Advances in Agronomy, Volume 45

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ADVANCES IN

AGRONOMY VOLUME 45

This Page Intentionally Left Blank

ADVANCES IN

AGRONOMY Prepured in Cooperation with the AMERICAN SOCIETY OF AGRONOMY

VOLUME 45 Edited by Nyle C . Brady Uniied Nutions Development Programme Wushington, D . C .

ADVISORY BOARD G . E. HAM

R. J . KOHEL

G. H . HEICHEL

S . MICKELSON

H . G . HODGES

R. H . MILLER

G . L. HORST

K . H . QUESENBERRY

D. E. KISSEL

C. W. STUBER

E. L. KLEPPER

N . L. TAYLOR

ACADEMIC PRESS, INC. Harcourt Brace Jovanovich, Publishers San Diego New York Boston London Sydney Tokyo Toronto

This book is printed on acid-free paper. @

COPYRIGHT 0 1991 BY ACADEMIC PRESS, INC. All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher.

ACADEMIC PRESS, INC. San Diego, California 92101 United Kingdom Edition pubfished by ACADEMIC PRESS LIMITED 24-28 Oval Road. London NWI 7DX

LIBRARY OF CONGRESS CATALOG CARD NUMBER:

ISBN 0-12-000745-2

(alk. paper)

PRINTED IN THE UNITED STATES OF AMERICA 91

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CONTENTS CONTRIBUTORS .............I........................................................... PREFACE. . . . . . . . . . . . . . . . . . . . . I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . .

ix

xi

NITROGEN DYNAMICS AND MANAGEMENT IN RICE-LEGUME CROPPING SYSTEMS

R. J. Buresh and S. K. De Datta 1. 11.

111. IV. V. VI . VII.

VIII. IX.

............................................... Rice Soils ......................... Legumes in Rice-Based Cropping Systems ................ ....................... Effect of Legumes on Soil Nitrogen ..................... Accumulation of Legume Nitrogen . ........................... Contribution of Legume Nitrogen to Rice .................................. Effective Management of Legume Nitrogen Conclusions and Research Needs ....

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

2 3 8 13 16 27 42 44 50 52

PLANT GENETIC RESOURCES: SOME NEW DIRECTIONS

J . T. Williams I. 11. 111. IV. V.

VI.

......................................... ies ... . .......... . ......... Areas of Research Which Impact Plant Genetic Resources Work ... ...... Sustainability ................. ........... ............ . ......... Current New Directions in Germplasm Management Concluding Remarks .............. .... . ........ . ............ ............................................... References ....... . ....

61 62 66 81 86 88 89

LONG-TERM IMPACTS OF TILLAGE, FERTILIZER, AND CROP RESIDUE ON SOIL ORGANIC MATTER IN TEMPERATE SEMIARID REGIONS

Paul E. Rasmussen and Harold P. Collins 1. 11.

Introduction ............ ........., , ., .......... ............. ....,.... ...................... Tillage Effects on Soil Organic Matter ............................................. V

94 99

vi

CONTENTS

111.

IV . V. VI . VII . VIII . IX .

X.

Fertilizer Effects on Soil Organic Matter ......................................... .......... Organic Residue Effects on Soil Organic Matter Organic Matter and Microbial Biomass ........................................... Management Effects on Physical Properties ............................. Cultivation and Future Change in Soil Organic Matter ........................ Impact of Soil Erosion ................................................................. Predicting Soil Organic Matter Turnover ......................................... Summary .................................................................................. References .................... ..........................................

102 105 114 119 120 121 123 129 131

EFFICIENT MANAGEMENT OF LEGUMINOUS GREEN MANURES IN WETLAND RICE

Yadvinder Singh. C . S. Khind. and Bijay Singh I. I1 . 111. IV . V. VI . VII . VIII .

IX . X. XI . XI1 .

Introduction ............................................................................... Green Manure Crops for Wetland Rice ... .............................. Biomass and Nitrogen Accumulation in G nures ..................... Time and Depth of Incorporation of Green Manures .......................... Yield Responses of Wetland Rice to Green Manuring ....... Nitrogen from Green Manure Crops ............................................... Transformations of Green Manure Nitrogen in Wetland Rice Soils ....... Effect of Green Manuring on Availability of Plant Nutrients Other Than Nitrogen ................. ............. .............. Effect of Green Manuring on Soil ies .................................... Green Manuring and Reclamation of Saline Alkali Soils ...................... Residual Effects of Green Manures Applied to Wetland Rice . Conc1us ions ............................................................................... References ............................. ............................

136 137 143 149 151 158 162 166 170 175 177 179 182

ADVANCES IN DISEASE-RESISTANCE BREEDING IN CHICKPEA

K . B . Singh and M . V . Reddy I. I1. 111.

IV . V. VI . VII . VIII .

Introduction .............................................................. Sources of Genetic Variability ....................................................... Breeding Techniques ................................................ Disease Resistance ...................................................................... Breeding for Multiple Disease Resistance ...................... Annual Wild Cicer Species as a Potential Source of Genes for Resistance ............................................................. Resistant Cultivars in Disease Management ............................. Conclusions and Future Needs .......................................... References ........... ..............................

191 192 193 193 215 216 217 218 219

CONTENTS

vii

GENETICS OF RESISTANCE TO INSECTS IN CROP PLANTS

Gurdev S . Khush and D . S . Brar I. I1 .

Introduction ...............................................................................

111.

............................................................ ................. ............... Sorghum ................................................................................... Barley ...................................................................................... Cotton ........................... ................................................. Fruits .......................................................................................

IV . V. VI . VII . VIII . IX . X. XI . XI1. XI11.

......

Vegetables . Forages and Legumes .................................................................. Tagging Insect Tolerance Genes with Molecular Markers Genetic Engineering and Insect Tolerance ....................................... Conclusions ........ ........................ ................. References ................................................................................

224 226 231 239 243 246 248 252 256 259 262 263 263 265

AGROFORESTRY IN ACID SOILS OF THE HUMID TROPICS

L . T . Szott. C . A . Palm. and P . A . Sanchez 1. 11. I11. IV . V. v1.

Introduction ............................................................................... Alley Cropping ................................. ........ Managed Fallows ........................................................................ Fruit Crop Food Production Systems .......... Research Needs .......................................................................... Summary .............................................. References .......... ....................................................

275 279 289 294 297 299

300

ASSESSMENT OF AMMONIA VOLATILIZATION FROM FLOODED SOIL SYSTEMS

Gamani R . Jayaweera and Duane S . Mikkelsen Introduction ........... .................................................. Theoretical Aspects .............................. Theory of Ammonia Volatilization ................................................. Factors Affecting Ammonia Volatilization Methods of Measuring Ammonia Volatilization ................................. Models for Predicting Ammonia Volatilization Epilogue ........................................... References ................................................................

303 305 308 310 331 332 353 354

INDEX .....................................................................................

357

I. I1. I11. IV . V. VI . VII .

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

D. S. BRAR (223), International Rice Research Institute, 1099 Manila, Philippines R. J . BURESH ( I ) , Agro-Economic Division, International Fertilizer Development Center, Muscle Shoals, Alabama 35662 HAROLD P. COLLINS (93), U . S . Department of Agriculture, Agricultural Research Service. Columbia Plateau Conservation Research Center, Pendleton, Oregon 97801 S. K. DE DATTA ( I ) , Agronomy-Physiology-AgroecologyDivision, International Rice Research Institute, Manila, Philippines GAMANI R. JAYAWEERA (303), Department of Land, Air and Water Resources, University of California, Davis, California 95616 C . S . KHIND (135), Department of Soils, Punjab Agricultural University, Ludhiana 141 004, India GURDEV S. KHUSH (223), International Rice Research Institute, 1099 Manila, Philippines DUANE S . MIKKELSEN (303), Department of Agronomy and Range Science, University of California, Davis, California 95616 C. A. PALM (275), Tropical Soils Research Program, Departments of Forestry and Soil Science, North Carolina State University, Raleigh, North Carolina 27695 PAUL E . RASMUSSEN (93), U.S. Department of Agriculture, Agricultural Research Service, Columbia Plateau Conservation Research Center, Pendleton, Oregon 97801 M. V. REDDY (191), lnternational Crops Research Institute for the Semi-Arid Tropics (ICRISAT),Patancheru, Andhra Pradesh 502 324, India P. A. SANCHEZ (273, Tropical Soils Research Program, Departments of Forestry and Soil Science, North Carolina State University, Raleigh, North Carolina 27695 BIJAY SINGH ( 1 3 9 , Department of Soils, Punjab Agricultural University, Ludhiana 141 004, India K . B . SINGH (191), International Center for Agricultural Research in the Dry Areas (ICARDA),Aleppo, Syria YADVINDER SINGH (135), Department of Soils, Punjab Agricultural University, Ludhiana 141 004,India

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CONTRIBUTORS

L. T. SZOTT' (275), Tropical Soils Research Program, Departments of Forestry and Soil Science, North Carolina State University, Raleigh, North Carolina 27695 J . T. WILLIAMS' (61), International Fund for Agricultural Research (IFAR), Arlington, Virginia 22209

' Present address: Centro Agronomico Tropical de Investigacidn y Ensenanza (CATIE); Turrialba, Costa Rica. * Address correspondence to 161 1 North Kent Street, Suite 600; Arlington, Virginia 22209.

PREFACE This volume of Advances in Agronomy is the 25th and final volume of the serial that I have had the privilege of editing. In total, these 25 volumes have accommodated 195 review articles, as well as the index for the first 30 volumes (Volume 32). Topics have ranged from the chemistry, physics, biology, and conservation of soils to biochemical genetics, plant breeding, crop husbandry, crop physiology, cropping systems, and the nutritive value of crops. About 20,000 research papers were cited by the 339 authors who helped prepare these reviews. Tens of thousands of agronomists and soil and crop scientists from around the world have benefitted from these extensive review efforts. Special thanks are due to the 339 scientists and educators from 24 countries who prepared these review articles. About half of the authors were associated with institutions in the United States. Approximately one-third of these were based at institutions of the federal government and two-thirds at universities. Forty of the other authors were at Australian institutions, 20 at institutions in the United Kingdom, 19 in other European countries, and 15 in Canada. Thirty-two were associated with international agricultural research centers located mostly in the tropics. Nineteen of the authors were located at national institutions in developing countries. These numbers all emphasize the international character of Advances in Agronomy and the degree to which it has attracted scientists from throughout the world. Another group of scientists and educators have contributed greatly to this serial-those who were kind enough to advise on topics for review and on potential authors for these reviews. The advisors include 42 scientists who over the years have served on the Advisory Board of the serial. The Board of Directors of the American Society of Agronomy also made valuable suggestions, as did numerous scientists, educators, and administrators from countries around the world. Their advice was invaluable in seeking out qualified scientists and scholars to prepare articles for this serial. Articles in Volume 45 continue the pattern of the previous 24 volumes. Topics of international interest are covered by scientists from five different countries. Each of these articles focuses on topics having implications for long-term sustainable agriculture. Three emphasize nitrogen systems of wetland areas. Three others emphasize the role of genetic resources, xi

xii

PREFACE

especially as a means of managing pests by other than chemical means. Two articles emphasize the role of soil and crop management systems on soil properties and productivity. Finally, thanks are due to Academic Press, the publishers of Advances in Agronomy, for permitting me to serve for nearly 25 years as editor of this important serial. I wish them and the new editor, Dr. Donald L. Sparks, the best, as this important serial continues. Its relevance today fully matches that which prevailed 25 years ago. NYLEC. BRADY

ADVANCES IN AGRONOMY, VOL. 45

NITROGEN DYNAMICS AND MANAGEMENT IN RICE-LEGUME CROPPING SYSTEMS R. J. Buresh' and S. K. De Datta2 '

Agro-Economic Division International Fertilizer Development Center Muscle Shoals, Alabama 35662 * Agronomy-Physiology-Agroecology Division International Rice Research Institute Manila, Philippines

I. Introduction 11. Nitrogen Dynamics in Rice Soils 111. Legumes in Rice-Based Cropping Systems A. Food Legumes IV .

V. VI.

VII. VIII.

IX.

B. Green Manure Legumes C. Dual-Purpose Legumes Effect of Legumes on Soil Nitrogen A. Conservation of Soil N B. Loss of Soil N Accumulation of Legume Nitrogen A. Symbiotic N Fixation B. N Removal with Legume Grain Contribution of Legume Nitrogen to Rice A. Mineralization of Legume N B. Belowground Legume N C. Losses of Legume N D. Residual N Effects E. Other Factors Contributing to Rice Yield Effective Management of Legume Nitrogen Integrated Nitrogen Management A. Loss of Fertilizer N B. Effective Use of N Fertilizer Conclusions and Research Needs References 1 Copynght 0 1991 by Academic Press. Inc. All rights of reproduction in any form reserved.

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R. 3. BURESH AND S. K.DE DATTA

I. INTRODUCTION More than half of the world’s population of over 5 billion live in Asia, where rice (Oryza sativa L.)is the staple food of millions of poor people. To meet the future demand for rice, the International Rice Research Institute (IRRI, 1989) estimated that the world’s annual rice production must increase from 458 million t in 1987 to 556 million t by 2000 and to 758 million t by 2020-a 65% increase in 33 years (1.7% per year). This increase in rice production can only be possible if soil and water resources and production inputs are used more efficiently in the future. Rice production increases must attain long-term sustainability with no adverse environmental impact. Sustaining the necessary rice yield and production increases in the future will require increased irrigated area and water use efficiency, more area planted to fertilizer responsive modern varieties, and development of cost-efficient fertilizer use technology. Nitrogen is the nutrient most limiting rice production worldwide. In Asia, where more than 90% of the world’s rice is produced, about 60% of the N fertilizer consumed is used on rice (Stangel and De Datta, 1985). An estimated 24% of the increase in Asian rice production from 1965 to 1980 was attributed to use of fertilizer, mainly N (Barker er al., 1985). Despite past gains in rice production through increased use of industrial N fertilizer, research has demonstrated that industrial N fertilizers generally are not efficiently utilized by rice and are prone to high losses as N gases (De Datta and Buresh, 1989). Recent observations of stagnant or declining yields under continuous rice cropping with high levels of industrial N fertilizer (Flinn and De Datta, 1984) have raised concerns about the longterm sustainability and possible adverse environmental impacts of monoculture rice receiving high inputs of industrial N fertilizer. Legumes, with their adaptability to different rice-based cropping patterns and their ability to fix N2, may offer opportunities to increase and sustain productivity and income in rice-based cropping systems. Food legumes provide protein for human and animal nutrition as well as economic benefits to farmers because of the high market value for legume grain and the generally declining real price of rice. Green manure legumes, forage legumes, and residues from food legumes can supply N to rice, improve soil physical and chemical properties, and decrease pests and diseases of rice. Rice is grown in irrigated and rainfed lowlands, which are characterized by bunded fields with surface water accumulation, and in uplands, which are characterized by naturally well-drained soils with no surface water accumulation. Worldwide, irrigated lowland rice accounts for about 50%

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

3

of the total rice area and 70% of the total rice production (IRRI, 1989). A legume can often be included in a rice-rice sequence when climatic conditions, such as cold temperature, and availability of water are not suitable for rice production. Rainfed lowland rice accounts for about 30% of the total rice area and about 20% of the total rice production (IRRI, 1989). In many rainfed lowlands, soil water conditions after a wet-season rice crop allow growth of a short-duration legume but not a cereal. Upland rice is smaller in worldwide importance, accounting for about 13% of the land area and 5% of the production (IRRI, 1989). Legumes can be intercropped, relay cropped, or grown in sequence with upland rice (Gupta and O’Toole, 1986). Leguminous trees and shrubs offer potential in erosion control and maintenance or buildup of soil fertility in acid uplands and sloping lands. Deepwater and tidal wetland rice comprise the remaining 7% of the world’s rice area (IRRI, 1989). In many deepwater rice areas, legumes can be grown during the interval between onset of monsoon rain and soil inundation (Kupkanchanakul et al., 1988). Nitrogen gains, losses, transformations, and fertilization in continuously flooded lowland rice fields have been extensively researched and reviewed (De Datta and Patrick, 1986; De Datta and Buresh, 1989). In contrast, little attention has been given to N transformations and losses over the longer term in lowland rice fields, which undergo soil drying between rice crops and soil flooding during rice cropping. Nitrogen accretion and contributions from leguminous green manures in rice-based cropping systems have attracted increased research interest. However, less attention has been paid to the role of food legumes in N cycling, gains, and losses in rice-based cropping systems, even though food legumes are more commonly grown than green manures in tropical ricelands. The objective of this article is to review ( 1 ) N dynamics in lowland rice fields with emphasis on how N dynamics are influenced by typical soil drying and wetting cycles, (2) the influence of legumes on soil N transformations and N accretion in rice-based cropping systems, (3) the N contribution of legumes to rice, and (4) the integrated management of legume N and industrial fertilizer N for rice.

II. NITROGEN DYNAMICS IN RICE SOILS Lowland rice soils typically undergo alternate saturation and drying. Soils are saturated for at least part of the time during production of rice, but during intervals between rice crops, the soil usually dries and becomes

4

R. J. BURESH AND S. K. DE DATTA

aerated. At this time, either the soil is left fallow or upland crops are grown. In Asia, lowland rice soils are frequently flooded before plowing and harrowing for rice production. The process of tillage at soil saturation, referred to as puddling, destroys soil aggregates, reduces downward water flow and loss of nutrients by leaching, and restricts gaseous exchange between the soil and the outer atmosphere (Sharma and De Datta, 1986). The rice crop is established either by transplanting or by broadcasting germinated seeds on flooded or saturated soil. In environments with a reliable irrigation supply and low percolation, puddled soils typically remain continuously saturated until just before rice harvest. In rainfed environments and imgated environments with inadequate or irregular water supply, the soil can undergo alternate drying and rewetting during rice growth. An alternative method of rice crop establishment, common in the United States, is to sow germinated seeds onto nonpuddled, flooded soil. The rice fields are irrigated and essentially left flooded throughout rice growth (Westcott and Mikkelsen, 1988). Some rainfed lowland rice in the tropics and much of the irrigated rice outside Asia are sown on aerobic, nonpuddled soil. Rice grows as a dryland crop until sufficient rainwater accumulates for soil submergence or until permanent flooding by irrigation. In aerobic soils, ammonium formed from mineralization of organic N or from N fertilizer can be nitrified to nitrate, which can accumulate in the soil or be used by plants. When aerobic soils are flooded, soil oxygen is rapidly depleted and soil nitrate is prone to loss by denitrification and leaching. In flooded soils, the conversion of ammonium to nitrate is restricted by the limited supply of soil oxygen; hence, ammonium is the form of mineral N that accumulates. At the end of a flooded rice crop, soil nitrate is normally negligible and soil ammonium, the dominant form of mineral N , is typically low because of N uptake by rice (Fig. 1). Subsequent drying of the soil favors conversion of ammonium N formed by mineralization to nitrate N. Soil water status (Linn and Doran, 1984), tillage (Dowdell et al., 1983), and weed growth (Buresh et al., 1989) influence the accumulation of soil nitrate. Intermittent rains can stimulate N mineralization and nitrate formation (Birch, 1958). In a survey of 28 Philippine lowland soils, nitrate N before flooding for rice ranged from 5 to 39 mg/kg and averaged 13 mg/kg (Ponnamperuma, 1985). In a greenhouse study, Ventura and Watanabe (1978) reported nitrate N levels of 19 to 35 mg/kg after a dry-season fallow. Cropping with rice during the dry season decreased nitrate N to 3 mg/kg before the subsequent wet-season rice crop.

5

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS Soil aerotion status Anaerobic

1

7

Rice

N concentration

,-N

loss

FIG. 1. Inorganic N dynamics in lowland rice soils as affected by soil aeration status.

Buresh et al. (1989) showed that substantial quantities of nitrate can accumulate during the dry season in a mung bean (Vigna radiata [L.] Wi1czek)-fallow-lowland rice sequence in the Philippines (Fig. 2). At maturity of late wet-season rice in January, no nitrate was present in the top 60-cm soil layer. During the subsequent dry-season mung bean crop, 25 and 18 kg nitrate Nlha accumulated in 1986 and 1987, respectively. Additional nitrate N accumulated during the fallow following mung bean; 52 and 77 kg nitrate N/ha were present in early June immediately before flooding by imgation for wet-season rice. The soil nitrate rapidly disappeared after flooding. Other researchers (Strickland, 1969; Bacon et al., 1986) have similarly reported rapid disappearance of nitrate after soil flooding. An incubation study with "N-labeled nitrate incorporated into flooded soil from the study site for the research shown in Fig. 2 revealed that the added nitrate completely disappeared after 9 days. Only 5% or less of the added "N-labeled nitrate N remained in the soil as ammonium N and organic N , indicating that nitrate assimilation and dissimilatory reduction to ammonium were negligible (Buresh et al., 1989). Denitrification and leaching appeared to be the mechanisms for nitrate disappearance.

6

R. J. BURESH AND S. K . DE DATTA

FIG.2. Nitrate N in the top 60-cm soil layer during a mung bean-weedy-fallow-lowland rice sequence in the Philippines. (Adapted from Buresh er al., 1989.)

Buresh et al. (1989) found that soil nitrate N before flooding for wetseason rice correlated inversely with dry matter and N accumulation of weeds (Fig. 3). Other research in the Philippines has shown significantly lower soil nitrate levels in weedy fallow than in weed-free fallow before wet-season rice (unpublished IFDUIRRI collaborative research). Other studies demonstrated a higher yield of wet-season rice following weedy fallow than following weed-free fallow (adapted from IRRI, 1986, p. 404): Grain yield (t/ha) ~

Prerice treatment

No applied N

35 kg N/ha

Weedy fallow Weed-free fallow

3.2 2.8

3.9 3.3

Lower soil nitrate and higher rice yield following weedy rather than weed-free fallow suggest that uptake of nitrate N by weeds conserves soil N from subsequent loss after soil flooding. Nitrate N taken up by weeds is

7

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS Nitrate N (kg/ha)

*\I

Y =95 -0.56X

r = - 0.80'"

30

Y = 103 -1.89X r = -0.84* *

0

1

1

I

1

I

I

50

70

90

110

15

20

0

25

.

30

35

Weed N (kg/ha)

Weed dry matter (g/m')

FIG.3. Relationship of nitrate N in the top 60-cm soil layer to weed dry matter and weed N before soil flooding for wet-season rice in the Philippines. (From Buresh er al., 1989.)

recycled to the soil when weeds are incorporated during land preparation. The relatively low accumulation of N by weeds growing in tropical ricelands before wet-season rice (Table I) and the appreciable soil nitrate even at the highest level of weed growth in Fig. 3 suggest that substantial nitrate N may still accumulate and be lost in traditional weedy fallow-wet-season rice cropping systems. The weed biomass incorporated before rice might be an important source of mineralizable N to flooded rice. Rerkasem and Rerkasem (1984),

Table I

Dry Weight and N Accumulation of Weeds in Unweeded Fallow Plots before Land Preparation for Wet-Season Rice at Los Baios, Philippines Aboveground dry weight (t/ha) 1.6 1.5

2.1 2.1 1.4

1.7 2.1 2.5

N accumulation (kdha) 25 21 18 20 I1 12 20 29

C/N ratio

31

Reference IRRI (1985, p. 413) IRRI (1986, p. 403) IRRI (1986, p. 416) John (1987) Alam (1989) Alam (1989) Alam (1989) R. J. Buresh et al. (unpublished)

8

R. J. BURESH AND S. K. DE DATTA

for instance, observed in a heavily weed-infested rice field in Thailand that removal of weeds before the rice crop resulted in a subsequent rice yield of 2.6 t/ha and a strong response of rice to N fertilizer. Incorporation of weeds increased yield of unfertilized rice by 40%, and the response to N fertilizer was less pronounced.

Ill. LEGUMES IN RICE-BASED CROPPING SYSTEMS Legumes are grown in rice-based cropping systems for protein, oil, fodder, green manure, and fuel production. In irrigated environments of the tropics and subtropics, legumes can be grown in rotation with one or more rice crops per year. In subtropical and temperate regions, where the growing period for rice is restricted by low temperatures, leguminous green manures can be grown as the winter crop. Rice growing areas in tropical Asia are typically monsoonal with a distinct wet and dry season. In rainfed lowlands, which comprise about 40% of the total rice area in South and Southeast Asia, only one rice crop is normally possible per year. Production of a second rice crop is limited to regions with a supplemental water supply or a long, reliable rainy season. Food legumes can be grown in the postmonsoonal period following rice when soil water is sufficient (Zandstra, 1982). A. FOODLEGUMES Food legumes are a rather minor crop in Asia as compared with cereals. Yet, they are an important component of Asian farming systems, both in terms of human and animal nutrition and as a source of biological N. The ability of legumes to fix N2 enables them to grow on soils with low plantavailable N and to produce high-protein seed and N-rich plant residues. Yields of food legumes are generally low because they are often grown with low management and inputs under marginal production conditions, in which cereals perform poorly or cannot grow. At least 18 food legume species are considered important at various locations in Asia (Byth et al., 1987). The major food legumes grown on ricelands include soybean (Glycine mux [L.] Merr.), mung bean, groundnut (Aruchis hypogaea [L.]), and cowpea (Vigna unguicutafa [L.] Walp.). Soybean is an important crop on ricelands in China, Indonesia, Vietnam, Thailand, and India (Carangal, 1986; Carangal et a / . , 1987). Mung bean is an important crop in India,

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

9

Thailand, Burma, and Indonesia (Singh, 1988). Cowpea is an important food legume in Sri Lanka (Singh, 1988). It performs better than other food legumes on highly acid soil (Pandey and Ngarm, 1985). In northern India, the production of irrigated mung bean as a third crop between wheat and rice is increasing (Singh, 1988). However, throughout tropical Asia most food legume production on lowland rice fields is under rainfed conditions immediately after an irrigated or rainfed rice crop (Chandra, 1988; Brotonegoro et af.,1988). When grown after wet-season lowland rice, legumes can encounter excess water during the vegetative phase and water deficit during the reproductive phase (Fig. 4). Postrice legumes depend primarily on residual soil water, and their roots may follow a receding water table (Timsina, 1989). Mung bean is more sensitive to reproductive-phase and full-season water deficit than are cowpea and soybean (Pandey et af., 1984; Senthong and Pandey, 1989). Water deficit reportedly reduces N2 fixation more than it reduces plant growth and N uptake (Kirda et af., 1989). When grown immediately before wet-season rice, legumes can encounter water deficit during the vegetative phase and excess water during the reproductive phase (Timsina, 1989). Soil saturation and temporary waterlogging adversely affect growth, N accumulation, and N2 fixation of food legumes (Wien et al., 1979; Lawn and Williams, 1987). Soybean is more tolerant of excess water than is cowpea (Wien et al., 1979; Hulugalle and Lal, 1986), and cowpea is more tolerant of temporary soil waterlogging than is mung bean (Minchin and Summerfield, 1976; IRRI, 1985, p. 410).

A

-

-

-

Po st rice

Pre rice

Saturated orflooded soil

FIG.4. Rainfed lowland rice cropping patterns in tropical Asia

10

R. J. BURESH AND S. K. DE DATTA

B. GREENMANURE LEGUMES Green manuring with effective N2-fixinglegumes can increase the soil N pool while also improving soil physical and chemical properties through the addition of organic matter ( Jiao, 1983). Green manures can be grown in rice fields before rice and then incorporated during land preparation for rice. Alternatively, the green manure crop can be grown elsewhere, such as border areas, nearby upland fields, or levees, and then transported as cut green matter to the rice field for incorporation. This practice is called green leaf manuring. In temperate regions, where temperature restricts the period suitable for rice, leguminous green manures have historically been grown as a winter crop in rotation with rice. In China, winter green manures, of which milk vetch (Astragalus sinicus L.) is the most important, continue to occupy large areas (Wen, 1989). Milk vetch tolerates cold temperature and shading, but it is sensitive to soil submergence. Milk vetch seeds are normally broadcast into the field before late rice is harvested in mid-November. In the following April, part of the vetch is typically removed for forage or compost and the remainder is directly incorporated as a green manure (Chen, 1988; Liu, 1988). Alternatively, green manure can be basally applied to rice after composting under waterlogged conditions (Wen, 1989). Wen (1989) indicated that waterlogged compost can eliminate possible adverse effects of toxins initially formed during anaerobic decomposition and provide a steady, long-lasting release of N. However, production and use of waterlogged compost is labor intensive and N can be lost during composting. The use of green manures in rice-based cropping systems has declined worldwide. In Japan, where milk vetch was formerly an important green manure, green manures are now of minor importance (Ishikawa, 1988). In the United States, green manure crops, including vetches and clovers, have been grown in rotation with rice, but use of green manure crops has declined to less than 5% of the planted rice area (Westcott and Mikkelsen, 1988). Berseem clover (Trifolium alexandrinum L.) is used as a winter green manure in Egypt (Hamissa and Mahrous, 1989). In the tropics, Sesbania species, especially dhaicha IS.cannabina, syn: S . aculeata), are used as green manure in rice cropping systems. Sesbania species are well adapted for use as a green manure before rice because of their ability to withstand soil waterlogging and flooding, to grow on finetextured soils, and to tolerate soil salinity (Evans and Rotar, 1987). Sesbania cannabina and Crotalariajuncea L. (sunn hemp) are common green manures in India (Abrol and Palaniappan, 1988; Garrity and Flinn, 1988). The inclusion of a green manure legume between wheat and rice in a

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

11

rice-wheat rotation in northern India requires irrigation (Singh et al., 1981). Therefore, in determining the cost effectiveness of green manures in this rotation one must consider the irrigation and fertilization, particularly phosphorus, required for the green manure. In a region of the Philippines, indigo (Indigofera tinctoria L.) is grown as a green manure after wet-season rice in rainfed environments and after a second rice crop in partially irrigated environments. Normally, it is intercropped with upland food or cash crops. Initial growth of indigo is rather slow. After the intercrop is removed, the indigo continues growing throughout the dry season. The indigo is incorporated during land preparation for wet-season rice, and rice is transplanted immediately after biomass incorporation (Bantilan et al., 1989; Garrity et al., 1989). Woody legume species, particularly Gliricidia sepium ( Jacq.) Steud., Leucaena leucocephala (Lam.) de Wit, and Sesbania bispinosa ( Jacq.) W. F. Wight (syn: S. aculeara, S. cannabina), are used as green leaf manures in rice-based cropping systems (Brewbaker and Glover, 1988). When grown near rice fields, these legumes can provide leaf matter for green manuring as well as for fodder and fuel. Green leaf manure incorporated before transplanting can significantly increase rice yield ( Jeyaraman and Purushothaman, 1988; Zoysa et al., 1990). Worldwide, the use of leguminous green manures in rice cropping systems is currently found primarily in irrigated environments. Rainfed rice environments prone to soil waterlogging appear to have the greatest potential for future green manure cultivation (Garrity and Flinn, 1988). The recent identification of flood-tolerant, stem-nodulating legumes has increased research interest in green manures for environments prone to waterlogging (Rinaudo et al., 1988). Sesbania rostrata (Rinaudo et al., 1983) and Aeschynomene afraspera (Alazard and Becker, 1987) have been examined in great detail for their potential as green manures. Production of seed and scarification frequently are constraints in the use of leguminous green manures, such as S. rostrata. An alternative is to grow S. rostrata by vegetative propagation (Becker et al., 1988, 1989). This method requires additional labor to make and plant cuttings, but it requires less seed, land preparation, and water management.

C. DUAL-PURPOSE LEGUMES The quantity of legume N available as a N source for a succeeding rice crop depends upon N accumulation by the legume and whether it is used for sole green manuring, seed production, or fodder. Rice farmers are often reluctant to devote land and resources to growth of legumes solely

12

R. J . BURESH AND S. K. DE DATTA

for green manure because it provides no immediate income or food, yet requires human labor. Food legumes, in contrast to green manures, offer the attractive dual benefits of seed production for income or food and production of residue, which can be used for animal feed or a N source on the following rice crop (Kulkarni and Pandey, 1988). Alam (1989) compared cowpea, mung bean, and Sesbania rosfrufuas prerice crops during the dry-to wet-season transition period in the Philippines. Each crop was sown on two dates and at three sites differing in internal soil drainage and water table depth. Aboveground biomass remaining after harvest of cowpea and mung bean grain was incorporated. Grain yields of legumes were adversely affected by soil waterlogging and heavy rains. Grain yields ranged from 0 to 0.73 t/ha for mung bean and 0 to 0.66 t/ha for cowpea. Mung bean biomass after removal of grain ranged from 0.2 to 2.5 t/ha and contained 3 to 30 kg N/ha. Cowpea biomass after removal of grain ranged from 0.5 to 3.9 t/ha and contained 7 to 79 kg N/ha. Nitrogen accumulation was consistently less for mung bean and cowpea residue than for S. rosfrata green manure. Rice yields were slightly increased by legume residues and S. rostrata green manure. Whenever soil drainge and water regime did not prevent production of legume grain, the economic benefit was greater for mung bean and cowpea than for S. rostrata because of the high market value for legume grain. Garrity and Flinn (1988) in a survey of green manure management systems in South, Southeast, and East Asia concluded that green manures considered only in terms of N fertilizer savings are currently not economical for rice farmers in many parts of Asia. Irrigated mung bean in northern India, grown with recommended management practices for grain production and incorporation of residue, reportedly reduces the industrial N fertilizer requirements on the following rice crop by 20 to 30 kg N/ha (Chandra, 1988). The benefits of legume residue are attributed both to direct N effects and improvement of soil physical properties. In some regions, legume residues may serve as animal feed. Ruminant animals are an important source of draft power in many rice-based cropping systems, but feed for these animals is frequently insufficient, especially during the dry season. Considerable opportunity still exists for increasing fodder and forage legume production in tropical rainfed rice environments (Blair et al., 1986). Recognizing that farmers are often reluctant to grow crops solely for animal feed, Carangal ef al. (1988) proposed postrice intercropping of food legumes or cereals with forage legumes to provide food, fodder, and residue for the next wet-season rice crop.

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

13

IV. EFFECT OF LEGUMES ON SOIL NITROGEN Legumes utilize both soil N and atmospheric N2 in meeting their N requirements. In general, the proportion of legume N derived from soil rather than from N2 fixation increases with increased availability of soil N (George et al., 1988; Herridge and Brockwell, 1988). Herridge et al. (1984) showed that nitrate in the top 120-cm layer of a high-nitrate soil was reduced during growth of irrigated soybean in Australia. Initial nitrate at 15 days after soybean sowing was 30 mg N/kg soil in the top 30-cm layer and 267 kg N/ha in the top 120-cm layer. Uninoculated soybean accumulated 164 kg N/ha after 126 days, and soil nitrate in both inoculated and uninoculated treatments was reduced to less than 8 mg N/kg soil in all soil layers to 120-cm depth at soybean maturity after 154 days. By comparison, nitrate in bare fallow fluctuated little between 15 and 154 days, except for redistribution down the soil profile, and was 292 kg N/ha after the 154-day soybean crop. Sharma et al. (1985), on the other hand, reported an increase in soil nitrate during growth of a mung bean crop between wheat and rice on a sandy loam in Punjab, India. During mung bean cropping, nitrate in the top 120-cm soil layer increased from 73 kg N/ha in April to 223 kg N/ha in June. Nitrate accumulation can also differ among legumes. Wetselaar et al. (1973) observed that soil nitrate, after three consecutive years of legume cropping in tropical Australia, was greater under cowpea and groundnut than under Townsville stylo (Stylosanthes humilis Kunth) and clusterbean (Cyarnopsis tetragonoloba [L.] Taub.).

OF SOILN A. CONSERVATION

Singh (1984) speculated that legumes grown in rotation with lowland rice can scavenge soil mineral N , which might otherwise be lost by denitrification or leaching after the soil is flooded for rice production. This hypothesis is consistent with observations of Furoc and Morris (1989) and Morris et al. (1989) (Table 11). Without green manure before wet-season rice, soil flooding for 25 days before land preparation increased rice yield and N accumulation as compared with leaving the field nonflooded. They speculated that nitrate accumulated in the nonflooded but not the flooded fallow. Accumulated soil nitrate in the nonflooded fallow would have been lost after soil flooding for rice. With Sesbania green manure, however, the prerice water regime had no effect on rice yield and N accumulation.

14

R. J. BURESH AND S. K. DE DATTA

Table I1 Effect of in Situ Growth of Green Manure and Soil Flooding for 25 Days before Green Manure Incorporation on Yield and N Accumulation of the Following Wet-Season Rice Crop in the Philippines” Grain yield @/ha) Water regime Nonfloodedd Flooded

Fallow 1.8 2.4

N accumulation (kglha)

Green manureC

Fallow

Green manureC

3.6 3.4

34 48

I8 14

Adapted from Furoc and Moms (1989) and Morris et al. (1989). All values are the mean for 2 years. No chemical N fertilizer or green manure added to rice. Each value is the mean of 6 Sesbania green manure treatments with a mean N addition of 135 kg Nlha for the nonflooded and 1 1 1 kg N/ha for the flooded water regime. Rice was transplanted 5 days after incorporation of green manure. Soil was flooded and puddled 5 days before rice transplanting.

Sesbania presumably utilized the accumulated soil nitrate in the nonflooded water regime, thereby preventing loss by denitrification and effectively cycling soil N through green manure N back to the soil for use by rice. Considerable nitrate may remain in soil after a N2-fixing legume crop. Postharvest levels of soil nitrate are often higher after food legumes than after nonfixing crops (Herridge, 1986). The increase in soil nitrate after growth of a Nz-fixing food legume, as compared with a nonfixing crop (cereal or unnodulated legume), ranged from 22 to 41 kg N/ha in six studies reviewed by Hemdge (1986). This phenomenon, referred to as nitrate sparing, has been attributed to less capacity of N2-fixing legumes than of nonfixing crops to utilize soil nitrate. Nitrate sparing, rather than a net increase in the soil N pool following growth of a food legume, may account for the N benefit of food legumes to a following upland crop (Herridge and Bergersen, 1988). Another possible benefit of legumes to soil N may be N released from roots and nodules during legume growth (Poth et al., 1986). Very few measurements of soil nitrate following growth of legumes on lowland rice fields are available. Buresh et al. (1989) observed 18 and 25 kg nitrate N/ha in the top 60-cm soil layer at harvest of mung bean grown after lowland rice in the Philippines. In another study in the Philippines (unpublished IRRI/Niftal/IFDC collaborative research), nearly identical soil nitrate levels were observed at harvest of postrice inoculated soybean, cowpea, and mung bean (Table 111). Soil nitrate level was similar following a nonnodulating soybean, but it was lower following a traditional weedy fallow.

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

15

Table I11

Soil Nitrate Levels at Harvest of Postrice Legumes in the Philippineso Soil nitrate (kg Nlha) Postrice treatment

0-20 cm

0-80 cm

Soybean Cowpea Mung bean Nonnodulating soybean Weedy fallow L S D ~(.05)

32 32 29 31 13 9

55 53 53 48 32 13

a Unpublished IRRI/Niftal/lFDC collaborative research. I/ Least significant difference.

All treatments in Table 111, including weedy fallow, were tilled before sowing legumes. Because tillage can enhance soil nitrate (Herridge, 1986), it is conceivable that soil nitrate levels would be lower when legumes are established with less or no tillage. Nonetheless, higher levels of soil nitrate remained after legumes than after a traditional weedy fallow. In upland cropping systems, this additional nitrate would be available to the next crop, but in legume-lowland rice sequences, this nitrate is prone to loss during soil wetting and flooding before rice. B. Loss OF SOILN Whereas nitrate sparing can benefit a following upland crop (Herridge and Bergersen, 1989, it appears undesirable in legume-lowland rice sequences. Effective use of soil nitrate by legumes growing before rice could conceivably reduce subsequent losses of soil N by leaching and denitrification and benefit the rice by cycling soil nitrate N through readily mineralizable, N-rich residue to the succeeding rice crop. Field research is needed to investigate this hypothesis. Soil nitrate N derived from N fertilizers applied to legumes could be more susceptible to N losses in legume-lowland rice sequences than in legume-upland crop sequences. Application of 30 kg ammonium sulfate N/ha as a starter dose to mung bean on a lowland rice field in the Philippines slightly increased nitrate N in the top 60-cm soil layer (unpublished IFDUIRRI collaborative research).

16

R. J. BURESH AND S. K . DE DATTA ~~~~

Soil nitrate (kg N/ha) Fertilizer N (kg N/ha)

Mung bean harvest (16 April)

Before soil flooding (2 June)

~

0

30

25 30

52 64

The nitrate N completely disappeared after soil flooding, presumably by denitrification and leaching (Buresh et al., 1989). Although the above differences in nitrate N are not significant at p = .05 (error df = 5 ) , they raise concern about the fate of residual nitrate N derived from N fertilizer applied to legumes in lowland rice environments. Denitrification in soils requires available carbon as an energy source for denitrifying microorganisms. Consequently, the addition of leguminous green manure and residues to soils low in available C could conceivably enhance denitrifying activity in soil (Beauchamp et al., 1989). Singh et al. (1988b) observed in an incubation experiment with a sandy loam (organic C = 3 g/kg) that addition of S. aculeara green manure (C/N = 13) increased the rate of soil nitrate disappearance after soil flooding. Nitrate disappearance presumably was due to denitrification. Addition of rice straw (C/N = 85) and wheat straw (C/N = 78) also lead to rapid nitrate disappearance. However, immobilization may be responsible for nitrate disappearance following addition of residues with high C/N ratio (Yoneyama and Yoshida, 1977).

V. ACCUMULATION OF LEGUME NITROGEN Nitrogen accumulation by legumes in tropical rice-based cropping systems is influenced by water regime (Alam, 1989), soil fertility (Herrera et al., 1989), photoperiod (Becker et al., 1990b), inoculation (Ndoye and Dreyfus, 1988), and legume growth duration (Bhuiyan et al., 1989). With an adequate water and nutrient supply, fast-growing, flood-tolerant legumes can accumulate more than 100 kg aboveground N/ha in 50 to 60 days (Table IV). Nitrogen accumulation by legumes sensitive to soil waterlogging, such as cowpea and mung bean grown before wet-season rice, is retarded by soil saturation (Alam, 1989; Morris et al., 1989). Slower growing drought-tolerant legumes, such as pigeonpea (Cajanus cajan [L.] Millsp.) and Indigofera tinctoria, are better suited for sowing after wetseason rice with subsequent N accumulation through the dry season and then incorporation immediately before the next wet-season rice (Garrity et al., 1989).

Table IV Abovegound N Accumulation by Green Manure (GM) Crops Grown in Lowland Rice Fields

Species and country Aeschynomene afraspera Philippines

Asfrugalus sinicus Japan Crotalaria juncea India

Duration0.' (d)

Dry herbage yield (tiha)

N accumulation (kdha)

CIN ratio

N

P

K

42 49 56

2.2, 3.9 3.1, 1.8 4.3, 7.2

17,78 155,204 138, 149

13, 16 -

0 0 0

0 0 0

0 0 0

FB

4.3

I38

13

0

0

0

50-55 50-55 50-55

91 120 149 110 85 I20 144

17 16

30 45 60

3.4 4.0 4.8 5.4 3.1 6.0 7.6

24 -

0 I5 15 0 NA NA NA

0 0 7 26 NA NA NA

0 0 0 0 NA NA NA

60

3.8

87

22

0

26

0

4

30 45

1 .o

60

3 .O

35 62 16

-

NA NA NA

NA NA NA

NA NA NA

5 5 5

60 Philippines

Cyamopsis tetragonoloba India Lablab purpureus Philippines

Fertilization of GM' (kdha)

1.9

15

Reference"

2

(continued)

Table IV (continued)

Species and country Indigofera tinctoria Philippines

Sesbania aegyptica India Sesbania aculeata (syn: S . cannabina) Bangladesh

Duration'.' (d)

Dry herbage yield (t/ha)

N accumulation (kdha)

C/N ratio

45 45 60 60 178

0.5 1.2

-

1.7 4.7 13.3

19 25 58 267

-

57

-

39

-

0.85 2.0 6.3 0.23 2.0 2.3 3.4 3.7 4.6

24 70 170 8 58 57 87 98

5.0

108 120 132 81 143 173

16 16 16 22

30 45

India

60 30 45 50-55 50-55 50-55

Philippines

60 60 60 60 30 45 60

4.8 5.6 3.9 6.7 8.0

110

104

-

-

Fertilization of GM' (kdha)

N

P

K

NA 0 NA

NA 0 NA 0

NA

5

0

NA 0

0

0

6 5 7 6

NA

NA

NA

8

0 0 0

0 0 0

0 0 0

36 26 0

15 I5

0

0 0 0 0 0 0 0

9 9 9 10 10 3 3 3

0 0

NA 0 NA 0

NA NA NA

7 NA 26 NA 26 NA NA NA

0

NA 0 NA 0

NA NA NA

Reference"

'*

11

4 12 10 5 5 5

Sesbania cannabina India

Philippines

-

60

98 147 I65 43-128 58-132 79 98-151 131-171

57

-

24

57

-

45 42 48' 48 49 49 49 49 49 49 49 56 60' 60

606

Sesbania grandiflora India Sesbania glabra India Sesbania sp.PL se-17 India Sesbania rostrata Philippines

18 20 23

3.1 5.3 7.3 1.8-3.6 2.5-4.1 4.9 4.9-6.3 6.7-7.2

45 55 60 4tIb 48 48

0 0

22 22 22 0 0

0

13 13 13 14 14 14 14 14

0

0

0 0

0 0

0 0 0 0 0 0 0

-

NA

NA

NA

8

27

-

NA

NA

NA

8

-

81-108

-

0

22

0

15

2.1, 2.6 2.5, 3.7 2.6, 5.3 5.0 6.0 6.3 6.4 11.2 12.4 8.4, 11.2 4.1, 5.4 6.9, 6.8 7.2,7.7

55,50 68, 111 89, 167 103 125 142 143 194 252 155, 194 83, 117 148, 179 176, 219

-

0 0 0 0 0 0 0

0

0 0 0 0 40 0 40 0 0 0 0 0 0

-

-

I

22, 24 -

-

0 0 0

0

30 0 0 0 0

0 0 0 0

40 40 0 0 0

0 0 0

1

14 14 16 16 16 16 16 16

16 16 14 14 (continued)

Table IV (continued)

Species and country Thailand

Dry herbage yield @/ha)

N accumulation (kdha)

C/N ratio

N

P

K

0.46-0.85 1.7 2.8-4.0 5.1 0.7, 1.1 2.0,2.1

16-24 66 76-100 116 21 62.48

-

0 0 0 0 0 0

0 22 0 22 0 22

0 0 0 0 0 42

17 17 17 17 17 17

60 84

2.9 3.4 4.7 4.9 4.4

91 112 130 156 83

-

0 0 0 0 NA

0 0 0 0 NA

0 0 0 0 NA

14 14 14 14 18

MAT

3.4-4.8

72-106

-

NA

NA

NA

19

60 60 30 45 45 45 45

2.8 6.9

13 113 21 62,70 63 67 74 34 80

32 -

NA 0 NA 0 NA 0 NA 0 NA

NA 26 NA 20 NA 0 NA 0 NA

NA 0 NA 0 NA 0 NA 0 NA

12 4 5 20 5 21 22 14

Duration'l.b

(4 46 46 61 61 61 61

13 0

Sesbania sesban Philippines

48b 48

w

Sri Lanka

Trifolium subterraneum U.S.A. Cowpea India Philippines

Fertilization of GM' Wha)

48

60

0.1

2.3, 2.5 2.4 2.5

-

1.8 3.6

15 15

-

Referenced

5

Mung bean Philippines

Pigeonpea Philippines Soybean Philippines

54 41-50 75-102 115 I36

-

60

2.3 4.5 4.7

45 60

1.3 3.6

45

2.6 4.8 7.9

30 30 40 45

60 60

-

NA NA NA NA NA

NA NA NA NA NA

NA NA NA NA NA

5 22 22 5 5

33 76

-

0 0

0 0

0 0

7 7

67 134 141

-

NA NA 0

NA NA 0

NA NA 0

5 5 7

-

Abbreviations: FB, full bloom; MAT, crop maturity.

z

* Green manure crop was grown on flooded soil for the last 25 days before incorporation. NA designates that information was not available in the reference. 1, Becker et a / . (1990b); 2, Ishikawa (1988); 3, Sharma and Mittra (1988); 4, Ben et al. (1989a); 5, IRRI (1986, p. 403); 6, Bantilan et a / . (1989); 7, Meelu et al. (1985); 8, Ghai et al. (1985); 9, Bhuiyan et al. (1989); 10, Khind et al. (1983); 11. Ben et al. (1989b); 12, Khind e r a / . (1982); 13, Bhardwaj andDev(1985); 14, M o m s e t a l . (1989); 15,Ghaietal. (1988); 16, Beckeretal. (1990a); 17, Hemeraetal. (1989); 18, Palmetal. (1988); 19. Dabneyetal. (1989); 20, John et al. (1989~);21, John et al. (1989b); 22, M o m s et al. (1986a).

22

R. J. BURESH AND S . K. DE DATTA

The growth and yield of legumes, like those of other upland crops, can be limited by nutrient deficiencies and soil acidity, which are serious crop production constraints in southeast Asia (Craswell et al., 1987). Food (Saraf, 1983; Craswell et al., 1987; Veeranna, 1987) and green manure legumes (Alberto, 1989; Table IV) frequently respond to P fertilization. Herrera et al. (1989) reported that P application to Sesbania rostrata on an infertile Aeric Palequult in northeast Thailand was essential for high N accumulation. They speculated that on soils highly deficient in P, it may be more effective to apply P to the green manure rather than to the following rice crop. In Punjab, India, the P fertilizer recommendation in a S. cannabina green manure-rice sequence is to apply the P recommended for rice to the legume and then omit P application to the succeeding rice (Gill, 1989). In winter green manure-rice sequences in China, it is reportedly more profitable to apply P to the legume than to rice (Chen, 1988; Wen, 1989). A starter dose of 20 to 25 kg N/ha is frequently recommended for tropical food legumes (Chatterjee and Bhattacharyya, 1986). Reports show that starter N can increase N accumulation of green manure legumes (Sharma and Mittra, 1988; Becker et al., 1990a) and yield of food legumes, particularly on infertile coarse-textured soils (Carangal et al., 1987)and for inoculated soybean (Sekhon et al., 1984). Increases in soybean seed yield can be much greater with inoculation than with N fertilizer, especially in environments where soybean is newly introduced (Duong et al., 1984; IRRI, 1987, pp. 490-491). A. SYMBIOTIC N FIXATION For legumes to maintain or increase the soil N pool as desired, they must

fix large amounts of atmospheric N2. However, estimates of NZfixation by legumes on ricelands are limited, particularly for food legumes other than soybean. Moreover, because legumes on ricelands are frequently grown under marginal conditions with limited inputs and management, researchers’ measurements of N accumulation by legumes and total legume N from fixation in well-managed experimental plots may overestimate the contribution of N2 fixation in farmers’ fields.

I . Food and Forage Legumes Factors affecting NZfixation by legumes include soil mineral N, inoculation, water regime, and soil and crop management. Root nodulation (Brockwell et al., 1989) and N2 fixation (Bergersen et al., 1989) dramatically decrease as plant-available soil N increases. Using results from

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

23

soybean experiments in Australia, Herridge and Bergersen (1988) showed that for soybean the percentage of N derived from symbiotic N2 fixation (Ndfa) correlated inversely ( r = - .88) with nitrate N, expressed in kg N/ha in the top 120-cm soil layer. Increased rates of inoculation can diminish but not eliminate the adverse effects of plant-available soil N on N2 fixation (Herridge and Brockwell, 1988). Peoples and Herridge (1990) used results of Herridge and Brockwell (1988) to illustrate the strong relationships (R2 = 0.80) between Ndfa and number of Bradyrhizobium japonicum in the seed zone at sowing and soil nitrate to 90-cm depth at sowing. Soil nitrate following a flooded rice crop is normally very low or undetectable (Figs. 1 and 2 ) . Therefore, in terms of suppressing symbiotic N2 fixation, soil nitrate conceivably may be a much less important factor for legumes following lowland rice than for legumes following a fallow or upland crop. Water deficit is known to dramatically decrease N2 fixation by legumes (Kirda et al., 1989). K u c ~ yet al. (1988b) showed that biweekly irrigation, as compared with weekly irrigation of soybean in Thailand, did not seriously reduce yield or N2 fixation, but delaying irrigation until symptoms of water deficit appeared on soybean markedly reduced yield and N2 fixation. Because legumes in tropical lowland rice environments are typically grown only on residual soil water, water deficit may be an important factor influencing Ndfa and total legume N from fixation in tropical rice-based cropping systems. Tillage generally increases soil nitrate N which, in turn, can suppress N2 fixation. Herridge (1986) observed greater nitrate N in the top 120-cm soil layer following a cultivated fallow (214 kg N/ha) than following a no-till fallow (185 kg N/ha). Soybean fixed more N following the no-till (236 kg N/ha) than following the cultivated fallow (132 kg N/ha). Nitrogen fixation exceeded N removal in the grain following the no-till fallow (54 kg Nlha), but not following the cultivated fallow (-29 kg N/ha). Rennie et al. (1988) reported that zero tillage rather than conventional tillage for establishment of soybean increased soybean yield and N2 fixation in two of three field trials in Thailand. Nitrogen fixation by food legumes in the tropics and subtropics is highly variable and inconsistent. For example, N2 fixation measured by "N dilution on dry-season soybean at two sites in Thailand ranged from 32 to 161 kg N/ha, and Ndfa ranged from 21 to 79% depending on soybean cultivar, Bradyrhizobium japonicum strain, and location (Kucey et al., 1988a). A literature review by Peoples and Herridge (1990) on N2 fixation by legumes in the tropics and subtropics revealed a large range in estimated Ndfa: 0 to 95% for soybean, 8 to 89% for cowpea, 22 to 92% for groundnut, and 10 to 88% for pigeonpea. The amounts of N2 fixed ranged

24

R. J. BURESH AND S. K. DE DATTA

from 0 to 450 kg N/ha. Estimated Ndfa tended to be higher for forage legumes than for food legumes. In the studies reviewed by Peoples and Herridge (1990), the Ndfa for forage legumes ranged from 50 to 100%. Among food legumes, soybeans normally give the most consistent response to inoculation. The greatest successes with inoculation have been achieved when a legume is newly introduced to a site and when rhizobia numbers in soil decrease greatly between legume crops (Henzell, 1988). Anaerobic conditions during growth of lowland rice between legume crops may result in depletion of soil rhizobia (Wood and Myers, 1987). Henzell (1988) listed identification and exploitation of situations in which inoculation of legumes gives economic benefit as a priority of applied biological nitrogen fixation research. Lack of effective inoculants to developing country farmers remains a constraint (Craswell, 1990).

2 . Green Manures Stem-nodulating legumes have received considerable recent examination for their potential as green manures in lowland rice environments prone to soil waterlogging. Stem nodulation has been reported in three genera of legumes: Sesbania, Aeschynomene, and Neptunia. Ladha et al. (1990) indicated that 17 species of Aeschynomene, 3 of Sesbania, and I of Neptunia are now reported to bear stem nodules. High acetylene reduction activity (ARA) is reported for stem nodules of S . rostruta (Dreyfus and Dommergues, 1981), A. scabra (Eaglesham and Szalay, 1983), and A . afruspera (Alazard and Duhoux, 1987). Whereas flooding adversely affects ARA of root nodules, stem nodules continue to actively fix N2 under flooded soil conditions (Saint Macary et a f . , 1985; Ndoye and Dreyfus, 1988). Soil mineral N reduces N2 fixation by root nodules, but stem nodules of S . rostrata (Dreyfus and Dommergues, 1980; Becker et al., 1990a), A . scabra (Eaglesham and Szalay, 1983),and A . afruspera (Becker et al., 1986) effectively fix N2 at high mineral N concentrations in soil. Becker et a f . (1990a) speculated that stem-nodulating legumes may effectively increase total soil N through N2 fixation, even on high-N soils. The unusual properties and potential benefits of stem nodulation are reviewed by Ladha et al. (1990). Pareek et a / . (1990) reported that Ndfa in well-nodulated S . rostrata and S . cannabina increased with plant age. Ndfa, estimated by the isotope dilution method, increased from 50 and 75% at 25 days after seeding to about 70-95% at 45 to 55 days. Between 45 and 65 days, nearly 100% of Sesbania N came from air. Ndfa was similar for S. rostrata and S . cannabina, but total N from fixation was greater for S . rostrata than for S .

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

25

cannabina because of higher N accumulation for S. rostrata. Ndfa reported by Pareek e f al. (1990) is greater than the 35 to 51%, estimated by isotope dilution, in a study by Ndoye and Dreyfus (1988) in which uninoculated Sesbania was the reference. Reports on the benefit of inoculation are conflicting (Ladha et al., 1990). Inoculation of S . rostrata has been reported both to increase N accumulation (Ndoye and Dreyfus, 1988; Ladha et al., 1989a)and to have no effect on N accumulation (Rinaudo et al., 1983). Ndoye and Dreyfus (1988) reported that inoculation of S . sesban increased N accumulation under drained but not under waterlogged soil conditions. A. afraspera is less photoperiod sensitive than S . rostrata (Visperas et al., 19871, making it superior in N accumulation to S. rostrata during the short-day period (Becker et at., 1990b). The higher N concentrations and lower biomass production of A. afraspera than of S . rostrata may offer the advantage of reduced labor for incorporation (Becker et al., 1990b),which is a major determinant of profitability for green manure use in rice cropping systems (Garrity and Flinn, 1988). Nitrogen fixation by leguminous green manures in the tropics is reviewed in greater detail by Ladha et al. (1988). Legume winter green manure crops reportedly derive most of their N from symbiotic Nz fixation. In China, estimated Ndfa was 84% for milk vetch and 88% for common vetch (Vicia satiua L.) (Wen, 1989). Comparable Ndfa values ranging from 67 to 84% were estimated for various winter legumes in the United States (Smith et al., 1987). Estimated Ndfa was lower, 36 to 40%, when legume growth was poor (Smith et al., 1987).

B. N REMOVAL WITH LEGUME GRAIN When legumes are grown in situ solely for green manure production, N2 fixed by the legume and added to the soil represents a net gain of soil N, provided that soil and legume N are not lost as gases or by leaching. Food legumes are capable of fixing large amounts of N2, but removal of seed or green pods can constitute an export of considerable N . The quantity of N in aboveground residues remaining after grain harvest (Table V) depends on the total N accumulation of the legume and the harvest index for N (NHI) (Myers and Wood, 1987).The NHI, which is the proportion of N removed in seed, varies considerably among species and cultivars of the same species. Soybean tends to have a higher NHI than do other species (Myers and Wood, 1987; Table V). Levels of N2 fixation are often not sufficient to offset the N removed with harvested grain. For example, estimated Ndfa in an experiment in Indonesia was 33% for soybean and 12 to 20% for cowpea (Sisworo et al..

26

R. J. BURESH AND S. K. DE DATTA Table V

Nitrogen Accumulation in Aboveground Legume Biomass Remaining after Harvest of Grain in Lowland Rice-Based Cropping Systems Grain

Remaining aboveground plant material

N (kg/ha)

Dry weight (t/ha)

N (kg/ha)

-

-

25-52

0.86

4.6

101

Crop and country

Yield (t/ha)

Mung bean Australia India

0.65 0.9 0.6 0.73 0.38 0.25 0.19 0.4-1.0

3.0 2.5

-

Philippines

Cowpea Philippines

0.4' 0.9 1.O

-

0.66 0.26 0.39 0.32 0.2-0.9 Lentil India Soybean Australia India

-

2.6

50 57

30 27 18 17 17-36

3.0 3.7 4.0 3.9 2.8 3.9 I .2

69 54 53 49 61 79

1.7

1.1 I .9

2.7

-

-

-

-

5.7

Reference"

43 60

2.5 2.4 1.1 1.4 1.2-2.3

2.5-4.0

C/N ratio

-

5

27 30 31

8 8 9 7

-

7

19 45-60

-

-

-

-

10 10

30 68 52

-

1

17

-

-

-

7 7 7

I 3

" I , Chapman and Myers (1987);2,Rekhi and MeeIu (1983);3,Prasad and Palaniappan (1987);4, Maskinaeral. (1990);5,IRRI(1985,p.413);6, IRRI(1986,p.416);7,Alam(1989);8, Johnetal. (1989~); 9,John et al. (1989b);10, John et al. (3989d). Weight of pods. 1990). The N removed by legume grain exceeded N2 fixation in all cases. Average net N loss was 26 kg N/ha for soybean and 42 kg N/ha for cowpea. Enhanced N2 fixation or N fertilization would be required to prevent depletion of soil N levels. Nitrogen fixation and net N contributions of

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

27

legumes in tropical and subtropical agriculture are reviewed by Peoples and Herridge ( 1990).

VI. CONTRIBUTION OF LEGUME NITROGEN TO RICE Many studies have shown that leguminous green manures (Table VI) and food legume residues remaining after harvesting grain (Table VII) increase the yield of a subsequent lowland rice crop and reduce the requirements for industrial N fertilizer. The saving in industrial N fertilizer by using legume N is frequently referred to as the N fertilizer equivalence. Nitrogen from 50- to 60-day-old green manure (Singh et af., 1990)and from mung bean haulm (Rekhi and Meelu, 1983) incorporated 1 day before transplanting on coarse-textured, nonacid soils in Punjab, India, generally substituted for about an equal or slightly greater amount of urea N. In environments other than northwestern India, the N fertilizer substitution was frequently less than the added green manure N (Table VI). In the limited number of experiments with food legumes listed in Table VII, N from incorporated haulm of prerice food legumes substituted for about an equal or somewhat less amount of fertilizer N. Rice yields following cowpea incorporated at the flowering stage as a green manure (66 kg N/ha, C/N = 15) and cowpea grown to maturity with removal of grain and pods and incorporation of remaining residue (54 kg N/ha, C/N = 28) were nearly identical (Fig. 5). Removal of the cowpea residue dramatically reduced yield of the subsequent rice crop. Reports on the contribution of soybean haulm to a succeeding rice crop are not consistent. In India, Rajendra Prasad (1985) reported that incorporation of residue remaining after harvest of soybean pods increased grain yield of the subsequent rice crop. On the other hand, in a 7-year rice-ricesoybean trial in Taiwan, cited by Morris and Meelu (1989, rice yield was not increased when soybean haulm was returned rather than removed. The N contribution of legume haulm and the comparative N contributions for legume green manure versus haulm depend on the NHI. Cowpea frequently has a lower NHI than do soybean and mung bean (Myers and Wood, 1987), and cowpea cultivars can vary greatly in NHI. Timsina (1989), while not presenting data for NHI, reported a range of HI from 16 to 65 for 24 diverse cowpea cultivars. In a study in the Philippines, 40-dayold mung bean incorporated as a green manure accumulated 93 kg N/ha (26.4 g N/kg), whereas mature mung bean produced 1.1 t/ha grain and aboveground residue containing 31 kg N/ha (14.8 g N/kg). Yield of the

Table W

Nitrogen Fertilizer Substitution by Incorporated Green Manures (GM) on a Following Lowland Rice Crop"

Species and country

G M duration

Interval from GM incorporation to transplanting

(d)

(4

NA 50-55 50-55

NA 1

50-55

60 2s 3s 45

1 I NA NA NA

60 30 4s 60 61 50

GM incorporated

Rice yield (t/ha)

N fertilizer equivalence (kg/ha)b

Crop years

Dry weight (tlha)

N (kg/ha)

Without

With

GM

GM

3 1 1 1 2 1 1 1

4.6 3.4 4.0 4.8 5.4 1.5 2.7 3.8

78 97 120 149 110 49 71 89

3.2 2.7 2.7 2.7 3.2 2.8 2.8 2.8

4.0 3.3 3.5 3.1 5.6 3.5 3.8 3.8

38 28 37 52 132 41 62 62

4 4

1

2

3.8

87

3.2

5.3

116

3

15

1

IS

1 1 1 2 1 3 1 1 1 1 1 1

0.85 2.0 6.3 NA NA NA 4.8 0.23 2.0 5.6 2.3 3.4 3.7

24 70 170 NA NA NA 120 8 58 132 57 87 98

2.3 2.3 2.3 2.6 1.5 1.1 3.0 2.4 2.4 2.4 2.5 2.5 2.5

3.0 4.0 4.5 5.6 2.7 2.2 5.2 4.0

Reference"

Crotalaria juncea

India

Philippines

Cyamopsis tetragonoloba India Sesbania aculeata Bangladesh

India

so

60

30 45 60 50-55 50-55 50-55

1

15 18 15

1 1 1 1

1 1

1 1

5.1

6.2 3.2 3.3 3.6

48d

>w >w 95 53d 58d 84

42d

>fad > 120d 24 27 38

1 2 2 2 3 4

5 5 5

6

1 7 8 9 9 9 2 2 2

Sesbania cannabina India Sesbania rostrata Philippines Sesbania sp. PL Se-17 India

Trifolium alexandrinum Egypt Vicia benghalensis U.S.A. Cowpea India Philippines

7.6 5.5 6.2 5.3 4.8

127 126 128 93 75

10 3

104 104

5.0 3.2 2.7 2.7 2.7

2.9

57

3.2

3.9

33

1

I

I .4

52

2.8

3.5

41

4

15

I 1 1

81 108

103

3.3 3.3 3.3 3.3

5.2 5.1 5.0 5.4

80 74 70 90

12 12

I

-

98

10

51

1

1

60 60 60 60

I

4.1 5.0 4.6 4.6 4.6

125 I08

1 7 14

2 4 4 4

NA

NA

3

25

NA

45 45 45 45

5 0

104

11

11 I1

12 12

NA NA

NA NA'

1 1

-

-

6.6 6.6

7.7 7.5

27 40

13 13

NA

NA"

5

NA

NA

3.0

4.9

51

14

60 60

1

45 45

45 15

3 2 1 I

2.8 6.9 2.5 2.3

73 113 70 62

3.0 3.2 3.4 3.3

5.3 5.7 4.2 4.3

89 137 34d 54d

8 3 15 I5

I

NA designates that information was not available in the reference. Nitrogen fertilizer equivalence was the amount of inorganic N fertilizer computed from rice response models to produce rice grain equivalent to that obtained with only green manure N applied to rice. Quadratic response models were used unless indicated to the contrary. I , Bhardwaj et al. (1981);2, Sharma and Mittra (1988); 3, Ben et al. (1989a);4, IRRI (1988, p. 484); 5, Bhuiyan ef al. (1989);6. Dargan eta/. (1975); 7,Tiwarietal. (1980);8,Khindetal.(1982);9,Khindetal.(1983);10,Singhetal.(1988a); ll,BerietaI. (1989b); 12,Ghaietal.(1988); 13,Hamissaand Mahrous (1989); 14, Williams et al. (1972); 15, John et al. (1989~). Linear response models were used to calculate N fertilizer equivalence. Rice was direct seeded rather than transplanted.

Table W Nitrogen Fertilizer Substitution by lncorporated Legume Biomass, Remaining after Grain Harvest, on a Following Lowland Rice Crop

Species and country

Interval from incorporation to transplanting (d)

Biomass incorporated Crop years

Dry weight (t/ha)

Lentil India Mung bean India

15 15

3

60 60

I

1

Without biomass

With biomass

N fertilizer equivalence (kglha)"

Referenceb

~

~

~

Cowpea Philippines

N (kg/ha)

Rice yield (t/ha)

2.7 3.1 4.0

53 54 53

2.6 3.4 3.3

3.5 4.5 4.2

31 44' 50'

2 2

1

2.7 5.7

-

4.1 2.8

4.3 3.3

56' 31"

3 3

3

4.6

101

3.2

6.5

1 1

100'

1

4

Nitrogen fertilizer equivalence was the amount of inorganic N fertilizer computed from rice response models to produce rice grain equivalent to that obtained with only legume biomass N applied to rice. Quadratic response models were used unless indicated to the contrary. 1, Kulkarni and Pandey (1988); 2, John ef al. (1989~);3, John el al. (3989d); 4, Rekhi and Meelu (1983). Linear response models were used to calculate N fertilizer equivalence.

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

31

Grain yield (t/ha)

/'8

MCowpea, green manure

Y =4.25t 0.030N - 0.000092 N' ( I?' 4Cowpea ,residue Y=4.30+0.U22N -0.000035N2 (R' I Cowpea, residue removed Y=3.27t0.031N-0.000068N2 (I?' b.-4 Pre-rice fallow Y=3.29t0.023N-0.000009N2 (I?'

c-

-

I 29

I I 58 87 Urea N applied (kg/ha)

= 0.991 =0.98) ~0.99) ~ 0 . 9 17 I

116

FIG. 5. Effect of prerice treatment on response of lowland rice to applied urea in the Philippines. (Average of 2 years; adapted from John et a / . , 1989c.)

following wet-season rice was greater after green manure (3.2 t/ha) than after residue incorporation (2.3 t/ha) (IRRI, 1984, pp. 419-420). At least part of the increase in rice yield from leguminous green manures and residue can be attributed to increased soil-available N following legume incorporation (Nagarajah, 1988).The trends in rice grain yield for the four treatments in Fig. 5 are directly related to the accumulation of soilextractable ammonium following rice transplanting (Fig. 6).

R.J. BURESH AND S. K. DE DATTA

32

Soil ammonium N (kg/ha) 45 I

o Cowpea, residue

5 -

A Cowpea, residue removed A Pre-rice fallow 0

FIG.6. Effect of prerice treatment on ammonium N in the top 30-cm soil layer during a lowland rice crop in the Philippines. Values for each sampling day followed by a common letter are not significantly different, based on LSD (.05). (Adapted from John, 1987.)

A. MINERALIZATION OF LEGUME N

The soil water regime during decomposition of green manures and residue varies among rice-based cropping systems. In irrigated and rainfed lowland environments with rice establishment by transplanting or sowing of germinated seeds, the soil is typically flooded or saturated. In irrigated, rainfed lowland, and upland environments where rice is established by sowing in dry or moist soil, the soil is typically aerobic until saturated by rainfall or irrigation. In rainfed lowlands with erratic rainfall, the soil may undergo alternate drying and flooding. Models of organic matter decomposition in upland (van Faassen and Smilde, 1985)and flooded soils (Bouldin, 1988)have characterized organic amendments as containing two distinct components: one decomposing rapidly within a few months and the other decomposing slowly over several years. Singh et a1.(1988b), for example, reported that the initially fast and subsequently slow release of mineral N during decomposition of

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

33

7-week-old Sesbaniu aculeata green manure could be described by two simultaneous first-order reactions. Nitrogen content, C/N ratio, and lignin content of legumes (Frankenberger and Abdelmagid, 1985) and soil temperature influence N mineralization rate in flooded and upland soils. Temperature must be considered when comparing research results between tropical and temperate areas. 1 . Flooded Soil

Flooded soils are characterized by a thin, oxidized, surface soil layer overlying an anaerobic soil layer (Ponnamperuma, 1972). After soil flooding, ammoniacal N accumulates. Extractable soil ammonium normally peaks by 20 days after rice transplanting and then decreases, presumably because of plant uptake (Nagarajah, 1988). Formation of nitrate is restricted to oxidized soil zones, but this nitrate can diffuse to anaerobic soil zones where it is prone to gaseous loss by denitrification (Reddy and Patrick, 1986). Oxidation of soil during periods of drying may lead to formation of nitrate, which can be lost by denitrification after soil wetting (Buresh and De Datta, 1990). The beneficial effect of green manures on yield of a following rice crop is dependent upon incorporation of the green manure in both nonpuddled soils with water-seeded rice (Williams and Finfrock, 1962) and puddled soils with transplanted rice (IRRI, 1986, p. 406). Green manures and plant residues incorporated immediately before or after initial soil flooding typically decompose under transitional aerobic to anaerobic soil conditions and then under anaerobic soil conditions. Although the rate of decomposition of plant material is slower under anaerobic than under aerobic conditions, the net release of ammonium may be greater under anaerobic conditions because of the lower N requirement for anaerobic metabolism (Patrick, 1982). Under high-temperature tropical conditions, the mineralization of organic amendments can be as great in flooded rice fields as in upland soils (Neue and Scharpenseel, 1987; Neue and Bloom, 1989). Moreover, net release of N from added plant material occurs at C/N ratios that are relatively higher under anaerobic than under aerobic soil conditions. Leguminous green manures decompose rapidly following incorporation in tropical flooded soils. Following incorporation of S . cannubina (syn: S . aculeata) (Khind et al., 1985; Nagarajah, 1988; Beri ef al., 1989a), S. rostrata (Nagarajah, 1988; Becker e f al., 1990a;Diekmann, 19901, Aeschvnornene afraspera (Diekmann, 19901, Crotalaria juncea (Nagarajah, 1988: Beri et al., 1989a). clusterbean (Beri et al., 1989a), and cowpea green

34

R. J. BURESH AND S. K . DE DATTA

manure (Beri et al., 1989a; Fig. 6) in tropical lowland rice fields, the accumulation of soil ammonium peaked at 7-20 days after rice transplanting and then gradually declined. After reaching a peak, soil ammonium N levels declined more rapidly in the Philippines with broadcast-seeded rice on wet puddled soil than with transplanted rice because of more rapid early growth and N uptake for broadcast-seeded rice (Diekmann, 1990). On a sandy loam soil in Punjab, India, about 80% of the total N in S . aculeata green manure was mineralized by 10 days after incorporation (Ben et al., 1989b). About 40% of the green manure C was evolved as carbon dioxide in 20 days, and about 50% was evolved as carbon dioxide in 40 days (Beri et al., 1989b). Grain yield of irrigated lowland rice in a field study in the Philippines with three Sesbania species of two growth durations was a direct function of extractable soil ammonium at 10 days after green manure incorporation (7 days after transplanting) (Furoc and Morris, 1989). Nagarajah et aL(1989) reported faster and larger accumulation of soil ammonium from incorporated S. rostrata than from Azolla microphylla even though they had similar N contents (41.2 and 42.5 g/kg) and C/N ratios (1 1 and 9). They attributed the differences to the lower lignin content of S . rostrata (94 g/kg) than of A. microphylla (205 g/kg) (Frankenberger and Abdelmagid, 1985). The higher N content, lower C/N ratio, and slightly lower lignin content of 7-week-old Aeschynomene afraspera than of S. rostrata grown in the Philippines raised speculation that A. afraspera green manure may release ammonium faster than does S. rostrata green manure (Becker et al., 1990b). Residues of grain legumes, which frequently have a lower N content than that of green manures, also rapidly release ammonium in tropical flooded soils. Nagarajah (1987) determined the net N release for two legume green manures (3.rostrata and Crotafariajuncea) and five legume residues (cowpea, mung bean, groundnut, pigeonpea, and soybean) after a 50-day incubation in flooded soils without rice. Plant N contents ranged from 11 g/kg for soybean to 27 g/kg for S . rostrata; C/N ratio ranged from 17 for S. rostrata,cowpea, and groundnut to 38 for soybean; and lignin content ranged from 57 g/kg for mung bean to 134 glkg for pigeonpea. Net recovery of plant N as ammonium (AR) at 50 days ranged from 16% for soybean to 43% for S . rostrata. It correlated directly with plant N (N) and inversely with C/N ratio (R): AR AR

= =

3.50 46.1

+ 0.59 N -

0.79 R

r = .94 r = -.91

Similar patterns of accumulation and decline in extractable soil ammonium have been observed for incorporated cowpea green manure (N =

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

35

27 g/kg, C/N = 15) and residue (N = 13 g/kg, C/N = 30) under field conditions in the Philippines (Fig.6). The net recovery of incorporated aboveground cowpea N as extractable soil ammonium N at 15 days after transplanting (30 days after incorporation) was 37% for green manure and 28% for residue. Leaves, stems, and roots of legumes can differ in rate of decomposition and N release because of differing N contents and C/N ratios (Palm et al., 1988). Ventura et al. (1987) reported much higher N content of leaves (51 g/kg) than of stems (1 1 g/kg) and root stubble (9 g/kg) for 47-day-old S. rostrata. Palm et al. (1988) similarly observed higher N content in leaves (38 glkg) than in stems (4.1 gfkg) and roots (7.3 g/kg), and lower C/N ratio in leaves (1 1) than in stems (107) and roots (55) for 84-day-old S. sesban. More than 80% of the leaf N was mineralized in 14 days, but 80% of the stems and 75% of the roots remained undecomposed after 56 days. Addition of green manure and plant residue to flooded rice soil can enhance formation of methane (Tsutsuki and Ponnamperuma, 1987). Methane is a greenhouse gas linked to global warming (Blake and Rowland, 1988; Bouwman, 1990).Therefore, enhanced emission of methane to the atmosphere could be an undesirable consequence from use of green manure and plant residues in flooded rice soils.

2 . Aerobic Soil In rainfed and irrigated environments where rice is dry sown in nonflooded, aerated soil, the incorporation and initial decomposition of leguminous green manures and residues are normally under aerobic soil conditions. Ammonium formed by mineralization of legume N can oxidize to nitrate (Singh et al., 1988b; Beri et ul., 1989b). Rates of N mineralization and nitrate accumulation depend on tillage and depth of residue placement (Wilson and Hargrove, 1986) and on soil water content, which can fluctuate as a result of intermittent rain or irrigation. In lowland environments, the soil is eventually flooded by either rain or irrigation, resulting in depletion of soil oxygen. Under these anaerobic conditions, nitrate can be lost by denitrification (Williams and Finfrock, 1962). In Louisiana, the yield of dry-sown rice averaged for four rates of urea application was about 10% greater following subterranean clover (Trifolium subterraneum L.) than it was following bare fallow (Dabney et al., 1989). Desiccating the clover with a herbicide and leaving the residue on the soil surface resulted in rice yields similar to or greater than those obtained after incorporating the clover with tillage to a 10-cm depth. Leaving legume residue on the soil surface rather than incorporating the

36

R. J. BURESH AND S. K. DE DATTA

residue decreases the mineralization rate of legume N in aerobic soil (Wilson and Hargrove, 1986). A reduction in mineralization of legume N during the period from rice sowing to a permanent flood could decrease the amount of soil nitrate susceptible to leaching and denitrification losses before and after permanent soil flooding (Dabney et al., 1987). In general, only small increases in grain yield and savings in inorganic N fertilizer have'been reported for tropical dry-sown rice following legumes grown for grain and green manure production. In Australia, rice sown 39 to 75 days before permanent flooding yielded slightly more following incorporation of either soybean green manure, soybean residue, mung bean residue, or S. cannabina residue than following either fallow or sorghum with incorporation of residue (Chapman and Myers, 1987). In the Philippines, yield of dry-sown lowland rice was about 0.2 t/ha higher following soybean than following sorghum (Furoc et al., 1979). However, the soybean and sorghum treatments in this study were not randomized. Little is known about the mineralization and N contribution to rice of haulm (stems and tops), roots, and nodules of postrice legumes grown in rainfed lowlands (Fig. 4). Haulm of postrice legumes typically remains unincorporated for several months until after the onset of rains in the next wet season, when the soil can undergo alternate wetting and drying cycles before permanent flooding. Soil nitrate formed from mineralization of legume N before soil saturation will likely be lost by denitrification or leaching rather than used by rice (Buresh et al.. 1989). Sisworo et al. (1990) examined the N contribution of plant residues to the following crop in upland rice-soybean-cowpea and rice-maizecowpea rotations on an Orthoxic Palehumult in the humid tropics of Indonesia. They concluded that the N contribution of a residue to a subsequent crop on upland soils was controlled by the N concentration of the residue and modified by the soil water status. From their results they developed an equation to predict the percentage of added residue N taken up by the subsequent crop(s):

S = -1.05

+ 4.37 N + 0.0067 N R

R2 = 0.69

where N is the percent N concentration in the residue and R is the expected rainfall in mm for the subsequent crop.

B. BELOWGROUND LEGUME N Reports vary greatly on the N content, N mineralization, and contribution to rice of legume roots. The conflicting reports may partly result from large differences in N content and rate of N mineralization for roots among

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

37

different species and cultivars of the same species (Nnadi and Balasubramanian, 1978). Chapman and Myers (1987) found 23 to 50 kg N/ha in the nodulated roots and stem bases of mature soybean, mung bean, and S . cannabina. Roots and stem bases accounted for about 11% of the total plant N for soybean and about 25% of the total N for mung bean and S. cannabina. Considerably lower levels of N in nodulated soybean roots were reported by Bergersen et al. (1989) (Table VIII). Root nodules have a higher N content and lower CIN ratio than do legume roots. Consequently, nodules can rapidly decompose and release mineral N (Chulan and Waid, 1981).Because the fraction of total legume N contained in root nodules is small (Bergersen et al., 1989),the contribution of mineralized nodule N to rice yield can be undetectable. Several studies indicate that roots of green manure legumes contain 10% or less of the total plant N (Table VIII). The low N content and slow mineralization of Sesbania roots suggest that they are not important contributors of N to a following rice crop (Crozat and Sangchyosawat, 1985; Palm et al., 1988). Field studies have confirmed that rice yields are comparable following incorporation of equivalent quantities of green manure N (Sesbania or cowpea) either grown in situ before the rice crop or transported from a nearby field (green leaf manuring) (Singh et a / . , 1988a; Morris et al., 1989). Moreover, when aboveground biomass of S . aculeata grown before rice was removed, yields of the following rice were not greater than those obtained following a fallow (Singh et a / . , 1988a). There are conflicting reports on the benefits of food legumes to a subsequent rice crop when aboveground legume biomass is removed. De et al. (1983), in a study with removal of aboveground biomass of crops grown before rice, reported increased yield of lowland rice following cowpea, mung bean, and black gram (Vigna mungo) as compared with yields following a maize fodder crop. Other studies, which compared grain legumes with fallow before rice, reported no increase in rice yield (John er a / . , 1989~;Fig. 5) or only a slight, nonsignificant increase in rice yield (John et al., 1989d) when aboveground legume residue was removed. Incorporation rather than removal of haulm from prerice mung bean can increase yield of (Maskina et al., 1990)and cowpea ( John et al., 1989~) a following transplanted rice crop. Conflicting reports on the benefits of legumes to rice, when aboveground legume biomass is removed, can be attributed at least partly to differences in the treatment used for comparison with the legume. For example, De et al. (1983) compared legumes with maize fodder, whereas John et al. (1989~)compared legumes with a traditional weedy fallow. Removal of maize, unlike incorporation of weeds following a fallow, results in net loss

Table Vm Nitrogen Accumulation in Aboveground Biomass and Roots of Legumes Aboveground Species and country Aeschynomene indica Thailand Sesbania aculeata India Philippines Sesbania cannabina Australia Sesbania rostrata Philippines Thailand Sesbania sesban Sri Lanka Mung bean Australia Soybean Australia

Roots

Plant N abovegroundb

Duration" (d)

Dry weight (t/ha)

N (kdha)

Dry weight (t/ha)

55

1.9

37

0.3

4

91

1

60 62

4.6 6. I

104 99

0.9 0.8

14 I

88 93

2 3

50

75

4

MAT

152

N (kdha)

(%I

Reference'

47 55

3.4 7.0

73 128

0.6 0.7

5 6

94 96

5 1

84

4.4

83

I .2

9

90

6

MAT

132

40

77

4

MAT MATd

292 105-342

37 3-10

89 96-98

4 7

MAT designates crop maturity. Percentage of the total plant N located in aboveground plant parts. I , Crozat and Sangchyosawat (1985);2, Ben et al. (1989b);3, IRRI (1986, p. 416); 4, Chapman and Myers (1987);5, Ventura et al. (1987); 6, Palm e f a / . (1988); 7, Bergersen et al. (1989). Roots plus nodules sampled at 105 days; aboveground N determined at maturity (146 days).

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

39

of soil N. Consequently, the apparent benefit of a legume would be enhanced by comparison with a nonfixing crop that removes soil N. In addition, many studies do not provide sufficient information on crop management and leaf fall from the legume. Even with removal of standing aboveground legume biomass at maturity, leaf fall during crop development can contribute legume N to the subsequent rice crop.

c. LOSSESOF LEGUME N In addition to quantity of added legume N and mineralization rate of legume N, the N contribution of legumes to rice depends on the magnitude of N losses from mineralized legume N. Studies with "N-labeled leguminous green manures incorporated before planting lowland rice have shown loss of N from added Crotalaria (Huang et al., 1981), Aeschynomene ufraspera (Diekmann et al., 1991), S . rostrata (Biswas, 1988; Diekmann et al., 19911, milk vetch (Mo and Qian, 1983), and purple vetch (Vicia benghulensis) (Westcott and Mikkelsen, 1987). Added "N not recovered in soil and rice at harvest of water-seeded rice was similarly large for basally applied ammonium sulfate (54 to 62%) and purple vetch (62 to 64%) in a field study in California (Westcott and Mikkelsen, 1987). Low "N recoveries may have resulted from sampling the soil for "N to only a 15-cm depth. In several pot experiments, on the other hand, N losses determined from "N balances were less from incorporated green manure than from urea. Nitrogen losses were 12% from vetch straw and 19% from urea in California (Huang and Broadbent, 1989); they were 19%from milk vetch and 59% from urea in China (Mo and Qian, 1983). Huang et al. (1981) reported N losses at rice maturity of 16% for Crotalaria, 23% for ammonium sulfate, and 20% for a mixture of Crotalaria and ammonium sulfate. Field "N-balance studies with transplanted irrigated rice in the Philippines have shown much less N loss from labeled green manures than from 1991). Biswas (1988) reported labeled urea (Biswas, 1988; Diekmann et d., 16% loss from 90 kg S. rostrata N/ha incorporated immediately before transplanting as compared with 35% loss from 60 kg urea N/ha incorporated before transplanting. Diekmann et a/. (1991) compared "N balances for 45-day-old S . rostrata and Aeschynornene afraspera incorporated as green manure 1 day before transplanting with "N balances for splitapplied urea (two-thirds basal and one-third at 5 to 7 days before panicle initiation). In the dry season when 90 kg Niha was applied, N losses were 7% for S. rostrata, 13% for A . afraspera, and 39% for urea. In the wet season when 60 kg N/ha was applied, N losses were 9% for S. rostrata,

'

40

R. J. BURESH AND S. K . DE DATTA

16% for A. afraspera, and 31% for urea. Higher N losses from A. afraspera than from S . rostrata were attributed to faster decomposition of A. afraspera due to its lower C/N ratio and higher shoot N concentration (Diekmann, 1990). D. RESIDUALN EFFECTS Leguminous green manures incorporated before cropping with lowland rice can increase grain yield of a following wheat (Tiwari et al., 1980; Bhardwaj et al., 1981; Sharma and Mittra, 1988)or rice crop (Moms el al., 1989;Diekmann et al., 1991).Morris et al. (1986b), however, did not detect a residual response for green manure N in a second rice crop in 4 years of field research in the Philippines with green manure applications averaging 83 kg N/ha to wet season rice. The residual effects observed by Morris et al. (1989) but not earlier (Morris et al., 1986b) were attributed by the researchers to higher rates of green manure application (98 to 219 kg N/ha). Gu and Wen (1981) reported that residual effects of 75 kg green manure Nlha on grain yield of a second rice crop in a green manure-ricerice rotation in China were 5% or less. In a rice-wheat rotation in India, application of 80 kg urea N/ha to rice had no effect on wheat yield, but application of 40 kg N/ha as Sesbania aculeata combined with 40 kg urea N/ha to rice increased wheat yield by 0.7 and 0.6 t/ha in 2 years (Mahapatra and Sharma, 1989). The residual effect was attributed to more hydrolyzable and nonhydrolyzable organic N in the treatment receiving green manure (Chakraborty et al., 1988). A small residual effect on the second crop after incorporation of organic matter is consistent with the hypothesis that organic amendments contain a component that slowly decomposes over several years (Bouldin, 1988). Residual effects of green manure application to rice in China are reportedly greater when the succeeding crop is wheat rather than rice (Gu and Wen, 1981).Mahapatra and Sharma (1989) speculated that the application of green manure to rice, besides providing N, may improve the soil physical conditions after rice and thus allow better growth of wheat on the soil that was puddled for rice production. Legumes grown solely for incorporation as green manures can increase the soil N pool provided the legumes effectively fix N2 and losses of legume N are minimized. Ladha et al. (1989a) determined N balances in a pot experiment for weedy fallow-rice-weedy fallow-rice (F/R/F/R) and S. rostrata-rice-S. rostrata-rice (S/R/S/R) rotations under continously flooded soil conditions. Sesbania rostrata was incorporated at 45 and 55 days after emergence for the first and second crop, respectively. In the

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

41

F/R/F/R treatment, there was a net decline (140 mg N/pot) in the soil N pool. The N gains for free-living and rice-rhizospheric N2 fixation and imgation water (106 mg N/pot) failed to match the N removal by the two rice crops (247 mg N/pot). In the S/R/S/R treatment with and without inoculation of S. rostrata, there was a net gain (151 and 159 mg N/pot) in soil N. The gains in N from N2 fixation, by S. rostrata, free-living and rice-rhizospheric Nz fixation, and irrigation water (873 and 712 mg N/pot) exceeded the N removal by the two rice crops (722 and 543 mg N/pot). Rinaudo et al. (1983) similarly reported greater soil N following a S. rostrata-rice sequence than following a fallow-rice sequence, when both sequences were under waterlogged soil conditions. The continuously saturated soil conditions used in the experiments of Ladha et al. (1989a) and Rinaudo e? a f .(1983) would minimize gaseous N losses (Ponnamperuma, 1985). The N2 fixed by food legumes can vary greatly, and it is often less than the N removed with the grain. In most situations, food legumes, unlike N2-fixing legumes used solely as green manure, probably do not increase the soil N pool (Herridge, 1986; Wood and Myers, 1987). Nonetheless, a greater net loss of soil N would typically be expected following a nonleguminous crop. The increase in rice yield following food legumes likely results from increased plant-available N during decomposition of legume residue and from factors besides N supply rather than from a net increase in total soil N.

E. OTHERFACTORS CONTRIBUTING TO RICEYIELD Legumes frequently have positive effects on a following cereal crop that result from factors (rotation effects) other than supplying N (Hesterman et a f . , 1987). Rotation effects can include improved soil physical properties, increased soil water-holding capacity, improved soil chemical properties (Willett and Intrawech, 1988), and decreased pests and diseases of cereals. Addition of legume biomass to soil can enhance soil microbial activity and possibly heterotrophic N2 fixation (Ladha et af., 1989b). Evidence for positive effects in addition to N supply are provided by observations of higher agronomic efficiency (kg grainikg N applied) for green manure N than for inorganic N fertilizer (Morris e f a f . ,1986a), higher yield potential for rice with addition of organic N (Bouldin, 1988), and improved soil buffering capacity and nutrient availability with application of green manure (Willet and Intrawech, 1988). Diekmann ( 1990) attributed higher rice grain yield with incorporated S. rosfrata green manure than with urea at a rainfed lowland site in the

42

R. J . BURESH AND S . K. DE DATTA

Philippines to enhanced soil water-holding capacity, which presumably moderated the adverse effects of periodic water deficits. Incorporation of leguminous green manure with urea can reduce gaseous N losses from urea (Biswas, 1988: Diekmann et al., 1991). However, the enhanced uptake of urea N observed by Huang and Broadbent (1989) in the presence of vetch straw is greater than can be explained by reduced loss of urea N. Tropical legumes may offer potential to reduce nematode populations for the succeeding crop (Reddy et al., 1986). Growth of S. rostrata with removal of aboveground biomass before flooded rice can reportedly increase rice yield by controlling nematodes (Germani et al., 1983). Pariselle (1987) further demonstrated that S. rostrata can serve as a trap-crop for the nematode Hirschmanniella oryzae. Incorporation of green manure into flooded soils can increase available soil P (Singh et al., 1988b; Nagarajah et al., 1989) and soil solution Fe2+, Mn2+,and K+ in at least some soils (Khind et al., 1987; Nagarajah et al., 1989). It can decrease soil solution Zn2+ and A13+ (Khind et al., 1987; Nagarajah et al., 1989). Leguminous green manures can also temporarily reduce soluble A1 in aerobic acid soils (Davelouis and Sanchez, 1989).

VII. EFFECTIVE MANAGEMENT OF LEGUME NITROGEN The optimum interval from legume incorporation to rice transplanting in flooded soils varies with soil type and climatic conditions. On coarsetextured, nonacid soils in tropical lowland rice environments, transplanting immediately after green manure incorporation gives higher rice yields than does delaying transplanting to allow for decomposition of green manure (Bhardwaj, 1982; Beri et al., 1989b). A delay between organic matter incorporation and transplanting on highly percolating soils may result in formation of nitrate, which can be lost by leaching or denitrification after soil flooding (Beri et al., 1989b). Immediate transplantingalso results in more efficient use of irrigation water. In a summary of field experiments with S . aculeata, Crotalaria juncea, and cowpea grown for green manure in Punjab, India during May-June before rice, Singh et al. (1990) reported that 50- to 60-day-old green manure incorporated one day before transplanting contained 41 to 150 kg aboveground Nlha and substituted for an equal or slightly greater amount of urea N (72 to 148 kg N/ha). On coarse-textured, acid soils, in contrast to nonacid soils, a delay between organic matter incorporation and transplanting may be beneficial. Herrera et al. (1989) observed slightly greater yield of rice when a delay of 14-21 days rather than 2 days was allowed between incorporation of

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

43

2.3 t/ha S. rostrata green manure (76 kg N/ha) and transplanting on a poorly buffered Aeric Palequult in northeast Thailand. Organic acids and toxins, which accumulate during anaerobic decomposition of organic matter, can retard root elongation, shoot growth, and nutrient uptake by rice (Cannell and Lynch, 1984). The adverse effects of organic acid on rice seedlings increase with decreasing soil pH (Tanaka and Navasero, 1967; Rao and Mikkelsen, 1977). On many tropical soils, a 1- to 2-week period for anaerobic decomposition of incorporated green manure before transplanting can increase or at least not be detrimental to rice yield. A 1-week anaerobic decomposition of incorporated Sesbania green manure significantly increased rice yield on a sodic soil in India with four levels of exchangeable sodium percentage ranging from 16 to 48 (Swamp, 1988). A 5-day decomposition for incorporated S . aculeata green manure, but not for Sesbania sp. PL Se-17 green manure, under flooded soil conditions significantly increased rice yield on a sandy loam with electrical conductivity of I .7 dS/m (Ghai et al., 1988).A 15-day decomposition period following incorporation of S. aculeata green manure made no significant difference on rice yield on a reclaimed saline sodic clay loam in India (Tiwari et ul., 1980). On flooded clay soils in the Philippines, initial growth of rice is occasionally retarded when transplanting immediately follows incorporation of readily decomposable organic matter. Diekmann (1990) observed that S. rostrata and A . afrasperu green manure incorporated one day before transplanting significantly lowered initial rice growth rate as compared with treatments receiving no N or only urea. Rice plants eventually recovered, and grain yield appeared unaffected by the early suppression of rice growth. On the other hand, similar rates of green manure incorporated immediately before broadcasting germinated seeds had no visible effect on growth of the rice. Rice plants are known to compensate for retarded growth following organic-matter addition, such that the reduction in grain yield is negligible or much less than the reduction in early plant growth (Cannell and Lynch, 1984). Nonetheless, it appears that more research is merited on the factors responsible for initial retarded growth of transplanted but not broadcast-seeded rice and on the probable benefits of a delay between incorporation of green manure and transplanting. Literature suggests that the maximum contribution of legume N to rice in the tropics occurs when soils are maintained anaerobic after incorporation of legume N. The relatively small contribution of incorporated legume biomass to rice sown on aerobic soils (Chapman and Myers, 1987) might be attributed to loss of legume N by denitrification or leaching. In temperate regions, the maximum contribution of legume N to rice likely occurs when the period between legume incorporation and permanent soil flooding is

44

R. J. BURESH AND S. K. DE DATTA

insufficient for conversion of appreciable legume N to nitrate (Williams and Finfrock, 1962). Leguminous green manures in the tropics, particularly stem-nodulating legumes, with an adequate supply of soil nutrients can accumulate more than 120 kg N/ha (Table IV) when grown for about 50 or more days before wet-season rice. Incorporation of such large quantities of green manure N can exceed the initial N requirements for wet-season rice, which is frequently limited in yield potential by low solar radiation in the monsoon season. Diekmann (1990) found that application of green manure N at high rates (103 to 190 kg N/ha) resulted in no more yield of wet-season irrigated rice in the Philippines than did application of 60 kg urea Nlha. Similarly, increasing aboveground N accumulation of S . rostrata from 103 to 143 kg N/ha or from 194 to 252 kg N/ha with fertilization of the S. rostrata had no effect on yield of the following wet-season rice (Becker et al., 1990a). Furoc and Moms (1989) concluded from field studies in the Philippines that the additional N (approximately 60 kg N/ha) accumulated by S. rostrata and S . cannabina between 48 and 60 days may offer little potential to increase wet-season rice yield beyond that obtained with the 48-day-old green manure.

VIII. INTEGRATED NITROGEN MANAGEMENT Legume N remaining after the removal of grain or all aboveground plant biomass will normally only partially meet the N requirements for a following high-yielding rice crop. Similarly, leguminous green manure N, except when large quantities are applied before rice with limited potential for responding to N (Becker et al., 1990a),will normally only partially substitute for industrial N fertilizer for the following rice. In a survey of current green manure management practices in South, Southeast, and East Asia, Garrity and Flinn (1988) found no case in which green manure substituted entirely for industrial N fertilizer. Therefore, use of legumes as an N source for lowland rice will typically require integrated use of industrial N fertilizer for sustained high rice yields. The effectiveness of integrated organic and industrial N fertilizer use depends on the magnitude of N losses, the timing of industrial N fertilizer, and the sources of N applied. A. Loss OF FERTILIZER N Several pot and field experiments have shown that application of leguminous green manure with urea to flooded soil can reduce but not eliminate loss of urea N. Application of vetch straw with urea reduced urea N losses,

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

45

as determined by "N balance, from 19 to 12% in a pot experiment (Huang and Broadbent, 1989). Application of milk vetch reduced loss of urea I5N from 59 to 46% in another pot experiment (Mo and Qian, 1983). In a field study with transplanted rice in the Philippines (Diekmann et al., 1991), basal incorporation of 30 kg S. rostrata N/ha with 60 kg urea N/ha reduced loss of urea 'N from 54 to 46%. Basal incorporation of 30 kg S. rosfruta N/ha with 30 kg urea Niha reduced loss of urea "N from 37 to 24%. Biswas and De Datta (1988) reported that losses of urea "N (60kg N/ha basal and 30 kg N/ha topdressed at 5 to 7 days before panicle initiation) were reduced from 35 to 26% when one-half (30 kg N/ha) the basal urea application was replaced with an equivalent quantity of cowpea green manure N. However, the reduced loss of urea N reported by Biswas and De Datta (1988) might also be due to decreased percentage loss of urea N with decreasing urea application rate, as observed by Diekmann et al. (1991). Results of Biswas (1988) and Diekmann (1990) indicate that ammonia volatilization was the N loss mechanism reduced by application of green manure. Ammonia volatilization is widely recognized as an important mechanism for loss of industrial N fertilizer applied to tropical lowland rice (Fillery and Vlek, 1986; De Datta e f al., 1989). High floodwater ammoniacal N concentrations following application of N fertilizer, high temperature common in the tropics, and elevated floodwater pH resulting from photosynthetic activity create a favorable environment for ammonia loss. Application of green manure with urea reduced floodwater pH (Fig. 7) and

Floodwater pH

-

7

9.0

0

8.6*' 8.8

8.28.07.8-

-vO

8.4

7.6f

0

\

?

\

I

I

j4zyg No Nab

d

(control)

I

2

,

4

I

6

,

8

Days after fertilizer application

FIG.7. Floodwater pH at 1300 to 1400 h as affected by Sesbania rostruta green manure (Sr) and prilled urea (PU) incorporated immediately before transplanting rice in the Philippines. N60, 60 kg N/ha; N!N, 90 kg N/ha. (Adapted from Diekmann, 1990.)

46

R. J. BURESH AND S. K. DE DATTA pNH3 (Pa)

0.25

7

0

2 4 6 8 Days after fertilizer application

FIG.8. Partial pressure of ammonia (pNH3) at 1300 to I400 h as affected by Sesbaniu rmtrata green manure (Sr) and prilled urea (PU) incorporated immediately before transplant-

ing rice in the Philippines. N30,30 kg Nfha; N60,60 kg N/ha; N90,90 kg N/ha. (Adapted from Diekmann, 1990.)

consequently the partial pressure of ammonia (Fig. 8). The lower floodwater pH was attributed to production of carbon dioxide during decomposition of green manure (Biswas, 1988; Diekmann, 1990). In other studies, when urea was applied after incorporation of green manure, losses of urea N were not reduced. Goswami e? al. (1988) found that the S. aculeata green manure incorporated 1 week before transplanting had no effect on loss of urea applied in equal doses at 10 and 30 days after transplanting (DT). Nitrogen losses from 60 kg urea "N/ha were 44% when rice followed a fallow and 42% when rice followed S. aculeata incorporated as a green manure. Corresponding N losses for 120 kg urea N/ha were 39% for each treatment. John et al. (1989b) similarly found no effect of either cowpea green manure or residue, incorporated 15 days before transplanting, on losses of urea applied to rice. Partial pressure of ammonia following application of urea was also not affected by either green manure or residue incorporated 29 days earlier.

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

47

Because the rate of carbon dioxide production decreases rapidly during decomposition of legume green manure in tropical flooded soil (Beri et al., 1989b), the period for effective reduction of ammonia loss is probably brief. It is uncertain whether urea application can be briefly delayed after green manure incorporation without reducing the beneficial effect of lowered ammonia loss. Nonetheless, the reported reductions in ammonia loss with green manure application are small or moderate. These reductions in N loss per se have not been demonstrated to significantly increase rice yield. In addition to loss by ammonia volatilization, inorganic N fertilizers can also be lost by denitrification, which is controlled in flooded soils by supply of available C and rate of nitrate formation. Application of leguminous plant material could then conceivably increase loss of fertilizer N in soils where available C limits denitrification. John et al. (1989a) reported that incorporation of cowpea green manure (C/N = 15) to a flooded clay soil 15 days before transplanting had no effect on total N loss and evolution of N2 and N2O from urea N applied 30 days later at 15 DT. On the basis of high levels of water-soluble organic C (101 mg C/kg in the top 15-cm soil layer) in plots not receiving green manure, very low floodwater nitrate following urea application, and very low evolution of urea N as NZand NzO, John et al. (1989a) concluded that nitrate formation rather than available C limited denitrification on this flooded clay. Because nitrification in flooded soils is restricted to a small aerobic zone, loss of added industrial fertilizer N by denitrification in most flooded rice soils is probably limited by nitrate formation and nitrate diffusion to anaerobic soil (Reddy and Patrick, 1986). The negligible soil nitrate levels and the disappearance of added nitrate without application of a C source observed in many flooded soils support this conclusion (Buresh and De Datta, 1990). Carbon would be expected to gain importance as the factor limiting denitrification when soils are low in available C and when flooded soils undergo periodic drainage and drying. B. EFFECTIVE USEOF N FERTILIZER Because the response of rice to N fertilizer depends on source and timing of N application, calculations of industrial N fertilizer equivalence for legume N depend upon the industrial N fertilizer treatment employed by researchers. Thorough interpretation of N fertilizer equivalence values, such as those shown in Tables VI and VII, requires knowledge of the industrial N source and management used for determining the N response models (Bouldin, 1988).

48

R. .I.BURESH AND S. K. DE DATTA

Mahapatra and Sharma (1989), for example, in a 2-year study on a clay loam in India observed higher lowland rice yield (0.8 and 0.3 t/ha) for basal application of 40 kg S. aculeata N/ha with 40 kg urea N/ha than for a split application of 80 kg urea N/ha (50% basal, 25% at tillering, and 25% at panicle initiation). Chakraborty et al. (1988), on the other hand, in a 3-year study on a sandy loam in India found no greater rice yield for basal application of 45 kg S. aculeata N/ha with 45 kg urea N/ha than for basal application of 90kg urea N/ha. Comparison of results for these two studies is confounded by the differences in N timing for the sole urea treatment. Because rice yield correlates with soil ammonium N following rice transplanting (Mahapatra and Sharma, 1989), such conflicting reports of N fertilizer equivalence by legume N could possibly result from differences in timing and availability of urea N. 1 . N Fertilizer Timing

In addition to reducing the industrial N fertilizer requirements for rice, application of legume N to rice might conceivably alter the optimum timing and management of industrial N fertilizer for rice. Watanabe (1984) suggested that in temperate climates a basal application of 20 kg N/ha as industrial N fertilizer together with green manure can increase rice yield by increasing early tillering that can be retarded by toxins formed during anaerobic decomposition and by slow N release from green manure. Some researchers in the tropics (Meelu and Morris, 1988) have suggested delaying industrial N fertilizer application until about panicle initiation when green manure is incorporated before transplanting. Singh et al. (1987), in a field study with Sesbania green manure incorporated before transplanting on sandy loam soil, found greater rice yield when 60 kg urea N/ha was applied in equal splits at 21 and 42 DT (8.4 t/ha) rather than in equal splits at transplanting and 21 DT (7.7 t/ha) or as a single application at 21 DT (7.8 t/ha). When 120 kg N/ha was applied, grain yield was greater for three equal splits at transplanting, 21 DT, and 42 DT (9.0 t/ha) than for two equal splits at 21 and 42 DT (8.4 t/ha). The same timings of urea were not examined at both N rates, and results were for only 1 year. The transferability of these research findings, obtained on coarse-textured, highly percolating soils, to fine-textured soils is unclear. The effect of prerice treatment (fallow, cowpea incorporated at flowering stage as a green manure, and cowpea grown to maturity with grain and pods removed and remaining residues incorporated) on response of lowland rice to two timings of urea was recently studied in the Philippines. Incorporation of green manure and residue increased dry-matter accumulation and grain yield, but dry-matter accumulation (Table IX) and yield (Table X) were consistently greater with the early rather than the late

NITROGEN IN RICE-LEGUME CROPPING SYSTEMS

49

Table IX Effect of Urea Timing at 58 kg Nlha on Dry-Matter Accumulation of Lowland Rice at Los Banos, Philippines" Sampling timeh (DT) 30

45 60 Crop maturity ( 1 10)

Dry-matter accumulationc (t/ha) Early N split

Delayed N split

Difference

1.06 3.24

0.94 3.12

5.57 10.41

4.56

0.12* 0.12NS 1.01*

].IS*

9.26 ~

~~

~

Unpublished IRRUIFDC collaborative research. All values are the mean of 3 prerice treatments (fallow, cowpea green manure incorporated, and cowpea residue incorporated). The prerice treatment by N timing interaction was not significant ( p = .05). DT designates days after transplanting. Early N split designates N applied two-thirds basal incorporation without standing water and one-third broadcast at 43 DT (approximately panicle initiation). Delayed N split designates N broadcast one-half at 14 DT and one-half at 55 DT (approximately 10 days after panicle initiation). * Significant at .01 probability level. NS, not significant.

split of urea. The absence of a significant prerice treatment by urea timing interaction suggests that the early N split, which is recommended in the absence of organic N inputs, would also be the more effective urea timing when integrated with incorporated legume N. Table X Effect of Prerice Treatment and N Source Applied at 58 kg Nlha on Grain Yield of Lowland Rice at Los Baiios, Philippines" Grain yield (t/ha)

Difference (t/ha)

Prerice treatment

Urea, DSb

Urea, ES'

USG"

DS vs. ES

DS vs. USG

Fallow Cowpea, green manure Cowpea, residue Cowpea, residue removed

3.8

4.6 5.8 5.4 4.8

5.2 5.1

0.8** 0.8** 1.0** 0.9**

0.7* 1.4** 1.4**

5.0 4.4 3.9

5.8 5.2

1.4**

Adapted from John e t a / . (1989~).All values are the mean of 2 years. one-half at 14 days after transplanting and one-half at 10 days after panicle initiation. Applied two-thirds basal incorporation without standing water and one-third broadcast at 5 days before panicle initiation. Urea supergranule all basal deep placed. * Significant at .05 probability level. ** Significant at .01 probability level.

* Broadcast

50

R.J. BURESH AND S. K. DE DATTA

Additional research is needed; experiments should include treatments without and with legume N addition in factorial combination with urea management practices at multiple urea N rates. The findings will aid in determining whether the recommended N fertilizer management practice for rice remains the optimal practice when legume N is added. 2. N Fertilizer Source

Placement of urea as large granules, referred to as urea supergranules (USG), at about 10-cm soil depth between hills of transplanted rice is frequently more effective than conventional broadcasting of prilled urea on puddled rice soils (Savant and Stangel, 1990). Dhane et ul. (1991) showed that the superiority of USG over conventional broadcast urea can be enhanced with green leaf manuring. Basal application of 2 t/ha of Gliricidiu sepium toppings increased rice yield by 0.2-0.7 t/ha for splitapplied urea and by 0.4-1 .O t/ha for USG. Rapid release of plant-available N from the green manure presumably complemented the slower availability of N from deep-placed USG. Whereas the results in Table X indicate no prerice treatment by N interaction when comparing the two prilled urea timings, there was a significant prerice treatment by N interaction when comparing prilled urea and USG. The increase in yield from USG as compared with the yield from the delayed split of urea was less for green manure than for the other three prerice treatments. Nitrogen conceivably was no longer limiting yield in the treatment with green manure and 58 kg N/ha as USG, and a comparable yield might have been obtainable with less USG N. Experiments with multiple N rates for each N source are required to clearly ascertain the possible interactive effect of legume N on effectiveness of urea placement.

IX. CONCLUSIONS AND RESEARCH NEEDS Most research on N contributions from legumes in the tropics has focused on short-duration legumes grown and subsequently incorporated solely as green manures immediately before the monsoon rice crop. Food legumes are frequently grown as postmonsoon rice crops and then followed by a fallow period during the dry season before remaining legume residues may be incorporated with land preparation for the next monsoon rice crop. Little is known about the transformations, losses, gains, and recycling of N from postnce legumes.

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More effective nodulation of legumes and selection of food legumes for high residue production (App et al., 1980) merit consideration for increasing fixed N2 in rice-based cropping systems. Postrice forage legumes cropped in association with food legumes or cereals may offer opportunities for providing fixed N2 to the subsequent rice crop in addition to food and fodder production (Carangal et al., 1988; Miah, 1988). Little is known about N transformations and contributions to rice in these forage-food intercrops. Nitrification during nonflooded periods between rice crops and then subsequent denitrification when soil is flooded for rice may be an important avenue for N loss. Little is known about the influence of legumes on these losses and the probable losses of legume N by nitrificationdenitrification. Research is needed to determine whether legumes influence losses and availability of native soil N by cycling soil nitrate N through residues incorporated before rice (George et al., 1990). The inclusion of legumes in rice-based cropping systems could conceivably result in enhanced formation of methane during anaerobic decomposition of leguminous plant material and in enhanced formation of nitrous oxide during nitrification and denitrification of legume N. Methane and nitrous oxide are greenhouse gases, and they have been linked to depletion of ozone in the stratosphere. Research is needed to quantify methane and nitrous oxide emissions in lowland rice-based cropping systems with and without legumes. Cultural practices should be developed to minimize the emissions of these gases from lowland rice fields. Integrated use of industrial fertilizers will be essential for sustained high yields in most rice-legume systems. Nitrogen from leguminous green manure and residue normally only partially meets the N requirements for a succeeding high-yielding rice crop. Moreover, P and micronutrients can limit legume production, particularly in infertile, acid soils. Effective inoculation may also be necessary for high N accumulation by legumes, especially when soybean is newly introduced to an area. The limited estimates of N2 fixation by legumes on ricelands suggest that in many situations with food legumes, the N removed by the grain exceeds the N2 fixed. Moreover, residues are often used for animal feed rather than as an N source for the succeeding rice crop. The N contribution of legumes in lowland rice-legume sequences, as in upland crop-legume sequences, depend on the quantity of legume N derived from N2 fixation, the NHI, the proportion of legume N mineralized, and the efficiency of use of this mineralized N by the succeeding crop (Myers and Wood, 1987). However, the anaerobic-aerobic soil cycles typical of lowland rice-legume sequences can lead to higher losses of N than would normally occur in upland crop-legume sequences, in which the soil is not flooded. Losses of nitrate N, formed from mineralization of soil

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ADVANCES IN AGRONOMY, VOL. 45

PLANT GENETIC RESOURCES: SOME NEW DIRECTIONS J. T. Williams International Fund for Agricultural Research (IFAR) Arlington, Virginia 22209'

I. Introduction 11. Development of Global Activities A. The Framework for Global Activities B. Availability of Material C. Security of Materials D. Progress on Collection and Conservation of Crop Gene Pools 111. Areas of Research Which Impact Plant Genetic Resources Work A. Increasing Production B. Wild Species C. Stabilizing Production D. Agroforestry IV. Sustainability A. General Issues B Plant Genetic Resources Research for Biodiversity Conservation V. Current New Directions in Germplasm Management and Research A. Cooperative Networking B. Management of Collections C. Safety of Collections D. Links to Applied Research VI. Concluding Remarks References

I. INTRODUCTION Activities on plant genetic resources have accelerated greatly in the past two decades. Many of the constraints associated with sampling gene pools and conserving and documenting materials have been removed in the case of crop and forage species; programs have been initiated in scores of institutions and countries. The time has come to review the progress made and assess how the systems serve agronomists and plant breeders, and to look further at new directions that the scientific community needs to follow to ensure susI

Address correspondence to 161I North Kent Street, Suite 600, Arlington, Virginia 22209. 61 Copyright Q 1991 by Academc Press, InC. All rights of reproductionin any form resewed.

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tained synergies between conservation and utilization. Such a review is timely because of a number of international developments: 1 . There is a widespread concern about the preservation of biological diversity, both genetic and ecological; there are overlapping needs for germplasm conservation and use for crop and forestry development and also ecosystem preservation. 2. There are major human population increases predicted especially in those areas where habitat protection is most needed and where land degradation and forest clearing continue. 3. There are major challenges in introducing sustainable agricultural systems that do not force a trade-off between current and future production but which meet expanding production needs. 4. Sustainable use of the environment, in both fragile areas and those of intensive agriculture, is essential, and agroforestry methods are now of great interest. 5 . The methodologies for using genetic resources to enhance crops have changed with the advent of new molecular techniques, and the types of materials useful in germplasm enhancement are now wider than envisaged in the past.

Recent years have highlighted the need to explore opportunities for integrated and well-managed farming systems that aim toward a decreased use of pesticides, fertilizers, and other chemicals. In this context it is expected that the sustainability aspects of emerging agricultural production systems include provisions for conserving biological diversity in the planning of development. Because of these concerns, those involved with the collection, conservation, and use of plant germplasm need to review how their current programs will meet actual needs in the immediate future. Perhaps the scientific community, in instituting its plant genetic resources programs, and expanding them over the past 2-3 decades has not always been aware that this time period has witnessed more adverse use of the environment and larger human population growths than have ever been witnessed in an equal period of time on this planet.

II. DEVELOPMENT OF GLOBAL ACTIVITIES A brief history of the development of global activities is necessary in order to appreciate the new directions needed in plant genetic resources work. The current activities grew from small beginnings in the 1960s. Crop scientists were aware that loss of diversity was inevitable as a result of

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agricultural development. This loss of diversity, or genetic erosion of the crop gene pools, was largely the loss of primitive populations, or land races, which had evolved over long periods of time under conditions of peasant agriculture. Certain regions of the world showed rich diversity for particular crops and traditionally plant breeders had been able to obtain materials from these regions for testing and use in crossing. The knowledge that this would become increasingly difficult led to proposals to collect and conserve samples of important staple crops, especially since the revolution stemming from the ever wider adoption of new high-yielding varieties of wheat and rice. At that time we saw the foundations laid for the establishment of international agricultural research centers (IARCs) which, in 1971, were to be associated into the Consultative Group on International Agriculture Research (CGIAR). In relation to crop genetic resources, the Food and Agriculture Organization (FAO) took a lead role in pointing to the needs and identifying priorities for collection and conservation; collaboration with the International Biological Program of the International Council of Scientific Unions strengthened this. Two parallel efforts made the voices of scientists more creditable; one was the establishment by the Rockefeller Foundation of committees to assess how complete were existing germplasm collections of major staple food crops (such as rice, wheat, maize, and sorghum), and to create field collecting teams to fill major gaps. These collections became integral parts of collections of existing, and still to be founded, IARCs. The second effort was a 1972 report of the U.S. National Research Council on genetic vulnerability, which addressed the need to meet future challenges to the adequacy of crop germplasm collections; this effort stemmed from implications of the southern corn blight epidemic. These and other efforts led to the creation of the International Board for Plant Genetic Resources (IBPGR) in 1974 as a center of the CGIAR, with a special relationship with F A 0 in Rome, Italy. The voices of crop scientists were echoed by the voices of those dealing with forestry, and again F A 0 took the lead. Whereas initially interest was aroused in collecting and conserving gene pools of widely used tree species, this interest is now concerned with genetic resources a p e c t s of arid and semiarid zone forestry and desertification control, agro-silvo-pastoral development, integrated watershed management and protection of the resource base leading to a major initiative such as the F A 0 Tropical Forestry Action Plan, and the call for action of a task force convened by the World Resources Institute, The World Bank, and UNDP in 1985. A number of these activities were foreshadowed by the consolidation in 1981 of a world conservation strategy through international conservation orga-

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nizations. The strategy influenced the larger conservation movement to think about plant genetic resources as integral to their activities. Up to now these diverse activities have developed with varying degrees of collaboration, often with recognition of common interests but, in practice, rarely with integrated scientific activities. Additionally there are now intergovernmental activities with the F A 0 promulgating an international undertaking and organizing a commission to oversee the implementation of the undertaking. The terms of reference of these F A 0 endeavors cover the wide range of plant genetic resources activities from work on crop gene pools to nature conservation. FOR GLOBAL ACTIVITIES A. THEFRAMEWORK

The programs that currently serve the needs of plant breeders and agronomists have grown out of programs that addressed specific needs. There were prototype genetic resources programs, which became greatly strengthened in countries such as the United States, the Soviet Union, Japan, the German Democratic Republic, and India; new genetic resources programs such as those of IRRI (rice), CIP (International Potato Center; potato), CIMMYT (wheat and maize), and later those of ICRISAT, ICARDA, IITA, CIAT, and ILCA for a range of crops and forages; and programs initiated de n o w largely through the stimulation of IBPGR. In the 1970s and 1980s there was the need to “build up” the collections and IBPGR put major emphasis on supporting widespread collecting of germplasm, due to the threat of genetic erosion, and early emphasis was on land races and primitive varieties. This emphasis was paralleled by stimulating the establishment, or scientific upgrading, of conservation facilities so that the materials could be stored and subsequently described. Numerous national programs became established. In the early years of IBPGR a number of attempts to organize regional programs faltered and the operational unit emerged as the national program. The global system that rapidly emerged resulted in the current wide array of national programs, some weak, some strong, and also the programs of the IARCs, all loosely federated according to mutual interest. The past few years have pointed to the real operational units being networked into an arrangement of institutions and scientists dealing with the germplasm of a particular crop rather than networks of national gene banks. It is now possible to envisage national collections as components of dispersed world collections of genetic resources of a range of crops. IBPGR is currently testing the feasibility of establishing such multidimensional networks by identifying participants and helping them to work

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together to determine the uniqueness of samples, the degrees of redundancy in collections, duplications for safety, and other joint activities. Ironically this approach would have been a logical follow-up from the early efforts of the Rockefeller Foundation mentioned above, but because in the 1970s and 1980s the global program was being built up with development assistance funding, a technical assistance approach was needed and asked for.

B. AVAILABILITY OF MATERIAL It has been a cardinal principle that crop genetic resources should be freely available to all users-breeders and scientists-and it has been widely observed in the past. Some governments have adopted policies of restricting the availability of genetic resources but these restrictions are largely related to industrial crops such as coffee, pepper, and others. A number of these examples-which do not accord with the international consensus-emerged in a period when great attention was being paid to mobilizing technology for world development. Political and economic considerations of the consequences of technological dependence in the least developed countries were pointing to the need to discover mutualities, to rectify the unease felt as a result of previous often shortsighted actions, and to find new possibilities and practices in the so-called NorthSouth relationships. It is not surprising that unease at the only existing global “system,” that of IBPGR, to make material available as an act of voluntary collaboration was expressed in the early debates leading to the international undertaking of FAO. There is no conflict because the whole international community wishes to see enhanced freedom in the availability of materials, but the discussions are useful to identify the constraints on programs in poor countries. Constraints and availability are interrelated and because availability relates to good management of collections (Chang et al., 1989). Additionally, there have been a number of misunderstandings on the “values” of germplasm and potential recompense mechanisms, which form a continuing dialogue, often to the bewilderment of the scientists involved in the practical work on genetic resources. C. SECURITY OF MATERIALS Seed materials are dried and stored at low temperatures for conservation. Such conditions obviate the need for frequent grow-outs to regenerate stocks. The more stringent storage conditions (base collections)

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ensure longer periods between regeneration and provide a degree of security. In order to avoid any disasters, duplicates are held elsewhere in other base collections. IBPGR built up a group of centers in all parts of the world which agreed to hold the germplasm of particular crops in base collections. Seeds, when they can be stored, are convenient units to handle because they have the full set of genetic information in the embryo, and most seeds are relatively small. Seed physiology research has provided scientific guidelines on the preparation and storage of seeds to assure long-term viability. Research in progress is aimed generally at more cost-effective storage, for example, the use of ultra-low seed moisture content as a substitute for low temperatures or the use of natural environmental conditions that save energy costs. Most of the major crops can be stored ex situ as seed in gene banks; however, some cannot. These are either clones that cannot be reproduced from seeds, certain trees with large seeds that have high moisture contents, or some crops that are sexually sterile. These types of materials are conserved as vegetative material (plants) in field gene banks but their security is not assured until better methods can be organized to maintain them as small pieces of tissue in culture. D. PROGRESS ON COLLECTION A N D CONSERVATION OF CROPGENEPOOLS

The major efforts on collecting germplasm, the priorities accorded over the past 15 years, and the development of facilities to conserve the collected materials have been described in the annual reports of IBPGR, in Williams (1985), and in Plucknett et al. (1987). These will not be reviewed here as the purpose of this paper is to highlight new directions in the shortto medium-term future.

Ill. AREAS OF RESEARCH WHICH IMPACT PLANT GENETIC RESOURCES WORK A. INCREASINGPRODUCTION

The success of crop production depends on the availability of appropriate germplasm and the sources of the samples of germplasm. In addition, the manipulation of the germplasm has changed markedly in the past 100 years (Duvick and Brown, 1989). Manipulation of germplasm through

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plant breeding, and use of the appropriate agronomic practices (tillage, monocultures, fertilizers, etc.) are the basis of modern agriculture. The germplasm used routinely is largely highly selected; this is essential as new cultivars rapidly replace each other. Breeders tend to use elite materials, rather than primitive, relatively unselected forms such as land races, because of the undesirable linkages in the latter. Whereas the land race material is adapted to the site of origin, it is rarely adapted for the new breeding aims, and additional generations of selection are not wanted by the breeders. Despite these generalities, crop breeding strategies continually require diverse sources of germplasm, often materials of the specific crop from widely separated geographical areas. Vavilov, the founder of the U.S.S.R. genetic resources work, exploited this principle. It was also an important aspect of the green revolution in cereals, for example, the dwarf wheats bred from hybrids between East Asian and U.S. cultivars (and the form used from Japan had in its lineage earlier U.S. cultivars). There are two aspects to continuing production; first, efforts to maintain stable production. and second, those to improve yield. The germplasm collectors and the curators of genetic resources collections bear heavy responsibilities because their decisions result in what is actually available for breeders, even in the future. The presence or absence of an allele can only rarely be supposed when plants are looked at in the field. Also, variation seen by the eye may be environmentally determined. Hence “looking for useful genes” is not tenable. Since breeders need specific alleles to transfer in their crossing program, should the strategy for collecting be to collect alleles (seen as a specific character or unseen, e.g., a resistance gene), or to collect genotypes? The widely accepted practice is to collect populations of genotypes because, in effect, breeders require certain alleles in plants that will be used as parents with general adaptation to the environments to which the progeny are aimed. The pragmatic decision is that germplasm available to breeders should represent an assemblage of populations from the range of geographies and ecologies of the crop gene pool without bias as to the presence or absence of rare alleles. In this way the required alleles will be present in the spectrum of genetic resources samples. Except for a few major crops, such as rice, this strategy has rarely been implemented since collections have been built up from amalgamation of old breeding samples along with certain recently or newly collected samples. As a result, the collectors and the curators have an urgent need to “sort out” the materials and document them properly, for example, by aggressively seeking missing collecting site data still in notebooks and by planning targeted new collecting. In this way the samples will be more accessible to breeders in their efforts toward continuing production.

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The current situation for many crops is that genetic resources exist and are available but are not yet known well enough for widespread use despite, for major crops, the existence of relatively large collections of land races. In practice, a great deal of diversity has been amassed for conservation by the salvaging of land races, work spearheaded by IBPGR in 1978-1988. This leads to the question: what more needs to be collected? Numbers of accessions in lists are an inadequate guide. Furthermore, there will always be needs and opportunities for supplementing the collection. Additionally, the emphasis has moved markedly towards incorporating samples from the wider gene pools, rather than solely from the cultivated ones.

B. WILD SPECIES Recent decades have seen interest in wild species related to cultivated plants as research has been carried out to elucidate evolutionary relationships and to understand how closely the species within gene pools are related and which species are the progenitors. Cultivated plants are relatively recent in time and the course of evolution of the wild species probably spanned millions of years during which gene mutations accumulated. In the field, some related wild species hybridize with domesticates when distributions overlap and introgression goes in both directions; weed races often occur, and Harlan (1975) saw this genetic enriching as a causal effect in creating microcenters of diversity. Due to the environmental changes that have occurred in relation to agriculture, of course, the currently seen ecologies of some related wild species may not be the same as when domestication took place. Nonetheless, the ecological amplitude of wild relatives may far exceed those of the crops developed from them. Hybridization between wild species and domesticates, especially in the 1970s, showed the potential of wild germplasm. For instance, expressions of heterosis or transgressive segregations for yield occurred in many crops: pearl millet, sorghum, barley, rice, wheat, maize, egg plant, sweet potato, oat, potato, groundnut, tobacco, and sugar cane. Maybe most interest stemmed from wild relatives proving to be sources of resistances to diseases and pests, but other attributes related to quality were also obvious in some cases. Use of wild species in breeding was largely limited by the ease of crossability but interest was apparent in the scientific community because of the widespread trend to narrow the genetic base of cultivars. Where the base was considered to be too narrow, breeders introduced germplasm from exotic cultivars when new sources of resistance were needed as in the case of soybean breeding in the United States. Duvick and Brown (1989)

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used this example to illustrate that backcrossing to eliminate as many as possible of the other exotic genes became supplemented with screening exotic cultivars for useful agronomic traits, and deliberate attempts were made to introduce maximum amounts of exotic germplasm into the elite background, thereby providing desirable agronomic backgrounds to new breeding stocks. Breeding materials are now far removed from the few original accessions which had been used as the basis for U.S. cultivars. Concern in the 1970s at narrowing the genetic base of crops, with possible problems of vulnerability, have indeed led to narrowing and broadening cycles in a number of crops. However, as mentioned in the case of soybean, o r for sorghum, wild species were not needed for these efforts. Although wild species are vital resources for breeders, they are usually used as a last resort and depend on the breeding history of the crop; they are rarely used in breeding barley, wheat, and maize but more frequently in potato, sunflower, and peanut. Two factors have caused advances in the use of wild species in breeding. The first has been the recognition, especially in the 1980s, of widespread environmental problems, loss of fragile ecosystems, and over-exploitation of natural areas, many of these the homes of the wild species. The second has been advances in biotechnology, which have made wide crossing easier and which provide new opportunities for crossing between more remotely related species. Breeders will never use wild species if they can find the genetic diversity they need in the cultivated germplasm. Hence the plant genetic resources community had to accelerate collection and conservation because of the threats to species’ gene pools and because rapidly developing genetic engineering was bringing these species quickly to the stage where a whole new resource will be available for exploitation. IBPGR accorded high priority to this work (Williams, 1985); long-standing work on building up collections of wild species of rice and potato at IRRI and CIP were supplemented by new or newer programs on peanut (IBPGR, U.S. and ICRISAT), sweet potato (IBPGR and CIP). pearl millet (IBPGRand ICRISAT), and Triticeae grasses (Chapman, 1989). In parallel with these shifts in emphasis the scientific community had witnessed a wide exploitation of biochemical methods. lsozyme research became commonplace in the early 1980s as tools for plant breeders, population geneticists, cytogeneticists, and others. Although many of the isozyme systems with the most promise had been known since the term isozyme had been coined (Markert and Moller, 1959), their application to help design experiments to introduce alien chromosome additions with markers was more recent. Whereas wide hybridization was used largely to generate new allopoly-

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ploids (e.g., Triticale) and as a mechanism to introgress genes from wild species into cultivated stocks, in uitro techniques became available to overcome barriers seen in attempts to obtain interspecific or intergeneric hybrids. They do not replace the value of allopolyploidy, which will remain a tool in reconstructing old crops or creating new ones or broadening genetic bases. Allopolyploids have the possibilities of new character combinations, increased vegetative vigor, and permanent hybridity (Simmonds, 1979). When wild relatives differ in ploidy level from the crop species creation of allopolyploids is a useful step in transferring desirable genes. Additionally, the use of highly heterozygous autopolyploids as parents for allopolyploids can generate variability. Although chromosome doubling cannot be used to produce these parents, protoplast fusion to produce somatic hybrids is one method. The in uitro techniques now used to overcome problems are: 1. Embryo culture. Immature embryos that abort can be rescued and transferred to in uitro culture, thereby permitting development that would not otherwise occur and producing a plant that is an interspecific hybrid. In some cases hybrid ovules-or whole ovaries-can also be cultured; 2. In uitrofertilization. Methods have been developed to culture ovules and pollinate them aseptically using diverse parents. A low number of these can sometimes produce plants; and 3. Somatic hybridization. Although not as widely used as originally envisaged, naked protoplasts have been fused, induced to divide, and plants regenerated, the latter being often the most difficult (Jensen, 1981).

Additionally, in uitro methods are used to aid pairing of chromosomes in alien crosses. This is done by generating substitution or addition lines by preferential elimination of most of the chromosomes of one genome. Culture may also increase genetic recombination between two genomes used in wide crossing (Orton and Steidl, 1980; Larkin and Scowcroft, 1981). Such experimentation also led to clearer recognition that plants regenerated from cell and tissue culture often exhibit variability not seen in the parental material (“somoclonal variation”) and that this can be used in breeding (Scowcroft, 1985). Options in breeding using somoclones were taken up by potato breeding programs, for example, in the United States, the United Kingdom, and the Federal Republic of Germany. A wide range of other programs can be found in the literature but problem-solving ideas are perhaps the most exciting, such as the development of resistance to black Sigatoka disease in Musa [Fischer, in International Institute of Tropical Agriculture (IITA), 19881. The literature is now so wide on the combined use of in uitro techniques,

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isozyme techniques. and breeding that wide crossing, and hence a much heightened interest in wild species as genetic resources, is firmly established, vindicating in part the pleas of a number of early founders of the genetic resources movement to pay more attention to wild species. It is not the purpose of this review to summarize all these scientific developments which, through user-driven demands, have caused a coalescing of interdisciplinary sciences, but rather to pose a number of questions that have not clearly been resolved and that will inevitably prompt new directions in scientific work in the immediate future. To further develop current systems so that specific areas of research can be addressed in a meaningful way, various constraints must be surmounted. These constraints are discussed next. In the first instance it is extremely difficult for any one institution to maintain a world collection. When IRRI was planning its strategy for the wild rice species it became apparent that location of their research in Los Baiios was not the most conducive to growing and regenerating all the wild species. Similarly, when a world collection-invaluable for research, prebreeding, and breeding-is established, it relates to the interests of the scientists and the institution where it is developed. A case in point is a world collection of wild material of Hordeum sensu lato at the Swedish Agricultural University. Materials from China, Peru, Mexico, California and Arizona, U.S.A., and scores of sites in the Mediterranean, Southwest Asia, and elsewhere represent very diverse ecologies posing major constraints on growing-out of samples and on maintaining populations as accessions in a genetic resources program. Nor would constraints, in any way, be removed if the collection was handed over to an IARC with responsibility for breeding barley, in this case ICARDA in Syria. Other collections of wild species exhibit similar constraints, whether they be several collections of wild potato species (variously at CIP, Peru; Sturgeon Bay, U.S.A.; Dutch-German Potato Genebank at FAL, Braunschweig, Federal Republic of Germany; Commonwealth Potato Collection, Scotland, U.K., or the collection at VIR, Leningrad, U.S.S.R.), groundnut (ICRISAT, India; or Texas, U.S.A.), or wheat (VIR, U.S.S.R.; Kyoto/National Seed Storage Laboratory, Japan; ICARDA, and others). IBPGR has clearly stated that most of these species are best left in the wild unless they are under threat. This is logical but conflicts with ( 1 ) the emerging needs for readily available samples for use, and (2) the needs to develop strategies on how wide specific gene pools need to be for future utilization with the rapid advances in biotechnology . It is my opinion that the full range of constraints to effective genetic conservation of wild species gene pools will not be removed by merging these special collections with those of cultivars. There are several convincing arguments for this opinion. First, most collections of cultivars are

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held in gene banks associated only with expertise in agronomy and traditional breeding; few such gene banks have access to facilities for embryo rescue nor staff well qualified in seed physiology and handling of wild species. Additionally, a range of accessions representing populations must be maintained and there is a tendency for collections to be species collections of a botanic garden type rather than a collection of wide gene pool diversity. Much more emphasis needs to be placed on developing a strategy for the collection and on how to build it up (e.g., for wheat, see Chapman, 1985). The newer concept of IBPGR to network collections will not remove the constraints on maintaining wild species collections, because they are best left in the hands of competent scientists with subsets kept along with the cultivated materials. Each crop will need to be sorted out on a case-bycase basis, and I expect that the special purpose collections need to go on being maintained in a diversity of institutions, whether they be specialist gene banks or university research departments. I have attempted to get IBPGR involved in devising a strategy for this and seeing that funding for genetic resources work-largely at present from development assistance funds-takes into account these other requirements. Additionally, with the world’s botanic gardens becoming organized through IUCN (International Union for the Conservation of Nature; Bramwell et al., 1987) and becoming educated slowly away from specimen collections to those of genetic diversity (Williams and Creech, 19871, the synergies are apparent and provide a clear base for strategic planning. Additional scientific interests in in situ conservation of crop relatives (e.g., barley in Israel) which can be sustained into the future will have to be built into the strategies, but by far the greatest synergy will be between preservation of populations of perennial species in in situ reserve areas and the germplasm in ex situ collections. There are great opportunities here, but to date little progress because, I suspect, getting the institutions with vested interests together is not the prime catalyst, due to funding situations; rather, the catalyst is the commissioning of scientific, institutionneutral strategic planning on their behalf. These questions are complex because the range of vested interests extends more widely than, on one hand, plant genetic resources interests, and on the other hand, interests in ecosystem preservation. Until recently, it was possible to address these in a mutual way (Frankel and Soule, 1981; Williams, 1982; Ingram and Williams, 1984);however, the whole question of biodiversity has assumed major significance and so too has sustainable use of the environment, particularly in relation to peasant populations in threatened areas. There is a tendency for compartmentalization of interests at the funding level, an explosion of interests in the areas of overlap-

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ping science, and we need a much clearer set of well-defined cooperative activities based on a diversity of institutional relationships. For instance, the People’s Republic of China assigns responsibility for cultivated germplasm to the Academy of Agricultural Sciences and for wild related germplasm to the network of botanic gardens; contrast this to the National Plant Germplasm System of the United States where they are integrated, or to IARCs where they may be integrated, or where wild species are covered by networking with other institutions. This makes strategic planning all the more essential in order to put in place the mechanisms needed now, not 5 or 10 years down the road. In some cases the wild species collections already serve a range of crop users. The wild grasses of Triticeae, to be found over a large portion of the earth’s surface, are of current interest to breeders of barley, wheat, rye, and to forage breeders. Currently collections exist for scientific research or for breeding of a specific crop; few are represented by high-quality seed accessions in long-term storage, and cooperation is almost wholly on an ad hoc basis. It should also be remembered that many crops not far removed from wild species genetically are those of major interest in sustainable development in the rural conditions in the tropics and subtropics. Many of these are perennials for which no adequate germplasm collections exist. For any enhancement, ex situ collections are essential and this area has been totally neglected up to the present. The problem has received minimal recognition by any international organization, and funding is virtually nonexistent since these materials hitherto have been outside the interest of food crop or forage development. Conservation of this type of material has to be put in place in relation to productive use; if not, it remains an imperative for ecosystem preservation. Whereas cost efficiency is now ranking high in terms of ex situ conservation of staple food crops, little attention and virtually no strategic research has been carried out on perennial materials in the tropics. A recent paper on management and use of collections stated: “The costly investment in plant germplasm collections must be justified by profitable returns through use and further enhancement,” and further, “The wild species generally remain the least conserved and little exploited category, although impressive advances in breeding have been attained in several crops such as wheat, rice, tomato, sugarcane and tobacco, with genes contributed by the wild taxa” (Chang, et al., 1989). In relation to a whole series of crops, these sentiments, based on work with major crops, will require reinvestigation. Lastly, as mentioned earlier in this section, the collection of wild species has shown significant advances. In the early 1980s “best-guess” as-

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sessments of the state of collections of wild relatives were made for the major food crops and progress since then has not yet been synthesized into a review. IBPGR might find this a useful exercise to promote support; it is unlikely that it can await new networking proposals with the subsequent time-consuming sorting out of collections. It is also becoming increasingly obvious that “yellow pages” in the form of directories of germplasm collections, so urgently needed over the past 10 years, no longer fulfill the information needs of enquirers. This was the opinion expressed by scientists at a meeting of the Institut de la Vie, in Washington, D.C. in May, 1990, which proposed a new program to address new and already apparent information needs. C. STABILIZING PRODUCTION In recent years attention has been paid to the phenomenon of variability in yield, and the question has been asked whether new production technologies and modern cultivars are inherently more variable. There is general agreement that yield variation can be greater when high-yielding modern cultivars are used, and that average yields continue to increase due to wider use of such cultivars along with the modern inputs that such cultivars are able to exploit. An important workshop on this question was held under the sponsorship of JFPRI and the German Stiftung fur Internationale Entwicklung/Zentralinstitut fur Ernahrung und Landwirtschaft (Hazell, 1986). Is there a correlation between variability of yields in modern agriculture and the narrowing of the genetic base related to the development of the successful cultivars; and what attention do breeders give to the development of cultivars with high and consistent performance? Holden (1986) points out that breeders achieve this latter goal by ( I ) purposive breeding from parents selected for their ability to give stable progeny, and (2) selection among advanced lines of progenies not specifically bred for stability, and through multisite trials to select those with more stable yields. Nonetheless, the priority given to yield stability in breeding programs will depend on the agricultural system where the cultivars will be grown. If, for instance, the farmer can control the systems by irrigation and chemicals, selecting for genetic stability may be less important than emphasizing yield. In many developing countries, local organizations still need to learn how to manage the newer high-yield cultivars. Agronomy becomes the overriding question, rather than extensive manipulation of the genetics of the cultivars. There is no evidence that the variability results from the narrowing of the genetic base; attempts to experiment with mixtures of pure lines, thus providing a degree of buffering due to heterogeneity, have not led to major

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advantages since management is difficult. Comments have often been made that the old land races, as mixtures of genotypes, provided a degree of stability, but comparisons with modem cultivars are spurious in that the latter are successful in producing high yields and have made adaptations and good resistance to environmental stresses. Duvick and Brown (1989) have eloquently pointed out that today’s practice of using genetic diversity in time-by genotype replacement over time-is more or less equivalent to the primitive practice of using genetic diversity in place-by hetrogeneous land races. They stress that even in primitive agriculture, diversity in time also occurred but at a slower rate. Modern breeding exploits in a purposive way sources of diversity and wide ranging germplasm exchange, phenomena of modern agriculture. A clear understanding of this somewhat negates well-intentioned efforts to conserve old land races on farms under conditions of primitive agriculture. Breeding for stability is therefore largely part and parcel of breeding for increased yield. It requires readily available germplasm from a wide range of sources, which has to be conserved and characterized and will rarely rely on locally conserved stocks, whether in a gene bank, or on a farm, or in some type of reserve. Genetically diverse parents from diverse areas will remain the key, and products of breeding have to be coupled with specific agronomic practices whether high- or low-input. Breeding programs for most crops have also shown that breeding for stresses such as drought requires screening of a wide gene pool rather than simply the pool of advanced material; the same occurs for disease resistances. Hence genetic resources will continue to be essential on a continuing basis.

D. AGROFORESTRY 1 . Past and Current Directions The development of farming systems that are sustained over time has constantly changed since the dawn of civilization, and historical changes have related to changing pressures on resources. The widespread alarm over environmental changes in recent decades also relate to changes in areas of productive capacity. According to FAO, 16.5% of the rainfed cropland in Africa will be lost by the year 2000 without renewed and improved management efforts; UNEP estimates that at least 80% of the croplands of the and to subhumid zones in Africa have lost a significant portion of their productive capacity. Clearly, these examples point to the need for new strategies because unscientific land-use practices on marginal soils rapidly cause soil erosion. Agroforestry provides one answer to a number of problems. It involves the integrated cultivation of woody species, mostly perennials, with crops

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and animals, so that in a symbiotic way, ecological interactions between woody and nonwoody plants sustain and diversify total output. Some agroforestry systems are ancient. Shifting cultivation where trees and crops alternate in time and space has continued in some areas (e.g., Amazonia) for millennia. However, due to population pressures, most of these systems are now out of balance, promote soil degradation, and lead to land degradation. For more than 15 years major international efforts have highlighted the need for modem agroforestry systems that combine food production with environmental protection. The International Council for Research in Agroforestry (ICRAF) was established in 1977 following a study initiated in 1975 by IDRC to address problems of tropical forestry. ICRAF began examining the technological and socioeconomic constraints limiting the spread of agroforestry practices, and other studies (e.g., a study of the Board on Science and Technology for International Development) stressed the urgent need for work on shrubs and trees for fuelwood production. It was widely appreciated that the demand for woody plants for various uses could not be met by the existing supplies of appropriate germplasm. Despite a plethora of terms-village forestry, agroforestry, community forestry, social forestry, agrisilviculture, and others-it took some time for scientists to distinguish between trees for forestry and trees for agroforestry. Until then there was no need to distinguish between them but that rapidly changed with the emergence of the concept of multipurpose trees. Information on plant materials that could be used in agroforestry systems was scattered, hence it was necessary to collate information available in the literature on species suitable for agroforestry. There are two problems: first, there is no distinct group of species; and second, most woody crops for use in agroforestry situations had been developed to suit monocropping. Essentially a starting point is indigenous knowledge since peasant farmers have adapted tree species to their particular agricultural and dietary needs. Often the peasant systems were low-input and agroforestry was always seen as integrated land use especially suited for marginal areas and low-input systems. ICRAF carried out a survey in 1978 that showed that some forms of agroforestry occur in almost all developing countries of the world, for example, the tanungya system, which spread widely from Burma for hill cultivation where the initial stages of forest plantations include agricultural crops. Research needs were many and ranged from identifying suitable forest species that permit an understudy crop to testing the shade tolerance of various agricultural crops. Emphasis on the research that resulted was heavily geared to the location-specific nature. Nonetheless, a number of generalizations were possible. First, agroforestry systems are essential for

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consideration in degraded situations or fragile environments and hence have major application in arid and semiarid zones, shifting cultivation areas, acid range areas of the tropics, and in areas of mountain agriculture. Second, the methods of admixture of species, although dependent on soils, climate, management, and other needs, can be grouped into broad categories: for example, intercropping (trees with agricultural field crops); planting shade-tolerant woody crops in strips in primary or secondary forests to provide a canopied mix of tree crops and forestry species; close planting as wood lots around habitation and as fences, windbreaks, etc. ;planting trees in a planned manner between areas of traditional agriculture; and specific methods to retain soil in hill areas or zonal strips in arid areas using shrubs for fodder and mulch. A number of publications gathered together data scattered in the literature, for example, on suitable agricultural species, both field crop and woody (Nair, 1980), on specific types of trees and shrubs for regions such as the Sahel, or for management of specific soils. The intensification of interest in understanding and designing agroforestry systems was spurred by two other factors. On one hand, a great deal of research had been done on multipurpose leguminous trees and shrubs and they were being widely used to address rural needs (e.g., Sesbania, see Brewbaker and Hutton, 1979; Leucaena, see Felker, 1979; Prosopis, see Saunders and Becker, 1989). On the other hand, attention was being paid to ecological development needs in the tropics with an aim to plan better for sustainable development through managing and conserving renewable resources (Lug0 et al., 1987) and data were beginning to flow from important development projects, especially in the tropics. What was the situation for plant genetic resources? With regard to agricultural field crops for use in agroforestry a great deal was known from agricultural research, although information on suitable genotypes of tropical tree crops has rarely been recorded. In some cases the information is rudimentary (e.g., “vanilla grows best under trees”), but there is no information other than on a limited number of varieties that form the basis of vanilla cultivation. Nothing is known about the potential of primitively cultivated forms in Central America; essentially successful incorporation into agroforestry schemes will be measured by how far the optimal growth requirements will be satisfied and by what effect the modified (i.e., agroforestry) environment will have on the growth and productivity of the species (Nair, 1980). A number of less familiar perennial food crops-breadfruit, peach palm, numerous oil-producing palm species, caryocar, jojoba, cow tree, perennial pigeonpea, mesquite, and others-are noted as having considerable

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potential for contributing to the more usual production from annual staple crops in intercropping situations (Rachie, 1983) but it was recognized that research is essential, including plant exploration, for the perennial species, their selection for complementarity with other crops, and specific genetic improvement under appropriate management techniques. Rachie stressed the real need for plant exploration for economically useful new perennials and tree crops. Research should stress those with established potential, which could then be more extensively collected, and genetic improvement and agronomy could be studied. Although we have seen over the past decade a certain amount of interest in some of these species, and although collecting has occurred (e.g., peach palm, Clement and Arkcoll, 1989; other native neotropical palms, Balick, 1989; and breadfruit, IBPGR, 1988), much more remains to be done before specific genotypes can be selected for specific agroforestry systems. For example, projects tend to use “likely” sources that may or may not be successful. In a trial in the upper Ecuadorian Amazon survival of fruit trees grown in combination in pastures showed Annona, avocado, breadfruit, guaba (Inga edulis), and guava (Prentice, 1979) giving vigorous growth on good sites and only guava on poor sites. There are weedy local forms that could be selected for poor sites but such gemplasm was not available for use. Long-standing research and development using nitrogen-fixing trees and others popularly grown (e.g., eucalypts and shrubs) have provided data and new plant management patterns, such as provision of fuelwood and/or wood under regimes such as pollarding or coppicing, either alone in woodlots or in agroforestry situations. An important stage in considering genetic resources was a workshop held by ICRAF, IBPGR, and CFI (and sponsored by ICRAF, IBPGR, and GTZ, Germany) in 1983 to discuss multipurpose tree germplasm (Burley and von Carlowitz, 1984). This examined existing priorities provided by F A 0 (largely from recommendations of a panel of experts on forest gene resources, IUFRO, CFI, CSIRO, NAS, NFTA, and others) and pointed out that it is clearly desirable to establish coordinated and compatible systems of data handling and to make these available. There is a need to short-list candidate multipurpose trees and shrubs, and ICRAF has built up a database of over 1,000 species which can be used for preselection, based on computerized matching of sites, uses, and tree characteristics and which focuses on species most likely to succeed in a given environment, technology, and land-use system (von Carlowitz, 1989). However, germplasm collections to supply a wide diversity of these candidate woody species hardly exist.

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2 . New Directions f o r Plant Resources Used in Agroforestry Although the 1983 workshop referred to above initiated a discussion on genetic resources collection, conservation, documentation, and use, it considered that prioritization was not easy since it needs to be considered at various levels: local, regional, and global. Existing lists, for example, those of F A 0 for fuelwood, multipurpose lists of IUFRO, master lists of nitrogen-fixing trees of NFTA, or those for specific purposes, such as savanna trees for Africa or fodder species for hill regions, should be considered only as illustrative examples. This approach has, however, led to little new action on collection, conservation, and documentation other than expansion of existing programs, often established with different aims. We are currently in a situation where some new priorities will have to be decided and acted on quickly, especially where there are recognized threats of genetic erosion, since few accessions are in gene banks and the range of genetic diversity available from suppliers is narrow. There are eight areas where research is urgent: 1. Existing documentation on genetic resources of annual crops and forages which will be used in agroforestry systems requires the formulation of additional descriptors and descriptor states relevant to agroforestry practices. A number of these will relate to broader evaluation, especially those for assessing agronomic importance, and there will be a range of expression due to environment-genotype interaction. They should be limited to descriptors of fairly wide application and not be too site specific. Additionally, further passport descriptors might enhance predictability for agroforestry testing. There are many land races or primitive cultivars that were or will be collected from sites such as small holdings, where admixtures of cultivated field crops and trees or shrubs are the norm. Current descriptor schemes do not include these types of data. Many food crops that have not received a great deal of agronomic or breeding attention would fit such a category, especially crops such as roots and pulses, in the tropics, although there would be data available, if acquired, on others that have been used in major breeding programs. 2. Perennial woody crops pose many more problems. Some, such as those that have been used widely in plantations, already have databases on germplasm holdings or their databases are in the process of being developed. Cacao is now the subject for an international databasing exercise, and it would be logical to consider the relevant descriptors for agroforestry purposes since the largest part of the crop is still produced by small holders. Unfortunately, databasing of collections of most of the perennial tree crops is either nonexistent or rudimentary and a great deal of work is

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needed in most cases to refine preliminary lists of descriptors or to devise them de novo. 3. Underexploited perennial crops are likely to find an important niche in agroforestry systems. Many are extremely variable. Germplasm collections exist but are usually geared to other interests, and frequently are not available in sites and countries where they are likely to be needed. Moreover, there is no overall funding to rectify this in the near future. In a survey of over 30 tropical and subtropical fruits and nuts only just over half have significant germplasm holdings (IBPGR, 1986), but making materials easily and rapidly available for testing programs for agroforestry will require specific support. The position is likely to improve as the new IFAR Tropical Tree Crop Program becomes fully operational, but this will work on a crop-by-crop basis and a large level of funding and time will be needed particularly at the national level. Some national programs have built up special-purpose collections which will be of great interest in agroforestry. The All India Coordinated Research Project on Arid Zone Fruits (AICRP) is a case in point, which is involved with evaluating materials at 12 centers of the AICRP and at 25 other centers. Pateek (1988) vividly points to the international need to hold materials in agroclimatically suitable locations as a strategy for international conservation efforts on this type of material. 4. Wild tree species that are known to be of potential use, for whatever purpose, are unlikely to receive attention except at the local level and virtually nothing is known of their genetic variation. Although there are continuing ethnobotanic interests, such species are likely to remain orphaned by the research community at present unless sufficient scientific interest can be generated, as in the case of peach palm. 5. Since agroforestry incorporates livestock into the systems, it is urgent that the priorities available for browse woody species be reassessed. Those developed by IBPGR are probably too general for meaningful technology development. 6. Whereas success of the agroforestry systems depends on the selection of suitable woody species with characteristics such as quick establishment, fast growth, and acceptable ideotypes, research is certainly needed on “tailoring” tree species to agroforestry systems. The basis for this will be greater knowledge of the genetic variation and its distribution for specific characters in natural stands and exploitation through breeding. In most cases exploitation is limited to provenance testing and selection but for a number of species breeding will be required. Sufficient knowledge exists for priorities to be determined; if these were produced and collecting accelerated it would reduce the current “discrepancy between demand and supply of germplasm” (Shankarnarayan, 1988). 7. Trees are usually collected and put into provenance stands. For

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agroforestry there is probably a justification for setting up special-purpose working collections as field gene banks with back-up storage of seed, if this is possible, in appropriate facilities such as deep-freeze chests, and also linked to multiplication to provide planting materials. This could be incorporated into a national genetic resources program, but we have not evidenced much planning in this area. Such facilities would aid a whole series of development activities other than crop or tree breeding; for instance, the integration of projects dealing with sustainable development in buffer zones of nature reserve areas, planned Iand-use changes, and others. 8 . Agroforestry research has much to gain from synergies with ecological research especially when wild species are to be used. There is substantial literature on natural disturbance and patch dynamics on the responses of woody plants to disturbance, including plant evolution in disturbed environments (Pickett and White, 1985) but little evidence of interdisciplinary research involving agriculturists. Similarly, the genetics of colonization, where the literature is largely related to annual species or herbs, would benefit from joint research. Whereas agroforestry is at the stage of recognizing many systems for growing trees (in fields, or farm boundaries, woodlots, etc.), the tree species have not been researched. In many cases it is not known whether it is possible to select fast-growing, high-yielding native tree species. Tejwani (1988) makes a plea for prioritization and a networking approach to research based on experience in India where traditional agroforestry practices are common. The time has come to devise a number of themes of strategic research and to deemphasize the major emphasis on on-site trials. Genetic resources collections will be essential and plans have not yet been more than promulgated. Lastly, it will be essential that germplasm systems are integrated with those that exist or are developing in national programs and research institutions.

IV. SUSTAINABILITY A. GENERAL ISSUES International agricultural research, particularly through the CGIAR, has been evolving from initial aims of producing broadly adapted high-yielding cultivars toward producing more and more cultivars tolerant of stresses, which do not require the heavy chemical inputs and hence are bred for more efficient use of nutrients and do not overtax available soil and water

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resources. This statement was part of the concluding remarks of a CGIAR Committee on Sustainability, which presented a report in May, 1990. Additionally, the committee pointed out that farm management priorities along with appropriate policy and social settings require technical assistance and training and the interplay of numerous international and natural institutions, universities, and voluntary organizations. The emphasis on sustainability of agricultural production systems has implications somewhat different from the wider sustainable use of the environment, although the two are inextricably linked. In terms of the former the main issues relate to: 1. protecting the genetic base of agriculture; 2. preserving the natural resource base; 3. research in less favorable environments; and 4. concern to reduce external inputs.

In terms of the latter, the major issues relate to land use, ecosystems preservation, and economics and government policies. Plant genetic resources are the very basis that provides insurance for agriculture. However, one conceptual problem must become more widely appreciated outside the large research centers and especially at the level of developing country programs; that is, the difference in use of resources. In modern plant breeding the genetic resources are largely used as sources of genetic material, genes, and gene assemblies, which are drawn on for particular purposive aims. In most cases the reservoir-a plant with a particular genotype-is less important. Nonetheless, plant resources are still used for plant introduction, a widespread practice in horticulture and range science. Additionally, forestry, dealing mostly with wild species, is largely plant introduction. It would also be advantageous to enhance the domestication of medicinal plants and local crops that are gathered and also semidomesticated. Much interest in wider sustainability must relate to selection of ecotypes of these latter examples rather than the plant breeding practiced by crop scientists where specific genes for a particular character state are transferred into adapted genotypes. Much of the plant introduction successes relate to agronomic packages developed at the same time. It should not be forgotten that some plantation crops, domesticated in recent times, have owed most of their increased yields to agronomy rather than to breeding. There has been a widespread tendency for national genetic resources programs in developing countries to merge the two functions mentioned above, and while trying to emulate the spectacular breeding programs in other parts of the world and in international centers, they have often lost sight of the often obvious needs for aggressive plant introduction work

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along with agronomic trials. It should not be forgotten that most breeding programs for intensive pasture management developed from introduction programs, especially in the United Kingdom, Australia, and more recent work in CIAT and ILCA. These programs have had major impact on pasture improvement in many parts of the world. Frankel (1985) stressed the difference between plant and gene introduction in the context of the crop germplasm collections held in Southeast Asian countries. In the former case the aim of the collection is mainly ecological relevance and in the event that no breeding is currently practiced nor envisaged, then the collection should be based on ecologically different cultivars or ecotypes rather than as sources of genetic materials that might never be used. Those aspects of breeding that will be geared to sustainability issues will have implications on the genetic resources programs. Almost certainly it would be prudent to place more emphasis on knowing more about the genetic variation in the land races that are already in collections, and more interest in sorting out specific groups of accessions from particular ecologies and screening for specific traits. This type of work has been built into the evaluation program of, for instance, the rice collection in IRRI, but parallel types of work still need to be initiated for collections of a number of other crops. There are millions of rural poor in areas with fragile production systems in vast arid and semiarid zones and in areas bordering tropical forests. Due to population increases sustainability issues are a high priority on the agenda, and breeders and germplasm curators need continuing dialogues to develop strategies in relation to the materials with which they work. Foresight is necessary to shorten the time scale needed to provide the technologies. Since, from a sustainability perspective, there is now a critical need to enhance agroforestry systems, the time has come in developing strategy to tailor plant genetic resources programs to address immediate needs. These very clearly need to build on the distinction made above for plant introduction and for genetic use. Of the materials used for gene sources there is the even greater need to accelerate the collection, conservation, and in parallel, the selection and breeding, of multipurpose tree species that will enhance the supply of food supplements, fuelwood, materials for building, and other local uses of poor farmers. Bamboos, although not trees, need high priority in this area. Fortunately, mosr multipurpose trees produce seeds that can be stored so that conservation for future needs can be relatively cost effective. This is not yet the case for bamboos because of erratic flowering. Conservation methodologies will require more research. Many of the remarks related to agroforestry and sustainability issues

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have pointed to what should be done rather than what currently is done. However, for plant genetic resources research the technology is in place; it is simply a question of applying it practically when good strategic planning and funding are in place. B. PLANT GENETICRESOURCES RESEARCH FOR BIODIVERSITY CONSERVATION It is not the purpose of this article to discuss plant genetic resources in relation to nature conservation nor to the whole issue of preservation of biodiversity. The issues are widely known and have been summarized in a recent publication of the World Bank, World Resources Institute, IUCN, Conservation International, and WWF (McNeeley et al., 1990). Nonetheless, there are some significant areas where crop genetic resources specialists will increasingly be called on for expertise and cooperation. Some of these areas are presented here. 1. In situ preservation of certain plant genetic resources in “traditional” agricultural systems, particularly tree crops, is important. There is a need to see that these are managed as sustainable systems, not “alternative” agriculture. Agronomists have a large part to play in designing more sustainable systems. While it is true that agroecosystems may incorporate local varieties and that this can complement ex situ conservation, there is no guarantee of conservation in perpetuity (Sastrapradja, 1989). This method is likely to become used more for species that are not far removedfrom-wild species and those that are associated with rural habitations. 2. Keystone species of ecosystems may require specific attention as one element in conserving the whole. In some cases to ensure population continuation in situ some genetic management might be prudent (Frankel, 1983) and conservation of genetic stocks for such management might need to be a special concern of a national program otherwise aimed at storing crop variability. 3. New work on domestication of a limited number of underexploited species has received a lot of interest. Examples would be several neotropical palms, and one, peach palm, is already in production. More interactions are needed between crop scientists and those involved with conserving ecosystems.

For the past decade there have been discussions on the role of population genetics in conserving threatened species and managing reserve areas (Frankel and Soule, 1981; Schonewald-Cox et al., 1983; SoulC, 1987). The discussions and research have focused on methods to estimate the viable

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size of populations, criteria for management of populations, and the design of reserves in relation to geographical dispersion and maintenance of genetic variability. Soule in 1987 summarized the problems as long-term persistence without significant demographic or genetic manipulation for the foreseeable ecological future (usually centuries) with a certain agreed on degree of certitude, say 95%. However, this assumes that for the ability of a population to maintain itself in nature there is a normal level of immediate fitness and there is sufficient genetic variation to adapt to minor environmental changes and disturbances. Evidence from field work on the distribution of closely related species of woody crops, especially those that have widely scattered populations, shows a degree of fragility in relation to certitude of perpetuation. In these cases, and when ex situ methodology is not applicable, it is foreseen that protocols for genetic intervention will have to be developed. These will draw heavily on experience of horticulturists, agronomists, and genetic resources conservation. They will include, as examples: 1 . storage of pollen, freeze dried, for artificial pollination; 2. hybridization between diverse genotypes to provide recombinants for local, natural selection after planting of progeny; and 3. planned interplanting from other populations. Although there is a clear scientific basis for the comments above, no strategic research has been carried out, and the three examples cited are simplistic suggestions pending more data on relationships between measures of fitness and genetic variation, knowledge about when inbreeding depression and population bottlenecks occur, and other aspects of population dynamics. It is a new direction which must be followed quickly by conservation biologists and where genetic resources specialists and agronomists must be consulted at the initial planning stages. A useful reference from the conservation biologists is provided by the Society of Conservation Biologists (Soule and Kohn, 1989). As a closing remark in relation to sustainability, it is salient to recall a lesson learned with a tropical crop, rubber. Leaving aside the problems related to its place in the world’s economy-with, at one, time an aggressive defense mounted against encroachments by synthetics, which proved untenable-reorientation of research and development has relied on two factors. First, there is the interdependence of the world in relation to resources, and second, there is modernization of small-holder operations with, on one hand, better planting materials and, on the other hand, better agronomy. These factors are basic to all future attempts at agroforestry and sustainable agriculture in most rural situations.

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V. CURRENT NEW DIRECTIONS IN GERMPLASM MANAGEMENT AND RESEARCH With many institutions working on germplasm across a very wide range of crops it is impossible in a short space to describe all the new directions in research. It is pertinent to group them under strategies and to provide references for further reading.

A. COOPERATIVE NETWORKING The development of a global network has been a major aim of F A 0 and IBPGR. Historical realities led to the designation of a number of centers that hold base collections for long-term seed storage; these centers and associated active collections need to be carefully linked. In recent years, IBPGR has been sorting out a conceptual framework based on proposals compatible with today’s political and financial realities (Perret, 1989; Marshall, 1989). Some of the main features outlined by Marshall follow. 1. A global network should include all significant collections, and there should be a special emphasis to include national collections as the primary source of most germplasm. 2. The concept of a few large base collections needs modifying. Each germplasm collection should have the responsibility for the long-term storage of materials unique to the collection. 3. The concept of separate base and active collections needs to be modified so that the network is a single network of collections; all will be active ones with selected ones assuming responsibility for longterm conservation of a specified set of germplasm. 4. National gene banks should be fully involved in policy making and international coordination. 5 . Participation would require a code of collaboration that includes free availability of materials and duplication of unique materials.

The functional unit would be based on crop-by-crop schemes, the crop networking referred to in Section II,A. Seminal to this is good databasing (Williams, 1984; Konopka and Hanson, 1985).

B. MANAGEMENT OF COLLECTIONS It has now become accepted that the selection of a subset of a large collection, as a core-with the major part banked for safety in long-term

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storage-can be a useful tool so that a manageable set of accessions can be worked on. The core should be a representative assembly based on ecogeographic origin and specific characteristics (Frankel and Brown, 1984; Brown, 1989). The selection of core collections should not be seen simply as developing a workable subset out of large collections, thereby negating the necessity of other aspects of management such as sorting out redundance and excessive duplication within and between collections (Perret, 1989). It can also be a useful management tool combined with better use of collections (Peeters and Williams, 1984; Williams, 1989).

C. SAFETY OF COLLECTIONS Most crops can be conserved as seed in seed storage gene banks; however, running such facilities can be costly. Hence, two areas of strategic research need to be pursued. First, a more cost-effective storage should be explored, for example, reducing seed moisture content and relaxing the degree of refrigeration, and storage using natural phenomena (e.g., permafrost). Second, the biggest use of seed of stored samples is in routine viability testing, and alternative nondestructive methods are needed. For conservation of other crops, other methods are needed. The conceptual framework for in uitro genebanks is well established but a great deal of research is needed before they can be implemented for more than a few crops (such as cassava, potato, apple, and pears). The past decade has seen the sorting out of principles (Withers and Williams, 1982, 1985) and the establishment of linkages to other genetic resources activities (Withers, 1989). Other sections of this article have pointed to the practical difficulties of managing collections of wild species and linking seed and in uitro conservation to materials conserved in situ.

D. LINKS TO APPLIED RESEARCH There has been much written about ex situ genetic resources work being justified by its applications and the need for better use of the materials conserved. In part this represents a misunderstanding of the methods currently used by breeders, whereby they tend, in the first instance, to use breeding materials with which they are familiar and which cause the fewest problems. Additionally the existing coliections need a great deal of “sort-

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ing out” and many more relevant characterizations and evaluation data generated. This is a lengthy and costly exercise (Williams, 1989). Germplasm collections are essential for much applied research at the molecular level, including genome mapping and studies of biodiversity. There are exciting challenges that will increase the utility of the collection for highly bred crops and rapidly enhance others that have not received a great deal of breeding attention. The dialogue between scientists involved with applied research and those with genetic resources will be a continuing process.

VI. CONCLUDING REMARKS The groundwork has been laid for a “system” to make genetic resources available and to conserve them for the future. In any system, embracing so many countries, institutions, and plant diversity, efficiency can certainly be increased by upgrading scientific standards and skills of those scientists involved. Many programs have started on the basis of good intentions but there is a duty to see that today’s poorly prepared partners are not tomorrow’s marginal workers. The future of a global heritage depends on the skills and productivity of the emerging work force to run an increasingly sophisticated system. The needs for rapid transfer of new technology and the forging of new partnerships is apparent from this article and this requires a new vision involving agronomists as well as breeders and research scientists. Against this vision stands a sobering reality: It is impossible to conserve everything, and only a small part of the system can be user-driven by breeders and others. The user-driven sector has been very successful in relation to staple crop gene pools; however, the need to preserve minor crops with a back-up in nature conservation is not user-driven. Additionally, the funding for crop genetic resources work has not grown to match even the needs of the 1980s, and estimates of funding are largely unchanged (Plucknett et al., 1987). One reason for this is that these funds are largely for development assistance. Trends in funding of relevant scientific research are worrisome since they have been transferred in many cases to molecular work. However, the future for plant genetic resources work is bright if the funding for scientific research can be targeted in a strategic way so that the development assistance part has a solid back-up of research and development. This, I believe, is the challenge for the 1990s and requires vision and new noncompetitive partnerships between agriculture, science, and wider conservation interests.

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REFERENCES Balick, M. J. 1989. In “New Crops for Food and Industry”(G. E. Wickens, N. Haq, and P. Day, eds.), pp. 323-332. Chapman & Hall, London. Bramwell, D., Hamann, O., Heywood, V., and Synge, H., eds. 1987. “Botanic Gardens and the World Conservation Strategy.”Academic Press, London. Brewkaker, J. L., and Hutton, E . M. 1979. In ”New Agricultural Crops” ( G . A. Ritchie, ed.), pp. 207-259. Westview Press, Boulder, Colorado. Brown, A. H . D. 1989. In “The Use of Plant Genetic Resources” (A. H. D. Brown, 0. H . Frankel, D. R. Marshall, and J. T. Williams, eds.), pp., 136-156. Cambridge Univ. Press, Cambridge, England. Burley, J., and von Carlowitz, P., eds. 1984. “Multipurpose Tree Germplasm.” ICRAF, Nairobi, Kenya. Chang, T. T., Dietz, S. M. N., and Westwood, M. N. 1989. In “Biotic Diversity and Germplasm Preservation” (L. Knutson and A. K. Stoner, eds.), pp. 127-159. Kluwer Academic Publishers, Dortrecht, The Netherlands. Chapman, C. G. D. 1985. “Genetic Resources of Wheat: A Survey and Strategy for Collecting.” IBPGR, Rome. Chapman, C. G. D. 1989. In “The Use of Plant Genetic Resources” (A. H. D. Brown, 0. H. Frankel, D. R. Marshall, and J. T. Williams, eds.), pp. 263-279. Cambridge Univ. Press, Cambridge, England. Clement, C. R., and Arkcoll, D. B. 1989. In “New Crops for Food and Industry’YG. E. Wickens, N. Haq, and P. Day, eds.), pp. 306-332. Chapman & Hall, London. Duvick, D. N., and Brown, W. L. 1989. In “Biotic Diversity and Germplasm Preservation” (L. Knutson, and A.K. Stoner, eds.), pp. 499-513. Kluwer Academic Publishers, Dordrecht, The Netherlands. Felker, P. 1979. In “New Agricultural Crops” (G. A. Ritchie, ed.), pp. 89-132. Westview Press, Boulder, Colorado. Frankel, 0. H. 1983. In “Conservation of Tropical Plant Resources” (S. K. Jain, and K. L . Mehra, eds.), pp. 55-65. Botanical Survey of India, Howrah. Frankel, 0. H. 1985. In “Proceedings of the International Symposium on South East Asian Plant Genetic Resources” (K. L. Mehra, and S., Sastrapradja, eds.), pp. 26-31. LIPI, Bogor. Frankel, 0. H., and Brown, A. H. D. 1984. In “Crop Genetic Resources: Conservation and Evaluation” ( J . H. W. Holden and J. T. Williams, eds.), pp. 249-257. Allen & Unwin, London. Frankel, 0. H., and Soule, M. E . 1981. “Conservation and Evolution.” Cambridge Univ. Press, Cambridge, England. Harlan, J. R. 1975. J . Hered. 66, 184-191. Hazell, P. B. R., ed. 1986. “Summary Proceedings of a Workshop on Cereal Yield Variability.” IFPRI, Washington, D. C. Holden, J. H. 1986. In “Summary Proceedings of a Workshop on Cereal Yield Variability” (P. B. R. Hazell, ed.), pp. 71-76. IFPRI, Washington, D. C. Ingrarn, G. B., and Williams, J. T. 1984. In “Crop Genetic Resources: Conservation and Evaluation” (J. H . W. Holden and J. T. Williams, eds.), pp. 163-179. Allen & Unwin, London. International Board for Plant Genetic Resources (IBPGR). 1986. “Genetic Resources of Tropical and Sub-tropical Fruits and Nuts (Excluding Musa).” IBPGR, Rome. International Board for Plant Genetic Resources (IBPGR). 1988. “Annual Report for 1987.” IBPGR. Rome.

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International Institute of Tropical Agriculture (IITA). 1988. “The Use of Biotechnology for the Improvement of Cassava, Yams and Plantain in Africa,” IITA Meet. Rep., Ser. 1988/2, IITA, Ibadan, Nigeria. Jensen, C. J. 1981. I n “Genetic Engineeringfor Crop Improvement” (K. 0. Rachie and J. M. Lyman, eds.), pp. 87-104. Rockefeller Foundation, New York. Konopka, J., and Hanson, J., eds. 1985. “Information Handling Systems for Genebank Management.” IBPGR, Rome. Larkin, P. J., and Scowcroft, W. R. 1981. Theor. Appl. Genet. 60, 197-214. Lugo, A. E., Clark, J. R., and Child, R. D. 1987. “Ecological Development in the Humid Tropics. Guidelines for Planners.” Winrock International Morilton, Arkansas. Markert, C. L., and Moller, F. 1959. Proc. Natl. Acad. Sci. U.S.A. 45,753-763. Marshall, D. R. 1989. I n “Plant Population Genetics, Breeding, and Genetic Resources” (A. H. D. Brown, M. T. Clegg, A. L. Kahler, and B. S. Weir, eds.), pp. 362-388. Sinauer Assoc., Sunderland, Massachusetts. McNeeley, J., Miller, K. R., Reid W. V., Mittermeier, R. A., and Werner, T. B. 1990. “Conserving the World’s Biological Diversity.” IUCN, WRI, CI, WWF-US, World Bank, Gland, Switzerland. Nair, P. K. R. 1980. “Agroforestry Species. A Crop Sheets Manual.” ICRAF, Nairobi, Kenya. Orton, T. J., and Steidl, R. P. 1980. Theor. Appl. Genet. 57,89-95. Pateek, 0 . P. 1988. I n “Plant Genetic Resources Indian Perspective” (R. S. Paroda, R. K. Arora, and K. P. S. Chandel, eds.), pp. 320-334. NBPGR, New Delhi, India. Peeters, J. P., and Williams, J. T. 1984. Plant Genet. Resour. Newsl. 60,22-32. Perret, P. M. 1989. I n “The Use of Plant Genetic Resources” (A. H. D. Brown, 0. H. Frankel, D. R. Marshall, and J. T. Williams, eds.), pp. 157-170. Cambridge Univ. Press, Cambridge, England. Pickett, S. T. A., and White, P. S., eds. 1985. “The Ecology of Natural Disturbance and Patch Dynamics.” Academic Press, San Diego, California. Plucknett, D. L., Smith, N. J., Williams, J. T., and Anishetty, N. M. 1987. “Gene Banks and the World’s Food.” Princeton Univ. Press, Princeton, New Jersey. Prentice, W. E. 1979. Zn “Proceedings of a Workshop on Agro-forestry Systems in Latin America,” pp. 153-157. UNUKATIE, CATIE, Turrialba, Costa Rica. Rachie, K. 0. 1983. I n “Plant Research and Agroforestry” (P. A. Huxley, ed.), pp. 103-1 16. ICRAF, Nairobi, Kenya. Sastrapradja, S. 1989. In “Biotic Diversity and Germplasm Preservation, Global Imperatives” (L. Knutson and A. K. Stoner, eds.), pp. 63-77. Kluwer Academic Publishers, Dordrecht, The Netherlands. Saunders, R. M., and Becker, R. 1989. I n “New Crops; for Food and Industry” (G. E. Wickens, N. Haq, and P. Day, eds.), pp. 288-302. Chapman & Hall, London. Scowcroft, W. R. 1985. In “Genetic Flux in Plants” (B. Hohn, and E. S. Dennis, eds.), pp. 217-245. Springer-Verlag, Vienna and New York. Shankarnarayan, K. A. 1988. I n “Plant Genetic Resources Indian Perspective” (R. S. Paroda, R. K. Arora, and K. P. Chandel, eds.), pp. 443-456. NBPGR, New Delhi, India. Shonewald-Cox, C. M., Chambers, S.M., MacBryde, B., and Thomas, W. L. 1983. “Genetics and Conservation: A Reference for Managing Wild Animal and Plant Populations.” Benjamin Cummings, Menlo Park, California. Simmonds, N. W. 1979. “Principles of Crop Improvement.” Longman Group, New York. SoulC, M. E., ed. 1987. “Viable Populations for Conservation.” Cambridge Univ. Press, Cambridge, England. SoulC, M. E., and Kohn, K. A., eds. 1989. “Research Priorities for Conservation Biology.” University of Michigan, Ann Arbor.

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Tejwani, K. 1988. I n “Multipurpose Tree Species for Small-farm Use” (D. Wilmington, K. G. MacDicken, C. B. Sastry, and N. R. Adams, eds.), pp. 13-25. Winrock International, USA/IDRC, Canada. von Carlowitz, P. G . 1989. I n “Multipurpose Trees Selection and Testing for Agroforestry” (P. A. Huxley, and S. B. Westley, eds.), pp. 31-33. ICRAF, Nairobi, Kenya. Williams, J. T . 1982. Nature and Resources, UNESCO 18, 14-15. Williams, J. T . 1985. I n “Genetic Resources: Conservation and Evaluation” (J. H. W. Holden, and J. T. Williams eds.), pp. 1-17. Allen & Unwin, London. Williams, J. T. 1985. I n “15 Years Collection and Utilisation of Plant Genetic Resources by the Institute of Crop Science and Plant Breeding FAL Braunschweig,” pp. 41-48. Braunschweig-Volkenrode, Germany. Williams, J. T. 1989. In “The Use of Plant Genetic Resources” (A. H. D. Brown, 0. H . Frankel, D. R. Marshall, and J. T. Williams, eds.), pp. 235-244. Cambridge Univ. Press, Cambridge, England. Williams, J. T., and Creech, J. L. 1987. I n “Botanic Gardens and the World Conservation Strategy” (D. Bramwell, 0. Hamann, V. Heywood, and H. Synge, eds.), pp. 161-173. Academic Press, London. Withers, L. A. 1989. In “The Use of Plant Genetic Resources” (A. H. D. Brown, 0. H. Frankel, D. R. Marshall, and J . T . Williams, eds.), pp. 309-336. Cambridge Univ. Press, Cambridge, England. Withers, L. A , , and Williams, J. T., eds. 1982. “Crop Genetic Resources-The Conservation of Difficult Material.” IUBS/IGF/IBPGR, IUBS, B42, Paris. Withers, L. A , , and Williams, J. T. 1985. I n “Biotechnology in International Agricultural Research,” pp. 11-26. Int. Rice Res. Inst., Los Batios, Laguna, Philippines.

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ADVANCES IN AGRONOMY, VOL. 45

LONG-TERM IMPACTS OF TILLAGE, FERTILIZER, AND CROP RESIDUE ON SOIL ORGANIC MATTER IN TEMPERATE SEMIARID REGIONS Paul E. Rasmussen and Harold P. Collins U. S. Department of Agriculture Agricultural Research Service Columbia Plateau Conservation Research Center Pendleton, Oregon 97801

I.

11.

111.

IV.

V. VI . VII. VIII.

IX. X.

Introduction A. Beneficial Effects of Organic Matter in Soil B. Determination of Organic Matter C. Factors Influencing Soil Organic Matter Content D. Temperate Semiarid Regions E. Effects of Cultivation of Grasslands F. Evaluating Changes in Organic Matter Content and Quality Tillage Effects on Soil Organic Matter A. Frequency of Fallow B. Intensity of Tillage C. Conservation Tillage Fertilizer Effects on Soil Organic Matter A. Nitrogen B. Phosphorus, Potassium, Sulfur, and Other Nutrients Organic Residue Effects on Soil Organic Matter A. Crop Residues B. Animal Manure C. Green Manure Organic Matter and Microbial Biomass Management Effects on Physical Properties Cultivation and Future Change in Soil Organic Matter Impact of Soil Erosion Predicting Soil Organic Matter Turnover A. Carbon Pools and Carbon Cycling B. Models of Soil Organic Matter Turnover Summary A. Progress B. Future Needs References 93 Copyright 0 1991 by Academic Press. Inc. All rights of reproduction in any form reserved.

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I. INTRODUCTION A. BENEFICIAL EFFECTSOF ORGANIC MATTERIN

SOIL

Organic matter in soil has been of concern for decades because it has a pronounced beneficial effect on soil management and crop productivity (Allison, 1973). In recent years, soil organic matter has received additional attention because of its potential to sequester carbon emanating from atmospheric Cot increases. Organic matter also has a strong influence on the persistence and degradation of pesticides and organic wastes in soil, yet full appreciation of this effect remains largely ignored in today’s agricultural sector. Presently, increasing awareness and concern that environmental quality is deteriorating has fostered renewed interest in improving soil and water management. It is therefore appropriate that we review past progress towards enhancing the level and quality of organic matter in soil. Allison (1973) listed the important contributions of organic matter to soil: (1) it is the major natural source of inorganic nutrients and microbial energy, (2) it serves as an ion exchange material and a chelating agent to hold water and nutrients in available form, (3) it promotes soil aggregation and root development, and (4) it improves water infiltration and water-use efficiency. A productive soil that is easy to till is identified as having “good tilth.” An appreciable amount of organic matter is usually a prime prerequisite for good tilth, especially in soils with high sand or clay content. Good tilth has no defined limits (Karlen et al., 1990), but is readily recognized by everyone from weekend gardeners to biological scientists.

B. DETERMINATION OF ORGANIC MATTER Most organic matter values are derived from organic carbon (organic C ) values because the quantitative determination of organic matter has high variability and questionable accuracy (Nelson and Sommers, 1982). A conversion factor of 1.724 is used to convert organic C to organic matter, even though it is generally recognized that the value can range from 1.6 to 3.3 (Jackson, 1958; Nelson and Sommers, 1982). Organic C analysis is reasonably accurate. Values from wet digestion with acid-dichromate and heat (modified Walkley-Black) correlate fairly well with results from dry combustion (Tabatabai and Bremner, 1970; Kalembasa and Jenkinson, 1973; Sheldrick, 1986).

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Organic C in soil is generally highly correlated with organic nitrogen (organic N) (Unger, 1968). Organic N comprises more than 99% of the total N present in soil in the absence of substantial N03-N accumulation (Allison, 1973). Analysis of total N by wet digestion (Kjeldahl) or dry combustion (Dumas) has been highly accurate since the 1880s (Bremner and Mulvaney, 1982). Accuracy and precision of Kjeldahl digestion has not changed substantially during the progression from macro- to microdigestion techniques. Modem combustion analyzers now have the capability to reliably determine both C and N simultaneously. Organic C values will be used whenever possible in this report, and references to soil organic matter content will be restricted to generalized statements. Unless otherwise noted, it is assumed that ( 1 ) organic N = total N, and (2) % organic matter = (% organic C) (1.724). Organic matter can be further separated into various fractions. The most commonly defined fractions are shown in Table I.

C. FACTORS INFLUENCING SOILORGANIC MATTERCONTENT The amount of organic matter in mineral soil can vary from less than 10 g/kg (1%) in coarse-textured sands to more than 50 gikg (5%) in fertile prairie grasslands. The level of organic matter in soil is influenced by climate, topography, parent material, vegetation and organisms, and time (Jenny, 1941; Allison, 1973; Stevenson, 1986). Jenny (1941) arranged the order of importance of these factors as climate > vegetation > topography = parent material > age. All of the factors are partially interactive. For example, higher rainfall (climate) generally results in greater biomass production (vegetation), greater weathering and higher clay content in soil (parent material), and perhaps modified relief (topography). Organic matter in soil reaches a stable equilibrium when all factors with the exception of time change very little. The time needed for organic matter to reach a stable level in uncultivated soil can range from less than 100 to over 2,000 years, depending upon climate conditions (Stevenson, 1986). It is possible to make some general statements about organic matter levels in virgin grasslands soils based on the pioneering work of Jenny (1941). 1 . Grasslands soils have higher organic matter content than forest soils. 2. Organic matter content increases with increasing precipitation and decreases with increasing temperature. 3. Fine-textured soils have higher organic matter content than coarsetextured soils.

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PAUL E. RASMUSSEN AND HAROLD P. COLLINS Table 1 Definitions of Organic Matter Fractions in Soil” Term

Organic residues Soil organic matter

Humus Soil biomass Humic substances

Nonhumic substances Humin Humic acid Fulvic acid

Definition Undecayed plant and animal tissues and their partial decomposition products Total of the organic compounds in soil exclusive of undecayed plant and animal tissues, their “partial decomposition” products, and the soil biomass Same as organic matter Organic matter present as live microbial tissue A series of relatively high molecular-weight, brown-to-blackcolored substances formed by secondary synthesis reactions. The term is a generic name to describe the colored material obtained on the basis of solubility characteristics. These materials are distinctive to the soil (or sediment) environment in that they are dissimilar to the biopolymers of microorganisms and higher plants (including lignin) Compounds belonging to known classes of biochemistry (e.g., amino acids). Humus probably contains most, if not all, of the biochemical compounds synthesized by living organisms The alkali-insoluble fraction of soil organic matter or humus The dark-colored material that can be extracted from soil by various reagents and that is insoluble in dilute acid The colored material that remains in solution after removal of humic acid by acidification

From Stevenson ( 1982). Reproduced from “HumusChemistry: Genesis, Composition, Reactions” by permission of John Wiley & Sons, Inc. Copyright 01982 by John Wiley and Sons, Inc.

4 . Naturally moist and poorly drained soiis have higher organic matter

than well-drained soils. 5. Soils in lowlands have higher organic matter than soils on upland positions. All of the above are affected when virgin land is cultivated. A much larger portion of biomass is removed for use as feed or fuel. Crop selection, crop rotation, and residue utilization influence the amount of biomass cycling in the ecosystem. Accelerated wind and water erosion may significantly modify the soil surface and alter organic matter accumulation, soil texture, and water-holding capability. Soil aeration may be changed by drainage, tillage pan development, or ripping of indurated layers. Tillage to control weeds or prepare a seedbed increases soil disturbance and accelerates organic matter oxidation.

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D. TEMPERATE SEMIARID REGIONS This article will primarily discuss organic matter relations in temperate zones with semiarid climate.Soi1 organic matter is of greater concern in semiarid regions because of its unusually large impact on water conservation, nutrient availability, and stabilization of yield. Temperate semiarid regions, in this article, will comprise those areas between 30 and 60 degrees latitude that were grassland in their virgin state, and if cultivated, have been cropped primarily to cereal grains. This encompasses the grasslands of mid-continent North America and Eurasia, and includes portions of Argentina, South Africa, Australia, and the northwestern United States. Native vegetation consists primarily of short- and medium-height grasses, with a limited shrub component. In Europe and Eurasia, this region is sometimes referred to the “The Steppes.” Drought stress occurs most years, and affects the level of production. The upper limit of annual precipitation is about 500 mm where winter precipitation dominates and 750 mm where summer rainfall dominates. Most of the soils are classified as Mollisols under the U.S. system, and were formerly included in the Chestnut and Chernozem great soil groups. Changes in soil properties in semiarid regions will frequently be compared with changes in more humid environments where numerous studies have been conducted. Comparisons will be restricted to studies in humid regions that involved grasslands or that were cropped primarily to cereal grains. E. EFFECTSOF CULTIVATION OF GRASSLANDS Virgin grassland soils traditionally lose organic matter rapidly after they are first cultivated (Allison, 1973; Mann, 1985). Organic matter is high in undisturbed soil because little native vegetation is removed, erosion is negligible, and oxidation is at a minimum. Root and crown tissue production is much greater for native grasses than for cultivated crops, and comprises a higher proportion of net primary productivity (Sims and Singh, 1978; Salaer al., 1988). Withcultivation, a substantial portionof dry matter production is removed for food or forage, wind and water erosion may increase, and frequent cultivation degrades soil aggregates and accelerates oxidation of easily decomposable root and crown tissue. The loss of organic matter with cultivation is usually exponential, declining rapidly during the first 10-20 years, then more slowly, and finally approaching a new equilibrium in 50-60 years (Jenny, 1941; Haas Pt a l . , 1957; Campbell, 1978). Some early investigators believed that a minimum

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PAUL E. RASMUSSEN AND HAROLD P. COLLINS

existed, below which soil organic matter content could not go. We now know this is not the case. The organic matter level depends on the rate of residue addition in relation to the rate of residue decomposition and soil erosion. Soil organic matter will continue to change as long as any of the controlling factors continue to change. New equilibrium levels will be highly dependent on farming practices, especially those involving crop residue utilization, crop rotation, and tillage.

F. EVALUATING CHANGES I N ORGANIC MATTERCONTENT A N D QUALITY Soil organic matter usually changes only slowly with time following a change in land use or management. Differences are difficult to measure against the large background of soil organic matter until sufficient years have elapsed for the differences to be larger than analytical variability. As a result, this requires long-term experiments with annotated history, or paired conditions that have been in place for 20-30 years. The time requirement can be shortened by determining changes in microbial biomass in relation to the change in organic C (Saffigna et al., 1989), but caution must be exercised since the microbial biomass : organic C ratio is influenced by crop management (Granatstein et al., 1987; Anderson and Domisch, 1989). Small changes in organic C or N can often be elucidated through the use of 14C and 15N isotopes. This aids substantially in interpreting long-term changes, and vastly improves the estimates of nutrient cycling in different organic matter fractions. Accurate assessment of results from long-term experiments requires close scrutiny to determine their validity. An evaluation of change over time may not be possible if soil C or N was not determined at the beginning of the experiment. If C and N have been determined periodically over time, values may require adjustment for different methods of analysis. Analytical results from historical samples may not be valid if samples have undergone change during storage. Specific methods of analysis are not always identified in published reports, which can lead to erroneous assumptions of what components were measured. The bulk density of soil (weighthnit volume) has not been determined in many instances, even though it has changed significantly over time and affects the amount of C or N remaining. This is especially true when virgin and cultivated sites are being compared, since cultivation can increase soil bulk density 30% or more. In spite of the potential problems associated with long-term experiments, they remain the primary method to identify organic matter changes over time. Carbon dating and isotope discrimination techniques are invalu-

SOIL ORGANIC MATTER IN SEMIARID REGIONS

99

able in defining nutrient fluxes and half-lives, but they enhance, not replace, valid long-term data.

II. TILLAGE EFFECTS ON SOIL ORGANIC MATTER A. FREQUENCY OF FALLOW Increasing the frequency of fallowing generally increases the loss of organic matter from soil. The loss is usually greater in higher rainfall zones. Ridley and Hedlin (1968) reported 49% less organic matter in a black lacustrine soil after 37 years when fallowed every other year rather than cropped annually. Haas et al. (1957) reported that cropland in grainfallow rotation lost more N than did annually cropped land at 13 of 14 locations throughout the midwestern U.S. The average loss after 30-43 years of cultivation was 24% with continuous small grain versus 29% with alternating grain-fallow. Dormaar and Pittman (1980) reported organic C levels of 19.6, 15.6, and 14. I g/kg in the top 13 cm of soil after 64 years of cropping a dark brown Chernozem soil in Canada to wheat (Triticum aestiuum L.)-wheat, wheat-wheat-fallow, and wheat-fallow rotation, respectively. This was a decrease of 21 and 28% in organic matter content when soil was fallowed 33 and 50% of the time, respectively, rather than cropped annually. Soil in west Texas, U.S. cropped to wheat-fallow contained 14% less organic matter in the top 8 cm of soil after 36 years than did soil cropped to continuous wheat (Unger, 1982). Biederbeck et al. (1984) and Insam e f al. (1989), in their reviews on cropping practices and frequency of fallow, reported similar losses of organic matter in a wide range of Canadian soils. Loss of C and N is a combination of increased oxidation due to more cultivation, lower residue return to soil, and, frequently, increased wind and water erosion. Frequency of cultivation can be estimated from established farming practices and residue input calculated from crop yield with reasonable accuracy if 10 or more years are involved. But, isolation of erosion effects is difficult because accurate soil losses are not easily calculated from climatic and agronomic data.

B. INTENSITY

OF

TILLAGE

Appropriate data specifically comparing the long-term effects of tillage intensity on depletion of soil organic matter are not readily available. Most often reported are comparisons of disking versus plowing and experiments

100

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

that involve “delayed tillage.” Delayed tillage usually occurs in cerealfallow rotations where tillage is delayed following harvest until late fall or the following spring. Thus, delayed tillage does not always reduce the number of operations, but simply moves tillage from the summer when soil temperature is high to the fall or spring when it is much lower. Summer tillage can stimulate oxidation rates substantially, especially in those areas where summer rain is sufficient to moisten the soil following harvest. In the Great Plains, the loss of soil N following initial cultivation was considerably greater with row crops than with small grains (Haas et al., 1957). Increased loss was attributed to both less surface protection from rainfall and more tillage to control weeds. Greater loss of soil N with plowing rather than subsoiling or listing occurred at Archer, Wyoming, but not at Hays or Garden City, Kansas, or at Lawton, Oklahoma. In general, spring plowing was less detrimental than fall plowing, and delaying spring plowing further reduced N loss. Fall and early spring plowing often increased the number of secondary tillage operations to control weeds. Soil organic matter in a wheat-fallow system in Texas after 36 years was 27% higher with delayed tillage compared to tillage immediately following wheat harvest (Unger, 1982). C . CONSERVATION TILLAGE

Conservation tillage is described as noninversion tillage that leaves a significant fraction of crop residue on or only shallowly incorporated into the soil to control erosion, reduce energy use, and conserve soil and water (Unger and McCalla, 1980). Stubble-mulch, ecofallow, no-till, directdrilling, and trashy-fallow are all forms of conservation tillage. Tillage for cereal grains is usually performed with unidirectional disks or sweeps that undercut the residue without substantial burial. Many studies have shown that conservation tillage increases organic C and N in the top 5-15 cm of soil compared to conventional methods of tillage (Table 11). The rate of increase is biased to some extent by the sampling depth. In general, the increase averages from 1 to 2%/yr for both C and N , in the upper 15 cm of soil. The range for C in Table I1 is -0.1 to 7.3%/yr, and the range for N is 0.1 to 5.1%/yr. Below the upper few cm, the amount of C and N has been either equal or less than that in conventional tillage (Doran, 1980). Thus, the net change in the soil profile is not as positive as it might seem, even though the amount near the surface is much greater. Increased levels of C and N near the surface are attributed to delayed residue decomposition, slower oxidation of soil C, reduced erosion, or any combination of these factors (Pam and Papendick, 1978;

101

SOIL ORGANIC MATTER IN SEMIARID REGIONS

Table I1 Effect of Conservation Tillage on Organic C and N in Soil Location and soil

Soil depth (cm)

Length of study (yr)

Tillage system“

412 412

10 10

10 10

30 30 30

5

345 307 389

15 15

698

S. Africa Haploxeralf Haploxeralf Germany “Podsol” “Podsol” ”Podsol” Australia Western Psamment Alfisol Alfisol Queensland Pellustert Canada Saskatchewan Chernozem United States N . Dakota Haploboroll Haploboroll Argiboroll Kansas Haplustoll Nebraska Haplustoll

C

N

Reference”

TT NT

5.6 7.3

3.4 5.1

1 1

6

NT NT NT

3.2 2.4 I .3

1.4 I .6 1.3

2 2 2

NT NT NT

1.6 0.7 1.4

-

I5

9 9 9

-

3 3 3

10

6

NT

I .2

1.3

4

I5

6

NT

6.7

2.8

5

45 45 45

25 25 25

SM SM SM

I .u -0.1 0.5

1.3 0. I 0.4

6 6 6

15

I1

NT

0.7

0.6

7

446 446

9 10

15 15

NT NT

2.8 1.2

2.4

1 .o

n n

416

15

44

SM

0.3

0.4

9

560

5

10

NT

I .9

2.0

10

2.2 -0.1 7.3

1.7 0. I 5. I

375 375 375

Oregon Haploxeroll Washington Haploxeroll Mean Minimum Maximum ~

~~

Increase (%lyr)

Annual precipitation (mm)

5

-

~

TT, tine-till; NT. no-till; SM, stubble-mulch. I . Agenbag and Maree (1989); 2. Fleige and Bauerner (1974); 3, White (1990); 4. Saffigna ei t i / . (1989); 5, Campbell et a / . (1989); 6, Bauer and Black (1981); 7. Havlin et a/. (1990); 8. Doran (1980); 9, Rasmussen and Rohde (1988); 10, Granatstein ef al. (1987).

102

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

Doran, 1980). There is very little evidence that organic C or N moves substantially from the zone where it is placed if it is stabilized into the humus fraction of soil.

111. FERTILIZER EFFECTS ON SOIL ORGANIC MATTER A. NITROGEN I . Influence on Vegetative Production

Nitrogen addition often has an effect on the amount of C and N incorporated into soil organic matter, but its effect in semiarid environments is not as pronounced as in humid environments. Biological systems are carbon controlled and N affects soil organic matter mainly through its influence on residue production. The primary effect of fertilizer N is to increase vegetative production and the amount of organic C available for recycling back into the soil system. Nitrogen is limiting for maximum vegetative production in vast areas of the world (Stevenson, 1986). Supplying additional N increases both growth rate and efficiency of water use of most grasses. In practically every instance, this results in higher vegetative production. Higher vegetative production does not always translate to higher grain yield of cultivated crops, however, because of the tendency for higher water use to intensify drought stress during seed formation. Even native grasslands in many semiarid regions are inherently N deficient, and N fertilization will increase production (Rogler and Lorenz, 1974). Introduced grasses generally outyield native grasses, and often are more responsive to N application (Power, 1980). Thus, cultivated crops and introduced grasses may have higher aboveground production capability than the original native grasslands. However, the total of net biomass is probably higher in native grasses because of their much larger reservoir of belowground crown and root biomass (Kucera et al., 1967; Sims and Singh, 1978). 2. Retention of Applied Nitrogen

Agricultural experiments suffer from “the nitrogen enigma”; complete recovery of N in plant and soil is seldom attained and the fate of the unrecovered portion cannot be determined. The recovery of fertilizer N by crops is seldom over 50% and often as low as 20% (Gilliam et al., 1985).

SOIL ORGANIC MATTER IN SEMIARID REGIONS

103

Recovery of N from manure application is also low, rangingfrom 40 to 86% (Bouldin et al., 1984). The unrecovered portion is of concern because of its potential to pollute ground and surface water. Leaching and denitrification are usually blamed because retention of N in soil organic matter is not easily determined. Incorporation of N into the organic fraction of soil is important because it reduces the movement of soluble N out of the root zone. The amount of N retained in the organic N reservoir can only be determined with properly designed N isotope experiments. Nitrogen applied to cultivated land in excess of crop removal may be incorporated into the soil organic fraction, remain in inorganic form, or leach below the root zone. Long-term studies in Oregon (Rasmussen and Rohde, 1988) indicated that 18%of the N applied to a wheat-fallow system was incorporated into the organic fraction. The amount of N that is leached depends on the amount and intensity of rainfall, and time of N application in relation to crop need. The tendency of N to leach below the root zone is very low in soils with a calcareous horizon in the profile (Stevenson, 1986). Nitrogen applied to grassland in excess of crop need in these soils tends to accumulate as inorganic N with only partial incorporation in the organic fraction (Sneva, 1977; Power, 1983). 3 . Inorganic versus Organic Sources

Inorganic N sources are generally commercially manufactured fertilizer. The sources are either of ammonium or nitrate origin. Nitrate materials comprised a majority of fertilizer applied prior to 1940, but have since declined dramatically as synthetic ammonia manufacture became more economical. The form of inorganic fertilizer used (nitrate or ammonium) has seldom affected crop yield or inorganic N transformations in soil, except where long-term addition has changed soil pH, Ammonium-based fertilizers are acid forming and sustained use can lower soil pH to levels detrimental to plant growth (Mahler et al., 1985; Rasmussen and Rohde, 1989). Fertilizer use is not the only contributor to soil acidity; some semiarid Australian soils in long-term wheat-legume-pasture rotations (ley farming) have become acid because of mineralization of biologically fixed N (Haynes, 1983). The effect of increasing acidity on microbial populations, N mineralization, and the rate of turnover of easily decomposable and resistant organic matter is not well defined for semiarid regions, although its effect has been studied in humid regions. Organic sources of N are usually green manure and animal manure. Organic waste from processing plants represents a minor source, primarily because of transportation problems. Green manures can be a legume, a

104

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

grass, or a grass-legume combination. The legumes are most often clovers and the grasses cereal grains. Green manures are usually incorporated into soil before they reach seed formation. Animal manure in semiarid regions is primarily from cattle or sheep. Because confined-feeding operations are localized and farm size quite large, there is limited use of manure in the United States and Canada. There is little difference between inorganic and organic N sources for supplying N to plants if sufficient time is allowed for mineralization to N03-Nprior to crop need. Organic materials contain many other nutrients while inorganic N sources usually do not. The major problem with organic N sources is the uncertainty in the amount and availability of N supplied. The actual amount of dry matter and N in animal or green manure at the time of incorporation is seldom determined, although materials may contain up to 70% water. The average water content of manure is about 50%, that of air-dry forage 10-15%, and that of green manure 50-75%. Actual nutrient input from organic materials is much more variable than that of inorganic materials such as lime or fertilizer. This variability may influence short-term reaction rates, but should have little effect on long-term nutrient turnover in soil. B. PHOSPHORUS, POTASSIUM, SULFUR, AND OTHERNUTRIENTS

The effect of nutrients other than N on organic matter in soil is much less pronounced. Their availability, to some degree, is derived from the mineral fraction, thus they are less likely to be affected by a change in organic matter level or biological reaction rate. Organic P constitutes from 15 to 80% of the total P, and organic S from 50 to 70% of the total S in soil (Allison, 1973). The organic fraction of K, Ca, Mg, and many micronutnents constitutes a much lower proportion of the total in soil. Deficiencies of these nutrients occur so infrequently in grassland soils that their influence on vegetative production and nutrient cycling is limited. Phosphorus deficiency occurs in parts of the Great Plains (Read et al., 1977; Power, 1983; Nuttall et al., 1986). Even native grassland soils are sometimes P deficient (Power, 1983). Phosphorus fertilization may increase dry matter yield, contributing to increased organic matter in fine or coarse textured soil. Extensive organic matter loss may lower available P in soil. In Canada, an organic matter loss of 35% was accompanied by a 12% decrease in available P concentration (Tiessen et af., 1982). All P loss was generally accounted for by the decrease in the organic fraction. Sulfur is the most likely element other than N to have an influence on

SOIL ORGANIC MATTER IN SEMIARID REGIONS

105

organic matter in soil since it is derived primarily from the organic fraction and is required in direct proportion to N for protein synthesis. But S deficiency rarely occurs in the Great Plains, and only infrequently in Canada and the western United States (Beaton and Soper, 1986; Rasmussen and Kresge, 1986). Sulfur deficiency is also found in some Australian soils (Blair and Nicolson, 1975). Increases in vegetative production from applied S are usually much less than those obtained with N application. The overall potential for S to affect organic C and N in soil is therefore not large.

IV. ORGANIC RESIDUE EFFECTS ON SOIL ORGANIC MATTER A. CROPRESIDUES 1 . Type of Residue

It now appears that residue input plays an important role in setting a new organic matter equilibrium level in soil. The effect of crop residue on soil organic matter content is highly related to the amount and only weakly related to the type of residue applied. Larson et al. (1972) found that alfalfa, cornstalks, oat straw, sawdust, and bromegrass produced similar increases in organic C in a Hapludoll in Iowa (Fig. 1). The influence of residue type on organic N was similar but more variable, with sawdust providing significantly less N retention than the other materials. Horner e? al. (1960) also found little difference between effects of wheat straw and alfalfa hay applied at rates from 0 to 1.63 t/ha to a Pachic Argixeroll in Washington. Sowden (1968) and Sowden and Atkinson (1968) found little differences between the effects of straw, alfalfa, and deciduous leaves incorporated into soil for 20 years in Canada (Table 111). All prevented further decline in organic C and N in a clay soil and increased levels in a sandy soil. Peat, muck, and manure increased C and N more than did straw, alfalfa, or tree leaves. Sauerbeck (1982) in Germany also concluded that different types of crop residue had similar effects on soil organic matter. Residue decomposition is a fundamental factor in organic matter stabilization, since degradation products are incorporated into various soil organic matter pools. Biological decomposition of plant materials is influenced by temperature, moisture, aeration, pH, C, N, lignin content, particle size, and degree of burial in soil (Parr and Papendick, 1978).

106

PAUL E. RASMUSSEN AND HAROLD P. COLLINS 20

A

18

0

Y \

0

v

z 0

16

0

0

5

14

0 LT

0 12

10

CARBON CHECK ALFALFA

0 CORNSTALKS

NITROGEN (x 0.1) SAWDUST OAT STRAW

0BROMEGRASS

FIG.1. The influence of different types of residue on organic C and N in the top 15 cm of an Iowa soil. (From Larson et al.. 1972. Reproduced from Agronomy Journal, 64(2), MarchApril 1972, pp. 204-208, by permission of the American Society of Agronomy, Inc.)

Tenney and Waksman (1929) initially suggested that the rate and nature of residue decomposition depended upon the chemical composition of the plant material. The most important residue constituents were the amount and nature of cold-water-soluble C, the abundance of cellulose and hemicellulose, the N content, and the amount of lignin. Decomposition of plant material occurs in several steps involving both chemical and physical transformations. In general, water-soluble C fractions (sugars, organic acids, and proteins and part of the nonstructural carbohydrates) are degraded first (Reber and Schara, 1971; Knapp et al., 1983), followed by structural polysaccharides (cellulose and hemicellulose) (Harper and Lynch, 1981), and then lignin, which decomposes at a much slower rate (Herman et al., 1977; Collins et al., 1990). Tracer techniques make it possible to follow the fate of residues during decomposition. In a classical study, Jenkinson (1965)followed the decomposition of buried 14C-labeledryegrass (Lolium spp.) straw over a 10-year period. After one year, approximately 33% of the original C remained in

107

SOIL ORGANIC MATTER IN SEMIARID REGIONS Table 111 Effect of Type of Residue Added on the Change in Organic C and N in Sand and Clay Soil, 1945-1965, Ottawa, Canada" ~

Change, 1945-1965 (%) Rideau clay'

Uplands sand"

Residue addedb

C

N

C

N

None Straw Alfalfa Deciduous leaves Peat Muck Manure Rye (green manure)

- I8

- 14

-1

+3 +1 -8 -8 + 33 +7 - I3

- 10 + 28 + 10 +46 +80 + I35 + 59

- 24 +7 +5 +4 +9 +68 +35 -9

a

-1

0

+ 27

+ 51 +8 - I6

+ 19

Data from Sowden and Atkinson (1968) and Sowden (1968). Residues added annually at 11.1 t/ha. Soil C and N content in 1945 was 29.1 and 2.38 g/kg, respectively. Soil C and N content in 1945 was 13.7 and 1.29 g/kg, respectively.

the soil, of which one third was associated with soil microbial biomass. About 20% of the I4C label was found in the soil microbial biomass after 4 years and 12% of the initial labeled C remained in the soil after 10 years (Jenkinson, 1977). Voroney et uf. (1989) found that 20-30% of added C became stabilized in the soil organic matter after 10 years. Other researchers have shown similar results, although the rate of decomposition varied due to abiotic conditions (Shields and Paul, 1973; Nyhan, 1975). The level of organic matter in soil depends on both the amount and chemical composition of the material added. Stabilization of soil organic matter is more a function of microbial product recalcitrance than of the initial residue composition (Voroney et af., 1989). Soil organic matter decomposition averages from 2 to 5% a year, with turnover of newly formed humus more rapid than that of old humus. Soil organic matter can be partitioned into old and young fractions, as shown by radiocarbon dating (Table IV). Most laboratory incubations indicate that from 60 to 75% of crop residue C is evolved as C 0 2after one year in soil (Martin and Stott, 1983). Most of the remaining C becomes stabilized in new soil humus, with 5-15% incorporated into soil microbial biomass. Stott et uf. (1983) found that the majority of polysaccharide and protein C in wheat straw became associ-

108

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

Table IV Radiocarbon Ages of Soil Organic Matter Reference Decalcified soil Hydrolysate Residue from hydrolysis Humus Unfractionated Fulvic acid Humic Acid Humus Virgin Oxbow soil Cultivated Oxbow (15-yr) Cultivated Oxbow (60-yr)

1,450 515 2,560 1,240 870 495 1,235 1,140 250 f 65 295 f 75 710 C 60

Jenkinson and Rayner (1977)

Campbell et al. (1967)

Martel and Paul (1974)

ated with the fulvic acid fraction of new soil humus. From 36 to 54% of the C derived from wheat straw lignin was found in the humic acid fraction. Corn (Zea mays) residue underwent a similar trend of incorporation into new humus fractions. Lignin and other phenolic compounds are the most resistant to microbial degradation and probably serve as the primary source of material found in highly stable fractions of soil organic matter. Immature plant tissue contains a low percentage of lignin and generally has limited capability to increase stable organic matter components even though it may increase labile N fractions. 2 . Rate of Addition

Several studies show that organic C and N in soil respond linearly to increasing rates of residue addition (Table V). Horner et al. (1960) summarized some of the early research in the Pacific Northwest, U.S.,which found linear increases in soil C and N with rates of residue application from 0 to 3.5 t/ha. Results were similar for studies in 240- and 564-mm rainfall zones. Oveson (1966) and Rasmussen et al. (1980) reported on changes in soil C and N in a long-term wheat-fallow experiment in eastern Oregon that included straw, pea (Pisurn satiuurn) vine, and manure residues. Soil C and N continued to decrease with time for all residue additions except manure (Fig. 2). The rate of decrease was related to the level but not type of residue returned to the soil (Fig. 3).

SOIL ORGANIC MATTER IN SEMIARID REGIONS

109

Table V The Influence of Rate of Residue Addition on Organic C and N in Soil" Location and time of study

Crop rotationb

Soil depth (cm)

Organic C

Organic N

b

U

a ~

Culbertson, MT 1964-1972 Lind, WA 1923-1946 Pendleton, OR 1931-1966 Pullman, WA 1922-1952 1922-1952 Shenandoah, IA 1953- 1966

b

Reference'

~~~~~

W-F

I5

+56

0.83

-11.9

0.046

1

W-F

15

-86

0.12

-

-

2

W-F

30

-389

0.17

-32.7

0.019

3d

W-F

30 30

-406 -117

0.21 0.15

-45.5 -18.8

0.022 0.011

2 2

15

-366

0.14

-

4

w-w c-c

~

~

~~~~~

a As defined by the regression equation Y = a + bX, where Y = change in soil C or N (kg/ha/yr) and X = carbon input (kg C/ha/yr). W, wheat; F, fallow; C, corn. ' 1. Black (1973); 2, Homer et al. (1960); 3, Rasmussen el al. (1980); 4, Larson et al. (1972). Data modified slightly by additional measurements.

\ \

-

w 22 tiha MANURE, NO BURNING A 2.2 t/ha PEA VINES, NO BURNING

* 45 kg "ha,

-

NO BURNING

0 0 kg N/ha, NO BURNING 0 0 kg N/ha, FALL BURNING

I

I

1

1881

1901

1921

I

1941 YEAR

I

I

1961

1981

I

FIG.2. The effect of management practices on the long-term change in organic C in the top 30 cm of a Haploxeroll soil in Oregon. (From Rasmussen er a / . , 1989.)

110

PAUL E. RASMUSSEN AND HAROLD P. COLLINS L

0

*

100

al

x

> .f y"

0

-

-100

-

-200

-

BURN

STRAW

PEA VINES 0 MANURE A

v

w (3

Z

a

I 0 -300 Z 0

m-400

**. '

I

5

Y = 0.18OX

-

460

'

I

Rz = 0.66 I

'

I

'

'

"

'

'

'

FIG.3. The effect of the rate of carbon input on organic C change in a Haploxeroll soil in Oregon. Study conducted from 1967 to 1986.

Black (1973) applied straw-mulch rates of 0, 1.68, 3.36, and 6.73 t/ha biennially to a spring wheat-fallow system in Montana for 8 years and measured organic C and N at the beginning and end of the study. Different combinations of N and P fertilizer rates were included. Residue addition increased soil organic C and N levels linearly, with 7040% of the applied C retained in the organic fraction at the end of 8 years. This percentage is much higher than reported in other studies. The difference may be partially attributable to a difference in residue burial. Residue was incorporated in other studies but remained on the soil surface in the Montana study. About 50% of straw had not yet decomposed by seeding, some 12 months after application. Thus a new equilibrium may not have been attained during the lifetime of this experiment. Sampling procedures do not indicate if coarse organic matter was removed before C analysis. Allmaras et al. (1988) reported that 23-46% of wheat residue did not pass a 0.5-mm sieve after 12 months of burial in soil. The Montana study (Black, 1973) indicated that neither N nor P application altered the rate of organic C or N retention in soil, although both increased grain yield and residue production. Residue rates were established by complete removal and subsequent return of specific amounts, which eliminated any effect of N or P on residue input. As in other studies, carbon control of biological reactions was indicated by the failure of fertilizer to affect C or N content in soil. In a humid region (Iowa), Larson et al. (1972)returned different rates of cornstalks to continuous corn for 13 years and measured organic C and N in soil. Both C and N increased linearly with increasing rate of residue. From the studies listed in Table V, it is possible to calculate the amount

SOIL ORGANIC MATTER IN SEMIARID REGIONS

111

of C and N retained in the system and the amount of residue need to prevent a decline in organic C or N in soil. The regression equation Y = a + bX can be developed, where Y = the change in C or N divided by number of years of study (in kg/ha/yr) and X = annual C input from residue (kg/ha/yr). Except for the study by Black (19731, the slope of the regression line ranged between 0.14 and 0.21, suggesting limited variation in the proportion of organic residue that is ultimately retained in soil organic matter under a variety of climatic conditions. Data from Washington and Oregon (Table V) suggest that the percentage of retention may increase with increasing precipitation and decrease with intensity of cropping. Less residue was required to prevent further decline in organic C and N under annual cropping than under wheat-fallow rotation, even though the rate of C retention appeared to be slightly lower. In the studies listed in Table V, the maximum rate of residue applied exceeded the average residue production for that area. Linearity indicates that soil is capable of sequestering from 10 to 25% of the C supplied as processing waste, feedlot manure, or crop residue. Rates of feedlot wastes from 30-90 t/ha applied to soil have shown only limited decrease in the fraction converted into organic matter (Somrnerfeldt et al., 1988). The negative intercepts in Table V indicate that loss of organic matter will continue in many of the present cropping systems without adequate residue return to soil. The amount of residue required to prevent further loss can be estimated by dividing the absolute value of intercept by the

Table Vl Increase in Organic C in Soil with Residue Addition (1947-1954)and Subsequent Decrease after Termination of Residue Input (1954-1WO)'~6 ~~

~

Rate of change g C/kglyr

Material added' ~~

Rotted manure Fresh manure Straw Green manure None (NPK) a

1947- 1954

1954-1970

+ 1S O

-0.51 -0.41 -0.36 -0.21 -0.09

Time required to return to original level" (yr)

~~

+ 1.06 +0.69 +0.43 0

Adapted from Sauerbeck (1982). Silt loam on loess soil, 865-mm precipitation zone, Germany. Residue added at 20 t DM/ha/yr for 6 years. Original level was 13.0 g Cfkg.

20.6 18.0 13.3 14.3

112

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

slope and multiplying by 2.38 to convert organic C to total residue. Residue returns of 1.7, 5.4, and 4.6 t/ha/yr were required in wheat-fallow regions of the Pacific Northwest, U.S. receiving 240,416, and 564 mm of precipitation. Much lower residue return was needed each year if cropped annually (1.9 t) rather than to a crop-fallow rotation (4.6 t). The Iowa data projected that a residue return of 6 t/ha/yr was required to prevent further organic matter loss for continuous corn in a humid climate. While residue input can increase organic matter content, continued input must be sustained. Large applications of residue for 6 years in Germany increased soil organic C substantially (Table VI). But when residue addition was discontinued, organic C returned to its original level within 13 to 2 1 years. It appears from this study that very little of the added C was incorporated into relatively stable C fractions in soil. 3 . Residue Burning

Luebs (1962), Oveson (1966), and Rasmussen et al. (1980) in the United States and Dormaar et al. (1979) and Biederbeck et al. (1980) in Canada addressed the long-term effects of residue burning on cereal grain yield and soil nutrient content. Most of the early work involved burning for less than 20 years and did not find any reduction in grain yield or soil organic matter content. More recent studies (Biederbeck et al., 1980; Rasmussen et al., 1989) have shown accelerated C loss and lower microbial activity in soil where straw has been burned for over 20 years. The failure of burning to increase C loss from soil when 50-70% of the residue C is volatilized probably results because much of the charred residue left after the burn is not biologically active. It is likely that burning is changing the quality rather than the quantity of organic matter in soil. To our knowledge, no one has determined if there is a change in the equivalent-age of any of the organic fractions as a result of repeated burning of crop residue. 4 . Residue Removal

Crop residues are used for fuel or animal feed in many areas of the world. Residue removal decreases C input into soil and thus inherently lowers organic matter level. Specific studies to determine the effects of residue removal have seldom been conducted. The effects of residue removal on soil organic matter can be estimated from the residue-rate studies of Horner er al. (1960), Larson et al. (1972), and Black (1973). Few semiarid regions have a productivity level that permits substantial residue removal without accelerating soil organic matter depletion. Present pro-

SOIL ORGANIC MATTER IN SEMIARID REGIONS

113

duction ranges from 1 t/ha in arid soils with low organic matter content to 6 t/ha in subhumid soils with high organic matter levels. Current input in most areas is presently only about 80% of the amount needed to prevent further loss of organic matter. Residue removal is more feasible in humid regions where productivity is higher (Larson ef al., 1978).

B. ANIMALMANURE The value of animal manure in relation to crop residue is difficult to evaluate. Comparisons of C inputs from manures and crop residues are not always possible because the dry matter and C content of manure was not determined. Most mature air-dry plant residue contains about 900 g dry matterjkg and 420 g Cikg of residue. Manure, on the other hand, usually contains significantly more water and the organic C content is normally much less than 420 g/kg. In general, manure contains about 500 g dry matterlkg and 150 g C and 11 g N/kg of dry material. Yearly variation and the 1 1-year average C and N content of manure applied in two long-term studies is shown in Table VII. Nitrogen content is especially variable, with a coefficient of variation over 50%.

Table VII

Dry Matter (DM), C, and N Content of Manure Applied at Two Locations for 11 Consecutive Y e a d Consecutive year

Pendleton. Oregon, U.S.A.

Lethbridge, Alberta, Canadab

DM

C

N

DM

C

N

11

540 568 367 434 437 544 480 817 470 468 468

59.9 52.3 69.4 75.5 86.1 62.0 66.2 31.9 49.8 78.6 96.2

4.91 3.80 4.66 4.82 5.59 4.79 5.28 3.43 4.65 6.22 6.45

517 492 52 I 659 658 495 512 574 55 I 476 653

99.8 119.6 86.0 110.1 111.2 99.5 104.4 75.8 29.2 36.7 136.5

9.10 9.64 10.32 9.16 11.78 9.70 7.83 9.36 3.86 4.33 12.02

Average Std. error of mean CV(%)

508 35 23

66.1 5.4 27

4.96 0.86 58

555 21 13

91.7 10.0 36

8.83 2.50 94

1 2 3 4 5 6 7 8 9 10

Manure obtained from same source at each location. Values are given in g i k g (moist weight basis). Sommerfeldt et al. (1988).

114

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

In most studies, the effect of manure on soil organic matter exceeded that of plant residue. Organic C and N levels in soil in many areas were higher with manure application than with straw or legume addition (Haas et al., 1957; Horner et al., 1960; Sowden, 1968; De Haan, 1977;Sauerbeck, 1982). It is not possible to determine if C input from manure was the same as that of other residues. In two long-term experiments where the nutrient content of manure was measured (Table VII), there were wide yearly differences in dry matter, C , and N content even though the manure was always obtained from the same source in each study. Variability would be expected to be even greater if different sources and different storage methods were included. Using average values for dry matter, C , and N content to calculate manure inputs when it is not reported is tenuous at best. Where the C content of manure has been determined, the effect of manure on organic C and N appears to be the same as that of legume and straw residues (Fig. 3). But if the Pendleton values for manure are used to estimate C input from manure in the Pullman and Lind studies (Horner et a!., 1960), the manure data does not fit the regression line obtained with straw addition. Manure appears to have greater effect, suggesting that either the calculated input is incorrect or the materials were not equally beneficial.

C . GREENMANURE Green manures have generally been less effective than crop residues or animal manures for stabilizing or increasing soil organic matter levels (Haas et al., 1957; De Haan, 1977; Power, 1990). The primary function of green manure is to sequester biologically fixed N in sufficient quantity to meet the requirement of the following crop, As such, vegetation is normally incorporated into soil before it is mature, and as a result, does not have the same chemical composition (i.e., lignin) that is found in mature plants. Lignin content has a large influence on the stabilization of C and N in recalcitrant soil fractions (De Haan, 1977).

V. ORGANIC MATTER AND MICROBIAL BIOMASS Soil organic matter exerts a positive influence on the soil biomass, which mediates processes of soil organic matter turnover (McGill et al., 19861, and nutrient cycling and soil aggregation (Aspiras et af., I97 1; Molope et af., 1987).There is a dramatic decrease in microbial biomass as well as soil

SOIL ORGANIC MATTER IN SEMIARID REGIONS

115

organic matter when a virgin soil is cultivated (Martel and Paul, 1974; Houghton er al., 1983). Factors that affect crop production ultimately affect the size and activity of the soil microbial biomass (Biederbeck et al., 1984). Net primary production of native grasslands is generally greater than that of agroecosystems, with the majority of fixed C accumulating in belowground biomass (Kucera et al., 1967; Allison, 1973; Anderson and Coleman, 1985). Typically, perennial grassland soils contain about twice the amount of root biomass as agricultural soils (Yegorov and Dyuryagina, 1973; Sims and Singh, 1978; Sala et al., 1988), and therefore maintain higher soil organic matter contents. The amount of root biomass is important since it supplies a significant quantity of available C to the microbial biomass (Lynch and Panting, 1980; McGill et al., 1986). In most cases, the microbial biomass of grassland soils is about twice that of cultivated soils. Microbial biomass C ranges from 100 to 600 mg C/kg soil when cropped to cereals (Insam et al., 1989; Anderson and Domsch, 1989) and can exceed 1500 mg C/kg soil under native grassland or managed grass pasture (Ross et al., 1980). Extended cultivation usually reduces soil biomass, which influences organic matter cycling. Reductions in microbial biomass result from lower C inputs and environmental stresses created by management. These stresses include increased soil acidity from ammoniacal fertilizer use, soil erosion that decreases C, N , and other essential nutrients, and increased soil density, which reduces aeration and water availability. It is generally assumed that microbial biomass C and activity measurements are correlated with soil organic C because soil biomass depends on the quantity of degradable C sources present in soil (Adams and Laughlin, 1981). Anderson and Domsch (1989) evaluated this relationship over a range of soils and Insam et al. (1989) evaluated over different climatic zones. Both found a correlation but the relationship was complicated by a number of integrative factors, especially in drier regions. Anderson and Domsch (1989) surveyed 134 plots located on 25 experimental sites within a narrow temperate climatic zone of central Europe and found a high correlation between soil microbial biomass C (CM)and soil organic C (CO) (Fig. 4a). Microbial biomass C averaged 2.3 and 2.9% of organic C for monocultures and crop rotations, respectively. The difference was primarily due to the type and amount of organic C input; soil physical properties (i.e., texture) were of minor consequence. They suggested that monocultures and rotations were comparable with respect to steady state conditions, but that no universal equilibrium constant could describe the increase in microbial C per unit of soil C between cropping systems. Regression analyses indicated that higher CM: CO ratios were characteristic of soils with regular crop rotation (Fig. 4a). Fallow in the rotation reduced soil organic matter and subsequently influenced the CM: COratio.

116

PAUL E. RASMUSSEN AND HAROLD P. COLLINS 1000

a

-

-

CROP ROTATIONS

600 -

.$

400 -

(5,

> 24

200

Ir -

-

E

v

z

i!u Q:

CONTINUOUS MONOCULTURE Y = 22.4X + 26 R2 = 0.89

0 1000

:

-

800 -

b

- CROP ROTATIONS Y R’

= 13.0X = 0.34

+

*

193

R2 = 0.50

01 0

I

10

I

20

I

30

I

40

ORGANIC C (g/kg) FIG.4. The relationship between microbial biomass and organic C in soil with continuous monoculture and crop rotations. ( From Anderson and Domsch, 1989 (a); and from Insam et al., 1989 (b). Reproduced from Soil Biology and Biochemistry, 21, pp. 214-216, 476, by permission of Pergamon Press PLC. Copyright 0 1989 by Pergamon Press PLC.)

In a similar study of North American soils, Insam et a / .(1989) found low correlation between microbial C and soil organic C (Fig. 4b), and concluded that the relationship was dependent upon factors other than organic C. They found that the CM:CO ratio was influenced by macroclimate, particularly the combined variables of precipitation and evaporation (Fig. 5). Variance across climatic zones was attributed to differences in soil texture, fertilization, tillage, and crop rotation. Climatic effects on soil microbial biomass tended to increase as conditions become drier. Insam et al. (1989) concluded that, since CM: CO is influenced by climatic factors,

117

SOIL ORGANIC MATTER IN SEMIARID REGIONS 50 40 0

0

cn

30

-

Y

\ 0

20-

A

mloL 0

I

0.1

0.2

I

0.3

A

I

I

I

0.4

0.5

0.6

I

0.7

:

0.8

0.9

PE FIG. 5. The effect of climate on microbial biomass C per unit of organic C. Climate is defined as PE index, or the ratio of precipitation to pan evaporation (in mm). (From Insam et al., 1989. Reproduced from Soil Biobgy and Biochemistry, 21, p. 217, by permission of Pergamon Press PLC. Copyright 0 1989 by Pergamon Press PLC.)

the equilibrium constant should be replaced by an equilibrium function determined from prevailing climatic variables. Powlson e? af. (1987) proposed that shifts in biomass C measured over relatively short time periods could indicate changes in soil organic matter levels long before they could be detected by other methods. Anderson and Domsch (1989) stated that “soil systems tend towards a state of equilibrium if both the environment and agricultural practices remain constant over long periods.” They suggested that the microbial biomass responds more quickly to a change in management than does soil organic matter. This is not altogether unexpected, since microbial biomass in soil is related to residue input and residue production in semiarid regions is dependent on cultural and climatic factors. Annual cropping, cultivation, residue management and N fertilization influence the amount and distribution of soil organic matter and ultimately, microbial biomass (Biederbeck et al., 1984; Coote and Ramsey, 1983; Rasmussen et af.,1989). Differences in microbial activity were associated with the distribution of residue, increased moisture, and moderation in soil temperature. Doran (1987)reported that microbial biomass and potentially mineraiizable N in no-till soils was 54 and 37% higher, respectively, in the surface soil of conservation tillage systems than in the surface horizon of plowed soils. Adoption of conservation tillage practices increased both biomass C and N , and soil C and N mineralization potentials, but had little

118

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

effect on the soil organic matter level after 16 years (Carter and Rennie, 1982). In a similar study, Campbell et al. (1989) supported these observations, but concluded that reduced tillage had a net positive effect on soil organic matter accumulationin the top 8 cm of soil. Tillage systems usually have little effect on soil C below 8 cm (Doran and Smith, 1987). Potentially mineralizable C and N may provide sensitive parameters to assess changes in soil organic matter induced by tillage or other soil management strategies (Carter and Rennie, 1982; Campbell et al., 1989). High concentrations of active C and N enhance organic matter accumulation. Soil organic matter can be divided into active (labile) and recalcitrant fractions. Schimel et al. (1985) suggested that cultivation reduces active fractions since they are readily mineralized. Net mineralizable C released as CO2 from laboratory incubations clearly shows different accumulation of labile C under different management practices (Fig. 6). The percentage of C mineralized from a grass pasture and cultivated soils under wheat-pea, continuous wheat, and wheat-fallow rotation were 2.6, 2.0,

600

-

y"

PGP 2.6%

500 -

400 -

\ (5,

------

'f -

-

w-P 2.0%

W-F 1.6%

DAYS FIG. 6. Net carbon mineralization from soil during 30-day incubation as affected by cropping systems; Pendleton, Oregon. PGP, permanent grass pasture; W-P,wheat-pea rotation; W-W, wheat-wheat rotation; W-F, wheat-fallow rotation. Percentages reflect the percent of total C mineralized.

SOIL ORGANIC MATTER IN SEMIARID REGIONS

119

1.8, and 1.6%, respectively. Fertilization practices generally increase soil microbial biomass through increased production of plant material and greater return of crop residues to soil (Biederbeck et al., 1984). Organic amendments produce more microbial biomass than inorganic fertilizers because they increase the proportion of labile C and N, directly stimulating the activity of the biomass.

VI. MANAGEMENT EFFECTS ON PHYSICAL PROPERTIES Cultivation of grassland soil usually increases bulk density. An increase in bulk density is also likely with erosion of topsoil. Changes in bulk density can have a pronounced effect on the amount of organic C and N in soil, and if not measured, can lead to inaccurate estimates of nutrient loss or gain. Voroney et al. (1981) reported that 70 years of cultivation in the Canadian prairie increased the bulk density of surface soil by 16%. The increase in North Dakota was 1 1 % (Bauer and Black, 1981). Bulk density of a cultivated Haplustoll in Agrentina was 13% higher than in its virgin counterpart (Miglierina et al., 1988). Bulk density increases for six vertisols in Australia ranged from 13 to 28% (Dalal and Mayer, 1986). Residue addition tends to decrease bulk density. Residue addition in Montana decreased soil bulk density in the 0-7.5- and 7.5-15-cm soil layers 0.015 and 0.011 g/cm3, respectively, per ton of residue applied (Black, 1973). In the loess plateau of China, straw addition decreased bulk density 0.020 g/cm3 per ton of residue (Siming et al., 1988). Incorporation of organic materials into soil promotes the aggregation of soil particles (Smith and Elliott, 1990). Under native grasslands, stable soil aggregates can be formed through differential dehydration as a result of water uptake (Tisdall and Oades, 1982). Root exudates also stimulate microbial activity and increase production of polysaccharides that promote aggregate stability (Aspiras et d.,1971; Molope etal. 1987). Continuous cultivation of soil generally leads to a reduction in soil organic matter and an increase in soil erodibility. Studies in Texas (Unger, 1982) and Canada (Nuttall et al., 1986) show that more intensive tillage decreased aggregate stability and increased the erodible fraction (<0.84 mm). Tillage affects C availability to the microbial biomass by disrupting soil structure and exposing protected organic material. After long periods of cultivation, microbial activity may become C limited. This will subsequently reduce the production of aggregating compounds and create a soil structure that no longer resists soil detachment and transport by water.

120

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

VII. CULTIVATION AND FUTURE CHANGE IN SOIL ORGANIC MATTER While some studies indicate that loss of soil organic matter will cease after 50 to 60 years of cultivation (Voroney et al., 1981; Bauer and Black, 1981; Unger, 1982), other studies project a continuing decline (Tiessen et al., 1982; Rasmussen et al., 1989). The difference between studies is likely related to the rate of residue input in relation to climate and cropping system. Some systems have reached equilibrium, others have not. The role of management in determining the equilibrium level is illustrated in Fig. 2. The range in the organic C after 55 years due to different management practices is nearly as large as the total amount of C lost in the first 50 years of cultivation. This clearly indicates that cropping practices and residue management have an important role in maintaining organic matter in soil. Reducing the frequency of fallow will help to stabilize the system, since less residue is needed to prevent organic matter loss when soils are cropped more intensively. Although the mechanisms are not well understood, having a crop on the land has the potential to reduce microbial activity and slow the turnover of soil organic C (Reid and Goss, 1983; Sparling et al., 1983). Reid and Goss (1983) suggested that the release of inhibitory compounds from roots, preferential use of root exudates over soil organic C, greater microbial predation in the rhizosphere, and plant competition for organic compounds were likely mechanisms. Greater use of conservation tillage shows promise for preventing further decline in organic matter. Technological advances that increase the productive capability of the land also have the potential to increase soil organic matter content. This potential is tempered by the large fraction of root and shoot biomass found in noncultivated grasses (Sirns and Singh, 1978). Root and crown biomass undergo rapid oxidation with cultivation and are almost depleted after the first 20-30 years of farming. Where this fraction no longer exists, higher production has greater potential for improving the organic matter content of soil. Cereal grain yields have been steadily increasing for the past 30 years. Although there has been a shift toward shorter growth habit and higher harvest index, the amount of straw produced still appears to be greater than prior to the 1960s. Table VIII shows the change in straw production in the Pacific Northwest, U.S. brought about by improvements in wheat varieties and crop management. Straw production the past 20 years is 13 to 66% greater than it was during the previous 35 years. Aboveground production is presently substantially greater than the estimated production of native grassland. Thus, it is

SOIL ORGANIC MATTER IN SEMIARID REGIONS

121

Table VlII Annual Straw Production for Different Cereal Rotations at Pendleton, Oregon for the 1931-1966 and 1%7-1986 Periods in Relation to Grassland Vegetative Production Straw yield (tlhalyr) Rotation Wheat-fallow Wheat-fallow Wheat-pea Wheat-wheat Grassland"

Nitrogen applied

No Yes Yes Yes No

Magnitude of change

1931- 1966

1967-1986

(%)

2.17 3.37 4.81 3.50 2.52

2.66 3.82 5.90 5.81 2.52

+ 23 + I3 + 23 +66 0

Grassland production estimated from Johnson and Makinson (1988) and Daubenmire ( 1970).

possible that we may see a shift towards increasing organic matter levels in some soils in future years. But, as predicted by Voroney et af. (1981), changes will not be dramatic. Government farm programs that divert highly erodible cropland back to grassland should increase the organic matter in soil. The primary benefit will be decreased erosion and greater retention of organic C and N. Conversion of cultivated soil back to grassland will not produce a quick rise in organic matter content. Both White et al. (1976)and Dormaar and Smoliak (1985)found only low rates of increase in organic matter after cropland was seeded back to grass. Belowground biomass remained 36% lower in revegetated than in native range some 55 years after return to grass (Dormaar and Smoliak, 1985). It may be that improved management under cultivation accompanied by maximal residue return will be just as successful as periodically seeding cropland back to grass.

VIII. IMPACT OF SOIL EROSION Soil erosion is a much overlooked factor contributing to the loss of soil organic matter (Slayter and Carleton, 1938;Voroney et al., 1981).Perhaps the most difficult part of defining organic matter change in soil has been the accurate assessment of erosion. Continued erosion will have a pronounced effect on the stability of organic matter levels in soil, and eventually reduce the long-term productivity of many agroecosystems. Soil erosion rates have been measured on few long-term experiments, thus it is not possible to separate erosion losses from those due to accelerated oxidation or

122

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

reduced C input. Fortunately, most long-term experiments are located at or near research centers and have been intensively managed. Thus, wind and water erosion have been minimized. On the negative side, most of the research centers are located in the most fertile areas (by virtue of agricultural settlement) and are generally located on level to gently sloping landscapes. This means that they are not subject to the degree of erosion common to steeply sloping land. Erosion tends to selectively remove the smallest and least dense particles. The highest nutrient concentration in soil is associated with organic matter and with clay particles. This means that sediment eroding from the landscape contains more nutrient quantitatively than the matrix from which it is eroding; this is termed the “sediment enrichment factor.” Barrows and Kilmer (1963) summarized nutrient losses from soils and stated that the sediment enrichment factor ranged from 1 . 1 to 5.0. They selected a value of 2.0 to estimate nutrient loss when it was not reported. Young et al. (1985) found sediment enrichment ratios of 1.5 for conventional tillage and 2.1 for no-till in Minnesota. Soil loss was, however, much less with no-till, which completely offset the increase in enrichment ratio. Enrichment ratios were similar for soils in Minnesota and Indiana, but higher in Mississippi where C content was lower. De Jong and Kachanowski (1988) used an enrichment factor of 1 . 1 to describe wind erosion, based on saltation and suspension values obtained in wind tunnel studies. Estimates of erosion did not agree well with measured soil loss, however, indicating that the factor of 1.1 was not appropriate. Present data indicate that soil erosion surpasses accelerated mineralization as the dominant factor affecting organic matter loss from soil after about 50 years of cultivation. Early work by Slayter and Carleton (1938) projected that erosion could account for nearly all of the C and N loss from soil with cultivation. Subsequent work by Gregorich and Anderson (1985) estimated that erosion accounted for 20% of C loss from a black Chernozem soil cultivated 20 years and 70% from other soils cultivated for more than 50 years. De Jong and Kachanowski (1988) estimated that C losses since 1960 on the middle and upper slopes of coarse-textured soils were primarily due to erosion. Woods (1989) reported that erosion substantially reduced the active fraction of soil organic matter in a grazed native shortgrass prairie. Loss of the top 1 cm of an uncultivated soil resulted in 33,28, 54, and 67% reduction in biomass C, biomass N , respirable C, and rnineralizable N , respectively. The projected effect of continued erosion on soil organic matter in Canadian prairie soils is illustrated in Fig. 7. It is quite apparent that not even “acceptable” levels of wind or water erosion can be tolerated if we are to maintain or increase the organic matter content of soil. An erosion rate of 22 t/ha/yr will remove about 277 kg C and 25 kg N/ha from a soil

SOIL ORGANIC MATTER IN SEMIARID REGIONS

123

a

-

100

EROSION PROTECTION FACTOR = 0.75 - STRAW REMOVED IN FIRST 50 YEARS

NO EROSION

0' I 100

b

- EROSION PROTECTION FACTOR = 0.30

-

0

80

f

60

z

I

STRAW RESIDUES RETAINED

W

rn 40

0

I

I

100

200

I

300

I

400

YEARS OF CULTIVATION FIG.7. Effect of soil erosion on organic carbon in the top 15 cm of a Canadian prairie soil under (a) crop-crop-fallow and (b) continuous cropping (no fallow). (From Voroney et a / . , 1981.)

with 20 g/kg organic matter and a bulk density of 1.25, assuming a sediment enrichment ratio of 1.5. This is equivalent to the input of 4.4 t/ha/yr of residue to a soil that retains 15% of the carbon input. That amount comprises a substantial portion of the annual dry matter production in many semiarid regions.

IX. PREDICTING SOIL ORGANIC MATTER TURNOVER A. CARBONPOOLSA N D CARBON CYCLING

Transformations of organic C in terrestrial ecosystems are biologically controlled and occur for the most part in soil. The carbon cycle can be essentially considered a perfect cycle since nearly all C is returned to the

124

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

environment as C 0 2 about as fast as it is removed. The constant interaction of atmospheric and terrestrial CO;?allows the cycle to feed itself (Fig. 8). Transformations within the C cycle involve conversions of inorganic C to organic forms (immobilization) and conversion of organic C back to an inorganic form (mineralization). Photosynthesis immobilizes C from a large atmospheric reservoir into terrestrial ecosystems. Estimates of atmospheric content of C range from 690-700 x lo9 tons, whereas soil organic matter contains approximately twice this amount (Woodwell et al., 1978; Hobbie and Melillo, 1984). Cultivated soils account for slightly less than 10% of the earth’s surface but maintain over 12% of the world’s total C as detritus (Schlesinger, 1977). Estimates set annual C fixation in grasslands and cultivated lands at 10 and 5 x lo9 t of C, respectively (Hobbie and Melillo, 1984). Decomposition and respiration activities of soil biota account for a nearly equivalent return of C02 to the atmosphere as that fixed in photosynthesis (Hobbie and Melillo, 1984). The majority of energy acquired by the soil biota comes from the oxidation of carbonaceous materials. As a result, C02 is evolved continuously during decomposition and in large amount.

i

Plant Carbon

I

I Animal Carbon I

IT ! 1 I

A1

I

lI3

1I

I

I

r ..-

Soil Organic Matter

Microbial Cells, Decayed Residues

Carbon Dioxide

-

1-

1I l c i

I

A, Photosynthesis C, Respiration, animal D, Autotrophic microorganisms B, Respiration, plant E, Respiration, microbial

FIG. 8. The carbon cycle. (From Alexander, 1977. Reproduced from “Introduction to Soil Microbiology” by permission of John Wiley & Sons, Inc. Copyright 0 1977 by John Wiley & Sons.)

SOIL ORGANIC MATTER IN SEMIARID REGIONS

125

B. MODELSOF SOILORGANICMATTERTURNOVER Modeling the dynamics of C flow through agroecosystems requires a description of biological, chemical, and physical processes involved in organic matter stabilization (Frissel and Van Veen, 1978). Early models describing soil organic matter decomposition used simple first-order rate reactions based on a single-state variable of soil C concentration (Jenny, 1941).This type of analysis implies that soil organic matter decomposition rates are proportional to the organic matter concentration (Van Veen and Paul, 1981) and biological activities of soil are not rate limiting at any time (Van Veen et al., 1981). Jenkinson and Rayner (1977) described the effects of long-term cropping and manure on the production and stabilization of organic matter by radiocarbon dating various fractions of soil organic matter. Data describing organic matter turnover were obtained from 10- to 100-year-oldexperiments conducted at the Rothamsted Experiment Station in England. Simulations of soil organic matter turnover were accomplished by following the flux of C through five soil organic matter pools. These were: decomposable plant material, resistant plant material, soil biomass, physically stabilized organic matter, and chemically stabilized organic matter. Half-lives of these soil organic matter fractions range from a few months for easily decomposable plant material to nearly 2,000 years for chemically stabilized fractions (Jenkinson and Rayner, 1977; see table below). Comoartment

Half-life (yr)

Decomposable plant material Resistant plant material Soil microbial biomass Physically stabilized Chemically stabilized

0. I7 2.31 1.69 49.5 1980

At the end of a 10,000-year simulation, the model predicted that soil receiving 1 t C/ha/yr would contain 24 t C/ha in the top 23 cm of soil. The correlation between predicted and observed data was good for unmanured treatments but poor for those receiving inorganic fertilizer, tending to overestimate the amount of soil organic C produced and underestimate soil biomass C pools. Campbell (1978) incorporated separate compartments for labile and stable pools within soil organic matter, which produced estimated turnover rates of 53 and 1429 years, respectively. Paul and Van Veen (1978) improved on this approach by including a correction factor for microbial growth and microbial product stabilization. Earlier models considered that

126

PAUL E. RASMUSSEN AND HAROLD P. COLLINS

C from plant material was the only available substrate for soil microorganisms. Variability in turnover rates of specific compounds were interpreted as resulting from protection of substrates against microbial decomposition (Jenkinson and Rayner, 1977). In a later model, Van Veen and Paul (1981) incorporated modifications that quantified the protection of organic matter by soil components and expanded descriptions of soil organic matter compartments (Fig. 9). Native soil organic matter was divided into three fractions: (1) “active” (microbial biomass), (2) decomposable organic matter (microbial products, litter, and root lignin), and (3) recalcitrant. The latter two can vary due to physical and chemical protection by the soil matrix. Lignin was assumed to enter the decomposable organic matter fraction where it could either decompose or be directly incorporated into recalcitrant organic matter. This fraction had a rate constant derived from the mean residence time (equivalent age) of old recalcitrant organic materials (Table IV). Lignin can have a strong influence over decomposition rates and its concentration varies for different plant materials (Herman et al., 1977; Collins et af.,1990).Temperature and moisture effects were evaluated independently in Van Veen and Paul’s model, and combined effects determined by applying reduction factors to an optimal condition. Under grassland, it was assumed that 50% of the organic matter was protected. Under cultivation, protection was reduced to 20% for the plow layer and 40% for lower layers.

1 p 1 I 80 %

87 %

pecomposablel G o u s fraction fraction

fraction

20

p g n q fraction

Not physically protected

protected Chemical

I

k o r g a n i c - m a t t e r / ‘.,. P h x ] protected

FIG.9. Long-term carbon turnover model. (From Van Veen and Paul, 1981.)

SOIL ORGANIC MATTER IN SEMIARID REGIONS

127

The model illustrated in Fig. 9 was very sensitive to factors involving soil organic matter protection. Soil organic matter turnover and biological activity varied with organic matter input, temperature, and moisture. Moisture and temperature directly influenced the rate of decomposition and plant production. Thus, C inputs were strongly controlled by the prevailing environmental conditions. Early models of soil organic matter turnover predicted that steady-state equilibrium would be achieved 80 to 100 years following implementation of management practices that encourage soil organic matter retention (Lucas et al., 1977; Sauerbeck and Gonzalez, 1977). Voroney et al. (1981) made further modifications to the model by including effects of long-term cultivation and erosion. Erosion losses were predicted by incorporating the universal soil loss equation (Wischmeier and Smith, 1965). The model accurately predicted soil organic C levels after 70 years of cultivation and projected equilibrium at 60% of the original after 100 years of cultivation (Fig. 7). Simulations that included soil erosion significantly increased the loss of organic matter, particularly after 50 years of cultivation. The previous discussions centered on models describing reductions in soil organic matter. Parton et al. (1987) developed a soil organic matter formation model (Century Model), which simulates steady-state organic matter levels in grassland soils of the Great Plains. The model incorporates multiple organic matter compartments, simulates litter decomposition as a function of monthly soil temperature and precipitation, and describes transformations of C and N in soil. Decomposition rate coefficients of the steady-state variables were constant except for structural and active soil organic matter decay rates. The former was a function of the plant lignin content and the latter dependent upon soil texture. The model assumed that all transformations of organic C were the result of microbial activity, with 55% of the C lost due to microbial respiration. Lignin concentration in dead root and aboveground biomass was indirectly controlled by annual precipitation. Soil texture influenced the rate of active organic matter decomposition and the efficiency of stabilization. The model also included plant production and N submodels, and evaluated the influence of partial grazing. Steady-state organic C and N levels were very sensitive to grazing. The Century model overestimated soil C and N levels for fine-textured soils, underestimated them for sandy soils with high initial C and N content, but fit well for medium-textured soils. In addition, the data base was used to generate maps of plant production and soil C and N distribution as related to soil texture and climate of the Great Plains. The model successfully explained trends in organic matter dynamics and had an overall error of about 15%.

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Parton et al. (1988) subsequently modified the Century model to simulate changes in composition of C, N, P, and S in virgin and cultivated soils. The revised model included additional submodels describing P and S transformations. The model was relatively successful at simulating the formation of soil organic matter and describing the impacts of cultivation on organic C, N , P, and S in soil. Organic matter formed during a 10,000 year simulation reached 80% of the final level within 2,500 years and 100% within 5,000 years (Fig. 10). Aboveground plant production was similar to soil C and N accumulation, with 80% of maximum produced in the first 1,500 years. After 800 years, N became limiting and plant production reflected soil N mineralization rates. 8000

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Simulations involving cultivation adequately described decreases in organic C, N , P, and S after 60 years (23, 25, 18, and 20%, respectively) but underestimated the loss of C after 90 years (Parton er al., 1988). They stated that this should be expected since no erosion losses were assumed in the model. Voroney et al. (1981) projected that erosion significantly influences soil organic matter loss (see Fig. 7). Cultivation also reduced the C:P and C:S ratios in organic matter because of an increase in the chemically recalcitrant organic fraction. Investigations of soil organic matter dynamics and the development of deterministic and stochastic models are invaluable tools for describing transformations within agroecosystems. However, further research is necessary to substantiate the validity of current models and their application to other semiarid regions of the world.

X. SUMMARY A. PROGRESS The early 1800s saw new concepts in chemistry and microbiology transferred to soil science. The first crop rotation and nutrient input experiments were established in 1843 at Rothamsted, England. Similar studies were later established in the United States and Canada. Early civilizations in Europe and Asia cultivated semiarid land but not continuously or intensively. Widespread intensive cultivation of semiarid land in most areas of the world began in the late 1800s. By the early 1900s concern was being expressed that drought and wind erosion were reducing soil quality. This produced some of the first experiments in semiarid regions to evaluate the effect of cultivation on soil organic matter. By the 19OOs, organic matter losses were being defined, and factors causing the greatest decline were identified. Frequent fallowing, intensive tillage, and removal of crop residue were responsible for accelerated loss of organic matter. Manure and N application reduced the rate of organic matter loss. Erosion losses were termed “detrimental” but their effect on organic matter decline could not be isolated. The period from 1950 to 1980 produced more changes, some beneficial and some detrimental. Long-term studies indicated that soil organic matter was no longer declining in some cropping systems. Annual cropping replaced fallow in many areas, which reduced organic matter loss from soil. Greater fertilizer use and varietal improvement increased cereal grain yield and straw production, which raised the level of C return to the soil.

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Carbon input was shown to have a significant impact on the organic matter level. Stubble-mulchand no-till systems conserved up to 2% more organic matter per year in surface soil than plowing. Crop rotation, green manuring, and reduced tillage practices lost some of their glamour with the advent of chemical fertilizers and pesticides, and many of the long-term experiments were discarded for more pressing research. Fertilizer and tillage research expanded, and crop improvement received new impetus. Less reliance on crop rotation and green manure were partially responsible for increasing use of inorganic fertilizer. Soil erosion tended to increase with less crop rotation and greater reliance on mechanical tillage and clean fallow. The 1980s produced increasing signs of environmental degradation. Greater concern for nitrogen and pesticide effects on food, soil, and water quality suddenly appeared, creating a shift toward research to thoroughly evaluate humans’ effect on soil and water management. Carbon input was shown to be critical for the long-term maintenance of both soil organic matter and soil fertility. Fortunately, carbon dating and isotope discrimination techniques became available to aid in defining changes in organic C and N over time, and their movement in and out of the different organic matter compartments. Tremendous advances in computer technology permitted the development of well-designed models to test nutrient cycling in soil. Isotope discrimination techniques became economical to the point where research could be extended to many areas of the world. The applicability and sensitivity of these emerging models will continue to be tested with greater interest in the next few years as concern about global environmental degradation increases.

B. FUTURE NEEDS There are several areas that need specific attention to increase progress in our understanding the soil environment. The role of microbial biomass in governing biological reaction rates and the portioning of C and N into the various organic matter compartments are still vague. The pathway for transferring lignin and other complex compounds into the slowly decomposable organic matter fraction has not been determined. Long-term effects of increasing soil acidity from greater use of ammonium-based fertilizer on microbial activity and nutrient transformation rates have not been defined. And, probably of most importance, there is the pressing need to assess the role of erosion on carbon storage and nitrogen utilization in soil. Erosion losses, if not reduced, can negate most of the present positive strategies to increase organic matter levels in soil.

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ADVANCES IN AGRONOMY, VOL. 45

EFFICIENT MANAGEMENT OF LEGUMINOUS GREEN MANURES IN WETLAND RICE Yadvinder Singh, C. S. Khind, and Bijay Singh Department of Soils Punjab Agricultural University Ludhiana 141 004, India

I . Introduction 11. Green Manure Crops for Wetland Rice A. Green Manure Crops for in Siru Incorporation B. Green Leaf Manures 111. Biomass and Nitrogen Accumulation in Green Manures A. Fertilizer Application to Green Manure Crops B. Inoculation C. Effect of lmgation IV. Time and Depth of Incorporation of Green Manures V. Yield Responses of Wetland Rice to Green Manuring A. Dual-Purpose Leguminous Green Manures B. Optimum Application Rate of Green Manures VI. Nitrogen from Green Manure Crops A. N Fertilizer Equivalence B. N Transfer from Green Manure to Rice C. Integrated Use of Green Manure and Fertilizer N VII. Transformations of Green Manure Nitrogen in Wetland Rice Soils A. N Mineralization from Green Manures B. Loss of N from Green Manured Soils VIII. Effect of Green Manuring on Availability of Plant Nutrients Other Than Nitrogen A. Macro- and Secondary Nutrients B. Micronutrients IX. Effect of Green Manuring on Soil Properties A. Electrochemical and Chemical Properties B. Physical Properties C. Biological Properties X. Green Manuring and Reclamation of Saline Alkali Soils A. Green Manure Crops for Saline Alkali Soils B. Reclamation Process C. Effects on Rice Yields XI. Residual Effects of Green Manures Applied to Wetland Rice A. Soil Organic Matter B. Crop Yields XII. Conclusions References 135

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YADVINDER SINGH E T A L .

I. INTRODUCTION Of the total rice (Oryza sativa L.) production in the world, more than 90% is in Asia, and it is increasing annually at the rate of 2.7% [International Rice Research Institute (IRRI), 19861. From 1965 to 1980, around 24% of the increase in rice production in Asia has been attributed to use of fertilizer, mainly N (Barker et al., 1985). Despite increasing use of N fertilizers, soil N and leguminous N2 fixation remain important N sources for rice production in a vast area (Bouldin, 1986; Herdt and Stangel, 1984). For centuries farmers in the tropics have harvested low but consistent rice yields with no fertilizer N inputs. Most probably, of all the N harvested from cropped soils that has subsequently been replenished, a major portion has been through leguminous N2 fixation. In China, India, and Japan leguminous green manure crops had been recognized as an important source of N for wetland rice much before the advent of modern agricultural technology (Bin, 1983; Singh, 1984; Watanabe, 1984). Until the 1960s, farmers often used to grow and incorporate a N2 fixing green manure crop before rice. During the last two decades, due to crop intensification and increased availability of chemical fertilizers, use of green manures declined substantially. For example, at the end of the 1970s milk vetch (Astragalus sinicus L.) green manure was grown in 9 million ha of rice fields in China. By the mid-l980s, the area decreased to 6 million ha (Chen, 1988). A similar trend has been observed in Japan (Ishikawa, 1988). In some countries (e.g., India), fertilizer prices have been subsidized, thereby encouraging farmers to opt for fertilizers to be applied in production-maximizing doses. In recent years, however, with increasing pressure to produce high yields from a single crop and higher total yields under intensive cropping systems, concern for sustainable soil productivity has emerged out as an issue of vital importance. Coupled with concern about ecological sustainability and increasing prices of N fertilizer in relation to price of rice, it has clearly resulted in a tremendous renewal of interest on the part of researchers, farmers, and planners in the old practice of green manuring. It is increasingly appealing as a means to reduce losses of soil organic matter, compaction, and soil erosion and still maintain economic returns. Since high temperature and moisture cause rapid decomposition of organic matter in soils under rice (Grist, 1986), addition of organic matter in the form of green manure may improve physical condition of the soil and

GREEN MANURING IN WETLAND RICE

137

water retention, and reduce leaching of nutrients. Green manuring may also favorably alter the availability of several plant nutrients including micronutrients through its impact on chemical and biological properties of soils. Keeping in view the needs of modern high-yielding N-responsive varieties of rice, recent research in green manuring has been directed more towards its integrated management with inorganic fertilizers. The renewed interest in green manures has led to identification of some hitherto unknown legume plants that have green manuring potential for rice (Alazard et al., 1987; Rinaudo et al., 1982) and short duration leguminous green manure crops that a farmer can insert into an intensified cropping system (Roger and Watanabe, 1986; Abrol and Palaniappan, 1988; Meelu and Morris, 1988). This article reviews some new research in green manuring of wetland rice. Consideration is given to what has been already known and to some extent rediscovered and what is not known about the agronomic advantages of applying green manures to wetland rice as a source of both nitrogen and organic matter. Changed physical, chemical, and biological behavior of soils due to organic matter addition through green manuring, and consequential influence on the availability of several plant nutrients is also reviewed. Green manure crops can be leguminous as well as nonleguminous and can be grown in situ or brought from outside as cuttings of trees and shrubs. The latter practice is called green leaf manuring (GLM). This review will be confined to leguminous green manures whether grown in situ or as GLM, because these are more commonly used in wetland rice fields.

II. GREEN MANURE CROPS FOR WETLAND RICE Ladha et al. (1988) have listed several characteristics that an ideal leguminous green manure crop for wetland rice should possess. Although several legume species have been used as green manure crops in different countries, it has been difficult to find one that possesses all the needed characteristics. More often, green manure crops are sown and turned under in the same field. Interplanting of green manure crops with wetland rice is also practiced. Both root as well as stem-nodulating leguminous crops are used for in situ incorporation. Leaves and cuttings of perennial plants grown along field borders or elsewhere and wild legumes collected from nearby fields and forest areas are used as GLM.

138

YADVINDER SINGH E T A L .

A. GREENMANURE CROPSFOR in Situ INCORPORATION

i . Root-Nodulating Crops Sunn hemp (Crotolaria juncea) and Sesbania aculeata syn. cannabina are the most widely grown green manure crops in India (Table I). Sunn hemp is less tolerant of salinity, acidity, and excess water than S . aculeata but it performs better in low rainfall and limited soil moisture areas (Vachhani and Murty, 1964; Panse et al., 1965). Clusterbean (Cyarnopsis retragonoloba) is fairly drought tolerant and can be used as both vegetable and green manure crop (Veeraswamy and Kunjamma, 1958). Cowpea, valued both as food and green manure crop possessed higher water-use efficiency in terms of dry matter and N production than S . aculeata and clusterbean (N. T. Singh et al., 1981). In south India, Tephrosiapurpurea under drought conditions and pillipesara (Phaseolus trilobus) in erosionprone areas were found promising (Palaniappan et al., 1990). Sesbania speciosa can grow as a perennial plant and is more drought tolerant than S. aculeata (Patnaik et al., 1957). Milk vetch (Astragalus sinicus) is the chief green manure grown in winter season in China. S . cannabina is an important summer green manure. Aeschynomene indica has been recently introduced as a green manure for late rice in China (Liu, 1981). It adapts to warm weather, and tolerates shade, humid conditions, and high temperatures. Green manure crops commonly used in Japan, Taiwan, and Cameroon are listed in Table I. Besides S . rostrata and A . afraspera, milk vetch, sunn hemp, Sesbania, alfalfa and cowpea are used as green manure crops in Senegal (Rinaudo et al., 1988). In Thailand, S. aculeata, sunn hemp, pigeonpea and S . rostrata are among the important green manure crops for wetland rice (Arunin et al., 1988). In Indonesia, Crotolaria usararnoensis, C. anagyroides, and sunn hemp are the important green manure crops for wetland rice (Staker, 1958). Important green manures used in the Philippines are S . cannabina, S . rostrata, cowpea, mung bean (Vigna radiata), and sunn hemp (Table I). Vicia faba, purple vetch, berseem clover (Trifoliurn alexandrinum), subterranean clover, and winter peas are the green manure crops used in the U.S. rice-based cropping system (Westcott and Mikkelsen, 1988; Dabney et al., 1989). In China, S. cannabina is transplanted as an intercrop in the first rice crop and incorporated into land preparation for the second rice crop (Chen, 1988). In eastern India, seeds of S . aculeata and S . speciosa mixed with rice are broadcasted together on dry soil. Green manure is incorporated at 40-50 days after seeding. In south India, farmers sow wild Zndigo, S . speciosa, and Cassia leschenaultiana as green manure in the standing

I39

GREEN MANURING IN WETLAND RICE Table I Biomass and N Accumulation of Green Manures ~~

Green manure crop

~

Age" (days)

Dry matter (tlha)

N accumulated (kglha)

S . aculeata Sunn hemp Cowpea Pillipesara Sunn hemp

60 60 60 60 60

23.2" 30.6' 23.2' 25.0' 4.6

133 134 74 102 78

S . aculeata Cowpea Clusterbean Cowpea Sunn hemp S. aculeata S. aculeata S . aculeata

60 49 49 60 60 60 45 56

2.9 4.4 3.2 6.9 5.4 5.0 2.5 3.7

57 99 91 1I3 110 108 53 98

Sunn hemp S. aculeata

58 50 60 50 60 50 60 45

4.8 4.7 5.9 3.4 5.3 5.0 6.1 3.5

149 85 131 68 110 96 145 77

Reference

India

Sunn hemp S . rostrata

Sunn hemp

Sanyasi Raju (1952)

Bhardwaj et a / . (1981) Singh et a / . (1982) Ben et al. (1989a)

Joseph (1986) Sharma and Mittra (1988) Salam et a / . (1989)

Y.Singh (unpublished data)

China

Milk vetch Sesbania sp. Sunn hemp Common vetch Sweet clover Aeschynornene indica

F

30

22.5-75" 22.5-75' 15.0-37.5' 22.5-45.0' 30.0-60. 0' 15"

101-338 113-375 60-150 105-210 150-300 -

Bin (1983)

Liu (1988)

Jupirn

Milk vetch Soybean

F

19.0-37.5" I I .0-30.0"

65-131 64- I74

Watanabe (1984)

140

YADVINDER SINGH ET A L .

Table I (continued) Green manure crop

Age" (days)

Medicago den ticulata

Dry matter (tlha)

N accumulated (kglha)

0.3-5.6b

18-35

92 89 34-35 26

S . sesban Sunn hemp Cowpealpeas Soybean

Reference

Staker (1958)

Cameroon Crotolaria caricial Sesbania sp. Tephrosia sp.

70- I00

35 .O-45 .Ob

-

30.0-45.0b

-

(50% F)

90

Roy e r a [ . (1988)

Senegal S. rostrata A . afrasperalA.

52 49

16.0-19.0

267-303 423-532

nilotica

Rinaudo et al. (1983) Alazard and Becker ( 1987)

Thailand

S . rostrata

55

-

131

A . indica S . rostrata

55 61

2.1-5.1

41 48-116

Crozat and Sangchyosawat (1985) Herrera et al. (1989)

Philippines

S . acuteata

40 45 48 60 48 48 60 60

4.9 7.5 1.8 3.3 7.0 8.9

86 74 79 198 34 98 157 199

Sunn hemp Soybean

60

8. I

60

6.4

143 138

Mung bean Cowpea S. cannabina Mung bean S. rostrata

Morris et a / . (1986a) Morris et al. (1989)

Meelu and Moms (1988)

141

GREEN MANURING IN WETLAND RICE

Table I (continued) Green manure crop

Age" (days)

Dry matter (t/ha)

N accumulated (kgiha)

Reference ~

Cowpea Pigeonpea Mung bean Indigofera tinctoria

60 60 60 60

3.3 3.6 3.6 3.2

~~

75 76 93 84

U.S.A.

Subterranean clover Crimson clover Hairy vetch Common vetch Purple vetch

Nov-May -

-

Sep-Apr

3.4-4.8 6.7 4.2 4.3 0.8-1.3

72-106 170 I53 134 27-49

Dabney et a/. (1989) Hargrove (1986) Williams et al. (1957)

Sri Lanka

S . sesban

84

4.3

83

Palm et al. (1988) ~

~~

F, flowering. Fresh matter.

rice crop and use it for green manuring in the following main season crop (Vachhani and Murty, 1964). In the Philippines, Indigofera green manure is planted during the wet to dry season transition period. It grows slowly during the dry season and is incorporated in wet season rice (Garrity and Flinn, 1988). Hati (1987) green manured rice by killing S . aculeata plants by spraying 0.9%propanol weedicide after 20 days of germination.

2. Stem-Nodulating Crops Among the stem-nodulating legumes, S. rostrata and A . afraspera have received particular attention. These are characterized by profuse stem nodulation, fast growth, and more active N2 fixation than most rootnodulating legumes. Also, these are less affected by excess water than root-nodulated ones and are able to nodulate and fix N2 with levels of combined N high enough to inhibit root nodulation (Rinaudo et al., 1988). The stem-nodulating legumes usually show a high sensitivity to climatic variations, particularly to temperature and photo period (Dreyfus et al., 1985). S. rostrata grows well in saline and alkaline soils. Although S.

142

YADVINDER SINGH ETAL.

rostrata has performed better in south India (Salam et al., 1989; Palaniappen et al., 1990) and Thailand, it did not do well in northern India (Sharma and Mahapatra, 1990).

B. GREENLEAFMANURES Green leaf manures are preferred when raising green manure crops in situ is not possible, especially in areas with limitations such as lack of irrigation water and due to loss of main crop growing season. Woody species of the genera Gliricidia, Leucaena, and Sesbania, which are widely used in food crop systems in the tropics, are the important GLMs. Some other legumes that produce large amounts of green matter for incorporation in wetland rice include Aeschynomene americana, Phaseolus trilobus, and Flamingo congestis (Vachhani and Murthy, 1964;Brewbaker and Glover, 1988; Nair, 1988). Calliandra calothyrsus, Erythrina spp., Albizia falcataria, S . grandijlora, Flemingia macrophylla, F. congesta, and Delonix elata grown on plot and field boundaries or in woodlots are also used as GLM (Nair, 1988). Species of Sesbania (mostly S . sesban) are used for in situ green manure as well as GLM (Arunin et al., 1988; Palm et al., 1988; Rao et al., 1989). Abdul Samad and Sahadevan (1952) and Sanyasi Raju (1952) have listed a number of tree species and other plants used extensively for GLM in the southern Indian states. Some of the important ones are Cassia auriculata, Melia azadirachta, Calotropis gigantea, Tephrosia purpurea, Gliricidea maculata, T. candida, and Cassia tora. Other plants used as GLM include ipil-ipil (Laolao et al., 1978), Zndigofera tinctoria (Meelu and Morris, 1988), Artimisia vulgaris, Eupatorium gladiosa, and S . formosa (Maskey and Bhattarai, 1984). Potential of Leucaena with wetland rice is limited because it does not tolerate flooding, and must be lopped aggressively to avoid shading. Several wild legumes available from the uncropped land and forest areas (Tephrosia purpurea, T. pumila, A . americana, and A . sesban) can also be used as green manure in wetland rice (Singh, 1971). The most often overlooked aspect in GLM cropping technologies is the amount of plant material available under normal farming conditions, particularly in the semiarid regions where climate imposes a serious restriction on the biomass production. Transplanting and handling the bulky green materials is also a major problem in the adoption of a cut-and-carry practice (Weerakoon and Seneviratne, 1984).

143

GREEN MANURING IN WETLAND RICE

Ill. BIOMASS AND NITROGEN ACCUMULATION IN GREEN MANURES Leguminous green manure species differ widely in biomass production and N accumulation. Different workers have measured biomass production and N accumulation under diverse cultural, climatic, and edaphic conditions and for different durations (Table I). The most productive green manure crops yielded about 4-5 t/ha of dry biomass in 50-60 days. Clusterbean has generally been less productive than Sesbania, sunn hemp, and cowpea in descending order (N. T. Singh et al., 1981; Beri et al., 1989a). The biomass production in Sesbania is mainly controlled by age factor (Fig. la). Soil factors seem to be less important. This observation shows the wide adaptability of Sesbania to diverse soil and climatic conditions. Chen (1988) observed that milk vetch production averaged 30-45 t/ha fresh matter (3.0-4.5 t/ha dry matter) at the full-bloom stage in China, and that Sesbania's yield was similar to milk vetch. Ishikawa (1963) reported that dry matter yield of milk vetch was 2.5 t/ha at blooming, and it rapidly increased to 4.5 tlha during blooming season. Cowpea is very sensitive to 7. 5

-z

6 5-

170

Y = - 2 . 6 5 + 0 135X r = 0.91**

-

(n =36)

.c 0

0

.c

5 5-

\,130-

-z

Z

1

0 c

4

0

45-

k2

3

I

110-

3

3

f

V

u 35-

a

90-

V

V

a

(L

W

$

Y=-47.1+ 2 97x 1 5 0 - r = O 68"" ln=36)

Z

25-

70-

I > 1 5 -

0 51 25

50-

I

I

35

65

I

55

I

30-

c

'

I

65

AGE OF SESBANIA ( d a y s )

FIG.1. Dry matter (a) and N accumulation (b) as a function of age of S. aculeata in India.

144

YADVINDER SINGH E T A L .

waterlogged conditions and produced significantly less biomass than Sesbania and sunn hemp (Morris et al., 1986a). In California, Williams et al. (1957) reported 0.9-1.4 t/ha dry matter yield of purple vetch. Dry matter yield of subterranean clover ranged from 3.4-6.0 tlha (Dabney et al., 1989; Hoyt and Hargrove, 1986). Rainfall and temperature influence the biomass production of green leaf manures. Gliricidia sepium shrub raised on the field boundaries produces about 1-3 t dry leaf material per month from 10,000trees/ha. In India, G. maculata was reported to produce about 14 kg green leaf per shrub in the month of July, which could be used for green manuring the main season rice crop. Sesbania speciosa planted during the month of August on the boundaries of a hectare field (1 150 m) produced, within four months, an average of about 42 t/ha of green matter for incorporation in the rice crop transplanted in January. The seedlings planted in February on the boundaries during the second season gave about 4.0 t/ha green matter for the main season rice crop transplanted in July (Vachhani and Murty, 1964). In Sri Lanka, Weerakoon and Gunasekera (1985) showed that about 2.5 tlha leaf dry matter of Leucaena leucocephala could be obtained every cropping season. S. sesban used as GLM gave total N yields of 32,46, and 47 kg Nlha in the first, second, and third year, respectively, of growth on sodic soils in northern India, (Rao et al., 1989). In Thailand, S. sesban produced leaf yields of 542-683 g/plant in wet season and 167-377 g/plant in dry season, and was more productive than S.formosa and S . grandijiora (Arunin et al., 1988). Mukherjee and Agarwal (1950) and Ghai et al. (1985) reported that N content of different green manures (8 weeks old) ranged from 1.5 to 4.85%. Roger and Watanabe (1986)reported that N content in legumes varies from 0.2 to 0.6% (fresh weight basis). Ghai et al. (1985) and Hernandez et al. (1957) observed that N content in Sesbania, sunn hemp, and T. candida tops was maximum at 45 days of growth and decreased thereafter. In milk vetch, N content before flowering was 4.5%, decreasing gradually to 3.2% at the full-broom stage (Ishikawa, 1988). Morris et al. (1986a) observed that different green manures showed a linear relationship between N accumulation and dry weight irrespective of green manure species, and were affected by the age of green manure crop. It was found that green manures had maximum N content of 2.54% at 45 days and decreased to 1.88% in 60-day-old green manures. N accumulation in the tops of several leguminous green manure crops is shown in Table I. The values in excess of 100 kg N/ha are common for 45-50-day-old legumes. Hernandez et al. (1957) found that N yield of 45-day-old green manures ranged from 56-226 kg N/ha. Milk vetch and S. cannabina in China fixed about 100-350 kg N/ha at full blooming. In the

GREEN MANURING IN WETLAND RICE

I45

United States, hairy vetch, crimson clover, subterrarean clover, and common vetch accumulated 56-209 kg N/ha, but in most cases it was between 100-150 kg N/ha (Smith et al., 1987). In Hawaii, Evans and Rotar (1987) reported that high yielding accessions of annual Sesbunia produced 817 t/ha dry matter containing 150-245 kg N/ha when sown at 125,000 plantslha and harvested at 98 days after sowing. The highest yielding varieties were related to S . cannuhinu, which are grown as green manures in the Asian lowland rice system. Like dry matter production, N accumulation is related to the age of the green manure crop. Ishikawa (1963) reported that N yield of milk vetch was 1.8 kgiha at the start of flowering, and increased to 156 kg Nlha during flowering (14 days later). N accumulation of S. aculeata as related to its age is shown in Fig. Ib. Palaniappan et ul. (1990) reported that at 45 days, S. aculeata and S. rostrata in south India accumulated 185 and 219 kg N/ha, respectively. Chapman and Myers (1987) reported that soybean green manure at early flowering stage ( I 10 days old) fixed 124-167 kg N/ha in different years. Evans et af. (1989) indicated that dry matter yield varied from 2.0- 14.3 t/ha and of narrow leaf lupin (Lupinus ~~iigustifalius) total N in the shoot ranged from 45-267 kg N/ha. Mahler and Auld (1989) studied the green manuring potential of Austrian winter peas (Pisurn satiuurn aruense spp.) and reported mean biomass and N yield of 8.3 tlha and 167 kg N/ha, respectively. The contribution of roots to total N yield is generally small in most leguminous green manures. In S. uculeafu,root dry matter averaged about 1.O t/ha, adding about only 10 kg N/ha at 50-60 days of growth (Morris et ul., 1986a; Beri et al., 1989a; Meelu et ul., 1990). The root-to-top ratio of milk vetch is about 0.05 and will supply only a negligible quantity for rice production (Ishikawa, 1988). Westcott and Mikkelson (1988) reported that sweet and crimson clovers have 24-26% of the entire crop biomass in the roots, which contain 2.0-2.3% N; the tops contain 2.4-2.9% N. Vetch has 17-19% of the total biomass in the roots. Using ''N isotope dilution technique, Chapman and Myers (1987) estimated that 60-72% of total plant N was from biological N2 fixation when the legumes were grown after 12 months of fallow, and 93-95% when grown immediately following dry season crop. Smith et al. (1987) concluded that N2 fixation values for legume cover crops ranged from 6 7 4 4 % . Using difference method, Meelu et al. (1990) observed that 80% of the total N in the tops of 52-day-old S . uculeata was from biological N2 fixation. Similar estimates of N2 fixation have been made for S . rostrata and S. cannabina by Pareek (1989) using different methods of evaluation. In the past, only limited research has been directed toward enhancing biological N2 fixation in the leguminous green manures. The important

146

YADVINDER SINGH ETAL.

approaches in this direction may involve: selection of superior plant and rhizobium genotypes, including the consideration of plant-microbe interaction; refinement of inoculation technology; increased understanding of rhizobium ecology; and improved management practices (Smith and Knight, 1984). Alikhan et a f . (1983) developed a SSI selection of sunn hemp which gave 37% increase in green matter yield and 70% increase in N yield at 50 days of growth. TO GREEN MANURE CROPS A. FERTILIZER APPLICATION

Application of inorganic fertilizers (N and P) and organic matter has been reported to stimulate nodulation and Nz fixation by legume crops (Gibson ef a f . , 1982). Phosphorus, which is required for efficient N2 fixation, is often a limiting nutrient in the tropical lowland soils. Results from several studies have shown that P application increased biomass and N accumulation of green manures (Table 11). The green manures generally responded more to P application on soils low in available P and pH. Venkatachalam et al. (1969) found that uptake of 32P by rice was greater from P applied to the green manure crop than its direct application made in four soil types. In China (Liu, 1988) and Japan (Ishikawa, 1988), application of P has been recommended for obtaining high biomass and N yield of milk vetch. Beri and Meelu (1980) found that on a soil testing low in available P, application of 13 kg P/ha increased biomass production and N accumulation of S. aculeata green manure and gave better yield of rice than P applied directly to rice. Many other research workers (Sanyasi Raju, 1952; Sen and Rao, 1953; Desai et al., 1957; Singh and Verma, 1969; Chen, 1988) have reported similar results. On soils testing high in available P, application of P fertilizer did not show any beneficial effect on biomass yield and N accumulation of green manures (Relwani and Ganguly, 1959; Desai et a f . , 1957). Gu and Wen (1981)reported that if available P content is below 15 mg/kg in the acid and neutral soils or below 10 mg/kg in the calcareous soils, P application to the green manures would be markedly efficient. The results of 311 experiments showed that application of 11-167 kg P/ha gave an average response . (1988) reported that of 347 kg fresh biomass and 1.21 kg N/kg P ~ O SChen while rice absorbed 66.2% of P applied to the green manure crop, it absorbed only 14.7%of the P added directly just before transplanting. The good effects of K fertilizer on the yield of green manure has been found in some soils, and K can give effects similar to P on such soils (Chen, 1986). In China, Liu (1988) recommended application of K2S04/KCI at 75-105 kg/ha to milk vetch.

Table I1 Effect of P Application on Accumulation of Biomass and N of Green Manures Green manure crop Sesbunia aculeata

S. aculeara Sunn hemp S. uculeara S. rostrata S . aculeara

N accumulation (kgiha)

Biomass (t/ha)

Age (days)

Available soil P (kgiha)

Fertilizer P rate (kgiha)

-P

+P

-P

60 60 56 56 61 64

4.5 Low Low 6-3 1 11.0

26.4 13.2 13.2 13.2 22.0 26.4

45.2 4.0 4.0 3.4 4.0 8.0

58.2 4.2 4.8 3.7

1.02 88 120 87 86 I17

5.1

9.6

1. Singh el nl. (1968); 2, Beri and Meelu (1981); 3. Sharma and Mittra (1988); 4, Herrera e r a l . (1989); 5, Singh (1990). g/6 plants.

+P 1.35

I05 I49 98 116 142

Reference" Ib

2 3

3 4

5

148

YADVINDER SINGH ETAL.

Rational application of N fertilizer can also increase the N2 fixation rate of a green manure crop. At low level of N, a starter dose of N was found to promote nodulation and N2 fixation by legume crops (Gibson et al., 1982). Gu and Wen (1981) reported that 1 kg of fertilizer N could increase 1.7 0.9 kg N in the green manures. Chapman and Myers (1987) found that application of a starter N dose (25 kg/ha as urea) increased 10 and 30% N in the tops of Sesbania and soybean at the flowering stage in the first year of study. Sharma and Mittra (1988) observed that application of 15 kg N/ha as urea increased N accumulation of sunn hemp and Sesbania by 23 and 30 kg/ha, respectively. Application of 25.5 kg N/haat the stem elongation stage gave a three- to 4-fold increase in fresh biomass of milk vetch over its application at the seedling stage. The plant recovery of fertilizer N applied at the seedling stage was 32%, and that applied at the stem elongation stage was about 78% (Gu and Wen, 1981). Soil organic matter can affect growth and survival of rhizobia in soil. Application of 7.5 t/ha of farmyard and poultry manure enhanced root nodulation of soybean and increased N2 fixation by 209% and 149%, respectively, over unamended treatments (Dev and Tilak, 1986). In Thailand, Herrera et al. (1989) observed that application of small rates of farmyard manure (3 t/ha) was slightly more advantageous when applied to S. rostrata rather than to rice.

*

B. INOCULATION Inoculation enhances the onset and number of effective nodules and N2 fixation by legumes. Ishikawa (1988) observed that inoculation of milk vetch seed with rhizobia before sowing increased green matter production by more than 3 times than without inoculation during the first year. In subsequent years the increase was about 48%. Chu (1954) reported that inoculation of soybean seed used for green manuring can help increase rice yields by 20.7% over no inoculation. Ladha et al. (1989) reported that both stem and soil + seed + stem inoculation methods produced significantly more nodules (stem and roots) and biomass of stem-nodulating legumes ( S . rostrata) than did the control. The plants that were not inoculated on the stem did not develop stem nodules. Alazard and Duhoux (1987) reported that plant dry weight of 9-week-old A . afraspera was 8.0 g/plant when only roots were inoculated but it increased to 46 g/plant when both stem and roots were inoculated. The corresponding values for N accumulation were 158 and 366 mg/plant. Arunin et al. (1988) reported that inoculation of S . rostrata with improved strains of ORS 571 markedly increased (34-50%) its dry matter

GREEN MANURING IN WETLAND RICE

149

(plant weight + pod weight) under both flooded and upland conditions. The improved strain was more effective than native strain. In S. cannabina, S. speciosa, and S . uculeatu inoculation helped to improve their growth (29-242%) under flooded conditions only. In Sri Lanka, Kulasooriya and Samarakoon (1990) reported that decapitation and stem inoculation of S . rostratu increased dry weight/plant by more than two times and N yield by about three times over the control.

C. EFFECTOF IRRIGATION Singh and Lamba (197 1) recommended that cowpea should be irrigated when the available water in the 180-cm profile is depleted by 35%. Gaul et al. (1976) reported that during summer in northern India, about 600650 mm of irrigation water would be required for raising a 74-day-old green manure crop of S . aculeata on alkali soil. N . T. Singh et al. (1981) found that irrigation frequency (irrigation water/pan evaporation = 0.5- 1 .O) exerted a significant influence on the dry matter and N yields of 7-week-old green manure crops of S. aculeata, cowpea, and clusterbean in semiarid regions of Punjab, India. In China, Gu and Wen (1981) reported that for optimum yield of milk vetch, surface soil moisture (0-10 cm) should be maintained at about 70% of water-holding capacity until winter in order to speed up the root growth.

IV. TIME AND DEPTH OF INCORPORATION OF GREEN MANURES Traditionally, green manures were grown in fallow fields on rainwater and incorporated 2 to 4 weeks before sowing of the following crop. This practice is, however, not feasible in the context of intensive agriculture when there is a fallow period of only 40-60 days before transplanting of rice. While studying the possibility of green manuring in the present-day rice-based cropping systems, Bhardwaj (1982), Ghai et al. (1988), and Beri et al. (1989b) showed, on the basis of yield responses, that a 2-week delay between incorporation of green manure and transplanting of rice was not only unnecessary but also disadvantageous (Table 111). In fact, Williams and Finfrock (1962) and Vachhani and Murty (1964) had already demonstrated that green manure could be incorporated even at the time of transplanting rice seedlings. The reason for low efficiency of green manure when incorporated for a longer period before transplanting rice or flooding

150

YADVINDER SINGH E T A L . Table 111 Effect of Interval between Incorporation of Green Manure and Rice Transplanting on Rice Yield (t/ha)

Decomposition period (days)

Bhardwaj (1982) ~

Beri et al. (1989b)

5.9 6.1 6.1 5.4 -

6.2 5.3 4.8 -

~~

0- 1 5-7

5.9

10

5.7 4.4

14-15 20

Ghai et al. (1988)

-

could be the loss of green manure N released during aerobic decomposition through ammonia volatilization, nitrification-denitrification, and leaching after flooding of rice fields (Ishikawa, 1988; Chapman and Myers, 1987; Williams and Finfrock, 1962). Ishikawa (1963) observed that with simultaneous flooding and milk vetch incorporation, loss of N through apparent denitrification was small. When flooding began 10 days after application, milk vetch decomposed rapidly under 10-day aerobic conditions and NH4+-N was converted to N03--N, which was lost upon flooding, possibly through denitrification. A few investigations have shown that it is not always necessary to incorporate green manure a day or two before transplanting rice (Iso, 1954; Staker, 1958; Roy et al., 1988; Tiwari et al., 1980; Rana et al., 1988). Swamp (1987) showed in field experiments that allowing decomposition of Sesbania green manure for 1 week under flooded conditions in sodic soils significantly improved rice yields over simultaneous incorporation and transplanting of rice, possibly through improvement of physicochemical properties of sodic soils. Wen (1984)and Herrera et al. (1989) reported that it is better to turn under green manure crop about 15 days before transplanting rice seedlings so that plants do not suffer damage from the decomposition products of the green manure. To avoid losses of green manure N it was recommended to keep the fields flooded during the decomposition period before transplanting rice. Ishikawa (1988) concluded that only in poorly drained fields with low rates of nitrification was rice yield not influenced by flooding time in relation to application of milk vetch green manure. Soil moisture conditions during the preflooding period significantly influenced the effectiveness of green manure (Williams and Finfrock, 1962). Under conditions favorable to nitrification during the preflooding period, the shorter the period, the greater the effectiveness.

GREEN MANURING IN WETLAND RICE

151

The results of an experiment conducted by the Central Rice Research Institute at Cuttack, India showed that incorporating 8-week-old Sesbania crop immediately before transplanting gave a similar rice yield compared to the Sesbania crop ploughed down 4-8 weeks before transplanting. However, with the 12-week-oldSesbania, it was better to turn it under 4-8 weeks before transplanting (Vachhani and Murty, 1964). The occurrence of oxidized and reduced zones in a flooded soil provides an ideal environment for simultaneous nitrification and denitrification (Patrick and Reddy, 1976). The depth of incorporation of green manure determines the susceptibility to loss of the N contained in it, and thus determines its use efficiency by rice. From a 3-year study, Williams and Finfrock (1962) showed that effectiveness of vetch green manure increased with greater depth (10-15 cm) of its placement. In Punjab, India, the best depth, as measured by the yields of the following rice crop, for placing Sesbania into the soil turned out to be 25 cm (Staker, 1958). In Indonesia, Van de Goor (1954) reported increases in rice yield when green manure was incorporated into the soil rather than applied on its surface. Although in actual practice it is difficult to accomplish a favorable depth of placement of green manures, it should be well turned into the soil for more effectiveness.

V. YIELD RESPONSES OF WETLAND RICE TO GREEN MANURING A great deal of literature exists on direct effects of green manuring on the grain yield of wetland rice. The major effect of green manure is undoubtedly due to its N contribution but the favorable effects of organic matter addition and availability of other nutrients cannot be overlooked. In India, Panse er al. (1965) analyzed results of 583 experiments conducted throughout the country on green manuring in rice farming using less N-responsive and low-yielding rice cultivars. The average response of rice to green manuring was 0.24 t/ha, with a range of 0.1-0.3 t/ha. The responses were more in the irrigated than in the nonirrigated rice and were related to the age of green manure crop, which determined the amount of biomass and N added. Sethi et al. (1952) reviewed the early work and concluded that green manuring with S.aculeata and sunn hemp increased rice yield by 21 to 114%. Coarse textured soils low in organic matter and nitrogen showed greater response to green manuring than the high-fertility soils. Many researchers (Rao and Ghosh, 1952; Staker, 1958; Relwani and Ganguly, 1959; Vachhani and Murty, 1964; Chela and Gill, 1973) have

152

YADVINDER SING11 E T A L .

observed yield responses of wetland rice to green manuring similar to those reported by Sethi et al. (1952) and Panse et a / . (1965). Yield response of high-yielding rice cultivars to green manuring in India are shown in Table IV. Yield responses ranged from 0.65 to 3. I t/ha and were generally higher than those reported for low-yielding rice cultivars. Nevertheless, the responses were higher under coarse-textured soils testing low in organic matter, just as for low-yielding cultivars. Work done on green manuring in wetland rice in China has been reviewed by Gu and Wen (1981), Chen (1988), and Liu (1988). In low-fertility soils, rice yields with green manuring increased by 78% compared with 21.6% in the high-fertility soils (Gu and Wen, 1981). Bin (1983) reported that in 588 experiments conducted in south China, addition of I t/ha of fresh green matter increased rice yield by 38 to 80 kg/ha. Depending on the amount of biomass incorporated, A . indica green manure increased rice yield by 5 to 38% over the control (Jiao et al., 1986). Chen (1988) reported that green manuring with milk vetch or vetch increased rice grain yield, on the average, by 1.02 t/ha (13.5%). Recent studies in the Philippines showed that incorporation of 40-60day-old green manures increased rice grain yield by 30 to 128% (Table IV). In earlier studies (Borja, 1952; Hernandez et al., 1957), green manuring resulted in an 80-100% increase in rice grain yield. In a large number of field experiments in Japan, Yamazaki (1959) found that incorporation of 22.5 t/ha of milk vetch increased rice yield by 1.9 tlha (82.6% over the control). In long-term studies carried out in Japan, green manuring with milk vetch increased grain yield of rice by 45 to 85% (Table IV). In Thailand, green manuring increased rice yield by 0.4-2.1 tlha (2049%) over the control (Table IV). In earlier studies, it was reported that green manuring increased rice grain yield by 22 to 49% over the control (Technical Division, Rice Department, Ministry of Agriculture, 1961).

In Java, green manuring with 53-day-old sunn hemp (20.6 t/ha of green matter) increased rice yield, on the average, by 1.18 t/ha over the control (Staker, 1958). In another long-term study, incorporation of 72-day-old sunn hemp green manure (15.2 t/ha green matter) increased rice grain yield by 0.74 t/ha (19.4%) over the control. In Cameroon, a 20-45% increase in rice yield has been obtained due to green manuring with Sesbania and Crotolaria (Table IV). In Sri Lanka, recent studies have shown a greater than 100% increase in rice yield due to green manuring as compared to only a 20% increase reported in an early study (Table IV). In the United States, green manuring with purple vetch, adding 30-45 kg Nlha, increased rice yield over the control by 1.O to 2.5 tlha depending on the depth of incorporation (Williams et al., 1957; Williams and Finfrock,

GREEN MANURING IN WETLAND RICE

153

Table IV Rice Grain Yield Responses to Green Manuring Yield (tiha) Green manure crop

Age" (days)

Increase -GM

+GM

(96)

13 years (mean) 54 years (mean) -

2.9

4.2

44.8

2.0

3.4

85.0

1.3

1.9

46.2

S . speciosa

-

4. I I .7 3.0 4.7 1.1 1.3

5.5 2.1 3.6 6.8 1.6 2.3

34.2 19.8 21.7 43.2 45.2 84.0

S . speciosa

-

2.0

2.5

25.0

S . rostrata

ISh

1.6

2.2

37.5

S . aculeata

60

3.2

4.0

25.0

Sunn hemp S. aculeata

60 50 60

3.2 1.6 2.7

3.9 2.7 5.5

21.9 68.8 105

60 56

2.7 2.6

5.8 3.7

1 I5

50 56 70

3.3 4.5 2.4

6.1 6. I 3.2

84 20b

2.0

2.6

4.0 5.9

40-45

2. I

4. I

95.2

S . rostrata

48

I .8

3.5

94.4

S . cannabina S . aculeataisunn hemp

60 60

1.8 3.3

4.1 4.5

128 36.4

Milk vetch Milk vetch Soybean Sesbania sp. Sesbania sp. Crotolaria caricia

S . aculeatalsunn

hemp/cowpea S. aculeata S . aculeatalsunn hemp S . aculeata

S.aculeata S . rostruta

s. sesban S. rostrata

Cowpealmung bean

42.3 85.0 35.6 33.3

loo 127

Reference lshikawa (1988)

Chapman and Myers (1987) Roy er a/. (I 988)

Sawasdee et a/. ( 1976) Arunin et a/. ( 1988) Herrera ef al. (1989) Bhardwaj ei a / . (1981) Tiwari et al. (1980) Beri ei al. (1989a) Beri et a / . (1989b) Sharma and Mittra (1988) Ghai ei al. (1988) Anti1 et a / . (1988) Rabindra et al. (1989) Palm e t a / . (1988) Kalidurai and Kannai yan ( 1990) Morris el al. (1986a) Morris et al. (1989)

O.P. Meelu (unpublished data) (continued)

154

YADVINDER SlNGH ETAL.

Table IV (continued) Yield (tiha) Green manure crop

Age" (days)

-GM

+GM

(%I

S . rostrata

60 52

3.3 2. I

4.3 6.0

30.3 186

S. rostrata

-

2.3

4.5

95.7

Aeschynomenr

49

4.8

8.9

85.4

F

3.3

4.4

33.3

Soybean/mung bean

afrasperalA. nilotica Cowpea a

Increase Reference

Rinaudo et al. (1983) Camara and Diara ( 1986) Alazard and Becker (1987) John et al. ( 1 9 8 9 ~ )

F, flowering.

' Biomass (t/ha). kg Nlha.

1962). In another study, Williams et al. (1972) obtained a yield increase of 1.9 tiha (63%) over the control. Westcott and Mikkelsen (1987) found that application of 120 kg N/ha through vetch green manure increased rice yield by 2.4 t/ha (43.3%) over the control. Recently, Dabney et al. (1989) reported that green manuring with subterranean clover increased grain yield of wetland rice by about 10% in both till and no-till systems. In microplot studies, yield increases due to green manuring with stemnodulating legumes ranged from 84 to 181% in Senegal (Table IV) and these results were conspicuously higher than those reported in other countries. Significant direct grain yield responses of wetland rice to leguminous green manures have been observed in Russia, 24% (Churikov, 1938); Taiwan, 10% (Staker, 1958); Surinam, 1 t over the control (Ten Have, 1959);Nepal, 40.4% (Karki and Basal, 1978);and Australia, 46.2% (Chapman and Myers, 1987). The response to GLM in wetland rice depends on the amounts of green matter added, their succulence, and nutrient content. Krishna Rao et al. (1961) reported that green manuring with cuttings of different quickgrowing shrubs increased yield of rice by 21 to 114% (mean 51%). Singh (1971) evaluated different wild legumes as GLM (35 t/ha) in wetland rice and recorded yield increases from 17 to 59% over no GLM treatment. Tephrosia spp. and Aeschynomene americana were the most efficient GLMs, probably due to their greater succulence, N content, and decomposibility. Chatterjee et al. (1979) reported that incorporation of GLM of

GREEN MANURING IN WETLAND RICE

155

Ipornoea carnea and S . bispinosa (10 t/ha, dry weight basis) gave as much yield of rice as the incorporation of 40 kg Nlha (as urea applied at transplanting). Jha et al. (1980) reported that rice grain yield with I . carnea GLM was comparable or even superior to that obtained with similar N levels applied through ammonium sulphate. Green leaf manuring with G. maculata, 1. carnea, and G. sepium resulted in an 18-69% increase in rice yield (Reddi er al., 1972; Jha et a l . , 1980; Dhane et al., 1989). Nagarajah and Amarasiri (1977) observed that application of GLM of G. rnaculata and Tithonia diversifolia (9 t/ha) increased rice yield by 0.30.8 t/ha. Weerakoon and Gunasekera (1985) and Jeyaraman and Purushothaman (1988) reported that application of 10 t/ha cuttings of L . leucocephala increased rice yield by 0.8 t/ha and gave a N fertilizer equivalence of 43-50 kg N/ha. Maskey and Bhattarai (1984) used GLMs of four different crops, adding 100 kg Nlha, which increased rice yield by 13% (with Eupatoriurn gladiosa) to 54% (with Adharoda vasica). Laolao et al. (1978) reported that ipil-ipil leaves as GLM (120 kg N/ha) were as effective as ammonium sulphate in rice. Morris et al. (1986a, 1989) have shown that at moderate green N levels the agronomic efficiency in wetland rice in the tropics was similar to that obtained for the fertilizer N . They noted that mean response of rice to green manuring was 16 to 24 kg grain/kg N . However, low agronomic efficiency has been reported from the experiments in which green manure N exceeding 100 kg/ha was applied (Crozat and Sangchyosawat, 1985). Recently, Shukla et al. (1989) reported that application of 60 kg Sesbania green manure N/ha gave agronomic efficiency of 25 kg grain/kg N compared to 18 kg for urea N applied at 90 kg/ha. Agronomic efficiencies in several other experiments ranged from 7-30 kg grain/kg N (Sanyasi Raju, 1952; Rao and Ghosh, 1952; Chatterjee et al., 1979; Tiwari et al., 1980; Beri et al., 1989a,b). Smith ei a!. (1987) presented three possibilities for understanding the yield responses of wetland rice to green manuring. In the first case (Fig. 2a) there is yield benefit from the green manure at low N rates suggesting that the only significant effect of the green manure is to increase N supply to the rice crop. There are very few examples available in the literature to show such an effect in rice. Since complete N response curves are not available in most cases, judgments cannot be made about whether or not large amounts of fertilizer N would ultimately give yields that would match those obtained with green manuring. In Fig. 2b, the green manure has an effect on yield potential that no amount of fertilizer N can achieve. In this case there is an indication that green manure provides benefits beyond N supply. Existence of this pattern can be found in the works of Dargan e t a / . (1975), Chatterjee et al. (1979), Tiwari et al. (1980), Rekhi and Meelu

156

YADVINDER SINGH E T A L .

I

N FERTILIZER

C

RATE

FIG.2. Hypothetical yield curves as a function of N fertilizer rate for rice following green manuring (+GM) or without green manuring (-GM). (Adapted from Smith ef al., 1987.)

(1983), Roy et al. (1988), Beri et al. (1989b), John et al. (1989c), and many others. Bhatti et ul. (1985) found that maximum rice yield with fertilizer N alone was 3 t/ha, but fertilizer along with green manure increased yield potential to 4 t/ha. Reddi et ul. (1972) observed that in the presence of 7.5 t/ha green manure, an additional rice yield of 0.68 t/ha (12.4%) was obtained at recommended fertilizer N application. The yield potential further increased to 1.08 t/ha when 15.0 t/ha of green manure was applied. Possible explanations for this response pattern may include more favorable physical, chemical, and biological conditions of the soil amended with green manure. A third hypothetical case (Fig. 2c) exists when sufficient N fertilizers are applied and rice yields following green manuring are lower than those with no green manuring. Such types of examples are very few in the literature. The yield reduction could be due to excessive N causing lodging in rice, root toxicity due to accumulation of toxic chemicals released from green manure (Ishikawa, 1988),or Fe and Mn toxicity due to increased reduction in the presence of green manure (Katyal, 1977).

A. DUAL-PURPOSE LEGUMINOUS GREENMANURES Short duration pulses such as mung bean and cowpea can be grown in the fallow period before the transplanting of rice. They provide much needed protein for human consumption and their residues can still be turned under to serve as a green manure. From a three-year study, Rekhi and Meelu (1983) reported that in addition to about 0.9 t graindha, mung bean residue supplied about 100 kg N/ha, and when incorporated into the soil along with 60 kg N/ha through urea, gave as much rice yield as

GREEN MANURING IN WETLAND RICE

157

obtained with the application of 120 kg N/ha through urea alone. Xiao (1980) reported that incorporating a winter crop of beans (Phaseoli4s uulgaris L.) after pod harvest gave a 19% increase in the yield of a subsequent rice crop. At IRRI (John et al., 1989c), yield increases in transplanted rice in the plots with cowpea residue incorporated were equivalent to 44-50 kg Nlha in the fallow plots. Cowpea gave average seed yield of about 1 .O t/ha and residues contained about 54 kg N/ha. Using cowpea residues, John et al. (1989~)observed no significant reduction in N contribution to rice when compared with cowpea green manure treatment. However, growth of cowpea for grain production rather than for green manuring would necessiate the diversion of land to cowpea for approximately 30 additional days. In tropical regions where two rice crops are grown in a rotation, incorporating crop residues of short-duration grain legumes (mung bean, black gram, cowpea) substituted for SO% N in wet season rice (Kulkarni and Pandey, 1988).Grain legumes of cowpea and mung bean are unsuitable for poorly drained soils where short-term flooding occurs during the cropping season.

B. OPTIMUM APPLICATION RATEOF GREENMANURES Liu (1988) reported that milk vetch green manure produces on the average 22-40 t/ha fresh matter and in some cases can produce up to 75 t/ha. The amount recommended for green manuring is only about 22 t/ha; the fresh biomass from a I-ha high-yielding field may be utilized for a 2- to 3-ha rice field. Similar observations have been made by Ishikawa (1988). High amounts of green manure can be unfavorable, even harmful, to plant growth because the nutrients are released faster and are more concentrated. The result is ineffective tillering and lodging. The results of a field experiment applying different amounts of milk vetch to rice showed that maximum rice yield was obtained with 33.8 t/ha fresh matter (= 135 kg N/ha) (Ishikawa, 1988). Even at this level, rice plant showed symptoms of excess N and grain quality was low. Through anaerobic decomposition of excessive organic matter added through green manure, the soil redox potential drops, harmful substances such as organic acids are formed, and rice plant roots suffer injury. Yamazaki (1959) reported that when excess milk vetch was applied to drained and undrained plots, the rice yield from the drained plots was greater than that from undrained plots. In India, B. Singh et al. (1988) observed a progressive increase in rice yield with increasing rates of S . aculeata up to 35 tlha fresh matter on coarse-textured soils. Bhardwaj and Dev (1985) and

158

YADVINDER SINGH E T A L .

Bhardwaj (1982) observed no significant increase in rice yield beyond 5.5 t/ha dry matter after adding about 100 kg N/ha. From the data reported by Reddi et al. (1972), it was found that 28.5 t/ha of Gliricidia green leaf manure was required to obtain maximum yield of rice.

VI. NITROGEN FROM GREEN MANURE CROPS A. N FERTILIZER EQUIVALENCE

The N contribution from green manures is their most commonly observed benefit in wetland rice. Direct measurements of N actually transferred from the green manure crop to the rice crop are not easily made, and limited data are available. Many studies provide an indirect measurement of the N contribution by comparing rice yield response to N fertilizer with and without green manures. The nitrogen fertilizer equivalence (NFE) of a green manure is often calculated as the quantity of fertilizer N that must be applied to wetland rice in the fallow treatment to attain grain yield equal to that obtained with green manure and no N fertilizer. This approach implies that all of the yield response is due to the N contribution, while green manures also have physical and biological effects on the soil. The values of NFE of different green manure crops in wetland rice are given in Table V. These range from approximately 34 to 148 kg N/ha, but more typically are between 50 and 100 kg Niha for 45-to 60-day-old green manure crops. Roger and Watanabe (1986) reported that incorporating one legume crop is equivalent to applying 30-80 kg fertilizer N/ha in rice. The differences in N accumulation by green manure crops (due to age and/or species used), and in the recovery and utilization of the incorporated N due to differences in crop management, cultivars, soils, and weather may explain the wide range in values of NFE of green manure crops. To increase precision of the estimate, some research workers (Ghai et al., 1988; Singh et al., 1990) have used regression equations of the response to varying fertilizer N levels for computing NFE of green manures. Many workers have reported an equal or even greater efficiency of green manure N compared to fertilizer N when applied on an equal N basis (Table V). Yamazaki (1959) showed that in the well-drained wetland rice fields yields from the plots manured with milk vetch were almost the same as from the plots fertilized with ammonium sulphate. However, in medium or poorly drained soils, the yields from the green manured plots were less than the yields from ammonium sulphate-fertilized plots. Stickler et al. (1959) reported that the relative efficiency of green manure N (calculated as NFE divided by the amount of legume N added) generally

159

GREEN MANURING IN WETLAND RICE

Table V Nitrogen Fertilizer Equivalence (NFE) of Green Manures ~~

Green manure crop Purple vetch Crotolaria quinyuifolia Sesbania aculeata S. aculeata S. aculeata S. aculeaia Sunn hemp S.rostrata S.cannabina S. rostrata Milk vetch Mung beanlcowpea Aeschynomene afrasperal A. nilotica S. rostrata S. aculeata S.aculeatalsunn hemp Milk vetch

S. sesbarz S. aculeata Sunn hemp S. aculeatalsunn hemp1 cowpea S. cannabinalcowpeal sunn hemp S. cannabina S. rostratalsunn hemp S. acirleuta S . aculeata

Age" (days)

NFE (kglha)

Reference

Sep- Apr I05 67 50 50 50 52 45-65 55

27-49 23 57 78 98- 147 131

34 100 34 80 80 50 75 130 100-120 80

40-45 49

90 74-86 -

90 80 >loo

Rinaudo et ul. (1983) Bhardwaj and Dev (1985) Crozat and Sangchyosawat ( 1985) Jiao et al. (1986) Morris et a/. (l986a) Alazard and Becker (1987)

50 45 F 23.4 tlha (GM) 84 56 56 60

I09

70 123 40-60 94

Ventura et al. (1987) Ghai et a/. (1988) Roy et al. (1988) Ishikawa (1988)

-

-

Williams et al. (1957) Ten Have (1959) Vachhani and Murty (1964) Dargan et al. (1975) Tiwari et al. (1980) Bhardwaj et al. (1981)

83 108-1 13

96 45 60 120

Palm et ul. (1988) Sharma and Mittra (1988)

60

-

50- 105

O.P. Meelu (unpublished

48

70 45-75 97- I 50 41-70 121 55-80

80 70 90 72 136 72 148 98

-

60 -

S.aculeata

-

Sunn hemp Sunn hemp Cowpea

-

"

Green manure N (kglha)

-

Beri et a/. (1989a,b)

data) Morris et al. (1989) Rabindra et al. (1989) Shukla et al. (1989) Y . Singh er a / . (1990)

F, flowering; GM, green matter.

falls between 25 and 50% in maize as compared to about 100% in rice (Table V). Krishna Rao et al. (1961) and Jiao et al. (1986) have reported that green manure N was as effective as fertilizer N when added on equal N basis. Anti1 er 01. (1988) computed optimum N rates for wetland rice as 152, 74, and 66 kg Niha after fallow, S . aculeata, and sunn hemp, re-

160

YADVINDER SINGH E T A L .

spectively. Like fertilizer N , application of green manure N in excess of that needed for the highest rice yields could result in its poor efficiency (Bhardwaj, 1982; Bhardwaj and Dev, 1985; Morris er al., 1989). B. N TRANSFER FROM GREEN MANURE TO RICE Similar to fertilizer N , the recovery of green manure N will vary considerably with soil type, management, and weather. Working on a clay soil and using I5N labeled vetch green manure, Westcott and Mikkelsen (1987) recorded 10% N recovery of added vetch N (60-120 kg N/ha). Recovery was 16-25% with ammonium sulphate added on an equivalent N basis. Apparent N recovery was also lower with vetch N (9-26%) than with ammonium sulphate (19-53%). They observed that when conditions inhibited the early season mineralization of green manure N , recovery rates of green manure N would not compare favorably with that of fertilizer N. Contrarily, Williams and Finfrock (1962) working on different soils and rice cultivars found apparent vetch N recovery rates as high as 103%. Chapman and Myers ( 1987) indicated that inefficient management of green manure resulted in its low efficiency in flooded rice. Apparent green manure N recoveries have been reported to vary from 25 to 58% (Table VI). Generally, recoveries of N from green manure were similar to those from fertilizer.

USEOF GREENMANURE A N D FERTILIZER N C. INTEGRATED The amount of N accumulated by different green manures is not likely to be able to provide the levels of N currently required by the high yielding rice cultivars (Talley and Rains, 1982). Therefore, to achieve the yield potential it often needs to be supplemented with inorganic fertilizers. Supplementing basally applied green manure with top dressed fertilizer N helps in maximizing both green manure and fertilizer N recovery (Morris et al., 1986a,b). In situations where green manure N is sufficiently high, it may be advisable to cover more area to green manuring so as to get increased rice yields. This practice will also help avoid crop injury caused by excess application of green manure. Several workers (Beri and Meelu, 1981; Nagarajah and Nizar, 1982; Rekhi and Meelu, 1983; Khind et al., 1985; Joseph, 1986; Rana et al., 1988; Mahapatra and Sharma, 1989; Kalidurai and Kannaiyan, 1990) have reported that green manure plus 50% of the recommended fertilizer N resulted in higher rice yields than when recommended N rates were applied.

161

GREEN MANURING IN WETLAND RICE Table V1 Recovery of Green Manure N by Rice under Different Soil and Climatic Conditions N recovery (95)

Green manure crop

GM

Fertilizer

Reference

Appurent N recovery

Mung beanicowpea Arschynomenr ufrusprral A . nilotrca

S.aculeatu S. aculeata Cowpea S. rostruto Sunn hemp S . rostrata s. aculrata

33-49 25-35

33-49 25

Morris el a / . (1986b) Alazard and Becker (1987)

44 42 2 1-29 41 34 34-51" 58

38 50 25-43 34 34 61

Ghai et al. (1988) Y.Singh et al. (1988) John et a/. ( 1 9 8 9 ~ ) Rabindra et a / . (1989) Ladha rt al. (1989) Shukla rt a / . (1989)

" N rrcouerv

Milk vetch Seshania sp.

Sunn hemp Milk vetch Milk vetch S . uculeata "

"

25" 30-34 34-4s 38 30 32

5 1-64 57-60 25 51

Gu and Wen (1981) H u a n g e t a l . (1981) Liu (1981) Mo and Qian (1983) Biswas (1988)

Pot study. Mean of 10 experiments.

Tiwari et ul. (1980) reported that green manure plus 40 kg fertilizer N/ha produced rice yield comparable with 120 fertilizer N/ha alone. Ishikawa (1988) reported that combining green manure and fertilizer N (56 : 38) resulted in greater rice yields than from fertilizer N alone. Rabindra ef u l . (1989) showed that application of a part of N (30%) through green manure produced significantly more rice yield and N uptake than from 100 kg urea N/ha alone. In most of the studies, rice yield potential was high when green manure and an optimum quantity of fertilizer N were applied toget her. Since a major fraction of green manure N is released and becomes available to the rice plant within 2 to 3 weeks of its incorporation, the N requirement of rice in the early growth period could be met by green manure. Thus, Desai et al. (1957) observed that in rice green manured with sunn hemp, top dressing of fertilizer N after first weeding (25-30 DT) produced significantly higher yield (10%) than its application at transplant-

162

YADVINDER SINGH ET AL.

ing. Meelu and Morris (1988) showed that N applied with green manure in a single dose at panicle initiation growth stage increased rice yield more than the split-applied N . Results of field experiments conducted on a coarsetextured soil showed that Sesbania N was sufficient for the wetland rice at the early growth stages, and application of fertilizer N at transplanting could be delayed without any adverse effects on rice yield (Khind et af., 1987b; Singh et al., 1987). Biswas (1988) reported that application of 30 kg Nlha as urea 5-7 days before panicle initiation with basal incorporation of Sesbania green manure improved grain yield, N uptake, and agronomic efficiency. There is an obvious need to work out precise rate and time of fertilizer N application to rice grown on fields amended with green manure under different soil and climatic conditions.

VII. TRANSFORMATIONS OF GREEN MANURE NITROGEN IN WETLAND RICE SOILS The fate and availability of N in green manures are determined by the rate and extent of manure decomposition and associated N mineralization. The composition of green manure affects the overall mineralization rate. The stem and roots of green manure are generally poorer in N content and have wider CIN ratios than that of foliage portion (Palm et a f . , 1988). These parts decompose slowly and could result in immobilization of N. The net N release from green manure is the balance of all the N transformation processes occurring in the different parts of green manure. The efficiency of green manure N should depend on the extent of N losses, and the rate of N supply to the growing crops through mineralizationimmobilization turnover rate. A. N MINERALIZATION FROM GREENMANURES Release of mineral N from green manure is initially rapid, but slows markedly within a fairly short time (P. K. Singh et al., 1981; Khind et af., 1985; Y . Singh et al., 1988; Bhardwaj and Dev, 1985). This behavior is typical of most organic amendments (Van Faassen and Smilde, 1985). In the absence of rice plants, N release increased rapidly up to 2 weeks and reached a plateau (Aspiras, 1966; Nagarajah, 1988; Nagarajah et af., 1989) (Fig. 3). In the presence of rice plants, soil solution NHd+-N peaked at 2-4 weeks after green manure addition and then declined to low levels at 6-12 weeks (Fig. 3). The decline was attributed largely to plant uptake. The time

GREEN MANURING IN WETLAND RICE

I63

DAYS AFTER TRANSPLANTING

FIG.3. Effect of Sesbania green manure on exchangeable NH4+ N in a field (a) without rice crop and (b) with rice crop. (Adapted from Nagarajah, 1988.)

of occurrence of peak of mineral N released from green manure varied greatly in different studies. It should not be surprising keeping in view the effect of plant composition and environmental factors on rate of N release. In some studies conducted in the absence of rice plant, a decline in NH4+-Nafter a peak has been observed (P. K. Singh et al., 1981; Bhardwaj and Dev, 1985; Khind et al., 1987b; Beri et al., 1989b). It could be due to losses of N via nitrification-denitrification and volatilization as NH3. The simplest model representative of the N mineralization kinetics of organic substrates added to soil is the mathematical formulation for the first-order kinetics. Frankenberger and Abdelmagid (1985) found first order N mineralization rate constants for the legume residues incubated at field capacity moisture regime to range from 0.045 to 0.325Iweek. Bouldin (1988) proposed a simple two-component model to describe the N mineralization pattern of green manures. The organic material is treated as if there are two distinct components-one decomposes rapidly, the other slowly. It was proposed that 65% of the added N mineralizes during the first crop, 14% mineralizes during the second crop, and 3.3% mineralizes during each succeeding crop. Recent work of Y. Singh rt al. (1988) indicated that N mineralization kinetics of green manure could be described by two simultaneous first-order reactions: an initial fast reaction ( k = 2.12/week) followed by a slow release of inorganic N ( k = 0.069Iweek). Gale and Gilmour (1988) studied C and N mineralization from alfalfa as a threephase process. Under anaerobic conditions, the rate constant for slow phase was near zero, and for rapid and intermediate phases these were 0.118 and 0.024/day, respectively. Gilmour et al. (1985)confirmed that the amount of net N mineralized was related to net C mineralization. There have been few studies on decomposition and N mineralization of green manures under waterlogged conditions. And in some of the studies inconclusive results have been obtained due to simultaneous loss of miner-

164

YADVINDER SINGH E T A L .

alized N via ammonia volatilization and/or denitrification (Weeraratna, 1979; Y. Singh et al., 1988). Nevertheless, along with an extensive literature on plant litter decomposition in general, a number of references on N mineralization of green manures under aerobic soil conditions are available. Thus, only a qualitative understanding of the factors regulating N mineralization kinetics is possible. While listing different regulating factors an attempt has been made to discuss some of these specifically related to N mineralization of green manures in wetland rice soils. Green manure characteristics determining decomposition and mineralization kinetics include N content, C/N ratio, and lignin and lipid contents, which are primarily determined by green manure species and age and plant part of legume crops. In a study on four Philippines rice soils, it was found that at the same N equivalent, NH4+-Nrelease from Azolla rnicrophyllu was slower and lower than that from Sesbania rostrata, despite its lower C/N ratio (Nagarajah et al., 1989). The difference was attributed to the much higher lignin content of A . microphylla (20 vs. 9%). Shi et al. (1981) reported that recovery of N by the first rice crop was 25.4 and 37.6%from Azolla and milk vetch, respectively. Both these materials had an almost similar C/N ratio ( 1 1.2 and 1 1 3)but Azolla had a greater amount of lignin (20.2%) than milk vetch (13.5%). Kundu et al. (1990) found that rate and magnitude of N release for Gliricidia were higher than that from Sesbania when incorporated into submerged rice fields at transplanting. Gliricidia green manure consisted of green twigs and leaves, which had a higher rate of N mineralization than that of Sesbania green manure, which consisted of whole plants. However, Beri ef al. (1989a) could not observe significant differences in the N mineralization pattern of different green manures. As the plant matures, the amount of N, proteins, and water-soluble constituents decrease, and lignin and C/N ratios increase. John er al. (1989~)reported that initially, N mineralization from cowpea green manure (C/N ratio = 15 : 1) was faster than from cowpea residue (C/N ratio = 21 : l ) , but at 30 days after transplanting, mineral N was higher in residue-incorporated plots. In a pot culture study using alluvial sandy loam soil (pH 7.4), Bhardwaj and Dev (1985) found that release of mineral N after 49 days of incubation under flooded conditions was 112, 80, and 76 kg/ha for 45-, 55-, and 65-day-old, respectively, green manure crops of S . cannabina. Palm et al. (1988) found that the leaves of Sesbania green manure, which contained 88% of the total N in the aboveground parts (83 kg/ha), released about 73% of the N during the first 4 days, and 88% after 14 days of incubation under submerged soil condition. Release of N from stems and roots with CIN ratios of 107 and 55, respectively, was marginal compared to that from leaves. Important edaphic and management factors influencing N mineraliza-

GREEN MANURING IN WETLAND RICE

165

tion of green manure include soil type (pH, texture, clay mineral, etc.), temperature, water management, cropping history, method of incorporation, and drying of green manure before incorporation. The addition of the same rate of green manure N to different soils did not release equal amounts of NH4+-N,indicating that N release from green manure depended on soil type (Nagarajah, 1988). Zhu et ul. (1984) observed that N release from vetch green manure and rice straw combined was 26 and 16% at 32 days and 41 and 29% at 72 days of incubation in clay loam and heavy clayey soil, respectively. In contrast to organic matter decomposition, N mineralization proceeds more rapidly under anaerobic than under aerobic conditions (Tusneem and Patrick, 1971; Watanabe, 1984; Gale and Gilmour, 1988). Increased N mineralization in the anaerobic system could be due to the lower metabolic efficiencies of the anaerobic microbial populations (Williams et ul., 1968). Ishikawa ( 1963) reported that decomposition and N release from milk vetch green manure increased with increasing temperature. At 30"C, N mineralization reached its maximum (70% of the N contained in green manure). Thus, relatively cool early season conditions in some rice soils may retard N availability from green manures (Westcott and Mikkelsen, 1985). Groffman et a / . (1987) and Varco ef a / . (1987) reported that clover residue incorporated conventionally into the tilled soil decayed nearly twice as fast as the clover remaining on the surface in the no-till soil. Soluble hemicelluloses in green manures get converted into less soluble forms by drying and retarded decomposition ( Joachim, 1931). Gu and Wen (1981), however, reported that incorporation of fresh or dried milk vetch into the soil produced similar yield responses of rice.

B. Loss OF N

FROM

GREENMANUREDSOILS

Under flooded conditions, mineralization of green manure generally resulted in accumulation of NH4+-N, which is susceptible to ammonia volatilization loss. Incorporation of green manure may, however, affect NH3 volatilization through its influence on pH and Pco,. In an incubation study (Venkatakrishnan, 1980) on a sandy loam soil (pH 8.3), cumulative NH3 volatilization was greater from the unamended than from the green manure amended. In a laboratory study using forced-draft chamber technique, Khind et LII. (1989) observed no N H 3 volatilization 1 0 5 s in a sodic soil (pH 10.0) amended with Sesbuniu green manure (6 t/ha dry biomass; 2.5% N on dry weight basis). At day 16, cumulative NH3 volatilization was 4.5% for urea applied at 200 kg N/ha as basal and 1 .O% for green manure combined with urea applied at 100 kg N/ha as basal. In a field experiment

166

YADVINDER SINGH E T A L .

on a silty clay loam soil (pH 8.4), Santra et al. (1988) observed that cumulative loss of N through NH3 volatilization was highest when the whole quantity of N (90 kg N/ha) was applied basally as urea and was minimum when urea was applied in combination with Sesbania green manure (50 : 50). Green manure application caused a reduction in floodwater pH, and thus loss through NH3 volatilization was small. Similar results have been obtained by Sarvanan et al. (1988) on a clay loam soil (pH 7.4). In a waterlogged alkali soil (pH 10.6), Rao and Batra (1983) reported 4.5% N loss via NH3 volatilization from green manure (applied to supply 60 ppm N) as compared to 28.9% from urea. Although estimation of ammonium volatilization losses has been made following widely different approaches, it has been shown that green manuring can effectively reduce ammonia volatilization losses. John et al. (1989a) observed that green manuring had no effect on N loss from urea applied to rice as assessed from I5N balances and pNH3 in flood water. Incorporation of green manure into soil increases the availability of organic C as a substrate for denitrifiers. This may enhance the loss of applied fertilizer N via denitrification. John et al. (1989b) observed that incorporation of cowpea as green manure at 15 days before transplanting of rice had no effect on loss of urea N applied to rice at 15 days after transplanting via denitrification. Low flood water NO3- levels following urea application suggested that denitrification loss from urea was controlled by the supply of NO3- rather than availability of organic C . Bhagat et al. (1988) reported that leaching losses of N in urea (90 kg N/ha in 3 splits) and green manure with urea (1 : 1) were small but similar. In an acid clay loam soil loss of applied nitrogen in treatments of ammonium sulphate, sunn hemp, and combined application of the two averaged out to be 23.2, 20.4, and 16.2%, respectively (Huang et al., 1981). It indicates that the loss of inorganic nitrogen could be reduced when applied along with green manure. Furoc and Morris (1989) reported that at green manure N levels exceeding 100 kg/ha, more than 70% was not recovered by two rice crops. Further research is therefore needed to determine the fate of this N.

VIII. EFFECT OF GREEN MANURING ON AVAILABILITY OF PLANT NUTRIENTS OTHER THAN NITROGEN A. MACRO-A N D SECONDARY NUTRIENTS Legume plants have the ability to utilize insoluble phosphates through the well-developed root system, and when used as green manures, upon mineralization, release Pin the available forms (Gu and Wen, 1981; Singh,

I67

GREEN MANURING IN WETLAND RICE

1984). Green manuring also helps in increased utilization of fertilizer P by the crops (Venkatarao and Govindarajan, 1960). Krishna Rao el al. (1961) and Subbiah and Mannikar (1964) have shown that green manure taps subsoil P and makes it available to the shallow-rooted crops. Upon decomposition of green manure, organically bound P is mineralized and becomes available to crops. P mineralization is closely related to the analogous transformation of N (Thompson et al., 1954).Phosphorus release would be most rapid under soil and climatic conditions favoring ammonification (Alexander, 1977). Phosphorus content of the added organic matter is perhaps the most important factor in regulating the release of P (Fuller et af., 1956; Singh and Jones, 1976). In waterlogged soils, green manure increases availability of P through the mechanisms of reduction, chelation, and favorable changes in soil pH (Hundal et al., 1987). Changes in soil pH due to green manuring can influence solubility of P (P. K. Singh er af., 1981). The effect of green manuring on available P content in the soil has been reported to be greater in acidic and sodic soils than on calcareous soils (Table VII). Ranjan and Kothandaraman (1986) reported increased availability of P from rock phosphate applied to rice with green manuring. The decomposition products of green manures have significant chelation capacity, lowering the activity of polyvalent cations such as Ca, Fe, and A1 that form insoluble salts with P and thus liberating phosphates from the basic phosphates of these elements at very low pH values (Agboola, 1974). Hundal et al. (1988) reported that green manure incorporation significantly reduced P sorption capacity of waterlogged soils. Anaerobic decomposition of green manure reduced the bonding energy and P sorption maxima. This effect was ascribed to release of P during mineralization of green manure, and accumulation of organic acids-complexed metal cations, thereby inducing solubilization of native soil P or reduced fixation of added inorganic P through the acidifying and chelation mechanisms.

Table VII Effect of Incorporation of Sesbania Green Manure (GM) on Olsen P (mg/kg) in the Soils at Different Days after Flooding

P.K. Singh a / . (1981) Soil pH 5.8

el

Y . Singh e t a / . (1988) Soil p H 8.5

Swarup (1987) Soil pH 10.3

Treatment

20 days

40 days

14 days

28 days

30 days

60 days

- GM

2.8 9.7

15.1 23.7

11.4 14.6

11.8 15.3

14.0 lY.0

13.0 20.0

+ GM

168

YADVINDER SlNGH E T A L .

The leguminous green manure plants have a strong ability to absorb the rather inaccessible K in the soil (Gu and Wen, 1981). Many workers have reported increased availability of K in soils due to green manuring (Kute and Mann, 1969; Debnath and Hajra, 1972; Katyal, 1977; Tiwari et al., 1980; Nagarajah et al., 1989; Swarup, 1987). Increase in soil solution concentration of K, Ca, and Mg in flooded soils was directly related to the concentration of water-soluble Fe2+and Mn2+(Katyal, 1977). A significant increase in water-soluble Ca and Mg with application of green manures to the flooded soils has been observed by Katyal (1977) and Khind et af. (1987a). The peaks of Ca and Mg concentration were observed after 8 days of application of green manure. Like K, increase in soil solution concentration of Ca and Mg in the green manure-amended waterlogged soils is due to release of Fe2+ and Mn2+ under highly reduced conditions. In the green manure-amended soils, active biodegradation coupled with an extensive C02 production can lead to the dissolution of Ca and Mg carbonates. In waterlogged soils, addition of readily decomposable organic matter in the form of green manure can markedly influence the chemical equilibrium of sulphur (Pan, 1985).

B. MICRONUTRIENTS Micronutrient contents of leguminous green manure crops do not spectacularly differ from those of the nonleguminous cereal crops. Nevertheless, the changes in the oxidation-reduction regimes, particularly in the submerged soils, and increased chelation capacity brought about by addition of organic matter as green manure dictate the transformations of micronutrients. A number of workers have studied the influence of green manures on the kinetics of soil solution Fe2+ and Mn2+ in submerged calcareous and noncalcareous soils (Thind and Chahal, 1983), black, red, and lateritic soils (Katyal, 1977), sodic soils (Sadana and Bajwa, 1985), neutral soils (Khind et al., 1987a),and acidic soils (Nagarajah et al., 1989). In all the soils both Fe2+ and Mn2+ in the soil solution increased by submergence over a period of 10 to 12 weeks, but a peak concentration of Fe2+ (about 2 weeks after submergence) and Mn2+ ( I to 2 weeks after submergence) was conspicuous when the soils were green manured. The extent of increase of total Fe2+ and Mn2+ as a result of green manuring varied from very low (<2%) in sodic soils (Sadana and Bajwa, 1985) to as high as 30-fold in an acid lateritic soil (Katyal, 1977). Soil pH had a remarkable effect on the amount of peak concentrations of Fe2+and Mn2+ in the solution of green manure-treated submerged soils (Fig. 4). Organic matter added in the form of green manure also functioned as a chelating

169

GREEN MANURING IN WETLAND RICE 1 .o .pM////

->E - 0.5

-

1

+

-1.0

",

-2.0

-2.5

C

b

-1.5

W

b

0

b b

b0

0

a

0 I

I

,

b

FIG.4. Relationships between peak concentration of (a) pFe2+ and (b) pMnZf, and soil pH in several soils amended with green manure. (Data from: 0, Katyal, 1977; 0 ,Thind and Chahal, 1983; X , Sadana and Bajwa, 1985; A,Nagarajah et ul., 1989.)

agent for water-soluble Fe2+and Mn2+.Work of Bao e f al. (1978) revealed that at the beginning of submergence, the rate of formation of Fe2+ as a result of reduction in the presence of green manure lags behind that of organic reducing substances. Later on, most of the Fe2+in the soil solution was found to be in the chelated form. After about a week or so, there appears a peak of chelated Fe2+ when, due to intensive decomposition of green manure, amount of chelating agent is at maximum. The role of green manuring in increasing the availability of Fe and Mn has been studied in terms of different availability indices and increased supply to crop plants. In a calcareous sandy loam soil incubated with S . aculeata (2 g/kg soil), DTPA-extractable Fe and Mn increased by severalfold over the initial values during a 4-8-week period (B. Singh, unpublished data). Gopala Rao (1956), Meelu and Rekhi (1981), and Swamp (1987) obtained similar results with Gliricidia maculata, mung bean straw, and Sesbania aculeara, respectively. From a field experiment on a coarsetextured soil, Takkar and Nayyar (1986) found that Fe deficiency in the wetland rice was more effectively corrected by Sesbania green manure than by soil-applied ferrous sulphate. Similarly, from a pot experiment with a red loam soil, the success of green manure plus submergence in mobilization of soil iron as a result of intense reduction and subsequent retention in available form at a sufficiently high level during the growth of rice nurseries has been demonstrated by Sharma and Katyal (1982) and Maskina et al. (1985). Several workers (Katyal, 1977; Iu e f a l . ,1981; Thind and Chahal, 1986; Khind et al., 1987a)have reported that water-soluble or DTPA-extractable Zn declined with the duration of flooding whether or not the soil was green manured. As liberation of water-soluble Fe" and Mn2+was enhanced by

170

YADVINDER SINGH ETAL.

green manuring, it helped in the further lowering of soil solution Zn concentration in most of the investigations. Only in a sodic soil having pH 10.2, could green manure increase the availability of applied Zn (Swamp, 1987), possibly due to a significant reduction in soil pH as a result of green manuring.

IX. EFFECT OF GREEN MANURING ON SOIL PROPERTIES A. ELECTROCHEMICAL AND CHEMICAL PROPERTIES On a laterite soil (pH 6.4), application of green leaf manure resulted in a decrease in soil pH by 1.1-2.3 units (Sahu, 1965). Application of green manure along with gypsum to sodic soils accelerates the reduction in pH due to increase in Pco, and production of organic acids (Sadana and Bajwa, 1985). The pH of the calcareous paddy soils is controlled by the chemical equilibria of the CaC03-C02 system. Application of Sesbania green manure to such soils lowers pH by as much as 0.5 unit (Katyal, 1977). Addition of green manure resulted in a decline in pH to 7.70 and 5.87 compared with 8.03 and 7.61 under the no-green manure treatment at 2 weeks after incubation of calcareous and noncalcareous soils, respectively (Thind and Chahal, 1986). In a laboratory incubation study, P. K. Singh er al. (1981) reported an increase in pH of an alluvial soil (pH 5.8) by 0.8 units after 40 days of incubation with green manure. Khind et al. (1987a) also observed a conspicuous increase in soil pH after incorporating S. aculeata (Fig. 5). Soil temperature influences changes in soil pH through its effect on the rate of decomposition of green manure (Cho and Ponnamperuma, 1971). Shortterm variations in pH do not necessarily reflect the overall long-term changes but may have a marked effect on the plant growth. Addition of green manure to waterlogged soils leads to a reduced redox potential (Ed. In a laboratory study, Yu (1985) observed that the diffusion current (a voltametric measure of reducing substances) for the red soil without the addition of green manures was only 0.39 pA/cm2 at 700 mV. The current in the green manure-amended soil increased to 2.94 pA/cm2, due apparently to the increase in the amount of reducing substances produced by decomposition of green manure. Several studies have shown that green manures caused dramatic reduction in Eh of waterlogged soils differing in pH, organic matter, and easily reducible Fe and Mn contents (Katyal, 1977;Thind and Chahal, 1983; Sadana and Bajwa, 1985; Khind et al., 1987a). The magnitude of depression was more pronounced during the

GREEN MANURING IN WETLAND RICE

0 1 2 3 DAYS AF1'ER FLOODING

171

5 10 20 30 40 50 I

FIG.5. Effect of green manure incorporation on changes in (a) Ehand (b) pH of a Crowley silt loam soil after submergence.

early stage of submergence (Fig. 5). More reduction has been reported in noncalcareous than in calcareous or sodic soils. In an acid soil with a low organic matter content, green manuring reduced Eh within 1 to 2 days of flooding from +200 mV to -200 mV (Yu, 1985). Katyal (1977) observed greater depression in Eh of the black clay soil, which contained smaller amounts of reducible Fe and Mn than laterite or red soils. Katyal(l977) and Sadana and Bajwa (1985)observed higher and sharper peaks of PCO, in the soil amended with green manure. High PCO, may increase the water-soluble Fe to toxic amount or HC03- may directly poison the rice plant. COz produced during decomposition of green manure can directly influence the photosynthesis process of rice plants (Shivashankar and Vlassak, 1978). The increase in electrical conductivity (EC) of the soil after submergence is related to increase in the amounts of NH4+, Na+, K + , Fez+, Ca2+,and Mg2+ ions and to decomposition of organic matter of the soil. Katyal (1977) and Sadana and Bajwa (1986) observed that addition of organic matter into soil caused a sharp increase in EC within 14 days of flooding. Sudden initial increase in EC may cause the death of rice plants. Thind and Chahal (1986) observed a marked increase in EC of the flooded soils amended with the green manure. The increase was more in the noncalcareous than in the calcareous soils, and was explained by greater release of Fez+and Mn2+ions in the former soil. During decomposition of a green manure several organic compounds accumulate in waterlogged soils. Ishikawa (1988) showed that organic

172

YADVINDER SINGH E T A L .

acids can accumulate in significant amounts during decomposition of milk vetch green manure under the waterlogged conditions. Low temperature favored the production and persistence of the fatty acids. Formation of organic acids was less when flooding began 5 days after application of milk vetch green manure. This was due to fast and simultaneous production and decomposition of organic acids under the aerobic conditions. Volatile fatty acids (mainly acetic acid), nonvolatile aliphatic acids (mainly tartaric acid), phenolic acids, and alcohols (methanol, ethanol, x-propanol, and n-butanol) accumulated in large quantities with green manure incorporation under waterlogged conditions (Wang et al., 1967; Tsutsuki, 1984). Accumulation of aldehydes (mainly acetaldehyde) and ketones (acetone and methylethyl ketone) in the soils amended with green manure was also detected under the submerged conditions, but the amounts formed were low. Accumulation of amines (putresine, ethylamine, isobutylamine) has been detected during anaerobic decomposition of clover plant residue (Fujii er al., 1972). Application of green manure to soil can stimulate formation of ethylene (C2H4), which acts as a plant hormone, and is suspected to be a regulating agent for plant pathogeneity and root growth (Smith, 1976; Primrose, 1979). Organic acids can retard root elongation, restrict nutrient uptake, and reduce shoot weight (Watanabe, 1984). A concentration of acetic acid greater than 1 mM can restrict the uptake of P and K (Rao and Mikkelsen, 1977). A phenolic acid concentration of 1-10 pl/L in soil atmosphere can be toxic to the plants. To understand the possible toxicity or stimulation that green manuring may cause in the rice plant, precise quantitative determination of the metabolites is needed, particularly in the presence of rice plant.

B. PHYSICAL PROPERTIES In most soils, although the amount of organic matter is relatively small, its influence on the soil physical properties can be large. Green manuring can help to maintain or increase soil organic matter and thus improve the soil physical properties. MacRae and Mehuys (1985) reviewed the literature on the effect of green manuring on the physical properties of soils of the temperate regions. Changes in the physical properties of the wetland soils as influenced by green manuring might differ from those reported for upland soils. Organic materials act as binding agents in holding the primary soil particles together to form soil aggregates. Improvement in soil aggregation by green manuring has been reported by several workers (Darra el al.,

173

GREEN MANURING IN WETLAND RICE

1968; Havangi and Mann, 1970; Yaacob and Blair, 1981; Jiao et al., 1986; Liu, 1988). Boparai (1982) observed that green manuring in wetland rice increased water-stable aggregates, between 0.1 to 0.5 mm, by 68% over no-green manuring. Chaudhary and Bajwa (1979), Jiao et al. (1986), and Liu (1988) reported that green manuring increased the water-stable aggregates in paddy soils (Table VIII). Joshi et al. (1990) reported that the settling percentage of wet soil aggregates after rice harvest was 10.8 in the Sesbaniu-treated plots compared with 14.2 in the inorganic fertilizertreated plots. Effect and effectiveness of green manuring did not last long unless continuous additions were made every year (MacRae and Mehuys, 1985). In addition to adding organic matter, green manure crops, due to their extensive and sturdy root system, exert a favorable influence on soil permeability and lowering of bulk density (Padma Raju and Deb, 1970; Sharma and Singh, 1970). Boparai (1982), Sood (1988), and Liu (1988) reported a marked decrease in bulk density of the soil in green manured Table VIII Effect of Green Manuring (GM) on Physical Properties of Soils Reference and treatment

>0.25 mm

Chaudhary and Bajwa (1979)" -GM + gypsum +GM + gypsum

4.5 13.7

>0.1 mm

Modulus of rupture (bars)

Hydraulic conductivity (cm/h)

15.3 25.1

4.3 2.4

0.49 0.65

Soil aggregates (%)

Soil aggregates (%) ~

Jiao er nl. (1986)h -GM + GM

I'

~

~

2-1 mm

1-0.5 mm

0.5 mm

Total

9.0 34.5

5.9 13.6

4.0 2.3

3.4 5.1

22.3 55.5

Aeration (%)

Bulk density (g/m3)

36.5 45.9

I .48 1.33

Soil aggregates in 0-10 cm layer (%)

Liu (1988)' -GM + GM

~~

5-2 mm

1-0.5 mm

0.5 mm

0.25 mm

'Total

Maximum water-holding capacity (mm)

0.7 3.1

0.6 1.7

2.3 4.2

3.6 9.0

43.6 46.5

Pot study on sodic soil.

' 3-Year field study.

' 3-Year field study on saline coastal soil.

174

YADVINDER SINGH E T A L .

plots under wetland rice (Table VIII). The effects of green manure, however, decreased with time. Chaudhary e? al. (1986) and Sood (1988) have also shown an increase in the infiltration rate of loamy sand soil due to green manuring. Chaudhary and Bajwa (1979) observed a favorable effect of green manuring on hydraulic conductivity of a sodic soil under wetland rice (Table VIII). Water retention in soil is enhanced through increased total porosity, storage pore space ( 4 0 pm diameter), and the water absorption capacity of soil organic matter. Biswas et al. (1970) reported that incorporation of green manures increased hydraulic conductivity, water-holding capacity, and aggregate stability of the soil under rice. Liu ( 1988) observed that incorporation of Sesbania green manure increased porosity and water-holding capacity of the wetland rice soil (Table VIII). Recently, Joshi et al. (1990) observed that during the growth of rice when the soil was saturated, there was not much difference in moisture retentiveness of the green manured and chemically fertilized plots. However, after the harvest of rice, Sesbania-treated plots retained 4% more water in the top 30-cm soil layer than did the plots that received inorganic fertilizers. Chaudhary and Bajwa (1979) reported a decrease in the modulus of rupture of the soil amended with green manure (Table VIII).

C. BIOLOGICAL PROPERTIES The literature on the effects of green manuring on microbial population and activity is limited. Obviously, application of green manures caused a high level of zymogenic response of the microbial population due to the availability of an easily decomposable source of energy and carbon (Thomas and Shantaram, 1984). With green manuring, a population of asymbiotic N;?-fixingbacteria and phosphate solubilizers increased considerably (Kute and Mann, 1969; Lynch and Harper, 1980). Sanyasi Raju (1952), Ramaswami and Raj (1973), and Azam e? al. (1985) recorded a significant increase in the bacterial population and microbial biomass of N in the soil amended with green manure. Thomas and Shantaram (1984) observed marked increases in dehydrogenase, phosphatase, and urease activities in the rhizosphere due to the application of green manure. Bhattacharya e? al. (1986) could obtain a significant effect of green manures on selected microbiological processes in the rice rhizosphere and their residual effect on the rhizosphere of following wheat. Gopalaswamy and Vidhyasekaran (1987) found a marked increase in soil microbial activity measured as dehydrogenase activity in the soil treated with green leaf manures as compared to urea. Green manuring by increasing microbial populations in soil may also have an

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antagonistic effect on soil-borne plant pathogens. Germani et al. (1983) reported a marked decrease in the nematode population in a rice soil in the presence of green manure.

X. GREEN MANURING AND RECLAMATION OF SALINE ALKALI SOILS Green manuring has been recognized as a useful practice for reclaiming saline alkali soils. The reclamation process consists of successful growing of a salt-tolerant green manure crop followed by its incorporation to bring about favorable changes in the physicochemical properties of saline alkali soils, which ultimately leads to an increased yield of rice on these soils. A. GREENMANURE CROPS FOR

SALINE

ALKALISOILS

Among different legume species used as green manures, Sesbania spp. are remarkably suited to saline and alkali soils (Keating and Fisher, 1985; Rao, 1985; Evans and Rotar, 1986) Sesbania invariably gave double the biomass yield over that of clusterbean and sunn hemp in alkali soils (Uppal, 1955). Increasing salinity levels up to 62.3 dS/m and alkalinity levels up to pH 10.6 had no significant adverse effect on the growth and number of nodules of Sesbania spp. (Bhardwaj, 1974; Singhbutra et al., 1987). Jen et al. (1965) reported that Sesbania tolerated salt concentration from 0.42 to 1.04% in the seedling stage and from 0.92 to 1.39% as it reached maturity. Swarup (1987) has found that in sodic soils, increasing ESP (exchangeable sodium percentage) from 16 to 32 had no significant effect on biomass and N yield of S. aculeata. At 45 days, S. aculeata could produce a green matter yield of 20-24 t/ha containing about 95-1 15 kg N in alkali soils (Rao, 1985). Germination, growth, and nodulation of green manure crops, including S. aculeata, are adversely affected only by high levels of salinity and alkalinity (Singh and Rai, 1973; Gill, 1979; Sinha, 1982; Hussain and Arshad, 1984; Hansen and Munns, 1985). In Pakistan, Khan and Awan (1968) analyzed soils from a farm where Sesbania crop was luxurient, patchy, or had failed. Total soluble salts in the surface 23-cm soil horizon were 0.43, 1.39, and 3.15%, respectively. In several situations, Sesbania may require some soil amendment before it can be grown. For example, Abrol and Bhumbla (1979) obtained low yields (negligible to 2. I t/ha fresh biomass) of S. aculeara on unamended sodic soils, but gypsum application

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at 7.5 t/ha markedly increased the yields (16-47 t/ha). Dutt et al. (1983) reported that growth of S . sesban seedlings was almost doubled when an alkaline soil pH was reduced from 8.4 to 7.9 by sulfur application. Poonia and Bhumbla (1972) reported that Sesbania dry matter yield decreased considerably as soil ESP increased from 2 to 77. Increased rates of gypsum (2-8 meq/100 g saline-sodic soil) were found to increase dry matter yield (Poonia and Bhumbla, 1973). B. RECLAMATION PROCESS The incorporation of easily decomposable plant material in soil through green manuring causes increased and rapid production of C02 (Katyal, 1977; Bhardwaj and Dev, 1985; Beri et al., 1989b)that in turn enhances the solubility of Ca in the soil. Ca2+ replaces Naf on the exchange complex resulting in improvement of saline alkali soils. Wetland rice, due to its high tolerance to exchangeable sodium, is the most suitable crop recommended for the reclamation of sodic soils. Beneficial effects of submergence on rice growth become more pronounced by incorporation of green manure. Application of green manure contributes to the reclaiming action of gypsum by improving the physicochemical properties of the soil and by markedly decreasing soil pH, Eh, and increasing EC, Pco2, Ca2+,Mg2+,Na+ concentration in equilibrium solution (Yadav and Agarwal, 1961; Sadana and Bajwa, 1986). Higher amounts of Na+ and lower levels of Ca2+ + Mg2+in the soil solution under gypsum and green manure combined treatment as compared to gypsum alone suggested that removal and leaching of sodium can be greatly enhanced by applying gypsum and green manure together. In a calcareous sodic soil, incorporation of Sesbania plant material reduced an initial ESP by 36% over a 10-week incubation period, whereas barley straw resulted in only a 10% reduction (Singh, 1974). In a field experiment, application of gypsum (20 t/ha) along with green manures to a sodic soil resulted in a marked reduction in soil pH and ESP compared to that upon application of gypsum alone (Swarup, 1987). Both green manuring and gypsum favorably affected soil structure and hydraulic conductivity of saline sodic soils resulting in leaching of displaced sodium ions into the deeper soil layers (Yadav and Agarwal, 1959; Jen et al., 1965; Anonymous, 1966). Yadav and Agarwal (1961) could observe complementary effects of gypsum and Sesbania green manuring; the former facilitating base exchange reactions and the latter improving physical characteristics. Increases in both permeability and removal of soluble salts due to green manuring with Sesbania were attributed to an extensive and sturdy root system, which renders the leaching process

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much easier (Rao, 1985). It is interesting to note that root growth of Sesbania also caused a marked decrease in ESP and an increase in soil porosity (Jen et ul., 1965; Swarup, 1987). Organic acids and C 0 2liberated by the roots of Sesbania helped in solubilizing native calcium carbonate and gypsum applied to the alkali soils. C. EFFECTSON RICEYIELDS

Results from several field studies on sodic soil indicated that incorporation of 40- to 50-day-old Sesbaniu resulted in rice yield equivalent to that obtained with 80-120 kg N/ha (Dargan et al., 1975; Swarup, 1987; Ghai et al., 1988). In Thailand, growing and incorporation of S . speciosa green manure in saline alkali soils helped obtain rice yields of 1.25 t/ha compared to 0.4 t/ha in no-green manure treatment (Arunin et al., 1988). Agarwal (1957) demonstrated to the farmers that a rice yield increase of 37% could be obtained using green manure alone, an increase of 97% using gypsum alone, and an increase of 173% using both combined. Combinations of green manuring and gypsum or sulfur or lignite fly ash or press mud or pyrite amendments helped in obtaining large increases in crop yields on the saline-sodic soils (Dhawan et al., 1961; Mendiratta et u l . , 1972; Mahalingam, 1973; Shetty, 1975; Jauhari and Verma, 1981; Somani and Saxena, 1981). Shirwal and Despande (1977)demonstrated that rice grown with N-P-K alone yielded 0.92 t/ha, but when the soils were reclaimed with 2.5 t/ha gypsum and green manuring with Sesbania, yields increased to 3.7 tiha. Misra (1976), using Sesbanin green manure incorporated at 5.6 tiha or gypsum at 12 tiha on a saline-sodic soil, increased rice yields by 57 and 23%, respectively. These results indicated that gypsum alone is sometimes not as effective as green manuring.

XI. RESIDUAL EFFECTS OF GREEN MANURES APPLIED TO WETLAND RICE A. SOILORGANIC MATTER Green manuring will either increase soil organic matter or increase the immediate supply of N and other plant nutrients, but cannot effectively do both at the same time (Allison, 1973; Warman, 1980). As already discussed, the higher the lignin content of added plant material, the higher is the humification coefficient-the fraction of organic carbon left after one

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year of decomposition. Both soil properties and climatic conditions affect the humification coefficient. Gu and Wen (1981) reported that the humification coefficient of green manures ranged from 0.18 for milk vetch to 0.43 for Azolla. Later, Wen (1984) gave a typical humification coefficient of 0.10, 0.20, and 0.40 for leaves, aerial parts, and roots of milk vetch green manure, respectively. It has been found that mixed cultivation of leguminous and nonleguminous green manure crops often gives a higher humification coefficient, thus being advantageous to the accumulation of organic matter in soil (Woodward and Burge, 1982; Chen, 1986). This may be a promising way of cultivating green manure crops under the conditions where enough quantity of crop residues is not returned to the soil. Higher accumulation of organic matter and N in three different soils was observed from the application to rice of 65-day-old Sesbania green manure as compared with 45- or 55-day-old crops (Bhardwaj and Dev, 1985). Both quantity and composition of the green manure changed markedly with age. The experimental results from China (Bin, 1983) show that in most cases, the effect of green manuring on accumulation of organic matter is obvious. Ishikawa (1988) observed that long-term (10-51 years) application of milk vetch green manure increased organic matter and N content of soils. Singh and Verma (1969) also observed that organic carbon content of soil was high when green manuring was practiced every year, suggesting that the effect of green manures on soil organic matter levels are shortlived unless continuous additions are made. Joffee (1955) reviewed some aspects of green manures and concluded that green manures did not cause any increase in soil organic matter content. In humid tropics and subtropics, mineralization rather than humification dominates the decomposition reactions of organic materials incorporated in soil (Singh, 1962). In later studies, Singh (1967) observed no appreciable increase in organic carbon content N in green manured plots over that in those receiving purely inorganic fertilizers. Some researchers have not accepted that green manures can even maintain soil organic matter levels (Pinck et ul., 1946; Polyser et al., 1957). B. CROPYIELDS The residual effect of green manure application to wetland rice has generally been measured in terms of grain yield of the succeeding crop. Reviewing green manuring research in India, Sethi et al. (1952) concluded that the residual effect of green manure applied to rice was low. Recent work (App et al., 1980; Beri and Meelu, 1981; Dargan and Chhillar, 1980; Hesse, 1984; Morris el al., 1986a, 1989) has also shown that there is little or

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no cumulative (over 3 to 4 years) benefit of green manuring of rice to the succeeding crop. Using 15N labeled vetch green manure, Westcott and Mikkelsen (1987) recovered 15-35% of the added green manure N from the soil after rice harvest. In green house and field experiments with vetch and Sesbania green manures, N recovery by the second rice crop was about 6% of the original application, representing 14-26% of the labeled vetch N remaining in the soil at rice harvest (Westcott, 1982; Biswas, 1988).The grain yield of the second rice crop was significantly higher (0.3 t/ha) than that obtained in the urea-treated plots (Biswas, 1988). Significant residual effects of green manures applied to rice on the following crop have been reported by Singh (1971),Tiwarietal. (1980),Zhuetal. (1984), FurocandMorris(1989),and Maskina et al. (1990). Jha et al. (1980) observed that rice yield and N uptake increased by 0.7 t/ha and 18 kgfha on plots where GLM was applied during the previous six seasons continuously over that measured when ammonium sulphate was applied, respectively. Rinaudo et al. (1988) observed a 40-46% increase in yield of the second rice crop taken after green manured rice, compared with inorganic N treatment. In these studies, two-thirds of the total green manure N remained in soil after the harvest of the first rice crop. Residual effects of green manuring on the succeeding crops are location specific. The reasons for such variations are not very clear and need further investigations. Bouldin (1988) suggested that the residual effects of green manure on a second crop would be small when only one application of green manure is made, but the cumulative effects of several annual applications are expected to give appreciable residual effects. Residual effects of green manure under tropical climates are in fact likely to be smaller than under temperate climates.

XII. CONCLUSIONS Fast-growing leguminous green manure crops have a tremendous potential in harnessing the atmospheric Nz, and act as substitute for fertilizer N in wetland rice. There is a large range of drought- and waterlogged-tolerant green manure species. Sesbania aculeata, which is quite tolerant to waterlogging and soil salinity and alkalinity, has shown promise in the tropics and subtropics. Perennial tree legumes are slow growing, and can be used for green leaf manuring. Milk vetch, purple vetch, and clovers are most suitable green manure crops for the temperate regions. The stem-nodulating legumes (S. rostrata and A . afraspera) represent a

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further step in adaptation to waterlogging and N2 fixation in soil with high amounts of combined nitrogen. Sesbania speciosa is an ideal leguminous green manure for sowing in the standing rice crop, and on the field boundaries. The dual-purpose legumes such as mung bean and cowpea can be grown with advantage where the fallow period interval before rice transplanting is more than 60 days, and the soils are well drained. It is clear that in a favorable climate with proper management, leguminous green manures accumulate well over 100 kg N/ha in 50-55 days. It appears that most of the N (80%) will be derived from biological N2 fixation. In some cases, especially with S.rostrata, inoculation has been found to be necessary or usefuI. The other important factors that may limit N accumulation are P, soil pH, N , temperature, and soil moisture supply * The most studied benefit of leguminous green manure is its contribution to N nutrition of the following rice crop. Considerable evidence has accumulated that the use of leguminous green manure can significantly raise rice yields. The increases in rice yield were found to be greater on the less fertile coarse-textured soils than on the fertile medium- and fine-textured soils. Indirect estimates generally indicated that leguminous green manure can supply 50-120 kg chemical fertilizer N/ha. The increase in yield of rice is proportional to the amounts of dry matter (and N) added. However, large quantities of green matter added to poorly drained soils can adversely affect rice growth. Green manure N generally shows N-use efficiency and N recovery similar to that for fertilizer N. It has been repeatedly observed that green manuring helped raise the yield potential of rice, which cannot be achieved even by applying additional fertilizer N. The supply of P through green manure appeared to be more beneficial in enhancing the yields of rice than the direct application of P to rice crop. Allowing extended periods of green manure decomposition before rice transplanting generally resulted in a lesser contribution to the subsequent rice crop. Release of N from succulent green manures is quite rapid, especially under tropical and subtropical climates. Supplementing basally applied green manure with top-dressed fertilizer N helped in maximizing both green manure and fertilizer N recovery. Limited information available suggested that application of fertilizer N to the green manured rice can be delayed up to the panicle initiation stage. Relatively less is known about the processes of N loss from green manure N. Green manuring can improve both the physical and biological properties of soil. The data from a few studies indicated that the physical parameters more likely to be affected by green manuring are aggregate stability and bulk density. Several studies have shown that green manuring caused a marked reduction in soil Eh, and a significant reduction in soil pH. Green

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manuring can also have a favorable influence on the availability of P, K, Fe, and Mn in the soils. Green manuring can help maintain organic matter levels under particular, though not well-defined, soil conditions. Rarely, soil organic matter levels will be increased by green manuring. The residual effects of green manure on the succeeding crop are small but the cumulative effects of several applications are expected to give a significant residual effect. Green manuring hastens the reclamation of saline and sodic soils, and has thus proved an important management practice for their reclamation. The practical advantages from green manuring are great enough to justify further research. IRRI (1988)has prepared a long list of future needs for research on green manuring in rice. Important areas proposed for future studies are (1) selection of leguminous green manure crops for different soil and agroclimatic conditions, (2) development of management practices for green manures, (3) determining the rate of decomposition and N mineralization of green manures and model the process of decomposition, (4) determining the effect of green manuring on N and other plant nutrient transformations in diverse soil and climatic conditions, ( 5 ) investigating the fate of biologically fixed N by using "N-labeled green manure crops, (6) understanding the effects on the physical, chemical, and biological properties of soil, (7) modeling soil organic matter levels after longterm application of green manures, (8) studying integrated management of inorganic N and green manures for maximizing N-use efficiency, and (9) quantifying N contribution from green manures into a model of N fluxes. It can be expected that future research, particularly with isotopically labeled green manures, will provide more insight into the rate of N release and uptake, and the extent of N losses from the green manures. There is a need to define necessary conditions that can ensure accumulation of 100 kg or more of N/ha by a green manure crop. Additional experiments for comparing the fate of N from green manure versus inorganic fertilizer will be of considerable value. Identification of management practices that reduce the losses of green manure N and factors that influence the transfer of green manure N to the rice plant will be critical for the practical utilization of biologically fixed N for rice.

ACKNOWLEDGMENTS The authors are grateful to Dr. M. S. Bajwa, Professor and Head, and Dr. 0. P. Meelu, Chief Scientist, Department of Soils, for providingfacilities. We thank Mr. Subhash Chander for typing the manuscript.

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ADVANCES IN AGRONOMY. VOL. 45

ADVANCES IN DISEASE-RESISTANCE BREEDING IN CHICKPEA' K. B. Singh2 and M. V. Reddy3 International Center for Agricultural Research in the Dry Areas (ICARDA) Aleppo, Syria International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) Patancheru, Andhra Pradesh 502 324, India

I. Introduction 11. Sources of Genetic Variability 111. Breeding Techniques IV. Disease Resistance A. Fungal Diseases: Soil-Borne B. Fungal Diseases: Foliar C. Viral Diseases D. Nematode Diseases E. Breeding for Resistance to Other Diseases V. Breeding for Multiple Disease Resistance V1. Annual Wild Ciccr Species as a Potential Source of Genes for Resistance VII. Resistant Cultivars in Disease Management VIII. Conclusions and Future Needs References

I. INTRODUCTION Chickpea (Cicer arietinurn L.) is a diploid species with 2n = 16 chromosomes. It is a self-pollinated crop with natural cross-pollination ranging between 0 and 1% (Singh, 1987). Most probably chickpea originated in southeastern Turkey (Ladizinsky, 1975). There are two types of chickpea: desi (local), characterized by small, angular, colored seeds; and kabuli (an allusion to origin in the Afghani capital, Kabul, before it reached India), characterized by large, ram-head-shaped, beige-colored seeds. The desi type is primarily grown in the Indian subcontinent and East Africa, and the

' Journal Article No. 1124;joint contribution from the International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria, and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT). Patancheru, Andhra Pradesh 502 324, India. 191 Copyright 0 1991 by Academic Press, Inc. All rights of reproduction in any form reserved

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kabuli type is mostly grown in the Mediterranean region and Central and South America. It is believed that the small-seeded desi type is the original form of chickpea and that the kabuli type developed through mutation. The chickpea is grown primarily on conserved moisture and rarely receives fertilizers or protection from diseases and insect pests. The protein content of the seed is comparatively low (23%), but its biological value is the best among pulses. Chickpea is consumed as fresh, immature green seed, whole seed, dhal, and flour. Of the food legumes, chickpea ranks second in area and third in production. It was grown on 9.6 million ha with a production of 6.7 million t from 1986 to 1988. It is an important crop in South and West Asia, and is also grown in Central and South America, East Africa, North Africa, and southern Europe. The average per hectare production of 704 kglha is low (Food and Agriculture Organization, 1988), a major cause being susceptibility of land races to diseases. Diseases can be controlled by application of fungicides, by cultural practices, or by use of host-plant resistance. Although effective fungicides have been identified (Hanounik and Reddy, 1984), they are often impractical. Modification of cultural practices can often reduce yield loss from diseases, but yield per se also may be reduced. Hence, the best strategy to control diseases is through use of resistant cultivars. The purpose of this article is to review the past work on disease resistance breeding in chickpea and to discuss strategies to tackle unsolved disease problems.

II. SOURCES OF GENETIC VARIABILITY Sufficient genetic variability exists in the chickpea germplasm collections maintained at national, regional, and international genetic resources centers (Malhotra et al., 1987; Pundir et al., 1988; Singh et al., 1983). The largest collection ( 1 5,945 accessions) is maintained at ICRISAT (International Crops Research Institute for the Semi-Arid Tropics) Center in India (R. P. S . Pundir, personal communication) and the second largest collection (over 8,000 accessions) is maintained at ICARDA (International Center for Agricultural Research in the Dry Areas), Syria (L. Holly, personal communication). Granted that some accessions are common to both collections, total accessions exceed 20,000. Evaluation of 5,000 to 15,000 accessions for reaction to six biotic and abiotic stresses at ICARDA resulted in identification of sources resistant to all except seed beetle and cyst nematode (Singh, 1989). The most extensive germplasm evaluation has been for resistance to Ascochyta blight and Fusarium wilt. Germplasm

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lines maintained at ICRISAT and ICARDA warrant further evaluation for resistance to other diseases.

Ill. BREEDING TECHNIQUES Methods for breeding disease-resistant chickpea cultivars are similar to those used for yield breeding, except that the segregating materials are challenged by the pathogen and selection is made for disease resistance along with other attributes. Some of the techniques employed by breeders are as follows: 1. Selection from introductions. Selection from introductions is a potent method of breeding, especially for countries with limited resources or area. Following this technique, Karachi was released as a wilt-resistant cultivar in Myanmar, Burma in 1923; Lebanon released Janta 2 as an Ascochyta blight-resistant cultivar in 1989. Many cultivars have been released in the intervening period. 2. Hybridization. Resistance breeding usually begins with selection from introductions, but subsequently it is dominated by hybridization as this offers an opportunity to combine desirable traits from two or more parents in one line. In chickpea, hybridization is followed by three breeding methods: (1) pedigree, (2) bulklpopulation, and (3) backcross. Combinations of these methods, such as bulk-pedigree and backcrosspedigree, are commonly adopted. 3. Mutation. Mutation techniques have been used to create new variability, but sometimes even cultivars have been developed.

IV. DISEASE RESISTANCE Chickpea is subject to numerous diseases. Nene et al. (1989a) listed I15 pathogens known to infect chickpea, including fungi, bacteria, viruses, mycoplasmalike organisms, and nematodes. Fortunately, only a few of them cause economic losses, but in certain areas they severely limit chickpea production. Some diseases such as wilt, root rots, Ascochyta blight, and Botrytis gray mold can cause major losses and prevent farmers from realizing the potential yield of the crop. This is because farmers do not implement necessary practices to prevent losing the crop by diseases. Though work on diseases such as Ascochyta blight and wilt has been

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conducted since the beginning of the century, research effort has only occurred over the past 15 years. The establishment of international agricultural institutes such as ICRISAT and ICARDA, in which chickpea is a mandated crop, has given momentum to research on chickpea diseases. Also, national research programs in India and Pakistan, where chickpea is an important grain legume crop, have increased efforts considerably during the past 10-15 years. Though considerable progress has been made in understanding and managing some diseases, more research is needed. Since chickpea disease research has been reviewed in detail by several workers (Greco and Sharma, 1991; Haware et al., 1991; Kaiser et al., 1991; Nene and Reddy, 1987; Reddy et al., 1991), the scope of this paper will be restricted to summarizing host-plant resistance research on the most important chickpea diseases. A. FUNGAL DISEASES: SOIL-BORNE Fungal diseases are by far the most important. These diseases can be broadly divided into two groups: soil-borne and foliar. Soil-borne diseases are relatively more serious in the lower latitudes (0-20") where the chickpea growing season is short, warm, and dry. Foliar diseases are more important in higher latitudes (20-40") with relatively long, cool, and wet growing seasons. Soil-borne diseases, such as wilt and root rots, occur regularly, whereas foliar diseases, such as Ascochytu blight, do not occur every season, but only when rain occurs during the cropping season. Losses from soil-borne diseases are not high; however, when foliar diseases occur in epidemic form the entire crop is usually destroyed. Chickpea suffers from several major soil-borne diseases (Table I) including wilt, root rots, and stem rots. Very often more than one disease occurs in the same field; a single plant may be infected by more than one disease. The disease may affect the crop from seedling stage to maturity. 1 . Fusarium Wilt [Fusarium oxysporum Schlect. emend Snyd. & Huns f . s p . ciceri (Padwick) Snyd. & Hans.]

a . General Description of Disease. Fusarium wilt, the most important soil-borne disease, is prevalent in most chickpea-growing countries (Table I). It is a typical vascular disease causing xylem browning or blackening. The disease affects the crop at all stages. The expression of symptoms is most rapid at high temperatures (>30°C). A susceptible cultivar (e.g., JG

BREEDING DISEASE RESISTANCE IN CHICKPEA

I95

Table I Important Soil-borne Fungal Diseases of Chickpea and Their Distribution" Disease

Causal organism

Fusarium wilt

Fusarium oxysporum Schlecht. emend Snyd & Hans. f.sp. ciceri (Padwick) Snyd. & Hans.

Verticillium wilt Dry root rot

Collar rot

Verticillium dahliae Reinke & Berth Rhizoctonia baraticola (Taub.) Butler [Macrophomina phaseolina (Tassi) Goid.] Sclerotium rolfsii Sacc.

Wet root rot

Rhizoctonia solani Khun

Black root rot

Fusarium solani (Mart.) sacc. Phytophthora megaspermu Drechs. Pythium ultimum Trow

Phytophrlioru root rot Pythium root and seed rot Foot rot

Stem rot

Operculella padwickii Kheshwalla Sclerorinia sclerotiorum (Lib.) de Bary

Countries where prevalent Algeria, Argentina, Australia, Bangladesh, Chile, Colombia, Ethiopia, India, Iran, Iraq, Kenya, Malawi, Mexico, Morocco, Myanmar (Burma), Nepal, Pakistan, Peru, Spain, Sudan, Syria, Tunisia, U.S.A. Pakistan, Tunisia, U.S.A. Australia, Bangladesh, Ethiopia, India, Iran, Kenya, Lebanon, Mexico, Pakistan, Spain, Syria, U.S.A. Bangladesh, Colombia, Ethiopia, India, Mexico, Pakistan, Syria Argentina, Australia, Bangladesh, Chile, Ethiopia, India, Iran, Mexico, Morocco, Pakistan, Syria, U.S.A. Argentina, Chile, India, Mexico, Spain, Syria, U.S.A. Argentina, Australia, India, Spain India, Iran, Turkey, U.S.A. India Algeria, Australia, Bangladesh. Chile, India, Iran, Morocco, Pakistan, Syria. Tunisia, U.S.A.

From Nene et al. (1989a)

62) under such conditions may be killed within 15 days of sowing in a wilt-infested field. The freshly wilted plants show drooping of the foliage, but retain their green color. In tolerant cultivars (e.g., K 8501, the disease causes general yellowing and drying of the lower leaves and late wilting. The root systems of wilted plants do not show any apparent symptoms. Losses from wilt have not been estimated precisely. In India, the disease is suspected to cause about 10% loss annually (Singh and Dahiya, 1973).

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Sattar et al. (1953) estimated a loss of about U.S. $ 1 million annually due to wilt in Pakistan. Estimating losses due to wilt alone in farmers’ fields is difficult as it is usually accompanied by root and stem rot diseases. Wilt initially appears in a field in small patches; these patches enlarge if chickpea is cultivated in the same field year after year. In soils favorable to Fusarium oxysporum f.sp. ciceri, the field becomes completely infested within three seasons. The wilt pathogen is both seed and soil borne and can survive in soil up to six years in the absence of a host plant. The fungus has been found to have distinct physiologic races; seven races have been reported from India, Spain, and the United States (Haware and Nene, 1982; JimenezDiaz et al., 1989; Phillips, 1988). b. Sources of Resistance. Field, greenhouse, and laboratory inoculation techniques have been standardized for screening chickpeas for wilt resistance (Nene et al., 1981). Effective “sick plots” have been developed in almost all the important chickpea growing countries, including Bangladesh, Ethiopia, Mexico, Morocco, Myanmar (Burma), Nepal, Peru, Spain, Tunisia, and the United States. Lines resistant to Fusarium wilt have been identified in all these countries. A few lines with broad-based resistance to wilt, such as ICC 2862, ICC 9023, ICC 9032, ICC 10803, ICC 11550, and ICC 11551, also have been identified (Nene et al., 1989b). Although resistant lines are not killed, they show internal blackening or browning indicating fungal infection. The mechanism of resistance to wilt is not fully understood. Exudates from susceptible cultivars such as JG 62 are known to stimulate mycelial growth and germination of conidia and chlamydospores, while exudates from the resistant cultivar CPS- 1 inhibited these processes (Satyaprasad and Ramarao, 1983).

c . Genetics of Resistance to Fusarium Wilt. Knowing the genetics of resistance to diseases helps plant breeders eliminate or reduce yield losses through appropriate breeding strategies. Ayyar and Iyer (1936) were first to report that a single recessive gene conferred resistance to Fusarium wilt in chickpea; this finding was confirmed later by several studies (Table 11). Lopez Garcia (1974) presented evidence that two pairs of recessive genes controlled the genetics of resistance to Fusarium wilt. Upadhyaya et al. (1983a) reported that different chickpea genotypes varied as to the time required before the initial symptoms of Fusarium wilt appeared. In particular, C-104 wilts much later than JG-62; the difference appears to be controlled by a single gene. Upadhyaya and co-workers (1983a) found that at least two genes control resistance to race 1. Further studies by Upadhaya et al. (1983b) confirmed that the cultivar C-104

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BREEDING DISEASE RESISTANCE IN CHICKPEA Table I1

Inventory of Inheritance of Resistance to Fusarium Wilt (Fusarium oxysporum f.sp. ciceri) in Chickpea ~~

Nature of inheritance

Genotype

References

Incomplete dominance, single gene Two pairs of recessive genes Single recessive gene Single recessive gene Single recessive gene Single recessive allele Monogenic recessive gene Single recessive gene Three independent loci designated H , , H2. and H3

Strain No. 468 19 Lines Strain 315 9 Lines JG 315 WR 315, CPSl 7 Desi lines I23 I , 32-35-8/7 P 436-2, C PSI, WR 315, BG 212 JG 62, C 104, H 208, K 850 JG 62, C 104, H 208, K 850 K 850, C 104

Ayyar and Iyer ( I 936) Lopez Garcia (1974) Pathak et a / . (1975) Haware et a/. (1980) Tiwari et nl. (1981) Kumar and Haware (1982) Phillips (1983) Sindhu et al. (1983) Srnithson ef a / . (1983)

Two recessive genes to race 1 Two recessive genes to race 1 Digenic nature of wilt resistance K 850 and C 104 each carry independent recessive allele

Upadhyaya et a / . (1983a) Upadhyaya et al. (1983b) Singh et a/. ( 1986) Singh et al. (1987)

appears to differ from WR-315 and CPS-1 by a single locus, which results in delayed wilting when in homozygous recessive form. The same researchers also suggested that data are consistent with the hypothesis that JG-62 carried the two genes in a homozygous dominant condition ( H I H I H2 H2); C-104 is homozygous recessive at the second locus (HI H I h2 h2); and the resistant parents (WR-3 15, CPS-1, BG-212, and P-436-2) are homozygous recessive at both loci (h, h l h2 h2). Singh et af. (1987) reported that K-850 carried a recessive gene that is different than and independent of the gene in C-104 and that the two together confer complete resistance. Thus, K-850, like C-104, is a late-wilting cultivar. Early wilting is partially dominant over late wilting. They concluded that at least two loci control resistance to race 1. Unpublished data from H. Singh suggests that a third locus may be involved. Singh et af. (1988) have found a digenic nature of wilt resistance with epistasis. Clearly, the inheritance of resistance to Fusarium wilt is not simple. All studies at ICRISAT Center have been made against race I of F . oxysporum f.sp. ciceri. The existence of at least four races has been reported from India (Haware and Nene, 1982). The situation may be complicated further if a study is made against two or more races. Further, resistant plants have

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been recovered from crosses between two susceptible parents, indicating a complementary type gene action (Singh et al., 1987). Singh and coworkers have suggested that chickpea germplasm may be classified in three categories: early wilter, late wilter, and resistant. d . Breeding for Fusarium Wilt Resistance. Recognizing the severity of wilt in Myanmar, McKerral(l923) evaluated a large number of Burmese and introduced collections for resistance to wilt and yield. Based on resistance and superior yield performance, he released a cultivar, Karachi, which was subsequently grown extensively. While reviewing 50 years of progress in pulse research in Bombay state of India, Chavan and Shendge (1957) described the development of four wilt-resistant cultivars: Dohad206-8, Dohad-1597-2-1, ChaffaTr. 1-7, and Nagpur Tr. 1-2. These cultivars produced more seed yield than Chaffa in fields infested by the wilt pathogen, but produced less seed yield than Chaffa in wilt-free fields. This was a common feature of all resistant lines developed in the early years of breeding. As a result, wilt-resistant cultivars never became popular with farmers. In Pakistan, Khan (1954) developed C 612 from an F 8 x C 144 cross. This cultivar had the same yield potential as previously released cultivars. Breeding for wilt-resistant cultivars in India was a discontinuous effort (Singh, 1974). Singh summarized the work on breeding for wilt resistance carried out between 1943 and 1953 and stated that, in the absence of an efficient screening technique, only limited progress was made. G 24, a cultivar from Punjab, India, was reported to be resistant to wilt. Singh listed 17 lines that were reported resistant in India up to 1974. Kanpur (India) has the distinction of being the first place in the world where a wilt-sick plot was established (Singh et al., 1974). Several hundred lines were screened in this nursery and 12 lines were identified as resistant. Of these, strain Nos. 100, 101, 106, and 6002 were crossed with high-yielding lines T I , T2, and T3, and promising lines were developed. Outside the Indian subcontinent, Mexico is the only country where concentrated wilt-resistance breeding has been practiced. Singh (1987) reviewed work conducted in Mexico and reported that three large-seeded kabuli chickpea cultivars, Surutato 77, Sonora 80, and Santo Domingo, were bred following the hybridization technique; a wilt-sick plot established at Culiacan in 1960 was utilized. Later, the wilt-sick plot was found to be infested with other soil-borne diseases and viruses (I. W. Buddenhagen, personal communication). Despite progress made in resistance to wilt, confusion existed in the identity of the causal organism of wilt disease. To tackle this problem, a

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199

symposium on gram (chickpea) wilt was organized in 1973 at New Delhi and the recommendations were summarized by Jain and Bahl(1974). The need to distinguish the differences between wilts caused by pathogens and wilts caused by environmental factors was stressed. It was clear that as late as 1973, the mystery of the wilt complex remained unresolved, an indication that whatever progress made until then was not based on sound scientific knowledge. The work of Nene et al. (1978) at ICRISAT, India, resolved the mystery of the wilt complex. Wilt, it was clearly suggested, is caused by several distinct pathogens and not by environmental factors. Among the pathogens, wilts and a number of root rot and stem rot diseases were separated out. This work helped put Fusarium wilt-resistance breeding on a sound scientific footing. Since 1980, wilt-sick plots have been established at many research centers including ICRISAT Center and Ludhiana (India), Faisalabad (Pakistan), Beja (Tunisia), Santella (Spain), Debre-Zeit (Ethiopia), and the Central Valley (California, U.S.A.). The establishment of wilt-sick plots in these and other places has facilitated planned breeding programs and led to the breeding of a number of high-yielding, wilt-resistant cultivars. Singh (1987) listed chickpea cultivars released up to 1984; Table Ill presents an updated list of resistant released cultivars. Fusarium wilt-resistant cultivars have been bred by researchers in many countries (Table HI), but they have seldom been grown on a large scale by farmers for two reasons. First, Fusurium wilt incidence in the field is usually associated with other soil-borne diseases. Wilt-resistant cultivars are thus affected by other soil-borne diseases. Second, most breeders have developed race-specific resistant genotypes, whereas different races of F. oxysporum f.sp. ciceri have been identified from various locations within countries (Haware and Nene, 1982; Jimenez Diaz et al., 1989). This suggested that breeders and pathologists should consider a different strategy. First, they should pyramid genes for resistance to different races in one line for use in hybridization programs. Second, soil-borne disease-sick plots should be developed rather than wilt-sick plots as in the past. In the soil-borne disease-sick plot, pathologists could then incorporate in the plot pathogens of Fusurium wilt, root rots, and other soil-borne diseases, including nematodes, that are prevalent in the region. To some extent, this is being done at ICRISAT. Sick plots for wilt and dry root rot have been developed. Pathologists and breeders together should screen germplasm lines in the soil-borne diseases-sick plot, identify sources of resistance, and use these in hybridization programs to breed resistant lines.

200

K. B. SINGH AND M. V. REDDY Table 111 List of Disease-Resistant Cultivars Released between 1923 and 1989"

Country

Disease

Cultivar

Algeria Bangladesh Bulgaria Chile Cyprus France India

Blightb Unspecified Blight Root rot Blight Blight Blight

ILC 482, ILC 3279 Sabour-4, Fatehpur-l , Bhaugora Plovdiv 19, Obraztsov, Chijlik-I. Plovdiv 8 California-INIA, Guasos-SNA Yialousa, Kyrenia TS 1009, TS 1502 F 8, C 12/34, C 235, G 543, Gaurav, BG 261, GNG 146, PBG I C 612, S 26, G 24. C 214, G 130, H 208, H 355, G L 769, Pusa 212, Pusa 244, Pusa 256, Pusa 408, Pusa 413, Pusa417, JG 315, Avrodhi Califfo, Sultan0 Janta 2 Surutato-77, Sonora-80, Santo Domingo ILC 195. ILC 482 Karachi F 8, C 12/34, C 235, C 727, CM 72, C 44. AUG 480 C 612 Elmo, EIvar Alcazaba. Almena, Atalaya, Fardan, Zegri Ghab I . Ghab 2 Chetoui, Kassab Amdoun 1 ILC 195, Guney Sarisi 482, Damla 89, Tasova 89 Mission UC IS, UC 27 Alpha, Mugucii, Skorospelka, Vir 32, Nut Zimistoni

Wilt'

Italy Lebanon Mexico Morocco Myanmar Pakistan Portugal Spain Syria Tunisia Turkey U.S.A. U.S.S.R

Blight Blight Wilt Blight Wilt Blight Wilt Blight Blight Blight Blight Wilt Blight Root rot Wilt Blight

From Nene er a/. (1989a). Ascochytn blight. Mainly Fusariurn wilt.

2. Verticillium Wilt (Verticillium albo-atrum Reinke h Berth) Verticillium wilt has been reported from Pakistan, Tunisia, and the United States. Both Fusarium and Verticilliurn wilts were found to occur in the same field and plant in Tunisia. Verticillium wilt is difficult to distinguish from Fusarium wilt, based on symptoms. Sources of resistance to Verticillium wilt have been reported from Tunisia (Halila and Harrabi, 1987).

BREEDING DISEASE RESISTANCE IN CHICKPEA

20 1

3. Dry Root Rot [Rhizoctonia bataticola (Taub.) Butler = Macrophomina phaseolina (Tassi)Goid.]

Dry root rot is the most important and widely spread root rot affecting chickpea. Though infection can occur in the early stages of growth, maximum disease expression occurs from podding time onwards. The maximum disease incidence usually coincides with moisture stress and high temperature (>30"C), stresses that are favorable for disease development. Under field conditions, the disease is manifested as scattered dead plants, whereas wilt appears in patches. The root system of diseased plants shows extensive rotting with most of the lateral roots destroyed. Affected roots are brittle, and there is shredding of the bark. Sclerotial bodies of the fungus sometimes can be seen on the surface of the root or inside the wood. Susceptibility of chickpeas to dry root rot increases with age. At ICRISAT, screening numerous germplasm lines in a wilt and root rot nursery helped identify a few chickpea lines, such as ICC 2862 and ICC 4023, having resistance to wilt and tolerance to dry root rot. In spite of extensive root rotting, these lines do not die until maturity. High levels of resistance may be difficult to develop as the pathogen has a very wide host range. Both wilt and dry root rot infections can be found in the same plant in wilt and root rot-sick plots at ICRISAT and Beja, Tunisia. Monogenic dominance was found to confer resistance to dry root rot (Ananda Rao and Haware, 1987).

4 . Other Root and Stem Rots

Collar rot (Sclerotium rolfsii Sacc.), wet root rot (Rhizoctonia solani Kuhn), black root rot [Fusarium solani (Mart.) Appel & Wr.], stem rot [Sclerotinia sclerotiorum (Lib.) de Bary], phytophthora root rot (Phytophthora megasperma Drechs.), pythium root and seed rot (Pythium ultimum Trow), and foot rot (Operculella padwickii Kheshwalla) are the other important soil-borne diseases affecting chickpea. Most of these diseases mainly affect chickpea in the seedling stage when soil moisture is relatively high. Collar rot, wet root rot, black root rot, and stem rot are more widespread than the phytophthora and pythium root rots and foot rot. Collar rot usually affects the crop in the seedling stage; susceptibility decreases with age. High soil moisture, presence of undecomposed organic matter on the soil surface, and high temperatures at sowing time favor disease development. The disease is usually a problem in areas

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K. B . SINGH AND M. V. REDDY

where chickpeas are sown following paddy. Kabuli types are more susceptible than desi types. Diseased plants show yellowing of foliage before death. They develop a cankerous lesion at the collar region, or rotting of most of the root system, which is covered with white mycelial growth and sclerotial bodies. Little research has been conducted on standardization of inoculation techniques, or on identification of resistance sources. Though a few lines are reported to be resistant under field conditions, their resistance under artificial inoculation remains unconfirmed. It may be difficult to obtain high levels of resistance to a fungus such as S. rolfsii having a wide host range. Wet root rot is most likely to attack at the seedling stage, but can affect the crop in advanced stages of growth if the soil moisture level is high. The root system of affected plants shows rotting, which may extend up the stem. In the case of black root rot, affected plants initially show a black cankerous lesion at the point of attachment of cotyledons to the stem. Rotting later extends to the whole root system. Wet, black root rots favor relatively lower temperatures (around 25°C) than those favored by collar rot. Little research has been directed toward inoculation techniques or identification of resistance sources. Stem rot is a problem at higher latitudes where cool, wet weather prevails. Excessive vegetative growth favors its development. The disease may affect the collar region killing the'whole plant, or may affect individual branches. Affected plants or branches turn chlorotic before dying. White mycelial growth and large irregular-shaped sclerotial bodies can be seen on the affected portions of the plant. At present, stem rot is not considered to be a serious disease. However, standardization of inoculation techniques and identification of resistance sources would be useful. Phytophthora root rot has been reported from Argentina, Australia, India, and Spain. Disease symptoms include yellowing and drying of the foliage and decay of the lateral roots and the lower portion of the tap root. Lesions on the remainder of the tap root are dark brown to black and extend to and, in some cases, reach above ground level. The advancing margins of these lesions are often preceded by a reddish-brown discoloration (Vock et al., 1980). Screening tests in Queensland, Australia, have revealed that some lines, such as CPI 56564, have field resistance. India, Iran, Turkey, and the United States have reported pythium root rot and seed rot, but it is particularly a serious problem in the Palouse region, Washington, U.S.A. The disease is more common in kabuli types than in desi types. Seed rotting is usual. The fungus is pathogenic to the roots of chickpea seedlings, which become stunted. Larger roots are

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203

necrotic and are devoid of feeder rootlets. Affected plants frequently die before flowering (Kaiser and Hannan, 1983). Foot rot is reported only from India. The disease appears under wet soil conditions. Aboveground symptoms are similar to those of wilt; rotting of the root is evident from the collar region downward. Internal discoloration appears above the rotten portion, but this discoloration is brown and does not involve the pith as do Fusarium and Verticillium wilts (Nene et al., 1978).

B. FUNGAL DISEASES: FOLIAR Foliar diseases seriously limit chickpea yields in several important chickpea-producing countries. Foliar diseases occur in areas (20"-40" latitude) that are otherwise highly suited to chickpea production. These areas usually receive winter rains during the crop season, which benefit crop growth but promote foliar diseases. Lack of precipitation eliminates the foliar diseases problem, but reduces yields due to drought. A relationship between chickpea yields and Ascochyta blight is shown in Fig. 1. Foliar diseases control is a prerequisite for increasing chickpea yields in these regions. The most important foliar diseases are Ascochyta blight [Ascochyta rabiei (Pass.) Labr.], Botrytis gray mold (Botrytis cinerea Pers. ex. Fr.), Alternaria blight [Alternaria alternata (Fr.) Kiessler], rust [Uromyces ciceris-arietini (Grogn.) Jaj & Beyer], and Stemphylium blight [Stemphylium sarciniforme (cav.) Wilts.] (Table IV). Among these, Ascochyta blight occurs in slightly cooler (20°C) environments than the other diseases (25°C). While rain is essential for infection and spread of Ascochyta blight, the other foliar diseases can develop in its absence if high humidity is created in the crop canopy by irrigation, heavy dew, high soil moisture, or excessive vegetative growth.

Chickpea

No rains No blight

Low yield

FIG. 1. Relationship between chickpea yield and Ascoch.vra blight.

K. B. SINGH AND M. V. REDDY

204

Table 1V Important Foliar Fungal Diseases of Chickpea and Their Distribution" Disease

Causal organism Ascochyta rabiei (Pass.)

Ascochyta blight

Lab. (Mycosphaerella rabiei

Kovachevski)

Botrytis gray mold

Botrytis cinerea Pers. ex

Alternana blight Stemphylium blight Rust

Alternaria alternata (Fr.)

Fr.

Countries where prevalent Algeria, Australia, Bangladesh, Bulgaria, Canada, Colombia, Cyprus, Egypt, Ethiopia, France, Greece, Hungary, India, Iran, Italy, Jordan, Lebanon, Mexico, Morocco, Pakistan, Portugal, Romania, Spain, Sudan, Syria, Tanzania, Tunisia, Turkey, U.S.A., U.S.S.R. Argentina, Australia, Bangladesh, Canada, Colombia, India, Nepal, Pakistan, Spain, Turkey, U.S.A. Bangladesh, India, Nepal

Kiessler Stemphylium sarciniforme

Bangladesh, India, Iran, Syria

(Cav.) Wills Uromyces ciceris-arietini

(Grogn.) Jacz & Beyer

Algeria, Afghanistan, Bulgaria, Chile, Cyprus, Ethiopia, France, India, Iran, Lebanon, Libya, Malawi, Mexico, Morocco, Nepal

From Nene et al. (1989a).

1 . Ascochyta Blight [Ascochyta rabiei (Pass.)Labr.]

a . General Description of Disease. Ascochyta blight is by far the most destructive disease of chickpea. It is particularly serious in India, Pakistan, and the countries around the Mediterranean Sea. i t does not occur every season, but usually in cycles of about 5 years. Once it does occur, it continues for 2-3 years. The disease usually appears in epiphytotic form from the flowering stage onwards when temperatures are optimum for blight infection and development. Earlier in the season, temperatures are too low for disease development. The disease initially appears in small patches and, under favorable conditions (15 to 25"C, rains accompanied by winds and cloudy days), spreads very rapidly. Rain splash helps spread the disease. Figure 2 shows the relationship between temperature, humidity, and Ascochyta blight. When both temperature and relative humidity are optimum, Ascochyra blight develops in epiphytotic form. The disease affects all aboveground parts of the plant. If the infection

BREEDING DISEASE RESISTANCE IN CHICKPEA

205

Temperature

"c

Blight severity

Humidity (RH%)

FIG.2. Relationship between temperature, humidity, and chickpea Ascochyra blight at Tel Hadya, Syria, 1982-1983.

occurs through seed-borne inoculum, the seedlings show brown cankerous lesions at the collar region before they collapse. Symptoms on leaves and pods are circular spots with pycnidia of the fungus usually arranged in concentric rings. On stems, the lesions are elongated and, when the lesions engirdle the stem, portions above the lesions either dry up or break off. The pathogen infects seed and sometimes causes deep cankerous lesions. Despite 50 years of efforts to manage the disease, Ascochyra blight continues to cause heavy losses. In Pakistan during the 1979-1980 season, the disease caused about 50% yield loss (Malik and Tufail, 1984), while in India during the same period, it was estimated to have destroyed the crop on about one million hectares. The perfect state of the fungus (Mycosphaerella rabiei Kovachevski) is reported from a few chickpea-growing countries-Bulgaria, Greece, Hungary, Syria, the United States, and the Soviet Union (Gorlenko and Bushkova, 1958; Haware, 1987; Kaiser and Hannan, 1987; Kovachevski, 1936; Kovics et al., 1986; Zachos et al., 1963). The epidemiology of the disease is not clearly understood. Infected seed and diseased debris have long been known as primary sources of inoculum. In the United States, ascospores were found to play an important role in disease survival and spread (Kaiser and Muehlbauer, 1988).

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Studies indicate that the blight pathogen is highly variable. Variation in the pathogen has been reported from all the major chickpea-growing countries such as India, Pakistan, Syria, and Turkey (Acikgoz, 1983; Bedi and Aujla, 1970; Qureshi, 1986; Reddy and Kabbabeh, 1985; Vir and Grewal, 1974). Frequent changes in pathogen virulence have resulted in a breakdown of resistance of several cultivars. There is further need for standardization of the method for race identification in Aschocyta rabiei. b. Sources of Resistance. Efforts have considerably increased during the past 15 years to identify resistance sources and to breed resistant cultivars. Efficient inoculation techniques for use in greenhouse and field have been standardized. Inoculating plants grown in pots, bags, or trays and covering them with polyethylene or cloth bags or cages for 24-48 hr results in good infection. Temperatures congenial for infection range from 15 to 25°C. Presence of a moisture film on the leaf surface is essential for infection. In the field, inoculation by scattering diseased debris or spraying a spore suspension over plants followed by sprinkler irrigation results in a high and uniform disease level (Reddy et al., 1984). Rating scales for scoring disease severity have been standardized. Available chickpea germplasm has neither high nor stable resistance to all the prevalent races of A. rabiei (Singh et a f . ,1984). In general, pods are more susceptible than vegetative parts. Lines such as PK 5 1836 x NEC138-2 show resistance in the vegetative stage against a wide range of isolates, but are not resistant to pod infection. Several lines with foliage resistant to isolates prevalent in the countries around the Mediterranean Sea have been identified (Singh et a f . , 1984; Reddy and Singh, 1984). Through the Chickpea International Ascochyta Blight Nursery, resistant lines have been evaluated in blight-prone areas between 1979 and 1989 and a few lines with broad-based resistance have been identified. These include kabuli types (ILC 72, ILC 182, ILC 187, ILC 196, ILC 200, ILC 202, ILC 2506, ILC 2956, ILC 3279, ILC 3346, ILC 3866, ILC 3868, ILC 4421) and desi types (ICC 5035, ICC 5566, ICC 6304, ICC 7028, Pch 70, NEC 138-2) (K. B. Singh and M. V. Reddy, unpublished data). However, there are no lines in India and Pakistan that have a high and stable level of resistance. Most of the lines that showed resistance in the vegetative and podding stages in the Mediterranean region are tall, erect, and late maturing. Preliminary studies carried out at ICARDA in Syria showed that when plants of these lines had their stems bent over mechanically, some developed a higher level of infection on pods. c . Genetics of Resistance to Ascochyta Blight. Reported inheritance studies results indicate that resistance is conferred by either a single

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dominant gene or a single recessive gene (Table V). Allelic studies by Tewari and Pandey (1986) indicated the presence of three independent dominant genes in EC 26446, P 1252-I , and PG82- 1. Similarly, Halila et al. (1989) found that ILC 182, ILC 191, and ILC 482 had an independent dominant gene, though Singh and Reddy (1989) found through allelic tests that the same dominant resistant gene was present in ILC 72, ILC 202, ILC 2956, and ILC 3279. The variations in reaction of four resistant lines, when tested in 13 countries and against six races ofA. rabiei, appeared to be due to the presence of some other resistance genes in addition to a common gene. All inheritance studies have been made in the field or against a single isolate or race of a given country. Further, genotypic reactions at the seedling and podding stages of the plant vary. Temperature and relative humidity also influence disease reaction. Duration of favorable disease development conditions also influences disease reaction. d . Breeding for Ascochyta Blight Resistance. Ascochyra blight resistance breeding began in the 1930s in India and the Soviet Union. The first resistant desi cultivar, F 8, was released 50 years ago in India (Luthra et al., 1941). This line was a selection from an introduction of material from France. In the Soviet Union, three cultivars-Skorospelka, Alpha, and

Table V Inventory of Inheritance of Resistance to Ascochyfa Blight (Ascochyfa rubiei) in Chickpea Nature of inheritance

Genotype

Single dominant gene Single dominant gene Single dominant gene Single dominant gene

F 8, F 10 1-13 Code No. 72-92 ILC 72, ILC 183, ILC 200. ICC 4935 ILC 191 ILC 200, ILC 201 72012, ILC 195, NEC 138-1 EC 26446, PG 82-1 P 919, P 1252-1, NEC 2451 BRG 8 ILC 72, ILC 202, ILC 2956, ILC 3279 ILC 182, ILC 191, ILC 482 ILC 195

Single recessive gene Single dominant gene Single recessive gene Single dominant gene Single recessive gene Single dominant gene Single dominant gene Single recessive gene

References Hafiz and Ashraf (1953) Vir e r a / . (1975) Eser (1976) Singh and Reddy (1983)

Acikgoz (1983) Tewari and Pandey (1986)

Singh and Reddy (1989) Halila ef al. (1989)

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Mogucii-were developed, following a complex hybridization technique, and were released in 1946 (Guscin, 1946). Later, a hybridization technique was adopted in India and Pakistan and several cultivars released. Table I11 lists resistant cultivars. Until 1984, no Ascochyta blight-resistant cultivar was released in the Mediterranean region where Ascochyta blight is the most serious disease. Cultivars released in India, Pakistan, and the Soviet Union never became popular with farmers, with the exception of C 235. One of the main reasons for their unpopularity was that they yielded less than susceptible cultivars during the disease-free years, and disease-free years are more frequent than blight years. Two other factors contributed to the lack of sustained breeding work: resistant cultivars soon became susceptible due to the occurrence of new races of A . rabiei, and a reliable and simple screening technique, which could be adopted by breeders to evaluate large segregating populations, was lacking. The ICRISAT-ICARDA Kabuli Chickpea Project was established in 1978 at ICARDA, Syria. The project helped to develop an easy, reliable screening technique (Singh et al., 1981), which was further refined by Reddy ef at. (1984). Using this screening technique, more than 15,000 germplasm accessions maintained at ICARDA and ICRISAT were evaluated and a large number of resistant lines were identified. Many of the original accessions were mixtures of resistant and susceptible plants; these were purified and assigned new accession numbers. Resistant lines were evaluated for yield potential on the ICARDA farm, and high-yielding lines were provided to national programs. Hybridization work also was initiated in 1978to combine high yield with resistance to Ascochyta blight. Using off-season advancement facilities, more than 900 Ascochyta blight-resistant and high-yielding lines were bred between 1981 and 1989 and freely shared with national programs. Eleven countries released 26 cultivars from these materials between 1984 and 1989. This rapid progress was possible in the 12-year period because Ascochyta blight-resistant segregating populations were grown on an 8-ha plot each year during the main season, and three generations (FI, F3, F6/F7) were advanced in the off season on a 4-ha plot each year. The bulk-pedigree method to breed Ascochyfa blight-resistant chickpeas at ICARDA is shown in Fig. 3. In addition to resistance to Ascochyta blight, this method is designed to breed photoperiod-insensitive chickpeas with resistance to other stresses. ICARDA research had a catalytic effect on national programs. Now Ascochyta blight resistance breeding work has been launched in the Mediterranean region, India, Pakistan, and the United States. Many countries

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4

pq-bGM>04p] 1-

7 FIG. 3. Bulk-pedigree method for breeding chickpeas resistant to Ascoclivto blight and other stresses. MS. Main season; 0s. off season.

have developed resistant lines and may soon release them for commercial cultivation. Table 111 lists the release of resistant cultivars. Several new problems emerged after the initial success in breeding for Ascochyta blight-resistant chickpeas. Most of the previously released cultivars have succumbed to new races; the life span of resistant cultivars has been short. No cultivar has been developed with resistance to all known races. Some strategies for development of durable blight-resistant cultivars are discussed here. 1 . Pyramiding multiple gene resistance. Eight lines (ILC 72, ILC 201, ILC 202, ILC 2506, ILC 2956, ILC 3279, ILC 3856, and ILC 5928), are resistant to 4-5 races out of 6 races prevalent in Syria and Lebanon (Singh and Reddy, 1990). Since none of the lines was resistant to all 6 races, an attempt is being made to combine genes that will confer resistance against all 6 races in one line. A similar effort is being made at Ludhiana, India (G. Singh, personal communication). Lines with resistance to all existing races in a given country or region would be very useful in a breeding program.

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2. Polygenic resistance. Although most published work on genetics of resistance to Ascochyta blight in chickpea suggests monogenic resistance, there are indications in at least some parents that the inheritance of resistance is governed by polygenes. If this is true, then breeding for partial resistance should be considered. 3 . Release of more than one cultivar in each country. Release of several cultivars, possibly with known reactions to different races, will be useful; if resistance breaks down in one cultivar, others are then available to farmers. Morocco is an example. ILC 195 and ILC 482 were released in 1987; ILC 482 became susceptible in 1989 and was withdrawn; and now Moroccan farmers are cultivating ILC 195. 4. Withdrawal of susceptible cultivars from cultivation. Once resistant cultivars are released, even though their resistance may be weak, farmers should be advised to stop cultivating susceptible cultivars. This will reduce the build-up and spread of the disease. Earlier, when a susceptible check was included in all ICARDA yield trials grown in Jindiress (Syria) and Terbol (Lebanon), Ascochyta blight infected the susceptible checks and spread to other lines almost every year. After this practice was stopped in 1986, the disease has been seen only once in 4 years. 5 . Mapping of races. There is a pressing need to map the existing races in the world. This will assist breeders to develop resistant cultivars suited to different regions.

No single strategy in breeding for Ascochyta blight-resistant cultivars may succeed, so a combination of different strategies should be employed. Genes conferring resistance to blight in wild Cicer species should be transferred to cultivated species. Likewise, mutation techniques could be used to develop higher levels of resistance. Breeders and pathologists working on blight resistance should meet periodically to discuss strategies to control Ascochyta blight disease. 2. Botrytis Gray Mold (Botrytis cinerea Pers. ex Fr.) Botrytis gray mold is the second most important foliar disease after Ascochyta blight. The disease occurs on a regular basis, but damage is greatest in years of extensive winter rains and high humidity. The extent of losses due to this disease has not been precisely estimated. In Nepal, visual estimations during the 1987-1988 season indicated about 40% loss (Reddy et al., 1988). Only limited research has been conducted on this disease whose importance has been recognized only recently. The disease is visible in the field from flowering stage onwards.

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The disease affects all aboveground parts, producing brown necrotic lesions on leaves, stems, flowers, and pods. Seeds are also infected and, under certain conditions, the crop killed. Sporulation of the fungus can be seen on affected parts in the morning hours when dew is present. Many times, without any apparent symptoms on leaves and stems, the disease can cause flowers to drop, resulting in poor pod set. This type of damage usually goes unnoticed. Plants produce few pods at the upper nodes late in the season when conditions become unfavorable for the disease. It results in extended duration of the crop. Close planting, excessive vegetative growth, early sowings, and irrigation favor disease development of Botryris gray mold. Limited screening of germplasm and breeding material in “hot-spot’’ locations in India and Nepal has failed to identify high levels of resistance. There are a few lines, such as ICC 1069, ICC 6250, ICC 7574, and ICC 10302, which show field tolerance under moderate levels of disease (Rathi et al., 1984; Sahu and Sah, 1988). Chickpeas are more susceptible in the flowering stage than in the vegetative stage. A few reports indicate variation in the pathogen B . cinerea (Singh and Bhan, 1986). Laboratory inoculation techniques and rating scales need to be standardized. Inheritance of Botrytis gray mold resistance was studied in the resistant line ICC 1069. When ICC 1069 was crossed with BGM 413 and BG 256, monogenic dominance conferred resistance, but when ICC 1069 was crossed with BGM 419 and BGM 408, a ratio of 13 susceptible : 3 resistant was obtained indicating the presence of epistatic interactions. Thus, major gene resistance was found for Botrytis gray mold disease in chickpea (Rewal and Grewal, 1989). Botrytis gray mold is a highly devastating disease in certain years and regions, and a breeding program has been recently initiated jointly by ICRISAT and Pant University of Agriculture and Technology in India. No resistant cultivars have been released so far.

3 . Alternaria Blight [Alternaria alternata (Fr.)Kiessler] Alternaria blight, though not very widespread, occurs in Bangladesh, India, and Nepal. It has been reported to be serious in parts of northeast India in certain seasons and usually occurs along with Botryris gray mold and Stemphyfium blight as the conditions favoring these diseases are similar. Necrotic lesions are produced on all aboveground parts. In severe cases, the disease causes defoliation. A few lines, tolerant under field conditions, have been reported, but their resistance to artificial inoculation is yet to be confirmed.

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4 . Stemphylium Blight [Stemphylium sarciniforme (Cau.) Wilts] Stemphylium blight has been reported in Bangladesh, India, Iran, and Syria and is particularly serious in parts of Bangladesh. Kabuli-type genotypes with a compact and erect canopy appear to suffer less from the disease than desi, spreading types. The disease is also favored by high humidity within the crop canopy.

5 . Rust [Uromyces ciceris-arietini (Grogn.)Juj & Beyer] Rust, a very widespread disease occurring in almost all chickpeagrowing countries, is not considered to be important, as it occurs late in the season when the crop is maturing and does not cause significant losses. However, in some years it causes yield loss in Ethiopia and Mexico. It produces brown or black powdery pustules on leaves and stems. Cool, humid weather favors its development. C. VIRAL DISEASES Though as many as 16 viruses are known to infect chickpea, only stunt caused by bean (pea) leaf roll virus is economically important at present. This virus belongs to the luteo virus group. It is prevalent in most of the chickpea-growing countries. Stunting, browning (desi types), or yellowing (kabuli types), and thickening of the foliage and phloem browning are the characteristic symptoms of the disease. It has a wide host range and is transmitted by aphids such as Aphis craccivoru Koch. and Acyrthosiphon pisum (Harris). The first symptoms of the disease in the field are noticed a month after sowing; plants affected early may wilt before maturity. Diseased plants produce few pods. The virus is not seed borne. Diseased plants are usually scattered in the field. Extensive screening of germplasm and breeding materials at Hissar, northern India, a hot-spot location for the disease, revealed quite a few lines, such as ICC 403, ICC 591, ICC 685, ICC 2385, ICC 2546, ICC 3718, ICC 4949, ICC 6433, ICC 10466, ICC 10596, and ICC 1 1 155, to have field resistance. Desi types are comparatively less susceptible than kabuli types. Early sowing and wide spacing were found to increase disease incidence at Hissar. Most of the cultivars bred in northern India, such as L 550, G 130, and JG 62, are tolerant to the disease. The high natural incidence of the disease in these areas might have inadvertently aided

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selection of resistant plants. Breeding efforts to develop virus-resistant, high-yielding lines are under way at ICRISAT Center, India.

D. NEMATODE DISEASES Though more than 50 nematodes are known to infect chickpea, only a few are economically important. Work on nematode diseases has been very limited; more research is needed to obtain a clear picture of nematode problems. Root-knot, cyst, and lesion nematodes are relatively more important than the others.

1 . Root-Knot Nematodes Meloidogyne incognita (Kofoid and White) Chitw., M . jauanica (Treub) Chitw., and to a lesser extent, M. arenaria (Neal) Chitw., are of importance in the Indian subcontinent, Egypt, and Malawi, along with M. artieflia Franklin in the Mediterranean area. Infected roots show characteristic galls whose size depends upon nematode species and plant cultivar. The first three of these species have wide host ranges, including wild plant species. These species prefer hot weather and can cause serious problems in regions where summers are long and winters are short and mild, such as peninsular India. However, severe damage also occurs in north India and in the Terai region of Nepal where minimum temperatures fall below 15°C for many days during the winter crop season. Meloidogyne artiellia can infect chickpea even at soil temperatures below 15°C (Di Vito and Greco, 1988). Galls caused by this nematode are small, or may be absent with the only visible symptoms on infected roots being egg masses. These can be seen by early April on roots of winter chickpea. Meloidogyne artiellia survives during dry seasons as anhydrobiotic second-stage juveniles. Its host range is confined to cereals, legumes, and crucifers. Spring chickpea is more susceptible to M . artiellia than winter chickpea, the tolerance limits being 0.016 and 0.014 eggs/cm3 of soil, respectively. Complete crop failure occurs in fields infected with more than 1 egg/cm3of soil (Di Vito and Greco, 1988). Although M . artiellia is widespread in the Mediterranean area, severe damage to chickpea has been reported only from Italy, Spain, and especially Syria.

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2. Cyst Nematodes

The chickpea cyst nematode, Heterodera ciceri Vovlas, Greco, and Di Vito, has been reported from northern Syria and is the only cyst nematode that causes severe damage to chickpea. It develops when the soil temperature rises above 10°C. Cysts are evident from late April onwards and can persist in soil for several years (Greco et al., 1988). Infected roots show small necrotic spots from which females later emerge. Heterodera ciceri causes damage whenever its population density exceeds 1 egg/g' of soil (Greco et al., 1988); complete crop failure occurs where there are over 64 eggs/g' of soil. Its host range is, however, rather narrow compared to root-knot nematodes. Other good hosts are lentil, pea, and grass pea. 3. Root-Lesion Nematodes Among root-lesion nematodes, Pratylenchus thornei Sher and Allen is distributed worldwide and damages chickpea in Syria and India. Other Pratylenchus spp. ( P . zeae, P . brachyurus) are also common on legumes and may infect chickpea as well. They cause cavities within the cortical parenchyma. Infected roots show many necrotic segments. Even though P . thornei seems to develop better from late winter to early spring, lesion nematodes are adapted to a large range of environmental conditions and have wide host ranges. Damage caused by P . thornei is less impressive than that caused by the previous two species, but the tolerance limit of chickpea to this species has not been determined in the field. 4 . Sources of Resistance to Nematodes

At ICARDA, Syria, 8,200 chickpea accessions have been evaluated up to April 1990, but no source of resistance was found (Di Vito et al., 1988; K. B. Singh, M. Di Vito, N. Greco, and M. C. Saxena, unpublished). However, when 137 accessions of eight wild Cicer species were evaluated, 21 accessions of C. bijugum K. H. Rech. were found resistant to cyst nematode (Singh et al., 1989a). In recent screening, five accessions of C . pinnat$dum Jaub & Sp. and one accession of C. reticulatum Ladiz. were found to be resistant. Efforts are under way to transfer the gene for resistance to the nematode from C. reticulatum to a high-yielding line of C. arietinum.

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Strain No. 501 has been identified as resistant to root-knot nematode (Mani and Sethi, 1984). Several mutants resistant to root-knot nematode have been developed (Bhatnagar et al., 1988). Despite identification of resistance sources, planned hybridization work to transfer the gene for resistance to high-yielding lines has yet to be undertaken.

E. BREEDING FOR RESISTANCE TO OTHERDISEASES Diseases other than Ascochyta blight and Fusarium wilt are only of localized importance, and include Botrytis gray mold, rust, stunt, Phytophthora root rot (Phytophrhora megasperma f.sp. medicaginis), and two nematodes (root-knot and cyst). Some progress has been made toward development of cultivars resistant to Botrytis gray mold disease and to stunt (pea leaf roll virus) at ICRISAT, India (Nene and Reddy, 19871, Phytophthora root rot in Australia (Brinsmead, 1985), cyst nematode at ICARDA, Syria (Di Vito et al., 1988; Singh, et al., 1989a), and root-knot nematode at ICRISAT, India (Sharma and Mathur, 1985).

V. BREEDING FOR MULTIPLE DISEASE RESISTANCE Disease-resistant cultivars of chickpea have never been grown widely, mainly because they lack resistance to all the important diseases of a country or region. Singh et al. (1991) have strongly advocated the breeding of cultivars with resistance to all the important diseases of a country, and have also suggested that attempts should be made to breed cultivars with multiple stress resistance. For north Africa, cultivars with resistance to Ascochyta blight and Fusarium wilt are required. If cultivars are resistant to only one disease they will not be grown extensively. In west Asia, Ascochyta blight and cold-tolerant cultivars are required for winter sowing of chickpea, where the crop is traditionally grown in spring. In south India, cultivars with resistance to pod borer (Helicouerpa spp.) and Fusarium wilt are required. Since the mid 1980s, attempts have been made to breed cultivars with multiple disease resistance. It is hoped that in the 1990s cultivars with multiple stress resistance will be bred and released. Singh et al. (1991) have listed important diseases and insect pests in different regions. This list needs to be expanded to include other stresses; the multiple stress-

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resistant accessions of wild Cicer species, described in the succeeding section, will be useful in breeding.

VI. ANNUAL WILD ClCER SPECIES AS A POTENTIAL SOURCE OF GENES FOR RESISTANCE Forty-three Cicer species, including 9 annual and 34 perennial types, have been reported (van der Maesen, 1987). Since maintenance of perennial species is difficult, scientists other than germplasm botanists are mainly interested in annual species. ICARDA holds 233 accessions of 8 wild Cicer species and ICRISAT maintains 97 lines of both annual and perennial wild species. When accessions maintained at ICARDA were evaluated for resistance to Ascochyru blight, Fusurium wilt, and cyst nematode, higher levels of resistance than any available in cultivated species were found for the two diseases, as well as the only known source of resistance to cyst nematode (Table VI). Wild Cicer species have been investigated for resistance to diseases. Cicer juduicum was found resistant to Ascochyta blight, Fusarium wilt, and Botrytis gray mold (van der Maesen and Pundir, 1984). Nene and Haware (1980) also found C . judui-

Table VI Evaluation of Cicer spp. for Resistance to Ascochyta Blight, Fusarium Wilt, and Cyst Nematode, at Tel Hadya, Syria, 1987-1989" Ascochyta blight Cicer species

Mixture of race 1-4

Mixture of race 1-6

Fusarium wiltb

cyst nematode

C. bijugum K.H. Rech. C. chorassanicum (Bge) M. Pop. C . cuneatum Hochst. ese Rich C . echinospermum P.H. Davis C . judaicum Boiss. C . pinnatifidum Jaub. & Sp. C. reticulatum Ladiz. C . yamashitae Kitamura

R S S S R R S S

R

F NT NT F F F F NT

R S S S S R R S

S S S R S S S

F, Free from damage; R, resistant; S, susceptible; NT, not tested. Evaluation was done at Istituto Sperimentale per la Patologia Vegetale, Rome, Italy,

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cum resistant to Fusarium wilt. Singh et a f . (1982) have reported C . pinnat$dum to be resistant to Botrytis gray mold. Accessions of wild species have been evaluated for reaction to six different biotic and physical stresses, and resistance sources have been identified for all stresses including seed beetle (Caffosobruchuschinensis L . ) and cyst nematode, for which no sources of resistance were found in the collection of cultivated species (Singh et al., 1989b). The most important achievement in evaluation of wild species was identification of genotypes having genes for resistance to four or five stresses. For example: accession No. ILWC 7-1 of C. bijugum is resistant to Ascochyta blight, Fusarium wilt, leaf miner, cyst nematode, and cold; accession No. ILWC 331s-4 of C . pinnatijdum is resistant to Ascochyta blight, Fusarium wilt, seed beetle, and cyst nematode. No accession of the cultivated species has been found to have genes for resistance to more than one stress. Wild species are therefore potentially most important for disease and other stress-resistance breeding. Hence, it is strongly advocated that (1) wild species should be evaluated for other diseases, (2) embryo and ovule rescue techniques should be employed to transfer genes for resistance from noncrossable wild species to cultivated species, and (3) in view of the usefulness of wild species, more collections should be made.

VII. RESISTANT CULTIVARS IN DISEASE MANAGEMENT Chickpea is grown primarily by resource-poor farmers on residual moisture with little if any inputs. The short growing season at lower latitudes (0-20") also limits yields. The fast-rising temperatures at the reproductive phase force the crop into premature drying. Thus, yields are low (less than one t/ha). At present productivity levels, use of disease-resistant cultivars appears to be the best alternative for management of chickpea diseases. Singh ( 1987) listed the disease-resistant cultivars developed in different countries; an updated list is presented in Table 111. Several cultivars are resistant to soil-borne diseases (mostly resistant to Fusarium wilt) and Ascochyta blight. Though cultivars bred for resistance to soil-borne diseases have maintained their resistance, Ascochyta blight-resistant cultivars have shown frequent resistance breakdown due to appearance of new races. As there are no cultivars with high levels of Ascochyta blight resistance, especially when the disease develops in epiphytotic form, tolerant cultivars should be used in combination with other management practices. Seed free of the Ascochyta blight pathogen should be produced under arid

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conditions (Kaiser, 1984) or alternatively, seeds should be dressed with fungicide before sowing (Reddy, 1980). If seed yields of over 2 t/ha are expected, as is generally the case with winter-sown chickpea in the Mediterranean region, then a combination of a tolerant cultivar like ILC 482 and one foliage spray with chlorothalonil (tetrachloroisophthalonitrile)can be beneficial (Reddy and Singh, 1990).

VIII. CONCLUSIONS AND FUTURE NEEDS The disease problems of chickpea are well identified and their distribution and importance are known. Though considerable progress has been made in managing the diseases, more work remains. Among soil-borne diseases there has been encouraging progress on Fusariurn wilt in standardization of inoculum techniques, identification of resistance sources, and understanding the genetics of resistance, variability in the pathogen, and breeding for resistant cultivars. The mechanisms of resistance, however, need to be investigated further. Progress with other soil-borne diseases has been very limited. Standardization of inoculation techniques, identification of resistance sources, and breeding for resistant cultivars all require much more research. As wilt and root rots usually occur together, there is a need to breed cultivars having multiple disease resistance to soil-borne diseases. Progress on the management of foliar diseases during the past 10-15 years, especially through the use of resistant cultivars, has been remarkable. In the case of Ascochyfa blight, effective inoculation techniques and rating scales have been standardized. Some information on the genetics of resistance and on variability in the pathogen have been obtained. Steady progress has been made in identifying resistance sources and in breeding resistant cultivars for countries around the Mediterranean basin. However, progress on identification of resistance sources and breeding resistant cultivars in India and Pakistan has been limited. In these two countries, high, stable resistance levels need to be identified. Though the existing germplasm collection does not appear to have high levels of resistance, there is a significant amount of variability in susceptibility to the disease. A germplasm enhancement program to accumulate available genes for resistance may prove useful. Further studies on genetics of resistance, mechanisms of resistance, and the relationship between plant height, maturity, and resistance will be useful for better exploitation of resistance sources. Research on the other foliar diseases has been very limited. Losses

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caused by these diseases, though yet to be estimated, may be substantial. Work on standardization of inoculation techniques, development of rating scales, and identification of resistance sources to Botrytis gray mold, Alternaria blight, and Stemphylium blight needs to be undertaken. Though field-tolerance sources and cultivars are available for stunt disease (pea leaf roll virus), there is a need to develop cultivars with combined resistance to stunt and major soil-borne and foliar diseases. Nematodes can cause substantial damage to chickpeas; efforts should be made to locate sources of resistance to root-knot, cyst, and lesion nematodes and to incorporate them in disease-resistant backgrounds. Unlike cereals or major grain legume crops such as soybean, diseaseresistant cultivars of chickpea have never been grown widely. The main reason for this is that the yield potential of the resistant cultivars is lower than susceptible cultivars. Second, most released cultivars possess resistance to only one disease, whereas under most situations the chickpea plant is attacked by two or more diseases. Therefore, future breeding programs should attempt to upgrade the yield potential of resistant cultivars to, or above, that of susceptible cultivars, and to combine genes for resistance to the most important diseases prevalent in the region. Wild Cicer species are known to possess genes for resistance to several diseases, but they have never been transferred to cultivated species. Genes for resistance from two species, C . echinospermum and C . reticulaturn, could easily be transferred to cultivated species by normal hybridization techniques. Furthermore, through the use of embryo and ovule rescue techniques, efforts should be made to transfer genes for resistance from the currently noncrossable Cicer species to the cultigens.

REFERENCES Acikgoz, N. 1983. Ege Bolge Zirai Arastirma Enstitusu Yayinlari No. 29 (in Turkish). Ananda Rao, P. K . , and Haware, M. P. 1987. Plant Breed. 98, 349-352. Ayyar, V. R., and Iyer, R. B. 1936. Proc. Indian Acad. Sci. 3,438-443. Bedi, P. S., and Aujla, S. S. 1970. J. Res. (Punjab Agric. Uniu.) 6, 103-106. Bhatnagar, C. P., Handa. D. K., andMisra, A. 1988. Inr.Chickpea News/. No. 19, pp. 16-17. Brinsmead, R. B. 1985. Plant Dis.69, 504-506. Chavan, V. M., and Shendge, P. V. 1957. Poona Agric. Coll. Mag. 48,78-91. Di Vito, M., and Greco, N. 1988. Reu. Nematol. 11,221-225. Di Vito, M., Greco. N., Singh. K. B., and Saxena, M. C. 1988. Nematol. Medit. 16, 17-18. Eser, D. 1976. Ankara Uniu., Ziraar Fak. Yayin. (in Turkish). 620,40 pp. Food and Agriculture Organization. 1988. " F A 0 Production Year Book," Vol. 42. FAO, Rome, Italy. Gorlenko, M. V., and Bushkova, L. N. 1958. Plant Pror. (Moscow)3,60 (in Russian). Greco, N., and Sharrna, S. B. 1991. In "Proceedings of the Second International Workshop

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on Chickpeas” (H. A. Van Rheenen and B. J. Walby, eds.). ICRISAT, Hyderabad, India (in press). Greco, N., Di Vito, M., Reddy, M. V., and Saxena, M. C. 1988. Nemarologica 34,93-114. Guscin, I. V. 1946. Sors. Zernouoe Khoz. 4,35-40 (in Russian). Hafiz, A., and Ashraf, M. 1953. Phyroparhology 43,580-581. Halila, H. M., and Harrabi, M. M. 1987. Plant Dis. 71, 101. Halila, H. M., Harrabi, M., and Haddad, A. 1989. Agric. Med. 119, 148-151. Hanounik, S. B., and Reddy, M. V. 1984. I n “Ascochyra Blight and Winter Sowing of Chickpea” (M. C. Saxenaand K. B. Singh, eds.), pp. 111-116. Martinus Nijhoff/Dr. W. Junk Publishers, The Hague, The Netherlands. Haware, M. P. 1987. Inr. Chickpea Newsl. No. 17, pp. 29-30. Haware, M. P., and Nene, Y. L . 1982. Plant Dis. 66,809-810. Haware, M. P., Kumar, J., and Reddy, M. V. 1980. In “Proceedings of the International Workshop on Chickpea Improvement” ( J . M. Green, Y. L. Nene, and J. B. Smithson, eds.), pp. 67-69. ICRISAT, Hyderabad, India (available from ICRISAT, Patancheru, A.P. 502324, India). Haware, M. P., Jimenez-Diaz, R. M., Amin, K. S., Phillips, J. C., and Halila, H. M. 1991. In “Proceedings of the Second International Workshop on Chickpea” (H. A. Van Rheenen and B. J. Walby, eds.). ICRISAT, Hyderabad, India (in press). Jain, H. K., and Bahl, P. N. 1974. Indian J . Genet. Plant Breed. 34,236-237. Jimenez-Diaz, R. M., Trapero-Casas, A., and Cabrera de la Colina, J. 1989. NATO AS1 Ser., Ser. H 28,515-520. Kaiser, W. J. 1984. In “Ascochyra Blight and Winter Sowing of Chickpeas” (M. C . Saxena and K. B. Singh, eds.), pp. 117-122. Martinus Nijhoff/Dr. W. Junk Publishers, The Hague, The Netherlands. Kaiser, W. J., and Hannan, R. M. 1983. Planr Dis. 67,77-81. Kaiser, W. J . , and Hannan, R. M. 1987. Plant Dis. 71, 192. Kaiser, W. J., and Muehlbauer, F. J. 1988. Inr. Chickpea Newsl. No. 18, pp. 16-17. Kaiser, W. J., Ghanekar, A. M., Nene, Y. L., Rao, B. S., and Anjaiah, V. 1991. I n “Proceedings of the Second International Workshop on Chickpeas” (H. A. Van Rheenen and 8. J. Walby, eds.), ICRISAT, Hyderabad, India (in press). Khan, S. 1954. Agric. Pak. 4, 157-162. Kovachevski, I. C. 1936. Issued by Ministry of Agriculture and National Domains, Sofia, Bulgaria (in Russian). Kovics, G. V., Holly, L., and Simay, E. J. 1986. Acta Phytopathol. Entom. Hung. 21,7-15 (in Hungarian). Kumar, J., and Haware, M. P. 1982. Phytopathology 72, 1035-1036. Ladizinsky, G. 1975. Notes R. Bot. Garden Edinburgh 34, 201-202. Lopez Garcia, H. 1974. Agric. Tee. Mex. 3,286-289. Luthra, J . C., Sattar, A., and Bedi, K. S. 1941. Indian J . Agric. Sci. 11,249-264. Malhotra, R. S., Pundir, R. P. S . , and Slinkard, A. E. 1987. In “The Chickpea” (M. C. Saxena and K . B. Singh, eds.), pp. 67-82. C. A. B. International, Oxon, U.K. Malik, B. A., and Tufail, M. 1984. In “Ascochyta Blight and Winter Sowing of Chickpeas” (M.C. Saxena and K. B. Singh, eds.), pp. 229-235. Martinus Nijhoff/Dr. W. Junk, Publishers, The Hague, The Netherlands. Mani, A., and Sethi, C. L. 1984. Inr. Chickpea Newsl. No. 10, p. 15. McKerral, A. 1923. Agric. J . India 28,608-613. Nene, Y . L., and Haware, M. P. 1980. Plunr Dis. 64,379-380. Nene, Y. L., and Reddy, M. V. 1987. In “The Chickpea” (M. C. Saxena and K. B. Singh, eds.), pp. 233-270. C. A. B. International, Oxon, U. K.

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Nene, Y. L.. Haware, M. P., and Reddy, M. V. 1978. ICRISATlnf. Bull. 3, 1-44. Nene, Y. L . , Haware, M. P., and Reddy. M. V. 1981. ICRISAT lnf. Bull. 10. Nene, Y. L., Sheila, V. K., and Sharma. S. B. 1989a. Legumes Pathol. Prog. Rep. 7. Nene, Y. L., Haware, M. P., Reddy, M. V., Phillips, J. C . , Castro. E. L., Kotasthane, S. R., Gupta, 0.. Singh, G., Shukla, P., and Sah. R. P. 1989b. Indian Phytopathol. 42,499. Pathak, M. M., Singh, K. P., and Lal, S. B. 1975. Indian J. Farm Sri. 3, 10-1 1. Phillips, J . C. 1983. Agron. Abstr. p. 76. Phillips, J. C. 1988. Int. Chickpea Newsl. No. 18, pp. 19-21. Pundir, R. P. S., Reddy, K. N., and Mengesha. M. H. 1988. “ICRISATChickpeaGermplasm Catalog: Evaluation and Analysis. International Crop Research Institute for the SemiArid Tropics. Patancheru, A.P. 502324, India. Qureshi, S. H. 1986. In “Ascochyta Blight Resistance in Chickpeas” (M. H. Ibrahim, B. A. Malik, and M. V. Reddy, eds.), pp. 43-46. ICARDA, Aleppo, Syria. Rathi, Y. P. s..Tripathi, H. S., and Chaube, H. S. 1984. Int. Chickpea Neu3sl. No. 11, pp. 31-33. Reddy, M. V. 1980. Int. Chickpea Newsl. No 3, p. 12. Reddy, M. V., and Kabbabeh, S. 1985. Phyropathol. Medit. 24,265-266. Reddy, M. V . , and Singh, K. B. 1984. Plant Dis. 68, 900-901. Reddy, M . V., and Singh, K . B. 1990. Indian J . Plant Prot. 18,65-69. Reddy, M . v . , Singh, K. B., and Nene, Y . L. 1984. In “Ascochyta Blight and Winter Sowing of Chickpeas” (M. C . Saxena and K. B. Singh, eds.), pp. 45-54. Martinus Nijhoff/Dr. W. Junk, Publishers, The Hague, The Netherlands. Reddy, M. V . . Singh, 0..Bharati, M. P., Sah, R. P., and Joshi, S. 1988. Int. Chickpea Newsl. No. 19.p. 15. Reddy, M. V., Nene, Y. L., Singh, G., and Bashir, M. 1991. In “Proceedings ofthe Second International Workshop on Chickpea” (H. A. Van Rheenen and B. J. Walby, eds.). ICRISAT, Hyderabad, India (in press). Rewal, N . , and Grewal, J. S. 1989. Euphvtica 44,61-63. Sahu, R.. and Sah, D. N. 1988. In?. Chickpea Newsl. No. 18, pp. 13-15. Sattar, A.. Arif, A. G.. and Mohy-un-din, M. 1953. Pak. J. Sci. Res. 5 , 16-21, Satyaprasad, K . , and Rarnarao. P. 1983. Indian Phytopathol. 36,77-81. Sharma, G.L., and Mathur, B. N. 1985. Int. Chickpea N e w s / . No. 12, pp. 31-32. Sindhu, J. S ., Singh, K. P., and Slinkard. A. E. 1983. J . Hered. 74,68. Singh, D. V., Misra, A. N., and Singh, S . N. 1974. Indian J . Genet. Plant Breed. 34,239-241. Singh, G . , and Bhan, L. K. 1986. Plant Dis. Res. 1,69-74. Singh, G., Kapoor, S . , and Singh, K. 1982. Int. Chickpea Newsl. No. 7, pp. 13-14. Singh, H.. Kumar, J., Smithson, J. B.. and Haware, M. P. 1987. Plant Pathol. 36,539-543. Singh, H., Kumar, J.. Smithson, J. B., and Haware, M . P. 1988. J . Agric. Sci. 110,407-409. Singh, K. B. 1987. In “The Chickpea” ( M . C. Saxena and K. B. Singh, eds.), pp. 127-162. C. A. B. International, Wallingford, U . K . Singh, K. B. 1989. In “Proceedings of Breeding Research: The Key to the Survival of the Earth” (s.Iyama and G. Takeda, eds.), 6th Int. Congr. SABRAO, pp. 237-240. Tsukuba, Japan. Singh, K. B., and Dahiya, B. S. 1973. In “Symposium on Wilt Problems and Breeding for Resistance in Bengal Gram,” Abstr., pp. 13-14. Indian Society of Genetics and Plant Breeding, IARI, New Delhi. Singh, K . B., and Reddy, M. V. 1983. Crop Sci. 23,9-10. Singh, K . B . , and Reddy, M. V. 1989. Crop Sci. 29,657-659. Singh, K. B., and Reddy, M. V. 1990. Plant Dis. 74, 127-129. Singh, K. B., Hawtin, G. C., Nene, Y. L.. and Reddy, M. V . 1981. P h n t Dis. 65, 586-587.

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Singh, K. B., Malhotra, R. S., and Witcombe, J. R. 1983. “Kabuli Chickpea Germplasm Catalog.” ICARDA, Aleppo, Syria. Singh, K. B., Reddy, M. V., and Nene, Y. L . 1984. Plant Dis. 68,782-784. Singh, K. B., Di Vito, M., Greco, N., and Saxena, M. C. 1989a. Nernafol. Medir. 17, 113-114. Singh, K. B., Weigand, S . , Haware, M. P., Di Vito, M., Malhotra, R. S., Tahhan, O., Saxena, M. C., and Holly, L. 1989b. Eucarpia Congr., Vortr. Pjanzenzuechtung, 12th. Singh, K. B., Kumar, J., Haware, M. P., and Lateef, S. S. 1991. In “Proceedings of the Second International Workshop on Chickpea” (H. A. van Rheenen and B. J. Walby, eds.). ICRISAT, Hyderabad, India (in press). Singh, L. 1974. Indian J . Genet. Plant Breed. 23,247-250. Singh, V., Singh, F., and Gupta, P. K. 1986. Perspect. Cyrol. Genet. 5,853-856. Smithson, J. B., Kumar, J., and Singh, H. 1983. Int. Chickpea Newsl. No. 2 , pp. 21-22. Tewari, S. K., and Pandey, M. P. 1986. Euphyrica 35,211-215. Tiwari, A. S., Pandey, R. L., Misra, P. K., and Kotasthane, S. R. 1981. Jawaharlal Nehru Krishi Viswa Vidyalaya (Jabalpur, India) Res. J . 15, 133-134. Upadhyaya, H . D., Haware, M. P., Kumar, J., and Smithson, J. B. 1983a. Euphyrica 32, 447-452. Upadhyaya, H. D., Smithson, J. B., Haware, M. P., and Kumar, J. 1983b. Euphytica 32, 749-755. van der Maesen, L. J. G. 1987. In “The Chickpea” (M. C. Saxena and K. B. Singh, eds.), pp. 11-34. C. A. B. International, Wallingford, U.K. van der Maesen, L. J. G., and Pundir, R. P. S. 1984. Plant Genet. Resour. Newsl. No. 57, pp, 19-24. Vir, S ., and Grewal, J. S. 1974. Indian Phyroparhol. 27,255-260. Vir, S., Grewal, J. S., and Gupta, V. P. 1975. Euphytica 24,209-21 I . Vock, N. T., Langton, P. W., and Pegg, K. G. 1980. Ausr. Plant Pathol. 9, 117. Zachos, D. G., Panagopoulos, G. G., and Makaris, S. A. 1963. Ann. Inst. Phyropathol. Benaki 5, 167-192 (in French).

ADVANCES IN AGRONOMY. VOL. 45

GENETICS OF RESISTANCE TO INSECTS IN CROP PLANTS Gurdev S. Khush and D. S. Brar International Rice Research Institute 1099 Manila, Philippines

I. Introduction 11. Rice

Brown Planthopper ( Nilnparuatu lugens ) Whitebacked Planthopper (Sogatellafitrrfferu) Green Leafhopper ( Nephotettix uirescens ) Zigzag Leafhopper (Recilia dorsalis) Gall Midge ( O r s e o h oryzae ) F. Striped Stem Borer ( Chilo suppressalis) Wheat A . Hessian Fly ( Mayetiola destructor) B. Greenbug ( Schizaphis graminrim ) C. Cereal Leaf Beetle ( Oulema melanopus ) D. Wheat Stem Sawfly ( C e p h u s cinctus ) Maize A. European Corn Borer ( Ostrinia nubilalis ) B. Corn Earworm (Heliothis w u ) C. Western Corn Rootworm (Uiubrotica uirgifera ) D. Corn Leaf Aphid ( Rhopalosiphum niaidis ) E. Fall Armyworm ( Spodopteru .frugiperda) Sorghum A. Corn Leaf Aphid ( Rhopalosiphum maidis ) B. Greenbug ( Schizaphis gruminum ) C . Shoot Fly ( A t h e r i g o m soccatu ) D. Sorghum Midge ( Contarinirr .sorghicda ) E. Chinch Bug (Blissus leucopterus ) Barley A. Hessian Fly ( Mayetiola destructor) B. Cereal Leaf Beetle ( Oulema melanopus ) C. Greenbug (Schizaphis gruminum ) D. Corn Leaf Aphid (Rhopnlosium maidis ) Cotton A . Boll Weevil ( Anthonomus grundis ) B. Thrips ( Thrips spp.) C. Tobacco Budworm (Heliothis uirescens ) D. Jassids ( Enipoasca spp.) E. Tarnished Plant Bug ( L y g u s lineolaris ) F. Pink Bollworm (Pectinophorn gossypiella ) A.

B. C. D. E.

111.

IV.

V.

VI.

VII.

223

Copyright D 1991 by Academic Press. Inc. All rights of reproduct~onin any form reserved.

224 VIII.

IX.

X.

XI. XII. XIII.

GURDEV S. KHUSH AND D. S. BRAR Fruits A. Rosy Leaf Curling Aphid of Apple (Dysaphis deuecta ) B. Rosy Apple Aphid (Dysaphis plantaginea ) C. Wooly Apple Aphid (Eriosoma lanigerum) D. Rubus Aphid (Amphorophora rubi) E. Black Currant Curling Midge (Dasyneura tetensi) F. Black Currant Gall Mite (Cecidophyopsis ribis) G. Red Scale Pest of Citrus (Aonidieila aurantii) Vegetables A. Melon Aphid (Aphis gossypii) B. Red Pumpkin Beetle (Aulacophorafoveicollis) C. Striped Cucumber Beetle (Acalymma uitfatum) D. Two-Spotted Cucumber Spider Mite ( Tetranychus urticae) E. Squash Bug (Anasa tristis) F. Pumpkin Fruitfly (Dacus cucurbitae ) G. Lettuce Root Aphid (Pemphigus bursarius) H. Lettuce Leaf Aphid (Nasonouia ribisnigri) I. Arthropod Pests of Tomato Forages and Legumes A. Mexican Bean Beetle (Epiiachna uarivestis) B. Bean Weevil (Callosobruchus chinensis ) C. Cowpea Seed Beetle ( Callosobruchus maculatus ) D. Cowpea Aphid (Aphis cracciuora ) E . Spotted Alfalfa Aphid ( Therioaphis maculara ) F. Pea Aphid of Alfalfa ( Acyrthosiphon pisum ) G . Sweet Clover Aphid (Therioaphis riehrni) Tagging Insect Tolerance Genes with Molecular Markers Genetic Engineering and Insect Tolerance Conclusions References

I. INTRODUCTION Humans and insects have always competed for food and fiber, so they have been constantly at war with each other. Insects cause millions of dollars’ worth of losses annually to food crops and other plants all over the world. Scientists have devised various control measures to minimize these losses. The most practical and economical control measure is varietal resistance to insects. Painter (1951)and others demonstrated that clear-cut cases of host resistance existed in crop species of importance to agriculture. During the last 50 years, screening techniques for evaluating germplasm for insect resistance have been developed and sources of resistance to major insects in several important crop species have been identified. Resistant entries from germplasm collections have served as resistance

GENETICS OF RESISTANCE TO INSECTS

225

sources in crop improvement programs. Resistant varieties of major crops are now grown on millions of hectares annually. The most dramatic examples of the success of host resistance programs are the control of the hessian fly through breeding of hessian fly-resistant wheats in the United States and the control of brown planthopper (BPH) of rice in Asia through resistant varieties. Information on the inheritance of resistance is useful to the breeder in deciding on the breeding methodology and the breeding strategies to be adopted. Diverse genes for resistance are needed to cope with the development of new biotypes, to develop multiline varieties, and to attain regional deployment of genes. Entomologists and breeders have investigated the inheritance of resistance to insects of major crops to identify diverse genes for resistance. The usefulness of genetic analysis for insect resistance is illustrated by the success of the host resistance program for the BPH in rice. Sources of resistance to the BPH were identified in 1967 (Pathak et al., 1969). The program on breeding and genetics was started in 1968. Two genes for resistance, Bph-Z and bph-2, were identified in 1970 (Athwal et al., 1971). The first resistant variety with Bph-I, IR26, was released in 1973 (Khush, 1977a).The variety was widely accepted in the Philippines, Indonesia, and Vietnam but became susceptible in 1976-1977 because of the development of biotype 2 of the BPH. By that time, varieties IR36 and IR38 with the bph-2 gene had been developed and released (Khush, 1977b). IR36 soon replaced IR26 and became the dominant rice variety. Its resistance to BPH has held up for 14 years in most areas and it is still widely grown. Meanwhile, 29 additional resistant varieties were analyzed genetically and two new genes, Bph-3 and bph-4, were identified (Lakshminarayana and Khush, 1977). These genes were incorporated into the improved germplasm. In 1982, when a biotype capable of damaging IR36 appeared in small pockets in the Philippines and in Indonesia, IR56 and IR60 with the Bph-3 gene for resistance were released [International Rice Research Institute (IRRI), 19831.1R66with bph-4 for resistance was released in 1987 and IR68, IR70, IR72, and IR74, all with Bph-3, were released in 1988. These varieties are now widely grown in tropical and subtropical ricegrowing countries. If we had neglected gene identification work, the planned incorporation of diverse genes for resistance to BPH would have been impossible and we would not have been able to keep ahead of this shifting enemy of the rice crop. The value of the genetic analysis of resistance cannot therefore be overemphasized. In this article we review the status of knowledge about genetics of resistance to insects in crop plants.

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II. RICE Rice is the host of more than 100 insect species, the most important of which are the BPH, whitebacked planthopper (WBPH), green leafhopper (GLH), gall midge, and stem borers. Inheritance of resistance to these five insects has been investigated.

LUGENS) A. BROWNPLANTHOPPER ( NILAPARVATA

The BPH is the most serious of the rice pests. It causes considerable damage by direct feeding. It also transmits grassy stunt and ragged stunt virus diseases. High levels of resistance to this insect have been found in rice cultivars. More than a hundred resistant cultivars have been genetically analyzed. Athwal et al. (1971) showed that the resistance in.Mudgo, C022, and MTU15 was governed by the same dominant gene, which they designated Bph-J . A single recessive gene, designated bph-2, conveyed resistance in ASD7. Bph-1 and bph-2 are closely linked and no recombination between them has been observed. Chen and Chang (1971) also reported that a single dominant gene controls resistance in Mudgo. Athwal and Pathak (1972) reported that MGL2 possesses Bph-1, and Ptb 18 possesses bph-2. Martinez and Khush (1974) investigated the inheritance of resistance in two breeding lines of rice that originated from the crosses of susceptible parents. One of the lines, IR747B2-6, possessed Bph-J for resistance; the other, IRll54-243, possessed bph-2. TKM6, the resistant parent of IR747B2-6, is susceptible, but a small number of the F2 progenies from its crosses with other susceptible varieties such as TN1, IR8, or IR24 are resistant. It was hypothesized that TKM6 is homozygous for Bph-I as well as for a dominant inhibitory gene i-Bph-I, which inhibits Bph-I. In a genetic study of 28 varieties, Lakshminarayana and Khush (1977) found 9 varieties with Bph-I, 16 with bph-2, and one variety with both genes. Two varieties were found to have new genes. A single dominant gene, which conveys resistance in Rathu Heenati was designated Bph-3. This gene segregates independently of Bph-J. A single recessive gene, which controls resistance in Babawee, was designated bph-4. This gene segregates independently of bph-2. Genetic analysis of 20 resistant varieties by Sidhu and Khush (1978) revealed that 7 varieties had Bph-3, 10 had bph-4. and resistance in the remaining 3 was governed by 2 genes. Sidhu and Khush (1979) also reported that Bph-3 and bph-4 were closely linked. Genes bph-4 and Glh-3 are also linked with a map distance of 34 units. The bph-4 gene appeared to be linked with sd-J (recessive gene for semidwarf

GENETICS OF RESISTANCE TO INSECTS

227

stature). However, bph-4 and Xa-4 (gene for bacterial blight resistance) are inherited independently. Ikeda and Kaneda (1981) also found that bph-2 as well as Bph-1 segregate independently of both Bph-3 and bph-4; whereas Bph-3 and bph-4 as well as Bph-l and bph-2 are closely linked. Ikeda and Kaneda (1982) reported that Bph-l segregated independently of the gene for dwarf virus resistance in Kanto PL-3 and also of the gene governing stripe disease resistance in Kanto PL-2. On the basis of trisomic analysis, Ikeda and Kaneda (1981) identified the loci of Bph-3 and bph-4 on chromosome 10. In another study, Ikeda and Kaneda (1983) located Bph-l on chromosome 4. No linkage was detected between Bph-l on one hand and Ig and d-1 I markers of chromosome 4 on the other. However, bph-2 was found linked with d-2, with a 39.4% recombination value. Khush et al. (1985) carried out a genetic analysis of ARC10550. This cultivar is resistant to BPH populations in Bangladesh and India (biotype 4) but is susceptible to biotypes 1 , 2 , and 3. It was found to have a single recessive gene, bph-5, for resistance, which segregates independently of Bph-1, bph-2, Bph-3, and bph-4. Seventeen additional rice cultivars, resistant to biotype 4 but susceptible to biotypes 1, 2, and 3, were genetically analyzed by Kabir and Khush (1988). Seven were found to have a single dominant gene for resistance. The dominant gene(s) of these cultivars segregated independently of bph-5. The dominant gene of cultivar Swarnalata was designated Bphd. In the remaining 10 cultivars, resistance is conferred by single recessive genes. The recessive genes for resistance of eight cultivars were found to be allelic to bph-5. However, the recessive genes of two cultivars are nonallelic to bph-5. The recessive gene of T12 was designated bph-7. Two Thai varieties, Col. 5 Thailand and Col. 1 I Thailand, and Chin Saba from Burma were reported to have single recessive genes for resistance, which are allelic to each other but are nonallelic to bph-2 and bph-4. Similarly, cultivars Kaharmana, Balamawee, and Pokkali were found to have single dominant genes that are allelic to each other but are different from Bph-1 and Bph-3 (Ikeda, 1985). Since these cultivars are resistant to biotypes 1, 2, and 3, as compared to cultivars with bph-5, Bph-6, and bph-7, which are susceptible, Nemoto et a / . (1989) concluded that the recessive gene of Col. 5 Thailand, Col. I 1 Thailand, and Chin Saba must also be different from bph-5 and bph-7. They designated this gene as bph-8. Similarly, they designated the dominant gene of Kaharmana, Balamawee, and Pokkali as Bph-9. Four BPH biotypes are known. Biotypes 1 and 2 are widely distributed in Southeast Asia, biotype 3 is a laboratory biotype produced in the Philippines, and biotype 4 occurs in the Indian subcontinent. Bph-I confers resistance to biotypes 1 and 3; bph-2 conveys resistance to biotypes 1

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GURDEV S. KHUSH AND D. S. BRAR

and 2; Bph-3 and bph-4 confer resistance to all known biotypes; bph-5, B p h d , and bph-7 convey resistance to biotype 4 only; and bph-8 and Bph-9 provide resistance to biotypes 1,2, and 3. Their reaction to biotype 4 is not known (Table I).

B. WHITEBACKED PLANTHOPPER ( SOGATELLA FURCIFERA ) More than 300 cultivars resistant to the WBPH have been identified and about 80 of them have been analyzed genetically. Five genes for resistance, one recessive and the others dominant, have been identified. A single dominant gene, designated Wbph-1, was found to convey resistance to the WBPH in the variety N22 (Sidhu et al., 1979). Resistance in ARC10239 is governed by a single dominant gene designated Wbph-2 (Angeles er al., 1981). This gene segregates independently of Wbph-1. Nair et al. (1982) investigated 21 additional varieties: 19 had Wbph-1 and two had Wbph-1 and an additional recessive gene. The resistance of 2 of the 14 varieties analyzed by Hernandez and Khush (1981) was governed by Wbph-2. Eleven varieties each had a single dominant gene that segregated independently of Wbph-1 and Wbph-2. The dominant gene of one such variety, ADR52, was designated Wbph-3. Only one variety, Podiwi A8, had a recessive gene, which was designated wbph-4. Saini et al. (1982)

Table I Interrelationshipsbetween Biotypes of Brown Planthopper and Genes for Resistance in Rice Reaction to biotypes" Variety

Gene

I

2

3

Mudgo ASD 7 Rathu Heenati Babawee ARC 10550 Swarnalata T 12 Chin Saba Balamawee TN 1

Bph-1 bph-2 Bph-3 bph-4 bph-5 Bphd

R R R R S S S R R S

S R R R S S S R R S

R S R R S S S R R S

' R, resistant;

bph-7

bph-8 Bph-9 None

S, susceptible; -, not known.

4

S

GENETICS OF RESISTANCE TO INSECTS

229

analyzed 13 additional varieties. Resistance was governed by Wbph-1 in four varieties, Wbph-2 in six, Wbph-1 and Wbph-2 in two, and a single dominant gene in Hornamawee segregated independently of Wbph-1 and Wbph-2. Wu and Khush (1985) investigated the inheritance of resistance in 15 varieties. They found that resistance in nine was controlled by Wbph-1, and resistance in four was conferred by two genes. The remaining two varieties had single dominant genes for resistance, which segregated independently of Wbph-I, Wbph-2, and Wbph-3. The dominant gene of N'Diang Marie was designated Wbph-5. Jayaraj and Murty (1983) studied the inheritance of resistance in nine varieties. They found that it was controlled by a single dominant gene in three varieties and by a recessive gene in six other varieties. Inheritance of resistance in 10 cultivars was investigated by Singh ef al. (1990). Eight cultivars, i.e., ARC5838, ARC6579, ARC6624, ARC10464, ARCl 1321, ARCl 1320, Balamawee, and IR2425-90-4-3, were found to have single recessive genes for resistance. The recessive genes of IR241590-4-3, ARC5838, and ARCl 1324 were found to be allelic to each other. Resistance in Ptbl9 and IET6288 was found to be under dominant gene control. ( NEPHOTETTIX VIRESCENS) C. GREENLEAFHOPPER

The inheritance of resistance to the GLH was first investigated by Athwal et al. (1971) in varieties Pankhari 203, ASD7, and IRE. They found that resistance in each variety was controlled by one dominant gene. The dominant gene in Pankhari 203'was designated Glh-1; that in ASD7, Glh-2; and that in IR8, Glh-3. The three genes segregated independently of each other. Two more genes were identified by Siwi and Khush (1977): one recessive, designated glh-4; the other dominant, designated Gth-5. Two dominant genes Glh-6 and Glh-7, were identified by Rezaul Karim and Pathak (1982). Avesi and Khush (1984) studied the inheritance of resistance in 18 varieties. Two had Glh-1, three had Glh-2, two had Glh-3, one glh-4, and three had two genes. The allelic relationships of the resistance genes of seven varieties are still not known. Ruangsook and Khush (1987) analyzed 15 rice cultivars genetically. The resistance was governed by two dominant genes in Katia Baudger 13-20, Laki 659, Lasane, Asmaita, and Choron Bawla, but by single dominant genes in the remaining ten cultivars. Allele tests with the known genes revealed one of the two dominant genes of Choron Bawla is allelic to Glh-2. The single dominant gene in Chiknal and one of the two dominant genes of Laki 659 are allelic to Glh-3. The

230

GURDEV S. KHUSH AND D. S . BRAR

second of the two dominant genes of Katia Badger 13-20, Laki 659, and Lasane are allelic to Glh-5. The two dominant genes of Asmaita and the single dominant gene of Hashikalmi, Ghaiya, ARC10313, and Garia are nonallelic to and independent of Glh-1, Glh-2, Glh-3, glh-4, and Glh-5. Tomar and Tomar (1987) studied the inheritance of resistance in 11 cultivars. Resistance in eight cultivars was found to be governed by single dominant genes, but single recessive genes conferred resistance in the three other cultivars. Inheritance of resistance in 12 cultivars was investigated by Ghani and Khush (1988): single dominant genes confer resistance in six cultivars, two independent dominant genes govern resistance in four cultivars, and single recessive genes provide resistance in two other cultivars. The single recessive gene in ARC7012 is allelic to glh-4 but that in DV85 is nonallelic to and independent of glh-4. The new recessive gene was designated glh-8.

D. ZIGZAG LEAFHOPPER ( RECILIADORSALIS) The genetics of resistance to the zigzag leafhopper (ZLH), WBPH, BPH, and GLH in cultivars Rathu Heenati, Ptb21, and Ptb33 was investigated by Angeles et al. (1986). Single dominant genes that segregate independently of each other and conveyed resistance to ZLH were designated Zlh-1 (Rathu Heenati), Zlh-2 (Ptb21), and Zlh-3 (Ptb33). Tests for independence of the various genes for resistance to leaf and planthoppers revealed that Zlh-1, Zlh-2, and Zlh-3 are independent of Wbph-3. Zlh-2 and Zlh-3 also segregated independently of bph-2 and Bph-3.

E. GALLMIDGE( ORSEOLIA ORYZAE) Resistance to gall midge has been postulated to be due to two genes in W1263 and four in Ptbl8 (Shastry et al., 1972). Sastry and Prakasa Rao (1973) inferred the presence of three recessive genes for resistance in W1263 and W12708. Satyanarayanaiah and Reddi (1972), however, showed convincingly that resistance in W1263 was governed by a single dominant gene. Resistance in CR57-MR-1523 was governed by two to three dominant complementary genes (Sastry et al., 1984). Chaudhary et al. (1986) studied inheritance of resistance in five cultivars. All of them were found to have a single dominant gene for resistance. Allele tests revealed that Usha, Samridhi, and BD6-1 have the same gene for resistance, which was designated Gm-I. Surekha and IET6285 have the same gene for resistance, which is nonallelic to and independent of Gm-1; this

GENETICS OF RESISTANCE TO INSECTS

23 1

gene was designated Gm-2. Kalode et al. (1976) found differential reactions of W1263 and JBS446 at two locations, indicating biotypic variation in gall midge.

F. STRIPED STEMBORER( CHILOSLJPPRESSALIS) Reports on the inheritance of resistance to stem borer are fragmentary. From an analysis of the F2 population and F3 lines from the cross of Giza 14 and Sydney A , Koshiary et al. (1957) showed that the field resistance of Giza 14 to stem borer was under polygenic control. On the other hand, the field resistance of TKM6 to stem borer, as measured by the incidence of whiteheads, was reported to be governed by a single recessive gene (Dutt et al., 1980). Athwal and Pathak (1972) studied the inheritance of resistance in the greenhouse. Each of the 113 F2plants from the cross between Rexoro (susceptible) and TKM6 (resistant) was infested with 10 larvae of the striped borer. Plants on which the survival rate and body weight of the larvae were normal were considered susceptible. Resistance was dominant in the FI. Larval weight was used as an index of resistance to stem borers. From the frequency distribution of mean body weights of surviving larvae on the F2plants, it was concluded that the particular component of resistance to stem borer may be simply inherited.

Ill. WHEAT A number of insects attack wheat; however, the genetics of resistance has been studied mainly for the hessian fly, greenbug, cereal leaf beetle, and wheat stem sawfly.

A. HESSIANFLY( M A Y E T ~ O LDAE S T R U C T O R ) Among the insect pests, the hessian fly provides the classical example of the gene-for-gene relationship between resistance in the host (wheat) and virulence in the insect. The interaction between wheat and hessian fly genotypes is highly specific. Eleven biotypes (GP, A, B , C, D, E, J , L, M, N , and 0)of the hessian fly have been reported (Cartwright el al., 1959; Gallun and Reitz, 1971; Gallun, 1977; Sosa, 1981; Obanni et al., 1989b). Nineteen genes (I8 dominant and 1 recessive) for resistance to this insect have been identified (Gallun. 1984; Roberts and Gallun, 1984; Hatchett et

232

GURDEV S. KHUSH AND D. S. BRAR

al., 1981; Stebbins et al., 1983; Maas et al., 1987, 1989; Patterson et al., 1988; Obanni et al., 1988,1989a,b). These genes have been designated H-I and H-2 (Cartwright and Weibe, 1936; Noble and Suneson, 1943), H-3 (Caldwell et al., 1946; Abdel-Malek et al., 1966), h-4 (Suneson and Noble, 1950),H-5 (Shands and Cartwright, 1953),H-6 (Allan et al., 1959),H-7and H-8 (Patterson and Gallun, 1973), H-9 (Stebbins et al., 1980), H-I0 (Stebbins et al., 1982), H-11 (Stebbins et al., 1983), H-12 (Oellermann et al., 1983), H-13 (Hatchett et al., 1981; Gill et al., 1987),H-14 and H-15 (Maas et al., 1989),H-16 (Patterson et al., 1988),H-17 (Obanni er al., 1988),H-18 (Maas et al., 1987; Obanni et al., 1988), and H-19 (Obanni er al., 1989b). Among these, eight genes ( H - I , H-2, H-3, h-4, H-5, H-7, H-8, H - 1 2 ) have been identified in common wheat. The other 11 genes ( H - 6 , H-9, H-10, H-11, H-14, H-15, ff-16,H-17, ff-18,H - 1 9 ) have been derived from durum wheat and H-13 from Aegilops squarrosa ( Triricum tauschii). New genes for resistance to the hessian fly are continuously sought and incorporated into commercial wheat cultivars. The reaction of some of the wheat strains to five biotypes (A, B , C, D, L) of the hessian fly is shown in Table 11. Certain genotypes such as Arthur 71 and Abe, which have H-3 and H-5 genes, are resistant to the four biotypes. PI94587 ( T. turgidum ) is also resistant to biotypes A, B , C, and D. Common wheats with resistance derived from PI94587, such as Knox 62 and Lathrop, inherited only one dominant gene for resistance to biotypes A and B. Ribeiro, a source of H-5 gene, is resistant to biotypes A, B, C, and D. Breeding lines 916,920, and 941 derived from PI94587 have H-11, which is closely linked with H-5. H-11 confers a higher level of resistance than H-5 at higher temperature (27°C). Carlson et al. (1978) reported resistance to biotype D in Elva and C117714 ( T . Turgidum L.). One of the derived common wheat lines had a single dominant gene and the two other lines contained two linked dominant genes for resistance to biotype D. Hatchett er al. (1981)identified new sources of resistance to biotype D in five accessions of T . tauschii. Stebbins et al. (1983) studied the inheritance of resistance of PI94587 T . turgidum wheat (durum group) to biotypes B and D. Results indicated that its resistance to biotype D was due to two independent dominant genes. The test cross progenies susceptible to biotype D were tested for resistance to biotype B. Besides H-6, two or three genes segregated in the test cross progenies. Thus, it appears that PI94587 may have four or five independent dominant genes for resistance. Three selections from the crosses of PI94587-916,920, and 941 were found to have a common dominant gene. This gene is linked with H-5 with 4.40 -+ 1.78 map units and was designated H-11 . Oellermann et al. (1983) studied the inheritance of resistance in Luso to

233

GENETICS OF RESISTANCE TO INSECTS Table I1

Interrelationships between Biotypes of the Hessian Fly and Genes for Resistance in Wheat Reaction to biotypes"

Cultivar or breeding line

Gene(s) for resistance

GP

A

B

C

D

L

Big club 60 Arthur Arkan Arthur 7 I Abe Knox 62 Lathrop Caldwell Seneca PI94587 822-34 916,920, 941 Kay Elva Stella 817-1 Ella Luso KS81-H 1640-HF ELS6404-160-5 PI94587 PI428435 Brule PI422297 Jori Blueboy

H - I , H-2 H-3 H-3 H-3, H-5 H-3, H-5 H-6 H-6 H-6 H-7, H-8 H-6, H-11 H-9 H-11 H-1 I H-9, H-I0 H-9, H - I 0 H-9, H-I0 H-9 H-12 H-13 H-14, H-IS H-16 H-17 H-18 H-19 H-20 None

R R R R R R R R R R R R R R R R R R R R R R R R R S

-

S

-

S S S R R S S S S R R R R R R R R R R R

S S S S S S S S S R S S R R R/S R R R R RIS R R S

~~

R

R

R R R R S R

-

R R R R R S

R

R R

-

-

R R R R

R R R R R R R

-

R

-

-

-

R

-

R

R R R

S S S S R R R R R R MR R R R -

-

-

-

S

S

S

R R R R S

~

R, resistant; MR. moderately resistant; S, susceptible; RIS, mixture of resistant/susceptible plants; -, not known.

determine the number of genes for resistance to biotypes B or D. The partial resistance of Luso to biotypes B and D was found to be due to a single dominant gene. The results indicate that this gene was distinct from, and probably independent of, all the known genes that confer resistance to biotype D ( H - 5 , H-9, H-10, and H-11 ). The new gene designated H-12 is most likely located in the A or B genome of wheat. A comparison of resistance levels conferred by H-12 and other genes indicates that H-12 does not confer as high a level of resistance as H-5, H-6, H-9, and H-10. Lines with H-6 and H-11 do not have resistance to biotype L but PI94587 has. A single partially dominant gene was trans-

234

GURDEV S. KHUSH AND D. S. BRAR

ferred from PI94587 to susceptible durum D6647. Reaction to biotypes B, C, D, and L indicated it was not H-10, H-12, or the Marquillo gene. The newly isolated gene was designated as H-16 (Patterson et al., 1988). Maas etal. (1989)found that ELS6404-160-5 is resistant to biotypes B, C, D, and L and resistance to biotype D is stable at three temperatures. The genes from ELS6404-160-5 were designated H-14 and H-15. Obanni et al. (1989b) analyzed a number of genes controlling the resistance of PI422297 to biotype D. The two genes governing resistance were independent of H-5, H-9, H-10, H-14, H-15, and H-17. One of the two genes in PI422297 is different from all known genes for resistance and was designated H-19. Recently, Amri et a f . (1990) tested 217 Tunisian wheats for resistance to GP biotypes and to biotypes D and L, and 25 Moroccan wheats were evaluated for resistance to biotypes D and L. Among the Tunisian wheats, 88% were considered potential sources of resistance to biotype GP, 86% to biotype D, and 59% to biotype L, whereas 60% of the Moroccan wheats were resistant to one or both biotypes. Four resistant Moroccan durum wheats-Qued Zenati, BD1026 (land races), and Jori and Hajj Mouline (cu1tivars)-were intercrossed as well as crossed with either one or two susceptible checks, Zerameks and ACSAD65. The Fz and F3 populations showed that three genes in the Morocco durum wheats appear to be different from the previously designated H-1 through H-13, based on reactions to biotypes D and L and to populations of hessian fly in Morocco. The presence of three independent genes in a sample of four durum wheats indicates that North African germplasm is a rich source of new genes for resistance to hessian fly. Hatchett et al. (1981) crossed hessian fly-resistant synthetic amphiploids of diploid and tetraploid wheats with susceptible wheat cultivars Amigo and Eagle, and found that resistance to biotype D derived from T. tauschii was controlled by a single dominant gene. This T. tauschii gene is different from H - I , H-2, H-7, or H-8 and it was designated as H-13 (Gill et al., 1987). Obanni et al. (1989a) determined the reaction of 11 wheat lines to biotype D at 19,23, and 26°C. The lines Portugal 2536, Portugal 2852, and Ribeiro are stable at high temperatures and are highly resistant to biotypes B, D, and L. Further, the genetic background influenced the expression of certain genes for resistance. The durum line IN8464 showed resistance to H-5 in 100% of the seedlings but was expressed in lower proportions of Abe. Stebbins et al. (1980, 1982, 1983) and Oellermann et a f . (1983) have summarized the interrelationships among wheat genes for resistance to the hessian fly. The genes H-11 and H-5 are linked with a 4.4% recombination value. H-9 and H-6 are linked with a 2.0% recombination value. The resistance gene of Luso ( H - 1 2 ) segregates independently of H-5, H-9, H-10, and H-11. The genes H-3 and H-6 showed a 9.0% linkage value,

GENETICS OF RESISTANCE TO INSECTS

235

whereas H-3 and H-9 are linked with a 15.5% recombination value (Patterson and Gallun, 1977; Stebbins et al., 1980). Genes H-9 and H-10 are also linked with a map distance of 36 units, and H-3 and H-5 segregated independently of each other. The H-6 derived from PI94587 and conferring resistance to A and B biotypes was found to be on chromosome 5A (Gallun and Patterson, 1977). The gene order on chromosome 5A appears to be H-10, H-3, H-6, H-9 (Patterson and Gallun, 1977; Stebbins et al., 1982). H-5 and H-11 are located on chromosome IA (Roberts and Gallun, 1984). Telocentric stocks were used to locate H-13 on the long arm of chromosome 6D at 35 crossover units from the centromere (Gill et af., 1987). This is the first hessian fly resistance gene mapped on a D genome chromosome. The gene H-17 is probably located on chromosome 5A (Patterson et af., 1988). Sunderman and Hatchett (1986) analyzed FZ and F3 progenies of crosses of near isogenic lines of PI488960 segregating for reaction to powdery mildew ( P m - 3 a ) and hessian fly ( H - 3 ) . Pm-3a and H-3, previously located on chromosome 1A and 5A, respectively, were found to be linked in repulsion. The linkage appeared to be due to 1A-5A translocation. Recently, Friebe et a f . (1990) tested four tissue culture-derived wheatrye lines (ND7532 x Chaupon) for resistance to biotype L. ND7532 is susceptible to biotype L whereas the rye parent Chaupon is resistant; thus the resistance in wheat-rye lines is from rye. Of the four resistant lines, two were chromosome addition lines carrying either the complete rye chromosome 2R or only the long arm of 2R, while the two other resistant lines were cytologically identified as 2BS/2RL wheat-rye translocations. Thus, the gene or gene complex conditioning larval antibiosis to biotype L is located on the long arm of chromosome 2R. Considerable progress has been made in utilizing hessian fly resistance genes and during the period from 1950 to 1983, 60 hessian fly-resistant cultivars have been released in the United States (Hatchett et al., 1987). B. GREENBUG ( SCHIZAPHIS GRAMINUM) The greenbug causes serious losses to wheat as well as to sorghum, oats, and barley. Resistance to the greenbug in wheat was reported to be conditioned by a single recessive gene (Painter and Peters, 1956).Other workers have confirmed these results and suggested that modifying factors are also involved (Daniels and Porter, 1958;Porter and Daniels, 1963;Abdel-Malek et al., 1966). Five sources of resistance have been identified. Resistance in the five germplasm entries DS28A (Curtis et al., 1960), Amigo (Sebesta and Wood, 1978), Largo (Joppa et al., 1980), CI17959 (Harvey et al.,

236

GURDEV S. KHUSH AND D. S. BRAR

1980), and CI17882 (Tyler et al., 1986) is controlled by single genes. The genes governing resistance in DS28A, Amigo, Largo, CI17959, and CI17882 have been designated as Gb-I, Gb-2, Gb-3, Gb-4, and Gb-5, respectively (Tyler et al., 1987). The interaction of resistance genes with four biotypes of greenbug is shown in Table 111. At least six greenbug biotypes (A, B, C, D, E, and F) have been identified. Puterka et al. (1988) identified two new (G, H) biotypes. Starks and Merkle (1977) identified a recessive gene, gb, in C19058 and Dickinson 485 (T. turgidum), which conditions resistance to biotype A but not to biotypes B, C, and D. Sebesta and Wood (1978) reported that Argentine rye Insave FA, had a single dominant gene for resistance to most biotypes of the greenbug. This resistance gene has been transferred to the wheat cultivar Amigo. Amigo carries a wheat-rye translocation and provides an excellent usable source of insect resistance. Both Amigo and Largo have single dominant genes for resistance (Joppa et al., 1980; Hollenhorst and Joppa, 1983). Crosses of Amigo and Largo indicated that the genes for resistance to biotype C in these cultivars were independent. Further studies using Chinese Spring monosomics showed that the gene for resistance in Amigo is located on chromosome IA, whereas the single dominant gene of Largo is on chromosome 7D (Hollenhorst and Joppa, 1983). Largo (CI17895), an amphiploid of T. durum and T . tauschii, is resistant to greenbug biotypes C and E (Porter et al., 1982). The dominant gene of Largo conveys resistance to biotypes of the greenbug and is being used as

Table 111 Interrelationships between Biotypes of Greenbug and Genes for Resistance in Wheat Reaction of biotypesb Germplasm

Origin ~~

DS28A Amigo Largo CI 17959 C117882

Triticum turgidum &rum Secale cereale T. taicschii T . tauschii T . speltoides

Gene

A

~~~

B

C

~~

Gb-1 Gb-2 Gb-3 Gb-4 Gb-5

E ~

R

S

S

S

R

R S S S

R R R R

S R R R

-

-

-

From Tyler e f al. (1987). Reproduced from Crop Science, 27(3), pp. 526-527 by permission of the Crop Science Society of America, Inc. and the Plant Science & Water Conservation Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Stillwater, Oklahoma. R, resistant; S, susceptible; -, not known.

GENETICS OF RESISTANCE TO INSECTS

237

a source of resistance in several breeding programs. Amigo germplasm was used extensively in breeding programs until a new biotype (E) that severely damaged Amigo was detected (Porter et al., 1982). Kindler et al. (1984) showed that biotype E was widespread in the Great Plains. The other source of greenbug resistance such as Gaucho (an octoploid triticale having the Insave rye genome) is also susceptible to biotype E. Harvey et al. (1980) studied greenbug resistance derived from T. tauschii var. strangulata and typica in synthetic hexaploid wheats. The resistance of strangulata and typica was conditioned by different single dominant genes. Wheat germplasm KS8H640 GB, resistant to biotype E derived from T. Tauschii var. strangulata, was released in 1982 (Martin et al., 1982). Tyler et al. (1985, 1986) reported resistance to biotype E in wheat streak mosaic virus (WSMV)-resistant germplasm, with resistance derived from T. speltoides. Resistance to biotype E in CI17882 is governed by a single dominant gene that is not linked to WSMV resistance gene. Webster and Inayatullah (1984) reported resistance to biotype E in six introductions of triticale. Tyler et al. (1988) analyzed 11 accessions of rye for resistance to biotypes B, C, E, and F of greenbug. Rye accessions CI187 and PI240675 segregated for resistance to all four biotypes. Resistance to biotype B and/or E in CI187 is correlated with resistance to biotype C, but is independent of resistance to biotype F. C. CEREALLEAFBEETLE( OULEMA MELANOPUS) Resistance to cereal leaf beetle in small grains was reviewed by Webster (1977)and Webster and Smith (1983). In wheat, resistance to the cereal leaf beetle is due to leaf pubescence, which inhibits oviposition. The distribution, length, and rigidity of leaf hairs affect the resistance level. CI9321, a spring wheat introduction from the Soviet Union has been the major source of pubescence. Ringlund and Everson (1968) investigated the inheritance of resistance in crosses of five pubescent (resistant) Russian wheats and four nonpubescent (susceptible) wheats. Analysis of the pubescence in the F1,FZ,and backcross progenies indicated that the trait was quantitatively inherited and the gene action is mainly additive. The F1 of a cross of glabrous (susceptible) Genesee with pubescent (resistant) CI9321 showed intermediate pubescence and intermediate reaction to larval feeding. Using chromosome substitution lines, Smith and Webster (1973) located major genes for resistance on chromosome 4A and minor genes on 5A, 2A, and 7B. Wallace et al. (1974) found two cultivars with one dominant gene for pubescence and a third cultivar with more than one

238

GURDEV S. KHUSH AND D. S. BRAR

gene. Leisle (1974) found that the presence of hairs (pubescence) was controlled by two or three major genes, but hair length was governed by a few additive genes. Webster et al. (1975) reported that the superior resistance of CI9321 to oviposition compared with Selkirk was due to greater hair density. However, the higher resistance of Selkirk as compared with Chris was due to the greater hair length of Selkirk. By the early 1980s, one cereal leaf beetle-resistant cultivar and 17 resistant wheat germplasms had been released (Webster and Smith, 1983). Roberts et al. (1984) developed five pubescent-leaved soft red winter wheat lines possessing increased tolerance to cereal leaf beetle.

D. WHEATSTEMSAWFLY ( CEPHUS CrNcTus) Resistance to the wheat stem sawfly is related to the pithiness of stem. Solidness of the stem acts as a deterrent to egg laying and survival of the larvae. The inheritance of resistance to the stem sawfly has largely been investigated through genetics of stem solidness. Stem solidness is conditioned by one or more dominant, recessive, or complementary genes in different parents (Wallace and McNeal, 1966). Larson (1957) found that in Chinese Spring, chromosomes 2A, 2D, 6D, and 7D carried genes for hollow stems and chromosome 4B had a gene for solid stem. However, Larson and MacDonald (1959) reported that in the variety S615, chromosomes 3B, 3D, 5A, and 5B carried genes for solid stem and chromosomes 2D, 6D, and 7D had genes for hollow stems. Chromosomes 3B and 5A of Rescue wheat had important genes for stem solidness, and 6A and 6D for stem hollowness. McKenzie (1965) studied the inheritance of resistance to sawfly in a cross of Red Bobs (susceptible) and C.T.715 (resistant) strains, and found that the trait was governed by at least three genes. However, one gene played a major role. Hybrids between solid-stemmed and hollow-stemmed wheat varieties show intermediate levels of stem solidness as well as resistance to sawfly (McNeal et al., 1971; Wallace et al., 1973). The tetraploid wheats ( T. durum ) with solid stems are also resistant to the stem sawfly and have been used as a source of resistance (Tsvetkov, 1973). Some high-yielding sawfly-resistant cultivars such as Lew and Glenman in the United States (McNeal and Berg, 1977; McNeal et a/., 1984) and Leader in Canada (De Pauw et al., 1982)have been released. The breeding of such cultivars indicates that stem solidness is not a limiting factor for yield improvement.

GENETICS OF RESISTANCE TO INSECTS

239

IV. MAIZE At least SO insect species can attack maize. The genetics of resistance has been investigated for five insects: European corn borer, corn earworm, corn rootworm, corn leaf aphid, and fall armyworm.

NUBILALIS) A. EUROPEAN CORNBORER( OSTRINIA

The genetics of resistance to the European corn borer has been studied more thoroughly than that of any other insect species attacking corn. There are two generations (broods) of corn borer each season. The first brood attacks young plants, the second affects the developing grain. Resistance to the first and second generations is not conditioned by the same genes (Russell et al., 1974). Marston and Dibble (1930) studied crosses of Amargo (bitter maize) and Michigan varieties and found resistance to be monogenic recessive. Patch et al. (1942) and Schlosberg and Baker (1948) suggested that resistance was due to the cumulative effect of several genes. Singh (1953) studied the F2 and backcross generations of crosses between resistant and susceptible plants and postulated two genes for resistance. Ibrahim (1954) investigated the resistance to first-generation leaf feeding in F3 and backcross progenies and concluded that two or more genes were involved. Similar tests with progenies from susceptible x resistant cross (B14 x N32) indicated one or two genes for resistance (Penny and Dicke, 1956). In two crosses, the resistance was found to be conditioned by a single gene. The gene for resistance was linked with g/-7 and v-17 genes of the resistant parents with crossover value from 31 to 37% (Penny and Dicke, 1957). Mohamed et a/. (1966) reported that resistance was governed by two or more genes. Other studies indicate that resistance to the European corn borer is quantitative (Scott et a/., 1964, 1965; Scott and Guthrie, 1967; Chiang and Hudson, 1973; Jennings ef al., 1974; Onukogu el al., 1978). The resistance is of quantitative nature where no single gene confers enough resistance and the gene loci are scattered throughout the chromosome complement. In these studies, resistance to leaf feeding by first-generation European corn borer was found to be conditioned by genes at several loci with additive effects. lbrahim (1954) located genes for resistance on specific chromosomes through the use of translocation stocks. The resistance

240

GURDEV S. KHUSH AND D. S. BRAR

factors differentiating the inbred line A41 1 from the susceptible line A344 were associated with three chromosomes: one gene on the long arm of chromosome 3, one on the long arm of chromosome 4, and probably another on the long arm of chromosome 5 . In C131A, genes for resistance were found on the short arms of chromosomes 1,2, and 4 and on the long arms of chromosomes 4 and 6. Inbred B49 has genes for resistance to first-generation larvae on these chromosome arms (possibly allelic to those of C131A) plus an additional gene for resistance on the long arm of chromosome 8 (Scott et al., 1964,1966). Onukogu et al. (1978) located genes for resistance to sheath collar feeding by second-generation borers on seven arms of six chromosomes. Jennings et al. (1974) determined the genetic basis of antibiosis type of resistance to second-generation borers. The data indicated that resistance was due to the cumulative effect of several genes. The expression of resistance could be influenced by cytoplasmic genes. On the basis of diallele analysis involving 10 inbred lines and 45 single crosses, additive type of gene action was inferred. Andrew and Mosley (1980) identified two inbreds, which consistently contributed low damage scores to their progeny. The diallele analysis showed highly significant year x genotype interaction. Selection procedures for the exploitation of additive type of gene action should be effective for improving the levels of resistance to European corn borer. Studies on the resistance to the European corn borer suggest there are several genes for resistance, and several independently inherited mechanisms for resistance may be involved. Recurrent selection procedures were used to develop a composite maize population MO-ECB-2 (S1)CS resistant to the second generation of the European corn borer (Barry and Zuber, 1984). Similarly, Klenke et al. (1986) followed recurrent selection to improve resistance to the European corn borer and developed BS9 synthetic. Russell and Guthrie (1982) developed germplasm possessing resistance to the corn borer at all stages of growth of the plant. The biochemical basis of resistance to the first brood is known to be due to DIMBOA. The additive gene effects are important in controlling high DIMBOA level (Gallun et al., 1975). Williams et al. (1983) and Williams and Davis (1985) found that larval growth of the corn borer on callus cultures derived from resistant lines was much slower than on callus obtained from susceptible lines. Larval weights on callus and their high correlation with leaf feeding indicate that tissue culture could be used as an additional technique in selecting corn genotypes resistant to southwestern corn borer.

GENETICS OF RESISTANCE TO INSECTS

24 1

B. CORNEARWORM ( HELIOTHIS ZEA ) Two species of the corn earworm ( H . zea in the New World and H . armigera in the Old World) are known to attack a wide range of crops. The inheritance of resistance to this pest is not well understood. Walter (1961, 1962) reported dominance of resistance in some inbreds and recessiveness in others. Robertson and Walter (1963) studied the crosses of inbred A166 with a series of interchange stocks of inbred 245 and showed that inbred 245 carries genes for resistance on chromosomes 1,3,5,and 10. No genes for resistance could be located in inbred A166. In another study, Widstrom and Wiseman (1974) reported genes for resistance on chromosomes 4 and 5 of inbred 245, chromosome 3 of inbred 20, and chromosome 8 of inbred La2W. Genes for resistance were not detected on any arm of the other chromosomes of the most resistant parent, inbred 259, indicating a quantitative type of inheritance. Widstrom and Hamm (1969) and Keaster et af. (1972) reported that general combining ability for resistance was highly significant, being 6 to 8 times more than the specific combining ability. They suggested that the resistance was quantitatively inherited. Widstrom and McMillan (1973) studied the inheritance of resistance in 1 1 sweet and 1 1 dent corn inbreds. The findings indicated that additive and dominance gene effects were important in the sweet corn group but not in the dent lines. The antibiosis was suggested to be controlled by several genes. Brewbaker and Kim (1979) studied the inheritance of husk number and insect damage to the ear. Resistance was higher in corn with the higher husk number. The general and specific combining ability mean squares for husk number were highly significant. Two synthetics (GT-CEW-R-58, GT-R14) with corn earworm resistance have been developed (Widstrom et al., 1984b). C. WESTERN CORNROOTWORM ( DIABROTICA V I R G I F E R A) Inheritance of resistance to feeding on silk by adult rootworms was investigated by Sifuentes and Painter (1964). The parental inbreds, FI , Fz, and F3 families, were evaluated for field damage injury to whorls and leaves. A single recessive gene was found to govern resistance in one cultivar. Ortman et al. (1974) reported that resistance to rootworms is multigenic. The cross of Zea mays X Tripsuciim dactyloides was susceptible to larval feeding, although the reciprocal cross was resistant. Resistance probably was inherited through the cytoplasm or genes for resis-

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tance were on the Tripsacum chromosomes, which were eliminated (Branson and Guss, 1972). Howe et al. (1976) found association between cucurbitacins and susceptibility to corn rootworm; higher the cucurbitacins, the greater the damage. In corn germplasm, variabi!ity for tolerance to rootworms exists and resistance has also been shown to be heritable. The lack of well-defined screening procedures accounts for limited studies on inheritance of resistance. Recently, Riedell (1989) devised a greenhouse technique to determine the damage caused by rootworm. The damage to roots of infested plants reared in the greenhouse was quite similar to damage under field conditions. Such techniques could be useful for screening of corn germplasm resistant to rootworms. D. CORNLEAFAPHID( RHOPALOSIPHUM MAIDIS) The corn leaf aphid attacks barley, maize, and sorghum. Resistance in maize is due to antibiosis. Chang and Brewbaker (1975) reported that resistance in Hawaii was conditioned by a single recessive gene that is linked with maize rust resistance gene Rp-1 located on chromosome 10. Pathak and Saxena (1976) reviewed the resistance to be complex and controlled by many genes with varying degrees of dominance and additive effects. Long et al. (1977) studied 12 inbreds under natural infestation and reported the resistance to corn leaf aphid to be controlled by many genes. DIMBOA resistance factor for European corn borer was also found to be an active ingredient for resistance to corn leaf aphid. Beck er al. (1983) found hydroxamic acid to be an important component for resistance to corn leaf aphid. A highly significant negative correlation ( r = - 0.63) was obtained between aphid infestation and hydroxamic acid concentration. E. FALLARMYWORM ( S P O D O P T E R A FRVGIPERDA)

The fall armyworm is one of the most important pests of maize in tropical and subtropical areas of the Americas. It infests the maize plant from the early seedling stage to grain maturity. Widstrom et al. (1972a) studied resistance among eight inbreds and their FI progeny and reported significant additive gene effects. Williams et al. (1978) found both general and specific combining ability effects to be highly significant, which indicates that resistance is quantitative. Maize lines with resistance to fall armyworm have been developed by the pedigree method. Several resistant strains (MP705, MP706, MP707) have been developed (Williams and Da-

GENETICS OF RESISTANCE TO INSECTS

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vis, 1984). Williams et al. (1989) made a diallele cross of six resistant and susceptible lines that were resistant or susceptible to both fall armyworm and southwestern corn borer. The resulting 28 single cross hybrids were analyzed for larval growth and survival of fall armyworm and southwestern corn borer. General combining ability was a highly significant source of variation. Fall armyworm larval survival and weight were highly correlated with southwestern corn borer survival and growth on the same hybrids. The results suggest that selection for greater resistance to one of these insects could increase resistance to the other, and that genes for resistance to fall armyworm also confer resistance to the southwestern corn borer.

V. SORGHUM A number of insects attack sorghum. Inheritance of resistance to corn leaf aphid, greenbug, sorghum shoot fly, sorghum midge, and chinch bug has been investigated. A. CORNLEAFAPHID( RHOPALOSIPHUM MAIDIS) The corn leaf aphid is widely distributed throughout the world in temperate and tropical regions where it is a pest of crop species such as maize, sorghum, and sugarcane. Five biotypes of the corn leaf aphid are known (Painter and Pathak, 1962; Wilde and Feese, 1973). Two biotypes have been used in genetic studies (Cartier and Painter, 1956). The resistance of cultivar Piper428-2 to biotype KSl was due to antibiosis and was a dominant trait in the FI and F3generations of a cross of resistant and susceptible varieties.

B. GREENBUC ( SCHIZAPHIS GRAMINUM) Biotypes A and B of the greenbug have been serious pests of wheat and barley. Biotypes C and E have become serious pests of grain sorghum in the Great Plains of the United States (Porter et al., 1982). Hackerott and Harvey (1971) found that resistance was conferred by dominant genes at more than one locus. Weibel et al. (1972) and Starks et al. (1970) studied the F I and F2populations and found a single incompletely dominant gene for resistance. Starks ef al. (1976) reported that S5 lines from KP2BR

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GURDEV S. KHUSH AND D. S. BRAR

(breeding population) had as high greenbug resistance as the better parent sources. However, none of the Fs lines derived from the crosses of resistant and susceptible parents were as resistant as the better parent. The population breeding approach for greenbug resistance appears to be a better alternative to the widely used practice of introducing insect resistance genes into new parental lines through backcrossing. Peiretti et al. (1980) found that the tolerance of S h a h grain and IS809 for greenbug was inherited independently of the bloomless trait. The greenbug exhibited a significant nonpreference for 50- to 70-day-old bloomless plants as compared to the susceptible check. Comparison of near isogenic pairs of bloom and bloomless sorghum lines indicated that four-week-old bloomless plants become a nonpreferred host to biotype C (Weibel and Starks, 1986). Starks et al. (1983) found less damage by biotype E in the bloomless plants, with a rating of 1.5, compared to 7.3 in the susceptible check. Webster et al. (1984) found that the resistance to biotype E is controlled by a single incompletely dominant gene. There is positive association between bloomlessness and greenbug resistance. Gracen (1986) summarized eight sources of resistance to biotype C: IS809, PI264453 from S. bicolor; KS-30, PI38108 from S. uirgaturn; SA 7536-1 from S. nigricans; PI302236 from S.hewisenti; and PI220 248, and PI308976 from S. Sudanese. Johnson et al. (1982b) developed four sorghum composites resistant to greenbug: TAMBk41, TAMBk42, TAMBk43, and TAMBk44. SOCCATA) C. SHOOTFLY( ATHERIGONA

The shoot fly is a serious pest of sorghum in Asia and Africa. Blum (1969) studied F1 and F2 populations of eight crosses involving four resistant and two susceptible parents under high insect infestation. The F, progenies were susceptible, and resistance behaved as a recessive trait in all F2 populations. Starks et al. (1970) and Harwood et al. (1973) reported that resistance to shoot fly was a quantitative trait. Kulkarni ef al. (1978) reported a nonadditive type of gene action for shoot fly resistance. Rao et al. (1974,1978), Balakotaiah et al. (1975), Sharmaetal. (1977), and Ranaet al. (1975, 1981) identified a nonpreference mechanism to be predominant. The Ft was intermediate between the two parents. Resistance was polygenic and governed by genes with predominantly additive effects. They suggested that resistance showed partial dominance under low to moderate shoot fly infestation but the relationship could shift under heavy infestation levels. Borikar and Chopde (1981, 1982) evaluated stability of resistance to shoot fly and suggested that segregating populations from the crosses of resistant and susceptible parents could be exploited for isolating

GENETICS OF RESISTANCE TO INSECTS

245

resistant lines with desirable agronomic traits. In such crosses, predominance of additive genetic variance was recorded. Halalli et al. (1982)found resistance to shoot fly, trichome density, egg count per plant, and percent dead hearts (killed central shoots) to be controlled by both additive and nonadditive gene effects. However, recovery from insect damage was governed by additive gene effects. Biradar and Borikar (1985) also found additive gene effects governing resistance at different stages of plant growth. Dabholkar et al. (1989) reported both additive and nonadditive gene effects governing eggs per plant and percent dead heart. Shoot fly resistance is affected by the trichome characteristics. Short, pointed trichomes on the leaf sheath confer resistance to this pest. Lines exhibiting short trichomes and glossy-leaf seedling characters are more resistant than lines that exhibit only one of these traits. Agarwal and House (1981) identified several shoot fly-resistant lines at ICRISAT, Hyderabad, India through screening of glossy and trichomed traits. Maiti and Gibson f 1983) studied trichomed and trichomeless F2-derived lines in F3 and F4 generations. Trichomed lines had significantly lower percentages of plants with shoot fly eggs after 18 days of emergence and had the lower incidence of dead hearts. At least two additional loci, which interact with each other, are involved in resistance. Gibson and Maiti (1983) reported that the presence of trichomes was a recessive trait controlled by a single gene ( t r ) . Genetic analysis showed that the same locus was involved in controlling the presence of trichomes in all the four parents; IS1054, IS1082, IS2312, and IS5604. D.

SORGHUM

MIDGE( CONTARINIA SORGHICOLA )

Midge is one of the most widespread and important insects that attack sorghum. Widstrom et al. (1972b) reported that resistance is governed by polygenes. They observed highly additive gene effects in most of the crosses. In the cross SGlRL-MR-I X 130, the dominant genes conditioned susceptibility to midge injury. Epistatic effects were also observed. Faris et al. (1979) found Eberhart and Russell’s regression technique a valuable tool for identifying stable resistance to midge. Midge resistance in the variety AF-28 was governed by 2 or 3 recessive genes with additive effects. Page (1979) identified two grain sorghum lines IS12608C and 1S12664C having higher degree of resistance to midge attack. Boozaya-Angoon et al. (1984) studied F, , F2, F3, and backcross populations derived from crosses of resistant stocks SC0175, SC0423, MB-10, and SGlRL-MR-I with susceptible entries Wheatland, OK94, and Caprock. The resistance was controlled by recessive genes at two or more loci.

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GURDEV S. KHUSH AND D. S. BRAR

Widstrom et al. (1984a) studied F 1 ,F2, F3, and backcross populations and found two different genetic mechanisms governing resistance in PI383856 and in SG IRL-MR- 1. Resistance in PI383856 appeared to be governed by recessive genes. Johnson et al. (1973) found the most obvious difference between resistant and susceptible sorghum was in the size of the glumes; resistant exotic stocks have smaller glumes than those of susceptible sorghums. Small glumes in sorghum might be used as an index character to select midge resistance in populations when there is a lack of adequate midge infestation. Johnson et al. (1982a) listed 28 midge-resistant germplasm lines derived from crosses of resistant and susceptible parents. A sorghum composite (SG IRL-MR-2) had resistance to sorghum midge (Wiseman et al., 1984). Peterson et al. (1989) used yield losses and visual scoring for evaluating germplasm for resistance to midge. Cultivars identified with resistance by both methods were IS8232C, IS8237C, IS81 12C, IS2740C, IS3390C, IS7132C, IS2685C, 1S957C, IS7193C, IS2144C, and IS 12572C. High midge density is required during anthesis to differentiate between resistant and susceptible genotypes.

E. CHINCH BUG ( B~rssusLEUCOPTERUS) The reactions of F3 progenies from the cross of Sharon Kafir (resistant) and dwarf yellow milo (susceptible) indicate that the resistance to chinch bug is governed by a single dominant gene (Painter, 1951). Dahms and Martin (1940) evaluated sorghum hybrids for resistance and found resistance to chinch bug was dominant. Webster et al. (1984) reported resistance to chinch bug governed by one or two dominant genes.

VI. BARLEY Barley is attacked by four common insects: the hessian fly, cereal leaf beetle, greenbug, and corn leaf aphid. A. HESSIAN FLY( MAYETIOLA DESTRUCTOR) Resistance to the hessian fly in barley cultivar Delta is governed by a single dominant gene, Hf,at cooler temperature (Olembo et al., 1966). At higher temperature, resistance is governed by two complementary factors, Hfl and Hf2.

GENETICS OF RESISTANCE TO INSECTS

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B . CEREAL LEAFBEETLE( OULEMA MELANOPUS) Hahn (1968) found a recessive gene for tolerance to cereal leaf beetle in barley variety C166. The mechanism is nonpreference by the larvae for feeding, and differential egg laying. Gallun et al. (1966) identified four barley cultivars, Manchuria, Smooth Awn 86, Sunrise, and Tregal, showing some resistance. Webster and Smith (1979) reported 38% yield loss in seven leaf beetle-susceptible cultivars, which had an estimated density of 1.6 larvae per stem. In general, fewer eggs and larvae were found on resistant barley than on the susceptible cultivars.

C. GREENBUG ( SCHIZAPHIS GRAMINUM) Both tolerance and antibiosis seem to be involved in conferring resistance to the greenbug in barley, and both types of resistance are probably inherited independently. On the basis of reduction in plant growth as a measure of damage, Dahms et al. (1955) determined that resistance was governed by two or more genes. Chada et ul. (1961) and Gardenhire and Chada (1961) reported that resistance in barley cultivar Omugi was controlled by a single dominant gene designated as Grb. No association was found between Grb and several markers of the seven chromosomes. Smith et al. (1962) found that the resistance in Omugi, Dobaku, Kearney, and C.1.5057b varieties was controlled by the same gene. Later, however, Gardenhire (1965) and Gardenhire et al. (1973) found that the dominant gene Grb for resistance was located in the centromeric segment of chromosome 1 of TI-6a translocation. This gene confers resistance to biotypes C and E. Webster and Starks (1984) reported a new source of resistance (PI42676)to biotypes C and E. The cultivar Post is a derivative of Will and carries the Grb gene for resistance from Omugi. Genetic studies involving PI42676 and Post indicated that the resistance in each line is governed by a single dominant gene, and that these two genes are nonallelic and independent (Merkle et al., 1987). The previously assigned Grb is designated as Rsg-la and the newly identified gene as Rsg-2b. D. CORN LEAFAPHID( RHOPALOSIPHUM MAIDIS) Gill and Metcalfe (1977) studied the crosses between resistant parent DL-117 and two susceptible cultivars and found resistance to be dominant. Gulati et al. (1978) studied resistance to corn leaf aphid in barley. The FI was susceptible. The F2 segregation showed that resistance was governed

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GURDEV S. KHUSH AND D. S . BRAR

by two recessive complementary genes. Dayani and Bakshi (1978) found a single recessive gene for resistance to corn leaf aphid in barley cultivar EB92 1. Resistance of barley cultivar DL-200 was found to be due to two recessive complementary genes, s - f and s-2 (Ram, 1983).

VII. COTTON Inheritance of resistance to cotton pests such as boll weevil, thrips, tobacco budworm, jassids, tarnished plant bug, and pink bollworm has been studied by several workers. A. BOLLWEEVIL ( ANTHONOMUS GRANDIS) Resistance to boll weevil is associated with morphological traits that are simply inherited. Characters such as frego bract, red stem color, high degree of plant pubescence, and male sterility contribute toward resistance to boll weevil. The frego bract mutant, having comparatively narrow, elongated, and twisted bracts, inhibits oviposition by weevils until population pressure becomes heavy (Hunter er al., 1965). Pieters and Bird ( 1977) evaluated different cotton genotypes and found that those possessing the okra leaf (L'L") and frego bract (fgfg) had 60% fewer boll weevil ovipositional punctures than the broad-leaved and normal-bracted cottons. Red plant color conditioned by the dominant gene R - f also confers boll weevil resistance. Isely (1928) worked with intense red genotypes and showed a distinct nonpreference of the weevil for red plants. Antibiosis has been found in five Gossypium species and is associated with red plant color (Bailey et al., 1967). Preference and nonpreference have also been associated with red plants and hairy bract. The characters such as frego bract, male sterility, and red color all contribute to nonpreference of A . grandis (Reddy, 1976; Weaver and Reddy, 1977). Boll weevil resistance is also known to be due to a high degree of plant pubescence, controlled by the H - f and H-2 genes (Stephens and Lee, 1961). The H-2 gene contributes more resistance to the boll weevil than H - I . Male sterility also conditions nonpreference by boll weevil. Weaver (1974) and Reddy and Weaver (1975) observed a strong nonpreference for cytoplasmic male-sterile cotton. Glover et al. (1975) observed a similar reaction of boll weevil on male-sterile plants. The boll weevil oviposition was partially suppressed in BC2 F3 progenies derived from crosses of

GENETICS OF RESISTANCE TO INSECTS

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Deltapine 16 with primitive race stocks (T-759, T78) possessing resistance to boll weevil oviposition (McCarty et al., 1982). Weaver (1985) analyzed crosses of high-gossypol BW76-31 x PD 695 (which has an unknown factor for resistance to Heliothis). The F4-derived progenies showed higher tolerance to bollworm than BW76-31; perhaps the two factors for tolerance are synergistic in action. McCany et al. (1986) developed two germplasm lines, MWR-1 and MWR-2, carrying resistance to boll weevil.

( THRIPS SPP.) B. THRIPS

Pilosity affects resistance to thrips in upland cotton. Ramey (1962) studied the genetics of pubescence in cotton relative to thrips resistance. Three partially dominant genes, H - / and H-2 (hairy) and Sm (glabrous), affected pilosity (nonpreference). H - / has been used in Africa to reduce attack by jassids. The presence of both H - / and Sm results in very few trichomes and increased pubescence of the terminals. Thus, genotypes having both the H - / and Srn have reduced thrip susceptibility in the terminals. Quisenberry and Rummel (1979) also found that pilose ( H-2 ) was associated with a high level of resistance to thrips. Other morphological characters such as okra-leaf shape ( L " ) , red plant color ( R - I ) , glandless ( g l - 2 , g l - 3 ) , nectariless ( n e - I , ne-2), or smooth-leaf (Sm-/, Sm-2 ) did not contribute to the resistance of plants. The leaf area damaged by thrips was less on the pubescent Tamcot SP-37 cultivar than on the glabrous Tamcot SP-21. Endrizzi and Ramsay (1983)found that H-1, H-2, and SM-2 are all located on the long arm of chromosome 6, about 4 crossover units from the centromere. Allele tests between the three genes showed that they are allelic. c . TOBACCO BUDWORM ( HELIOTHIS VIRESCENS) Glands on cotton plants produce gossypol, which confers resistance to tobacco budworm. Shaver et al. (1980) found a significant linear relationship ( r = 0.86-0.90) between reduction in larval weight of budworm and gossypol content in flower buds of the cotton plant. A high density of glands and a high concentration of antibiosis type of resistance are positively correlated with nonpreference and antibiosis type of resistance. Two dominant genes, (31-2 and (31-3, are responsible for the presence of glands and hence resistance. Most of the currently grown commercial cotton varieties in the United States have glands and are of the genotype G1-2 GI-2 GI-3 (31-3. Wilson and Lee (1971) showed that seedling damage to

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GURDEV S. KHUSH AND D.S.BRAR

cotton was least and larval numbers were lowest on genotype GI-2 GI-2 GI-3 G1-3, intermediate on gl-2 gl-2 G1-3 GI-3, and GI-2 G1-2 gl-3 gl-3, and highest on glandless genotype gl-2 gl-2 gl-3 gl-3. The two genes appear to act additively. Singh and Weaver (1972) found that low gossypol level was dominant to high gossypol level and that the gossypol level in flower buds was conditioned by a single gene. Maxwell et ai. (1976) reported that the nectariless trait reduces the incidence of bollworms on cotton plants. Meredith et al. (1979) studied the effect of cytoplasm of five Gossypium species. The cytoplasm of G . tomentosum (with AD3 genome) decreased the weight of 7-day-old larvae of tobacco budworm by 35% but increased the number of leafhoppers by 70%. These findings suggest that a back-up cytoplasmic system could be developed to reduce the damage of tobacco budworm and other insects like leafhopper on cotton. Jenkins et al. (1982) developed a technique for uniformly infesting a large number of field plots with first-instar larvae of tobacco budworm. With that technique, Jenkins et al. (1986) screened 30 cotton genotypes and found Stoneville 506 and Tamcot CAMD-E as sources of resistance to budworm. The results indicated the possibility to increase budworm resistance by direct selection for the ability to resist yield loss when progenies are uniformly infested with tobacco budworm. MHR-1 composite of cotton resistant to tobacco budworm has been developed (Jenkins et al., 1984), and several germplasm lines of cotton resistant to tobacco budworm and boll weevil have been developed (Culp et al., 1990).

SPP.) D. JASSIDS ( EMPOASCA

Jassid is a serious pest of cotton in Africa and India. The main source of resistance has been the Cambodia cottons from India, which have hairy leaves and stems. Pubescence (hairiness) is usually associated with jassid resistance. Knight (1952)showed that resistance in G . barbadense was due to a partially dominant gene H-1, together with several modifier genes. Hairiness and jassid resistance were also controlled by a dominant gene in varieties of G . hirsutum, G . tomentosum, and G . arboreum. Knight and Saad (1953, 1954) and Knight (1954) reported that the gene controlling hairiness in upland variety Pubescent T661 was identical with the G. tomentosum gene H-2. The gene H-1 is linked with chl-1. In addition to H-2, G . herbaceum carries minor H genes and modifying genes that affect hair length. Muttuthamby et al. (1969) found that two complementary genes, H-1 and H-2, controlled hairiness. One gene was present in Pak 51

GENETICS OF RESISTANCE TO INSECTS

25 1

and L l l from Pakistan, and the other in Empire Red Leaf and Acala. Hairiness, and hence jassid resistance, was a simply inherited and dominant trait. The variety Hirsu-anom (H59) resistant to jassids has been derived from a G. hirsutum and G. anomalum cross. Hairiness is associated with jassid resistance but with susceptibility to oviposition by bollworms. Hence it is difficult to get high expression of resistance to both jassids and bollworms in a single variety.

E. TARNISHED PLANTBUG ( LYGUSLINEOLARIS) Although glabrousness is a desired trait because it confers resistances to bollworm, pink bollworm, and tobacco budworm, Meredith and Schuster (1979) found that glabrous cottons were more sensitive to plant bugs than the pubescent cottons. Germplasm improvement for tolerance for plant bugs can be facilitated through field evaluations of Sm-2 sm-2 (glabrous isoline) hybrids. Meredith et al. (1979) did not find any evidence of variation in tolerance for tarnished plant bugs in five cytoplasmically different cottons. Bailey et al. (1984) compared nymph emergence on nectaried and nectariless isolines of Deltapine 16 cotton. The nectariless trait significantly reduced the number of plant bug nymphs.

F. PINKBOLLWORM ( PECTINOPHORA GOSSYPIELLA) Pink bollworm is a serious pest of cotton. The genetic variability for pink bollworm resistance is rather limited, Also, the stocks of cotton resistant to pink bollworm are usually inferior to commercial cultivars in agronomic and fiber properties. A low level of resistance has been shown by cottons carrying mutant characters such as okra leaf Lo-2 and smooth or glabrous leaf. The glabrous trait is conditioned by three genes designated as Sm, Sm-1, and Sm-2 (Lee, 1971). Wilson and George (1979) studied the combining ability for pink bollworm resistance in two cultivars and four breeding stocks. Two breeding stocks, Texas 167 and AET-5, showed significant general combining ability for low seed damage; specific combining ability was not significant. In another study involving 6 parents, 15 F1 hybrids, and reciprocals, Wilson and George (1980) found significant general combining ability estimates, thus suggesting the possibility of transferring resistance to pink bollworm from Texas 167 to other cultivars without much difficulty. Crosses of AET-5 with a nectariless breeding line ( n e - 1 , ne-2) showed the gene to be primarily additive for seed damage, the

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GURDEV S. KHUSH AND D.S. BRAR

narrow-sense heritability estimates being significant. The genotype x environment interaction was not significant and resistance was conditioned by as few as two genes (Wilson and George, 1983). Wilson and George (1982) analyzed eight isolines of okra leaf, frego bract, and smooth leaf in LA71-7 (Stoneville) background. The results indicated that okra leaf imparts resistance to pink bollworm whereas frego bract isolines did not show significant increase in resistance over normalbract counterparts. The smooth leaf did not show any advantage for pink bollworm resistance. In another study, Wilson (1987) studied isolines of morphological markers: nectariless, okra leaf, and smooth leaf in AET-5, a pink bollworm-resistant stock. The resistance level increased by transferring nectariless (N) or okra leaf (L) but not by smooth leaf (S). Further, transferring both N and L in AET-5 did not show significant increase in the resistance level above the level found in either N or L isolines.

VIII. FRUITS The genetics of resistance to several insects that attack the fruits has been studied. A few examples are discussed. A. ROSYLEAFCURLING APHIDOF APPLE( DYSAPHIS DEVECTA) High levels of resistance to the rosy leaf curling aphid have been detected. Four genes governing resistance to three aphid biotypes have been identified (Alston and Briggs, 1968, 1977). Apple cultivars and young seedlings were repeatedly infested with leaf curling aphid from six locations in southeast England to determine their reaction to the insect. Resistance to each biotype is determined by two dominant genes, a basic or precursor gene and a biotype-specific gene. Three genes for resistance to aphid have been detected. The Cox’s orange pippin carries the gene Sd-1 for resistance to biotypes 1 and 2, and Northern spy had Sd-2 for resistance to biotype 1. A single gene Sd-3 was identified conferring resistance to biotype 3 in Malus robustra Ma1 5919 and M . zumi Ma1 6815. Worcester Pearmin, Cox, McIntosh, and Lanes Prince Albert are heterozygous for a precursor gene Sdpr without which Sd-1, Sd-2, and Sd-3 are ineffective. The cultivars James Grieve, Northern spy, Ashmeads kernel, and Cox’s orange pippin possess single genes for resistance.

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PLANTAGINEA ) B. ROSYAPPLEAPHID( DYSAPHIS

Resistance to rosy apple aphid is governed by a single dominant gene, Smh (Alston and Briggs, 1970). No biotypes have been reported.

C . WOOLYAPPLEAPHID( ERIOSOMA LANICERUM) The wooly apple aphid has a very wide host range and is known to attack several fruits such as apple and pear, and trees such as hawthorn, mountain ash, and elm. Resistance in apple cultivars has existed in heterozygous condition for more than 100 years (Painter, 1951). The cultivar Northern spy possesses a single dominant gene, Er, for resistance, closely linked to a gene for pollen sterility (Knight et al., 1962). Some resistant cultivars such as Winter Mayetin and MM-112 in crosses with susceptible types do not give clear segregation into resistant and susceptible types (Knight, 1968). MacKenzie and Cummins (1982) showed a different genetic system controlling resistance in Robustra 5 (R5). About 10% of seedlings from R5 x M9 and R5 x M27 were as immune to wooly aphid as R5 and about 25% were resistant but not immune. Bowman and Cummins (1984) found that resistance in the R5 is controlled by a single dominant gene.

D. RUBUSAPHID( AMPHOROPHORA RUM) Aphid-transmitted virus diseases and direct feeding damage are common causes of serious yield losses in raspberry crops. A large number of cases of host resistance to Rubus aphid have been reported. Schwartze and Huber (1937) reported that the resistance of the cultivar Lloyd George was controlled by two dominant genes. Knight et al. (1959) identified a dominant gene A-1 in the resistant variety Baumforth A. The gene A-1 provides strong resistances to strains 1 and 3 . A-I is linked with the normal allele of a semilethal dwarfing gene fr-I. Keep (1989) summarized the interaction of genes for resistance with four biotypes of Rubus aphid (Table IV). Knight et af. (1960) identified a number of genes for resistance to the Rubus aphid. The cultivar Chief has six dominant genes: A-5, A-6, A-7, for resistance to strain 1, and A-2, A-3, and A 4 for resistance to strain 2. The A-2 gene is dominant and confers complete resistance by itself, but A-3 and A 4 are dominant complementaries since neither, by itself, can convey any resistance. A-l confers resistance to strains 1 and 3. In combinations with A-3, it also gives resistance

254

GURDEV S. KHUSH AND D. S. BRAR

Table IV Reaction of Rubus Species with Specific Genes for Resistance to Four Known Biotypes of Rubus Aphid" Plant reaction to biotypesb Genes for resistance

Rubus species

R . idaeus Baumforth A Chief Chief Chief Chief Chief Chief R . idueus strigosus L 518 L 519 R. occidentalis Cumberland ( R . idaeus) Klon 4a R . coreanus R. coreanus

1

2

3

4

A-1 A-2 A - I , A-3 A-3, A 4

R S

A-5 A-6 A- 7

R R R

S R R R S S S

R S R S S S

S S S S S S S

A-8 A-9

R R

R R

R R

R R

A-I0

R

R

R

R

A-kln A-car 1 A-cor 2

R

R R R

R

R R

R S

R -

S

R S

-

From Keep (1989). Adapted by permission from Plant Breeding Reviews (Janick, ed.), 6. 0 1989 by Timber Press, Inc.

R, Resistant; S, susceptible; -, not known.

to strain 2. The fourth strain of the aphid is able to develop on Malling Landmark, which is resistant to strains 1 and 3 (Briggs, 1965). The genes A-8 and A-9 from Rubus idaeus strigosus selection provide moderate resistance to all four strains (Knight, 1962). Keep and Knight (1967) identified another gene, A-10, for resistance to strains 1, 2, and 3. Most of the breeding lines at East Malling, United Kingdom, carry the gene A-I0 from the black raspberry cultivar Cumberland. This gene has remained fully effective over six generations of backcrossing (Keep, 1984). Keep et al. (1970) showed that resistance to all four strains in Klon 4A is governed by a single dominant gene, A-k4a. The resistance of R . occidentalis cultivar, L503,i s conditioned by a single dominant gene, which is probably identical to A-10. Major genes for resistance to leaf aphid have been found in several Rubus varieties including the wild species. There is a specific interaction between some of the resistance genes and individual A . idaei strains (Table

GENETICS OF RESISTANCE TO INSECTS

255

IV), whereas other resistance genes are effective against all known populations of this aphid. The wild raspberries, including R . odoratus and R . procerus, have many new genes for resistance. Keep and Parker (1974) identified gene A-1 for resistance to strains 1 and 3 in Malling Delight, and A-10 in Leo, which conveys resistance to four biotypes in the United Kingdom. The cultivars Glen and Clova have partial resistance, which is controlled by several minor genes. Jones (1976) found that varieties such as Glen Clora and Norfolk Giant with minor genes for resistance showed less infestation of A . rubi and slow virus spread. The two other cultivars Malling Orion with A-1 and East Malling selection (888/49) with A-10 remained free of virus. Another species of aphid, Arnphorophora aguthonica, occurs on wild and cultivated red and black raspberries. The gene Ag-1 confers resistance to this species in Lloyd George (Daubeny, 1966, 1972).Daubeny and Stary (1982) identified dominant complementary genes Ag-2 and Ag-3 from wild R . idaeus strigasus. Daubeny and Sjulin (1984) have selected promising germplasm (BC72-1-7) homozygous for Ag-1. E. BLACK CURRANT LEAFCURLING MIDGE( DASYNEURA TETENSI) Leaf curling midge is a pest of nursery stocks of black currant (Ribes spp.). Resistance is lacking in the old western European cultivars of R . nigrum. However, cultivar Ben Sarek from the Scottish Crop Research Institute shows a high degree of resistance. Keep (1985b) reported that resistance to midge in R . dikuscha derivatives is controlled by a single dominant gene designated D t . The Sunderbyn 11, a derivative of R . dikuscha, also showed major genes governing midge resistance. The Dt gene was found to be linked with mildewresistance gene(s) in R . dikuscha.

F. BLACKCURRANT GALLMITE ( CECfDOPHYOPSlS R I B I S ) Susceptibility of black currant ( Ribes nigrum ) germplasm to gall mite is an important problem in Britain. The main donor of resistance to gall mite is the gooseberry. Knight et a / . (1974) transferred resistance to gall mite from gooseberry to black currant through backcrossing. Keep (1985a) reported that the gene Ce governing gall mite resistance is linked with Lf-1, one of the two genes controlling season of leafing out. The genes Ce and Rf-Z are linked with crossover values of 0.14 while Ce and Lf-1 are located at a distance of 36 map units (Keep, 1986).

256

GURDEV S. KHUSH AND D. S. BRAR

G. REDSCALEPESTOF CITRUS( AONIDIELLA AURANTII) Red scale is a serious pest of citrus crops. Cameton et al. (1969) reported resistance to be quantitatively inherited.

IX. VEGETABLES The genetics of resistance to insects in several vegetable crops, particularly the cucurbitaceous species, has been studied. Some examples follow.

A. MELONAPHID( A P H I S GOSSYPII) The melon aphid causes damage to the host and is also an important vector of muskmelon virus. Kishaba et al. (1971) screened melon germplasm and identified LJ90234, a resistant source. Resistance to melon aphid is manifested by antixenosis (nonpreference), tolerance, and antibiosis. Tolerance is controlled by at least two dominant genes (Bohn et al., 1973). Kishaba et al. (1976) postulated that at least two dominant genes control antibiosis. McCreight et al. (1984) using backcrossing procedures developed three muskmelon aphid-resistant breeding lines (AR Hale’s Best Jumbo, ARS, and AR-Topmark). B. REDPUMPKIN BEETLE( AULACOPHORA FOVEICOLLIS) The red pumpkin beetle is a serious pest of summer squash and causes heavy damage during early phases of plant growth. Both field and cage evaluations have been employed to identify the resistance sources (Nath, 1966, 1971; Dhillon and Sharma, 1989). Dhillon and Sharma (1989) evaluated resistance in 22 summer squash genotypes and found heritability values of 87% and 78%, respectively, under field and cage conditions. Vashistha and Choudhury (1974) studied the inheritance of resistance to the red pumpkin beetle in muskmelon. A single dominant gene was found to confer resistance. VITTATUM) C. STRIPED CUCUMBER BEETLE( ACALYMMA

Nath and Hall (1963) found that resistance to striped cucumber beetle in resistant squash cultivars Royal Acorn and Early Golden Bush Scallop was governed by several genes.

GENETICS OF RESISTANCE TO INSECTS

257

Chambliss and Jones (1961) demonstrated that susceptibility of squash to the spotted cucumber beetle was correlated with concentration of cucurbitacins; the higher the cucurbitacin content, the greater was the damage done by beetles. Sharma and Hall (1971) also found that in Cuciubitapepo, cultivars with reduced cucurbitacin content are less attractive to the spotted cucumber beetle and that a single recessive gene is responsible for reduced cucurbitacin content. This gene in Early Golden Bush Scallop was designated as cu.

D. TWO-SPOTTED CUCUMBER SPIDERMITE( TETRANYCHUS URTICAE) In earlier studies, resistance to the two-spotted cucumber spider mite was reported to be associated with bitter principle, cucurbitacin C (Kooistra, 1971). From the study of a cross of bitter and nonbitter parents, Da Costa and Jones (1971) reported that the resistance was due to the presence of cucurbitacin C regulated by the gene Bi. De Ponti (1979) provided evidence that cucurbitacin may not be involved in resistance but the association between resistance and cucurbitacin may be due to linkage between genes for these traits. De Ponti and Garretsen (1980) found that resistance to the two-spotted spider mite as determined by acceptance and oviposition was determined by several genes, with additive gene action. Because of the relatively low and variable heritability for resistance, selection in segregating generations should be followed by at least one generation of line selection before making backcrosses.

BUG( ANASAm r s n s ) E. SQUASH The squash bug attacks all the cucurbits and vine crops, but the insect shows a marked preference for squashes and pumpkins. Pearson et al. (1951) in a study of an interspecific cross (Cucurbita moschata x C . maxima ) showed resistance to be dominant. Benepal and Hall (1967) studied the inheritance of resistance to the squash bug in summer squash varieties and found that resistance was partially dominant and quantitative in nature. The results indicated higher additive variance than the dominance variance.

F. PUMPKIN FRUITFLY ( DACUSCUCURBITAE 1 Fruitfly is one of the most serious insect pests of cucurbitaceous crops and has a wide host range, attacking several species of vegetable crops.

258

GURDEV S. KHUSH AND D. S. BRAR

Chelliah and Sambandam (1973) studied the interspecific cross of Cucumis callosus and C . mefoand found resistance to the fruitfly to be controlled by complementary dominant genes. Nath et al. (1976) reported that the resistance in pumpkin cultivar Arka Sweya Mukhia was controlled by a single dominant gene, Fr. G . LETTUCE ROOTAPHID (PEMPHIGUS BURSARIUS) Lettuce root aphid is an important pest of summer lettuce, particularly in the United Kingdom and parts of northern Europe and the United States. The reaction of progenies from crosses of resistant cultivars, Avoncrisp and Avondefiance, with two susceptible varieties, including reciprocals, indicated that resistance is controlled by cytoplasmic as well as genetic factors (Dunn, 1974). Resistance to root aphids in lettuce varieties derived from Imperial 45634-M is cytoplasmically inherited. Modifying genes might also be involved. Crute and Dunn (1980) reported that many varieties with high resistance to root aphid also carried the gene Dm-6 for specific resistance to downy mildew, thus suggesting the possibility of linkage between the genes controlling resistance to root aphid and downy mildew.

H. LETTUCE LEAFAPHID( NASONOVIA RIBISNIGRI) Leaf aphid is a problem in lettuce growing, as it damages the crop by feeding, and transmits virus diseases. Nasonouia ribisnigri is common in the Netherlands and is particularly harmful because it feeds on the youngest leaves and deforms plants. Eenink er al. (1982b) transferred resistance from Lactuca uirosa to cultivated lettuce (L. sativa) by using L. serriola as a bridging species. This resistance is governed by a dominant gene, Nr (Eenink et a f . , 1982a). Reinink and Dieleman (1989) tested three lines of lettuce possessing resistance to N. ribisnigri and four lines showing partial resistance to another aphid species ( M y z u s persicae). Two biotypes, WNI (N. ribisnigri), and WMpL ( M . persicae ), were used for screening lettuce lines. The gene Nr also gives partial resistance to another aphid species ( M . persicae), but the level of resistance is influenced by other genes. 1. ARTHROPOD PESTS OF TOMATO

Several species of arthropod insects attack tomato species. The wild species are known to possess high levels of resistance or near immunity to

GENETICS OF RESISTANCE TO INSECTS

259

16 such pests. Among these species, Lycopersicon hirsutum provides high resistance to 14 of these parasites and is the only known source of resistance to 9 pests (Rick, 1982).The nature of resistance differs for each pest. Some accessions, PI126449, PI127826, and PI134417-3 of L . hirsutum show a high degree of resistance to tomato fruitworm (Fery and Cuthbert, 1974; Dimock and Kennedy, 1983). Recently, Sinha and McLaren (1989), using petri dish bioassay technique, identified several other accessions of wild species resistant to both tomato fruitworm and cabbage looper. Fery and Kennedy (1983) observed a strong association between tobacco hornworm resistance in tomato and 2-tridecanone concentration. Resistance to tobacco hornworm and high levels of 2-tridecanone was conditioned by three recessive genes.

X. FORAGES AND LEGUMES The sources of resistance to a number of insects that attack forages and legume crops have been identified. The genetics of resistance in some of them has been investigated.

VARIVESTIS) A. MEXICAN BEANBEETLE( EPILACHNA

The Mexican bean beetle is a major insect pest of soybeans in the southern and mid-Atlantic states of the United States. Van Duyn et al. (1971) identified germplasm lines PI 171451, PI227687, and PI229358 showing resistance to oviposition and feeding. Kogan (1972) found that the F1 progenies of a cross between resistant and susceptible parents had intermediate reaction. Sisson et al. (1976) evaluated F3 lines from the crosses between resistant and susceptible cultivars and the results indicated a quantitative inheritance of resistance. Two or three major genes for resistance also were suggested (Kilen et al., 1977; Kilen and Lambert, 1986). Rufener et al. (1989) used antibiosis technique to analyze crosses involving resistant and susceptible parents. The resistance of F I plants was intermediate to that of their parents. The distribution of F2 was continuous. However, the number of segregating loci was small. Mebrahtu et al. (1990) reported that several genes may be involved in conditioning resistance. The genotypic correlations indicated that the genes governing resistance also influenced lodging and maturity in soybean. Such analysis indicates the difficulty of selecting Mexican bean beetle-resistant, early-maturing, and lodging-resistant soybean lines. Kraemer et af. (1988, 1990) have

260

GURDEV S . KHUSH AND D. S. BRAR

identified several new resistant sources from different maturity groups of soybean. B. BEANWEEVIL( CALLOSOBRUCHUS CHINENSIS) A single dominant gene ( R ) has been found to govern the resistance to Azuki bean weevil (Kitamura et al., 1988). The wild species ( Vigna sublobata) strain TC1966 carries a gene for resistance to the weevil. Ishimoto and Kitamura (1988) found that a-amylase inhibitor is involved in imparting resistance to the Azuki bean weevil. Morphological features such as hairiness of the pod and seed coat hardness also confer some degree of resistance to this pest (Talekar and Lin, 1981). C. COWPEASEEDBEETLE( CALLOSOBRUCHUS MACULATUS) Cowpea seed beetle, commonly known as bruchid, causes loss during storage. Singh et al. (1985) screened 8,000 germplasm lines of cowpea and identified three (TVu2027, TVull952, TVull953) resistant sources. Adjadi et d.(1985) studied the F I , FZ,and backcross populations involving three resistant (TVu202, TVull952, TVull953) and two susceptible (TKx133-16D-2, cross 1-6E-2) parents. The resistance to bruchid was controlled by two recessive genes, designated as rcrn-f and rcrn-2. The level of trypsin inhibitor has been found to be correlated with resistance to cowpea seed beetle (Gatehouse and Boulter, 1983).

D. COWPEAAPHID( APHIS

CRACCI~ORA )

The cowpea aphid is a major insect pest of cowpea, particularly in Africa and Asia, and causes direct damage by feeding on seedlings, flowers, and pods and indirect damage by transmitting mosaic viruses. The inheritance of resistance to the aphid was studied in crosses of three resistant (TVu36, TVu801, TVu3000) and three susceptible (TVx3236, IT82E-16, IT82E-60) parents. The segregating populations were screened in the greenhouse using artificial infestation with aphids. The resistance was found to be controlled by a single dominant gene (Bata et al., 1987).The three resistant cultivars, TVu36, TVu801, and TVu3000, have the same gene for resistance, designated Rac. Pathak (1988) also determined the inheritance of resistance from the F, ,FZ,and BC1 populations arising from the crosses of four resistant cultivars, ICVlO, ICVll, ICV12, and TVu310, with suscep-

GENETICS OF RESISTANCE TO INSECTS

26 1

tible cultivar ICV1. The resistance in each of these cultivars was governed by a single dominant gene. Two independent genes, Rac-1 and Rac-2, were identified. MACULATA) E. SPOTTEDALFALFAAPHID ( THERIOAPHIS

The spotted alfalfa aphid was first reported in the United States in 1954 and is now considered the most widespread and serious pest of alfalfa. Howe and Smith (1957) found the cultivar Lahonton to be resistant to spotted alfalfa aphid and attributed the resistance to antibiosis and tolerance. Since then Lahonton has been used in the development of a large number of varieties and synthetics. Howe et al. (1963) studied polycrosses of six clones and indicated that antibiosis was a heritable trait. Jimenez et al. (1989) studied heritability for spotted alfalfa aphid tolerance, which was 25% in selfed progeny and 20% in polycross progeny. Reduction in heritability of tolerance suggests that dominance effects may control expression of this trait. Pesho et al. (1960) recognized the first biotype ENT-A to distinguish it from ENT-B, the original population introduced in the United States in 1954. Several distinct biotypes of T. maculata have been identified and there is a gene-for-gene relationship between some of these biotypes and specific plants of the variety Hayden (Nielson and Don, 1974). Most of the biotypes were differentiated on the basis of their response to nine parent clones of Moapa cultivar. Stanford (1977) identified four biotypes, each of which attacks a different set of alfalfa cultivars. The interactions between the clones of alfalfa and the biotypes of the aphid suggest a gene-for-gene relationship between the host plant and the insect. Nielson and Olsen (1982) and Nielson and Kuehl(1982), however, suggest that certain alfalfa clones such as Lahonton and Mesa-Sirsa are a source of genes for horizontal resistance. Some germplasm lines, KS187, KS189, and KS108 GH5, having resistance to spotted alfalfa aphid, have been developed (Sorensen et al., 1985a, 1985b, 1986).

F. PEA APHIDOF ALFALFA ( ACYRTHOSIPHON PISUM) Resistance is usually associated with a high concentration of saponins in the tissues of the host plant. Jones ef al. (1950) and Glover and Stanford (1966) found that the resistance was controlled by a single dominant gene. Several biotypes of the insect are known. Recurrent selection procedures have been used to develop promising germplasm possessing multiple resis-

262

GURDEV S. KHUSH AND D. S. BRAR

tance to pea aphid and spotted alfalfa aphid, including resistance to diseases (Sorensen et al., 1985b, 1986).

G. SWEET CLOVER APHID( THERIOAPHIS

RIEHMI)

The mechanism of resistance to the sweet clover aphid is of the nonpreference type. Manglitz and Gorz (1968) studied the F, , F2, and backcross progenies from the crosses of resistant and susceptible cultivars and found that a single dominant gene conveyed resistance. An additional complementary gene for resistance appeared to be present in some resistant cultivars.

XI. TAGGING INSECT TOLERANCE GENES WITH MOLECULAR MARKERS During the last 5 years, RFLP (restriction fragment length polymorphism) maps have been developed in various crop plants such as maize, tomato, potato, rice, lettuce, and others. The RFLP markers can be used to tag genes governing agronomic traits including quantitative trait loci (QTL) and genes for insect resistance. Nieunhuis et al. (1987) detected association of some RFLP loci with QTL, affecting expression of insect resistance in a wild species (L. hirsutum ) of tomato. The F2 ( L . hirsutum x L . esculentum ) population was assayed calorimetrically for a toxic methyl ketone compound, 2-tndecanone (2TD), for insect resistance. The RFLP loci on three different linkage groups were found to be associated with expression of calorimetric absorbance. RFLP-based selection may be helpful in increasing the frequency of favorable alleles associated with expression of 2TD-mediated insect resistance. Zamir et al. (1984) found that the morphological markers s p and sti and the isozyme locus Prx-7 were associated with expression of 2TD. In rice, the gene Wbph-Z governing resistance to whitebacked planthopper has recently been tagged with RFLP marker (RG 148) (S. McCouch, personal communication). It is expected that in the future, tagging of genes governing insect tolerance with molecular markers would facilitate selection for desired genotypes possessing increased tolerance for insect pests.

GENETICS OF RESISTANCE TO INSECTS

263

XII. GENETIC ENGINEERING AND INSECT TOLERANCE Recent advances in molecular biology have made it possible to clone useful genes for insect resistance from a number of sources and for their introduction into crops to produce transgenic crop plants with new genetic properties (Uchimiya et al., 1989). Two notable examples include Bt gene from Bacillus thuringiensis and trypsin inhibitor gene ( CpTi ) from cowpea. The Bt gene has been cloned and introduced into tobacco, tomato (Sekar et al., 1987; Vaeck et a/., 1987; Fischhoff et al., 1987), and other crops. The resulting plants have been tested under both laboratory and field conditions (Fraley, 1988). Larvae of lepidopteran insects that fed on transgenic plants produced very little feeding damage. The information available on laboratory as well as field tests indicates that introduction of insect toxin genes into plants would be a practical method for providing protection against certain insect pests. Another approach is to produce genetically engineered plants capable of producing serine proteinase inhibitors. Hilder et al. (1987) cloned a gene from cowpea ( Vignu unguiculata) encoding for a trypsin inhibitor. When introduced into tobacco, this gene imparted resistance to Heliothis virescens. It appears that introduction of such cloned genes would be another method of producing insect-tolerant germplasm.

XIII. CONCLUSIONS This article demonstrates that considerable information on genetics of resistance to insects of major crops has been obtained and many genes for resistance have been identified (Table V). These genes have been utilized in developing insect-resistant cultivars. Insect-resistant cultivars of major food crops such as rice, wheat, corn, sorghum, and barley are grown on millions of hectares annually. Farmers who grow these cultivars save billions of dollars in insecticide costs and supply lower cost food to the consumer. Insect-resistant cultivars have greater yield stability and thus are responsible for greater food security. As an example, rice variety IR36, which is resistant to brown planthopper, green leafhopper, yellow stem borer, striped stem borer, and gall midge was planted in over 10 million ha of riceland of the world annually (IRRI, 1982). Its cultivation alone yielded an additional income of one billion dollars annually to rice growers and

264

GURDEV S . KHUSH AND D. S. BRAR Table V Genetics of Resistance to Ma.ior Insect Pests of Crop Plants

Crop Rice

Insect pest Brown planthopper Whitebacked planthopper Green leafhopper Zigzag leafhopper Gall midge Striped stem borer

Wheat

Maize

Sorghum

Barley

Cotton

Apple

Raspberry

Hessian fly

Greenbug Cereal leaf beetle Wheat stem sawfly European corn borer Corn earworm Western corn rootworm Corn leaf aphid Fall armyworm Spotted stem borer Corn leaf aphid Greenbug Shoot fly Sorghum midge Chinch bug Stem borer Hessian fly Cereal leaf beetle Greenbug Corn leaf aphid Boll weevil Thrips (Thrips spp.) Tobacco budworm Jassids (Empoa.tccr spp.) Tarnished plant bug Pink bollworm Rosy leaf curling aphid Rosy apple aphid Woolly apple aphid Rubtts aphid, (Atnphorophora rubi) ( A . aguthonica)

Gene(s) for resistance Bph-I, bph-2, Bph-3, bph-4, bph-5, Bph-6, bph-7, bph-8, Bph-9 Wbph-1, Wbph-2, Wbph-3, wbph-4, Wbph-5 Glh-1 Glh-2, Glh-3, glh-4, Glh-5, Glh-6, Glh-7, glh-8 Zlh-I, Zlh-2, Zlh-3 Gm-I, Gm-2 Monogenic (antibiosis) Polygenic (tolerance) H-I, H-2. H-3. h-4. H-5, H-6, H-7, H-8, H-9, H-10, H-119 H-12, H-13, H-14, H-15, H-16, H-17, H-18, H-19 gb (Gh-l),Gb-2, Gb-3, Gb-4, Gh-5 2-3 genes, polygenic (leaf pubescence) 1-4 genes (stem solidness) Pol ygenic Pol ygenic Monogenic, pol ygenic Monogenic, polygenic Pol ygenic Polygenic

Monogenic, 2-3 genes Polygenic, tr (trichome on leaf surface) 2-3 genes, polygenic Monogenic, 1-2 dominant genes Pol ygenic H-.L Hf-1 , Hf-2 Monogenic Grb (Rsg-la),Rsg-2b s - 1 s-2 (complementary) A few genes (pubescence, frego bract, okra leaf) H-I, H-2, Sm (hairiness, smooth leaf) nonpreference GI-2, GI-3 (nonpreference/antibiosis) H , H-1, H-2, a few modifiers (hairiness) A few genes, polygenic

S d - I , Sd-2, Sd-3, Sd-pr Stnh Er A-I, A-2, A-3, A l l . A-5, A-6, A-7. A-8, A-Y?A-10, A - k h , A-iorl, A-cor2 Ag-1, Ag-2 Ag-3 (complementary)

GENETICS O F RESISTANCE TO INSECTS

265

Table V (ctmrinired) Crop Black currant Citrus Muskmelon Cucumber Summer squash Pumpkin Lettuce Okra Tomato Potato Soybean Mung bean Common bean Cowpea Alfalfa

Insect pest

Gene(s) for resistance

Leaf curling midge Gall mite Red scale Melon aphid Red pumpkin beetle Striped cucumber beetle Two-spotted spider mite Squash bug

Dl

Fruitfly Leaf aphid Root aphid Cotton jassid Fruit borer Potato tuber moth Mexican bean beetle Azuki bean weevil Leafhopper Cowpea aphid Cowpea seed beetle Spotted alfalfa aphid Pea aphid of alfalfa Sweet clover aphid

Fr (two complementary dominant genes) Nr Cytoplasmic and nuclear genes (modifiers) Polygenic, monogenic (cotyledonary stage) Pol ygenic A few genes, polygenic 2-3 genes, polygenic Monogenic Pol ygenic Rac. Roc-I, Roc-2 rcm-1, rcm-2 A few major genes Monogenic Monogenic

CE

Polygenic Monogenic Monogenic, polygenic cu, polygenic Bi. polygenic Pol ygenic

processors. Numerous rice cultivars with multiple resistance to insects have been developed and are widely grown (Khush, 1989). However, for the continued success of host resistance, we must have dynamic programs for gene identification. New genes for resistance must be continuously utilized in breeding programs to ensure the availability of resistant cultivars when old ones become susceptible because of the development of new biotypes. Various strategies for utilization of resistance genes in host resistance programs have been discussed by Gallun and Khush (1980). Insect-resistant cultivars are the major components of integrated pest management programs. REFERENCES Abdel-Malek, S . H., Heyne, E. G., and Painter, R. H. 1966. J . Econ. Entornol. 59,707-710. Adjadi, O., Singh, B . B., and Singh, R. R. 1985. Crop Sci. 25,740-742. Aganval, B. L., and House, L. R. 1981. In “Sorghum in the Eighties,” pp. 435-446. ICRISAT, Hyderabad, India.

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Obanni, M., Ohm, H. W., Foster, J. E . . and Patterson, F. L. 1989b. Crop Sci. 29,267-269. Oellermann, C . M., Patterson, F. L., and Gallun, R. L. 1983. Crop Sci. 23,221-224. Olembo, J . R., Patterson, F. L., and Gallun, R. L. 1966. Crop Sci. 6, 563-566. Onukogu, F. A., Guthrie, W. D., Russell, W. A., Reed, G. L., and Robbins, J. C. 1978. J . Econ. Entomol. 71, 1-4. Ortman, E. E., Branson, T. F., and Gerloff, G. D. 1974. Proc. Summer Inst. Biol. Control Plant Insects Dis., 1972, pp. 344-358. Page, F. D. 1979. Aust. J . Exp. Agric. Anim. Husb. 97, 101. Painter, R. H. 1951. “Insect Resistance in Crop Plants.” Macmillan, New York. Painter, R. H., and Pathak, M. D. 1962. Proc. l n t . Congr. Entomol. Ilth, 1960 pp. 110-1 15. Painter, R. H . , and Peters, D. C. 1956. J . Econ. Entomol. 49,546-548. Patch, L. H., Holbert, J . R., and Everly, R. T. 1942. US., Dep. Agric., Tech. Bull. 823,l-22. Pathak, M. D., and Saxena, R. C. 1976. Curr. Adv. Plunt Sci. 8, 1233-1252. Pathak, M. D., Cheng, C. H., and Fortuno, M. E. 1969. Nature (London)223,502-504. Pathak, R . S. 1988. Crop Sci. 28,474-476. Patterson, F. L.. and Gallun, R. L. 1973. Proc. Int. Wheat Genet. S y m p . , 4th, 1973 pp. 445-449. Patterson, F. L., and Gallun, R. L. 1977. J . Hered. 68,293-296. Patterson, F. L., Foster, J. E., and Ohm, H. W. 1988. Crop Sci. 18,652-654. Pearson, 0. H . , Hopp, R., and Bohn, G. W. 1951. Proc. Am. SOC. Hortic. Sci. 57,310-322. Peiretti, R. A., Amini, I., Weibel, D. E., Starks, K. J., and McNew, R. W. 1980. Crop Sci. 20, 173- 176. Penny, L. H., and Dicke, F. F. 1956. Agron. J . 48, 200-203. Penny, L. H., and Dicke, F. F. 1957. Agron. 1.49, 193-196. Pesho, G. R., Lieberman, F. V., and Lehman. W. F. 1960. J . Econ. Entomol. 53, 146-150. Peterson, G. C., Ali, A. E. B., Teetes, G. L., Jones, J . W., and Schaefer, K. 1989. Crop Sci. 29, 1136-1 140. Pieters, E. P., and Bird, L. S. 1977. Crop Sci. 17,431-433. Porter, K. B., and Daniels, N. E . 1963. Crop Sci. 3, 116-1 18. Porter, K . B., Peterson, G. L., and Vise, 0. 1982. Crop Sci. 22,847-850. Puterka, G. J., Peters, D. C., Kerns, D. L., Slosser, J. E., Bush, L., Worral, D. W., and McNew, R. W. 1988. J . Econ. Entomol. 81, 1754-1759. Quisenberry, J. E., and Rummel, D. R. 1979. Crop Sci. 19, 879-881. Ram, M. 1983. SABRA0 J . 15, 1-5. Ramey, H. H . 1962. Crop Sci. 2,269. Rana, B. S., Tripathi, D. P., Balakotaiah, H. K., Damodar, R., and Rao, N. G. P. 1975. Indian J. Genet. 35, 350-355. Rana, B. S . , Jotwani, M. G., and Rao, N. G. P. 1981. Insect. Sci. Appl. 2, 105-109. Rao. N. G. P., Rana, B. S . , Balakotaiah, K., Tripathi, D., and Fayed, M. F. S. 1974. Indian J . Genet. 34, 122-127. Rao, N. G. P., Rana, B. S., and Jotwani, M. G. 1978. In “Plant Breeding for Resistance to Insect Pests,” pp. 63-78. IAEA, Vienna. Reddy, M. S. 1976. Diss. Abstr. Int. B 3 6 , 37168. Reddy, M. S., and Weaver, J. B. 1975. Proc. Beltwide Cotton Prod. Res. Conf. pp. 1-97. Reinink, K., and Dieleman, F. L. 1989. Euphytica 40,21-29. Rezaul Karim, A. N. M., and Pathak, M. D. 1982. Crop Prof. 1,483-490. Rick, C. M. 1982. I n “Plant Improvement and Somatic Cell Genetics” (I. K. Vasil, W. R. Scowcroft, and K. J. Frey, eds.), pp. 1-28. Academic Press, New York. Riedell, W. E. 1989. Crop Sci. 29, 412-415. Ringlund, K., and Everson, E. H . 1968. Crop Sci. 8,705-710.

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Roberts, J. J., and Gallun, R. L. 1984. J . Hered. 75, 147-148. Roberts, J. J., Foster, J. E., Gallun. R. L., and Patterson, F. L. 1984. Crop Sci. 24, 1221- 1222. Robertson, D. S., and Walter, E. V. 1963. J . Hered. 54,267-272. Ruangsook, B., and Khush, G. S. 1987. Crop Prof. 6,244-249. Rufener, G . K., Martin, S. K., Cooper, R. L., and Hammond, R. B. 1989. Crop Sci. 29, 6 18-622. Russell, W. A., and Guthrie, W. D. 1982. Crop Sci. 22,694. Russell, W. A., Guthrie, W. D., and Grindeland, R. L. 1974. Crop Sci. 14, 725-727. Saini, R. S . , Khush, G. S., and Heinrichs, E. A. 1982. Crop Prof. 1,289-297. Sastry, M. V. S., and Prakasa Rao, P. S. 1973. Curr. Sci. 42,652-653. Sastry, M. V. S., Prasada Rao, U., Kalode, M. B., and Sain, M. 1984. Indian J . Genet. 44, 325-328. Satyanarayanaiah, K., and Reddi, M. V. 1972. Andhra Agric. J . 19, 1-8. Schlosberg, J., and Baker, W. A. 1948. J. Agric. Res. 77, 137-159. Schwartze, C. D., and Huber, G. A. 1937. Science 86, 158-159. Scott, G . E., and Guthrie, W. D. 1967. Crop Sci. 7, 233-235. Scott, G. E., Hallauer, A. R., and Dicke, F. F. 1964. Crop Sci. 4,603-604. Scott, G . E., Dicke, F. F., and Penny, L. H. 1965. Crop Sci. 5,261-263. Scott, G . E., Dicke, F. F., and Pesho, G . R. 1966. Crop Sci. 6,444-446. Sebesta, E. E., and Wood, E. A. 1978. Agron. Abstr. 61-62. Sekar, V., Thompson, D. V., Maroney, M. J., Brookland, R. G., and Adang, M. J. 1987. Proc. Nail. Acad. Sci. U . S . A .84,7036-7040. Shands, R. G., and Cartwright, W. B. 1953. Agron. J . 45, 302-307. Sharma, G. C., and Hall, C. V. 1971. J . Am. SOC.Hortic. Sci. %, 750-754. Sharma, G . C., Jotwani, M. G., Rana, B. S., and Rao, N . G. P. 1977. J . Entomol. Res. 1, 1-12. Shastry, S. V. S., Freeman, W. H., Seshu, D. V., Israel, P., and Roy, J. K . 1972. in “Rice Breeding,” pp. 353-365. Int. Rice Res. Inst., Los Bahos, Laguna, Philippines. Shaver, T. N., Dilday, R. H., and Wilson, F. D. 1980. Crop Sci. 20,545-548. Sidhu, G . S., and Khush, G. S. 1978. Theor. Appl. Genet. 33, 199-203. Sidhu, G. S., and Khush, G. S. 1979. Euphytica 28,233-237. Sidhu, G . S ., Khush, G. S., and Medrano, F. G. 1979. Euphytica 28,227-232. Sifuentes, J., and Painter, R. H. 1964. J . Econ. Entornol. 57,475-477. Singh, B. B., Singh, R. R., and Adjadi, 0. 1985. Crop Sci. 25,736-739. Singh, R. 1953. Indian J. Genet. 13, 18-47. Singh, J. P., Pandey, M.P., and Pathak, R. K. 1990. Euphytica 46,95-100. Singh, D. N., and Weaver, J. B. 1972. Crop Sci. l2,294-297. Sinha, N. K., and McLaren, D. G. 1989. Crop Sci. 29,861-868. Sisson, V. A., Miller, P. A.. Campbell, W. V., and Van Duyn, J. W. 1976. Crop Sci. 16, 835-837. Siwi, B. H., and Khush, G. S. 1977. Crop Sci. 17, 17-20. Smith, D. H., and Webster, J. A. 1973. Proc. Int. Wheat Genet. Symp., 4rh, 1973 pp. 761-764. Smith, 0. D., Schlehuber, A. M., and Curtis, B. C. 1962. Crop Sci. 2,489. Sorensen, E. L., Stuteville, D. L., and Horber, E. K. 1985a. Crop Sci. 25,889. Sorensen, E. L., Horber, E. K., and Stuteville, D. L. 1985b. Crop Sci. 25, 1132. Sorensen, E. L., Stuteville, D. L., and Horber, E. K. 1986. Crop Sci. 26, 204-205. Sosa, 0. 1981. J. Econ. Entomol. 74, 180-182. Stanford, E. H. 1977. Calq. Agric. 31,22-23.

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ADVANCES IN AGRONOMY, VOL. 45

AGROFORESTRY IN ACID SOILS OF THE HUMID TROPICS L. T. Szott,' C. A. Palm, and P. A. Sanchez Tropical Soils Research Program Departments of Forestry and Soil Science North Carolina State University Raleigh, North Carolina 27695

I. 11.

Ill.

IV.

v. VI.

Introduction A. The Knowledge Gap B. Diagnosis of the Yurimaguas Region Alley Cropping A. Germplasm Selection B. Nutrient Content C. Nutrient Release from Prunings D. Weed Suppression E. Soil Properties F. Crop Yields G. Conclusions Managed Fallows A. Weed Suppression B. Biomass and Nutrient Stocks C. Economically Productive Fallows Fruit Crop Food Production Systems A. The Need for Selection and Improvement B. Agronomic Management Research Needs Summary References

I. INTRODUCTION The majority of the soils in the humid tropics are acid and infertile. Oxisols and Ultisols comprise two thirds, and Psamments and Spodosols together account for another 7% of the humid tropical land mass (Table I). On a continental basis, Oxisols and Ultisols are most prevalent in tropical South America and are present to a lesser extent in Africa and Asia.

' Present address: Centro Agronomic0 Tropical de Investigacion y Ensenanza (CATIE). Tumalba, Costa Rica. 275

Copyright 0 1991 by Academic Press. Inc. All nghts of reproduction in any form reserved.

276

L. T. SZOTT ET AL. Table I Distribution of Acid Soils in the Humid Tropicsa Humid tropical America

Humid tropical Asia and Pacific

Humid tropical Africa

Total humid tropics

Soilorder

(106ha)

%

(lo6 ha)

%

(lo6ha)

%

(lo6 ha)

%

Oxisols Ultisols Psamments Spodosols

332 213 6 10

50 32 I 2

179 69 67 3

40

14 131 17 6

4 35

525 413 90 19

35 28 6

16 I5 1

4

2

1

From Sanchez (1989).

Constraints to plant production on these soils are primarily low nutrient availability and aluminum toxicity (Table 11). It has been suggested that agroforestry systems are the most appropriate forms of sustainable, productive management of soils in the humid tropics because perennial woody vegetation can recycle nutrients, maintain soil organic matter, and protect the soil from surface erosion and runoff (Nair, 1984). Data supporting this contention, however, are scarce (Sanchez, 1979, 1987). Moreover, those systems most often cited as examples of successful agroforestry are found in areas dominated by base-rich naturally fertile soils such as Alfisols and Andosols. These systems include the homegardens of Asia and Africa (Michon et al., 1986; Fernandes et al., 1984), coffee and cacao production systems in Latin America (Russo and Budowski, 1986), and alley cropping (Kang et al., 1990).

Table I1 Extent of Major Soil Constraints in the Humid Tropics" Soil constraint

lo6 ha

% of humid tropics

Low nutrient reserves Al toxicity High P fixation Acid, but not Al toxic High erodibility Poor drainage Low CEC

980 850 565 270 255 195 165

66 57 38 18 17 13 I1

From Sanchez (1989).

AGROFORESTRY IN ACID SOILS

277

A. THEKNOWLEDGE GAP Notwithstanding the importance of such favored systems on fertile soils, agroforestry is considered especially applicable to marginal soils of the tropics. However, it remains to be determined whether the three main functions of agroforestry (nutrient recycling, soil organic matter maintenance, and protection from erosion and runoff) can be attained in acid soils.If so, agroforestry may represent a major alternative to slash-andburn agriculture. In their recent review on alley cropping Kang et al. (1990) cited the urgent need to evaluate agroforestry systems in humid tropical areas dominated by acidic soils with high levels of extractable aluminum and low fertility. This article summarizes 6 years of agroforestry research conducted primarily at the Yurimaguas Research Station in the Amazon Basin of Peru. The project was initiated in 1982 with diagnosis of the factors limiting agricultural productivity and how these might be overcome with the use of agroforestry techniques. It is conducted jointly by Peru's Instituto Nacional de lnvestigacion Agropecuaria y Agroindustrial, the International Council for Research in Agroforestry, and North Carolina State University (Torres et al., 1983). Research is supported by the U.S. Agency for International Development and Canada's International Development and Research Centre.

B. DIAGNOSIS OF THE YURIMAGUAS REGION Yurimaguas is located in the lowland rainforest zone of the Amazon basin of Peru (76"05' W longitude, 5" 45' S latitude, 182 m above sea level). Climatic conditions and soil constraints are fairly typical of much of the western half of the basin. Annual rainfall averages 2,200 mm with precipitation exceeding evapotranspiration 9 months of the year, and monthly temperature averages 26°C with little variation. Upland soils under these conditions are highly weathered and consist primarily of fine-loamy, siliceous, isohyperthermic Typic Paleudults with pH values between 4.2 and 4.7, aluminum saturation values of 60-80%, low cation-exchange capacity, and low reserves of nitrogen, phosphorus, and exchangeable nutrient cations (Tyler et al., 1978). Shifting cultivation is the predominant farming system in the region and is characterized by the extensive use of land and the intensive use of labor. The majority of farm holdings are less than 20 ha, of which 1 to 2 ha are in production at any time with the remainder in secondary forest fallow. Rice or corn are grown for cash and are usually followed by subsistence plant-

278

L. T. SZOTT ET AL.

ings of cassava and plantain before fields are allowed to revert to fallows. Grain yields are usually on the order of 2 tlha or less. Fallow periods generally range from 5 to 15 years in duration, but due to land use pressure periods of approximately 5 years are most common (Bidegaray and Rhoades, 1987). Land clearing, planting, and harvesting are seasonally regulated by rainfall patterns, creating a peak demand for labor that is felt simultaneously by most farmers in the region. As a result, labor shortages currently constrain overall productivity by preventing farmers from clearing and tending larger areas. Moreover, the lack of savings and credit, or cash-generating off-farm employment opportunities prevents farmers from hiring additional labor to overcome these shortages (Torres et al., 1983). Given the current high rates of migration to the region and restricted availability and access to land, decreasing soil fertility due to shortened fallow periods also constrains productivity. Three agroforestry systems were identified by the study team as possibilities to overcome these constraints to production: ( 1 ) alley cropping systems; (2) managed leguminous fallows to accelerate the restoration of soil fertility and reduce the duration of the fallow period; and (3) fruit tree-annual crop sequential cropping systems. These technologies represent a range of agroforestry options, the suitability of which will vary with the relative availabilities of land, labor, and capital (Raintree, 1987). For example, alley cropping may contribute to the maintenance of soil fertility under annual cropping by improved nutrient cycling, but the system’s total labor and possibly capital requirements are likely to be greater than those with shifting cultivation. Hence, the system seems appropriate for situations of limited land availability. In contrast, managed fallows might reduce the duration of the fallow period and improve productivity per unit time by accelerating weed suppression and nutrient accumulation in the fallow biomass. This system requires relatively small quantities of labor and capital, but like most fallow-based systems, it requires moderate to high land availability. Finally, cultivation of fruit trees can help alleviate labor and capital constraints by spreading labor over periods of low demand and by providing additional income through the sale of fruits and other products. In this case, labor and capital requirements are low to moderate, but the requirement for land availability is moderate to high. This project may be the first systematic research effort on agroforestry options for strongly acid soils of the humid tropics. Unlike most other locations where agroforestry is being conducted, the fundamental challenge is how to recycle nutrients in soil-plant systems that have limited quantities of them.

AGROFORESTRY IN ACID SOILS

279

I I . ALLEY CROPPING Research on alley cropping, or hedgerow intercropping, at Yurimaguas has concentrated on (1) identifying species potentially adapted to acid, infertile soil conditions, (2) measuring their pruning and nutrient yields, (3) characterizing rates of decomposition and nutrient mineralization from prunings, and (4) quantifying the effects of pruning additions on soil chemical properties, weed biomass, and crop yields.

A. GERMPLASM SELECTION The need for selecting woody legume species tolerant to acid soil conditions became evident during an initial evaluation of native and exotic species. Species widely used in Africa, Leucaena leucocephala and its more acid-tolerant relative, Leucaena diuersifolia, failed to develop adequately probably due to aluminum toxicity. Cajanus cajan, a species that appears to be aluminum tolerant also was eliminated due to its limited life-span. Two Amazonian species, Inga edulis and Erythrina sp., showed excellent biomass production and coppicing ability, while two other acidtolerant legumes ( Desmodium gyroides and Cedrelinga cataeniformis ) did not (Szott et al., 1987a). A subsequent trial of one year duration identified several additional promising species: Cassia reticulata, Inga felulei, and to a lesser extent, Calliandra calothyrsus, Samanea saman, and Gliricidia sepium (Salazar and Palm, 1987; Salazar et al., 1989) (Table 111). Many Amazonian as well as exotic species failed due to susceptibility to leaf-cutter ant attacks. For those species with high survival and coppicing ability, biomass production was comparable to levels reported for other species at more fertile sites (Kang et al., 1981, 1984, 1985, 1990; Yamoah et al., 1986a; Duguma et al., 1988). Under actual alley cropping, pruning yields of the most promising species encountered to date ( l n g a edulis, Cassia reticulata, Gliricidia sepium, and Erythrina sp.), have ranged from 2 to 5 kg/m hedgerow, equivalent to 5-12.5 t/ha/yr at a 4-m interhedge spacing with 3 to 4 prunings per year (Szott, 1987; A. Salazar, unpublished data). These biomass yields, as well as the nutrient concentrations of the prunings (Table IV), compare well with those reported for other species from more fertile sites (Kang et al., 1981, 1984, 1985; Kass, 1985; Yamoah et al., 1986a,b; Duguma et al., 1988). Pruning production by Inga edulis and Etythrina sp. did not respond to one application of 2.5 tons limeiha (Szott, 1987),and Cassia reticulafa and

280

L. T. SZOTT ET AL. Table 111

Survival, Growth Rate, and Pruning Yields of Various Leguminous Tree Species during the First Year after Planting on an Ultisol' ~

~

Survival

i%)

Growth rate (cm/mo)

Pruning yield (kg/m/yr) 3.54 4.12 I .42 I .90 2.70 -

Tree species

Typeh

Cassia reticulata Inga felulei Calliandra calothyrsus Samanea saman Gliricidia sepium Cassia sp. Schizolobium amazonicum Pithecellobium duke Acacia auriculiformis Flemingia congesta Albizia procera

N N E N N N N

100 100 80

70

40.9 30.9 23.0 20.3 15.9 12.4 10.3

N E E E

100 70 0 0

9.5 7.6 6.0 2.3

100 85 100

' From Salazar and Palm (1987). N , native; E, exotic.

Gliricidia sepiurn showed little response to low rates (11-25 kg/ha) of applied phosphorus (A. Salazar and C. A. Palm, unpublished data). The similarity in biomass and nutrient accumulation ability between these acid-tolerant species in Ultisols and Leucaena leucocephala in Alfisols is striking and suggests that the former are well adapted to extremely acid soil conditions. Table IV Average Tissue Nutrient Concentration of Four Periodically Pruned Tree Species Used in Hedgerow Intercropping Systems on Ultisols" Tissue nutrient concentrations (7%) Leaf

Branch

Species

N

P

K

C a M g

Cassiareticulata Gliricidiasepium Erythrina sp. Inga edulis

3.9 3.4 3.3 3.1

0.35 0.24 0.24 0.20

1.6 1.7 1.7 0.9

1.1 1.0 0.8 0.7

0.29 0.41 0.33 0.19

N

P

0.8 0.9 1.4 1.2

0.13 0.20 0.20 0.15

K C a M g 1.3 1.3 0.9 1.1

Sources: Szott (1987). Palm (1988), and A. Salazar (unpublished data).

0.8 0.6 0.4 0.4

0.12 0.12 0.20 0.10

28 1

AGROFORESTRY IN ACID SOILS

It should be noted that the native species included in these trials were not systematically selected. Improved performance of woody perennials can be expected with proper provenance selection. For example, provenances of Gliricidia sepium presently being evaluated show large differences in growth and biomass production. Provenance 14/84 (Oxford Forestry Institute International Gliricidia sepium Provenance Trial) from Retahuleu, Guatemala appears to be better adapted to acid soil conditions at Yurimaguas than other provenances in the study (Fernandes, 1990). Provenance selection and improvement are areas of agroforestry research deserving more attention since relatively simple techniques, easily applied under developing country conditions, can result in large improvements in tree performance. B. NUTRIENTCONTENT Prunings of Inga, Erythrina, Cassia, and Gliricidia, at levels of production noted above, are potentially capable of supplying most of the macronutrients required for moderate production levels of upland rice. Quantities of some nutrients supplied in prunings (Table V) compare favorably with the amounts required for an average upland rice grain yield of 2 t/ha (Table VI). Comparing Tables V and VI, nutrients accumulated in prunings exceed requirements for calcium (20 vs. 5 kg Ca/ha) and magnesium (6 vs. 3.4 kg Mg/ha), but not those of the other major elements. Quantities of nitrogen in prunings exceed plant growth demand by a narrow margin (66 vs. 55 kg N/ha); potassium accumulation is slightly inferior (33 vs. 37 kg Table V Average Quantities of Nutrients Contained in Prunings of Four Leguminous Tree Species Used in Hedgerow Intercropping Systems" Nutrient contents per pruning (kglha)h Tree species

N

P

K

Ca

Mg

Cassia reticulafa Gliricidia sepium

72 64 67 62 66

7 5 6 5 6

37 37 36 24 33

25 22 16 I5 20

6 8 7

Erythrina sp. Inga edulis Mean

4

6

" Sources: Szott (1987), Palm (1988), and A. Salazar (unpublished data). Values given are for average dry matter yield of 2.5 t/ha per pruning. and one pruning per crop.

282

L. T. SZO'IT E T A L . Table VI Nutrient Uptake of an Upland Rice Crop''* Nutrient (kg/ha) Plant part

N

P

K

Ca

Mg

Grain Straw Total

46 9 55

9 1 10

13 24 31

2 3

0.4 3.0 3.4

5

Calculated from Sanchez (1976). Crop yield was 2 tiha grain and 2 tiha straw.

Klha), but only 60 percent of phosphorus needs are balanced by prunings additions (6 vs. 10 kg P/ha). Therefore, based on nutrient budgets, the recycling potential of these alley cropping systems is clearly inadequate for phosphorus and potassium and marginal for nitrogen, even for upland rice, which has low nutrient requirements. These balances would be even less favorable if more nutrient-demanding crops like maize are used or if higher levels of yield are expected. As an example, in higher fertility Alfisols, the phosphorus content of Leucaena leucocephala prunings (Kang and Wilson, 1987) is inadequate for one crop of maize.

C. NUTRIENT RELEASE FROM PRUNINCS The previous calculations assume complete nutrient transfer efficiency from prunings to crop. Nutrient transfer efficiencies from pruned material have yet to be determined at Yurimaguas. Such transfers depend on the synchrony between nutrient mineralization from the pruned material and the timing of plant nutrient demand. Mineralization rates vary with the particular nutrient and the quality of the prunings (Swift et al., 1981). Mulch or litter quality is a term used for the comparative rate of decomposition of plant residue (Anderson and Swift, 1983; Swift et al., 1979). High quality is associated with rapid decomposition and nutrient release. However, high-quality material may not always be desirable because nutrient release may exceed plant nutrient demands resulting in asynchrony between supply and demands (Swift, 1987), as found with green manures incorporated in maize systems in Oxisols of the Cerrado of Brazil (Bowen, 1988).

Leguminous materials are generally high in nitrogen and have low carbon : nitrogen ratios. Hence, it is frequently assumed that decomposition

283

AGROFORESTRY IN ACID SOILS

of these materials will rapidly release large quantities of nitrogen. This assumption forms part of the rationale for including leguminous perennials in alley cropping systems, since it is expected that rapid mineralization of nitrogen from prunings will result in increased nitrogen availability to the associated crops. In laboratory incubations and field studies, Palm and Sanchez (1991) found that legume leaves with high contents of soluble polyphenols ( Inga edulis and C a j n n ~ scujan ) decomposed and mineralized nitrogen less rapidly than those with low polyphenol contents ( Erythrina sp.) (Fig. 1). Hence, although most leguminous material has low carbon : nitrogen ratios, it should not be expected that all material will serve as a readily available source of nitrogen. The polyphenolic : nitrogen ratio of leguminous materials may serve as a useful index of mulch quality (Palm and Sanchez, 1990; Fig. 2). The relationship of mineralization of other nutrients to legume quality was generally similar to that of nitrogen (Palm and Sanchez, 1990). In general, mineralization of phosphorus, potassium, calcium, and magnesium is faster from high-quality Erythrina leaves than from those of lowquality Inga edulis or Cajanus cujan leaves. Erythrina leaves mineralized approximately 40% of their initial phosphorus and calcium contents and 75% of their magnesium and potassium contents within 4 weeks; all elements were reduced to 25% or less of initial levels by 20 weeks. With leaves of Cajanus cujan and Inga edulis, however, there was little net mineralization of phosphorus, calcium, and magnesium during the first 8-12 weeks. At 32 weeks, phosphorus was reduced to approximately 40%,

INGA

rn rn

40

Ea

20

Q

CAJANUS

w

0

10

20

30

WEEKS FIG. 1. Decomposition of the leaflets of three leguminous species at Yurimaguas. (Source: Palm and Sanchez, 1991.)

284

L. T. SZOTT E T A L . 60

Y = -21.87 * In (x) + 18.77 R = 0.87

-

nm

P+

50

-

40

-

CONTROL SOIL = 24.01 pg N/g soil

-

30 -

20 -

f0

-

10 -

0.0

0.5

1.o

1.5

2.0

%POLYPHENOLIC-tO-o/oNITROGENRATIO FIG.2. Nitrogen release patterns from the leaves of leguminous trees as related to their polyphenolic-nitrogen ratio at Yurimaguas. (Source: Palm and Sanchez, 1990.)

and calcium and magnesium to 50-80% of their initial contents. By 32 weeks the percentage of initial potassium remaining in the material was 10% for both species. D. WEEDSUPPRESSION Weed suppression by prunings is related to mulch quality. Slowly decomposing mulches such as Znga suppressed weeds more effectively than mulches that decomposed more rapidly (Table VII). Weed suppression by prunings, however, is also modified by factors such as previous history of the field, weather during the cropping period, and crop competitiveness.

E. SOILPROPERTIES It is often hypothesized that additions of prunings in the alley cropping systems should increase levels of exchangeable nutrient cations, organic carbon, and total nitrogen compared to soil without pruning additions (sole cropped). This has not proven true. In both alley-cropped and sole-crop systems, neither of which received inorganic inputs, exchangeable nutrient cations declined to similar levels with time (Fig. 3). Possible reasons

285

AGROFORESTRY IN ACID SOILS

Table VII Weed Biomass in AUey-Cropped Upland Rice Systems in Relation to Quantity and Type of Prunings Applied" Alley crop species

Prunings applied (t/ha)

Weed biomass (kg/ha)

None

0.0

535

Inga edulis (low quality)

3.3 6.7

287 10

Eryrhrina (high quality)

3.3 6.7

53 1 575

'I

From Palm ( 1988)

for this are: (1) the quantity of prunings, hence nutrients, applied to the hedgerow intercropped plots (Table V) were too low to produce differences in soil nutrient levels; (2) the nutrients applied in the prunings were retained in organic or inorganic forms that are not detectable by the routine analytical techniques used (Hunter, 1974); and (3) the nutrients were removed by crop harvest or otherwise lost. Lime and fertilizer applications in other control plots did increase topsoil base status and available phosphorus simply because the amounts added were in excess of the amounts likely to be removed. Soil acidity, however, increased with time, as measured by pH decreases and increases in exchangeable aluminum, suggesting a strong acidification effect of fertilization.

F. CROPY ~ E L D S There are two main questions related to crop yields obtained with alley cropping compared to those from sole-cropped systems: (1) within a given cropping period, are yields greater in the alley cropping systems?; and (2) are yields in the alley cropping systems more sustainable over time? Tables VIII and IX provide some relevant data. Crop yields shown in Table VIII were measured in mulched areas of plots lying outside the competitive influence of the hedges. Rice crop residues were also removed, hence the yields show only the effect of mulch applications. The results show that rice yields from plots receiving high quality Erythrina mulch were always superior to those of the check plot, and that after the first crop, a similar situation occurred with the low quality Inga mulch. In both cases there was a yield response to mulch that was similar to that

286

L. T. SZOTT ETAL. 5.4

A

I

52

A

50

&

4.8

0

46

Sole crops, fertilized and limed Sole crops, not fertilized or limed

lnaa edulis alley crop, not fertilized or limed

4.4

4.2

0

5

9

12

17

22

25

31

5

9

12

17

22

25

31

Cajanus caion orley crop, not fertilized or limed

20 r\

1

16

2

12

2

08

E

04

0 00

5

'

9

12

17

22

25

31

0' 5

9

12

17

22

25

31

0.0

,- 32 01

Y

16

\ 24

12

v

a

a

(;n

E

4

00' 5

9

12

17

22

25

31

16

a

Months after burning

FIG.3. Changes in soil chemical properties (0-15 cm) in systems alley cropped with Inga edulis,Cajanus cajan, or cropped without trees. One of the treeless controls received lime and fertilizer, the other did not. (Source: Szott, 1987.)

obtained with inorganic nitrogen fertilization. Without organic or inorganic inputs however, rice yields decreased with time. This decline was less pronounced if mulch or fertilizer nitrogen was applied. A different study in which crops were not isolated from the effects of hedges of Inga edulis presents a different picture (Table IX). For a given crop, yields in the alley cropping systems were less than or similar to those from the nonfertilized, treeless control. Yields generally increased with

287

AGROFORESTRY IN ACID SOILS Table VIII Upland Rice Grain Yield for Four Crops",b ~

Input applied Ingu edulis (low quality) Eryihrina sp. (high quality) Fertilizer (I00 kg Niha per crop) Not mulched or fertilized

~

~~~~

Pruning rate per crop (tiha)

1

2

3

6.7

1,306

2,235

1,103

930

6.7

2,748

1,718

1,197

1,303

-

1,844

2,104

1,159

1,173

0

1,921

690

I87

54 I

Rice grain yields per crop (kg/ha) 4

From Palm (1988). Yield as affected by two mulch sources, in comparison with nitrogen fertilization and a check plot during a period of 20 months. There were no hedgerows present; therefore there was no competition from leguminous shrubs.

Table I X Relative Grain Yields by Distance from the Hedge in an Ingu edulis System on an Ultisol" Distance from the hedge (m)

Cowpea

Rice

Rice

Cowpea

Rice

0.75 1.25 1.75 2.25 Check yield (kglha)d

40 49 54 55 I .064

27 59 44 43 488

48 54 55 79 306

64 13 74 76 527

120 I29 113 382

Relative grain yield (%)h,'

69

From Szott (1987). Data include both mulch and hedge effects. ' In each crop, the yield from plots without hedges, prunings, or fertilizers was used to calculate % relative yield. I n the hedgerow intercropped plots, the distance between hedges was 4.5 m. " No hedges or prunings.

288

L. T. SZOTT ET AL.

distance from the hedges and crop yields in all systems declined with time, despite crop residue return and hedgerow intercropping. We hypothesize that the crucial difference between the two studies was the competition between the hedges and the crop plants. Patterns of tree and rice root distribution in relation to distance from the hedges suggest that belowground competition for water and nutrients reduce crop yields near the hedges. Approximately 30% of the root mass on an Znga edulis hedgerow was in the upper 20 cm of soil and 85% was within 1.75 m of the hedgerow (L. T. Szott and R . J. Scholes, unpublished). Cannell (1983) suggested that frequent aboveground pruning of hedges reduces belowground competition with crops because root growth is checked as the hedges adjust their root : shoot ratio. We have observed that fine root mortality of Znga hedges increases after pruning, but coarse roots remain viable and give rise to new fine roots within a few weeks (Fernandes, 1990). G . CONCLUSIONS

Although it is possible to find woody species that grow and coppice well in acid soils, and whose prunings can benefit associated annual crops, these benefits are much reduced due to competition with the hedges. Further work on the belowground interactions between the hedgerows and crops is needed. This work should include relatively simple studies quantifying root distribution and more dynamic measures of water and nutrient uptake by the different plant components in these systems. Measurements of the effects of various management techniques for reducing belowground competition, such as the frequency and height of aboveground pruning of the hedges, root pruning of the hedges, tillage, and arrangement of hedgerows to minimize the hedgerow-crop interface, are critical; also needed is research on management techniques to reduce the labor inputs required in alley cropping. To date, much of the work on alley cropping has been in the context of continuous cropping. The emerging picture, is that such a system is not sustainable on acid, infertile soils without additions of chemical fertilizers, chiefly due to the native infertility of the soil and the insufficient recycling of nutrients from prunings. We suggest that current concepts of alley cropping on acid, infertile soils emphasize its use in situations where it is clearly beneficial (e.g., in areas where land availability is severely limited or for erosion control terrace formation on slopes) and/or as a “head start” to fallow regrowth in improved shifting agriculture systems. At this point, our results do not show sufficient evidence to recommend alley cropping for continuous cropping on acid soils of the humid tropics.

AGROFORESTRY IN ACID sorts

289

Ill. MANAGED FALLOWS Farmers practicing shifting cultivation most often abandon their fields due to the increasing difficulty of weed control and/or declining soil fertility. Use of managed fallows that suppress weeds and restore soil fertility more rapidly than natural secondary vegetation would allow farmers to increase the crop : fallow ratio and productivity per unit time. These concepts were examined during 4.5 years of managed leguminous fallow growth in an abandoned shifting cultivation field (Szott, 1987; Szott et al., 1987b; Palm and Szott, 1989). The managed fallows included the following acid-tolerant leguminous species: Centrosema macrocarpum, Stylosanthes guianensis, and Pueraria phaseoloides (all stoloniferous plants); Cajanus cajan and Desmodium ovalifolium (shrubs); and Inga edulis (a tree). All were planted in monospecific stands and were allowed to grow unmanaged. Aboveground biomass accumulation by weeds and other vegetation and changes in aboveground and belowground nutrient stocks under these treatments were compared to those of a natural secondary forest fallow. A summary of the results based on the previously cited reports follows.

A. WEEDSUPPRESSION Some managed fallows proved more effective than the natural fallow in weed suppression. Within 8-17 months after fallow planting, weed biomass was reduced to less than 1 t/ha in the fallows with stoloniferous legumes compared to 3 t/ha in the natural forest fallow (Fig. 4). Viable weed seeds in the topsoil were also significantly lower in these fallows compared to others (Fig. 5). Such rapid reductions in weed biomass were related to the establishment of a dense, uniform, and extensive vegetation canopy by the stoloniferous fallows. Over longer periods of time, patterns of weed suppression varied among managed fallows. After 1.5 years of fallow growth, weed biomass in the Pueruria and Centrosema treatments remained at low levels due to the continued presence of the planted fallow species. Except for Stylosanthes, weed biomass also declined in the other treatments, and was related to biomass accumulation and, presumably, shading by trees. By 4.5 years after fallow planting, weed biomass was low in all treatments except the Stylosanthes treatment, which had little legume aboveground biomass or cover. In summary, weed suppression was achieved in 3.5-4.5 years in most

290

L. T. SZOTT E T A L . 6000

r

5000 4000 3000

2000 1000

0

CM SG

IE

CC

FF

DO BF

CM SG

IE

CC

PP

DO BF

m

a 2

u

3000 I

6000

5000 4000 -

53

41 m o

mo

3000 2000 1000

0

CM SG

IE

CC

FP DO

BF

C M SG

IE

CC

PF DO

BF

FALLOW SPEC1ES FIG.4. Changes in weed biomass with time after planting of different managed fallow treatments. Weed biomass includes grasses, sedges, and broad-leaved herbaceous plants. Fallow treatments are: Centrosema macrocarpum (CM), Stylosanthes guianensis (SG), Inga edulis (IE), Cajanus cajan (CC). Pueraria phaseoloides (PP), Desmodiurn ovalifolium (DO), and natural secondary vegetation (BF).

29 1

AGROFORESTRY IN ACID SOILS n

8000 T

"

INGA

DESMO

CAJANUS CENTRO

STYLO

PUER

NATURAL

FALLOW SPECIES FIG.5. Number of viable weed seeds found in the top 5 cm of soil in the fallow treatments 33 months after fallow planting. Treatments with different lower case letters are significantly different (p < .05).

fallow treatments, including the natural fallow, but was achieved earlier by some of the stoloniferous species: Pueruria, Centrosema, and Desmodium. The use of such fallows should be considered in situations where problems of weed control is a main cause of field abandonment.

B. BIOMASS A N D NUTRIENT STOCKS Biomass and nutrient stocks in aboveground vegetation, litter, and soil to a 45-cm depth were measured at varying intervals during 4.5 years following fallow planting. Legume and total aboveground biomass increased in all treatments during the first 2 years (Fig. 6). After 2.5 years, legume biomass declined in all treatments, but total aboveground biomass decreased only in the Centrosemu and Pueraria treatments. Increases in total biomass were primarily due to increases in tree biomass; tree invasion was suppressed by the stoloniferous Centrosema and Pueraria and delayed by Srylosanthes, a bush-type legume. During the first 2.5-3.5 years of fallow growth, aboveground stocks of

292

L. T. SZOTT ETAL.

Natural fallow Desmodium

/

lnga Caj anus Stylosanthes Centrosema Pueraria

0

10

20

30

40

50

60

MONTHS AFTER FALLOW PLANTING

FIG. 6. Aboveground accumulation of living biomass t litter in the different fallow treatments, Yurimaguas, Peru.

nitrogen and phosphorus in most planted fallows weregreater than those in the natural fallow. This was attributed to greater biomass accumulation and/or higher tissue concentrations of these elements than that attained in the natural fallow. Increases in aboveground nitrogen during early stages of most fallows, associated with high legume biomass production suggests that the nitrogen status of a fallow system might be enriched by the inclusion of legumes. However, this nitrogen advantage disappeared as legume biomass decreased at later dates. Accumulation of all other nutrients varied with total biomass accumulations; that is, there was no disproportionate effect of the legumes on accumulation of these nutrients. Quantities of nutrients present at various times during fallow growth compared to those present at field abandonment provide an indication of the time course of nutrient recovery. By 24 months, total nitrogen (vegetation + soil) and total available potassium (vegetation + exchangeable soil) in the best fallow treatments (Desmodium, Inga, and natural fallow) exceeded levels measured at abandonment (Fig. 7). Phosphorus (vegetation + modified Olsen extractable soil phosphorus) in the same treatments increased rapidly, and quantities present after 4.5 years greatly exceeded those at abandonment. Presumably, most of this phosphorus was mineralized from organic forms, converted from inorganic forms not readily extractable by the modified Olsen extractant, or was taken up from below the 45-cm depth. Further work on phosphorus transformations during fallow growth, focusing on soil organic phosphorus and microbial biomass phosphorus pools, is needed.

AGROFORESTRY IN ACID SOILS

-

100

--c

90

80

I

70

0

12

24

36

48

22

MO

ieo 160

Slylosanthes

lnga Cajanus Pueraria Desmodium Natural Fallow

,

400

v)

140

.-c a

120

2

100

c

CBntrosema

60

0)

.-c .-c

293

300

c L

c

0 a,

x)O

80 100 60

r L 40

2

'

0

a,

, 12

24

I 36

48

0

60

12

24

36

48

a

120

I

Ca 100

80

60

40

.= .

0

12

24

36

48

60

0

12

24

36

48

60

Months after fallow planting

FIG. 7. Changes in total nutrient stocks (living biomass + litter + soil) in the managed fallow treatments relative to quantities present at field abandonment, Yurimaguas, Peru.

Calcium and magnesium stocks (vegetation + exchangeable soil Ca + Mg) declined rapidly during the first 17 months after abandonment and remained relatively stable at succeeding sampling dates. Potassium stocks (vegetation + exchangeable K ) increased slightly for the first 2 years and then decreased in most treatments. Loss of calcium, magnesium, and potassium likely involve soil acidification caused by soil organic matter decomposition and proton extrusion by growing vegetation, and the leach-

294

L. T. SZOTT ET AL.

ing action of large quantities of rainfall. Much of the “lost” calcium, magnesium, and potassium may have accumulated below the 45-cm sample depth and may eventually be recycled by deep-rooted species. This would require a relatively long period of time and it is uncertain whether calcium and magnesium stocks would be completely replenished. On acid soils, in which quantities of exchangeable calcium and magnesium are small, such apparent losses seriously call into question the long-term sustainability of fallow-based production systems. It is open to question whether long-term enrichment of the nitrogen and phosphorus status of managed fallows can be improved even further by associating fast-growing, relatively long-lived leguminous trees with a rapidly establishing leguminous cover crop. It is also interesting to speculate whether the maintenance of biomass accumulation by forage legumes through cut-and-leave management would aid in increasing biomass and nutrient stocks in managed fallow systems.

C. ECONOMICALLY PRODUCTIVE FALLOWS Apart from fallows that are biologically enriched with legumes, fallows enriched with trees or other vegetation that produces economically important products may also be a significant agroforestry option for improving shifting cultivation systems on acid soils. Economically enriched fallows are also more likely to be adapted by farmers compared to biologically enriched fallows (Raintree, 1987). Vegetation that produces fruits or forage for grazing animals over long periods of time would effectively remove the land from the shifting cultivation cycle since farmers would be reluctant to cut a valuable source of income. The actual form of these systems will depend on the biological requirements for light, water, and nutrients of the associated species, farmers’ preferences for annual field crops, the amount of land available, marketing possibilities, and the amount of labor that could be invested in fallow maintenance.

IV. FRUIT CROP FOOD PRODUCTION SYSTEMS Annual tree crop food production systems may be one of the agroforestry options that is most attractive to resource-limited small farmers. Such systems can produce a variety of products for home consumption or sale in the market, provide a steady flow of income, reduce risks, spread labor demand through time, and may have more “closed” nutrient cycles than annual cropping systems.

AGROFORESTRY IN ACID SOILS

295

A variety of species with market potential have been identified for acid soil conditions in the Peruvian Amazon. These include peach palm ( B a c tris gasipaes), achiote (Bixa orellana ), araza (Eugenia stipitata), guaran8 (Paullinia cupana, P. sorbilis), and Brazil nut (Bertholletia excelsa). We intend to use our experience with peach palm to illustrate some of the research lines and questions that can be addressed for each of these species in the establishment and management of fruit crop production systems. Peach palm (Buctris gasipaes syn. pijuayo, pejibaye, chontaduro, pupunha) is native to the Amazon basin and parts of Central America. The palm possesses several characteristics that make its inclusion desirable in agroforestry systems on acid, infertile, upland soils (Clement, 1989; Clement and Mora Urpi, 1987). It is well adapted to acid, infertile soil conditions; it has a relatively small canopy, lessening the possibility of shading associated plants; it grows and reaches reproductive stage fairly rapidly; and it can be coppiced regularly. Economically, the tree produces a variety of useful products: fruit, heart of palm, and parquet material. The fruit has significant quantities of nutrients and can be used for human or animal consumption while heart of palm is an important export product. The palm reaches fruit-bearing age in approximately 5 years and produces about 10-20 t of fresh fruit per ha per year for 15 years. Heart of palm, requires 18-24 months for the first harvest; subsequent coppicing shoots can be harvested every 12-18 months. A N D IMPROVEMENT A. THENEEDFOR SELECTION

Peach palm, like many other potentially promising fruit tree species for acid soils, is semidomesticated and requires selection to improve its agronomically important characteristics. A first step in this process is collecting and characterizing germplasm. Approximately 300 lines of peach palm were collected throughout the Amazon Basin and are being evaluated in Peru and other tropical Latin American countries. Results from the first 6 years of evaluation show that considerable variability exists with respect to precocity and the quantity and quality of fruit production. Although most plants reached commercial production within 5 years, some began to produce after 2 years. At 5 years, production reached up to 18 t/ha fresh weight in some varieties; most varieties, however, produced between 3.5 and 9 t/ha, depending on the soil type. It is expected that production will increase with time up to approximately 10 years of age before leveling off. Peach palm fruits vary widely with respect to their protein, fat, fiber, and vitamin contents (Perez, 1984; J. Mora Urpi, personal communication), thus providing wide scope for future selection and improvement for spe-

296

L. T. SZOTT E T A L .

cific agroindustrial purposes such as flour, animal feed, and oil. The development of specific fruit types will depend on selection for useful characteristics, such as the position of fruit set as well as various parameters of fruit quality, the determination of inheritance patterns of these characteristics, and the development of controlled pollenization and vegetative propagation techniques including tissue culture, for their rapid multiplication.

B. AGRONOMIC MANAGEMENT The development of agroforestry systems for acid soils requires an understanding of how the components respond to low soil fertility and high aluminum levels. Peach palm has been established simultaneously with annual crops using a low-input rice-cowpea rotation described by Sanchez and Benites (1987). Income from grain yield in these systems exceeded the cost of plantation establishment and acted as a source of income during the early, vegetative stage of plantation growth. Following 2 years of annual crops, the needs for soil protection, weed control, and a source of nitrogen and organic matter suggest that leguminous cover crops have an important role to play in peach palm and other fruit crop systems. The types of cover crops, the timing of their planting, and subsequent management are important questions that must be considered. In the case of peach palm, growth was affected differently by a variety of leguminous ground covers (e.g., Mucuna cochichinensis, Pueraria phaseoloides, Desmodium ovalifolium, or Centrosema macrocarpum ) and by time of establishment. Palm growth with a Mucuna cover crop planted after 2 years was greater than that with other leguminous cover crops and was similar to that resulting from applications of 100 kg N/ha/yr (J. M. PCrez, unpublished data). Simultaneous planting of leguminous cover and palms, however, resulted in reduced palm growth and increased maintenance costs, since the covers tended to grow over and smother the small palm trees. Interplanting with acid-tolerant food crops for 1 or 2 years before establishing the cover crop appears to be the best option. Further work is needed on the resource allocation between trees and other plant species in mixed intercropping systems. Although it is clear that peach palm is adapted to acid, infertile soil conditions, it is also apparent that its growth is affected by soil nutrient levels (Perez et al., 1987; Szott et al., 1991). Growth during the first 5 years, in a field previously cleared by bulldozer, was strongly affected by nitrogen (Fig. 8) and potassium but not phosphorus, lime, or magnesium, despite topsoil properties of 90% A1 saturation and 0.1 cmol/L Ca + Mg. In this experiment fertilization was terminated after 5 years but residual

297

AGROFORESTRY IN ACID SOILS

0

1

2

3

4

YEARS AFTER TRANSPLANTING

FIG.8. Growth response of peach palm to various nitrogen fertilizer rates applied during 4 years following outplanting.

nutrient effects on fruit production were apparent in subsequent years. At 7 years of age (first year of commercial production), there was a tendency for fruit yield to increase with rates of nitrogen applied previously. In a different plantation, potassium fertilization initiated simultaneously with the onset of commercial fruit production resulted in a quadratic response in fruit yield (Fig. 9). Similar responses to potassium have been reported for fruit production of other palm crops (Kelpage, 1979). More work is also needed on applied aspects of fertilizer management, especially for heart of palm, and the residual effects of fertilization. Analyses of plant biomass and nutrient partitioning should be included as important complementary components of these studies. Besides applied research, more basic work is also required on mechanisms of A1 tolerance and nutrient uptake, including the importance of mycorrhizal infection by the palm tree.

V. RESEARCH NEEDS Alley cropping, managed fallows, and fruit crop systems are potentially useful agroforestry systems for acid, infertile soils in the humid tropics. However, major questions remain regarding these systems’ ability to overcome the chemical constraints to plant production imposed by these soils: 1. In alley cropping, further work on patterns of water and nutrient uptake by the crops and hedges is needed. Research on management

L. T. SZOTT E T A L .

298

0

0

4

K

n 2

b 3 K

L

0

k O

50

100

150

POTASSIUM APPLIED (kg Wha)

FIG.9. Peach palm fruit production as related to K fertilization rates.

techniques for reducing hedge-crop competition is critical. Studies of the long-term dynamics and internal cycling of nutrients contained in the hedgerow prunings are also required. 2. Although some managed leguminous fallows can suppress weeds more rapidly than natural secondary vegetation, their ability to accelerate restoration of nutrient cations, such as Ca and Mg, remains in question. The mechanisms involved in phosphorus transformations and in cation loss and techniques for avoiding these losses require further investigation. 3. For peach palm, and other relatively unknown acid-tolerant fruits, more collections and evaluation of germplasm, followed by selection, are needed. Agronomic research on nutrient requirements and management techniques, especially related to leguminous cover crops, are required. Studies on resource allocation by different plant components in mixed species systems are needed, but will be specific to the system in question. 4. In all these systems, selection and improvement of acid-tolerant germplasm is very important and should continue. It may also be necessary to select for plant characteristics that are favorable in mixed-species systems. 5 . The suitability of these and other agroforestry systems will vary with the biological and socioeconomic environment at a given site. The latter

AGROFORESTRY IN ACID SOILS

299

factors should be allowed to guide the formulation and research of agroforestry alternatives.

VI. SUMMARY Several agroforestry systems are successful in relatively fertile soils but little work has been done on food-production agroforestry systems in acid soils of the humid tropics. The main constraints in this ecosystem are aluminum toxicity, low nutrient reserves, and weed encroachment. Of these, aluminum toxicity can be overcome by selection of tolerant germplasm. Low nutrient reserves impose major limitations for nutrient cycling while weed encroachment must be controlled primarily by the rapid development of a complete ground cover. Investigations at Yurimaguas, Peru have focused on three agroforestry options: alley cropping, managed fallows, and tree-crop production systems as alternatives to or improvements of shifting cultivation. Several acid-tolerant, fast-growing, coppicing hedgerow species have been identified: Inga edulis, Eryrhrina sp., Cassia reticulata, and Gliricidia sepium. Nutrient release patterns from prunings vary widely according to their lignin and total soluble polyphenolic contents. The needed synchrony between nutrient release from hedgerow prunings and crop nutrient uptake has not been achieved on a sustainable basis. Phosphorus appears to be the most limiting nutrient. Crops are severely affected by root competition from hedgerow species. As a result, the desirability of alley cropping on humid tropical acid soils has not been conclusively proven, except for the obvious soil erosion control in steep slopes. Managed leguminous fallows may decrease the length of the fallow period for shifting cultivation. Several stoloniferous species were more effective in suppressing weeds than the natural secondary forest fallow during a 4-year period. Nutrient stocks (vegetation plus available nutrients in the top 45 cm of soil) increased over that at abandonment in the Inga edulis, Desmodium ovalifolium, and the secondary bush fallow. Nitrogen and phosphorus stocks increased consistently during the 4-year period while calcium and magnesium stocks decreased drastically during the first 2 years and leveled off. The processes involved need to be investigated. Fruit crop production systems established with a low-input upland rice-cowpea rotation and fotlowed by a legume cover crop, seem highly promising for the region and as a way to move from shifting cultivation to settled farming. The potential for fruit crop production systems is great, but much work remains to be done in germplasm selection and improvement, and the development of management techniques to optimize positive interactions among the plant components of multispecies systems.

300

L . T . SZOTT ETAL. REFERENCES

Anderson, J. M., and Swift, M. J. 1983. I n “Tropical Rainforests: Ecology and Management” (S. L. Sutton, T . C. Whitmore, and A. C. Chadwick, eds.), pp. 287-309. Blackwell, Oxford. Bidegaray, P. and Rhoades, R. E. 1987. “The farmers of Yurimaguas.” Int. Potato Center, Lima, Peru. Bowen, W. 1988. Ph.D. Thesis, Cornell University, Ithaca, New York. Cannell, M. G. R. 1983. In “Plant Research and Agroforestry,” (P. A. Huxley, ed.), pp. 455-487. Int. Counc. Res. Agrofor., Nairobi, Kenya. Clement, C. R. 1989. Agrofor. Syst. 7,201-212. Clement, C . R., and Mora Urpi, J. 1987. J . Econ. Bot. 41,302-31 1. Duguma, B., Kang, B. T . , and Okali, D. U. U. 1988. Agrofor. Syst. 6, 19-35. Fernandes, E . C. M. 1990. Ph.D. Dissertation, North Carolina State University, Raleigh. Fernandes, E. C. M., O’Ktingati, A,, and Maghembe, J. 1984. Agrofor. Sysr. 2 , 7 3 4 6 . Hunter, A. H. 1974. “International Soil Fertility Evaluation Laboratory Procedures.” Soil Science Department, North Carolina State University, Raleigh. Kang, B. T., and Wilson, G. F. 1987. “Agroforestry: A Decade of Development” H. A. Steppler and P. K. R. Nair, eds., pp. 227-243. Int. Counc. Res. Agrofor., Nairobi, Kenya. Kang, B. T., Wilson, G. F., and Lawson, T . L. 1981. Plant Soil 63, 165-179. Kang, B. T., Wilson, G. F., and Lawson, T. L. 1984. “Alley Cropping: A Stable Alternative to Shifting Cultivation.” Int. Inst. Trop. Agric., Ibadan, Nigeria. Kang, B. T., Grimme, H., and Lawson, T. L. 1985. Plant Soil 85,267-277. Kang, B. T., Reynolds, L., and Atta-Krah, A. N. 1990. Adu. Agron. 43,315-359. Kass, D. L. 1985. Alleycropping of annual food crops with woody legumes in Costa Rica. Presented at the Seminar on Advances in Agroforestry, Sept. 1-11, 1985, CATIE, Turrialba, Costa Rica. Kelpage, F. S. C. P. 1979. “Soils and Fertilizers for Plantations in Malaysia.” Incorporated Society of Planters, Kuala Lumpur. Michon, G., May, F., and Bompand, J. 1986. Agrofor. Syst. 4,315-338. Nair, P. K. R. 1984. “Soil Productivity Aspects of Agroforestry,” ICRAF Science and Practice of Agroforestry I. Int. Counc. Res. Agrofor., Nairobi, Kenya. Palm, C. A. 1988. Ph.D. Dissertation, North Carolina State University, Raleigh. Palm, C. A., and Sanchez, P. A. 1990. Biotropica 22,330-338. Palm, C. A., and Sanchez, P. A. 1991. Soil Biol. Biochem. 23,8348. Palm, C. A., and Szott, L . T. 1989. “TropSoils Technical Report 1986-1987,” p. 70. North Carolina State University, Raleigh. Perez, J. M. 1984. “ T h i s de Ingeniero Forestal.” Universidad Nacional d e la Amazonia Peruana, Iquitos, Peru. Perez, J. M., Davey, C. B., McCollum, R. E., Pashanasi, B., and Benites, J. R. 1987. “TropSoils Technical Report 1985-1986,” pp. 26-27. North Carolina State University, Raleigh. Raintree, J. B. 1987. In “Land, Trees and Tenure,” (J. B. Raintree, ed.), Proc. Int. Workshop on Tenure Issues in Agroforestry, Nairobi, Kenya, pp. 35-78. Int. Counc. Res. Agrofor. and Land Tenure Center, Nairobi, Kenya and Madison, Wisconsin. Russo, R. O., and Budowski, G. 1986. Agrofor. Syst. 4, 145-162. Salazar, A., and Palm, C. A. 1987. I n “Gliricidia sepium: Management and Improvement,” Spec. Publ. 87-01, pp. 61-67. Nitrogen Fixing Tree Assoc., Honolulu, Hawaii. Salazar, A., Palm, C. A., Perez, J. M., and Davey, C. B. 1989. “TropSoils Technical Report 1986-1987,” pp. 56-58. North Carolina State University, Raleigh.

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Sanchez, P. A. 1976. “Properties and Management of Soils in the Tropics.” Wiley, New York. Sanchez, P. A. 1979. In “Soils Research in Agroforestry” (H. 0. Mongi and P. A. Huxley, eds.), pp. 79-124. Int. Counc. Res. Agrofor., Nairobi, Kenya. Sanchez, P. A. 1987. In “Agroforestry: A Decade of Development” (H. A. Steppler and P. K. R. Nair. eds.), pp. 205-223. Int. Counc. Res. Agrofor., Nairobi, Kenya. Sanchez, P. A. 1989. In “Tropical Rainforest Ecosystems: Biogeographical and Ecological Studies” (H. Leith and M. J . A. Werger, eds.), pp. 73-86. Elsevier, Amsterdam. Sanchez, P. A., and Benites, J. R. 1987. Science 238, 1521-1533. Swift, M. J. 1987. “Tropical Soil Biology and Fertility Programme. Interregional Research Planning Workshop,” Biol. Int. Spec. Issue 13. IUBS, Paris. Swift, M. J., Heal, 0. W., and Anderson, J. M. 1979. “Decomposition in Terrestrial Ecosystems.” Univ. of California Press, Berkeley. Swift, M. J., Russell-Smith, A., and Perfect, T. J . 1981. J . Ecol. 69,981-995. Szott, L. T. 1987. Ph.D. Dissertation, North Carolina State University, Raleigh. Szott, L. T . , Davey, C. B., and Palm, C. A. 1987a. “TropSoilsTechnical Report 1985-1986,” pp. 23-26. North Carolina State University, Raleigh. Szott, L. T., Davey, C. B., Palm, C. A,, and Sanchez, P. A. 1987b. “TropSoils Technical Report 1985-1986,” pp. 31-35. North Carolina State University, Raleigh. Szott, L. T., Fernandes, E. C. M., and Sanchez, P. A. 1991. “Soil-Plant Interactions in Agroforestry Systems.” University of Edinburgh Centennial Symposium (in press). Torres, F., Raintree, J., and Davey, C. B. 1983. “Research to Develop Agroforestry Systems for the Upper Basin of the Peruvian Amazon.” Report to the Int. Dev. Res. Cent. (IDRC), Canada, ICRAF, Nairobi, Kenya. Tyler, E. J., Buol, S. W., and Sanchez, P. A. 1978. Soil Sci. Soc. Am. J. 42,771-776. Yamoah, C. F., Agboola, A. A,, and Mulongoy, K. 1986a. Agrofor. Syst. 4,239-244. Yamoah, C. F., Agboola, A. A,. Wilson, G. F., and Mulongoy, K. 1986b. Ecosysf. Enuiron. 18, 167-177.

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ADVANCES IN AGRONOMY. VOL 45

ASSESSMENT OF AMMONIA VOLATILIZATION FROM FLOODED SOIL SYSTEMS Gamani R. Jayaweera’ and Duane S. Mikkelsen*

’ Department of Land, Air and Water Resources Department of Agronomy and Range Science University of California Davis, California 95616

I. 11.

111.

IV.

V. VI.

VI1.

Introduction Theoretical Aspects A. Chemical Aspects B . Volatilization Aspects Theory of Ammonia Volatilization Factors Affecting Ammonia Volatilization A. Primary Factors Affecting N H 3 Volatilization B. Secondary Factors Affecting Ammonia Volatilization Methods of Measuring Ammonia Volatilization Models for Predicting Ammonia Volatilization A. Basic Models in Mass Transfer B. Bouwmeester and Vlek Ammonia Volatilization Model C. Moeller and Vlek Ammonia Volatilization Models D. Jayaweera and Mikkelsen Ammonia Volatilization Model Epilogue References

I. INTRODUCTION Ammonia volatilization from flooded soil systems involves a complex pathway in the terrestrial-atmospheric nitrogen (N) cycle. Ammonium N derived from natural sources (fertilized rice paddies and industrial byproducts, lakes, streams, ponds, animal wastes, etc.) are potential materials for NH3 volatilization. In recent years, losses of soil N fertility via volatilization have been identified as a major constraint to crop production, both with upland and lowland crops, particularly rice grown on flooded soils. I n flooded rice culture, where ammonium ( N G - N ) fertilizers are broadcast directly onto the soil or water without incorporation, 303 Copyllpht Z 1991 by Academic Pre% Inc All nghtr of rsproductlon In any form reserved

304

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

NH3 volatilization losses range from 10 to 60% of the fertilizer N applied. In contrast, where the fertilizer N is placed in the soil (e.g., 10 cm deep) by either mixing, placement, or banding techniques, NH3 losses may be very minimal (<5%). Poor fertilizer management practices may contribute significantly to low fertilizer-use efficiency with resultant poor crop yields. A variety of water, soil, biological, and environmental factors and management practices influence the kinetics and extent of NH3 volatilization from flooded soil systems. Ammoniacal N concentration, pH, Pco,, alkalinity, buffering capacity, temperature, depth, turbulence, and biotic activity are several floodwater characteristics that influence NH3 volatilization. The N G - N concentration in floodwater is influenced by N management practices such as source, timing and method of application, and water depth as well as biotic activity. The dominant soil factors affecting NH3 volatilization are soil pH, redox status, cation exchange characteristics, CaC03 content, soil texture, biotic activity, and fluxes affecting adsorption and desorption of NI$-N at the soil-water interface. Atmospheric conditions such as windspeed, PNH,, air temperature and solar radiation also influence NH3 volatilization. Management practices concerning the crop, water, and soil together with weather conditions prior to and after crop establishment have a direct effect on NH3 losses. Problems of measuring NH3 volatilization losses to accurately reflect dynamic field conditions have long been a concern of researchers and planners. Methods used to measure NH3 loss have been described by Fillery and Vlek (1986) and also by Harper (1988) who identify the problems associated with quantifying losses under undisturbed field conditions. They describe three micrometeorological methods that have promise, mainly eddy correlation, gradient diffusion, and mass balance. The behavior of NI$-N in flooded soil systems and the mass transfer of NH3 across the water-air interface is a dynamic process involving numerous interactions. An understanding of the rate-controlling factors described in a simplified model will enable us to predict losses, allow simplified measurements, and subsequently aid the planning and decision making processes in controlling NH3 losses to the atmosphere from natural systems, as well as designing more efficient fertilizer management strategies. Only a few models have been published which analyze the floodwater chemistry and atmospheric conditions affecting NH3 volatilization (Bouwmeester and Vlek, 1981a; Moeller and Vlek, 1982; Jayaweera and Mikkelsen, 1990a). Several good reviews have been published which summarize the general information on NH3 volatilization in flooded soil systems (Vlek and Cras-

NHj VOLATILIZATION FROM FLOODED SOILS

305

well, 1981; Fillery and Vlek, 1986). Readers new to the field may wish to refer to these reviews for the early research.

I I . THEORETICAL ASPECTS Volatilization is the process by which a substance is transferred from a liquid or solid phase to a vapor phase, generally the atmosphere. Ammoniacal N occurring in a floodwater system may be transferred to the atmosphere as gaseous NH3 across the water-air interface.

A. CHEMICAL ASPECTS The ammonium ion, N a - N is the source of NH3, which is formed as a N-transformation product in flooded soil, and also found following N fertilizer applications. The N G - N pool establishes an equilibrium with dissolved NH3 gas, NH3(,q),which is governed by the pH of the medium. The dissociation reaction of NI$/NH3(,,, equilibrium is of first order, whereas the association reaction is considered to be of second order (Alberty, 1983). Volatilization of a chemical from a water body is described as a firstorder process (Smith et al., 1981). Several researchers have shown that NH3 volatilization per se follows first-order kinetics (Folkman and Wachs, 1973; Vlek and Stumpe, 1978; Moeller and Vlek, 1982). The reaction sequence for NH3 volatilization is as follows:

where dissociation rate constant for NI-@NH3(aq)equilibrium; association rate constant for NG/NH3(aq)equilibrium; and k, k v = ~ volatilization rate constant for NH3. kd

= =

B. VOLATILIZATION ASPECTS The transfer of NH, across a water-air interface is described by the two-film model proposed by Whitman (1923), a useful concept to describe the mass transfer of a gas across a liquid-gas interface (Coulson et a / . . 1978). According to this model, the main body of each fluid is assumed to

306

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

be well mixed by convection currents and the concentration differences are regarded as negligible except in the vicinity of the interface between the phases. On either side of the interface it is supposed that turbulent eddies die out and that there exists a thin film of fluid in each phase, the flow of which is considered to be laminar and parallel to the surface (Fig. 1). This film, however, can also be considered as a stagnant layer on either side of the interface. Most of the resistance to mass transfer, and hence most of the concentration gradient, lies in these films. Outside this layer, turbulent eddies supplement the action caused by the random motion of the molecules, and the resistance to transfer becomes progressively smaller. The basis of the theory is the assumption that the zones in which the resistance to transfer lie can be replaced by two hypothetical layers, one on each side of the interface, in which the transfer is solely by molecu-

INCREASING CONCENTRATION

CgNi

I TURBULENT TRANSFER

1

I

INTERFACE

TURBULENT TRANSFER

BOllOM

I 1 I

DEPTH

I

1

FIG.1. Two-film model of a gas-liquid interface: C,, and CIN.average NH, concentrations in bulk gas and liquid phase, respectively; CgNiand CIN,,average NH3 concentrations at the interface in gas and liquid phase, respectively. (Adapted from Liss and Slater, 1974).

NH3 VOLATILIZATION FROM FLOODED SOILS

307

lar diffusion. The concentration gradient is therefore linear in each of these layers and zero outside. Under given conditions of turbulence, however, the layer thicknesses vary both spatially and temporally (Liss and Slater, 1974). According to Smith and Bomberger (1979), high turbulence in the liquid causes the liquid film or boundary layer to be thin; similarly, high turbulence in the gas causes the gas layer to be thin. At the interface, there is a concentration discontinuity and NH3 occurs at equilibrium across the interface as determined by Henry’s law constant. Henry’s law constant is a distribution coefficient that expresses the proportionality between the concentration of a gas dissolved in a solvent and its partial pressure (Prausnitz, 1986). In equation form, Henry’s law is

P = HC

(2)

where P is the partial pressure of the gas, C is the concentration of the dissolved gas, and H is the Henry’s law constant. Henry’s law constant is a function of temperature for a particular gassolvent system. Each gas-solvent system, however, has its own unique Henry’s law constant. Typically, Henry’s law breaks down when partial pressure exceeds 5- 10 atmospheres and/or when the dissolved concentration exceeds 3 mol percent (Prausnitz, 1986). At the interface, there is an equilibrium, and on either side transfer is affected entirely by molecular diffusion. Diffusion occurs when the chemical experiences a drop in potential as a result of the transfer. Volatilization continues until this difference is eliminated and equilibrium is established. According to Mackay (1980), although it is possible to use chemical potential to describe volatilization, it is more convenient to use the concept of chemical fugacity or partial pressure. Therefore, the driving force of diffusion can be regarded as the partial pressure difference between the water and air for the particular gas. Ammonia in air is in equilibrium with an aqueous solution and generally the concentration of NH3 in water is many times greater than in the air. There is, therefore, a large concentration gradient across the interface. This, however, is not the controlling factor in the mass transfer. It is generally assumed that there is no resistance at the interface itself, where equilibrium conditions exist. However, the measurements of concentration profiles show that there is a diffusion resistance for gas exchange and it lies in the film on either side of the interface (Coulson et al., 1978; Mackay et al., 1979). Therefore, the controlling factor is the rate of diffusion through the two films where all the resistance exists. This shows that the liquid-phase or gas-phase resistance, or both, determine the overall mass transfer rate of a chemical.

308

GAMANI R . JAYAWEERA AND DUANE S. MIKKELSEN

The volatilization of NH3, according to the two-film model, can be described as the diffusion of NH3 from the bulk of floodwater to the interface, followed by transfer across the interface, and finally diffusion from the interface to the bulk of the air phase. Ammonia concentrations immediately on either side of the interface are in equilibrium, which is expressed by the Henry's law constant for NH3. It is interesting to note the views of Danckwerts (1970) in his book on gas-liquid reactions on the two-film model. According to Danckwerts, the two-film model is not entirely realistic and it would not be seriously contended that a discontinuity really exists near the surface, still less that it has a uniform thickness. Nevertheless, the film model incorporates an essential feature of the real system, namely, that the gas must get into the liquid by dissolution and molecular diffusion before it can be transported by convection. He further states that the predictions based on the film model are remarkably similar and sometimes identical to those based on more sophisticated models. In view of its simplicity it is often preferable to use the film model for the purposes of discussion or calculation. Liss (1973) endorsed the concepts of Danckwerts and adapted the two-film model to study gas exchange across an air-water interface. This concept has since been adapted by other researchers and has been used to predict the interfacial transfer of carbon dioxide (Liss, 1973),sulfur dioxide (Liss and Slater, 1974), and various organic chemicals (Liss and Slater, 1974; Mackay and Leiononen, 1975; Dilling, 1977; cohen et al., 1978; Southworth, 1979; Mackay er al., 1979; Rathbun and Tai, 1981; Slater and Spedding, 1981; Smith et al., 1981; Atlas et al., 1982). The two-film model simplifies the theoretical calculation of gas exchange at the air-water interface (Liss and Slater, 1974) and is the most widely used kinetic model in estimating the volatilization of chemicals (Sanders and Seiber, 1984).

Ill. THEORY OF AMMONIA VOLATILIZATION The NH3 volatilization process is directly influenced by five primary factors (Jayaweera and Mikkelsen, 1990a). They are floodwater N G - N concentration, pH, temperature, depth of floodwater, and windspeed. They have developed a theory that describes the effect of these factors on NH3 volatilization (Fig. 2) (Jayaweera and Mikkelsen, 1990b). The rate of NH3 volatilization is principally a function of two parameters, (1) the NH3(aq)concentration in floodwater, and (2) the volatilization rate constant for NH3, kvN . rate of NH, volatilization = fl [NH31aq,k v ~ )

(3)

NH3 VOLATILIZATION FROM FLOODED SOILS

309

1 I

TEMPERATURE OF FLOODWATER

*

HN

' -b N

DEPTH OF FLOODWATER

FIG. 2. Theory of NH3 volatilization in flooded systems: a, degree of dissociation of N e ; H N ,kvN. K O N ,k g N , and K I N are the Henry's law constant, volatilization rate constant, overall mass transfer coefficient, and gas-phase and liquid-phase exchange constants for NH3, respectively. (From Jayaweera and Mikkelsen, 1990b.)

Ammonia concentration in floodwater, NH3(aq),is determined by (1) N@-N concentration in floodwater, and (2) fraction of dissociation, Q of N G . Fraction of dissociation is governed by the dissociation and association rate constants of N@/NH3(,,, equilibrium, and the H+ ion concentration in the system as represented by the pH of the medium. Rate constants are ultimately determined by the temperature of the system. Therefore, NH3(aq)concentration in floodwater

=

A [ N a - N ] , temperature, pH).

(4) The volatilization rate constant, kvN, is determined by (1) the depth of floodwater, and (2) the overall mass transfer coefficient for NH3, which is influenced by the Henry's law constant for NH3 and liquid- and gas-phase exchange constants. Henry's law constant is a function of temperature and exchange constants, which are dependent on the windspeed. Therefore, volatilization rate constant for NH3 = flwater depth, temperature, windspeed). (5)

310

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

By equating Eqs. (4) and ( 5 ) to Eq. (31, we obtain

rate of NH3 volatilization = A[N&-N], temperature, pH, water depth, windspeed). (6)

IV. FACTORS AFFECTING AMMONIA VOLATILIZATION Ammonia volatilization in flooded rice and similar systems is influenced by a variety of water and soil characteristics, fertilizer and crop management practices, and environmental factors (Mikkelsen, 1987). Several floodwater characteristics such as N e - N concentration, pH, Pco,, total alkalinity, buffering capacity, temperature, depth, turbulence, and biotic activity influence NH3 volatilization. Soil factors affecting NH3volatilization are pH, redox status, CaCOs content, cation exchange capacity, soil texture, and biotic activity. Wind speed, turbulence, PNH,, air temperature, and solar radiation are several atmospheric conditions influencing NH3 volatilization. Nitrogen source, timing, and method of application are three fertilizer management practices affecting NH3 loss. Water management can also affect the fluxes controlling the movement of N s - N between soil, water, and air. Jayaweera and Mikkelsen (1990a)subdivided these rate-controllingfactors into two categories: ( I ) primary factors, and (2) secondary factors. A. PRIMARY FACTORS AFFECTING NH,

VOLATILIZATION

Primary factors directly influence the process of NH3 volatilization. Numerous secondary factors, however, modify the primary ones. The primary factors that influence NH3 volatilization are N&-N concentration, pH, temperature, depth of floodwater, and windspeed ( Jayaweera and Mikkelsen, 1990a). 1 . Effect of Floodwater N&-N Concentration

Volatilization of NH3 from floodwater is described as a first-order exponential decay process. Therefore, the rate of NH3 volatilization is directly related to the concentration of aqueous NH3, which in turn is a function of N&-N concentration. Various researchers have shown a pronounced influence of N@-N concentration on overall NH3 loss (Mikkelsen et al., 1978; Vlek and

NH3 VOLATILIZATION FROM FLOODED SOILS

31 1

Stumpe, 1978; Terman, 1979; Vlek and Craswell, 1979; Bouwmeester and Vlek, 1981a; Denmead et al., 1982; Craswell and Vlek, 1983; Fillery et al., 1984; Fillery and Vlek, 1986; Mikkelsen, 1987; Jayaweera and Mikkelsen, 1990b). Fillery and Vlek (1986) state that the quantity of N G - N in floodwater is an index of the potential NH3 volatilization and the rate of NH3 loss is partially dependent on the equilibrium vapor pressure of NH3 in floodwater. Vlek and Stumpe (1978) reported that the rate of NH3 volatilization is directly related to the concentration of aqueous NH3 and therefore to the concentration of N G - N and pH. Fertilizer management, through its influence on the concentration of N G - N in floodwater, has a pronounced effect on the overall NH3 loss (Fillery et al., 1984). Bouwmeester and Vlek (1981a), using their model, showed that the rate of NH3 volatilization is increased with increasing N G - N concentration in floodwater. In a recently developed model by Jayaweera and Mikkelsen (1990b) they showed an increase in NH3 volatilization with increasing floodwater N G - N concentration, under a particular pH, temperature, water depth, and windspeed (Fig. 3). Volatilization rate is increased as a result of an increase in NH3(aq)concentration in floodwater. They have further shown that by decreasing pH, temperature, and windspeed, and by increasing the water depth, the NH3 volatilization rate is decreased at any N G - N concentration and vice versa (Fig. 3). A decrease in pH decreases the NH3taq)concentration in floodwater; a decrease in temperature decreases both NH3(aq)concentration and the volatilization rate constant, whereas a decrease in windspeed and an increase in floodwater depth decreases only the volatilization rate constant ( Jayaweera and Mikkelsen, 1990b). This clearly shows that the NH3(aq)concentration at any N G - N concentration is an interactive result of various factors associated with the floodwater system.

2. Effect of Floodwater p H Ammonium/ammonia equilibrium is governed by the pH of the medium. Since NH3 volatilization is directly related to the concentration of aqueous NH3 in floodwater, pH plays an important role in NH3 loss. By considering the chemical equilibrium of NG/NH3(,,, in floodwater, it is possible to relate pH, the equilibrium constant, K , and the concentrations as shown in Eq. (7). pH = pK

+ log(1 -CYCCY)c

(7)

312

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN 50

40 n

0 1

17

9

NH$-N

25

33

41

49

CONCENTRATION (rnqk)

FIG.3. Effect of floodwater N@-N concentration on NH3 volatilization. MEAN: pH, 8.5; TEMP (temperature), 25°C; WD (water depth), 10 cm; Us(windspeed at 8 m), 6 m/s. In other simulation runs, all other conditions are maintained constant at their mean values except for the listed variable.

and by rearranging, the fraction of NH3(aq)a in the system can be determined: a=

10 exp(pH - pK) 1 + 10 exp(pH - pK)

(8)

where pH is the pH of floodwater; and pK is -log K . The pK value is temperature dependent. Jayaweera and Mikkelsen (1990a) derived the following expression to compute pK as a function of absolute temperature. pK(T)

=

2729 0.0897 + T

(9)

where pK( T) is -log K, equilibrium constant for N&/NH3(aql system at absolute Kelvin temperature T. By substituting Eq. (9) into (8), they obtained the following expression to compute the fraction of NH3 in solution as a function of pH and absolute temperature. a=

10 exp (pH - 0.0897 - 2729/T) 1 + 10 exp (pH - 0.0897 - 2729/T)

(10)

313

NH3 VOLATILIZATION FROM FLOODED SOILS 1 .oo

-

-.

-I

++ r Z

LL

0 0.75--

z

i

0

+ 0 a

K 0.50-LL

Z

2 I-

i

i

5 0.25-0 v)

111

n 0.00

1

m-

@/@

7

2

FIG.4. Effect of pH on fraction of dissociation of NH;. (From Jayaweera and Mikkelsen, 1990a.)

Figure 4 illustrates the effect of pH on the fraction of dissociation of NHfi (Jayaweera and Mikkelsen, 1990a).

Numerous researchers have shown that B oodwater pH has a tremendous impact on NH3 volatilization (Vlek and Stumpe, 1978; Mikkelsen et al., 1978; Terman, 1979; Bouwmeester and Vlek, 1981a; De Datta, 1981; Vlek and Craswell, 1981; Ferrara and Avci, 1982; Pano and Middlebrooks, 1982; Denmead et al., 1982; Craswell and Vlek, 1983; Fillery et al., 1984; Fenn and Hossner, 1985; Fillery and Vlek, 1986; Jayaweera and Mikkelsen, 1990b). Fenn and Hossner (1985) reported that floodwater pH appears to be the primary contributing factor controlling NH3 loss from flooded soils. Aqueous NH3 in floodwater increases about tenfold per unit increase in pH in the range 7.5-9.0 (Vlek and Stumpe, 1978; Vlek and Craswell, 1981),permitting a high level of NH3 volatilization, but when the pH value is 6.6 or less, there is no removal of NH3 from a waste water stabilization pond (Pano and Middlebrooks, 1982). Bowmer and Muirhead (1987) reported the importance of pH by demonstrating the change in ratio of NH3 to N G from .056 to 5.6 (at 25°C) as the pH increases from 8.0 to 10.0. Various models have been used to calculate NH3 volatilization rates under different conditions such as pH. Bouwmeester and Vlek (1981a) suggested that the effects of pH, wind, and temperature on NH3 volatilization are of the same order of magnitude. They further stated that for high pH (> - 9) the volatilization rate is controlled mainly by the transfer rate

314

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

in the liquid diffusion layer, and for low pH the volatilization rate is limited mostly by the NH3 transfer rate in the air. Moeller and Vlek (1982) found a correlation between NH3 loss and pH that is independent of the volatilization kinetics and this correlation was used experimentally to monitor the NH3 volatilization. If sources of extraneous acids and bases are eliminated, the ammoniacal concentrations in solution can be determined by measuring pH. They used this method to gather volatilization data in a series of experiments. Jayaweera and Mikkelsen (1990b), using their model, showed that an increase in solution pH increases the percentage of NH3 loss per day (Fig. 5 ) , as a result of an increase in NH3(aq)in floodwater. However, by changing other primary factors such as temperature, depth of floodwater, and windspeed, the NH3 volatilization is varied. An increase in temperature from 10°C to 40°C increased both the NH3(aq)and volatilization rate constant for NH3, k , N , at various pH levels, thus increasing the NH3 loss per day. Shallow water enhances NH3 loss even at fairly low pH values due to the high volatilization rate constant. On the contrary, with increased water depth, NH3 is significantly lost only at high pH values (Fig. 5). This shows

100

s U

80

v,

9

/

60

m

/

r Z

6

zz

40

2w

20

*-•

MEAN TEMP: 1 0 d e g C TEMP: 40 deg C WD: 1 em WD: 1 9 c m

.--. A-

A-A

0-0

- A

W

a

0

7

8

FLOODWATER pH

9

10

FIG.5. Effect of floodwater pH on NH3 volatilization. MEAN: N G - N concentration in floodwater, 25 mg/L; pH, 8.5; TEMP (temperature), 25°C; WD (water depth), 10 cm; Us (windspeed at 8 m), 6 m/s. In other simulation runs, all other conditions are maintained constant at their mean values, except for the listed variable.

NH3 VOLATILIZATION FROM FLOODED SOILS

3 15

that even with high NH3(aq)concentrations in floodwater, volatilization can be controlled by low volatilization rate constants, which are achieved by increased water depth. They have further shown that the role of windspeed is highly significant at various pH levels. At high pH values, NH3 volatilization is maintained at low values as a result of low windspeed (Fig. 5 ) due to low volatilization rate constants.

3. Effect of Floodwater Temperature Temperature affects the equilibrium constant of N@/NH3(,,, system (Bates and Pinching, 1949) and an increase in temperature of floodwater increases the equilibrium constant as shown by Jayaweera and Mikkelsen (1990a). Temperature also influences the Henry’s law constant for NH3, and using a mathematical model Jayaweera and Mikkelsen (1990a) computed the Henry’s law constant for NH3 as a function of floodwater temperature. The dependency of Henry’s law constant on temperature for a particular gas-solvent system is well documented (Burkhard et al., 1985). In the temperature range typical for tropical climates, NH3 volatilization is increased by approximately 0.25% per 1°C increase in temperature, suggesting an exponential increase of NH3 loss with temperature (Vlek and Stumpe, 1978; Terman, 1979). Vlek and Craswell (1981), however, found that at a given NHi-N concentration, NH3(aq)concentration increases in proportion with increasing temperature, which suggests that temperature has an approximately linear effect on NH3 volatilization. Temperature influences the rate of NH3 volatilization in the same order of magnitude as windspeed and pH (Bouwmeester and Vlek, 1981a). An increase in temperature increases the volatilization rate of NH3 and the NH3 loss per day (Fig. 6). The higher volatilization rate of NH3 at high temperature is due to an increased floodwater NH3(aq)concentration and the volatilization rate constant for NH3 ( Jayaweera and Mikkelsen, 1990b). As discussed in the theory for NH3 volatilization, floodwater NH3(aq) concentration and the volatilization rate constant for NH3 are influenced by the degree of dissociation and the Henry’s law constant, respectively (Jayaweera and Mikkelsen, 1990b). They have shown that pH, depth of floodwater, and windspeed influence the NH3 volatilization process by several orders of magnitude at various temperatures (Fig. 6). Floodwater pH controls the NH3(aq)concentration, while the water depth and windspeed control the volatilization rate constant for NH3.

316

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

-

loo--

+

-

/

10

LEGEND:

20 30 FLOODWATER TEMPERATURE ("C

40

FIG.6. Effect of floodwater temperature on NH3 volatilization. MEAN: N x - N concentration in floodwater, 25 mglL; pH, 8.5; TEMP (temperature), 25°C; WD (water depth), 10 cm; Us (windspeed at 8 m), 6 m/s. In other simulation runs, all other conditions are maintained constant at their mean values, except for the listed variable.

4 . Effect of Water Depth

The role of depth of floodwater in NH3 volatilization is twofold. Primarily it affects N&-ion concentration by virtue of its dilution effect. Further, it influences the volatilization relationships kvN ( Jayaweera and Mikkelsen, 1990a) that have not been addressed in previous research. All transformations in an ecosystem, such as NH3 transfer across the water-air interface, must obey the law of conservation of mass. To avoid any violation, therefore, it is important to consider the material balance of the system (Neely, 1980). For interpretation, suppose there is a container of water, depth d, containing NH3(aq)which is volatilized from the surface via a first-order reaction process. By dimensional analysis, the material balance of this system can be determined as

where CN is the NH3(aq)concentration in the solution, mollL'; V is the volume of the solution, L3; A is the area of the surface, L 2 ; KON is the overall mass transfer coefficient for NH3, Llt; L is the length; and t is the time.

NH, VOLATILIZATION FROM FLOODED SOILS

317

FIG.7. Effect of floodwater depth on NH, volatilization. MEAN: N c - N concentration in floodwater, 25 mg/L; pH, 8.5; TEMP (temperature), 25°C; WD (water depth), 10 cm; Us (windspeed at 8 m). 6 m/s. In other simulation runs, all other conditions are maintained constant at their mean values, except for the listed variable.

Dividing Eq. (1 1) by V yields

where d is the depth of solution in the container. The ratio & N / d is a first-order volatilization rate constant for NH3, k v ~

In the case of flooded systems, d represents the mean depth of floodwater. This relationship shows that the volatilization rate constant for NH3 is inversely related to the depth of floodwater. The volatilization rate constant, kvN, and the half-life, t I l 2(0.693/kVN)for NH3 desorption are calculated as a function of floodwater depth by using the model developed by Jayaweera and Mikkelsen (1990a). An increase in depth of floodwater , increases the half life, decreases the volatilization rate constant, k , ~ and tlI2.

Using computer simulation runs, Jayaweera and Mikkelsen (1990b) showed that as the depth of floodwater increases from 1 to 19 cm, the volatilization rate of NH3 loss per day decreases from 100 to 53% (Fig. 7). This is due to a decrease in volatilization rate constant, k V N when other factors are maintained at constant values ( N G - N concentration,

318

GAMANI R. JAYAWEERA A N D DUANE S. MIKKELSEN

25 mglL; pH, 8.5; temperature, 25°C; and windspeed at 8 m height, 6 mls). As shown in Fig. 7, at any particular water depth and at a constant N G - N concentration, an increase in pH, temperature, and windspeed increases the percentage of NH3 loss and vice versa. It is interesting to note that, by managing the depth of floodwater, it is possible to modify NH3 losses from flooded systems. Thibodeaux (1979) showed the fraction of NH3 desorbed with water depth for a small stream in southern Arkansas. For example, at pH 8.0 and temperature 60”F, nearly 90% of NH3 is desorbed at 0.1 ft water depth, about 70% is lost at 0.5 ft, and around 20% of NH3 is lost at a depth of 1 ft during the same duration of time. According to Thibodeaux, the volatilization of NH3 from deep rivers is significantly lower than in small streams mainly because of water depth. 5 . Effect of Windspeed

Kanwisher (1963) showed that at low windspeeds, there is little effect on the gas exchange rates until a critical value is reached. At this unique speed, the wind gets a better “grip” on the water surface. Cohen et a / . (1978) also reported the importance of wind effect above a critical speed, and accordingly, above the critical speed, shear stress at the interface is large enough to set the interface and the liquid below in motion. Above the critical value, the exchange rate is supposed to increase as the square of the windspeed (Kanwisher, 1963). Broecker and Peng (1974) reported the same observations. Therefore, gusty winds may account for a large fraction of the exchange, even though they are only of short duration. Water waves, created as a result of high windspeeds, tend to increase the interfacial area directly. However, Kinsman (1965) reported that wave height to wave length ratio is probably at most 0.143, and according to Cohen et al. (1978) this wave height to wave length ratio cannot account for more than a 4% increase in transfer rate. Several researchers have shown that windspeed is an important environmental parameter in NH3 volatilization. Fillery er al. (1986a) concluded that high windspeeds in the field promoted NH3 loss and probably precluded any important N loss via nitrification-denitrification. Vlek and Stumpe (1978) reported that the relation between the loss of NH3 from solution and the air exchange rate is curvilinear with a rapid increase in NH3 volatilization at the lower flow rates that they tested. Several researchers observed a linear relationship between NH3 loss and windspeed in field experiments (Fillery er af.,1984; Fillery and Vlek, 1986). Denmead et af. (1982) showed that NH3 volatilization increased with the approxi-

3 19

NH3 VOLATILIZATION FROM FLOODED SOILS

mate square of windspeed in furrow irrigated maize, implying an exponential increase in NH3 volatilization with windspeed. In a recent greenhouse study, Katyal and Carter (1989) reported that the relationship between airflow rate and NH3 loss was logarithmic rather than linear in nature, and they concluded that this may be due to cooling of floodwater associated with high air flow rates. These various relationships observed by researchers may be due to the variety of conditions that they encounter in their experiments. Jayaweera and Mikkelsen (1990b), by using model simulation runs, showed the effect of windspeed on NH3 volatilization under various conditions (Fig. 8). They show clearly that the nature of the relationship changes tremendously depending on existing conditions. For example: at pH 10.0, all the N&-N in floodwater is lost at a windspeed as low as 2 m/s at 8 m height, compared to 12% loss at 12 m/s windspeed when the pH is 7.0. This illustrates that even with a high volatilization rate constant, if the NH3(aq)in floodwater is low, only a small amount of NH3 is lost. Bouwmeester and Vlek (1981a), using their diffusion model found that at low windspeeds the volatilization rates are very small, and the gas-phase resistance dominates. However, with increasing windspeed the volatilization rates increase, and the liquidphase resistance becomes more significant due to depletion of NH3 in the

0

4

8

12

WIND SPEED AT 8 rn HEIGHT (rn/s)

FIG. 8. Effect of windspeed on NH, volatilization. MEAN: NHi-N concentration in floodwater, 25 mg/L; pH, 8.5; TEMP (temperature), 25°C; WD (water depth), 10 cm; U8 (windspeed at 8 m), 6 m/s. I n other simulation runs, all other conditions are maintained constant at their mean values, except for the listed variable.

320

GAMANl R. JAYAWEERA AND DUANE S. MIKKELSEN

surface film of the liquid phase. They reported that this shift from gasphase resistance to liquid-phase resistance is more evident at high pH values. Fillery and Vlek (1986) reported that there was a good fit ( R2 = 0.90) in the following relationship between the partial pressure of NH3 (PNH,)in the floodwater and windspeed at 1.2 m ( W,) during the volatilization process. F

=

k PNH,Wz

(14)

where F is the flux of NH3, and k is a constant. Windspeed, however, influences the NH3 volatilization process by virtue of its role on the volatilization rate constant (Jayaweera and Mikkelsen, 1990a,b). Other factors such as temperature, pH, and depth of floodwater, however, could vary the rate of volatilization depending on the conditions.

B. SECONDARY FACTORSAFFECTING AMMONIA VOLATILIZATION Secondary factors influence the primary factors in the process of NH3 volatilization. Each primary factor is a function of several secondary factors. Thus, the NH3 volatilization process is the overall result of numerous characteristics of soil, water, fertilizer management, and atmospheric conditions. I . Effect of Secondary Factors on Floodwater N s - N Concentration Ammonia volatilization is generally influenced most by the factors that influence the N e - N concentration in floodwater. Mikkelsen et al. (1978) showed that higher concentrations of N e - N in rice floodwater increased NH3 volatilization losses. Nitrogen source, rate and method of application, soil CEC, biotic component such as urease activity, assimilation by algae, weeds, and rice, and immobilization by soil components are important secondary factors that influence NH3 volatilization. The source of fertilizer N plays an important role in determining the N G - N concentration in floodwater, thereby influencing the NH3 volatilization. Urea is currently the most important fertilizer source in rice cultivation, followed by ammonium sulfate. Freney et al. (1985) reported that there is a worldwide move to use urea as the primary form of fertilizer N. Urea is hydrolyzed by the urease enzyme to form (NH4)2C03 (Fenn and Hossner, 1985) and NHfl, whereas (NH4)2S04provides N G directly into

NH, VOLATILIZATION FROM FLOODED SOILS

32 I

the system. The kinetics of urea hydrolysis in moist soils have given different results. Some researchers reported that urea hydrolysis is a first-order reaction with respect to urea concentration (Overrein and Moe, 1967; Sankhayan and Shukla, 1976). Recent studies, however, showed zero-order kinetics for urea hydrolysis (Sahrawat, 1980; Vlek and Carter, 1983). In flooded soils, Eriksen and Kjeldby (1987) reported that urea hydrolysis exhibited a zero-order reaction when urea super granules were point-placed at a 10-cm soil depth. There are numerous reports comparing the effect of urea and (NH4)2S04 in NH3 volatilization. When (NH4)2S04is applied to puddled soil, Vlek and Stumpe (1978) observed nearly 11% of the N applied was lost as NH3. Vlek and Craswell (1979), however, found a higher rate of loss (50% N applied) when urea is applied. These findings show that urea is more prone to N losses in flooded soils. Recently, Fillery and De Datta (1986) reported NH3 fluxes of up to 38 and 36% of the N applied from (NH4)?S04and urea, respectively. In several other field studies, high losses of N have been detected following the application of urea and (NH4&304 (Craswell et al., 1985; Katyal et al., 1985; Vlek and Byrnes, 1986).These findings confirm the earlier reports of Mikkelsen ef al. (1978) and Vlek and Craswell (l979), but contradict other studies (MacRae and Ancajas, 1970; Ventura and Yoshida, 1977; Wetselaar et al., 1977; Freney et ul., 1981). These contradictions may be due to the differences in the alkalinity of various sources of water used to irrigate flooded rice (Vlek and Stumpe, 1978; Vlek and Craswell, 1979). Fillery et al. (1986b), however, in trying to explain these contradictions reported that alkalinity in floodwater as a result of evaporation and/or respiration contributed to the rapid loss of NH3 following the application of (NH4)?S04and urea to the floodwater. Even though there may be the same amount of NH3 loss from urea and (NH4)$j04, the pattern of loss differed between these fertilizers in an 8-day period. Several researchers detected NH3 fluxes immediately after the application of (NH4)2S04to flooded soils (Freney et al., 1981; Fillery and De Datta, 1986; Fillery et al., 1986b) and within 2-4 hours after the application of urea (Freney et al., 1981; Simpson et al., 1984; Fillery and De Datta, 1986; Fillery et al., 1986b). Maximum NH3 fluxes are generally observed immediately following the application of (NH4)2S04 (Mikkelsen ef al., 1978; Freney et al., 1981; Fillery and De Datta, 1986; Fillery et ul., 1986b)or a few days after the urea application (Freney ef al., 1981; Fillery et al., 1984, 1986b; Fillery and De Datta, 1986). The different pattern of NH3 fluxes from urea and (NH4)2S04were primarily due to the differences in the pattern of N@-N concentration in floodwater (Wetselaar et al., 1977; Fillery et al., 1986b). There has been an interest in modifying the dissolution rate of urea by

322

GAMANI R. JAYAWEERA AND DUANE S . MIKKELSEN

coating the granules, adding chemical additives, by increasing the particle size of the granule, or formulation of controlled release materials. Sulfur-coated urea (SCU), in particular, is known to be an effective N source for rice (De Datta and Gomez, 1981; De Datta et al., 1983; Flinn et al., 1984; Katyal et al., 1985; Buresh, 1987; Rao, 1987). Craswell et al. (1981) reported that N G - N concentrations in floodwater are much lower after basal incorporation of SCU than after urea applications. Lac-coated urea (LCU), urea coated with shellac resin, however, was ineffective in reducing peak ammoniacal N levels or losses (Rao, 1987). Phosphate rock-coated urea (PRCU), an experimental material prepared by Madras Fertilizer Limited, Madras, India (Buresh, 1987), has been field evaluated with rice in India, and comparable rice yields for PRCU and urea have been reported (Singh and Yadav, 1985). Guanyl urea sulfate (GUS) is a slowly mineralized source of N by microbial action under aerobic and anaerobic conditions (Davies, 1976; Ebisuno and Takimoto, 1981; Buresh, 1987). Ammonia formation and presumably loss were least for GUS according to Buresh (1987) who reported that the negligible NH3 concentration in floodwater may be due to the slow mineralization and acidifying effect of GUS. Urea phosphate, which is known to produce an acidifying effect and to reduce loss of urea N as NH3 (Bremner and Douglas, 1971a; Stumpe et al., 1984), failed to reduce pNH3 under flooded condition due to the stimulation of algal photosynthetic activity by added P (Buresh, 1987). Urea-forms, which are condensation products of urea and formaldehyde, were less prone to NH3 loss than urea in a greenhouse study with rice (Carter et al., 1986) and in a field study (Buresh, 1987). This may be due to the slow release of N from urea forms through microbial action (Corke and Robinson, 1966). Rao (1987) reported that urea supergranules (USG), spherical granules of 1 g each, reduced the peak N s - N levels to <2 g/m3 and N losses to 3.9%. Eriksen and Kjeldby (1987) reported that NH, volatilization was noticeably reduced by the surface application of urea calcium nitrate (UCN) on flooded soil as compared with USG. According to them, the total N loss from USG after 30 days was 17% of applied urea, but when the same amounts of urea and nitrogen were applied as UCN this loss was reduced to 3% and 6%, respectively. Rate of N application obviously should control the amount of N a - N that comes into the floodwater. Vlek and Craswell (1979) reported that reduced N application rates reduced NH3 volatilization by lowering the level of N G - N in floodwater. MacRae and Ancajas (1970), in a laboratory study, found that an increased application of both (NH4)*S04and urea resulted in increased losses of NH3 through volatilization. Fenn and Hossner (1985) reported the same.

NH3 VOLATILIZATION FROM FLOODED SOILS

323

Method of N fertilizer application influences the ammoniacal N concentration in floodwater (Fillery et ul., 1984) and therefore plays an important role in NH3 volatilization. Basically, there can be three ways of applying fertilizer N to flooded soils: ( 1 1 broadcast application; (2) broadcast and incorporation; and (3) deep placement. Broadcast applications can be done in several different ways. They are: broadcast as a basal dose, broadcast as a top-dressing at different stages of crop growth, or broadcast and incorporate the fertilizer material into the soil. Deep placement is a practice that places the fertilizer in the reduced layer of the flooded soil so that the concentration of urea and N G in floodwater remains essentially zero. This can be done in several ways, namely soil injection, mud ball placement, drill placement, band placement, or point placement. In the last decade, there have been numerous papers published on aspects of N fertilizer management. Mikkelsen et al. (1978) reported considerable losses of NH3 when urea and (NH4)2S04were applied directly to floodwater, but less than 1% of the total N applied was volatilized when N fertilizer was placed at a depth of 10-12 cm. In a paper presented at the 14th International Congress of Soil Science, Kyoto, Japan (August 12-18, 1990), Rolston and his co-workers in a simulation study showed that the amount of NH, volatilization is affected by windspeed for the cases of N G - N fertilizer applied to the floodwater and incorporated into the soil (Fig. 9) (Rolston et al., 1990). Deep placement reduces the NH3 volatilization largely by reducing the N G - N level in floodwater. Vlek and Craswell (1979), MacRae and Ancajas (1970), Fillery et al. (1984), and Ericksen et a!. (1985) reported the same. Uniform placement of prilled urea and point placement of urea super granules have given low total N (urea + NH:-N) concentration in floodwater and demonstrates that these methods can be used to reduce N losses in lowland rice production (Cao et al., 1984). The highest concentrations of N G - N and highest level of NH3 have been detected when urea or (NH4)*S04was applied to floodwater 2-4 weeks after the transplanting Fillery et al., 1984, 1986b). Rao (1987) found the highest concentrations of N G - N in floodwater and NH3 loss when granular urea was applied wholly as a basal dose. Higher total N concentration in floodwater was recorded after split application (2/3 basal-broadcast and incorporated, and 1/3 top-dressed, 5-7 days before panicle initiation) than in band placement of urea, indicating greater potential for NH3 volatilization (Cao et al., 1984). Rao (19871, however, reported that a split urea application (112 at transplanting, I /4 each at 21 days and 42 days after transplanting of rice) reduced peak N a - N levels and NH3 volatilization losses. The differences in their conclusions may be due to timing and amount of split application. The observations of Cao et al. (19841, however, show that substantial N

324

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN 100

C

0

5

0

5

10

15

I

10

15

20

TIME (days)

FIG. 9. Ammonia volatilization as affected by windspeed under two different fertilizer managements: (a) NHfi-N fertilizer applied to floodwater; and (b) N G - N fertilizer incorporated into soil. Water depth and pH are constant at 5 cm and 8.5, respectively. (Adapted from Rolston et al., 1990.)

losses can still occur when N is broadcast and incorporated before transplanting. Draining the floodwater from the soil and incorporating urea before transplanting reduced the extent of N loss (Fillqry et al., 1986a). Cao et al. (1984) also reported reduced losses and high "N recovery following a thorough incorporation of urea. However, high concentrations of N G - N are found in floodwater (Craswell et al., 1981; Cao et al., 1984) and substantially lower "N recoveries have been reported when incorporation is attempted without first removing the floodwater (Cao et al., 1984; Craswell et al., 1985). Therefore, it appears necessary to drain the floodwater from puddled soils before the application of urea if high N crop efficiency is to be achieved without deep placement of fertilizer (Fillery et a/., 1986a). It

NH3 VOLATILIZATION FROM FLOODED SOILS

325

is interesting to note that Buresh (1987) reported that thorough incorporation of GUS and SCU is not necessary to prevent NH3 loss. With all this information, it is easy to conclude that with fertilizers such as urea and (NH&SO4, deep placement reduces NH3 volatilization, and applying ammoniacal N fertilizer into floodwater can lead to large losses of gaseous N. Nonetheless, Asian farmers still frequently broadcast N fertilizer without subsequent incorporation into the soil (Mikkelsen er al., 1978; De Datta, 1981). This practice may occur because small-scale farmers prefer to apply their fertilizer only after the crop is established and broadcast application is the only mode of application at that time (Freney er al., 1985). Cation exchange capacity (CEC) of a soil affects the retention capacity of a soil for cations. CEC could potentially affect NHfI concentration in floodwater, which indirectly influences the extent of NH3 loss (Vlek and Craswell, 1979; Freney et al., 1983). Several researchers have found an inverse relationship of NH3 volatilization to CEC of the soil (Overrein and Moe, 1967; Matocha, 1976; Fenn and Kissel, 1976; Fenn et al., 1982; Fenn and Hossner, 1985; Mikkelsen, 1987). Recently, however, Eriksen and Kjeldby (1987) found low NH3 loss from urea super granules in a soil with low CEC. Fleisher et al. (1987) in a model of NH3 volatilization from calcareous soils reported that most NH3 loss is due to the interactive effect of high soil pH and low CEC. Because of the dynamic nature of soil CEC, it is easy to understand why there is no consistent agreement among researchers regarding the relationship of CEC to N G retention. Biotic activity in a flooded rice ecosystem could have a dominant role in controlling the NHfI concentration in floodwater. Urease activity (Freney et al., 1983; Mikkelsen, 1987), assimilation of N G - N by algae, weeds, and rice plant (Craswell et al., 1985), and immobilization of N in the soil (Freney et af.,1983) could control the NH3 volatilization by influencing the NHfI concentration. As mentioned earlier, urease activity could follow zero-order or firstorder kinetics (Overrein and Moe, 1967; Sankhayan and Shukla, 1976; Sahrawat, 1980; Vlek and Carter, 1983; Eriksen and Kjeldby, 1987). Depending on the degree of urease activity, urea can provide N G to the flooded system. According to Fenn and Hossner (1985), NH3 loss from flooded soils is favored by urease activity. There have been many attempts to control the reaction rate of urease with metabolic inhibitors (Bremner and Douglas, 1971b) using toxic heavy metals and organic compounds. Vlek et al. (1980) showed that phenyl phosphodiamide (PPD), added at a rate of 2% (w/w)delays the appearance of NH3 in floodwater after broadcasting urea. Application of PPD (1%

326

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

w/w) with urea inhibited urease activity for up to 3 days in a field study (Fillery and De Datta, 1986; Fillery et al., 1986~).Fillery et al. (1986~) suggested that the effect of PPD on NH3 volatilization is largely a function of the delay in the buildup of N G - N in the floodwater and not as a result of delaying the increase in pH of floodwater as suggested by Byrnes et al. (1983). Byrnes et al. (1983) showed that PPD (1% w/w) inhibited urease activity for up to 1 I days. These differences may be due to the variations in the rate of degradation of PPD under various conditions. Austin et al. (1984) showed that PPD degradation is highly dependent on pH and temperature. From these observations it is clear that PPD seems to decompose rapidly in flooded soils. Therefore, more effective urease inhibitors are needed to minimize the accumulation of N G - N in floodwater to reduce NH3 volatilization after urea application (Fillery and Vlek, 1986). Nonetheless, controlling NH3 loss by inhibiting urease enzyme is a worthy effort, but the ultimate urease inhibitor, however, should be specific to urease, inexpensive, effective in low concentrations, and should not pollute the environment. Craswell et al. (1985) have shown that a significant quantity of 15N(15% N applied) can be detected in algae and weeds after 2 weeks of urea application. This may reduce NH3 loss by virtue of low N g - N concentration in floodwater. Craswell et al. (1981) found low NH, loss when N fertilizer is applied when root systems are well developed.

2 . Effect of Secondary Factors on Floodwater p H Floodwater pH is the resultant interaction of several properties including concentration of dissolved C 0 2and NH3, biotic activity, alkalinity, pH buffering capacity, and temperature (Keeney and Sahrawat, 1986). These floodwater properties are influenced by other practices such as fertilizer management, water quality, and the stage of crop development (Mikkelsen et al., 1978). Ponnamperuma (1978) reported that the pH of floodwater is largely a function of C 0 2 concentration and HCOS activity. pH = 7.85

+ log (HCOj)

Pco,

(15) Constant removal of C 0 2may increase the pH and addition of C02 may decrease the pH of floodwater. Mikkelsen et al. (1978)found a relationship between floodwater pH and the biotic activity. They observed a diurnal change in pH, which appears to be synchronized with the cycle of photosynthesis and respiration. They reported pH values as high as 9.5-10.0 by -

NH, VOLATILIZA7'10N FROM FLOODED SOILS

327

midday and decreasing as much as 2-3 pH units during the night (Fig. 10). Several others reported the biotic influence on floodwater pH (Park et ul., 1958; Mikkelsen and De Datta, 1979; Craswell et uf., 1981; Morel, 1983; Fillery ef ul., 1984). It is interesting to note that Bowmer and Muirhead (1987) were able to dampen the diurnal fluctuation in pH for 6 days, and significantly increased the ammoniacal N concentration in floodwater by using a photosynthetic inhibitor, terbutryne [2-( terf-butylamino)-4-(ethyl-

amino)-6-(methylthio)-S-triazine]. Bouldin (1986) summarized the sequence of events that happens during the day. Photosynthesis depletes C 0 2 , increases pH, and increases partial Percent mole fraction of H2C0,. HCOj and CO; 100 I

40 -9.0

30 -8.0

20 -7.0

10 - 6 0

I

I

I

I

1

0

J

5.0

Time FIG. 10. Changes in the pH and components of the carbonic acid system of rice floodwater 3 days after application of N fertilizer on Maahas clay, Los Banos. Philippines, 1976 wet season. (From Mikkelsen e t a / . , 1978.)

328

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

pressure of NH,. Therefore, NH, volatilization is increased during the day. At night, as respiration supplies C02, the sequence of events are reversed and the NH3 volatilization is decreased. Fillery et al. (1986b) reported that the algal enumerations in their study showed relatively low algal biomass. Nevertheless, they observed large fluctuations in pH of floodwater. This study shows that large algal populations are not required to increase floodwater pH to high values that support rapid NH, loss. Growth of algal biomass, however, is not a limitation in most rice growing ecosystems. Pantastico and Suaya (1974) reported that algal biomass is often regarded as a problem in rice floodwater in the Philippines. In Australia, large populations of diatoms and other algae sometimes smother the young rice seedlings (Dunigan and Hill, 1977), while in Bengal at least 1 million ha of transplanted rice are infested with stonewarts (Mukherji, 1968). The alkalinity of water is a measure of its capacity to accept protons. In natural waters, the alkalinity is generally established by the concentration of HCO;, COi-, and OH- ions. Other species, such as NH,, silicates, borates, and phosphates in natural waters may also contribute to the alkalinity of the system. Alkalinity and acidity are interrelated. Basically, acidity and alkalinity are a good measure of the buffering capacity of a given system. Ammonia volatilization is an acidifying process due to the release of Hf to the system. If there is no alkalinity in the floodwater, the pH may decrease and thereby reduces NH, volatilization. According to Vlek and Stumpe (1978), to sustain NH3 volatilization, alkalinity (chiefly HCOS) must be present in floodwater to buffer the production of H+. Several sources may provide alkalinity to floodwater. In Asia, artesian or ponded water is chiefly used as the irrigation source for dry-season rice crops (Stangel, 1979) and it may provide sufficient alkalinity to buffer the system. Vlek and Craswell(l981) reported that sufficient alkalinity can be found in areas with calcareous soils or when soils are irrigated with alkaline well waters. When N forms such as (NH4)2S04or (NH4)2HP04are used, irrigation water is probably the major source of alkalinity in floodwater systems (Fillery and Vlek, 1986). However, Fillery er al. (1986b) reported that regardless of the quality of irrigation water applied at the time of fertilizer application, the alkalinity in the floodwater can increase through evaporation or other processes. This highlights the likelihood that many flooded rice fields in Asia could contain an adequate quantity of alkalinity with modest rates of NH3 loss from N@-N. Urea hydrolysis produces HCO; that can buffer H + production when urea is used as the fertilizer. Therefore, NH3 loss from urea is less dependent on inherent alkalinity (Vlek and Craswell, 1981). Ammonium sulfate

NH3 VOLATILIZATION FROM FLOODED SOILS

329

application, on the other hand, will lead to NH3 volatilization only if the aqueous system is alkaline (Vlek and Stumpe, 1978). As discussed before, the various differences that had been reported (MacRae and Ancajas, 1970; Wetselaar et al., 1977; Ventura and Yoshida, 1977; Mikkelsen et al., 1978; Vlek and Craswell, 1979; Freney et al., 1981; Craswell et al., 1985; Katyal et al., 1985; Fillery and De Datta, 1986; Fillery et al., 1986b; Vlek and Byrnes, 1986) in NH3 fluxes for (NH4)2S04 and urea may be due to the degree of buffering capacity in floodwater as a result of alkalinity in the system. Fertilizer management and the stage of crop development influence the magnitude of diurnal fluctuations in pH of floodwater, presumably because of their effect on the algal biomass (Mikkelsen et ul., 1978). Terman (1979) reported that both N and P fertilizer contribute to algal bloom accompanied by higher water pH. Urea phosphate fertilizers promoted rapid algal growth immediately following either basal incorporation or broadcast application into floodwater (Buresh, 1987).He suggested that this elevation in pH was apparently due to the stimulation of algal photosynthetic activity by added P, and it may explain the failure of a phosphoric acid amendment to urea (urea phosphate) in reducing pNH3. Fillery et al. ( 1986b)observed the effect of stage of crop development on the diurnal fluctuation of pH in floodwater. According to them, the diurnal fluctuations in floodwater pH were lower when urea was added 5-7 days before panicle initiation. This effect probably resulted from lower photosynthetic rates in the floodwater, since the crop canopy was appreciably more dense in the fertilized areas that had earlier received the urea 14 or 21 days after transplanting. Fillery et al. ( 1984)also detected low rates of NH3 loss after urea was applied to flooded rice at the panicle initiation stage. According to them, aside from N uptake, it appeared that the rice crop shaded floodwater and thereby suppressed the increased pH attributed to photosynthetic activity in floodwater. Ventura and Yoshida (1977) reported that NH3 volatilization in flooded soil increased markedly with an increase in soil pH, which implies that soil pH has some effect on floodwater pH. MacRae and Ancajas (1970) reported the same. Vlek and Craswell(l979). however, showed that soil pH has little effect on the pH of floodwater and therefore on NH3 volatilization.

3 . Ejfect of Secondary Factors on Floodwater Temperutirre The secondary factors that influence the temperature in floodwater have an influence on the overall NH3 volatilization process. Temperature of

330

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

floodwater seems to be a function of solar radiation, windspeed, relative humidity, water depth, plant cover, and suspended materials in floodwater. The solar energy is received by the waterbody in the form of short-wave radiation. A fraction of incoming solar energy is returned to space by reflectionlscattering as short-wave radiation. The fraction that is returned from incoming solar radiation is known as albedo. It is interesting to note, the albedo of a natural water surface, about 6%, is the lowest of any natural surface (Hasse and Dobson, 1986). According to them, heat storage is quite different for water versus solid surfaces. In water, part of the solar energy may penetrate to several meters depth, although strong surface (0-10 cm) heat stratification usually occurs in flooded rice. In water, the turbulent motions may distribute the heat absorbed in the uppermost few centimeters throughout a deeper layer. Therefore, water surface temperatures respond only slowly compared to land surface temperatures. Leuning et a f . (1984), however, found that thermal stratification in turbid floodwater significantly influenced rates of NH3 loss. This may be due to a reduction in incoming solar radiation caused by suspended materials in floodwater. This shows that solar radiation, water depth, and suspended materials influence the temperature of floodwater. Atmospheric conditions, such as windspeed and relative humidity, influence the evaporation of water from a free water surface. Floodwater temperature decreased by 3°C to 15°C when airflow rate was increased from 5 to 20 L/min. Lowering of temperatures with increasing airflow rate was due to an acceleration in evaporative cooling (Katyal and Carter, 1989). 4 . Effect of Secondary Factors on Water Depth

Water depth is usually a function of supply and crop management practice. In irrigated agriculture, the farmer has the ability to control the water depth according to crop cultural needs. However, in rainfed agriculture during the wet season, intensity and duration of rainfall partially determine the depth of floodwater. Therefore, the depth of water can or cannot be controlled depending on the season, site, and the crop situation. 5 . Effect of Secondary Factors on Windspeed

When there is a crop canopy, the effect of wind on the water surface becomes minimized. Therefore, the structure of the crop canopy is an

NH, VOLATILIZATION FROM FLOODED SOILS

33 I

important secondary factor that influences the effect of windspeed on the water surface. The crop canopy also exerts a strong influence on the photosynthetic rates of the aquatic biota, which limits their effects on the water chemistry. Low rates of NH3 loss (10-15% of the N applied) were detected after urea was applied in flooded rice at panicle initiation (Fillery et al., 1984) and they concluded that dense plant canopy at panicle initiation may have restricted air exchange at the floodwater interface to minimize NH3 volatilization.

V. METHODS OF MEASURING AMMONIA VOLATILIZATION There are various methods available to measure NH3 volatilization from flooded systems. These include: ( I ) the enclosure methods with or without air exchange; (2) micrometeorological techniques; and (3) labeled tracer techniques. The methodology used generally influences the conclusions of a study and each of these methods has its own advantages and disadvantages. There are several excellent reviews on the methodologies used in NH3 volatilization measurements (Terman, 1979; Vlek and Craswell, 1981; Fenn and Hossner, 1985; Fillery and Vlek, 1986; Harper, 1988). Enclosure methods are most commonly used in NH3 volatilization measurements (Denmead, 1983). There are a variety of enclosure designs that are used to measure NH3 losses (Harper, 1988). These methods are simple and convenient, and can be used successfully to evaluate NH3 losses under a variety of experimental variables. The disturbance of natural conditions, however, make the interpretations of these measurements somewhat questionable in terms of actual field conditions. Micrometeorological techniques, on the other hand, have an advantage in that they do not disturb the natural environment conditions that influence NH3 volatilization. They provide an average integrated flux over a large area, which minimizes the sampling variability. These techniques. however, are difficult to use in practice as they are costly in instrumentation, are laborious, and are site specific and weather dependent in their application to the experimental area. There are three general types of micrometeorological methods: ( 1) eddy correlation; ( 2 )gradient diffusion; and (3) mass balance (Harper, 1988). Labeled tracer N has also been used to calculate NH3 loss. This is an indirect measurement and consequently, all other transformations including nitrification, denitrification, runoff, leaching, and plant uptake must be precisely determined to provide meaningful values for NH3 volatilization. As stated by Harper (1988),I5N balance cannot be used to evaluate NHq

332

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

loss from flooded soils since NH3 volatilization and nitrificationdenitrification proceed simultaneously with the addition of N to the soil.

VI. MODELS FOR PREDICTING AMMONIA VOLATILIZATION Assessments of NH3 volatilization can be made by understanding the system represented by a simplified model. The behavior of N a - N in flooded soil systems and the mass transfer of NH3 across the water-air interface is a dynamic process, however, involving numerous interactions. In an NH3 volatilization model it is vital to understand the various chemical and physical processes controlling the emission rates. Few models have been developed to predict NH3 losses as a function of floodwater chemistry and atmospheric conditions (Bouwmeester and Vlek., 1981a; Moeller and Vlek, 1982; Jayaweera and Mikkelsen, 1990a). A. BASICMODELSI N MASSTRANSFER

When there are two phases, the mass transfer of diffusing solute takes place from the bulk fluid of one phase into the interface, and then from interface to the bulk of the second phase. The concentration of the diffusing solute is virtually constant in the bulk fluid of both phases as a result of mixing caused by turbulence. Near the interface, in the boundary layer, the turbulence diminishes, resulting in a concentration gradient as the interface is approached and the mass flux experiences a resistance due to the mechanism of diffusion. Experimental verification of the conditions at or around the interface is difficult to achieve. Therefore, to understand the mass transfer in the interface region, it is necessary to develop theoretical models and validate these with overall mass-transfer experiments. Few basic hydrodynamic models have been presented in the literature to describe mass transfer across a gas-liquid interface. All these models represent a simplified mode of mass transfer. The mass transfer between two phases is described by three major models: (1) film model; (2) penetration theory (Higbie’s model); and (3) penetration theory (Danckwerts’s model). I . Film Model The first hydrodynamic model to describe the transport processes between two phases was the two-film model by Whitman in 1923 (see Fig. 1).

NHj VOLATILIZATION FROM FLOODED SOILS

333

He suggested that the resistance to transfer in each phase is confined in a thin stagnant, or laminar-flow film close to the interface between the two phases, in which the fluid is turbulent. This film is assumed to have a definite but unknown thickness. The mass transfer across these films is regarded as a steady-state process of molecular diffusion and it is assumed that there is no convection in the film.

2 . Penetration Theory: Higbie’s Model Higbie (1935) proposed a model to describe the hydrodynamic conditions in the liquid phase close to a gas-liquid interface. He suggested that the eddies in the fluid bring an element of fluid to the interface where it is exposed to the second phase for a definite interval of time, after which the surface element is mixed with the bulk again. Therefore, the fluid element where initial composition corresponds with that of the bulk fluid is remote from the interface, which is suddenly exposed to the second phase. This model considers the liquid surface to be composed of a large number of small elements that are being replaced by fresh elements from the bulk of the phase after a fixed time period. As the fresh liquid elements continually replace those interacting with the interface, the mass transfer is accomplished by the systematic removal of the interface. The exposure time of such fluid elements at the interface is so short that steady-state conditions do not develop, and any mass transfer of material takes place only as a result of unsteady-state molecular diffusion.

3 . Penetration Theory: Danckwerts’s Model

Danckwerts (1951) improved the surface renewal model proposed by Higbie, suggesting that the fluid element can have a variable surface residence time, which is exposed to the second phase; it may vary from zero to infinity. This means that each fluid element of surface would not be exposed for a constant time period as proposed by Higbie, but rather a random distribution of times could exist. This refinement of the surface renewal model is a result of an assumption that the probability of an element of surface being destroyed and mixed with the bulk fluid was independent of how long it has been on the surface. All three models share the feature that the rate of mass transfer is directly proportional to the concentration difference. In many instances the difference between predictions made on the basis of these three models will be less than the uncertainties about the values of the physical quantities used in the calculations, and, therefore these models can be regarded

334

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

as interchangeable for many purposes. It is merely a question of convenience concerning which of the three models is used. When numerical computations are involved, it is generally simple to use Higbie’s model rather than Danckwerts’s model to compute the rate of transfer per unit area of the interface. The computations relating to the film model are, of course, simpler since they involve ordinary rather than partial differential equations. In most cases, however, the film model would lead to almost the same predictions as the surface renewal models (Danckwerts, 1970).

B. BOUWMEESTER A N D VLEK AMMONIA VOLATILIZATION MODEL The NH3 volatilization model developed by Bouwmeester and Vlek (1981a) has a resemblance to the penetration theories of Higbie and Danckwerts. Major difference in their analysis, however, is that the surface liquid element has a known time of exposure to the atmosphere, depending on the wind velocity and the location of the element in the rice paddy. By considering the following chemical reaction NHI 3 N H 3 + H+

(16)

where k l and kz are the forward and reverse rate constants, Bouwmeester and Vlek (1981a) developed the following relationship to calculate the average NH3 volatilization rate per unit area,

e.

where AN is the ammoniacal N concentration in the bulk liquid; and td = F/Ud is the time during which the water chemistry, wind, and water conditions are supposed to remain steady depending on the fetch, F, and surface drift velocity, u d ; and

P

=

kakH/D(l

+ R)

*

(18)

where k, is the bulk transfer coefficient of NH3 in air, k~ is the Henry’s constant, and D is the molecular diffusivities; and

R

=

(H+ k 2 / k l ) = (H+/K)

(19)

where H+ is the hydrogen ion concentration in the system, and K is the equilibrium constant. Equation (17) includes the effect of ammoniacal N concentration, pH,

NH3 VOLATILIZATION FROM FLOODED SOILS

335

temperature, wind, and fetch on the process of NH3 volatilization. The temperature effects are reflected in the coefficients, D, k H , and R. In developing the model, Boumeester and Vlek (1981a) assumed that for the time ( t d ) when the liquid element is at the surface, the chemical reaction does not change the pH. Hoover and Berkshire (1969) in studying the CO:! exchange across an air-water interface also applied the same concept. They made this assumption because of the high mobility of the hydrogen ion. They argued that as the hydrogen ions have eight times the mobility of the bicarbonate ions, there would be no possibility of building up a significant concentration gradient. Therefore, the ratio N H 3 / N G is constant throughout the diffusion layer with spectator ions maintaining the electroneutrality . Bouwmeester and Vlek (198 la) validated the model in a wind-water tunnel experiment, which simulated the flooded rice paddies. Considering the complexity of the physical and chemical processes, they reported that the validation study seems to support the numerous assumptions made in developing the basic model equation in NH3 volatilization. Although the quantitative agreement is not fully satisfactory, the results suggest that the mathematical model may be applied to analyze the rate-controlling factors of NH3 volatilization from rice paddies. By simulations they found that the rate of NH3volatilization is increased with increasing N G - N concentration, pH, temperature, and wind velocity but is decreased with increasing fetch. The results suggest that the effects of wind, temperature, and pH on NH3 volatilization are of the same order of magnitude. At a high pH, the volatilization rate of NH3 is controlled by the transfer rate in the liquid diffusion layer and the effect of high windspeed is reduced. At low pH, the volatilization rate is limited mostly by the NH3 transfer rate in the air.

c. MOELLERA N D VLEK AMMONIA VOLATILIZATION MODELS Moeller and Vlek (1982) developed two mechanistic models, the pH constant model, and the pH gradient model, for the transport of NH3 from aqueous solution to the atmosphere. These models are adaptations of the stagnant-film model used in studying gas exchange across an air-water interface (Danckwerts, 1970; Liss, 1973). Considering Fick’s first law of diffusion, and integrating over the thickness of the gas and liquid phase films, they obtained the following equations for the ammonia flux.

336

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

where J , is the NH3 flux in the gas phase, D, is the diffusion coefficient of NH3 in air, 6, is the thickness of the gas film, and the superscripts b and o designate the bulk and surface concentrations or activities. ~ O A N )

where JI is the total ammoniacal flux in the liquid phase, DIis the diffusion coefficient for NH;f in aqueous solution, SI is the thickness of the liquid film, and (IAN is the total ammoniacal activity a N H , -k a N H z =

(1

+ aH'IK1) UNH,

(22)

where K I is the equilibrium constant for NI$/NH3 system. At steady-state condition, when the diffusion flux through the liquid equals that through the gas, they obtained the following expression by equating the right-hand sides of Eqs. (20) and (21) and expressing the ammonical nitrogen activity at the surface in terms of H + , K I and U N H , . ~

61Dg ([NH,]; 06,

-

[NH& =

a b A ~-

(1

+ aO"+/KI)QONH,

(23)

The 6, and 6, parameters are determined experimentally. However, to solve for U'NH, to calculate the flux using Eq. (21), it is necessary to determine three independent variables, [NH3],b, a'L, and [NHJ:. Therefore, they obtained three additional relationships. By assuming that the instantaneous steady-state flux is known, they obtained the following relationship to calculate [NH3],b.

[NH3],b = J A / S

(24)

where A is the surface area of the solution and S is the airflow rate being passed over the solution (volume/time). In practice, however, J is not known without having first solved for the surface concentrations. They used an iterative procedure with the bulk gas phase NH3 concentration set initially at zero and the surface concentration calculated in the manner described below. The NH3 flux can then be calculated and the bulk NH3 concentration can be determined. By assuming that the aqueous NH3 and gas phase NH3 are in equilibrium at the interface, they obtained the following relationship for [NH3]:.

"H31," = k~ ~ O N H , / ( RT) (25) where k H , R , and T are the Henry's law constant for NH3, the gas constant, and absolute temperature, respectively. The surface hydrogen ion activity, U'H+ is determined by two different

NH3 VOLATILIZATION FROM FLOODED SOILS

337

methods, which differentiate the two models they developed. In the pH constant model, as assumed by Hoover and Berkshire (1969), they treated pH as a constant across the liquid film. Therefore, =

b

(26) In the pH gradient model, by following the treatment of Quinn and Otto (1971), they developed a cubic expression for the surface hydrogen ion activity . aoHb

a0H+3

H+.

+ pa''H+* + q a o H + + r = 0

(27)

with

r

=

-C K1 K ,

and

where y is the activity coefficient, "a+] and [SO:-] are the spectator ion concentrations, and K , is the equilibrium constant for water. Moeller and Vlek (1982) tested the two stagnant-film volatilization models in a series of laboratory experiments. They employed a small volatilization chamber connected to an airflow system, an experimental technique that is suited for the investigations of the fundamental processes of NH3 volatilization in systems artificially maintained free of CO?. It was evident from the experimental results that the model that assumes a pH gradient in the liquid diffusion film accurately predicts the observed volatilization rate, whereas the pH constant model does not. This indicates that the surface layer retains some importance as a resistance to volatilization at moderate and low pH. Bicarbonate and other buffers, however, can mitigate this pH gradient (Moeller and Vlek, 1982). It is interesting to note that the effective thicknesses of the liquid- and gas-phase stagnant films calculated from NH3 volatilization and water evaporation rates in the chamber are similar to corresponding parameters found in larger scale wind tunnel experiments. Therefore, Moeller and Vlek (1982) stated that it is possible to perform NH3 volatilization studies in small chambers. Bouwmeester and Vlek (1981a,b) also reached a similar conclusion in their studies.

338

GAMANI R. JAYAWEERA AND DUANE S . MIKKELSEN

D. JAYAWEERA A N D MIKKELSEN AMMONIA VOLATILIZATION MODEL The NH3 volatilization model developed by Jayaweera and Mikkelsen (1990a) computes the rate of NH3 volatilization as a function of five primary factors, which include the floodwater N&-N concentration, pH, temperature, depth of floodwater, and windspeed. In previous models researchers have taken these factors into consideration but not the depth of floodwater. The role of depth of floodwater in NH3 volatilization is twofold. It directly affects N&-N concentration by virtue of its dilution effect. Further, it influences the volatilization relationships ( Jayaweera and Mikkelsen, 1990a).

1 . Model Development

The ammonia volatilization model presented by Jayaweera and Mikkelsen (1990a) consists of two parts: (1) chemical aspects (N&/NH3(aq, equilibrium in floodwater); and (2) volatilization aspects (NH3 transfer from floodwater across the water-air interface). a . Chemical Aspects of the Model. The chemical dynamics of NH3 volatilization from floodwater is described as follows:

where kd and ka are dissociation and association rate constants for NI-@ NH3(,,, equilibrium and kvN is the first-order volatilization rate constant for NH3. By chemical kinetics, Jayaweera and Mikkelsen (1990a) derived the following expression to determine the rate of NH3 volatilization from a flooded system.

}

k d (AN - “H3Iaq -d“H$ - = k , {I - k d (AN - “H3Iaq) (31) dt kJH’1 + k,N where A N is the ammoniacal N concentration, [NH3],, is the aqueous NH3 concentration, and [H+]is the hydrogen ion concentration in floodwater at equilibrium. They have estimated the rate of NH3 volatilization by the rate of change in N G concentration in floodwater with the assumption that no other process changes the NI$ in the system. There are various processes, however, which bring N& into floodwater, such as soil desorption, organic matter mineralization, and those which remove N& from flood-

NH, VOLATILIZATION FROM FLOODED SOILS

339

water, such as soil adsorption and biotic assimilation. It is assumed that these processes quickly equilibrate and subsequently affect little change in floodwater N G concentration. Further, by making frequent N@ measurements and by using these values as model inputs, any error due to this assumption will be minimized. Equation (31) estimates the rate of NH3 volatilization as a function of ammoniacal N concentration, aqueous NH3 and H + concentration in floodwater, rate constants k d and k, for the NIlfi/NH3(aq)equilibrium, and the volatilization rate constant for NH3, k v N . The N@-N concentration and pH of floodwater are experimentally determined. Rate constants k d and k,, whose determination is discussed next, are computed in the chemical aspects of the model. Volatilization rate constant, k v is~ computed in the volatilization aspect of the model. Aqueous NH3 is computed as a function of N@ concentration, pH, and temperature. The rate of NH3 volatilization can be computed by applying these values to Eq. (31). The rate constants at various temperatures are calculated in the model. First, the equilibrium constant, K, for the N&/NH3(aq) system is computed, followed by the association rate constant, k,. Finally, the dissociation rate constant, k d is obtained with the use of K and k,. By applying the Clausius-Clapeyron equation to the N@/NH3(,,, equilibrium, and by using the values pK at 25°C as 9.24 and AHo as 12,480 cal (Dean, 1986) Jayaweera and Mikkelsen (1990a) derived the following expression to compute pK at any temperature. 2729 pK(T) = 0.0897 + (32) T where pK( T ) is -log K, equilibrium constant for NIlfi/NH3(,,, system at absolute Kelvin temperature T . A similar equation has been derived by Bates and Pinching (1949) by a different methodology. The association reaction between NH3 and H + in water, as measured by Eigen and co-workers, is diffusion controlled (Alberty, 1983). Therefore, Jayaweera and Mikkelsen (1990a) assumed that the rate constant for the association reaction is proportional to the diffusion coefficient. By using Stokes-Einstein equation (Laidler and Meiser, 1982) and with the use of the association rate constant at 25°C (Alberty, 1983) and the viscosity of water at different temperatures (Dean, 1986), Jayaweera and Mikkelsen (1990a) developed the following relationship to compute k, values as a function of absolute Kelvin temperature T.

k,( T ) = 3.8 x 10"

-

3.4 x 109T + 7509700 T2

(33)

By using the equilibrium relationship, the dissociation rate constant, k d for the NG/NH3(aq)system at various temperatures can be computed.

340

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN kd(

T ) = K( T ) X

ka(

T)

(34)

where K ( T) is the antilog of pK( T) at absolute Kelvin temperature T. b. Volatilization Aspects of the Model. The volatilization aspect of the model is based on the two-film theory proposed by Whitman in 1923 . and is used to compute the volatilization rate constant for NH3,k v ~The controlling factor for the mass transfer of NH3 across the interface is the rate of diffusion through the two films on either side of the interface, where all the resistance lies. This shows the liquid phase or gas phase resistance or both, and determines the overall mass transfer rate of NH3. In developing this model, Jayaweera and Mikkelsen (1990a) have assumed that an N@/NH3(aq)equilibrium is established in the floodwater, and that NH3 in aqueous phase diffuses from the bulk of the liquid phase to the interface across the thin film. It is assumed, although perhaps inconclusively, that the pH in the surface film remains constant. Hoover and Berkshire (1969) and Bouwmeester and Vlek (1981a) made the same assumption in their gas exchange studies. Computation of various parameters of the volatilization aspects of the model is presented as follows: 1. Determination of volatilization rate constant for NH3, k v N : By material balance of the NH3 system, Jayaweera and Mikkelsen (1990a) showed that the volatilization rate constant for NH3,kvN is represented as a ratio: kvN =

~

Kon d

(35)

where KON is the overall mass transfer coefficient for NH3, and d is the mean depth of floodwater. The relationship expressed by Eq. (35) shows that the volatilization rate constant for NH3 is inversely related to the depth of floodwater. To estimate the volatilization rate constant, however, it is necessary to know the overall mass transfer coefficient for NH3, KON. 2. Determination of overall mass transfer coefficient for NH3, K O N : The rate of NH3 transfer through the gas film is the same as through a liquid film, under steady-state conditions. Since the movement through the film layers is by molecular diffusion, it can be described by Fick’s first law of diffusion.

where FN is the flux of NH3 gas through the surface films in x direction, D N is the molecular diffusion coefficient or diffusivity of NH3, and d C N / d x is the concentration gradient of NH3 gas across the film of thickness x.

34 1

NH3 VOLATILIZATION FROM FLOODED SOILS

The ratio of D N I A x in Eq. (36) can be considered as a constant, k N , under a given set of conditions and is the exchange constant for NH3 gas, which has the dimensions of velocity, Llt. k

N -

DN Ax

(37)

It is possible to obtain another form of the Fick's law equation generally used in gas exchange studies by substituting Eq. ( 3 7 ) into Eq. (36).

FN = kN ACN (38) where A C N is the concentration difference of NH3 across the layer of thickness x. By transforming Eq. (38), the exchange constant for NH3, k ~ is, obtained as

Therefore, it is seen that the exchange constant for NH3, k N , is a measure of the flux of NH3 per unit concentration difference across the layer of thickness x. The value of kN depends on many factors, of which the degree of turbulence in the fluids on both sides of the interface is important. Under steady-state conditions and by applying Eq. (38) to the two-film situation and with the nondimensional form of Henry's law constant, Jayaweera and Mikkelsen (1990a) obtained the following expression after simplifying by introducing two constants: FN

=

KGN( C g N

- HnN CIN) =

KLN[(CgN/HnN)

-

c IN1

(40)

where

l/KGN = l/k,N

+ HnN/klN

(41)

~ / K L N= l/klN

+ l / H n kgN ~

(42)

and

where KGNand KLN are the overall gas phase and liquid phase coefficients for NH3, kgN and klN are the exchange constants for NH3 in gas phase and liquid phase, respectively, and H n is~ the nondimensional Henry's law constant for NH3. The total resistance of NH3 transfer can be expressed on either a gas phase, I I K G N , or a liquid phase, l I K L N , basis. For convenience, Jayaweera and Mikkelsen (1990a)considered ~ I K L Nas the total resistance for NH3 flux from a water body, and it was rearranged to determine the overall

342

GAMANI R. JAYAWEERA AND DUANE S . MIKKELSEN

mass transfer coefficient for NH3, K O N , which is numerically equal to the overall liquid phase coefficient for NH3, K L N . (43) + kgN -t klN) To estimate KON,it is necessary to determine the nondimensional Henry’s law constant for NH3, H n ~and , the gas and liquid phase exchange constants for NH3, kgN and k l ~respectively. , 3. Determination of Henry’s law constant for NH3, H N , MPa m3/mol: Henry’s law constant is a coefficient which represents the equilibrium distribution of a material between gas and liquid phases. The Henry’s law constant should be obeyed reasonably well under flooded conditions, because of relatively low concentrations of NH3 in floodwater. Several researchers have used the Henry’s law relationship in their NH3 volatilization studies in floodwater systems (Bouwmeester and Vlek, 1981a; Moeller and Vlek, 1982; Leuning et ul., 1984; Jayaweera and Mikkelsen, 1990a,b). The Henry’s law constant for NH3, HN, in MPa m3/mol, can be expressed in an equation form as follows: KON = KLN =

( H n N kgNklN)/(HnN

PN

HN = - MPa m3/mol CN

(44)

where P N is the partial pressure of NH3 gas in MPa and CN is the concentration of NH3(aq)in floodwater in mol/m3. a. Determination of partial pressure of NH3 gas, P N , MPa: Jayaweera and Mikkelsen (1990a) derived an expression to estimate the mole fraction of NH3 in floodwater, XN, as a function of pH and absolute temperature. xN

=(C/17.03) (A11

(Cl17.03) (All + A) + A) + (C/18.04) (111 +A) + 1O6p,/18.O2

(45)

where A = 10 exp (pH - 0.0897 - 2729lT) (46) C is the total N e - N concentration in floodwater, pw is the density of

water in gm/cm3 at T, pH is the pH of floodwater, and T is the absolute Kelvin temperature of floodwater. By using the Henry’s law relationship, they obtained the following expression for the partial pressure of NH3 in the gas phase in equilibrium with its solution. P N = 18.62 exp (-1229/T)X~MPa

(47)

According to Eq. (49, the partial pressure of NH3 in the gas phase varies with N@-N concentration, pH, and temperature of floodwater. b. Determination of concentration of NH3(aq),CN,mol/m3: If the total ammoniacal N concentration is C mg/L, by proper conversion, the con-

NH3 VOLATILIZATION FROM FLOODED SOILS

343

centration of NH3, CN, can be determined in mol/m3 (Jayaweera and Mikkelsen, 1990a). CN = (C/17.03)

[lo exp (pH - 0.0897 - 2729/T)] movm3 (48) [l + 10 exp (pH - 0.0897 - 2729/T)]

By using Eqs. (47) and (48), they obtained the Henry’s law constant in MPa m3/mol. 4. Determination of nondimensional Henry’s law constant for NH3, H n ~Henry’s : law constant for NH,, which is computed in MPa m3/mol, H N , can be transformed into nondimensional form as follows:

HN HnN = RT

(49)

where R is the gas constant, 8.315 x lop6 MPa m3/mol/deg K, and T is absolute Kelvin temperature. 5. Determination of gas phase, kgN, and liquid phase, k l N , exchange constants: Exchange constants have dimensions of velocity and can be considered as the velocity at which NH3moves through the fluid films. The value of exchange constants kgN and klN depend on the degree of turbulence in the fluids on either side of the interface, chemical reactivity of the substance, temperature, and the properties of the solute, such as diffusivity or molecular size (Liss and Slater, 1974; Mackay and Yeun, 1983). These exchange constants, however, have not yet been readily computed using basic physical principles and generally are determined empirically (Thomas, 1982). Henry’s law constant of a chemical gives some insight into the distribution of resistances in the liquid and gas films. The Henry’s law constant for NH3 varies between 4.36 x to 6.59 x lop6 MPa m3 mol in the usual temperature range found in floodwater, i.e., 10-40°C (Jayaweera and Mikkelsen, 1990a). According to the model developed by Jayaweera and Mikkelsen (1990a), the process of NH3 volatilization is therefore controlled by both gas and liquid phase resistances (Mackay et al., 1979). Liss and Slater (1974), however, suggested that the rate of NH3 volatilization is controlled by the gas phase resistance, whereas Leuning et al. (1984) found that NH3 fluxes were controlled by transport processes in both the atmosphere and the water. By using the data of an experiment performed by Liss (1973) in a wind tunnel, a regression equation was developed to relate the water vapor exchange constant, k,w (cmlh) and the windspeed (Jayaweera and Mikkelsen, 1990a). kgw = 18.5683 + 1135.89 U0.l

(50)

344

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

where U0.1 is the windspeed at 0.1 m above the water surface in the wind tunnel. Jayaweera and Mikkelsen (1990a) developed a relationship between the windspeed in the wind tunnel used by Liss (1973) and the equivalent field wind speed at 8 m:

us = 1.5686 uo.1

(51)

This is in close agreement with the relationship developed by Bouwmeester and Vlek (1981a). The water vapor exchange constant, kgw is transformed into field situations with Eq. (51), and is adjusted to NH3 transfer with the use of the molecular weight ratio of water and NH3 (Liss and Slater, 1974) to obtain the gas phase exchange constant for NH3, k g (Jayaweera ~ and Mikkelsen, 1990a). kgN =

19.0895 + 742.3016 US

(52)

Similarly, the COz exchange constant data of Liss (1973) were fit into a logistic equation and adjusted to field situation by Eq. (51) for the molecular weight ratios to obtain the liquid phase exchange constant for NH3, k l ~ . klN =

{12.5853/[1 -k 43.0565 exp (-0.4417 us)]}1.6075

(53)

By using the model (Jayaweera and Mikkelsen, 1990a), k l N and k g ~ values are computed at various windspeeds; both constants show an increase with increase in windspeed. They have developed a relationship to transform the measured windspeed at any height over a water surface to a windspeed at 8 m height by assuming a logarithmic wind profile, which is used in the NH3 volatilization model (Jayaweera and Mikkelsen, 1990a).

Us =

11.51 In ( Z / 8 x 10-5)

uz (54)

where US is the windspeed at 8 m height in m/s, and UZis the windspeed at Z m height in m/s. It should be noted, however, that Eq. (54)is based on the assumptions of neutral stability and windspeed measurements over flat water surfaces. These assumptions may be violated at night or at times of very low or very high evapotranspiration rates, or if plant cover exists above the water surface, which would decrease the accuracy of the equation ( Jayaweera et al., 1990).

NH3 VOLATILIZATION FROM FLOODED SOILS

345

2. Model Execution The ammonia volatilization model ( Jayaweera and Mikkelsen, 1990a)is executed with several input variables. They are floodwater N G - N concentration, mg/L (AMC); pH; temperature, "C (TEMP); depth of floodwater, cm (WD); windspeed, m/s (WS); and the height of wind measurement, m (WH) (Fig. 1 1 ) . The model calculates the initial volatilization rate of NH3 (VRAMI). Ammonia loss for a specific period is obtained by entering the time period as an input and the model computes the decrease in volatilization rate as a function of the time with a successive approximation loop. The final output is the predicted NH3 loss for the selected time period.

3. Sensitivity Analysis

The sensitivity analysis has been performed on the model to test the influence of various determinants on NH3 volatilization. Floodwater NI$-N concentration shows a linear relationship to NH3 volatilization when other factors such as pH, temperature, depth of floodwater, and windspeed are kept constant. This direct relationship is due to an increase in NH3(aq)in floodwater as a function of NHfN concentration as has been reported (Vlek and Stumpe, 1978; Vlek and Creswell, 1979; Fillery and Vlek, 1986;Jayaweera and Mikkelsen, 1990b).Therefore, in the sensitivity analysis performed by Jayaweera and Mikkelsen (1990b), the floodwater N G - N concentration is kept at a constant value of 25 mg/L. The effect of four other factors, pH, temperature, depth of floodwater, and windspeed were tested in sensitivity analysis under these different sets of conditions. At each condition, one factor is varied while the others are kept constant. The final output, NH3 loss per day, is shown in Fig. 12. The sensitivity (slope) of NH3 loss per day with respect to pH, temperature, water depth, and windspeed is shown in Table I. A detailed account of the sensitivity analysis was presented by Jayaweera and Mikkelsen ( 1990b). In summary, under conditions 1 , 2 , and 3 , pH was the most sensitive variable; temperature was the least sensitive under conditions I and 2 ; and water depth showed the least sensitivity under condition 3 (Table I, Fig. 12). The sensitivity analysis shows clearly that it is not possible to generalize on the effect of one variable without considering the other interacting conditions. Therefore, the magnitude of NH3 loss from floodwater can be predicted only by taking into account all five primary factors simulta-

346

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

Input TIME

1

Q Calculate NH3 loss Display NH3 loss

Qirl Print NH, loss

Ino

(G-) FIG. 11. Flow chart for NH3 volatilization model. (From Jayaweera and Mikkelsen, 1990b.)

347

NH, VOLATILIZATION FROM FLOODED SOILS

--

E

CONDITION 1: AMC = 25 rng/L pH = 8.0 TEMP = 20 deg C WD = 7 crn Ug = 4 rn/s

10-

-.--.-

v)

3 20E

Y

CONDITION 2:

WD = 1 0 crn Us = 6 rn/s

n I

z

CONDITION 3:

T-T

Wind speed a t 8 rn, rn/s

04 pH TEMP, deg C

WD,crn U8. m/S

(Ug) -

;

8

9

10

20

30

I d0

7

13

19

4

8

12

I

I

1 I

0

I

+

FIG.U. Sensitivity analysis for NH3 volatilization model AMC (NHi-N concentration in floodwater). (From Jayaweera and Mikkelsen. 1990b.l

348

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN

Table I Sensitivity Analysis of Model (Slope) Affected by pH, Temperature, Depth of Floodwater, and Windspeed" Condition

Percent NH3 loss/d/unit change 7.25

1

2 3

I 2 3

1

2 3

1

2 3

7.75

2.5 4.5 7.4

7.0 11.6 16.5

12.5

17.5

0.2 0.6 0.5

0.3 0.7 0.3

2.5

5.5

-3.9 -0.2 0.0

-1.1 -1.0 0.0

1

3

I .2 3.5 8.1

1.4 3.0 2.8

pH', 8.25

d. e

8.75 19.0 11.3 3.7

16.0 20.0 18.4

Temperature, "Cb,d . ' 22.5 27.5 0.4 0.7 0.9

0.5 0.6 0.0

Water depth, cmb, " ' 8.5 11.5 -0.5 -0.9 0.0

-0.3 -0.8 0.0

Windspeed, m/sb, c . 5 7

I .9 2.7 0.8

1.5 I .7 0.0

9.25

9.75

4.5

0.5 0.0

0.0 0.0 0.0

32.5

37.5

0.6 0.4 0.0

0.6 0.2 0.0

14.5

17.5

-0.2 -0.6 0.0

-0.1 -0.5 0.0

9

11

1.5 0.7 0.0

0.9 0.3 0.0

" NHZ-N concentration was 25 mglL for all three conditions. pH values for conditions 1, 2, and 3 were 8.0.8.5, and 9.0, respectively.

' Temperatures for conditions 1 , 2 , and 3 were 20, 25, and 30, respectively. Water depths for conditions 1, 2, and 3 were 7, 10, and 13, respectively.

' Windspeeds for conditions I , 2, and 3 were 4 , 6 , and 8, respectively.

neously , which determine the NH3(aq)concentration and the volatilization rate constant for NH3. 4 . Model Validation

The ammonia volatilization model predicting NH3 loss as a function of input variables was validated using a wind tunnel to simulate rice paddy conditions and direct field experiments (Fig. 13) (Jayaweera et al., 1990).

NH3 VOLATILIZATION FROM FLOODED SOILS

349

FLOODWATER DEPTH

FIG. 13. Diagrammatic representation of the experimental field setup. (From Jayaweera e t a / . , 1990.)

There were a total of 13 wind tunnel runs to determine the effect of 5 composite combinations of variables on NH, volatilization. A central composite statistical design including mean values for each variable, as well as maximum and minimum values of each variable, were used in the experiment as described in Table 11. The solution samples collected during the wind tunnel runs show the N a - N depletion rate under various treatment conditions. For each run, by using first-order kinetics, a straight line was fitted after logarithmic transformed concentration values and the rate constants and half-life values of NHi-N depletion were calculated. The highest rate constant and the shortest half-life for N a - N depletion were observed when the pH is 10.5 and the lowest rate constant and the largest half-life value occurred when the pH is 6.5. It is interesting to note that the rate constant almost doubled, from 0.00028 to 0.00054, when the temperature was increased from 20 to 30°C, which is common for chemical reactions (Jayaweera et ul., 1990). The average value for the predicted -+ observed NH3 loss for the 13 wind tunnel runs is 1.2, suggesting that on the average, the model predicted NH3 loss quite close to the observed values under the experimental conditions in the wind tunnel. Linear regression of the observed NH3 loss on predicted values indicates that the regression coefficient R2 improved greatly when the high windspeed (8.9 m/s), high pH (10.9, and low pH (6.5) runs were omitted, indicating that the model has some limitations under certain conditions. Then the regression equation becomes observed NH3 = -0.43

+ 0.99 (predicted NH3 loss)

(55)

with a R2 of 0.98. The close fit (Fig. 14) of the observed on predicted values shows that the

Table 11 Experimental Details, Equivalent Field Windspeed at 8 m Height, Us,and Observed and Predicted NH, Loss for Wind Tunnel Runs

Variable (Wind tunnel run) Mean (1) Mean (2) Mean (3) NHZ-N concentration Low (4) High (5) PH Low (6) High (7) Temperature Low (8) High (9) Water depth Low (10) High (I 1) Windspeed at 8 m Low (12) High (13)

Initial NHi-N conc. (mglL)

PH

Temp. (“C)

Water depth (cm)

Free stream windspeed (mls)

(mls)

Observed NH3 loss (mgW

Predicted NH3 loss (mg/L)

Predicted + observed

52.3 52.6 53.2

8.5 8.5 8.5

25 25 25

11.0 11.0 11.0

2.9 2.8 2.7

4.4 4.2 4.1

8.3 8.3 7.9

9.5 9. I 8.9

1.1 1.1 1.1

26.2 102.5

8.5 8.5

25 25

11.0 11.0

2.6 2.7

4.1 4.1

3.5 24.8

4.3 49.8

1.2 2.0

52.7 49.8

6.5 10.5

25 25

11.0 11.0

2.6 2.9

4.1 4.4

1.8 24.8

0. I 49.8

0.1 2.0

52.5 53.1

8.5 8.5

20 30

11.0 11.0

2.7 2.9

4.1 4.4

5.5 11.8

6.2 13.3

1.1 1.1

52.7 50.3

8.5 8.5

25 25

6.4 21.3

2.8 2.8

4.2 4.2

14.6 4.5

14.6 4.7

1 .O

51.6 52.9

8.5 8.5

25 25

11.0 11.0

1.9 5.3

2.9 8.2

6.5 12.2

5.7 22.3

0.9 1.8

U8

I .O

35 1

NH3 VOLATILIZATION FROM FLOODED SOILS 20 0

r)

r z 13 VI m

0

5l

'I

10

0

,f

**

* ' 0 //* OBS = -0.43

+ 0.99 PRED.

0

0 0

0 , 0

1

5

I

10

15

20

PREDICTED NH3 LOSS (mg/L)

FIG. 14. Regression of observed on predicted NH3 loss in wind tunnel runs. (From Jayaweera et al., 1990.)

model predicted NH3 loss quite well within the range of conditions usually found in flooded systems. Field experiments show a close agreement of predicted values with observed data collected during 3 days at two different time periods and averaged for 6 h and 24 h (Fig. 15). Regression of observed N a - N depletion data on predicted values to test the closeness of fit also showed a close agreement. However, as the averaging period is increased to 24 h, the regression slope is increased to a value slightly greater than 1.O, and the intercept decreases below 0 (Jayaweera et al., 1990). In general, it is seen that observed values from the wind tunnel and field experiments agreed closely with the predicted values from the model. By scrutinizing the data (Jayaweera et al., 1990) it is established that the amount of NH3 loss, which is a function of volatilization rate of NH3, is quantitatively described by the concentration of NH3(aq)in the floodwater, which in turn is governed by N G - N concentration, pH and temperature , is a of floodwater, and the volatilization rate constant for NH3, k v ~which function of temperature, water depth, and windspeed. The NH3 volatilization model presented by Jayaweera and Mikkelsen (1990a,b) has several unique features. It has a menu-driven computer program that can be easily executed. It requires only 5 input variables to predict NH3 loss and no input constants since the model computes all necessary constants, depending on the variables provided. Input variables

352

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN 55 -

August 4

h

1 -I

,

F

v

z

0

8

*=.-*-

O B S m

A-

A PREDlcTm

0-0 O B S m

.r,

th.--a-

45--

A- APRED~CTED .---I-

-a\&

g

z z 0

LEGEND

.-a

August 8 35

!!-%-

a-$-Qh 0-e-

z I

-

. Q B

6 h AVERAGE

+I"

-4

Q-Q-

I

251

-

1 _I

F

55

-

v

g

g w

v

z

0

-I* -0-0

-

- ---a--=&-

0 z I

24 h AVERAGE

I

0BSm

A PRmICTED

0-0 OBSEIIYED A - A PRmICIEU

-*\*

August 8 35--

A-

-

45--

+-t

z

LEGEND:

August 4

"-

--

I

-0

25 '1

FIG. 15. Predicted and observed N K - N depletion in the field. (From Jayaweera ef al., 1990.)

are easily measurable with simple, inexpensive instrumentation. Analytical measurements are needed only for the initial foodwater N$-N concentration. Depth of floodwater is measured initially and generally remains constant, thus frequent measurements are needed for only three variables, pH, temperature, and windspeed (Jayaweera et al., 1990). Jayaweera et al. (1990) concluded that the model is useful in simplifying the complex NH3 volatilization process by considering only two major parameters: (1) aqueous NH3 concentration; and ( 2 ) volatilization rate constant for NH3 as a function of five variables, N$-N concentration, pH, temperature, water depth, and windspeed, which determine the volatilization rate of NH3 to accurately predict the NH3 loss in the range of conditions found in flooded systems.

NH3 VOLATILIZATION FROM FLOODED SOILS

353

VII. EPILOGUE Ammonia volatilization is a major mechanism for N loss from flooded soil systems such as rice paddies, ponds, lakes, wastewater ponds, and manufacturing systems. Losses of NH3 from rice paddies have been identified as a factor associated with low fertilizer use efficiency and reduced crop yields. The preceeding discussion has been directed primarily to the basic aspects of NH3 volatilization wherein N G - N concentrations in floodwater directly influence aqueous NH3 levels and where water pH and temperature determines the fraction of N G I N H 3 dissociation. The higher the water N G - N content and water pH and temperature, the higher is the aqueous NH3 concentration and NH3 volatilization from floodwater. It is shown that the volatilization rate constant for NH3 is determined by temperature, water depth, and wind speed. Elevated water temperatures, high wind speeds, and shallow water depths increase the volatilization rate constants, and consequently the quantity of NH3 to be lost from flooded soil systems. Theoretical aspects of the models are presented together with laboratory and field verification data in such a manner that the NH3 volatilization process can be understood and assessments can be made of NH, volatilization losses. Only two parameters, aqueous NH3 concentration and the volatilization rate constant for NH3 as influenced by 5 variables (water N G - N concentration, pH, temperature, water depth, and wind speed), figure prominently in NH3 volatilization process. A knowledge of how NH3 volatilization occurs, assessments of field losses in agricultural crop production, and an appreciation of how agronomic principles can be used will help to minimize losses. Improved crop, soil, and water management practices can be used to increase N-use efficiency (especially in flooded rice), to conserve costly fertilizer materials, and to minimize environmental pollution.

ACKNOWLEDGMENTS The authors wish to express deep appreciation to the William G. Golden and Kathleen H . Golden Fellowship Fund (University of California, Davis) and U.S.-AID Grant No. DAN1406-G-SS-4079-00for partial financial support of the research conducted by them on ammonia volatilization. We also express our deep gratitude to Sarah S . Magalong for the typesetting of this manuscript.

354

GAMANI R. JAYAWEERA AND DUANE S. MIKKELSEN REFERENCES

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NH, VOLATILIZATION FROM FLOODED SOILS

355

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INDEX A

nitrogen in rice-legume systems and, 1 1, 24,33-34,39-40 Aeschynomene afraspera, green manure in wetland rice and, 141, 148 Agroforestry, genetic resources and, 62, 75-81,83-85 Agroforestry in acid soils of humid tropics, 275-277,299 alley cropping, 279,288 germplasm selection, 279-281 nutrient content, 281-282 nutrient release form prunings, 282-284 soil, 284-285 weed suppression, 284 yield, 285-288 fruit crop food production, 294-297 managed fallows, 289, 294 nutrient stocks, 291-294 weed suppression, 289-291 research needs, 297-299 Yurimaguas region, 277-278 Air-water interface, ammonia volatilization from flooded soils and, 308,335 Alcohols, green manure in wetland rice and, 172 Aldehydes, green manure in wetland rice and, 172 Alfalfa green manure in wetland rice and, 163 soil organic matter in semiarid regions and, 105 Algae, ammonia volatilization from flooded soils and, 326,328-329 Aliphatic acids, green manure in wetland rice and, 172 Alkaline soils, green manure in wetland rice and, 141, 149. 166, 175-177, 179 Alkalinity, ammonia volatilization from flooded soils and, 304, 310, 321, 326, 328-329 Alleles disease-resistance breeding in chickpea and, 207 genetic resources and, 67

Abiosis, soil organic matter in semiarid regions and, 107 Academy of Agricultural Sciences, genetic resources and, 73 Acetic acid, green manure in wetland rice and, 172 Acetylene reduction activity, nitrogen in rice-legume systems and, 24 Acid soil of humid tropics, agroforestry in, see Agroforestry in acid soils of humid tropics nitrogen in rice-legume systems and, 42, 51 Acidification agroforestry in acid soils and, 285 ammonia volatilization from flooded soils and, 322 Acidity ammonia volatilization from flooded soils and, 328 genetic resources and, 77 green manure in wetland rice and, 166- 168 nitrogen in rice-legume systems and, 22 soil organic matter in semiarid regions and, 103, 115, 130 Adaptation, genetic resources and, 67, 82 Additive effects, resistance to insects and, 242, 244-245,257 Aeration, soil organic matter in semiarid regions and, 96, 105, 1 I5 Aerobic conditions ammonia volatilization from flooded soils and, 322 nitrogen in rice-legume systems and. 5 1 legume nitrogen contribution. 33, 35-36,42 management of nitrogen, 43,47 Aerobic soil, green manure in wetland rice and, 164, 172 Aeschynomene green manure in wetland rice and, 138, 142, 152, 154 357

358

INDEX

resistance to insects and, 227, 229, 253, 262 Alley cropping, agroforestry in acid soils and, 276-288,297,299 Allopolyploids, genetic resources and, 70 AIternaria blight, resistance breeding in chickpea and, 203,211,219 Aluminum agroforestry in acid soils and, 277,279, 285,296 green manure in wetland rice and, 167 nitrogen in rice-legume systems and, 42 toxicity, 276, 279, 299 Amines, green manure in wetland rice and, I72 Ammonia green manure in wetland rice and, 167 nitrogen in rice-legume systems and, 46-47 soil organic matter in semiarid regions and, 103, 115 Ammonia volatilization, green manure in wetland rice and, 150, 163-166 Ammonia volatilization from flooded soils, 303-305,353 measurement, 331-332 models, 332-334 Bouwmeester and Vlek, 334-335 Jayaweera and Mikkelsen, 338-352 Moeller and Vlek, 335-337 sensitivity analysis, 345, 347-348 primary factors, 310 ammonium concentration, 3 10-3 1I pH, 311-315 temperature, 315-316 water depth, 316-318 windspeed, 318-320 secondary factors, 310 ammonium concentration, 320-326 pH, 326-329 temperature, 329-330 water depth, 330 windspeed, 330-331 theory, 305-310 Ammonium ammonia volatilization from flooded soils and, 303-305,308-310,353 effect, 310-312, 315-319 models, 332,335-336,338-339, 342, 345,349-351 secondary factors, 320-326

nitrogen in rice-legume systems and, 4-5, 31, 33-35.48 soil organic matter in semiarid regions and, 103, 130 Ammonium sulfate ammonia volatilization from flooded soils and, 320-323,325,328-329 green manure in wetland rice and, 155, 158, 160, 166, 179 nitrogen in rice-legume systems and, 15,39 Amphorophora, genetics of resistance to insects and, 255 Anaerobic conditions ammonia volatilization from flooded soils and, 322 green manure in wetland rice and, 157, 163, 165, 167 nitrogen in rice-legume systems and, 33, 35,43,47, 5 1 Animal manure, soil organic matter in semiarid regions and, 103-104, 113-1 14 Annona, genetic resources and, 78 Arthropod pests of tomato, genetics of resistance to, 258-259 Antibiosis, genetics of resistance to insects and, 259, 261 barley, 247 cotton, 249 maize, 240, 242 sorghum, 243 vegetables, 256 Aphids disease-resistance breeding in chickpea and, 212 genetics of resistance to, 242-243, 247-248,253-256,258,260-262 Aridity genetic resources and, 77,83 organic matter and, 113 Artificial pollination, genetic resources and, 85 Aschochytu blight, resistance breeding in chickpea and, 192-193.215-218 fungal diseases, 194, 203-210 Ascospores, disease-resistance breeding in chickpea and, 205 Association rate, ammonia volatilization from flooded soils and, 305, 309 Avocado, genetic resources and, 78

359

INDEX Azolla green manure in wetland rice and, 164. 178 nitrogen in rice-legume systems and, 34

B

Backcross disease-resistance breeding in chickpea and, 193 genetic resources and, 69 resistance to insects and, 260, 262 fruits, 254-255 maize, 239 sorghum, 244-246 vegetables, 256-257 wheat, 237 Bacteria disease-resistance breeding in chickpea and, 193 green manure in wetland rice and, 174 Bamboo, genetic resources and, 83 Barley genetic resources and, 68-69.71,73 genetics of resistance to insects and, 235,242-243,246-248 Bean, green manure in wetland rice and, 157 Bean weevil, genetics of resistance to, 260 Biodiversity conservation, genetic resources and, 84-85 Biomass agroforestry in acid soils and, 278, 291 alley cropping, 279-281, 285 managed fallows, 289-294 ammonia volatilization from flooded soils and, 328-329 green manure in wetland rice and, 139-142 nitrogen accumulation, 143-149 saline alkali soils, 175 yield responses, 152, 157 nitrogen in rice-legume systems and, 7. 12,25, 31, 42 soil organic matter in semiarid regions and, 95-96, 102, 120-122, 127 Biotechnology, genetic resources and, 71 Biotic activity, ammonia volatilization from flooded soils and, 304, 310, 320. 326-321. 339

Biotypes, genetics of resistance to insects and, 225,261, 265 barley, 247 fruits, 252,254-255 rice, 227-229,231 sorghum, 243-244 wheat, 231-237 Black currant curling midge, genetics of resistance to, 255 Black currant gall mite, genetics of resistance to, 255 Black root rot, resistance breeding in chickpea and, 201-202 Boll weevil, genetics of resistance to, 248-249 Borryris gray mold, resistance breeding in chickpea and, 193,203, 210-211, 215, 217,219 Bradyrhizobium, nitrogen in rice-legume systems and, 23 Breeding, disease-resistance in chickpea and, see Disease-resistance breeding in chickpea Broadcast application, ammonia volatilization from flooded soils and, 323-325, 329 Bromegrass, soil organic matter in semiarid regions and, 105 Brown planthopper, genetics of resistance to, 225-228.230 Buffering capacity, ammonia volatilization from flooded soils and, 304, 310,326, 329 Bulk density green manure in wetland rice and, 173, 180

soil organic matter in semiarid regions and, 98, 119, 123

c Cacao, genetic resources and, 79 Cajanus, agroforestry in acid soils and, 279,283,289 Calcareous soil ammonia volatilization and, 328 green manure in wetland rice and, 146, 167-168, 170-171, 176 semiarid regions and, 103 Calcium agroforestry in acid soils and

360

INDEX

alley cropping, 281, 283-284 fruit crop food production, 296 managed fallows, 293-294 research needs, 298-299 green manure in wetland rice and, 167-168, 171, 176 soil organic matter in semiarid regions and, 104 Calcium carbonate ammonia volatilization from flooded soils and, 304,310 green manure in wetland rice and, 170, 177 Culliandru, agroforestry in acid soils and, 279 Canopy agroforestry in acid soils and, 289, 295 ammonia volatilization from flooded soils and, 329-331 disease-resistance breeding in chickpea and, 203,212 Carbon green manure in wetland rice and, 163, 166, 174. 177-178 nitrogen in rice-legume systems and, 16,47 soil organic matter in semiarid regions and, 94-95.98, 130 cultivation, 120- 121 erosion, 122-123 fertilizer, 102-105 management, 119 microbial biomass, 115-1 19 organic residue, 105-1 14 tillage, 99-102 turnover, 124-125, 127-129 Carbon cycle, soil organic matter in semiarid regions and, 123-124 Carbon dioxide ammonia volatilization from flooded soils and, 308,326-328,335,337.344 green manure in wetland rice and, 168, 176 nitrogen in rice-legume systems and, 34, 46-47 soil organic matter in semiarid regions and, 94, 107, 124 Carbonhitrogen ratio agroforestry in acid soils and, 282-283 green manure in wetland rice and, 162, 164

nitrogen in rice-legume systems and, 16, 33-34,37,40 Cassia

agroforestry in acid soils and, 279, 281, 289 green manure in wetland rice and, 138, 142 Cation-exchange capacity agroforestry in acid soils and, 277 ammonia volatilization from flooded soils and, 304,310,326,329 Cellulose, soil organic matter in semiarid regions and, 106 Centromeres, resistance to insects and, 235,241,249 Centrosema. agroforestry in acid soils and, 289-291 Cereal leaf beetle, genetics of resistance to, 237-238,247 Chelation green manure in wetland rice and, 167-169 soil organic matter in semiarid regions and. 94 Chickpea, disease-resistance breeding in. See Disease-resistance breeding in chickpea Chinch bug, genetics of resistance to, 246 Chlorosis, disease-resistance breeding in chickpea and, 202 Chromosomes genetic resources and, 69-70 resistance to insects and, 227, 235-242, 247, 249 Cicer, disease-resistance breeding in chickpea and, 210,214, 216-217,219 CIP (International Potato Center), genetic resources and, 64,69, 71 Climate agroforestry in acid soils and, 277 ammonia volatilization from flooded soils and, 315 genetic resources and, 77 green manure in wetland rice and, 141, 143, 167, 178-181 nitrogen, 161- I62 nitrogen in rice-legume systems and, 3,48 soil organic matter in semiarid regions and, 95,99, 112 cultivation, 120

36 1

INDEX microbial biomass, 115-1 17 turnover, 127 Clones, genetics of resistance to insects and, 261, 263 Clover green manure in wetland rice and, 138, 145. 154, 172, 179 nitrogen in rice-legume systems and, 10. 35 soil organic matter in semiarid regions and, 104 Clusterbean, green manure in wetland rice and, 138, 143, 149, 175 Collar rot, disease-resistance breeding in chickpea and, 201-203 Colonization, genetic resources and, 81 Competition, agroforestry in acid soils and, 285,288,298-299 Conservation genetic resources and. 62. 64. 88 research, 77, 79 sustainability, 83-85 of soil nitrogen, in rice-legume systems, 13-15 soil organic matter in semiarid regions and, 97 Consultative Group on International Agriculture Research, genetic resources and (CGIAR). 63, 81-82 Cooperative networking, genetic resources and, 86 Coppicing, agroforestry in acid soils and, 279, 295,299 Corn agroforestry in acid soils and, 277 soil organic matter in semiarid regions and, 108, 110, 112 Corn earworm, genetics of resistance to, 24 I Corn leaf aphid, genetics of resistance to, 242-243,247-248 Cotton, genetics of resistance to insects and, 248-252 Cowpea agroforestry in acid soils and, 296, 299 genetics of resistance to insects and, 263 green manure in wetland rice and, 138. 180 nitrogen accumulation, 143. 149 transformations, 164, 166 yield responses, 156-157

nitrogen in rice-legume systems and, 8-9, 12-14 management of nitrogen, 42,45-49 nitrogen accumulation, 16, 23, 25-26 nitrogen contribution, 27, 33-37 Cowpea aphid, genetics of resistance to, 260-26 1 Cowpea seed beetle, genetics of resistance to, 260 Crop rotation, see Rotation Crop selection, soil organic matter in semiarid regions and, 96 Crossover, resistance to insects and, 239, 249,255 Crotalaria

green manure in wetland rice and, 138, 152 nitrogen in rice-legume systems and, 10, 33-34, 37,42 Culture, green manure in wetland rice and, 143 Cycling, soil organic matter in semiarid regions and, 115 Cyst nematodes, disease-resistance breeding in chickpea and, 214, 2 16-2 I7 D

Decay ammonia volatilization from flooded soils and, 310 disease-resistance breeding in chickpea and. 201 green manure in wetland rice and, 165 soil organic matter in semiarid regions and, 127 Decomposition, nitrogen in rice-legume systems and legume nitrogen contribution, 32-33, 35,40 management of nitrogen, 42-43,46-47 Dehydration, soil organic matter in semiarid regions and, 119 Delayed tillage, soil organic matter in semiarid regions and, 100 Demographics, genetic resources and, 85 Denitrification ammonia volatilization from flooded soils and, 318,331-332 green manure in wetland rice and,

362

INDEX

150-151, 163-164, 166 nitrogen in rice-legume systems and legume nitrogen contribution, 33, 35-36 management of nitrogen, 43.47 rice soils, 4-5 soil nitrogen, 13-16 soil organic matter in semiarid regions and, 103 Desmodium,agroforestry in acid soils and, 289-291, 299 Diffusion, ammonia volatilization from flooded soils and, 304 models, 332-333,335-337,339-340 primary factors, 314 theory, 307-308 DIMBOA, resistance to insects and, 240, 242 Disease, nitrogen in rice-legume systems and, 2,41 Disease resistance, genetic resources and, 68,70 Disease-resistance breeding in chickpea, 191-195,218-219 Cicer, 216-217 fungal diseases foliar, 194, 203-212 soil-borne, 194-203 genetic variability, 192-193 multiple disease resistance, 215-216 nematode diseases, 213-215 resistant cultivars, 217-218 techniques, 193 viral diseases, 212-213 Disking, soil organic matter in semiarid regions and, 99 Dissociation rate, ammonia volatilization from flooded soils and, 305, 309,313, 315,339 Drainage green manure in wetland rice and, 180 soil organic matter in semiarid regions and, 96 Drought, disease-resistance breeding in chickpea and, 202 Drought stress, soil organic matter in semiarid regions and, 97, 102 Drought tolerance green manure in wetland rice and, 138, 179

nitrogen in rice-legume systems and, 16 Dry root rot, disease-resistance breeding in chickpea and, 201 E

green manure in wetland rice and, 170-171, 176, 180 Ecology genetic resources and, 62,83 research, 67-68,76-77, 81 green manure in wetland rice and, 136, 138, 146 Economics agroforestry in acid soils and, 294-295 nitrogen in rice-legume systems and, 12 Ecosystem agroforestry in acid soils and, 299 ammonia volatilization from flooded soils and, 316,325,328 genetic resources and, 62,72-73,82,84 soil organic matter in semiarid regions and, 96, 121, 124-125, 129 Ecotype, genetic resources and, 82-83 Edaphic conditions, green manure in wetland rice and, 143, 164 Eddy correlation, ammonia volatilization from flooded soils and, 304,306,331 Electrical conductivity (EC), green manure in wetland rice and, 171, 176 Embryo culture, genetic resources and, 70 Embryo rescue, genetic resources and, 72 Energy green manure in wetland rice and, 174 soil organic matter in semiarid regions and, 124 Energy use, soil organic matter in semiarid regions and, 100 Environment ammonia volatilization from flooded soils and, 310,318,331 disease-resistance breeding in chickpea and, 199,214 genetic resources and, 62 research, 67,69,72, 75-79, 81 sustainability, 82, 85 genetics of resistance to insects and, 25 1-252 green manure in wetland rice and, 163 nitrogen in rice-legume systems and, 2 , 4 Eh,

363

INDEX legume nitrogen, 22, 32, 35 legumes, 8, 11, 16 management of nitrogen, 42,45 soil organic matter in semiarid regions and, 94, 1 15, 117, 124, 127, 130 Environmental protection, genetic resources and, 76 Enzymes, ammonia volatilization from flooded soils and, 320,326 Epistasis, disease-resistance breeding in chickpea and, 197,21 I Equilibrium ammonia volatilization from flooded soils and models, 334, 336, 338-340, 342 primary factors, 311-312, 315 theory, 305, 307-309 soil organic matter in semiarid regions and, 95,98 cultivation, 120 microbial biomass, 115, 117 organic residue, 105, 110 Erosion agroforestry in acid soils and, 276, 288, 299 genetic resources and, 75,79 green manure in wetland rice and, 136 nitrogen in rice-legume systems and, 3 soil organic matter in semiarid regions and, 97, 127, 129-130 cultivation, 121 impact, 121-123 management, 119 microbial biomass, 115 tillage, 99-100 Erythrina, agroforestry in acid soils and, 279. 281,283, 285, 289 Ethylene, green manure in wetland rice and, 172 European corn borer, genetics of resistance to, 239-240 Evaporation ammonia volatilization from flooded soils and, 321, 330, 337 soil organic matter in semiarid regions and, 116 Evapotranspiration, agroforestry in acid soils and, 277 Evolution, genetic resources and, 68, 81 Exchangeable sodium percentage, green

manure in wetland rice and, 175-176 Exotic genes, 69 F

Fall armyworm, genetics of resistance to, 242-243 Fallow agroforestry in acid soils and, 277-278, 288,299 management, 289-294 research needs, 297-298 green manure in wetland rice and, 145, 149, 156, 158-159, 180 nitrogen in rice-legume systems and legume nitrogen, 23, 35-37, 41 rice soils, 4-7 soil nitrogen, 13, 15 soil organic matter in semiarid regions and, 120, 129-130 fertilizer, 103 microbial biomass, 115, 118 organic residue, 108, 110-1 11 tillage, 99-100 Fatty acids, green manure in wetland rice and, 172 Ferrous sulphate, green manure in wetland rice and, 169 Fertilizer agroforestry in acid soils and, 285-286, 288,296-297 ammonia volatilization from flooded soils and, 303-305 primary factors, 3 10-3 I 1 secondary factors, 320-321, 323-326, 329 use efficiency, 304, 353 genetic resources and, 62 green manure in wetland rice and, 136, 178-180 nitrogen, 158-162 nitrogen accumulation, 146-148 nutrient availability, 167 yield responses, 155-156 nitrogen in rice-legume systems and. 3,51 legume nitrogen accumulation, 22, 26 legume nitrogen contribution, 27, 30. 36,41 legumes, 11-12, 15-16

364

INDEX

management of nitrogen, 44-45,47-50 rice soils, 4, 8 use efficiency, 2 soil organic matter in semiarid regions and, 102-105, 125, 129, 130 microbial biomass, 116-117, 119 Fetch, ammonia volatilization from flooded soils and, 334-335 Fick’s law, ammonia volatilization from flooded soils and, 340-341 Film model, ammonia volatilization from flooded soils and, 332-333 Fitness, genetic resources and, 85 Flamingo,green manure in wetland rice and, 142 Flooded soils, ammonia volatilization from, see Ammonia volatilization from flooded soils Flooding, green manure in wetland rice and, 142, 149-151, 157, 164, 171 nutrient availability, 167-169 Flowering, genetic resources and, 83 Fodder, genetic resources and, 77,79 Food and Agricultural Research Centers (FAO), genetic resources and, 63-65, 75, 79,86 Food legumes, nitrogen in rice-legume systems and, 8-9, 12,22-24,27 Foot rot, resistance breeding in chickpea and, 201,203 Forage agroforestry in acid soils and, 294 genetic resources and, 61,64,73,79 soil organic matter in semiarid regions and, 97 Forage legumes, nitrogen in rice-legume systems and, 22-24 Fruit agroforestry in acid soils and, 278, 294-297,299

genetics of resistance to insects and, 252-256

Fulvic acid, soil organic matter in semiarid regions and, 108 Fungal diseases, resistance breeding in chickpea and, 193 foliar, 194,203-212 soil-borne, 194-203 Fungicide, disease-resistance breeding in chickpea and, 192,218

Fusarium wilt, disease-resistance breeding in chickpea and, 192, 216-218 fungal diseases, 194-200, 203 nematode diseases, 2 15 G

Gall midge, genetics of resistance to, 230-23 1

Gas exchange, ammonia volatilization from flooded soils and, 308,318,335, 340-341

Gas-liquid interface, ammonia volatilization from flooded soils and, 332-333

Gene banks, 64,156, 72,75,79,87 Gene pools, 6 I , 88 development of global activities, 63, 66 research, 67-69,71-72,75 Gene transfer, disease-resistance breeding in chickpea and, 214,217, 219 General combining ability, resistance to insects and, 241-243 Genetic diversity, 69, 72,75, 79,88 Genetic engineering, insect tolerance and, 263

Genetic resources, 61-62, 88 development of global activities, 62-64 availability of material, 64 framework, 64-65 gene pools, 66 security of material, 65-66 germplasrn, 86 applied research, 87-88 cooperative networking, 86 management of collections, 86-87 safety of collections, 87 research agroforestry, 75-81 increasing production, 66-68 stabilizing production, 74-75 wild species, 68-74 sustainability, 81-85 Genetic variability, disease-resistance breeding in chickpea and, 192-193 Genetics disease-resistance breeding in chickpea and, 216-219 fungal diseases, 196-198.206-210 nematode diseases, 214

INDEX of resistance to insects, 224-225, 263-265 barley, 246-248 cotton, 248-252 forages and legumes, 259-262 fruits, 252-256 maize, 239-243 molecular markers, 262 rice, 226-231 sorghum, 243-246 tolerance, 263 vegetables, 256-259 wheat, 231-238 Genomes, genetic resources and, 70.88 Genotype disease-resistance breeding in chickpea and, 196-197, 199,207,212,217 genetic resources and, 67,75,77-79, 82.85 green manure in wetland rice and, 146 resistance to insects and, 262 cotton, 248-250 maize, 240 sorghum, 246 vegetables, 256 wheat, 231-232 Germplasm agroforestry in acid soils and, 279-281, 295, 298-299 disease-resistance breeding in chickpea and, 192, 216, 218 fungal diseases, 198-199, 201, 206 viral diseases, 212 genetic resources and, 62, 83 development of global activities, 63-66 research, 66-67, 69,72-76,78-81 genetics of resistance to insects and, 224-225,255-256,259,261 cotton, 249-25 1 maize, 240,242 sorghum, 246 wheat, 234-235.237-238 Gliricidia agroforestry in acid soils and, 279-281, 299 green manure in wetland rice and, 142, 155, 158, 164, 169 nitrogen in rice-legume systems and, I I 50 Gossypium, see Cotton

365

Gradient diffusion, ammonia volatilization from flooded soils and, 304, 331 Grasslands, soil organic matter in semiarid regions and, 95 cultivation, 97-98, 120 fertilizer, 102-104 management, 119 microbial biomass, 115 turnover, 124, 126 Grazing agroforestry in acid soils and, 294 soil organic matter in semiarid regions and, 127 Green leaf manure nitrogen in rice-legume systems and, 11, 37.50 in wetland rice, 137, 142, 154-155, 174, 179 Green leafhopper, genetics of resistance to, 229-230 Green manure agroforestry in acid soils and, 282 soil organic matter in semiarid regions and, 103-104, 114, 130 Green manure in wetland rice, 136-137, 179- 181 green leaf manure, 142 incorporation, 149-151 nitrogen fertilizer equivalence, 158-160 integrated use, 160-162 transfer, 160- 161 nitrogen accumulation, 143- 146 fertilizer application, 146-148 inoculation, 148-149 irrigation, 149 nutrient availability, 166-170 residual effects, 177-179 root-nodulating crops, 138-141 saline alkali soils, 175-177 soil properties biological, 174- I75 chemical, 170-172 physical, 172- 174 stem-nodulating crops, 141-142 transformations, 162 N IOSS, 165-166 N mineralization, 162- 165 yield responses, 151-156 application rate. 157-158

INDEX

366

dual-purpose manures, 156-157 Green manure legumes, nitrogen in rice-legume systems and, 2-3.8, 10-12,50 management of nitrogen, 42.44-48,50 nitrogen accumulation, 17-22,24-25 nitrogen contribution, 27-29,31-37, 39-42 soil nitrogen, 13-14, 16 Greenbug, genetics of resistance to, 235-237,243-244,247 Groundnut genetic resources and, 68,71 nitrogen in rice-legume systems and, 8, 13,23, 34 Guanyl urea sulfate, ammonia volatilization from flooded soils and, 322,325 Guava, genetic resources and, 78 Gypsum, green manure in wetland rice and, 175-177

H Habitat, genetic resources and, 62 Harvest agroforestry in acid soils and, 278 nitrogen in rice-legume systems and, 25 soil organic matter in semiarid regions and, 100 Harvest index, soil organic matter in semiarid regions and, 120 Hedgegrow intercropping, agroforestry in acid soils and, 279-281, 285,288, 298-299 Hemicellulose green manure in wetland rice and, 165 soil organic matter in semiarid regions and, 106 Henry’s law, ammonia volatilization from flooded soils and, 307-309,336, 341-343 Heritability, resistance to insects and, 242, 256-257,261 Hessian fly, genetics of resistance to, 225, 231-235,246 Heterodera ciceri, disease-resistance breeding in chickpea and, 214 Heterogeneity, genetic resources and, 74-75 Heterosis, genetic resources and, 68

Heterotrophy, nitrogen in rice-legume systems and, 41 Heterozygosity genetic resources and, 70 genetics of resistance to insects and, 252-253 Hirschmanniella, nitrogen in rice-legume systems and, 42 Homozygosity disease-resistance breeding in chickpea and, 197 genetics of resistance to insects and, 226,255 Hordeum, genetic resources and, 71 Hormones, green manure in wetland rice and, 172 Host-plant resistance in chickpea, 192, 194 Humid tropics, agroforestry in, see Agroforestry in acid soils of humid tropics H u midity ammonia volatilization from flooded soils and, 330 disease-resistance breeding in chickpea and, 203-204,207,210,212 green manure in wetland rice and, 138, 178 nitrogen in rice-legume systems and, 36 soil organic matter in semiarid regions and, 97, 102, 110, 112-113 Humification, green manure in wetland rice and, 177-178 Humus, soil organic matter in semiarid regions and, 105, 108 Hybridization disease-resistance breeding in chickpea and, 193, 198-100,208,215, 219 genetic resources and, 67-68,70, 85 resistance to insects and, 243, 246,251 Hydraulic conductivity, green manure in wetland rice and, 173-174 Hydrodynamic models, ammonia volatilization from flooded soils and, 332-333 Hydrogen, ammonia volatilization from flooded soils and, 309,328,334-338

I IARCs (international agricultural research centers), genetic resources and, 63-64, 71,73

367

INDEX IBPGR (International Board for Plant Genetic Resources), genetic resources and, 64-65, 86 research, 68-69,72,74,78,80 ICARDA (International Center for Agricultural Research in the Dry Areas) disease-resistance breeding in chickpea and, 192-194,215-216 fungal diseases, 206,208,210 viral diseases, 214 genetic resources and, 64, 71 ICRAF (International Council for Research in Agroforestry), genetic resources and, 76, 78 ICRISAT (International Crops Research Institute for the Semi-And Tropics) disease-resistance breeding in chickpea and, 192-194.215-216 fungal diseases, 197, 199, 208, 21 1 viral diseases, 213 genetics of resistance to insects and, 245 Inbreeding depression, genetic resources and, 85 Indigo, green manure in wetland rice and, 138, 155 Indigofera green manure in wetland rice and, 141-142 nitrogen in rice-legume systems and, 1 1 , 16 Znga, agroforestry in acid soils and, 289, 299 alley cropping, 279, 281, 284-288 Inhibition ammonia volatilization from flooded soils and, 325-327 disease-resistance breeding in chickpea and, 196 genetics of resistance to insects and, 226, 237,248,260 green manure in wetland rice and, 141,

nitrogen in rice-legume systems and, 13, 22,24-25,41 Insects, genetics of resistance to, see Genetics of resistance to insects Intercropping, genetic resources and, 77-78 International Rice Research Institute (IRRI) genetic resources and, 64,69,71,83 green manure in wetland rice and, 136, 157, 181 nitrogen in rice-legume systems and, 2-3,6, 14-15, 22 Iron green manure in wetland rice and, 167-171, 181 nitrogen in rice-legume systems and, 42 toxicity, 156 IRRI, see International Rice Research Institute Irrigation ammonia volatilization from flooded soils and, 321,328 disease-resistance breeding in chickpea and, 206,211 genetic resources and, 74 green manure in wetland rice and, 142, 149 nitrogen in rice-legume systems and, 2, 4-5,9, 1 1 legume nitrogen, 23, 32,35,39,41 management of nitrogen, 42,44 Isotopes green manure in wetland rice and, 145 soil organic matter in semiarid regions and, 98, 103, 130 Isozymes genetic resources and, 70 genetics of resistance to insects and, 262 IUCN (International Union for the Conservation of Nature), genetic resources and, 72,84

160

soil organic matter in semiarid regions and, 120 Inoculation disease-resistance breeding in chickpea and, 218-219 foliar fungal diseases, 205-206, 21 1 soil-borne fungal diseases, 196, 202 green manure in wetland rice and, 146, 148-149

J

Jassids, genetics of resistance to, 250-251 K

Ketones, green manure in wetland rice and, 172

368

INDEX

Kinetics ammonia volatilization from flooded soils and, 304,314.321 models, 338. 349 theory, 305,308 green manure in wetland rice and, 163-164, 168

L Labeled tracer techniques, ammonia volatilization from flooded soils and, 331 Labor, agroforestry in acid soils and, 277-278, 294 Land races, genetic resources and, 63-64, 67-68,75,83 Lateritic soils, green manure in wetland rice and, 168, 170-171 Leaching agroforestry in acid soils and, 293-294 ammonia volatilization from flooded soils and, 331 green manure in wetland rice and, 137, 150, 176 nitrogen in rice-legume systems and, 4-5.36 soil organic matter in semiarid regions and, 103 Legumes agroforestry in acid soils and, 278,296, 298-299 alley cropping, 279-281 283 managed fallows, 289,291-292.294 disease-resistance breeding in chickpea and, 192, 194,219 green manure in wetland rice and, see Green manure in wetland rice nitrogen dynamics in rice-legume cropping, see Nitrogen dynamics in rice-legume cropping soil organic matter in semiarid regions and, 103-104, 114 Lettuce leaf aphid, genetics of resistance to, 258 Lettuce root aphid, genetics of resistance to, 258 Leucaena agroforestry in acid soils and, 279-280, 282 genetic resources and, 77

green manure in wetland rice and, 142, 144, 155 nitrogen in rice-legume systems and, 1 1 Lignin agroforestry in acid soils and, 299 green manure in wetland rice and, 164, 177 nitrogen in rice-legume systems and, 33-34 soil organic matter in semiarid regions and, 105-106, 108, 114, 126, 130 Lime agroforestry in acid soils and, 279, 285, 296 soil organic matter in semiarid regions and, 104 Linkage genetic resources and, 67 resistance to insects and, 226, 232, 234-235,250,257 Lipid, green manure in wetland rice and, 164 Liquid-gas interface, ammonia volatilization from flooded soils and, 305 Lodging genetics of resistance to insects and, 259 green manure in wetland rice and, 157 Lupin, green manure in wetland rice and, 145 M

Magnesium agroforestry in acid soils and, 296, 298-299 alley cropping, 281-284 managed fallows, 293-294 green manure in wetland rice and, 168, 170, 176 soil organic matter in semiarid regions and, 104 Maize agroforestry in acid soils and, 282 ammonia volatilization from flooded soils and, 319 genetic resources and, 69 genetics of resistance to insects and, 239-243 green manure in wetland rice and, 159 nitrogen in rice-legume systems and, 36-37

369

INDEX Manganese green manure in wetland rice and, 168-171, 181 nitrogen in rice-legume systems and, 42 toxicity, 156 Manure, see also Animal manure; Green manure soil organic matter in semiarid regions and, 108, I 1 1 Mapping of races, disease-resistance breeding in chickpea and. 210 Maps, genetics of resistance to insects and, 226,232, 235,255 Mass balance, ammonia volatilization from flooded soils and, 304, 309, 331 Mass transfer, ammonia volatilization from flooded soils and, 304,316 measurement, 332-334 models, 340, 342 theory, 305-307 Meloidogyne, disease-resistance breeding in chickpea and, 213 Melon aphid, genetics of resistance to, 256 Methane, nitrogen in rice-legume systems and, 35.51 Mexican bean beetle, genetics of resistance to, 259-260 Microbial activity ammonia volatilization from flooded soils and, 322 green manure in wetland rice and, 174 nitrogen in rice-legume systems and, 41 soil organic matter in semiarid regions and, 103, 108, 112, 116, 120, 127 Microbial biomass agroforestry in acid soils and, 292 green manure in wetland rice and, 174 soil organic matter in semiarid regions and, 98, 107, 114-119, 130 turnover, 125-126 Micrometeorological techniques, ammonia volatilization from flooded soils and, 33 1 Milk vetch green manure in wetland rice and, 136, 138, 172, 178-179 incorporation, 150-15 1 nitrogen, 143-144, 146, 148, 158 transformations, 164-165 yield responses, 152, 157 nitrogen in rice-legume systems and, 10, 25, 39.44

Millet, genetic resources and. 68-69 Mineralization agroforestry in acid soils and, 279, 282-283,292 ammonia volatilization from flooded soils and. 322,338 green manure in wetland rice and, 160, 178, 181 nutrient availability, 166-167 transformations, 162- 164 nitrogen in rice-legume systems and, 4, 7 , 15. 51 legume nitrogen contribution, 32-37, 39 soil organic matter in semiarid regions and, 103-104, 117-118, 122, 128 Moisture disease-resistance breeding in chickpea and, 206 green manure in wetland rice and, 136 soil organic matter in semiarid regions and, 105. 117, 126-327 Moisture stress. disease-resistance breeding in chickpea and, 201 Molecular markers, genetics of resistance to insects and, 262 Mucuna, agroforestry in acid soils and, 296 Mulch agroforestry in acid soils and, 284-286 genetic resources and, 77 soil organic matter in semiarid regions and, 110, 130 Mung bean green manure in wetland rice and, 138, 156-157, 169, 180 nitrogen in rice-legume systems and, 5 , 8-9, 12-16 nitrogen contribution, 27, 36-37 Musa. genetic resources and. 70 Mutation disease-resistance breeding in chickpea and, 192-193, 210, 215 resistance to insects and, 248, 251 Mycorrhizal infection, agroforestry in acid soils and, 297 N

Narrow-sense heritability, resistance to insects and, 251 Natural selection, genetic resources and, 85

370

INDEX

Ndfa, nitrogen in rice-legume systems and, 23-24 Nematodes disease-resistance breeding in chickpea and, 192-193, 199,213-217,219 green manure in wetland rice and, 175 nitrogen in rice-legume systems and, 42 Neptunia, nitrogen in rice-legume systems and, 24 Nitrate nitrogen in rice-legume systems and legume nitrogen, 23, 33, 35-36 management of nitrogen, 42,44,47 rice soils, 4-7 soil nitrogen, 13-16 soil organic matter in semiarid regions and, 103 Nitrification ammonia volatilization from flooded soils and, 318,331-332 green manure in wetland rice and, 150-151 nitrogen in rice-legume systems and, 51 Nitrogen agroforestry in acid soils and, 277,299 alley cropping, 281-284, 286 fruit crop food production, 296-297 managed fallows, 292 ammonia volatilization from flooded soils and, 303-305 effect, 310,318,320,322, 324-328 green manure in wetland rice and, 136, 144, 177-181 accumulation, 139-141, 143-149, 180 fertilizer equivalence, 158-160 incorporation, 149-150 integrated use, 160-162 IOSS, 163-164 mineralization, 162- 165 transfer, 160-161 yield responses, 151-152, 154-157 soil organic matter in semiarid regions and, 130 cultivation, 121 erosion, 122 fertilizer, 104- 105 management, 119 microbial biomass, 115, 117-1 19 organic residue, 105-1 I I , 113-1 14 tillage, 100-102 turnover, 127-129

Nitrogen dynamics in rice-legume cropping, 2-3, 50-52 legume nitrogen accumulation, 16-22 N removal, 25-27 symbiotic fixation, 22-25 legume nitrogen contribution, 27-32 belowground legume N, 36-39 losses of legume N, 39-40 mineralization, 32-36 residual N effects, 40-41 rice yield, 41-42 legume nitrogen management, 42-44 loss of fertilizer N, 44-47 use of fertilizer N, 47-50 legumes in rice cropping, 8 dual-purpose legumes, 11-12 food legumes, 8-9 green manure legumes, 10-1 I soil nitrogen, 13-16 rice soils, 3-8 Nitrogen fertilizer source, 50 timing, 48-50 Nitrogen fertilizer equivalence, green manure in wetland rice and, 158-160 Nitrogen fixation genetic resources and, 78-79 green manure in wetland rice and, 136, 141, 174, 180-181 biomass, 144-146, 148 rice-legume systems and, 41, 5 1 legume nitrogen accumulation, 22-26 legumes, 9-10, 13-14 soil organic matter in semiarid regions and, 114 Nitrogen harvest index, nitrogen in rice-legume systems and, 25,27 Nitrogen use efficiency, green manure in wetland rice and, 180-181 Nodulation green manure in wetland rice and, 138-142, 146, 154, 175 nitrogen in rice-legume systems and, 24, 37, 44 0

Oats genetic resources and, 68 genetics of resistance to insects and, 235 Oryza saliva L., see Rice

INDEX Oxidation green manure in wetland rice and, 151 nitrogen in rice-legume systems and, 33,35 soil organic matter in semiarid regions and, 96, 99-100, 120, 124 Oxygen, nitrogen in rice-legume systems and. 4

P

Palm agroforestry in acid soils and, 283, 295-298 genetic resources and, 77, 84 Pathogeneity, green manure in wetland rice and, 172, 175 Pea disease-resistance breeding in chickpea and, 214 green manure in wetland rice and, 138, 145 soil organic matter in semiarid regions and, 108, 118 Pea aphid of alfalfa, genetics of resistance to, 261-262 Peach palm agroforestry in acid soils and, 295-296, 298 genetic resources and, 80, 84 Peanut, genetic resources and, 69 Pedigree disease-resistance breeding in chickpea and, 193 resistance to insects and, 242 Penetration theory, ammonia volatilization from flooded soils and, 333-334 Percolation, nitrogen in rice-legume systems and, 4 , 4 2 , 48 Pesticides genetic resources and, 62 soil organic matter in semiarid regions and, 94, 130 PH agroforestry in acid soils and, 277, 285 ammonia volatilization from flooded soils and, 304,353 effects, 310-315,318-320,326-329 models, 334-335, 337, 339, 342, 348-35 I

37 1

theory, 305,308-310 green manure in wetland rice and, 146, 170, 176, 180 nutrient availability, 167-168, 170 transformations, 165-166 soil organic matter in semiarid regions and, 105 pH constant model, ammonia volatilization from flooded soils and, 335,337 pH gradient model, ammonia volatilization from flooded soils and, 335,337 Phaseolus, green manure in wetland rice and, 142, 146 Phenolic acids, green manure in wetland rice and, 172 Phenolics, soil organic matter in semiarid regions and, 108 Phenyl phosphodiamide, ammonia volatilization from flooded soils and, 325-326 Phosphate ammonia volatilization from flooded soils and, 328 green manure in wetland rice and, 166-167, 174 Phosphate rock-coated urea, ammonia volatilization from flooded soils and, 322 Phosphorus agroforestry in acid soils and, 296, 298-299 alley cropping, 280, 282-283 managed fallows, 292 ammonia volatilization from flooded soils and, 329 deficiency, 104 green manure in wetland rice and, 172, 177, 180-181 nitrogen accumulation, 146- 147 nutrient availability, 166-167 nitrogen in rice-legume systems and, I I , 22.51 soil organic matter in semiarid regions and, 104, 110, 128-129 Photosynthesis ammonia volatilization from flooded soils and, 322, 326-327.329.331 green manure in wetland rice and, 171 nitrogen in rice-legume systems and. 45 soil organic matter in semiarid regions and, 124

372

INDEX

Phytophthora root rot, resistance breeding in chickpea and, 201,215 Pigeonpea green manure in wetland rice and, 138 nitrogen in rice-legume systems and, 16, 23,34 Pink bollworm, genetics of resistance to, 251-252 Plant genetic resources, see Genetic resources Ploidy, genetic resources and, 70 Plowing, soil organic matter in semiarid regions and, 99-100, 117, 130 Pollen storage, genetic resources and, 85 Pollution, soil organic matter in semiarid regions and, 103 Polycross, genetics of resistance to insects and, 261 Polygenic control, resistance to insects and, 231,244-245 Polygenic resistance, disease-resistance breeding in chickpea and, 210 Polyphenols, agroforestry in acid soils and, 283,299 Polysaccharides, soil organic matter in semiarid regions and, 106-107, 119 Population, genetic resources and, 84-85 Population pressure genetic resources and, 76 genetics of resistance to insects and, 248 Potassium agroforestry in acid soils and, 281-284, 292-294,2%-297 green manure in wetland rice and, 146, 168, 171-172, 177, 181 nitrogen in rice-legume systems and, 42 soil organic matter in semiarid regions and, 104 Potato, genetic resources and, 68-71 Precipitation agroforestry in acid soils and, 277 soil organic matter in semiarid regions and, 97, 1 1 1-1 12, 116, 127 Protein disease-resistance breeding in chickpea and, 192 soil organic matter in semiarid regions and, 105 Protein C, soil organic matter in semiarid regions and, 107

Proton extrusion, agroforestry in acid soils and, 293 Protoplasts, genetic resources and, 70 Provenance, agroforestry in acid soils and, 28 1 Pruning, agroforestry in acid soils and, 279,28 1-285,288,298 Pubescence, genetics of resistance to insects and, 237-238,248-250 Puddling, nitrogen in rice-legume systems and, 4, 34,40, 50 Pueraria, agroforestry in acid soils and, 289-291 Pumpkin fruitfly, genetics of resistance to, 257-258 Purple vetch, green manure in wetland rice and, 179 Pyramiding multiple gene resistance, chickpea and, 209 Pythium root rot, resistance breeding in chickpea and, 201-202 Q Quantitative resistance, insects and, 242, 244,256-257,259 Quantitative trait loci, resistance to insects and, 262 R

Radiocarbon, soil organic matter in semiarid regions and, 107-108 Rainfall agroforestry in acid soils and, 277, 294 ammonia volatilization from flooded soils and, 330 disease-resistance breeding in chickpea and, 203,210 nitrogen in rice-legume systems and, 32.36 soil organic matter in semiarid regions and, 95,97,99-100, 103, 108 Reciprocal cross, resistance to insects and, 24 1 Reclamation of soil, green manure in wetland rice and, 176-177 Recombination genetic resources and, 70 resistance to insects and, 227, 234-235

373

INDEX Recurrent selection, resistance to insects and, 261 Recycling, agroforestry in acid soils and, 288, 294 Red pumpkin beetle, genetics of resistance to, 256 Red scale pest of citrus, genetics of resistance to, 256 Redox status, ammonia volatilization from flooded soils and, 304,310 Release of cultivars, disease-resistance breeding in chickpea and, 210 Residue agroforestry in acid soils and, 285, 288 green manure in wetland rice and, 156-157 nitrogen in rice-legume systems and, 12, 27, 32, 35-36,48 soil organic matter in semiarid regions and, 98-100, 129 cultivation, 120-121 effects, 105-1 14 Resistance, disease, see Disease resistance Resistance to insects, genetics of, see Genetics of resistance to insects Respiration, ammonia volatilization from flooded soils and, 321, 326,328 Restriction fragment length polymorphism, genetics of resistance to insects and, 262 Rhizobium green manure in wetland rice and, 146 nitrogen in rice-legume systems and, 24 Rhizosphere green manure in wetland rice and, 174 nitrogen in rice-legume systems and. 41 soil organic matter in semiarid regions and, 120 Rice agroforestry in acid soils and, 277, 285-288,296,299 ammonia volatilization from flooded soils and, 353 factors, 310, 320-322, 325, 328, 330-331 genetic resources and, 67-69,71,73,83 genetics of resistance to insects and, 226-23 1, 263-265 wetland, green manure in, see Green manure in wetland rice

Rice-legume cropping, nitrogen dynamics in, see Nitrogen dynamics in rice-legume cropping Root-knot nematodes, resistance breeding in chickpea and, 213,215,219 Root-lesion nematodes, resistance breeding in chickpea and, 214 Root-nodulating crops, green manure in wetland rice and, 138-141 Root rot, resistance breeding in chickpea and, 194, 196,201-203 Rosy apple aphid, genetics of resistance to, 253 Rosy leaf curling aphid of apple, genetics of resistance to, 252 Rotation agroforestry in acid soils and, 296, 299 green manure in wetland rice and, 157 nitrogen in rice-legume systems and, 8, 10-11, 13, 36,40 soil organic matter in semiarid regions and, 96, 98, 121, 129 fertilizer, 103 microbial biomass, 115-1 16, I18 organic residue, 11 1 tillage, 99-100 Rubber, genetic resources and, 85 Rubus aphid, genetics of resistance to, 253-255 Rust disease-resistance breeding in chickpea and, 203, 212, 215 resistance to insects and, 242 Rye genetic resources and, 73 genetics of resistance to insects and, 235-236 Ryegrass, soil organic matter in semiarid regions and, 106 S

Saline soil, green manure in wetland rice and, 141, 175-177, 179, 181 Salt tolerance, green manure in wetland rice and, 175 Samuneu, agroforestry in acid soils and, 279 Saponins, genetics of resistance to insects and, 261

374

INDEX

Sediment enrichment factor, semiarid regions and, 122-123 Seed moisture, genetic resources and, 87 Seed rot, resistance breeding in chickpea and, 201-202 Seed storage, genetic resources and, 86-87 Segregation, resistance to insects and, 235, 244,247, 253, 257 Selection, resistance to insects and, 243, 257,262 Selection from introductions, disease-resistance breeding in chickpea and, 193 Semiarid regions genetic resources and, 77,83 green manure in wetland rice and, 142 soil organic matter in, see Soil organic matter in semiarid regions Sequential cropping system. acid soils and, 278 Sesbania genetic resources and, 77 green manure in wetland rice and, 138, 141- 142, 179-1 80 incorporation, 150-151 nitrogen, 159, 162 nitrogen accumulation, 143- 146, 148-149 nutrient availability, 167, 169 residual effects, 178-179 saline alkali soils, 175-177 soil properties, 170, 173-174 transformations, 164- 166 yield responses, 151-152, 155-157 nitrogen in rice-legume systems and legume nitrogen accumulation, 18- 19, 22,24-25 legume nitrogen contribution, 33-42 legumes, 10-14, 16 management of nitrogen, 42-43, 45-46,48 Sesbania rostrara, green manure in wetland rice and, 141-142, 180 Shade, agroforestry in acid soils and, 289 Shade tolerance genetic resources and, 76-77 green manure in wetland rice and, 138 Shoot fly, genetics of resistance to, 244-245 Short-wave radiation, ammonia volatilization from flooded soils and, 330

Sodic soils, green manure in wetland rice and, 167-168, 170, 175-177, 181 Sodium green manure in wetland rice and, 171, 175-176 nitrogen in rice-legume systems and, 43 Soil agroforestry in, see Agroforestry in acid soils of humid tropics flooded, ammonia volatilization from, see Ammonia volatilization from flooded soils green manure in wetland rice and, 170- 175, 180- 18 1 nitrogen in rice-legume systems and, 3-8, 13-16 Soil moisture disease-resistance breeding in chickpea and, 201-203 green manure in wetland rice and, 149-150, 180 Soil organic matter in semiarid regions, 94-97 changes in content, 98-99 cultivation, 97-98, 120-121 erosion, 121-123 fertilizer, 104-105 nitrogen, 102- I04 future needs, 130 management, 119 manure, 113-114 microbial biomass, 114-1 19 progress, 129-130 residue, 113-114 burning, 112 rate of addition, 108-1 12 removal, 112-113 types, 105-108 tillage conservation, 100-102 frequency of fallow, 99 intensity, 99-100 turnover carbon cycle, 123-124 models, 125-129 Solar radiation, ammonia volatilization from flooded soils and, 310,330 Sole-crop systems, agroforestry in acid soils and, 284-285 Somatic hybridization, genetic resources and, 70

INDEX Sorghum genetic resources and, 68-69 genetics of resistance to insects and, 235,242-246 nitrogen in rice-legume systems and, 36 Sorghum midge, genetics of resistance to, 245-246 Soybean disease-resistance breeding in chickpea and, 219 genetics of resistance to insects and, 259-260 green manure in wetland rice and, 148 nitrogen in rice-legume systems and, 8-9, 13-15,51 nitrogen accumulation, 22-26 nitrogen contribution, 27, 34, 36-37 Specific combining ability, resistance to insects and, 241-242, 251 Spotted alfalfa aphid, genetics of resistance to, 261-262 Squash bug, genetics of resistance to, 257 Stagnant-film model, ammonia volatilization from flooded soils and, 335,337 Stem-nodulating crops green manure in wetland rice and, 137, 141-142, 148, 169 nitrogen in rice-legume systems and, 11 Stem rot, resistance breeding in chickpea and, 194, 196, 199,201-202 Stem solidness, genetics of resistance to insects and, 238 Stemphylium blight, resistance breeding in chickpea and, 203, 212, 219 Sterility, genetics of resistance to insects and, 247, 253 Stoloniferous fallows, agroforestry in acid soils and, 289, 291 Straw nitrogen in rice-legume systems and. 16 soil organic matter in semiarid regions and, 119-121, 129 residue, 105-108, 110, 112, 114 Stress disease-resistance breeding in chickpea and, 192,201, 215,217 genetic resources and, 75, 81 soil organic matter in semiarid regions and, 115 Striped cucumber beetle, genetics of resistance to, 256-257

375

Striped stem borer, genetics of resistance to, 231 Stunt virus, disease-resistance breeding in chickpea and, 215, 219 Stylosanfhes, agroforestry in acid soils and, 289,291 Subtropics genetic resources and, 73.80 genetics of resistance to insects and, 225, 242-243 green manure in wetland rice and, 178- I80 nitrogen in rice-legume systems and, 23,27 Sugar cane genetic resources and, 68, 73 genetics of resistance to insects and, 243 Sulfur deficiency, 105 green manure in wetland rice and, 168, 176-177 soil organic matter in semiarid regions and, 104-105, 128-129 Sulfur-coated urea, ammonia volatilization from flooded soils and, 322,325 Sulfur dioxide, ammonia volatilization from flooded soils and, 308 Sunflower, genetic resources and, 69 Sunn hemp, green manure in wetland rice and, 138, 166, 175 nitrogen, 159, 161 nitrogen accumulation, 143-144, 146, 148 yield responses, 151-152 Surface renewal model, ammonia volatilization from flooded soils and, 333-334 Susceptibility disease-resistance breeding in chickpea and, 201,208,218-219 genetics of resistance to insects and, 259-260,262,265 barley, 247 cotton, 249,251 fruits. 253 maize, 239-240,242-243 rice, 226-227 sorghum, 243-244,246 vegetables, 257-258 wheat, 231,234,237 Sustainability genetic resources and, 77,81-85 green manure in wetland rice and, 136

376

INDEX

Sweet clover aphid, genetics of resistance to, 262 Sweet potato, genetic resources and, 68-69 Symbiosis, genetic resources and, 76 Symbiotic nitrogen fixation, rice-legume systems and, 22-25

T Tanungya system, genetic resources and, 76 Tarnished plant bug, genetics of resistance to, 251 Temperate regions genetics of resistance to insects and, 243 green manure in wetland rice and, 172, 179 soil organic matter in, see Soil organic matter in semiarid regions Temperature ammonia volatilization from flooded soils and, 304,353 effects, 310-316, 318,320, 326, 329-330 models, 335-336,339, 342-343,345, 348-351 theory, 307-310 disease-resistance breeding in chickpea and, 217 fungal diseases, 194, 201-202, 204, 206-207 nematode diseases, 205-206 genetic resources and, 66 genetics of resistance to insects and, 232,234,246 green manure in wetland rice and, 136, 138, 141. 165, 172, 180 nitrogen in rice-legume systems and, 3, 8, 10, 33 soil organic matter in semiarid regions and, 95, 100, 105, 126-127 Tephrosia, green manure in wetland rice and, 138, 142, 144, 154 Terbutryne, ammonia volatilization from flooded soils and, 327 Thrips, genetics of resistance to, 249 Tillage agroforestry in acid soils and, 288 conservation, 100-102 delayed, 100

green manure in wetland rice and, 154, 157 nitrogen in rice-legume systems and, 15, 23.35 soil organic matter in semiarid regions and, 96,98-102, 129-130 management, I19 microbial biomass, 116-1 18 Tirhonia diuersifolia, green manure in wetland rice and, 155 Tobacco genetic resources and, 68,73 genetics of resistance to insects and, 263 Tobacco budworm, genetics of resistance to, 249-250 Tomato genetic resources and, 73 genetics of resistance to insects and, 263 Toxicity, green manure in wetland rice and, 156, 172 Translocation, genetics of resistance to insects and, 235-236,239, 247 Transplantation ammonia volatilization from flooded soils and, 323-324, 328-329 green manure in wetland rice and, 142, 180 incorporation, 149-151 nitrogen, 144, 146, 161-162 transformations, 164, 166 yield responses, 156 nitrogen in rice-legume systems and, 4, 1 1 legume nitrogen contribution, 31, 33-34,39 management of nitrogen, 42-43, 46-48,50 2-Tridecanone, genetics of resistance to insects and, 259, 262 Tririceae, genetic resources and, 69, 73 Triticum, genetics of resistance to insects and, 232,236-238 Tropical Tree Crop Program, genetic resources and, 80 Tropics agroforestry in acid soils of, see Agroforestry in acid soils of humid tropics genetic resources and, 73,77, 80, 83, 85 genetics of resistance to insects and, 225,242

377

INDEX green manure in wetland rice and, 178-180 nitrogen in rice-legume systems and, 23 Trypsin inhibitors, resistance to insects and, 260, 263 Turbulence, ammonia volatilization from flooded soils and, 304, 310, 330 models, 332-333, 341 theory, 306-307 Turnover green manure in wetland rice and, 162 soil organic matter in semiarid regions and, 103-104, 107, 114 carbon cycle, 123-124 models, 125-129 Two-film model, ammonia volatilization from flooded soils and, 308, 340-341 Two-spotted cucumber spider mite, genetics of resistance to, 257 U

Urea ammonia volatilization from flooded soils and. 320,323-326,328-329 hydrolysis, 321 green manure in wetland rice and, 156. 174, 179 nitrogen, I61 - 162 transformations, 165- 166 nitrogen in rice-legume systems and legume nitrogen contribution, 39-42 management of nitrogen. 43-50 Urea calcium nitrate, ammonia volatilization from flooded soils and, 322 Urea phosphate, ammonia volatilization from flooded soils and, 322, 329 Urea supergranules ammonia volatilization from flooded soils and, 322-323, 325 nitrogen in rice-legume systems and. 50 Urease, ammonia volatilization from flooded soils and. 320, 325-326 V

Vanilla, genetic resources and, 77 Vegetables, genetics of resistance to insects and, 256-259

Vegetation, soil organic matter in semiarid regions and, 95, 97, 114. 121 fertilizer, 102, 104-105 Verticillium wilt, resistance breeding in chickpea and, 200,203 Vetch, see also Milk vetch green manure in wetland rice and, 138, 145, 154, 179 nitrogen in rice-legume systems and, 25, 44-45 Viability agroforestry in acid soils and, 288 genetic resources and, 87 Vicinfaba, green manure in wetland rice and, 138 Viral diseases, resistance breeding in chickpea and, 193, 198, 212-213 Volatilization, ammonia, from flooded soils, see Ammonia volatilization from flooded soils W

Water deficit, nitrogen in rice-legume systems and, 9 , 4 2 Water depth, ammonia volatilization from flooded soils and, 353 factors, 311, 315-318, 330 models, 345. 348. 350-351 Water-holding capability, soil organic matter in semiarid regions and, 96 Water-holding capacity green manure in wetland rice and, 149, 174 nitrogen in rice-legume systems and, 4 1-42 Water-air interface, ammonia volatilization from flooded soils and, 304-305. 316 Waterlogging green manure in wetland rice and, 144, 179- 180 nutrient availability, 167- 168 soil properties, 170-172 transformations, 163, 166 nitrogen in rice-legume systems and, 9-12, 16.24-25,41 Wave length ratio, ammonia volatilization from flooded soils and, 318 Weather agroforestry in acid soils and, 284 green manure in wetland rice and, 160

378

INDEX

Weed suppression, agroforestry in acid soils and, 278, 296,298-299 alley cropping, 284-295 managed fallows, 289-291 Weedicide, green manure in wetland rice and, 141 Weeds ammonia volatilization from flooded soils and, 320,325-326 green manure in wetland rice and, 161 nitrogen in rice-legume systems and, 6-8 soil organic matter in semiarid regions and, 96, 100 Western corn rootworm, genetics of resistance to, 241-242 Wet root rot, disease-resistance breeding in chickpea and, 201-202 Wetland rice, green manure in, see Green manure in wetland rice Wheat genetic resources and, 67-69,73 genetics of resistance to insects and, 231-238,243 green manure in wetland rice and, 174 nitrogen in rice-legume systems and, 9, 1 1 , 13,40 soil organic matter in semiarid regions and, 99, 103, 118, 120 organic residue, 108, 110-1 12 Wheat stem sawfly, genetics of resistance to, 238 Whitebacked planthopper, genetics of resistance to, 228-230 Wild species, genetic resources and, 68-74 Wind, ammonia volatilization from flooded soils and, 313, 334-335 Windspeed, ammonia volatilization from flooded soils and, 304, 353 models, 335,343-345,348-351

primary factors, 310-311, 315-316, 318-320 secondary factors, 323, 330-33 1 theory, 308-310 Withdrawal of cultivars, disease-resistance breeding in chickpea and, 210 Wooly apple aphid, genetics of resistance to, 253 X Xylem, disease-resistance breeding in chickpea and, 194 Y

Yield agroforestry in acid soils and, 279, 285-288 ammonia volatilization from flooded soils and, 304,353 genetic resources and, 74 green manure in wetland rice and, 136-137, 160, 178-180 incorporation, 149-150 nitrogen accumulation, 143-145, 148 responses, 15 1-158 nitrogen in rice-legume systems and, 8, 11 legume nitrogen contribution, 27, 37.41 management of nitrogen, 47-48

z Zigzag leafhopper, genetics of resistance to, 230 Zinc green manure in wetland rice and, 169-170 nitrogen in rice-legume systems and, 42