field observations of a number of soil characteristics, and the soils classified on the basis of variations in one or many of these simultaneously. Avery (1968) argues forcefully that a coordinate system of classification is more appropriate for soils than a hierarchical system. The advantage to a coordinate system being that each differentiating criterion is given equal weight, at least a priori. It should be pointed out also that a coordinate system can be used to construct a number of hierarchical systems, by arranging the differentiating criteria in different categorical orders. In the following discussion of the various statistical methods applied to soil classification, it will be observed that much of the work has assumed that soils (mainly soil profiles) fall into natural clusters or groups which can then be ordered into a classification. For the limited sets of soils used, this appears to be a correct assumption. Although little work has been done toward the development of a coordinate classification scheme, it is made clear that some of the statistical methods described can be used effectively for this purpose assuming that soil characteristics vary in such a way as to form a continuum through the whole population of soils. A method is suggested by which soils can be classified using a set of well-separated centroids or conceptual modal soils and classes formed on the basis of the general affinity of real soils to the centroids. II. Numerical Taxonomy or Cluster Analysis of Soils

A. GENERAL THEORY

Numerical taxonomy is defined by Sneath and Sokal (1973) as the grouping by numerical methods of taxonomic units into taxa on the basis of their

40

RODNEY J. ARKLEY

character states. Groupings are formed using the following general procedures: First, data for a number of units, such as soil profiles, are assembled including a sizable number of selected variable properties for each unit. Because this discussion is confined to the classification of soil units, they will be simply referred to as soils. The data are commonly arranged into a matrix consisting of soils by columns and soil properties by rows. Next an over-all estimate of resemblance is obtained between pairs of soils by some mathematical function of all differences between the values for each property of the two soils. After numerical values for the estimate of resemblance (either estimates of similarity or of difference can be used) between all pairs of soils included in the study are obtained, the matrix of n(n-1)/2 values is subjected to a sorting strategy which forms groups of similar soils. The nature of the groups formed and their relationships or taxonomic structure can be presented in various ways; these may include dendrograms, reordered matrices, ordination, or simply tables of coordinates.

B. DATA SELECTION

The choice of soils to be included in the data should be such that the number of soils is large and the general kinds of soils included are well represented. For example if the soils included are mainly well drained and without evidence of wetness, then the inclusion of a very few poorly drained soils may interfere with the analysis because those. soil properties associated with wetness may not be representative of the range of variation in those properties. Tllis is particularly important in cluster analysis as the order of cluster formation is affected by the number of soils in the clusters or groups formed in some clustering techniques. The selection of soil properties is even more important to a successful analysis than the selection of soils. Although all kinds of both field and laboratory data can be used, there are certain kinds that should be excluded or that need special treatment. Some soil properties, such as the field moisture content, are generally irrelevant to soil classification and should be excluded. Logically correlated properties, such as dry and moist colors, are generally so highly covariant that one or the other should be included. Particle size distribution values for sand, silt, and clay always add up to 100% and so one of the three should be eliminated from the data. The inclusion of large numbers of logically related properties should be avoided, as they tend to create an inadvertent extra weight to such a group of properties in the classification. For example, in the initial list of properties used by Sarker et ul. (1966) were 6 particle size ratios, 5 of which were intercorrelated above the 0.90 level. This kind of redundancy among properties should be avoided or dealt with by analysis of variables as discussed later in this paper. Soil data obtained from laboratory analysis are almost always continuous

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

41

variables as are a number of field measurements such as thickness and depths of recognizable characters. Hue, value, and chroma (soil color) are continuous variables even though the color chart commonly used is made up with discrete steps. However, field observations such as soil texture, structure, and consistency are usually discrete or multistate variables and need to be treated with special care. Data of this kind should be coded in such a way as to reflect their proper rank order reflecting their importance to soil behavior or development. For example, soil texture classes might be coded in order of their relative clay content or water retention characteristics. Structure is a particularly difficult soil property to code as a ranked multistate variable. For surface soils an appropriate order of structure type might be single grained, massive, platy, crumb, granular, subangular blocky and angular blocky; for subsoil layers the order might be single grained, massive, platy, granular, subangular blocky , angular blocky, prismatic, and columnar. Structure grade or distinctness such as weak, moderate, and strong coded 1, 2, 3 might well be multiplied by the code for structure type coded 0 to n and a value for size of peds added to give a single value for type-grade-size of structure. The system suggested is only one of many possible ways that soil structure might be treated. Arkley (1971) and Cipra et al. (1970) have used type and grade omitting structure size with some success. Barkham and Norris (1970) treated soil structure type, grade, and size as separate characters. Soil color mottling is troublesome to code. Cipra et al. (1970) used a combination of abundance, size, and contrast of mottles scaled from 0 to 8. Cuanalo and Webster (1970) used abundance percent and position on peds separately. Rayner (1966) used abundance, size, and contrast as separate variables. Dichotomies such as the presence or absence of earthworms, concretions, carbonates, iron pans, manganese stains are sometimes used (Rayner, 1969; Muir et al., 1970). Dichotomies require special treatment which will be discussed in relation to the standardization of variables. The same is true for unranked multistate variables.

C. WEIGHTING AND STANDARDIZATION OF VARIABLES

I . The Problem of Weighting of Variables Sneath and Sokal (1973) present cogent arguments in favor of weighting all variables equally, especially where a classification is intended t o be a “natural” or basic classification for general use rather than one for a specific objective. These arguments against “a priori” weighting appear to be on sound rational grounds. This is in direct opposition to the methods of orthodox or conventional

42

RODNEY J. ARKLEY

hierarchical classification wherein the differentiating characteristics used at higher categorical levels take precedence over those at lower levels, and therefore have greater effective “weight.” For example, in the Soil Classification of the Soil Survey Staff, U.S. Department of Agriculture (1960), certain diagnostic horizons are considered more important than others; a case in point is the use of the mollic epipedon at the “Order” level to separate the Mollisol soil order from other orders, irrespective of the nature of the subsoil horizons to a large degree, whereas most of the other orders are separated on the basis of the nature of subsoil horizons. Decision such as the one cited are based on intuition or human judgment, both of which are fallible. Sneath and Sokal (1973) also argue in favor of the use of a large number of variables (i.e., soil properties) in numerical taxonomy, on the grounds that the use of variables greatly evens out the effective weight which each one contributes. This argument presupposes that all pertinent groups of covariant properties are about equally represented in the data. In the data used for numerical classification research on soils, this is clearly not true in many cases. Some kinds of measurement on soil properties are more easily obtained than others, or have been of more interest to the investigator, and so are overrepresented and thus unduly weighted. Also the use of a large number of variables involves a great deal of time and expense, especially if the classification is intended to encompass a large number of individuals. However, in the first stages of analysis, the use of a large number of variables standardized so as to give equal weight to each is certainly a sound approach. For the final classification it may be possible to reduce the number of variables to a manageable but still effective size by analysis of the covariance among them.

2. Covariant Soil Variables In the past, covariance among soil variables was rarely analyzed, but with the advent of electronic computers the tedium of the calculation of correlation coefficients has been removed. In several papers involving numerical taxonomy of soils, correlation matrices have been published, revealing how much covariance exist among soil variables. Moore and Russell (1967) analyzed 10 trace elements in 28 soil profiles and found that the correlation matrix of 45 r-values contained 27 which were significant (P < 0.01) and ranging from 0.49 to 0.90; Moore et al. (1972) show 50 of 91 r-values significant (P < 0.01) ranging from 0.18 to 0.80 for 14 variables in 4 layers of 40 soils. Sacker et al. (1966) found that 39 of 61 soil properties were correlated with at least one other at the level of r > 0.50; Russell and Moore (1967) show 57 of 136 r-values significant (P>0.01) ranging from 0.40 to 0.80 for 17 variables and 43 soils. Reexamination of my own data sets used for analysis of variables also revealed similar levels of communality among variables as shown in Table I (Arkley, 1971).

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

43

TABLE I Number of Variables SigniFcantly Correlated with other Variables in Analyses Reported by Arkley (1971) Variables with rvalues significant at P < 0.01

Number of

Soils

Variables

59

621 220 81 87

1+

>2

21 23 34

4 1 7 0 23

8 21

0

34

44

0

53

2

44 51

30 42 46

0

>4 1

20 26 40 38

The extensive covariance among soil variables in the widely differing data sets described in Table I is strong evidence that a long list of soil variables is not necessary to classify soils effectively by either conventional or numerical methods. Also, it is evident that analysis of variables should be among the first steps in the development of a classification system. There should be no objection to weighting variables according to their predictive values as revealed by the analysis of variables as this would not be considered a priori weighting.

3. Standardization of Variables Most procedures for obtaining an estimate of resemblance require that the variables be standardized to a common range of values. It is clearly inappropriate to compare differences in a variable with a range of 0.0 to 1.0 with those in a variable with a range of 100 to 1000. For continuous variables standardization may be by range, i.e.,

x' = (x- Xndn) I x,,

-~ m i 1 n

or by variance, i.e .,

X'=(X-X)/SDx The former gives each variable a range of 0.0 to 1.O, the latter a mean of 0.0 and a standard deviation of k1.0. These methods can also be applied to ranked multistate variables, but with more risk of injecting spurious information. For data containing both continuous and discrete variables, either dichotomous or multistate, Crigal and Arneman (1969) applied a method proposed by Talkington (1967): For a variable that can assume a number of discrete and mutually exclusive states (i.e., soil structure types) which is coded as 1.O for no

44

RODNEY J. ARKLEY

more than one of these states and 0.0 for all others, the maximum possible contribution to the differences or the sum of the square of the differences between two individuals is 2.0 (Table 11). Continuous variables are therefore standardized so that the maximum contribution to the squared difference is also 2.0; such variables are standardized by range and then multiplied by 21'2 or 1.414.

Another method for equalizing the contribution of discrete and continuous variables based upon information theory has been developed by Burr (1 968) but so far has not been applied to soils. Continuous variables are standardized to a mean of 0 and a standard deviation of +21n by the formula

x'=(X-X)/(1.414X SDx) And dichotomous and multistate variables by the formula

M 2= M(t-1) /

[2tp, (s, - I)]

where M' is the standardized variate, M is an unstandardized variate (as coded in Table 11), t is the total number of individuals (soils) with nonmissing data,p, = the proportion of t in state s(sn/t), sn is the number of individuals in state s, and ,S is the number of possible states of variate M. Burr proposes to call this procedure standardizing by reciprocal proportions since the weight of each state is weighted inversely to its frequency of occurrence @,). The formula given above weights a multistate variate M equally with a continuous variable. If one considers that each state s should be weighted equally with a continuous variable, then the parameter S (, - 1) can be omitted from the formula. The problem of highly skewed data should be considered in the standardization of variables. In some cases it would be appropriate to use a logarithmic or square root transform for known skewed distributions as was done by Moore and Russell (1967). Talkington (1967) advocates a slight truncation of the range for extreme values which occur very rarely as was done by Grigal and Arneman TABLE I1 Individuals Variable states (s) $1

Sl s3

84

Difference A

B

(4

0 1 0 0

0 0 0 1

0 1 0 1 2

d' 0 1 0 1

2

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

45

(1969). In this connection it should be pointed out that the use of ratios as data variables may well lead to highly skewed distributions because of the hyperbolic nature of ratios; in general they should be avoided. In any case a careful examination of the data for errors or aberrant data should precede the analysis, simply as a good analytical practice. Where highly skewed variables are suspected, they should be examined in a frequency distribution and perhaps plotted against related variables in a scatter diagram before a decision is made as to their treatment. D. MEASURES OF SIMILARITY OR DIFFERENCE

Various procedures are available for calculating an over-all estimate of resemblance, which can be based upon measures of either similarities or differences. Sneath and Sokal (1973) use the term “similarity coefficient” t o cover coefficients both of similarity and of dissimilarity; the one being the complement of the other. They describe four somewhat fuzzy classes of similarity coefficients as (1) distance Coefficients, (2) association coefficients, (3) correlation coefficients, and (4) probabilistic coefficients, of which the first and third have been used in soil studies most commonly. 1. Distance Coefficients

The simplest practical form of “distance” measure called mean character difference (MCD) is: where Xi . . . n are standardized variates and j and k are two individuals such as soil profiles. However, this coefficient is rarely used and suffers from the fact that a large difference in a single variable is inadequately represented in the coefficient. MCD has been applied by Moore and Russell (1967) and Webster and Burrough (1972). A much more commonly used distance coefficient is the familiar Euclidean distance (d) in the form: d , k = [ a i (X,j-X,)’ i= 1

1

lR

The expression l / n is introduced into the equation in order to equalize differences introduced by missing data, or differing numbers of variates used. The average Euclidean distance coefficient has the advantage of being more readily visualized and can be plotted in two or three dimensiocc although not in n-space where n is greater than 3. It also has other statistical properties which are advantageous. This coefficient has been used in soil studies by Cipra et al. (1970), Crichton (1975), Grigal and Arneman (1969), Moore et al. (1972),

46

RODNEY J. ARKLEY

Lamp (19721, and Webster and Burrough (1972). Cuanalo and Webster (1970) used d2 rather than d. Another distance that has been used several times is referred to as the Canberra metric (dc). It was developed by Lance and Williams (1967b) and has the advantage of needing no prior standardization of variables. It is in the form of n

dc

=z

<&j-X% I)/(&j

+ Xik)

i= 1

However, it has the unfortunate characteristic that a difference in the upper part of the range of a variate (i.e., when the denominator is large) is minimized as compared to an equal absolute difference in the lower part of the range and thus is sensitive to proportional rather than absolute differences between individuals (soils). Another coefficient of similarity [of Bray and Curtis (1958)l was applied to soils by Hole and Hironaka (1960), the first to use numerical taxonomy in soil classification, and later by Bidwell and Hole (1964), Bidwell et al. (1964), Sarkar et ul. (1966), and Moore and Russell (1967). The Similarity Index (SI) mathematically restated is: n

n

i=l

i=1

SIB = z IXi, - X, I / z (Xij + X,)

All variables must be standardized to a common range and positive in sign. It is particularly useful where the data are all in percentages as in species composition of plant communities. Another distance coefficient, Mahlanobis D 2 , is suitable only for use with predetermined groups of individuals. It was applied to soils by Hughes and Lindley (1955) and by Van den Driessche and Maignien (1965). It is based on comparisons of variances within and between groups and is closely allied to discriminant function analysis. However, it is computationally involved and heavily dependent upon multivariate normality. The reader should consult Sneath and Sokal(l973) and Rao (1948) for details of the method.

2. Simple Matching Coefficient For data coded as two state characters (0 and l), a simple matching coefficient (S,) can be used. S, is simply the number of matches 2 vs. 1 or 0 vs. 0) divided by the total number of matches and mismatches. A related coefficient called the coefficient of Jaccard (SJ)omits zero matches from both the numerator and denominator. The coefficient S, was examined by Moore and Russell (1967) but was applied to continuous variables by coding data in rank intervals. This involves considerable loss of information content, and so is not recommended. It was also used for classifying soil bacteria by Brisbane and Rovira (1961). The coefficient of Jaccard was used by Varty and White (1964) to classify montmorillonite clay.

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

47

3. Correlation Coefficients The product moment correlation coefficient (r) has also been used as a similarity coefficient in soil studies (Cipra et al., 1970; Cuanalo and Webster, 1970; Dryden, 1935; Moore and Russell, 1967; Moore et al., 1972; Russell and Moore, 1967). However, the use of r in this way has several disadvantages in soil classification. It is a measure of pattern rather than of magnitude of difference; for example if the values of Xq are 1, 2, and 3, and of X i k are 7, 8, and 9, then r j k = 1.0 indicating the individuals j and k are identical, while they evidently differ in terms of magnitude. Another problem arises in ranked multistate variables, in that the direction of scaling may influence the sign of the correlation coefficient as pointed out by Eades (1965).

4. Comparison of Similarity Coefficients Moore and Russell (1967) compared the results of using five different similarity coefficients, namely, (1) simple matching Coefficient (Sm),(2) mean character difference (MCD), (3) Euclidean distance (4,(4) the Canberra metric &), and (5) correlation coefficient (r). They concluded that the Euclidean distance is probably most appropriate for soils because it is sensitive to magnitude, is metric, and provides a model that can be readily visualized. Webster (1975) criticizes the Euclidean distance measure because of its sensitivity to magnitude, in that a single large difference makes a disproportionate contribution to the calculated dissimilarity between pairs of individuals. This might be true in the case where only a very few soil properties are used; but where a larger number is used, say 15 or more, then the contribution of a single large difference is less and appears to the author to be appropriate for soil classification. Euclidean distance is especially useful for data containing all continuous variables, and can be used effectively for mixed data containing both continuous and multistate variables. For data consisting mainly of 2-state variables, the simple matching coefficient (S,) or the Coefficient of Jaccard (SJ)would be more appropriate.

E. SORTING STRATEGIES

Generally, the matrix of pair-wise similarity coefficients produced from the analysis of the data matrix is very large as the number of pairs is equal to n(n-1)/2, where n is the number of individuals. Thus the similarity matrix usually cannot be adequately interpreted by simple visual inspection. A large and confusing array of sorting strategies have been developed for describing the

48

RODNEY J. ARKLEY

pattern of relationships within the matrix. At least ten different methods have been applied to soil data of which only the more commonly used will be described in any detail. Sneath and Sokal (1973) describe the various methods and combinations of methods for sorting a similarity matrix in “Taxonomic Structure.” The most commonly used procedures in soil studies are included under systems called “sequential, agglomerative, hierarchic, nonoverlapping clustering methods” by Sneath and Sokal. In these procedures, the first step is a search of the matrix for the most similar pair (or pairs) of individuals (maximum similarity or minimum difference) which are joined to form the initial cluster(s). Then the matrix is reexamined for maximum similarity among remaining pairs or individuals or between individuals and prior clusters or between pairs of prior clusters, and the most similar pairs are joined to form new or enlarged clusters. This process is repeated until all individuals are accounted for, and the degree of similarity at each combination recorded. The results are generally presented in the form of a dendrogram or a phenogram, as it is called by Sneath and Sokal. This seems to be a perfectly straightforward method, but there are a variety of algorithms available for the definition of maximum similarity between clusters of individuals and clusters.

1. Single Linkage or Nearest Neighbor Clustering

This method uses the criterion for joining based upon the two most similar individuals between the two clusters. This procedure has the undesirable characteristic of frequently leading to long, wandering clusters; a result that is referred to as “chaining.” Nevertheless, single linkage clustering has been used by a few soil scientists, namely Anderson (1971), Rayner (1966), and Muir et al. (1970), and it has been compared with other methods by Moore et al. (1972). 2. Complete Linkage or Farthest Neighbor Clustering This method forms clusters directly opposite in character to those formed by nearest neighbor sorting. It is based upon the similarity of the least similar pairs of individuals in the two clusters. It forms tight, hyperspherical clusters which join others generally at low levels of similarity and often leave a number of isolated individuals.

3. Average Linkage Clustering This most commonly used clustering methods in soil studies are intermediate between the extremes of the two methods described previously and are forms of arithmetic average linkage methods. The simplest form is the unweighted pair-

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

49

group method using arithmetic averages (UPGMA) and was first used by Rohlf (1963). Individuals or clusters are joined on the basis of the average similarity between all pairs of individuals in one cluster and those in another cluster, after the initial pair or pairs are joined. This method is thus based upon average between-group differences and produces results very similar to the more exact centroid sorting described below. It has been used in soil studies by Anderson (1971), Barkham and Norris (1970), Bidwell and Hole (1964), Bidwell et al. (1964), Cipra et al. (1970), Cuanalo and Webster (1970), and Sarkar et al. (1 966). Unweighted pair-group centroid method (UPGMC) is similar to the WGMA method except that it is based upon the centroid of each cluster, which is calculated from the original data considered as coordinates in n-space for n variables or from the scores of individuals in n-space for n-dimensions derived from analysis of variables. The centroid is defined as the average coordinates of the members of a cluster. For soil studies this is an attractice method because the centroid of a group of soils is conceptually akin to the modal soil concept of the soil series, in which the modal soil is considered to be one near the centroid of the members of that soil series. It also can be represented accurately in two or three dimensions using 2 or 3 standardized variables or factor score dimensions. UPMGA usually gives similar results but it lacks the latter advantage. Unweighted centroid sorting has been examined by Anderson (1971), Campbell et al. (1970), Cuanalo and Webster (1970), and Moore and Russell (1967). Weighting can be applied to the calculation of either the arithmetic average or the centroid method. These are called “weighted pair-group method using arithmetic averages” (WPGMA) and “weighted pair-group centroid method” (WPGMC), respectively, by Sneath and Sokal (1973). In these procedures the individual most recently added to a cluster is weighted equally with all previous members of the cluster. The WPGMA method was used by Grigal and Arneman (1969) but they gave no reason for its selection. There seems to be no rational purpose in using this kind of weighting for soils.

4. Variable Group Clustering Rather than permitting clusters to form by pairs of individuals and/or clusters, it is possible to allow several individuals and/or clusters to join at a single step in the procedure. This requires that an arbitrary criterion level of similarity be specified at each step in the clustering for joining individuals or clusters. The criterion may be based on the change of average within-group similarity introduced by the merger after the first step in which initial clusters are formed by joining individuals above another specified criterion level of similarity. Variable-group centroid sorting is also amenable to an iterative procedure which converges on a stable configuration. As individuals are added to initial

50

RODNEY J. ARKLEY

clusters formed with specified within-group similarity, the centroids are shifted, possibly in the direction of individuals on the outer fringe of other clusters. So after the first clustering, the centroids are established and all individuals are reallocated to the centroid which has the most similar coordinates (closest in n-space). This process is reiterated until the centroids remain stable. Usually, only a few iterations are required, Unweighted variable-group centroid sorting with iteration was used by Arkley (1968, 1971); criteria for joining were based upon change in within-group variance. Cuanalo and Webster (1970) compared a weighted variable-group method with weighted and unweighted pair-group methods and found the results to be very similar for the three sorting strategies. Sokal and Sneath (1963) describe the variable-group methods, but in their later book (Sneath and Sokal, 1973) they indicate that there is little to choose between the methods and so omit the variable-group procedures, mainly because they are more difficult to program for the computer than pair-group methods.

5. Flexible Sort Clustering Lance and Williams (1967a) developed a general formula for S A H N clustering procedures in the form D(i,j),k=aiDi,k+ajDj,k + bDi,j+ cIDi,k-Dj,kI

where D is a measure of difference or dissimilarity, i and j are a joined pair of individuals or groups, and k is a candidate for joining the group, a (alpha) is a parameter that may be set at or a function of the numbers of individuals (t) included in i,j, or k such as = tilt&k

and

aj = tjltj,k

as in UPGMA and UPGMC; c is generally zero except that it is equal to - for nearest neighbor and for farthest neighbor sorting; b is usually zero except in unweighted centroid sorting (UPGMC) where b is equal to n,ai and D is squared Euclidean distance. Lance and Williams (1967a) proposed a method which they called Median sorting in which ai = aj = b = -%, and c = 0. This places the centroid of the combined group midway between the centroids of i and j irrespective of the number of members in i and j rather than nearer the larger of group i or j as in true centroid sorting. Flexible sorting was applied as above with b = - # by Campbell et al. (1970), Crichton (1975), Moore et al. (1972), Russell and Moore (1967, 1968). Moore and Russell (1967) used another form of flexible sorting in which ai = aj, b = 1 (Ui t aj), and c = 0. This procedure was intended to produce especially tight clusters of high within-group similarities. Anderson (1971) also used a “mini-

4

t,

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

51

mum variance clustering” which minimizes the within-group variance in which ai = (ti -k f k ) / ( t i t f j t f k ) ,

aj = ( f j + f k ) / ( f i+ f j

fk),

b = 1 -(Ui t U j )

and c = 0. The clustering algorithm between cluster k and the combined cluster ( i j ) is thus Dk,ij = [ ( t i + f k ) D k i t ( f j t t k ) D k i - t k D i j ] / ( t i t f j t t k )

where t is the number of individuals in clusters i, j , and k. This author points out that the results can be presented as an analysis of variance, because the sum of squares being subdivided is that due to the samples t samples X attributes effects.

6. Information Content Clustering A clustering technique based upon information theory has been used by Norris and Dale (1971) and by Moore et al. (1972) applied to all two-state variables (transition matrix). Clustering is based upon the minimum information gain upon the fusion of two pairs or groups of individuals. The method is explained in detail in Sneath and Sokal(l973); however, they indicate serious reservations with regard to the assumptions on which the method is based. Since most soil data include continuous and ranked multistate variables, the method is not generally applicable in soil classification (see also Section IV,B,3).

7. Sorting Strategies: Divisive Divisive sorting systems have been applied to soil classification in only a few cases. hvisive systems begin with the whole population, and, progressively divide it into smaller and smaller groups using the similarity matrix. Traditional categorical soil classification proceeds in a similar way, generally making separations using a single dichotomous criterion for separation (monothetic) or perhaps two or more criteria simultaneously (polythetic). Norris (1972) used the technique of “Association analysis.” The variables are analyzed for covariance and the first is selected which has highest communality with other variables which can be computed from the maximum sum o f ? for a variable compared to each other variable (ZF1 rtj). Thus this is the variable with the highest predictive value. The population is divided into two classes using this variable as a criterion. Thereafter each subset is further subdivided by the same procedure. The process is terminated when a specified number of classes have been formed or when the maximum sum of r2 falls below a specified level for all remaining variables. Karmeli et al. (1968) devised a procedure for specific design purposes similar to “Association analysis,” which was called “Maximum Uniformity Classifica-

52

RODNEY J.ARKLEY

tion.” The method suggested uses separation on a primary variable with high communality together with minimum variance and t-tests and discriminant functions to increase the separation of groups.

8. Comparison of Sorting Strategies Using the same similarity matrix as Muir et al. (1970), Anderson (1971) compared five sorting strategies: nearest neighbor, farthest neighbor, group average (UPGMA), centroid (UPGMC), and minimum variance clustering. He concluded that the 63 soil profiles sampled from 4 soil series were classified most effectively by farthest neighbor and minimum variance clustering. Campbell et al. (1970) compared centroid, flexible (b = -0.25), and median sorting and concluding that the flexible sort ( b = -0.25) appeared to be the most effective in forming groups, but the appearance of the dendrogram resulting from centroid sorting appeared to be equally effective to this writer. Cuanalo and Webster (1970) compared unweighted pair-group (UPGMA), weighted pair-group (WPGMA), and weighted variable-group methods. They concluded that all gave similar results and printed only the results from UPGMA. Moore and Russell (1967) compared nearest neighbor, farthest neighbor, centroid sort and flexible sort (see above). They found the typical chaining effect of nearest neighbor sorting, but the other three produced dendrograms in which 7 groups could be consistently detected in the 28 soils used. Examination of these comparisons suggests clearly that in soil studes, the single-linkage (nearest neighbor) sorting with its strong tendency to form long chains rather than tight spherical clusters is to be avoided. Unweighted pairgroup or group average clustering (UPGMA), unweighted centroid sorting (UPGMC), and minimum variance clustering are appropriate for soil studies as they produce moderately “tight” initial clusters of reasonable homogeneity and the central “core” of the cluster can be identified. However, as pointed out by Moore and Russell (1967), clustering and its representation in a dendrogram provides a two-dimensional representation of a multidimensional system (nspace) and clearly must contain distortion of the true configuration. They also point out that distortion is least at the lower levels of the hierarchy produced; thus the initial groups formed have the most validity, larger groups formed by merging smaller groups the least. Thus groupings formed at the higher levels should be treated with caution.

F. PRESENTATION OF RESULTS OF SORTING PROCEDURES

A similarity matrix can be shown effectively in a shaded similarity mafrix as in Fig. 1 provided the indiviudals are ordered in such a way that the highest

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

53

similarities are at or near the diagonal. However, if the number of individuals is large, manual sorting to produce the optimum order may be very difficult. In the example shown in Fig. 1, the order was according to the results of a clustering procedure (Fig. 2). By far the most common visual presentation of the results of the similarity matrix sorting procedures is in the form of a dendrogram such as that shown in Fig. 2. In a dendrogram, the individuals are indicated by symbols at the end of each branch, and the length of the branches are proportional to the degree of dissimilarity; the scale of dissimilarity used is often shown, although in this case it was not. Dendrograms have the advantage of being readily interpreted, but it should be remembered that they are two-dimensional representations of a Sornilaroty cwtfeient “!.I

ol.

26

27 25 24 34 33 32 28 35 29 43 36 40

818 90-99 El80-89 70-79

38

site NO

39 41 30 4 31 37 42 19 3 22 1

2 21 20 5

6 23 7 8 10 11

14 12 9 13 18 15 17 16 ~6n24343332283529~364038g41304 313742193 22 1 2 2l20 5 6 2 3 7 8 10 111412 9 1318151716 Slts

No

FIG.1. Shaded similarity matrix for 43 soil bodies. Reprinted from Russell and Moore (1967) by permission of the publisher, Geoderma.

RODNEY J. ARKLEY

54

I

t

1 LL r I

?

1011 14 12 9 13 Y) 15ff 16

433640383941 30 4 3 37 42

GKW

-'

1

n

m

l ! z

FIG. 2. Dendrogam showing relationships between soil bodies using flexible sorting procedure (b = -0.25). Reprinted from Russell and Moore (1967) by permission of the publisher, Geoderma.

multidimensional system and so suffer some distortion. Sometimes some of the distortion can be relieved by changing the order of the initial clusters so as to bring the nearest members of two clusters adjacent to each other. I I I. Ordination of Soils

Another approach to the examination of taxonomic structure is through ordination, which is normally used when the distribution of indiviudals in n-space tends to be continuous rather than in distinct clusters. Thus some form of ordination seems to be appropriate for soils when large numbers of individuals

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

55

are included, if one considers the universe of soil individuals to be represented b y one large hyperspherical swarm of points in n-space with n corresponding to the numbers of independent factors or processes involved. Two kinds of ordination have been used in soil studies. Q-type ordination or analysis of objects operates on a similarity matrix of objects and examines the distribution of objects in object-space to find dimensions along which the objects are distributed. R-type ordination or analysis of variables operates on the covariance matrix variables to find dimensions in variable-/space. These dimensions are formed by clusters of covariant variables. Objects then can be located in varible-space by their coordinates along the axis of these dimensions.

A. Q-TYPE ORDINATION

Ordination of this type was used in one of the first attempts at numerical classification of soils by Hole and Hironaka (1960) and Bidwell and Hole (1964); however, the method is suboptimal as shown by Rayner (1969). The method of principal coordinates analysis (PCO) developed by Gower ( I 966) operates best on a Euclidean distance matrix (dissimilarity coefficients) but may be used with other similarity coefficients. The procedure is discussed in detail by Webster (1975) who points out that PCO gives a good view of the general structure of a population but that distances between indiviudals are imperfectly represented. This is just the opposite of cluster analysis; thus PCO is complementary to cluster analysis in exploring relationships in n-space. A problem of representing the results of PCO comes from the fact that for soils a number of principal axes are often produced, whereas only two, or at the most three, can be shown in a single diagram. Thus it may take a number of diagrams, each showing a pair of principal coordinates to represent the results. The interpretation of such two-dimensional scatter diagrams must be done with care, because two individuals which appear to be closely similar in one diagram, may actually be at an considerable distance along another axis in another diagram. Another problem is that variation along a principal coordinate is not always interpretable as to its source; i.e., variation due t o differences in reaction, clay content, etc. The first use of this approach was by Rayner (1966) who utilized the method of Gower (1 966); and it was again used in a later publication by Rayner (1969). Anderson (1 971) used Rayner’s similarity matrix and applied a Q-type technique called “Nonmetric Multidimensional Scaling,” which uses the rank order of the elements of a similarity matrix rather than the raw matrix. Muir et al. (1970) also used PCO on 63 soil profiles of four soil series in Scotland. They plotted the individual soils on the first two coordinates but found that three of the four soil series could not be well separated. This is not surprising since the first two

56

RODNEY J. ARKLEY

coordinates accounted for only about 28% of the total variance. Norris and Dale (1971) used a slightly modified form of PCO as part of a procedure for comparing the classifications derived from two sets of data (field and laboratory) on the same soils and found a high degree of correlation between the two; canonical correlations between the two sets for the first three principal coorinates were 0.89,O. 62, and 0.58, respectively.

B. R-TYPE ORDINATION

1. Principal Components Analysis The most commonly used R-type procedure is the Principal Components Analysis (PCA) which operates on the matrix of correlation coefficients (r) between all pairs of variables. It extracts orthogonal, independent dimensions from the data which are called principal axes. The coordinates of individuals on these axes are linear combinations of the original variables. Commonly, as few as three principal axes will account for a large portion, as about 75%, of the original total variance of the data matrix. Like Principal Coordinates Analysis (PCO), it provides an accurate representation of the relationships between major groups and clusters, but is less accurate in reproducing differences between closely similar individuals. Also like PCO,it is often difficult to interpret the significance of an axis (dimension) in that it is made up of a combination of all variables. Sometimes an axis may be interpreted rather generally by examination of the so-called factor loadings of the variables on the dimension. However, a threedimensional representation of the individuals plotted in relation to the three axes gives a general picture of the taxonomic structure. More importantly, the coordinates for individuals in each dimension (factor scores) can be used as the data for one of the clustering methods, rather than the raw data matrix. This greatly reduces the number of variables used in clustering. Principal components analysis has been used in a number of soil studies: Anderson (1971) applied this method to the data of Rayner (1966) and then refined the results by examination of the residuals (residual variance) on each individual after extracting the variance represented by two dimensions; he also applied another procedure called “minimization of a quatradic loss function,” which is a procedure for extracting the best minimum number of dimensions from the total number. Barkham and Norris (1970) used principal components analysis on both the vegetation and soils and examined the realtionships between the two by comparing the first two vegetative components with four soil components and various soil variables and by canonical correlations between components of the two

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

57

systems. They considered this procedure to provide a workable strategy to investigate a complex ecosystem. Cipra et al. (1970) used PCA together with cluster analysis to study relationships among 59 world soils. A three-dimensional diagram based on the first three principal components revealed n o very distinct clusters, but a number of remotely related individual soils. The three axes could be interpreted as composites of various soil properties but these did not appear to be very logically related. The first component contained high factor loadings on chroma and clay content. However, ArMey (1971) using factor analysis on these same data found chroma and clay content to fall into separate, independent dimensions. Still, Cipra et al. (1970) considered this a meaningful method of visualizing relationships between soils. Cuanalo and Webster (1970) also used both principal components with projection of individuals on the first two dimensions together with clustering methods. They concluded that soil data be first examined by ordination by principal componenets before attempting a classification of a set of soils. Norris (1971a) applied PCA t o two groups of soils using two sets of date: laboratory and field for each group. From the examination of two-dimensional diagrams, they concluded that the variation of soils can be characterized by the variation of a relatively few properties, and that there is a considerable correspondence between groupings based upon field and laboratory data separately. They suggest that where this is generally the case, soil classification might well be based on a relatively few dimensions defined by a few soil variables, but rarely by one singly. Norris (1972) applied the results derived above (Norris, 1971a) to applied problems in soil mapping and classification and as an aid in understanding the causes for soil variation. Norris (1971b) also used PCA to assist in the solution of a statistical problem which arises in the use of soil data resulting from the fact that many variables are included. This problem is called matrix singularity and may result from a variable being completely determined by one or more other variables (i.e., there is a high degree of correlation among groups of variables) or when the matrix is overdefined (i.e., there are more variables than individuals). Thus the use of PCA reduces the large number of variables to a few components or dimensions, and the overdefinition is relieved with a minimum loss of information.

2. Principal Factor Analysis Principal factor analysis (PFA) has been used much less frequently than principal components analysis in soil studies. PFA differs from PCA in that in the latter the diagonals of the correlation matrix of variables are filled with unities, whereas in PFA the unities are replaced by so-called communalities, the percentage of variation due to the common factors. In PCA the axes are

58

RODNEY J. ARKLEY

orthogonal, whereas in factor analysis they can be rotated and can be permitted to become obliquely related, i.e., correlated. This is particularly suited to soil data, which are often highly intercorrelated, as discussed earlier in this paper. Arkley (1968, 1971) used a form of factor analysis described by Tryon and Bailey (1970) which they call Cumulative Communality Cluster Analysis of variables (CC5), wherein each dimension is defined by a minimal number of definer variables which are both intercorrelated and have closely similar patterns of correlations with other variables in the analysis; at the same time the dimensions are held to be as independent of each other as possible. This has the great advantage that the dimensions produced in this way are defined by one a few variables, rather than by factor loadings on all variables, and thus are readily identifiable. Arkley (1971) analyzed the data for 59 soils, used also by Cipra et ul. (1970), by both PCA and PFA and obtained five dimensions which were identical except for the number of definer variables. The exact comparison was made possible by a program by Tryon and Bailey (1970) called cluster summary analysis (CSA2); this program extracted definer variables from PCA which could be compared with those from CC5. The computer program package developed by Tryon and Bailey is a tremendously powerful tool, as it contains a wide variety of options including various methods of principal component and factor analyses which can be applied with great simplicity for purposes of comparison. Also, the output contains a thorough set of statistical parameters for analytic purposes. The package also contains an iterative centroid clustering program for indiviudals, which can be modified at will. Arkley (1971) used the programs described to analyze six different sets of soil data and found that five dimensions accounted for 85% of the squared raw correlations in 220 California soils, 87% in 620 California soils, and 72.1% in 59 world soils; seven dimensions accounted for 75.5% of the squared raw correlations in 148 Ohio soils, and 80.9% in 86 world soils. In every case only about three or four definer variables were required for each dimension. The evidence is clear that relatively few, say 20 to 25, variables are sufficient for soil classification.

C. PRESENTATION OF RESULTS OF ORDINATION

Ordination can be presented as two- or three-dimensional scatter diagrams of the component or factor scores of the individuals along each axis. A typical two-dimensional scatter diagram is shown in Fig. 3 in which the two axes are the first and second components of a principal components analysis (PCA). However, in interpretation of such a diagram it must be kept in mind that individuals that appear to be in close proximity on the diagram, may actually be separated at considerable distance along the axis of a third component.

59

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

I

I

71.

47.

89.

L

-6

-4

-2

I

0 la1 component

2

4

6

FIG. 3. Scatter diagram in which the first principal component is plotted against the second for 85 soil profiles. Reprinted from Cuanalo and Webster (1970), by permission of the publisher, Oxford University Press.

Three-dimensional diagrams are more difficult to prepare than two-dimensional ones, but can be prepared using a computer; and these can represent relationships more completely. The pin and ball diagram, a commonly used type, is shown in Fig. 4 and a rotated view of the same is depicted in Fig. 5. Again it should be kept in mind that a fourth component may well separate individuals which appear in close proximity. Where a number of independent factors or components are needed to represent the taxonomic structure, a number of diagrams may be required to present a complete picture of the structure. IV. Soil as an Anisotropic Entity

Soil descriptions and analytical data have been treated in several different ways in an attempt to solve the problem of homology, i.e., the comparisons of profiles, layers, or horizons. It is sometimes difficult to decide which horizons should be compared between soils with different sets of horizons designated in the conventional way by soil scientists. Comparisons based upon identical depths

60

RODNEY J. ARKLEY

-

~-

I ~

FIG. 4. Front view of a three-dimensional scatter diagram based upon centroid component analysis projections. Reprinted from Cipra et uf. (1970), by permission of the publisher, American Society of Agronomy.

are often inappropriate due both to inherent differences in thickness in the soil or to depths altered by erosion.

A. SOIL PROFILE AS AN ARRAY OF SOIL PROPERTIES One approach that has been used considers the soil profile as an entity, and the conventional designation of master soil horizons A, B, C, and R in the soil description have been used as a basis of comparison. Soil properties such as the color and structure of the A1 and B2 horizons, texture of the Al, B2, and C, and difference between maximum clay in the B and minimum clay in the A horizon have been used. This treatment has been applied by Bidwell and Hole (1964), Bidwell et al. (1964), Cipra et al. (1970), Hole and Hironaka (1960), Moore and Russell (1967), Rozkov (1974), Sarkar etal. (1966), Webster (1973), and Arkley (1 968,197 1). The use of soil “profile” data or soil horizon data has been criticized on the grounds that (a) the designation of horizons by the field scientist is subjective and thus violates one objective of numerical classification which is maximum objectivity, and (b) that it is subject to human error, even when the designation of horizons follows defined rules. This author is inclined to the view that the designation of horizons according to well-established rules such as those published in soil survey guides and handbooks or in “Soil Classification” (Soil

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

61

77

\ /

‘ I

Y+)q \ &

I(+)

FIG. 5. Same as Fig. 4 viewed from the reader’s right.

Survey Staff, U.S. Department of Agriculture, 1960) is sufficiently objective and accurate for the purposes of soil classification when carried out by a trained soil scientist. However, this is a personal view biased by my own long expeirence as a soil surveyor, and I have no wish to dispute the opposite view. The use of selected “profile” data or data by specified pedogenic horizons does have certain advantages, in that the mathematical treatment does not involve the analysis of a three-dimensional data matrix of variables X layers (or horizons) X soil individuals.

B. SOIL DATA BY LAYERS OR HORIZONS

1. Uniform Soil Depth Layers-Direct Comparison Soil samples taken at specified depths and compared directly have been used by Barkham and Norris (1970), Cuanalo and Webster (1970), Hughes and Lindley (1955), Horris (1971a, 1972), Norris and Loveday (1971), and Webster and Burrough (1972). This method is appropriate only over small areas where

62

RODNEY J. ARKLEY

the arbitrary depths chosen can reasonably be expected to sample comparable portions of the soil profiles.

2. Horizon or Layer Matching Methods Rayner (1966) devised a method of calculating similarity between soils by average of maximum similarity between all pairs of horizons; matching first the horizons of soil A with soil B and then soil B with A. There are two difficulties with this procedure. First, the amount of computer time is multipled by twice the number of horizons, and second, maximum simiiarity may well occur between surface horizons and deep horizons as in the C horizons, which seem inappropriate. This method was also used by Lamp (1972), and the similarity matrix of Rayner (1966) was also used by Anderson (1971) and Muir et al. (1970). In order to remedy both objections to Rayner’s method, Grigal and Arneman (1969) devised a similar method except that for a given horizon of soil A, comparisons are limited to three of soil B. The three are the horizons of soil B at the equivalent depth to the horizon of soil A plus the one just above and just below. The horizons of soil B are then compared t o A in the same way, and the average of the maximum similarity between pairs used for comparison of the two profiles.

3. Soil Profilesas a Sequence of Layers Norris and Dale (197 1) developed a method based on a statistical device called a “transition matrix.” In their procedure, all layers or horizons are grouped by one of the clustering methods into classes which are assigned an arbitrary number as a designation. Each profile then is described by a sequence of horizon-type numbers. Thus for a 10-layer profile in which the first 3 layers are of type 2, and the remaining layers type 5, the soil profile is defined as 2,2,2,5,5,5,5,5,5,5. Each soil profile then is redefined as a transition matrix which records the number of times each type-number follows every other type-number down the sequence. In the example given above, the transition matrix of n X n horizons types for that soil would contain all zeros except for matrix position (2,2) would contain a 2, position (2,s) would contain a 1 , and position ( 5 , s ) would contain a 6. Soil profiles defined by transition matrices can be sorted on the basis of minimum information gain statistic of Dale et al. (1970). Norris and Dale (1971) claim several advantages to the method: (1) horizons or layers are conveniently and objectively classified, (2) the transition matrix includes information about relative position, and (3) the number and thickness of layers need not be identical. A major difficulty is the amount of computer time and computer storage space involved. This author agrees that the

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

63

first advantage mentioned is a real one. However, I examined their matrices of profile X horizon types and found that a simple matching coefficient followed by UPGMA gave almost identical soil profile groupings as their much more complicated method. Also it appears to me that there is considerable loss of information in converting the horizon data into a transition matrix. The transition matrix method was also used by Moore et al. (1972). They point out that grouping based upon the transition matrix is dependent entirely on the relation between each layer and the one preceding it.

C. SOIL PROFILE AS AN ARRAY OF DEPTH FUNCTIONS

Colwell (1 970) introduced a procedure applicable to continuous variables such as chemical data. In this method, the depth function for each variable is characterized by fitting the data to an orthogonal polynomial. Colwell found that a polynomial of the fifth degree gives a reasonably accurate fit. The coefficients of the polynomial were used to characterize mean depth trends of four Great Soil Groups for 9 variables, and their confidence intervals at various depths. However, no classification of individual soils was attempted. Campbell et al. (1970) used the coefficients of orthogonal polynomial depth functions as a means of characterizing soil profdes, but concluded that such a smooth depth function will not adequately describe the profile, and did not use the technique further. Moore et al. (1972) used orthogonal polynomial coefficients to represent shape and profile means to represent magnitude as variables for comparing soil profiles. They found wide variation in goodness-of-fit between profiles and between soil properties. However, when the profile mean was weighted equally (5 X) to the 5 polynomial coefficients, they found profile groups similar to those produced by layer by layer comparison weighted by a negative exponential depth function ce-‘” where y is depth in centimeters and c is a constant. They adopted c = 0.02 as most appropriate.

V. Statistical Methods for Comparing Classification

As pointed out by Sneath and Sokal (1973), there is n o general agreement on the optimal classification, except in cladistics where the optimal classification is one best representing the branching pattern of organisms through evolutionary history. For soils there is clearly n o such criterion. However, it is possible to make some statistical comparisons which may be useful.

64

RODNEY J.ARKLEY

A. COPHENETIC CORRELATION

This procedure is described in detail by Sneath and Sokal (1973); it analyzes the level at which the individuals are joined to each other in a dendrogram, and compares that matrix of similarity with the original one by correlation coefficient between the two arrays of values. The higher the correlation coefficient, the more accurately the dendrogram represents the original pattern of similarities. This method was applied by Lamp (1972), and by Grigal and Arneman (1969). The latter compared different sets of data on the same soils and found the cophenetic correlation between field properties alone, and other data sets were 0.817 for comparison with all properties, and greater than 0.74 for three other data sets. Cipra et al. (1970) also applied cophenetic correlation to ordination by three principal components, and to dendrograms based on Euclidean distance and correlation coefficient; the correlations obtained were 0.78, 0.83, and 0.62, respectively.

B. COEFFICIENT OF ASSOCIATION

Grigal and Arneman (1969) used a method of comparing classifications developed by Goodman and Kruskal(l954) to compare numerical classifications with the Seventh Approximation Classification of the U.S.Department of Agriculture and found a low order of correspondence attributed to the differences in criteria used.

C. WILK’S CRITERION

Webster (1971) describes this method based on within group and between group variance extended to multivariate data. He illustrated its use comparing soil map classes at three different map scales and by comparing classes formed according to profile appearnace and by numerical methods. He concluded that the criterion can be used to compare classifications effectively. Webster and Burrough (1972) used Wilk’s criterion to help determine the number of classes most appropriate to use in soil mapping over a small area and to determine the similarity between clusters and previously established soil series. VI. Conclusions and Evaluation

From this welter of different methods employed, including different ways of treating soil profile data, different coefficients of similarity, clustering, and

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

65

divisive methods, is it possible to decide which are the best methods to apply to soils? Although there is no criterion by which a classification can be judged to be the best, it does appear that some methods can be applied more logically to soils than others.

A. THE CHOICE OF METHODS

1. Dhta Selection and Standardization First let us consider the kinds of data that have to be dealt with in soil classification. Field descriptions contain much information that is probably best treated as either ranked or unranked multistate variables. Laboratory data are primarily continuous variables. Thus most soil data sets contain mixed variable types. The data scaling method of Talkington (1967) with standardization of variables by range, and that of Burr (1968) with standardization by variance can accommodate mixed data. If Euclidean distance is used as the similarity coefficient, the results from either method will be about the same. Very rare extreme values on a variable should probably be truncated as advocated by Talkington (1967). Variables with highly skewed distributions should be transformed by logarithmic or square root transformation. The choice of variables to be used will depend, of course, upon the nature of the data available or the purpose of the classification. However, for a general classification my investigations (Arkley, 1968, 1971) suggest that a minimal set of soil properties should include at least one or several measurements representing the following dimensions: 1. Soil reaction such as surface and subsoil pH, carbonate depth, exchangeable Na or S.A.R. 2. Hue and chroma. 3. Texture or contents of clay and sand, or clay and silt, and gravel or stone con tent. 4. Soil color value such as thickness of surface layer with value of 3 or less, or color value per se. 5 . Depth to and degree of mottling and/or other evidence of wetness or poor drainage. 6. Degree of profde differentiation such as difference in clay content between the surface and B-horizon or subsoil, clay films, and structure of the subsoil. 7. Solum thickness. Most of these, as can be seen, are properties measurable in the field. Since the purpose of soil classification is related mainly to land use or plant growth in the field, it is relevant only to soil distributions that are mapped by field methods primarily, supplemented by laboratory analysis only to a limited degree. As indicated in the section (II,C,2) on data selection, soil variables in a data set are

66

RODNEY J. ARKLEY

often highly correlated. Norris (1971a), Grigal and Arneman (1969), Hole and Hironaka (1960), and Norris and Dale (1971) all found a high degree of similarity between the soils classified by numerical methods when the results of laboratory versus field data were compared.

2. Similarity Coefficients Comparisons of two or more similarity coefficients are included in several papers including those of Moore and Russell (1967), Cipra et al. (1970), and Cuanalo and Webster (1970). These comparisons provide no basis for unequivocal recommendations, but it appears that the Euclidean distance is most suitable to soil data on theoretical grounds as well as its ease in conceptual representation. The correlation coefficient and the Canberra metric seem to be less suitable.

3. Sorting Strategies Of the numerous sorting strategies available, nearest neighbor or single linkage sorting seems to be the least useful for soil classification because of its characteristic “chaining.” Furthest neighbor or complete linkage sorting produces the least chaining but is conceptually less satisfactory for soils than centroid sorting (UPGMC) or average linkage (UPGMA). Centroid sorting requires a larger computer storage capacity, but it has the advantages or producing initial clusters of specified degree of within-group homogeneity and also can be applied iteratively to find a stable taxonomic structure. The minimum withingroup variance clustering of Anderson (1971) is also an attractive form of centroid clustering as it can be presented as an analysis of variance.

4. Ordination Methods Ordination per se does not provide a classification but does reveal relationships between individuals and groups when presented in one or several two- or three-dimensional scatter diagrams. Ordination by principal coordinate analysis (PCO), a Q-type analysis of the similarity matrix shows relationships between individuals but the axes are often difficult to interpret. Principal components analysis (PCA), an R-type analysis of the variables is more easily interpretable, but still the components are made up of variable weights on all variables, and further examination or analysis is required to identify the meaning of each component. Factor analysis (PFA), another form of R-analysis, can be used for ordination as well as a means of reducing the number of variables in the analysis, and the axis can be identified as to the nature of the dimensions they represent. In applying either PCO or PFA, the correlation matrix should be examined for

STATISTICAL METHODS IN SOIL CLASSIFICATION RESEARCH

redundant variables (i.e., with very high correlation coefficients as one of the pair eliminated before proceeding further.

67

> 0.95) and

B. A SUGGESTED PROCEDURE FOR A GENERAL SOIL CLASSIFICATION The cluster analysis of soils described herein is based on the assumption that soils do indeed fall naturally into discrete clusters or classes. For large numbers of soils, as in an entire nation, a whole continent, or the world, this assumption may not be valid and soils may well form a continuum in multidimensional variable space. For the latter case, a procedure suggests itself which is based upon the idea of arbitrarily defined, well-separated centroids, each centroid thus representing an hypothetical or perhaps an actual modal soil. In order to define the centroids, each variable or dimension is divided into appropriate segments of its total range and the midpoint of each segment established as an arbitrary centroid. For example if we accept the meaningful range of soil clay content to be from 0 to 50, the segments would be 0-10, 10-20, 20-30,3040, 40-50+ and the mid-point centroids would be located at 5, 15, 25, 35, and 45%clay. With this approach, soil individuals would be allocated to the centroid to which it is nearest in n-space on the basis of Euclidean distance. For soils considered as a continuum, this has the greatest advantage over conventional heirarchical classification in that no dichotomous separation is made on the basis of a single variable separated at a single point along its range. For example the soils classified as Mollisols are separated from other soils at a high category on the basis of a specified thickness of a dark, organic rich surface soil. With this kind of dichotomy a small variation in this single property for two soils separates them regardless of the degree of similarity of all other properties. The allocation of soils by over-all similarity to definite centroids avoids this problem entirely, so that each class is distinct from every other in at least one dimension, and individuals within a class are all closely similar to the defined centroid. It is interesting to consider the number of classes formed by this kind of procedure. The number depends upon the number of segments into which each variable is divided raised to the power of the number of variables as follows: Number of dimensions or variables Number of Segments

4

6

5

3 4 5

81 256 625

243 1,024 3,125

7 ~

~~

729 4,096 15,625

2,187 16,384 78,125

8

9

6,561 65,536 390,624

19,683 262,144 1.95 X lo6

~~~

68

RODNEY J. ARKLEY

On the basis of intuition, it appears that seven dimensions divided into five segments each producing 78,125 classes of which perhaps 20% might remain unoccupied would be adequate for a classification of the soils of the world. However, it might be necessary to first stratify the soils such as separating organic soils from mineral soils,and perhaps separating soils of arid regions from those of humid regions as different soil properties might be used as criterion variables for classification of the two major kinds of soils. Soils of subhumid regions then might be classified according to both systems, thus avoiding a dichotomous separation between arid and humid regions. Factor analysis of the kind used by Arkley (1968, 1971) seems to be an effective way of finding a suitable number of independent dimensions for such a classification procedure. This kind of system could be used for setting up a number of hierarchical arrangements depending upon the categorical order in which the dimensions are used, or it could be used as a coordinate system of classification. The latter would be particularly useful to show relationships among soils. For example, if we have five segments labeled VL, L, M, H, VH and seven dimensions, then a sequence of soils varying only in one dimension would be found in classes labeled such as:

VL, H, H, H, H,H,H L, H, H, H, H, H, H M,H, H, H,H,H, H H, H, H, H, H, H, H VH, H, H, H, H, H, H Assuming all classes to be occupied, there would be 15,625 possible such sequences to be examined. These should very well keep the pedologist of the world occupied for some time. Finally, it appears that cluster analysis of soils is a most effective means of classifying soils when the number of distinct soils or soil groups is limited as within a relatively small land area. For large areas including large numbers of soils, clusters of similar soils are likely to be either nonexistent or existing only with diffuse boundaries. In which case a coordinate system based upon predefined centroids is more likely to produce an effective classification system.

REFERENCES Anderson, A. J. B. 1971. J. Int. Assoc. Marh. Geol. 3.1-14. Arkley, R. J. 1968. Trans. Int. Congr.SoilSci.,9rh, 1968 Vol. IV,pp. 187-192. Arkley, R. J. 1971. SoilSci. Soc. Am, Proc. 35,312-315. Avery, B. W. 1968. Trans. Int. Congr. SoilSci., 9th, 1968Vol. IV, pp. 169-176.. Barkham, J. P., and Norris, J. M. 1970. Ecology 51,630-639. Bidwell, 0.W., and Hole, F. D. 1964. Soil Sci. Soc. Am., Roc. 28,263-268.

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Bidwell, 0. W., Markus, L. F., and Sarkar, P. K. 1964. Trans Int. Congr. Soil Sci., 8th, 1964 Vol. V, pp. 933-941. Bray, J. R., and Curtis, J. T. 1958. Ecol. Monogr. 27,325-349. Brisbane, P. G.,and Rovira, A. D. 19611.J. Cen. Microbiol. 26,379-392. Burr, E. J. 1968. Aust. Comput. J. 1.97-99. Campbell, N. A., Mulcahy, M. J., and McArthur, W. M. 1970. Aust. J. Soil Res. 8,42-58. Cipra, J. E., Bidwell, 0. W., and Rohlf, F. J. 1970. Soil Sci. Soc. Am. R o c . 34,281-287. Colwell, J. D. 1970. Aust. J. SoilRes. 20, 221-238. Critchton, J. E. 1975. Ph.D. Thesis, Dep. Soil Sci., University of Sydney, New South Wales, Australia. Cuanalo, H. E. de la C., and Webster R. 1970. J. Soil Sci. 21,340-352. Dale, M. B., McNaughton-Smith, P., Williams, W. T.,and Lance, G.N. 1970. Aust. Comput. J. 2,9-13. Dryden, L. 1935. Am. J. Sci. 29,393-408. Eades, D. C. 1965.Syst. Zool.l4,98-100. Gibbons, F. R. 1968. Trans. Int. Congr. Soil Sci., 9th, 1968 Vol. IV, pp. 159-168. Goodman, L. A., and Kruskal, W. H. 1954.J. Am. Stat. Assoc. 49,123-163. Gower, J. C. 1966. Biometriku 53,325-338. Grigal, D. F., and Arneman, H. F. 1969. Soil Sci. SOC.A m , Proc. 33,433-438. Hole, F. D., and Hironaka, M. 1960. Soil Sci. SOC.Am., Roc. 24,309-312. Hughes, R. E., and Lindley, D. V. 1955. Nature (Lmdon) 175,806-807. Karmeli, D., Pitkovski, G., and Regev, J. 1968. Technion-lsr. Inst., Tech. Fac. Agric. Eng., h b l . 50,l-10. Lamp, J. 1972. D. Agric. Dissertation, Fac. Agric., Christian-Albrechts University, Kiel. Lance, G. N., and Williams, W. T. 1967a. Comput. J. 9,373-380. Lance, G. N., and Williams,W. T. 1967b. Aust. Comput. J. 1,15-20. Moore, A. W.,and Russell, J. S. 1967. Geoderma 1,139-158. Moore, A. W., Russell, J. S., and Ward, W. T. 1972. J. Soil Sci. 23,193-209. Muir, J. W., Hardie, H. G . M., Inkson, R. H. E., and Anderson, A. J. B. 1970. Geoderma 4, 81-90. Norris, J. M. 1971a. J. Soil Sci. 22,69-89. Norris, J. M. 1971b. Pedobiologia 11,410-416. Norris, J. M. 1972. J. Soil Sci. 23,62-75. Norris, J. M., and Dale, M. B. 1971. Soil Sci. Soc. Am., Proc. 35,487-491. Norris, H. M., and Loveday, J. 1971. J. Soil Sci. 22,395-400. Rao, C. R. 1948. J. R. Stat. Soc., Ser. B 10, 159-193. Rayner, J. H. 1966. J. Soil Sci. 17, 79-92. Rayner, J. H. 1969. Sysf. Assoc. 8, 31-39. Rohlf, F. J. 1963. Ann. Entomol. SOC.Am. 56,798-804. Rozhkov, V. A. 1974. Geoderma 12,175-182. Russell, J. S., and Moore, A. W. 1967. Geoderma 1,47-68. Russell, J. S., and Moore, A. W. 1968. Trans Int. Congr. Soil Sci., 9th, 1968 Vol. IV, pp. 205-21 3. Sarkar, P. K., Bidwell, 0. W., and Marcus, L. F. 1966. Soil Sci. SOC. Am., Proc. 30, 269-272. Sneath, P.H.A., and Sokal, R. R. 1973. “Numerical Taxonomy.” Freeman, San Francisco, California. Soil Survey Staff, U.S. Department of Agriculture. 1960. “Soil Classification.” US Govt. Printing Office, Washington, D.C. Sokal, R. R., and Sneath, P.H.A. 1963. “Principles of Numerical Taxonomy.” Freeman, San Francisco, California.

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Talkington, L. 1967. Syst. Zool. 16,149-152. Tryon, R. C., and Bailey, D. E. 1970. “Cluster Analysis.” McCraw-Hill, New York. Van den Driessche, R., and Maignien, R. 1965. Pedologie 3,79-88. Varty, A., and White, D. 1964. Clay Miner. Bull. 5 , 4 6 5 4 7 3 . Webster, R. 1971. J. Soil Sci. 22,254-260. Webster, R. 1973. Math. Geol. 5,27-31. Webster, R. 1975. Soil Sci. 119,394-404. Webster, R., and Burrough, P. A. 1972. J. Soil Sci. 23,210-221.

NITRATE ACCUMULATION IN VEGETABLES D. N. Maynard,' A. V. Barker,' P.

L. Minotti? and N. H. Peck3

I. Introduction .................................................. 11. Hazards of Nitrate and Nitrite to Human Health . . . . . . . . . . . . . . . . . . . .

.

.

.

A. AcuteToxicity .............................................. B. Other Effects ............................................... C. Relative Dangers of Nitrite Poisoning from Various Nitrate or Nitrite Sources .................................................... D. Nitrosamines ................................................ ... . . .. 111. Factors Affecting Nitrate Accumulation . . . . . . . . . . . . . . A. Environmental Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Genetic Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . .. .. . . C. Nutrient Supply ............................................. IV. Nitrate Concentrations in Vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . A. Distribution in the Plant . . . . . . . . . . . . . . . . . . .. . . . . . . . . B. Fresh Vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Processed Vegetables . . . . . . . . . , . . . . . . . .. ... .. . .. . . . . . . . . D. Critical Nitrate Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Growth and Nitrogen Management of Vegetable Crops . . . . . . . . . . . V. Conclusions ................................................... References ....................................................

.

.

.

.. . .

.

....

.. .

.

.. . . . .. .. . .. .

..... . .

. .. .

. ..

.

.

71 72 72 73 74 76 77 71 88 94 98 98 99 101 104 108 112 114

I. Introduction

Nitrate accumulation in plants is a natural phenomenon resulting from uptake of the nitrate ion in excess of its reduction and subsequent assimilation. As discussed in the following pages, accumulation of nitrate is dependent on and related to the genetic makeup of the plant, the nitrate supplying-power of the soil, and the environmental conditions under which the plant is grown. In addition, nitrate concentrations differ in plant parts and with age of the plant. Much recent interest and investigation has focused on nitrate in the environment, in drinking water, and in foods and feeds for man and his livestock. The

' Department of Plant and Soil Sciences, University of Massachusetts, Amherst, Massachusetts. 'Department of Vegetable Crops, Cornell University, Ithaca, New York. Department of Seed and Vegetable Sciences, New York State Agricultural Experiment Station, Geneva, New York. 71

72

D. N. MAYNARD ET AL.

potential for nitrate reduction to nitrite and its adverse effect on human and animal health is in large measure responsible for this concern. Several recent reviews on the general importance of nitrate have been prepared (Committee on Nitrate Accumulation , 1972; Deeb and Sloan, 1975; Viets and Hageman, 1971; Wright and Davison, 1964), and the reader is referred to them for a general consideration of the scope and magnitude of the “nitrate problem.” Among the food products consumed by man, fresh and processed vegetables have most often been cited as the major source of dietary nitrate intake. For this reason, much research has been conducted in the United States and elsewhere in the past few years to study nitrate accumulation in vegetables and the factors influencing its occurrence. This review is based largely on the authors’ own work with vegetable crops and is generously supplemented with supporting data from the recent literature. I I. Hazards of Nitrate and Nitrite to Human Health

Man is continuously exposed to nitrate and nitrite through drugs, water, and foods. Usually the amounts of nitrate and nitrite are small, and no harm results, but nitrate or nitrite in high concentrations or under special circumstances may cause great economic losses through illness or death. Nitrate toxicity is relatively low and varies widely, the fatal adult dose in humans being in the order of 15 to 70 mg of nitrate-N per kilogram of body weight (Burden, 1961; Lee, 1970). Nitrite, formed from the reduction of nitrate or present as a food additive, is the factor that presents health hazards. A lethal dose of nitrite also varies widely but appears to be about 20 mg nitrite-N per kilogram of adult body weight (Burden, 1961; Lee, 1970). Before ingestion, the reduction of nitrate to nitrite may occur through the action of microorganisms present in water, plants, or food during storage or by bacterial contamination of sterile food in opened containers. Natural plant enzymes may contribute to some nitrite accumulation in stored foods. Nitrite may also be formed from nitrate after ingestion. In humans with healthy alimentary canals, nitrate is absorbed rapidly without reduction in the upper intestines, but gastrointestinal disturbances may delay absorption and increase the chances for reduction. Reduction is more likely in infants than in adults, on one hand, because of the lesser acidity in the gastrointestinal tract which allows nitrate-reducing coliform and clostridial bacteria to survive and, on the other hand, because of higher frequency of digestive disturbances which might bring the nitrate-reducing bacteria into the upper intestinal tract. A. ACUTE TOXICITY

If the nitrite ion is absorbed into the blood, the ferrous iron of hemoglobin may be oxidized to the ferric form producing methemoglobin which cannot

NITRATE ACCUMULATION IN VEGETABLES

73

transport oxygen. Methemoglobin may compose naturally about 1 % of the hemoglobin in healthy adults, 4%in newborn infants, and 6%or greater in babies with respiratory illness or diarrhea (Kubler, 1958; Lee, 1970. Luhrs, 1973). The small amount of methemoglobin normally produced can be converted enzymatically back to hemoglobin (Lee, 1970. Stolk and Smith, 1966); however, if the capacity for reconversion is exceeded, methemoglobin will build up to abnormal concentrations. Babies are much more susceptible to methemoglobin accumulation than older children or adults. Fetal hemoglobin, which may be 80% of the total hemoglobin in the newborn, is much more easily converted to methemoglobin than the regular hemoglobin of older children and adults. Infants, also, may have a temporary deficiency of the enzyme of red blood cells which converts methemoglobin to hemoglobin (Finch, 1948; Lee, 1970; Luhrs, 1973). Acute nitrite toxicity is shown by cyanosis, a bluish-purple discoloration of the skin and lips, and occurs when about 15% of the hemoglobin is oxidized to methemoglobin. A proportion of methemoglobin of 70%or more of the total hemoglobin may be fatal (Lee, 1970; Luhrs, 1973) unless relief from intravenous injection of methylene blue or thionine is provided (Lee, 1970; Stecher, 1968). Methemoglobin accumulation may be caused by chemicals other than nitrite, such as carbon monoxide, sulfa drugs, phenacetin, and aniline dyes of furniture polish, laundry-marking inks, and crayons (Luhrs, 1973). Genetic defects may cause high levels of methemoglobin to be inherited (Finch, 1948). Although generally it is the infants who are most liable for nitrite poisoning, adults who are exposed to conditions which increase methemoglobin accumulation, who have genetically high methemoglobin levels in their bloods, or who are anemic must be cautious against ingestion of nitrate or nitrite.

B. OTHER EFFECTS Acute cases of nitrate or nitrite toxicity are shown by cyanosis or methemoglobinemia as described above, but other effects more chronic in nature also result. Nitrate or nitrite in animal diets has been linked to vitamin A deficiency due to degradation of carotene by nitrite in the alimentary canal (Phillips, 1966). Also, in animals nitrate may increase the need for iodine due to abnormalities being produced in the thyroid gland (Bloomfield er al., 1961). Nitrite may also produce rapid heartbeat, peripheral vasodilatation, vomiting, and diarrhea (Luhrs, 1973). High levels of dietary nitrite have been shown to give abnormal electroencephalograms in rats (Shuval and Gruener, 1972), and although most patients with hereditary methemoglobinemia do not have mental or neurological disorders, mental retardation has been reported in patients with hereditary methemoglobinemia (Joffe and Heller, 1964). In cattle, sheep, and other livestock, abortions m a y result from their consumption of feeds

74

D. N. MAYNARD ET AL.

high in nitrate (Wright and Davison, 1964), but the methemoglobin content of the blood apparently must exceed 4050% for pregnancies to be terminated (Winter, 1964). Cancer, mutations, and birth defects are caused by nitrosamines, compounds formed by the reaction of nitrite and certain organic amines. More is said on this subject in the review below (Section 11, D).

C. RELATIVE DANGERS OF NITRITE POISONING FROM VARIOUS NITRATE OR NITRITE SOURCES

1. Drugs

Methemoglobinemia associated with the therapeutic use of cardiac nitrites (nitroglycerine, amyl nitrite, sodium nitrite), antidiarrheal agents (bismuth subnitrate), diuretics (ammonium nitrate), or burn treatments (silver nitrate) are rare complications from drugs (Goodman and Gilman, 1965; Greenberg er al., 1945; Marcus and Joffe, 1949; Strauch er al., 1969).

2. Water A report by Comly (1945) is responsible for our present concern over the possibility of nitrate or nitrite poisoning of infants, for the most common cause of methemoglobinemia is from the drinking of water with high nitrate concentrations, resulting in nearly 2000 cases in the United States and Europe. Numerous infants, but no adults, have died from this cause (Luhrs, 1973). Babies are naturally more susceptible to nitrite methemoglobinemia and additionally they take in proportionally more water and hence more nitrates than adults. Sterilization of water by boiling for infant formula may tend to increase the nitrate concentration in the water. In the United States all cases but one have been associated with private, usually rural, well-water supplies (Vigil et al., 1965). A survey by Walton (1951) led the United States Public Health Service in 1962 to establish a standard limiting nitrate to 10 ppm nitrate-N in drinking water (U. S. Public Health Service, 1962), since no case of infant methemoglobinemia in the United States has been reported from ingestion of water with nitrate concentrations below this standard (Walton, 1951). This standard can be met easily by municipal water supplies. The adequacy of this standard is being reevaluated, however (cf. Luhrs, 1973).

3. Foods

a. Cured Meats and Fish. Nitrate or nitrite is used in the United States for curing of meat and fish products. Cured meat or fish is permitted to have either nitrate or nitrite added at 200 ppm (U. S. Public Health Service, 1962). The

NITRATE ACCUMULATION IN VEGETABLES

75

purposes of these additives are to fix a reddish pink color (nitrosylmyoglobin) in the products, to add flavor, and to protect against bacterial growth, notably Clostridium botulinum. In Europe, nitrate and nitrite are added to cheese and flour as well. Cases of methemoglobinemia have occurred with children and adults as the result of accidental use of excessive amounts of these additives in meat (Bakshi et ul., 1967; Singley, 1962), but no cases have occurred at the permitted levels of addition. b. Vegetables. Richardson (1907) reported on a survey of nitrate concentrations of fresh vegetables obtained in retail markets in the Chicago area. He concluded that the nitrate concentrations of fresh vegetables, including beets (Beta vulguris L.), radish (Raphanus sutivus L.), spinach (Spinach oleruceu L.), eggplant (Solanum melongenu L,), lettuce, (Luctucu sutivu L.), celery (Apium gruveolens L.), turnips (Brussicu rupu L.), parsley (Petroselinum crispum Nym.), summer squash (Cucurbitu pep0 L.), cabbage (Brussicuoleruceu var. cupituta L.), cauliflower (Brussica oleruceu var. botrytis L.), and carrots (Dmnts curota L.), in most cases were higher than those of cured meats. He also concluded that the average person would take in more nitrate from vegetables than from meat foods. Based on the available data in subsequent surveys (Brown and Smith, 1966, 1967; Jackson et ul., 1967; Maynard and Barker, 1972; Wilson, 1943, 1949) since Richardson’s time, it is suggested that the nitrate concentrations in fresh vegetables have not changes appreciably in the past 65 years. Nitrate is a natural constituent in plants, and concentrations within plants vary with a number of environmental and genetic factors. Plant parts eaten as the vegetable and the amount of nitrate available in the soil appear to be major factors determining whether or not a vegetable will behigh in nitrate. Any N fertilizer added as nitrate or capable of being oxidized to nitrate by soil microorganisms and applied in generous quantities to a crop will usually lead to nitrate accumulation. These and other factors are discussed in more detail in other parts of this article (Sections 111, A and 111, C). Although the nitrate content of vegetables can be rather high, the nitrite content of vegetables is relatively low (Committee on Nitrate Accumulation, 1972). Nitrate may be converted to nitrite during storage of plant products as the result of bacterial action or plant nitrate reductase activity (Kubler, 1958; Luhrs, 1973). About 50 cases of methemoglobinemia from eating vegetables have been reported, and very few of these occurred in the United States (Luhrs, 1973). All of the reported cases occurred with infants under one year of age, and all but one case, which occurred from strained beets, have involved fresh spinach or carrots which had been prepared into baby food (Committee on Nitrate Accumulation, 1972; Keating et ul., 1973; Luhrs, 1973). Many of the cases of methemoglobinemia occurred with these baby foods prepared from fresh vegetables and stored without refrigeration for a day or more (Luhrs, 1973; Phillips, 1968). No federal standards are established for nitrate concentrations in canned or

76

D. N. MAYNARD ET AL.

fresh vegetables, but Simon (1966) recommended that no spinach should be given to children under 3 months of age, that spinach used for infant feeding contain no more than 0.07% nitrate-N on a dry weight basis, and that prepared spinach be kept refrigerated. Knauer (1970) estimated the maximum safe level of nitrate-N to be 0.1% of the dry matter. Most baby foods (Lee, 1970) appear to equal or exceed the standard suggested by Simon, but millions of jars of canned spinach, beets, and carrots are sold annually in the United States without medical reports of infant methemoglobinemia although it is conceivable that many cases go unreported. Simon’s value seems to be rather low considering the facts that only when spinach is grown in unfertilized plots or solely on ammonium-N nutrition will this proposed standard be met (Barker et al., 1971; Mills, 1975). Lorenz and Weir (1974) and Maynard and Barker (1974) indicated that it would be very difficult for an adult to get a toxic dose of nitrate from even excessively fertilized vegetables, assuming the estimates of toxic doses are valid.

D. NITROSAMINES The presence of nitrite and secondary amines together may lead to the formation of nitrosamines, which are carcinogenic, teratogenic, and mutagenic compounds (Committee on Nitrate Accumulation, 1972). Nitrite may be formed from the nitrate in foods or may be added to foods as a preservative. Information on the occurrence of secondary amines in the environment is scanty, but they are potentially present from a number of sources including foods, tobacco smoke, and flavorings (Lijinsky and Epstein, 1970). Evidence for nitrosation in foods is limited, and some of the reports of nitrosamine occurrence in foods may have been based on inadequate analytical procedures (Wolff and Wasserman, 1972). Most analytical procedures are subject to criticism because of the wide range of physical properties of nitrosamines and the difficulty of detecting nitrosamines at low concentrations. It must be questioned, therefore, as to whether or not nitrosamines exist in the environment (Walters, 1973). Some cases of occurrence of nitrosamines in feeds and foods are apparent. An outbreak of liver disease in sheep in Norway was attributed to a diet of herring preserved with nitrite (Sakshaug et al., 1965). Sen et al. (1969) reported that fish preserved with nitrite formed nitrosamines upon cooking. Cooking apparently increases the presence of secondary amines (Lijinsky and Epstein, 1970). Sen (1972) found some nitrosamines in a few samples of processed meats. Few reports of nitrosamines in vegetable foods are known. A close association was found between the occurrence of esophageal cancer in Bantu tribespeople and Mo deficiency in pumpkins (Cucurbira pep0 L.), Phaseolus, and corn (Zeu mays L.) (Burrell er al., 1966). Nitrosamines have been detected in the fruit juice of

NITRATE ACCUMULATION IN VEGETABLES

77

Solanurn incanum, which is used by the Bantu people to curdle milk (Du Plessis et al., 1969). Hedler and Marquardt (1968) found nitrite and nitrosamines in wheat and flour. Keybets et al. (1970) could not detect nitrosamines in nitratecontaining spinach under normal processing conditions. 111.

Factors Affecting Nitrate Accumulation

A. ENVIRONMENTAL FACTORS

All things being equal, nitrate concentrations of plant tissues can be expected to bear some relationship to the availability of nitrate in the root zone and, in many cases, to the amount of fertilizer-N applied. Environmental variables may exert a marked effect on nitrate accumulation, but they are difficult if not impossible to manipulate under production conditions and are equal from one crop growing situation to another only by rare coincidence. Thus, it would be risky to generally equate high nitrate concentrations in tissues with high or excessive applications of fertilizer-N. Without attempting to determine cause, the role of environment will be illustrated with a few examples. 1. Magnirude and Significance

The data in Table I show a straightforward relationship between the nitrate concentration of outer leaves of head lettuce and the amounts of fertilizer-N applied within a given planting date and N source. However, environmental effects were so pronounced as to completely mask, in some cases, the effects of fertilizer rates. A summer crop to which no fertilizer was applied contained as much or more nitrate when mature than the spring crop receiving 112 kg N/ha. Similarly, summer lettuce receiving 112 kg N/ha as NaNOJ had higher nitrate concentrations than spring lettuce receiving 224 kg N/ha; summer lettuce receiving 56 kg N/ha as (NI-L,)2S04 accumulated more nitrate than the spring crop fertilized at 4 times that rate. In other unpublished work on organic soils, Minotti sampled onions (Allium cepa L.) in mid-July for 4 consecutive years from plots receiving the same yearly N applications. Nitrate concentrations varied considerably from year to year within N treatment, and in some cases the year-to-year variations were as large as differences caused by 1 12 kg N/ha. The previous examples demonstrate the effects of relatively long-term climatic variables; however, environmental variables can exert an appreciable effect on nitrate concentration in a matter of hours as illustrated in Fig. 1 (Minotti and Stankey, 1973). Nitrate concentrations in whole beet plants changed as much as twofold in periods as short as 8-12 hours. Minimum concentrations were found

TABLE I Effect of Rate and Source of Nitrogen and Planting Time on the Nitrate Concentration and Yield of Minetto Head Lettuce Grown on Organic Soil in Oswego, New York' Nitrogen applied Source

Rate (kg/ha)

spring cropb

23May

17 June ~

Summer crop 5 July

27 June

15 July

b

Fresh wt/carton'

6Aug.

Spring

Summer

~~

NO, -N, % dry wt

NO,-N, % dry W t

kg

NaNO,, NaNO, NaNO,

Zero 56 112 224

0.12 0.40 0.46 0.6 1

0.13 0.58 0.76 0.96

0.10 0.20 0.32 1.12

0.31 0.50 0.76 0.87

0.73 1.08 1.19 1.28

0.41 0.78 1.09 1.59

14.1 20.8 23.6 23.5

19.2 19.8 20.8 20.8

(NH,),SO, (NH,),SO, (NH,),So,

56 112 224

0.14 0.15 0.1 1

0.29 0.37 0.35

0.23 0.41 0.49

0.48 0.52 0.65

1.00 1.01 1.13

0.67 0.79 1.16

21.0 21.9 21.3

20.2 21.7 21.2

'P. L. Minotti, unpublished data. bSpring crop planted in April and harvested at maturity on 5 July; summer crop planted in June and harvested on 6 August in adjacent plot. 'Carton of 24 heads.

79

NITRATE ACCUMULATION IN VEGETABLES

c 35 -

&

30-

W w

22

20-

Ly

e

15-

10 -

8

1

2

4

8

1

1

4

8

1

2

4

8

1

2

4

8

1

2

HOUR

FIG. 1. Diurnal fluctuations in air temperature, soil temperature and nitrate-N concentration of beet plants over a 52-hour period (Minotti and Stankey, 1973).

at 4 p.m. after which nitrate increased, reaching maximum levels at 4 a.m. and 8 a.m. Most vegetables are grown in outdoor environments where rapid changes in climatic factors are expected. However, even environmental differences existing between two types of greenhouses were found t o appreciably modify nitrate concentrations. Lettuce was grown to maturity during the period August to October in (I) a conventional pad-cooled, completely enclosed glasshouse and (11) a double-layered, plastic-topped house with open sides and ends in which temperatures and humidities more closely paralleled the outdoor environment. Although identically grown and fertilized in both cases the plants in system I1 invariably contained lower concentrations of nitrate; yet, their total N concentration excluding nitrate was generally higher (Table 11). Plants in system I1 were higher in dry matter and required more frequent watering.

80

D. N. MAYNARD ET AL. TABLE I1 Effect of Different Greenhouse Environments, Closed PadCooled Glass (CG) and Open-Sided, PlastioTopped (OP), on N Constituents and Growth of Several Lettuce Cultivars‘

N (excl.

Variety

mb

Minetto Oswego (H) ParrisIsland (R) SummerBibb (B) Buttercrunch (B) GrandRapids Q SaladBowl(L.)

NO,-N (7%dry wt)

NO,)

Dry matter

(% dry wt)

(%I

CG

OP

CG

OP

CG

op

CG

op

1.69 1.38 1.41 1.21 1.24 1.41 1.43

0.87 0.96 0.77 0.64 0.58 0.63 0.69

3.4 3.6 3.1 3.9 3.2 3.5 3.6

3.4 4.6 4.4 4.9 4.9 3.9 4.2

3.4 3.8 5.1 4.6 4.1 4.2 5.0

4.8 5.0 5.3 4.3 4.4 5.4 5.1

1.21 1.66 0.67 0.42 0.80 1.10 0.63

1.24 1.71 1.30 0.72

Fresh wt (kg/head)

1.05 1.05 0.97

‘P. L. Minotti, unpublished data. bH= crisp head, R = romaine, B = butter head, L = leaf.

It is of interest in this example that climatic factors acted in such a way as to decrease nitrate without decreasing the nonnitrate fraction, much of which consists of useful protein and amino-N. In situations where changes in nitrate are mediated by changes in applied N, one usually finds that increments of fertilizer simultaneously increase nonnitrate N, and this parallel effect extends beyond the “critical concentration” ranges (Section IV,D). The above experiments were obviously not designed to separate the effects of individual climatic factors on nitrate concentrations, but they do illustrate the significance of environment. Applications of N fertilizers are probably too often blamed in instances of high nitrate accumulation. Retail produce sampled for nitrate fluctuates widely (Section IV,B), whereas fertilizer-N programs for any specified crop do not diverge to the same extent. This also suggests, although indirectly, that factors other than fertilizer are heavily involved. Schuphan et al. (1967) showed the involvement of other factors, environmental and genetic. Spinach harvested at optimum maturity from several fields over a period of years varied in nitrate concentration by a factor of 5 or more with the same amount of fertilizer.

2. General Mechanism The concentration of nitrate in plant tissues is always in a dynamic state since it represents the difference between rates of absorption and rates of assimilation within the plant. For a particular plant part, translocation of absorbed nitrate to or from the part is also involved. Thus, a factor may modify tissue nitrate by

NITRATE ACCUMULATION IN VEGETABLES

81

affecting any one or all of the processes of absorption, assimilation, and translocation. If absorption is limited due to low availability of nitrate; then, the effect of assimilation and translocation rates will be minimized since tissue accumulation will tend to be low regardless of these factors. Similarly at greatly excessive soil nitrate levels, tissue nitrate may tend to be high regardless of assimilation and translocation rates. Most vegetable crops would be fertilized between such extremes since it is self-defeating to nutritionally starve a crop and senseless to overuse N, considering its cost, availability, and environmental repercussions (Minotti, 1975). Thus, factors affecting assimilation or translocation could play a significant role in regulating nitrate concentrations under most production situations.

3. Specific Factors

a . Light. It is well documented that reductions in light intensity are often associated with increased nitrate concentrations in plants (Schuphan et al., 1967; Viets and Hageman, 1971; Wright and Davison, 1964). The first step in nitrate assimilation is the reduction of nitrate to nitrite mediated by the enzyme nitrate reductase (NR), a metallo-flavoprotein (Beevers and Hageman, 1969). It is considered a rate-limiting step because nitrate may accumulate while other intermediates in the process normally do not, at least prior to the amino-N stage (Kessler, 1964). The enzyme in leaf tissue loses activity rapidly in the dark (Candella et al., 1957; Hageman and Flesher, 1960), and provided other factors are not limiting, maximum activity has been associated with maximum solar radiation incident to the leaf surface (Hageman et al., 1961). Further, these same workers have shown the enzyme to exhibit a diurnal variation such that peaks in leaf NR activity corresponded to depletion of leaf nitrate concentrations. Accordingly, light is presumed to modify tissue nitrate concentrations primarily by regulating NR activity, although the mechanism by which light modifies NR is still uncertain (Viets and Hageman, 1971). Certainly a large part of the diurnal variation in nitrate in beets, as depicted by Fig. 1, might be explained by the above reasoning. Attempts to assess the magnitude of the light effect independent of other variables, such as temperature and humidity, are fraught with difficulties; therefore, completely enclosed growth chambers with fluorescent tubes supplemented by incandescent bulbs are usually employed. In this manner Cantliffe (1972a) demonstrated dramatic differences in the nitrate concentration of spinach grown for 35 days at 2400 ft-c and then for an additional 2 weeks at intensities of 600, 1600, 2400, and 3500 ft-c. Average values for the percentage nitrate-N of leaves were 1.26,0.49,0.34, and 0.34, respectively. In greenhouse experiments using shade cloth and supplementary light to vary intensities, Cantliffe (1973a) obtained equally dramatic reductions in nitrate concentrations with increases in the intensity of light over beets and spinach

82

D. N. MAYNARD ET AL.

growing in pots of Ontario fine sandy loam differentially fertilized with N (Table 111). As predicted from the scheme describing the processes of nitrate absorption, translocation, and assimilation (Section 111, A, 2), light factors were particularly significant at moderate N levels since at low N levels, nitrate concentrations were relatively low, and at high N levels, concentrations were high. Light still exerted a marked effect at high N levels. Moreover, total N content over the experimental period was much greater at higher light levels suggesting that the reduced nitrate concentrations are indeed resulting from increased nitrate assimilation rates. Although growth was greatly accelerated at higher light intensity, the concentrations of nonnitrate N were not reduced, indicating that the lower nitrate concentrations are not resulting from simple dilution effects. Working under field conditions, Schuphan et al. (1967) found considerable variation in the nitrate concentrations of spinach harvested at different dates, and concentrations found were negatively correlated with the hours of sunshine the plants received in the week immediately prior to harvest. He subsequently protected spinach plots from direct sunlight by using various types of shading materials. Both light and strong shading accentuated nitrate accumulation. Also working in the field, Knipmeyer et al. (1962) found that shading markedly affected nitrate concentrations in leaves of several varieties of corn without commensurate changes in total N concentrations. They obtained similar results whether the shading was caused by shading screens or by adjacent corn plants. Increases in the nitrate concentrations of beet leaves (Fig. 2) were obtained by 1.2 LENGTH OF THE LIGHT PERIOD

R

I 0

0 0

8 HOURS 12 HOURS 16 HOURS

0 20 HOURS

I

I

I

100

200

300

400

NITROGEN ADDED (pounds per acre)

FIG. 2. The effect of photoperiod on the nitrate-N concentration of beet leaves grown at different fertilizer rates (Cantliffe, 1972b).

TABLE 111 Effect of N and Light Intensity on N Constituents and Dry Weight of Spinach Leaves and Beet Leaves and Rootsa

NO,-N (% dry wt) Crop

N (excl. NO,) (% dry wt)

Growth @ dry Wt/POt)

N Content (dry wt X % total Ny High

Low

Nitrogen applied (mg/kg soil)

Highb

Low

High

Low

High

Low

0 100 200

0.09 0.35 0.72

0.14 1.09 1.61

2.69 3.61 3.76

3.19 3.25 2.84

0.22 1.27 1.25

0.22 0.57 0.42

0.61 5.02 5.60

0.73 2.47 1.86

0

100

0.06 0.18 1.12

0.15 0.50 1.26

1.46 1.73 1.61

1.54 1.70 1.72

2.04 2.87 3.49

0.99 1.41 1.80

3.10 5.19 9.52

1.67 3.10 5.36

0 50 100

0.02 0.04 0.35

0.04 0.13 0.44

1.33 1.40 1.72

1.38 1.51 1.77

1.28 2.67 2.99

0.68

1.72 3.84 6.18

0.96 1.80 2.98

(glpotx 102)

~~~

Spinach leaves

Beet leaves

50

Beet roots

'Adapted from Cantliffe (1973a). 'High = 3.23 X lo4 Ix (3000 ftc); low = 1.08 '%TOM N = % NO,-N + % N.

X

1.10 1.35

lo4 lx (1000 ft-c).

00

w

84

D.N.MAYNARD ET AL.

shortening the photoperiod at a constant light intensity of 2500 ft-c, and similar results were shown for the beet roots (Cantliffe, 1972b). Extended photoperiods reduced total N concentrations, but since data on plant growth were not presented it is not certain whether or not these were dilution effects. In another growth chamber experiment at 2500 ft-c and a constant 12-hour photoperiod, Cantliffe harvested radish leaves and roots, spinach leaves, and snap bean pods (phuseolus vulgaris L.) at the end of the dark period and 6 and 12 hours after initiating light. Each additional 6 hours of light decreased the concentration of nitrate-N by approximately 0.18% in radish leaves, and although little nitrate accumulated in snap bean pods there was an approximately one-third reduction in their nitrate concentration when harvested at the middle or end of the light period. Nitrate concentrations in spinach leaves did not change with response to the additional light period under these conditions. Harper and Paulsen (1968) attempted to assess the effects of light quality on nitrate assimilation in wheat (Triticum uestiuum L.). After 28 days, leaf nitrate concentrations were consistently lower under blue light (380-470 nm), and NR activity was markedly higher than in red light (680-740 nm). However, neither the radiant energy nor growth data were reported under each regime; so, interpretation remains tenuous. b. Temperature. It is difficult to make a general statement about the effects of temperature on nitrate accumulation because the processes of absorption, translocation, and assimilation are all affected. The relative degree to which each process is affected depends on other factors such as light, moisture, and N availability which can be markedly affected by temperature. It is not surprising then to find nitrate accumulation associated with both temperature increases (Kretschmer, 1958; Younis et ul., 1965), temperature decreases (Nightingale et ul., 1930) or not appreciably affected by temperature. For field-grown plants, temperature may diverge widely in a short time span (Fig. 1). Moreover, root and shoot temperatures differ with the result that shoots can be considerably warmer at midday; yet, the roots are warmer at night. In addition, roots are exposed to a gradient of temperature with soil depth. These root-shoot temperature relationships should not be ignored in considering diurnal nitrate fluctuations in shoots. Considering that all biological processes are temperature moderate, a low night temperature would seem to have a lesser effect on root absorption than shoot assimilation of nitrate; thus, the temperature drop favors accumulation in accordance with observed diurnal patterns. In organic soils, temperature exerts a pronounced effect on rate of mineralization and subsequent nitrification, and such effects are undoubtedly involved in the high accumulation found in the summer-grown lettuce crop as compared to the spring crop (Table I). Similarly, soil nitrification rates and nitrate availability are likely involved in Kretchmer’s (1958) finding that nitrate accumulation in everglades forages was positively correlated with d d y low temperature-the higher the daily low, the greater the nitrate concentration.

NITRATE ACCUMULATION IN VEGETABLES

85

The effect of temperature can vary with species (Bathurst and Mitchell, 1958). When nitrate concentrations were compared at temperatures regulated upward from 7°C in approximately 5" intervals, nitrate was lowest in Dallisgrass (Paspalum dilatatum Poir.) at 18" but lowest in ryegrass (Lolium sp., L.) at 7". Particularly high temperatures (30°C and above) have decreased NR activity in corn (Younis et al., 1965) and in barley (Hordeum uulgare L.) (Onwueme et al., 1971) especially when coupled with mild water stress (Huffaker et al., 1970). Investigations with lettuce grown under field conditions in the Imperial Valley of California (Mayberry and Rauschkolb, 1975) have shown close correlations between the mean weekly temperature (MWT) of the ambient air and N uptake. When the MWT was below 12.7"C, applications of N did not result in increased uptake or in midrib nitrate levels high enough to maintain growth or correct deficiency. It was recommended that applications be given before the cooler weather began, since at warmer temperatures uptake was sufficient to raise midrib-nitrate levels high enough to sustain plant needs through the subsequent cold period. Cantliffe ( 1 9 7 2 ~ )regulated growth chambers at 5 , 10, 15,20,25, or 30°C for 28 days starting with 1-month-old spinach plants growing in pots of Ontario fine sandy loam. Light intensity was maintained at 1500 ft-c and photoperiod at 12 hours, conditions conducive to nitrate accumulation. In general, nitrate concentrations increased with increasing temperature at 3 levels of applied N (0,50,or 200 mg/kg of soil). There was a temperature X N interaction such that at 0 N, nitrate did not begin to accumulate until the temperature was raised above 15", but at 50 and 200 N, nitrate accumulation began at 10" and So, respectively. The effects were interpreted to be caused primarily by increased uptake from the media since total N concentration also increased. This of course does not mean that assimilation rates were unaffected by temperature but simply that effects on uptake were relatively greater. It would be of interest to repeat this same kind of experiment under conditions of lighting and photoperiod that would not limit assimilation. c. Temperature X Light Interactions. A beautiful example of a temperature X light interaction is provided by the data of Hoff and Wilcox (1970) (Table IV) who showed that temperature exerted its greatest effect on tomatoes (Lycopersicon esculentum Mill.) at high N and low light and that light exerted its greatest effect at high temperature and high N. In these experiments in growth chambers, light intensities were maintained at 3000 or 600 ft-c for an unstated photoperiod. The high temperature regime was 27°C day-21" night, and the low regime was 21" day-15" night. High N consisted of supplemental fertilization with NH4N03. d . Carbon Dioxide Concentration. Gradients in C 0 2 concentration around plant canopies can occur, particularly in full greenhouses where supplementary COz is often successfully used to increase vegetable and flower yields. Further, plant-mediated depletion of atmospheric C 0 2 beyond ambient levels is not

86

D. N. MAYNARD ET AL. TABLE IV Effect of Temperature, Nitrogen, and Light Levels on Accumulation of NitrateN in Tomato Leaves and Fruit Before Harvest'

Environmental Factors

Treatment levels

Nitrogen: Light: Temperature:

High High High

Low Low

Low

High

High Low

High

Low Low

High

Low

ppm NO, -N, fresh wt

Leaf 1st exp. 2nd exp. Fruit Unripe Ripe

420 500

475 568

1100 1510

230 228

420 448

250 26

475 228

330 106

10 11

6 12

50 46

24 11

22 9

20 11

13 15

12 14

'From Hoff and Wilcox, 1970.

uncommon in full growth chambers (Raper et ul., 1973). Partial depletion of C 0 2 in growth cambers was shown to elevate nitrate concentrations in tobacco (Nicotianu tabucum L.) leaves (Raper et al., 1973), and C 0 2 enrichment was shown to lower nitrate concentrations in the leaves (W. W. Weeks, P. L. Minotti, C. D. Raper, and R. C. Long, unpublished data, North Carolina State University, Raleigh). Nitrate reduction appears dependent on photosynthetically produced substrate for the generation of reducing equivalents (NADH) in chlorophyllous tissue (Klepper er ul., 1971). Further, synthesis and maintenance of NR in leaves could be linked to active photosynthesis since the NR in leaves of Perilla decayed in an illuminated, C02-free atmosphere at levels similar to that which occurred when the leaves were placed in the dark (Kannangara and Woolhouse, 1967). Obviously, photosynthetic rates fluctuate diurnally in the same manner as NR activity and nitrate concentrations. Even in roots nitrate reduction is dependent on respiratory substrate from shoots (Minotti and Jackson, 1970). e. Water Relations. The review of Wright and Davison (1964) cites several studies reporting excessive nitrate accumulation in forages subject to drought, some leading to poisoned cattle (Davidson er ul., 1941; Gamer, 1958; Mayo, 1895). Such accumulations probably result because water stress decreases both NR activity (Huffaker et al., 1970) and photosynthesis; and, therefore, nitrate assimilation prior to the time absorption from the soil is depressed. Accordingly,

NITRATE ACCUMULATION IN VEGETABLES

87

tissues remain high in nitrate throughout the stress period or until conditions are once again favorable for assimilation and growth. Moreover, dry periods have been shown to result in upward movement and a buildup of nitrate in the topsoil as it dries out (Robinson and Gacoka, 1962). Since growing vegetables without irrigation is such a risky proposition, nitrate accumulation caused by extended drought would be less common than with forages. However, temporary restrictions in assimilaton caused by combined effects of high temperature and mild water stress without commensurate restriction in nitrate uptake appear more likely. The effects of humidity and, thus, transpiration on nitrate accumulation have not been studied; yet, these are uncontrolled variables in all the work discussed thus far in Section 111, A. In the field, clear skies and high light intensities are accompanied by lower humidities and higher transpiration rates. These rates would be subject to the same diurnal pattern previously discussed for nitrate accumulation, NR activity, and photosynthesis. Artificial or mutual competitive shading can also alter the humidity and possibIy the temperature of the leaf microenvironment. In a l l probability, higher light intensities were compounded with differential humidity and water relations in the growth chamber studies cited below. The environment of the closed glass greenhouse (Table I) was more humid than that in the open plastic house, where a higher frequency of watering was required. Light intensity was about 10% lower in the open plastic house; yet, the lettuce accumulated much less nitrate and had a greater dry matter percentage. This was true at three stages of growth and regardless of whether mean temperatures in the plastic house the week before harvest were lower or higher than those in the glass greenhouse for the corresponding period. Thus, it appears that something other than light intensity, temperature, or nutrient supply is responsible for the differential nitrate accumulation observed. The association between nitrate accumulation and high humidity is of interest in view of the fact that the exact manner in which light affects NR and assimilation is still uncertain (Viets and Hageman, 1971). Nitrate reductase is a substrate inducible enzyme, and the light effect could well be indirect, possibly facilitating nitrate movement to induction sites (Beevers ef al., 1965). Also NR in roots has the same characteristics and requirements as that in shoots. Further, when extraction media contain compounds to remove inhibitors (Dirr ef al., 1973), the specific activity (per unit protein) of root NR activity in many species approaches that of shoots. Moreover, Beevers et al. (1965) found induction of NR to occur in the dark in corn seedlings and radish cotyledons, although higher amounts were induced in the light. They postulated that light was acting indirectly, possibly by increasing the permeability of tissue (Warburg and Negelein, 1920) to the inducer. Possibly, reduced humidities and increased transpiration rates are involved in

88

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maintaining a continuous movement of nitrate to induction sites, thereby helping to maintain NR and keeping accumulated nitrate low. Enzyme activity and nitrate assimilation are associated with the lamina whereas most of the accumulation occurs in vascular tissue. Previously accumulated nitrate reportedly does not maintain activity as NR decays in the dark or when plants are placed in a nitrate-free solution even though tissue nitrate remains high (Jackson ef al., 1973). Thus, it is necessary to keep new nitrate moving to induction sites or from vascular to laminar tissues, and the role of water relations in this process seems worthy of further investigation.

B. GENETIC FACTORS

1. Evidence a. Spinach. Schuphan ef al. (1967) analyzed 19 varieties of field-grown spinach sown at the same date, fertilized with 120 kg N/ha, and harvested at “optimum time” for each variety. He concluded that only small differences, if any, exist among the 19 varieties tested in this trial; yet, his data show an approximately twofold difference in the nitrate concentration between the highest and lowest values for the 10 varieties harvested simultaneously. He presumably minimized the varietal effect because it was less dramatic than that associated with sampling time and solar radiation, and possibly because at reduced solar insulation all the varieties tended to be high in nitrate. Subsequent workers, however, have amply documented significant varietal differences in spinach nitrate concentrations over a spectrum of screening conditions (Barker ef al., 1971, 1974; Cantliffe, 1972a,b, 1973b; Maynard and Barker, 1974; Sistrunk and Cash, 1974). Using spinach potted in Ontario fine sandy loam and grown at rates of 0 or 250 mg N/kg soil in the greenhouse under a 9 hour photoperiod and a minimum light intensity of 1800 ft-c, Cantliffe (1973b), screened 31 plant introductions and commercial cultivars. None of the cultivars accumulated appreciable nitrate without added N but ranged from 0.62 to 1.21% nitrate-N at the 250 mg/kg rate of N. Barker et al. (1974) separated 18 spinach cultivars into 3 groups of 6 according to whether they possessed smooth, heavily savoyed, or semisavoyed leaves. As a group, smooth-leafed cultivars were considerably lower in nitrate than heavily savoyed cultivars when grown in the greenhouse (Table V). Similar results were obtained when these cultivars were grown simultaneously in the field on Hadley fine sandy loam at 3 rates of N except that all nitrate concentrations were considerably lower. Some intermediate or semisavoyed cultivars were low nitrate accumulators while others were high accumulators. In an extension of this work

NITRATE ACCUMULATION IN VEGETABLES

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TABLE V Nitrate Concentration in Different Types of Spinach Leaves from Greenhouse Studies' Leaf part and nitrate treatment (mEq/liter) Blades LeafType

7.5

Savoyed Semisavoyed Smooth

0.30

15.0

Petioles

7.5

15.0

NO, -N %, dry wt 0.18 0.08

0.56 0.50 0.45

1.15 0.84 0.42

2.95 2.48

2.56

'From Barker etal. (1964).

Maynard and Barker (1 974) determined that the critical nitrate-N concentration (Section IV, D) under greenhouse conditions for Hybrid 424, a typical smoothleaf variety was about one-third of that for America, a typical savoyed leaf cultivar. Similarly, unpublished work of N. H. Peck, R. W.Robinson, and C. Y. Lee of the Geneva, New York Experiment Station has shown marked differences in nitrate concentrations between the smooth-leafed Tuftegard and the heavily savoyed Bloomsdale spinach cultivars. Although the case presented by Barker et al. (1974) relating nitrate concentrations to leaf type is convincing, the relationship is not infallible, and they found one of the smooth leaf cultivars, High Pack, to be a high accumulator. Moreover, Cantliffe (1973b) reported that leaf type was not related to nitrate concentration in his experiment with 31 varieties where leaf types were categorized on a scale of 1 to 9 depending on degree of Savoy. Likewise, Sistrunk and Cash (1974) working with seven lots of canned spinach found that nitrate and nitrite were not necessarily related to leaf type. Both the highest and lowest nitrate accumulators were smooth-leafed. They generally concluded that differences resulting from cultural practices may not be as important as processing techniques and length of storage periods as far as canned spinach was concerned (Sistrunk and Cash, 1975). b. Lettuce. Table I1 shows differing nitrate concentrations in different lettuce types with highest concentrations found in the crisphead cultivars. However, the crisphead cultivars can vary tremendously; thus, P. L. Minotti (unpublished) found differences as great as fivefold when 14 cultivars were screened under various field situations. The magnitude of the differences depended on environmental conditions. From one field situation to another, some shifting in the

90

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relative position of cultivars ranking intermediate in nitrate occurred, but high accumulators always remained high and low accumulators remained low in relative ranking order. Continued comparison of two particular varieties, Minetto and Val Rio, under nine growing situations showed that nitrate vaned considerably with the environment, plant age, and plant part, but Minetto was without exception higher in nitrate concentration and lower in dry matter percentage (Table VI). Total N did not show a consistent pattern. It appears that genetic influences on nitrate accumulation can be of enough significance so as not to be masked by environmental effects, as great as the latter are. c. Other Oops. Differential capacity for nitrate accumulation has also been noted in radishes and snap bean pods (Cantliffe, 1972a). Consistent, although relatively small, varietal differences have been documented for other crops such as oats ( h e m sutiva L.), corn, sugar beets, perennial ryegrass (Lolium perenne L.), timothy (Phleum pretense L.), and cotton (Gossypium sp., L.) (Wright and Davison, 1964). 2. Mechanism Differences in nitrate accumulation may be related to differences in uptake, assimilation, or translocation. In attempting to explain the basis for the differences in smooth-leaf versus savoyed-leaf cultivars, Olday (1973) found the NR activity of the smooth-leaf Hybrid 424 was 2.1 to 3.3 times greater than that in the heavily savoyed America depending on the plant organ being studied. Although uptake was not measured, it is unlikely that uptake rates would vary by this order of magnitude; hence, it appears that differential assimilation is indeed the primary cause of differences in this particular case. When total N determinations represent the average N concentration of the whole plant and the Kjeldahl or other total N analysis has been executed so as to prevent loss of nitrate during digestion, total uptake from growth until harvest can be calculated by multiplying percentage N X total dry weight. Applying this method to total plant harvests and analyses of Val Rio and Minetto lettuce (Table VI) indicates a primary role for differential assimilation capacity since total N uptake was often greatest in Val Rio, the cultivar lowest in nitrate. Possibly the ratio of nitrate-N concentration to total-N concentration can be taken as an indirect measure of assimilatory capacity since it indicates the units of reduced-N present for every unit of nitrate-N in tissue at a given time. Such ratios again suggest a major role for assimilation rates in both the spinach screened by Cantliffe (1973b) and the unpublished lettuce work of Minotti since lower nitrates often occur with relatively high total-N concentrations as one compares cultivars. Since nitrate concentrations can markedly fluctuate in a few hours such ratios are used with caution in suggesting mechanism, particularly if only plant parts are analyzed or total weights are not given.

TABLE VI: Nitrate and Total-N Concentrations and Dry Matter in Two Crisphead Lettuce Varietiee NO,-N (% dry wt)

Growth situation

Plant age

Composited plant part

Minetto

Val Rio

Total N (% dry wt)

Minetto

Val Rio

Dry matter (%)

Minetto ~~

Greenhouse 1972 flats, peatlite mix Field 1972 mineral soil 1970 mineral soil 1970 organic soil 1970 organic soil 1972 mineral soil 1972 mineral

Young seedlings

Whole plants

Young seedlings Mature

Whole plants Outer leaves Outer leaves Outer leaves Quartered heads Stems Roots

12- to 14Leaf stage Mature Mature Mature

soil 1972 mineral soil

Mature

1972 organic soil

12-Leaf stage

Leavesb 1-8 9-1 6 17-24 25-32+ Stems Whole plants Roots

Val Rio ~

~~

2.84

1.86

4.50

4.49

4.02

4.48

0.25

0.18

4.10

4.26

8.99

9.50

1.43

0.43

3.56

3.61

ND

ND

0.79

0.39

ND

ND

ND

ND

1.27

0.22

ND

ND

ND

ND

0.95 1.11 0.62

0.39 0.44 0.20

3.36 2.96 1.88

3.13 2.98 1.58

3.83 6.44 9.72

4.54 8.10 12.67

0.94 1.23 0.7 1 0.56 1.19 0.97 0.69

0.61 0.6 1 0.52 0.45 0.64 0.6 1 0.58

3.63 3.14 2.89 3.44 3.09 4.37 3.27

3.13 2.89 2.73 3.5 1 3.20 4.63 3.42

5.09 3.14 3.42 4.64 5.80 4.48 5.67

5.64 4.28 3.97 5.17 7.02 4.7 1 6.24

‘P. L. Minotti, unpublished data. ND = no data. bouterrnost leaf samples designated No. 1. Numbers increase as newest growth is approached inside the head.

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D. N. MAYNARD ET AL.

Perhaps there is merit in seeking to elucidate a common or primary mechanism by which varieties differ in nitrate, particularly from a plant improvement point of view. It may well be, however, that varieties vary for a number of reasons; thus, one is low because of high NR in leaves, another is high because of rapid uptake from the media and a low shoot-root ratio, and another may be low because of relatively high capacity for the root system to reduce nitrate, thus transporting a smaller proportion of the N to shoots as nitrate. Simple structural characteristics may be involved as well and should not be overlooked. For example, petioles and vascular tissue (veins) are sites of accumulation but have low NR (Peck et ul., 1974) whereas the lamina, by contrast, is high in NR and low in nitrate. Thus, the size and number of petioles and veins or the ratio of vascular to laminar tissue could account for observed differences in leaf nitrate. Thus, leaves with relatively large midribs and numerous veins might, also, misleadingly appear to be lower in NR unless specific activity is expressed in terms of protein which resides mostly in laminar portions. Although correlation by no means establishes cause, the invariably higher percentage moisture of Minetto lettuce which parallels its invariably higher nitrate content when compared to Val Rio is provocative (Table VI). In general, those situations that caused the greatest divergence in dry matter contents between the two varieties also resulted in the greatest divergence in nitrate concentrations. Moreover, when percentage dry matter is calculated for the data of Maynard and Barker (1974), it turns out that at the N concentrations in the media where the cultivars America and Hybrid 424 widely differ in nitrate they also differ in dry matter in the same manner as the lettuce, that is, the low accumulator is higher in percentage dry matter. Whether such associations are coincidental or result from involvement of water relations in nitrate accumulation requires further investigation. a. Environmental Interaction. The plant breeder who decides that developing strains with lower nitrate concentrations is a worthy objective is beset with many problems, not the least of which concerns previously discussed environmental effects, particularly N supply and light. Ideally, selections should be made under several environments, and at least two would seem a prudent minimum. (For example, a moderate but not excessive supply of N with temperature adequate for good growth coupled with light intensities and photoperiods that, on the one hand, would favor accumulation and, on the other, permit maximum assimilation.) Especially low or deficient levels of N can be omitted since all cultivars may concentrate negligible nitrate under these conditions (Cantliffe, 1973b; Maynard and Barker, 1974). Likewise, excessive N levels might be omitted since all cultivars tend to be high, particularly if high N levels are coupled with conditions not conducive to rapid nitrate assimilation. N. H. Peck and R. W. Robinson (unpublished) screened inbred spinach lines growing in an outdoor sand-nutrient solution containing 1 mEq/liter

NITRATE ACCUMULATION IN VEGETABLES

93

ammonium-N and 14 mEq/liter nitrate-N at an equidistant spacing of 10 X 1 0 cm. They found all lines to be high in nitrate under these conditions, averaging 1.1% in the blades and 3.7% NOJ-N dry weight in the petioles. They concluded that breeding alone would not solve the problem of high nitrate concentrations in spinach. b. Quality. Some consideration needs to be given to factors such as vitamin and mineral content, reduced N content, oxalate content, color, and texture since it would be somewhat self-defeating to develop a low nitrate cultivar at the expense of one or more other quality features. There is an assumption in all this that a lower nitrate variety will further reduce the risk from nitrite poisoning, even if slight to begin with. However, postharvest physiologists are just beginning to thoroughly investigate nitrate to nitrite conversions after harvest and during storage (Sistrunk and Cash, 1975). It seems to be a matter of bacterial contamination and when the proper organisms are present at sufficient populations, the conversion and subsequent nitrite buildup can occur under refrigeration as well as at room temperatures (Hicks et al., 1975; Lee et al., 1971a). Lee and associates (1971b) regulated the nitrate content of fresh table beets and spinach by differential fertilization and found that conversions to nitrite were not necessarily related to fertilizer applied or initial nitrate levels. Nothing is known about the influence of variety on these conversions. Since nitrite and not nitrate is the toxic principle, it is a bit disconcerting to realize that efforts to develop a low nitrate accumulator could be to n o avail if the cultivar turned out t o be more likely to form nitrite after harvest and during storage for reasons other than initial nitrate content. Such considerations certainly indicate the desirability of involving post harvest physiologists and food scientists in efforts to develop lower nitrate cultivars. c. Selection cziteria. The simplicity of the smooth vs. the savoyed spinach leaf has appeal but should be used with caution since Cantliffe (1973b) did not obtain good correlation between leaf type and nitrate concentration, and Barker et al. (1974) had one smooth leaf variety in their group of six that behaved as a high accumulator. Certainly, selection for high NR activity in both shoots and roots warrants consideration since high NR activity is a heritable characteristic (Hageman et al., 1967; Schrader er al., 1966; Warner er al., 1969). Moreover, NR activities were higher in the smooth-leaved Hybrid 424 spinach than the savoyed America (Olday , 1973). Because NR is substrate inducible, cultivar differences could result from differences in nitrate absorption capacity; thus, higher NR activities are not necessarily correlated with lower nitrate concentrations. In fact, Purvis (1972) reported that genotypic differences in NR levels of corn were independent of tissue nitrate content. Also working with corn, Deckard (1970) found correlations between NR activity and leaf nitrate concentrations only in the

94

D. N. MAYNARD ET AL.

grain development phase when leaf nitrate was extremely low. Possibly, the varietal differences in nitrate assimilation may result from differences in factors other than NR, such as differences in photosynthetic capacity, differences in ability to generate and translocate respiratory substrate and reducing equivalents, or differences in capacity to translocate absorbed nitrate to reduction sites. Another consideration is that it is unlikely that breeding lines would reach the same degree of maturity at precisely the same time. Nitrate concentrations may be declining rapidly as crops are reaching maturity, particularly when fertilized at planting time, and the N supply is being depleted (Peck et al., 1974). Comparing selections at more than one sampling time as well as under more than one environment would reduce chances for error but this increases the work involved manyfold.

C. NUTRIENT SUPPLY

High nitrate concentrations accumulate in plants only if the nitrate supply in the nutrient medium is high or if something interferes with normal nitrate metabolism within the plants. The relationship between nutrient supply and nitrate accumulation has received much attention throughout the world (Commoner, 1970). Most of this attention has been directed toward field and forage crops; however, nutritional factors that affect nitrate accumulation by these crops apply in principle to vegetable crops. This section will deal primarily with aspects of mineral nutrition which affect nitrate accumulation in vegetables but will include occasional reference to other crops when appropriate. I . Nitrogen a. Supply, Source, and Application. Nitrate in vegetables is derived primarily from nitrate added or formed in the nutrient medium; therefore, the N supply is the most important nutritional factor governing nitrate accumulation in vegetables (Barker and Maynard, 1971 ; Brown and Smith, 1966, 1967; Lorenz and Weir, 1974). The amount and source applied and the time and method of application govem the effects of N fertilizers on nitrate accumulation in vegetables. The usual effect is that increasing the level of N nutrition increases the nitrate concentrations of vegetables (Arora and Luthra, 1971; Barker and Maynard, 1971; Barker et al., 1971; Brown and Smith, 1966, 1967; Gately, 1971; Hanway and Englehorn, 1958; Peck et al., 1971; Regan e t al., 1968; Schmidt et al., 1971; Trevino and Murray, 1975). Most commercial fertilizers contain N as nitrate, ammonia (ammonium), or urea, and a few contain organic N forms other than urea. Due to mineralization and nitrification, nitrate is the primary soil-

NITRATE ACCUMULATION IN VEGETABLES

95

derived N form regardless of the source of N applied; therefore, within limits as much nitrate may be accumulate from organic or ammoniacal fertilizers as from nitrate carriers (Barker, 1975; Peck et al., 1971) if sufficient time is allowed for mineralization to occur. Crops that follow a leguminous green manure crop will accumulate nitrate from mineralization of the crop which is plowed-under (Hanway and Englehom, 1958). Materials that mineralize slowly, such as dried cow manure, lead to lesser nitrate accumulation in vegetables than materials that mineralize more rapidly (Barker, 1975). The rates of application of slowly mineralizable materials may have to be markedly increased to maintain crop yields equivalent to those produced with chemical and easily mineralized organic fertilizers (Atanasiu and Hamdi, 1964). Clearly, if crops are fertilized for maximum yields, nitrate accumulation by them is a natural and unavoidable process. Barker er al. (1971) showed that urea, ammonium nitrate, and potassium nitrate sidedressed to a rapidly growing spinach crop increased the nitrate concentrations in its leaves but that urea gave the least increase and potassium nitrate the greatest. Peck et al. (1971) noted that urea sidedressed to table beets resulted in lesser nitrate levels in the beet roots and shoots than did potassium nitrate. The differences were larger at higher levels of N fertilization. Lorenz and Weir (1974) also showed that nitrate sources led to higher nitrate accumulation in vegetables than did ammoniacal sources of N. Barker et al. (1971) further noted that sidedressing N fertilizer to a growing spinach crop resulted in lower nitrate concentrations in its leaves than did broadcasting the N before planting. Peck et al. (1971) observed that nitrate accumulation from sidedressed urea or potassium nitrate tended to increase in the plant with time after application. Thus, the longer that a plant is in contact with a nitrate-rich medium the greater will be its tendency to accumulate nitrate. The accompanying cation has an influence on the absorption of nitrate and hence its accumulation by plants. Minotti et al. (1969) found that ammonium ions suppressed nitrate absorption relative to the effects of Ca, K, Na, or Mg ions. Wallace and Mueller (1957) with lemon (Cifnrs limon Bum. f.) cuttings and Lycklama (1963) with ryegrass also found that ammonium ions restricted absorption. Ammonium ions appear to be the nutritional repressor (Losada ef ul., 1970; Shen, 1969) and nitrate the nutritional inducer (Beevers et al., 1965) of NR in plants. No evidence is available to indicate that the presence of nitrate and ammonium ions simultaneously in the nutrient medium leads to enhanced accumulation of nitrates in plants, but, in fact, the evidence indicates that the nitrate concentrations will be lowered if part of the N supply is ammoniacal. The effects of other cations on nitrate absorption will be covered in following sections. b. Nitrification Inhibitors. The use of ammoniacal fertilizers and an inhibitor of nitrification may be used to control nitrate accumulation in vegetables.

96

D. N. MAYNARD ET AL.

Mills (1975)and Mills et ul. (1976)found that the use of ammonium sulfate and the nitrification inhibitor, 2-chloro-6-(trichloromethyl)pyridine,virtually eliminated nitrate accumulation in spinach and radish. Ammonium toxicity, especially with high rates of N application, tended to decrease yields relative to treatments in which the major portion of the N was from a nitrate source, and at extremely high levels the inhibitor has some phytotoxicity (Mills et ul., 1973). Others (Bengtsson, 1968;Spratt and Gasser, 1970)with field studies found that yields of spinach, ryegrass, wheat, and kale (Brussicu oleruceu var. ucephulu DC) were often higher with the inhibitor and an ammoniacal N source because of N conservation against leaching losses.

2. Other Nutrients a. Phosphoms and Sulfur. Phosphorus supply does not have a marked effect on nitrate accumulation by vegetables. Barker and Maynard (1971)and Brown and Smith (1966, 1967) found no effect of moderate P deficiency on nitrate accumulation by vegetables. Arora and Luthra (1971) found that P fertilization decreases nitrate concentrations in mung bean (Phuseolus uureus L.) leaves, but on the other hand, Hills et ul. (1970) found that P-deficient sugar beets did not absorb nitrate as well as those adequately supplied with P. Arora and Luthra (1971) found that S deficiency was associated with nitrate accumulation in mung bean leaves. Evans and Nason (1953)established that NR extracted from higher plants had a sulfhydryl requirement. Schrader et ul. (1968) indicated that the sulfhydryl group is essential for NR activity with NADH as the cofactor. Sulfur deficiency may therefore interfere with NR activity in vivo and lead to nitrate accumulation. b. Potassium. Studies in the field (Brown and Smith, 1966,1967)and with nutrient solutions (Barker and Maynard, 1971) have shown little effect of moderate K deficiency on nitrate accumulation by vegetables. An abundant supply of K is said to stimulate nitrate absorption. Both of these ions undergo luxury consumption by plants, and one may be absorbed after the accumulation of the other to preserve electrical neutrality in the plant (Wright and Davison, 1964). Regan et ul. (1968) found that K fertilization in the field increased nitrate accumulation in spinach and that the effect was greater on limed soils than on unlimed soils. Other studies with solution culture have shown that K generally stimulates nitrate absorption with respect to the effects of other cations (Minotti et ul., 1968;Tottingham et ul., 1934)and that increasing the K supply increases nitrate accumulation, especially at high levels of nitrate nutrition (Barker, 1962). Nightingale et ul. (1930), on the other hand, showed that tomato plants devoid of K nutrition accumulated high levels of nitrate but appeared N-deficient. c. Calcium and Mugnesium. No definite effect of Ca supply on nitrate

NITRATE ACCUMULATION IN VEGETABLES

97

accumulation by vegetables is apparent (Barker and Maynard, 1971; Brown and Smith, 1966, 1967). Calcium has an effect on nitrate uptake (Nightingale et al., 1931) and possibly an effect on its reduction by plants (Minotti et al., 1968). Calcium deficiency restricts root development markedly and thus may have an indirect effect on nitrate absorption. No evidence is available to indicate that Mg supply has an effect on nitrate accumulation other than its effects on general plant metabolism and chloroplast development and subsequently on NR activity (Kessler, 1964). d. Minor Elements. Molybdenum is a component of NR and thus is a requirement for the enzymatic reduction of nitrate to nitrite (Afridi and Hewitt, 1964; Evans and Hall, 1955; Hewitt and Gundry, 1970; Merkel et al., 1975; Randall, 1969). In Mo-deficient plants, nitrate may accumulate to very high levels in the leaves, sometimes exceeding 3% on a dry weight basis (Hewitt and Smith, 1975). Plants grown on ammonium nutrition apparently d o not have a Mo requirement (Hewitt and Gundry, 1970). In lower organisms, Fe in addition to Mo is an essential constituent of NR in that the system contains a b-type cytochrome (Garret and Nason, 1967). In higher plants Fe has a role in NR in that reduced ferredoxin formed by illuminated chloroplasts participates in the reduction. Chloride in the soil is antagonistic to nitrate uptake. The expression of the antagonism is related to the background concentrations of nitrate and chloride in the soil (James et al., ,1970). Deficiency of Mn has been associated with nitrate accumulation in oats and canary grass (Phaluris sp., L.) (Leeper, 1941). Burstrom (1939) with wheat seedlings confirmed that nitrate assimilation required Mn. A specific role of Mn in nitrate assimilation is unknown.

3. Nonessential Elements Bains and Fireman (1964) found that increasing the exchangeable Na in the soil increased the absorption of nitrate from ammonium sulfate applied to nonsterile soil and increased the nitrate concentrations in corn, sorghum (Sorghum vulgare Pen.) and ryegrass, had little effect on nitrate in tomato, and decreased nitrate concentrations in safflower (Gzrthanus tinctorius L.) plants. Minotti et al. (1969) showed that Na was essentially as effective as Ca, K, or Mg in maintaining nitrate absorption over a 24-hour period by N-starved wheat plants. Increasing the potential pressure or salt concentration in the soil increased the percentage of nitrate in bean plants (Wadleigh and Ayres, 1945). Tungsten has been used as a competitive inhibitor of Mo function in plants, and its use leads to nitrate accumulation in plants (Heimer et al., 1969). Afridi and Hewitt (1964), however, found no effect of W or V on nitrate reductase in cauliflower. Nickel (Maranville, 1970) was shown to stimulate nitrate reductase in extracts of sorghum (Sorghum bicolor L.) and sundangrass (Sorghum vulgare

98

D. N. MAYNARD ET AL.

var. sundanense Hitchc.) but reduced the activities in wheat, corn, and soybean (Glycine max Merr.). The effect was thought to be in the protection against cyanide inhibition, and no metabolic effect of the Ni was assumed. Vanadyl sulfate sprayed on sugar beet leaves increased the nitrate concentration in the plant (Singh and Wort, 1970). The effects of Al ions on nitrate uptake appear to be somewhat stimulatory in barley (Bassioni, 1971; Nagata, 1954).

IV. Nitrate Concentrations in Vegetables

A. DISTRIBUTION IN THE PLANT

Nitrate tends not to be uniformly distributed throughout the plant but rather tends to accumulate in certain plant parts. Although this observation was first made by Berthelot (1884a,b,c), few reports since have provided complete analysis of plant parts for nitrate in a single experiment. Therefore, the generalities concerning nitrate accumulation in plant parts are drawn from many sources and may be subject to the limitations of the internal and environmental effects on nitrate uptake and reduction as discussed elsewhere in this paper (Section 111). Nonetheless, it generally appears (Hanway et al., 1963; Viets and Hageman, 1971; Wright and Davison, 1964) that nitrate concentrations are lowest in floral parts, and increasing concentrations are found in fruit or grain, leaves, roots, and petioles or stems in that order. Within a plant part, nitrate concentrations are higher in older tissue (cf. Table VIII). Bodiphala and Ormrod (1971) have confirmed this pattern of nitrate accumulation for the aerial parts of the spinach plant. In the garden pea (Pisum sativum L.), nitrate accumulates in the vegetative aerial part of the plant while the seed has a relatively very low concentration of nitrate (Trevino and Murray, 1975). Lorenz and Weir (1974), working with table beets, found the highest nitrate concentrations in petioles with lesser concentrations in roots and leaf blades in that order. In tomato plants (Gomez-Lepe and Ulrich, 1974), highest nitrate concentrations were also found in petioles with lesser concentrations in leaf blades, stems, and roots in that order. Thus, it appears from the available data on nitrate distribution in vegetable crops that the generalities cited above are applicable to most plants. However, certain plants are typically nitrate accumulators while others are not. Thus considerable variation in nitrate-N concentrations may occur among the same organs of different plants, e.g., roots of beet and radish generally have high nitrate-N concentrations while carrot and sweet potato (Ipomea batatas L.) roots generally have very low concentrations (cf. Table VII).

NITRATE ACCUMULATION IN VEGETABLES

99

B. FRESH VEGETABLES

The tendency for nitrate to accumulate in certain species was first noted by Berthelot (1 884a) and has been the topic of numerous investigations since that time. As pointed out elsewhere, accumulation represents the difference between uptake and reduction of nitrate. Certain vegetables, because of a very efficient uptake system, an inefficient reductive system, or an unfavorable combination of both, tend to accumulate more nitrate than others. Beets, spinach, and radishes are noted by Lee (1972) as being nitrate accumulators. The Committee on Nitrate Accumulation (1972) adds broccoli (Brussicu oleruceu var. itulicu Plenck.), celery, lettuce, kale, mustard greens (Brussicu junceu Coss.) and collards (Brussicu oleruceu var. ucephulu DC) to the list of nitrate accumulators. We have complied (Table VII) comparable data from the literature which supports the contention that spinach, celery, beets, and radishes are nitrate accumulators. The data in Table VII are not sufficient, however, to justify classifying lettuce and broccoli as nitrate accumulators. Other data in this review (cf. Tables I, 11, IV) indicate that lettuce is a nitrate accumulator while data not shown in Table VII support the inclusion of collards, mustard greens, and kale as nitrate accumulators. Splittstoesser and associates (1 974) have shown that mustard greens and collards accumulate high nitrate concentrations. With applications of 112 kg/ha N as ammonium nitrate, mustard green leaves had 780 ppm nitrate-N and collard leaves 1160 ppm on a fresh weight basis. Comparable data for kale are not available, but the nitrate concentrations obtained using the data of Brown and Smith (1967) and assuming 10% dry weight appear to justify including kale as a nitrate accumulator. Because of the great time span over which nitrate concentration data are available for vegetable crops, it is possible to compare nitrate-N concentrations at a time when most of the fertilizer applied was organic (Richardson, 1907) with a later period when most fertilizers are inorganic. Comparisons between organic and inorganic sources of N can be made for twelve vegetables. Nitrate-N concentrations in the more recent data appear t o be considerably higher in cabbage and cauliflower, slightly higher in celery, carrot and potato (Solunum tuberosum L.), unchanged in spinach, beet, sweet potato, and radish, somewhat less in snap bean and onion, and considerably less in lettuce. It is obviously difficult to make any meaningful generalizations relative to the effects of organic vs. inorganic N sources on nitrate accumulation in vegetables. In addition to the comparison between organic and inorganic N sources discussed above, one may also compare nitrate-N concentrations in vegetable crops over a period of years when the use of inorganic N fertilizers increased. In 1945, total N fertilizer consumption was 595,313 tons (Hargett, 1970). By 1970 consumption of fertilizer N had increased to 7,459,004 tons in the United States (Hargett, 1974). Total harvested crop acreage remained constant from 1945 to

c

0 0

TABLE VII Nitrate-N Concentrations in Fresh Vegetables Plant part

Richardson (1907)

Wilsona

Jackson et d.

Lee

Maynard and Barker

Vegetable

(1949)

(1967)

(1972)

(1972)

Cabbage Lettuce Spinach Celery Rhubarb Beet Carrot Sweet potato Radish

46 378 434 340 587 15 15 413

-

43-276 92 69-541 743 230-1045’ 307’ 75 70-270 -

100 12 52 17 34

230-1254’ 12 14 181-885‘ 460’

ppm NO,-N, fresh wt Leaves Petiole Roots

Fruit

Stem Bulb Tuber Flower parts

Peas Snap bean Tomato Asparagus Onion Potato Broccoli Cauliflower

-

‘NO,-N concentration of expressed sap. ’Field samples. ‘D. N. Maynard and A. V. Barker, unpublished data.

72 153 121 64 1 275 23 10 343 11 53 17 40 24 12

207 63 468 226

-

548 76 45 6 -

-

-

214 238

165 170 524 535 91’ 600 32 0 402 26‘ 35 20 25‘ 14 42

-

NITRATE ACCUMULATION IN VEGETABLES

101

1970; thus, one can conclude that each harvested acre received about twelve times more fertilizer N in 1970 than it did in 1945. It would be improper to apply this increase to vegetable crop acreage since vegetables have been traditionally liberally fertilized. Nonetheless, it would seem realistic to assume a two- to threefold increase in N fertilizer applicaton for vegetable crops during this 25-year span (Lorenz and Bartz, 1967). The data of Wilson (1949) can be compared with data of Jackson et al. (1967), Lee (1972), and Maynard and Barker (1972) for thirteen vegetable crops. This comparison shows two vegetables with greatly increased nitrate-N concentrations, four with slightly increased concentrations, three with slightly lower concentrations, three with much lower concentrations and one with a similar concentration during the period of increased fertilizer N consumption. Thus, it is impossible to generalize with respect to the relationship between increased fertilizer usage and nitrate-N concentrations in vegetable crops. Although considerable information concerning the nitrate concentrations in vegetables has been amassed, the data are based on sporadic and limited sampling. Consequently, the data do not reflect the great variations that can occur in nitrate concentrations in fresh vegetables resulting from genetic, environmental, or nutritional factors (Section 111). These variations are shown in Table VIII for celery, lettuce, and spinach. P. L. Minotti (unpublished) determined the nitrate concentration in these vegetables by sampling for several months and found as much as an eightfold difference in nitrate concentrations for a given vegetable between sampling dates. Certainly some of the difference in nitrate concentration between sampling dates can be attributed to genetic factors, although the cultivars were not known. A part of the difference can be accounted for by nutritional factors since fertilizer applications vary somewhat with geographical location and season of growth. Probably most of the difference in nitrate concentration between sampling dates, however, can be related to environmental conditions before and at harvest (Section 111,A). Nitrate in plants is in a dynamic state constantly responding to changes in environment; thus, extreme variation in nitrate concentrations in plants is normal and to be expected. Nonetheless, the average values obtained with repeated sampling are similar to the average of values shown in Table VII. Presumably, average values based on a sufficient number of samples will largely circumvent the problem of variability.

C. PROCESSED VEGETABLES

The concentration of nitrate in a processed vegetable is usually much less than that in the comparable fresh vegetable. The earliest reported data for processed vegetables showed that nitrate concentrations in canned spinach averaged only 60% of that in fresh spinach (Richardson, 1907). This finding has been generally

102

D. N. MAYNARD ET AL. TABLE VIII Nitrate Concentrations in Fresh Vegetables Purchased in Ithaca, New York Supermarkets' Celery Date sampled

Outer petioles

Lettuce

Inner petioles

Outer leaves

3 April 10 April 17 April 24 April 1 May 7 May 15 May 22 May 5 June 12 June 18 June 15 October 21 October 28 October 5 NovembeI

577 181 337 425 975 277 625 243 575 752 787 465 1000 930 472

187 42 322 106 300 175 137 90 218 156 122 262 387 335 262

ppm NO,-N, 356 450 500 212 231 437 287 168 187 468 487 600 287 237 262

Average:

5 75

207

346

Spinach

Inner leaves fresh wt 143 125 143 112 100 156 117 107 113 162 193 100 156 118 137 132

Petioles only

Petioles and lamina

1850 1050 1175 750 2250 1250 750 950 1275 1250 2250 900 1475 1312 1037

685 355 5 25 3 15 985 511 289 455 500 475 1050 7 25 412 536 5 19

1228

556

'P. L. Minotti, unpublished data.

confirmed by Bodiphala and Ormrod (1971) for spinach and snap beans and by Lee et al. (1971b) for spinach and beets. The loss in nitrate during processing is attributed to leaching during the blanching process (Lee et al., 1971b), and most of the loss occurs within the first minute of blanching (Bodiphala and Ormrod, 1971). 1. Nitrate and Internal Can Corrosion

In addition to the potential health hazards (Section It), the preservation of canned vegetables may be adversely affected by high nitrate concentrations. Sweet potatoes (Smittle and Scott, 1969), snap beans, carrots, spinach (Farrow et al., 1969), and especially tomatoes (Farrow et al., 1971; Hoff and Wilcox, 1970; Myazaka, 1975) act in storage on the tin coating of the can to reduce the shelf-life of the product. Nitrate, acting as an oxidizing agent, has been determined to be the principal detinning agent in these products.

NITRATE ACCUMULATION IN VEGETABLES

103

In many cases, however, other constituents or properties of the product may act in concert with nitrate or independently to cause can detinning. Thus, can corrosion by sweet potatoes (Smittle and Scott, 1969) was related to both phenolase activity and high nitrate concentrations. Oxalic acid and product pH, as well as nitrate, were associated with can corrosion by spinach. Detinning by snap beans was related to pH and nitrate concentrations while low product phosphate concentrations along with high nitrate concentrations caused detinning by carrots (Farrow et at!, 1969). It appears that even vegetables typically quite low in nitrate (Section IV, B), like sweet potatoes, snap beans, and sometimes carrots, may cause internal can corrosion in association with other product constituents.

2. Nitrate and Processed Product Quality The confounding of external and internal factors affecting absorption of nitrate and NR activity may affect other metabolic processes within plants, and the degree of effect may depend on the stage of growth, development, and maturation of the plants. Therefore, the concentration of nitrate in plant tissue at harvest is only a part of the effect of nitrate during the growing season, leading to the end result of total N in the plant tissue. A relation of concentration of nitrate to total N or other N compounds obtained only at harvest may be misleading as to the overall perspective of relationships of nitrate to total N in plants. Nitrogen fertilization and the accumulation of nitrate in vegetable crops may have marked effects on quality components of certain processed products. This is well illustrated in sugar beets (Ulrich et al., 1959; Ulrich and Hills, 1973) and is applicable to table beets where sugar and glutamine (Bourne and Robinson, 1967; Lee, 1974; Lee et al., 1971a; Peck et al., 1974; Shallenberger and Sayre, 1960; Shallenberger et al., 1959; Shannon et al., 1967) contents are related to N fertilization. Both glutamine and sugar have organoleptic significance on the quality of table beets. The effects of time and rate of N fertilizer on nitrate-N and glutamine in the roots of table beet plants are shown in Figs. 3 and 4 and Table IX. Without N fertilizer the beet roots had low concentrations of nitrate and glutamine and a low final yield at harvest. Nitrogen fertilizer applied before planting resulted in beet roots with a high concentration of nitrate in the seedling stage which gradually decreased with time to a low of only 0.01% nitrate-N dry weight at harvest, yet produced a high yield of roots with 1.79% total N and 2.93% glutamine (Table IX). Nitrogen fertilizer, sidedressed only, increased the concentrations of total N, nitrate-N, and glutamine in the roots, but yields were not as high as from N fertilizer applied before planting. However, N fertilizer applied before planting or sidedressed had about the same effects when expressed as

104

D. N. MAYNARD ET AL.

NJTRATE - N IN ROOTS

2

6 a

0.2

0.1 No ffllll2fM N

0 30

7

I5

JUNE

JULY

JULY

22 JULY

29 JULY

5 12 AUGUST AUGUST

FIG. 3. Effects of N fertilizer (112 kglha) applied before planting and/or sidedressed during the growing season on the concentration of nitrate-N in table beet roots (adapted from Peck ef al., 1974).

content of total N, nitrate-N and glutamine in the roots at harvest (Table IX). Nitrogen fertilizer applied before planting plus sidedressed had an additive effect on total N, nitrate-N, and glutamine but not on yield. Due to the accumulation of glutamine with increased N-fertilization of table beets, the formation of 2-pyrrolidone-5-carboxylicacid (F'CA) from the heatlabile glutamine during processing is also enhanced. PCA causes a distinctive off-flavor in canned beets. Lee and associates (1971b) have shown that glutamine accumulation in beets is directly related to N fertilization and that the concentration of PCA in the processed product was directly related to the glutamine content of the fresh beets. The concentration of PCA in processed beets can be controlled to some extent by the processing time.

D. CRITICAL NITRATE CONCENTRATIONS

The prediction of fertilizer requirements from plant analysis is based on the critical concentration of a nutrient within the plant. This concept as developed by Ulrich (1952) and expanded by Ulrich and Hills (1967) defines critical concentration as the nutrient concentration of a plant when the nutrient is just

105

NITRATE ACCUMULATION IN VEGETABLES

I

"O

/

t

01

30 JUNE

I

7 JULY

15 JULY

22 JULY

29 JULY

5 AUGUST

12 AUGUST

FIG. 4. Effects of N fertilizer (112 kg/ha) applied before planting and/or sidedressed during the growing season on concentrations of glutamine in roots of table beet plants (adapted from Peck el ul., 1974).

deficient for maximum growth. As a matter of convenience and practice, the critical concentration usually has been determined at a 10%restriction in growth resulting from a deficiency of the nutrient under study. Plant variables such as tissue, tissue age, nutrient fraction, or cultivar may affect critical concentration values. In like manner environmental and soil variable such as light, temperature, or moisture supply influence the critical concentration. These and other relationships have been reviewed by Bates (1971). Precise critical nitrate-N concentrations have been extracted from the literature and are presented in Table X. Due to the number of variables affecting critical concentrations, it might be more appropriate and meaningful to use a narrow range of concentrations around the determined values. Despite these limitations, the determination of critical nitrate-N concentrations for vegetable crops offers an effective procedure for predicting nitrate requirements. Thus, N fertilization can be equated with crop requirements, and excessive nitrate-N accumulation can be avoided. It is unfortunate that critical nitrate-N concentrations are documented in the literature for only eight vegetable crop species. The paucity of such data perhaps can be explained by the high cost of conducting these experiments, the large number of different vegetable

TABLE IX Effect of Ammonium Nitrate Fertilizer on Growth and NCompounds in Table Beet Roots at Harvest'

P

Ammonium nitrate (kg N/ha) Before planting

Sidedressed

Total N

0 0 112 112

0 112 0 112

1.20 2.42 1.79 2.77

'From Peck etal. (1974).

NitrateN

Fresh

Glutamine

Sugar

0.01 0.11 0.04 0.18

1.37 4.53 2.93 5.36

56.9 48.9 53.9 48.8

wt

Dry wt

Total N

NitrateN

Glutamine

Sugar

17,000 21,100 29,900 28,100

3360 3250 5490 4930

40 79 98 137

0.3 3.6 2.2 8.9

46 147 161 264

1910 1590 2960 2410

z

5 3

*

r

TABLE X: Critical Nitrate-N Concentrations at a 10% Growth Restriction for Various Vegetable Crops Critical Conc. crop Cucumber

Species Cucumis sativus L.

Lettuce

Lactuca sativa L.

Potato

Solanum tuberosum L.

Radish

Raphanus sativus L.

Spinach

Spinach oleracea L.

Cultivar Cubit Blackseeded Simpson White Rose Cherry Belle America Heavy Pack

Squash

sweet melon

Tomato

Cucurbitapep0 L.

Lycopersicon esculentum Mill.

Plant tissue

42 days from seeding Market Maturity

Mature petioles

18 days vegetative growth Market Maturity Market Maturity Market Maturity

Hybrid 424

Market Maturity

Black Zucchini

42 days from seeding 42 days from seeding 46 days from seeding

Cucumis melo var. du&im Naud.

Sampling time

Ginza 4

4 VF145-21

Entire aerial portion Petiole 2 from terminal Root

% NO,-N Dry wt

0.200

El-Sheikh et al. (1970) Maynard and Barker (1971)

0.200

Ulrich and Fong (1973) 0.200 0.500

Entire aerial portion Entire aerial portion Entire aerial portion Mature petiole

Reference

Maynard and Barker (1971) Maynard and Barker (1974)

0.170 Maynard and Barker (1974)

c

0.150 Maynard and Barker (1974)

bl

0.045 El-Sheikh ef at! (1970)

0.100 Mature petiole Petiole 2 from terminal

0.300

El-Sheikh et al. (1970)

0.050

Gomez-Lepe and Ulrich (1974)

c)

s

108

D. N. MAYNARD ET AL.

crops grown commercially, the demonstrated (Maynard and Barker, 1974) cultivar differences in critical concentrations, and the need to define the environmental conditions preceding the sampling period (Section 111, A). Excess nitrate accumulation in plants may be defined as the amount of nitrate found in the tissue above the concentration required for maximum growth. The data compiled in Table XI indicate that excess accumulation varies considerably among species and probably depends upon the tissue being sampled, tissue age, and environmental conditions. Specifically, excess nitrate-N accumulation relative to that required for maximum growth varies from 103% for leaf lettuce to 384% for squash. Data such as these confirm that plants have a great capacity to accumulate nitrate beyond the concentrations required for maximum growth. At present the best available basis for assessing and predicting nutritional requirements is through the critical concentration concept. The use of critical concentrations should be expanded and encouraged as critical nitrate-N values are obtained, recognizing that nitrate concentrations in plants fluctuate and, therefore, that some caution should be applied to its use.

E. GROWTH AND NITROGEN MANAGEMENT OF VEGETABLE CROPS

A N fertilization program for vegetable crops should be managed to provide adequate, but not excessive available N for reliable production of yield and quality, while avoiding or minimizing losses of N to the environment. Yield and quality of produce per unit of N available from all sources during the growing season should be used to evaluate N-use efficiency, rather than units of N per area of land. Improvement in cultural practices other than N management may increase N-use efficiency. For instance, plant selection can be used as a means of increasing production per unit of N (O’Sullivan ef al., 1974). The concentration of nitrate in various portions of plants may be considered as a measure to evaluate the balance between adequate and excessive available N for optimum growth and development during the growing season. Typically, however, this balance assumes two greatly different modes depending on the particular vegetable crop under consideration. Flants that develop fruit or storage organs, such as tomatoes or potatoes, usually show a decline in nitrate-N concentrations in the petioles as the crop approaches harvest (Ceraldson ef al., 1973). The decline in petiole nitrate concentrations is associated with translocation of soluble-N to the developing storage organ, as well as a gradual decrease in available soil-N (Allaway, 1975). A greatly different pattern of nitrate accumulation occurs in vegetables that do not develop storage organs as the food product in that nitrate generally continues to accumulate with age in celery (Zink, 1963), Iettuce (Zink and Yamaguchi, 1962), and spinach (Barker ef al., 1971).

109

NITRATE ACCUMULATION IN VEGETABLES TABLE XI Nitrate-N Culture Levels Resulting in Maximum Yields and Maximum Nitrate-N Accumulation for Various Vegetable Crops Maximum yield

Maximum NO, -N accumulation

NO,-N level (mEq/liter)

NO,-N accumulation (% dry wt)

NO,-N Level (mEq/liter)

NO, -N accumulation (%dry wt)

NO,-N Excess (% dry wt)

6

0.57

48

1.74

1.17

Lettuce

12

1.41

24

1.45

0.04

Potato

16

3.15

64

3.96

0.81

Radish

12

1.04

48

1.42

0.38

Squash

6

0.44

48

I .69

1.25

Sweet melon

6

0.72

48

1.75

1.03

16

2.67

64

3.29

0.62

Crop Cucumber

Tomato

Reference El-Sheikh er al. (1970) Maynard and Barker (1971) Ulrich and Fong (1973) Maynard and Barker (1971) ElSheikh er al. (1970) El-Sheikh et al. (1970) Gomez-Lepe and (Ulrich (1974)

NOTE: Refer to Table X for species, cultivar, sampling time, and plant tissue.

The stage of growth, development, and maturation of plants must be considered, when relating optimum concentration of nitrate in any plant part to the N status of the plant (Chamberland and Doiron, 1973; Geraldson et al., 1973; Maynard and Barker 1972; Peck er al., 1974; Smith and Salmon, 19.47). Vegetable crops have the characteristic sigmoid growth curve of plants consisting of three interrelated stages of growth during their relatively short life from planting to harvest: (1) seedling and early growth, (2) frame, and (3) maturation (Peck, 1975). 1. Seedling and Early Growth Stage A high concentration of nitrate in seedlings indicates that adequate N is available in the limited rooting zone to promote early, vigorous, uniform growth. Uniform emergence and growth of a crop is essential for the production of a high-yielding, quality crop (Peck and Clark, 1973). Therefore, factors affecting nitrate availability at planting may have a continuing effect on the plants from planting until harvest. Generally, because of nitrification, N is absorbed from soils in the nitrate form by plants, and nitrate produces better growth than the ammonium form (Hewitt, 1970; Ingested, 1972; Polizotto er al., 1975), especially for seedlings (Barker er al., 1970; Patnaik et al., 1972). The rate of nitrification of ammonium to nitrate is dependent upon soil environmental conditions (Alexander, 1965; McLaren, 1969).

110

D. N. MAYNARD ET AL.

The capacity of soils to supply available N over the growing season may be estimated from the N mineralization potential of soils (Giles et al., 1975, Stanford and Smith, 1972). Nitrogen mineralization rates indicate the amount of soil N available to the plants over a period of time; thus, one can calculate the rate and amount of N fertilizer needed during the growing season for adequate available N for plant growth based on potential or expected yield (Stanford, 1973). Requirements for fertilizer-N can also be estimated by plant analysis, particularly when these determinations are made early in the growth cycle (Geraldson et al., 1973). With potatoes, for example, maximum yields occur when nitrate-N concentrations are at least 1.20% on a dry weight basis in the most recently matured petioles during the early (before blossoming) plant growth stage (Tyler et al., 1961). Nitrate sufficiency values have been established for a number of other vegetable crops during the early plant growth or seedling stage (Geraldson et al., 1973), but in sweet corn, a rather poor relationship was found between nitrate concentration at the 8-leaf stage and yield. 2. Frame Stage A medium concentration of nitrate in plant tissues during the frame or midgrowth stage indicates sufficient available N in the rooting zone to maintain growth and development in the plants. Carter et al. (1971) interpreted the time-dependent decrease in concentration of nitrate in petioles of sugar beet plants during the growing season to predict the need for supplemental N fertilizer for the remainder of the season. Halvorson et al. (1975) found that fresh juice can be used to determine nitrate-N in petioles of beet plants. However, a petiole test, preferably together with a soil test, early in the growing season is more useful for determining the requirements for optimal N fertilizer applications. Nitrate concentrations in roots, petioles, and blades of table beet plants grown with different rates and time of application of N fertilizer were determined during the growing season (Peck et aL, 1974). Within the range of about 0.04 to 0.60% nitrate-N on a dry weight basis, the linear correlation ( r 2 ) between percentage nitrate-N in the roots and blades was 0.76 (Fig. 5). Within the range of nitrate of about 0.04 to 0.60% nitrate-N in the roots and 0.07 to 2.0% in the petioles, the linear correlation between percentage nitrate-N in the petioles and roots was 0.82. Thus, with the close correlation between percentages of nitrate in petioles and roots and the wider range of nitrate in the petioles than in blades, petioles are a more sensitive sampling tissue than blades to indicate the nitrate status of the roots. In potato petioles, at least 0.90% nitrate-N on a dry weight basis at midseason is required to insure maximum yields (Tyler et al., 1961). Geraldson et al. (1973) reported the following nitrate-N concentrations at midgrowth as being

NITRATE ACCUMULATION IN VEGETABLES

111

sufficient: carrot petioles, 1 .OO%; celery petioles, 0.90%; spinach petioles, 0.80%;and sweet potato petioles, 0.35%, on a dry weight basis.

3. Maturation Although N fertilizer applications generally increase the concentration of nitrate in plants, the concentration of nitrate in plants at harvest time has not been consistently related to N fertilization (Wright and Davison, 1964). When

?

0.6 -

ILu

petio\ec

z

2

$

0.2

Lu

z* o V

PER C E N T NITRATE-N BLADES A N D PETIOLES

FIG. 5. Correlations of concentrations of nitrate in roots, petioles and blades of table beet plants (adapted from Peck etal., 1974).

potassium chloride fertilizer is applied to soil, plants absorb and accumulate the K and C1 ions, which remain in the plant tissues in amounts nearly proportional to the rate applied (Peck and MacDonald, 1972). In contrast, when ammonium nitrate fertilizer is applied to soil, plants absorb most of the N in the nitrate form, and with adequate growing conditions, most of the nitrate is assimilated and metabolized to other N compounds within the plants (Peck et al., 1974). Long-term effects of N fertilizer applied before or at planting may have less influence on the concentration of nitrate in plant tissues at harvest time than short-term effects (Section 111, A) such as soil and air temperature, solar radiation, awilable soil water and evapotranspiration stress on the plants at or near harvest (Hanway ef al., 1963). Brown and Smith (1966) reported that table beet roots, grown with 0 to 448 kg N/ha from ammonium nitrate applied at planting, had very low concentrations of nitrate in response to N fertilization. However, as they explained the higher rates of N fertilizer may have increased early vegetative growth which was followed by a reduced supply of available nitrate in the soil; thus, accumulation of nitrate did not occur as evidenced by sampling only at harvest. In a later study, Brown and Smith (1967) reported that N increased the concentration of nitrate in the roots harvested on 26 June when table beet plants were grown in 1964 with 0 to 224 kg N/ha. Roots harvested on 19 July, however, had a higher

112

D. N. MAYNARD ET AL.

nitrate concentration than those harvested on 26 June, probably due to a cool and wet spring followed by warmer soil temperatures which increased available nitrate in the soil. In 1965, N fertilizer increased the concentration of nitrate-N in the tops of the beet plants from 0.19 to 0.78% dry weight but did not affect nitrate in the roots. The inconsistent effect of N fertilizer on concentration of nitrate in the beet roots at harvest justifies the necessity of monitoring nitrate in the plants during the growing season. In addition, environmental factors that affect nitrate availability in the root zone, uptake by the plants, and metabolism of nitrate within the plants must be considered in order to evaluate the cause of different concentrations of nitrate in the roots at harvest. Their conclusion (Brown and Smith, 1966, 1967) that in general, the use of fertilizer N in excess of 56 kg/ha causes nitrate accumulation in most vegetables is obviously a misleading guide to efficient use of N fertilizer for table beets. In order to evaluate the economic response of table beets to N fertilizer, information is needed on plant population per unit area, especially in rows close enough for commerical production. Thus, returns per unit of N fertilizer can be expressed per unit of production rather than unit area of soil. The concentration of available N in the rooting zone must be adjusted to the response or requirements of the plants at various stages of growth, development, and maturity in order to supply adequate but not excessive available N for optimum N efficiency. Using the definitions of concentration and contents as proposed by Farhoomand and Peterson (1968), the concentration of nitrate, expressed as percentage nitrate-N on a dry weight basis, generally decreases during the growing season for crops producing fruit or storage organs. A high concentration of nitrate in the early growing season may increase the growth of plants so that at harvest, plants may have a low concentration of nitrate/unit of dry weight but a high content of nitratelha in the total dry weight of plants. For vegetative crops, concentration and content of nitrate may increase with maturity. V. Conclusions

The threat of nitrate toxicity to man from ingestion of vegetables has stimulated widespread interest and research in nitrate accumulation by vegetable crops. Findings summarized herein tend to minimize the hazard associated with consumption of nitrate-containing vegetables by adults and by infants over 3 months of age when the food is given sanitary preparation, proper refrigeration, and timely consumption. Nonetheless, it appears important to incorporate low nitrate-accumulating cultivars, fertility and management practices resulting in restricted nitrate concentrations, and manipulation of environmental variables into the crop production scheme for vegetable crops. Much progress has been made on the delineation of vegetables and their parts which tend to accumulate

NITRATE ACCUMULATION IN VEGETABLES

113

nitrate and on the nutritional and environmental factors affecting this accumulation. Considerably less attention has been directed toward developing low nitrate-accumulating cultivars. This may in large measure be related to the time-consuming nature of plant improvement research. Some of the more notable contributions discussed are related directly to methods of limiting nitrate concentrations in the consumable portion of the vegetable plant. They are summarized below. 1. Spinach is one of the vegetables having inherently high nitrate concentrations, and petioles have severalfold higher concentrations than leaf blades. Therefore, partial or total removal of petioles prior to processing or preparation appreciably reduces nitrate intake. 2. Because of the light requirement for nitrate assimilation in shoots, nitrate concentrations tend to be lower in the afternoon than in the morning and on sunny days than on cloudy days. Therefore, adjustment of the harvesting schedules may reduce the nitrate concentration in vegetables. 3. Nitrate concentrations in plants are at least partially related to the fertilizer-N applied to the crop. Schedule applications of N-fertilizers, as developed for table beets, help to ensure a product low in nitrates and high in quality. 4. On organic or other soils where significant mineralization of N may occur, applications of N-fertilizers should be made t o complement the predicted rate of mineralization at that part of the growing season when the crop is actually in the field. 5 . Nitrate, due to nitrification, is the most common form of available N present in soils. A portion of the N from fertilizer may be applied in the ammonium form, with a nitrification inhibitor, to restrict nitrate uptake and accumulation. Proportions of nitrate and ammonium, and concentrations of the nitrification inhibitor for maximum yields and minimum nitrate accumulation have been determined for spinach and radishes, two nitrate-accumulating vegetables. 6. Plant tissue analysis together with the determination of critical nitrate concentrations are useful tools to monitor nitrate availability to plants.

ACKNOWLEDGMENTS Contribution from the Massachusetts Agricultural Experiment Station and the New York Agricultural Experiment Station. Much of the authors' research reported herein has been conducted under Regional Research Project NE-39, Factors Affecting the Accumulation of Nitrates in Soil, Water, and Plants. This research was supported in part by grant FD-00282 from the Food and Drug Administration to A. V. Barker. The clerical assistance of Mrs. Dolores J. Kovalski and Mrs. Charlotte L. Maynard is greatly appreciated.

114

D. N. MAYNARD ET AL. REFERENCES

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THE PROGRESS. PROBLEMS. AND PROSPECTS OF PLANT PROTOPLAST RESEARCH

.

lndra K Vasil Department of Botany. University of Florida. Gainesville. Florida

I. Introduction .................................................. I1. Isolation of Rotoplasts .......................................... A . Mechanical Methods .......................................... B. Enzymatic Methods .......................................... C. Sources of Rotoplasts ........................................ I11 Culture of Protoplasts ........................................... A . Methods of Culture ........................................... B. NutrientMedia .............................................. C. Physiological Studies ......................................... D Growthin Vitro ............................................. IV. Protoplasts and the Genetic Modification of Plants ..................... A Fusion of Protoplasts ........................ ................ B. Uptakeof DNA ............................................. C UptakeofCellOrganelles ...................................... D. Cytoplasmic Male Sterility ..................................... E. Uptakeofviruses ............................................ F. Nitrogen Fixation ............................................ V TheFuture ..................................................... References ....................................................

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I

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119 120 120 121 125 126 126 128 129 132 135 136 143 144 146 147 149 152 153

Introduction

Two of the most important developments in experimental botany in recent years have been the production of haploid plants from the culture of whole anthers or isolated microspores (Kasha. 1974; Vasil and Nitsch. 1975). and the isolation. culture. and fusion of higher plant protoplasts' leading to the regeneration of whole plants (Vasil and Vasil. 1971; Cocking. 1972; Tempe. 1973;

' The term protoplasf. as used in this review. describes that part of the plant cell which lies within the cell wall and can be plasmolyzed. and which can be isolated by removing the cell wall by mechanical or enzymatic procedures The protoplast is. therefore. only a naked cell-surrounded by the plasma membrane-which is potentially capable of cell wall regeneration. growth. and division The present discussion is. however. limited to protoplasts of angiosperms only.

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119

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Gamborg et ul., 1974; Gamborg, 1975). The potential of these research techniques in the understanding of many important biological phenomena and for the genetic improvement of crop plants has attracted a large number of scientists with diverse interests and technical know-how to the field of plant cell and tissue culture. Agronomists, geneticists, and plant breeders have not lagged behind, but have shown a keen interest in the above developments and have begun attempts to use these elegant techniques for the improvement of crop plants. This review, written especially for colleagues in the agricultural sciences, should be useful in providing the basic information about the isolation, fusion, and culture of plant protoplasts, in pointing out some of the new research approaches that may be useful in the production of better varieties of crop plants, and in understanding the basic processes involved in the growth and differentiation of higher plants. II. Isolation of Protoplasts

Protoplasts can be isolated from a variety of plant tissues and cultured cells. However, it has often proved difficult to obtain consistently high yields of viable protoplasts from fresh plant tissues. The most important factor responsible for such variability appears to be the physiological condition of the source tissue or plant, which affects the susceptibility to digestion of the cell walls and the stability of the protoplasts (Uchimiya and Murashige, 1974; Watts et uZ., 1974; Zaitlin and Beachy, 1974; Shepard and Totten, 1975). The nutrition and age of the plants, as well as the temperature and illumination (duration and intensity) at which they are grown, directly affect the isolation of protoplasts and their suitability for further growth. These parameters vary from species to species and must be determined experimentally for the material being used. It is essential that the isolated protoplasts not be contaminated with microorganisms like bacteria and fungi. The usual techniques of sterilizing plant tissues and organs are used during protoplast isolation. Antibiotics can be used to control the growth of microorganisms (Watts and King, 1973a; Davey et uZ., 1974), but the presence of such compounds introduces an undesirable variable.

A. MECHANICAL METHODS

Early attempts to isolate plant protoplasts relied entirely on mechanical methods, and were essentially limited to tissues containing rather large and vacuolated cells, or to filamentous structures with elongated cells. The plasmalemma of such cells retracts away from the cell wall during plasmolysis resulting in the formation of a rounded protoplast in the center of the cell. When tissues containing such plasmolyzed cells are cut into thin strips, the end walls are often

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cut cleanly without damaging the protoplasts which lie safely away from the cell wall. Protoplasts from such cut cells are easily released by osmotic swelling which takes place when the tissue is placed in solutions causing rapid uptake of water. Klercker (1892) was the first to report on this technique to isolate protoplasts from the plasmolyzed cells of Srratiotes azoides, and the method is still used by some for certain physiological studies. Mechanical methods for the isolation of higher plant protoplasts have neither improved much, nor become popular, due to the restricted choice of plant tissues (such as leaf, bulb-scale, and fruit epidermises, storage tissues) suitable for this technique, and the very limited number of protoplasts obtained after a rather tedious procedure. Nevertheless, many of the early and pioneering studies and some of the recent work on the expansion capacity of naked protoplasts, the effects of auxins on the plasmalemma, the osmotic relations of plant cells, the effect of fungal toxins on the plasmalemma, the fusion of protoplasts, etc., were carried out using mechanically isolated protoplasts (Klercker, 1892; Seifriz, 1928; Chambers and Hofler, 1931; Plowe, 1931; Levitt et al., 1936; Michel, 1937; Tomava, 1939; Koningsberger, 1947; Tribe, 1955; Whatley, 1956; Vreugdenhil, 1957; Pilet, 1971, 1973; Pilet et al., 1972). A combination of mechanical and enzymatic methods has also been found to be useful (Bui-Dang-Ha and Mackenzie, 1973; Harada, 1973).

B. ENZYMATIC METHODS

The disadvantages inherent in the mechanical methods of protoplast isolation were largely overcome by the development of an enzymatic procedure by Cocking in 1960, employing a comparatively crude cellulase preparation from the fungus Myrothecium verrucaria to isolate protoplasts from tomato roots. Similar enzyme preparations were later used to isolate large populations of protoplasts from a variety of tissues (Gregory and Cocking, 1963, 1965; Ruesink and Thimann, 1965, 1966). It thus became possible not only to obtain very large populations of active and viable protoplasts, but also to avoid their exposure to the deleterious effects of excessive plasmolysis, and to obtain protoplasts from comparatively non-vacuolated meristematic cells in which plasrnolysis does not occur readily. It must be recognized, however, that the enzymatically isolated protoplasts are exposed to a variety of exogenous as well as endogenous (from burst or damaged cells) enzymes for considerable periods of time, while the mechanically isolated protoplasts are exposed only to the endogenous enzymes for comparatively brief periods of time. Protoplast preparations, whether obtained by mechanical or by enzymatic methods, almost always contain a considerable amount of cellular debris in the form of undigested tissue, broken cell

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walls, membranes, nuclei, cell organelles, etc., all of which must be removed rapidly and adequately. This is partially but satisfactorily achieved by filtration through Miracloth or stainless steel and nylon filters, followed by washing on Millipore filters or by centrifugation. Repeated centrifugation, even at low speed (ca. 100 g), can be harmful, but has been used successfully to obtain viable protoplasts from several species. Protoplast preparations can also be purified by floating on sucrose solutions (Gregory and Cocking, 1965; Chupeau and Morel, 1970; Evans et al. 1972; Pilet et al., 1972), and by filtration through various sieves followed by separation of pure protoplast populations at the interface of an aqueous dextran-polyethylene glycol two-phase system (Kanai and Edwards, 1973). It is not established if such procedures have deleterious effects on protoplast viability, and on their capacity for cell regeneration and division. One of the principal factors contributing to the rapid development of the techniques for the enzymatic isolation of protoplasts, and their use in the investigation of a variety of biological phenomena of applied as well as basic research interest, has been the easy availability of a number of potent enzyme preparations since 1969. Of these, the most widely used and effective are the Japanese manufactured preparations of cellulase (from Wchoderma uiride), Driselase (from a Basidiomycete and rich in cellulase and pectinase), and Macerozyme (from Rhuopus; rich in pectinase); xylonase-showing a broad spectrum of activity-has been used by Landovl and Landa (1975) to isolate protoplasts from the leaves and petals of several members of the Asteraceae. These comparatively crude enzyme preparations may contain various toxic substances and impurities, including nucleases (especially ribonucleases), lipases, peroxidases, proteolytic and various other enzymes, phenolics, etc. Partial purification of these enzymes by elution through Sephadex G-25 or Biogel-which removes phenolics, salts, and inert material-facilitates the ease with which protoplasts can be isolated (Schenk and Hildebrandt, 1969a; Kao et al., 1971; Cocking and Evans, 1973; Vasil et al., 1975). However, most workers have used the commercially available enzymes without any further purification to obtain good yields of protoplasts which are capable of further growth and development. Very highly purified and crystalline enzyme preparations are not only prohibitively expensive, but are also relatively useless for protoplast isolation, as these are unable to breakdown the chemically and structurally complex plant cell walls which contain hemicellulose, pectin, lignin,lipids, and proteins, in addition to cellulose. Complex enzyme mixtures, cleansed of toxic substances and impurities, are thus most useful for the complete breakdown of the cell walls and the release of the protoplasts. Two principal methods have been used for isolating protoplasts from plant tissues. In the so-called sequential method, developed by Takebe et al. (1968), plasmolyzed leaves of Nicotiana tabacurn are cut into small pieces after peeling off the lower epidermis, and macerated with the help of Macerozyme, a crude

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polygalacturonase preparation (Suzuki et al., 1967). This treatment results in the release of mesophyll cells, which after washing are treated with Wchodemza uiride cellulase to digest the cell walls to obtain protoplasts. Addition of low molecular weight potassium dextran sulfate considerably enhances the separation of cells and the stability of the isolated protoplasts, possibly by binding to some of the proteins present as contaminants in the crude enzyme solutions. Although the removal of the lower epidermis is a tedious procedure, many workers have found it to be a useful step which ensures the rapid access of the enzymes to the tissues, resulting in high yields of protoplasts from the leaves of a wide variety of plant species (Otsuki and Takebe, 1969a; Cocking and Evans, 1973; Constabel et al., 1973; Wakasa, 1973; Kao et al., 1974; Pelcher et al., 1974; Vasil and Vasil, 1974; Watts et al., 1974). A short period of incubation in vacuum, followed by incubation under normal pressure, has also been found to be helpful (Durand et al., 1973; Kanai and Edwards, 1973). The other and the most commonly used technique involves a mixture of pectinase and cellulase, which not only macerates the tissues by attacking the middle lamella, but also releases protoplasts by breaking down the cell walls (Power and Cocking, 1968, 1970). Recently, we (V. Vasil and I. K. Vasil) have used the following procedure-developed by Durand et al. (1973) for Petunia hybniia-to obtain rapid release oflarge populations of protoplasts from young leaves ofNicotiana tabacum and Viciafaba. Freshly picked leaves are washed thoroughly in running water, cut into 1 mm or thinner slices, and again washed several times to remove cellular debris. The sliced material is then placed in a pectinase-mannitol (2% and 0.4 M , respectively) solution under vacuum for 2 minutes, followed by incubation at 30°C for 30 minutes without any shaking. The pectinase solution is then gently drained off and replaced by a cellulase-mannitol (2% and 0.4 M,respectively) solution, and the tissue is again incubated for 30 minutes at 30°C with occasional shaking to liberate the free cells as well as many protoplasts. The entire mixture is then filtered through a 100 pm stainless steel mesh to remove coarse debris, and the filtrate is centrifuged at 100 g for 2 minutes to obtain a pellet of cells and protoplasts. The pellet is resuspended in a fresh cellulase-mannitol solution and incubated at room temperature with occasional shaking. Protoplasts are released, depending on the species used, during the next 20 minutes to 3 hours. This procedure eliminates the need to peel off the lower epidermis and, more importantly, protects the cells and protoplasts from the harmful effects of various substances released into the enzyme mixture during the early period of incubation, and also separates the protoplasts from the undigested tissues at an early stage. We have been able to maintain protoplasts of V. faba, isolated by this procedure, in culture for 2 to 3 weeks. During this period the protoplasts enlarge, show cytoplasmic streaming, cell wall formation as evidenced by budding and/or elongation, and the chloroplasts aggregate around the nucleus in the

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center. However, we have not been able to induce any sustained cell divisions so far, apart from an occasional division resulting in the formation of two cells (this may be due to the general difficulty of culturing legume protoplasts rather than to the method of their isolation). Pectinase alone will also readily release protoplasts from the locule and placental tissues of Lycopersicon esculentum (Gregory and Cocking, 1965) and Solanum nignzm (Raj and Herr, 1970) berries. The cell walls in such tissues are known to be partially or completely hydrolyzed during the ripening process. Driselase, which has high cellulase and pectinase activities, can sometimes be used alone for isolating protoplasts, although it generally works better when combined with additional cellulase or pectinase. Protoplasts lose the protection of the cell wall and become highly susceptible to osmotic damage and shock as they are released into the surrounding medium during the gradual breakdown of the cell walls. It is essential, therefore, that the isolation medium-though allowing slight plasmolysis-should ensure the osmotic stability of the protoplasts (Ruesink and Thimann, 1966; Schenk and Hildebrandt, 1969a,b). This is commonly achieved by preparing the enzyme solutions in 0.4-0.8 M mannitol and/or sorbitol, sucrose, or glucose, or better still, with a combination of ionic as well as non-ionic osmotica. Meyer (1974) reports obtaining high yields of stable protoplasts, irrespective of the physiological condition of the plant used, by using salt solutions to maintain suitable osmotic conditions. However, salts may inhibit enzyme activity and also cause the formation of abnormal walls. Plasmolysis is known to influence a variety of cell functions (Greenway, 1970). It is important, therefore, that the cells be plasmolyzed as little as possible during protoplast isolation. Shepard and Totten (1975) have shown that by controlling the growth and nutrition of plants, it is possible to obtain large quantities of viable tobacco mesophyll protoplasts using 0.2 M sucrose as the primary osmoticum. Other important factors that affect the yield, stability, and further growth of the protoplasts, are the pH of the incubation medium, presence of Ca2*, and the temperature and duration of the enzyme treatment. The duration of protoplast isolation should be as short as possible to minimize deleterious effects from impurities in the enzyme preparation, and materials released during cell wall digestion, which may cause damage to the plasmalemma, resulting in reduced survival and viability of the protoplasts. It should be remembered that plasmolysis during the isolation procedure must necessarily result in a substantial reduction of the surface area (as much as 25%) by infolding of the plasmalemma, and the formation of large vesicles in the cytoplasm. These vesicles can transport considerable amounts of the surrounding solutions directly into the protoplasts (Withers and Cocking, 1972). It has been suggested, therefore, that in order to minimize the effect of the enzyme

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solutions on the protoplasts, the cells and tissues be placed first in the plannolyticum only, followed by normal incubation in the plasmolyticum-enzyme mixture (Cocking, 1972). It is the experience of many workers that plants that yield perfectly good protoplasts at one time of the year may fail to do so at oth2r times. This problem is apparently caused by differences in the chemical and/or physical nature of the cell wall and the osmotic conditions of cells and tissues, which are known to vary according to age, nutrition, and growing conditions of the plant. Variations in the amount and nature of the hemicellulose and lignin content of the cell wall-which are age related and apparently quite common-and the presence of enzyme inhibitors in the wall, interfere with the accessibility of p-1,4-glucanase to the cellulose microfibrils. Such problems can be largely remedied by growing the experimental plants under carefully controlled nutritional and environmental conditions, by using leaves from shoots differentiated in vitro (Binding, 1975b), or by using rapidly growing callus or cell suspension cultures, preferably grown in defined nutrient media.

C. SOURCES OF PROTOPLASTS

In pioneering work on the isolation of protoplasts with cell wall-digesting enzymes, root tips of seedlings and the locular tissue of mature solanaceous berries were used (Cocking, 1960; Gregory and Cocking, 1965). Since then protoplasts have been obtained from a wide variety of tissues and organs (Cocking and Evans, 1973), such as leaves (Takebe et al., 1968; Otsuki and Takebe, 1969a; Ohyama and Nitsch, .1972; Evans et al., 1972; Durand et al., 1973; Kartha et al., 1974b; Vasil and Vasil, 1974; Watts et al., 1974), cladodes (Bui-Dang-Ha and Mackenzie, 1973), shoot apices (Gamborg et al., 1975), fruits (Raj and Herr, 1970), roots (Ruesink and Thimann, 1966; Power et al., 1970; Bawa and Torrey, 1971; Landgren and Torrey, 1973; Vasil and Vasil, 1974), legume root nodules (Davey et al., 1973; Vasil et al., 1975), coleoptiles (Ruesink and Thimann, 1965; Hall and Cocking, 1971), aleurone layer of cereal grains (Taiz and Jones, 1971), microspore mother cells (Ito, 1973a), microspore tetrads (Bhojwani and Cocking, 1972; Rajasekhar, 1973; Wakasa, 1973), and pollen tubes (Condeelis, 1974). Of these, the protoplasts isolated from the mesophyll tissue of leaves-though highly differentiated and specialized in structure and function-have proved most suitable for culture and further growth. Protoplasts have also been isolated from a variety of callus (Ruesink and Thimann, 1965; Motoyoshi, 1971; Wakasa, 1973; Vasil and Vasil, 1974; Vardi et al., 1975) and suspension cultures (Eriksson and Jonasson, 1969; Schenk and Hildebrandt, 1969a,b; Kao et al., 1971; Grambow et al., 1972; Maretzki and Nickell, 1973; Gamborg et al., 1974). Isolating protoplasts from tissue cultures

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has several advantages. The cells and tissues are grown under aseptic and controlled physiological and environmental conditions. The callus tissues are generally quite friable while the suspension cultures comprise single cells or groups of loosely held cells. Further, these cells and tissues are already conditioned to growth in culture, and the requirements for their continued growth, and in some cases differentiation and organogenesis, are already known. Lignification of the walls of cultured cells makes it difficult to isolate protoplasts from such cells, but this problem can be remedied by inducing rapid growth of the cultures, or increasing the frequency of subculture and select for rapidly growing strains, and harvesting the cells for protoplast preparation during the early phases of active growth. Ill. Culture of Protoplasts

The stability and further growth of protoplasts are largely dependent on the procedures used for their isolation and the nutritional, physiological, and physical conditions of their culture. As much of the work on the isolation and culture of protoplasts started only around 1969-1970, success has so far been limited to only a few species of plants. Development of more efficient and standardized techniques for the handling and culture of protoplasts from a wider variety of plants are urgently needed.

A. METHODS OF CULTURE

Most of the current techniques for the culture of protoplasts have been adopted from those already in use for many years for the culture of plant cells. Protoplast suspensions, washed free of cellular debris and enzymes, are generally cultured as described below. 1. Suspension and Drop Cultures

Protoplasts are suspended in a liquid medium, at a density of about 1 X 105/ml,and cultured in 25-50 ml Erlenmeyer flasks. The cultures are shaken slowly, at 25-50 rpm, and incubated at 25"-28"C in continuous light (5002000 lx). Adequate aeration of the cultures can be obtained even without shaking when a small volume (about 2 ml of the protoplast suspension in a 25 ml Erlenmeyer flask) of the medium is used (Vasil and Vasil, 1974) or when Ficoll is added to the medium which causes the protoplasts to float on the surface (Eriksson and Jonasson, 1969).

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An important modification of the suspension culture technique, called the liquid droplet method, was developed by Kao et al. (1971) and has been used very successfully (Grambow et al., 1972; Gamborg et al., 1973; Kartha et al., 1974a). Suspensions of protoplasts (1 X lo4 or 1 X 105/ml) are placed in 50 pl drops in plastic petri dishes, sealed with Parafilm, and incubated at 25"-30°C at low intensities of light (100-500 lx) or in the dark. After cell wall regeneration and the initiation of cell divisions, fresh nutrient media can be added to the same cultures, and eventually cell suspension cultures can be obtained. The small size of the drops provides enough aeration.

2. Plating Protoplasts suspended in a liquid medium are mixed gently but quickly with an equal volume of the medium prepared in agar and kept at about 45°C. Small (5 ml) aliquots of the protoplast-containing agar medium (5-7.5 X lo3 protoplasts/ml) are then poured into petri dishes, which are sealed with Parafilm and placed upside down in an incubator at 28°C with continuous illumination at 2300 lx. This method, first used by Nagata and Takebe (197 l), is a modification of the plating technique of Bergmann (1960), and has been used successfully, with or without further modifications, for the culture of protoplasts (Horine and Ruesink, 1972; Frearson et al., 1973; Takebe and Nagata, 1973; Wallin and Eriksson, 1973; Melchers and Labib, 1974). Aeration of protoplasts, which are embedded in shallow layers of the agar nutrient medium, is adequate as demonstrated by their continued growth and development. An important advantage of this technique is the fact that the protoplasts remain in a fixed position, and thus it is possible to follow the growth and behavior of individual protoplasts. Once small colonies of cells have been formed, these can be transferred to agar media to start callus cultures. Vasil and Vasil (1974) used a combination of the suspension and plating techniques for the regeneration of tobacco plants from mesophyll protoplasts. This combination has also proved useful for protoplasts of several other species (Kao et al., 1974; 0 . L. Gamborg, personal communication).

3. Microculture Chambers A still better method for observing the development of individual protoplasts at high resolution under the microscope is the microculture chamber technique, used successfully for mesophyll protoplasts of tobacco (Vasil and Vasil, 1973, 1974) and Petunia (Durand et al., 1973). It is a useful technique to follow the fusion of protoplasts and to monitor the development of the fusion products, particularly in those cases where even morphological markers to identify the

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fusion products are not available. The method, first developed by Jones ef al. (1960), has been perfected to the extent that single, isolated cells of tobacco can be grown to whole plants (Vasil and Hildebrandt, 1965). A droplet of ca. 30 pl

of the nutrient medium containing one to several protoplasts is placed on a microscope slide and is enclosed by a cover glass resting on two cover glasses placed on either side of the drop. The culture is sealed by paraffin oil. After colonies of 75 or more cells have been formed, these are mechanically transferred to nutrient agar media in routine cultures.

B. NUTRIENT MEDIA

Isolated protoplasts generally have the same basic nutritional requirements as those determined for cultured cells and tissues. The following two defined nutrient media are most commonly used: (i) A modified version of Murashige and Skoog’s (1962) medium, extensively and erroneously referred to as the Nagata and Takebe medium in spite of the fact that in the original publication it is clearly referred to as a modification of the Murashige and Skoog medium (Nagata and Takebe, 1971;Ohyama and Nitsch, 1972; Bui-Dang-Ha and Mackenzie, 1973; Durand et al., 1973; Frearson et al., 1973; Wallin and Eriksson, 1973; Vasil and Vasil, 1974). (ii) The B5 medium (Gamborg ef al., 1968), which was originally developed for the culture of soybean cell suspensions, and which has proved especially useful for protoplasts derived from suspension cultures (Grambow et aL, 1972; Kartha et al., 1974b; Michayluk and Kao, 1975). The organic growth factors in the above media need to be carefully controlled for each species. In some cases cell-free conditioned media have also been used to grow protoplasts (Kao et al., 1970; Maretzki and Nickell, 1973). Maintenance of proper osmotic conditions during the culture of protoplasts is essential, and this is achieved by including various substances like glucose (Kao and Michayluk, 1974; Michayluk and Kao, 1975), mannitol (Nagata and Takebe, 1971; Vasil and Vasil, 1974), sorbitol (Eriksson and Jonasson, 1969; Keller ef al., 1970), sucrose (Cocking, 1961; Mackenzie et al., 1973; Michayluk and Kao, 1975), or xylose (Michayluk and Kao, 1975), alone or in combination, as osmotic stabilizers. Once cell wall regeneration has taken place and sustained cell divisions started, the cell colonies can be transferred to media containing sucrose and/or glucose as the sole carbon sources. The use of metabolically active osmotic stabilizers (glucose, sorbitol, sucrose, etc.) along with metabolically inert osmotic stabilizers (mannitol) may be advantageous, because such substances will be gradually used by the protoplasts during early growth and cell wall regeneration, resulting in a gradual reduction of the osmoticum. Such a procedure will eliminate the sudden change in osmotica when the regenerated cells are transferred to nutrient media for further growth. The stability, viability,

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and future growth of the protoplasts is closely related to the maintenance of proper osmotica during isolation and subsequent culture. The concentration of protoplasts in the nutrient medium during their culture is another important limiting factor. In general a population density of 1 X lo3 to 1 X 105/mlis required to ensure cell wall regeneration and induction of cell division, provided other parameters remain favorable. Raveh er al. (1973) and Raveh and Galun (1975) have used nondividing, X-irradiated protoplasts as feeder (nurse) cells to support the division of viable protoplasts plated at densities as low as 5-50 per milliliter. Kao and Michayluk (1975) have recently obtained sustained cell divisions and tissue formation from a single protoplast of Vicia hajasrana cultured in 4 ml of a very complex nutrient medium. Plant protoplasts or cells have never before been successfully cultured at such low population densities, and it is hoped that the availability of this new medium will be of much help in the culture of protoplasts and cells of problem species.

C. PHYSIOLOGICAL STUDIES

The plant cell wall has proved to be a major impediment to physiological studies of the plasmalemma. Protoplasts being naked cells devoid of a cell wall are thus an ideal experimental system to study the effect of various plant growth substances, etc., on the physical and physiological properties of the plasmalemma. This assumes that the plasmalemma is not altered during protoplast isolation and that the cell wall is not essential in the in vivo regulation of cell permeability. Studies on isolated protoplasts from roots, fruits, leaves, and coleoptiles have indicated a rapid and direct effect of auxins causing increased vacuolation and cyclosis, water uptake, expansion, and bursting (Cocking, 1962; Gregory and Cocking, 1966; Power and Cocking, 1970; Pilet, 1971, 1972; Bayer, 1973; Hall and Cocking, 1974). The bursting of isolated protoplasts in media containing physiological levels of indole-3-acetic acid is inhibited when the anti-auxins, transcinnamic acid or 4chlorophenoxyisobutyric acid, are added to the medium, showing that these responses are specifically induced by the auxin which apparently changes the permeability of the protoplast membrane system. Such auxin effects on membrane permeability possibly play an important role in the rapid elongation of the cell wall, and also affect protein and nucleic acid synthesis. The occurrence of pinocytosis in plant cells has been suggested as a possible mechanism for the rapid uptake and transport of various substances, including water, solutes, and even virus particles. The use of protoplasts has provided substantive and elegant demonstration of the formation of pinocytotic vesicles and the pinocytotic uptake of ferritin, polystyrene latex spheres, and tobacco

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mosaic virus particles (Mayo and Cocking, 1969a; Aoki and Takebe, 1969; Takebe and Otsuki, 1969; Power and Cocking, 1970). The differential staining of the protoplast plasmalemma caused by phosphotungstic acid shows that the stained regions of the membrane have a distinct and different chemical composition than the unstained areas of the plasmalemma as well as other organelle membranes including the tonoplast (Mayo and Cocking, 1969b). In addition, the presence of vesicles in the cytoplasm containing ferritin and bounded by membranes stained by phosphotungstic acid suggests that the vesicles were formed by infoldings of the plasmalemma, resulting in the pinocytotic uptake of ferritin. Plant protoplasts are maintained in vitro in comparatively high osmotica, generally between 0.4 and 0.8 M. In view of the fact that pinocytosis can be induced or inhibited by a variety of substances and/or conditions, it is not yet clear whether the extent of pinocytosis observed in isolated protoplasts is close to or greatly in excess of that in the normal plant cell. However, it is clear that substantial pinocytotic uptake of materials from the surrounding medium takes place during the marked shrinkage of the protoplast caused by infoldings of the plasmalemma during the breakdown of the cell wall. The variety of materials used as osmotica to stabilize protoplasts in vitro also affect the nature of the protoplast surface membrane, and thereby the uptake of various substances across the plasmalemma (Ruesink, 1973). Selection of a proper osmoticum is, therefore, a critical factor for the growth of isolated protoplasts. In some of the early experiments RNase was shown to cause lysis of protoplast membranes (Ruesink and Thimann, 1965), the lysis resulting not from a specific attack upon RNA but rather from the RNase behaving as an ionic detergent in destabilizing the membrane (Ruesink, 1971). Divalent cations inhibit the RNaseinduced lysis, indicating that such lysis involves the interaction of RNase with negatively charged sites on the plasma membrane surface. Important structural and biochemical changes take place in the protoplasts (Section III,D) during their isolation in solutions containing various cell walldigesting enzymes. Fortunately, most such changes are temporary, readily reversible phenomena as the protoplasts revert to a normal or near normal condition within a short time after incubation in appropriate nutrient media following the removal of the enzymes (Pilet etul., 1972; Gigot et ul., 1973, 1975; Pilet, 1973; Ruesink, 1973). Condeelis (1974) has used protoplasts isolated from the pollen and the pollen tubes of Amaryllis belladonna to study the physiological and mechanochemical basis of cytoplasmic streaming. Cytoplasmic fibrils of the pollen tube are composed of numerous 6 nm thin filaments which have been shown to be F actin, suggesting that they might be involved in the production as well as the transmission of the motive force of cytoplasmic streaming during pollen tube growth.

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Although there have been very few studies on the metabolic activity of isolated protoplasts, the information available strongly indicates that the protoplasts behave very much like normal cells once the enzymes have been removed and the protoplasts have stabilized in the environment of the nutrient medium. There is no loss in the rates of carbon dioxide fixation or light-dependent oxygen evolution in freshly isolated spinach protoplasts, which show photosynthetic activity comparable to intact leaf tissues (Nishimura and Akazawa, 1975). High photosynthetic activity in mesophyll protoplasts freshly isolated from several species of C3 as well as C4 plants has been demonstrated by Ku et ul. (1974) and Gutierrez et ul. (1974). Protoplasts are thus useful in studies comparing the photosynthetic processes of C3 and C4 plants, and are generally more stable than isolated chloroplasts. Normal turnover of protein and RNA takes place in nondividing pea mesophyll protoplasts (Watts and King, 1973b), and the transcription activity of nucleisynthesis of RNA-isolated from mesophyll protoplasts of Nicofiunu is 10- to 100-fold higher than that of nuclei isolated from intact cells and tissues by purely mechanical means (Blaschek et ul., 1974). RNA metabolism of protoplasts obtained from suspension cultures of Centuureu cyunus is comparable to whole cells (R. R. Kulikowski and J. P. Mascarenhas, personal communication). Protoplasts isolated from haploid and diploid tobacco plants a n be regenerated into whole plants after exposure to X-ray irradiation (Galun and Raveh, 1975). Ultraviolet irradiation of protoplasts isolated from suspension cultures of soybean causes them to lose their ability to regenerate a cell wall or form cell colonies, apart from markedly inhibiting DNA, RNA, and protein synthesis (Ohyama et ul., 1974). The freshly isolated protoplasts from suspension cultures of Duucus curotu synthesize both cytoplasmic and nuclear DNA (Howland and Yette, 1976) and have the capacity for the quick repair of DNA strand breaks caused by physical (irradiation) or chemical mutagens (Howland et ul., 1975). The high degree of efficiency and the readiness with which isolated protoplasts can repair DNA damage further emphasizes their suitability for recovering viable but genetically modified cells from mutagenic experiments. Leaf protoplasts isolated from susceptible and resistant strains of Zeu mays exhibit a differential response to the toxin produced by the fungus Helminthosporium muydis race T (Pelcher ef ul., 1975). Protoplasts from resistant corn are not affected by toxin concentrations 100-fold greater than those that cause extensive damage to protoplasts from susceptible corn. Helminfhosporium muydis causes southern corn leaf blight in plants containing the Texas T or related male-sterile cytoplasms and was responsible for devastating corn crops in the United States during recent years by producing a toxin that causes considerable plasma membrane damage in susceptible host cells. Strobe1 (1975), using sugarcane leaf protoplasts, found evidence for the localization of the toxin-binding protein on the surface of the cell membranes

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(plasmalemma). The toxin is also known to markedly affect mitochondria, particularly their membranes (H. C. Aldrich and V. E. Gracen, personal communication), and it is still not clear whether the primary damaging effect of the toxin is on the plasma membrane or the mitochondrial membranes. Use of protoplasts to study the effect of the fungal toxins provides a reliable and fast method for the screening and selection of toxin-resistant cells for use in breeding programs.

D. GROWTH in Vitro Protoplasts isolated with due care and washed free of cell wall-digesting enzyme solutions initiate growth rapidly when placed in appropriate nutrient solutions [this is so far possible only in a limited number of species (Section III,D,2)]. They show rapid cytoplasmic streaming, increasing rates of respiration, synthesis of RNA, protein, and polysaccharides, and a general increase in the number of most cell organelles, e.g., Golgi bodies, mitochondria, lipid bodies, plastids, ribosomes and polysomes, and endoplasmic reticulum, which seems to take place during the period of enzyme treatment. The increase in cell organelles indicates a general activation of the metabolic machinery of the protoplast for the regeneration of a new cell wall. The protoplasts increase in size, new cytoplasmic strands are formed, and most of the cell organelles, particularly the chloroplasts, aggregate conspicuously around the nucleus. In a study of the subcellular changes during isolation and culture of tobacco mesophyll protoplasts, Gigot et al. (1975) observed two distinct phases: an initial “shock phase” consequent upon isolation, and the following phase of rapid dedifferentiation to a meristematic state. The cytoplasm at first becomes vacuolated and poor in ribosomes, while the chloroplast and nuclei appear condensed. Later the cytoplasm becomes enriched in membranes, ribosomes, and polysomes with the onset of high metabolic activity, and the nuclei once more appear normal. The chloroplasts undergo the most striking changes, culminating in complete dedifferentiation. 1. Cell Wall Regeneration

One of the first visible signs of growth in protoplasts is the formation of a new cell wall,which results in a change of the characteristic spherical shape. Electron microscopic examination of freshly isolated protoplasts, after specific and sensitive staining and freeze etching procedures, shows that all traces of the original cell wall have been removed (Fowke et al., 1973; Nagata and Yamaki, 1973; Takebe et al., 1973). However, there has been some speculation that fragments of the original wall occasionally remaining attached to the plasmalemma serve as primers or “anchors” for the deposition of the new cell wall (Ruesink, 1973).

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Such fragments, when retained, are removed from the surface of the plasmalemma by the first layer of the regenerated wall and do not appear to be involved in the formation of the new wall (Burgess et d., 1973a; Willison, 1973; Burgess and Fleming, 1974a). Initial wall regeneration around protoplasts may be abnormal (Mishra and Colvin, 1969; Horine and Ruesink, 1972), but the fact that normal whole plants can be regenerated from protoplasts of at least some species shows that the initial abnormalities, which may in fact be caused by the complete removal of the original wall and the absence of a primer, are subsequently fully corrected. It is not surprising, therefore, that isolated protoplasts are being increasingly used to study cell wall regeneration and biosynthesis. In the early studies of cell wall regeneration in tomato fruit protoplasts, cell wall formation was shown to begin almost immediately after the removal of the enzyme solutions (Pojnar et ul., 1967; Mishra and Colvin, 1969). There is some doubt, however, whether the small and discontinuous amounts of material seen on the plasmalemma during the first few hours of culture represent a new cell wall or are actually the remaining fragments of the original wall due to incomplete digestion (Burgess and Fleming, 1974a). Also, some of the peculiarities observed, like the formation of a multilamellar system, during cell wall regeneration in the above system may be related to the type of cells used, rather than being representative of cell wall regeneration in general. It is only recently that protoplasts isolated from leaves or from cells in suspension culture have been used for a detailed examination of cell wall regeneration. In such protoplasts the earliest stages of wall regeneration can be recognized only after 24-48 hours of culture (Nagata and Yamaki, 1973; Burgess and Fleming, 1974a; Fowke et ul., 1974a; Willison and Cocking, 1975). Plant growth substances, particularly the synthetic auxins (not indole-3-acetic acid) and cytokinins stimulate wall synthesis. The first structures to appear on the surface of the plasmalemma are randomly oriented cellulosic microfibrils, which later become parallel to the plasmalemma. It is reasonable to assume, however, that the material deposited on the plasmalemma during the earliest stages of wall formation is lost during preparation of the material for electron microscopy, and what we see as a random orientation of fibrils is only a later stage when the newly formed wall has developed at least some cohesiveness. An examination of microfibril synthesis at the surfaces of isolated tobacco mesophyll protoplasts with the help of freeze-fracturing, freeze-etching, and deep-etching techniques shows that the first-formed microfibrils of the regenerating wall appear after 24 hours of culture, parallel to and in close association with the plasmalemma (Willison and Cocking, 1975). These results also suggest that microfibril assembly probably occurs within the outer half of the unit membrane, or within a thin coating on its outer surface, as the microfibrils appear to sink into or arise from the membrane. L.C. Fowke and F. A. Williamson (personal communication) have also studied very early stages of cell wall formation in Vicia protoplasts with the help of platinum-palladium replicas, and

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observed the deposition of microfibrils within the first hour of culture. After 20 hours of culture, the protoplast surface was covered with microfibrils. These protoplasts were derived from cell cultures, and showed no evidence of remaining cell wall fragments at the start of cultures. The only cellular structure clearly involved in new wall synthesis seems to be the endoplasmic reticulum, which becomes fairly distended and is associated with ribosome-like particles. It has not been confirmed that outgrowths of the plasmalemma, reverse pinocytosis, smooth and coated vesicles, or the Golgi bodies, which were initially thought to be involved in the deposition of a new cell wall in cultured protoplasts (Pojnar et al., 1967; Prat and Roland, 1971; Roland and Part, 1973), are in fact involved in synthesizing or transporting cell wall materials. The cell walls regenerated around protoplasts isolated from cells in suspension culture or from the leaves of tobacco plants are normal in structure and comparable to the cell walls of tissues in culture or in nature. Further work is needed to identify the specific site of synthesis of cellulose and the methods of deposition and the orientation of the initial cellulosic microfibrils on the plasmalemma. 2. Cell Division, Tissue Formation, and Regeneration of Plants from Isolated Protoplasts Only nucleated protoplasts regenerate cell walls, and cell wall formation generally precedes cell division (Kao et al., 1970, 1971; Nagata and Takebe, 1970), although the presence of a rigid cell wall may not always be necessary (Fowke et al., 1974b; Meyer, 1974; Meyer and Abel, 1975). However, nuclear divisions, without accompanying cytokinesis, have been reported to occur in cultured protoplasts and result in the formation of multinucleate structures (Eriksson and Jonasson, 1969; Motoyoshi, 1971; Kao et al., 1973; Reinert and Hellmann, 1973; Fowke et al., 1975a). Mitosis and cytokinesis in cultured protoplasts are normal and similar to events taking place in higher plant cells in nature (Fowke et al., 1974b). The first cell division after the formation of the new wall takes place between 2 and 7 days after culture, subsequent divisions following more rapidly. There does not appear to be any fixed pattern of divisions. Protoplasts isolated from differentiated cells, like the mesophyll cells of leaves which do not divide in nature, take longer to undergo the first division than those isolated from cells dividing rapidly in tissue cultures (Vasil and Vasil, 1974). Multicellular clumps are formed within 1-3 weeks after the initiation of sustained cell divisions. As stated earlier, the presence of auxins and cytokinins is critical for the continuation of cell division activity. Once cell masses have been formed, these can be transferred to appropriate nutrient media for further growth and multiplication of the callus and the regeneration of shoots and roots resulting in the formation of plantlets. Here again, proper auxin:cytokinin ratios play an important role and must be deter-

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mined for each species used. The first plants regenerated from isolated protoplasts in culture were those of Nicotiana tabacum (Takebe et a l , 1971; Nagata and Takebe, 1971). Plants have also been regenerated from protoplasts of carrot (Grambow et al., 1972), Asparagus officinalis (Bui-Dang-Ha and Mackenzie, 1973), Atropa belladonna (Gosch et al., 1975), Bromus inemis (Kao et al., 1973), Datura innoxia (Schieder, 1975b), Petunia hybrida (Durand et al., 1973; Frearson et al., 1973; Vasil and Vasil, 1974), P. parodii (Hayward and Power, 1975), Brassica napus (Kartha et al., 1974b), and Ranunculus sceleratus (Dorion et al., 1975). Formation of embryoids, but not plants, has been reported from protoplasts isolated from roots of carrot (Kameya and Uchimiya, 1972), leaves of Antirrhinum majus (Poirier-Hamon et al., 1974; recent ultrastructural evidence indicates that these embryoids are highly abnormal in having multinucleate cells or incomplete walls between daughter cells, Prat and PoirierHamon, 1975), and ovular callus of Citrus sinensis (Vardi er al., 1975). Cell clusters or calli have been regenerated from protoplasts of the following plants: soybean (Kao et al.. 1970), Haplopappus gracilis (Kao et al., 1971), Pisum sativum (Constabel et al., 1973), sugar cane (Maretzki and Nickell, 1973), Arabidopsis thaliana (Gamborg and Miller, 1973), Pharbitis nil (Messerschmidt, 1974), Phaseolus vulgaris (Pelcher et al., 1974), Ammi visnaga, Cicer arietinum, Linum usitatissimum. Medicago sativa, Melilotus alba, Vicia hajastana (Gamborg et al., 1974), Vigna sinensis (Davey et al., 1974; Gamborg et al.. 1974), Nicotiana acuminata, N alata, It glauca, N langsdorfii, N. longiflora, N noctiflora, N. paniculata, N. sylvesm’s (Chupeau et al., 1974), Cucumis sativus (Coutts and Wood, 1975), Catharanthus roseus (Koblitz, 1979, Hyoscyamus niger (Kohlenbach and Bohnke, 1975), Solanum tuberosum (Upadhya, 1975), etc. Plants have also been regenerated from protoplasts isolated from haploid plants of Nicotiana tabacum (Ohyama and Nitsch, 1972),N. alata (J. P. Bourgin and Y. Chupeau, personal communication), Oryza sativa (Anonymous, 1975), and Datura innoxia (Schieder, 1975b), and from haploid (Binding, 1975a) as well as cytoplasmic male sterile (Vasil and Vasil, 1974) plants of Petunia hybrida. Considering the fact that sustained cell divisions in cultured protoplasts were first reported in 1970, this is indeed encouraging and commendable progress. However, it is also clear that success has so far been limited to a narrow range of species. As cell regeneration and plant development from isolated protoplasts are essential prerequisites for the success of somatic hybridization or the genetic modification of plant cells, it is of utmost importance that protoplasts of a much wider variety of plants be cultured in vitro and regenerated to whole plants.

I V . Protodasts and the Genetic Modification of Plants

Since World War 11, increased industrialization, economic and social prosperity, and improved health care have helped to increase world population at an alarming

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rate. Impressive gains have also been made during the same period in food production, but these have generally fallen far short of providing enough food for the growing millions, with the result that we have lived from one crisis to another, witness the Indian subcontinent, the Sahel region in Africa, etc. Conventional methods of plant improvement, though highly successful, are necessarily slow and time consuming and depend on exploiting the natural genetic variability within a very narrow range of material. In the case of many important crop plants, such genetic variability has nearly been exhausted (Harlan, 1966,1979, particularly in the cereals and legumes which are of most vital importance to man. It is quite encouraging, therefore, to see that many new and innovative approaches are being tried to introduce greater genetic variability into important crop plants, so &at these can then be used as the starting material in hybridization and plant improvement programs. These include methods of overcoming natural barriers to sexual compatibility between taxonomically and genetically divergent species (Knox et al., 1972a,b; Bates et al., 1974; Vasil, 1973, 1974; Pandey, 1975), mutagenesis (Chaleff and Carlson, 1974), genetic transformation by incorporation of foreign genetic material in the form of DNA (Doy et al., 1973; Holl et al., 1974; Hess, 1975; Hess et al., 1976; bdoux, 1975), haploid cells and plants (Kasha, 1974; Vasil and Nitsch, 1975), and somatic hybridization by protoplast fusion (Gamborg et al., 1974). It would not be an exaggeration to say that much of the current widespread interest in plant protoplast research is based on the demonstration that higher plant protoplasts are totipotent, can be induced to fuse readily with each other, can take up macromolecules and whole cell organelles and, therefore, are potentially of great value in experiments on somatic cell genetics and the genetic improvement of plants which circumvent the normal sexual processes. The beginnings of such work can be traced to two memorable papers, one by Power et al. (1970) showing induced fusion of isolated protoplasts, and the other by Carlson et ul. (1972) reporting the first successful production of a parasexual hybrid by protoplast fusion. The work on the modification of the information content of plant cells using protoplasts has followed two major approaches: (i) fusion of genetically different protoplasts and (ii) the direct transfer and incorporation of foreign genetic material into the protoplasts. As expected in any new area of scientific endeavor, the progress has been slow and limited, but in this case steady and promising.

A. FUSION OF PROTOPLASTS

Plant protoplasts undergo two distinctly different types of fusion: spontaneous fusion and induced fusion (Power et al., 1970). Spontaneous fusion of two or more adjoining protoplasts takes place when their plasmodesmatal connections expand rather than break during cell wall degradation in enzyme

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solutions (Withers and Cocking, 1972) and is commonly seen in protoplasts prepared from tissue cultures. It is less common in leaf protoplasts. The coenocytic protoplasts formed by spontaneous fusion can regenerate a cell wall and their nuclei undergo mitoses and sometimes fuse to form polyploid nuclei (Fowke el al., 1975a). Spontaneous fusion bodies do not develop much further and are of no practical use in somatic hybridization. Formation of spontaneous fusion bodies may, however, prove useful in the study of the ultrastructure of the plasmodesmata, the physiology and control of synchronous mitoses, and nuclear fusion. Protoplasts isolated from meiocytes of Lilium longijlomm and Wllium h m t schaticum show high incidence (up to 30%) of spontaneous fusion, and continue their meiotic development (Ito, 1973b; Ito and Maeda, 1973). Another interesting characteristic of these protoplasts is their ability to fuse with each other simply on contact and without the help of any inducing agent. Thus, fusion frequencies of up to 90% have been observed in protoplasts isolated from meiocytes in prophase. Interspecific fusion of meiocyte protoplasts also takes place when these are brought in contact with each other. Apart from the possible usefulness of such fusion products in studies of meiosis, etc., they might also be of help in understanding the process of fusion itself. For example, the extremely high rates of fusion in meiocyte protoplasts are related to their rapid isolation-only 5 to 20 minutes in enzyme solutions-and their rapid physical contact following isolation. In contrast, protoplasts from most other tissues can be isolated only after prolonged-2-20 hours-enzyme treatment. It is quite possible that such prolonged exposure to the enzyme solutions, and the numerous impurities in them, affects the nature of the plasma membrane and thereby reduces the ability of the protoplasts to readily fuse, and increases the requirement for chemical-inducing agents to bring about agglutination and fusion. Development of techniques for the rapid isolation of protoplasts, and the availability of more efficient enzyme preparations may, therefore, not only be of help in protoplast fusion but also in their ability for subsequent growth and development. Fusion of mechanically isolated protoplasts was reported as early as 1909 (Kiister, 1909, 1910), but such fusions were rare, and often nonreproducible (Michel, 1937; Hofmeister, 1954). Reproducible and controlled fusion of enzymatically isolated protoplasts was first induced by sodium nitrate treatment by Power et al. (1970). Although sodium nitrate-induced fusion has produced some highly successful results (Carlson et al., 1972), it is generally limited to protoplasts with near identical osmotic characteristics, has a poor effect on protoplast viability, and at best produces a very low incidence of fusion (Potrykus, 1973b; Burgess and Fleming, 1974b; Melchers and Labib, 1974). Several other techniques have, therefore, been tried to obtain high fusion frequencies. Some of these effectively agglutinate protoplasts but do not cause fusion (Hartmann et al., 1973; Withers, 1973; Burgess and Fleming, 1974b;

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Glimelius et al., 1974), while others produce only low fusion frequencies and are not always conducive to the maintenance of protoplast viability (Eriksson, 1971; Schenk and Hildebrandt, 1971; Kameya and Takahashi, 1972; Keller et al., 1973; Potrykus, 1973b). Keller and Melchers (1973) obtained much improved (more than 25%) fusion frequencies by incubating protoplasts in media containing high Ca2+ at high temperature (37°C) and at the highly alkaline pH of 10.5 (the negative charge present on the protoplast plasma membrane is lost under these conditions, resulting in agglutination followed by fusion; G. Melchers and T. Nagata, personal communication). Another very successful and popular method for the fusion of protoplasts was developed by Kao and associates (Kao and Michayluk, 1974; Constabel and Kao, 1974), which involved agglutination with the aid of high molecular weight polyethylene glycol (PEG) and fusion following the elution and/or dilution of PEG from the incubation medium. PEG-induced fusion is nonspecific and thus useful for both inter- and intraspecific fusion, and fusion frequencies of up to 100% have been demonstrated (Kao et aZ., 1974; Vasil et al., 1975). Further improvement in PEG-induced fusion and the survival of fused protoplasts is attained by treating protoplasts with PEG in the presence of, or by eluting with solutions containing, high Ca2+ at high pH and high temperature (Burgess and Fleming, 1974b; Kao et aZ., 1974; Wallin et al., 1974). One frequent problem in fusion experiments is the formation of large clumps by the fusion of several protoplasts. Such clumps are of no practical use. However, by careful control of the molecular weight of PEG used, its concentration, the pH of the fusion mixture, and the duration and temperature of PEG treatment, it is possible to obtain more fusions between 2 or 3 protoplasts and nearly eliminate the formation of large coenocytic clumps. PEG causes rapid desiccation of the protoplasts resulting in their visible shrinkage, apart from inducing rapid and tight agglutination, characterized by a close association of adjacent membranes, often with no intervening spaces or structures over long distances (Burgess and Fleming, 1974b; Fowke et al., 1975b; Vasil et al., 1975). Actual fusion of the membranes occurs during dilution of the PEG by washing. The protoplasts then revert to their normal spherical shape. According to Wallin et aL (1974), induction of fusion is a very early event in the aggregation sequence during PEG treatment, while cytoplasmic mixing takes place only after the removal/dilution of PEG. The actual mechanism of fusion mediated by PEG is not clearly understood, although some theories have been proposed (Constabel and Kao, 1974; Grout and Coutts, 1974; Kao and Michayluk, 1974; Wallin et al., 1974). When protoplasts of two genetically different plants are induced to fuse in vifro, a majority of the fusions generally take place between identical protoplasts, resulting in the formation of homokaryons, which again are of no use in somatic hybridization. Fusion of genetically diverse protoplasts, and the forma-

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tion of heterokaryons, is much less common (Carlson et d., 1972). However, much higher frequencies (3530%) of heteroplasmic fusion are obtained with PEG (Kao et al., 1974; Vasil et d., 1975). PEG causes no apparent damage to the protoplasts, which continue to grow after fusion to form small cell clusters, (Kao et al., 1974; Kartha et al., 1974b; Constabel et al., 1975). Fusion of protoplasts does not necessarily result in the fusion of their nuclei. Nuclear fusions, if they take place at all, are extremely rare, and there are no known techniques that will induce fusion of nuclei in the heterokaryons. There are only three cases where formation of true hybrid cells after induced protoplast fusion has been effectively demonstrated (Carlson et d., 1972; Melchers and Labib, 1974; Gleba et al., 1975b), all involving fusion between closely related species or varieties of Nicotiana. Nuclear fusion and true hybrid cell formation following intergeneric fusions between protoplasts of taxonomically unrelated species have been reported (Kao et al., 1974; Constabeletal., 1975). Fusion between protoplasts of Saccharum offcinarum var. Badila and several clones, including S.spontaneum vars. Mandaley, Tobago, and Tobago hybrids, has been obtained with the use of PEG by Krishnamurthi, who has observed multiple divisions in the fusion products (personal communications from A. Maretzki and 0. L. Gamborg). The heterokaryocytes formed after fusion of protoplasts often undergo synchronous mitotic divisions resulting in the formation of a chimeral callus mass, but a critical demonstration of the formation of true hybrid nuclei and cells following most such fusion experiments is presently lacking. Nevertheless, the results obtained so far in interspecific or intergeneric fusion and the survival of the fusion products are most encouraging, and highlight the potential of protoplast fusions in obtaining somatic hybrids. Fusion of protoplasts resulting in the formation of true hybrid cells is at best an infrequent event and only the first step toward somatic hybridization, for it is generally the unfused parental protoplasts which grow vigorously to form cell colonies. The few hybrid cells that may be formed and may also divide a few times are either lost among the massive growth of unfused protoplasts or can not otherwise compete with the parental protoplasts; these may also be “lost” due to various incompatibility reactions between the parental cells, or due to the gradual elimination of chromosomes of one of the parents. Recovery of hybrid cells under such conditions is unlikely, if not totally impossible. The lack of effective selective methods which would support the growth of only the hybrid plant cells-so elegantly developed and employed for the isolation and growth of animal somatic cell hybrids (Harris, 1970; Ephrussi, 1972; Davidson, 1974)further accentuates the problem and is at present a major impediment in the progress of research on somatic hybridization in plants. The rare instances where such selective screening methods for the growth of hybrid cells are available, have indeed been used successfully to produce somatic hybrids in plants. Thus, Carlson et al. (1972) used the differential growth characteristics and nutritional requirements-and a bit of “good fortune” (Carl-

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son, 1973b; Melchers and Labib, 1974)-of unfused as well as hybrid protoplasts and cells of Nicotiunu gluucu and N. langsdorfii to produce the first somatic or parasexual hybrids by protoplast fusion. Protoplasts of the two parental species do not regenerate into a callus in the medium used, while about 0.01% of the protoplasts of the amphidiploid hybrid give rise to a callus mass. These different growth characteristics of the protoplasts were used to recover growing hybrid cells from a mixed population of the plated protoplasts. It has been reported that sodium nitrate does not induce the high degree of fusion (25%) in tobacco mesophyll protoplasts (Melchers and Labib, 1974) as claimed by Carlson et al. (1972). It is also noteworthy that an analysis of the composition of Fraction I protein isolated from the leaves of the parasexual hybrid plants (all derived from a single protoplast fusion product) showed that the small subunit polypeptides of both the parent species and the large subunit polypeptides of only N. glauca were present (Kung et ul., 1975). This indicates that in the plant being analyzed nuclear genes coding for the small subunit of Fraction I protein of both the parents were expressed, but chloroplast DNA coding for the large subunit of only N. glmtcu-but not N. lungsdorfii-is expressed. One would normally expect such a situation in a N. gZauca (female parent) X N. langsdorfii (male parent) sexual hybrid, where nuclear genes of both the parents will be present along with chloroplast genes from the female parent (N. glauca) only, since there is no transfer of plastids from the male parent (N. lungsdorfii). Kung et al. (1975) speculate “whether the expression of only one of the parental chloroplast genomes is a general phenomenon, and, if so, whether there is an equal chance that the chloroplasts will be of N. glmtca or the N . lungsdorfii type.” It is also conceivable that only one chloroplast genome can express itself in a hybrid cytoplasm derived from the fusion of two protoplasts, but that both chloroplast genomes function in the cytoplasm of an unfused protoplast, as indicated by the activity of transplanted chloroplasts of N. sauveolens into the protoplasts of N. tabucum (Kung et ul., 1975). Similarly, Melchers and Labib (1974) took advantage of genetic complementation in the fused protoplasts from two haploid, chlorophyll-deficient, lightsensitive varieties of N. tubacum to selectively isolate somatic hybrids which are resistant to high light intensities and have normal green leaves; Gleba et al. (1975b) also have reported similar results. Recently, Schieder (1975a) obtained a complemented fusion hybrid of the liverwort Sphaerocurpos donnellii by fusing protoplasts from a normal green, nicotinic acid-deficient female plant and a pale green, glucose-deficient male plant. Genetic complementation has also been demonstrated in fused protoplasts obtained from chloroplast mutants of Zea mays (Ciles, 1973, 1974), but sustained cell divisions in root or mesophyll protoplasts of Z. mays have not been obtained so far (Vasil and Vasil, 1974). In the absence of suitable nutritional and biochemical mutants, such *complementation/selection procedures hold much promise for the future, particularly in those plants where light-sensitive chlorophyll mutants have already been

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described and where plant regeneration from protoplasts is feasible. The recent success in producing whole plants from the mesophyll protoplasts of Pehlnia parodii (Hayward and Power, 1975) is noteworthy, owing to the fact that this species is known to cross sexually-though rarely-with Nicotiana tabacum (Pogliaga, 1953), and because the protoplasts of both species can be regenerated under identical conditions of culture. However, it must be pointed out that the production of somatic hybrids between species which can be hybridized sexually will, at best, be of limited value. It is quite obvious from the foregoing that the availability of sensitive and powerful selection techniques, which will allow the growth of hybrid cells only, can greatly aid future research on somatic hybridization. No suitable biochemical mutants are known in higher plants. Many efforts are, therefore, being made to produce and isolate mutants which can be used for the development of selection procedures (Carlson, 1970, 1973c; Binding et al., 1970; Binding, 1972; Dulieu, 1972, 1974, 1975; Widholm, 1972, 1974a,b; Lescure, 1973; Maliga et al., 1973a,b, 1975; Bright and Northcote, 1974, 1975; Chaleff and Carlson, 1974; Cocking etal., 1974; Ohyama, 1974; Marton and Maliga, 1975; Power and Cocking, 1976). Nutritional or auxotrophic mutants, temperature- and light-sensitive mutants, drug-resistant mutants, etc., can all be helpful. However, it must be recognized that the natural polyploid nature of most higher plant genomes may cause such mutants to be leaky, rendering them less useful in selection systems. It is unlikely, therefore, that suitable auxotrophs can be obtained from diploid or polyploid cells. Haploid cells would be more suitable for such experiments, and there is thus an urgent need for intensive efforts not only to use haploids to isolate mutants of various types, but also to produce haploid cells and plants from a wider variety of species than has hitherto been possible (Vasil and Nitsch, 1975). In the absence of any sure and “easy” means of selecting hybrid cells in mixed populations, other more elaborate and painstaking methods are being used to identify the hybrid cells in mixed cultures. The high incidence of heteroplasmic fusions obtained by PEG treatment is of advantage in the visual identification and mechanical isolation of the fusion products. Visual markers such as the presence or absence of chloroplasts and other plastids or pigments, and cytological markers based on differential staining characteristics or the morphology of the chromosomes, are the most obvious and useful (Potrykus, 1971;Keller et al., 1973; Kao and Michayluk, 1974). Protoplasts obtained from leaf epidermis peels, which can be easily differentiated from the green mesophyll protoplasts, should prove suitable for fusion with a variety of protoplasts. Regeneration of whole plants or organs from epidermal peels of several species has been achieved (Tran Thanh Van et al., 1974). Kao et al. (1974) have fused chloroplastcontaining mesophyll protoplasts with nonpigmented protoplasts derived from suspension cultures and were able to follow fusions and cell divisions in the

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resulting heterokaryons. Similarly, fusion products of the mesophyll protoplasts of tobacco and the bacteroid-containing protoplasts from the root nodules of lupin can be easily identified due to the characteristic shape and structure of the nodule protoplasts (Vasil et al., 1975). Hybrid cells resulting from such fusions could be mechanically isolated when cell wall regeneration and a few cell divisions have taken place. Protoplasts cultured in microculture chambers at very low densities can be monitored and identified with ease during growth (Vasil and Vasil, 1973) or fusion, and hopefully grown to whole plants (vasil and Hildebrandt, 1965). Raveh and Galun (1975) have used a feeder layer of protoplasts inactivated by irradiation to stimulate division in an overlaid layer of normal protoplasts at low densities, and subsequent regeneration of plants. Similarly, the newly developed medium by Kao and Michayluk (1975), which is capable of supporting the growth of a single protoplast in a relatively large volume (4 ml), might be helpful in the culture of mechanically isolated fusion products. Protoplasts can also be labeled with fluorescein-isothiocyanate (FITC), which does not affect their ability to regenerate a cell wall or undergo cell divisions (Hess, 1973). The fluorescence of such marked protoplasts can be used as a marker to identify hsion products. Characterization of the hybrid tissues, in the absence of regenerated hybrid plants, can be done with serological techniques, or through the study of isoenzyme patterns and karyotype analysis. The progress made toward somatic hybridization should not be taken to mean that we are at the threshold of doing away with normal sexual processes which developed and evolved in nature over hundreds of millions of years as the major means of hybridization in higher plants, and that protoplast fusions will provide hybrids between any two desirable species. We face many major, technical as well as biological, hurdles in obtaining intergeneric somatic hybrids of higher plants. Recalling the experience with animal somatic cell hybrids (Harris, 1970; Ephrussi, 1972), one would anticipate serious difficulties in the chromosomal stability of somatic hybrid cells produced by fusion of protoplasts from widely different species and expect some eventual limits to the range of species that can be combined parasexually, just as there are limits to sexual hybridization in nature. Somatic hybridization will surely be of use in the future, though its actual utilization for plant improvement has yet to be demonstrated. It is a little premature to describe somatic hybridization as a cure-all or “magic wand” for creating new varieties and species from any two desirable parents to solve the food problem and eliminate the need for nitrogen fertilizers, or for proper irrigation and disease control by producing cereal plants that will fix their own nitrogen and drought- and disease-resistant varieties. Great advances have been made in animal genetics with the help of somatic cell hybridization (Harris, 1970; Ephntssi, 1972; Davidson, 1974; Davidson and de la Cruz, 1974; Pontecorvo, 1975). Fortunately, in the case of animals somatic cell

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fusion is only an analytical tool, but in the case of plants, with the demonstrated totipotency of their somatic cells (Vasil and Vasil, 1972), it can be an analytical as well as a powerful synthetic tool with important and far-reaching possibilities. Nevertheless, it is regrettable that plant scientists have in general failed to learn from the wider and longer experience of animal somatic cell geneticists and their elegant techniques.

B. UPTAKE OF DNA Attempts to transform higher plant cells by the introduction of foreign DNA are aimed at expanding the genetic base of important crop plants. In order for transformation to take place, it is not only necessary that the foreign DNA be taken up and survive in the host cells, but also that it be expressed through transcription and translation in its new environment, be integrated into the host genome and finally, be replicated in the transformed host cells. It has been suggested that the use of haploid plant cells, with specific biological markers, may be helpful in the identification and selective recovery of the transformed cells (Holl et ul., 1974; Vasil and Nitsch, 1975). Transformation in higher plants has been explored by using intact cells, seeds, seedlings, or whole plants (Ledoux, 1971, 1975; Hess, 1972; Hess et ul., 1976; Doy et ul., 1973; Holl et ul., 1974; Markham et ul., 1975). Much of this work is inconclusive (Kleinhofs et ul.. 1975; Lurquin and Behki, 1975; Lurquin and Hotta, 1975), and there is considerable disagreement about the suitability and reliability of the techniques employed, the results obtained and their interpretations. The use of protoplasts for DNA uptake studies should be particularly advantageous in view of the excessive enzymatic degradation of DNA in the cellular environment (Holl, 1973; Cocking, 1973). Uptake and survival of bacterial and higher plant DNA has been reported in protoplasts (Ohyama et ul., 1972, 1973; Hoffmann, 1973; Hoffmann and Hess, 1973; Holl et ul., 1974; Gleba et ul., 1975a). This is neither surprising nor unexpected, as protoplasts are known to readily take up a variety of materials, including virus particles and RNA (see Section IV,E), proteins (Hess, 1973), and latex particles (see Section 111,C). The fate of the DNA taken up by the protoplasts has not been followed critically, although there are reports that at least some of it is located in the nuclear region (Hoffmann, 1973; Hoffmann and Hess, 1973). D. Hess (personal communication) has recently shown that nuclei isolated from Petunia protoplasts and incubated with Escherichiu coli DNA, transcribe both petunia and the bacterial DNA. However, no transcription of the bacterial DNA takes place if the nuclei are washed after treatment with E. coli DNA, indicating that the transcription activity is localized either on the nuclear surface

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or in the surrounding medium but not within the nuclei. These experiments indicate that the petunia polymerases can transcribe bacterial DNA, an important prerequisite if the foreign DNA is to be of any lasting use in the protoplasts. To .summarize, we can be reasonably certain of only the first step toward transformation through protoplasts, namely, the uptake of foreign DNA. Whether this DNA is largely degraded upon uptake, and whether it is located in the cytoplasm or the nucleus, is not known. The expression, integration, and replication of the foreign DNA within the protoplasts has not been achieved. Transfer of whole foreign DNA into protoplasts necessarily involves many genes, if not the whole genome, and is quite comparable to fusion of different protoplasts. Use of defined DNA fractions, with known genetic characteristics, or phages, plasmids, and plant DNA viruses, might be more useful. However, the techniques for such experiments are still in early stages of development and until these become more refined and are better understood, the transfer of DNA into protoplasts will be of little, if any, practical significance.

C. UPTAKE OF CELL ORGANELLES

Successful transfer and “c~lture’~ of cell organelles into foreign cytoplasm may provide a new method for studying the development, behavior, and activity of cell organelles, and for understanding nucleo-cytoplasmic interactions. Plant protoplasts, lacking a cell wall, would appear to be ideal for such experiments. Intraspecific chloroplast transfer has been reported by Potrykus (1973a,b) in Petunia hybrida, and by Carlson (1973a,b) in Nicotiana tabacum. Bonnett and Eriksson (1974) recently reported on the high frequency of algal chloroplast (Vatcheria dichotoma) uptake by carrot protoplasts. Considering the methods employed for the isolation of chloroplasts in the above experiments, it is quite doubtful that photosynthetically or otherwise viable chloroplasts were used. The chloroplast preparations were more likely suspensions of fine, inert “particles.” However, Carlson (1973a,b) reported regenerating whole plants with green functional chloroplasts from protoplasts (lacking any green, functional chloroplasts) of a maternally inherited, variegating, albino mutant, which had been placed in a medium containing wild-type tobacco chloroplasts. Unfortunately, both reports by Carlson are sketchy and provide no technical details of his experiments, and it is not surprising, therefore, that his observations and interpretations have been severely criticized (Poyrykus, 1973a,b, 1975; Bonnett and Eriksson, 1974; Giles, 1976). The earlier experiments of Carlson (1973a,b) have been recently extended by Kung et al. (1973, using isolated chloroplasts of Nicotiana suaveolens for transfer into the protoplasts of N. tabacum. A single so-called “hybrid” plant was isolated in these experiments and the analysis of the Fraction I protein obtained from the leaves of this plant shows that

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chloroplast as well as nuclear DNA of N. suaveolens are present along with those ofN. tabacum. In none of the above reports is there any evidence of the photosynthetic integrity of the chloroplasts before or after uptake, the number of chloroplasts transferred as well as the proportion of protoplasts taking up chloroplasts (maximum of 16% reported by Bonnett and Eriksson, 1974) are rather low, and finally there is no definitive ultrastructural evidence of chloroplast uptake. Vasil and Giles (1975), using protoplasts of Neurospora cram and chloroplasts of spinach, demonstrated that almost 50% of the protoplasts take up one or more chloroplasts. In many cases the number of chloroplasts transferred into the protoplasts was well over 40, and the latter looked more like mesophyll protoplasts of angiosperms rather than fungal protoplasts. The increased frequency and rapidity of chloroplast uptake, and the large number of chloroplasts transferred, could very well be related to the fact that the Neurospora protoplasts were not exposed to any cell wall-degrading enzymes known to affect the nature of the plasmalemma. In addition, they demonstrated the photosynthetic ability of the chloroplasts at least until the time of uptake, clearly showed the chloroplasts within the fungal cytoplasm with the help of electron micrographs, and observed cytoplasmic streaming in the protoplasts for several hours after the uptake of chloroplasts. Similar experiments with higher plant protoplasts may provide a possible direct approach to modify the photosynthetic ability of crop plants by transferring into their cells chloroplasts isolated from species known for their highly efficient photosynthetic systems, such as corn and sugar cane. One must, however, remember that these plants have complex morphological and physiological compartmentalization in their leaves. Considering the fact that fully differentiated and mature chloroplasts seldom divide, attempts should also be made to isolate and introduce proplastids or newly differentiated chloroplasts. PEG, which is highly effective in bringing about agglutination and fusion of protoplasts, is also suitable for inducing uptake of chloroplasts (Bonnett and Eriksson, 1974; Vasil and Giles, 1975). The high percentage of protoplasts taking up chloroplasts (Vasil and Giles, 1975) should be of advantage in the recovery of protoplasts with transplanted chloroplasts from mixed populations. It must be realized, however, that such experiments will be of use only if the transplanted organelles continue their normal activities in their new environment, the nuclear genes of the host cell are compatible with those of the organelles, and the transplanted organelles can multiply in number. It is encouraging to note that chloroplasts can survive, and possibly also multiply, in foreign cytoplasm (Taylor, 1968; Trench, 1969; Trench et al., 1969; Giles and Sarafis, 1972; Giles, 1976), but serious doubts still remain about the extent of the genetic autonomy of higher plant chloroplasts and mitochondria (Givan and Leech, 1971; Tewari, 1971; Giles, 1976).

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Cell organelles are normally isolated from plant cells by mechanical grinding, etc. Since protoplasts lyse easily and rapidly in hypotonic solutions, they can be a valuable new source of viable cell organelles. Potrykus (1975) reported isolating chloroplasts, nuclei, and tonoplasts from the protoplasts of various species by lysing, but in the absence of any information about the activity of the isolated organelles it is not possible to judge whether the preparations were biologically active and viable. Also, it has been reported that chloroplasts obtained by lysing of protoplasts tend to be held together in groups, often with mitochondria, and are surrounded by membranes which may fuse with the surface membranes of the protoplasts and transfer the cell organelles en masse (Giles, 1976). (Edwards (1975) and Rathnam and Edwards (1976) isolated chloroplasts from several plant species by forcing the protoplasts through a 20 gm nylon sieve. Such chloroplasts have higher photosynthetic activity as compared to mechanically isolated chloroplasts, and should be valuable in those species where mechanical isolation of viable and photosynthetically active chloroplast preparations has proved elusive. Blaschek et al. (1974) isolated nuclei from mesophyll protoplasts of Nicotiana glauca, A! langsdorjli, and Petunia hybrida, and showed that the transcription activity of tobacco nuclei so isolated was 10- to 100-fold higher than of nuclei isolated by conventional mechanical procedures. Transfer of nuclei of Petunia hybrida into the protoplasts of P. hybrida, Nicotiana glauca, and Zea mays has also been claimed (Potrykus and Hoffmann, 1973). Here again, the evidence for nuclear transfer is inconclusive, and there is no data to show that the nuclei were functional units rather than dead and inert particles. It has generally been assumed that nuclei and chloroplasts are taken up by protoplasts by the process of pinocytosis, much like the polystyrene latex, virus, and other particles described in Sections III,C and IV,E. However, Burgess et al. (1973b) have suggested that pinocytosis is not involved in the uptake which appears to be nonphysiological. Vasil and Giles (1975) also did not see any extra membranes surrounding spinach chloroplasts introduced into protoplasts of Neurospora c r a w It is possible that the chloroplasts are initially enclosed in a pinocytotic vesicle formed by the plasmalemma of the host protoplast, and that this is later “digested” within the host cytoplasm as observed in transplanted yeast cells in the protoplasts of Parthenocissus trimspidata (Davey and Power, 1975). D. CYTOPLASMIC MALE STERILITY An understanding of the mechanism of cytoplasmic male sterility is important in view of the fact that a large number of plant breeding programs are dependent on this phenomenon. It is not known where the genes causing cytoplasmic male

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sterility are located in the cytoplasm. However, it has been shown that mutations or alterations in the mitochondrial or chloroplast DNA produce cytoplasmically inherited phenotypic alterations (Sager, 1972; Flavell, 1974). It is possible, therefore, that the genes determining cytoplasmic male sterility are located in the DNA of mitochondria and/or chloroplasts (Duvick, 1965; Flavell, 1974). Plant protoplasts have been suggested as a model system to test this hypothesis (Vasil and Vasil, 1974). For example, it should be possible to introduce chloroplasts or mitochondria from cytoplasmic male sterile plants into the protoplasts of normal male fertile plants. Cells and tissues regenerated from such ‘altered’ protoplasts could then be examined for structural or biochemical changes, and plants produced from these tissues could provide definitive information about the role of mitochondrial or chloroplast DNA in cytoplasmic male sterility and be used in studying other nucleo-cytoplasmic interactions involved in this phenomenon. Fusion of whole protoplasts from normal and cytoplasmic male sterile plants, or of protoplasts from different cytoplasmic male sterile strains, could also be useful for such an understanding. As a first step in this direction, Vasil and Vasil (1974) have regenerated whole plants from protoplasts isolated from normal as well as cytoplasmic male sterile Petunia hybrida, with pollen abortion in plants produced from the latter.

E. UPTAKE OF VIRUSES

Plant viruses are incapable of penetrating intact plant cell walls. Consequently, their infection depends on the presence of wounded cells. The study of virus infection in higher plants has further been made difficult because even under the most ideal conditions the number of cells infected is rather small, and infection is random and asynchronous. The recent use of plant protoplasts in studies of virus infection makes it possible not only to infect a large population of cells simultaneously but also to eliminate the possibility of secondary infection. Successful inoculation of protoplasts with tobacco mosaic virus (TMV) was first demonstrated in 1969 by Aoki and Takebe, Cocking and Pojnar, and Takebe and Otsuki. It is largely through the elegant studies of Takebe and his associates in Japan that protoplasts have become important and standard experimental materials in plant virus research. In contrast to the discouraging and inconclusive results from studies of DNA uptake by protoplasts (Section IV,B), work on viral infection of protoplasts has provided critical and valuable information about the process of virus infection and multiplication in plant cells (Cocking, 1970; Zaitlin and Beachy, 1974; Takebe, 1975). The success with plant viruses that contain RNA would suggest similar attempts with plant viruses that contain DNA, for example cauliflower mosaic virus, for transfer of foreign DNA into higher plant cells.

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In addition to TMV (Otsuki and Takebe, 1969b) and its infectious RNA (Aoki and Takebe, 1969) mesophyll protoplasts of tobacco have been successfully inoculated with cucumber mosaic virus (Otsuki and Takebe, 1973), potato virus X (Otsuki et ul., 1974), brome grass mosaic virus (Burgess et ul., 1974a), pea enation mosaic virus (Burgess et ul., 1974b), and several other viruses (Zaitlin and Beachy, 1974; Takebe, 1975). Protoplasts isolated from suspension cultures of Emu and mesophyll tissue of barley, cowpea, petunia, and tomato leaves have also proved useful for such infection studies (Takebe, 1975). Carlson (1973a) reported the infection of Hordeurn vulgure protoplasts with bacteriophage T3 and the appearance of two phage-specific enzymes, T3 RNA polymerase and S-adenosylmethionine-cleavingenzyme, in the protoplasts. Unfortunately, detailed experimental procedures have not been provided in the publication but, if confirmed, the results would provide strong evidence that bacteriophage genes can be transcribed and translated in higher plant cells. Addition of a high molecular weight polycation, poly-L-ornithine, to the inoculum virus is essential for obtaining a high frequency of infection (70+0%) in isolated protoplasts (Takebe and Otsuki, 1969). This is particularly true of viruses which are negatively charged under the experimental conditions; poly-Lomithine is not essential for viruses carrying a positive charge (Motoyoshi and Hull, 1974; Motoyoshi et ul., 1974). The percentage of protoplasts infected can be readily determined by the use of a virus antibody labeled with a fluorescent dye (Otsuki and Takebe, 1969b). However, it has been suggested by Burgess et ul. (1973b) that the function of poly-L-ornithine and other treatments used to obtain virus infection of protoplasts is to stress the cell membrane to allow a nonphysiological entry of high molecular weight materials. Poly-L-ornithine is apparently involved in achieving the adsorption of the virus on the protoplast plasmalemma which is preceded by the formation of a virus:poly-L-ornithine complex. The early studies of Cocking (1966) suggested that TMV was taken up by the isolated tomato fruit protoplasts by pinocytosis. Later studies indicated this to be the general rule, even when other viruses were used for infection (Cocking, 1970; Hibi and Yora, 1972; Otsuki et ul., 1972; Honda et ul., 1974; Takebe, 1975). On the other hand, according to Burgess et ul. (1973b,c), the virus particles attach themselves preferentially to localized sites on the plasmalemma which have been damaged by poly-L-ornithine, the virus later entering the protoplast as the damaged plasmalemma is repaired, and that pinocytosis is not involved in such uptake. The efficiency of inoculation by viral RNA is lower (less than 10% of the protoplasts are infected) due to the inactivation of the inoculum RNA by cellular enzymes (Aoki and Takebe, 1969). Recently, Sarkar et al. (1974) obtained nearly 100% infection of tobacco mesophyll protoplasts with only microgram quantities of TMV-RNA by suspending the protoplasts in an alkaline

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buffer (pH 9.0) having a relatively high salt concentration; no poly-L-ornithine was required for such infection. They suggested that the low amount of TMVRNA “needed for an efficient infection opens up the possibility of using the present experimental conditions to achieve the introduction of foreign nucleic acids, other than TW-RNA, where the quantity of nucleic acids available might be limiting.” Protoplasts might also prove useful in studying the host specificity of viruses, in developing more sensitive and precise bioassays for virus infection, in the screening for potential viral chemotherapeutic agents, and in the introduction of foreign material into plant cells (Zaitlin and Beachy, 1974).

F. NITROGEN FIXATION Symbiotic furation of nitrogen, which is mediated by bacteria of the genus Rhizobium, is limited to leguminous plants, with the exception of Dema canabina (Trinick, 1973). This economically important association accounts for a major proportion of the nitrogen incorporated into the biosphere and for maintaining nitrogen fertility in agriculture (Hardy and Havelka, 1975). The benefits of Rhizobium-legume symbiosis have been used by man from ancient times by rotation of leguminous and nonleguminous crops, although the actual basis for this was not understood until about 1830 (Burris, 1974). Owing to the obvious importance of nitrogen in plant growth and development, and many ecological and economic limitations to the heavy use of chemical fertilizers, and the steadily increasing cost of synthetic fertilizers derived from petroleum, the search for methods to extend the range of symbiosis between Rhizobium and nonleguminous plants has acquired a new sense of urgency. Many different experimental approaches are being followed to achieve an increase in the quantum of biological nitrogen futation and to understand the biology of nitrogen futation by Rhizobium. One is the establishment of symbiotic association between Rhizobium and tissue cultures derived from legumes as well as nonlegumes (Holsten er al., 1971; Child and La Rue, 1974; Phillips, 1974; Child, 1975; Scowcroft and Gibson, 1975; Werner and Oberlies, 1975; Werner e l al., 1975). In some of these the bacteria are reported to enter cells in culture and establish themselves much in the same way as within the nodule cells in nature (Holsten er aZ., 1971). In others, the bacteria remain outside the cells and the expression of the nitrogenase gene of the bacterium is elicited by a diffusible factor secreted by the plant cells in culture. The fact that a diffusible factor, common to legumes as well as nonlegumes, will initiate nitrogenase activity in free-living Rhizobium (Child, 1975; Scowcroft and Gibson, 1975; Werner and Oberlies, 1975; Werner et al., 1975), indicates that it may be possible to extend rhrzobial symbiosis to nonleguminous crop plants. A similar “extra-cellular

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symbiotic system” has been described by Carlson and Chaleff (1974), involving Azotobucter and carrot tissue cultures. It is encouraging to note that nitrogenase activity has recently been obtained in pure cultures of Rhizobium in the absence of a plant host or its products (Pagan et ul.. 1975; Kurz and LaRue, 1975; McComb et ul., 1975). The genetic transfer of nitrogen furation genes (nif) to bacteria that do not naturally fix nitrogen, as from Klebsiellu pneumoniue to Eschen‘chiu coli (Dixon and Postgate, 1972) or Azotobucter vinelandii (Dixon et al., 1976; Cannon and Postgate, 1976), is another approach being used, as is the transfer of the nif operon to cereals and other important food and fiber plants for increasing the availability of biologically fured nitrogen to cultivated plants. Plasmids containing the nif operon might be introduced into protoplasts of selected crop plants and the protoplasts then grown to mature plants carrying the introduced genetic information in their cells as well as seeds (Hardy and Havelka, 1975; Shanmugam and Valentine, 1975). This is not a purely speculative approach, as may appear initially, because phage-mediated transfer of lactose and galactose operons from E. coli to tomato and Arabidopsis tissue cultures has previously been reported (Doy et al., 1973). Three other techniques to increase nitrogen furation are (i) fusion of legume and nonlegume protoplasts in the hope of regenerating hybrid plants which will have the capacity to fix nitrogen in symbiosis with Rhizobium (Kao and Michayluk, 1974; Kao et ul., 1974; Kartha et ul., 1974a); (ii) fusion of bacteroidcontaining protoplasts from root nodules of legumes with protoplasts from legumes and nonlegumes (Vasil et ul., 1975); and (iii) transfer of nitrogen-fEing strains of Rhizobium or Azotobucter to protoplasts and regeneration of plants. Some of these are discussed below in more detail. Vasil et ul. (1975) used PEG solutions to induce a very high incidence of fusion between bacteroid-containing protoplasts [Further electron microscopic examination of the nodule protoplasts suggests that a fragment of the original nodule cell wall may sometimes still be present after enzyme treatment. If this is true and common, the nodule protoplasts isolated by Davey et al. (1973) and Vasil et al. (1975), will actually be sphaeroplasts rather than true protoplasts.] from the nitrogen-fixing root nodules of Lupinus ungustifolius with mesophyll protoplasts isolated from the leaves of lupin and Nicotiunu tubacum. They observed acetylene reduction activity in root nodule slices during the period of incubation in cell wall degrading enzyme solutions but were unable to detect any such activity in the isolated nodule protoplasts. The structural organization of the nodule plays an important role in rhizobial nitrogen fixation by providing an environment with a reduced p O z , and the disruption of this very specialized relationship probably contributes to the loss of activity in the isolated protoplasts. If so, special procedures must be developed to retain the nitrogen-fixing ability during protoplast isolation by protecting the oxygen-sensitive nitrogenase under aerobic conditions of isolation and culture.

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As a method for exploring the potential of Rhizobium-nonlegume associations, fusion of leaf and nodule protoplasts offers several experimental advantages, provided of course that the genes coding for nitrogenase can be incorporated, replicated, and expressed in the isolated protoplasts, and that the fusion products can be cultured successfully: (i) It helps to overcome the difficult infection barrier; (ii) the necessary interaction between the legume and bacterial genomes has already taken place tuming on the nitrogenase ,genes in the bacteroids; (iii) the bacteroids are well established within the legume cytoplasm and are protected by the plant membrane which surrounds them. Uptake of whole rhizobia by pea leaf protoplasts has been reported (Davey and Cocking, 1972). The uptake takes place by engulfment of bacteria into vesicles formed by the contraction and invagination of the protoplast plasmalemma during plasmolysis and cell wall breakdown and not by conventional pinocytosis; no uptake takes place when bacteria are incubated with isolated protoplasts. The bacteria are incubated, along with leaf material, in a complex enzyme solution for 20 hours during which the uptake takes place, but it is not known what effect this has on the viability of the bacteria. In comparison, the fusion of bacteroid-containing nodule protoplasts with legume or nonlegume protoplasts appears more promising. Many fungi are known to establish ecto- or endomycorrhizal associations with the roots of higher plants, particularly the tree species. If it were possible to introduce nitrogen-fixing ability into such fungi, then the host plant would certainly be able to derive benefit from the association. K. L. Giles and H. C. M. Whitehead (personal communication) have recently obtained very encouraging results with just such a system. They incubated protoplasts of the fungus Rhizopogon, which is known to form a mycorrhizal association with Pinus radiata, with the free-living and nitrogen-furing Azorobacrer vinelandii. The protoplasts were then washed free of the bacteria, and any additional adhering bacteria were lysed with a lysozyme wash (other control procedures were also used). The treated protoplasts were then plated on media containing penicillin, which prevents the growth of Azorobacrer, but lacking any nitrogen. A very small number of the treated protoplasts were able to grow on the nitrogen-free medium and regenerate fungal colonies which showed acetylene reduction activity. Untreated fungal protoplasts can also regenerate colonies on appropriate media but these neither grow on nitrogen-free media nor reduce acetylene. No bacterial cells were detected in the treated fungal protoplasts, or in the hyphae regenerated from them, after incubation with Azorobacrer. The fungal hyphae regenerated from Azorobacter-treated protoplasts contained deposits of poly-0hydroxybutyric acid-a characteristic intracellular reserve of Azorobacrer-and structurally modified mitochondria. The mechanism of transfer of the nitrogenfuring ability of the bacterium to the fungus is presently not understood, but the significance of the experiments need hardly be emphasized here.

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The material presented in this article clearly shows the rapid and remarkable progress in techniques for the isolation, culture, and fusion of plant protoplasts, and the modest beginnings in the culture of fused protoplasts and in introducing cell organelles and foreign genetic material into protoplasts. Based on the experience during these last few exciting years of protoplast research, the following areas would appear most urgent and important: (i) Availability of more efficient and suitable enzyme preparations for rapid production of protoplasts; (ii) improvements in the handling and culture of protoplasts; (iii) isolation and culture of protoplasts from economically important species, particularly of the Gramineae, Leguminosae, Cruciferae, etc.; (iv) development of techniques for the successful culture of hybrid cells; (v) development of suitable selection systems to achieve preferential growth of hybrid cells in mixed populations, with the help of mutants, haploids, and genetically transformed cells with nutritional or other markers; (vi) methodology for the introduction of DNA,chloroplasts, mitochondria, nuclei, etc., into protoplasts, and the culture and selection of the genetically “modified” protoplasts and cells. In view of the rapid progress already made in protoplast research during the last 5-6 years, and provided that adequate research support is available, one may predict that at least some of the above goals will be achieved in the next decade. There is an urgent need for extensive research on protoplasts so that the great potential of these techniques in pure and applied research can be realized. The technology resulting from such research will be used by plant geneticists and breeders in their intensified search for better and more efficient plants for the future. It is interesting to note that most of the research on protoplasts has been done in Canada, England, Germany, and Japan and not in the United States. The success in these countries suggests that greater attention should be given in the United States to this rapidly evolving area of research. To summarize, the prognosis is healthy and cautiously optimistic, and hopefully the results of protoplast research will play an increasingly important role in agriculture in the future, but plant improvement through protoplast fusions and genetic modification-somatic hybridization and genetic engineering-will probably never replace the most elegant and sophisticated systems evolved in nature.

ACKNOWLEDGMENTS

Thii review was prepared during my sabbatical leave from the University of Florida. During this period I was supported by a Climate Laboratory Fellowship (1974-1975) of the Department of Scientific & Industrial Research, New Zealand, at the Plant Physiology Division, D.S.I.R., Palmerston North, and by the Senior United States Scientist Award for

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Research (1975-1976) of the Federal Republic of Germany, at the Lehrstuhl fur Botanische Entwicklungsphysiologie, Institut f i r Genetik, Universit'at Hohenheim, Stuttgart. 1 am deeply indebted to the many friends and colleagueswho generously supplied preprints of their publications and other valuable unpublished information about their research. This has helped to make this r e v i h up to date. 1 am especially grateful to DI. Oluf L. Gamborg (Saskatoon, Canada), Dr. Ernest G. Jaworski (St. Louis, U.S.A.), Dr. Herbert E. Street (Leicester, England), and my wife, Dr. Vimla Vasil, for their critical review of the manuscript and many helpful suggestions.

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CROP WATER DEFICITS

.

.

John E Begg and Neil C Turner CSIRO Division of Plant Industry. Canberra. A.C.T., Australia

..................................................... .............................................. .................................

I . Introduction I1. Evapotranspiration A Development of Plant Water Deficits ............................. B Components of Water Potential 111. Measurement of Crop Water Status ................................. A Total Water Potential ......................................... B . OsmoticPotential ............................................ C. Matric Potential ............................................. D. Pressure Potential ............................................ E. Indirect Methods ............................................ IV . Effects of Water Deficits on Crop Growth and Development . . . . . . . . . . . . . . A . Sensitivity of Crops at Different Stages of Development . . . . . . . . . . . . . . B . Morphological Effects ......................................... C Physiological Effects .......................................... D. Recovery from Water Deficits ................................... V . Adaptation to Water Deficits ...................................... A. Drought Resistance ........................................... B. Mechanisms of Adaptation ..................................... VI . Effects of Water Deficits on Crop Yield .............................. A. Effects on Economic Yield ..................................... B. Effects on Yield Components ................................... C. Yield Compensation .......................................... D. Interaction between Nutrient Deficiency and Water Deficits ........... VII . Water Use Efficiency ............................................ A . Plant Factors ............................................... B. Antitranspirants ............................................. C. Environmental Control ........................................ VIII . Differences in Response of Plants Grown Under Controlled Conditions andintheField ................................................ IX . Summary and Conclusions ........................................ References ....................................................

. . .

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161 163 164 166 167 167 169 169 169 170 170 170 172 174 180 182 182 183 188 188 190 192 193 195 197 199 201 202 205 207

I . Introduction

Water is the earth’s most abundant compound and yet on a worldwide scale a deficit of water is the single most important factor limiting crop yield.Although agriculture gains directly from rainfall on its crops and pastures. it is still the 161

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major consumer of water and billions of dollars have been spent on irrigation schemes to alleviate water shortages and improve crop and pasture yields. The increasing demands being placed on both food and water resources throughout the world require that agriculture be more efficient in its water use without sacrificing production of food and fiber. Thus in both irrigation and dryland agriculture, a greater understanding of crop water deficits and their influence on growth, development, and yield, the subject of this review, is essential. The subject of soil-plant-water relations was last reviewed in this serial publication by Russell (1959).’ In the seventeen intervening years there has been a major change in emphasis away from the influence of soil water deficits on plant growth, water use, and yield to a general recognition that plant growth is controlled directly by plant water deficits and only indirectly by soil water deficits. In fact, with adequate soil water supply, plant water deficits can occur as a result of increased evaporative demand by the atmosphere. The plant water deficit that develops in any particular situation is the result of a complex combination of soil, plant, and atmospheric factors, all of which interact to control the rate of water absorption and water loss (Kramer, 1959, 1963; Vaadia et al., 1961). Although soil-plant-waterrelations have not been reviewed in this publication for many years,’ the subject has received considerable attention elsewhere. Books on various aspects of plant water relations have been published by Kozlowski (1964), Knight (1965), Slatyer (1967), Briggs (1967), Kramer (1969), and Levitt (1972). In addition, edited books on the subject have been published by Rutter and Whitehead (1963), Slavik (1965), Pierre et al. (1966), Taylor (1970), Larson and Eastin (1971), Brown and Van Haveren (1972), and Stone (1975), plus a series of volumes edited by Kozlowski (1968a,b, 1972, 1976) on “Water Deficits and Plant Growth.” Additionally there have been reviews by Vaadia et al. (1961), Brouwer (1961), Slatyer (1962), Dainty (1963, 1969), Kramer (1963, 1974), Henckel (1964), Gates (1964, 1974), Weatherley (1965, 1970), Fischer and Hagan (1969, Philip (1 966), Slavfk (1 966), Hsiao (1 973), Jarvis (1 975), and Turner and Begg (in press). To review the subject of plant water relations yet again with such a voluminous list of publications elsewhere may seem unnecessary. However, the emphasis in the majority of previous reviews has lain heavily upon plant water relations, whereas in the present review the effect of water deficits on the crop as a community of plants under field conditions will be emphasized wherever possible. Because of the difficulty of interpretation of some field observations and the paucity of field data, reliance on controlled environment and glasshouse studies of effects of water deficits on growth and development is unavoidable: some of the difficulties in extrapolating from controlled environments to the field Nore udded in proof: During the preparation of this review, the authors were unaware of the review by J. S. Boyer and H. G. McPherson Adv. Agron. 27,l-23 (1975).

CROP WATER DEFICITS

1 63

are highlighted. Inevitably the emphases in this review reflect the personal interests of the reviewers rather than providing a complete summary of the very extensive literature on this subject. I I. Evapotranspiration

Evaporation from plant communities is frequently termed evapotranspiration, to signify the combined soil-plant nature of the evaporating surfaces. The two words are used interchangeably in most applications when free water surface evaporation is not involved (Slatyer, 1967). The evaporation of water, whether it be from a free water surface, wet soil, or as transpiration from plants is an energy-dependent process involving a change in state from the liquid to vapor phase, and the rate is a function of the vapor pressure gradient, the resistance to flow, and the ability of the soil and plant to transport water to the sites of evaporation (Gardner et al., 1975). Radiation from the sun is the primary source of energy, supplying the latent heat requirement for the vaporization of water; secondary sources include scattered and reflected radiation from the sky and clouds, as well as sensible heat transferred from the adjacent air, crop, and soil (Slatyer, 1967). When water is freely available a large proportion of the energy is dissipated as latent heat, but as the soil dries out some of this energy has to be partitioned into other sinks, such as sensible heat (Beg et ul., 1964). For a detailed treatment of energy in relation to evapotranspiration, see Slatyer and McIlroy (1961), Rose (1966), and Slatyer (1967). With solar radiation as the primary driving force for evapotranspiration and the rate being dependent on the vapor pressure gradient between the water at the evaporating surface and the bulk air, evapotranspiration from nonstressed crops is largely governed by meteorological conditions in the atmosphere external to the soil-plant system rather than by plant and soil factors (Gardner, 1965). The plant, in contrast to the soil, does exercise some control over water loss through its stomatal and cuticular resistances in the water pathway (Waggoner and Zelitch, 1965; Waggoner and Turner, 1971; Turner, 1975) and also through its ability to reduce the radiation load through active and/or passive changes in leaf orientation (Begg and Torssell, 1974). Because these controls are located at the leaf surface, the internal water status of the plant is closely coupled to that of the soil and less closely coupled to the atmosphere (Gardner et al., 1975). The processes of transport of water from the soil into the plant and through the plant to the atmosphere must be understood before the plant response to its environment will be clear. The pathway and processes involved in the uptake of water from the soil and its transfer through the vascular system of the plant to the sites of evaporation within the leaf, from which it diffuses into the atmosphere, have been the subject of a number of recent comprehensive reviews, for example Weatherley

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(1970), Newman (1974), Jarvis (1975), and Gardner et al. (1975). It is generally

accepted that water moves through the soil-plant-atmosphere continuum along a gradient of decreasing water potential from the soil, through the plant to the atmosphere (Gradmann, 1928; Van den Honert, 1948; Weatherley, 1965; Slatyer, 1967; Kramer, 1969; Van Haveren and Brown, 1972; Gardner et al., 1975). Moreover, because water is capable of storing heat and carrying substances in either solution or suspension, all or parts of the continuum may provide a pathway for energy and nutrient transport, as well as for water transport (Van Haveren and Brown, 1972). Recent attempts to apply the methods of irreversible thermodynamics to clarify these various transfer processes (e.g., Fiscus, 1975) appear, at present, to be useful only in very simple systems which are linear and in which the mechanisms and pathways of transport of the linked entities are identical. The processes of the soil-plant-atmosphere continuum conspicuously fail to satisfy these requirements (Philip, 1966). The evaporation of water in the leaf provides the major driving force for the absorption of water by transpiring plants against the gravitational potential and frictional resistances in the pathway of water through the plant (Kramer, 1956; Jarvis, 1975), and the rate of water uptake is controlled primarily by the rate of water loss (Kramer, 1956). The active absorption of water by roots as a result of osmotic and nonosmotic forces that result in the development of root pressure, plays only a minor role in the absorption of water by plants or is evident only when transpiration is low or ceases (Kramer, 1956; Stocking, 1956).

A. DEVELOPMENT OF PLANT WATER DEFICITS

As water evaporates from the mesophyll cells of the leaves the water potential of the cell wall matrix adjacent to the liquid-air interface falls, and water moves toward the interface from sources of higher water potential distributed both throughout the plant and in the soil. As a consequence of water movement through the plant along a series of frictional resistances, gradients of water potential result, with the largest drops in potential where the flow rates and resistances are largest. The lowered water potential in the transpiration pathway provides the driving force for the movement of water out of adjacent tissues such as the leaf mesophyll, cortex, and phloem. As a result of this loss, water deficits develop in the leaf, stem, and root tissues. Thus water deficits occur as an inevitable consequence of the flow of water along a pathway in which frictional resistance and gravitational potential have to be overcome (Jarvis, 1975), and do not only occur when the loss of water from the leaves in transpiration exceeds the supply from the roots, as is so often stated. Thus for a plant going into stress, transpiration will exceed water uptake by the roots as water is drawn out of tissues surrounding the xylem. When the water potential of these tissues has equilibrated with the water potential in the xylem, a steady

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state is reached in which transpiration equals water uptake. During recovery from stress as the water deficit in these tissues is being replenished, transpiration will be less than water uptake. Thus in plants experiencing water deficits, transpiration can exceed, be equal to, or be less than water uptake. In general all plants undergoing active transpiration are experiencing some degree of water deficit. The extent of any imbalance between transpiration and water uptake is limited by the storage capacity of the plant, which for crop, forage, and pasture species is usually less than 10% of the daily transpiration, whereas in trees it can represent 100%(Jarvis, 1975). Since the plant can only extract water from the soil when the water potential in the plant is lower than that in the soil, the water in the plant is seldom in equilibrium with the water in the soil. The difference in water potential between the plant and the soil depends on the rate of uptake of water from the soil and the water-conducting properties of the soil and plant (Gardner and Nieman, 1964). The progressive changes in soil and plant water potential as the soil dries out are presented schematically in Fig. 1 (Slatyer, 1967). This assumes the same evaporative conditions prevail each day, and the upper limiting curve shows the progressive decline in the water potential of the bulk soil, $soil ,as it dries from an initially wet condition E 0). The other curves show the water potential at the root surface, $mot, and in the leaves, $leaf, assuming that transpiration proceeds for 12 hours and then ceases for 12 hours. The water potential in the leaf shows marked diurnal fluctuations and very little dependence on The $soil merely sets the limit of recovery possible by the plant during the dark period, so that the maximum values for $leaf and $root follow the decline in $soil down to, and beyond the wilting point. 0

K

Lu

: I-

-15

-20 1

-

-

2

3

TIME

4

-

I

5

6

(days)

FIG.1. Schematic representation of changes in leaf water potential ($leaf), root water potential ($root), and soil water potential ($soil) as transpiration proceeds during a drying cycle. The same evaporative conditions are considered to prevail each day, and the horizontal dashed line indicates the value of $leaf at which wilting occurs (from Slatyer, 1967).

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plant water stress and drought stress are frequently treated as being synonymous in the water relations literature (e.g., Levitt, 1972). In the field, drought stress is often associated with above average radiation and temperature and below average relative humidity in addition to restricted water supply, whereas in controlled environments radiation levels are usually low and temperatures and relative humidities are maintained about average. Thus the only aspect of drought stress generally under study in controlled environments is the water deficit induced by restricted water supply.

B. COMPONENTS OF WATER POTENTIAL

Water in soils and plants is subject to several force fields caused by the presence of the solid phase, dissolved salts, external gas pressure, and the gravitational field. These effects are quantitatively expressed in terms of the potential energy of the water (Gardner, 1965). Potentials are usually measured in bars, joules per kilogram, or pascals (1 bar = 1.00 X lo6 dyne/cm2 = 1.00 X lo5 Newtonslm' = 0.987 atm = 1017 cm water = 75.0 cm Hg = 14.50 lb/in2 = lo5 Pa = 100 J/kg). The total potential, or water potential, $, at any point in the system can be partitioned into: (1) the osmotic potential, n, due to the presence of dissolved solutes; (2) the pressure potential, P,due to the turgor pressure acting outward on the cell walls and internal membranes in plants, and in soils it is related to the hydraulic or hydrostatic pressure found under saturated conditions (Van Haveren and Brown, 1972); (3) the matric potential, 7 , due to forces of capillarity, and molecular imbibitional forces associated with cell walls and colloidal surfaces which bind some of the water (Brown, 1972; Miller, 1972; Spanner, 1972); (4) the gravitational potential, G,due to the gravitational forces on the water in the plant; and ( 5 ) an interaction term, I , can be included to emphasize that the components of water potential are not independent of each other, and so are not strictly additive quantities: individual water molecules are often influenced simultaneously by interacting matric and osmotic forces, and distortion of the cell wall in a turgid cell may alter matric forces in the wall (Brown, 1972; Miller, 1972). Thus $=a+P+T+G+z

(1)

In most crop situations the gravitational potential is insignificant and, if not, is

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easily measured: the movement of water against gravity involves a potential gradient of 0.1 bar/m. While the concept of an interaction term is frequently acknowledged (Warren Wilson, 1967; Brown, 1972; Miller, 1972), the discrepancy resulting from the interaction between A and 7 is in practice assigned to either component according to the definition, or measurement method, used (Warren Wilson, 1967). Thus the total water potential is effectively represented by

JI=ntPtr

(2)

In fully turgid tissue the water potential will be a function of osmotic and pressure potentials, since r approaches zero as the colloids and matric surfaces become saturated, whereas when the tissue is under water stress, the osmotic and matric effects increase and the pressure term approaches zero (Boyer, 1967b; Brown, 1972; Shepherd, 1975).

Ill. Measurement of Crop Water Status

In recent years the measurement of crop water status has received considerable attention and thus will not be discussed in detail. Barrs (1968a) provides a most comprehensive review of the methods for measuring the relative water content (RWC), J/, A, P, and stomatal aperture. Reviews by Boyer (1969), Wiebe et al. (1971), Sullivan (1971), Turner (1972), and Slavik (1974) provide further details, and the proceedings of a symposium edited by Brown and Van Haveren (1972) gives information on aspects of thermocouple psychrometry in water relations research.

A. TOTAL WATER POTENTIAL

The most accurate measurements of J/ can undoubtedly be obtained by thermocouple psychrometry, except in cases in which large concentrations of solutes occur on the leaf surface or are released in the psychrometer chamber (Klepper and Barrs, 1968). Since, however, a wet bulb depression of 1°C approximates a value of J/ of -80 bars, strict temperature control was, until recently, required for accurate measurements of J/ with the thermocouple psychrometer. Further, long equilibration times (Millar, 1974) prevent frequent samplings unless a large automated system with many chambers is available. For these reasons thermocouple psychrometers have been less widely used for field studies than for controlled environment studies. However, the development of temperature-compensated thermocouple psychrometers (Hsieh and Hungate,

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JOHN E. BEGG AND NEIL C. TURNER

1970; Meeuwig, 1972; Hsieh et al., 1972; Calissendorff and Gardner, 1972) and dew point hygrometers (Neumann and Thurtell, 1972; Campbell et al.. 1973; Campbell and Campbell, 1974; Neumann et al., 1974) has relaxed the requirement for strict temperature control and has led to the development of in situ psychrometers or hygrometers for the measurement of J/ in soil (Rawlins and Dalton, 1967), roots (Fiscus, 1972), stems (Wiebe et al., 1970), and leaves (Neumann and Thurtell, 1972; Hoffman and Rawlins, 1972; Neumann et al., 1974; Campbell and Campbell, 1974). In situ psychrometers and hygrometers have been used in a number of field studies (Wiebe et al., 1970; Hoffman and Rawlins, 1972; Campbell and Campbell, 1974; Denmead and W a r , 1975), but no rigorous comparisons with other methods of measuring J/ have been undertaken under field conditions. Campbell and Campbell (1974) compared $J measured with an in situ leaf hygrometer with that measured with the pressure chamber for wheat and a number of tree species in a growth room. They showed that there was a 1:1 relationship between the two estimates, but the range for the in situ hygrometer was generally 2 bars and increased to 7 bars for values of $J above -2 bars. The authors attribute the scatter to failure of the hygrometer to properly sense the dew point at water potentials above -1 or -2 bars and errors in the hygrometer calibration. Under field conditions, temperature gradients between leaf and psychrometer thermocouple may increase the scatter still further. The in situ psychrometer or hygrometer should, however, be useful in observing the dynamic change in 9,since it is a nondestructive technique, or in pinpointing the correct timing for absolute readings by destructive means when only a limited amount of plant material is available. It was the rediscovery of the pressure chamber by Scholander et al. (1964, 1965) that made measurement of J/ under field conditions both simple and routine. With the technique, a leaf or branch is cut and placed in a chamber that can be pressurized when the cut surface is just protruding into the atmosphere through a seal in the top of the chamber. Pressure is slowly applied to the leaf or twig until the meniscus just returns to the cut surface and this balancing pressure approximates J/ (Boyer, 1967a; Turner et al., 1971; Ritchie and Hinckley, 1975). Although the technique was initially used with trees, modifications have been suggested for leaves of crop species with and without petioles (Turner et al., 1971). The technique is largely insensitive to temperature: Tyree et al. (1974) showed that J/ usually varied less than *2 bars over the temperature range for 0 to 36°C. Moreover, readings can frequently be obtained in less than 2 minutes, allowing a large number of observations to be obtained whenever sufficient plant material is available for destructive sampling. The rapidity and simplicity of the technique make it particularly applicable to agronomic studies: for further details readers are referred to the recent comprehensive review by Ritchie and Hinckley (1975).

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B. OSMOTIC POTENTIAL

A number of methods for measuring n are available (Barrs, 1968a). The thermocouple psychrometer, or commercial vapor pressure osmometers and cryoscopes are probably the most widely used: alternatively the pressure chamber can be used. In all cases P must be reduced to zero before the measurement of n. When samples are prepared for the thermocouple psychrometer, vapor pressure osmometer, or cryoscope, P is usually reduced to zero by killing the tissue with heat or cold and n is measured on the cell sap expressed from the tissue under pressure. With psychrometry it is also possible to freeze the tissue in the chamber and thereby measure 3/ and n on the same tissue: measurement of n on frozen tissue rather than extracted cell sap assumes that T is negligible, an assumption that may not be valid (Section 111,C). For details of the use of the thermocouple psychrometer in measuring n, readers are referred to the review by Brown (1 972). In the pressure chamber P can be reduced to zero by applying pressure directly to the leaf. Scholander et al. (1964, 1965) described a method of using the pressure-volume relationship of leaf cells at zero turgor to determine n. The technique is slow and in crops has only reportedly been used to measure n of sunflower (Boyer and Potter, 1973), maize, oats, and peaches (Turner, 1976).

C. MATRIC POTENTIAL

Miller (1972) recently reviewed methods of measuring T . The two simplest techniques involve either the direct measurement of T using the pressure chamber to determine the pressure required to express water from frozen and thawed tissue (Boyer, 1967b) or an indirect method using the thermocouple psychrometer (Boyer, 1968, 1969; Shepherd, 1975). In the latter, frozen and thawed tissue is placed in the psychrometer chamber and the thermocouple output compared with that of expressed sap from frozen and thawed tissue. Matric forces are still present with the tissue in the chamber, but are absent in expressed sap and thus T can be obtained by difference.

D. PRESSURE POTENTIAL

No direct methods of measuring P on whole plant tissue are available at present and P is usually obtained by difference, i.e.,

P=+-n-r assuming other compents are negligible.

(3)

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JOHN E. BEGG AND NEIL C. TURNER

E. INDIRECT METHODS

A number of indirect methods are available for the measurement of water deficits. Visual symptoms of stress such as wilting or color changes of foliage may be sufficiently accurate measures of deficit for irrigation scheduling. Others such as measurement of leaf temperature by infrared thermometry, leaf thickness by &gauging, or changes in stem diameter, fruit diameter, or stomatal aperture can all be used as estimates of deficits and can provide valuable comparisons in circumstances where J/ and its components cannot be measured. Barrs (1968a) refers to a number of these indirect methods and we shall only enlarge on the measurement of stomatal aperture or conductance. Recently, Slavk (1971), Jarvis (1971), and Stigter (1972) have reviewed methods of measuring stomatal aperture or conductance. For field studies, infiltration techniques (Oppenheimer and Engelberg, 1965), portable mass flow (Alvim, 1965; Bierhuizen et ul., 1965), or diffusion (e.g., Wallihan, 1964; Van Bavel et ul., 1965; Turner and Parlange, 1970) porometers have been developed that enable many measurements of relative stomatal aperture, leaf permeability, or diffusive conductance, respectively, to be observed per hour. IV. Effects of Water Deficits on Crop Growth and Development

A. SENSITIVITY OF CROPS AT DIFFERENT STAGES OF DEVELOPMENT

The effects of water deficits at different stages of development on crop growth and yield have generally been studied empirically, and earlier work in this area has been summarized by Salter and Goode (1967). They concluded that while a differential response to water at various stages of growth has not been reported for all plants there is considerable evidence that most determinate crops are especially sensitive to water deficits from the time of floral initiation, during flowering, and, to a lesser extent, during fruit and seed development. In indeterminate crops where these stages overlap the situation is less clear: perennial crops are sensitive to water deficits at the same stages, but it is doubtful whether the sensitivity during fruit development is more pronounced than it is during vegetative development. This is particularly the case when fruit development and vegetative growth are concurrent or when the rate of growth during a particular period largely determines the yielding capacity of the crop in the following season, as is the case with apricots (Uriu, 1964; Fischer and Hagan, 1965). Earlier work has also indicated that each organ and physiological process may respond differently to increasing water deficits; for example, in tomato retarded

CROP WATER DEFICITS

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development as a result of wilting was greater in the laminae of the leaf than the stem (Gates, 1955a,b). Also, in tomato the young actively growing tissues suffered the greatest check to growth, but they were more tolerant of water deficits than older tissues in the sense that protein hydrolysis was not active and they resumed active growth again upon relief of stress (Gates, 1964, 1968). Similar responses have been observed by Husain and Aspinall (1970) with the barley shoot apex: a period of water deficit resulted in a rapid inhibition of primordia production, but the differentiation of existing primordia was less affected. In contrast, older tissues undergo accelerated senescence during water stress and may not recover following a severe water deficit (Fischer, 1973; Ludlow, 1975). While the concept that crops are more sensitive to water deficits at particular stages of development has been widely accepted in the literature largely on the basis of witholding the supply of water or their response to irrigation, it cannot be assumed that the levels of plant water stress which developed at the various stages within the same experiment have been equal. Although some workers have accurately defined and reproduced the soil stress cycles, the water deficit which develops in the plant is also dependent upon the resistances in the soil-plant-atmosphere continuum which may vary with plant age (Reicosky et al., 1975) and particularly on the potential evaporative power of the atmosphere which certainly varies daily and seasonally (Section 11). This work is now being placed on a sounder footing through experiments in which the level of water deficit in the plant has been measured and in some experiments where the same levels of stress were imposed at each stage of growth. Hiler et al. (1972) measured the response of peas to three levels of plant water deficit (-14, -21, and -28 bars) at each stage of development. The yield of dry peas was most sensitive to stress at flowering for all levels of stress. At low and intermediate stress, pod development was more sensitive than vegetative growth, whereas under severe stress the reverse was true, and at the vegetative stage resulted in a marked stunting of the plant in terms of height and leaf area. These results indicate that the relative sensitivity of different stages of development to stress can vary with the degree of stress and this raises the question of the usefulness of the crop susceptibility factor developed by Hiler et al. (1974) for use in irrigation timing by the stress day index method. Fischer (1973) applied a series of single stress treatments to wheat within the period 3 weeks either side of ear emergence. For any given level of plant water stress, grain filling was reduced most when the stress arose about 10 days before ear emergence, and the sensitivity to stress decreased markedly at later stages of development. Despite careful control to achieve the same potential transpiration rate and initial soil water content for the drying cycle at each stage of development, the plants reached different levels of stress depending on their stage of growth, possibly because of a lower sensitivity of stomatal aperture to stress in

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JOHN E. BECG AND NEIL C. TURNER

older plants. This possibility has been neglected in most experiments aiming to investigate sensitivity to water stress at various stages of development.

B. MORPHOLOGICAL EFFECTS

The growth and development of a plant depends basically, on continuing cell division, on the progressive initiation of tissue and organ primordia, and on the differentiation and enlargement of cells until the characteristic form of the plant is realized (Slatyer, 1973a). It has often been stated that cell division appears less sensitive to water deficits than cell enlargement (Vaadia et ul., 1961; Gates, 1964; Clements, 1964; Salter and Goode, 1967; Slatyer, 1967; Hsiao, 1973). Evidence for this view is given by the observation that cell number is frequently of the same general order in plants exposed to water stress compared with controls, although cell size is greater in the latter (Petinov, 1965; Brouwer, 1963), and by the phenomena of more rapid growth on recovery from stress compared with controls (Gates, 1955a,b). This could result from cell division continuing during stress, though at a reduced rate (Gardner and Nieman, 1964), and thus providing an opportunity for a relatively rapid resumption of growth when stress is removed (Slatyer, 1973a). The stress effect on cell division may not be a direct one; for example, Doley and Leyton (1968) concluded that the cambial initials in ash need to expand to a diameter of 6 /.un before division commences. In this case the effect of water stress is possibly indirect via suppressed cell expansion, a hypothesis that Hsiao (1973) points out would explain the reduction in the rate of division under mild stress observed in some cases (Gates, 1968; Kirkham ef al., 1972). Recent work by Meyer and Boyer (1972) and McCree and Davis (1974) also draws attention to the possibility of equal sensitivity of cell division and enlargement to water stress in soybean and sorghum. The sensitivity of cell enlargement to water deficits in some species has been clearly demonstrated by the work on maize. Leaf enlargement declined rapidly at leaf water potentials below -2 bars and ceased at potentials of -7 to -9 bars (Boyer, 1970a; Hsiao et al., 1970; Acevedo et al., 1971). However, field measurements of leaf extension in maize by Watts (1974) have shown that there was no reduction in leaf extension rate until leaf water potentials were below -8 or -9 bars. The apparent insensitivity of field-grown maize to low leaf water potentials could be due to differences in osmotic potential and to gradients within the leaves (see Section VIII). In general there is a rapid and then more gradual decline in the rates of cell enlargement as water stress develops, with enlargement ceasing .when turgor pressures are still positive, for example, as large as 6 to 8 bars in sunflower and maize (Boyer, 1968, 1970a). This extreme sensitivity of growth to water stress

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has been described by an equation showing the relationship between cell enlargement and turgor pressure in elongating cells (Green, 1968; Green et d , 1971; Greacen and Oh, 1972);

where G is the rate of growth, E is a coefficient for the gross extensibility of the cell walls,and Pmin is the minimum pressure below which growth will not occur. The equation indicates that growth is proportional to the gross extensibility of the cell and the turgor pressure above a minimum threshold level, which as Boyer (1968, 1970a) has shown can be quite high. Thus growth may cease well before P falls to zero, and can be highly sensitive to water deficits of only a few bars. However, Green (1968) and Green et al. (1971) have indicated that gross extensibility and threshold turgor are not constants and can change under water deficit so as to permit resumption of growth at reduced turgor. This adaptation to stress may occur as a result of an increase in extensibility and/or a decrease in the threshold turgor. However, if under severe water stress turgor pressure fell to zero, then no amount of adjustment of these two parameters would premit a resumption of growth. In situations where turgor pressure is approaching zero, the plant can only maintain growth through osmotic adaptation (see Section V,B). One of the most important consequences of the sensitivity of cell enlargement to small water deficits is a marked reduction in leaf area. As leaf growth is generally more sensitive to water stress than stomatal resistance and COz assimilation (Section IV,C), it should no longer be assumed that crop growth is not affected if plant water deficits do not reach a level that directly reduce stomatal aperture and photosynthesis (Fischer and Hagan, 1965; Hsiao and Acevedo, 1974). A reduction in leaf area will reduce crop growth rate particularly during the early stages of growth when there is incomplete light interception. One of the most damaging features of a reduction in leaf area is the fact that the effect is permanent and in the case of a determinate crop there is no scope for compensation via an increase in the number of leaves. On the other hand, while a reduction in photosynthesis will reduce growth during the period of stress, the rate of photosynthesis can recover on the relief of stress (Section IV,D). Water stress can also affect leaf area through its effect in hastening the rate of leaf senescence (Fischer and Hagan 1965; Fischer and Kohn 1966c; Fischer, 1973; Slatyer, 1973a; Ludlow, 1975). In determinate crops such as wheat where the leaf area is fixed at flowering, yield under dryland conditions has been inversely related to the rate of leaf senescence after flowering, which in turn was related to plant water stress (Fischer and Kohn, 1966~). Although total plant growth is reduced during water stress, root growth is generally favored relative to shoot growth as indicated by frequently reported increases in the root-to-shoot ratio (Pearson, 1966; El Nadi ef d., 1969; Hoff-

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JOHN E. BEGG AND NEIL C. TURNER

man er al., 1971). In a study considering the effects of both nutrients and water on root-to-shoot ratios in perennial ryegrass and white clover, Davidson (1969) concluded that a decrease in the availability of water, nitrogen, or phosphorus caused an increase in the relative weight of roots. Furthermore, in the presence of a deficiency of water, nitrogen, or phosphorus an increase in any one of these factors caused a further increase in the root-to-shoot ratio. In addition to the effect of environmental factors on root growth, there is evidence from a number of crops that at certain physiological stages of growth, especially during flowering and the formation of fruit, root growth is retarded or has ceased completely (Leonard, 1962; Salter and Goode, 1967). When root growth is reduced, the rate of water absorption by plants becomes increasingly dependent on the flow of water through the soil to the root surface. Since the conductivity of unsaturated soil is very low (Marshall, 1959), severe water stress will soon occur in plants that are making little or not root growth under conditions of high evaporative demand, particularly where the existing root system has only occupied a relatively small volume of soil. The reduced root activity during the development of the reproductive organs may explain the beneficial effect of irrigation at such times. In some cases, stress appears to enhance root growth not only relative to shoot growth but absolutely. Hsiao and Acevedo (1974) presented evidence for this in the case of a crop of maize and the possible benefit to root crops such as sugar beet. The explanation offered was that the stress was insufficient to markedly affect C02 assimilation although shoot growth was noticeably reduced. The increase in assimilates as a result of the reduced shoot growth permitted osmotic adjustment (Section V,B) and extra root growth. This stress-induced preferential root growth may possibly constitute an adaptive mechanism (Hsiao and Acevedo, 1974). Also, Clements (1964) reported that a period of water stress in the first year of a 2-year crop of sugar cane generally increased yield as it caused deeper rooting and less susceptibility to stress at later stages of growth.

C. PHYSIOLOGICAL EFFECTS

Several comprehensive reviews on the physiological responses to water deficits have been published in recent years (Gates, 1964; 1968; Henckel, 1964; Crafts, 1968; Slatyer, 1969, 1973a; Laude, 1971; Hsiao, 1973). Emphasis in this review will therefore be primarily placed on the effects of a water deficit on the physiological processes associated with crop productivity, viz., stomatal behavior, photosynthesis, respiration, translocation, and the partitioning of assimilates. The omission of reference to changes in other physiological processes such as hormonal balance or nitrogen metabolism induced by water deficits does not deny their importance. Indeed, the recent discoveries that endogenous levels of

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abscisic acid and proline increase severalfold when plants are subjected to stress (e.g., Wright and Hiron, 1969; Barnett and Naylor, 1966), and that abscisic acid closes stomata and reduces transpiration (e.g., Little and Eidt, 1968; Jones and Mansfield, 1970) while proline accumulation may be linked to drought resistance (Singh et al., 1972, 1973), have generated considerable interest. Recent reviews on these topics include those by Naylor (1972), Lime and Vaadia (1972), Hsiao (1973), Milborrow (1974), and Raschke (1975).

1. Stornatal Behavior The responsiveness of stomata to water deficits has been known for many years. Because guard cells occupy a key position in the pathway for gaseous exchange between the plant and atmosphere, their importance as regulators of water loss and carbon dioxide uptake has been recognized and has generated a resurgence of interest in their response to water deficits. It is now generally recognized that the stomata do not respond to changes in $leaf or RWC until a critical threshold level of these parameters is reached, and that the stomata close over a narrow range of $leaf or RWC. The typical response for a range of field crops is shown in Fig. 2. Recently, the stomata of field-grown grapes, sugar beet, wheat, and barley have been shown to close at -13 bars (Smart, 1974), -13 bars (Milford, 1975), -7 to -19 bars (Connor, 1975; Millar and Denmead, 1976), and -30 bars (Biscoe et aZ., 1975), respectively. As Turner (1974a) pointed out, however, there is not a unique value of $leaf for stomatal closure in any

Cotton

sorgh”mLl Maize

-24

-16

-8

0

LEAF WATER POTENTIAL (bars)

FIG. 2. Relationship between stornatal conductance, as a percentage of the maximum conductance, and leaf water potential for several crop species. AU data were obtained in the field and for any one species at similar irradiances (from Turner, 1974a).

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particular species of cultivar, but the &f for stomatal closure vanes with position of the leaf in the canopy (Turner, 19741,; Millar and Denmead, 1976), plant age (Frank et al., 1973), and growth conditions such as the number of cycles of stress (Brown, 1974b; McCree, 1974) or whether the plants are grown in a controlled environment or field (Section VIII). Since changes in stomatal aperture involve changes in the turgor relations of guard cells and/or subsidiary cells (Meidner and Edwards, 1975), Turner (1974a) suggested that stomatal conductance may be better related to 4eaf than $leaf. From the limited data available, it was shown that stornatal conductance changed little until a threshold Pleafof between 0 and 3 bars was reached, below which a further decrease in Pkaf induced a large decrease in stomatal conductance. Thus, species exhibiting a wide diversity in $leaf required to induce stomatal closure showed only a small range in the values of Pkaf required for stomatal closure, although recent evidence from wheat (Millar and Denmead, 1976) suggests that the range may be greater than initially anticipated, However, because of the differences in osmotic potential and osmotic adjustment (Section V,B) between plant species, Phf is considered a more reasonable measure of stress than $leaf for stomatal relations. Although there have been a considerable number of comparisons of stomatal response to stress between species, there have been few varietal comparisons and those that have been reported are restricted to sorghum. Henzell et al. (1975) compared the stomatal response to soil water depletion in 23 sorghum genotypes and found a marked diversity in response; Shallu stomata had a greater sensitivity to $soil than M35-1 or I.S. 1598C. Blum (1974) also showed a wide diversity of stomatal conductances in 14 different genotypes growing under field conditions when soil and leaf water deficits developed. This contrasts with another report by Blum and Sullivan (1974) showing no significant differences between stomatal conductance and $leaf in 5 sorghum varieties tested in a growth room. The authors offer no explanation for the differences in response, but the various methods of applying the water deficit probably account for the differences observed (Section VIII). 2. Photosynthesis Since stomata act as regulators for COz exchange, as well as regulators of water loss, water deficits sufficient to close stomata must also depress photosynthesis. However, the transfer and fixation of COz internal to the stomata may also be affected by water deficits; the influence of stomatal and nonstomatal factors on the decrease of photosynthesis under stress has received considerable attention by physiologists. It is now generally accepted that the initial reduction in photosynthesis due to an increase in plant or soil moisture stress arises from

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changes in conductance of COz through the stomata. Consequently, the change in net photosynthesis with $leaf follows that of stomatal conductance shown in Fig. 2 (e.g., El-Sharkawy and Hesketh, 1964; Kriedemann and Smart, 1971; Ludlow, 1976), and changes in leaf photosynthesis with increasing soil or leaf water deficits mirror changes in transpiration measured concurrently (Schneider and Childers, 1941; Brix, 1962; Shimshi, 1963; Baker and Musgrave 1964;Barrs, 1968b; Willis and Balasubramaniam, 1968; Boyer, 1970b; Boyer and Bowen, 1970; Beadle et al., 1973; Beardsell et al., 1973; Catsky et al., 1973; Doley and Trivett, 1974). The conclusive evidence for stomatal closure being the primary cause of depressed photosynthesis under water limiting conditions was provided by Troughton (1969). The stomatal conductance of cotton decreased at a RWC of 80%, whereas the internal conductance of COz was only reduced at a RWC of 75% (-1 5 bars). In a subsequent study in which air with different levels of COz was passed through the leaf, Troughton and Slatyer (1969) showed that the internal conductance of COz of cotton was unchanged when the RWC varied between values of 92 to 56%: later work has shown that in soybean and maize (Boyer, 1970b; Slatyer, 1973b, Mederski e l al., 1975a,b), tomato (Duniway and Slatyer, 1971), kidney bean (Moldau and Rahi, 1971; Moldau 1973),horse bean (Moldau and Rahi, 1971), wheat, and millet (Slatyer, 1973b), the internal conductance of COz was unaffected at water deficits much greater than those required to close the stomata. On the other hand, Boyer (1971) showed that in sunflower nonstomatal effects on photosynthesis were apparent at the same value of $leaf at which the stomata closed: inhibition of chloroplast activity by low water potential in sunflower (Boyer and Bowen 1970; Boyer and Potter, 1973; Potter and Boyer, 1973) tends to confirm that the nonstomatal effects on COz exchange may be equally as sensitive as stomata in this species. Others have reported nonstomatal reductions in photosynthesis in certain varieties of maize (Heichel and Musgrave, 1970), in tobacco (Redshaw and Meidner, 1972), and in Mitchell grass (Doley and Trivett, 1974). Furthermore, chloroplasts or cell-free extracts of maize and sorghum show reduced activity under stress (Giles et al., 1974; Sullivan and Eastin, 1974). It can be concluded that photosynthesis declines initially as a result of stomatal closure, but prolonged and severe water stress can lead to depression of chloroplast and enzyme activity and to nonstomatal effects on photosynthesis. It is well documented that water stress leads to assimilate accumulation in the leaf and it has been proposed that this is a mechanism by which stress limits photosynthesis. However, evidence for assimilate inhibition of photosynthesis is inconclusive (Neales and Incoll, 1968). As was the situation with stomatal behavior, there has been little attempt to compare the photosynthetic response to drought among varieties. Diversity in the photosynthetic response to stress within a species has been demonstrated by

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Heichel and Musgrave (1970). The authors compared the photosynthetic rate and $leaf of 12 varieties of maize in the field during a 9-day period in which the plant water deficit increased, and showed that the plants exhibited three distinct types of response. Three varieites showed a major decrease in the rate of photosynthesis at a critical $ leaf , when leaf temperature measurements suggested that the stomata closed. Four varieties showed a small decrease in net photosynthesis, but no major decrease to values of $leaf as low as -27 bars, while in a third group of 5 varieties the variation in net photosynthesis was so great that no response to $ leaf could be distinguished. Although the variation in response was high, possibly as a result of the plants undergoing different numbers of cycles of diurnal stress and recovery, it is clear that some varieties of maize are more responsive to water deficit than others and that photosynthesis declines at lower values of $leaf in some varieties than in others. Further studies of this nature seem necessary to establish the degree of variation in the response to water deficit within a species so that the possibility of utilizing this feature in breeding programs can be evaluated.

3. Respiration Current evidence indicates that in crop species dark respiration is depressed whenever the water deficit is sufficiently great to close stomata and decrease photosynthesis, but the decrease in the dark respiration is less than that of net photosynthesis. For example, in tomato, respiration and photosynthesis were unchanged until $leaf fell below -9 bars, but at -14 bars net photosynthesis was zero whereas the dark respiration was depressed only 30% (Brix, 1962). Boyer (1970a) showed that the dark respiration rate of shoots of soybean, sunflower, and maize decreased steadily between values of $leaf from -8 to -18 bars. In a subsequent study, he found a smaller decrease in dark respiration of sunflower leaves below -10 bars (Boyer, 1971), suggesting that the respiration rate of the stem and meristematic tissue included in the earlier experiment may have decreased to a greater extent than the leaf tissue. Water deficits have been reported to increase, decrease, or have no effect on photorespiration. Heath and Meidner (1961), Meidner (1961, 1962), and Heichel and Musgrave (1970) have all reported an increase in the COz compensation point with increasing water deficit, which was initially taken as an indication that photorespiration increased with water deficit. Troughton and Slatyer (1969), on the other hand, observed no change in the COz compensation concentration and no change in COz exchange in oxygen-free air with water stress and concluded that photorespiration was not affected by short term water deficits, while Boyer (1971) showed by two different methods that photorespiration was decreased by an increased water deficit. It is now known that the increase in C 0 2 compensation point under water stress arises from a depression

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of COz uptake and not an increase in photorespiration (Meidner, 1967). Further, photorespiration increases with temperature; therefore, a rise in leaf temperature as a result of stomata1 closure may result in an apparent increase in photorespiration (Slatyer, 1969). However, since the substrates for photorespiration arise from products of the photosynthetic pathway, any decrease in photosynthesis must ultimately depress photorespiration (Heichel, 1971). Thus, any increase in photorespiration appears to be an artifact of the method of measurement, and photorespiration is unaffected by short-term stress, but ultimately decreases as the substrates for photorespiration are depleted.

4. Translocation Since the long distance transport of assimilate from the site of assimilation to the point of utilization is affected by the rate of assimilation, the rate of utilization, the loading and unloading of the seive elements, and the velocity of assimilate movement in the seive tubes, an effect of water deficit on any one of these processes will be apparent as an effect on overall translocation. The movement of assimilate from stems to roots and buds in desiccated, dormant Phalaris tuberosa (McWilliam, 1968) suggests that the transport system is highly resistant to desiccation. Furthermore, Wardlaw (1967, 1969, 1971) has shown that the velocity of assimilate movement in the vascular systemis little affected by water stress down to about -30 bars in wheat at grain filling or in darnel (Lolium temulentum L.) at the vegetative stage. However, the water deficit did decrease the translocation of assimilates in both plants. In the case of the darnel in which the sink for assimilates, i.e., the expanding leaf, was more sensitive to stress than photosynthesis of the source leaf, the inhibition of leaf growth was considered to be the major factor reducing translocation (Wardlaw, 1969). However, in wheat, in which the sink for assimilates, i.e., the grain, was less sensitive to water stress than the photosynthesis of the source leaf, the reduced source of assimilates and a reduction of loading into the vasular system were considered to be the most likely factors limiting the translocation (Wardlaw, 1967, 1971). Recently, Munns and Pearson (1974) and Moorby et al. (1975) concluded that translocation to potato tubers was reduced solely in proportion to the reduction in net photosynthesis of the leaves and that vein loading and transport in the vasular system was unaffected by values of $leaf as low as -14 bars. In one of the few field studies in which the effects of a water deficit on translocation has been studied, Brevedan and Hodges (1 973) showed that during grain filling of maize, water stress that reduced 3/leaf to -26 bars reduced vein loading. This resulted in an increased retention of labeled carbon in the leaf up to 6 hours after labeling and a proportionately smaller movement of assimilate to the kernels. On the basis of current evidence there is no reason to alter the

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basic conclusion of Wardlaw (1968) that reduced translocation under water stress is the result of a reduction in photosynthesis of the source or growth of the sink rather than any direct effect on the conducting system.

5. Distribution of Assimilates Since the factors controlling the distribution of assimilates in the adequately watered plant are largely unknown, the majority of the reports on the effects of a water deficit on distribution patterns remain purely descriptive. The differential influence of a water deficit on extension, photosynthesis, vein loading, and grain filling mentioned above and the different degrees of stress in different organs will alter the distribution pattern of assimilates depending on the time and severity of water stress, the stage of development, and the prehistory of the plant. Moorby et al. (1975) showed that reduction of $leaf from -2 to -9 bars reduced leaf photosynthesis, but was insufficient to alter the distribution of assimilates. Wardlaw (1969) compared the effect of two degrees of stress on the distribution of assimilates in darnel and showed that with an increase in stress more assimilate was distributed to the young expanding leaves and less to the crown. Wardlaw (1967, 1969) showed that the stage of development was important in the distribution of assimilates under stress conditions: in darnel stressed at the vegetative stage, labeled assimilates moved preferentially to young leaves, sheaths, and roots, whereas in wheat stressed at the grain-filling stage, reduced leaf photosynthesis resulted in assimilates moving from the lower leaves, stems, roots, and crown to the ear. Under field conditions Brevedan and Hodges (1973) showed that, in the short term, water stress reduced the translocation of labeled carbon to the cob and kernels in maize, but in the long term, as will be shown in Section VI,C, there is a greater movement of assimilates from the stem to the grain under water stress at least in wheat (Wardlaw, 1967; Passioura, 1976).

D. RECOVERY FROM WATER DEFICITS

Alleviation of water stress results in a rapid rise in $leaf and recovery of turgor, but there is frequently a delay in the opening of stomata and the recovery of photosynthesis (Schneider and Childers, 1941; Stilfelt, 1955; Iljin, 1957; Glover, 1959; Shchez-Diaz and Kramer, 1971; Kriedemann and Loveys, 1974; Loveys and Kriedemann, 1973). The delay of stomatal opening in tobacco and bean leaf discs placed on water to recover from stress was shown to be dependent on the degree and duration of the stress treatment (Fischer et al., 1970). Although a small number of guard cells remained permanently closed (Iljin, 1957; Allaway and Mansfield, 1970), and the intercellular C02 concentra-

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tion had a small carry-over effect (Fischer, 1970; Allaway and Mansfield, 1970), the major aftereffect of stress clearly resided in the guard cells and was subsequently shown to be due to the persistence of abscisic acid which has a direct effect on guard cells (Allaway and Mansfield, 1970; Jones and Mansfield, 1970; Kriedemann and Loveys, 1974, 1975). Other inhibitors may also have a role in aftereffects of stress (Ogunkanmi et d., 1974; Wellburn et QL, 1974). However, photosynthesis does not recover from stress as quickly as stomatal conductance and abscisic acid levels in the leaf. Kriedemann and Loveys (1975) and Kriedemann et al. (1975) provide evidence that phaseic acid, a derivative of abscisic acid, may inhibit photosynthesis at least under some conditions. A frequently observed effect on recovery from stress is a more rapid rate of growth and development than in unstressed controls. For example, Gates (1955a, 1968) showed that upon rewatering of previously stressed plants, the growth rates of tomato were higher than those in the unstressed controls and the primordium development of lupins was faster than those in the unstressed controls. Leaf enlargement was earlier shown to be very sensitive to stress (Section IV,B): relief of stress resulted in transitorily greater rates of leaf enlargement in both sunflower and maize (Boyer, 1970a; Hsiao et d., 1970; Acevedo et d.,1971). If the stress was brief, full recovery was possible (Acevedo et al., 1971), but with long or severe stress full recovery did not occur (Boyer, 1970a; Acevedo et d., 1971). Similarly, Ludlow and Ng (1974) report that the photosynthetic rate of leaves subjected to stress was greater on recovery than leaves of similar chronological age that had not undergone stress. The species used by Ludlow and Ng (1974) was green panic which showed a rapid decline in net photosynthesis with age after full leaf expansion. The changes in growth and development induced by stress have been described as “a senescent decline in growth during wilting and the development of a physiologically younger condition upon rewatering” (Gates, 1964). Recently, Ludlow (1975) has suggested that water stress merely suspends the aging of physiologically young leaves and Ng et d. (1975) conclude that earlier studies showed the same results. Their conclusions are based on the results of Ludlow and Ng (1 974), showing that upon rewatering the photosynthetic rates of surviving leaves was greater than those in the controls of the same chronological age, but comparable with those of the same physiological age, if it is assumed that senescence was suspended at values of $leaf below about -12 bars. In light of the fact that physiological and biochemical processes are affected by different degrees of stress (Hsiao, 1973), it is difficult to visualize that all the processes contributing to aging cease and recommence at a single critical $leaf. The results may simply be a product of the rapid development of and recovery from stress in their study, and a product of the rapid decline of photosynthesis with age in the green panic. Gates (1974) suggested an interesting mechanism for the suspension of aging based on the biological activity of macromolecules in the protoplast.

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V.

Adaptation to Water Deficits

A. DROUGHT RESISTANCE

The ability of a crop variety or species to grow satisfactorily in areas subjected to periodic water deficits has been termed its drought resistance (May and Milthorpe, 1962). It is generally recognized that plants are resistant to drought because they either avoid the development of severe deficits or tolerate severe deficits (May and Milthorpe, 1962;Levitt, 1972). 1. Avoidance of Severe Deficits

In some areas with a marked dry season, such as Mediterranean or wet-dry subtropical climates, crops usually are grown in the wet season to avoid severe deficits, or grown at the end of the wet season and complete their life cycle on water stored in the soil.Success in adapting a crop to an area of seasonal drought usually has been achieved by shortening the growth cycle of the crop so that the plants mature before soil water limits yield (May and Milthorpe, 1962). However, given adequate water supply, yield is usually positively correlated with maturity date, so that in practice a grower has to offset the potentially higher yield of a late variety against the risk of yield reduction by early stress. In addition to avoiding severe stress by completing the life cycle within a period of adequate moisture supply, crop plants can also avoid severe deficits by conserving water during periods of adequate supply. For example, Passioura (1972) showed experimentally that increasing the resistance of the root system of wheat to water flow by reducing the number of seminal roots, conserved water during the vegetative phase and resulted in a greater yield than in plants with a normal root system, when grown on stored water. Alternatively, plants may avoid stress by preventing the development of severe dehydration even in arid environments. To achieve this the plant must have a low cuticular conductance for water vapor and close its stomata firmly when a water deficit develops. The classic example of plants that are able to prevent dehydration are succulents, e.g., pineapple. Szarek and Ting (1974)showed that the internal $ of the cactus Opunfia basilaris did not fall below -16 bars even after 4 months without rain. Although mesophytic crops do not possess such well-developed dehydrationresistant mechanisms, it is clear from the observations of Turner (1974b), Blum (1974), and Peake ef al. (1975) that species and varieties develop different degrees of leaf water stress under similar conditions of soil water and evaporative demand.

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2. Tolerance of Severe Deficits Almost all flowering plants can withstand severe deficits in the dormant seed stage, but the degree to which plants can tolerate severe desiccation at other stages of their life cycle varies considerably. The extreme case is shown by the poikilohydrous “resurrection” plants, which include several grass species. Even after $leaf falls to below -5000 bars, they have the ability to recover turgor and grow within a few hours of rewatering (Gaff, 1971; Gaff and Hallam, 1974). In a recent summary of the variation in drought tolerance among crop species, Ludlow (1976) found that the degree of drought tolerance was associated more with the environment to which the plants had adapted than to taxonomic grouping. Also, Sullivan and Eastin (1974) and Singh et al. (1972, 1973) have shown that varietal differences exist in the tolerance of severe deficits in sorghum and barley. for example, Sullivan and Eastin (1974) found that the value of J/ to which leaves can be stressed and show 50% recovery varied from -31 to -48 bars between the sorghum varieties. The methods used to evaluate desiccation tolerance (see Sullivan, 1971), however, still need to be related to drought tolerance in the field. Whether drought tolerance or drought avoidance mechanisms are the most suitable for a particular crop will depend on the degree and duration of expected deficit. In areas with a definite dry season and in determinate crops showing a strong correlation between soil water content at anthesis and yield (Nix and Fitzpatrick, 1969), water-conserving machanisms during the vegetative stage and dehydration-tolerant mechanisms in the grain-filling stage should provide the most appropriate conditions for high yield. On the other hand, in areas of short and irregular periods of deficit, drought avoidance mechanisms that maintain high) I and P may be all that is required. Readers requiring further information on drought resistance are referred to reviews by Henckel(1964), Parker (1968), and Levitt (1972).

B. MECHANISMS OF ADAPTATION

1. Morphological Mechanisms

Since cell division and expansion are very sensitive to stress, water deficits in the vegetative stage can have a marked effect on leaf area (Section IV,B). Further, as the rate of evapotranspiration is determined by leaf area, particularly at leaf area indices less than three (Turner, 1966; Fischer and Kohn, 1966a; Ritchie and Bumett, 1971; Ritchie, 1974), reduction of leaf expansion can provide a mechanism for reducing water loss from the soil and delaying the

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development of more severe stress. Similarly, leaf shedding or the accelerated senescence of the physiologically older leaves (Section IV,B) is also an adaptive mechanism for reducing water use: Turner (1966) provided indirect evidence that this alleviated severe deficits at a later stage of development in wheat. Positive leaf movement to orient the leaf parallel to the incident radiation (parahelionasty) and the flagging or rolling of leaves when wilted are additional adaptive mechanisms that reduce the effective leaf area and hence the energy load upon the plant. Parahelionastic leaf movements have been identified in stressed beans (Dubetz, 1969), and Townsville stylo (Be@ and Torssell, 1974). Similarly, the orientation of wilted leaves is an effective load-shedding mechanism that can reduce the development of severe deficits. This is demonstrated in Fig. 3 which shows the incident radiation on wilted, vertically hanging sunflower leaves of different orientation compared with an unstressed leaf. The development of enlarged white hairs under stress is an adaptive mechanism in silver sunflower (Helianthus argophyllus L.) and other species, which increases the reflection of radiation by the leaf and decreases the conductance of water through the boundary layer of the leaf (Woolley, 1964; Wuenscher, 1970; Johnson, 1975). The wax bloom noted on some sorghum leaves acts in a similar way in reducing net radiation, the boundary layer conductance, and transpiration (Shchez-Diaz et al., 1972; Chatterton et al., 1975). The 20% reduction in

2400

I

I

I

I

I

I

I

1

I

I

I

l

l

TIME OF DAY (h)

FIG.3. Diurnal changes in irradiance (400-900 nm) of wilted, vertically hanging sunflower leaves (dashed lines) oriented north (N), south (S), east (E). or west (W), and the diurnal changes in an unstressed sunflower leaf (solid line) exhibiting diaphotonastic leaf movements (Shell et ul., 1974) that orient it normal to the direct radiation. The irradiance on a horizontal plane (HOR) is shown for comparison.

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transpiration which they recorded suggests that the wax bloom also occluded stomata. The effect of a water deficit on the preferential development of the root over the shoot, mentioned in Section IV,B, is an adaptive mechanism that enables the crop to explore a greater soil volume for water. If soil water is available at depth, the development of a deeper root system would clearly be a useful adaptive feature (Passioura, 1974). Varietal differences in rooting depth have been demonstrated in wheat (Hurd, 1968; Derera et al., 1969), soybeans (Raper and Barber, 1970), and tomato (Zobel, 1975), and Hurd (1968, 1974) showed that deeper rooting varieties yield better under drought stress. An alternative proposed by Passioura (1972) for situations in which soil water is not available at depth and plants have to survive on limited resources of stored water near the surface, is to decrease the hydraulic conductance of roots. In pot experiments he was able to show that decreasing the hydraulic conductance of wheat by reducing the seminal roots to one, substantially reduced the water loss before anthesis and increased the final weight of grain. The decrease in the hydraulic conductance of the root must limit loss by creating values of $leaf that reduce the expansion of leaf area or decrease the stomatal conductance (Brouwer, 1961).

2. Physiological Mechanisms Stomata1 closure in response to stress is a powerful mechanism for regulating water loss and reducing the development of further stress (Waggoner et al., 1964; Waggoner and Zelitch, 1965; Van Bavel, 1967; Szeicz er al., 1973), although Turner (1975) showed that in maize stomatal closure did not completely prevent further development of stress. As pointed out in Section IV,C, stomata are insensitivie to stress until PIeaf reaches a critical values and the stomata close rapidly. In the field this means that stomata frequently begin to open as radiation increases during the morning and then quickly close as Pleaf falls below the critical value (Turner, 1974a,b). This is an adaptive mechanism that enables the plant to briefly photosynthesize during the morning to keep the plant in positive carbon balance and to conserve water during the remainder of the day. Henckel (1961, 1964) and co-workers proposed a method of increasing the resistance to dehydration by treating the seed prior to sowing. The presowing treatment involved allowing the seed to take up water to 30%dry weight, leaving at 10” to 25°C for 24 hours and then air drying. May er al. (1962), summarizing their review of the Russian work, concluded that “there is considerable evidence to show that the drought resistance of plants can be increased by subjecting seeds to a cycle of wetting and drying prior to sowing.” Since then a number of workers have studied the potential of presowing hardening of seeds, but with variable results. From the results obtained, it can be concluded that the seed

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JOHN E. BEGG AND NEIL C. TURNER

pretreatment does not affect the physiological resistance to drought (Jarvis and Jarvis, 1964), but speeds up germination (Keller and Black, 1968; Heydecker et al., 1973) and root growth (May et al., 1962; Austin et al., 1969), and delays the development of deficits sufficient to close stomata (Woodruff, 1969). This sometimes leads to increases in yield under drought in some varieites (Chinoy, 1960; Waisel, 1962; Husain et al., 1968; Salim and Todd, 1968; Woodruff, 1969). Unless early germination in cold soils is an advantage, as it may be in some horticultural crops (Heydecker et al., 1973), the uncertain results do not warrant the extra labor required in pretreating the seeds. The most important physiological mechanism enabling plants to tolerate stress is the lowering of IT, termed osmoregulation or osmotic adjustment (Turner and Begg, in press). Any loss of water from cells during a water deficit must concentrate the solution within the cell and lead to a decrease in IT.The magnitude of the decrease in IT with decrease in J, is known to vary with species (Gardner and Ehlig, 1965; Shchez-Dim and Kramer, 1973; Turner, 1974a,b) and has generally been considered to be due to differences in cell wall elasticity between species (Weatherley, 1970). However, in addition to the decrease in IT due to solute concentration as J, decreases, it is now becoming clear that stress induces a net increase in solutes, i.e., osmotic adjustment. In a simple, but elegant experiment, Meyer and Boyer (1972) demonstrated that with different degrees of soil water deficit imposed over 24 hours, IT of soybean hypocotyls decreased about 5 bars with decreasing soil and plant J,, thereby maintaining the turgor potential constant, whereas when the deficit was imposed quickly by applying pressure to the hypocotyl, IT changed little as the deficit increased. The negligible degree of osmotic adjustment when the cotyledons were removed suggested that the transfer of solutes from the cotyledons to the hypocotyl was the primary cause of the osmotic change. Similarly, a decrease in IT of about 6 bars was observed in pea roots in response to a decrease in of 5.5 bars (Greacen and Oh, 1972). It has long been known that ITleaf will decrease in response to a change in IT of the rooting medium when the osmoticum is either salt or polyethylene glycol (Bemstein, 1961, 1963; Janes, 1966, 1968; Ruf et al., 1963, 1967; Chu et al., 1976), but since plants can absorb both these osmotica it is not clear whether the changes in ?r arise from absorption and translocation of the osmoticum to the leaves or from an increase in solutes induced by lowering $leaf. Field studies reported by Kreeb (1963) show nkd exceeding -27 bars in barley with a limited soil water supply compared with -14 bars in well-irrigated barley. Similarly, we have observed values of riled below -50 bars in sunflower (N. C. Turner, unpublished) and cotton (C. T. Gates, unpublished) grown on a restricted soil water supply compared to values of qeafof -10 bars in wellwatered plants grown under similar conditions: these decreases in q e a f induced by restricting the water supply are too large to arise simply from water loss by

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the leaves. This is confirmed by Kassam and Elston (1974) who showed that in field-grown beans, nkaf at wilting decreased from -1 0 to -1 5 bars because of a net increase in solutes as and $leaf decreased. Similarly, we have observed a decrease in nleaf at wilting from -17 to -21 bars in field-grown sunflower and from -14 to -18 bars in field-grown sorghum over a 5-day interval as the soil dried (N. C. Turner and J. E. Begg, unpublished). The solutes accumulating during osmotic adjustment in plants are largely unknown. Earlier it was pointed out that proline accumulated under stress (Section IV,C). Proline is responsible for osmotic adjustment in some microorganisms (Tempest er al., 1970; Schobert, 1974; Measures, 1975) and some halophytes (Stewart and Lee, 1974), but appears to be insufficient to account for significant changes in n in barley leaves (Chu er al., 1976). Sugar alchols (Lewis and Smith, 1967; Brown, 1974a), organic acids (Osmond, 1963), potassium (Christian and Waltho, 1964; Measures, 1975), and soluble carbohydrates have all been proposed as osmotic regulators. At this stage, it appears that the rise in soluble carbohydrates may be the primary source of net solute increase in crop plants. Iljin (1957), among others, has reported a concurrent rise in soluble sugars and fall in starch under stress. Recently, MUMS and Pearson (1974) showed that even though absolute amounts of starch and sugar changed little in stressed potato leaves, the proportion of labeled carbon incorporated into insoluble polysaccharides was only one fifth that incorporated into soluble carbohydrates in stressed leaves compared to a ratio of 1:1 in the unstressed leaves. This suggests that the starch may not act as a source of soluble sugars for osmotic adjustment, but that current assimilates may be directed into soluble fractions to provide the solute for osmotic adaptation. Osmotic adaptation provides an explanation for the decrease in the threshold water potential for stomatal closure (Section N,C) after a series of cycles of stress (Brown, 1974b; McCree, 1974; Turner and Begg, 1974) and the differences between field and controlled environment studies discussed in Section VIII. Osmotic adaptation of roots (Greacen and Oh, 1972) also may be important in allowing preferential growth of roots under stress (Hsiao and Acevedo, 1974). Little research has been conducted on the magnitude and conditions required to maximize osmotic adaptation or on the heritability of any differences between varieties; further investigation is clearly warranted. There has, in fact, been little breeding or direct selection for specific drought resistance characters. Although variation exists in several characters that might provide crops better adapted to water deficits, their heritability has not been investigated. Finlay and Wilkinson (1963) proposed a method for analyzing yield responses of varieties in a range of environments that enabled plants with general adaptability to all environments to be identified from those with specific adaptability to either favorable or unfavorable environments. Eberhart and Russell (1966) have proposed a modified form of the analysis used to study the

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performance of winter wheat cultivars grown in a wide range of environments (e.g., Stroike and Johnson 1972); however, the characters specifically beneficial in poor environments, with the exception of deeper rooting characteristics in wheat (Hurd, 1974), have not been identified (Finlay, 1968). Hurd (1971) has outlined the steps that are required to breed for increased drought resistance. VI. Effects of Water Deficits on Yield

A. EFFECTS ON ECONOMIC YIELD

There are numerous reports in the literature showing that water deficits limit yield and/or that irrigation increases yield. The degree of yield reduction by a water deficit or enhancement through irrigation will depend on the degree, duration, and timing of the deficit and on the proportion of the total yield that comprises the economic yield of the crop. In this section the dependence of the effect of a water deficit on the proportion and nature of the total crop yield that is harvested for economic or marketable yield will be briefly reviewed. Because of the greater sensitivity of leaf area development than photosynthesis and translocation to a water deficit, crops such as pasture and ensilage, tobacco and green vegetables, whose yield comprises the bulk of the above-ground portion of the crop, are often more sensitive to stress than crops such as wheat, peas, or fruits, whose yield is the reproductive portion of the plant only. Anderson and White (1974) provide an example of this with green peas: the lack of irrigation reduced the total yield by 47%, but the yield of peas by only 36%. On the other hand, a water deficit at a critical stage of development in a determinate crop can markedly reduce the economic yield with a smaller effect on total above-ground dry matter yield. For example, Turner (1966) observed a 70% decrease in grain yield of wheat from a water deficit imposed 5 weeks prior to ear emergence, but only a 52% decrease in total dry matter by the same treatment. Downey (1971) provides an example of the importance of timing of stress on the relative effects on grain and total dry weight in maize. In his study, when drought stress was allowed to develop for 20 days during male meiosis in maize, the total above-ground dry matter at harvest was reduced by 29% but the grain yield was unaffected. On the other hand, when drought stress was allowed to develop during grain filling, the reduction in total dry matter was still only 30%,but the grain yield was reduced by 47%. The importance of a water deficit on yield also depends on whether the economic yield is based on the fresh or dry weight component of yield. Many fruits and vegetables are sold on the basis of fresh weight or size. Ih fruits and

CROP WATER DEFICITS

189

vegetables the fresh weight often continues to increase even after dry weight has ceased (Chalmers and van den Ende, 1975). Since the size and weight at this stage depend more on the plant water potential than on photosynthesis (Davenport et al., 1974a), a water deficit will have a greater effect on fruit size and weight than on the less important dry weight. Davenport etal. (1974b) report a small but significant decrease in volume from omitting the final irrigation in a peach orchard. Since a small decrease in volume can decrease the size class of fruits, the 4% reduction in size reported by Davenport et al. (1974b) could have a marked effect on the market value of the crop. In tree crops, growth and development in a particular year is often affected by conditions in the previous season. Uriu (1964) showed that the yield of unirrigated apricots was correlated with the date at which the soil water was depleted in the previous season; the later the date of depletion the greater the yield. This arises because the floral buds are laid down in the previous season and water stress during their development reduced the number of flowers and fruit produced the following season. Thus, in perennial tree crops water deficits in two seasons can influence yield. Water deficits can also influence the length of the reproductive growth and development period in indeterminate crops. Hearn (1975a,b) showed that both watering frequency and date of final watering, in a tropical environment with a definite dry season, influenced the length of flowering and boll set in cotton. Less frequent watering and earlier termination of watering both reduced the period of flowering, boll development and yield. Allowing the development of a water deficit can be used as a method for making machine harvesting easier and more timely: increasing the watering frequency increased the seed yield of cotton by 19 to 20% when handpicked, but only 10 to 13%when machine picked (Hearn, 1975a). Further, cessation of watering early in the season reduced the number of defoliant sprays required before machine harvesting (Hearn, 1975b). It must be emphasized that water stress influences not only economic yield but yield quality: the effect on yield quality can be either beneficial or detrimental depending on use. For example, water stress increases the nitrogen percentage of small grains such as wheat and barley (Konovalov, 1959; Storrier, 1965; Turner, 1966; Campbell et a l , 1969); in the case of a water deficit imposed on wheat 5 weeks before ear emergence, the nitrogen percentage of the grain was increased 53% over that in the well-watered controls (Turner, 1966). An increase in nitrogen percentage would increase the quality of feeding and baking wheat and barley, but decrease the quality of malting barley. Cotton quality is also reduced by drought stress (Marani and Amirav, 1971). Additionally, Talha and Osman (1975) showed that water stress at a l l stages of development reduced the quality of sunflower oil, as indicated by the linoleic: oleic ratio, although both the percentage of oil and quality of the oil was very

,

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JOHN E. BEGG AND NEIL C. TURNER

low in this particular study. Mild stress near to harvesting can increase the accumulation of soluble carbohydrates (Iljin, 1957; Clements, 1964), a feature that increases the quality of some fruits. The maintenance of low plant water stress at all stages of growth may not always produce maximum yields and in fact yield and quality may be increased by subjecting plants to water stress. Fischer and Hagan (1965) pointed out that high levels of water supply during and shortly after flowering may actually reduce fruit set and sunrival in cotton, beans, tomatoes, and alfalfa. Also, stress prior to harvest in sugar cane prevented undesirable flowering and increased the accumulation of soluble carboyhydrates (Clements, 1964) and stress late in the growth of guayule (Parrhenium argentarum) considerably increased the yield of rubber despite a 20% reduction in total plant growth (Wadleigh et al., 1946). Lodging is frequently a problem in irrigated cereals and cotton grown under high levels of nitrogen (Day, 1957; Weibel and Pendleton, 1964; Fischer and Hagan, 1965), and restricted watering helps prevent lodging and its associated loss of yield through reduced photosynthesis, increased incidence of disease, and intensification of harvesting problems.

B. EFFECTS ON YIELD COMPONENTS

The components of yield that are influenced by water stress depend largely on the timing of stress in relation to the development of the portion of the plant utilized for economic yield. In general, it can be concluded that a plant organ is most sensitive to stress during its period of rapid development. In an earlier section (Section IV,A), it was pointed out that most determinate annual crops are especially sensitive to water deficits from the time of floral initiation and during flowering. Slatyer (1969,1973a) reviewed the influences of water stress on inflorescence development, fertilization, and grain filling in cereals. Although he showed that water stress during inflorescence development reduced the number of primordia and the development of these into fertile florets, he did not point out that stress prior to ear emergence can markedly reduce the number of heads that emerge. Figure 4 shows the number of tillers in adequately watered wheat, and wheat subjected to a soil water deficit from the time that maximum tiller numbers was reached. The water deficit increased the rate of tiller death from 3/m2/day in the controls to ll/m2/day in the stressed wheat and also reduced the number of tillers bearing ears by 55% (Turner, 1966). Aspinall et al. (1964), Bingham (1966), Campbell et al. (1969), Day and Intalap (1970), and Fischer (1973) have all reported reductions in ear-bearing tillers in wheat, and Blum (1973) and Bagga et al. (1973) have reported a reduction in panicle numbers in sorghum.

191

CROP WATER DEFICITS

N

E

\

a

1000

c

I

I

I

100

150

200

Water stress applied to W,

W

s 2

z

0

50

DAYS FROM SEEDLING EMERGENCE

FIG. 4. Changes in the number of tillers and ears with time in a wheat community. The soil was either kept near field capacity (W,) or watering was restricted OK,) from the time denoted by arrow (from Turner, 1966).

An interesting effect of water stress during inflorescence development has been observed recently in maize (Damptey and Aspinall, 1976). A water deficit of -1 1.5 bars during the period of initiation and early development of the male inflorescence (tassel) reduced its subsequent growth rate and final size, and also produced 2 to 3 mature female cobs instead of the normal single cob when no stress was applied. The authors suggest that the multiple axillary cob growth is normally inhibited by plant factors originating in the tassel and that the water deficit modifies this inhibition. In the determinate cereals, water stress prior to ear emergence also influences the number of grains set per spikelet. Fischer (1973) showed that the period 5-15 days before ear emergence in wheat was the most sensitive stage and that as Jlplant decreased below -12 bars fewer grains were set per spikelet. It has been shown that anther development and meiosis (Henckel, 1964; Bingham, 1966) are particularly sensitive to stress, although defoliation (Turner, 1966) and shading (Fischer, 1973) suggest that the fall in grain numbers per ear may not arise from water stress per se but from a deficiency of carbohydrates in the developing ear and florets. Photosynthesis of ears, stems, and leaves during the grain ffling period is generally recognized as the major contributor to grain yield in the cereals (e.g., "home, 1966; Allison and Watson, 1966; Evans et ul., 1975). A reduction in photosynthesis or of the photosynthetic surface by water stress should lead to a reduction in yield. For example, Fischer and Kohn (1966~)showed that the yield of field-grown wheat was inversely correlated with the rate of senescence

192

JOHN E. BEGG AND NEIL C. TURNER

of photosynthetic tissue after anthesis when soil moisture deficits induced senescence. However, in a later study, also with wheat, Fischer (1973) showed little reduction in yield arising from short but severe deficits imposed approximately 15 days after ear emergence: presumably the potential for compensation for short periods of stress in the grain filling period is high.

C. YIELD COMPENSATION In Section IV,D, it was pointed out that during recovery from a temporary water deficit, the apparent rate of development, expansion, or growth was greater than that in the controls of the same chronological age. Similarly, during floral development, alleviation of stress results in a more rapid development of the floral organs whose development was hindered by stress. For example, Nicholls and May (1963) showed that in barley the rate of primordia production of the apex was reduced by a soil water deficit, but alleviation of stress caused an accelerated rate of primordium formation so that the final number of primordia and the apex length were the same as the controls. Gates (1968) showed that the lupin apex responded in a similar manner and Damptey and Aspinall (1976) showed a rapid development of the female axillary inflorescence in maize after a delay due to water deficit at tassel initiation. However, in determinate annuals, if an ear has not emerged, florets have aborted or fertilization has been incomplete, compensation by producing more ears, florets, or fertilized flowers is out of the question. Depending on the stage and degree of loss, however, compensation can occur such that yield need not be reduced. For example, Blum (1973) and Bagga et al. (1973) both showed that when the number of panicles of sorghum was reduced by drought stress, the weight of grain per panicles could be increased by either an increase in the number of grains per panicle (Blum, 1973) or by larger grains (Bagga et al., 1973). Similarly, a reduction in the number of grains set can be compensated for by larger and heavier grains (Turner, 1966), but there is evidence that a genotype has a maximum grain size (Fischer, 1973; Gallagher et al., 1975), so the potential for compensation by increasing grain size or weight is limited. In the previous section it was pointed out that the rate of photosynthesis and the size of the photosynthetic surface after anthesis were considered important in determining yield in cereals. Until recently, the contribution of assimilates other than current photosynthate was considered to be a small component of yield (See Thorne, 1966). However, Yoshida (1972) cited several studies with limited nitrogen fertilization of rice in which up to 40% of the final grain yield was translocated from the stem, and Gallagher er ul. (1975) showed that up to 70% of the final grain yield in barley was translocated from the stem under extreme conditions. Wardlaw (1967) showed that under water stress, wheat

CROP WATER DEFICITS

193

translocated assimilates from the stem and lower leaves to the grain to compensate for the loss of flag leaf photosynthesis. The importance of this is highlighted by Passioura (1976). He showed that about two thirds of the final grain weight came from redistribution of assimilates after anthesis and only one third from current assimilation in the period after anthesis in severely stressed wheat plants grown on a limited amount of stored water. The degree of variation in redistribution of assimilates to the grain under water stress clearly warrants further study.

D. INTERACTION BETWEEN NUTRIENT DEFICIENCY AND WATER DEFICIT

A reduction in the uptake of nitrogen and phosphorus induced by a water deficit has been well documented (Gates, 1957; Storrier, 1965; Turner, 1966; Greenway et al., 1968, 1969; Klepper and Greenway, 1968; Greenway and Klepper, 1969). The uptake of several other elements also has been shown to be reduced by water stress (Greenway and Klepper, 1969; Gates, 1974). Greenway et al. (1969) showed that the uptake of phosphorus was reduced slightly when the potential of the root medium was reduced to -2 bars and decreased linearly as the potential of the root medium was reduced further, until at -10 bars phosphorus uptake was negligible. The recent steep increases in the cost of nitrogenous fertilizers has refocused attention on nitrogen fixation by legumes as in alternative source of nitrogen: the work of Sprent and colleagues has shown that the nitrogen-fixing ability of legume root nodules is greatly influenced by the availability water to the host plant (Sprent, 1971, 1972; Engin and Sprent, 1973; Pankhurst and Sprent, 1975). In the most recent research report, Pankhurst and Sprent (1975)showeda rapid fall in nitrogen fixation, measured by the acetylene reduction technique, of detached soybean nodules when the apparent $nodule fell from -2 bars to -20 bars. The authors showed that, at a $nodule of -8 bars, but not at more severe deficits, the nitrogen-furing ability of detached nodules could be restored by increasing the availability of oxygen, suggesting that water stress induced a physical barrier to oxygen diffusion. Similar reductions in activity were also observed in attached nodules with an increase in soil water deficit (Engin and Sprent, 1973). For a fuller review of this topic, readers are directed to Sprent (1976). These results clearly suggest that the reduced growth observed as a result of moderate water deficits may, in part, arise from a disturbance in mineral nutrition as well as any direct effect of water deficits. The implications of this for the field are obvious. Nutrient levels in the field are usually highest near to the surface that is the first part of the soil profie to dry in a drying cycle.

194

JOHN E. BEGG AND NEIL C. TURNER

Although the plants may have roots penetrating the deeper and wetter part of the soil profie, the relative lack of nutrients in the subsoil and the unavailability of nutrients in the dry surface soil may limit growth and yield more than the soil water deficit per se. This was well illustrated in a study reported by Garwood and Williams (1967). They showed that when the soil surface was dry, injection of nutrients, particularly nitrogen, at a depth of 45 cm substantially increased the dry matter of herbage produced by a perennial ryegrass sward over that produced by a similar sward given a surface application of nitrogen (Table I). Simpson and Lipsett (1973) observed a similar response of alfalfa yields to deep placement of phosphorus under conditions of simulated surface drought: yield increases from deep placement of phosphorus were only observed when the soil was also amended by addition of borate and lime that stimulated lateral root proliferation in the amended layer. The soil nutrient status can also markedly influence the water use by crops, and hence the time of onset of drought stress where soil water is limited, or the strategy for irrigation where water supply is not limited. In situations of limited water supply, heavy nitrogen fertilizer use, or growth of wheat after a legume have been shown to produce vigorous vegetative growth that depletes soil water and can lead to a lower yield than with low fertilizer application (Barley and Naidu, 1964; Fischer and Kohn, 1966a,b,c; Bond et al., 1971). For example, Barley and Naidu (1964) showed that in a dry season with soil of medium fertility, wheat yields were 15 to 33%lower after the application of 130 kgba of nitrogen than when no additional nitrogen was applied, while Fischer and Kohn (1966a,b) showed that application of nitrogen increased the leaf area and evapotranspiration in the vegetative phase and reduced the available soil water in the root zone at ear emergence and leaf RWC during grain filling. Similarly, Fisher (1970) showed that application of phosphorus to Townsville stylo swards reduced the ability of the sward to withstand extended periods of drought due to earlier soil water depletion. In the indeterminate crop, cotton, Hearn (1975b) observed that in a dry tropical environment there was little advantage as far as lint yield was concerned in supplying high levels of nitrogen unless watering was prolonged, because heavy nitrogen fertilization prolonged flowering and increased the boll maturation period. Thus, nitrogen and phosphorus both influence water use in different ways, i.e., by increasing leaf area and prolonging development or by increasing root proliferation, but both can have detrimental effects on yield when soil moisture is limited. Potassium has yet another effect on water use. Potassium deficiency reduces stomatal conductance and transpiration, as shown by Peaslee and Moss (1966, 1968), at levels of extractable potassium below 2 mg/g fresh weight. Since potassium is involved in stomatal opening, the deficiency of potassium was thought to act directly on the guard cells. However, Graham and Ulrich (1972) have shown that potassium deficiency also reduces the water permeabil-

195

CROP WATER DEFICITS

TABLE 14 Herbage Yields on 8 September from a Perennial Ryegrass Pasture Given 55 kg N, 28 kg K, and 35 kg P per ha on 30 July and 13 August either as a Surface Application or Injected at 45 cm, Compared with Controls Given No Fertilizer. The Surface Soil at Harvest Was Dry Yield (kdha)

Surface application Injected at 45 cm

Control

Fertilized

490 480

590 1350

“Adapted from Garwood and Williams (1967).

ity of roots of sugar beet, thereby lowering the $leaf under a transpirational load. Although the authors do not clearly demonstrate that the lowered +leaf is sufficient to induce stomatal closure, they do infer that the observed stomatal closure in potassiumdeficient plants arises indirectly from the lowered $14 and not from a lack of potassium per se in the guard cells. Thus a good supply of potassium in the soil will increase the rate of water loss by the crop and increase root permeability to water. VII. Water Use Efficiency

The water use efficiency WE) of field crops is often discussed in very broad and nonspecific terms. The definition used here is

WUE =

dry weight produced evapotranspiration

Water use efficiency can be expressed in various units, such as pounds or tons of dry weight produced or marketed per acre-inch of evapotranspiration (Viets, 1966), grams of dry matter per kilogram of water used (Ritchie and Burnett, 1971), or as a simple ratio, of say, kilograms of dry weight per kilogram of evapotranspiration. When expressed in the latter dimensionless form, it is similar to the reciprocal of the older term, transpiration ratio, except that WUE also includes the water evaporated from the soil surface as well as that transpired by the plant. Many authors have expressed WUE in terms of the transpiration ratio (e.g., Burton, 1959; Kramer, 1959; Slatyer, 1964). This can be confusing since

196

JOHN E. BEGG AND NEIL C. TURNER

W E increases as the transpiration ratio decreases and it is not always clear whether the ratio is based on transpiration or evapotranspiration data. If it is based on transpiration, the ratio overestimates WUE, or gives a lower transpiration ratio, than that based on evapotranspiration, particularly at an early stage of growth when a large fraction of the water used in the field is lost through direct evaporation from the soil rather than being transpired by the plant (Ritchie, 1974). Transpiration ratios calculated from rates of transpiration and net photosynthesis further overestimate WUE as the ratio based on the weight of COz in gas exchange measurements is approximately two thirds of that based on dry matter. Water use efficiency and drought resistance (Section V,A) are often taken loosely as synonymous, although they are frequently unrelated (Hsiao and Acevedo, 1974; Reitz, 1974). WUE refers to a parameter of yield, total or harvestable per unit of water used, and a major objective of research in this area is to attain high WUE while maintaining high productivity. However, in drought resistance the emphasis is frequently on survival during periods of stress resulting from low water supply, and the high radiation, temperature, and evaporative demand conditions often associated with drought. In many cases the ability to withstand severe moisture stress is negatively correlated with productivity (Jarvis and Jarvis, 1963; Begg and Jarvis, 1968; Reitz, 1974), and many species such as jojoba [Simmondsiuchinensis (Link) Schneider] and other desert shrubs that can tolerate severe stress do not make efficient use of water in the absence of stress (Maximov, 1929; McGinnies and Arnold, 1939; Levitt, 1972). There are, of course, other species well adapted to the stresses of desert environments that do make efficient use of available water. An outstanding group of plants in this context is the succulents which exhibit carassulacean acid metabolism and the associated pattern of nocturnal stomatal opening and daytime closure. Transpiration is reduced more than photosynthesis and WUE is higher than for most other species (Slatyer, 1964; Neales, 1970). The WUE of field crops has increased considerably over the past fifty years. This has been achieved largely through increasing crop yields rather than through any appreciable conservation of water use (Pendleton, 1966). The yields of wheat, barley, rice, cotton, and soybeans have doubled, while those of corn sorghum and tobacco have trebled in the United States over the last fifty years (Anonymous, 1972) without a concomitant increase in water consumption. The contribution from cultural practices in increasing yield and W E have been reviewed recently; tillage and water conservation by Bertrand (1 966), fertilizer application by Black (1966) and Viets (1966), control of weeds, disease, and insect pests by Pendleton (1966); these studies will not be considered here. In general any cultural practice that reduces the limitations to growth imposed by factors other than water will increase the WUE.

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197

A. PLANT FACTORS

1. Species

Plants have been classified into two main groups, C3 and C4 species, according to the number of carbon atoms in the molecule of the first carboxylation product of photosynthesis (Hatch and Slack, 1966, 1970; Hatch ef al., 1967; Hatch, 1976; Hatch and Osmond; 1976). The occurrence of C4 photosynthesis among plants has been recently reviewed by Downton (1975). It is now well established that WUE of C4 species is generally twice that of C3 species (Downes, 1969, 1970; Slatyer, 1970; Bjorkman, 1971; Downton, 1971; Ludlow and Wilson, 1972; Teare ef al., 1973; Ludlow, 1976). This difference between C3 and C4 species increases with temperature over the range 2Oo-3S0C (Bjorkman, 1971), and is evident at the leaf, individual plant, and sward level when comparing C4 pasture grasses with C3 legumes (Ludlow, 1976). The field data of Shantz and Piemeisel (1927) when grouped into C3 and C4 species also clearly illustrates this twofold difference for the subgroups dicots and grasses (Table 11). Factors contributing to the higher WUE of C4 species include their generally higher photosynthesis and growth rates, particularly under high light and temperature (Downton, 1971; Bjorkman, 1971) and their higher stomatal resistance (Slatyer, 1970; Downes, 1971; Turner and Incoll, 1971; Ludlow, 1971; Turner and Beg, 1973; Turner, 1974a,b; Gifford, 1974), resulting in a relatively greater reduction in transpiration than photosynthesis. Thus over a wide range of

TABLE I1 Water Use Efficiency Cp Dry Wt/kg of Water) for a Number of C, andC, Speciesa Water use efficiency Cplkg)

Dicots Grasses

C, species

C, species

3.44 3.14

1.59 1.49

“Data from field experiments at Akron, Colorado, 1911-1917 (Shantz and Piemeisel. 1927), regrouped by Downes (1969).

198

JOHN E. BEGG AND NEIL C. TURNER

environmental conditions the WUE of C4 species is superior to that of C3 species, and is achieved under high light and temperature as a result of higher rates of photosynthesis and under low light conditions as a result of lower rates of transpiration (Downton, 1971). By growing C4 crops in high energy regions or seasons and restricting the growth of C3 crops to temperate humid regions or seasons,WUE can be increased.

2. Plant Breeding The selection and breeding of higher yielding varieties and hybrids has greatly increased the W E of a wide range of crops. In relatively recent years some outstanding examples of crop improvement have come from the hybridization of normally cross-pollinated plants, such as maize, sorghum, and forage grasses. It has been estimated (Pendleton, 1966) that hybrid maize increased WUE by about 20% in the original comparisons, and with the advent of more intensive cultural practices this has been further increased. This approach is also being attempted with several highly self-pollinated crops such as small grains, cotton and soybeans. Another approach has been the development of earlier maturing varieties. Cotton provides a good example of what can be achieved (Namken et al., 1974). Varieties that mature in 120 to 130 days after planting, compared with 150 to 180 days for conventional varieties, were developed for use in narrow-row, high population planting systems which require a short statured plant. The increased plant population compensated for the reduced yield potential per plant, so that yield per hectare was at least maintained and in some cases was increased by 5 to 15% compared with conventional plantings. Namken et al. (1974) calculated the total evapotranspiration for two cotton production systems, each producing approximately 1000 kg lint per hectare. They found that the short season, narrow-row, high population planting system used approximately 20% less water than the conventional system, i.e., a 25% increase in WUE. Another way of reducing crop water use is to grow the crop under a lower thermal or energy regime, by moving the growing season to a cooler or lower potential evapotranspiration period of the year. This involves selection or genetic modification to increase cold tolerance during germination and seedling establishment. This is being attempted with crops such as potatoes (Richardson and Weiser, 1972) and cotton. The C4 crops with their economy of water use also provide the plant breeder with a challenge to extend their range of adaptation to cooler climates. Some C4 grasses have become adapted to temperate areas, and Duncan and Hesketh (1968) have shown that races of maize from high altitudes were better adapted to cool temperatures. Plant breeders have also contributed to yield stability and increased WUE through the development of disease and insect

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resistant varieties, for example, rust resistant and Hessian fly resistant wheat varieties.

B. ANTITRANSPIRANTS Another approach to the improvement of WUE by plants has been through the use of foliar sprays or coatings to reduce transpiration. The objectives are (1) to increase stomatal resistance so that transpiration is reduced relatively more than photosynthesis, or (2) to reduce water use and the likelihood of severe water deficits developing during a critical stage of growth, or (3) to reduce water loss during the final stage of fresh weight development in fruit and increase fruit size, or (4) to increase the yield of water from watersheds by reducing transpirational losses from vegetation. A number of different materials have been used to retard transpiration and these may be grouped under three headings according to their mode of action, i.e. those that (1) close stomata, (2) are film forming, or (3) increase plant reflectivity (Gale and Hagan, 1966).

I . Stomata1 Closing Compounds The theoretical basis for closing stomata as a means of reducing transpiration relatively more than photosynthesis has been described by Zelitch (1961,1964), Zelitch and Waggoner (1962a,b), Waggoner and Zelitch (1965), and Waggoner (1966). Shimshi (1963) and Slatyer and Bierhuizen (1964) present resistance data indicating that under certain conditions a decrease in stomatal conductance will reduce transpiration relatively more than photosynthesis and should increase WUE. An important qualification to this statement is that with a reduction in transpiration as a result of decreased stomatal conductance the leaf is shifted to a higher thermal regime with higher temperatures and water vapor pressures at the evaporating surfaces. However, Gale and Hagan (1966) and Poljakoff-Mayber and Gale (1972) conclude that only under extreme conditions of high incident radiation and very low windspeed would leaf temperature rise more than 2" or 3°C above air temperature as a result of a 40-50% reduction in transpiration. This will tend to increase the transpiration and respiration rate and may decrease WUE. Many spray materials commonly applied to plants close stomata and reduce transpiration. These effects have been reported for herbicides, fungicides such as phenylmercuric acetate (PMA), metabolic inhibitors, and growth hormones (Gale and Hagan, 1966). Zelitch (1967) evaluated the effect of several inhibitors on stomatal opening. The most promising then were PMA and certain alkenylsuccinic acids, but subsequent work showed that PMA reduced growth more

200

JOHN E. BEGG AND NEIL C. TURNER

than water use (Waggoner and Turner, 1971). The main problem with antitranspirants of the stomatal closing type is to obtain nontoxic materials that only affect the stomata and which are long lasting (Poljakoff-Mayber and Gale, 1972). Abscisic acid is a nontoxic plant hormone that closes stomata (Section IV,C; Raschke, 1975); it has recently been shown to be effective in increasing WUE in wheat and barley seedlings grown in pots in the glasshouse (Jones and Mansfield, 1970), although it proved to be ineffective in field trials (Mizrahi et al., 1974). Where water yield is more important than plant growth as in water catchments, stomatal closing compounds such as PMA that decrease WUE have been shown to be effective (Waggoner and Bravdo, 1967; Turner and Waggoner, 1968; Waggoner and Turner, 1971). 2. Film-Forming Compounds Film-forming polymer materials have been sprayed on plants to provide a physical barrier over some, if not all, the stomata and to reduce transpiration. This increases leaf water potential and results in wider stomatal apertures immediately under the film,as well as on those parts of a partially treated leaf not covered by the frlm (Davenport et al., 1974a). Photosynthesis is also reduced, but whether the growth of a particular plant part is reduced or increased depends on whether current photosynthesis or plant water potential is more important for its development. Thus the application of film forming antitranspirants during the final stage of fresh weight development in fruit increases the fresh weight and size of the fruit (Davenport et al., 1972, 1973, 1974a,b). There appears to be little chance of finding a polymer with selective permeability in favor of carbon dioxide since the coefficient of diffusion of gases and vapors in polymer films is inversely proportional to their molecule weight (Waggoner, 1967; Poljakoff-Mayber and Gale, 1972). This means that photosynthesis will be depressed as much or more than transpiration. However, this is not so important in the context of the sizing of fruit, the protection against water stress during a critical stage of growth, the protection against dehydration of evergreens when soil temperatures are low (Turner and De Roo, 1974), and increasing the yield of water from watersheds (Waggoner and Turner, 1971). 3. Reflecting Materials

This is a basically different approach to the problem of reducing transpiration. The objective is to apply a reflective pigment to increase the albedo and thus decrease the net radiation load and the leaf temperature. By developing pigments that selectively reflect radiation below 400 nm and above 700 nm, it should be

CROP WATER DEFICITS

20 1

possible to reduce transpiration without affecting photosynthesis and thus increase WUE (Gale and Hagan, 1966; Davenport et al., 1969; Poljakoff-Mayber and Gale, 1972). Preliminary work suggests that this could be a promising technique (Baradas et al., 1974).

C. ENVIRONMENTAL CONTROL

1. Windbreaks The transfer of sensible heat to the surface of a crop by advection is a significant source of the energy used in evapotranspiration. The amount of advection varies with season and location and in some situations a third of the energy used in evapotranspiration comes from advection (Hagen and Skidmore, 1974). Windbreaks, through a reduction in windspeed reduce the amount of advective energy brought to the leaves and increase the water vapor content of the air near the leaves (Stoeckeler, 1962; Rosenberg and Brown, 1973). Thus transpiration is reduced, photosynthesis may benefit from an increase in stomatal conductance, and WUE is increased. The use of tall crop plants to shelter a lower growing crop is discussed by Hagen and Skidmore (1974). The choice of crop variety for sheltering lower growing crops depends on the water available. For dryland conditions the highest yielding varieties may be those that minimize vegetative growth and conserve water until the critical period. Such varieties should not be too tall and thus susceptible to lodging and should have high disease resistance. In areas where soil moisture is expected to be adequate throughout the growing season, maize has been used as a windbreak for soybeans and given yield increases of 10 to 30% (Radke and Burrows, 1970).

2. Fertilizing with Carbon Dioxide Fertilizing with C02 has been proposed many times as a means of increasing WUE. High concentrations of COz increase photosynthesis and simultaneously tend to decrease stomatal conductance and reduce transpiration. The effect of C02 in both decreasing transpiration and increasing photosynthesis has been demonstrated for maize (Moss et al., 1961). In this sense COz may be considered to be an ideal antitranspirant as it operates favorably on both the numerator and denominator of WUE [Eq. (S)] . While attempts to achieve this have generally been unsuccessful under most natural field crop conditions because of rapid gaseous exchange with the bulk atmosphere (Waggoner, 1969; Allen et al., 1974), it is an attractive method for increasing the WUE of greenhouse crops (Wittwer, 1967; Pallas, 1970). Class or plastic greenhouses also provide a means

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of maintaining high humidity in the air around the plant, thus reducing transpiration and increasing WUE. VIII. Differences in Response of Plants Grown Under Controlled Conditions and in the Field

There is an increasing body of evidence building up in the literature indicating that the response functions of plants grown in controlled environments differ from those grown in the field, particularly in response to water deficits (Evans, in press). For example, the growth responses of maize, sunflower, and soybean to a decline in plant water potential in growth chambers reported by Boyer (1970a) and Acevedo et d. (1971) differ from those of field-grown plants (Cary and Wright, 1971; Ritchie, 1973, 1974; Burner and Begg, 1973; Watts, 1974). The growth chamber data indicated a marked reduction in leaf expansion in maize as $leaf decreased from -2 to -4 bars with complete cessation of growth at -7 to -9 bars, whereas the field data have shown that a decline in leaf water potential to -8 or -9 bars had little apparent effect on the rate of leaf expansion (Fig. 5 ) and leaf growth did not cease until about -17 bars in sorghum (McCree and Davis, 1974). The data of Watts (1974) and McCree and Davis (1974) also indicated that leaf expansion continued day and night at the same rate despite a diurnal change in leaf water potential from -1 to -7 or -9 bars. This apparent insensitivity of field-grown plants to low J,w could be due to differences in and to gradients of J, within the leaves. Cells enlarge in response to the turgor component of J,; thus the field and controlled environment plants may have similar P values at these differing values of J, if the osmotic potentials were lower under the higher light environments of the field (Section V,B). In addition, large gradients in water potential can develop in actively transpiring leaves in the field (Yang and de Jong, 1971), so that the water potential measured on the exposed leaf lamina would have been lower in the field plants than the water potential at the base of the leaf where cell enlargement was taking place. The possibility of osmotic adjustment and the development of rl, gradients would have been minimal in Boyer’s work as the plants were placed in a dark humid chamber in order to measure the mean rate of leaf enlargement over a 24hour period at a constant leaf water potential. Both Boyer (1970a) and Acevedo et al. (1971) have shown that as stress developed leaf growth stopped before photosynthesis was noticeably affected, and that photosynthesis declined markedly below -8 bars and was very low at -16 bars. As was the case with leaf growth, the water potential at which photosynthesis and stomatal conductance rapidly decline, is lower in field-grown plants. Jordan and Ritchie (1971) found that the stomatal conductance of cotton declined rapidly in growth chamber plants at -16 bars while the stomatal

,

CROP WATER DEFICITS I

I

203

I

I . A

/

,’

A/ I

I I*

0

ALA I

I I

I

0

0

0 0 0

0

I

I

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LEAF WATER POTENTIAL (bars)

FIG. 5. Relationship between leaf extension and leaf water potential for maize grown in the field (o), or grown in controlled environments in the dark at 28°C (e), or in the light at 30°C (A) (from Watts, 1974).

conductance of field-grown plants remained high even at leaf potentials of -27 bars. Similar differences in response by field and growth room plants have been reported for maize (Ritchie, 1973), sorghum (McCree, 1974), and vines (Kriedemann and Smart, 1971) and have been discussed by Turner (1974a), Ritchie (1974), and Ludlow (1976). Ludlow and Ng (1976) determined response functions for green panic (Pant cum maximum var. trichoglume) grown in pots in controlled environment rooms and outdoors. The growth chambers were programmed to simulate the average outdoor values for daylength, maximum and minimum temperature, and relative humidity. Photosynthetically active radiation was 66% of that received outdoors during a 3-week period without rain. The leaf water potentials at which stomatal conductance decreased substantially (-6 bars) and at which both leaf elongation and net photosynthesis ceased (ca. -12 bars) were similar for both growth room and outdoor potted plants. Thus any possible difference in response by growth room versus field-grown plants that may be associated with the constancy or “artificiality” of square wave “climates” in controlled environments could be minor compared with the differences associated with restricting the roots in small containers and thus accelerating the rate of onset of stress when water is withheld.

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A number of workers have drawn attention to the differences between pot experiments and studies carried out on deep field soils in terms of the rate of development of moisture stress: Hagan et al. (1957), Fischer and Hagan (1965), Salter and Goode (1967), Jordan and Ritchie (1971), Ritchie (1974), and Ludlow and Ng (1976). The roots of field-grown plants usually have access to larger volumes of soil than those growing in small pots and once most of the water in surface horizons has been extracted, more water is obtained as the plant grows and roots extend into deeper soil. Even when the roots reach the lower parts of the soil profile, more water is extracted from the upper part of the profile because the root density is usually greater and the specific free energy of the water near the surface makes it more accessible than water deep in the profile. Thus the development of stress during a drying cycle is more gradual in a field-grown plant, and the possibility of overnight recovery is greater as it may still have access to water in the lower part of the profile. Whereas in the small pots used in most growth chamber and glasshouse experiments, the root density is high and the entire root system of the plant is subjected to a uniformly increasing moisture stress with relatively little capacity for overnight recovery during a drying cycle. Thus the plant water potential decreases rapidly and the plant experiences a severe water deficit as evidenced by stomatal closure and marked reduction in photosynthesis. In the field, the more gradual transition from mild to severe stress allows time for further root development and osmotic adjustment (Section V,B) during the early stages of stress when the rate of cell enlargement and possibly leaf area is reduced, but not the rate of photosynthesis. The point missed by many shortterm physiological experiments is that there is more time for field-grown plants to adapt to developing stress, and that in a field crop, growth is initially reduced by a reduction in leaf area well before there is a reduction in photosynthesis (Fischer and Hagan, 1965). Also any reduction in leaf area causes an irreversible reduction in growth in a determinate plant, whereas a reduction in the rate of photosynthesis is only temporary and photosynthesis can recover on relief of stress. Thus one of the major limitations of controlled environments for plant-water relations studies could be overcome by using soil containers that allow for more realistic root development in volume and depth. This is not to detract from the importance of providing higher light in the photosynthetically active, 400-700 nrn waveband, and more realistic soil temperatures in controlled environments. In this context the thermal mass of a large volume of soil will assist in achieving more realistic soil temperatures in growth rooms. A consequence of osmotic adjustment and the differences in response between field and controlled environments is that much of the data obtained in controlled environments cannot be applied directly to the field situation. For example, from the controlled environment studies of Boyer (1970a,b), both

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stomata1 conductance and the rate of photosynthesis in maize decreased at values of $leaf below -8 bars and were very low at -16 bars. Thus, at values of $leaf of -12 to -15 bars observed in well-watered maize in the field, stomata might be expected to be closed and photosynthesis low; this was not the case (Turner and Beg, 1973). An example of the application of controlled environment data to the field situation leading to an unlikely conclusion is provided by Reicosky et al. (1975). They concluded that in maize, ‘‘leaf growth rate decreased considerably as the sun rose, almost stopped by 0800, and did not resume till almost sunset.” This conclusion was based on the controlled environment data of Boyer (1970a) and Acevedo et al. (1971) indicating that the leaf elongation rate in maize was essentially zero at values of $leaf below -7 bars, and their own field measurements of $leaf. However, in the light of field observations by Watts (1974) showing no apparent effect of $leaf values above -9 bars on leaf elongation rate, it is unlikely that elongation ceased during the day in their study. Clearly, simulators of crop growth and development in the field must use caution when making use of short-term response data obtained from plants grown in controlled environments. I X . Summary and Conclusions

Since the 1950s, when the emphasis was on the measurement of soil water stress and attempts were made to relate plant growth to these measurements, the emphasis has moved to the measurement of plant water potential following the realization of the importance of atmospheric demand in determining plant water deficits. The total water potential concept has greatly increased our understanding of the movement of water through the soil-plant-atmosphere continuum in response to gradients in water potential, and of the soil, plant, and atmospheric factors that influence the development of water deficits in plants. However, it is still frequently stated in the literature that “a water deficit occurs whenever water loss exceeds absorption” implying that water deficits only occur under these conditions. This ignores the fact that once such a deficit develops it will be maintained while transpiration equals absorption, that a decreasing deficit will persist during the recovery phase when absorption exceeds transpiration, and that all actively growing and transpiring plants experience some degree of water deficit. Whether or not growth and development processes are temporarily or permanently affected will depend on the degree and duration of the water deficit and the ability of the plant to adapt during development of the deficit. The use of total water potentid as the best single indicator of plant water status has its limitations when attempting to understand the effect of water deficits on the various physiological processes involved in plant growth. For example, plant growth is controlled directly by the components of the total

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water potential and only indirectly by the total water potential. Water potential is important in bringing water to the cell (Gale, 1975); once there, the turgor pressure and osmotic potential become important for growth (Wiebe, 1972). The turgor component is important in cell expansion and cell division, the osmotic component influences cell metabolism and enzyme activity, and the matric component also has a marked influence on seed germination. Steep gradients in water potential can develop in plants as they become stressed; thus it is important when studying the effect of water stress on plant growth that the water potential and its components are measured in the tissues where the growth process is taking place. This has not been done when studying the effect of water stress on leaf expansion in grasses. Also if the particular process occurs in relatively few cells, for example, the guard cells of stomata, then the measurement of leaf water potential and its components provides only an indication of the potentials in those cells. One of the major difficulties in extrapolating from controlled environment studies to field conditions appears to be related to the more rapid development of severe water stress by plants growing in small containers. This rapid develop ment of stress, under relatively low light provides little opportunity for plants to adapt through morphological and physiological mechanisms such as an increase in root growth or in osmotic potential. When stress develops slowly there is more time for osmotic adjustment to occur and maintain sufficient turgor pressure for the continuation of growth processes such as photosynthesis, cell division, and cell elongation. Studies involving the rapid development of stress emphasize the response functions of those processes such as stomatal closure, photosynthesis, and transpiration that operate on a relatively short-time scale and provide little or no information on processes such as leaf area development and root growth, which take place on a time scale of days or weeks. Thus water stress may reduce photosynthesis dramatically for a short period but upon rewatering photosynthesis recovers, whereas a gradual and possibly irreversible reduction in leaf area can have a significant effect on growth, development , and yield. On the other hand, there are few examples of field studies in which both water stress parameters and growth, development, and yield characters have been measured on the same crop, so that it is difficult to determine the morphological and physiological mechanisms responsible for reduced yields in most field studies. Greater emphasis needs to be placed in controlled environment studies on more closely mimicking stress conditions in the field, and in agronomic studies on the measurement of physiologically meaningful parameters. Plant breeding has provided some outstanding examples of crop improvement in terms of yield, disease resistance, and WUE. The most impressive gains have come from crops grown under irrigation or in favorable rain-fed natural environments. Further gains appear possible in less favorable rain-fed environments through the development of short-season, early maturing varieties, that enable an

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economic yield to be achieved by avoidance of severe water stress. As future gains become more difficult to achieve it will require a systematic approach with coordinated contributions from plant breeders, crop physiologists, agronomists, and others to design a workable system that the growers can readily adapt to their needs.

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Turner, N. C. 1974a. R. SOC.N. Z., Bull. 12,423432. Turner, N. C. 1974b. Plant Physiol 53,360-365. Turner, N. C. 1975. Plant Physiol. 55,932-936. Turner, N. C. 1976. J. Exp. Bot. 27 (in press). Turner, N. C., and Begg, J. E. 1973. Plant Physiol. 51, 31-36. Turner, N. C., and Begg, J. E. 1974. Aust. C.S.I.R.O., Div. Plant I n d , Annu. Rep. p. 102. Turner, N. C., and Begg, J. E. In “Plant Relations in Pastures” (J. R. Wilson, ed.). CSIRO, Melbourne (in press). Turner, N. C., and De Roo, H. C. 1974. For. Sci. 20, 19-24. Turner, N. C., and Parlange, J.-Y. 1970. Plant Physiol. 46,175-177. Turner, N. C.. and Incoll, L. D. 1971. J. Appl. Ecol. 8,581-591. Turner, N. C., and Waggoner, P. E. 1968. Plant Physiol. 43,973-978. Turner, N. C., De Roo, H. C., and Wright, W. H. 1971. Conn., Agric. Exp. Stn., New Haven, Spec. Soils Bull. 33,l-9. Tyree, M.T., Dainty, J.,and Hunter, D. M. 1974. Can. J. Bot. 52,973-978. Uriu, K. 1964. R o c . Am. SOC.Hort. Sci. 84,93-97. Vaadia, Y., Raney, F. C., and Hagan, R. M. 1961. Annu. Rev. Plant. Physiol. 12,265-292. Van Bavel, C. H. M. 1967. Agric. Meteorol 4,165-176. Van Bavel, C. H. M., Nakayama, F. S., and Ehrler, W. L. 1965. Plant Physiol. 40,535-540. Van den Honert, T. H. 1948. D&cuss. Faraaky SOC.3,146-153. Van Haveren, B. P., and Brown, R. W. 1972. In “Psychrometry in Water Relations Research” (R. W. Brown and B. P. Van Haveren, eds.), pp. 1-27. Utah Agric Expt. Stn., Logan. Viets, F. G. 1966. In “Plant Environment and Efficient Water Use” (W. H. Pierre e t al., eds.), pp. 259-274. Am. SOC.Agron. and Soil Sci. SOC. Am., Madison, Wisconsin. Wadleigh, C. H., Gauch, H. G., and Magistad, 0. C. 1946. [IS., Dep. Agric., Tech. Bull 925, 1-34. Waggoner, P. E. 1966. In “Plant Environment and Efficient Water Use” (W. H. Pierre et al., eds.), pp. 49-72. Am. SOC.Agron. and Soil Sci. Am., Madison, Wisconsin. Waggoner, P. E. 1967. BiometeoroL, Roc. Int. Biometeorol. Congr., 4th, 1966, Vol. 3, pp. 41-52. Waggoner, P. E. 1969. In “Physiological Aspects of Crop Yield” (R. C. Dinauer, ed.), pp. 343-373. Am. SOC.Agron., Madison, Wisconsin. Waggoner, P. E., and Bravdo, B. 1967.Proc. Natl. Acad. Sci. U.S.A. 57,1096-1102. Waggoner, P. E., and Turner, N. C. 1971. Conn., Agric. Exp. Stn., New Haven, Bull. 726, 1-87. Waggoner, P. E., and Zelitch, I. 1965. Science 150,1413-1420. Waggoner, P. E., Monteith, J. L.,and Szeicz, G. 1964. Nature (London) 201, 91-98. Waisel, Y. 1962. Physiol. Plant. 1 5 , 4 3 4 6 . Wallihan, E. F. 1964. Plant Physiol. 39,86-90. Wardlaw, I. F. 1967. Aust. J. Biol. Sci 20,25-39. Wardlaw, I. F. 1968. Bor. Rev. 34.79-105. Wardlaw, I. F. 1969. Aust. J. Biol. Sci 22.1-16. Wardlaw, I. F. 1971. Aust. J. Biol. Sci. 24,1047-1055. Warren Wilson, J. 1967. Aust. J. Biol. Sci. 20,329-347. Watts, W . R. 1974. J. Exp. Dot. 25,1085-1096. Weatherley, P. E. 1965. In “The State and Movement of Water in Living Organisms” (G. E. Fog, ed.),pp. 157-184. Cambridge Univ. Press, London and New York. Weatherley, P. E. 1970. Adv. Bot. Res. 3, 171-206. Weibel, R. O., and Pendleton, J. W. 1964. &on. J. 56,487-488.

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Wellburn, A. R., Ogunkanmi, A. B., Fenton, R., and Mansfield, T. A. 1974. Planta 120, 255-263. Wiebe, H. H. 1972. In “Psychrometry in Water Relations Research” (R. W. Brown and B. p. Van Haveren, eds.), pp. 194-197. Utah Agric. Exp. Stn., Logan. Wiebe, H. H., Brown, R. W., Daniel, T. W., and Campbell, E. C. 1970. BioScience 20, 225-226. Wiebe, H. H., Campbell, G. S., Gardner, W. H., Rawlins, S. L., Cary, J. W., and Brown, R. W. 1971. Utah, Agric. Exp. Stn., Bull 484,l-71. Willis, A. J., and Balasubramaniam, S. 1968. New Phytol. 67,265-285. Wttwer, S. H. 1967. Int. Hort. Congr. Proc., 17th Congr. 3, 311-322. Woodruff, D. R. 1969. Aust. J. Agric, Res. 20,13-24. Woolley, J. T. 1964. Agron. J. 56,569-571. Wright, S. T. C., and Hiron, R. W. P. 1969. Nature (London) 224,719-720. Wuenscher, J. E. 1970. New Phytol. 69,65-73. Yang, S . J., and de Jong, E. 1971. Con. J. Plant Sci. 51,333-336. Yoshida, S . 1972. Annu. Rev. Pknt Physiol 23,431-464. Zelitch, I. 1961.Proc. Natl. Amd. Sci. U.S.A. 47,1423-1433. Zelitch, I. 1964. Am. SOC.Agron., Spec. Publ. 4,104-113. Zelitch, I. 1967. Am. Sci 55,472-486. Zelitch, I., and Waggoner, P. E. 1962a.Proc. Natl. Acad. Aci. U.S.A. 48, 1101-1108. Zelitch, I., and Waggoner, P. E. 1962b. b o c . Natl. Amd. Sci. U.S.A. 48,1297-1299. Zobel, R. W. 1975. In “The Development and Function of Roots” (J. G. Torrey and D. T. Clarkson, eds.), pp. 261-275. Academic Press, New York.

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USE OF TRACERS FOR SOIL AND FERTILIZER NITROGEN RESEARCH R. D. Hauck and J. M. Bremner Division of Agricultural Development, Tennessee Valley Authority, Muscle Shoals, Alabama, and Department of Agronomy, Iowa State University, Ames, Iowa

I. Introduction .................................................. A. Occurrence and Separation of Nitrogen Isotopes .................... B. Definitions ................................................. 11. Assumptions .................................................. Ill. Advantages and Disadvantages of Nitrogen Tracer Techniques ............. IV. Determination of Nitrogen Isotopes ................................. A. Sample Preparation ........................................... B. Isotope-Ratio Analysis ........................................ C. Calculation of Results ......................................... V. Sources and Cost of Nitrogen Tracer Materials ......................... Vl. Use of Nitrogen Tracer Materials ................................... A. "N-Enriched Materials ....................................... B. '5N-Depleted Materials ....................................... C. Use of Variations in Natural Nitrogen Isotope Abundance ............. VII. Perspective .................................................... References ....................................................

219 220 221 223 225 226 227 230 235 239 242 243 257 259 260 261

I. Introduction

Tracer techniques based on the use of the stable isotope "N are now common in laboratories engaged in nitrogen research. This isotope was discovered about 45 years ago by Naude (1930), and a practical method for its concentration was reported by Urey et al. (1937). Soon thereafter it was used by Schoenheimer et al. (1938) for research on animal metabolism and by Vickery et al. (1939) for research on plant metabolism. The first application of "N in agronomic research was by Norman and Werkman (1943), who used it to study uptake of nitrogen by soybeans. Since this study, more than 1500 papers relating to the use of "N tracer techniques in agronomy and related sciences have been published.

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A. OCCURRENCE AND SEPARATION OF NITROGEN ISOTOPES

Of the six known isotopes of nitrogen, only those having mass numbers 14 and 15 are stable and occur naturally (Table I). The isotope of mass 13 is the longest-lived of the four radionuclides, but its half-life (10.05 minutes) is too short for use as a tracer in most research on biological systems (for examples of such use, see Section VI, A, 1). The stable nitrogen isotopes have been used almost exclusively as tracers in biological systems. Their use as tracers is based on the fact that 14N and I5N occur naturally in an almost constant ratio. Except for slight variations in the nitrogen isotope ratios of natural nitrogenous substances (the significance of which will be discussed later), the ratio of I 4 N to "N is about 272: 1 (i.e., naturally occurring nitrogen contains about 0.366 atom % "N or about 3660 ppm "N). Materials with an unusually high or low concentration of 14N or "N can be used as tracers, provided their nitrogen isotope composition is measurably different from that of unlabeled nitrogen at the time the system under investigation is sampled. Addition of a material with an unusually high or low concentration of "N to a system will result in an increase or decrease in "N concentration in all or part of the system, the extent of change depending on how much tracer was incorporated into the various nitrogenous components of the system. The change in nitrogen isotope ratio in samples obtained from the system permits study of the transformations of the added tracer material. The amount of change in isotope ratio from the background level permits calculation of the extent to which the tracer has interacted with and become part of the system. The chemical properties of 14N and "N are identical. Slight differences in their behavior in biological systems are a function of their difference in mass and, therefore, physical properties. For most tracer studies, these differences can be considered neghgible (for exceptions, see Section VI, C). The commercial separation of the nitrogen isotopes leading to concentration or dilution of "N (i.e., to production of l5 Nenriched and Is Ndepleted materials, respectively) depends on the fact that I4N and "N in the form of ammonia, ammonium ions, or nitrogen oxides behave differently in exchange colums or distillation columns. Until about 1960, "N was concentrated mainly by counter-current exchange of ammonia with ammonium ions, 15N atoms being extracted from ammonia vapor and concentrated in the liquid phase. Currently most "N-concentrating facilities use a system based on the Nitrox process (Taylor and Spindel, 1958, 1960), which involves the exchange of nitric oxide with nitric acid in a two-section cascade system. Recently, the Los Alamos Scientific Laboratory of the United States Atomic Energy Commission (now under the Energy Research and Development Administration) placed into operation a

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22 1

TABLE I Stable and Radioactive Isotopes of Nitrogen Mass number

Natural abundance (%)a

Half-Web

12 13 14 15 16 17

-

0.0125 seconds 10.05 minutes

99.634 0.366 -

-

-

7.36 seconds 4.14 seconds

aFrom analyses of atmospheric nitrogen by Junk and Svec (1958) indicating that the absolute ratio of I4N/"N in atmospheric nitrogen is 272 f 0.3 (% abundance of ''N, 0.3663 f 0.0004). bFrom data compiled by Friedlander and Kennedy (1955).

facility that produces "N-enriched and l5N-depleted materials by cryogenic distillation of nitric oxide. Various small-scale laboratory methods are available for the separation of "N (e.g., see Monse et al., 1961), but all "N separation methods require special apparatus and relatively large amounts of raw materials and/or energy.

B. DEFINITIONS Certain terms relating to isotope chemistry are not always used correctly in reports of biological research in which tracers have been used. A clear understanding of isotope chemistry is essential for accurate interpretation of tracer data which reflect the net results of opposing reactions, so common in biological systems. Following are comments on terms commonly used:

1. Isotope effect. This term refers to the effect arising from mass differences between stable or radioactive isotopes. It is the effect of nuclear characteristics other than atomic number on the nonnuclear chemical and physical properties (size, mass, spin, etc.) of nuclides which lead to variations in the expression of these properties. An isotope effect can be manifested as an isotope shift, as a change in rate of diffusion or reaction, or as change in distribution of isotopes at equilibrium. Bigeleisen and Wolfsberg (1958) and Melander (1960) reviewed the theory of isotope effects in chemical reactions, and their reviews are useful to those using "N-labeled substances to study the kinetic and equilibrium properties of isotopically-labeled materials. Those using "N as a tracer in natural nitrogen transformation studies need rarely be concerned about significant error from differences in reaction rates of 14N and "N, but isotope effects must be

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considered when working in the region of natural variation in nitrogen isotope abundance. Each experimenter should be aware of the conditions under which an isotope effect may be observed and should evaluate its significance in the system under study. 2. Isotope shift. In atomic spectrometry, this phenomenon is observed as a slight difference in wavelength for a given spectral line of one isotope as compared with another. In denitrification studies, it may introduce error in infrared determination of "N-labeled nitrous oxide evolved from soil or other growth media (see Section IV,B). 3. Isotope exchange. This term refers to the exchange of places by two atoms, but different isotopes, of the same element in different molecules. Also, it is the transfer of isotopicallylabeled atoms from one chemical form or valence state to another, without a net chemical reaction taking place. An example of isotope exchange is given by Eq. (1). ISNH,

+14NH,N0, *14NH, +'*NH4NOS

(1)

Note that the exchange is between atoms in ions or molecules and not merely an interchange of ions or molecules, defined subsequently as turnover. Isotope exchange relations involving most nitrogen compounds are insignificant under ambient conditions. They occur to a measurable extent only in systems where there is opportunity for many-fold exchange or where highly active nitrogen compounds such as NH3 or NO are involved. Isotope exchange between NH3 and NH4* reaches rapid equilibrium even at temperatures as low as -60°C. However, no observable exchange occurs between NH4+ and most forms of nitrogen, between NO2- and NO3-, in reactions involving N 2 0 , or between N2 and other nitrogen forms over a wide range of temperatures extending to 1000°C. The inertness of N2 in isotope exchange reactions insures that "Nlabeled samples, unlike samples labeled with the C, H, and O isotopes, will not change in isotopic composition as a result of storing in air. The significance of isotope exchange in particular nitrogen transofrmation processes will be indicated in this review where appropriate. Numerous references to isotope exchange reactions are included in the bibliography compiled by Hauck and Bystrom (1970). 4. 12lmover-Biological and chemical interchange. Although these terms are used in literature concerning nitrogen tracer research, they are not concerned with isotope effects. Turnover is defined here as the continual renewal of a substance without change in its net concentration; turnover is independent of the presence or absence of isotopes. The presence of isotopes in turnover processes permits measurement of the extent and dominant direction of these processes. Turnover may occur when the labeling atoms are incorporated through synthesis, or undergo isotope exchange, or when labeled ions or molecules replace unlabeled ions or molecules, as in transposition from one pool to

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another. Biological and chemical interchange are defined here as specific turnover processes, being functions of biological activity and chemical reaction, respectively. In many soil nitrogen transformation studies, it is not possible to distinguish between biological or chemical interchange and isotope exchange. Where this is possible, it is often impossible to measure accurately the relative contributions of these processes to observed changes in isotope distribution in a system. 5. Isotope dilution. This term refers to the decrease in concentration (as opposed to content) of an isotope in a pool by introduction of ions or molecules of a lower isotope concentration. It is the net consequence of turnover, as is its corollary, isotope concentration. The accurate interpretation of nitrogen tracer data depends on how well the factors that contribute to isotope dilution are understood (see Sections VI,A, 2,3).

I I. Assumptions

Three fundamental assumptions are central to the use of the nitrogen isotopes as tracers in biological systems: (i) Complex elements (those containing two or more isotopes) in the natural state have a constant isotope composition; (ii) living systems can distinguish one isotope from another of the same element only with difficulty, if at all; and (iii) the chemical identity of isotopes is maintained in biochemical systems. None of these assumptions are entirely valid for all experimental situations, but they may be considered valid for most studies in which labeled nitrogen substances are used as tracers for naturally occurring nitrogen. Their validity is questionable only in studies in which isotope effects significantly affect the accuracy of measurement or interpretation of results, as will be discussed later. Several other assumptions are made in tracer studies of nitrogen cycle processes. Some of these assumptions are not valid under most experimental conditions. Others have been ignored without adequate consideration of their significance in the experimental system being used. Listed below are twelve assumptions that should be kept in mind in the planning and conduct of tracer research and in the interpretation of nitrogen tracer data obtained in studies of soil-plant systems. Their validity and significance will be discussed more fully later in relation to particular nitrogen transformations:

1. The isotope concentration of the tracer at zero experimental time is identical to its concentration before introduction of the tracer into the experimental system. If the isotope composition of the tracer is altered immediately after introduction through processes other than those under study or consideration, erroneous interpretation of data will result because calculations will be

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based on an assumed composition of the tracer starting material instead of the actual composition. 2. All the tracer nitrogen added to the experimental system can be recovered at zero experimental time. 3. Gains of nitrogen through fixation of atmospheric N2 or sorption of other nitrogen gases and losses of nitrogen through enzymatic or nonenzymatic processes leading to evolution of nitrogen gases are negligible during the experimental period. 4. The quantity of tracer nitrogen that is immobilized and subsequently remineralized is negligible, i.e., (i) nitrogen assimilated by soil heterotrophic microorganisms does not subsequently become available to the plant, (ii) nitrogen absorbed by the plant does not reenter the soil nitrogen pool, and (iii) root excretions, dead root tissue, and plant exudates do not contribute to the soil nitrogen pool to any measurable extent during the experiment. In long-term experiments, the significance of repooling must be critically examined. 5 . All of the inorganic nitrogen that is added or that is known to be present through measurement is equally available to higher plants and microorganisms. 6. Microorganisms and crop plants use only inorganic nitrogen. No organic nitrogen is assimilated directly. 7. None of the ammonium nitrogen fmed within clay lattices becomes available for higher plant or microbial use during the experimental period. 8. The distribution of applied labeled nitrogen among different plant parts or within a plant part is uniform. Its distribution within a plant part is the same for all growth periods. It is generally recognized that these assumptions are not valid, and because of this, ”N has been used to determine the partitioning of applied nitrogen among plant parts and metabolic fractions with time. However, ”N-labeled plant tissue often is added to soil to study the decomposition of organic matter without considering the probable nonuniform distribution of Is N between labile and more stable nitrogenous constituents. 9. The observed “priming effect” on the decomposition of soil organic matter (see Section VI, A, 2, b) does not result from underestimation of the significance of biological and chemical interchange in soil. 10. In the study of soil nitrogen transformations, the principal factors governing the rate of intermediate and sometimes opposing reactions are known and sufficient information is available to permit correct interpretation of data that represent the overall net effects. 11. The changes that occur in the system to which nitrogen is added are qualitatively and quantitatively identical to those occurring in the control. Although this assumption is not valid, it is usually made during the interpretation of data obtained from conventional nontracer experiments in which response to applied nitrogen is determined from an increase in yield above the

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control. Use of nitrogen tracers obviates the need to make this particular assumption. 12. In field plot experimentation with 15N, the significance of border effects can be evaluated. Many nitrogen tracer studies are designed to obtain information needed to test the validity of some of the above assumptions. In some studies, the significance of these assumptions cannot be accurately assessed and this must be accepted as contributing to the overall experimental error. The key to testing the validity and significance of most of these assumptions is measuring the extent of turnover, preferably stepwise, over short-time intervals throughout the experimental period.

I l l . Advantages and Disadvantages of Nitrogen Tracer Techniques

The obvious advantages of I4N and I5N as tracers are derived from their inherent nonradioactivity. Since they are stable isotopes, their use in an experimental system is not limited by time, i.e., there is no isotope decay with time. Their use does not pose a health hazard to the experimenter, nor do they cause radiation effects on the biological systems under study. The residues of an experimental system do not create a disposal problem; in fact, the residues are sometimes used in subsequent experiments. No permit is needed to conduct a stable nitrogen tracer experiment in the field, and analyses may be performed in any appropriate laboratory without licensing or radiation monitoring. Tracer methods offer several advantages over nontracer methods for research on nitrogen cycle processes. One is that tracer methods permit positive identification of the labeled nitrogen entity as it may enter, be transformed within, or leave the system under study. For example, when purified I5N-labeled N2 is introduced into a system, the presence of "N in the fixed nitrogen constituents of the biomass or substrate is unequivocal evidence that biological or chemical fixation of N2 has occurred. Similarly, direct measurements of denitrification are possible by means of nitrogen isotope-ratio analysis of nitrogen gases evolved from N-labeled substrate. A second advantage of nitrogen tracer techniques is that no control treatments are needed, obviating the need to make certain assumptions regarding the similarity of transformation processes in treated and control systems. Each isotope-ratio measurement is primary information that can be used without reference to other data, although its usefulness can be enhanced considerably when used in relation to other data. The accuracy of large-scale field experimentation is improved when no control is needed because it is almost impossible to find two experimental areas with identical properties

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(one of these areas would be designated as the control in a nontracer study). There is less need to obtain background data for an experimental area in which tracer is used. This leads to a third advantage, that of saving time in large-scale experimentation. Data collection can begin immediately after introduction of the tracer into the experimental system and the interpretation of the data is not necessarily dependent upon obtaining background information. Notwithstanding the above advantages, there are disadvantages and limitations in the use of nitrogen tracers. Compated to radionuclides such as 32P, "N is expensive, and until recently was in limited supply. Besides the high cost of "N, a major hindrance to more extensive use of "N-tracer techniques has been the high cost of the equipment needed for "N analysis and the problems encountered in maintenance and operation of this equipment. Also, until recently, comparatively large samples 0 . 5 mg N) were needed for accurate "N analysis and even now, with improved instrumentation and techniques, accurate determination of nitrogen isotope concentrations on samples containing microgram amounts of nitrogen is difficult. Where budgets have limited the amount of N that can be purchased for use in an experiment, the size and design of the experiment often have been dictated by the cost of the nitrogen tracer. Sometimes, because of cost considerations, experimenters have used levels of "N enrichment so low as to preclude following the tracer through successive nitrogen pools because of eventual dilution to a level that borders on experimental error. In general, radioactive tracers can be diluted to a much greater extent than stable nitrogen tracers because radioactive assay methods are usually extremely sensitive and background radiation levels are normally low. The severity of the limitations in the use of stable nitrogen isotopes as tracers has been markedly decreased by recent advances in nitrogen isotope separation processes, instrumentation, and methodology of nitrogen tracer use. IV. Determination of Nitrogen Isotopes

Although use of "N-tracer techniques has been restricted by the high cost of "N-enriched compounds, the major hindrance to extensive use of these techniques has undoubtedly been the difficulty of performing the nitrogen isotope analyses required in "N-tracer research. The methods available for stable isotope analysis are unfortunately usually considerably more complicated and time-consuming than the methods for radioactive isotope analysis, and, until quite recently, the isotopic analyses required in "N-tracer research could not be performed satisfactorily without use of a mass spectrometer, which is an expensive instrument requiring trained personnel for proper maintenance and operation. Performance of nitrogen isotope analyses also has been complicated by difficulties encountered in preparation of samples for these analyses.

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When the authors started to use "N-tracer techniques for soil and fertilizer nitrogen research, the literature did not contain satisfactory descriptions or discussions of anlaytical procedures for N research or adequate information concerning various problems in N analysis, and no techniques were available for nitrogen isotope-ratio analysis of several forms of nitrogen is soils. This is no longer true because many articles describing and discussing l5 N analysis procedures have been published during the past 15 years and most, if not all, of the problems in "N analysis have been identified and studied. The literature on N analysis is now so extensive that it cannot be reviewed adequately here. References to most of this literature can be found in review articles by Hauck and Bremner (1964), Bremner (1965, 1968), Bremner et al. (1966), Martin and Ross (1968), and Fiedler and Proksch (1975), and in the bibliography compiled by Hauck and Bystrom (1970).

A. SAMPLE PREPARATION

The analytical procedures most commonly employed in tracer investigations using N-enriched compounds are developments of modifications of the procedure introduced by Rittenberg and Sprinson (Rittenberg et al.. 1939; Rittenberg, 1948; Sprinson and Rittenberg, 1948, 1949), which involves the following three steps: 1. Conversion of the labeled nitrogen to ammonium. 2. Conversion of the ammonium to N2 by oxidation with alkaline sodium hypobromite in the complete absence of air. 3. Determination of the isotopic composition of the N2 by mass spectrometer analysis. The labeled nitrogen is converted to N2 because, to determine the isotopic composition of stable elements by mass spectrometry, it is necessary to convert the element under analysis to a gas that meets certain requirements. In the case of nitrogen, the gas which best meets these requirements is N2. Emission spectrometry has recently been used instead of mass spectrometry for "N analysis in tracer research, but the methods used to prepare samples for analysis by this technique also involve conversion of labeled nitrogen to N 2 . The main advantages of converting labeled nitrogen to N2 for isotope analysis are: (i) It is easier to convert different forms of nitrogen to N2 than to NO, NO2, or NH3, and N2 can be separated more easily than other nitrogen gases; (ii) unlike nitrogen gases such as NO and NO2, N2 is inert and does not react with components of equipment used for mass and emission spectrometry; and @)interpretation of isotopic analyses of N2 is simple because interferences from other elements are negligible.

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Experience has shown that there are many sources of error in the three-step procedure for "N analysis described and that considerable care is required in this procedure to obtain satisfactory results. The various sources of error have been discussed at some length in several reviews (Hauck and Bremner, 1964; Bremner, 1965, 1968; Bremner et ul., 1966; Martin and Ross, 1968; Fiedler and Proksch, 1975), but it is evident from recent reports of "N tracer research that some of the problems in "N analysis are not generally appreciated. Sources of error in the techniques commonly used to convert labeled nitrogen to Nz via ammonium are listed in Table 11. The importance of performing this conversion quantitatively deserves emphasis because failure to effect quantitative conversion can lead to erroneous conclusions in 15N tracer research. For example, the Kjeldahl techniques used in most "N tracer investigations to determine total nitrogen and convert labeled nitrogen to ammonium do not include oxidized forms of nitrogen, and many tracer studies of denitrification in soils have been vitiated by use of Kjeldahl techniques that do not give quantitative recovery of nitrate or nitrite. Simple methods of eliminating or greatly reducing crosscontamination during distillation of ammonium samples for N analysis (Table 11) are now available (Bremner and Edwards, 1965; Newman, 1966; Martin and Ross, 1968), but some workers seem reluctant to use these methods, presumably because they are not convinced that cross-contamination can lead to significant error in lSN analysis. Although volatile amines are usually listed when sources of error in 15N analysis are discussed, we have been unable to detect volatile amines in Kjeldahl digests of soils and plant materials, and it seems very unlikely that "N analysis of ammonium in such digests is ever complicated by the presence of methylamine or other amines (Bremner, 1965; Martin and Ross, 1968). Mass spectrometer analysis of Nz gas samples is affected by NzO and other gaseous impurities evolved during hypobromite treatment of ammonium samples, but simple and effective methods of removing such impurities are available (see Bremner, 1965; Martin and Ross, 1968; Ross and Martin, 1970), and evolution of Oz by hypobromite decomposition in oxidation of ammonium to Nz can be suppressed by use of sodium hypobromite treated with potassium iodide (Sims and Cocking, 1958) or by use of lithium hypobromite instead of sodium hypobromite (Ross and Martin, 1970). Until fairly recently, conversion of labeled nitrogen to ammonium for "N analysis in tracer studies of soil and fertilizer nitrogen problems was performed almost exclusively by Kjeldahl procedures designed to convert total nitrogen to ammonium, and few attempts were made to determine the nitrogen isotope ratios of specific forms of nitrogen. But methods are now available by which specific forms of nitrogen in soils, including exchangeable ammonium, fixed ammonium, nitrate, nitrite, hexosamine, amino acid, and urea nitrogen, can be readily converted to ammonium for "N analysis (Bremner, 1965; Bremner and Edwards, 1965; Biemner and Keeney, 1966; Keeney and Bremner, 1966,

''

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TABLE I1 Sources of Error in Preparation of Nitrogen Samples for I N Analysis When Hypobromite Is Used to Oxidize Ammonium to N, Step

Sohce of error

Conversion of labeled nitrogen to ammonium

Use of nonspecific method of conversion. Incomplete conversion Incomplete distillation. Crosscontamination during distillation Loss of ammonium as NH, ,Contamination of sample by atmospheric NH, Incomplete removal of dissolved and gaseous N, before conversion. Incomplete conversion of ammonium to N, . Failure to completely recover dissolved N, after conversion. Aix leakage during conversion. Contamination of N, by N, 0 and other gaseous impurities evolved in treatment of ammonium with hypobromite

Distillation of ammonium Concentration of ammonium sample Conversion of ammonium to N, by hypobromite technique

1967a,b; Silva and Bremner, 1966; Bundy and Bremner, 1973), and these methods permit analyses that greatly increase the scope and value of tracer research on nitrogen transformations in soils. Detailed descriptions and discussions of Kjeldahl techniques for conversion of total nitrogen to ammonium in "N analysis have been published (Bremner, 1965; Fiedler and Proksch, 1975). The Dumas method of determining total nitrogen has considerable attraction for determination and isotope-ratio analysis of total nitrogen in l5 N-tracer research because the combustion performed in this technique converts total nitrogen directly to N2. But many difficulties have been encountered in attempts to utilize the Dumas combustion technique for "N analysis, and it is only within recent years that promising techniques have been developed. Descriptions and discussion of Dumas-type combustion techniques for conversion of total labeled nitrogen to Nz for isotopic analysis can be found in articles by Barsdate and Dugdale (1965), Desaty et al. (1969), Bremner and Tabatabai (1971), Fiedler and Proksch (1972a, 1975), Proksch (1972), and Tsuji ef al. (1973, 1975). Research to develop satisfactory Dumas techniques has been greatly stimulated by improvements in methods of determining Is N by emission spectrometry because Dumas techniques have special advantages for "N analysis by emission spectrometry, and the emission spectrometers available commercially for nitrogen isotope-ratio analysis are equipped with Dumas combustion units for preparation of Nz gas samples. But problems have been experienced in direct conversion of total nitrogen to N2 by Dumas combustion

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R. D. HAUCK AND J. M. BREMNER

techniques, and some workers have preferred to convert total nitrogen to ammonium by a Kjeldahl technique and subsequently convert this ammonium to N2 by Dumas combustion (see Fiedler and Proksch, 1975). Although the methods used to prepare N2 gas samples for "N analysis by emission spectrometry are similar in principle to those used to prepare samples for mass spectrometer analysis, they differ significantly in practice because the amount of N2 gas suitable for analysis by emission spectrometry (0.2-10 pg of nitrogen) is much smaller than the amount required for satisfactory analysis by mass spectrometry (30-2000 pg of nitrogen). Convenient equipment and procedures for hypobromite oxidation of ammonium to N2 in "N analysis have been described by Bremner (1965) and Ross and Martin (1970). The procedure described by Ross and Martin (1970) has significant advantages when a large number of N analyses must be performed. Walker et al. (1975) have recently described a novel procedure for total nitrogen and "N analysis of plant tissue, water, and soil samples. In this procedure, total nitrogen is converted to NH3by a reductive pyrolysis technique involving use of H2 and a heated nickel catalyst. To estimate total nitrogen in the sample pyrolyzed, some of the ammonia is collected in water and determined by a conductivity detector. The remainder is collected in a cold finger reaction vessel and subsequently converted to N2 for mass spectrometer analysis by a thermal decomposition technique involving use of hydrogen and a rhenium filament heated to 1050°C.

B. ISOTOPE-RATIO ANALYSIS

As noted previously, the isotope-ratio analysis stage of procedures developed for "N analysis in tracer research was initially performed exclusively by mass spectrometry. This technique is still the method of choice in most work requiring nitrogen isotope-ratio analysis, but the difficulties encountered in use of mass spectrometry have stimulated research to find alternative methods for determination of nitrogen isotopes, and methods involving use of emission spectrometry, nuclear magnetic resonance (NMR) and other techniques have been proposed. Of these, only emission spectrometry has gained acceptance for nitrogen isotope ratio analysis in tracer investigations. It should be noted, however, that NMR and other techniques have applications in nitrogen research. The stable nitrogen isotopes have nuclei that behave like spinning magnets. When placed in a magnetic field, these nuclei can absorb radio-frequency energy, and measurements of the extent of absorption can be used to calculate isotope concentrations and to identify structural relationships between nitrogen nuclei and other groups of nuclei, especially protons. Until recently, NMR techniques could be applied only to solutions or other nonviscous fluids, but advances in

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

23 1

pulse NMR instrumentation have made it possible to appply these techniques to heterogeneous systems (e.g., clay suspensions). This suggests that it may be possible to use NMR techniques to distinguish between ammonium nitrogen and organic nitrogen trapped within clay lattice structures when these two forms of nitrogen are highly enriched with "N. Infrared spectrometry also has potential value for soil nitrogen research because an isotope shift occurs during absorption of infrared radiation by nitrous oxide, and the extent of this shift can be used to measure nitrogen isotope-ratios in nitrous oxide (Kluyver and Blokhuis, 1954). However, more important in regard to soil nitrogen research is the fact that this isotope shift is seen as a broadening and overlapping of infrared absorption bands when infrared spectrometry is used to determine nitrous oxide evolved by denitrification of nitrate in soils. This shift makes it difficult to accurately compare the absorptivity of the "N-labeled unknown with that of the appropriate unlabeled standard and probably leads to underestimation of the amount of nitrous oxide evolved (Hauck and Melsted, 1956).

I . By Mass Spectrometry As its name suggests, a mass spectrometer separates ions into a spectrum according to their masses, or to be more precise, according to the ratio of mass to charge (M/e). This separation is achieved by an appropriate combination of electrical and magnetic fields, and the relative abundances of ions of different M/e ratios are determined by collecting the ions on an insulated electrode (or electrodes) and measuring the currents they produce. Before neutral molecules such as N2 can be separated in a mass spectrometer, they must be ionized, and this is usually accomplished by bombarding the molecules with a stream of electrons emitted from a hot tungsten filament. These electrons may knock other electrons out of the molecules, leaving positively charged ions, or they may decompose the molecules into charged fragments. The ions produced by electron bombardment of N2 in the mass spectrometer are ("N"N)+ , (l4 N I' N)', (l4N l4 N)+, (" N)', (l5N" N)", (l4 N l5N)'*, (l4 N)', and (l4 N14N)'+. For reasons discussed by Nier (1948), the isotopic composition of N2 is best determined by measurement of the ion currents corresponding to mass 28 (14N14N), mass 29 ("NI4N), and mass 30 (15N"N). Nitrogen isotope abundance values are calculated from these measurements as described in Section IV, c. Various types of mass spectrometers have been developed, including single collector, double collector, time of flight, cycloidal focusing, and radio frequency (quadrupole) instruments. Discussion of these instruments is beyond the scope of this article (for references, see Bremner, 1975; Fiedler and Proksch, 1979, but it should be pointed out that major advances in instrumentation for mass spectrometry have occurred in recent years and that these advances have

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R. D. HAUCK AND J. M. BREMNER

led to development of mass spectrometers that permit remarkably accurate and precise determination of "N. For example, the Micromass Model 602C mass spectrometer developed by VG-Micromass Ltd. (Nat Lane, Winshire, Cheshire, England) and the Nuclide Model 3-60-RMS mass spectrometer developed by Nuclide Corporation (642 East College Avenue, State College, Pennsylvania) are much superior in their price range to instruments available ten years ago and allow very accurate and precise determination of small variations in the nitrogen isotope ratios of natural substances. Freyer and Aly (1975) recently reported that the Micromass instrument permits isotopic analysis of N2 with a precision of less than kO.05 A"N (see Sections IV, C and VI, C). Until fairly recently, isotopic analyses of N2 samples in "N-tracer research were performed largely with single collector instruments, but double collector instruments are gaining favor. The main advantages of double collector instruments are that they permit compensation for fluctuations in the ion source and have greater precision than single collector instruments. Assuming that the mass spectrometer used for nitrogen isotope-ratio analysis is capable of providing the accuracy and precision of analysis required and is properly maintained and operated, the only significant errors in mass spectrometer analysis are those caused by the presence of impurities such as NzO or volatile amines in the Nz gas samples analyzed or by comtamination of these samples by air during their preparation or analysis. The errors that can arise through the presence of impurities such as Nz 0, COz , and volatile amines have been discussed in several articles (e.g., Hauck and Bremner, 1964; Bremner, 1965; Martin and Ross, 1968), and it suffices here to point out that these errors should be insignificant when proper precautions are observed in preparation of Nz gas samples for isotopic analysis. In other words, if other stages of the "N analysis procedure have been performed satisfactorily, the only serious source of error in isotopic analysis of N2 gas samples by mass spectrometry is contamination of these samples by air during their preparation or analysis. The presence of air is indicated by a peak at M/e 32 due to oxygen and confirmed by the presence of a peak at M/e 40 due to argon, and measurements of these peaks have been used to correct for contamination by air (see Rittenberg, 1948; Sprinson and Rittenberg, 1948; Holt and Hughes, 1955; Yemm and Willis, 1956; Capindale and Tomlin, 1957; Sims and Cocking, 1958; Huser et al., 1960; Newman and Oliver, 1966). Correction based on measurement of the peak at M/e 32 due to oxygen involves the assumption that all the oxygen in the sample is of atmospheric origin. This assumption is invalid because most of this oxygen usually originates by hypobromite decomposition. Correction based on measurement of the peak at M/e 40 due to argon is more specific, but has the disadvantage that the experimental error in determination of the small peak at M/e 40 is magnified by the high nitrogenlargon ratio in air. Also, these corrections involve the assumption that the Oz/Nz or Ar/N2 ratio of the air in the gas

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

233

sample analyzed is identical to that of normal air, and this assumption is certainly invalid (see Hauck and Bremner, 1964; Balestrieri, 1968; Martin and Ross, 1968). For these reasons, it is clearly desirable to avoid the need to correct for air contamination, and epxerience in our laboratories has shown that contamination by air is rarely significant when proper precautions to minimize such contamination are observed during preparation and analysis of N2 gas samples. When contamination is significant, it is usually easily detected by discrepancies between the results of duplicate analyses. For obvious reasons, the effect of air contamination depends on the volume and "N enrichment of the N2 sample analyzed and is most serious in analysis of very small amounts of nitrogen highly enriched with N.

2. By Emission Spectrometry One of the most significant advances in regard to nitrogen isotope-ratio analysis during the past decade has been the development and improvement of instruments for determination of "N by emission spectrometry. The main attractions of emission spectrometry for 15N analysis are that this technique is considerably simpler than mass spectrometry from a technical point of view (e.g., high vacuum is not required) and that the cost of emission spectrometric equipment suitable for 15N analysis is less than one-half the cost for mass spectrometric equipment. Other advantages claimed for emission spectrometry are that only a few micrograms of nitrogen are needed for "N analysis by this technique, that the equipment needed can be installed and supervised by any experienced analyst, and that analysis of Nz gas samples can be repeated many times since it is in almost all cases nondestructive (Fiedler and Proksch, 1975). The emission spectrometric method of nitrogen isotope-ratio analysis is based on the fact that Nz molecules emit characteristic light in the ultraviolet spectrum when excited at low pressure in an electrodeless discharge tube by a high-frequency generator (Broida and Chapman, 1958). More specifically, excited 14N14N, IsNl4N, and lsN"N molecules emit light at 2977, 2983, and 2989 A, respectively. To utilize this phenomenon for "N analysis, light emitted by the excited N2 molecules is resolved by a monochromator. The monochromator output is detected by a photomultipler and a signal is amplified and fed to a chart recorder. The peaks heights corresponding to "N2, "N2, and 'ON2 permit "N abundance to be calculated as in "N analysis by mass spectrometry. Essentially, the equipment used for nitrogen isotope-ratio analysis by emission spectrometry consists of four units: (i) a microwave @gh-frequency) power generator for excitation of the N2 molecules in the gas sample tube; (ii) a device for transferring the power from this generator to the gas sample tube; (iii) a monochromator that resolves light of different wavelengths and is fitted with a device that allows automatic scanning of the wavelengths corresponding to

234

R. D. HAUCK AND J. M. BREMNER

zaN2, "Nz, and jONz ;and (iv) a photomultipler-amplifier-recordersystem that converts light outputs to electrical signals and provides measurable peaks for calculation of "N abundance. Three instruments for "N analysis by emission spectrometry have been developed commercially. Two of these-the Statron Model NO14 and NOI-5 analyzers-are manufactured in East Germany (Statron, 124 Furstenwalde, Ehrenfried-Jopp-Strasse 59, DDR). The other (the Jasco Model NIA-1 analyzer) is manufactured in Japan (Japan Spectroscopic Co., Ltd., Hachioji City, Tokyo). The Statron instruments could be purchased in the United States a few years ago from Packer Instruments Co., Downers Grove, Illinois, but they are no longer marketed by this company. The NO14 instrument is currently available in England through Carl Zeiss Jena Ltd., 2 Elstree Way, Boreham Wood, Herts, and the Jasco instrument can be purchased in the United States from Jasco Incorporated, 21 8 Bay Street, Easton, Maryland. Several workers have reported studies to evaluate the Statron instruments (e.g., Fiedler and Proksch, 1972b; Heltai et al., 1972; Karlsson and Middelboe, 1972; Tedesco, 1972; Keeney and Tedesco, 1973; Lloyd-Jones et al., 1974; Meyer et al., 1974), and Guiraud and Buscarlet (1975) have recently reported studies to evaluate the Jasco instrument. Although there is some disagreement in the literature concerning the optimal amount of nitrogen for "N analysis by emission spectrometry, there is no doubt that the amount of nitrogen needed for anlaysis by this technique is considerably smaller than the amount needed for mass spectrometer analysis. The quantity of nitrogen required for emission spectrometric analysis can be reduced to as little as 0.2 pg with the aid of noble gases (see Cook et al., 1967; Goleb and Middelboe, 1968; Fiedler and Proksch, 1975); and this is clearly an important advantage for tracer research in which it is necessary to determine the "N contents of very small amounts of nitrogenous materials separated by techniques commonly used in biochemical research (e.g., by paper, thin layer, or gas chromatography). It is difficult, however, to avoid contamination and sampling error in analysis of very small amounts of nitrogen, and it is not necessary or desirable to perform "N analysis on very small amounts of nitrogen in most tracer studies of soil and plant systems. It is, in fact, a disadvantage of emission spectrometry that '' N analysis cannot be performed by this technique on Nz gas samples containing appreciable amounts of nitrogen because this complicates preparation of these samples for isotopic analysis (fine grinding and very thorough homogenization of biological materials are required to avoid serious sampling error). Many problems have been encountered in operation of emission spectrometers and recent literature reflects considerable divergence of opinion concerning several aspects of '' N analysis by emission spectrometry, including accuracy, amount of nitrogen needed, precision and memory effects (see Perschke et al., 1971; Fiedler and Proksch, 1972b, 1975; Tedesco, 1972; Keeney and Tedesco,

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

235

1973; Lloyd-Jones et al., 1974; Meyer et al., 1974). Nevertheless, emission spectrometry has proved useful for "N analysis in a variety of tracer investigations (see Kumazawa and Goleb, 1969; Akkermans, 1971; Fiedler and Proksch, 1972b; Muhammad and Kumazawa, 1972, 1974, 1976; Tedesco, 1972; L'vov and Kretovich, 1973; Muhammad et aZ., 1974; Yoneyama and Kumazawa, 1974; Kano er al., 1975; MacRae, 1975; Stein et al., 1975), and it is to be hoped that further research will lead to development of emission spectrometers that will be relatively easy to maintain and operate and will prove satisfactory for routine determination of "N in many types of tracer research on nitrogen transformation processes. It should be emphasized, however, that the emission spectrometers currently available commercially are not sensitive enough for satisfactory research with Is N-depleted materials or for research requiring measurement of slight variations in the nitrogen isotope ratios of natural substances.

C. CALCULATION OF RESULTS

As noted previously, nitrogen isotope-ratio measurements in tracer research are usually performed by mass or emission spectrometric analysis of Nz prepared from the nitrogenous material under study. Since the methods used to calculate the results of analysis by emission spectrometry are similar to those employed when analysis is performed by mass spectrometry (see Fiedler and Proksch, 1975), only the latter will be discussed here. During mass spectrometer analysis of Nz, nitrogen ions of the formulas ( I 4 N2 )+ (l4 N" N)', and (I5 Nz )+ appear in the mass spectrum with the relative number of ions of each species approaching the ideal statistical values given by the terms of the equation (a t b)Z =a2 t 2ab t b2

(2)

where a is the atom fraction of 14N, b is the atom fraction of "N, and a t b = 1. The mass spectrometer can be caused to measure the ion currents at M/e 28, M/e 29, and M/e 30, which are proportional to the respective molecular ions. It is usually not necessary to measure the ion current corresponding to M/e 30 [('5N1sN)+] to determine that at. % "N because of the random distribution of isotopes in the N2 molecules (see, however, Section VI, A, 4). From the ratio (R) of the ion current at M/e 28 and M/e 29, it can be shown that at. % "N = 100/(2R t 1)

(3)

or, for a mass spectrometer equipped with a ratiometer that gives a direct reading of M/e 29/28, designated (R'), at. % "N = 100R'/(2 t R')

(4)

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R. D. HAUCK AND J. M. BREMNER

[for more complete discussion and derivation of these expressions, see Rittenberg (1948), Bremner (1965), and Hauck (1966), among others]. Equation (3) or (4) for at. % "N is convenient to use at concentrations of "N below 5 at. %. In the concentration range of 5 to 95 at. % "N, highest accuracy can be achieved by measuring the peaks at M/e 28, 29, and 30. A measure of the accuracy of a mass spectrometer can be made by using the equations

M / e 29 = 2A/(100 - A )

M / e 30 = [A/(lOO - A ) ]

(5)

where A is the at. % "N and the intensity of the ion current at M / e 28 is taken as unity. The term at. % "N excess is commonly found in the literature. This term refers to the actual atom percent concentration of "N minus the natural background concentration. Users of this term assume a constant value for natural "N abundance, which is incorrect, or determine this value for the natural material they are using as a standard, which may not be the reference used by others. We prefer to relate all nitrogen isotope ratios to the currently accepted value of 0.3663 0.0004 at. % "N for atmospheric Nz (Junk and Svec, 1958), i.e., to adjust the mass spectrometer so that it gives this value for atmospheric N2 or to use an instrument correction factor for both standard and unknown. The correction factor is calculated by

*

0.3663 at. % "N of standard or by an equivalent formula expressed in terms of isotope ratios. Use of a single correction factor assumes a linear response of the mass spectrometer to change in "N concentration. The natural variations in nitrogen isotope abundance,. designated as AlSN (or 6 l5 N), are generally expressed as parts per thousand differences from the "N to 14N ratio in a standard, usually atmospheric N2 : A15N = (15N/14N), - (lsN/14N) atm (15N/14N) atm

looo

(7)

where ( l5 N/I4 N), and ( lJ N/ l4 N)atm are the nitrogen isotope ratios of the sample and atmospheric Nz, respectively. The terms per mil difference and per mil enrichment also have been used. Recently, A'' N values have been reported based on the expression

Values of A"N calculated from the expression based on the use of istotope ratios [Eq. (7)] are slightly lower than those based on the use of N concentrations [Eq. (8)], but the differences due to method of calculation are well within the limits of analytical error and can be considered negligible.

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

237

Most "N tracer studies of soil and fertilizer nitrogen problems involve the technique of isotope dilution analysis. A specified amount of l5 N-labeled material is added to a mixture (e.g., soil) containing unlabeled nitrogen invarious forms. Some of the nitrogen in the mixture acts as an unlabeled diluent for the added tracer. To detect the amount of dilution requires only that a portion of the tracer be recovered in a chemically definable state. The relation between added and recovered tracer is simple where, as is usually the case, the tracer is markedly different from the diluent and the diluent contains the nitrogen isotopes in natural concentrations. The general formula for assaying a compound in a mixture of compounds using isotope dilution techniques is x 2 =

[(C1/Cz)-lI

'X1 .(M2/MI)

(9)

where X1 is the weight of the tracer compound added, X, is the weight of unknown (unlabeled) compound, C2 is the isotopic content (expressed as at. % excess) of the compound recovered from the mixture, and C1 is the isotopic content of the original tracer compound. The term M2/M1 corrects for the change in molecular weight of the compound as its isotopic composition changes upon dilution. An expression similar to Eq. (9) calculates the amount of "N-labeled fertilizer taken up by plants or remaining in soil after cropping,

X = (TN) (c - b ) U

(10)

where X is the amount (e.g., kg/ha) of labeled fertilizer nitrogen in the plants or soil, TN is the total amount of nitrogen (kg/ha) in the plant or soil sample, a is the at. % "N excess in the fertilizer, and b and c are the "N contents expressed as at. % in the standard and sample, respectively. The same expression, but using various sets of different symbols, can be found in the literature on tracer use. We prefer to calculate the percent recovery of fertilizer nitrogen by crop plants from the equation

% nitrogen recovered =

100 P(c - b )

f(a - b ) where P is the total milliequivalents of nitrogen found in plant materia1,fis the milliequivalent of fertilizer nitrogen applied, and a, b , and c, are the at. % "N concentrations in the fertilizer, soil (or, more accurately, in plants grown on unfertilized soil), and plants grown on soil receiving tracer nitrogen, respectively. When "N-depleted fertilizer is used as the tracer material, change the terms (c - b) and (a - b ) in Eq. (1 1) to (b - c) and (b - a), respectively. For highest accuracy, the amounts of nitrogen in the fertilizer, soil, and plant samples are corrected to reflect the isotopic composition of the samples using the expression

MN = 0.01 [at. % 'N

(15.000) t at. % 14N (14.003)]

(1 2)

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R. D. HAUCK AND J. M. BREMNER

where MN is the average atomic weight of nitrogen in material of a particular nitrogen isotopic composition. Failure to make this correction introduces only slight error into the calculation of percent recovery of applied tracer. The calculations for interpreting mass spectrometer values obtained from studies of denitrification are discussed in Section VI, 4. The user of Is N usually obtains N materials from a supplier at an enrichment other than needed for the experiment. The amount of unlabeled compound that must be added to the labeled compound to obtain a mixture at the desired "N enrichment level can be calculated from

where A 2 is the at. % "N desired, T and A . are the weight and at. % "N of nitrogen in the compound to be diluted, respectively, and D and A l are the weight and at. % N (usually the natural abundance) of nitrogen in the diluting compound, respectively. It should be noted that the use of "N per se does not increase the accuracy of data obtained from an experimental system. The overall accuracy of data from a tracer study is directly related to the accuracy by which the amount of labeled material added at the beginning of the experiment can be determined. This addition usually can be made with a greater degree of accuracy than other analyses made during the study, e.g., the determination of total nitrogen by a Kjeldahl procedure. Using an expression similar to (13), let T be the amount of tracer added, P be the total amount of nitrogen in the (unlabeled) soil nitrogen pool before tracer addition, A o , A l , and A 2 be the at. % "N concentrations of tracer, soil nitrogen before tracer addition, and soil nitrogen after tracer addition, respectively, and assume complete mixing of labeled and unlabeled nitrogen. Then the expression

A. =

FA0 -P*A1 T+P

can be rewritten to calculate the amount of total nitrogen present in the soil initially from the at. % "N concentrations of the nitrogen components.

It is obvious that improvement in the accuracy by which P is determined is a function of T. For example, if 100 mg of tracer nitrogen is added to 6 kg of soil containing 0.1 % N and completely mixes with the soil nitrogen, an error of 2% in the determination of the total nitrogen in the mixture would be equivalent to

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

239

120 mg of nitrogen (this could be interpreted in a nitrogen balance study as an apparent loss or gain of 120 mg of nitrogen). However, if the determination of nitrogen in the tracer material is accurate to 1%, it can be seen from Eq. (15) that the error is reduced to k60 mg of nitrogen, regardless of the "N concentration of the starting material (assuming negligible error due to nonlinear instrument response to isotopic composition).

V. Sources and Cost of Nitrogen Tracer Materials

The high cost of "N-enriched compounds is usually mentioned when problems in the use of "N are discussed, and this has certainly restricted use of this isotope for field studies. But compared with the instrumentation and labor costs in "N work, the cost of the isotope is usually very small for laboratory work and reasonable even for pot experiments. It has been evident for many years that the cost (and, therefore, the price) of "N could be reduced significantly by a substantial increase in the demand for this isotope, but the problem here has been a paradox-the demand has been dictated by the price, and the price has been dictated by the demand. This problem and the related problem of "N being in limited supply have been reduced by recent advances in nitrogen isotope separation processes leading to a substantial reduction in the cost of producing "N commercially and by the decision of the United States Atomic Energy Commission (now under the Energy Research and Development Administration) to produce kilogram quantities of "N-enriched materials as part of the ICONS (Isotopic Carbon, Oxygen, Nitrogen, and Sulfur) project designed to lower the cost and increase the use of stable isotopes of carbon, oxygen, nitrogen, and sulfur (see Hammond, 1972). Substantial quantities of Is N-enriched nitrogen have recently been produced under this project at the Los Alamos Scientific Laboratory in New Mexico by cryogenic distillation of nitric oxide, and "Nenriched compounds from this source can now be purchased from Monsanto Research Corporation, Mound Laboratory, P.O. Box 32, Miamisburg, Ohio. (The Mound Laboratory is operated for the United States Energy Research and Development Administration.) The forms and cost of "N available from this source are indicated in Table 111. Other sources of "N-labeled compounds are listed in Table IV. Sources are mentioned here because it is surprisingly difficult to obtain reliable information on this subject. Several companies advertising '' N-enriched compounds a few years ago can no longer supply such compounds. Other companies now advertising purchase I' Nenriched compounds from other companies or undertake production of these compounds only when orders are received. Also, comparison of the prices quoted for "N-enriched compounds by different companies is

240

R. D. HAUCK AND I. M. BREMNER TABLE 111

Forms and Cost of "N Distributed by Monsanto Research Corporation (Mound Laboratory)a

Form

Enrichment (at. %

Price per gram of 15Nb

Grams of "N per unit compound

Ammonium sulfate Potassium nitrate Ammonia Ammonium sulfate Nitric acidC Potassium nitrate Nitrogen gas

40 40 95-99 95-99 95-99 95-99 99

$60.00 $60.00 $95.30 $95.30 $95.30 $95.30 $95.30

0.089519 solid O.O588/g solid 0.645/STP liter gas 0.21 l/g solid O.l06/g solution 0.138/9 solid 1.32/STP liter gas

"Mound Laboratory has the responsibility of distributing ''N and other stable isotopes produced under the ICONS project of the United States Energy and Research Administration at Los Alamos. bAugust 11,1975. CSuppliedas an approx. 10M solution. Prices quoted do not include cost of container, packaging, and handling.

complicated by lack of standardization in methods of quoting prices. For example, the prices quoted by the Monsanto Research Corporation do not include the cost of the container or the cost of packaging, handling, and shipping, whereas the prices quoted by other companies include these costs. Also, the price depends to a considerable extent on the amount and form of "N needed and the "N enrichment required. The Monsant Research Corporation is the cheapest current source of a substantial amount of "N in the form of potassium nitrate, ammonium sulfate, nitric acid, ammonia or nitrogen gas, but this company does not supply other forms of "N. Several companies (e.g., Isocommerz GmbH and Prochem/BOC Ltd.) can provide a variety of organic and inorganic nitrogen compounds with low, medium, and high "N enrichments. Isocommerz GmbH can supply about 180 *'N-labeled compounds, including amides, imides, amino acids, pyridine and quinoline derivatives, nitro compounds, cyanides, ammonium salts, nitrates, nitrites, choline, and hydroxylamine. The success of research to reduce the cost of producing "N can be gauged from the fact that the sales price in the United States of 1 g of "N in the form of "N-labeled ammonium sulfate containing 95-99 at. % "N decreased from about $400 in 1967 to approximately $95 in 1975. Recent discussions of the economics of "N production and of problems in synthesis of "N-labeled compounds suggest that no further appreciable decrease in the cost of "N tracer materials can be anticipated (Edmunds and Lockhart, 1975; Matwiyoff et al., 1975).

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

Sources of

Is

24 1

TABLE IV N-Enriched Compounds

~~~~~

United States and Canada

Europe

Bio-Rad Laboratories" 32nd and Griffin Avenue Richmond, California 94804

Azote Products Chimique 40 Avenue Hoche Paris 8 eme. France

ICN Pharmaceuticals, Inc. Life Sciences Group 2727 Campus Drive Irvine, California 92664

BOC Ltd. (Prochem) Deer Park Road London SW19 3UF, England

Koch Isotopes, Inc. 72 Rogers Street Cam bridge, Massachusetts 0 1438

Institute for Stable Isotopes (Cluj) Chimimportexport 10 Republicii Blvd. P. 0. Box 525 Bucharest, Romania

Merck and Co., Inc./Isotopes 4545 Oleatha Avenue St. Louis, Missouri 63116 Merck Sharp & Dohme Canada Ltd. Isotope Division P. 0. Box 899 Pointe Claire/Dorval700 Quebec H9R 4P7, Canada Prochem 47 Meadowbrook Place Maplewood, New Jersey 07040 Stohler Isotope Chemicals 49 Jones Road Waltham, Massachusetts 02154

Isocommerz GmbH DDR 1115 Berlin Lindenberger Weg 70, East Germany (DDR) Ministrio de Industria Junta de Energia Nuclear Avenue Complutense Madrid 3, Spain SAS Scientific Chemicals Ltd. Victoria House Vernon Place London WClB 4DR, England

"Offices in England, Germany, Italy, and Brazil.

Although the high cost of "N is a serious hindrance to use of this isotope as a tracer for field studies, there is increasing need and administrative support for such use in environmentally oriented studies. Use of tracer materials at low (<1%) levels of ''N enrichment and the use of "N-depleted nitrogen for tracer research is attracting attention (see Section VI, B). Large quantities of "N-depleted nitrogen have recently been produced at the Los Alamos Scientific Laboratory in New Mexico as a by-product of the cryogenic distillation method of separating "N, and this nitrogen can be purchased from Monsanto Research Corporation (Mound Laboratory) as a 40% aqueous solution of ammonium

242

R. D. HAUCK AND J. M. BREMNER

sulfate containing 0.003-0.009 at. 76 "N. The relatively low cost of this highly purified I4N ($145/kg) and its potential availability in large amounts (several tons per annum are projected) should encourage its use for field studies of soil and fertilizer nitrogen problems. VI. Use of Nitrogen Tracer Materials

Nitrogen tracers have been used to study nitrogen mineralization-immobilization reactions in soils, gains of nitrogen by, and losses of nitrogen from soils and waters, plant recovery of applied nitrogen, nitrogen movement through soils to water, nitrogen balance in productive ecological systems, and virtually all known aspects of nitrogen cycle processes. A survey of "N-tracer studies over the past years reveals the following trends: (i) Interest in using "N to study the biochemistry of biological fixation of atmospheric N2 remains high although such studies no longer dominate the "N literature on work pertinent to agriculture; @)there is increasing interest in evaluating the potential for symbiotic and associative N2 fixation in different environments and with different cultivars; (iii) increasingly more studies with "N are being directed toward assessing and increasing the efficiency of fertilizer nitrogen in crop production; (iv) few studies provide reliable quantitative information for estimating nitrogen balance between the atmosphere and biosphere or within their nitrogen subcycles, although there is increasing interest in, and need for obtaining such information; (v) large-scale use of nitrogen tracers in field studies is now being made for the first time; and (vi) methods and apparatus for effective use of 15N continue to be refined. Our purpose here is not to discuss the major findings of soil and fertilizer tracer nitrogen research. The abstracts of such research have been compiled and cross-referenced in an extensive bibliography on "N use in agricultural research (Hauck and Bystrom, 1970), and this bibliography is already undergoing revision because of the marked increase in "N use within the last 5 years (800 additional references have been collected since 1970). Reviews and commentaries on the findings and use of '' N research as related to various aspects of the nitrogen cycle are also available (e.g., Bartholomew, 1956,1971;Broadbent, 1956; Allison, 1966; Jansson, 1966, 1971; Bremner, 1968; Fried, 1971; Hauck, 1973; Cherepkov, 1974; Koren'kov and Lavrova, 1973). Our purpose in this section is to discuss the various avenues of approach using nitrogen tracers which are open to investigators of soil and fertilizer nitrogen transformation processes and to draw attention to the limitations as well as the advantages of such approaches. The literature cited has been selected more for its direct bearing on a method or principle involved in study of a particular nitrogen transformation than for the quantitative information which it contains. The many references to methodol-

USE OF TRACERS FOR SOIL NITROGEN RESEARCH

243

ogy in preceding and subsequent sections reflect the importance we attach to the dissemination of such information.

A.

N-ENRICHED MATERIALS

I. Biological N 2 Fixation Although it is generally accepted that measurement of lsN2 fixation is the most reliable method of measuring biological nitrogen fixation and is the standard to which other methods should be referred, only about 200 of the numerous papers concerning biological nitrogen fixation published during the past 30 years have reported use of "N-tracer techniques. In contrast, more than 300 papers published during the past 3 years alone have reported use of the acetylene reduction method of studying nitrogen fmtion, which is based on the relatively recent finding that nitrogenase reduces acetylene to ethylene (Dilworth, 1966; Schollhorn and Burris, 1966) and involves gas chromatographic determination of the ethylene produced when N2-fixing systems are exposed to atmospheres containing acetylene in gas-tight chambers (KO& and Evans, 1966; Stewart et al., 1967; Hardy et al., 1968). It is not difficult to account for the rapid acceptance and widespread use of the acetylene reduction method because this technique is much simpler and considerably less expensive than the 15N2 method and has much greater sensitivity and flexibility. It is, nevertheless, an indirect method of measuring nitrogen fixation and its results must be checked against those obtained by a direct method before they can be interpreted in terms of nitrogen fixed. As Burris (1972, 1974) has emphasized, the direct method of choice for this interpretation is reduction of I s N 2 . Although papers reporting use of Is N tracer techniques represent a very small fraction of the total literature on biological N2 fixation, they account for a substantial fraction of the literature since 1940 reporting use of "N-enriched compounds for research related to agriculture. Initially most of the "N work concerning nitrogen fixation related to nonsymbiotic fucation, but approximately half the work now published has been related in some way to symbiotic fixation. The basic assumption in use of 15N2 for research on biological nitrogen furation is that the N2 -fixing system under study does not discriminate between 14N and "N. The only reported investigations of this assumption appear to be studies by Hoering and Ford (1960) and Delwiche and Steyn (1970) indicating that very little, if any, nitrogen isotope discrimination occurs in fixation of N2 by Azofobacter vinelandii. Similar studies with other N2-fixing systems are clearly desirable in view of the importance of the ISN2 reduction technique in research on biological N2 fixation.

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It is noteworthy that the radioactive isotope, I3N, was used before "N to study nitrogen fixation. The first use of I3N2in nitrogen fixation research was by Ruben er al. (1940) in studies of N, fixation by nonleguminous plants, whereas the first use of "N, was by Burris and Miller (1941) in studies of N2 fixation by Aztobacrer uinelundii Since 1940, Nicholas et al. (1961) have used I3N2 to study nitrogen furation by bacterial cells and cell extracts, and Campbell er al. (1967) have used 13Nz to assess the nitrogen fixation potential of microorganisms isolated from sub-Arctic soils. The l 3 N-tracer technique is considerably more sensitive than the "N-tracer technique, but I3N2 has such a short half-life (10.05 minutes) that it must be generated continuously when used as a tracer and is suitable only for experiments which can be completed within about 2 hours. The major hindrance to use of I3N2 is that very expensive and sophisticated equipment is required for production and purification of this gas. It is produced by cyclotron bombardment of I4N2 and must be carefully purified to remove other radioactive isotopes produced in the cyclotron target chamber. For these reasons, it seems unlikely that 13N2 will be used to any significant extent in future research on nitrogen fixation. a. Methodology. Although Is N-enriched ammonium and nitrate compounds have been used to study the effects of nitrogen fertilizers on biological N2 fixation and to assess nitrogen fixation by leguminous plants under field conditions (for recent examples, see Broeshart, 1974; Johnson et al., 1975), most "N-tracer studies concerning nitrogen fixation have involved exposure of the Nz-fixing system under study to IsNz in a sealed vessel. The techniques developed for such studies have been described in recent articles by Burris (1972, 1974). Briefly, the methodology consists of exposure of the N2-fixing system to 15N-enriched N2 in a gas-tight container fitted so that it allows addition and removal of gas. Class containers are usually employed, but Saran bags have proved satisfactory and these have significant advantages for work with bulky systems (Burris, 1973). A pN, of 0.1-0.3 atm is generally sufficient to saturate nitrogenase and avoid waste of expensive lsN2. After exposure for the time selected, nitrogenase in the system under study is inactivated by addition of acid (or by other means) and a sample of the gas in the exposure vessel is removed with a gas-tight hypodermic syringe and injected directly into a mass spectrometer to determine the "N concentration of the N, to which the system was exposed. It is essential in this analysis to measure the peaks corresponding to mass 28 ( l4 N,), mass 29 ( 14N"N), and mass 30 ( I 5 N 2 ) because the gas in the exposure vessel may have been contaminated with air (such contamination results in a nonequilibrium distribution among masses 28, 29, and 30, which precludes use of the usual 29/28 ratio for calculating "N concentration). After gas from the exposure vessel has been analyzed, the vessel contents are subjected to Kjeldahl analysis to determine total nitrogen. To determine the "N concentration of this nitrogen, an aliquot of the ammonium

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solution obtained by distillation of the Kjeldahl digest is concentrated and the N2 produced by treatment of this concentrated solution with alkaline hypobromite is transferred to a mass spectrometer for isotopic analysis. The analyses for total nitrogen in the system studied and the determinations of the "N concentration of this nitrogen and of the N2 to which the system was exposed permit calculation of the amount of "N2 fixed. Akkermans (1971) and MacRae (1975) have reported use of emission spectrometry instead of mass spectrometry for 15N analysis in studies of lsN2 fixation. The 15N2 required for the procedure described can be purchased as such or can be prepared from "N-enriched ammonium by the method described by Burris and Wilson (1957). In this method, ammonia is generated from an ammonium salt with sodium hydroxide solution, and the ammonia is circulated over hot copper oxide in a gas-tight system to convert it to N2 . "N-enriched N2 also can be generated by treatment of ammonium salts with alkaline hypobromite solution in the apparatus described by Rittenberg et al. (1939) for conversion of ammonium to N2 for mass spectrometer assay of "N or in modifications of this apparatus (see Burris, 1974). Whatever method is used to generate l5 N-enriched N2, this gas should be purified before use to remove nitrogen oxides and other impurities. Use of unpurified "N, has been a common source of error in tracer studies of nitrogen fixation. Reputedly pure l s N 2 can be purchased commercially, but users should be warned that some suppliers do not effectively remove nitrogen oxides and other impurities from their products. Steyn and Delwiche (1970) used acidified FeS04 solution, a liquid nitrogen trap and an ascarite filter to remove impurities from "N2 to be used for research on nitrogen fixation. Burris (1972, 1974) recommends use of a KMn04-KOH solution for removal of nitrogen oxides and of a H2 SO4-NaZ SO4 solution for removal of ammonia. b. "N2 Reduction versus Acetylene Reduction. Many workers studying nitrogen fixation by the acetylene reduction method have calculated Nz fixed from estimates of C2H2 reduced by using the theoretical conversion factor (C2H2 reduced/N, fixed) of 3.0. Burris (1972,1974) has been highly critical of this practice and has exhorted users of the acetylene reduction method to establish valid conversion factors for assessment of nitrogen fixation. He also has stressed that reduction of "N2 is the primary method of choice for validation of results obtained by the acetylene reduction and other indirect methods of measuring nitrogen fixation and has emphasize that, to interpret acetylene reduction data in terms of nitrogen fixation, it is essential to measure 15N2and acetylene reduction for the same exposure times under identical conditions. Despite Burris's admonitions, very few comparisons of the acetylene reduction and Is N2 reduction methods have been reported, presumably because most users of the acetylene reduction technique lack the facilities for "N work. Recent review of literature relating to factors for calculation of nitrogen

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fixation from acetylene reduction data indicate that the average of experimentally determined factors for legumes is about 3.4 (Hardy et al., 1973; Criswell et al., 1975). Average factors calculated for other N2-fixing systems are about 3.6 for nitrogenase in vitro, 4.3 for bacteria, 3.2 for blue-green algae, and 2.4 for nonlegumes. Most of the experimentally determined factors for soils have ranged between 3.0 and 6.3, but much higher values (up to 25) have been obtained for soils under waterlogged or anaerobic conditions. Only a few of the conversion factors thus far reported have been established by comparing acetylene reduction and lSN2 reduction under identical conditions as recommended by Burris (1972, 1974). Although such comparisons are clearly essential for reliable interpretation of acetylene reduction data in terms of nitrogen fixed, until more users of the acetylene reduction method acquire the capacity for "N work it may be more useful to stress the need for adequate controls in use of the acetylene reduction technique. A survey of the several hundred papers in which this technique has been used to study nitrogen futation indicates that very few investigators have performed control experiments to check that the N2 - f d n g system under study does not produce ethylene in the absence of acetylene and does not take up ethylene produced by reduction of acetylene. The need for such controls has been indicated by accumulation of evidence that soils and other natural systems can take up ethylene and can produce ethylene in the absence of acetylene. Also, the need to check that materials used to construct sealed systems for studies of acetylene reduction do not sorb or evolve ethylene has been indicated by the finding that rubber can both sorb and evolve this gas (Kavanagh and Postgate, 1970). 2. Mineralization-Immobilization More than 130 papers reporting the use of ''N in studies of turnover of organic nitrogen in soils have been published, over 60%of which have appeared since 1970. The aspects of turnover studied have included: The chemical nature of soil organic matter; the distribution of immobilized nitrogen among different chemical fractions of soil; straw decomposition; enzyme activity during turnover; residual value of immobilized nitrogen; the rate and extent of turnover, as affected by different forms of inorganic nitrogen, other salts, nitrification inhibitors, soil water content, temperature, alternate wetting and drying, presence of living microorganisms and higher plants, and soil sterilization; and extent of turnover in forest, paddy, and nonflooded agriculture soils. a. Net ?"ransfomation. Turnover is the process in soil whereby losses and gains of organic matter occur simultaneously. It has been defined as the flux of organic nitrogen going through the organic matter, as modified by the inorganic nitrogen pool. The net reactions are of practical importance in regard to crop

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production and efficient use of nitrogen fertilizers, but study of net transformations contributes little to an understanding of the extent and nature of the separate opposing reactions. For study of the individual soil nitrogen transformation processes and their interrelationships, use of "N is essential. Studies with "N suggest that soil organic matter acts as two interacting organic pools-a relatively small, active and readily mineralizable pool consisting of the living and newly deceased biomass (fresh organic residue) and a larger, more passive pool containing 8 5 9 0 % of the total soil organic nitrogen (Jansson, 1958). Inorganic nitrogen entering the labile pool may be immobilized temporarily. Some portion of this nitrogen may remineralize and some may revert to forms increasingly resistant to biological and chemical degradation (Broadbent and Nakashima, 1965; Allen et al., 1973). The processes leading to organic matter stability are not well understood. Several equations have been proposed for describing changes in the levels of soil organic matter and its carbon and nitrogen components (for a review of these equations, see Jenkinson, 1966a). Unfortunately, few data are available from field studies to test the validity of these equations and most of the limited data available describe changes only in the nitrogen component of soil organic matter during turnover. For these data to be useful, it must be assumed that changes in soil organic nitrogen accurately reflect changes in soil organic matter. Whether changes in organic matter, organic carbon, and total nitrogen occur in a parallel manner depends on the amount of inorganic nitrogen present in the soil and on the amount and C/N ratio of the fresh organic material added to the soil, among other factors. It cannot be assumed that materials of similiar C/N ratios will decompose at the same rate or that all chemical fractions of a single organic material will decompose to the same extent. Several investigators (Jenkinson, 1966b; Sauerbeck and Fiihr, 1966; Scharpenseel, 1966) have called attention to the need for obtaining uniform carbon-labeling in plant materials used in turnover studies and it follows that uniform "N-labeling in such materials is also essential. The technique of multiple labeling using "N and I3C, 14C, and/or other isotopes has the greatest potential for following the course of soil organic matter turnover. Over 50 papers have been published in which "N has been used with other isotopes in turnover and related studies. Most of these studies have been variations of studies made previously. Although they have provided additional data relating to the dynamic equilibria in soils, they have been concerned largely with the measurement of net transformations and have contributed little to enlarging our concept of biomass dynamics. More step-by-step studies are needed in which metabolic intermediates are identified by taking numerous samples at short time intervals over a long period of time. Such work involves processing tens of hundreds of samples for chemical and isotope-ratio analysis, but rapid

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and accurate methods of analysis are now available for easing the work load. It is important that turnover and related studies be verified by detailed work in productive ecological systems under practical farm situations. b. Priming Effect. Fresh organic matter or inorganic nitrogen added to soil may stimulate or retard the decomposition of organic matter already present in the soil. This priming effect, known also as the priming action of soil amendments, was first studied with tracers in relation to carbon balance in soil, but recent studies with "N reflect considerable interest in the priming action as it affects nitrogen balance. Jenkinson (1966b) in his review of the priming action of 14C-labeled green manures suggested that the priming action in the field could be determined by making a series of I4C measurements on labeled plant material added to two plots, one of which is subsequently bare-fallowed and the other cropped. A similar procedure can be used with "N, alone or in combination with other isotopic tracers. An increase in mineralization after addition of fertilizer nitrogen has been observed in studies with "N in the laboratory (Broadbent, 1965; Andreeva and Scheglova, 1968; Broadbent and Nakashima, 1971; Westerman and Tucker, 1975), the greenhouse (Low and Piper, 1957), and the field (Westerman and Kurtz, 1973). Jansson (1971) questions whether the observed increase in mineralization is caused entirely by a priming action of added nitrogen on mineralization. He points out that during the early stages of incubation following addition of organic residues or fertilizer to soil, temporary changes in biomass activity, and, therefore, turnover give results that are erroneously interpreted as a priming effect. Nevertheless, increasing the amount of inorganic nitrogen added to soil apparently results in corresponding increases in the mineralization of soil organic nitrogen (e.g., Leg and Stanford, 1967; Atanasiu, 1968; Andreeva and Scheglova, 1969). Jansson (1971) attributes this effect not to a real stimulation of mineralization but to a dilution of the labeled inorganic nitrogen pool. In his view, mineralized nitrogen either may be immediately reimmobilized or it may mix with the inorganic nitrogen pool, thereby diluting added inorganic nitrogen. The larger the size of the inorganic pool, the smaller the amount of mineralized nitrogen that is reimmobilized (part of the nitrogen being immobilized is the added, labeled nitrogen). This explanation of the apparent effect of nitrogen fertilizer additions on mineralization is supported by the work of Stewart et al. (1963) and NUmmik (1968), but is questioned by Broadbent (1965) and Broadbent and Nakashima (1971), who observed increased mineralization of soil organic nitrogen following solubilization of the organic matter by added ammonium and other salts, this solubilization resulting from pH and osmotic concentration changes in soil after salt addition. Others take the view that addition of ammonium salts stimulates microbial activity (Westerman and Kurtz, 1973; Westerman and Tucker, 1975), a view that differs from Jansson's biological interchange concept in that it considers the priming action to be real,

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involving an increase in net mineralization. Legg and Stanford (1967) also consider the priming action to be real, but to be the result of decreased immobilization and increased mineralization in the rhizosphere where, in the absence of fertilizer nitrogen, the C/N ratio is high compared to that of the total soil organic matter. Negative priming effects also have been observed (Cadet and Soubies, 1966), especially in the presence of high concentrations of salts applied with ammonium (Westerman and Tucker, 1975). Laura (1974, 1975) has recently suggested that the apparent priming effect of ammonium fertilizers results from proton transfer reactions in soils. This suggestion is based on his hypothesis that ammonium is formed chemically in soils. According to this hypothesis, it is protons in the soil environment rather than microorganisms which cause ammonium formation and any factors which increase the supply of protons in soils increase the mineralization of soil nitrogen. To account for the priming effect of ammonium fertilizers, Laura (1975) postulates that ammonium ions supply protons to nitrogenous bases in soils and thereby accelerate mineralization of these bases. None of the suggested explanations of the apparent priming action of nitrogen fertilizer additions completely explains the observed net effects. It is not begging the issue to conclude that several mechanisms can be involved in producing a partly real, partly apparent priming effect. We have dealt with this phenomenon in some detail because it has been a source of controversy since it was first reported by Lohnis (1926) in relation to carbon balance and because the question of whether the priming action is real, partly real, or results from misinterpretation of "N data affects the correct use of nitrogen tracers in studies of turnover and plant uptake of applied fertilizer nitrogen. 3. Plant Recovery of Applied Nitrogen

There is increasing concern for maximizing the efficiency of fertilizer nitrogen use in crop production and this concern is reflected in the exponential increase in the use of "N to study the uptake of applied nitrogen. About 100 papers concerning recovery of "N-labeled fertilizers by crop plants were published during the period 1942-1968. Slightly more than one-half of these appeared during the last 3 years of this period. Since 1968, more than 150 additional papers on this topic have been published. The majority of these papers report empirical data which are largely of local interest, and relate mainly to the single-season uptake of applied fertilizer nitrogen, as affected by various soil characteristics and management practices. The main test crops have been pasture grasses, oats, wheat, and rice. This is understandable because experiments with grasses and small grains can be made using smaller plots requiring less tracer nitrogen than experiments with larger plants such as maize. Much of the

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information on crop recovery of applied nitrogen could have been obtained with less effort and expense without use of "N. We advocate the use of "N only when the information needed can be obtained in no other way, or use of "N provides a more accurate or convenient method of study, or its use provides information in addition to that obtained from a nontracer experiment. a. Tracer versus Nontracer Methods. The recovery of applied nitrogen by plants can be determined by any one of four methods: (i) In the difference method, the amount of applied nitrogen taken up by the crop is calculated as the difference between total nitrogen uptake from fertilized and unfertilized plots. Users of this method assume that immobilization-mineralization and other nitrogen transformations during the course of the experiment are the same for both treated and untreated soils. As already noted in the discussion of the real or apparent priming action, this assumption usually is not valid. (ii) In the isotope dilution method, the amount of fertilizer nitrogen taken up by the plant is calculated from the results of total nitrogen and nitrogen isotope-ratio analysis of plant samples taken from the fertilized plot [see Eq. (1 l), Section IV, C] . No data from control plots are required. (iii) Where multiple rates of nitrogen have been used, crop recovery of applied nitrogen can be calculated by linear regression. For nontracer studies, calculations of linear regression of total nitrogen in plants on rates of applied nitrogen are made from

Y=atbX where Y is the total nitrogen in plants, a is the intercept which represents total nitrogen in plants where no nitrogen has been applied (control plots), b is the regression coefficient (100 b is the percent applied nitrogen recovered), and X is the amount of applied nitrogen. (iv) Where multiple rates of "N-labeled nitrogen have been used, Eq. (16) is used to calculate the linear regression of applied nitrogen in plants, where Y is the amount of applied nitrogen taken up by the plant, a theoretically is zero because it is the intercept which represents the amount of applied nitrogen in the control plants (no control is used), b is the regression coefficient, and Xis the amount of applied "N-labeled nitrogen. Linear regression of total nitrogen in plants on rates of nitrogen applied [nontracer method (iii)] has given higher values for recovery of applied nitrogen by plants than linear regression of labeled nitrogen in plants on rates of labeled nitrogen [method (iv)] , but recovery values determined by tracer methods (ii) and (iv) have been found to be similar (Westerman and Kurtz, 1974). The determination of percent recovery of applied nitrogen by the difference method [indirect, nontracer method (i)] usually gives higher values than those obtained by isotope dilution [direct, tracer method (ii)]. In eight nitrogen fertilizer trials summarized by b u c k (1971a), recovery values obtained with method (i) ranged from 3 to 7% higher (e.g., 60% versus 67%) than those obtained with method (ii). However, in two other experiments, each involving

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two lSN-labeled fertilizers at three nonzero rates of application, Westerman and Kurtz (1974) found the indirect method to give nitrogen recovery values 17-35% higher, and they have suggested that use of "N-labeled nitrogen is almost essential for estimating nitrogen recovery in many argonomic experiments. This view is held also by Fried et al. (1975), who advocate the use of a single rate of labeled nitrogen application. However, Terman and Brown (1968) and Jansson (1971) suggest that "N tracer methods offer no distinct advantage over nontracer methods in most studies of nitrogen fertilizer efficiency when multiple rates are used. In our view, it is incorrect to assume that nitrogen tracer methods necessarily give a more accurate value than the nontracer methods. All methods involve use of assumptions that may not be entirely valid leading to some error in data interpretation. Users of the indirect methods (i) and (iii) must erroneously assume that addition of nitrogen to the soil does not alter the amount of soil nitrogen taken up the plant. However, users of the direct tracer methods (ii) and (iv) assume that their interpretation of the "N data is not confounded by the unknown extent of biological interchange of labeled nitrogen with unlabeled soil nitrogen. It is reasonable to assume that the determination of percent recovery of applied nitrogen by plants can be made more accurately through use of "N, but it can be said with certainty only that nitrogen tracer and nontracer methods usually give different recovery values. The difference in these values is less when the amount of soil nitrogen mineralized during the experimental .period is small, the total amount of nitrogen removed from the soil by the plant is small, and/or when measurements of nitrogen recovery values are made at the end of the growing season (the difference in recovery values usually is greatest during the early harvests of a sequential harvest experiment). b. A-Value Concept. This concept is derived from the assumption that a plant having two sources of a nutrient will absorbe this nutrient from these sources in direct proportion to the amount available (Fried and Dean, 1952). The quantity of available nutrient in the soil can be estimated in terms of a standard amount of that nutrient added to soil by using the relationship

where A is the amount of nutrient available in the soil, B is the amount of nutrient in the standard, and y is the proportion of the nutrient in the plant derived from the standard. Where "N-labeled fertilizers are used, y is the percent of the total nitrogen in the plant derived from fertilizer. Equation (17) is a modified form of Eq. (9) which is used to calculate the amount of compound in an unknown mixture by isotope dilution analysis. A-values have been calculated for soil nitrogen using "N-labeled nitrogen as the standard. For a particu-

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lar soil-plant system, the A-value has been reported to remain constant with different amounts of applied nitrogen (Legg and Stanford, 1967; Aleksic ef al., 1968; Fried and Broeshart, 1974), which implies that the amount of soil nitrogen taken up by the plant is a direct linear function of the amount of nitrogen applied. This is possible only when addition of nitrogen in different amounts causes a corresponding increase in the amount of soil nitrogen made available to the plant, and the effects of any transformation process such as denitrification or immobilization which reduces the amount of added nitrogen must be balanced by processes that cause a corresponding decrease in the amount of available soil nitrogen. Fried and Dean (1952), in their original paper on the A-value concept, called attention to several restrictions imposed on the correct interpretation of A-values in regard to plant uptake of nutrient. Of these it is important to note that the expression A refers to nutrient that is derived from a single source only of that nutrient in soil, which means that “each form of nutrient will have a coefficient of availability peculiar to it and the environmental condition.” They pointed out the necessity of setting up suitable methods of experimentation in order to meet the restrictions on availability of soil nitrogen imposed by the growth pattern of plants, nonuniform availability of added and soil-derived nutrient, soil characteristics, and other factors. Broadbent (1970) calculated A-values from several nitrogen fertilizer trials published in the 15N literature and concluded that use of the A-value as an index of nitrogen availability in soils requires careful definition of conditions under which it is determined. We discuss the A-value concept here because of recent disagreements concerning the value of A-values as a basis for evaluating factors responsible for the priming effect (Fried and Broeshart, 1974; Westerman and Kurtz, 1974; Laura, 1975) and because of the use of A-values in single-treatment nitrogen fertilizer experiments using 15N (Fried et al., 1975). In our view, A-values, being undefined at zero rates of nitrogen application, are no more valuable in explaining the real or apparent priming effect than other mathematical transformations that must be extrapolated to zero. The value A in Eq. (1 7) is a function of y and B, both of which are subject to errors of analysis and interpretation. In tracer studies, the quantity y , the proportion of nitrogen in the plant derived from the added labeled fertilizer, is calculated from ”N data, and in making the calculation, it is assumed that turnover processes have not changed the 15N concentration of the labeled nitrogen soon after its addition to soil. In addition to biological effects, rapid chemical exchange and interchange reactions also can affect the ”N concentration of added nitrogen. Stojanovic and Broadbent (1960) found the amount of ”N-labeled ammonium extracted from different soils immediately after addition to be influenced by the method of preparing soil prior to extraction, ammonium salt used, soil pH, ammonium-fixing capacity, and other soil characteristics. The influence of such factors during the time interval between ammonium addition to, and “immedi-

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ate" extraction from soil can alter the nitrogen isotope concentration and amount of N-labeled ammonium extracted from soil at zero experimental time, and this, in turn, can affect the apparent values for amount and "N concentration of nitrogen which are used in calculating plant uptake of added nitrogen, In the single-treatment method of studying nitrogen fertilizer recovery by plants, "N-labeled fertilizer is used in only one of several plots that represent various treatments such as fertilizer source, time of application, or fertilizer placement (Fried et al., 1975). All treatments, as far as the plant and soil are concerned, are said to be identical, the only difference being which of the fertilizer applications within a given treatment is labeled with "N. However, the method relies on the constancy of the A-value for a given soil, and as already indicated, the A-value for a given soil can change depending on conditions of the soil-plant system. We offer here no definitive answer to questions concerned with accurate determinations of the proportional uptake of soil and fertilizer nitrogen by plants but have discussed some of the potential sources of minor and major errors. The addition of nitrogen fertilizer to soil at nontoxic rates has several actual or apparent effects on soil nitrogen transformation and plant uptake of nitrogen: (i) Mineralization of soil organic matter is increased, which tends to increase the available nitrogen pool and decrease its average N concentration; (ii) immobilization of added and perhaps mineralized nitrogen is increased, which tends to decrease the available nitrogen pool and also decrease its average "N concentration; (iii) growth of the plant is increased, which increases the volume of soil explored for nitrogen by the plant roots, and (iv) the plant becomes healthier, thereby absorbing and using more nitrogen or using it more efficiently. Effects (i) and (ii) are involved in the priming action and may lead to some misreading of tracer data. Effect (iii) is minimized in a greenhouse pot experiment and is largely a function of plant characteristics and crop management practices. The rationale for effect (iv) has been developed in nutrient culture work but it is difficult in field work to determine the extent to which plant physiological characteristics enhance nitrogen uptake and use. Clearly, much of the confusion concerning the effects of soil nitrogen transformations on the efficient use of nitrogen by plants could be decreased by performing detailed step-by-step studies with "N, which are specifically directed toward assessing the validity of a particular explanation of these effects.

4. Denitnflcation Most estimates of nitrogen loss from soils via denitrification processes are based on presumptive evidence, i.e., the estimate of loss is not based on direct measurement of all nitrogen gases known to be evolved, but is obtained by

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indirect means. The indirect method most commonly used involves measurement of the difference in nitrogen content of a system at the beginning and end of an experimental period, t h i s difference being presumed to represent the denitrification loss (other known loss mechanisms and analytical errors having been taken into consideration). In numerous studies, decrease in the content of substrate nitrate has been equated with denitrification loss. In other studies, measurement of N 2 0 in the soil atmosphere has been used as an index of total denitrification in field soils (e.g., Roulier and Fetter, 1973) and measurement of the degree of N 2 0 saturation of seawater has been used to estimate denitrification losses from Oceans (e.g., Hahn,1974). Sampling and anlaytical errors can serious limit the accuracy of estimates of denitrification loss when such estimates are made by indirect methods. Foremost among the analytical errors is that associated with the determination of total nitrogen, especially where the amounts of fixed ammonium, nitrite, and nitrate in the system being analyzed are appreciable. Loss of nitrogen during the drying and preparation of wet soil for analysis also may lead to serious error. As indicated previously, the accuracy of the estimate of denitrification loss can be improved through use of the isotope dilution technique. Considerably more accurate estimates of denitrification loss in small-scale laboratory systems can be made by following the decrease in added nitrate over time. Use of 15N is advantageous in such studies to estimate the extent to which the added labeled nitrate pools with residual nitrate and nitrate produced in the soil through mineralization. Stanford et al. (1975) question whether nitrate disappearance is an accurate index of denitrification for all soils because they found that substantial amounts of labeled nitrate were reduced to ammonium and assimilated by microorganisms during anaerobic incubation of some soils. MacRae et al. (1968) found that from 8 to 41% of the nitrogen added as labeled nitrate to 4 of 6 soils studied was converted to organic nitrogen after 6 weeks incubation under waterlogged conditions. On the other hand, Wijler and Delwiche (1954) and Nommik (1956) found only negligible amounts (<1%) of ammonium produced and assimilated from nitrate under anaerobic incubation in soils. Our present knowledge indicates that the presence of certain denitrifying organisms such as Bacillus licheniformis (Stanford el al., 1975) and the amount of carbon available to the denitrifying microorganisms are the important factors controlling the production of ammonium, nitrite, and nitrogen gases in denitrifying soils (Burford and Bremner, 1975). It is suggested that researchers using the indirect method of estimating denitrification loss by following decrease in substrate nitrate ascertain with "N whether nitrate reduction to ammonium is appreciable for each soil system under study. Few estimates of denitrification loss from soils have been made by direct measurement of the gases evolved. Semi-direct methods have included systems which measure increase in gas pressure [e.g., the use of a Van Slyke technique by

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Yamane (1957)]. Direct measurements have been made by one of two methods. First, the gases formed during denitrification are permitted to evolve into a confined space containing a Nz-free atmosphere, usually consisting of a mixture of oxygen and argon or helium. [A neon atmosphere was used by Nommik and Thorin (1972), the neon being used also as an internal standard.] The nature and amounts of evolved gases are then determined by gas chromatography or mass spectrometry. Use of tracer nitrogen is not essentia for making accurate measurements of the nitrogen gases evolved into a N2-free atmosphere, but in the absence of a labeled substrate, the fractional contribution of each source of the evolved gases cannot be determined. Methods that use a Nz-free atmosphere cannot be adapted for use in the field because of the near impossibility of purging an in situ field soil of Nz. Use of a labeled substrate is essential to the second direct method of estimating denitrification. In this method, labeled nitrogen gases are permitted to evolve into a confined but otherwise natural (insofar as possible) atmosphere. In the case of Nz, the problem is to measure a relatively small amount of Nz evolving into an atmosphere containing over 78%Nz . The refinements and limitations of the apparatus required to do this have been reviewed by Ross et al. (1964) and Hauck (1966). Two major problems are (i) maintaining a natural atmospheric composition and environmental condition in the close system and (ii) designing a suitable small-volume system into which the gases are evolved. Too small a volume creates problems associated with reabsorption of the evolved gases by soil. Too large a volume reduces the sensitivity of measurement. Measurement of the evolved gases is made using a mass spectrometer or, preferably, a mass spectrometer for Nz and an infrared spectrophotometer for NzO. Calculations of mass spectrometer isotope-ratio data for Nz cannot be based on the usual equation at. % ” N = 100R‘/(2 t R ’ )

(4)

where R’ is the corrected M/e ratio 29/28. As already discussed, t h i s equation is based on a random distribution of the three molecular species of Nz ,a distribution not obtained during chemical of biological processes which lead to the formation of Nz molecules from nitrogen atoms derived from two or more compounds having different nitrogen isotope compositions (Hauck et al., 1958; Hauck, 1966). The evolved Nz and the original atmospheric Nz contain different sets of l4NI4N, 14N1’N, and lsN”N molecules which retain their isotopic identities; that is, these different sets of molecular species do not measurably proceed toward an isotope exchange equilibrium. The accurate estimation of evolved Nz [for method of calculation, see Hauck (1966)l requires the measurement of masses 28,29, and 30, which, in turn, requires that the ‘s N enrichment of the substrate being denitrified is sufficiently high e l 0 at. % “N) to insure the production of measurable amounts of ”N”N. However, the fact that the

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14N and "N atoms of the evolved N2 and original atmospheric N2 are not randomly distributed in the mixture permits one to calculate the average "N enrichment of all sources of nitrogen which contributed to the evolved N2. This calculation can be made periodically with no need to sample the substrate. Its possible usefulness in determining the extent of mineralization-immobilization in a denitrifying system has been discussed by Hauck (1966). Goering and Dugdale (1966) found this calculation useful in their study of denitrification in ocean water. The resolution of mass spectra obtained with the gaseous products of denitrification has been discussed by Cady and Bartholomew (1960). The accurate calculation of amounts of evolved gases is, at best, difficult, because of contributions of more than one constituent to the peak heights at masses 28,30, and 44. We prefer to separate N2 from N 2 0 by freezing or by use of a gas chromatographic technique, before analysis. Guiraud and Berlier (1970) suggest that the accurate determination of N2 and N 2 0 is possible only after such separation. Nevertheless, studies continue to be reported in the literature where no attempt has been made to estimate the error involved in failure to recognize the nonrandom distribution of 14N and "N among different molecular nitrogen species or the contribution of contaminating ion fragments on the mass spectrum. For a fuller discussion of these and related problems, see Hauck and Melsted (1956), Hauck and Bremner (1964), and Cheng and Bremner (1965). Measurements of N 2 0 distribution within soil profiles have been reported, but, to date no accurate quantitative estimate of denitrification loss has been made in the field by direct measurement of N2 and N 2 0 . Apparatus is available which meets several requirements for field studies, but such apparatus is more useful for studying rates of gaseous diffusion in soil and as a field respirometer (McGarity and Hauck, 1969). The gas-tight laboratory growth chamber (gas lysimeter) of Ross et al. (1964,1968) remains as the most satisfactory approach to a simulated field environment plant-soil system which can also be used for making direct measurements of evolved nitrogen gases. Stefanson and Greenland (1970) using similar chambers (with an oxygen-argon atmosphere but no N) reported patterns of N2 and NzO evolution similar to those obtained in the field. Despite the limitations imposed by a confined atmosphere, use of the field respirometer with ''N appears to be the most promising approach to quantifying denitrification in the field.

5. Nitrogen Movement World consumption of fertilizer nitrogen has increased tenfold during the period 1950-1975 (from 3.8 to 38.7 million metric tons), and it will continue to increase rapidly, because the world's need for food and fiber cannot be met without greatly increased use of fertilizer nitrogen. This trend will result in increased levels of nitrogen in soils, natural waters, crop residues, and municipal

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and agricultural wastes, and there is increasing concern about its potential adverse effects on environmental quality. The concentration of nitrate in some surface and ground waters in technologically developed countries has increased in recent years. The main sources of this nitrate can usually be identified, but their relative contributions are difficult to assess. Nitrogen tracer techniques are now being used to study the fractional contribution of soils and nitrogen fertilizers to nitrate enrichment of water resources. Until recently, the high cost of ” N has mitigated against large-scale field studies of plant uptake, soil transformations, and movement in soil of applied nitrogen using management practices typical of productive agricultural systems. Two main developments now make such studies practical. One is the increased level of funding of studies bearing directly on the quality of the environment. The second is the increased availability of nitrogen tracer materials at substantially lower cost, compared to 5 years ago. Several research programs in the United States using nitrogen tracers are currently directed toward studies of nitrogen fertilizer use and its effects on water quality (Broadbent, 1975; Carlton and Hafez, 1973; Hauck and Kilmer, 1976; Matiwiyoff etal., 1975). It remains a major task to prepare for accurate nitrogen isotope-ratio analysis the thousands of plant, soil, and water samples generated annually by these programs. Although rapid and convenient methods are available for the determination of total nitrogen in plants and soils and inorganic nitrogen in water and aqueous extracts, no convenient method is available for concentrating ammonium and nitrate nitrogen in water samples to give an aliquot containing sufficient nitrogen for accurate isotope-ratio analysis by mass spectrometry. Evaporation of solutions to concentrate their solutes can introduce serious error through crosscontamination of samples with isotope or through loss of nitrogen, in addition to being time-consuming, wasteful of laboratory space, and otherwise inconvenient. Currently under development in our laboratories is a technique whereby ammonium or nitrate nitrogen in low concentrations (e.g., 1-10 ppm) is extracted from water samples (500-1000 ml) with an appropriate ion exchange, resin, after which the nitrogen is liberated from the resin during steam distillation (ammonium nitrogen is steamdistilled directly from the resin after addition of excess potassium or sodium ions and MgO; nitrate nitrogen is quantitatively removed from the resin during its reduction to ammonium by Devarda’s alloy in th epresence of excess chloride ion and MgO). A second technique under test for preparation of inorganic nitrogen in water samples for isotope-ratio analysis uses the principle of isotope dilution.

B.

”N-DEPLETED

MATERIALS

N ( Is N-enriched Materials with a greater than natural concentration of materials) have been used in most nitrogen tracer studies. Materials with a lower

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than natural concentration (I' N-depleted materials) also can be used as tracers (see Section I, A). Several chemical exchange processes that concentrate "N in nitrogen compounds concommitantly produce these compounds with very low "N concentrations (Spedding et al., 1955;United States Atomic Energy Commission, 1971). About 100 kg of ammonium sulfate low in I5N concentration (0.03 at. % I5N) was prepared at the Ames (Iowa) Laboratory of the Atomic Energy Commission during the 1950s.This material had accumulated during the preparation of "Nenriched ammonium sulfate by a cation exchange method (Spedding et al., 1955). As mentioned in Section V, substantially larger amounts (several hundred kilograms) of N-depleted ammonium sulfate (containing 0.009-0.003 at. % "N) have recently been produced at the Los Alamos Scientific Laboratory in New Mexico by cryogenic distillation of nitric oxide. The first use of "N-depleted materials as tracers in agronomic studies was reported by Edwards and Hauck (1968, 1974) who compared "N-depleted ammonium sulfate (0.031 at. % "N) and "Nenriched ammonium sulfate (0.739 at. % "N) as tracers in studies of nitrogen uptake by ryegrass (Lolium multifzomm) in the greenhouse. Their results and those of Starr et al. (1974) show that "Ndepleted nitrogen fertilizer added to soil can be measured with accuracy and precision in plants cropped to the soil and that the use of such fertilizer gives nitrogen recovery values similar to those obtained with fertilizer containing "N at a comparable level of enrichment. The first large-scale use of "N-depleted ammonium sulfate was initiated in 1972 by the University of Illinois in cooperation with the Tennessee Valley Authority at the Northeast Agronomy Research Center, Elwood, Illinois, in a nitrogen balance study conducted on large (15.4 X 3.1 m) lysimeter plots cropped to maize (Zea mays L.) [for a description and preliminary results of this study, see Hauck and Kilmer (1976)l. About the same time, large-scale field trials with "N-depleted ammonium sulfate were initiated in the San Joaquin Valley by the University of California (Carlton and Hafez, 1973). Since 1972, more than 1500 kg of "N-depleted ammonium sulfate have been used in field experiments conducted by the Agricultural Research Service, United States Department of Agriculture, and the land-grant universities in cooperation with the Tennessee Valley Authority. Maize has been the test crop in most of these studies, but "N-depleted ammonium sulfate has been used in studies with soybeans (Glycine m a ) and bell peppers (Capsicum spp.) (see Hauck and Kilmer, 1976)and rice (Oryza sativa L.) (Patrick et al., 1974). Use of "N-depleted materials as tracers presents few problems other than those also encountered with the use of Nenriched materials. Currently isotoperatio analysis of the nitrogen in samples must be made by mass spectrometry (present-day emission spectrometers are not sufficiently sensitive to N concentrations below 3000 ppm for isotope-ratio analysis of "N-depleted materials). Most mass spectrometers currently in use in laboratories engaged in soil and fertilizer nitrogen research have a precision of at least k0.002 at. % "N, which

''

''

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will permit detection of "N-depleted nitrogen after it has been diluted 180-fold by nitrogen of a natural isotope composition. Therefore, the use of "Ndepleted materials is restricted to experimental systems where excessive dilution does not occur, e.g., in single-season studies of plant uptake of applied nitrogen or movement of applied nitrogen from soils to waters. Highly sensitive mass spectrometers are available which will permit detection of Is N-depleted nitrogen diluted almost 2000-fold with naturally occurring nitrogen, but their use usually does not significantly extend the usefulness of l5 N-depleted materials because the variations in "N concentration of naturally occurring nitrogen may fall within the increased limits of detection. For example, if nitrogen fertilizer containing 0.003 at. % "N is diluted 180-fold, the resultant concentration of the diluted fertilizer is 0.364 at. % "N, a concentration which may well be within the range of Is N concentrations of naturally occurring nitrogenous constituents of soils (see Section VI, C). Fertilizer depleted in "N is of little value for studies of plant uptake of residual soil nitrogen. Where information on residual nitrogen is desired, nitrogen materials containing 5-10 at. % "N are required. Several large-scale field studies using "N-depleted ammonium sulfate currently in progress have adjacent to them small-scale companion experiments using l5 N-enriched materials, the information obtained from these two groups of studies being complementary. Kilmer er al. (1974) presented an outline of research topics for use of "N-depleted versus "N-enriched nitrogen fertilizers, with special reference to studies on nitrogen fertilizer use and its effect on water quality. C. USE OF VARIATIONS IN NATURAL NITROGEN ISOTOPE ABUNDANCE

Over 60 papers have been published on the occurrence of slight variations in the nitrogen isotope compositions of natural substances (see Hauck and Bystrom, 1970). These variations result from isotope effects during biological and chemical reactions involving nitrogenous substances and have been found in animal and plant proteins, atmospheric N2, coal, crude oils, minerals, nitrogen in natural gas, rocks, soils, and other natural substances [see Hauck (1973) for summary with references]. Fractionation of the nitrogen isotopes during biological processes has been observed in denitrification of nitrate (Wellman et aL, 1968) and in nitrification of ammonium (Delwiche and Steyn, 1970). The denitrification process produces gaseous nitrogen slightly depleted in N and residual nitrate (that remaining in the nitrate pool being acted upon) slightly enriched in "N. The nitrification process usually produces nitrite and nitrate depleted in "N and substrate ammonium enriched in "N (there is no net change in 15N concentrations if the reaction goes to completion in a closed system). The net result of these and other isotope effects usually is a slight increase in the average "N concentration of soil nitrogen (Cheng er al., 1964).

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Equations (7) and (8) calculate A15N, the difference in nitrogen isotope ratio between sample and standard (usually atmospheric Nz), where one A" N unit equals i0.00037 at. % *'N. A positive A" N value indicates a higher "N concentration than the standard and a negative value indicates a lower 15N concentration. The natural variations in nitrogen isotope abundances are small, usually within 10 AISN units, but A1' N values greater than *lo are not uncommon. Several publications have discussed the possible use of such variations for studies of nitrogen cycle processes (see Hauck, 1973). The authors in 1963 first became interested in variations in ''N abundance in soil nitrogen fractions as a possible source of error in nitrogen tracer work and concluded that this would not be a serious problem in the usual nitrogen tracer study. They concluded also at that time that use of variations in "N abundance in soils showed little promise for quantitative evaluation of nitrogen cycle processes. Recently, Kohl et aL (1971) reported estimation of the fractional contributions of soil and fertilizer nitrogen to nitrate in surface water in an Illinois watershed by a method based on the finding that the "N enrichment of total soil nitrogen is usually slightly higher than that of atmospheric N2 (Cheng et al., 1964) and on the deduction that the l5 N enrichment of soil-derived nitrate will be higher than that of fertilizer-derived nitrate. In this work, the soil, in effect, was being used as a nitrogen tracer, very slightly enriched in "N (conversely, the fertilizer nitrogen could be considered as a tracer, very slightly depleted in "N). The results obtained by Kohl et UL (1971) generated considerable comment, and the approach adopted in their work is open to a variety of criticisms (see Edwards, 1971; Hauck, 1971b, 1973; Hauck et aL, 1972) and there is evidence that it is invalid (Bremner and Tabatabai, 1973; Edwards, 1973). However, current studies are beginning to generate the kind of information that is needed to evaluate the possible use of variations in natural nitrogen isotope abundance in environmental studies (e.g., Meints et al., 1975; Shearer and Legg, 1975). Considerable additional work is needed for adequate evaluation of this approach to environmental studies. On the basis of current knowledge, we regard methods based on the use of variations in natural nitrogen isotope abundance capable of giving only qualitative (at best, roughly quantitative) information.

V I I. Perspective

Use of nitrogen isotope tracer techniques for research on soil and fertilizer nitrogen problems has increased markedly over the past decade, and it seems certain that tracer techniques will be used even more extensively during the next decade. The need for nitrogen tracer use is generally recognized by those engaged in research on nitrogen cycle processes, but use of nitrogen tracers has been restricted by the high cost of "N and by the difficulty of performing

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26 1

nitrogen isotope-ratio analysis. These restrictions have been reduced by recent developments leading to reduction in the cost of "N-enriched and "N-depleted compounds and by improvement and simplification of techniques for nitrogen isotope-ratio analysis. Although the costs and difficulties of using nitrogen tracers have been substantially decreased, many potential users lack the necessary equipment and funding for use of nitrogen tracers. This problem may be remedied in part by further improvement of techniques for nitrogen isotope-ratio analysis by emission spectrometry and by the development of less versatile, and therefore less expensive, mass spectrometers designed specifically for nitrogen isotope-ratio analysis at the level of precision and accuracy needed in most tracer studies on biological systems. The authors regret withdrawal from the market of single collector, peak-reading mass spectrometers which, although they could easily be improved, already give satisfactory results and which usually are faster and more convenient to use than the highly sensitive, more expensive mass spectrometers being marketed today. (There is, of course, also a need for these more sensitive instruments.) Recent advances in instrumentation leave little doubt that manufacturers of mass spectrometers could design relatively low-cost, easy to maintain instruments suitable for routine nitrogen isotope-ratio analysis, but they will not be persuaded to do this until there is a substantil demand for such instruments. Nitrogen tracer research on nitrogen cycle processes is now entering a new era. The availability of large and relatively dependable supplies of nitrogen tracer materials at costs several times less than they were a few years ago now makes practical for the first time large-scale nitrogen tracer studies in the field. Such studies are needed using management practices typical of productive ecological systems to find ways of maximizing the efficiency of soil and fertilizer nitrogen use in crop production without adversely affecting the quality of the environment. Only through use of "N-depleted and "N-enriched materials can accurate information be obtained on the movement of nitrogen into, within, and from soil. The improvements in Is N-tracer techniques now available may encourage intensive step-by-step study of opposing soil nitrogen processes, stimulate research on the role of residual soil nitrogen in productive ecological systems, and provide means of obtaining reliable quantitative information on nitrogen gains and losses in the biosphere.

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88,599-600. Schollhorn, R., and Burris, R. H. 1966. Fed. Proc., Fed. Am. SOC. Exp. Biol. 25, 710 (abstr.). Shearer, G.B., and L e g , J. 0. 1975.SoilSci. SOC.Am., Proc. 39,896-901. Silva, J. A., and Bremner, J. M. 1966.Soil Sci. SOC.Am., Proc. 30,587-594. Sirns, A. P., and Cocking, E. C. 1958.Nature (London) 181,474. Spedding, F. H.,Powell, J. E., and Svec, H. J. 1955.J. Am. Chem. SOC.77,61254132. Sprinson, D . B., and Rittenberg, D. 1948. US.Nav. Med, Bull., Suppl. pp. 82-93. Sprinson, D. B., and Rittenberg, D. 1949.J. Biol. Chem. 180,707-714. Stanford, G., L e g , J. O., Deziena, S., and Simpson, E. C., Jr. 1975.Soil Sci. 120, 147-152. Starr, J. L., Broadbent, F. E., and Stout, P. R. 1974.Soil Sci. SOC.Am., Proc. 38,266-267. Stefanson, R. C., and Greenland, D. J. 1970.Soil Sci. 109.203-206. Stein, T. P., Leskiw, M. J., Liquori, E. M., Brooks, H. B., Wallace, H. W., and Blakemore, W. S. 1975.Anal Biochem. 66,481488.

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NUCLEO-CYTOPLASMIC RELATIONSHIPS IN WHEAT

..

6 C M.Sage Plant Breeding Institute. Cambridge. England

I . Introduction .................................................. I1. Cytoplasmic Variation in Wheat .................................... A. Cytoplasmic Male Sterility in Wheat as an Indicator of Cytoplasmic Variation ................................................... B . Cytoplasm-Differentiating Genes ................................ C. Sources of Restoring Genes .................................... D . The Interaction of RestorerGene Sources and Particular Cytoplasms .... I11. The Genetics of Fertility Restoration ............................... A. Importance ................................................. B . Partial Restoration ........................................... C. Environmental Effects on Male Sterility and Restoration .............. D Types of Restoring Gene and Their Interaction ..................... E . Conventional Genetic Analysis .................................. F . Monosomic Analysis .......................................... G. A Hypothetical Mechanism for Restoration of Male Fertility. . . . . . . . . . . . H. The Development of Restorer Lines .............................. IV . Cytoplasmic Effects Other than Male Sterility ......................... A Deleterious Effects ............................................ B . Morphological and Physiological Effects ........................... C Advantageous Cytoplasmic Variation ............................. D. Restoration of Morphological and Physiological Effects ............... E . Summary of Nucleo-cytoplasmic Interaction Effects ................. V The Biological Basis of Nucleo-cytoplasmic Interactions ................. A. Intervarietal Cytoplasmic Variation: A GeneforGene Hypothesis ....... B . The Mechanism of Male Sterility ................................ C Nucleo-cytoplasmic Interaction at the Cellular Level ................. D. The Origin of Nucleo-cytoplasmic Interaction ...................... E . The Value of Possible Future Developments ........................ VI Cytoplasmic Variation in the Absence of Male Sterility .................. VII . Conclusion .................................................... References ....................................................

.

. .

.

.

.

267 268 268 269 272 274 274 274 275 275 279 281 282 283 283 286 286 287 288 289 289 290 290 290 292 294 295 295 296 297

I . Introduction

In the genetic improvement of wheat and other crop plants. workers have concentrated on nuclear variation and have tended to ignore the influence of the 267

268

G. C. M. SAGE

cytoplasm on plant development. The major exception to this general rule has been the considerable interest shown in cytoplasmically inherited male sterility and the nuclear genes that restore male fertility t o plants having aberrant cytoplasms. This work has had considerable economic consequences since in many crops cytoplasmic male sterility and restoring genes are the basis for the commercial production of hybrid varieties. The discovery of cytoplasmically inherited male sterility in wheat interspecies nuclear substitution lines (Klhara, 1951; Fukasawa, 1953; Wilson and Ross, 1962) precipitated extensive work on cytoplasmic differences in the Triticinae aimed at finding male sterility-restorer gene systems, comparable to those found in other crops, which might be utilized to produce hybrid wheat varieties. In this drive toward hybrid wheat it has become apparent that there is wide cytoplasmic variation in the Triticinae, that a wide range of plant characters are affected by nuclear gene-cytoplasmic interactions and that these interactions are very complex. However, the nature of some of this cytoplasmic variation suggests that in the future it may be of value in practical breeding programs and that breeders will become more conscious of cytoplasmic factors in wheat improvement. II. Cytoplasmic Variation in Wheat

A. CYTOPLASMIC MALE STERILITY IN WHEAT AS AN INDICATOR OF CYTOPLASMIC VARIATION

In numerous instances cytoplasmic male sterility has resulted from interspecific crosses followed by successive substitution backcrossing of the genome of one species into the alien cytoplasm of the other (Edwardson, 1970; Krupnov, 1971). In the resulting nucleo-cytoplasmic combinations (N-C combinations), the cytoplasmic effects on pollen fertility become apparent after sufficient backcrosses have eliminated all genes derived from the cytoplasm donor species. This, with one exception (Khara, 1968a), has always been the origin of cytoplasmic male sterility in wheat. If the imbalance in development brought about in N-C combinations by the interaction of nucleus and cytoplasm results in relatively stable male sterility, then it can be considered that the cytoplasms of the two species involved in the N-Ccombinations are distinct. On this basis the relative similarities and differences between the cytoplasms of Triticum aestivum and/or T. dumm and T. timophemi, on the one hand, and those of the other species of the Triticinae so far investigated are presented in Table I. Male sterility has been found to result from the incompatibility of T. aesrivum and/or T. durum genomes with 20 different cytoplasms, all of which

NLJCLEOCYTOPLASMICRELATIONSHIPS IN WHEAT

269

must therefore be distinct from the cytoplasms of T. aestivum and/or T. durum. Fewer cytoplasms have been shown to be distinct from that of T. timopheevi, since of the 12 cytoplasms in which the genome of T. timopheevi has been tested only three cases resulted in male sterility. Much of Table I is based on the work of Maan and Lucken (1972), and Maan (1973d). They found that, in general, the T. durum genome was more sensitive to the alien cytoplasms than the T. aestivum genome. Fewer backcrosses were necessary to eliminate all the nuclear genes or chromosomes from the cytoplasm donor species in the substitution backcross series of T. durum than in the substitution backcross series of T. aestivum. Consequently, cytoplasmic effects, which in some cases affected other plant characters in addition to pollen production, were usually observed in early backcross progenies of the T. durum series but became apparent only in advanced backcross progenies in the T. aestivum series. This has led to occasional confusion in the literature when reports have been made only to be altered after further backcrossing has been carried out. Within the group of cytoplasms shown by the manifestation of male sterility to be distinct from those of T. aestivum and T. durum, further classification can be made according to the additional phenotypic effects shown by the N-C combinations. It can be seen from Table I that some cytoplasms result in loss of vigor with both T. aestivum and T. durum genomes and some only with the genome of T. durum. Yet other cytoplasms do not apparently cause loss of vigor with either genome. These differences clearly indicate the distinctions of cytoplasms that cannot be differentiated on the basis of male sterility alone.

B. CYTOPLASM-DIFFERENTIATING GENES

The cytoplasms of T. timopheevi and Aegilops speltoides cannot be differentiated by the presence of T. aestivum genomes since both N-C combinations result in plants where male sterility is apparently the only deleterious effect. However, these two cytoplasms can be differentiated by their interaction with the genome of T. timopheevi since the N-C combination of A. speltoides cytoplasm with the genome of T. timopheevi [conventionally written as (speltoides) timopheevi (Tsunewaki, 1970)] is not only male sterile but has reduced vigor as well (Table I). The other combination (timopheevi)timopheevi is, of course, the normal T. timopheevi condition and is male fertile. The difference in behavior of these two cytoplasms with either T. aestivum or T. timopheevi genomes must be controlled by nuclear gene differences between the genomes. Such genes which control or affect the functioning of a particular cytoplasm so as to produce, for example, vigor or loss of vigor or male fertility

TABLE I Alien Cytoplasms of Nucleocytoplasmic Substitution Lines Which Interact with the Genomes of Triticum aestivum and/or T. durum and T. timopheevi to Produce Particular Phenotypes Phenotype Male sterility together with other phenotypic side effects inherited cytoplasmically

Male sterility only apparent phenotypic effect

Normal or near normal phenotypes

Genome

Genome

Genome Principal side effect

aestivumldurum

A. speltoides (16)

Reduced vigor

A. bicornis (8J6)a A. umbellulata (4,6,8) A. variabilis (8,161 T. boeoticum (23,161 S. cereale (8,151 Reduced vigor with durum genome only

timopheevi

timopheevi

aestivum/durum

timopheevi

A. speltoides (12,14,16)

A. bicornis ( 16) A. umbellulata (17)

A. variabilis (16) T. boeoticum (16)

A. longissima ( 8 ) A. sharonensis ( 8 ) A. cylindrica (8) A. heldreichii ( 8 ) T. monococcum (8,10,11)

aestivumldurum

with durum genome

A . longissima (8) A. sharonensis (8) A. cylindrica (8) A. heldreichii ( 8 ) T. monococcum (11 A. vennicosa (19)

with aestivum genome

Delayed maturity

A. ovatu (1,4,16)

Pistillody

A. caudata

A. caudata (16)

(3,4,16) Nongerminating grain

A. squarrosa (598)

with durum genome

with aestivum genome

{

A. squarrosa

A. squarrosa (16)

(5,8,16)

T. timopheevi (4,7,6,20,2 1) T.zhukovskyi (9,13,16,18) T. timonovum (18) T. ararticum (7,11,16) T. dicoccoides var. nudiglumis (7,12,16)

T. zhukovskyi (16)

T. araraticum (8,16)

T. dicoccoides var. nudiglumis (8,16)

T. dococcoides Kom (7,16)

T. dicoccoides Kom (16) T. durum (16) T. aestivum (16)

ONumbers in parentheses indicate the following references: 1, Fukasawa (1953); 2, Hori and Tsunewaki (1967); 3, Kihara (1951); 4, Kihara (1968b); 5 , Kihara (1973); 6, Maan (1972); 7, Maan (1973b); 8, Maan (1973d); 9, Maan and Lucken (1967a); 10, Maan and Lucken (1968b); 11, Maan and Lucken (1968a); 12, Maan and Lucken (1969); 13, Maan and Lucken (1970); 14, Mann and Lucken (1971a); 15, Maan and Lucken, (1971b); 16,Maan and Lucken (1972); 17, Muramatsu (1965); 18, Nettevich and Fedorova (1966); 19, Oehler and Ingold (1966a); 20, Schmidt et al. (1962); 21, Wilson and Ross (1962).

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or sterility have been referred to by Maan and Lucken (1972) as cytoplasm-differentiating genes.

C. SOURCES OF RESTORING GENES

The cytoplasm-differentiating genes most widely studied so far in wheat have been those genes that restore male fertility to male-sterile N-C combinations. In some early work on N-C combinations, Fukasawa (1953, 1955) produced the N-C combinations (ovafa) ovafa and (ovafa) duwm by backcrossing the amphidiploid A ovafa X T. durum to A. ovafa and T. dururn, respectively. The (ovafa) ovafa combination was similar to the original A. ovafa and was male fertile, but the (ovafa)durum combination was male sterile but similar morphologically to T. durum. During the substitution backcrossing some plants were found in A. ovafa cytoplasm which contained 14 bivalents from T. durum and, in addition, one univalent from A. ovafa. These plants were normal for pollen fertility; pollen grains with both 14 and 15 chromosomes being functional. The effect of the extra ovatu chromosome in restoring fertility was therefore sporphytic. Plants that consisted of (ovafa)durum plus several ovafa univalents were sometimes pollen fertile and sometimes not. Pollen fertility thus evidently depended on the interaction of the cytoplasm with particlar ovafa univalents. From this it appeared that sporophytic restoration of pollen fertility in (ovafa) durum could be brought about by single doses of genes carried on specific A. ovafa chromosomes. It has since been pointed out by Kupnov (1971) that all species capable of donating male sterility-causing cytoplasms to N-C combinations are also sources of the corresponding restoring genes, and this is to be expected if it is the absence of specific genes, brought about by their elimination during backcrossing, that causes pollen development to break down in malesterile N-C combinations. If the appropriate genes present in the genomes of the cytoplasm donor species of male-sterile N C combinations are transferred to the substituted genome in the N-C combinations, the original species association of nuclear genes and cytoplasm is reconstituted and male fertility is resotred. Such N-C combinations with their fertility restored can then be used as the male parent in crosses with male-sterile N-C combinations having the same cytoplasm and will transmit restoring genes and hence male fertility to the resulting F, hybrid. This has been the origin of several hexaploid lines capable of restoring fertility to male-sterile T. timopheevi cytoplasm N C combinations since they are derivatives of T. timopheevi and carry genes derived from it. The origins and derivation of the most widely studied sources of restoration capacity in wheat are given in Table 11. From this it can be seen that the genome of the cytoplasm donor is not the

TABLE I1

Origin of Some Sources of Male Fertility-Restoring Genes Cytoplasm restored

Designation in literature

Derivation

Reference

P168

Triticum dicoccoides var. kotschyanurn T. aestivurn var. etythrospermurn where chromosome 1D replaced by A. caudata chromosome C a t - 2

ABD-1

(T.dicoccoides var. spontaneo-nigrarn x

A . ovata

Fukasawa (1955) Kihara (1963a)

(IC)

Tahir (1969)

A. squarrosa rypica No. 2) A. caudata ABD-13

T. timopheevi

Nebraska restorer or R1 R2 Wilson or Kansas restorer or R3 R4 or R-D R-C R-K

R5 R6 or BR4704

T. compactum T. dicoccum VERNAL

X

A. squarrosa stranqulata

(T tirnopheeui derivative Nebraska 542437

X

Lee)

(T. tirnopheevi X Marquis') X Sonora 64 (T. tirnopheeui X Marquis3)

[(T timopheevi X A. squarrosa L.) X Dirk3] [(T.timopheevi X A. squarrosa L.) X Canthatch3 ] [(T.timopheeui X A. squarrosa L.) X Kam ] (T. zhukovskyi x Justin3) [(T.boeoticum X A. squarrosa) X T. dumrn] X T.aestivum CHINESE SPRING T. spelta var. duhamelianurn T. aestivurn PRIMEPI

Kihara (1963b) Kihara and Tsunewaki (1964a) Schmidt et al. (1962) Rodriques et al. (1966) Livers (1964) Yen et al. (1969) Yen et al. (1969) Yen et al. (1969) Maan and Lucken (1969) Maan and Lucken (1969) Kihara and Tsunewaki (1966) Oehler and Ingold (1966a)

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G. C. M. SAGE

only source of restoring genes since species other than the cytoplasm donors listed have also been shown to be sources of restoring genes.

D. THE INTERACTION OF RESTORER-GENE SOURCES AND PARTICULAR CYTOPLASMS

In contrast to Table 11, which shows that different sources of restorer genes are able to restore fertility to the same N-C combination, the results summarized in Table I11 show that some restorer-gene sources can restore fertility to different N-C combinations having different cytoplasms. For example, genes from T. compactum have been shown to restore fertility to both (caudata) aestivum and (umbellulata) aestivum and genes from T. aestivum var. PRIMEPI will restore fertility to (timopheevi) aestivum, (ventricosa) aestivum, and (timonovum) aestivum. But although some restorer-gene sources are capable of restoring activity in more than one cytoplasm no sources have been found that will restore fertility in all male sterility inducing cytoplasms. The interaction of nuclear genes and cytoplasm is thus very specific and this is particularly well illustrated by the different behavior of the restorer-gene sources R1, R2, R3, and R4, on the one hand, and R5 and R6, on the other. The restorer-genes carried by the former group of lines will restore T. timopheevi and T. araraticum cytoplasm N-C combinations but not those having T. boeoticum cytoplasm. The restorergenes carried by R5 and R6, however, will restore T. timopheevi and T. boeoticum cytoplasm N-C combinations but not those having T. araraticum cytoplasm. It is these specific and differential interactions of particular cytoplasms with different restorer-gene sources that have already enabled workers to show the distinctness of many cytoplasms in the Triticinae, and in fact most cytogenetically distinct species investigated to date have also been shown to have cytoplasmic differences (Maan, 1973~).Our knowledge of this cytoplasmic variation will no doubt grow as more restorer gene-cytoplasm interactions are studied and as cytoplasmic interactions with other cytoplasmic-differentiating genes, for example those affecting plant vigor, are studied more widely.

111. The Genetics of Fertility Restoration

A. IMPORTANCE

For the production of hybrid wheat a male-sterile N-C combination, referred to as the male-sterile line or A-line, is maintained and multipled on a large scale by wind pollination, the pollen being provided by the recurrent backcross parent

NUCLEO-CYTOPLASMIC RELATIONSHIPS IN WHEAT

275

of the N-C combination. This backcross parent, which is isogenic with the A-line, is referred to as the maintainer line or B-line. If the A-line is wind pollinated by a genetically distinct line, referred to as the restorer line or R-line, which carries restoring genes, the resulting F I generation is male fertile because it carries restoring genes in the heterozygous condition. To be an economic proposition as a hybrid crop such F1 generations must be very high yielding and since this yield is dependent on the efficiency of the restoring genes present, the study of the inheritance of restoration has been of major importance in the development of hybrid wheat.

B. PARTIAL RESTORATION

As can be seen from Table 111 restoration of male fertility is not in all circumstances complete. In some crosses and backcrosses between male-sterile lines and restorer lines, plants may be found in the F1 or subsequent generations which show varying degrees of partial restoration of fertility. It is characteristic of partially restored plants that such self-fertility as occurs tends to be at the base of the ear, a variable number of florets at the apex being male sterile. However, variation in restoration within the ear is not confined. to differences between apical and basal florets since within one floret it is possible to find both functional and nonfunctional anthers and even within single anthers varying proportions of viable and nonviable pollen. Different workers have attempted to quantify different degrees of partial restoration in different ways. Some have recorded the mean percentage of viable pollen produced, others have classified plants according to the proportion of spikelets containing nonfunctional anthers, and others have relied on percentage selfed seed sets in bagged ears.

C. ENVIRONMENTAL EFFECTS ON MALE STERILITY AND RESTORATION

While the cytoplasmic determinants of male sterility have in every case shown themselves to be extremely stable through long series of backcrosses, their interaction with restoring genes in different environments has been found in some cases to be extremely unstable. Several workers (Rockefeller Foundation Annual Report, 1964-1965; Fedorova and Nettevich, 1969; Maan, 1973d) have reported that in a range of male-sterile N-C combinations involving several different cytoplasms some have stable male sterility over a range of different environments, but others produce a variable amount of viable pollen and hence selfed seed in some environments. Maan, for example, found that (baeoticurn) durum or aestivurn had stable male sterility in all environments tested but that

TABLE 111 Level of Restoration of Male Fertility Induced by Different RestorerGene Sources in Nucleocytoplasmic Combinations Having Triticurn dururn andlor T.aestivum Genomes in Cytoplasms of Different Origin (SB = substitution backcross) Cytoplasm Restorer-gene source

No or very little restoration

Partial restoration

Complete or nearly complete restoration

Reference

T. cornpacturn 44

T. tirnopheevi A. ovata

A. caudata F ,

A. caudata S B , , A. umbellulata

Kihara (1968b)

P168

T. timopheevi A. caudata F,

A. ovata SB, A. caudata SB, A. urnbellulata

A . ovata F,

Kihara (1968b)

T.spelta var. duh. T. dicoccoides spont.

A. ovata A. caudata A. urnbellulata

T. aestivurn SALMON

T. tirnopheevi A. ovata A. caudata A. urnbellulata

T.durum reichenbachii

T.aestivum erythrospermrn

T. tirnopheevi A. ovata A. caudata

T. tirnopheevi F, + SB,

Kihara (1968b)

A . urnbellulata

T.aestivum

T. timopheevi A . ventricosa T. timonovum

PRIMEPI ABD-1 ABD-13

R1, R2, R3, R4

R5, R6

T.timopheevi T.timopheevi

A . ovata

A. ovata (dwarfed and did not head) A. caudata F,

A. caudata SB,

Tahir (1969) Tahir (1969) Kihara and Tsunewaki (1964a)

T.timopheevi

T. boeoticum A. caudata

A. ovata

T.araraticum

A. ovata

T. boeoticum

T.dococcoides var.

A. caudata A. umbellulata Secale cereale

T.timopheevi

nudiglclm-s A. speltoides

Oehler and Ingold ( 1966b) Drogacheva (1972a)

T. zhukovskyi T. araraticum T. dicoccoides var. riudiglumis A. speltoides

Maan and Lucken (1972)

Maan and Lucken (1972) Maan (1973d)

T. zhukovskyi

R4

T. boeoticum

Secale cereale

Maan (1972)

T. aestivum One rye chromosome

T. boeoticum A. umbellulata

Secale cereale

Maan and Lucken (1971b)

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G. C. M. SAGE

similar plants with A. umbellulata or Secale cereale cytoplasm has complete male sterility in the autumn but partial fertility during the spring season in the glasshouse; (timopheevi) aestivum var. SELKIRK or var. CHINESE SPRING were also completely male-sterile in the glasshouse in the autumn but showed nearly complete male fertility when grown in a growth chamber with a 12-hour photoperiod (Maan, 1973~).These findings suggest that male-sterile lines can carry latent restoring genes that are only expressed in certain environments and consequently have low penetrance. The fact that other nuclear genes affecting male fertility have variable expressivity is indicated by the interactions found between fertility-restored N-C combinations and environment. Kihara (1970) found that the degree of male fertility expressed was dependent on planting date, and Monteagudo el al. (1967), Lucken and Maan (1967), Wilson (1968b), and Schmidt el d . (1971) have all shown restoration to vary with location. It seems that, in general, a degree of male sterility appears or increases in restored N-C combinations with an increase in latitude degrees north. Wilson introduced the terms deep sterile, sterile, and shallow sterile to describe environments in which progressively greater degrees of restoration were expressed and suggested that deeply sterile environments, in which even normal varieties have a tendency to ear tip sterility, were associated with short growing seasons and low temperatures. In normal varieties of wheat, male fertility has been shown to be influenced by a number of environmental factors. Nanda and Chinoy (1945) found that long day photoperiodic treatments had a deleterious effect on pollen fertility, and Meletti (1961) showed that a combination of continuous light and low temperatures led to pollen sterility. Fukasawa (1953) induced male sterility very similar to cytoplasmic male sterilty in vernalized plants ripened in winter under long days. Thus he also found deleterious effects on pollen fertility with long day lengths and low temperatures. Bingham (1966), however, induced male sterility by the application of drought treatments at critical growth stages. The interaction of all these environmental factors, temperature, photoperiod, and water status, in their influence on the expression of fertility restoration in N-C combinations is implied by the findings of many workers that the conditions of growth in pots (Miri et al., 1970) or in glasshouses (Rajki and Rajki, 1966; McCuiston 1968; Schmidt et al., 1971) were more deeply sterile than field conditions. Holland (1966) suggested that both day length and temperature were responsible for the differences he observed in levels of restoration in the glasshouse and in the field, and Mihaljev (1972) reported that restoration was reduced in seasons in which hot dry conditions prevailed. Both these observations are supported by the controlled environment chamber work of Welsh and Klatt (1971) and Johnson and Patterson (1973), which showed in winter and spring wheat, respectively, that restoration was sensitive to photoperiod and to a

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greater extent to temperature. Long photoperiods reduced pollen viability in restored N-C combinations, and this would agree with the observation of deep sterile environments in more northerly latitudes and with the responses seen in normal varieties. Temperature effects, however, are obviously more complex since the reduction of pollen fertility brought about by high temperatures in the controlled environment experiments does not match the geographical observations. In populations segregating for restoring genes, it was found in an early investigation (Fukasawa, 1958a) that the proportion of partially restored plants relative to fully restored and fully male-sterile types and the degree of partial restoration was considerably affected by the environment. This has meant that all workers trying to study the inheritance of restoration have had great difficulty in accurately assigning plants to particular categories of restoration. Given this difficulty and the different criteria that different workers have used to measure the extent of male fertility restoration, it is not surprising that no very consistent picture has emerged as to the number and kind of genes involved.

D. TYPES OF RESTORING GENE AND THEIR INTERACTION

Kihara (1968b) classified wheat genotypes into four groups with respect to fertility restoration. In the first group, represented by T. compactum in A. caudata cytoplasm (Table III), the F1,(caudafa)aestivum X T. compacturn, shows low male fertility, as measured by percentage of viable pollen produced, which is gradually improved in the course of backcrossing to T. compactum. For this group Kihara assumed that homozygosity of the restoring gene or genes was required for full recovery of male fertility and consequently that there was recessivity of the gene or genes. Tsunewaki (1963) reported backcross segregations which indicated that T. compactum and T. aestivum eryfhrospermum differed by a single recessive gene, but Kihara (1962) produced evidence that T. compactum carries two complementary recessive genes for the restoration of male fertility. It is possible that the restoration shown by P168 and ABD-13 in A. caudafa cytoplasm (Table 111) is of the same type as that of T. compactum and that they also should be placed into Kihara’s first group of genotypes. Kihara’s second group of genotypes is represented by P168 in A. ovafa cytoplasm. Here the F, (ovafa)aestivum X P168 is completely male fertile, but this fertility decreases in the course of backcrossing to P168 until pollen fertility is reduced to about 50%. Here Kihara assumed the presence of one or more sets of dominant complementary genes which produced a heterotic effect in the F1 generation.

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The fact that P168 can be put into both these first two groups indicates that it does not restore fertility to the same extent in different cytoplasms. PI68 is a chromosome substitution line developed in the strain T. uestivum eryrhrospermum (Table 11) and since T. uesrivum eryrhrospermum itself will not restore either the A. cuudaru or A. ovara cytoplasms as P168 will (Table III), the restoring genes must be carried on the substituted chromosome which was derived from A. caudara. Since in the F, generation P168 restoration of ovara cytoplasm is more complete than in caudara cytoplasm the restorer genes in P168 derived from A. caudara are more effective in the heterozygous condition in a foreign cytoplasm than they are in their cytoplasm of origin. Kihara’s third group of genotypes is represented by T. speltu duhurneliunum in T. rimopheevi cytoplasm (Table 111). Here the F1 generation shows complete recovery of male fertility which is maintained through successive backcross generations. In this group Kihara assumed restoration to be due to one or more powerful genes that were effective in the heterozygous condition. Other examples of lines that might be included in this group are T. uestivum PRIMEPI, other restorer lines effective on T. rimopheevi cytoplasm, and T.speltu var. korschyunum on A. ovuta cytoplasm (Tables I1 and 111). The fourth group of lines classified by Kihara is comprised of lines such as T. uesrivum var. SALMON and T. durum reichenbuchii which have no restoring effect on any cytoplasm. From this classification of restorer genotypes it can be seen that restorer genes that positively enhance male fertility can be complementary, dominant, or recessive and may behave differently or differ in their effectiveness in different cytoplasms. But these genes are probably not the only kind of gene to influence male fertility in N-C combiantions. Tahir (1969) has shown that the synthesized hexaploid wheat ABD-1 (Table 11) will not restore male fertility in T. rimopheevi cytoplasm. However, one of the species from which it was derived, T. dicoccoides spontuno-nigrum, will do so (Table 111). Tahir explained this difference of behavior by supposing that the D genome contributed to ABD-1 by A. squurrosu typicu No. 2 carried genes which inhibited male fertility restoration. Since it appears that there are genes that either promote or inhibit fertility restoration, it is not surprising to find restoration behaving in a complementary manner in some cases since this may merely involve the absence of inhibitor genes. More positive evidence that the genes affecting fertility restoration interact with one another is given by the work of Nettevich (1969) who found that crossing two fertility-restored N-C combinations sometimes resulted in an F1 which had a reduced male fertility relative to the parental lines, and by that of Kihara and Tsunewaki (1964a) who found that in A. caudara cytoplasm a combination of T. compuctum and P168 genes produced a higher level of male fertility than either restorer line alone.

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28 1

E. CONVENTIONAL GENETIC ANALYSIS

In the development of male parental lines for hybrid wheat production, the restorer-gene action of those genotypes that fall into Kihara's third group is likely to be the easiest to exploit, and it is for this reason that the inheritance of restoration in these lines has been more extensively studied than in other lines. Numerous studies have been carried out of the segregation of male fertility in F2 and succeeding generations in crosses between male-sterile lines and group three restorer lines. In every case the initial genetic explanation put forward has been shown by subsequent work 'to be an oversimplification. For example, the restoration of A. ovatu cytoplasm N-C combinations by T. spelra var. kotschymum was originally explained by Fukasawa (1958a) on the basis of two major genes, but subsequently Gilmore (1970) has suggested two major and one minor gene. The restoration of T. timopheevi cytoplasm N-C combinations by PRIMEPI and other T. aestivum varieties has been claimed to segregate monofactorially in F2 (Oehler and Ingold, 1966b; Zeven, 1968; Skurygina 1970), but other workers have found the restoring ability of PRIMEPI to be due to more than one gene. Schmidt et ul. (1971) found different two gene segregations depending on the male-sterile lines used in the cross and on the environment. Miller and Schmidt (1 970) found two incompletely dominant genes for male fertility restoration with a major and a minor effect, respectively. Nettevich and Naumov (1970) suggested that the F2 segregation they observed was due to two incompletely dominant genes together with the epistatic action of a single recessive gene. Since then Shebeski (1971) has found an even more complex genetic situation by showing that PRIMEPI restoration involves one major dominant gene and one. minor dominant gene which act in a complementary manner together with one modifier gene and one inhibitor gene. Similar results have come out of comparable studies of the segregation of the restorer genes of the T. timopheevi derived restorer lines. Two major genes, sometimes influenced by modifier genes, have been claimed for both R1 and R3 (Anderson, 1964; Livers, 1964; Wilson, 1968b, Skurygina, 1970; Miri et al., 1970; Odenbach, 1970; Schmidt et ul., 1971), but other workers have considered the restoration capacity of R l to involve three or at any rate more than two genes (Bajwa and Lucken, 1968; McCuiston, 1968). In the most recent publication on the subject, Bahl and Maan (1973) considered that R1, R2, and R5 carried three genes for fertility restoration in T. timopheevi cytoplasm while R3 and R4 had only two. Similar work with other restorer-gene sources effective in T. timopheevi cytoplasm has also indicated that at least three genes are involved (Rockefeller Foundation Annual Report, 1964-1965; Sage, 1972). The overall impression of the genetic control of fertility restoration that can

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be gained from these conventional genetic analyses is that a few dominant or partially dominant genes, possibly differing in their effectiveness and interacting in an additive or complementary manner are responsible, but that the precise action of the major genes is subject to modification by minor modifying genes. Wilson (1968a) has described this genetic situation as cumulative dominance.

F. MONOSOMIC ANALYSIS

The picture of the genetic control of restoration given by conventional genetic analysis is reinforced by the results of the monosomic analyses that have been carried out (Table IV). Genes of differing effect which positively enhance male fertility, inhibiting or modifying genes, have been shown to be carried on 17 of the 21 chromosomes. So far only chromosomes lD, 3A, 3B, and 4D have not been implicated in fertility restoration. The fertility-enhancing genes carried by six different chromosomes have to date been allocated gene symbols. The genes carried by chromosomes 1A and 7D of R3 have been designated Rfl and Rf,, respectively, the gene carried by chromosome 1B of T. spelta var. duhamelianum has been designated Rf3 and those carried by chromosomes 6B and 6D of restorer line R-C have been designated Rf4 and RfS, respectively (McIntosh, 1973). In addition, the gene carried by the A. caudata chromosome C-sat-2 or 1C of P168 has been designated Rfcl (Tahir and Tsunewaki, 1971a). The monosomic analysis results for the three chromosomes 1B, 6D, and 7D are singular in that in the monosomic condition some workers have found them to carry restoring genes while others have found them to carry inhibiting modifiers. This suggests that there may be an allelic series at each locus; different alleles having different or even contrary effects on restoration. Bajwa and Lucken (1968) found some evidence of allelism, and Talaat (1969) has reported that the effect of chromosome 1A in restorer line R1 appears to be different from that of the chromosome 1A carried by either R3 or R4. Maan and Lucken (1967b) showed by investigating the effects of aneuploidy on fertility restoration that the dosage of a number of particular chromosome arms affected the level of fertility observed. In particular they reported that CHINESE SPRING mono-7D in T.t i m e pheevi cytoplasm was somewhat male fertile while disomic CHINESE SPRING with the same cytoplasm was male sterile. This result suggested that chromosome 7D of CHINESE SPRING carried a weak fertility inhibitor which in the hemizygous condition caused some fertility restoration. Tahir and Tsunewaki (1969) found a fertility-inhibiting gene on chromosome 7D of T. spelta var. duhamelimum. Since this gene was effective in the monosomic condition, it was assumed to be a stronger inhibitor than that found by Maan and Lucken in CHINESE SPRING which was only effective in the disomic condition. It may be that these two genes are part of an allelic series. The, at present, rather limited evidence of

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allelic series and gene dosage effects points, at least circumstantially, to the conclusion that restoration of male fertility depends on both the number and strength of the various kinds of restorer gene present and this strengthens Wilson’s impression (Wilson, 1968a) that restorer genes interact in a cumulative manner. The strong influence of different environments on the expression of restoration in segregating populations has led several workers to observe, in particular crosses, different segregation ratios depending on where or how the work was conducted. Talaat (1969), for example, could only detect the presence of the restoring gene on chromosome SA of restorer line R1 (Table IV)by monosomic segregations at Obregon in Mexico and not at Fargo in North Dakota. Talaat suggested that the variable penetrance of this gene might be due to its exhibiting a threshold effect. Sage (1972) has also invoked the concept of threshold levels to explain the inheritance of restoration in European wheats.

G . A HYPOTHETICAL MECHANISM FOR

RESTORATION OF MALE FERTILITY

The cumulative action of numerous restoring genes, which possibly only occurs if some minimum threshold level in the plant is exceeded, points to the activity of some hormone-like substance in restoration. Sage (1972) has suggested that the tendency for male fertility in partially restored genotypes to be localized at the base of the ear might mean that restoration is brought about by some substance that is translocated acropetally to the ears. Different genotypes might produce different quantities of this substance which, in turn, might not produce restoration in any given floret, anther or part of an anther unless present in a critical concentration. This critical concentration might not be so easily achicved at the top of the ear as at the base. The attraction of such a hormonal explanation of restoration is that it easily allows for the threshold genotypic levels that have been postulated, for gene dosage effects, for the differeing effectiveness of different genes or possibly even alleles and for the influence of photoperiod, temperature, and water stress since these might more easily affect the functioning of a hormonal restoration substance than the expression of the genes themselves.

H. THE DEVELOPMENT OF RESTORER LINES

One of the major difficulties encountered in developing restorer lines for hybrid wheat production has been that in the presence of an alien cytoplasm the effectiveness of restorer genes in the homozygous condition has been no guide to

TABLE IV Chromosomes Shown by Monosomic Analysis to Influence the Restoration of Male Fertility in T.timopheevi Cytoplasm Chromosomes with inhibiting modifiers

Chromosomeswith restorer genes

h)

m P

Sources of restorer genes

Restore+ line

T.timopheevi

R1

T. timopheevi T. timopheevi

R2 R3

T. timopheevi

R4

T. timopheevi

R-K RC R5

T. timopheevi T. zhukovskyi

Major genes 1A 1A 1A 1A 1A 1A 1A 1A 1A 1A 1A

Minorgenes 5A 6B

5A

6B 6B

Major

7D 7D 7D 7D 7D

1B

7D 7D 7D 7D

1B

6D 7B 7D

Minor 4A5B

1B

5B6D7A

Reference Talaat (1969) Bahl and Maan (1973) Bahl and Maan (1973) Tallaat (1969) Bahl and Maan (1973) Robertson and Curtis (1967) Talaat (1969) Bahl and Maan (1973) Yen er al. (1969) Yen er al. (1969) Yen et al. (1969) Bahl and Maan (1973)

Hexaploid wheats

Hexaploid wheats + A . caudata

PRIMEPI

1B

MINISTER T. spelta duh.

1B 1B

P168

5D

Bahl and Maan (1973)

4B

7D

Zeven (1970) Tahir and Tsunewaki (1969)

7D

1Cb

Tahir and Tsunewaki (197 la)

w m

Source of modifier genes

Chromosomes with modifier genes

01

7D

T. aestivum CHINESE SPRING T. aestiuum CHINESE SPRING

1B

Rescue P168 =For derivation, see Table 11. bNot effective in timopheevi cytoplasm.

2A

3D

6A 6B 6A

2B 2D

4A 5D

7A

4A

Maan and Lucken (1967b) Robertson and Curtis (1967) Yen et aL (1969) Tahir and Tsunewaki (1971a)

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their effectiveness in the heterozygous condition of F hybrids (CIMMYT, 1968-1969; Nettevich and Naumov, 1971; Lucken, 1973). Another complication in restorer line development has arisen from the frequent observation that some male-sterile lines are easier to restore than others and that some restorer lines are more effective than others (CIMMYT, 1968-1969; Wilson, 1968b; Schmidt et al., 1971; Nettevich and Naumov, 1971). These complexities of restorer line development are, at least in part, explicable in terms of the large number and variable interaction of the nuclear genes that have been shown to affect male fertility restoration. It is, incidentally, interesting to note here, with respect to the influence of drought on restoration, that the male-sterile lines found by Nettevich to be easier to restore than others were also distinguishable by their drought resistance. IV. Cytoplasmic Effects Other than Male Sterility

A. DELETERIOUS EFFECTS

As indicated in Table I, some N-C combinations exhibit cytoplasmically inherited phenotypic effects in addition to male sterility. If these effects are due to the absence of nuclear genes, as with fertility restoration, it is not surprising that most of these effects are deleterious or of no practical value. In addition to the reduced vigor and poor stunted growth frequently observed in N-C combinations, cases of abnormal chlorophyll development (Fukasawa and Mito, 1958) leading to variegation (Fukasawa, 1956a; Gilmore, 1970; Sanchez-Monge, 1970, 1971), abnormal stomatal development restricted to some parts of the plant (Fukasawa, 1958b), and pistillody (Kihara, 1962; Maan and Lucken, 1968a) have been reported. N-C combinations have to be female fertile, otherwise successive backcrossing could not be carried out but the functioning of the female parts of the flowers is frequently not completely normal so that cases have been reported of kernel shrivelling (Schmidt et al., 1971), reduced germination capacity (Kihara and Tsunewaki, 1961), and a greatly increased Occurrence of germless or nongerminating grain (Kihara and Tsunewaki, 1964a; Maan, 1973d). The frequency of Occurrence of germless grain is increased by open pollination (Kihara and Tsunewaki, 1964b) or by pollination by limited amounts of pollen or at low temperatures (Abramova, 1969). Presumably this results from the fusion of male gametes with polar nuclei only. This, in turn, may result from inadequate timing of pollen transfer or inadequate pollen tube growth or both. Reciprocal differences in the growth of pollen tubes and/or embryos have been observed in interspecies crosses (Fukasawa, 1957a; Fedosenko, 1969), but Fukasawa con-

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cluded that these differences were genomic in origin and were not caused by the cytoplasmic differences. It may be, then, that the germless grain character and indeed possibly the reduced germination and kernel shrivelling, which have been found associated with N-C combinations, are a result of the necessity of cross-pollination rather than a cytoplasmic effect. A number of cytogenetic abnormalities have been found to be associated with the presence of an alien cytoplasm in N-C combinations. Parthenogenetic development and the increased production of haploids and twin seedlings have been reported (Kihara and Tsunewaki, 1962a, 1963; Tsunewaki et QZ., 1968; Lacadena, 1968), and it has been suggested that this might be usefully exploited as a means of intentionally producing haploids in wheat (Kihara and Tsunewaki, 1962b). Persistent aneuploidy (Schmidt et QZ., 1971) and even the elimination of whole genomes (Lacadena, 1968; Lacadena and Sendino, 1970) have also been found in N-C combinations. Since Maan and Lucken (1967b) have shown that aneuploidy affects the expression of restoration, it is possible that some of the discrepancy between the genetic conclusions of different workers investigating the inheritance of restoration has been caused by such cytogenetic disturbances.

B. MORPHOLOGICAL AND PHYSIOLOGICAL EFFECTS

Cytoplasmic influences on morphological and physiological characteristics have been reported by those workers who have compared N-C combinations with the appropriate genome donor species (Hori and Tsunewaki, 1967, 1969; Nettevich and Sanduhadze, 1968; Sanchez-Monge, 1970, 1971; Tahir, 1971; Tahir and Tsunewaki, 1971b; Drogacheva, 1972b). Plant characters such as height, maturity, dry matter production, and various components of yield have all been shown to be affected by certain cytoplasms. Tsunewaki and Endo (1973) recently reported the results of an experiment where eight hexaploid wheat lines were substituted into four alien cytoplasms: A. caudata, A. umbellulata, A . ovata, and T. timopheevi. Twenty plant characters were measured on each N-C combination and on the original hexaploid lines. The twenty characters measured ranged from vegetative characters through reproductive traits to seed characters and were thus determined at different developmental stages. Aegilops umbellulata cytoplasm was characterized as showing a strong detrimental effect on all vegetative characters with relatively little effect on male organs and male gametophytes. Aegilops ovum cytoplasm drastically affected only pollen fertility and those characters determined during the late part of the vegetative period. Triticum timopheevi cytoplasm had very little detrimental effect on plant characters, such effects being limited to anther and pollen characters only. The mean measurements of seven of the common wheat lines backcrossed into T. timopheevi cytoplasm showed that there was no

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cytoplasm effect on tiller number, dry matter production, heading data, and number of spikelets per ear but a significant reduction in height due to a reduction of top internode length and a significant increase in flag leaf length and width. It is the lack of deleterious morphological effects in N-C combination involving T. timopheevi cytoplasm, together with the dominant nature of the appropriate restoring genes, that has led most hybrid wheat research to be concentrated on exploiting such N-C combinations. Tsunewaki and Endo found that their fourth cytoplasm, that of A. caudata, was similar in its effects to that of T. timopheevi except that detrimental seed characters, such as an increased percentage of twins, haploids and germless grain, were also found. The fact that the four cytoplasms were differentiated by their effects on groups of characters that were developmentally clustered and that these effects were, on the whole, inhibitory indicates that at different stages of development with different cytoplasms some very fundamental physiological changes from normal are brought about by the nucleo-cytoplasmic interaction. Fukasawa (1957b) found that the N-C combination ( o v m ) durum, in addition to being male sterile; was 2 weeks later to heading and was also shorter than the recurrent T. durum parent. The extent to which these effects were manifested varied with sowing date. The degree of delayed maturity depended on the particular variety of T. durum used as the recurrent parent. Variegation, which was more pronounced during the winter, was also shown by the N-C combinations to involve some but not all T. durum varieties. The fact that different cytoplasms induce different spectrums of effects which are, at least in one case, environmentally sensitive and dependent on the nuclear genotype, shows that morphological and physiological effects in N-C combinations behave very similarly to male fertility effects. This suggests that they may have the same or similar causes.

C. ADVANTAGEOUS CYTOPLASMIC VARIATION

The reduced height and larger flag leaves shown by the (timopheevi)uestivum combinations investigated by Tsunewaki and Endo are examples of possibly advantageous cytoplasmically induced variation which might be utilized in wheat improvement. Similar variation has also been found for winter hardiness. Both Msic (1966) and Abakumenko (1969) presented results that suggested that the cytoplasm might play a part in the inheritance of winter hardiness, and SanchezMonge (1970) reported that the frost resistance of certain hexaploid wheats was greater if the hexaploid genome was in A. ovutu cytoplasm. More recently, Sanchez-Monge et ul. (1973) have reported that both resistance and susceptibility to certain races of black rust can be induced by the presence of different alien cytoplasms. However, these indications of useful variation which is cytoplasmically controlled are all associated with male sterility. They can only be

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exploited by the use of restoring genes which have themselves been shown to modify the expression of morphological and physiological cytoplasmic effects.

D. RESTORATION OF MORPHOLOGICAL AND PHYSIOLOGICAL EFFECTS

Maan and Lucken (1971b) reported that the addition of one rye chromosome to the wheat genome restored male fertility (Table 111) and plant vigor to (cereale) aestivum combinations. Forty-four chromosome wheat plants with an additional pair of this rye chromosome in rye cytoplasm were male fertile and of normal vigor but were shorter than corresponding 43 chromosome plants carrying only one rye chromosome. This indicated that one dose of the rye chromosome was optimum for restoration of plant vigor. Plants telocentric for the critical rye chromosome resembled, in male fertility and plant vigor, those with one dose of the complete chromosome. The gene(s) for restoration of fertility and plant vigor were therefore located on the same arm of the critical chromosome. This suggests that either the same gene(s) effect restoration of both fertility and vigor and hence have pleiotropic activity or that distinct genes could be closely linked. The critical chromosome has since been tentatively identified as 3R (Maan, 1973a), and other rye chromosomes, lR, 2R, 5R, and DR, have been shown to partially restore male fertility and vigour. Maan (1972) also showed that the restorer line R4 would restore both male fertility (Table 111) and plant vigor to rye cytoplasm N-C combinations. The restoration of plant vigor in rye cytoplasm N-C combinations in thus shown by atl these results to behave in a manner exactly parallel to fertility restoration since in both, specific chromosomes of different effectiveness have been identified in the cytoplasm donor species, and genes from completely different species have also been shown to be effective. All this evidence would seem to favor a pleiotropic explanation of the similarities in behavior between fertility and vigor restoration. However, Maan and Lucken (1970, 1972) reported that restorer lines R5 and R6 restored both male fertility and plant vigor to (boeoticum) aestivum combinations, but that in F2 and F3 certain plants have complete or nearly complete restoration of male fertility together with highly reduced plant vigor. This indicated that in R5 and R6 the genes for restoration of male fertility and for restoration of plant vigor were distinct and not closely linked.

E. SUMMARY OF NUCLEO-CYTOPLASMIC INTERACTION EFFECTS

The study of cytoplasmic effects in wheat has shown that their major features are also found to be common in other crop plants (Edwardson, 1970; Duvick, 1965). Their major features can be summarized:

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G. C. M. SAGE

(1) They are inherited via genetically stable cytoplasmic determinants, but the degree of expression is dependent on the nuclear background. (2) A few nuclear (restoring) genes can completely or partially overcome the effects of the cytoplasm, but there are numerous nuclear genes that can act as modifiers of the restoring genes. (3) The expression of the cytoplasmic effect is dependent on environmental factors. (4) Not all parts of the plant are necessarily equally affected.

V. The Biological Basis of Nucleocytoplasmic Interactions

A. INTERVARIETAL CYTOPLASMIC VARIATION: A GENE-FOR-GENE HYPOTHESIS

The single case of cytoplasmic differentiation within a species of the Triticinae, that has so far been clearly demonstrated, was discovered by Kihara (1968b). Two varieties of A. caudara, var. typica and var. polyarhera, were shown to be anisoplasmic, the term used by Kihara to indicate the possession of distinct cytoplasms, because the reciprocal nuclear substitution lines behaved differently. Kihara explained this behavior, comparable examples of which have been found in other crops such as rice, by adopting a gene-for-gene hypothesis similar to that of the host-pathogen relationship. The nuclear fertility-restoring (Rf) genes were assumed to be functional only in the presence of a corresponding cytoplasmic unit. In general terms this hypothesis would require that each cytoplasm-differentiating gene would have a corresponding cytoplasmic unit. Recent studies of the mechanism of male sterility and fertility restoration are beginning to provide evidence that supports a gene-for-gene type of hypothesis to explain nucleo-cytoplasmic interactions and to indicate the possible nature of the cytoplasmic units.

B. THE MECHANISM OF MALE STERILITY

Viral infections have been shown to cause cytoplasmic male sterility in some host plants (Atanasoff, 1964), but viruses seem unlikely to be the causative agents in wheat since Zeven (1967) and Lacadena (1968) were unable to transmit cytoplasmic male sterility asexually across fertile-sterile embryoendosperm grafts and Zeven (1967) found that heat treatments for the inactivation of viruses failed to “cure” plants of cytoplasmic male sterility. On the other

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29 1

hand, the evidence is now very strong that in wheat, as in other graminaceous crops such as maize and sorghum, inherited aberrations in metabolism are the cause of male sterility. In wheat (Fukasawa, 1956b; Joppa et al., 1966; Coudhury etal., 1968), as in maize (Duvick, 1965) and sorghum (Alam and Sandel, 1964; Raj, 1968), meiosis is apparently normal in the anthesis of male-sterile plants but pollen development becomes aberrant at or after the first pollen mitosis. In both maize and wheat the symptoms shown appear to be those of starvation and result in a cessation of anther growth. Fukasawa et al. (1957), Erickson (1967), and Savchenko et al. (1968) have all reported anthers of male-sterile wheat plants to be deficient in sugars relative to normal fertile anthers during pollen maturation. Joppa (Joppa et al., 1966) found that the tapetal layer in male-sterile wheat formed less starch than in male-fertile plants and he and Chauhan and Singh (1966) both reported that it persisted longer than in normal development. Both these observations suggest that in male-sterile anthers the tapetal layer does not function normally as the nutritive source for the developing pollen grain (Chowdhury et al., 1968). Fukasawa et al. (1957) induced microspore abortion in culms of male-fertile T. durum cut at meiosis by keeping them in the dark. Since the addition of 5% sucrose solution to the culture medium prevented this abortion, it was presumably brought about by sugar starvation resulting from the lack of photosynthesis in the darkened and hence nonphotosynthesizing leaves. The addition of sucrose to the culture medium of culms of cytoplasmic malesterile T. durum improved microsporogenesis but did not result in any fully normal pollen. Sugar starvation was thus not the sole cause of pollen abortion in the cytoplasmically male-sterile plants. The lack of sugar in male-sterile anthers could itself be the result of a more fundamental cause of male sterility in that there is now good evidence of aberrant amino acid metabolism in male-sterile anthers. The free amino acids in anthers of male-sterile and normal plants have been compared by a number of workers. Kihara (1966) and Erickson (1967) working with different sources of cytoplasmic male sterility in wheat found there to be less proline than normal in male-sterile anthers. Fukasawa (1954) and Savchenko et al. (1968) also found that proline was deficient in male-sterile anthers of wheat and that asparagine accumulated in higher than normal quantities. Khoo and Stinston (1957) found high asparagine and low proline concentrations in male-sterile maize. However, the amounts of these two amino acids in plants carrying fertility-restoring genes was the same as in male-fertile maize. This last observation suggests that the aberrant-free amino acid concentrations found in male-sterile anthers are directly related to the male-sterile condition. Savchenko et al. (1968) found that in male-sterile wheat anthers the total amount of free amino acids was greater than in normal anthers and this, together with the high concentrations of asparagine observed, suggests that the abortive microspores are unable to utilize free amino

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acids normally. Proline is thought to be uniquely important in the determination of the overall shape of protein molecules (Fowden 1963), and Duvick (1965) considered that the relatively low amounts of proline observed in male-sterile anthers could thus be a direct cause of pollen abortion if it were an essential component of one or more enzymes of the developing pollen grain. Differences in the enzymes produced by male-fertile and male-sterile anthers have been shown by both Alam and Sandel (1969) in sorghum and Erickson (1967) in wheat who reported electrophoretic zymogram band differences for the enzyme cytochrome oxidase. This observation led Erickson (1969) to suggest that in wheat, mitochondria, which are the site of the cytochrome oxidase enzyme system in the cell, are involved in cytoplasmic male sterility. The implication that a cellular organelle may be involved in cytoplasmic male sterility is reinforced by the electron micrograph work of de Vries and Ie (1970), which showed that sterile pollen grains from cytoplasmically male-sterile wheat plants were characterized by having only a few physiologically active organelles.

C. NUCLEO-CYTOPLASMIC INTERACTION AT THE CELLULAR LEVEL

Support for the idea that sterility could result from changes within the plant cell organelles came with the proof that mitochondria and chloroplasts contain DNA essential for their structure and function (Nass, 1969; Taylor, 1970) and that mutations in their DNA cause phenotypic aberrations that are cytoplasmically inherited (Sagar, 1972). Mitochondria and chloroplasts, which are complex organelles with multiple functions, are thus assembled from, and under the control of, gene products specified by both nuclear and cytoplasmic DNAs. If the functioning of cytoplasmic gene products is dependent on their interaction with nuclear gene products and vice versa, then the harmony between nuclear and organelle genomes will be critical for organelle structure and function. Such nuclear cytoplasmic interaction is a likely basis for Kihara’s gene-for-gene hypothesis and suggests that male sterility and other cytoplasmically inherited traits are due to defective mutant organelles. However, this simple hypothesis does not explain why the organelles are not equally defective in all parts of the plant and why, for example, the same anther can contain both fertile and sterile pollen grains. It seems unlikely that certain cytoplasmic genes coding for organelle proteins are active only in pollen organelles, such that pollen organelles are different from those in other parts of the plant, or that different pollen grains have different types of organelle. To avoid these difficulties, Flavell (1974) has suggested that the failure of organelles to function and replicate in developing pollen is due to the presence of a substance

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which is produced in anthers as a normal part of pollen development but which inhibits the activity of organelles with structures altered by the cytoplasmically inherited mutations. Organelles from genotypes with “normal” cytoplasmic genes would have structures that are insensitive to this substance. T h s model has evolved from the experimental evidence that has recently been gained on the sensitivity of the mitochondria from male-sterile maize lines having the so-called “Texas” cytoplasm to a pathotoxin prepared from the Southern Leaf Blight disease organism Helminthosporium muydis race T. Mitochondria from seedlings with similar nuclear genotypes but normal male-fertile cytoplasm are completely insensitive to this pathotoxin. The pathotoxin almost certainly has a binding site on the inner mitochondrial membrane in Texas cytoplasm male-sterile genotypes, and this binding site is probably controlled by mitochondrial DNA. Turbin er ul. (1968) have shown by electron microscopy of the fine structure of maize anthers that the introduction of nuclear fertilityrestoring genes partially restores the aberrant structures of the cytoplasmic organelles, especially the mitochondria, that are seen in cytoplasmic male-sterile lines. Using H. maydis pathotoxin sensitivity as an assay for mitochondrial inner membrane structure, Barrett and Flavell(l975) have shown that in ten different nuclear genetic backgrounds the presence of nuclear fertility-restoring alleles at the Rf, locus alters mitochondria structure such that sensitivity to the pathotoxin is more similar to that in plants with “normal” cytoplasm. This provides strong evidence that altered mitochondria are involved in cytoplasmic male sterility in maize. The alteration in mitochondrial inner membrane in sensitive plants has little effect on mitochondrial activity in the absence of the pathotoxin. If a molecule of similar properties to the H. muydis pathotoxin were produced in anthers, then mitochondria in cytoplasmic male-sterile anthers would be inactivated while those in cytoplasmic male-fertile anthers would remain active. Confinement of this moecule to anther tissue would enable the altered organelles in somatic and egg tissues to function essentially normally. A non-even distribution of the molecule before pollen wall formation in the developing male-sterile anther would explain areas of fertile pollen in a mostly sterile anther and vice versa. Since production of such a molecule would be a regulated part of differentiation, it is not difficult to see how its production and transport could be influenced by the environment which would explain the effects of the environment on the degree of male sterility. Nuclear fertility-inhibitor or -restoring genes could operate either by altering the binding site of the molecule on the organelle or by affecting its production and transport. At present there is no concrete evidence that such organelle-specific developmental substances are present in wheat but the cumulative and possible hormonal nature of fertility and vigor restoration in wheat strongly suggests that they might.

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M. SAGE

D. THE ORIGIN OF NUCLEO-CYTOPLASMIC INTERACTION

There are other cytoplasms known in maize, besides Texas cytoplasm, that confer male sterility. The majority, but not all, of the plants having these cytoplasms are resistant to H. muydis race T. This suggests that they do not have the mitochondrial inner membrane structure that makes Texas cytoplasm sensitive to H. muydis pathotoxin and that the male sterility is caused by some other malfunction or changed structure of the organelles. The multiple functions of mitochondria and chloroplasts suggests that they could mutate to an aberrant form in a large number of ways several of which might, in the course of plant development, result in male sterility. It is possible that a similar range of organelle mutations might explain the cytoplasmic variation found in the Triticinae. Tahir and Tsunewaki (1971a) have drawn attention to the fact that most of the important major fertility-restoring genes so far found in wheat are located on the chromosomes of homoelogous group 1 (Table IV), regardless of their functioning cytoplasms. This fact suggests that at least a part of the cytoplasmic sterility-fertility restoration mechanism present in 7’riticum-Aegilopscomplexes has a common evolutionary basis involving “homo-ancestry” of the fertilityrestoring genes, on the one hand, and of the cytoplasmic determinants, on the other. In a recent review of extrachromosomal inheritance in plant breeding, Harvey et al. (1972) put forward a plausible theory of the origin of nucleocytoplasmic interactions. They suppose that if at some point in evolution the same information was carried by both nuclear and organelle DNA then a portion of this information might have undergone mutation or been lost from either site without any deleterious effect. Related species might then have evolved with the original genetic information coded for in the DNA of either the organelle or the nucleus. Interspecific hybridization between two such species followed by appropriate backcrossing to establish the nucleus of one species in the cytoplasm of the second, or the reciprocal, would then result in N-C combinations in which the original coded information was absent from both the organelle and the nucleus. The organelles of such combinations would then be malfunctional and, depending on the precise nature of the malfunction, this might well lead to physiological changes which in the course of development might result in a spectrum of abnormalities possibly including male sterility. Alternatively, the spectrum of cytoplasmic effects might well result from the absence from both organelles and nuclear DNA of more than one vital piece of coded information. Such N-C combinations would be expected to exhibit specific interaction with nuclear genes since all the original coded information or even part of it in nuclear DNA, whether obtained from the genome of the cytoplasm donor species or from distinct but related species would act to rectify the develop-

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mental aberrations and hence would act as sets of cytoplasm differentiation genes.

E. THE VALUE OF POSSIBLE FUTURE DEVELOPMENTS

The logical extension of this argument is that, as Hermsen (1965) suggested some time ago, cytoplasmic malfunctions in N-Ccombinations might be rectified equally well by introducing the missing coded information as cytoplasmic DNA as by introducing the right nuclear genes. Hermsen suggested that male sterility, even if it apparently was controlled solely by single recessive nuclear genes as in barley, was in reality a nucleo-cytoplasmic situation and that male fertility might result if the same genes were present in’ a different “restoring” cytoplasm. No such situation has yet been found in wheat, but Pfeifer (1972) has recently suggested a method of producing hybrid barley based on such a “restoring” cytoplasm. A single recessive gene in the cytoplasm of the variety Betzes causes male sterility when homozygous. The dominant allele at this locus, which is carried by normal male-fertile barley varieties, completely restores male fertility which segregates in F2 in the normal Mendelian manner in the presence of Betzes cytoplasm. However, the homozygous recessive condition in the cytoplasm of the variety Penrad is male fertile. In Pfeifer’s system of hybrid variety production such fertile plants are used to wind-pollinate isogenic lines which are male sterile by virtue of their possession of Betzes cytoplasm. The seed so produced gives 100% male-sterile plants in the next generation, and these can then be pollinated by any normal barley variety to produce a self-fertile F1 hybrid. The great advantage of this system is that it obviates the necessity of introducing nuclear-restoring genes into the male parental lines of potential hybrid varieties. A similar system in wheat might be much less costly than that at present used since it would considerably cheapen the cost of parental line development. The possibility of avoiding the considerable complexities found in breeding restorer lines in wheat by finding a set of cytoplasms in wheat comparable to those of Penrad and Betzes in barley means that considerable effort should now be put into investigating the nucleo-cytoplasmic relationships of those few lines found in wheat where male sterility is apparently due only to nuclear genes (Briggle, 1970). V I . Cytoplasmic Variation in the Absence of Male Sterility

Since 1966 the biochemical investigations of Sarkissian, McDaniel, and Srivastava (Sarkissian, 1972) and others (Fletcher, 1972) have suggested that the populations of mitochondria in plant cells are polymorphic. Sarkissian and his

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co-workers have shown that in wheat, maize, and barley, heterosis for seedling characters in F1 hybrids can be correlated with different aspects of mitochondrial activity which also exhibit heterosis. They have also shown that the mitochondrial activity of 1:1 mixtures of mitochondria extracted from parental lines approximates to the activity of the mitochondria of the corresponding F1 hybrid and that in heterotic hybrids the activity of these 1:l mixtures is significantly higher than that found in either parental line. They have suggested that mitochondria of different kinds are able to interact such that they complement one another both in vitro and in vivo. The significance of these results for the improvement of wheat suggests (1) that highly efficient growth and possibly even high yield is dependent on the collective efficiency of the mitochondria present and consequently is dependent also on mitochondrial genes, and (2) that in vitro measurements of mitochondrial complementation may be a means of estimating the potential combining ability of parental lines without the necessity of producing the actual F1 hybrid combination. If the level of mitochondrial efficiency is an important biochemical component of development and yield, selection for high mitochondrial efficiency should result in improved types. This possibility is, at present, limited by two circumstances. First, not all workers who have tried with wheat have been able to repeat the original work of Sarkissian et ul. (Zobl et ul., 1972; Ellis et ul., 1973) although some have (Sage and Hobson, 1973). Ultimately, these differences may be explicable in terms of the different material and techniques used by different workers. A more permanent limitation arises from the fact that even if mitochondrial efficiency is a measurable component of whole plant efficiency it is likely to be only one of many. Other factors in different genotypic backgrounds and in different field environments may have a greater influence than mitochondrial efficiency. This would, of course, severely limit the latter’s value as a selection criterion. This investigation of the physiological effects of mitochondrial variation is still at a very early stage. More work needs to be done both at a biochemical level and in the field before practical techniques for plant breeding emerge. However, it is likely that as knowledge of organelle biochemistry in wheat increases, breeders will increasingly be able to take advantage of it and in doing so will be manipulating cytoplasmic variation. V I I. Conclusion

What has been discovered, so far, about the interaction of nucleus and cytoplasm in wheat will certainly result in both theoretical and practical advances. At the practical level the cytoplasmic variation that has been demonstrated, together with corresponding nuclear variation, will allow breeders to

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develop sophisticated systems of hybrid wheat breeding (Lucken, 1973). The intentional production of haploid plants and the exploitation of advantageous cytoplasmic variation, such as induced disease resistance, may well, on the other hand, facilitate the breeding of pure-line varieties. Any increased use of fundamental biochemical selection criteria, such as mitochondria1 efficiency, would facilitate both pure-line and hybrid variety production. At a more theoretical level a greater understanding of the evolution of wheat has already been attempted by workers investigating nucleo-cytoplasmic relationships (Suemoto, 1968; Maan and Lucken, 1971a; Maan, 1973b) and this will no doubt continue. But perhaps the most interesting advances will come in the field of pure genetics because here the study of the interaction of nuclear and cytoplasmic DNA will provide a link between our genetical and physiological understanding of the wheat crop.

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ASPECTS OF THE COMPARATIVE PHYSIOLOGY OF GRAIN YIELD IN CEREALS

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L T Evans and 1 F Wardlaw Division of Plant Industry. CSIRO. Canberra. A.C.T., Australia

I. Introduction .................................................. I1. Originsand Adaptation .......................................... 111. Reproductive Development ....................................... A . Juvenile Stage ............................................... B. Vernalization ............................................... C. Response to Daylength ........................................ D. Inflorescence Development ..................................... IV . Root Growth and Nutrient Use .................................... A . RootGrowth ............................................... B . Nutrient Use ................................................ V. Canopy Growth ................................................ VI . Leaf Photosynthesis ............................................. A . Differences between C, and C, Cereals ........................... B . Differences between Cultivars ................................... VII . Canopy Photosynthesis .......................................... A . Canopy Architecture ......................................... B. Photosynthesis by Stems and Ears ............................... C. Respiratory Losses ........................................... VIII . Translocation .................................................. A. Loading and Export .......................................... B. Phloem Capacity and Speed of Movement ......................... C. Unloading of Assimilates ...................................... D. Distribution of Assimilates ..................................... E. The Role of Reserves ......................................... IX . GrainGrowth .................................................. A. The LagPeriod .............................................. B. DurationofGrainGrowth ..................................... C. The RateofGrainGrowth ..................................... D. Protein Storage .............................................. X . Limiting Stages in the Life Cycle ................................... A. Duration of Life Cycle Stages ................................... B. Photosynthetic Limitations to Yield a t the Various Stages ............. C. YieldComponents ........................................... XI . Conclusion .................................................... References ....................................................

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Introduction

Cereal grains are the major food of mankind . In many of the less developed countries of the world. cereals provide two thirds or more of dietary calories. 301

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Rice in Asia, maize in South America, sorghum in Africa, and wheat in the Middle East are recognized as the staple foods on whose yields famine or feast depends. Among the developed countries there are many, such as Russia and Japan, in which cereals still provide more than half of the diet calories. Although cereals make a smaller direct contribution to the diet of developed countries such as the United States and Canada, total cereal use per person is extremely high. However, most of the grain is fed to stock and becomes an indirect component of human diets. World production of cereals over the last twenty years has increased more rapidly than has world population, but with much more variation from year to year; for the world as a whole, increase in yield per unit area has contributed much more than increase in the area under cereal crops. This is particularly so in the developed countries, but in the less developed countries the rather smaller increases in grain production have been due about equally to increases in yield and in area. The world average yield of cereal grains is 1.7 tonnes per hectare, more than twice as great as that of legume crops and oilseeds. Partly because of their higher yielding ability, cereals are tending to displace the pulses in many less developed countries although they complement one another both agronomically and nutritionally. Also, the rate of increase in yield, on a world scale, is much greater in the major cereals than in the legumes, with the consequence that the cereals are becoming a progressively more predominant component of the world food supply. Given the restrictions on further increase in the area of land under crops (Kellogg and Orvedal, 1969), greater cereal yields are the key to increased food supplies. Improved agronomy, such as better weed control and more timely and effective fertilizer applications, has contributed greatly to the recent increases in cereal yields, as has better control of diseases and pests, whether by genetic or chemical means. Plant breeding has played a major role in three ways, by the selection of disease and pest-resistant cultivars, by developing shorter-statured forms that do not lodge at high levels of fertilizer application, and by selecting cultivars with greater yield potential which can respond to higher inputs. All three plant breeding approaches are essential and must be linked, so it is difficult to partition actual progress among them. At the lower yield levels, improved agronomy may be the major requirement for progress, as with maize in Africa (Eberhart and Sprague, 1973). As fertilizer inputs increase, lodging resistance becomes more important, while in high input systems increase in yield potential may be rate limiting. There have been fashions in the emphasis given to particular processes as the major limitation on cereal yields, and also to the stage of the crop life cycle regarded as most critical. Watson (1952) attached greatest importance to leaf growth, canopy development, and leaf area index (LAI)in the early stages of the crop. In subsequent years much more emphasis has been given to the final stage

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of the cereal life cycle, since Archbold (1945) demonstrated that grain growth is largely based on current assimilation. As a consequence, particular attention has been given to crop photosynthesis through the grain-filling period as a major determinant of yield. More recently, however, evidence has accumulated that the capacity to store assimilates in the grain may limit yields quite as much as the capacity of the crop to provide them during the grain-filling stage (cf. Evans, 1972, 1975; Rawson and Bremner, 1976; Thorne, 1973; Yoshida, 1972). The storage capacity of the crop is largely determined during the middle of its life cycle, in the period between inflorescence initiation and anthesis, partly by reproductive processes leading to the formation of the inflorescence and partly by the availability of photosynthate and nutrients at that time. In “source-versus-sink” arguments, it is important to remember that the potential size of the sink is largely determined by the photosynthetic assimilate supply at an earlier stage in the life cycle. Currently, therefore, more attention is being given to the middle “reproductive” stage of the cereal life cycle. But the plant breeder, and the crop physiologist, must consider all three stages-vegetative, reproductive and grain filling-because stable high yields will be obtained only when the yield-determining processes operating in all three are in balance with one another. Clearly, there is no one formula for achieving this, because the seasonal sequence of conditions under which the crop is grown plays a major part in determing the optimum balance of yield components. There are many paths to success as a crop plant, both within and between species. In this review we concentrate particularly on the physiological variety found among the various cereals and the ways in which this influences both yield and adaptation. II. Origins and Adaptation

The cereals were originally domesticated at tropical or low latitudes, but their most conspicuous agronomic development has been at higher latitudes, under longer days and cooler temperatures. This has required substantial change in their response to daylength, and also to temperature in the case of japonica rice. Consequently the cereals are now adapted to quite different sequences of seasonal conditions a t the various stages in their life cycles compared with those at their hearth of domestication. The overall range of adaptation within each species is now very wide. Even so, the major cereals still reflect their varied origins by occupying quite different agroclimatic niches. The wild diploid progenitor of wheat occurs throughout the Fertile Crescent of the Middle East, where it was first domesticated about 10,000years ago along with barley and several pulses (Harlan and Zohary, 1966) by the selection of nonshattering, larger-seeded forms. Tetraploid wheats also developed in this area

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at about the same time. The final step in the evolution of wheat was the hybridization of the tetraploids with Aegilops squarrosa to give the hexaploid bread wheat Triticum aestivum. Aegilops squarrosa occupies a wider range of environments than do the other wheat progenitors. As such it may have conferred on wheat not only the protein characteristics required for bread making but also a greatly increased adaptive range. This enabled wheat to become a crop of both subhumid and semiarid steppes (Zohary et al., 1969), capable of adaptation to more acid soils (Slootmaker, 1974), and leading to its subsequent spread through central Europe to higher latitudes and more humid environments. In its original environment, wheat germinated with the onset of autumn rains, grew through the winter to flower in early spring and mature its grains before the summer drought. It was a vernalizable long day plant. Barley (Hordeum vulgare) was domesticated at the same time and place as wheat, and may have been even more important than wheat in the early stages of domestication. A wholly diploid crop, its history of change is similar to that of wheat, but it is not so well adapted to extreme cold. Rye and oats, on the other hand, appear to have been weeds of wheat and barley in the Middle East, but to have become secondary crops of increasing importance as the temperate cereals spread to higher latitudes and cooler, wetter climates. Oats derive from a polyploid series like wheat, the hexaploid Avena sativa being the main cultivated form. Rye (Secale cereale) is diploid, like barley, with a notable winter hardiness and a capacity to grow on light and acid soils. By contrast with these temperate, small grain cereals, maize, sorghum, and the millets were all domesticated in the tropics and are adapted to growth at high temperatures, all being susceptible to frost injury. Originally they were all short day plants, unable to flower in the long days of temperate summers. Maize (Zea mays) was probably first domesticated in Central America, but no wild ancestor has been found. Intolerant of both shade and drought, it presumably originated in an area with alternately wet and dry seasons, in which control of life cycle timing by daylength was very important. Many tropical races of maize are short day plants (Stevenson and Goodman, 1972), whereas modem temperate-zone cultivars appear to be almost wholly indifferent to daylength. Sorghum (Sorghum bicolor) was probably domesticated in Africa, possibly 5000 years ago (de Wet and Harlan, 1971), in the savanna belt stretching from Lake Chad to the Sudan (Harlan, 1971). From there it spread through Africa and India to China. Many tropical sorghums are strict short day plants in which local adaptation of daylength response is very important. Among indigenous Nigerian sorghums, for example, Curtis (1968) found that local varieties had been selected to flower on the average date at which the rains ended in each locality, such behavior resulting in the most reliable yields over a period of years. As with soybeans, the requirement for short days initially confined sorghum to

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the southern United States, but the selection of earlier maturing varieties and hybrids led to its cultivation at higher latitudes (Ross and Eastin, 1972). Sorghum is not yet as well adapted to cool temperatures as is maize, but it is more drought resistant. Stomata in maize are more sensitive than those of sorghum to water stress and close sooner, but maize leaves tend to be more heat tolerant. The stomata of pearl millet (Pennisetum typhoides) are even more sensitive to water stress, and the leaves more tolerant to heat, than in maize (Sullivan and Blum, 1970). The millets as a group tend to be grown in areas with hotter, shorter seasons and poorer soils than those suitable for maize and sorghum, but there is considerable variety of behavior among the group. Of the 57 million hectares sown to millets, almost half are under pearl millet, particularly in southern Asia and North Africa. A quarter of the area is in Setaria millets, mainly in eastern Asia, 14% in panic millet (Panicurn miliaceum), 8% in Indian or finger millet (Eleusine coracana), and about 9% in several other species (Malm and Rachie, 1971). Several of them originated in Africa (Harlan, 1971). All are intolerant of cold. The millets have received far less agronomic and physiological attention than sorghum and maize and would repay more. Pearl millet has been the most extensively studied (Burton and Powell, 1968). The other major cereal is rice, in which there are two parallel series of species ranging from wild perennial to cultivated annual. One species (Oryza glaberrima) was domesticated in West Africa, the other (0.safiva)in Asia, near Burma. Rice crops are predominantly rainfed, their most characteristic environment being the flooded paddies of the tropics. Japonica varieties adapted to cooler temperatures and longer days than are the indica varieties were long ago selected in China, Japan and other countries (Chang and Oka, 1976). In rice, as in other cereals of tropical origin, response to daylength has also been considerably modified as the crop spread to higher latitudes. Most wild forms and tropical cultivars are short day plants and strongly photoperiodic, although a few of the traditional upland varieties are relatively insensitive to daylength. At higher latitudes the cultivars become even less sensitive (Oka, 1958; Velasco and de la Fuente, 1958; Katayama, 1964b). Clearly, the major cereals have all proved to be highly adaptable in the course of their evolution, and each now encompasses among its cultivars a wide range of behavior, particularly in the timing of its life cycle in relation to seasonal changes. This should be borne in mind throughout the following discussion. I I I. Reproductive Development

Control of the reproductive cycle by daylength or temperature is an important component of the adaptation of wild plants to their environment. It is also

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important in crop plants insofar as it determines both the overall length of the life cycle and the relative length of the three main phases in it. In the first or vegetative phase of the cereals, leaf and root growth and tillering predominate, but the extent of growth in this phase determines to some extent the responses during the following phase. The second phase, the reproductive period, extends from floral induction and the initiation of inflorescences to their anthesis and fertilization. Conditions during this phase determine the rate and extent of floral differentiation, and therefore the potential storage capacity of the crop. Nearly all stem growth in cereals occurs in this phase, and therefore in competition with the developing inflorescences. Conditions during the third or grain-filling phase then determine to what extent the potential grain storage capacity is realized in final yield. The length of the vegetative phase depends on whether or not there is a juvenile stage and on the extent to which floral induction is delayed by photoperiod or vernalization requirements.

A. JUVENILE STAGE The possible occurrence of a juvenile stage in the temperate cereals has received little attention. Some wheats can respond to long days as soon as their first leaf emerges (Cooper, 1956), but others may be insensitive to long days for some time (Gott, 1961). Among the warm climate cereals, however, a pronounced juvenile stage is known to occur as in pearl millet (Burton and Powell, 1968), in tropical cultivars of maize (Francis, 1972) and in rice (e.g., Katayama, 1964a; Vergara et al., 1969; Misra and Khan, 1973). There appears to be an inverse relation between the sensitivity to photoperiod and the length of the juvenile stage among tropical rice cdtivars. Indeed, domestication of tropical rice seems to have led to a progressive lessening of the requirement for short days coupled with an increase in the length of the juvenile stage (Chang and Oka, 1976). Clearly, this is an effective way of delaying inflorescence initiation in cultivars which may be grown over a range of latitudes and at several seasons of the year, in multiple crop systems.

B. VERNALIZATION

Vernalization responses to prolonged low temperatures are confined to the temperate cereals among which cultivars differ greatly in the extent of their response. Winter cereals may have a pronounced and absolute requirement for vernalization before they can respond to long days, which serves to delay inflorescence initiation until after winter in autumn-sown crops. But spring-sown

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cultivars may also have quite marked vernalization responses (e.g., Levy and Peterson, 1972), which can be of advantage in delaying inflorescence initiation until the risk of frosts has passed. Such delays in inflorescence initiation may also be of value by increasing the number of spikelets differentiated, and therefore the yield capacity in some circumstances (Rawson, 1970).

C. RESPONSE TO DAYLENGTH

Many early experiments, summarized by Samygin (1946), indicated a sharp distinction in their daylength response between the temperate and the tropical cereals. Wheat, oats, barley, and rye are all long day plants, whereas maize, sorghum, rice, and all the millets tend to be short day plants. However, the spread and adaptation to higher latitudes by the tropical cereals has been associated with-in fact made possible by-a reduction in their requirement for short days for inflorescence initiation. In maize, for example, whereas most tropical cultivars are very responsive to short days, many modem temperate-zone cultivars are relatively insensitive to daylength (Stevenson and Goodman, 1972; Francis, 1972), but still not entirely so (Hunter er al., 1974). The situation is similar in sorghum (Curtis, 1968; Doggett, 1970), millet (Razumov, 1955; Kornilov, 1960), and rice, the subject of numerous photoperiodic studies (e.g., Katayama, 1964a,b, 1974; Chandraratna, 1954; Velasco and de la Fuente, 1958; Dore, 1959). Vergara and Lilis (1967) found no long day plants among more than one hundred cultivars of rice. Cultivars less sensitive to short days may nevertheless be inhibited from flowering when night temperatures are low (Wu and Yao, 1974). The response of cereals to daylength not only determines how rapidly they initiate inflorescences, but may also affect their size, although data are lacking for most crops. More rapid flower induction of wheat by exposure to longer days hastens initiation of the terminal spikelet and thereby reduces spikelet number (Rawson, 1970; Wall and Cartwright, 1974). Possibly for this reason, wheat lines insensitive to daylength flowered sooner and yielded less in some environments than their daylength-sensitive isogenic counterparts (Lebsock er al., 1973). Moreover, daylength influences not only floral intiation but also the rate and course of floral differentiation. In fact, short days may be even more important for the development of inflorescences than for their initiation in some tropical rice cultivars (Owen, 1969). Some wheats that do not need long days for inflorescence initiation nevertheless require them for inflorescence development. Exposure to short days after inflorescence initiation leads to floret sterility in barley (Batch and Morgan, 1974), and may cause the transformation of stamens to ovaries in wheat (Fisher, 1972). By contrast, exposure to long days during

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their differentiation may cause abnormalities in the staminate inflorescences of maize (Galinat and Naylor, 1951).

D. INFLORESCENCE DEVELOPMENT

There is a substantial range in inflorescence structure among the cereals, from the open panicles of rice and oats, through the more condensed panicles of modem sorghum, to the spikes of wheat, barley, and rye and the highly condensed ear of maize. Some inflorescences, like those of wheat, are determinate, whereas others, like those of maize and barley, are not. Only in maize are there separate male and female inflorescences. Descriptions of the normal course of inflorescence differentiation have been given for maize, wheat, rye, barley, and oats by Bonnett (1967), for sorghum by Eastin (1972a), and for rice by Matsushima (1970). An important feature of many cereals is the trend toward closer synchrony of flowering and grain development, which allows more grains within each inflorescence to compete on relatively equal terms. This is clearest in the short day cereals in which there is a pronounced reversal in the gradient of differentiation during development. Whereas panicle branches differentiate acropetally, their subsequent development displays a basipetal gradient, as Nanda et al. (1957) first noted with Panicum rniliaceum and Nanda and Chinoy (1958) with pearl millet. Likewise, Eastin (1972a) has indicated that although the order of differentiation of primary, secondary, and higher order branches in the inflorescences of sorghum is acropetal, subsequent floret development is basipetal in order. Consequently, the order of anthesis is basipetal, as also in Setaria (Malm and Rachie, 1971) and the other millets. This is true of some species and cultivars of rice, but not of all (Katayama, 1970). As a result of this reversal in the gradient of development, the differences between florets in time to anthesis are reduced compared with those in the time of their initiation. A similar reversal may occur in oats, in which spikelet differentiation proceeds basipetally (Bonnett, 1967), and may therefore be a feature of the paniculate cereals. It occurs in wheat to the extent that the terminal spikelet, although the last to be initiated, soon becomes the most advanced. Within wheat spikelets, differentiation remains acropetal, but the later florets catch up on the early ones by the time meiosis occurs (Bennett et al., 1973). A continuation of this process is seen in the faster growth of the second floret grains compared with those of the basal florets in wheat (Rawson and Evans, 1970; Bremner, 1972). This trend toward closer synchronization of anthesis among the florets of an inflorescence is important in determining the number of grains set, particularly

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in cereals like wheat in which linear increase in grain weight growth begins a few days after anthesis. Apart from florets in favored positions, those reaching anthesis more than a few days after the earliest florets usually fail to set grain (Evans el al., 1972). Also, grains in the later developing florets tend to be smaller in their final size (Kirby, 1974). However, many other factors, such as position in the inflorescence, may also affect final grain size, the number of grains set, and even their protein content (e.g., Rawson and Evans, 1970; Bremner, 1972; Spiertz, 1974; Youngs and Shands, 1974). Environmental conditions markedly affect inflorescence development, pollen formation being particularly sensitive to stress. Matsushima (1970) concludes that the reduction division period is the most critical in the life of the rice plant. Satake and Hayase (1970) suggest that the young microspore rather than the actual reduction division stage is most sensitive to temperature in rice. While the critical temperature for japonicu rice at this stage is in the range 12'-15'C, a similar effect on wheat pollen can be seen at 0°-3'C (Toda, 1962). Either drought or excessive flooding during pollen meiosis may also cause infertility in rice (Matsushima, 1962). Water stress, low light intensities, or high temperatures during meiosis can also have adverse effects in wheat (Bingham, 1966; Fischer, 1973), oats (Skazkin and Lukomskaya (1962), and barley (Aspinall er al., 1964). The setting of grains following anthesis is another highly susceptible stage of development. Low light intensity, high temperatures, or water stress all reduce grain set in wheat (Hoshikawa, 1959; Asana, 1961; Wardlaw, 1970). Rice is particularly sensitive to low light intensities at grain setting (Wang and Yan, 1965; Yoshida and Parao, 1976), as is maize (Moss and Stinson, 1961; Prine, 1971). Maize is also very sensitive to water stress at silking (Denmead and Shaw, 1960). However, environmental conditions even during the earliest stages of inflorescence development may have marked effects on yield. Development is faster at higher temperatures, which tend t o reduce the number of spikelets differentiated in wheat (Friend, 1965; Rawson, 1970; Halse and Weir, 1974) and rice (Yoshida, 1973a; Yoshida and Parao, 1976). Higher light intensity, on the other hand, although often coupled with higher temperatures, tends to increase the number of spikelets differentiated in rice (Matsushima, 1970; Yoshida and Parao, 1976) and wheat (Friend, 1965). At least two quite separate elements may be involved in the effects of environmental conditions during inflorescence development on cereal yields. One is time, the other assimilate supply. The more favorable the photoperiod and the higher the temperature, the less time there is available for the differentiation of more panicle branches, more spikelets, or more florets, thereby reducing potential yield capacity. But the supply of assimilate, as influenced particularly by light intensity but also by nitrogen levels (Holmes, 1973), is also crucial at this stage in crop development.

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L. T. EVANS AND I. F. WARDLAW IV. Root Growth and Nutrient Use

The major roles of the root system of crops are to obtain essential nutrients and water from the soil and to support the plants, supplemented by a less well-defined role in the supply of special metabolites to the shoot.

A. ROOT GROWTH

A well-developed root system has been considered an important factor in yield for a long time, and there have been many studies of root growth and function (cf. Troughton, 1962; Brouwer, 1966; Baldy, 1973). There are several rooting strategies available to the plant in its utilization of underground resources, the relative effectiveness of which depend on soil properties such as water-holding capacity, porosity, depth, and nutrient status, as well as on the aerial environment through such factors as temperature, light, and rainfall patterns. Three critical features of root distribution that need to be assessed and analyzed are (1) the rooting density which influences the thoroughness with which a unit volume of soil is explored, (2) the duration and rate of root extension, which govern the ability to explore new soil, and (3) the depth of penetration, a measure of the ability to utilize distant resources such as a deep water table. There are many instances where the superiority in growth of one cereal or cultivar over another is attributed to variation in their rooting characteristics, yet these differences are not easily verified. Rye is used extensively in parts of Europe because of its ability to grow well under harsh and low nutrient conditions and one assumption is that it has a more efficient or larger root system than the other temperate cereals. Sorghum is favored over corn in drier areas with more erratic rainfall supposedly because of its more extensive root system, yet there have been few direct comparisons of the roots of corn and Sorghum under drought conditions.

I . Root Function and Growth Patterns When considering the physical dimensions of the root system, it is necessary to know how the parts of the system function. It appears that water, and the major nutrients (N, P, K) are taken up quite efficiently along the length of the root despite a considerable thickening of the endodermis (Scott Russell, 1970; Robards et al., 1973), unless the cortical cells become desiccated under a period of dry conditions (Clarkson et al., 1968). At lower temperatures, assimilates from the leaves are more uniformly distributed along wheat roots, which may be associated with more sustained ion uptake by the older parts of roots (Rovira and Bowen, 1973). In contrast, uptake of the divalent cation Ca2+appears to be

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limited to young root tissue except possibly in maize (Ferguson and Clarkson, 1975). The growth of roots is seldom continuous throughout development and there are many studies that point to a cessation of growth at about the time of heading in both temperate and subtropical cereals (Sugimoto, 1965; Welbank and Williams, 1968; Mengel and Barber, 1974). Under favorable nutrient and moisture conditions, however, root growth can continue well into the grain development period (McClure and Harvey, 1962; Hurd, 1968). Meaningful root measurements have also been difficult to obtain and assess, but several detailed studies have suggested that the growth of the whole root system and of its individual components are closely related. Primary root number in rice correlates with the number of secondary roots, total length, total dry weight, and whole surface area (Nagai er al., 1962). Hackett (1969) noted that in barley there tends to be a constant relationship between the total number of roots, their surface area, volume, and dry weight of the different members, and suggested that any one of these features could be used to express the absorbing activity of the root system. This relationship was roughly constant throughout development and was not greatly altered by root tip damage, which caused enhanced lateral branching (Hackett, 1971). A similar relationship was noted in Sorghum bicolor (Hackett, 1973).

2. Genetic Vm'ation Both varietal and species differences in rooting patterns occur (Troughton, 1962; Troughton and Whittington, 1969), but their importance is difficult to evaluate because of the variations caused by both soil and aerial environmental factors. Troughton (1962) found both depth of penetration and lateral spread of roots to be greatest in rye and least in oats among the four main temperate cereals grown in deep light soils. Van Dobben (1962) found that root dry weight was 70%greater in winter rye than in winter wheat, but Pavlychenko (1937) found no superiority in the rooting of a spring rye variety over that of barley or wild oats, nor is there any evidence for this in the work reported by Troughton (1962). More recent evidence (Welbank et al., 1973) suggests that there may be no consistent differences in rooting between spring wheat, oats, and barley. Winter cereals tend to develop a greater root system than spring types (Troughton, 1962), presumably because of a longer growth period, but Khan and Tsunoda (1970~)found that the modem spring wheats may eventually acquire a larger root system than either winter or primitive wheats. However, within the spring wheats there is evidence that the longer the vegetative period the greater is root development (Asana and Singh, 1967). Whether the dwarf habit influences root development remains unclear. Applications of the growth retardant CCC

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[(2-~hloroethyl)trimethyl ammonium chloride] stimulate root growth (Humphries, 1968), but Lupton et al. (1974) found little evidence that varietal differences in root habit are associated with stem height in wheat, except that shorter cultivars may have had relatively more root activity at depth. By far the greatest bulk of the root system of cereals occurs in the upper part of the soil profile (Welbank and Williams, 1968; Mengel and Barber, 1974). Varietal differences in root distribution in the 0 to 25 cm zone have been reported for wheat (Pinthus and Eshel, 1962). Although Hackett (1973) observed a mean root extension rate of 0.8 cm/member/day for Sorghum bicolor, which was 5-8 times the mean value reported for barley (May et al., 1965), the final depth of penetration of wheat roots (Kinoch et al., 1957; Adontsev et al., 1970) is comparable with those of corn and Sorghum (McClure and Harvey, 1962; Hsiao and Acevedo, 1974). Varietal differences in root patterns help to explain the yield performance of barley and wheat cultivars at different soil moisture levels (Salim et al., 1965; Hurd, 1968, 1974). Asana and Singh (1967) noted a positive correlation between root growth of wheat and the extraction of deep soil moisture. Greater depth of root penetration and root/shoot ratio are associated with greater survival of sorghum seedlings under water stress (Bhan et al., 1973). Deeper roots appear to become progressively more important in extracting water as the soil dries out, and may be of considerable significance during heading and ripening (Troughton, 1962; Passioura, 1972). 3. Environmental Control of Rooting Patterns Root growth occurs under far from uniform environmental conditions, and elongating roots are subject to a wide range of stresses during their development. The pattern of soil moisture availability has a pronounced effect on the patterns of root growth. According to Gingrich and Russell (1957), the greatest effect on root growth occurs at -1 to -3 atm tension. A tension of -9 bars appears to prevent root extension in wheat (Meyer and Gingrich, 1966), and cereal roots have little ability to grow through dry soil (Salim et al., 1965). However, soils do not dry out uniformly and when part of the root system is prevented from growing because it has entered a zone of dry soil, there is compensatory growth in the remaining parts. Troughton (1962) has pointed out that drying in the upper layers of soil can increase the growth of roots and uptake of water from the lower layers. An extreme example of this can be seen in the work of Passioura (1972) where growth of a single seminal root axis was comparable to that of the complete seminal root system of intact controls, due to compensatory branching in the restricted system. In a field study on corn grown in a sandy loam, Hsiao and Acevedo (1974) noted that water stress considerably enhanced root growth at depth.

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The level of nutrition can affect the growth of roots and shoots differentially, root growth generally being reduced under high levels of nutrition (May et al., 1967; Adontsev et al., 1970). The partitioning of dry material into the root relative to the shoot is high in the seedling stages of growth and steadily declines throughout development (Mann, 1957; Bruinsma and Schuurman, 1966). There is some evidence with barley that although the greatest total length of root occurs under the lowest nutrient status, this is due to greater branching rather than to increased extension rate (May et al., 1965). Such responses are not identical for all nutrients, however, and root growth is generally enhanced by a deficiency of nitrogen and phosphorus but not by a lack of potassium (Troughton, 1962; Brouwer, 1966; Hackett, 1969; Welbank et al., 1973). The optimum temperature for root growth, in isolation, is probably very similar to that for the shoot in most plants (Wardlaw, 1968). However, this is not always apparent in intact plants where shoot growth appears to have a competitive advantage over that of roots for a limited supply of assimilate except under conditions of water stress. For this reason, suboptimal temperatures tend to have a less adverse effect on root than on shoot growth (van Dobben, 1962). Temperature may also influence the angle of root growth (Onderdonk and Ketcheson, 1973), and hence penetration. High root/shoot ratios are generally associated with high light intensities (Troughton, 1962; Murata et al., 1965a; Brouwer, 1966), the usual interpretation being that roots are poor competitors for a limited supply of carbohydrate. Welbank et al. (1973) have noted that although growth in root weight is more sensitive to reduced light than is shoot growth of barley, root length may be less affected than weight.

B. NUTRIENT USE

The role of roots in yield determination is closely related to their effectiveness in nutrient and water uptake, but many other factors interact to control the distribution and function of nutrients in plants.

I . Uptake The uptake of nutrients by roots is a metabolic process and as such is sensitive to temperature. Consequently, nutrient uptake is dependent on a supply of carbohydrate from the shoot to the roots, and is enhanced under high light (Jackson et al., 1974). Uptake may be selective, as in the case of K' by barley seedlings. Movement of ions from the roots to the shoot is influenced by the transpiration rate and by water flow through the xylem. Pitman (1965) observed no change in the total uptake of Na and K with increasing transpiration rates in

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barley seedlings, but the proportion of Na to K taken up increased suggesting a role for water movement in the transfer of ions to the sites of active uptake in the roots. In addition to their function in nutrient uptake, roots play an important role in the reduction of N which can then be supplied to the shoot through the xylem both as inorganic N or as amino acids and amides. Nitrate reaching the shoot through the xylem is reduced in leaves in the light (Stoy, 1955; Minotti and Jackson, 1970). In barley, the nitrate reductase activity of the roots was equivalent to that in the leaves (Miflin, 1967). Roots are also known to synthesize growth substances such as cytokinins which may be important in leaf function and possibly in grain development. Nutrient uptake from the soil varies with development and generally falls with time. In some cases, little uptake occurs after heading (e.g., Mehrotra e f al., 1968; Halse ef al., 1969), but in others nutrient uptake may continue well into the grain development period if the supply of nutrients is maintained and the other environmental conditions are favorable (Carpenter et al., 1952; Hanway, 1962; Sims and Place, 1968; Roy and Wright, 1974). The time course for uptake of K may differ from that of other major nutrients in that uptake ceases earlier and K may actually be lost toward maturity (Sayre, 1948; Hanway, 1962; Roy and Wright, 1974). There are species and varietal differences in the uptake of nutrients by roots (Epstein and Jefferies, 1964; Langer, 1966), which appear to be related to morphological and anatomical differences rather than to variation in ion transport mechanisms. N o d e and Fried (1960) found that P absorption per gram of root was greater for millet than for barley at 30°C, but this temperature is well above the optimum for the latter cereal. Varietal differences in selective discrimination against specific ions may occur. Salt-tolerant varieties of barley translocate less Na and C1 to the shoot than do sensitive varieties when grown on high NaCl solutions (Greenway, 1962). 2. Partitioning and Redistn'bution Nutrients taken up by the roots are transferred to the shoot through the xylem. Thus the initial distribution is primarily to the actively transpiring leaves, and it is only after subsequent redistribution through the phloem transport system that many nutrients will reach the active sites of plant growth. Consequently the final distribution of a particular nutrient in a plant will depend on the ability of that nutrient to enter the sieve elements of the phloem and to be contained within this system during transport. About half of the K taken up by the youngest leaves of barley was derived fiom the redistribution of K from other parts of the plant (Greenway and Pitman, 1965). Similarly, there is considerable retranslocation of P from mature

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leaves to growing organs (Greenway and GUM, 1966). N, P, and K are among the most mobile elements (Williams, 1955). Others generally considered to be phloem-immobile, such as Ca, Fe, and Mn, show little movement between tillers (Lee and Ota, 1970). Phosphorus and potassium have a high concentration in all organs during the early growth of rice, but migrate to the panicle during grain development, while nonmobile elements, such as Ca and Mn, build up continuously in the leaves, but do not accumulate in the ear (Hasegawa, 1962). The work of Hanway (1962) on corn and of Roy and Wright (1974) on Sorghum demonstrates differences between the remobilization of N and P, on the one hand, and of K, on the other. In Sorghum 60-70% of the nitrogen and 68-78% of the P was in the grain at maturity, whereas there was relatively little redistribution of K, which largely remained in the stem. In corn, 66% of the total N and 75% of the total P, but only 3 1 4 % of the total K, was located in the grain at maturity. There is a close association between the translocation of P and that of photosynthate in wheat, the direction of movement being governed by the supply and demand for carbohydrates and not specifically by phosphate levels (Marshall and Wardlaw, 1973). Thus, if shoot growth is reduced by P deficiency, there will be less movement of carbohydrate to the deficient shoot and more to the roots, with the consequence that P remobilized from the leaves will also be preferentially transported to the roots. This is an additional reason why root growth, which also has first access to the external nutrient supply, will grow more actively than the shoot under P-deficient conditions. The similarity in distribution patterns suggests that N behaves in much the same way as P. Although K is phloem mobile, its less effective redistribution is probably related to its greater exchange with other tisuses (including the xylem) along the path of movement. V. Canopy Growth

Early growth of cereal canopies is approximately sigmoid in form in terms of both accumulated dry weight and leaf area index (LAI). The increase in LAI is closely paralleled by the increase in canopy photosynthesis, as Puckridge (1971) has shown for wheat. Also evident from his work is how much year-to-year variation there is in the course of canopy and LAI development, even with one cultivar at one site. The rate of early increase in LAI is, of course, dependent on light and temperature conditions. It increases with increased application of nitrogenous fertilizers, and particularly with increased sowing density (e.g., Williams et al., 1965, 1968; Puckridge and Ratkowsky, 1971; Fischer and Wilson, 197%). The maximum LAI reached is also so much influenced by climatic conditions, fertilizer status, and sowing density that valid comparisons between the major

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cereals are difficult to make. All can generate very high LAI values under favorable conditions. Accumulated dry weight bears a close relation to maximum LAI, as may total N uptake by the crop (e.g., Yoshida el al., 1972). Grain yield, on the other hand, increases with increase in maximum LAI only up to a point. It may plateau at still higher LAI values, as Yoshida and Parao (1976) have shown for rice, or grain yield may fall when very high maximum LAI values are attained. Whereas modem dwarf rice cultivars display a yield plateau, the tall traditional cultivars have an intermediate optimum LAI for grain yield (Yoshida, 1972). An optimum LAI at anthesis of 8-10 is also evident in the grain yields summarized by Thorne (1973) for modem wheat and barlzy cultivars. Maize may display an optimum LA1 at anthesis for grain yield, due t o the many barren plants found in dense stands. In the experiments of Williams et d.(1968), 5 plants m-' was the optimum crop density for grain yield, increasing barrenness at higher densities being associated with greater accumulation of sugars in the stems because of the absence of the usual sink for them. However, under other conditions there may be little decrease in grain yield of maize at much higher planting densities and LAI values (Duncan, 1975). Fischer and Wilson's (1975~)results with sorghum stands planted at a range of densities indicate a proportional increase in grain yield with increase in maximum LAI up to 10 (65 plants m-'). Current data suggest, therefore, that the cereals most adversely affected by crowding are maize (because of sterility) and tall cultivars of the small grains (because of lodging), whereas sorghum and the shorter cultivars of the small grains appear to be less affected. Another difference among the cereals appears to be the timing of anthesis in relation to when they usually reach maximum LAI and canopy development. Many wheat crops reach their maximum LAI 2-3 weeks before anthesis begins (e.g., Watson et al., 1963; Fischer and Kohn, 1966; Puckridge, 1971; Fischer, 1975). As a result, the LAI has usually begun t o fall well before the grain is set. On the other hand, anthesis occurs prior to the attainment of maximum LAI in maize (Williams et al., 1968; Kowal and Kassam, 1973), and coincides with it in sorghum (Fischer and Wilson, 197%; Soza, 1973). The cereals also differ markedly in the course of LA1 after reaching maximum canopy development. Later on we discuss the relation between leaf area duration after anthesis and grain yield. In those cereals, like wheat, in which maximum LA1 is reached well before anthesis, LAI may fall rapidly during early grain filling, as shown in Fig. 1. Under such conditions, common to many wheat growing areas, grain growth takes place during a period of no root growth, little canopy growth, increasing water stress, and declining LAI. However, even where water stress is less marked and temperatures are cooler, LAI still falls sharply during grain filling in the temperate cereals. This also happens in the warm climate cereals (e.g., Goldsworthy and Colegrove, 1974; Goldswbrthy et al.,

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Shoots

loooo

p L

x

2> K

r - 8

lO0OC

I - 6

'001

- 4

0

- 2

L 150

0

200

250

300

350

J -50 '2

D A Y OF YEAR

FIG. 1. Changes in the dry weight of roots, shoots, and grain, in LA1 and in leaf water potential during growth of a wheat crop. (Adapted from Connor, 1975.)

1974), but the fall in LAI is often slower and more delayed (cf. Fig. 4) in both maize (Allison, 1964) and sorghum (Fischer and Wilson, 1975c; Soza, 1973).

VI. Leaf Photosynthesis

Photosynthesis provides most of the increase in crop dry weight as well as the metabolic energy required for crop development. The course of crop photosynthesis must therefore be a major determinant of crop yield. Throughout the early life of cereal crops the leaf blades are the main photosynthetic organs and crop growth rate depends on both the rate of expansion of leaf area and the rate of photosynthesis per unit leaf area. Once the leaf canopy has closed, leaf photosynthetic rate becomes the more important determinant, depending not only on weather conditions but also on the geometry of the canopy. Toward the end of the life cycle photosynthesis by the stems, leaf sheaths, and inflorescences tends to becomes increasingly important as the leaves senesce, especially in temperate small grain crops subject to drought stress.

A. DIFFERENCES BETWEEN CJ AND Cq CEREALS

The action spectrum for photosynthesis by leaves of all the major cereal groups was found by McCree (1972) to be closely similar in wheat, oats, barley, triticale, rice, maize, and sorghum. Nevertheless, there exists within the cereals a major difference in the carbon pathway in photosynthesis, which has profound

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implications for both their productivity and their range of adaptation. Rice and the temperate small grain cereals depend entirely on the Calvin (C,) cycle, whereas in maize, sorghum, Italian millet (Setaria itulicu), panic millet (Panicum miliaceurn), finger millet (Eleusine coracaw), and probably pearl millet (Pennisetum typhoides) the Calvin cycle is preceded by C 0 2 furation in the C4-dicarboxylic acids (Downton, 1971). Several characteristics comprising the “C4 syndrome” have been used to establish that the tropical cereals other than rice operate by the C4 pathway, such as the identification of the earliest products of photosynthesis (Hatch et al., 1967), a low C02 compensation point (e.g., Downton and Tregunna, 1968), or the lack of enhancement of the photosynthetic rate at low oxygen concentrations (Downes and Hesketh, 1968). Also associated with the C4 pathway in cereals are other characteristics such as the Kranz anatomy of the leaves and closer spacing of the veins which may influence translocation as well as photosynthesis. It now seems that the Michaelis-Menten constant for the carboxylating enzyme in C3 plants (RuDP-carboxylase) is not much greater than that of PEP carboxylase which mediates the primary carboxylation in C4 plants. More importantly, refixation of C 0 2 by RuDP carboxylase in the bundle sheath cells of C4 cereals, after transfer and decarboxylation of malate or aspartate from the mesophyll, probably takes place at a much higher C02 concentration, and is therefore less susceptible to photorespiratory decarboxylation. Consequently, the minimum values for mesophyll (or residual) resistance to C02 uptake by leaves appear to be substantially lower in the C4 cereals than in the Calvin cycle species. For example, r,,, values of 0.7-0.9 s cm-’ (Gifford and Musgrave, 1973) and 1.0 s cm-’ (El Sharkawy and Hesketh, 1965) for maize are to be compared with minimum values of 4.1 s cm-’ for oats (El Sharkawy and Hesketh, 1965) and 2.7-3.1 s cm-’ for a range of wheat species (Dunstone et al., 1973). The smaller r,,, of the leaves of C4 compared with C3 cereals tends to be associated with a greater stornatal resistance, r,, hence the greater efficiency of the Cq cereals in dry matter production per unit of water transpired. Stomatal opening in the C4 cereals increases up to very high flux densities of light, as in maize (Gifford, 1971). Consequently, whereas photosynthesis by single leaves of the C3 cereals tends to reach light saturation at - 4 full sunlight, that of the C4 cereals increases with increasing intensity up to full sunlight (Hesketh and Musgrave, 1962; Hesketh, 1963). Even so, the minimum recorded gas phase resistances to C02 uptake tend to be rather lower in the C3 cereals, e.g., 0.7-0.8 s cm-’ in wheat (Dunstone et ul.. 1973) compared with 1.5 s cm-’ in maize (El Sharkawy and Hesketh, 1965). The maximum photosynthetic rates achieved by the C4 cereals are distinctly greater than those of the C3 cereals. Rates up to 240-280 ng C 0 2 cm-2 s? have been recorded in maize (Heichel and Musgrave, 1969), sorghum (Downes, 1971), and pearl millet (McPherson and Slatyer, 1973), compared with up to 120 ng

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cm-2 C1 in wheat cultivars at atmospheric C02 levels. However, rates up to 200 ng cm-2 S’ have been measured in the wild diploid wheats (Evans and Dunstone, 1970). The greater rates of photosynthesis in C4 plants, associated with their reduced photorespiratory losses and other characteristics listed above, have led to them being referred to as “efficient” plants, and to a search for nonphotorespiring forms among the temperate cereals such as oats and wheat (Moss and Musgrave, 197l), without success. Other characteristics of the C4 pathway in cereals should be considered, however. Although their greater photosynthetic rate may be of advantage at high light intensities, especially in view of their more efficient use of water, at low light intensities-in overcast weather or for leaves deep in the canopy-their photosynthetic rate may be less than that of C3 plants. This is particularly true when cooler temperatures are associated with low light, the conditions under which the temperate cereals usually make their early growth. Murata and Iyama (1963; Murata et ul., 196Sb) first drew attention to the poor photosynthetic performance of the tropical (C4) grasses at cool temperatures (-10°C) relative to temperate (C,) grasses and cereals such as barley and wheat. At high temperatures, on the other hand, photosynthesis by the C3 cereals falls off rapidly at temperatures above 30”C, as in wheat (Stoy, 1965; Friend, 1966; Sawada, 1970), whereas photosynthesis by the C4 cereals may reach its peak at temperatures of 30”-40”C, as in sorghum (El Sharkawy and Hesketh, 1964), maize (Hofstra and Hesketh, 1969), and pearl millet (McPherson and Slatyer, 1973). Although rice is a crop of tropical origin, its photosynthetic response to temperature resembles that of the other C3 cereals in having a broad optimum (Murata, 1961) with a rapid fall in rate at high temperatures. Cool temperatures, however, have a more adverse effect on photosynthesis in rice than in the temperate cereals, particularly on the indicu varieties (Kishitani and Tsunoda, 1974).

B. DIFFERENCES BETWEEN CULTIVARS

Between the C3 and C4 cereals, and to a smaller extent between indicu and juponicu rices, there are substantial differences in the rate of photosynthesis and in its environmental adaptation. To what extent are there comparable differences among the cultivars of each major cereal? What role have they played in crop evolution and selection for yield? In trying to answer these questions we are confronted with major problems of how to make valid comparisons of leaf photosynthesis rates, since these are so dependent not only on the conditions under which the rates are measured, but also on the rank, age, and previous treatment of the leaf, as well as on the demand within the plant for its photosynthetic products.

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1. Factors Complicating Comparisons

The ontogenetic rank of cereal leaves influences their peak photosynthetic rate under defined conditions of temperature, light intensity, and C02 concentration to a substantial degree, as shown for wheat by Sawada (1970) and Dunstone et al., (1973). Leaf age also has a pronounced effect and its time course seems to vary a great deal depending on conditions. In wheat, for example, the rate of flag leaf photosynthesis may fall progressively with time from anthesis, the fall being particularly rapid in the more primitive wheats (Evans and Dunstone, 1970). In more productive modern cultivars, on the other hand, the rate may fall after anthesis-when the demands of grain growth are low and stem reserves are being mobilized-only to rise again until grain growth slows (e.g., Evans and Rawson, 1970; Rawson and Evans, 1971). This pattern of change was also found by Rawson et al. (1976) for plants in which tillers were continuously defoliated, whereas flag leaves on intact plants of the same cultivar displayed a progressive fall in photosynthetic rate. Thus, the time course of photosynthetic rate in flag leaves of wheat appears to vary in response to the demand for assimilates from it. The nutritional condition of the crop also influences the time course of leaf photosynthesis, particularly the availability of N, but also the K content (e.g., Murata, 1961). A high correlation between % N in the leaf tissue and photosynthetic rate has been established in several cereals, e.g. wheat (Khan and Tsunoda, 1970b), barley (Natr, 1973), maize (Ryle and Hesketh, 1969), and rice (Takano and Tsunoda, 1971). Light and temperature conditions during leaf development may profoundly influence the subsequent photosynthetic capacity of leaves. In maize, growth under high temperature or light intensity increases the subsequent photosynthetic rate (Hesketh, 1968). Although photosynthesis in modern wheat cultivars was not greatly influenced by earlier light conditions, that in the primitive wheats was greatly affected (Dunstone et al., 1973).

2. Assimilate Demand and Photosynthetic Rate The important question to ask in this context is whether control of photosynthetic rate by the demand for assimilates can occur in cereals. The extent to which it does so will presumably depend on experimental and crop conditions. Thorne (1973) accepts that the phenomenon occurs in other crops, but not in cereals. Kiesselbach (1948) found that removal of maize ears at silking reduced final crop dry weight by 27%, which he considered was due to a feedback inhibition of photosynthesis in the absence of the major sink for assimilates. Moss (1962) subsequently demonstrated an initial decline in photosynthetic rate when fertilization of the ear was prevented in maize. With wheat plants, Birecka and

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32 1

Dakik-Wlodkowska (1 963) recorded a substantial reduction in total photosynthesis following ear removal. King er al. (1967) found the rate of flag leaf photosynthesis in wheat to fall by about 40% within one day of ear removal, and to be restored to a high level when the flag leaf was made to support the whole plant because all other leaves were removed or shaded. Similarly, the low rates of flag leaf photosynthesis in plants held in continuous light were increased when ear photosynthesis was inhibited with DCMU. These experiments thus showed that leaf photosynthesis in wheat can be reversibly lowered and raised as the internal demand for assimilates is lowered and raised. The changing pattern of demand for assimilates was demonstrated by concurrent analysis of l4 C distribution within the plants. Recent experiments by Rawson er al. (1976) also found flag leaf photosynthesis to be decreased by partial grain removal and increased by inhibition of ear photosynthesis, but not to as great an extent as in the experiments of King et al. (1967). These effects appeared to be due mainly to changes in stomata1 resistance of the abaxial leaf surface. Puckridge (1969) also presents evidence of reversible control of photosynthetic rate in wheat according to demand, his measurements and treatments being on a crop canopy in the field. Romer (cited by Michael et al., 1973) found that shading of barley ears led to a doubling of the rate of flag leaf photosynthesis and an increase in the proportion of its assimilates exported to the ear from 51 to 86%. Flag leaf removal led to a rise in the rate of photosynthesis by the penultimate leaf in his experiments, and to a rise in ear photosynthesis in those of Johnson er al. (1975). With oats, also, removal of the lower leaves increased the photosynthetic rate of the flag leaf (Criswell and Shibles, 1972), although removal of spikelets did not reduce it. Thus, there is clear evidence, with many of the cereals, that the photosynthetic rate of leaves can respond to internal changes in the demand for assimilates. Photosynthetic rate not only decreases when demand is reduced and alternative sinks for assimilate are limited, but can also increase, indicating the existence of spare photosynthetic capacity within the plant. However, failure to find photosynthetic rate responsive to demand has also been reported for wheat (Lupton, 1968; Dantuma, 1973; Austin and Edrich, 1975) and barley (Apel and Peisker, 1973; Natr, 1967; Apel et al., 1973). Low photosynthetic rates were recorded in many of these experiments, and Austin and Edrich (1975) estimated that only low rates were required in their experiments. However, Rawson er al. (1976) found little evidence of response in photosynthetic rate to demand even when grain growth and photosynthesis were rapid, as long as tillers were allowed to grow, but not when they were continually defoliated. Clearly, whether or not such a response is observed depends on both experimental and crop growth conditions, but there should be little doubt that it can occur in cereals.

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3. Cultivar Differences Given the complications discussed above, it is not easy to make satisfactory comparisons between cultivars in their photosynthetic rate, and even harder to assess their relation to yield differences. From a survey of 22 races of maize ranging from ancient varieties to modern hybrids, Duncan and Hesketh (1968) found no evidence that improvement of maize over the centuries has been associated with an increase in photosynthetic rate. There were, however, differences between races in the way their photosynthesis responded to temperature, which appeared to be adaptive. High altitude races, for example, had relatively lower rates at high temperatures. Differences between maize cultivars in their photosynthetic rate have been reported, but they appear to be very dependent on environmental conditions. Those found by Heichel and Musgrave (1969) in the Philippines, for example, were not always apparent at Comell (Gifford, 1970). Similarly, although heterosis in photosynthetic rate has been reported in some instances (e.g., Fousova and Avratovschukova, 1967; Heichel and Musgrave, 1969; Derieux et al., 1973), there are others where it was not found (e.g., Duncan and Hesketh, 1968). Heichel (1971) associated the lower photosynthetic rate of one cultivar with greater respiratory loss. Substantial differences in photosynthetic rate per unit leaf area have been found in wheat. The highest rates have been found in the primitive and wild diploid wheats (Evans and Dunstone, 1970; Khan and Tsunoda, 1970a; Dunstone et al., 1973), with a progressive fall in the course of evolution. Both between species and among modern cultivars the relation between maximum photosynthetic rate and leaf area is negative (Evans and Dunstone, 1970; Gale et al., 1974). Photorespiration was proportional to photosynthetic rate across many lines (Dunstone et al., 1973), and the latter was negatively correlated with mesophyll cell size (Dunstone and Evans, 1974), but only inconsistently with specific leaf weight (Khan and Tsunoda, 1970b; Dunstone et al., 1973). Dantuma (1973) has recorded limited differences between cultivars of wheat and barley in their photosynthetic rate, as has Murata (1964) for rice. Murata considered there was some correlation between photosynthetic rate and yield but his claim is not convincing in view of the low and narrow range of rates presented. Correlations between photosynthetic rate and crop dry weight or relative growth rate among 12 rice varieties were highly inconsistent (Osada and Murata, 1965). Taken overall, there is no clear evidence among the cereals of any increase in leaf photosynthetic rate in the course of either their earlier domestication or their recent improvement in yield ability. This is rather surprising in view of the central role of photosynthesis in relation to crop growth and yield, and of its rate per unit leaf area as a determinant of the closed canopy rate. Possibly some

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counterproductive feature may be associated with further increase in photosynthetic rate. There is, for example, the negative relation between cell and leaf size and photosynthetic rate in wheat, and the positive relation between leaf and grain size. Consequently, insofar as selection for increased yield involved increased grain size and therefore leaf size, this would have operated against any increase in photosynthetic rate. However, these negative correlations could probably be broken by selection as Wilson and Cooper (1970) have shown with ryegrass. Another possibly counterproductive association may be the inverse relation between the maximum rate and the duration of photosynthetic activity evident among the wheats (Evans and Dunstone, 1970). At present no clear answer can be given to this important question, which merits much more investigation among the cereals. VII. Canopy Photosynthesis

In the early stages of crop growth, the main determinant of its photosynthesis is the extent of leaf area development. As the leaf area index (LAI) increases, so does the extent of light interception, which exceeds 95% for most cereal crops with an LAI of about 4. Once the canopy is closed in this way, further increase in LAI has little effect on crop photosynthesis, which is then most influenced by the incident radiation and the structure of the canopy. Light interception by cereal crops is low during early establishment but then increases rapidly as the larger upper leaves expand and tillers develop. Earlier closure of the canopy can be effected by increase in sowing density, as Williams et al. (1968) have shown for maize. However, although this increases the early crop growth rate, in proportion to the increase in light interception (Williamser al., 1965), it may have little effect on subsequent crop growth rate and an adverse effect on grain yield. Canopy photosynthesis appears to increase asymptotically with increase in LAI, reaching a broad plateau at LA1 values above 4, as illustrated in Fig. 2 for wheat. This shows excellent agreement between field and phytotron-grown crops, and Puckridge and Ratkowsky (1971) found that, at a given level of incident radiation, the relation between net photosynthesis and LA1 was unaffected by either cultivar or sowing density. It is probably similar in the other cereals. The relation between canopy photosynthesis and incident radiation depends on LAI, species, and canopy structure. Both aerodynamic and enclosed canopy measurements suggest that the maximum rates of crop photosynthesis at high levels of incident radiation can be almost twice as high in maize as in wheat (cf. Baker and Musgrave, 1964; Puckridge and Ratkowsky, 1971; Gifford, 1974a). On the other hand, C3 crops may have the advantage at low radiation levels,

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-

2

4

I

I

6

8

I I 1 0 1 2

FIG.2. The relation between photosynthesis, respiration, and LAI in wheat crops (from Evans et al., 1975). The line is for a field crop, the circles for a crop in an artificially lit cabinet.

possibly because of greater stomatal closure in C4 cereals under weak light. Photosynthesis X radiation curves for crops of barley (Biscoe et al., 1975a), rice (Tanaka, 1972), and sorghum (Allen et al., 1974) were obtained in such different conditions as to preclude comparisons. The maximum crop growth rates (CGR) recorded for the various cereals over periods of a week or more may be more validly compared. There are many records of very high CGR for the C4 cereals. Up to 78 g m-' 6' has been recorded for maize by Haggar and Couper (1972), and rates of more than 50 g mm2 d-' by Kowal and Kassam (1973), Takeda and Akiyama (1973) and Williams el al. (1965). With sorghum, CGR of up to 46-51 g m-' d-' are recorded by Fischer and Wilson (1975~)and Williams et al. (1965). Pearl millet has also been found to sustain a high CGR, 54 g m-' d-' (Begg, 1965), and in a comparative study in the Nigerian savannah, Kassam and Kowal (1973) measured rates of 4 6 4 8 g m-' d-' in millet, 30-50 g m-' d-' in maize, and 3 0 4 0 g m-' d-' in sorghum. Crop growth rates for C3 plants are usually, but not always, substantially lower (Gifford,. 1974a; Evans, 1975). Among the C3 cereals, only in rice has a CGR of more than 50 g m-' d-' been recorded (Tanaka er al., 1966). In the very extensive Japanese IBP experiments, however, the highest CGR found for rice was 36 g m-' d-' whereas 52 g m-' d-' was found for maize, and the average values for the latter crop were also higher (Murata and Togari, 1975). Crop growth rates recorded for the temperate cereals are usually quite low, mostly

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less than 20 g m-2 d-' , although a CGR of 30 g m-2 d-' has been measured in wheat (King and Evans, 1967). Thus, in terms of the maximum CGR recorded, the C4 cereals appear to have a major advantage over the temperate C3 cereals. In fact, this advantage is almost too great to be accounted for solely in terms of greater leaf photosynthetic capacity. Associated with the C4 syndrome are many other characteristics, such as better adaptation to high temperature conditions, faster and more complete export of leaf assimilates, and higher maximum relative growth rates, which may also contribute to their higher CGR. So too may differences in canopy architecture.

A. CANOPY ARCHITECTURE

Individual plants of many C4 cereals are much larger than those of the C3 cereals. The size difference is reflected in the optimum planting densities, about 4-8 m-2 for maize and 10-60 m-2 for sorghum, compared with 250-300 m-2 for wheat and rice crops under favorable conditions. Height, leaf size and the vertical separation of leaves is greater in the C4 cereals, features that affect not only light penetration into the crop, but also its ventilation with C 0 2 . With the more distantly spaced plants of the C4 crops, the advantage in having more horizontally inclined leaves in the early stages of crop growth is greater than in the denser stands of the small grains. At later stages, when the LAI exceeds 4, more vertically inclined leaves-with their reduced canopy extinction coefficient-may be advantageous in improving light penetration into the canopy while at the same time reducing the extent of light saturation of leaf photosynthesis when the sun is at high elevation. This advantage should be of greater importance to the C3 cereals, because of their readier light saturation, than to maize, sorghum, and millet. Also, canopy structure in maize can be controlled by the density of planting far more than in the C3 cereals, in which greater tillering compensates for sparser planting. Consequently, increased fertilizer inputs, especially of N, can result in extremely dense communities of the small grain cereals, in which more vertical leaves are likely to be of greater importance than in the more controllable canopies of maize. Similarly, we should expect cultivars bred for lower input systems and sparser communities, in drier areas for example, to be less subject to selection for vertically inclined leaves. With barley, Angus er al. (1972) found crop photosynthesis to be greater with erect leaves; grain yield was greater with erect leaves at high sowing density, but with lax leaves at low density. Tanner et al. (1966) found a strong association between high yield and erect leaves among barley, wheat, and oat cultivars, as did Tanaka et al. (1966) and Hayashi (1966) among

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rice cultivars. More vertically inclined leaves were found by Tanaka (1972) to increase canopy photosynthesis of rice by more than 50% under high radiation levels, and to be associated with higher yields (Tanaka et ul., 1969). For the C3 cereals, therefore, more upright leaves may be advantageous to both photosynthesis and yield in high density crops. Although maize is the cereal in which the effects of leaf inclination have been most fully explored, ironically they remain less clear. Simulation models of maize crop photosynthesis by Duncan er ul. (1967) and Duncan (1971) suggest that although more horizontal leaves may have an advantage at LA1 values less than 3, more erect leaves could result in up to a 2-fold increase in photosynthesis at high LAI. However, Sinclair (quoted by Wallace et ul., 1972) did not find greater photosynthesis in more erect leaved stands. With regard to grain yield, Russell (1972) and Ariyanayagam et ul. (1974) found that yield tended to be higher with less erect than with more erect leaves at several plant spacings. Whigham and Woolley (1974) found greater light interception with less erect leaves but little effect on yield, while Winter and Ohlrogge (1973) found a small yield advantage with more upright leaves at high LAI. Overall, these results suggest that leaf inclination has a greater influence on yield in the C3 cereals than it has in maize and other C4 cereals (cf. Trenbath and Angus, 1975). More vertical orientation of leaves among the C3 cereals could account for Yoshida’s (1972) observation that the LAI at which maximum crop growth rate is reached is rather higher in them (6-8.8 in wheat, 4-7 in rice) than in maize (3-5).

B. PHOTOSYNTHESIS BY STEMS AND EARS An important characteristic of some cereals is the substantial photosynthetic contribution made by both stems and inflorescences, particularly in the later stages of grain growth. The overlapping leaf sheaths that wrap and support the lower parts of the stem can be as photosynthetically active as the leaf blades, e.g., in barley (Thorne, 1959 ). Consequently, they can act as photosynthetic traps for C02 respired by stems during the day. In the same way, the bracts and glumes of the inflorescences may serve as efficient photosynthetic traps for the substantial amounts of C02 respired by the grains during their growth (cf. Abdul-Baki and Baker, 1970). Moreover, the stems and ears of the temperate cereals tend to remain green after many of the leaves have dried off. Although most noticeable in water-stressed crops, the phenomenon is not confined to such conditions, as in the wheat crops examined by Spiertz et ul. (1971). Toward the end of grain filling, therefore, stem and ear photosynthesis can become the major source of current assimilate. But even in the earlier stages of grain growth, stem photosynthesis can be a substantial component (Evans and Rawson, 1970). Puckridge (1969) found stems and leaf sheaths to account for 39-44% of

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canopy photosynthesis in wheat crops. Net photosynthesis by the awned ears was rather less, but increased in relative importance as the elevation of the sun declined. In rice and the C4 cereals leaf senescence is less rapid, and stem photosynthesis is relatively less important. For example, Allison (1964) found leaf blades to comprise about 80% of the total green surface area in maize crops at both anthesis and maturity, whereas in wheat they comprised 50% at anthesis and only 10% at maturity. Nevertheless, leaf sheaths may contribute substantially to grain growth in sorghum under some conditions (Stickler and Pauli, 1961). The importance of photosynthesis by the inflorescence varies to a considerable extent among the cereals, depending on its position and structure. In those having a terminal inflorescence above the crop, with awned glumes, such as barley, rye, and many wheat cultivars, photosynthesis by the ears can be a major source of carbohydrates for grain growth, as Archbold (1945) first emphasized for barley. The ears are exposed to full light and high COz concentrations and their assimilates, being so close to the grains, are in the most favorable position to be used in grain growth. In barley, ear photosynthesis may comprise one quarter to one half of total crop photosynthesis, and contributes 24-84% of grain growth (Birecka et al., 1964, 1967; Biscoe et aL, 1973; Thorne, 1965). The large barley awns are responsible for three quarters or more of the photosynthesis and transpiration by ears (Biscoe et al., 1973; Johnson et al., 1975; Kjack and Witters, 1974). The awns of wheat, when present, are not so large (except in T. dumrn), and ear photosynthesis is not quite so important as in barley. Its contribution to grain growth vanes from 10 to 60% (Saghir et al., 1968; Lupton, 1969; Evans and Rawson, 1970). Cereal awns are not only active in photosynthesis, but may also increase the efficiency of water use by the crop (Johnson et al., 1975), modify the energy balance and turbulence above the crop (Benci et al., 1973; Ferguson et al., 1973), and may increase the movement of cytokinins to the grains (Michael and Seiler-Kelbitsch, 1972; Michael et al., 1973). They may increase the danger of lodging under humid conditions (Pinthus, 1973). The panicles of rice are not nearly so active in photosynthesis and do not even refix all the C 0 2 from grain respiration (Yoshida, 1972). For that reason they could, with advantage, be lowered into the canopy. The large, terminal inflorescences of sorghum can intercept 2 5 4 0 % of incoming radiation (Eastin, 1968). Their net photosynthesis is rather low, especially in the compact types, and confined to the early stages of grain development (Eastin and Sullivan, 1969). Thus, they might also be better recessed within the canopy, like those of rice. However, Fischer and Wilson (1971b) found inflorescence photosynthesis in sorghum to account for 6-18% of grain yield. In maize, the male tassels intercept 4-20% of the incoming radiation (Duncan et al., 19671, but the female inflorescence is positioned well down in the canopy. Although its husks are photosynthetic, their contribution to grain growth is probably slight.

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C . RESPIRATORY LOSSES

We consider here only that respiration, often called dark respiration, in which there is an efflux of COz as the metabolic cost of the cellular work done for growth or maintenance. Differences among the cereals in their “photorespiration,” as a result of the oxygenase activity of carboxydismutase, were discussed earlier in connection with photosynthesis. Respiratory losses represent a substantial fraction of the COz fixed in crop photosynthesis. For example, losses of 14C recorded over a period of weeks after its initial fixation include 20% for maize (Palmer er al., 1973), 25% for wheat (Rawson and Hofstra, 1969; Rawson and Evans, 1971), 33% for barley (Birecka er al., 1967), and 3 4 3 7 % in rice (Lian and Tanaka, 1967). These figures should not be taken as indicating differences among the cereals, because of differences in the stage and conditions in which the plants were exposed to l4COZ. But given the magnitude of the losses, we should ask whether there are differences among crops and cultivars that could be selected for. In early models of crop growth, respiration losses were assumed to be proportional to accumulated dry weight or leaf area of the crop. A consequence of this assumption was the prediction that there should be a clearly defined optimum LAI for crop photosynthesis and growth. Although sometimes recorded (cf. Yoshida, 1972), the usual situation is for net crop photosynthesis to approach an asymptote as LA1 increases. The explanation of this response is that crop respiration also approaches an asymptote, as may be seen from Fig. 2, rather than increasing in proportion to the LAI as earlier assumed. In fact, the respiration rate per unit dry weight of wheat crops falls asymptotically with time (Puckridge and Ratkowsky, 1971) to a minimum value of about 0.016 g g’ d-‘. As is evident from Fig. 2, crop respiration is approximately proportional to photosynthesis. However, it is more satisfactorily estimated on the basis proposed by McCree (1970) as the sum of two terms, one for maintenance and the other for growth. The distinction between these is operational rather than biochemical. Growth respiration represents the metabolic cost of converting the translocated products of photosynthesis to structural, cytoplasmic, or storage compounds. The theoretical efficiencies of the various conversions have been calculated by Penning de Vries (1972, 1975), who has shown them to be unaffected by temperature. Although there are differences between species and between organs, these probably reflect differences in their composition rather than differences in synthetic efficiency. There may, however, be substantial differences among crops and cultivars in the other term, for maintenance respiration. Whereas growth respiration represents the cost of producing new tissues, maintenance respiration is for the renewal or replacement of old structures. McCree (1970) related it to accumulated dry weight, and on that basis it becomes the dominant term in the

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respiration of crops toward the end of their life cycle. The rate of maintenance respiration depends on temperature and on other conditions. There are still too few estimates of it for different crops to be compared. For maize they range from 0.008-0.022 g S' d-' (Penning de Vries, 1972, 1975), lower than those for sunflower. Similarly, McCree (1974) found those for sorghum, 0.0068 g g-' d-' at 20°C and 0.01 1 g g' d-' at 30°C, to be only about half as great as those for white clover, even when expressed on the basis of protein rather than dry weight. A rate of 0.12 g g-' d-' fits the crop respiration measurements of Biscoe et al. (1975a) for barley, similar to those for C4 cereals and to the minimum rate for wheat crops mentioned above. Thus, the cereals all appear to have rather low rates of maintenance respiration compared with other crops like sunflowers, white clover, or cotton (Hesketh et al., 1971). Differences that may exist among the cereals are unlikely to be revealed by such comparisons, however. They require more direct analysis. Among 6 cultivars of wheat of varying height, Rawson and Evans (1971) found a 4-fold variation in the respiration rate of stems, the rate increasing as stem length was reduced. Heichel (1971) found the faster growing of two maize cultivars to have lower respiration rates in its leaves and roots, which suggests there could be very different rates of maintenance respiration in the two cultivars. How could these differences arise? To a large extent maintenance respiration probably derives from the turnover of enzymes and membrane proteins (cf. Penning de Vries, 1975). It is likely to be tightly coupled in the biochemical sense, but not necessarily in the physiological sense in that the rate of turnover may be dependent on substrate levels. Indeed, Penning de Vries (1975) offers evidence of such dependence in maize. This could account for the observations of Birecka and Dakit-Wlodkowska (1963) and Birecka et al. (1969) that the removal of wheat ears led to a 2-fold increase in the rate of stem respiration. On this basis, Heichel's (1971) slower growing maize would have a higher respiration rate because it grew slowly, not the other way round. But we need far more varietal comparisons before any conclusions about the effect of differences in respiration rate on yield can be drawn. VIII.

Translocation

Limitations to yield in cereals have often been considered in terms of the relative importance of the source (photosynthesis) and sink (grain growth), with little or no account being taken of the system transporting assimilates from source to sink. The capacity of this system could limit grain growth however, and changes in the transport and partitioning of assimilates are likely to have been a major component in the evolution of the cereals.

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A. LOADING AND EXPORT

Differences among the cereals, especially between those with the C3 and C4 photosynthetic pathways, are apparent at the very first step in the translocation process. The distance between the parallel veins in leaves of C4 gramineae is only half or less that in the C3 species (Lush and Evans, 1974) and the distance traversed from the site of fixation to the phloem is correspondingly smaller (Wardlaw, 1976). However, there is an approximately 2-fold range in these distances within the two groups and even between cultivars of a species (Khan and Tsunoda, 1971; Hanson and Rasmussen, 1975). Presumably related to this is the much faster export of assimilates from the C4 cereals. Hofstra and Nelson (1969) first showed this in comparisons between maize, sorghum, and millet with various dicotyledonous crops, and Moss and Rasmussen (1969) in comparisons between maize and sugar beet. Subsequent experiments (Lush and Evans, 1974; Gallaher et al., 1975; Wardlaw, 1976) have extended these comparisons to several C3 and C4 gramineae. Not only is initial export more rapid in the C4 cereals, it is also more complete; what is not exported immediately is stored as starch in the bundle sheath chloroplasts by day, and almost entirely mobilized and exported during the following night (Rhoades and Carvalho, 1944; Lush and Evans, 1974). In the C3 grasses and cereals, on the other hand, a greater proportion of assimilates is accumulated in the leaves, and these are exported more gradually. C3 and C4 plants may also differ in the loading of their assimilates into the phloem. This appears to be an active process in C3 plants, requiring metabolic energy and accompanied by the hydrolysis and resynthesis of sucrose, usually associated with movement against a concentration gradient. Such hydrolysis does not occur in sugar cane (Hatch and Glasziou, 1964) and loading into the phloem of C4 gramineae from the bundle sheath cells may take place down a concentration gradient (Lush and Evans, 1974). Possibly for this reason, initial export of assimilate is more adversely affected by low light intensity in the C4 grasses. The high sugar content of the bundle sheath cells may be associated with their greater resistance to injury by water stress, as in maize (Giles et al., 1974).

B. PHLOEM CAPACITY AND SPEED OF MOVEMENT

A manyfold increase in the need by ears to import assimilates through the peduncle has occurred in the course of evolution in cereals. In wheat, this increased need has been matched by a comparable increase in the area of phloem in the peduncle, with the result that the rate of transfer of assimilates per unit cross-sectional area of phloem has not changed (Evans er d.,1970). In fact, the rate in all genotypes is close to the average rate of 3.6 g cm-' phloem h-' which

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Canny (1960) found in a number of plant systems. This could be taken as indicating a limitation by phloem on the rate of translocation. However, the leaves of C4 gramineae maintain specific mass transfer rates 3 4 times higher than those in C3 grass leaves (Lush and Evans, 1974), and Passioura and Ashford (1974) have found specific mass transfer rates of up to 180 g cm-' sieve tube h-' in the upper root of wheat seedlings. Along with this greater rate of assimilate translocation in C4 gramineae, its speed may also be faster, although there are too few measurements to be sure. Speeds of up to 100 cm h-' have been measured in the peduncle of wheat (Wardlaw, 1965), up to 180 cm h-' in the leaves of rice (Troughton er al., 1974a), and up to 210 cm h-' in the leaves of maize (Troughton et al., 1974b; Moorby er al., 1974). Wardlaw and Marshall (1976) found translocation in Sorghum sudanense to be 2-3 times faster than in a C3 grass, u p to 200 cm h-'. However, the speed of movement appears to be very responsive to increased push from the sources, increased pull from the sinks, or restrictions in the vascular pathway. In both rice and maize the speed increases with increase in light intensity and leaf photosynthesis. In wheat culms it increases as the need for assimilates by the ear increases, whether due to more grains or the inhibition of ear photosynthesis (Wardlaw, 1965; Wardlaw and Moncur, 1976). Similarly, severing half of the vascular tissue in the stem soon leads to a compensating increase in transport through the remainder to the ear, both in sorghum (Fischer and Wilson, 1975a) and in wheat (Wardlaw and Moncur, 1976). These results suggest, therefore, that the capacity of the vascular system is unlikely to be a major limitation to yield in cereals. Diffusion of assimilates to the phloem in the leaves, and from the inflorescence phloem across the grains may, however, be a more significant limitation.

C. UNLOADING OF ASSIMILATES

In the earlier stages of crop growth much assimilate is unloaded from differentiating termini of the vascular system into meristematic tissue. In the case of the intercalary meristems of cereal leaves, they are clearly in a favored position to receive assimilates once their leaf blade begins photosynthesis, but the more peripheral root and shoot meristems are less favorably placed. The rate of diffusion of assimilates to them from the phloem may well limit their development, as Kirby and Rymer (1974) believe happens in the young barley inflorescence. At later stages in its development, the cereal inflorescence must compete with the stem and leaves for assimilates, and its size may be limited by the supply of assimilates it receives. During grain development, quite marked profiles in the supply of assimilates from leaves to the various parts of the inflorescence may be found. In wheat, for example, the more distal spikelets receive progres-

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sively less photosynthate from the leaves, which may reflect an inadequate supply to the upper parts of the ear. However, more labeled assimilates move there when there are more grains to attract them (Rawson and Evans, 1970). The pattern of demand is therefore a predominant influence on the distribution of assimilates, though modified to some extent by vascular patterns (e.g., Inosaka, 1957). Within the spikelet of wheat the continuity of the tracheary elements from the rachilla to the pericarp of the grain is interrupted by xylem discontinuities (Zee and O'Brien, 1970), and xylem and phloem transfer cells occur in the nodal plexus where the glumes and caryopsis are attached (Zee and O'Brien, 1971a). There is then no anatomical discontinuity in phloem cells from the rachilla to the vascular bundle up the crease of the grain and labeled assimilates from the leaves rapidly accumulate in the crease, according to Sakri and Shannon (1975). These workers believe sucrose hydrolysis and resynthesis is a prerequisite to the transfer of assimilates to the endosperm, which could imply loading against a concentration gradient, but Jenner (1973, 1974b) found no evidence of inversion. In fact, Jenner (1974a) has measured sucrose concentrations at various steps from the vascular bundle to the endosperm and shown them to fall progressively, so that movement into and across the grain could be by diffusion. The situation in the grains of the C4 cereals appears to be rather different. Phloem transfer cells are absent from the vascular traces leading to the caryopsis, at least in Japanese millet (Zee and O'Brien, 1971b), and the phloem terminates before the caryopsis. Assimilates presumably diffuse through the pigment strand cells in the gap of the seed coat to the nucellar projection, and from there to the nearby aleurone layer cells which are modified as transfer cells in the Seturia millets and also in maize (Kiesselbach and Walker, 1952). Inside these aleurone transfer cells in maize is a region of elongated, highly protoplasmic conducting cells with spirally thickened walls. According to Shannon (1968,1972), sucrose is hydrolyzed on leaving the conducting tissue, and diffuses through the endosperm as glucose and fructose at about 2.7 mm h-' . Since the rate of growth per kernel can be up to 5 times higher in maize than in the temperate cereals, the arrangements for unloading and transfer of assimilates within the caryopses of C4 cereals may be much more efficient than those in the C3 cereals.

D. DISTRIBUTION OF ASSIMILATES

The principles that govern the partitioning of assimilates among the organs of a plant are not fully understood. The pattern of distribution depends to a considerable extent on environmental conditions. Drought stress and low temperatures, for example, tend to favor root growth relative to shoot growth. Root growth is also relatively more important in the early stages of crop development.

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Rawson and Hofstra (1969) have described the changes in the pattern of 14C distribution from the various leaves of wheat as plants age. The second youngest fully emerged leaf is the major exporter of assimilates prior to anthesis, as also in rice (Shen, 1960), and the major supplier to the young leaves and shoot apex. Older leaves export predominantly downward, to roots and tillers. Even after anthesis, the lower leaves of the main stem may continue to export much of their assimilate to the tillers. When the grains begin to grow, however, they rapidly become the dominant sink for assimilates from the upper leaves. The awned ears of the primitive wheat progenitors are largely self-sufficient for assimilates, but selection for greater yield has resulted in the flag leaf and the leaves below it playing a greater role in the supply of assimilates for grain growth (Evans and Dunstone, 1970). Distribution patterns for 14C in wheat and barley, combined with the results of many defoliation and shading experiments, indicate that the flag leaf, stem and ear-the organs closest to the grains-are the main source of carbohydrates for grain growth. Perhaps because ear photosynthesis is less important in rice, leaves below the top two also supply the developing grain (e.g., Tanaka, 1958; Lizandr and Brovtsyna, 1964). The role of the lower leaves is even more important in sorghum. Of the assimilate exported by the five uppermost leaves, approximately the same proportion went to the panicle (Eastin, 1972a). With spaced plants, Fischer and Wilson (197 1 b) estimated that 93% of grain yield was due to photosynthesis by the head and upper 4 leaves, each contributing 17-21%, although the flag and penultimate leaves were much smaller than the leaves below them. Even more leaves are involved in the supply of assimilates to the centrally placed maize cob. A substantial fraction of the ''C-labeled assimilates from the leaves above the cob and down to 5 leaves below it ends up in the grains (Palmer, 1969; Eastin, 1969; Tripathy et al., 1972; Palmer et aL, 1973). Movement from the upper leaves is more rapid, and because of the higher light intensity at the top of the canopy, they are undoubtedly the major suppliers of the substrates for grain growth. However, defoliation experiments clearly indicate that leaves in the middle of the canopy, and even the lower leaves, are also important in supplying the grain and maintaining high yields (Allison and Watson, 1966; Pendleton and Hammond, 1969). In this respect, maize differs considerably from the temperate cereals. However, there is great flexibility in the pattern of assimilate distribution. In wheat, for example, most flag leaf assimilates go to the grain after anthesis, while lower leaves support the roots and tillers. If the upper leaves are removed or shaded, the lower leaves assume the role of supporting grain growth. If the ear and lower leaves are removed, on the other hand, the flag leaf then supports the roots and tillers (King et al., 1967; Marshall and Wardlaw, 1973). Thus, a large potential sink for assimilates, whatever its position, dominates the pattern of their distribution. In this respect, neither the central position of the maize cob

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nor the terminal position of other cereal inflorescences offers an advantage in terms of assimilate distribution.

E. THE ROLE OF RESERVES

Although carbohydrate reserves accumulated by cereals before anthesis were previously assumed to play a major role in grain growth, Archbold’s (1945) experiments with barley led to the realization that most grain growth is based on concurrent photosynthesis. Nevertheless, reserves do contribute to grain yield, to an extent that varies greatly both between the cereals and depending on environmental conditions. In the C4 cereals there is a rapid initial export from leaves of more than half the assimilated I4C, and nearly all the remainder is exported during the following night. In the C3 cereals, assimilate export from the leaf blades is more gradual. Starch does not usually accumulate in the leaves of wheat, oats, barley, and rye (Gates and Simpson, 1968), but other polysaccharides are present (Wardlaw and Porter, 1967). These can accumulate to quite high levels in the leaf blades-up to 45% of dry weight in wheat (King et aL, 1967)-and also in leaf sheaths and stems. Assimilate from the lower leaves and earlier photosynthesis tends to be stored in the lower internodes of wheat, whereas assimilate from the flag leaves after anthesis tends to be stored in the upper internodes and peduncle (Rawson and Hofstra, 1969; Wardlaw and Porter, 1967). As a result of this storage, stem weight may continue to increase after its elongation has ceased, and then fall during grain growth. The extent of the fall varies a great deal between crops, cultivars, and conditions. Not ail the mobilized material is stored in the grains. Some is lost by respiration, the proportion varying from 14 to 49% among 5 wheat cultivars (Rawson and Evans, 1971). In rice, respiratory loss accounted for 24% of the reserves (Cock and Yoshida, 1972). Thus, half to three-quarters of the mobilized reserves may end up in the grain. Direct evidence of such movement has been provided in rice (Murayama et al., 1961; Oshima, 1966; Cock and Yoshida, 1972) and wheat (Stoy, 1963; Wardlaw and Porter, 1967; Rawson and Hofstra, 1969). The contribution of these pre-anthesis reserves to grain yield has been estimated by a variety of techniques, and reviewed by Yoshida (1972). They appear to be most important in rice, contributing up to 40% of final grain weight (cf. Cock and Yoshida, 1972). In barley they contribute 20% (Archbold and Mukherjee, 1942) to 30% (Biscoe el aZ., 1975b), but only 5 1 0 % in wheat plants not under stress (Asana and Saini, 1958; Wardlaw and Porter, 1967; Rawson and Evans, 1971). With sorghum Goldsworthy (1970) estimated that most of the grain assimilates were produced after anthesis. According to Fischer and Wilson

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(1971a), pre-anthesis assimilates accounted for 12% of final grain weight in sorghum. However, the stem and leaf sheath reserves of carbohydrate in cereal crops are often not fully mobilized. Maize inbreds maintain a higher proportion of soluble carbohydrates in their stems than do more productive hybrids (Johnson and Tanner, 1972a), and up to 40% of stem weight may be sucrose not called on for storage in the grain (Campbell and Hume, 1970). Moreover, high stem sugar contents may be important in conferring greater resistance to stalk rot in maize and to frost injury in sorghum. In plants stressed by shading or defoliation, the reserves are mobilized to a greater extent in order to maintain grain growth, as in rice (Murayama et al., 1955), maize (Duncan et al., 1965) and wheat (Rawson and Evans, 1971). Under these circumstances, the reserves may contribute a much greater proportion of grain weight. On the other hand, greater applications of N fertilizer tend to increase growth at the expense of reserves, and may reduce the need to call on reserves (Yoshida, 1972). Thus, carbohydrate reserves in cereals can make a major contribution to grain yield in most crops under stress conditions, but where nutrition and water supply are favorable the reserves are often drawn on to only a limited extent, except in rice and perhaps hybrid maize. Although of value in adaptation and as an insurance against late stresses, they nevertheless represent unused yield potential. I X . Grain Growth

Under reasonably constant environmental conditions, there is a linear increase in the dry weight of kernels throughout most of the period of their growth, as may be seen from Fig. 3 for wheat. The period of linear increase is preceded by an initial lag after anthesis and may be terminated quite suddenly. Cessation of grain growth in maize is indicated by the formation of a black closing layer in the placental region (Kiesselbach and Walker, 1952), and Daynard and Duncan (1969) proposed the use of this criterion to determine physiological maturity and the duration of grain growth. In sorghum, also, the formation of the black layer coincides with cessation of the import of I4C-labeled assimilates by the kernels (Eastin, 1972a). Because of the linearity of increase throughout most of the period of kernel growth, not only the rate but also the effective duration of grain filling can be determined, in the latter case by extrapolation to the initial (at anthesis) and final kernel weights. We can therefore compare crops and cultivars in terms of the growth rate per kernel, the effective duration of growth, and the length of the lag period before linear growth begins.

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60 r-

18,

DAYS FROM ANTHESIS

FIG. 3. Increase in dry weight (left) and N content (right) in grains of Triple Dirk wheat with time from anthesis in three temperature regimes (Sofield et al., 1974).

A. THE LAG PERIOD

The initial lag period has been little studied, but may be important in relation to the number of kernels set in each inflorescence. Among wheat cultivars, the longer the initial lag period the more grains there were in each ear (Rawson and Evans, 1971; Sofield er al., 1974), especially at low temperatures. The length of the lag period in wheat is only a few days however, whereas in sorghum it appears to be about 14 days (Eastin, 1972b), and in maize 15-18 days, 47-85% as long as the effective duration of grain filing (Johnson and Tanner, 1972a,b). These much longer lag periods are associated with the presence of 10-100 times as many grains per inflorescence in maize and sorghum compared with wheat, and may be necessary to allow the later florets in the inflorescence to set grains. Assimilate requirements by the inflorescences during the lag period are relatively modest, and stem and leaf reserves tend to accumulate at that time. Because of the long lag period in maize and sorghum, these “post-anthesis reserves” are likely to represent a major component of grain yield, and deserve further study.

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B. DURATION OF GRAIN GROWTH

Because of the relative ease with which cessation of grain growth can be determined in maize and sorghum by observation of the black layer, more is known of the relations between yield and duration of grain growth in those crops than in the temperate cereals. Daynard et al. (1971) and Funnah (1971) found yield among maize hybrids to be highly correlated with the effective duration of filling, more so than with its rate. In a comparison of inbreds and hybrids Johnson and Tanner (1972a,b) found the effective duration of grain filling to be much longer in the hybrids, but their rates of grain growth per unit ground area were also higher. Data presented by Eastin (1972a) shows that the period from anthesis to maturity, which varies among lines from 31 to 56 days, is consistently longer in the higher yielding hybrids, and that there is a positive correlation between the length of this period and grain yield. However, no data are presented on how this period was partitioned between the initial lag and the linear grain growth phases. Pronounced differences among wheat cultivars have not yet been found in the period from anthesis to maturity (Marcellos and Single, 1972) or in the effective grain-filling period (Sofield e t al., 1974), but the experiments of Asana and Joseph (1964) suggest that they may occur, as they do in rice ( S . Yoshida, unpublished data). Comparisons are made difficult by the very great effect of temperature on the duration of grain filling in wheat, evident in Fig. 3. Field and phytotron experiments agree in showing a major increase in the duration of grain filling as temperature falls, whereas light intensity during grain filling has no effect on its duration. High temperatures, by day or night, also shorten the duration of grain filling in sorghum (J. D. Eastin, unpublished data) and in japonica rice to such a degree that grain yields are reduced and more carbohydrate reserves are left in the plants (Nagato and Ebata, 1959;Nagato et al., 1961; Sato and Takahashi, 1971). However, in tropical rice cultivars such as IR 20 the increased rate of grain growth may compensate for the reduced duration at high temperatures ( S . Yoshida, unpublished data). Tsunoda (1965) argues that more prolonged grain development is needed in rice cultivars grown under heavy N fertilization. The data presented by Shaw and Thom (1951) and Peaslee e l QZ. (1971) suggest that temperature has little effect on grain-filling duration in maize. An important question that cannot be answered with confidence for any cereal is “What causes the grains suddenly to stop growing?” Many lines of evidence from wheat experiments suggest that it is not from lack of assimilates. The leaves and stems may still be green and there may be ample reserves in the stems, indeed stem weights may be increasing. Jenner and Rathjen (1975) have shown that the sucrose concentration in both the free space and endosperm cells is

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higher in grains approaching full weight than at earlier stages, so the decline in starch accumulation cannot be due to lack of assimilate.

C. THE RATE OF GRAIN GROWTH

The rate of growth per kernel increases with temperature in rice (e.g., Nagato et al,, 1961; Sat0 and Takahashi, 1971), wheat (Thorne, 1970; Sofield ef al., 1974; Spiertz, 1974), and maize (Peaslee er al., 1971). With wheat andjaponica rice the increase in rate is not sufficient to compensate for the reduction in duration of filing, with the result that grain yield tends to be reduced at higher temperatures. The effect of light intensity on the rate of grain growth is more complex. Only at very low light intensities, combined with high temperatures, did an increase in intensity result in faster grain growth in some wheat cultivars (Sofield e t al., 1974). C02 enrichment had little effect on the rate of growth per kernel in 4 barley cultivars (Natr and Apel, 1974). It seems, therefore, that the rate of kernel growth in the temperate cereals is not markedly limited by the supply of current assimilates except at very low light intensities. In the experiments of Natr and Apel, the barley grains continued to grow rapidly even in the absence of C02 for 5 days. Similarly in maize, Duncan et al. (1965) found the rate of growth per kernel to be reduced only from 9.8 to 7.4 mg kernel-' d-' by complete defoliation of the plants and wrapping of the husks. Stem reserves were mobilized and used with high efficiency to sustain kernel growth in the defoliated plants. Growth rates per kernel in maize range from 6-10 mg d-' among cultivars, and are correlated to some degree with final kernel weight (Carter and Poneleit, 1973). Such rates are far higher than those of the temperate cereals, commonly less than 2 mg kernel-' d-'. Growth rates per kernel in sorghum are comparable to those of the temperate cereals, but there are of course far more kernels per inflorescence. Data to compare rates of grain growth on a per unit ground area basis among the various cereals are insufficient. Goldsworthy et al. (1974) record grain growth rates of up to 35 g m-* d-' in lowland tropical maize, but only up to 21 g m-2 d-' in highland crops (Goldsworthy and Colegrove, 1974), although the maximum crop growth rates were 35 g m-2 d-' at both stations. The data of Benoit ef al. (1965) indicate a grain growth rate of 30 g m-2 d-', but most of those recorded for maize crops are nearer 20 g m-2 d-' (e.g., Daynard et al., 1971; Johnson and Tanner, 197213). Eastin's (1972a) data for sorghum also yield rates of 15-19.1 g m-2 d-', which are probably comparable to those for many temperate cereal crops.

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D. PROTEIN STORAGE Only a few aspects of this large and important subject are considered here. A negative relation between % protein in cereal grains and their yield has often been found, but is by no means universal even with a single cultivar (e.g., Fernandez and Laird, 1959). Major yield advance in some cereals has been associated with a progressive fall in % protein as in Triticale (Zillinsky, 1974) and sorghum (Collins and Pickett, 1972). Selection for high % protein may reduce yield, as in maize (Woodworth et aL, 1952; Dudley, 1973). Low light intensity 'during grain development may affect storage of starch more than that of protein, leading to reduced grain yield but a higher percentage protein, as in rice (Cruz et al., 1970; Sato, 1971). Similarly, protein content is enhanced relative to starch content at high temperatures in rice (Sato and Takahashi, 1971) and wheat (Campbell and Read, 1968). Drought stress also enhances the relative protein content (e.g., Petinov and Pavlov, 1955). Under such conditions, therefore, there can be a negative relation between yield and percentage protein. This is not an obligatory relation, however, and it is much influenced by the adequacy of nitrogen nutrition during grain development. Under conditions where N uptake continues throughout grain filling, both protein and starch content of the grains may increase linearly until near maturity, as in wheat (Jennings and Morton, 1963; Bremner, 1972; and Fig. 3) and rice (Paul er al., 1971). Under these conditions the % protein in the grain need not fall, and may even rise, as storage proceeds (Johnson et al., 1967). Moreover, fertilizer N may be used with very high efficiency, as in the experiments of Hucklesby et al. (197 1) with wheat, and much of the grain protein may derive from N taken up during grain fdling (Pavlov, 1969). Where soil N is severely depleted by heading time, on the other hand, concurrent uptake may be insufficient to sustain the rate of protein storage in the grain, and remobilization of proteins in the plants may occur, often to a greater extent than that of carbohydrate reserves (e.g., Peterson er al., 1975). Cultivars appear to differ considerably in this respect (e.g., Cataldo er al., 1975). In those where remobilization is extensive, there may be rapid leaf senescence and starch storage may be more adversely affected than protein storage, resulting in low grain yields of high protein content (Termanetal., 1969; McNeal et al., 1972). There may be little relation between the protein percentage in the vegetative parts and that in the grain during the later stages of development in such plants, as in wheat (Pavlov and Kolesnik, 1974) and oats (Peterson er al., 1975). These major differences between cultivars in the extent of protein remobilization to the grain make comparisons between the cereal crops difficult. The considerable range in their protein content may, to a large degree, reflect the

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traditional uses and selection pressures under which the various cereals have developed. Cereals like maize and sorghum which were commonly supplemented by legumes may have been under less pressure to maintain a high protein content than those like wheat. X. Limiting Stages in the Life Cycle

An important characteristic of the cereals is the relatively clear separation between the phases of their life cycle in the organs undergoing growth. Root and leaf growth dominate the vegetative stage together with tillering, the extent of which depends on assimilate supply within the plant. In the second (reproductive) stage, ushered in by inflorescence initiation, the rapidly elongating stems and the differentiating inflorescence are the main competitors for assimilates, although root growth continues and expansion of the upper leaves is completed. Stem growth ceases soon after anthesis, and the developing grains then become the dominant sink for assimilates in the final stage of the life cycle, although root growth and tillering may be renewed if conditions are favourable. Discussions of whether source or sink limits yield refer mostly to this final stage of the life cycle, since most grain growth is supported by concurrent photosynthesis rather than by stored reserves of carbohydrate. However, the sink or storage capacity for assimilates at this late stage is to a large degree determined by the extent of photosynthesis earlier in the life cycle, especially during the reproductive stage of the crop. Thus, whether source or sink limits grain development depends on the balance between the various stages of the life cycle, as determined by cultivar and the sequence of growing conditions. In productive cultivars growing in the conditions and seasonal sequence to which they are adapted, source and sink should be in balance. In other conditions one or other of them may be the more limiting. Quite often both may seem to be limiting (Gifford et al., 1973; Gifford, 1974b). Surplus storage capacity is suggested by the formation of far more tillers than eventually bear ears, e.g., in wheat (Bingham, 1969), more spikelets than bear grains in maize and barley, and more florets than filled grains in wheat and rice. Moreover, grain size in most cereals other than rice can usually be increased when grain number is reduced (e.g., Bingham, 1967; Rawson and Evans, 1970), which suggests the existence of spare storage capacity even at a late stage in most cereal crops. At the same time, however, many cereal crops also have substantial unmobilized reserves of carbohydrate even at the end of grain filling (e.g., Johnson and Tanner, 1972a; Rawson and Evans, 1971), such as the high stem sugar contents of maize and sorghum noted earlier. Similarly, leaf area reduction or shading treatments late in the life cycle may reduce crop gruwth without reducing grain yield. The existence of spare photosynthetic capacity is also

COMPARATIVE PHYSIOLOGY OF GRAIN YIELD IN CEREALS

34 1

suggested by the finding that the low leaf rates late in grain filling may be raised when demand is raised (e.g., King et ul., 1967). How can both source and sink appear to have spare capacity? Gifford (1974b) presents a model that suggests that it is impossible to operate at both full source and full sink capacity simultaneously because of feedback inhibition of photosynthesis at sucrose levels required to maximize the rate of storage. Compartmentation may overcome this, however. Another possibility is that other processes besides the supply and storage of assimilates may be limiting, such as the capacity of the translocation processes, although evidence reviewed above indicates that this is unlikely. Rawson and Bremner (1976) have suggested that sink limitation may occur early in grain filling and source limitation toward the end, or sink limitation by day and source limitation by night, but this too is unlikely in many cases. For example, the presence soon after anthesis of additional grains, which can develop in wheat if growth correlations permit (Rawson and Evans, 1970; Evans et ul., 1972), suggests that storage capacity per se is not limiting at that time, just as the continuing presence of stem reserves late in grain filling suggests that source is not limiting at that stage. An evolutionary approach may be more helpful. Survival of plants in the wild, or in primitive agriculture, is likely to be aided by the accumulation of substantial reserves of both assimilates and potential seed sites. Recovery from adverse conditions, whether loss of photosynthetic capacity by drought or defoliation, or loss of seed sites by frost or insect attack, is then likely. The essence of cereal domestication and improvement has been to provide the conditions-through cultivation, fertilizer application, irrigation, herbicides, pesticides, etc.-which permit a reduction in the accumulation of reserves and a progressive increase in the proportion of assimilates invested in the grains (Evans, 1976a). Nevertheless, variation from year to year and from season to season in most agricultural areas is still sufficient for some selective advantage to accrue from the maintenance of surplus source and sink capacity. As control of the agricultural environment improves, so can the mobilization of these reserve capacities into additional grain production be increased, but the extent of seasonal variation still precludes their full exploitation, as may be seen in numerous analyses of crop yield in successive years (e.g., Campbell et ul., 1969; Murata and Matsushima, 1975; Fischer and Aguilar, 1976). A. DURATION OF LIFE CYCLE STAGES

The relative duration of the various stages, and their optimum balance, obviously depend to a very great degree on the seasonal conditions under which the crop is grown. Rice in the tropics, under intensive multiple cropping, may require only 25 days in the field for each of its three stages, although the first stage may be preceded by 20 days in the seed bed (Yoshida and Parao, 1976).

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Crops in cooler conditions may require longer at each stage, particularly for the vegetative stage in autumn-sown temperate cereals. Among 12 cultivars of sorghum in which days from planting to maturity varied only between 105 and 114 days, the percentage of the life cycle for each stage varied from 26-36%, 30-34%, and 34-41% for the vegetative, reproductive, and grain-filling stages, respectively (Eastin, 1972a). Within this group of cultivars, grown in Nebraska, higher yields were associated with shorter times in the vegetative stage and longer times in the grain-filling stage. Eastin emphasizes how important a few extra days of grain filling are to yield of sorghum in Nebraska, where grain growth is cut short by frost. In Texas, on the other hand, sorghum yields tend to increase as time to anthesis increases (Dalton, 1967). Clearly, the environment determines which stage of the life cycle it is more important to extend. In spring-sown wheat in Minnesota, with a total life cycle of 93 days, the grain-filling stage was the shortest, possibly reflecting the progressive rise in temperature (Krenzer and Moss, 1975). When the cultivars were grown under controlled temperature, the length of the vegetative stage was greatly reduced relative to the later stages, while the length of the grain-filling stage increased. Substantial year-to-year variation occurs in the relative length of the stages for crops even at one site (cf. Fischer and Aguilar, 1976). An adequately long vegetative stage is required to establish the root system and leaf canopy as a basis for later crop growth. It is also needed to establish the tillers and potential spikelet sites which contribute to eventual grain storage capacity, particularly in the temperate cereals in which tillering is more important and primordia accumulate at the shoot apex before inflorescence initiation occurs. Greater fertilizer use, early irrigation and denser planting all permit a shortening of the vegetative phase. Too little is known of the relations between yield and the duration of the reproductive stage in cereal crops for useful comparisons to be made, most attention having been given to the grain-filling stage. The integral of LAI with respect to time from anthesis to maturity, the leaf area duration (D), has been extensively analyzed in relation to yield in the temperate cereals. Earlier experiments indicated a reasonably close relation between D and grain yield in some temperate cereals (e.g., Watson et a l , 1963; Welbank et al., 1968). The aggregated data for wheat (Evans er al., 1975) indicate that the relationship tends to be closer at relatively low values of D and yield. At higher values, increases in D from additional N fertilizer are not associated with proportional increases in yield (Thorne and Blacklock, 1971). Indeed, Thorne (1973) has shown that there is little advantage to yield in raising the LAI at anthesis in wheat and barley crops above 6. The concept of leaf area duration involves several problems when comparisons are made between cereal crops. Because the LA1 falls, often sharply, with time from anthesis, D values tend to be dominated by the high LA1 values early in the

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grain-filling stage. However, LA1 values above 4 have little effect on crop photosynthesis (cf. Fig. 2) in spite of their large effect on estimates of D. On the other hand, small differences in LA1 late in the grain-filling stage may have a substantial effect on yield (e.g., Watson et al., 1963). Yield in cereals often bears a close relation to LA1 at anthesis, as in wheat (Simpson, 1968), maize (Eik and Hanway, 1966), and rice (Yoshida et aL, 1972). In these conditions, yield is largely determined by the yield capacity which is in turn determined by the extent of canopy growth or nitrogen uptake, often related to the maximum LAI attained. In these cases, the element of duration is of less importance. Under other conditions, the time element of D may be predominant in yield determination. In a comparison of wheat and maize, for example, Allison (1964) found that although D for both crops was similar (-260 days), the much greater yield of maize was associated with more prolonged grain growth and a correspondingly longer retention of green leaves (Fig. 4). It is an open question, of course, whether the maize leaves stayed green longer because of the demands from more prolonged grain growth, or vice versa. Prolongation of grain growth, at lower temperatures for example, can increase yields substantially in spite of reduced growth rates, as shown in Fig. 3. The increased duration at low temperatures reduces the photosynthetic limitation on

1

0

4

8

12

WEEKS FROM EAR EMERGENCE OR HALF SILK

FIG. 4. Relation between LA1 and grain growth with time from ear emergence in wheat or half-silk in maize (0).Solid lines represent LAI, broken lines grain growth. (Adapted from Allison, 1964.)

(A)

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L. T. EVANS AND I. F. WARDLAW

yield development, as evident in the results of Krenzer and Moss (1975) in which enrichment with C02 during either the reproductive or the grain-filling stage had no effect on yield for wheat crops grown at 13"/17"C although it enhanced yield substantially at 25"/20"C or in the field. Since both the duration of the grain-filling stage and D vary over a wide range for each crop, it is difficult to make useful comparisons between the major cereals. Very low D values have been reported for sorghum crops in the tropics (Krishnamurthy et al., 1973), but values for wheat and barley crops can be as low under hot dry conditions. In view of the comments made above, comparisons of D values for the various cereals and further analysis of the concept of D is unlikely to be rewarding.

B. PHOTOSYNTHETIC LIMITATIONS TO YIELD AT THE VARIOUS STAGES

The relative limitation to yield by photosynthesis at various stages of the life cycle, even in locally adapted cultivars, depends a great deal on the sequence of conditions for the particular crop examined. It varies not only from site to site, but also from year to year. With Yecora wheat grown under irrigation at Obregon, for example, shading reduced yield by up to 60% in 1973 when applied during the middle of the reproductive stage, whereas in 1974 the greatest yield reduction by the same degree of shading was only 16% and this occurred during the grain-filling stage (Fischer, 1975). Comparable results for the two preceding years are presented in Fig. 5 along with those of Yoshida and Parao (1976) for rice in the Philippines. These agree in showing that shading and reduced photosynthesis has least effect on yield when given during the vegetative stage, and most effect during the reproductive stage, with the grain-filling stage also being sensitive. For both crops early shading greatly reduced growth, and especially tillering, but not the number of tillers that produced ears. In Fischer's (1975) experiments, shading always reduced crop growth, in direct proportion to the reduction in radiation, even when it had little effect on grain yield. With spring wheat in a very different environment, Willey and Holliday (1971b) found results similar to those of Fischer (1975), yield being most affected by shading during the reproductive stage and least during the vegetative stage. With winter wheat, on the other hand, yield was equally sensitive to shading before and after heading (Pendleton and Weibel, 1965). Maize seems to be most sensitive to shading at the silking and grain set stages (Moss and Stinson, 1961). Shading treatments on crops of two barley cultivars had a pronounced effect on yield when applied before anthesis, but no effect after anthesis (Willey and Holliday, 1971a), which suggests that storage capacity was more limiting to yield

COMPARATIVE PHYSIOLOGY OF GRAIN YIELD IN CEREALS

345

9 w

> 4

RICE

3

n

w>

za

a

u

u1

E

4 w n

I

I

100

200

’I

I 300

I

I

I

400

500

600

cal cm-*d-’

70

60

/,

0

20

WHEAT I

I

I

I

40

60

80

100

% SUNLIGHT

FIG. 5. Effect on grain yield of shading at various stages in the life cycle of crops of rice in the Philippines (Yoshida and Parao, 1976) and of wheat in Mexico (Fischer, 1975).

than was the supply of assimilates during grain filling. With a barley crop grown late in the season, however, Gifford et al. (1973) found the adverse effect of shading on grain yield to be about equal when given before or after anthesis. However, C02 enrichment increased grain yield much more when given before rather than after anthesis, because the effects of post-anthesis enrichment on grain number per ear and kernel weight were much smaller than those of pre-anthesis enrichment on the number of ears. Fischer and Aguilar (1976) enriched Yecora wheat crops, grown under irrigation and high fertilizer levels, with COz applied during each of four 1-month periods, over 3 years. Although COz enrichment increased crop growth, it increased grain yield consistently only when applied during the reproductive stage. Applied during the grain-filling stage, it increased grain yield significantly only in one year. Krenzer and Moss (1975) applied COzenrichment to spring wheat crops in Minnesota, and found it to increase grain yield about equally in the pre- and post-anthesis periods, through increase in the number of ears and grains per ear in the earlier treatments, and in kernel weight from enrichment after anthesis.

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L. T. EVANS AND I. F. WARDLAW

Kernel weight in rice is not so readily increased by favorable conditions after anthesis as it is in wheat. Consequently, the main effect of C02 enrichment after anthesis for rice crops is an increase in the percentage of filled grains, with consequent increase in yield. C02 enrichment before anthesis causes a greater increase in yield of rice under tropical conditions, through effects on both grain number and kernel weight (Yoshida et al., 1972; Cock and Yoshida, 1973; Yoshida, 197313). Shading and COz-enrichment treatments can be applied for defined periods, and for that reason are more satisfactory than crop thinning treatments, which resemble C 0 2 enrichment in enhancing the photosynthetic rate of the plants, but right through to maturity rather than for a limited period. Early thinning of wheat crops led to an increase in ear number per plant; later pre-anthesis thinning increased the number of grains per spikelet, while post-anthesis thinning increased kernel weight (Fischer and Laing, 1976). The increase in kernel weight from crop thinning at anthesis ranged from 6% to 41%, being greater at higher temperatures. In sorghum, likewise, early thinning increased seed number while late thinning increased kernel size (Fischer and Wilson, 1975b). The shading, C02-enrichment and crop thinning treatments have indicated the very considerable variability between crops, cultivars, environments, and years in the relative limitation to yield by the pre- and post-anthesis stages. This is one reason why attempts to correlate yield and yield components with natural radiation levels at various stages of crop life cycles are unlikely to result in clear relations. There are, of course, many other problems in such work, one being correlations between pre- and post-anthesis radiation levels, and between radiation and temperature. The higher temperatures often associated with higher radiation levels may so shorten the duration of the reproductive or grain-filing stages as to mask any yield advantage from higher radiation and additional photosynthesis. Consequently, although grain yield may increase with increase in receipt of radiation during grain filling up to a certain level for temperate cereals, still higher radiation levels may not be associated with greater yields (e.g., Welbank et ul., 1968; Evans, 1973). When temperature is controlled, however, grain yield is higher the greater is the radiation receipt during grain filling (Evans, 1976b). In rice crops at higher latitudes, grain yield may be positively related to both temperature and radiation levels during grain filling, but negatively related to them at lower latitudes (e.g., Lee, 1972; Murata, 1975). Yoshida and Parao (1976) found spikelet number in rice crops to be related positively to solar radiation but negatively to temperature during the reproductive stage. Grain yield of maize in the Japanese IBP experiments was positively related to both radiation and temperature (Kudo, 1975). For each of the cereals, grain yield may be positively associated with both temperature and incident radiation in the lower part of their range, but nega-

COMPARATIVE PHYSIOLOGY OF GRAIN YIELD IN CEREALS

347

tively associated with temperature when it is high. In the higher part of the temperature range, therefore, the effects of increasing radiation and temperature may cancel out, or the adverse effects of high temperature may become predominant. In this respect, the C4 cereals are likely to be more tolerant of high temperatures, and therefore more able to take advantage of very high radiation levels during grain filling.

C. YIELD COMPONENTS

One reason for the success of cereals as crops is their capacity for yield component compensation, i.e., for the later-determined components of grain yield to compensate for earlier losses or restriction of development or to take advantage of favorable conditions late in the crop life cycle. The major cereals differ, of course, in the extent to which such yield component compensation can occur in the later stages of the life cycle. For example, kernel size is more restricted by glume size in rice than in other cereals, with the result that kernel weight in rice is far less variable and unable to accommodate additional carbohydrate when conditions during grain filling favor more rapid or prolonged grain growth (Matsushima, 1970). In wheat and barley, on the other hand, kernel weight displays a substantial range. If grain number per ear is reduced, the remaining grains may grow to a greater size in wheat (e.g., Bingham, 1967; Rawson and Evans, 1970). This did not occur in barley (Buttrose and May, 1959) or maize (Duncan and Hatfield, 1964), which suggests that assimilate supply was not limiting grain growth in intact ears. Although variation in kernel weight makes a degree of yield compensation possible late in the life cycle, except in rice, the scope for compensation is much greater earlier in the life cycle. Grain number per unit ground area, the major determinant of yield, can be influenced by the number of inflorescences, the number of spikelets per inflorescnece, the number of florets per spikelet, and the proportion of florets actually setting grains. These yield components are determined in succession, as Matsushima (1970) has shown for rice. Limitations by adverse conditions on the earlier-determined yield components can be compensated for in the later ones. Poor or variable establishment, or a low density of sowing, can be compensated for in many cereals by abundant tillering and the development of more ears per plant. For example, whereas tillers may account for only 30%of the total grain yield in a dense stand of wheat (300 plants m-’), about half of the plants producing only the main stem ear, at half that plant density 5040% of the yield may come from tillers and a third of the plants may have as many as four ears (Bremner, 1969). Compensation for the halved plant density was such that grain yield was reduced by only 9%.The temperate cereals produce tillers to

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an extent determined by incident radiation prior to inflorescence initiation (e.g., Evans et al., 1975), often to an extent far in excess of the number eventually bearing ears. Consequently, up to two thirds of the tillers may be “wasted,” but this wastage ensures considerable scope for compensation early in the life cycle. There is less scope in sorghum, in this respect, and still less in modem sparsely tillering forms of maize. In the latter, however, the main stem may bear additional ears, particularly in cultivars that tend to have fewer kernels per ear (Duncan, 1975). Increases in grain number per ear and in kernel weight may also help compensate for low stand densities. A striking example is provided by the work of Kirby (1969) with barley crops in which final grain yield was virtually unaffected by density over the range from 50 to 800 plants m-’. The 16-fold increase in planting density resulted in only a 90% increase in ear number m-’ , combined with a 40% reduction in grain number per ear and an 18% reduction in kernel weight. As a result of this remarkable compensatory power, grain yield in cereals is relatively insensitive to planting density, and displays a wide variety of negative correlations among the yield components (e.g., Leng, 1963). For the same reason there is considerable variation from site to site, cultivar to cultivar, and year to year in the component most closely related to grain yield. In rice, for example, grain yield may be closely related to the number of spikelets m-’ and bear little relation to the percentage of filled grains, or vice versa, depending on conditions (Murata and Matsushima, 1975). Soil fertility and water supply, and the usual seasonal sequence of conditions, may favor a particular balance among the yield components, as Grafius and Okoli (1974) argue for barley. But there are considerable differences among plant breeders in the emphasis they give to the various components, and many paths to success as a crop. Given the magnitude of year-to-year variations in weather, too precise a specification of yield components could be harmful, and selection for yield by emphasizing particular componenets is not always effective (e.g., Rasmussen and Cannell, 1970). Perhaps the most important feature to preserve is some capacity to “overproduce” the yield components determined at successive stages in their life cycle, even into the grain-filling stage. This must of course be wasteful of resources, and there may be an optimal degree of overproduction at each stage which will depend on the climatic variability at each site and stage. In spite of the great extent of compensatory variation within each of the major cereals, they nevertheless differ substantially one from the other in their yield component balance. To some extent this is determined by individual plant size, as in the range of optimum planting densities m-’ from 4-8 for maize and 30-60 for sorghum up to about 300 for wheat and rice under favorable conditions. They also reflect kernel size, which displays more than a 10-fold. range from

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20-25 mg for rice, 25-35 mg for sorghum, rather more for the temperate cereals, and up to 250-350 mg for maize. Grain number m-’ tends to vary inversely with kernel size from up to 5000 m-’ in maize to up to 25,000 m-’ in wheat and 45,000 m-’ in rice. Grain number per inflorescence shows the greatest range of all, from 15-50 in the temperate cereals, rather more in rice, 500-1 500 in maize, and from 1500 to more than 12,000 per panicle in sorghum (Pepper and Prine, 1972). Clearly, the balance among the yield components varies greatly not only between the major cereals, but also between cultivars of each, and for each cultivar according to the environment. Their potential overproduction at each stage in the life cycle is important in conferring adaptability to seasonal fluctuations, and tends to result in negative correlations among some of the yield components. Such negative correlations may be interpreted as implying that the supply of assimilate limits grain yield, and it may often do so. Paradoxically, evidence can also be adduced that spare assimilatory capacity and unmobilized reserves may be present even when negative correlations among yield components are found. The more the agricultural environment can be specified and controlled, the more these reserves of potential yield can be mobilized into actual grain yield. On this argument, it is the correlative and feedback mechanisms operating within the cereals that require modification to permit advance in yield quite as much as do the photosynthetic and storage systems.

XI. Conclusion

We have tried in this review to emphasize the comparative aspects of yield development in the major cereals. However, relatively few studies actually make physiological comparisons among them. One reason for this lack of comparative data on the major cereals may be that they have evolved to take advantage of such different environments that valid comparisons are difficult to make. Indeed, it is their capacity to exploit a wide range of complementary environments so effectively that makes the cereals so important and fascinating as crop plants. Our purpose in emphasizing their comparative behavior has been to obtain a better understanding of how yield develops and is limited in each of them. Many aspects have been left aside, but even among those we have examined, a quite remarkable range of behavior is apparent. This physiological diversity is to be cherished, as the source of adaptation to a wide range of environments. It may be confusing, and may seem unnecessary in the face of the progressive control and homogenization of our agricultural environments, But it should be preserved and explored in the search for increased level, stability and quality of yield from mankind’s most important source of food, the cereals.

3 50

L. T. EVANS AND I. F. WARDLAW ACKNOWLEDGMENTS

We are most grateful to Drs P. M. Bremner, R. M. Gifford, H. M. Rawson and S. Yoshida for their helpful comments on this review.

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THE BIOLOGICAL YIELD AND HARVEST INDEX OF CEREALS AS AGRONOMIC AND PLANT BREEDING CRITERIA C. M. Donald and J. Hamblin’ Waite Agricultural Research Institute, University of Adelaide, South Australia, and Department of Applied Biology, University of Cambridge, England

I. Introduction .................................................. 11. The Relationship of Biological Yield, Grain Yield, and Harvest Index to Each Other and to Other Plant Characteristics ............................. 111. The Influence of Environmental Factors ............................. A. PopulationDensity ........................................... B. Water Availability ............................................ C. Nitrogen Nutrition ........................................... D. The Interaction of Environmental Factors, Yield, and Harvest Index ..... IV. Biological Yield and Harvest Index as Criteria in Cereal Breeding .......... V. ConcludingComments ........................................... References ....................................................

361 364 375 375 318 382 390 390 402

404

I. Introduction

The biological yield of a cereal crop is the total yield of plant material, and the harvest index is the ratio of the yield of grain to the biological yield. Expression of the “efficiency” of grain production through an index was proposed 60 years ago by E. S. Beaven, a barley breeder at Warminster, Wiltshire, England. He defined the “migration coefficient” of cereals as “the proportion of dry matter of the entire ripe plant, excluding the root, which is accumulated in the grain” (Beaven, 1914, 1920). The term “migration coefficient” was chosen because, lacking our present understanding of postflowering photosynthesis, Beaven believed “that the yield of dry grain, as distinct from the total weight of the entire plant, depends on the effective transmission of the material accumulated in the stems of the plant .” Beaven noted that the migration coefficient is much more constant for the individual plants of a variety than is the number of tillers or the size of heads and that in different seasons the separate varieties tend to maintain much the same ranking for the ratio, although the mean of all varieties will vary from one season to the next. He further wrote that “we shall do better in the long run if we attach special importance to this character of good migration for the purpose in the first place, of selecting Presenr address: Department of Agriculture, Perth, Western Australia. 361

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C. M. DONALD AND J. HAMBLIN

individual plants and in the second place for the purpose of assessirig the comparative values of the small aggregates of each race (genotype) obtained within the first few generations.” He did not, however, present full data in support of these views. In the following years a few agronomists emphasized the usefulness of the migration coefficient; Engledow and Wadham (1923, 1924) wrote that “it seems possible that the coefficient might . . . prove to be of service as an index of the yielding power of single plants.” But it was not widely adopted. At the Rothamsted Experimental Station, the published results of many agronomic experiments included “the ratio of grain to total produce,” but apparently independently of Beaven’s writings (e.g., Russell and Watson, 1940). Among cereal breeders, Beaven’s advocacy of the migration coefficient was quite disregarded. The measurement of grain yield alone was simple and rapid and was believed to provide the significant information needed in breeding cereals for yield. This position continues substantially unchanged. After an interval of several decades, interest in the ratio among crop ecologists was stimulated when Niciporovic (1956), in a notable lecture to the Timijazev Institute of Plant Physiology, emphasized that successful crop production depends on the effective exploitation of photosynthesis to achieve maximum biological yield. But in most crops the economic product is not the whole crop but some particular part of it such as the grain or tubers (the “economic yield”). If economic yield is to be maximal, continued Niciporovic, there must be a correct distribution at the right time of the products of photosynthesis. Black and Watson (1960) comment that Niciporovic’s “discussion seems to assume that the final distribution of dry matter is the result of a phase of accumulation followed ‘at the right time’ by a phase of partition, but this is evidently not always true .” Niciporovic’s thoughts regarding economic yield were expressed in the following equation: Coefficient of effectiveness Biological yield X of formation of the economic = Economic yield part of the total yield ybiol

x Kecon = Yecon

It will be seen that Niciporovic’s “coefficient of effectiveness” is identical with Beaven’s “migration coefficient” except that he emphasized that it could be applied to any crop, whether the economic yield were grain, tubers, fiber, oil, or any other product. Unlike Beaven, Niciporovic placed equal emphasis on the attainment of high biological yield. In a discussion of these relationships as pertaining to plant breeding, Donald (1962) questioned whether plant breeders had a sufficiently positive approach toward increased grain production. Though they bred for the realization of yield

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BIOLOGICAL YIELD AND HARVEST INDEX

potential through such attributes as disease resistance or drought escape through earliness, they did not specifically seek to breed plants capable of greater photosynthesis or able to render a greater part of their biological yield as grain. The only advance in basic yield potential was by the selection of high yielding segregates without prior nomination of their characters. Measurement of biological yield and its relation to grain yield in breeding programmes was strongly advocated, and the term “harvest index” was proposed for the ratio of grain yield to biological yield, a term identical in meaning with the earlier coefficients, but without physiological or teleological overtones. Thus for each component of the equation for cereals there are a number of terms, including: Biological yield or Total yield or Yield of dry matter or Yield of grain + straw or Yield of total produce

Migration coefficient or Ratio of grain to total produce or X Coefficient of effectiveness or Harvest index

=

Grain yield

The terms adopted in this article are “biological yield,’’ “harvest index,” and “grain yield.” True biological yield includes the weight of roots, but since these are normally nonrecoverable, the term is usually applied, like its counterparts listed above, to the total weight of the tops. Harvest index, by definition, is a factor less than unity, say 0 to 0.55, but some workers prefer to use “harvest index (%),” in which they express the index as 0 to 55%. A term closely related to harvest index, and used by many cereal agronomists, is the grainlstraw ratio, or, for maize, the grainlstover ratio. Assuming that grain t straw equals biological yield, the grainlstraw ratio can easily be converted to harvest index or vice versa. We suggest, despite this easy conversion, that there is clear advantage in the use of the ratio:harvest index. First and foremost, harvest index links grain yield to the valuable measurement, biological yield; the determination of biological yield is a necessary step in the derivation of the harvest index. A second advantage is that its values tend to be linear rather than exponential in their relationship to grain yield. Thus if biological yield were constant, a situation approached in varying degree in many comparisons of genotypes, harvest indices of 0.2, 0.4, and 0.6 would indicate grain yields in those proportions, but the corresponding grainlstraw ratios would be 0.25,0.67, and 1.50. A further disability of ratios between grain and straw is, that though they are usually calculated as “grain-to-straw,” they are not infrequently expressed as “straw-to-grain,” a confusing inversion. The determination of harvest index, the term adopted in this paper, is usually based on a harvest at maturity. Mature plants are cut at ground level, weighed to give total yield, and threshed to give the yield of grain. An assessment based on air-dry material is usually adequate but if the harvested material is unusually wet or variable in water content, oven drying may be necessary.

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Some imprecision may also result from the determination of harvest index at maturity. Because of leaf loss and respiration, the apparent biological yield of the crop may be less at maturity than at a somewhat earlier stage. For example, in a study of wheat at widely different densities, Puckridge and Donald (1967) recorded the following values: Density @lants/m’ at 26 wk): Biol. yield @/ma)at 20 wk (early dough stage): Biol. yield @ma) at 26 wk (maturity):

1.4 105 126

7 466 483

35 891 812

154 932 891

447 852 738

At the density close to normal crop density (154/m2), the decrease in crop weight was 4.6%. There is not much information on this aspect in relation to different genotypes at a common density, but if they lose different amounts of leaf before maturity, their biological yields will be understated to an unequal degree. In the following pages we discuss the meaning and value of the biological yield and harvest index of cereals in agronomic studies and in cereal breeding. It is our view that each of these measures of performance by the crop or the single plant can contribute importantly to the advancement of cereal productivity. The lack of interest by plant breeders and many agronomists in biological yields-in the total production by their plants and crops-has seriously limited the understanding of cereal performance and biotype behavior. Though biological yield and the linking ratio to grain yield, harvest index, are extremely simplified statements of multiple and complex growth processes, they nevertheless permit a far more analytical interpretation of environmental and genotypic influences than is possible from grain yields alone. It. The Relationship of Biological Yield, Grain Yield, and Harvest Index to Each Other and to Other Plant Characteristics

Various models and actual relationships between biological yields and grain yields within a series of genotypes or agronomic treatments are shown in Fig. 1. Figure 1 [Graph l(a)] depicts the situation in which a number of varieties all have precisely the same biological yield but different grain yields. In Fig. 1 [Graph l(b)] these genotypes are ranked in order of increasing grain yield. In these two figures Grain yield is proportional to harvest index and their correlation is 1.OO.On the other hand, biological yield and harvest index are unrelated. This situation may be closely approached in varietal trials. In a series of trials in New South Wales, a comparison was made of six Australian wheats and the

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BIOLOGICAL YIELD AND HARVEST INDEX

German variety, Opal, all of normal height and two Mexican semi-dwarf wheats (Syme, 1970). The biological yield of the nine varieties showed the small range of 11,040 to 12,540 kg/ha, while the grain yields were from 2920 to 4890 kg/ha. The harvest indices ranged from 0.243 to 0.390; the correlation between grain yield and harvest index was 0.96, while that between biological yield and harvest index was 0.08. In most varietal comparisons the correlations between grain yield and harvest index is a good deal below 1.00 because biological yield is considerably more variable than in Syme’s study, but as the following values indicate, correlations of 0.6 or higher are commonly reported or can be calculated from published yield data.

con. YgJH.1. Finlay (private communication)

Thorne er u1. (1969) Hamblin (1971)

Singh and Stoskopf (1971) Nass (1973) Bhatia (1975)

Barley, 1962 Barley, 1963 Barley, 1964 Spring wheat Barley, at low N Barley, at high N Winter wheat Spring wheat Oats Spring wheat, 1971 Spring wheat, 1972 Wheat

0.73

Oh8 0.57 0.65 0.36 0.89 0.62 0.66 0.50 0.62 0.75 0.71

The contrary situation is that in which grain yields show dependence on biological yield. Figure 1 (Graph 2) shows this relationship in its full expression, whereby grain yield is strictly proportional to the biological yield. In this instance:

H.I.= K

and

Ygr= K. Ybiol

(2)

Thus grain yield has a correlation of 1.00 with biological yield. However, this positive correlation is not unique to the situation in Fig. 1 (Graph 2), but also applies in other situations in which grain yield rises with biological yield (Fig. 1, Graphs 3 and 4).

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YIELD AND H.I.

Varieties ranked

Varieties unranked YbiolL K Ygr a H.I.

A principal component of most comparisons of cultivars

H.I. = K ygr a ybiol As Ybiol increases,

YF increases proportionally. Tendency of genotypes in mixtures

Correlation ygr/ybiol Ygr/H.I. YbiodH.1.

0 1 0

1 0 0

FIG. 1. Model of relationships between biological yield, grain yield, and harvest index. (Ybiol is shown and discussed as constant or as increasing from left to right; however, the graphs can also be considered in mirror image.)

We believe that a strong positive relationship of biological yield and grain yield may be characteristic of genotypes competing in mixtures, as in a segregating population. In a barley F3 at crop density, Hamblin (1971) recorded correlations of Yv/Ybbl of 0.98 at low N and 0.95 at high N. The correlations of Y,/H.I. were 0.09 and 0.33 and of Ybbl/H.I. -0.10 and 0.03. Taller, leafy plants were successful in this competitive situation. In all comparisons of cdtivars, grain yields must by definition (Ybiol X H.I. = Y,) depend wholly on differences in their biological yields and differences in their harvest indices. The correlations of grain yield and harvest index in the several studies listed on p. 365 conform to the view (without proof of it, as we emphasize later) that the dominant relationship in field plot comparisons of genotypes in pure strands (that is to say, in crop situations) is a constant

367

BIOLOGICAL YIELD AND HARVEST INDEX

YIELD AND H.I.

AS Ybiol increases, Y p increases more than proportionally

AS Ybiol increases, Ygr increases less than proportionally

AS Ybiol increases Y, decreases

Typical of responses to water

Typical of responses to N.

Typical of responses to N when water is deficient

Correlation ygr/ ybiol YgJH.1. YbiodH.1.

1 1 1

1 -1 -1

-1 1 -1

FIG. 1 (cont'd)

biological yield with a variable harvest index [Fig. 1, Graph l(b)] ,as contrasted from the relationship depicted in Fig. 1 (Graph 2). Furthermore, as discussed in Section IV,most of the progress in breeding high-yielding cereal cultivars seems to be related to higher harvest indices with little change in biological yield. The foregoing discussion perhaps serves to illustrate that the calculation of correlations between harvest index and its components may be an inadequate means of examining relationships among cultivars. We illustrate this further by returning to the situation in Fig. 1 (Graph l(a) and (b)] in which biological yield is constant. It is evident from inspection of these graphs, or by consideration of Eq. (l), that random numbers bsed as simulated grain yields would, like any set of real yields, give a correlation H.I./Y, of 1.00. But this does not invalidate the implications in plant breeding of a constant biological yield as an

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C. M. DONALD AND J. HAMBLIN

important relationship among a group of genotypes. It is the constancy of biological yield which is the significant feature of this model. We can further examine the structural relationships between biological yield, harvest index, and grain yield by the use of two symbols, namely; a = yield of grain; b = yield of vegetative parts (all nongrain organs). Then, (a t b) = biological yield, and a/(a t b) =harvest index. The equation relating the terms is

Each of the terms may be derived from the other two. Usually harvest index is derived from measurements of biological yield and grain yield, but sometimes the biological yield may usefully be derived from published values of harvest index and grain yield. Table I shows correlation data for 60 cultivars of barley grown at Adelaide in 1962, 1963, and 1964 (data from K. W. Finlay). A model was then constructed in respect of each season, comprising 100 populations, each of 60 entries; each population had random a values (simulated grain yields) and random b values (simulated vegetative yields), restricted to give means, relative values of means, and variances equal to those of Finlay’s barleys for that season. The values of a and b were chosen independently and were ips0 fact0 uncorrelated. The simulated grain yields, a, biological yields, (a t b), and harvest indices, a/(a t b), were correlated within each population. The mean correlations for the 100 populations for each year are shown in Table I; it will be seen that the mean correlations derived from the random values are strongly related to those from the field study. Although the random values were subject to several significant restraints, including, for example, the degree of constancy of the biological yield, it is evident that, within any varietal comparison and even where grain yields and vegetative yields are uncorrelated, biological yield, grain yield, and harvest index will always show partially predictable mutual correlations because of the common terms in their formulas. Turner (1959) has examined the correlations between a ratio (W/B, kg wool/kg body weight of sheep) and its numerator (W, wool weight), and between the ratio and its denominator (B, body weight), in terms of the variances and covariances of its components. She showed that with phenotypic correlations between W and B of -0.4 to 0.4 and genetic correlations between W and B of -0.2 to 0.4, as in the wool and body weights of these Merino sheep, the genetic correlation between W and W/B was positive and usually over 0.5 in value, while the genetic correlation between B and W/B was negative and frequently greater than 0.5 in magnitude. Similar relationships emerge in Table 1, in which Y , and Y,, (i.e., a and b, equivalent to W and B in Turner’s study) show phenotypic correlations from -0.46 to 0.35. Harvest index, a/(a t b), is similar to Turner’s W/B,where W a .

369

BIOLOGICAL YIELD AND HARVEST INDEX TABLE I Correlations between the Components of Harvest Index for 60 Barley Varieties Grown at Adelaide in Three Successive Years, Together with the Mean Correlations in Each Season for 100 Model Populations Each of 60 Random Value@ Ygr

Correlation:

Ybiol

Ygr H.I.

Ybiol H.I.

ygr

Yveg

~~~

1962 Actual Randoma

-0.25 0.24

0.73*** 0.35

-0.81*** -0.46*** -0.77 0.02

0.68***

-0.36** -0.37

0.02 0.02

-0.33** -0.47

0.35** 0.02

1963 Actual Random

0.36** 0.35

0.55

1964 Actual Random

0.56*** 0.57*** 0.30 0.66

“Based on random values of Ygr and Yveg restricted to give means, relative values of means, and variances equal to those of the actual material in each season (see text). Note: Throughout this article * = P <0.05; ** = P <0.01;*** = P <0.001.

It is clear that the correlations within any actual set of varietal data can be partially matched by correlations based on random values of a and b, provided that those random values have means, relative values of means and variances equal to a and b in the field data. Our conclusion from all these considerations is that the calculation of correlations between biological yields, grain yields, and harvest indices within any group of genotypes is a limited analytical approach. (We emphasize both here and later that this comment does not apply to data from distinct sources.) In comparing genotypes or treatments within a single trial, the significant issues are the individual biological and grain yields, the individual harvest indices and the nature of the combination between them (for example, Fig. 4 or Table XIII). Graphs 3, 4, and 5 of Fig. 1 are in effect variations of Graph 2, in which grain yield is proportional to biological yield. Each of these relationships has been reported frequently in agronomic studies, and each is also feasible in comparisons of genotypes. With an increase in biological yield, the grain yields may rise more than proportionally (Fig. 1, Graph 3), less than proportionally (Graph 4) or may decline (Graph 5). These relationships are dealt with later in this article, but several points may here be noted. First, it is believed that the relationships of biological yield, grain yield, and harvest index shown in Fig. 1, including their mirror images, may embrace the principal relationships found in field situations. However, there may

370

C. M. DONALD AND J. HAMBLIN

be complexities due to nonlinearity and interaction with seasons, much as has been demonstrated for grain yield by Finlay and Wilkinson (1963). Second, in various agronomic situations there may be (and has been shown to be) strong inverse relationship between grain yield and harvest index, as in Graph 4 of Fig. 1. We believe too that this relationship in Graph 4, whereby differences in grain yields are proportionally less than differences in biological yield, may also be a component of many comparisons of cereal genotypes. And finally we point to the variable pattern of correlation between harvest index and its components in Graphs 3,4,and 5 (Fig. 1) and again emphasize the need for caution in the use of correlations of this kind in agronomic studies. We now turn to a consideration of the factors which seem a priori to contribute to a high harvest index in a cereal crop. These can be listed in two categories: those which make up grain yield and should have a relatively high expression, and those which make up the nongrain parts and should have a relatively low expression. The factors in the first group are “the components of yield” (Engledow, 1925), referring to grain yield. Those in the second group have usually been considered only indirectly in relation to grain production, as when dwarfness is sought to avoid lodging. For wheat, these factors are: A. High expressionindicated relative to components under B Weight per grain Grains per spikelet Spikelets per ear Ears per plant Plants per m*

B. Low expression indicated relative to components under A Weight of stems: Length Weight per an Stems per plant Plants per ma Weight of leaves: Length Weight per cm Leaves per stem Stems per plant Plants per m a Weight of chaff: (rachis + glumes) Ears per plant Plants per m’

It will be seen that there is an apparent conflict in the contribution by some characteristics to the value of harvest index. “Plants per m2” is shown in both Group A and Group B, while “ears per plant” conflicts with “stems per plant.” This indicates that harvest index, to be meaningful, must be relatively insensitive to plant density or plant size, and be related to performance per culm rather than performance per plant. This is indeed the case. For example, with a 300-fold range in the density of a wheat crop, the grain yield fell from 33

BIOLOGICAL YIELD AND HARVEST INDEX

37 1

g/plant at 1.4 plantslm’ to 0.4 g/plant at 447/m2 ;in contrast, the harvest index fell only from 0.36 to 0.25 (Puckridge and Donald, 1967). This represented a change in harvest index of approximately 0.01 for each doubling of the density. This independence of the index from plant size makes possible the pursuit of high harvest index even in nontillering plants of low per-plant yield. If ear density (earslm’) can be controlled, then neither plants/m’ nor ears/plant is critical to a high harvest index. Further, since the index is based only on the weight of grain, and not on the size or number of grains, the components of grain yield are not individually critical to a high harvest index. It is the performance of the community of culms, in terms of their yield of grain, that is important to harvest index and grain yield. With the foregoing considerations, the list of factors contributing effectively to a high harvest index can be summarized as follows: A. High expression indicated Weight of grain per ear Number of ears per mz

B. Low expression indicated Weight per leaf Leaves per culm Weight per stem Chaff per ear

It follows that a high harvest index in a crop will be achieved with many ears, each with a high yield of grain, relative ro short, light stems and few, short, narrow leaves per stem. We emphasize the point that all these values are high or low only in a relative sense. Thus ears of small absolute size will be relutively large if each of them is associated with a small quantity of vegetative tissue. This comment applies to all other organs. It will be seen that a high harvest index for a plant community does not per se indicate a high grain yield per unit area. For example, a single wheat plant on a square meter may have a high harvest index, but its yield per unit area would be low. Grain yields depend not only on the harvest index but equally on the biological yield per unit area. An analysis by Singh and Stoskopf shows the contribution by the various vegetative organs to the biological yield of three cereals (Table 11). The stems made a mean contribution of 32% to the biological yield or 56% to the vegetative parts. It follows that variation of the weight of stems is likely to have a greater influence on harvest index than any component other than the grain. A comparison by Singh and Stoskopf of tall (86 cm), medium (78 cm), and dwarf (58 cm) cultivars of winter wheat showed harvest indices of 0.38, 0.40, and 0.42, respectively. (In this instance the highest grain yields were obtained by the tall cultivars, but it may be calculated that the dwarf cultivars had 15% less biological yield at the common sowing rate.) As m a y be predicted from our earlier discussion, harvest index is negatively correlated with the individual vegetative components, particularly with stem

w

4 t4

TABLE I1 The Contribution to Biological Yield (Tops Only) of Various Plant Parts and the Correlation between Harvest Index and Those Plant Parts in Genotypes of Three Cereal# ~~~

Spring barley

Winter wheat

Plant part Leaves Stems Veg. tillers Chaff Grain Height (cm):

Oats

% of bioL yield

corr. of wt. of plant part Wm’) with H.I.

% of biol. yield

of plant part (g/m’) with H.I.

% of biol. yield

9 33 8 10 40

-0.18 -0.36* -0.29 -0.18 0.62**

6 28 5 10 51

-0.72* -0.83* -0.35 -0.46 0.66*

7 34 3 15 41

-0.60**

con. of wt.

-0.38

=Fifteen-centimeter row spacing, University of Guelph; Singh and Stoskopf (1971).

con. of wt. of plant part (g/m’) with H.I. -0.47 -0.57 -0.27 -0.58 0.50

-0.96**

U

0 2:

b

BIOLOGICAL YIELD AND HARVEST INDEX

373

weight (Table 11). Hamblin’s data for barley (Table 111) similarly show a negative correlation of harvest index with plant height and leaf length, together with positive relationships with grain yield and its components. All these correlations were much stronger at high nitrogen than at low nitrogen, where growth was sparse and competition for light and water was weak. In contrast to these results, a comparison of 26 pairs of near-isogenic tall (102 cm) and semi-dwarf (67 cm) lines of durum wheat, equal in mean grain yield, showed no difference in their biological yields and harvest indices (Joppa, 1973). This was interpreted to mean that in this instance the stem internodes of the semi-dwarfs,though shorter than those of the talk, were thicker. The autocorrelation of harvest index with the biological yield and grain yield of the same plants does not limit the validity of the direct comparison of these attributes between genotypes. Nor does it restrict the examination by correlation or otherwise, of the yields or harvest indices respectively of genotypes in different environments, or between years, or due to environmental factors such as density or fertility. Similarly, one may compare by correlation the relationship between harvest index or its components and other plant characteristics. We here examine the relationships with earliness and competitive ability. In Finlay’s study with 60 barley varieties (noted earlier), the correlations with flowering date were as follows:

~~

Ybiol

F1. date 1962 1963 1964

0.45*** 0.34** 0.43***

Ygr

H.I.

F1. date

F1. date

-0.60*** -0.20 0.00

-0.67*** -O.46* * * -O.45***

The general picture presented by these data is of increased plant growth by the later cultivars, but reduced harvest index (undoubtedly due in the Adelaide environment principally to water stress) and reduced grain yield by those late varieties. In a more favorable environment, Iowa, flowering date had a genotypic correlation of 0.53 with grain yield, but of -0.36 with harvest index. Thus, later varieties had a higher biological yield, only partly discounted by a falling harvest index (Rosielle and Frey, 1975b). Finally we comment on the relationship of harvest index to competitive ability. Since tallness and large leaves have long been established as important components of competitive ability (Clements et al., 1929), and since these characteristics will tend to increase the denominator (biological yield) of the

374

C. M. DONALD AND J. HAMBLIN TABLEIII Correlations between Harvest Index and Various Grain Yield Components and Vegetative Indices within F, Plots of Barley at Normal Crop Density" Correlation

At low N

At high N

H.I., leaf length H.I., plant height

-0.28 -0.46

-0.5 2 -0.54

H.I., ears/m* H.I., seeds/ear H.I., weight/seed HI., yield of grain

0.34 -0.08

0.78 0.19 0.65 0.89

0.27

0.36

NOTE: For 196 d.f.: r > 0.26, sig 0.001; r > 0.18, sip. 0.01. uHamblin and Donald (1974); Hamblin (1971).

harvest index, it follows that competitive ability and harvest index are likely to be negatively related. Jennings and de Jesus (1968) showed a significant inverse relationship between the grain yield of rice cultivars in pure stand and their competitive ability in mixtures (Table IV). The great competitive ability of tropical, village rices was associated with their tallness and length of leaves, as distinct from the short, compact, erect habit of modem cultivars. The harvest indices of these cultivars (derived from the published grainlstraw ratios) show a positive relationship to grain yield and a negative relationship to competitive ability. Thus the tall varieties were low yielding and had low harvest indices in pure stands, but were powerful competitors in mixtures. This relationship of harvest index to competitive ability was also examined in FS barley plots at Adelaide (Hamblin, 1971). Each plot comprised 16 central plants and 20 border plants, all at 8 X 8 cm. These 20 border plants were in competition with the border plants of neighboring plots (also at 8 cm), there being a different genotype along each of the four sides. Competitive ability was evaluated as the difference between seed yield per unit area in pure culture (the central 16 plants) and the seed yield per unit area when in competition with other genotypes (the 20 border plants). The correlation between harvest index of the central plants and their competitive ability with neighbors was -0.17* at low nitrogen, when the competition for light and water was weak, and -0.48*** at high nitrogen. These relationships accord with the finding of Hamblin and Donald (1 974) that there was a negative relationship in these plots between grain yield, on the one hand, and height and leaf length (which confer competitive ability), on the other.

375

BIOLOGICAL YIELD AND HARVEST INDEX TABLE IV The Relationship of Grain Yield, Competitive Ability, and Harvest Index in Rice CultivarP Plant type:

Short, erect, compact

Intermediate

Tall,leafy, spreading

Variety:

TN1

Ch242

M6

MTU

BJ

Grain yield (t/ha)? Harvest index:c Competitive ability:d

5.03 0.56 0.05

3.85 0.53 -0.65

3.95 0.48 -0.41

2.39

0.39

2.43 0.42 0.94

0.06

OJennings and de Jesus (1968). bIn pure stands; wet season, high nitrogen. CIn pure stands; derived from the published grainlstraw ratios. dcalculated by Jennings and de Jesus by the technique of Goulden (1952). AU cultivars other than BJ almost disappeared from mixtures within 3 generations.

Ill. The Influence of Environmental Factors

Like yield, the harvest index of cereal crops is sensitive to environmental influences. Here we discuss three of the components of the environment of the plant or the community which influence yield and harvest index, namely population density, water availability, and nitrogen supply. These three factors are of great significance in cereal production; two of them are subject to considerable control by man, the third, water availability, less commonly so.

A. POPULATION DENSITY

The relationship of the yield of cereals to population density has been broadly elucidated. Biological yield increases with density to a maximum value determined by some factor of the environment and at higher densities tends to remain constant, provided there are no interfering factors such as lodging. Grain yield increases to a maximum value but declines as density is further increased. It has been noted (Donald, 1963; Kirby, 1967) that the ceiling biological yield and the maximum grain yield are generally achieved at about the same density. Several sets of data showing the relation between density, biological yield, and grain yield are shown in Table V. In studies A, B, C, and D the harvest index declined before the maximum grain yield was attained, usually from the lowest density examined. In the fifth experiment, E, (Morrow and Hunt, 1891), there was an increase in harvest index up to the density giving the highest grain yield.

w

TABLE V

4

m

The Relationship of Density, Biological and Grain Yields, and Harvest Index in Cereals ~~~~

The study

~~

Population (000's/ha) and yields (t/ha) Populatbn: Biol. yield: Harvest indexa: Grain yield:

20 12.4 0.475 5.9

40 17.4 0.420 7.3

80 20.1 0.389 7.8

Population.. Biol. yield: Harvest index: Grain yield:

14 1.3 0.364 0.5

70 4.8 0.358 1.7

350 8.1 0.304 2.5

I540 8.9 0.262 2.3

C. Sorghum,Central Sudan. Gerakis and Tsangarakis (1969)

Population: Biol. yield: Harvest index: Grain yield:

80 2.27 0.169 0.38

120 2.87 0.141 0.40

160 2.68 0.141 0.38

200 2.95 0.125 0.37

D. Maize, Colorado Fairbourn et QL (1970)

Popuhtion: Biol. yield: Harvest index: Grain yield:

21 5.3 0.494 2.6

32 7.3 0.494 3.6

37 7.8 0.474 3-7

42 9.7 0.373 3.6

E. Maize, Illinois. Morrow and Hunt (1891)

Popuhtion: Biol. yield: Harvest index: Grain yield:

15 9.4 0.367 3.4

23 11.9 0.380 4.5

29 12.8 0.398 5.1

39 12.8 0.378 4.8

A. Maize, Alabama. Mean of 2 var. andlsimilar seasons. Scarsbrook and Doss (1973) B. Wheat, South Aust. Puckridge and Donald (1967)

=Harvest index calculated in a l l studies from full figures.

44 70 7.4

b

*r

0.251 1.8

59 13.9 0.343 4.7

b

ii 7 15.2 0.243 3.7

377

BIOLOGICAL YIELD AND HARVEST INDEX

All studies were consistent in showing a progressive decline in harvest index at densities above the maximum grain yield. These findings and views are incorporated in the model in Fig. 2, where biological yield and grain yield are depicted in relation to density, and where harvest index is derived as the height of the lower curve relative to the upper curve. At lower densities (below that giving maximum biological and grain yields) the grain curve shows greater relative convexity toward the yield axis than does the curve for biological yield. This leads to a progressive decline in harvest index from the lowest density at which competition begins, as shown by the figures across the graph. In this model the harvest index is negatively correlated with yield up to the maximum grain yield (e.g., in Scarsbrook and Doss’s study -0.64 in 1969 and -0.77 in 1970), with a cross-over to a positive relationship at densities above the maximum grain yield (e.g., at 350,00O/ha in Puckridge and Donald’s data). But Morrow and Hunt’s data are not consistent with this model and are of interest in showing maximum “efficiency” at maximum grain yield. The capacity of maize hybrids to maintain their fertility and yield per plant at high densities is a critical attribute in modem maize production. Hanway and Russell’s study (1969) of the total yields, grain yields, and harvest indices of a number of hybrids at two densities is therefore of considerable interest (Table VI). The biological yield of all hybrids at high density (52,0OO/ha) was 16% above that at low density (35,70O/ha), but because the harvest index fell from 0.44 to 0.40, the grain yield increased by only 5.5%. But individual hybrids showed different patterns: No, 11 showed a 36% increase in dry matter, but this was poorly reflected in grain yield because of a heavy fall in the harvest index; No. 5 showed a much smaller gain in biological yield but maintained its harvest index and gave a corresponding increase in grain yield. These figures suggest H , L / Y GRAIN ; CORR. -ve

I

H.I./

Y GRAIN; CORR. + v e

I BIOL. YIELD YIELD PER UNIT

.35

.30

AREA

GRAIN YIELD

DENSITY

FIG. 2. Model of the relationship of density, yield, and harvest index. The harvest index is the relative height of the two curves and is shown as a series of values across the graph. This model accords with most experimental data, but see text for its limitations.

378

C. M. DONALD AND J. HAMBLIN TABLE VI The Biological Yields, Grain Yields and Harvest Indices of Maize Hybrids at Ames, Iowaa

High density

Low density

H.I.

Grain yield (t/ha)

Biol. yield (t/ha)

15.5

0.44

6.8

17.9 +16%

0.40

7.2 +5.5%

No. 11

14.2

0.49

7.0

19.3 +36%

0.38

7.3 +5%

No. 5

15.9

0.40

6.3

18.5 +16%

0.40

7.4 +17%

Biol. yield (t/ha)

Mean of 11 hybrids

Hybrid

H.I.

Grain yield (t/ha)

UHanway and Russell (1969).

(subject to the limited replication in this study) that the yield of No. 5 could be further raised by increasing the population density still higher. Certainly the consideration of biological yield and harvest index as in Hanway and Russell’s study, should permit increased effectiveness in identifying high yielding lines for use at high densities. A factor likely always to be involved in the fall in harvest index at high densities, is the light profile withii the crop. (We discuss later the relationship of water and nitrogen supply to density and harvest index.) At high densities total light interception occurs earlier and competition between plants for light is more intense. The percentage of tillers producing ears, the number of grains per ear, and grain size are all reduced, even where water and nutrients are nonlimiting. In a field study near Brisbane, Fischer and Wilson (1975) varied both the population density of sorghum and, by the use of shade cloths, the light intensity. Table VII shows the parallel and additive effects of reduced light, on the one hand, and population increase, on the other, in bringing about a reduction in the harvest index. The influence of light on harvest index has also been recorded in rice production in the Philippines. Chandler (1969) noted that the harvest index of the cultivar Peta may be as low as 0.22 during the cloudy monsoon and as high as 0.47 in the sunny season. B. WATER AVAILABILITY

Studies on several species have clearly established that cereal crops suffering water stress not only have lower biological and grain yields, but also lower

379

BIOLOGICAL YIELD AND HARVEST INDEX TABLE VII The Influence of Light Intensity and Plant Density on the Harvest Index of Grain Sorghum in Field PlotP Percentage daylight Density @lants/ha, 000’s)

100

72

48

35

14 143 646

0.49 0.43 0.41

0.46 0.41 0.38

0.42 -

0.39 -

~

~~~

-

~

“Fischer and Wilson (1975).

harvest indices. The study by Poostchi er al. (1972) of supplementary spring irrigation of wheat under semi-arid conditions in southern Iran, showed a characteristic response pattern, which was remarkably consistent for each of the three years of the experiment (Fig. 3). As the water supply was increased, the 16

14

23 12

21 YIELD kg I Iia (000‘s)

1c

H.1.

19 HARVEST INDEX

17

/’

2.

01

I

400

1

GRAIN YIELD

I

1

600

1

800

IRRIGATION WATER (mm

FIG. 3. ,The responses of wheat to irrigation in southern Iran. Mean of three Seasons. Drawn from data by Poostchi et ul. (1972).

3 80

C. M. DONALD AND J. HAMBLIN

biological yield rose from 9.5 to 15.8 tonnes, the grain yield from 1.6 to 3.6 tonnes, and the harvest index from 0.172 to 0.229. Similarly, in a study by Doss (1974) of maize in Alabama, the harvest indices were 0.465, 0.459 and 0.338 for the nonirrigated crop in 1970, 1971, end 1972, respectively, and 0.477, 0.502, and 0.473 for the irrigated crop, with an average of 48% increase in grain yields. Varietal interactions with water status are likely to be reflected in their harvest indices. When an upland rice variety and a swamp rice variety were grown in pot cultures (Enyi, 1968), they had a similar harvest index at 100% soil saturation but the upland rice maintained a much better value than the swamp rice at 80% or 60% saturation (Table VIII). Conversely, though the two rices had similar biological yields when flooded, the swamp rice had a higher harvest index and grain yield. The interaction between water supply, density, row spacing, and yield in sorghum was studied by Bond er al. (1964) on the southern highlands of Texas. They emphasize the hazards of high populations and close rows in depressing grain yields through water deficit late in the season in this environment-a hazard common to all semi-arid cereal production. Four levels of water reserves were establisb.ed at sowing; the results from the extreme levels, 71 and 180 surface mm of stored water at sowing, are shown in Fig. 4. A high seed rate or narrow rows led to heavy biological yields, but when water was in limited supply, the heavier growth depressed the harvest index. With limited water all grain yields tended to low values, but the low population nevertheless gave 12% more grain than the high population and the wide rows 18% more than the narrow rows. With liberal water all treatments tended toward a common high

TABLE VIII The Influence of Degree of Soil Saturation on an Upland Rice Variety and a Swamp Rice VarietyaBb

Soil saturation Type of rice

60%

80%

100%

Flooded

An upland rice, Abgede

Biol. yield: Harvestindex: Grain yield:

129 0.17 22

171 0.19 33

194 0.21 41

170 0.16 28

A swamp rice,

Biol. yield: Harvest index: Grain yield:

145 0.13 19

208 0.13 27

244 0.21 52

152 0.26 40

BG79 “Yields: g/plant. bEnyi (1968).

BIOLOGICAL YIELD AND HARVEST INDEX

11

1

POP. OOO'rlha

ROWS

94

51

cm

51

BIOL. YIELD kp I ha

38 1

102

High population and narrow rows give increased biological yields, especially with ample water

5. 11

180

1

I

.so HARVEST INDEX

At low water, high populations and narrow rows intensify water stress and reduce harvest index. With ample water, a l l treatments tend to a common (high) harvest index

4 5 1 1 0 2 . e

941 102 94/51.

51

51 102 102

GRAIN YIELD

hplh

800%

110

71 WATER

RESERVES AT SOWING

At low water, low populations and wide rows give the best grain yields. With ample water, grain yields are proportional to biological yields so that high populations and MIIOW rows are best

(mm)

FIG. 4. The interaction of water availability, population density, row spacing, yield and harvest index in sorghum. Texas, 1958, natural rainfall 316 m m Drawn from data by Bond etaZ. (1964).

harvest index and hence to give grain yields proportional to their biological yields. The usual effect of water stress in reducing biological yield, harvest index, and grain yield seems well established, but the intensity of the effects may be greatly influenced by the developmental stage at which the stress occurs. Aspinall el ul.

382

C. M. DONALD AND J. HAMBLIN

(1964) have emphasized that “the organ which is growing most rapidly at the time of stress is the one most affected.” This relationship can actually lead to an increased harvest index under water stress because of strong reduction in vegetative growth. Maize, grown under irrigation at Griffith, New South Wales (Downey, 1971; Table IX) was subject to early stress (relative turgidity less than 90% for 20 days during male meiosis) and late stress (20 days during grain filling). Early stress reduced plant height and weight of stover and prevented any tillering. In contrast, the control plants produced additional tillers, many of them sterile. As a consequence the early stress plants had a grain yield equal to that of the controls, with a higher harvest index. In the late stress plants, sterile tillers made up 46% of the biological yield, and harvest index and grain yield were very low. TABLE IX The Influence of Early and Late Water Stress on the Yield (t/ha) and Harvest Index of Maizea No stress BioL yield Harvest index Grain yield

12.7

.28 3.6

Early stress 9.1

.42 3.8

Late stress

S.E.

8.9 .21 1.9

0.5

0.3

aDowney (1971).

A similar but less marked effect was recorded by Kirby (1968) who found that of five barley varieties which showed a gain in yield of 25% as a result of irrigation, four suffered a mean fall in harvest index from 0.485 to 0.460. As in Downey’s experiment, the effect of additional water was to promote more tillers, not sterile in this instance, but with small, late produced ears-that is to say, culms of low harvest index. Thus while biological yield, grain yield, and harvest index usually show a positive response to improved water supply, there are circumstances in which reduced water availability may so curtail height and tillering as to lead to an increased harvest index.

C. NITROGEN NUTRITION

The application of nitrogen to cereals commonly gives an increase in biological yield combined with a decrease in harvest index. This relationship was demonstrated at the Rothamsted Experimental Station last century by the application of nitrogen to wheat for the period 1852 to 1863 [Russell and Watson, 1940,

383

BIOLOGICAL YIELD AND HARVEST INDEX a

9-

9r

1-

BIOL. YIELD HARVEST INDEX

YIELD t /h a

-* GRAIN YIELD

1I

t

II

I I

0

50

100

I

150

200

NITROGEN APPLICATION (kg I ha )

b

8-

43 YIELD tlha

/*-*

.------* 0

GRAIN YIELD

1

1

I

1

0

25

50

15

100

NITROGEN APPLICATION ( k g I h a )

FIG. 5. The influence of nitrogen on biological yield, grain yield, and harvest index. (a) Wheat at the Rothamsted Experimental Station; mean of 12 years, 1852-1863. Drawn from data by Russell and Watson (1940). (b) Spring wheat at Bozeman, Montana, 1969. Drawn from data by McNealetal. (1971).

Fig. 5(a)]. The increase in biological yield (3.4 to 8.5 tonnes) greatly exceeded the decline in harvest index (0.36 to 0.30), so that grain yield rose from 1.2 to 2.6 tonnes with 192 kg N/ha. The Broadbalk plots at the same station provide a sustained account of the effect of nitrogen on harvest index. For the period 1852 to 1925, the harvest index (mean of 74 years) was 0.404 on the “minerals only” plot and 0.354 on

384

C. M. DONALD AND J. HAMBLIN

the “minerals t nitrogen” plot. This depression was consistent for every decade of the period (Russell and Watson, 1940). A similar relationship is shown in Fig. 5(b) for spring wheat in Montana in 1969 (McNeal et al., 1971), where the harvest index fell from 0.43 to 0.39 with nitrogen application. Soil water was considered adequate in that season, as indicated also by the uptake of 49 mm more water by the 90 kg N plots than by the no-nitrogen plots. This pattern of response to nitrogen gave a negative correlation of harvest index and grain yield (r = -0.97). When water is in limited supply, as is the case for a considerable part of the world’s cereal crops, the fall in harvest index associated with applied nitrogen may be more marked than the increase in biological yield, and grain yield declines. Luebs and Laag (1967) report that in 32 field experiments in California over 15 years, on soils with less than 0.1%N, there was no response in barley yields in 10 experiments and a decrease in yield in four. Similarly, there are numerous instances in Australia of depressions in the grain yield of wheat crops due to nitrogen application and these are attributed to increased vegetative growth and a depletion of the water supply (e.g., Barley and Naidu, 1964; Storrier, 1965; Fischer and Kohn, 1966). Increased tiller mortality, reduced

TABLE X A Lysimeter Study of the Influence of Nitrogen on Barley under Simulated Drought S t r e d Nitrogen application Wha) Crop characteristic

0

LAI 3.2 March 7 1.5 March 25 (after 1 week’s stress) Evapotranspiration (mm) 54 Jan. 25-Mar. 12 22 Mar. 19-Mar. 26 (under water stress) Relative turgidity (%) Mar. 26 a4 Apr. 29 76 Yield Biol. yield (kglha) 4750 Harvest index 0.45 2150 Grain yield &/ha) =Luebs and Laag (1969).

45

90

4.6 3.7

6.7 4.2

67 17

76 10

65 68

52 56

7000 0.37 2600

5 260 0.13 680

BIOLOGICAL YIELD AND HARVEST INDEX

385

grain number per ear, and reduced grain size may each or all be involved. “Thus, under dryland conditions,” write Fischer and Kohn, “there is an optimum level of vegetative growth, depending on water supply, for maximum grain yields.” This influence on soil water resources of increased vegetative growth due t o nitrogen, was demonstrated by Luebs and h a g (1969) in field lysimeters (Table X). Nitrogen application gave a greater leaf area index and led to increased evapotranspiration while water was freely available, but caused loss of turgidity when water became exhausted during a simulated drought period. At high nitrogen there were 78% barren culms, and only 61% of plants had an ear with more than 3 grains. The consequence was a severe depression in harvest index and grain yield compared to the unfertilized plot. TABLE XI The Influence of Nitrogen on the Growth and Harvest Index of Two Wheat Cultivars (Adelaide, South Australia. Moderate Fertility, Dry Season, 196 l)n N application (kglha)

0

61

134

Tillers/m of row Gabo Bencubbin

118 161

151 223

157 236

Tiller survival (%) Gab0 Bencubbin

69 45

56 33

41 32

Plant character

Biol. yield (t/ha) at ear emergence Gab0 Bencubbin Harvest indexb Gab0 Bencubbin Grain yield (t/ha) Gab0 Bencubbin

8.4 8.5 .36 .24 3.0 2.0

9.5 8.6 .28 .21 2.7 1.8

9.4 9.7 .21

.14 2.6 1.3

agarley and Naidu (1964). bCalculated using biological yield at ear emergence.

386

C. M. DONALD AND J. HAMBLIN

A related field study in Australia compared two wheat cultivars of contrasting habit at three levels of nitrogen supply (Table XI). These were Gabo, rather sparsely tillered, and Bencubbin, free tillering and later maturing. Nitrogen greatly increased tiller production, especially in Bencubbin, and resulted in decreased soil moisture at heading. Tiller survival was severely curtailed at high nitrogen, particularly in the free tillering Bencubbin. This death of tillers was reflected in depressed harvest indices and grain yields on the plots receiving nitrogen. A factorial study of the interaction of nitrogen and water was made by Ramig and Rhoades (1963) on wheat at North matte, Nebraska. The natural rainfall (mean 328 mm, October 1 to June 30), in the 3 years of study, was supplemented prior to sowing with several levels of water supply. Nitrogen and water each gave increased biological yields (grain -+ straw), with a strong positive interaction (Fig. 6). However, nitrogen depressed the harvest index severely at low water (0.36 at No to 0.24 at Nso) and to an appreciable though less extent at high water (0.41 to 0.38). The outcome was a modest absolute increase in grain yield with a small nitrogen dressing at low water (470 kg/ha at No and 538 kg/ha at Nzo ), and a grain yield strongly related to biological yield at high water. Finally we quote an instance in which an increase in both biological yield and harvest index was recorded with nitrogen application. Sorghum was grown (120,000/ha in 46 cm rows) during the monsoon season at New Delhi (Roy and Wright, 1973) at various levels of phosphorus and nitrogen supply, and presumably without limitation in water availability (Table XI). The crop showed an increase in harvest index due to 60 kg/ha nitrogen and to phosphorus. The authors found that the accumulation rate in the heads of fertilized plants was very high at 70 to 77 days compared to that of the unfertilized plants. The reason for this less usual pattern of response is not evident to us.

TABLE XI The Harvest Indices of Sorghum at New Delhi Fertilized with Nitrogen and Phosphond Nitrogen &/ha) Fertilizer application

0

60

120

0.37 0.43

0.42

0.43 0.49

Phosphorus (kglha) 0 26

‘Roy and Wright (1973).

0.50

387

BIOLOGICAL YIELD AND HARVEST INDEX

I

BIOL. YIELD kg I ha

000's

I

.45

,

.35

.

.25

.

HARVEST INDEX

1

1

74

150

206

74

150

206

1

0

/ N80

0

,*-•

-*

L

1

I

I

I

0

74

150

206

WATER

APPLIED

BEFORE SOWING

N80 N40

mm

FIG. 6. The interaction of nitrogen and water on the yield and harvest index of wheat at North Platte, Nebraska. Drawn from data by Ramig and Rhoades (1963). The rates of nitrogen application are shown on the curves (in lb/ac = 0.89 X kglha).

388

C. M. DONALD AND J. HAMBLIN

Some data are available on individual varieties. Gardener and Rathjen (1975) examined the responses to nitrogen at Adelaide, South Australia by 12 cultivars of barley of widely different origin and maturity. Figure 7 shows the influence of high and low nitrogen (275 and 0 kg N/ha) on their harvest indices. There was a trend toward a lower harvest index among the later varieties, presumably an effect of increased water stress in the early summer. The effect of nitrogen in depressing the harvest index was rather constant for all cultivars, with a mean reduction from 0.43 to 0.36.

*40. HARVEST INDEX

030.

VVE

VE

E

ME

M

ML

L

VL

MATURITY

FIG. 7. The harvest index of 12 cultivars of barley of differing maturity at Adelaide, South Australia at two levels of nitrogen supply. E = Early, M = Medium, L = Late, and V = Very. (The aberrantly low value of one of the very early varieties at low N was discounted in hand fitting the curves.) Drawn from data by Gardener and Rathjen (1975).

In contrast to Gardner and Rathjen's results, the comparison by Vogel er al. (1963) between efficient semi-dwarf wheat cultivars and standard height commercial varieties in eastern Washington demonstrated notable differences in the relationships of biological and grain yields (Table XIII). The harvest index of the semi-dwarfs was high not only at moderate fertility but also at high fertility. In contrast, the standard varieties, though showing a strong response to improved fertility in their biological yields, declined in harvest index.

BIOLOGICAL YIELD AND HARVEST INDEX

389

TABLE XI11 The Yield and Harvest Index at Two Fertility Levels of “Efficient Semi-dwarf Winter Wheats” and “Standard-Height Commercial Varieties” in Eastern Washington“

Plant type 3 efficient semi-dwarf winter wheats 5 standard height wheat varieties

Fertility level

Height (cm)

Biol. yieldb (t/ha)

H.I.

Grain yield (tlha)

Moderate

74

11.04

0.385

4.25

High

77

12.57

0.385

4.84

Moderate

117

10.65

0.305

3.25

High

122

12.46

0.276

3.44

“Calculated from data by Vogel et al. (1963). bCalculated from grain yields and strawlgrain ratios.

Similar relationships occur among rice genotypes (Langfield, 1961), where marked differences in the response of biological yields to nitrogen were accompanied by inverse movements in harvest index (Table XIV). Thus in the studies by both Vogel et al. and Langfield, there was a notable interaction between fertility, genotype, and harvest index.

TABLE XIV Tne Yields and Harvest Indices of Two Groups of Rice Genotypes at The Coastal Plains Research Station, Northern Territory, Australiaa Ybiol

Ygr

Genotype and N status

(t/ha)

H.I.

(t/ha)

At low N Oryza indica varieties Oryza japonica-indica hybrids

17.5 11.7

0.22 0.25

3.8 2.9

At high N Oryza indica varieties Oryza japonica-indica hybrids

28.6 18.2

0.16 0.30

4.5 5.4

“Langfield (1961).

390

C. M. DONALD AND J. HAMBLIN

D. THE INTERACTION OF ENVIRONMENTAL FACTORS, YIELD, AND HARVEST INDEX

There is striking parallelism between the data on population density and water supply from Bond er al. (1964) (Fig. 4) and on nitrogen and water from Ramig and Rhoades (1963) (Fig. 6). These two sets of results each in fact display the same phenomenon. High population density, narrow rows, and heavy nitrogen all lead to an increase in biological yield, and this increase is relatively greater if a l l other conditions, including water availability, are favorable. These increased biological yields will be reflected in the grain yields unless some other factor is in deficient supply, when the harvest index will be depressed. This depression can be very severe if there is a limited supply of water (e.g., 0.36 to 0.24 in Fig. 6 at 0 mm) but at high nitrogen a fall occurs even when water is adequate (e.g., 0.36 to 0.30 in Fig. 5(a) and 0.41 to 0.38 in Fig. 6 at 206 mm). The depression in harvest index due to nitrogen or a high population density in a well-watered environment is probably an effect of heavy vegetative growth on light relationships within the canopy. This adversely affects ear initiation, grain development, and harvest index. IV. Biological Yield and Harvest Index as Criteria in Cereal Breeding

The harvest index of cereal cultivars has tended to rise progressively, with little increase in biological yield. In Holland it rose from 0.35 in 1902 (cv. Wilhelmina) to 0.40 in 1954 (cv. Heine VII), with a slight decline in biological yield (van Dobben, 1962). In Victoria, Australia, the increased yield of more recent varieties of oats has been associated almost entirely with increased harvest index, with no significant change in biological yield; it rose from 0.33 in the old variety, Algerian, to 0.41 in the cultivars of 1963 (Sims, 1963). A comparison of wheat cultivars showed similar trends (Table XV). Sims considered the factors in these improved harvest indices to be shorter straw; earlier maturity, permitting better grain filling by drought avoidance; reduced tillering and better tiller survival; and, in oats, larger panicles. A comparison was made at the International Rice Research Institute between traditional tropical rice varieties and the modem cultivars bred in Taiwan and at the Institute (Chandler, 1969). The 6 old varieties were tall, had long leaves, and were negatively responsive to nitrogen because of lodging and internal shading; they had a mean harvest index of 0.36. The new dwarf, erect varieties, shortleaved and highly responsive to nitrogen, had a harvest index of 0.53. Chandler considered that poor tiller survival, because of intense mutual shading, and the

39 1

BIOLOGICAL YIELD AND HARVEST INDEX TABLE XV A Comparison of Three Groups of Cultivars at Melbourne, Australiaa

Group of cultivars

Height (cm)

cv. Federation (released 1901) 4 leading Victorian cultivars, 1968 2 Mexican semi-dwarf cultivars

104 90 15

Tiller sunrival (%) 56 66

70

H.I. 0.28 0.33 0.36

“Sims (1968).

cessation of growth after flowering contributed to the low index of the tall leafy varieties. Finally, comparisons are available from the United Kingdom showing the decreased height and increased harvest index in barley cultivars (Table XVI). The reduction in height, so evident in more recent cultivars, appears to lead to an increased harvest index not only through a reduction in the weight of vegetative parts but also through a direct contribution to grain production. The period of heavy allocation of assimilates to stem growth has been shown to coincide with the period of maximum growth of the ear. Shorter and lighter stems use less carbohydrate and this reduced competition may permit increased ear growth and grain number (Bingham, 1971; Fischer, 1975). While these examples demonstrate that the progress in breeding higher yielding cultivars has been associated with rising values of harvest index, it is again pointed out that no plant breeder has purposively sought this increase. On the contrary, any increase has been an unplanned secondary effort of breeding for grain yield, shorter straw, and earliness. Here lies the point at issue. If breeding for increased grain yield leads to a higher harvest index, is the corollary true-that breeding for a higher harvest index is a useful approach to higher grain yields? We first note the few data on the heritability of harvest index. The most comprehensive study (Rosielle and Frey, 1975a), based on the performance of oats in hill plots, showed similar values for the variance-component heritability percentages for biological yield (59%), harvest index (64%), and grain yield (61%). Singh and Stoskopf (1971), who grew 28 selections of winter wheat over three seasons, found that some gave a consistently high or low harvest index (for example, 0.46, 0.43, and 0.46; or 0.28, 0.35, and .32 over 3 years), but nevertheless that there was an interaction between selections and’ seasons. Fischer (1975) records a correlation of harvest indices between genotypes from one generation to the next of 0.75. The situation seems to be that the harvest index of cereals, like grain yield, is heritable to a considerable degree. And since

w W t3

TABLE XVI The Height and Harvest Index of Barley Cultivars in the United Kingdomsb Hayes (1968) Variety Spratt PlumageArcher Spratt Archer Kenia Proctor Herta Maris Badger Deba Abed Zephyr

Date of Release

PE-1900 1914 1914 1933 1953 1954 1963 1964 1966

Height

V.Td Tall Tall Medium Medium Medium Medium Semidwarf Medium

Watsonet ul. (1958)

Kirby (1967)

0.397

0.389

Cannell (1968)

Height (cm)

H.I.

101 93

0.401 0.487

83

81

0.550 0.5 35

76

0.571

0.380 0.454 0.479

0.432 0.400 0.454

=It is emphasized that comparisons between varieties are valid only within an individual trial because of the great influence of environmental conditions on mean varietal performance. bMainly Cannell(l968) and Hayes (1968).

U 0 2: P

r

*tl

3

393

BIOLOGICAL YIELD AND HARVEST INDEX

it involves not only grain yield components but also innumerable components of biological yield, it is necessarily under polygenic control. It is against this incompletely defined background that the use of biological yield and harvest index in cereal breeding has been advocated or examined (Donald, 1962, 1968; Sims, 1963; Singh and Stoskopf, 1971; Rosielle and Frey, 1975a,b; Fischer, 1975). We here discuss three possible ways in which these characters may be used. 1. The use of parental material of high biological yield or high harvest index. 2. The assessment of breeders’ lines in terms of the changes in biological yield and harvest index at high population density or high fertility. 3. The use of biological yield and harvest index as early generation selection criteria.

1. It is suggested that the selection of parents in breeding programs should be extended to include material of high harvest index, even involving genotypes of lower biological yield and grain yield. Within each of the cereals there may be unexplored sources of “high efficiency of grain production,” overlooked because their production is low. More specifically, there seems to be opportunity to combine a high biological yield with a high harvest index. For example, McEwan (1973) has proposed that the high harvest index of two Mexican semi-dwarf wheats be combined with the high biological yield of current New Zealand cultivars. Their comparative performances were: Ybiol

X

H.1. =

k/PW 2 Mexican semi-dwarf wheats 2 medium-height N.Z. cultivars

1142 x 0.455 = 1294 X 0.331 =

Yg,

WPW 520 429

Preliminary yield tests of hybrid stocks have proved promising. A similar proposal was made for combining the high biological yield of a genotype of field peas with the high harvest index of another (Donald, 1962). A striking contrast between two sorghum cultivars is reported from Nigeria (Goldsworthy, 1970). Farafara, a local variety, flowers in about 130 days and reaches a height of about 4 m. NK 300, an American short-season hybrid, flowers in 100 days or less and attains only about 1.5 m. In 1967, the tall Farafara produced 24000 kg/ha of dry matter, but only 1954 kg/ha of grain, with a harvest index of 0.08. The early maturing, short NK 300 had a total yield of only 9800 kg/ha but a grain yield of 4002 kg/ha, with a H.I. of .41. This extreme difference in harvest index was mainly due to the postheading allocation of assimilates, in Farafara largely to the stems, in NK 300 mainly to the grain. Goldsworthy points out that only long season varieties are suited to the

394

C. M. DONALD W D J. HAMBLIN

climate of this region and he examined the prospect of growing long-season hybrids of high yield potential. A long-season, dwarf hybrid (Samaru Hybrid) gave a biological yield (18,900 kg/ha) greater than that of NK 300, with a harvest index(0.24)greater than that of Farafara. Its grain yield exceeded that of NK 300 by 12%. Further increases would seem feasible, even though a unit weight of grain may need more assimilates than a unit of stem. The identification of parents of high harvest index is of course not possible unless biological yields as well as grain yields are measured. And even then a low or high harvest index may reflect many factors, as in Goldsworthy’s study, where maturity in relation to seasonal weather conditions, spikelet number and survival, structure of the leaf canopy and sink relationships between the grain and the stem all influenced the index. But the use of harvest index does serve to emphasize that some varieties, whether for known reasons or not, have high efficiency in grain production relative to their biological yields. It is clear that harvest index deserves full assessment as a potential criterion in the choice of parents. 2. Stringfield suggested in 1964 that breeding for tolerance to crowding at high fertility was potentially the greatest contribution that maize breeders in the United States could make in the ensuing decade. While there may be debate regarding the extent to which this has been achieved, few would disagree with Stringfield’s premise. Jennings and Herrera (1968) similarly refer to fertilizer and close spacing as “two major criteria of improved rice culture.” Biological yield and harvest index can contribute to this assessment of genotypes at high density and fertility. We have quoted Hanway and Russell’s study which indicates that maize varieties show different responses to increased population density, while the study by Vogel et al. demonstrates the differential changes in these characters in response to nitrogen application. Far greater understanding of potential breeding material is possible through this sort of assessment. The successful cultivar will have increased biological yield at high density or fertility together with a satisfactory maintenanc-,tf minimum decline of harvest index. 3. There are three simple ecosystems in which cereal genotypes are grown by plant breeders, namely as spaced plants, as plants within a mixed community of genotypes and as plants in a dense monoculture, a crop. Many intermediate relationships occur in agronomists’ and plant breeders’ plots but all lie “within the triangle” of these three apical situations. In each of the three systems, success will be achieved by different kinds of plants and one can postulate the characteristics of the cereal ideotype’ likely to give heavy grain production in each set An ideotype is defmed as “a biological model which is expected to perform or behave in a predictable manner within a defied environment” (Donald, 1968).

BIOLOGICAL YIELD AND HARVEST INDEX

395

of circumstances. Our own views are summarized in Table XVII. Others may not agree with all the characters listed, but our main purpose is to emphasize that the successful ideotype in any of the three situations will differ considerably from those in the other two. The characters shown for the isolated plant and the plant in the mixed community are those thought to lead to a high grain yield in the individual plant, while those for the crop ideotype are expected to give high grain yield per unit area. While many plant characters will influence production, those in Table XVII relate particularly to differences in competitive relationships in the three situations. The “isolation ideotype,” A, is a lax, free tillering, leafy plant, able to explore the environment as extensively as possible; the “competition ideotype,” B, is a tall, leafy, free tillering plant, able to shade its neighbors and gain a larger share of nutrients and water; and the “crop ideotype,” C, is an erect, sparsely tillered plant, with small erect leaves. These three ideotypes are so different from one another that one cannot assume that a plant of high grain yield in any one of these situations will be high yielding in the others. This is the plant breeder’s dilemma. His aim is to produce and identify genotypes which will be successful in the crop environment, but because of lack of seed in early generations and his limited land and facilities he must make his choice in other situations and hope that these selections will prove successful as crops. Yet when any plant or line is grown in a planting arrangement or at a density other than those of the field crop, or when it is intermingled with other genotypes, its yield in the test plots will be distorted to at least some degree relative to its own performance and that of other lines in the crop situation. When the plant breeder examines spaced plants or looks at lines or plants in widely spaced rows, he is rating at least partly for the “isolation environment” where lax, free tillering, leafy plants will do well. The distortion will be of different kind in close-planted segregating populations which provide a B or “competition environment” where tall, long leaved plants will succeed. In all segregating populations, the contrast from the C environment is further aggravated by heterozygosity and hybrid vigor, variation in the physical environment from plant to plant and the inability to replicate in space and time (Shebeski, 1967). These disparate plant arrangements, and the lack of criteria to move from one to the other, contribute heavily to the problems of early generation selection. If, for the purpose of this discussion, we disregard secondary criteria for grain production, such as disease resistance or the criteria for “yield realization” (absence of lodging, shattering, etc.), and the “visual criteria” of uncertain meaning, then those which remain for the assessment in early generations of potential grain yield in the crop situation are:

w

\o

TABLE XVII The Characteristics of the Cereal Ideotype for High Grain Production in Each of Three Contrasting Ecosystems ~

The ecosystem: The ideotype: The cereal community:

A. The plant in isolation The isolation ideotype Widely spaced plants or rows

B. The plant in a mixed community The competition ideotype The segregating population or varietal mixture at crop density Weight of grain per Plant

Criterion of yield:

Weight of grain per plant

Competitive ability

Of no significance

Strong competitive ability essential

Habit

Lax or prostrate

Taller than neighbors, especially during early growth

habit, permitting leaf cover over a maximum area canopy

Extensive leaf display for maxh u m light interception

Extensive leaf display to shade neighbors, especially during early growth

C. The plant in a dense monoculture The crop ideotype The crop

Weight of grain per hectare Weak competitive ability; minimum mutual interference among like plants Erect for minimum interference; dwarfness for mechanical strength and improved harvest index Minimum leaf display, sufficient only to form an adequate ear. Minimum interference with foliage of like neighbors

ch

Leaves

Many long, wide, thin, horizontally disposed leaves Rapid and sustained growth of roots to permit water and nutrient uptake a&quate for maximum growth

Tillering Culm survival

Free-tillering High survival

Ear size

Large ears

Many long, wide, thin, horizontally disposed leaves Early rapid growth of roots, exceeding that of neighbors, particularly into soil layers likely to be critical in competition for nutrients or water Freetillering Enough to exploit the residual environment, once dominance has been attained. Large ears

Grain number per ear

Many grains per ear

Many grains per ear

Grain size

Large grains

Large grains

Root system

Few small, erect leaves to give favorable light profile and a higher harvest index Adequate to ensure sufficient exploitation of the soil environment by the whole community of roots by the end of the season

Sparse or nil tillering Full survival

Ear size, grains per ear, and grain size not individually critical. Many florets per unit of biomass and per unit area. High weight of grain per unit of biomass (high harvest index) and per unit area when at optimum density

398

(a) (b) (c) (d)

C. M. DONALD AND J. HAMBLIN

Grain yield itself. The components of grain yield. Vegetative characters (plant form). Harvest index.

At present only the first two of these are widely used. Tie other two, vegetative characters and harvest index, are closely interrelated. (a) It has long been recognized that single plant selection based on grain yield in early generation, segregating populations is ineffective as a means of developing high yielding pure lines and that random selection is likely to be just as effective (e.g., Bell, 1963; Wiebe et al., 1963; McCinnis and Shebeski, 1968). In later generations the degree of efficiency attainable through the measurement of grain yield in rod rows or hill plots is still inadequately established. Frey (1965) demonstrated the high genetic correlation (0.98) between grain yield in hill plots and rod rows in a study with oats in Iowa, but his literature review in the same paper indicates that the relationship between hill plots and field plots or between rod rows and field plots is erratic. Yet performance in field plots is the only criterion of success. Though progress is being made toward identifying higher yielding genotypes, the extent to which this progress is based on precision of testing-as contrasted from precision of experimentation and random advance-remains unresolved. (b) The components of grain yield (ears per plant, grains per ear, and grain size) as selection criteria suffer the disability that they tend to be mutually compensating, so that an advance in any one component tends to be accompanied by negative change in another (e.g., review by Adams, 1967). As a consequence the pursuit of increased grain yields by selection for any individual yield component has usually proved disappointing. (c) A class of criteria now being developed for grain yield depends on vegetative characters, particularly as they relate to the photosynthetic capacity of the canopy and the competitive ability of the plant. Tsunoda (1959, 1962) showed that the types of rice whose grain yields are responsive to high fertility and high density are those with short, sturdy, erect stems and small, thick, erect dark green leaves. Yet they gave low biological yields at low density or low fertility compared to nonresponsive varieties. At the International Rice Research Institute, Manila, these characteristics of Japanese and Taiwanese rices have been incorporated into tropical rices to give highly productive cultivars such as IR8. In that program Jennings and Aquino (1968) proposed that tall, “spreading” types of rice should be eliminated from F2 populations by roguing to leave the short-statured, erect, potentially high yielding, and less competitive segregates. The value of plant form as a selection criterion was also demonstrated in a study with barley at Adelaide (Hamblin and Donald, 1974). There was no correlation between the grain yield of F3 single plants (normal crop density) and

BIOLOGICAL YIELD AND HARVEST INDEX

399

F5 plots (again at crop density), but there were significant negative correlations between F3 plant height and F5 grain yield (-0.55 at high nitrogen) and F3 leaf length and F5 grain yield (4.44). It was the shorter plants with shorter leaves that gave the highest F5 crop yields; these plants could be identified and selected in the F3, despite their lack of superior grain yield in that generation. Criteria relating to plant form thus clearly show promise in cereal breeding, quite apart from such direct physical contributions as that of resistance to lodging. They are intimately involved also in the use of harvest index as a selection criterion (discussed in the next section). (d) We again emphasize that the positive correlation of harvest index and grain yield within existing cultivars does not provide evidence of the value of harvest index as a selection criterion, but there is some evidence that harvest index may have real predictive value in certain situations. Syme (1972) grew 16 cultivars of wheat as single plants in pots in a glasshouse at Toowoomba, Queensland, and measured many characters on each plant. Using a stepwise regression analysis, he related these characters to the mean yield of the same cultivars grown at 63 sites throughout the world in the Fifth International Spring Wheat Yield Nursery (ISWYN). The analysis showed that of the single plant characters, harvest index accounted for 71.7%of the variance of the mean plot yields in ISWYN. When “days from sowing to the emergence of leaf 7” was included, 75.5% of the variance in yield was accounted for and when “grain size” was also included the figure rose to 78.5%. All other characters, including single plant grain yield, made no significant contribution to the regression. Direct correlation between IS%” grain yields and single plant characters gave correlations of 0.10 for grain yield, 0.85** for harvest index, and -0.80** for straw yield. However, it must be noted that the relationship between ISWYN means yields and the yield at individual sites was variable and sometimes weak. Here then were circumstances in which the harvest index of spaced plants (single plants in pots) had clear predictive value for crop yields in the field, while the grain yield of those same spaced plants had none. A study of prediction from performance of spaced plants in the field (60 cm spacing) to grain yields in large plots is reported from Mexico by Fischer (1975). The mean harvest index was 0.45 for the spaced plants and 0.42 for the plots (r = 0.75). Fischer’s results (Table XVIII) showed the superiority of the harvest index of the spaced plants over their grain yield for the prediction of crop performance, with correlations of 0.54 and 0.3 1, respectively. When Fischer based his comparison with plot yields on the harvest index of a central shoot of the spaced plants, the correlation was strengthened to 0.65. Single plants in pots or spaced plants in the field, as in Syme’s and Fischer’s experiments, were in a situation approximating to the isolation environment (A) of Table XVII, where free tillering genotypes are able to achieve high biological

400

C. M. DONALD AND J. HAMBLIN

TABLE XVIII Phenotypic correlations between the Grain Yields of 40 Wheat Genotypes in Large Plots and Various Characters Measured on Spaced Plantsa Character measured on spaced plant

Grain weight/plant Spikeslplant Spikelets/spike Grains/ spikelet Weight per grain Grains/plant Harvest index/plant Harvest index/shootb

Correlation coefficient

0.3 1* -0.11 -0.07 0.28

0.32* 0.04 0.54** 0.65**

nFischer (1975). bDetermined on single central shoots taken from spaced plants.

and grain yields-higher, relative to other genotypes, than they would in a crop situation. As a result, the relationship of grain yield of spaced plants to grain yield in crops is distorted and the correlation is low. On the other hand, harvest index, which depends much more on the performance of the individual culms, tends to be sustained across all culms of a genotype, whether it has many culms (as in spaced plants) or few culms (as in a crop). The harvest index of spaced plants therefore tends to show a lesser genotype/density interaction than does singleplant grain yield, and hence a better relationship to plot grain yield. We turn now to a consideration of the possible value of harvest index as a selection criterion in the “competition environment” (B)-segregating populations at about normal crop density. Jennings and Herrera (1968) showed in segregating rice populations that tall, leafy rices dominated dwarf plant types of high potential yield in pure stands. Though harvest indices are not available, it seems likely that the tall types, with substantially higher reproductive rates, also had higher harvest indices in this situation; if this were so then harvest index, like grain yield, would not have been of value as a selection index in this competitive situation. In a study with barley at Adelaide, F3 plants from a single cross were grown at 8 X 8 cm spacing, a “competition environment” (Hamblin and Donald, 1974). The successful plants were tall and had long leaves; they had the highest biological and grain yields and slightly higher harvest indices. In contrast, in F5 plots of the derived progeny, a “crop environment” (C), quite difference types of plants had the highest grain yields and highest harvest indices, namely the more dwarf, short-leaved types. In this circumstance, neither F3 grain yield nor F3 harvest index was of value for the prediction of F5 grain yield. (As recounted

BIOLOGICAL YIELD AND HARVEST INDEX

40 1

earlier, useful prediction was, however, possible through the negative correlation of F3 plant height and leaf length with F5 plot yields.) Because such contrasting kinds of plants are successful in the “competition environment” and the “crop environment,” the best guide to effective selection in the first environment for the second may well be to follow the injunction by Wiebe el al. (1963), “that the poorest plants should be saved from an advanced hybrid population rather than the good ones when yield is the criterion for Selection”! We believe that the same may prove true when harvest index is the criterion for selection in this particular circumstance (B environment to C environment). Though more evidence is needed, it seems in summary that harvest index may be a valuable criterion for early generation selection among spaced plants (Environment A) where performance per culm is carried forward to the crop situation (Environment C). On the other hand, it seems unlikely to be of value for the prediction of crop grain yields from a segregating population at crop density (Environment B) to the crop situation (C). Here vegetative characters may prove useful. An extensive study of harvest index, grain yield, and biological yield as selection criteria in hill plots was made by Rosielle and Frey (1975a) at Ames, using oat lines derived from a bulk population. They grew 1200 FPderived lines in replicated hill plots in 6 environments (3 sites X 2 seasons) in Iowa. Rosielle and Frey calculated that indirect selection for grain yield through harvest index would be only 43%as efficient as direct selection (i.e., using grain yield as the selection criterion) though they also concluded, despite this lower efficiency, that selection through harvest index would contribute usefully to yield, height reduction, and earliness of maturity and that “lines selected on the basis of harvest index may be agronomically superior to those selected for grain yield.” They then continued with an analysis in which restraints were placed on heading date and height, lateness and tallness being undesirable traits in oat production in lowa (Rosielle and Frey, 1975b). When these characters were held constant, selection for grain yield gave an efficiency only 57% of that attained by unrestricted selection. If, however, harvest index was now added as a secondary selection trait, the efficiency rose to 70%. When less severe restraints were imposed on movements in heading date and height, indirect selection through harvest index was almost as efficient in achieving high yields as was selection for grain yield itself. “This suggests,” wrote Rosielle and Frey, “with heading date and height fured much of the grain yield increase in oats may result from higher harvest index. Also in a population with limited genetic variation for heading date and height (for example in a population that has been subject to intense culling for these traits), harvest index may be useful for indirect selection for yield.”

402

C. M. DONALD AND J. HAMBLIN

This is a most significant study but we nevertheless express certain reservations. Rosielle and Frey assessed the predictability of grain yield and the efficiency of selection among genotypes in hill plots between six environmentsthat is to say, between physical environments, with differences in season or fertility. However, the main problem facing the plant breeder is prediction from one plant arrangement to another, as in prediction from isolated plants to field plots or from hill plots to field plots. Success in the identification in hill plots of genotypes which will be high yielding in hill plots in other physical environments may not ensure success in selecting for the crop situation. We also speculate as to whether Rosielle and Frey’s study may have been in a “competition environment” (B). We do so first because the hill plots were sufficiently closely spaced to make mutual competition between plots likely (30.5 cm spacing between plot centers); and second because there was a positive correlation between height and grain yield (r = 0.50) and between biological yield and grain yield (r = 0.88). If taller, more leafy cultivars did have competitive advantage in the hill plots, it would not follow that selection either through grain yield or harvest index would identify high yielding genotypes for the field crop situation, even though those taller types were again successful in hill plots in other physical environments with similar competitive relationships. V. Concluding Comments

The assessment of cereal genotypes by grain yield alone has contributed much to yield increases during the past century. but this wholly pragmatic procedure has two limitations. First, it is unlikely to lead the breeder toward radical combinations of plant characters able to give grain yields far beyond our present imaginings. Second, it is an uncertain and sometimes misleading criterion for early generation selection, so that superior genotypes may go unrecognized. As a consequence, progress through grain yields has depended on combinations of characters designated largely by chance, combinations which may be better than those of existing cultivars, but which advance toward any ideal combination only by a wandering path with many blind byways. Though biological yield and harvest index may seem blunt instruments for the better analysis of the growth of cereals in the field, their wider use in agronomic research and plant breeding would make a notable contribution to the understanding and advancement of crop performance. The measurement of biological yield must surely be the simplest and most significant step in growth analysis. Here is the integrated account of the exploitation of the environment by the genotype. It reports the capacity of the plant or crop to fix carbon when provided with certain quantities of water, minerals, and atmospheric resources in

BIOLOGICAL YIELD AND HARVEST INDEX

403

a particular time sequence. It provides the biological framework within which the cereal grower must produce his grain. We have discussed several studies that examine the influence of agronomic treatments on yield and harvest index. Commonly, grain yields show complex responses. But biological yield and harvest index each tend to present simpler relationships with treatment and thus to enlighten the whole situation. For example, it becomes clear that there is pressing need, as emphasized by Niciporovic, to develop cultivars which can maintain their harvest indices at high levels of nitrogen supply. Other studies have examined the interaction of biological yield, grain yield, and harvest index with plant density. The present practice in cereal agronomy and breeding-perhaps in all cereals but maize-is to test only at the current commercial density. This is patently invalid, since it presupposes that high yielding cultivars at that particular density will outyield any other combination of plant type and density. A fwed plant density is a restraint which should not and need not be imposed in the development of new cultivars. We must feel no little dismay when a cereal breeder or agronomist classes as equal two cultivars or treatments which each yield 100 units of grain-yet neither knows nor cares that one produces its grain from within 200 units of biomass and the other from within 300. Surely this is a crudity of procedure and thought unacceptable in crop research practice. Yet it is commonplace and even normal. In this situation the observer does not know whether a genotype has failed in terms of its biological yield or its efficiency of grain production-its harvest index. Similarly, any opportunity to combine these traits is lost, simply because they have gone unrecorded. It is generally accepted that tallness in cereals is undesirable because of lodging and depression of ear development. Yet should we accept that the biological yields of shorter cereal crops must fall below those of taller cultivars? We have only to look at temperate grasslands to appreciate the high biological yields attainable in dwarf communities. High biological yields by shorter cereals will call for plants of such form and physiology as to give high photosynthetic rates in crops of high plant density. The further need will be to maintain efficiency (high harvest indices) within these high biological yields, and then to develop still higher indices. All this may seem fanciful. And so it will remain while advances in the basic capacity of cereals to yield grain depend on the measurement of grain yield alone. We have suggested that it may be useful in plant breeding practice to distinguish between “isolation environments,” “competition environments,” and “crop environments” and to recognize that different sorts of plants will give high grain yields in each situation. The few available data suggest that the competition environment presents very difficult problems in plant selection. On the

404

C. M. DONALD AND J. HAMBLIN

other hand, there are indications that plants growing in isolation or at sufficiently wide spacing-though their grain yields are of no value as a guide to yields in a crop environment-may yet have harvest indices which are useful in early generation selection. This prospect is surely worth further pursuit. We appreciate, as Engledow has done for so long, that the analysis of grain production in physiological and biochemical terms must be the master key to ultimate grain yields. But until these more sophisticated guidelines are available to agronomists and plant breeders, we commend biological yield and harvest index as two simple but valuable criteria for the assessment of the performance of cereals.

REFERENCES Adams, M. W. 1967. Crop Sci 7,505. Aspinall, D., Nicholls, P. B., and May, L. H. 1964. Aust. J. Agr. Res. 15, 729. Barley, K. P., and Naidu, N. A. 1964. Aust. J. Exp. Agr. Anim. Husb. 4,39. Beaven, E. S. 1914. Rep. Br. Assoc. 83,660. Beaven, E. S. 1920. J. Farmers’ Club, London Part 6. Bell, G. D. H. 1963. Barley Genet. 1, Prm. Int. Symp., Ist, Wageningen, p. 285. Bhatia, C. R. 1975. Eupbytica 24,789. Bingham, J. 1971. Proc. Eucarpio Congr., 6tb, 1900 7, p. 15. Black, J. N., and Watson, D. J. 1960. Field Crop Abstr. 13, 169. Bond, J. J., Army, T.J., and Lehman, 0. R. 1964. Agron J. 56,3. Cannell, R. Q.1968. J. Univ. Newcastle upon Tyne Agr. SOC.22,3. Chandler, R. F. 1969. In “physiological Aspects of Crop Yield” (J. D. Eastin, F. A. Haskins, C. Y. Sullivan and C. H. M. Bavel, eds.), p. 265. Amer. SOC.Agron., Madison, Wisconsin. Clements, F. E., Weaver, J. E., and Hanson, H. 1929. Carnegie Inst. Wash. h b l . 398. Donald, C. M. 1962.J. Aust. Inst. Agr. Sci. 28,171. Donald, C. M. 1963. Adv. A w n . IS, 1. Donald, C. M. 1968. Eupbytica 17,385. Doss, B. D. 1974.Agmn. J. 66,105. Downey, L. A. 1971. &on. J. 63,569. Engledow, F. L. 1925.5. Agr. Sci. Camb. 15,125. Engledow, F. L., and Wadham, S. M. 1923. J. Agr. Sci. Camb. 13,390. Engledow, F. L., and Wadham, S. M. 1924. J. Agr. Sci. Camb. 14,281. Enyi, B. A. C. 1968.J. Agr. Sci Camb. 7 1 , l . Fairbourn, M. L., Kemper, W. D., and Gardner, H. R. 1970. Agron. J. 62,795. Finlay, K. W., and Wilkinson, G. N. 1963. Aust. J. Agr. Res. 14,742. Fischer, K. S., and Wilson, G. L. 1975. Aust. J. Agr. Res. 26, 11. Fischer, R. A. 1975. Int. Winter Wheat Con$, 1975. Fischer, R. A., and Kohn,G. D. 1966. Aust. J. Agr. Res. 17,281. Frey, K. J. 1965. Eupbytida 14,196. Gardener, C. J., and Rathjen, A. J. 1975. Aust. J. Agr. Res. 26,219. Gerakis, P. A., and Tsangarakis, C. Z. 1969.Agron. J. 61,872. Goldsworthy, P. R. 1970.J. Agr. Sci. Camb. 75,109. Goulden, C . H. 1952. “Methods of Statistical Analysis.” Wiley, New York. Hamblin, J. 1971. Ph.D. Thesis, Univ. of Adelaide, plus derived values.

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Hamblin, J., and Donald, C. M. 1974. Euphyficu 23,535. Hanway, J. J., and Russell, W. A. 1969. Agron. J. 61,947. Hayes, J. D. 1970. Ann. Rep. Welsh Plant Breeding Sfu., and private communication. Jennings, P. R., and Aquino, R. C. 1968. Evolufion 22,529. Jennings, P. R., and Herrera, R. M. 1968. Evolution 22, 332. Jennings, P. R., and de Jesus, J. 1968. Evolufion 22, 119. Joppa, L. R. 1973. Crop Sci 13,743. Kirby, E. J. M. 1967.J. Agr. Sci. Camb. 68,317. Kirby, E. J. M. 1968. J. Agr. Sci Cumb. 71,47. Langfield, E. E. B. 1961. Ausf. PlontBreed. Con$. 1961 (quoted in Donald, 1962). Luebs, R. E., and Laag, A. E. 1967. Agron. J. 59,219. Luebs, R. E., and Laag, A. E. 1969. Agron. J. 61,921. McEwan, J. M. 1973.Proc. Inf. Wheat Genef. Symp., 4fh, 1973, p. 557. McGinnis, R. C., and Shebeski, L. H. 1968. Proc. Int. Wheat Genet. Symp., 3rd, I968 p. 410. McNeal, F. H., Berg, M. A., Brown, P. L., and McCuire, C. F. 1971. Agron. J. 63,908. Morrow, C. E., and Hunt, T. F. 1891. Ill. Agr. Expt. Stu. Bull. 13. Nass, H. G. 1973. Cun. J. Plant Sci 53, 755. Niciporovic, A. A. 1956. “15th Timirjazev Lecture,” Timirjazev Inst. Plant Physiol. USSR Acad. Sci., Moscow. (Trans. Dept. Sci. Ind. Res. Great Britain, 1959). Poostchi, I., Rovhani, I., and Razmi, K. 1972. Agron. J. 64,438. Puckridge, D. W., and Donald, C. M. 1967. Ausf. J. Agr. Res. 18, 193. Ramig, R. E., and Rhoades, H. F. 1963. Agron. J. 55, 123. Rosielle, A. A., and Frey, K. J. 1975a. Euphyricu 24, 121. Rosielle, A. A., and Frey, K. J. 1975b. Crop Sci. 15,544. Roy, R. N., and Wright, B. C. 1973. Agron. J. 65,709. Russell, E. J., and Watson, D. J. 1940. Imp. Bur. Soil Sci., Tech. Commun. 40. Scarsbrook, C. E., and Doss, B. D. 1973. Agron J. 65,459. Shebeski, L. H. 1967.Proc. Can. Cent. WheufSymp., p. 249. Sims, H. J. 1963. Aust. J. Exp. Agr. Anim. Husb. 3, 198. Sims, H. J. 1968. J. Dep. Agr. Vic. 66, 10. Singh, 1. D., and Stoskopf, N. C. 1971. Agron. J. 63,224. Stonier, R. R. 1965. Aust. J. Exp. Agr. Anim. Husb. 5, 317. Stringfield, G. H. 1964. Adv. A p n . 16, 101. Syme, J. R. 1970. Aust. J. Exp. Agr. Anim. Husb. 10,350. Syme, J. R. 1972. Ausf. J. Agr. Res. 23,753. Thorne, G. N., Welbank, P. J., and Blackwood, G. C. 1969. Ann. Appl. Biol. 63,241. Tsunoda, S. 1959. Jup. J. Breed. 9,237. Tsunoda, S . 1962. Jup. J. Breed. 12,49. Turner, H. N. 1959. Aust. J. Agr. Rrs. 10,565. van Dobben, W. H. 1962. Quoted by Holliday, R., and Willey, R. W. 1969. Agr. Progr. 44, 56. Vogel, 0. A., Allan, R. E., and Peterson, C. J. 1963. Agron J. 55, 397. Watson, D. J., Thorne, G. N., and French, S. A. W. 1958. Ann. Bot. 22, 321. Wiebe, G. A., Petr, F. C., and Stevens, H. 1963. MAS.-N.R.C. Publ. 982,546.

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SUBJECT INDEX A Abscisic acid, 181,200 Aegilops bicornia, 270 Aegilops caudata, 211,273,276,219,280, 282,287,288,290 Aegilops cylindrica, 270 Aegilops heldreichii, 270 Aegilops Iongissima, 270 Aegilopsovata, 271, 272, 273,276,280, 281,287,288 Aegilops sharonensis. 270 Aegilops speltoides, 269, 270, 277 Aegilops squarrosa, 271, 213,280, 304 Aegilops umbellulata, 270, 276, 278, 287 Aegilops variabilis, 210 Aegilops ventricosa, 270, 277 Allium cepa, 77 Aluminum, 98 Amaryllis belladonna, 132 Ammi visnaga, 131 Ammonium nitrate, 95,99,106 Ammonium sulfate, 97 Antirrhinum majus, 137 Antitranspirants, 199-201 Apium graveolens, 75 Arabidopsis thaliana, 137 Asparagus, 100 Asparagus officinalis, 136 Atropa belladonna, 136 Avena saliva. 304 Azotobacter, 150 Azotobacter vinelandii, 243,244 B Barley, 85,98,175,186,189,200,295 grain yield, 366, 368-370, 372, 373-374, 382,384,388, 392,400 grain yield physiology, 304, 307, 31 1, 312,313, 314, 321,325. 327,334, 344,348 Bean, 175,187 mung, 96 snap, 84,99,100,102,103 Beet, nitrate accumulation, 75,77,79,81,

82,98,99, 100,102, 103-106, 111-112 sugar, 5,96,98,175,195,330 Beta vulgaris, 18, 75 Biological yield, 3 6 3 4 0 4 Brassica juncea, 99 Brassica vapus, 137 Brassica oleracea var. acephala, 96, 99 Brassica oleracea var. botrytis, 75 Brassica oleracea var. capitata, 15 Brassica oleracea var. italica, 99 Brassica rapa, 75 Broccoli, 99, 100 Bromegrass, 13,17 Brome, smooth, 24 Bromus inermis, 136 C

Cabbage, 75,99, 100 Qlcium, 96 Canary grass, 9 1 reed, 24 Carbon dioxide, nitrate accumulation, 85-86 Carbon dioxide exchange rate, growth estimator, 27-28, 32 Carbon dioxide fertilizing, 201-202 Carrots, 75,98,100, 102,103, 136,137, 145 Carthanus tinctorius, 97 Cauliflower, 75,97,99, 100 Celery, 75,99,100, 102,108 Cell wall regeneration, 134-1 36 Cereal, yield as breeding criteria, 3 6 1 4 0 5 Chloride, 97 4Chlorophenoxyisobutyric acid, 131 Chloroplast, transfer, 145-147 cicer arietinum, 137 citrus limon, 95 citrus sinensis, 137 Clover, subterranean, 25,27 white, 174, 329 Collards, 99 Corn, 76,82,85,97,98, 172, 312, 315 sweet, 110 407

408

SUBJECT INDEX

Corn-Continued see also maize Cotton, 22,175, 198 Cucumber, 107,109 Clrcumis melo var. dudaim, 107 Cucumis sativus, 107, 137 Clrcurbitapepo, 75,76,107 Cytoplasm-nucleo relationships, 267-300

D Dallisgrass, 85 Rn~cuscarota, 75 Denitrification, 253-256,257 Drought resistance, 182-183,185,187

Hardiness, 288 Harvest index, cereal, 3 6 1 4 0 5 Helhnthus argophyllus, 184 Helminthosporium maydis, 133, 293, 294 Hordeum vulgare, 85,304

I Indole-3acetic acid, 131 Inflorescence development, grain, 308-309 Ipomea batatas, 98 Isotope-ratio analysis, 230-239 J Jojoba, 196

E Eggplant, 75 EIeusine coracana, 303,318

K Kale, 96,99

L F Fertilizer, carbon dioxide, 201-202 organic, 94-9599, 113 Festuca arundinacea, 24 Foxtail, Garrison crested, 24

G Genetics, cereal yield as breeding criteria, 361-405 fertility restoration, 274-286 nitrate accumulation, 88,94 nucleo-cytoplasm relationships, 267-300 protoplast modification, 137-1 38 restorer genes, 279-284 root growth variation, 311-312 water use efficiency breeding, 198 Glycine max, 98 Grain growth, 335-340 Grain yield, 363405 comparative physiology, 301-359 Grape, 175 Green panic, 203 Grow rate, measurement, 8-14.21-28

H Haploids, 287 hkplopappus gracilis, 137

Lactuca sativa, 75,107 Leaf area index, 315-317,323,328, 342-34 3 Leaf area, stress estimator, 25-27 Leaf elongation, growth rate estimator, 21-25 Leaf nitrogen, 18-21 Lemon, 95 Lettuce, nitrate accumulation, 75,77,78, 79, 85, 89-90,99,100,102, 107, 108,109 Light, nitrate accumulation, 81-85 Lilium longiflorum, 139 Linum usitatissimum, 137 Lolium multiflorum, 18 Lolium rigidum, 20,23 Lolium sp., 75 Lycopersicon esculentum, 85,107,126

M Magnesium, 96 Maize, 291,293,376,377-378, 382, 394 grain yield physiology, 304,306, 307, 311,316,318,320,322,324,325, 326,327, 329,330, 332, 335,336, 337,338,339,340,343, 349 water deficit, 172,175,178, 179,181, 185,190,203,205

SUBJECT INDEX see also corn Male sterility, 147-148,268-269, 275-279, 290-292,294-296 Manganese, 97 Medicago sativa, 137 Melilotus alba, 137 Migration coefficient, 361-363 Millet, 307,324,330 finger, 305, 318 Italian, 318 Japanese, 332 panic, 305,318 pearl, 305, 306, 318,319, 324 Mineralization-immobilization, 246-249 Mitochondria, 295 Molybdenum, 97 Mustard greens, 99

N Needle grass, green, 24 Nicotiana acuminata, 137 Nicotiana alata, 137 Nicotianaglauca, 137,141,147 Nicotiana langsdorfii, 137,141, 147 Nicotiana noctiflora, 137 Nicotiana paniculata, 137 Nicotiana sylvestris, 137 Nicotiana tabacum, 86,125,136,137, 141, 142,145,151 Nitrate accumulation, vegetable, 71-119 Nitrate, toxicity, 72-74 Nitrfication inhibitors, 95-96 Nitrite poisoning, sources, 74-76 Nitrite, toxicity, 72-74 Nitrogen, 174,194, 309,313,315,320, 337,339 cereal yield, 382-389 leaf, 18-21 plant recovery, 249-253 stress in plants, 1-35 supply and accumulation, 94-96 tracers for soil and fertilizer research, 219-266 Nitrogen fixation "NeNiched, 243-246 protoplast research, 150-152 Nitrosamines, 76 Nucleo-cytoplasmicrelationship, 267-300 Nutrient deficit, water deficit interaction, 1 9 3 195

409

Nutrient stress, 6-7 0

Oat, 97,366,372,390,391 grain yield physiology, 304, 307, 308, 311,318,319,321,325,334 Onion, 77,99,100 Oryza glabem'ma, 305 Oryza indica, 389 Oryza japonica-indica, 389 Oryza sativa, 305 P Panicurn maximum, 203 Panicurn miliaceum, 305, 308, 318 F'arsley, 75 Paspalum dilatatum. 85 Pea, 98,100,171,188 Penniseturn typhoides, 305, 318 Petroselinum crispurn, 75 Petunia, 129,144 Petunlb hybrida, 125,136,137,145,141, 148 Petunia parodii, 137, 142 Ahalaris arundinacea, 24 Phalaris sp., 9 1 Ahalaris tuberosa, 24, 179 Pharbitis nil, 137 Phaseolus aureus, 96 Ahaseolus vulgaris, 84,137 Phenylmercuricacetate, 199-200 Phosphorus, 96,174,313, 314, 315 stress estimating, 31 Photoperiod, 278, 306,307-308, 309 Photosynthesis, 291 carbon dioxide exchange rate, 27-28 comparative physiology, 317-327, 344-347 water deficit and, 176-178,181,204 Physiology, grain yield, 301-359 Pisum sativurn, 98,137 Plant water deficit, development of, 164-166 Population density, cereal yield, 375-378, 394 Potassium, 96,194-195,313, 314,315, 320 Potassium nitrate, 95 Potato, 99,100,107,109,110,198

410

SUBJECT INDEX

Rotoplast research, progress, problems and prospects, 121-160 Pumpkin, 76

R Radish, 75,84,96,99,100,107,109

Ranunculus sceleratus, 137 Raphanus sativus, 75,101 Respiration, water deficit, 178-179

Rhizobium, 150 Rhubarb, 100 Rim, 290,374-375, 380,389, 390,398 grain yield physiology, 303, 305,306, 307,309,311, 315,316, 318,319, 324,325,326, 327,333, 334,337, 339,340,341, 343,345, 346,341, 348, 349 Root growth, cereal, 310-313 Root, nutrient use, 313-315 Rye, 289,304,307,311,321,334 Russian wild, 24 Ryegrass, 85,95,96,91 annual, 16,17,18,20,21 Italian, 5 perennial, 174,194

Sorghum vulgare, 97 Sorghum vulgare var. sundanense, 98 Southern Leaf Blight, 293 Soybean, 98 Spectrometry, emission, 233-235 IYUSS, 231-233 Spinacia oleracea, 75,107 Spinach, nitrate accumulation, 75,81,83, 84,85,88-89,95,96.99,100,101, 102,103,107,108,113 Squash, 107,109 summer, 75 Statistical methods, soil classification, 37-70 Stomatal conductance, 175-176,185,194, 199 Stress, nitrogen, 1-35 water, 22, 161-217, 309,326 Sulfur,96 Sugar-cane, 133,137 Sundangrass, 97 Sunflower, 172,175,181,187,189,329 silver, 184 Sweet melon, 107,109 Sweet potato, 98,100,102,103

T S

Saccharum officinaanrm, 141 Saccharum spontaneum, 141 Safflower, 97

Secale cereale, 210,277,278, 289, 304 Setaria, 308,332 Setaria italica, 318 Simmondsia chinensis, 196 Sodium, 97 Soil, ordination of, 54-59 Soil classification, statistical methods, 37-70

Sokanum melongena, I5 &blanum nigrum, 126 Sokanum tuberosum, 99,107 Sorghum,97,115,176,187,190,291,376, 380-381,385, 393 grain yield physiology, 304, 307, 315, 318, 319,324, 325,327,329,330, 333, 334,335,336,331,340,349 Sorphum bicolor. 97.304.311.312 &&hum sudanense, 331 .

I

Temperature, 278,309,310,313,337 nitrate accumulation, 84-85 Tiering, 347-348,382 Tobacco, 86,129,136,148,175 Tobacco mosaic virus, 148-150 Tomato, 85,86,97,98, 100, 107, 109 water deficit, 170-171,178,181 T ~ a n ~ c i n acid, ~ m i131 ~ Transformation, 144-145 Translocation, 329-335 water deficit and, 179-180 Transpiration, 313 Wfolium subterraneum, 16 WlIium hamtschaticum, 139 Wticum aestivum, 84,268,269,270,211, 273,214,275,216,278,279,280, 281,285,289, 304 Wticum ararticum, 271,274,271 Wticum boloticum, 270,273, 274,275, 277,289 Piticum compacturn, 274,276,279,280 Wticum dicoccoides, 211,273,276,280

SUBJECT INDEX Wticum dicoccum, 273 miticum dutum, 268,269,270,272,275, 216,280,288 Wticum monococcum, 270 Wticum spelta, 273, 216,280,282,284 Wticum timonovum, 271,277 Wticum timopheevi, 268,269,270,271, 272,273,274,216,280,281.284, 287,288 Wticum zhukovskyi, 211,277,284 Tungsten, 97 Turnips, 75

U Ultraviolet irradiation, 133 urea, 95

V Vanadyl sulfate, 98 Vegetables, nitrate concentrations in, 98-1 13 Vernalization, 306-307 Viciafaba, 125 Kcih hajastana. 137 Kgna sinensis, 131 Virus, uptake of, 148-150

W Water availability, cereal yield, 378-382, 384 Water, crop deficit, 161-217 nitrate assimilation, 86-88

A 8 C D E

6 7 B 9 O

F

1

C 2

H 3

I S

1 5

41 1

potential. 166-170 stress, 22,161-217,309,326 use efficiency, 195-202 Wheat, 84,96,98 biological yield, 364, 366, 310, 372, 376, 379-380,382-384,386, 389, 393, 399-400 grain yield physiology, 303-304. 306, 307, 308,309, 311,312, 318,319, 320-321,322,326,329,331,332, 333,334,335,336,337,339,340, 342,343,344,345-346, 347,348 nitrogen stress, 9-13,14-15,16, 17,19, 21,26 nucleo-cytoplasmicrelationship, 267-300 water deficit, 171,175,179,182,188, 189,190-192,194,200 Wheatgrass, crested, 24 intermediate, 24 western, 24 X X-ray irradiation, 133

Y Yield, nitrate nitrogen relation, 5 Yield compensation, 192-193

2 Zea maize, 76,133,142, 304

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