Food security and climate change [First edition.] 9781119180630, 1119180635

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Food Security and Climate Change

Food Security and Climate Change Edited by Shyam S. Yadav Freelance International Consultant in Agriculture, Manav Memorial Trust/Manav Foundation, Vikaspuri, New Delhi, India and Manav Mahal International School, Baghpat, Uttar Pradesh, India

Robert J. Redden RJR Agricultural Consultants, Horsham, Victoria, Australia

Jerry L. Hatfield USDA-ARS National Laboratory for Agriculture and the Environment, Ames, Iowa, USA

Andreas W. Ebert Freelance International Consultant in Agriculture and Agrobiodiversity, Schwaebisch Gmuend, Germany

Danny Hunter Healthy Diets from Sustainable Food Systems Initiative, Bioversity International, Rome, Italy and Plant and Agricultural Biosciences Centre (PABC), National University of Ireland, Galway (NUIG)

This edition first published 2019 © 2019 John Wiley & Sons Ltd All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. The right of Shyam S. Yadav, Robert J. Redden, Jerry L. Hatfield, Andreas W. Ebert and Danny Hunter to be identified as the authors of the editorial material in this work has been asserted in accordance with law. Registered Offices John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial Office The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com. Wiley also publishes its books in a variety of electronic formats and by print-on-demand. Some content that appears in standard print versions of this book may not be available in other formats. Limit of Liability/Disclaimer of Warranty While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Library of Congress Cataloging-in-Publication Data Names: Yadav, S. S. (Shyam S.), editor. Title: Food security and climate change / edited by Shyam S. Yadav, Robert J. Redden, Jerry L. Hatfield, Andreas W. Ebert, Danny Hunter. Description: First edition. | Hoboken, NJ : John Wiley & Sons, Ltd, 2018. | Includes bibliographical references and index. | Identifiers: LCCN 2018014807 (print) | LCCN 2018027212 (ebook) | ISBN 9781119180630 (pdf ) | ISBN 9781119180654 (epub) | ISBN 9781119180647 (cloth) Subjects: LCSH: Crops and climate. | Food security–Climatic factors. Classification: LCC S600.5 (ebook) | LCC S600.5 .F68 2018 (print) | DDC 630.2/515–dc23 LC record available at https://lccn.loc.gov/2018014807 Cover Design: Wiley Cover Images: ©ansonmiao/E+/Getty Images; ©danishkhan/iStock/Getty Images; ©no_limit_pictures/iStock/Getty Images; ©Juanillo1970/Shutterstock Set in 10/12pt WarnockPro by SPi Global, Chennai, India

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v

Contents List of Contributors xvii 1

Climate Change, Agriculture and Food Security 1 Shyam S. Yadav, V. S. Hegde, Abdul Basir Habibi, Mahendra Dia, and Suman Verma

1.1 1.1.1 1.1.2 1.1.3 1.1.4 1.2 1.2.1 1.2.2 1.2.3 1.2.4 1.3

Introduction 1 Climate Change and Agriculture 3 Impact of Dioxide on Crop Productivity 4 Impact of Ozone on Crop Productivity 5 Impact of Temperature and a Changed Climate on Crop Productivity 6 Climate Change and Food Security 6 Climate Change and Food Availability 7 Climate Change and Stability of Food Production 8 Climate Change and Access to Food 8 Climate Change and Food Utilization 9 Predicted Impacts of Climate Change on Global Agriculture, Crop Production, and Livestock 10 Climate Change Mitigation, Adaptation, and Resilience 11 Mitigation 12 Adaptation and Resilience 12 Policies, Incentives, Measures, and Mechanisms for Mitigation and Adaptation 13 Impact of Divergent & Associated Technologies on Food Security under Climate Change 14 Integrated Pest Management (IPM) 15 Technological Options for Boosting Sustainable Agriculture Production 15 Mechanization in Agriculture Sector 16 Food Processing and Quality Agro-Products Processing 16 Planning, Implementing and Evaluating Climate-Smart Agriculture in Smallholder Farming Systems 17 The Government of India Policies and Programs for Food Security 17 Conclusions 18 References 19 In Riculture Seri 21

1.3.1 1.3.2 1.3.3 1.3.4 1.4 1.4.1 1.4.2 1.4.3 1.4.4 1.4.5 1.5 1.6

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2

Changes in Food Supply and Demand by 2050 25 Timothy S. Thomas

2.1 2.2 2.3 2.3.1 2.4 2.5 2.5.1 2.6 2.7 2.8 2.9 2.10

Introduction 25 Model Description 26 Model Assumptions 26 Economic and Demographic Assumptions 26 Climate Assumptions 28 Results 30 Production 30 Underutilized Crops 38 Consumption 38 Trade and Prices 42 Food Security 46 Conclusion 48 References 50

3

Crop Responses to Rising Atmospheric [CO2 ] and Global Climate Change 51 Pauline Lemonnier and Elizabeth A. Ainsworth

3.1 3.1.1 3.1.2 3.1.3 3.2 3.2.1 3.2.2 3.2.2.1

Introduction 51 Rising Atmospheric [CO2 ] and Global Climate Change 51 Measuring Crop Responses to Rising [CO2 ] 53 Physiological Responses to Rising [CO2 ] 54 Crop Production Responses to Rising [CO2 ] 58 Effects of Rising [CO2 ] on Food Quality 59 Strategies to Improve Crop Production in a High CO2 World 61 Genetic Variability in Elevated [CO2 ] Responsiveness: The Potential and Challenges for Breeding 62 Strategies for Genetic Engineering 63 Acknowledgements 64 References 64

3.2.2.2

4

Adaptation of Cropping Systems to Drought under Climate Change (Examples from Australia and Spain) 71 Garry J. O’Leary, James G. Nuttall, Robert J. Redden, Carlos Cantero-Martinez, and M. Inés Mínguez

4.1 4.2 4.2.1 4.2.2 4.3 4.3.1 4.3.2 4.3.3 4.3.4

Introduction 71 Water Supply 72 Changing Patterns of Rainfall 72 Rotations, Fallow, and Soil Management 74 Interactions of Water with Temperature, CO2 and Nutrients 77 High Temperature Response of Wheat 77 High Temperature and Grain Quality of Wheat 79 Atmospheric CO2 Concentration and Crop Growth 79 Elevated Atmospheric CO2 and Grain Quality 80

Contents

4.4 4.5 4.6 4.7

Matching Genetic Resources to The Environment and the Challenge to Identify the Ideal Phenotype 80 Changing Climate and Strategies to Increase Crop Water Supply and Use 82 Beyond Australia and Spain 84 Conclusions 85 Acknowledgments 85 References 86

5

Combined Impacts of Carbon, Temperature, and Drought to Sustain Food Production 95 Jerry L. Hatfield

5.1 5.1.1 5.2 5.3 5.3.1 5.3.2 5.3.3 5.4 5.4.1 5.4.2 5.5 5.5.1 5.6

Introduction 95 Need for Food to Feed the Nine Billion by 2050 95 Changing Climate 96 Carbon Dioxide And Plant Growth 97 Responses of Plants to Increased CO2 97 Effect of Increased CO2 on Roots 100 Effect of Increased CO2 on Quality 100 Temperature Effects on Plant Growth 102 Responses of Plants to High Temperatures 102 Mechanisms of Temperature Effect on Plants 104 Water Effects on Plant Growth 106 Mechanisms of Water Stress 107 Interactions of Carbon Dioxide, Temperature, And Water in a Changing Climate 108 References 110

6

Scope, Options and Approaches to Climate Change 119 S. Seneweera, Kiruba Shankari Arun-Chinnappa, and Naoki Hirotsu

6.1 6.2

Introduction 119 Impact of CO2 and climate stress on growth and yield of agricultural crop 120 The Primary Mechanisms of Plants Respond to Elevated CO2 121 Interaction of Rising CO2 With Other Environmental Factors – Temperature and Water 121 Impact of Climate Change on Crop Quality 122 Climate Change, Crop Improvement, and Future Food Security 123 Intra-specific Variation in Crop Response to Elevated [CO2 ] - Current Germplasm Versus Wild Relatives 124 Identification of New QTLs for Plant Breeding 124 Association Mapping for Large Germplasm Screening 125 Genetic Engineering of CO2 Responsive Traits 125 Conclusions 126 References 127

6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11

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7

Mitigation and Adaptation Approaches to Sustain Food Security under Climate Change 131 Li Ling and Xuxiao Zong

7.1

Technology and its Approaches Options to Climate Change in Agriculture System 132 Adjusting Agricultural Farming Systems and Organization, with Changes in Cropping Systems 133 Changing Farm Production Activities 135 Developing Biotechnology, Breeding New Varieties to Adapt to Climate Change 135 Developing Information Systems, and Establishing a Disaster Prevention System 136 Strengthening the Agricultural Infrastructure, Adjusting Management Measures 137 Development and Implementation of Techniques to Combat Climatic Changes 137 Improving Awareness of Potential Implications of Climate Change Among All Parties Involved (from grassroots level to decision makers) 138 Enhancing Research on Typical Technology 138 Enhancing Research on Typical Technology for Different Areas 138 Enhancing Research on Food Quality Under Climate Change 138 Enhancing Research on Legumes and Its Biological Nitrogen Fixation 139 Developing Climate-Crop Modelling as an Aid to Constructing Scenarios 140 Development and Assessment Efforts of Adaptation Technology 140 References 141

7.1.1 7.1.2 7.1.3 7.1.4 7.1.5 7.2 7.2.1 7.2.2 7.2.2.1 7.2.2.2 7.2.2.3 7.2.3 7.2.4 8

Role of Plant Breeding to Sustain Food Security under Climate Change 145 Rodomiro Ortiz

8.1 8.2 8.2.1 8.2.2 8.2.3 8.2.4 8.2.5 8.3 8.3.1 8.3.2 8.4 8.5

Introduction 145 Sources of Genetic Diversity and their Screening for Stress Adaptation 146 Crop-related Species 146 Domestic Genetic Diversity 146 Crossbreeding 147 Pre-breeding 148 Biotechnology and Modeling as Aids for Breeding Cultivars 148 Physiology-facilitated Breeding and Phenotyping 149 Abiotic Stress Adaptation and Resource-use Efficiency 150 Precise and High Throughput Phenotyping 150 DNA-markers for Trait Introgression and Omics-led Breeding 151 Transgenic Breeding 152 References 153

9

Role of Plant Genetic Resources in Food Security 159 Robert J. Redden, Hari Upadyaya, Sangam L. Dwivedi, Vincent Vadez, Michael Abberton, and Ahmed Amri

9.1

Introduction 159

Contents

9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9 9.10 9.11 9.12 9.13 9.14 9.14.1 9.14.2 9.14.3 9.14.4 9.15 9.16 9.17 9.18 9.19 9.20 9.21

Climate Change and Agriculture 160 Adjusting Crop Distribution 160 Within Crop Genetic Diversity for Abiotic Stress Tolerances 160 Broadening the Available Genetic Diversity Within Crops 161 Crop Wild Relatives as a Novel Source Of Genetic Diversity 161 Genomics, Genetic Variation and Breeding for Tolerance of Abiotic Stresses 162 Under-utilised Species 163 Genetic Resources in the Low Rainfall Temperate Crop Zone 164 Forage and Range Species 166 Genetic Resources in the Humid Tropics 166 Genetic Resources in the Semi-arid Tropics and Representative Subsets 168 Plant Phenomics 168 Discovering Climate Resilient Germplasm Using Representative Subsets 170 Multiple Stress Tolerances 170 Drought Tolerance 170 Heat Tolerance 173 Tolerance of Soil Nutrient Imbalance 174 Global Warming and Declining Nutritional Quality 174 Crop Wild Relatives (CWR) - The Source of Allelic Diversity 174 Introgression of Traits from CWR 175 Association Genetics to Abiotic Stress Adaptation 176 Strategic Overview 177 Perspectives 177 Summary 179 References 179

10

Breeding New Generation Genotypes for Conservation Agriculture in Maize-Wheat Cropping Systems under Climate Change 189 Rajbir Yadav, Kiran Gaikwad, Ranjan Bhattacharyya, Naresh Kumar Bainsla, Manjeet Kumar, and Shyam S. Yadav

10.1 10.2 10.2.1 10.2.2 10.2.2.1 10.2.2.2 10.2.3 10.2.4 10.3 10.4 10.4.1 10.4.2 10.4.3 10.5 10.5.1

Introduction 189 Challenges Before Indian Agriculture 191 Declining Profit 191 Depleting Natural Resources: 193 Water: 193 Soil Health/ Soil Quality 193 Changing Climate 195 Climate Change Adaptation: Why it is Important in Wheat? 198 CA as a Concept to Address These Issues Simultaneously 199 Technological Gaps for CA in India 199 Machinery Issue 199 Non-availability of Adapted Genotypes for Conservation Agriculture Designing the Breeding Strategies 201 Characteristics of Genotypes Adapted for CA 202 Role of Coleoptiles in Better Stand Establishment Under CA 202

200

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Contents

10.5.2 10.5.3 10.5.4 10.6 10.7 10.8 10.8.1 10.9

Spreading Growth Habit During Initial Phase for Better Moisture Conservation and Smothering of Weeds 204 Exploitation of Vernalization Requirement for Intensification 205 Integrating Cropping System and Agronomy Perspective in Breeding for CA 209 Wheat Ideotype for Rice-Wheat Cropping Systems of Northern India 214 Breeding Methodology Adopted in IARI for CA Specific Breeding 215 Countering the Tradeoff Between Stress Adaptation and Yield Enhancement Through CA Directed Breeding 216 Yield Enhancement by Increasing Water Use Efficiency Through CA 218 Conclusions 220 References 221

11

Pests and Diseases under Climate Change; Its Threat to Food Security 229 Piotr Tre˛bicki and Kyla Finlay

11.1 11.2 11.3 11.4 11.5

Introduction 229 Climate Change and Insect Pests 231 Climate Change and Plant Viruses 235 Climate Change and Fungal Pathogens 238 Climate Change and Effects on Host Plant Distribution and Availability 240 Acknowledgments 241 References 241

12

Crop Production Management to Climate Change 251 Sain Dass, S. L. Jat, Gangadhar Karjagi Chikkappa, and C.M. Parihar

12.1 12.2 12.3 12.4 12.5 12.6 12.6.1 12.6.2 12.7 12.7.1 12.7.2 12.7.3 12.7.4 12.7.4.1 12.7.4.2 12.7.4.3 12.7.4.4 12.7.4.5 12.7.4.6 12.7.5 12.7.5.1

Introduction 251 Maize Scenario in World and India 251 The Growth Rate of Maize 254 Maize Improvement 256 Single Cross Hybrids 256 Pedigree Breeding for Inbred Lines Development 257 Seed multiplication 258 Single Cross Development 258 Preferred Characteristics for Good Parent 259 Female or Seed Parent 259 Development of Specialty Corn Schs 259 Baby Corn and Sweet Corn 259 Quality Protein Maize (QPM) 260 Improvement of Inbred Lines 260 Improvement of Inbred Lines through MAS 260 Foreground selection 260 Background selection 261 Marker Assisted Backcross Breeding strategies (MABB) 262 MABB at What Cost? 262 Doubled Haploid (DH) Technique 263 Steps Involved In Vivo DH Inbred Lines Development 263

Contents

12.7.5.2 12.7.6 12.7.6.1 12.7.6.2 12.7.6.3 12.7.7 12.7.7.1 12.7.8 12.7.8.1 12.7.8.2 12.7.8.3 12.7.8.4 12.7.8.5 12.7.9 12.7.9.1 12.7.9.2 12.7.9.3 12.7.9.4 12.7.9.5 12.7.9.6 12.7.9.7 12.7.9.8 12.7.9.9 12.7.9.10 12.7.9.11 12.8 12.8.1 12.8.2 12.8.3 12.8.4 12.8.5 12.8.6 12.8.7

Advantages of DH Lines over Conventional Inbred Lines 265 Transgenic Maize and its Potential 265 Abiotic Stresses 266 Drought Tolerance 267 Screening Techniques 267 Hybrid Seed Production 268 Pre-requisites of Single Cross Hybrid Seed Production 268 Important Considerations for Hybrid Seed Production 268 Isolation Distance 268 Male:female Ratio 269 How to Bring Male: female Synchrony? 269 Hybrid Seed Production Technology 269 Hybrid Seed Production Sites 272 Crop Production 272 Cropping System Optimization 272 Crop Sequence 273 Best Management Practices (BMP) for Crop Establishment 274 Crop Establishment 274 Raised Bed / ridge and Furrow Planting 276 Zero-till Planting 278 Conventional Till Flat Planting 278 Furrow Planting 278 Transplanting 279 BMP for Water Management 279 BMP for nutrient management 281 Nutrient Management Practices for Higher Productivity and Profitability in Maize Systems 283 Timing and method of fertilizer application 284 Integrated Nutrient Management (INM) 284 Biofertilizers 285 Micronutrient Application 285 Slow Release Fertilizers 285 Precision Nutrient Management 285 Conservation Agriculture and Smart Mechanization 286 References 287

13

Vegetable Genetic Resources for Food and Nutrition Security under Climate Change 289 Andreas W. Ebert

13.1 13.2 13.3

Introduction 289 Global vegetable production 290 The Role of Genetic Diversity to Maintain Sustainable Production Systems Under Climate Change 290 Ex Situ Conservation of Vegetable Germplasm at The Global Level 296 Access to Information on Ex Situ Germplasm Held Globally 302 SINGER: Online Catalog of International Collections Managed by the GCIAR and WorldVeg 303

13.4 13.5 13.5.1

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13.5.2 13.5.3 13.5.4 13.5.5 13.5.6 13.5.6.1 13.5.6.2 13.5.7 13.5.8 13.6 13.7

14

14.1 14.2 14.2.1 14.2.2

EURISCO: the European Genetic Resources Search Catalog 303 GRIN of USDA-ARS 304 GENESYS: the global gateway to plant genetic resources 304 The Crop Wild Relatives Portal 305 Crop Trait Mining Platforms 305 Crop Trait Mining Informatics Platform 305 The Diversity Seek Initiative 306 Trait information portal for CWR and landraces and crop-trait ontologies 307 Summary and Outlook 308 In Situ and On-farm Conservation of Vegetable Resources 310 Summary and Outlook 311 Acknowledgment 312 References 312 Annex 1 315 Sustainable Vegetable Production to Sustain Food Security under Climate Change at Global Level 319 Andreas W. Ebert, Thomas Dubois, Abdou Tenkouano, Ravza Mavlyanova, Jaw-Fen Wang, Bindumadhava Hanumantha Rao, Srinivasan Ramasamy, Sanjeet Kumar, Fenton D. Beed, Marti Pottorff, Wuu-Yang Chen, Ramakrishnan M. Nair, Harsh Nayyar, and James J. Riley

Introduction 319 Regional Perspective: Sub-Saharan Africa 320 The Effects of Climate Change in Sub-Saharan Africa 320 Interactions Between Climate Change and Other Factors Driving Vegetable Production and Consumption in Sub-Saharan Africa 321 14.2.3 Implications of Climate Change and Other Factors on Vegetable Production and Consumption in Sub-Saharan Africa 321 14.3 Regional Perspective: South and Central Asia 325 14.3.1 The Effects of Climate Change in South Asia 325 14.3.2 The Effects of Climate Change in Central Asia 326 14.3.3 Climate Change Adaptation Options in South and Central Asia 326 14.4 The Role of Plant Genetic Resources for Sustainable Vegetable Production 328 14.5 Microbial Genetic Resources to Boost Agricultural Performance of Robust Production Systems and to Buffer Impacts of Climate Change 329 14.6 Physiological Responses to a Changing Climate: Elevated CO2 Concentrations and Temperature in The Environment 330 14.6.1 CO2 and Photosynthesis 330 14.6.2 CO2 and Stomatal Transpiration 331 14.6.3 Dual Effect of Increased CO2 and Temperature 331 14.6.3.1 High Temperature (HT) Effect on Mungbean 332 14.6.3.2 Current and Proposed Mungbean Physiology Studies at Worldveg South Asia 332 14.6.4 Conclusion 334 14.7 Plant Breeding for Sustainable Vegetable Production 335

Contents

14.7.1 14.7.2 14.7.3 14.7.4 14.8 14.9 14.10 14.11

Formal Vegetable Seed System –Lessons Learned 335 Role of WorldVeg’s International Breeding Programs 336 Impact of WorldVeg’s Breeding Programs 337 Future Outlook 337 Management of Bacterial and Fungal Diseases for Sustainable Vegetable Production 338 Management of Insect and Mite Pests 342 Grafting to Overcome Soil-borne Diseases and Abiotic Stresses 344 Summary and Outlook 347 Acknowledgment 347 References 348

15

Sustainable Production of Roots and Tuber Crops for Food Security under Climate Change 359 Mary Taylor, Vincent Lebot, Andrew McGregor, and Robert J. Redden

15.1 15.2 15.2.1 15.2.2 15.2.3 15.2.3.1 15.2.3.2 15.2.3.3 15.2.3.4 15.2.4 15.3 15.3.1 15.3.2 15.3.2.1 15.3.2.2 15.4 15.5 15.5.1 15.5.1.1 15.5.2 15.5.3 15.6 15.7

Introduction 359 Optimum Growing Conditions for Root and Tuber Crops 361 Sweet Potato 361 Cassava 361 Edible Aroids 362 Taro 362 Cocoyam 362 Giant Taro 363 Swamp Taro 363 Yams 363 Projected Response of Root and Tuber Crops to Climate Change 364 Sweet Potato 364 Cassava 364 Edible Aroids 365 Yam 365 Climate Change and Potato Production 366 Sustainable Production Approaches 367 Agroforestry Systems 367 Combining Tree Crops and Roots and Tubers 367 Soil Health Management 368 Utilizing Diversity 368 Optimization of Root and Tuber Crops Resilience to Climate Change 369 Conclusion 371 References 371

16

The Roles of Biotechnology in Agriculture to Sustain Food Security under Climate Change 377 Rebecca Ford, Yasir Mehmood, Usana Nantawan, and Chutchamas Kanchana-Udomkan

16.1 16.2 16.3

Introduction 377 Reduced Water Availability and Drought 378 Drought-proofing Wheat and Other Cereals 378

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16.4 16.5 16.6 16.7 16.8 16.9 16.10 16.11 16.12 16.13 16.14

Drought Tolerance in Temperate Legumes 380 Drought Tolerance in Tropical Crops 381 Rainfall Intensity, Flooding and Water-logging Tolerance 383 Heat Stress And Thermo–tolerance 385 Thermo-tolerance and Heat Shock Proteins in Food Crops 385 Heat Stress Tolerance in Temperate Legumes 388 Salinity Stress, Ionic and Osmotic Tolerances 388 Salinity Tolerance in Rice 389 Salinity Tolerance in Legumes 390 Transgenics to Overcome Climate Change Imposed Abiotic Stresses 390 Conclusion 392 References 393

17

Application of Biotechnologies in the Conservation and Utilization of Plant Genetic Resources for Food Security 413 Toshiro Shigaki

17.1 17.2 17.2.1 17.2.2 17.3 17.4 17.4.1 17.4.2 17.4.3 17.4.4 17.4.5 17.4.6 17.5 17.5.1 17.5.1.1 17.5.1.2 17.5.2 17.5.2.1 17.5.2.2 17.5.3 17.5.3.1 17.5.4 17.6 17.6.1 17.6.2 17.6.3 17.6.4 17.7 17.7.1 17.7.2 17.7.3

Introduction 413 Climate change 413 Population Explosion 414 Vandalism 414 Collecting Germplasm 415 Conservation 415 In situ Collection 415 Ex situ Collection 416 Slow Growth in Tissue Culture 416 Cryopreservation 417 Herbarium 419 Svalbard Global Seed Vault 419 Characterization of Germplasm 420 Early Developments 420 RFLP 420 RAPD 421 New Developments 421 Genotyping by Simple Sequence Repeats (SSR) 421 Amplified Fragment Length Polymorphism (AFLP) 421 Recent Developments 422 Genotyping by Sequencing (GBS) 422 Future Prospects 422 Germplasm Exchange 422 Bioassay 423 Enzyme-Linked Immunosorbent Assay (ELISA) 423 PCR 423 Loop-mediated Isothermal Amplification (LAMP) 423 Germplasm Utilization 425 Embryo Rescue 425 Somatic Hybridization 426 Molecular Breeding 426

Contents

17.7.4 17.7.5 17.8

Genetic Engineering 426 Biosafety 428 Future Strategies and Guidelines for the Preservation of Plant Genetic Resources 428 References 430

18

Climate Change Influence on Herbicide Efficacy and Weed Management 433 Mithila Jugulam, Aruna K. Varanasi, Vijaya K. Varanasi, and P.V.V. Prasad

18.1 18.2 18.3 18.4 18.4.1 18.4.2 18.4.3 18.5

Introduction 433 Herbicides in Weed Management 434 Climate Factors and Crop-Weed Competition 434 Climate Change Factors, Herbicide Efficacy and Weed Control Effects of Elevated CO2 and High Temperatures 438 Effects of Precipitation and Relative Humidity 440 Effects of Solar Radiation 441 Concluding Remarks and Future Direction 442 Acknowledgments 442 References 442

19

Farmers’ Knowledge and Adaptation to Climate Change to Ensure Food Security 449 Lois Wright Morton

19.1 19.2 19.3 19.4 19.5 19.6

Farmers and Climate Change 449 Knowledge About Climate 451 Weather and Climate 452 Values and Beliefs About Climate Change 453 Farmer Climate Beliefs 454 Vulnerability, Experiences of Risk, Concern About Hazards and confidence 456 Climate Related Hazards 458 Adaptation Factors 460 Water is the Visible Face of Climate 462 Making Sense of Climate: Local, Indigenous and Scientific knowledge System Adaptation or Transformation 465 References 467

19.7 19.8 19.9 19.10 19.11

438

463

20

Farmer and Community-led Approaches to Climate Change Adaptation of Agriculture Using Agricultural Biodiversity and Genetic Resources 471 Tony McDonald, Jessica Sokolow, and Danny Hunter

20.1 20.2 20.3 20.4

Introduction 471 Impact of Climate Change on Farming Communities 472 Inequity of Climate Change across Farming Communities 474 Impact of Climate Change on the Many Elements of Genetic Resources and Agricultural Biodiversity 475 Monocultures 475

20.5

xv

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Contents

20.6 20.7

Wild Species 476 Role of Genetic Resources and Agricultural Biodiversity in Coping with Climate Change 477 20.8 Brief Overview of Approaches Using Genetic Resources and Agricultural Biodiversity to Cope with Climate Change 478 20.9 Identification of a Spectrum of Examples of Farmer-led Approaches 482 20.10 Examination of Barriers to Implementation of Farmer-led Approaches 483 20.10.1 Farmers & their Communities 490 20.10.2 Institutional & Collaborative mechanisms 491 20.10.3 Contextual & Background 492 20.11 Systems that are working 493 20.12 Conclusion 494 References 494 21

Accessing Genetic Diversity for Food Security and Climate Change Adaptation in Select Communities in Africa 499 Otieno Gloria

21.1 21.2 21.2.1 21.2.2 21.3 21.3.1 21.3.2

Introduction 499 Methodology 501 Reference Sites and Crops 501 Data and Methods 502 Results and Discussion 504 Summary of Climate Change in Selected Sites 504 Finding Potentially Adaptable Accessions from a Pool of National and International Plant Genetic Resources 504 21.3.2.1 Zambia 505 21.3.2.2 Zimbabwe 508 21.3.2.3 Benin 508 21.4 Conclusions and Policy Implications 520 References 521 Index 523

xvii

List of Contributors Michael Abberton

Fenton D. Beed

IITA Genetic Resources Centre International Institute of Tropical Agriculture Ibadan Nigeria

Food and Agriculture Organization of the United Nations (FAO) Rome Italy Ranjan Bhattacharyya

Elizabeth A. Ainsworth

USDA ARS Global Change and Photosynthesis Research Unit Urbana USA

Indian Agricultural Research Institute ICAR New Delhi India Carlos Cantero-Martinez

International Center for Agricultural Research in Dry Areas (ICARDA) Rabat Morocco

Department of Crop and Forestry Science, Agrotecnio Universitat de Lleida Lleida Spain

Kiruba Shankari Arun-Chinnappa

Wuu-Yang Chen

Centre for Crop Health University of Southern Queensland Toowoomba Australia

World Vegetable Center Shanhua Tainan Taiwan

Naresh Kumar Bainsla

Gangadhar Karjagi Chikkappa

Indian Agricultural Research Institute ICAR New Delhi India

ICAR-Indian Institute of Maize Research New Delhi India

Ahmed Amri

Sain Dass

Ex Director Maize Indian Council of Agricultural Research New Delhi India

xviii

List of Contributors

Mahendra Dia

Otieno Gloria

Department of Horticultural Sciences North Carolina State University Raleigh North Carolina USA

Bioversity International Regional Office of Uganda Kampala Uganda Abdul Basir Habibi

Thomas Dubois

World Vegetable Center, Eastern and Southern Africa Duluti Arusha Tanzania Sangam L. Dwivedi

International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) Patancheru Telangana India Andreas W. Ebert

Freelance International Consultant in Agriculture and Agrobiodiversity Schwaebisch Gmuend Germany Kyla Finlay

Agriculture Victoria Research Horsham Victoria Australia

Afghanistan Agriculture Input Project Ministry of Agriculture, Irrigation & Livestock, Kabul Afghanistan Bindumadhava Hanumantha Rao

World Vegetable Center South Asia Greater Hyderabad Telangana India Jerry L. Hatfield

National Laboratory for Agriculture and the Environment, USDA-ARS Ames Iowa USA V. S. Hegde

Division of Genetics Indian Agricultural Research Institute Indian Council of Agricultural Research New Delhi India Naoki Hirotsu

Rebecca Ford

Environmental Futures Research Centre Griffith University Nathan Queensland Australia Kiran Gaikwad

Indian Agricultural Research Institute ICAR New Delhi India

Tokyo University Japan Danny Hunter

Healthy Diets from Sustainable Food Systems Initiative Bioversity International Rome Italy and Plant and Agricultural Biosciences Centre (PABC) National University of Ireland Galway (NUIG)

List of Contributors

S. L. Jat

Ravza Mavlyanova

ICAR-Indian Institute of Maize Research New Delhi India

World Vegetable Center, Central Asia and the Caucasus Tashkent Uzbekistan

Mithila Jugulam

Department of Agronomy Kansas State University Manhattan USA

Andrew McGregor

Koko Siga Pacific Fiji Yasir Mehmood

Chutchamas Kanchana-Udomkan

Environmental Futures Research Centre Griffith University Nathan Queensland Australia

Environmental Futures Research Centre Griffith University Nathan Queensland Australia M. Inés Mínguez

Manjeet Kumar

Indian Agricultural Research Institute ICAR New Delhi India

Centre for The Management of Agricultural and Environmental Risk (CEIGRAM-ETSIAAB-UPM) Technical University of Madrid Madrid Spain

Sanjeet Kumar

World Vegetable Center Shanhua Tainan Taiwan

Lois Wright Morton

Department of Sociology Iowa State University Ames Iowa

Vincent Lebot

CIRAD-AGAP Vanuatu Pauline Lemonnier

USDA ARS Global Change and Photosynthesis Research Unit Urbana USA Li Ling

Legume breeder Liaoning Institute of Cash Crops Liaoyang Liaoning Province China

Ramakrishnan M. Nair

World Vegetable Center South Asia Greater Hyderabad Telangana India Usana Nantawan

Environmental Futures Research Centre Griffith University Nathan Queensland Australia

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List of Contributors

Harsh Nayyar

P.V.V. Prasad

Department of Botany Panjab University Chandigarh India

Department of Agronomy Kansas State University Manhattan USA

James G. Nuttall

Srinivasan Ramasamy

Agriculture Victoria Research Department of Economic Development Jobs, Transport and Resources Horsham Victoria Australia

World Vegetable Center Shanhua Tainan Taiwan

Garry J. O’Leary

Agriculture Victoria Research, Department of Economic Development Jobs, Transport and Resources Horsham Victoria Australia Rodomiro Ortiz

Department of Plant Breeding Swedish University of Agricultural Sciences (SLU) Sundsvagen Alnarp Sweden C.M. Parihar

Robert J. Redden (Retired)

RJR Agricultural Consultants Horsham Victoria Australia James J. Riley

College of Agriculture and Life Sciences University of Arizona Tucson USA S. Seneweera

Centre for Crop Health University of Southern Queensland Toowoomba Australia and

ICAR-Indian Agricultural Research Institute New Delhi India

National Institute of Fundamental Studies (NIFS) Kandy Sri Lanka

Marti Pottorff

Toshiro Shigaki

Department of Botany and Plant Sciences University of California Riverside USA

Laboratory of Plant Pathology University of Tokyo Tokyo Japan

List of Contributors

Jessica Sokolow

Hari Upadyaya

Research Associate The Cabrera Research Lab Ithaca New York

International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) Patancheru Telangana India

and The College of Human Ecology Cornell Institute of Public Affairs Cornell University Ithaca New York

Vincent Vadez

International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) Patancheru Telangana India

Mary Taylor

University of the Sunshine Coast Queensland Australia Abdou Tenkouano

CORAF/WECARD Dakar-RP Senegal Timothy S. Thomas

International Food Policy Research Institute (IFPRI) Washington, DC USA Tony McDonald

Institute of Land Water and Society Charles Sturt University Australia Piotr Tre˛bicki

Agriculture Victoria Research Horsham Victoria Australia

Aruna K. Varanasi

Department of Agronomy Kansas State University Manhattan USA Vijaya K. Varanasi

Department of Agronomy Kansas State University Manhattan USA Suman Verma

Government Holkar Science College Devi Ahilya Vishwavidyalaya Indor India Jaw-Fen Wang

Department of Agronomy National Taiwan University Taipei Taiwan

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Rajbir Yadav

Indian Agricultural Research Institute ICAR New Delhi India Shyam S. Yadav

Manav Foundation Vikaspuri New Delhi India

and Manav Mahal International School Lohara Ami Nagar Sarai Baghpat Uttar Pradesh India Xuxiao Zong

CAAS China

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1 Climate Change, Agriculture and Food Security Shyam S. Yadav 1,6 , V. S. Hegde 2 , Abdul Basir Habibi 3 , Mahendra Dia 4 , and Suman Verma 5 1

Manav Foundation, Vikaspuri, New Delhi, India Division of Genetics, Indian Agricultural Research Institute, Indian Council of Agricultural Research, New Delhi, India 3 Afghanistan Agriculture Input Project, Ministry of Agriculture, Irrigation & Livestock, Kabul, Afghanistan 4 Department of Horticultural Sciences, North Carolina State University, Raleigh, North Carolina, USA 5 Government Holkar Science College, Devi Ahilya Vishwavidyalaya, Indore, India 6 Manav Mahal International School, Lohara, Ami Nagar Sarai, Baghpat, Uttar Pradesh, India 2

1.1 Introduction During recent years, worldwide heavy rainfalls and floods, forest fires, occurrences, and the spread of new diseases, as found in the new strains of different pathogens and viruses, abnormal bacterial growth, and higher incidences of insect pests are direct indications of drastic environmental changes globally. It is now well established and documented that anthropogenic greenhouse gas (GHG) emissions are the main reason for the climate change at global level. It is also well recognized that agriculture sectors are directly affected by changes in temperature, precipitation, and carbon dioxide (CO2 ) concentration in the atmosphere. Thus, early and bold measures are needed to minimize the potentially drastic climate impacts on the production and productivity of various field crops. In most of the developing countries in Africa, Asia, and Asia Pacific regions, about 70% of the population depend directly or indirectly for its livelihood on the agriculture sector and most of this population lives in arid or semiarid regions, which are already characterized by highly volatile climate conditions (Yadav et al., 2015). Food, from staple cereal grains to high protein legumes and oilseed crops, is central to human development and well-being (Misselhorn et al., 2012); however, the complexity of global food security is challenging and will be made more so under climate change. The world continues to face huge difficulties in securing adequate food that is healthy, safe, and of high nutritional quality for all (Redden et al., 2014a). Considering the complexity of climatic change, the crop, plants, and livestock are inherently affected by too much or too little water, too high or too low temperatures, the length of the growing season, seasonal variation, other climatic extremes, etc. If we consider weather extremes during 2010 – 11, in Russia there were severe heat waves and approximately 30% of grain crops were lost due to burning, which resulted in huge losses to the Russian economy. Likewise, in Pakistan, the worst floods in 80 years of history occurred, and it was suggested in different media reports that one–fifth of the country area and more than 14% of cultivated land were submerged. Considering Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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the Indian weather scenarios during recent years some parts are having good rains and some parts are under drought and cultivation of many field crops is difficult in those areas and crop productivity is adversely affected. The Intergovernmental Panel on Climate Change (IPCC) defined “climate change as any change in climate over a time period that alters the composition of the global atmosphere and this change might be due to natural climate variability or a result of human activity”. According to the United Nations Framework Convention on Climate Change (UNFCC) climate change refers to “a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and is in addition to natural climate variability observed over comparable time periods”. Human activities, most importantly the burning of fossil fuels, natural causes, industrialization, and changes in land use are modifying the concentrations of atmospheric constituents or properties of the surface that absorb or scatter radiant energy. The majority of the warming observed over the last 50 years was likely due to the increase in greenhouse gas concentrations (IPCC, 2001) and future changes in climate are expected to include additional warming, changes in the amount of rainfall and its distribution pattern, rise in sea-level, and increased frequency and intensity of some climate extreme events such as flood, drought, and temperature severity. According to the Special Report on Emissions Scenarios (Nakic’enovic’ and Swart, 2000), the carbon dioxide concentration (CO2 ) in the atmosphere which was 284 ppm in 1832 will increase to approximately 550 ppm by 2050. This, in combination with other changes in the atmosphere, is likely to change the Earth’s climate, making it warmer by an average of 1.80 C to 4.00 C by the end of this century (IPCC, 2007). The temperature increase is widespread over the globe, and is greater at higher northern latitudes, while land regions have warmed faster than the oceans. This warming will increase the evapotranspiration of water from wet surfaces and plants, leading to increased but more variable distribution of precipitation. The concentration of ozone (O3 ) will also increase as a result of industrialization and this will have a negative impact on crop growth and productivity. The global average sea level has risen since 1961 at an average rate of 1⋅8 mm/year and since 1993 at 3⋅1 mm/year with contributions from thermal expansion, melting glaciers and ice caps, and the polar ice sheets (IPCC, 2007). The annual average Arctic sea ice extent has shrunken by 2⋅7% per decade, with larger decreases in summer of 7⋅4% per decade. Mountain glaciers and snow cover on an average have declined in both hemispheres (IPCC,2007). These general features of climate change act on natural and biological systems. The changes in climate, particularly increases in temperature have already affected a wide range of physical and biological systems in many aquatic, terrestrial and marine environments in various parts of the world. The climate change will increase the risks of extinction of more vulnerable species and loss of biodiversity. The extent of damage or loss and the number of systems affected would increase with the magnitude and rate of climate change. The human systems that are sensitive to climate change mainly include water resources, agriculture and forestry, coastal zones and marine systems, human settlements, and human health. The extent of the vulnerability of these systems depends on the geographical location and environmental conditions. The projected adverse impacts of climate change on human systems (IPCC, 2001) include: i) a general reduction in potential yields of crops in most of the tropical and sub-tropical regions for increases in atmospheric temperature; ii) a general reduction in potential crop yields in most of the regions in Mid-latitudes due to increases in

1.1 Introduction

annual average temperature of more than a few 0 C; iii) decreased availability of potable water for populations in many water-scarce regions, particularly in the Sub-tropics; iv) increased incidences of vector-borne and water-borne diseases and an increase in heat-stress mortality; v) increased risk of flooding for many human settlements because of increased occurrences of heavy precipitation and also a rise in the sea-level; and vi) a general increase in the demand for energy due to higher summer temperatures in different parts of the world. Climate change is also known to have some beneficial effects on the human system (IPCC, 2001). The positive impacts of climate change include: i) an increase in the potential yields of some crops in some of the regions in Mid-altitudes for increases in temperatures of less than a few 0 C; ii) a potential increase in global supply of timber from well managed forests; iii) an increase in the availability of water in some water-scarce regions in some parts of Southeast Asia; iv) A decrease in the winter-mortality in mid- and high altitudes; and v) reduced demand for energy due to higher winter temperatures. 1.1.1

Climate Change and Agriculture

The world population will continue to grow and is expected to reach 9.1 billion by 2050 (Charles et al. 2010). The total food production will have to be increased by 70–100%, if all these people are to be fed sufficiently (Smil, 2005; World Development Report, 2008). Increasing food production to feed this ever-increasing world population in a sustainable way is a great challenge, moreso at a time of rapid environmental change with rising temperatures and extreme climate events threatening food production globally. Agriculture is inherently sensitive to climate variability and change, as a result of either natural causes or human activities (Wheeler and Braun, 2013). Climate change caused by emissions of greenhouse gases is expected to directly influence crop production systems for food, feed, or fodder; to affect livestock health; and to alter the pattern and balance of trade of food and food products. Climate change has already started affecting agricultural growth and these impacts will vary with the degree of warming and associated changes in rainfall patterns, as well as from one location to another. According to the Intergovernmental Panel on Climate Change (IPCC, 2014), climate variations affect crop production in several regions of the world, with negative effects more common than positive, and developing countries highly vulnerable to further negative impacts. Climate change is estimated to have already reduced global yields of maize and wheat by 3.8% and 5.5% respectively (Lobell et al., 2011), and several researchers predicted steep decreases in crop productivity when atmospheric temperatures exceed critical physiological thresholds of agricultural crops (Battisti and Naylor, 2009; Wheeler et al., 2000). Climate change is already happening and represents one of the greatest environmental and societal threats facing the planet and our own existence. With the Paris Agreement on Climate Change in force this month and the skeptics who threaten its implementation, the time for bold and unprecedented action has never been more critical. For the livelihoods of the so-called “forgotten billion”, who live in dryland, on the margins of environmental sustainability, and where the harshest climate change scenarios are the fact of life, such action is vital! It is expected that drylands will expand by 11% by 2100 due to climate change. Fifteen out of 24 ecosystem services are already in decline, making drylands increasingly unproductive. About 10% of drylands are already degraded, and more land will continue to degrade in the upcoming years. Yet, drylands and agricultural research in drylands do not receive much attention or investment from the wider

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community of scientific research, development agencies, policy makers, or the private sector. This is in part due to huge misconceptions or oversimplifications socioeconomic factors, and the valuable things we can learn about climate change mitigation and adaptation from examining the complex interactions of these factors in drylands. 1.1.2

Impact of Dioxide on Crop Productivity

An important change for agriculture system is increased concentrations of carbon dioxide (CO2 ) in the atmosphere. As per the IPCC Special Report on Emission Scenarios (SRES), the atmospheric CO2 concentration is projected to increase to >550 ppm by 2050 and 800 ppm by 2100. Higher concentrations of CO2 will have a positive effect on many crops resulting in enhanced accumulation of biomass and the overall yield. However, the magnitude of this effect varies depending on type of management of crop (e.g. irrigation and fertilization regimes) and also crop type. Experimental yield response to elevated CO2 show that under optimal growth conditions, crop yields increase at 550 ppm CO2 in the range of 10% to 20% for C3 crops (such as wheat, rice, and soybean), and only 0–10% for C4 crops such as maize and sorghum (IPCC, 2007). It has been projected that in the next few decades, CO2 trends will be likely to increase global crop yields approximately by 1.8% per decade. The impact of climate change on nutritional quality of agricultural produce is not properly understood. However, some cereal and forage crops, for example, show lower protein concentrations under elevated CO2 conditions (IPCC, 2001). Some aspects of global climate change are expected to benefit agriculture. It has been projected that in the next few decades CO2 trends will likely increase global crop yields by roughly 1.8% per decade (IPCC, 2001). The increasing concentrations of CO2 in the atmosphere can have a positive impact on the rate of photosynthesis, particularly in C3 plants. Rising CO2 is estimated to account for approximately 0.3% of the observed 1% increase in global wheat production (Fischer and Edmeades, 2010). The free air carbon dioxide enrichment (FACE) experiments have shown that the average yield increase of C3 species was 11%, but no significant responses in case of C4 species such as maize and sorghum (Long et al., 2005). The CO2 affects the water use by crop plants because higher concentrations cause partial closure of stomata, and the decrease in the aperture of stomata reduces the rate of water consumption. The FACE experiments in potatoes have shown that CO2 enrichment increased tuber yield by 43%, decreased water consumption by 11%, and as a result increased the water use efficiency (WUE) by about 70% (Magliulo et al., 2003). In a similar experiment on sugar beet, it was found that the amount of water consumed during the growing season reduced by 20% while yield increased by 8% (Manderscheid et, al., 2010). The magnitude of increased CO2 effects on dry matter production depends upon the illumination conditions, water availability, N supply, and the transport and storage of the photosynthates (Jaggard, et al., 2010). In all cases of FACE experiments, the relative response to enriched CO2 was generally positive when the Nitrogen amount applied was inadequate, as in the case of wheat (Kimball, et al., 1999), rice (Kim et al., 2003). Thus, the enriched CO2 atmosphere should help to sustain the crop yield even when the use of nitrogenous fertilizer is restricted to protect the environment.

1.1 Introduction

1.1.3

Impact of Ozone on Crop Productivity

Ozone (O3 ) in the atmosphere is concentrated mostly in the upper layers of the atmosphere (Stratosphere) where it absorbs UV radiation. It is also present in the lowest layer of the atmosphere, called the troposphere or the Earth’s surface. Tropospheric O3 is a spatially and temporally dynamic air pollutant as well as a powerful greenhouse gas (Ainsworth, 2017). As a result of increased industrialization and human activities Tropospheric O3 has risen from approximately 100 ppb in the late 1800s to monthly average daytime concentrations exceeding 40–50 ppb at present (Monks et al., 2015). This increased concentration of O3 in the atmosphere has made it the third most potent anthropogenic greenhouse gas after CO2 and methane (IPCC, 2013). The distribution of O3 over the land surface is not uniform globally. It varies from region to region and also from season to season within the region. Ozone concentrations vary from about 20 ppb in parts of Asia, the Middle East, Europe and North America (Gillespie et al., 2012). According to Ramankutty et al. (2008), croplands in parts of China, India, and the USA are exposed to higher concentrations of O3 than croplands in Australia or Brazil. In India, O3 concentrations are the highest during the spring (Rabi) crop growing season (October – April) with 8 h daily concentrations reaching 100 ppb (Roy et al., 2009). Unlike India, O3 concentrations in the Corn Belt of the Mid-west USA are at the maximum during the summer growing season (Huang, et al., 2007). In India, O3 concentrations increased 20% from 1990 to 2013 and in the case of China its concentrations increased 13% over the same period (Brauer et al., 2016). Thus, many of the world’s most productive crop growing regions are exposed to continuously increasing concentrations of O3 resulting in an adverse impact on agricultural productivity and hence food security. Yield reductions owing to ozone pollution can start at concentrations as low as 20 ppb (Ashmore, 2002). The higher concentrations of O3 during crop growing seasons found to have significant negative impact on crop yields (Burney and Ramanathan, 2014). Feng and Kobayashi (2009) found that by 2050 probable yield reductions will be 8.9%, 9% and 17.5% for barley, wheat and rice, whereas 19.0 and 7.7% for bean and soybean, respectively. Globally, it is estimated that 4–15% of wheat yields, 3–4% of rice yields, 2–5% of maize yields and 5–15% of soybean yields are lost to O3 pollution (van Dingenen et al., 2009; Avnery et al., 2011). In the absence of stricter air pollution control, it is projected that increased O3 will further reduce wheat yields by 8.1–9.4% in China and 5.4–7.7% in India by 2020 (Tang et al., 2013). Tai et al. (2014) found that increased O3 pollution in South Asia could reduce wheat production as high as 40% in 2050. Such a trend would lead to increased demand for land area devoted to crops by as much as 8.9% in Asia in order to meet the increasing demand for food (Chuwah et al., 2015). The magnitude of negative impact of O3 on crop yield depends on the growing season temperature and water availability, and during dry years yield reductions in soybean and maize ranged from 10–20%, depending on growing season temperature (McGrath et al., 2015). Crops can experience both high background O3 concentrations throughout the growing season (termed chronic exposure) as well as acute O3 stress when concentrations exceed approximately 100 ppb that can lead to hypersensitive response and induction of cell death. By 2050 the impact of rising O3 is likely to eliminate most of the beneficial effects

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of yield increase due to increasing CO2 in C3 crops and cause a yield decrease of at least 5% in C4 species (Nelson, et al., 2009). As a result of the dynamic nature of O3 , there may be little potential for adaptation of crops to rising O3 concentrations in the atmosphere through altered crop management practices (Teixeira et al., 2011). However, the studies with rice indicate that there is scope to select for reduced O3 sensitivity. Therefore, recent efforts are focused on breeding and biotechnological approaches for genetically improving crops that can tolerate and respond to higher concentrations of Tropospheric O3 (Ainsworth, 2008; Frei, 2015). 1.1.4

Impact of Temperature and a Changed Climate on Crop Productivity

The temperature variations and changes in the amount and distribution of rainfall associated with increased CO2 concentration and continued emissions of greenhouse gases will bring about changes in land suitability for crop cultivation and crop yields. According to the Intergovernmental Panel on Climate Change (IPCC, 2007), global mean surface temperature is projected to rise in a range from 1.8∘ C to 4.0∘ C by 2100. In temperate latitudes, higher temperatures are expected to be beneficial to agriculture and as a result the area under agricultural cropping is likely to increase. The length of the growing period will also increase at higher latitudes and because of which there may be increased accumulation of biomass resulting in higher crop yields (Parry et al., 2004. Fisher et al. (2005) predicted that world cereal production will increase from 1.8 Gt to between 3.7 and 4.8 Gt by 2080 and much of this increase will be the result of cropping on an additional 320 million ha in the Northern Hemisphere. However, in low latitudes crop yields are likely to decrease, mainly because of increased temperature which shortens the period for grain filling and sometimes stresses the plants at the time of flowering and seed-set. A moderate incremental warming in some humid and temperate grassland may increase pasture productivity and reduce the need for housing and for compound feed (Rosenzweig et al., 2002). There may also be reduced livestock productivity and increased livestock mortality in semi-arid and arid pastures. In drier areas, there may be increased evapotranspiration and lower soil moisture levels (IPCC, 2001) and because of which some existing cultivated areas may become unsuitable for cropping and some tropical grassland may become increasingly arid. Temperature rise will also expand the range of many agricultural pests and diseases and increase the ability of pest populations to survive the winter and attack spring crops. In general, warming trends are likely to reduce global yields by about 1.5% per decade in the absence of effective adaptation. Thus, the increases in the atmospheric temperature are likely to impact adversely against the advantages of increasing concentrations of CO2 in the atmosphere. Extreme weather events are more likely to happen in the changed climate of the future (Gornall et al., 2010).

1.2 Climate Change and Food Security The Food and Agriculture Organization (FAO) defines food security as a “situation which exists when all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life”. This definition of the FAO involves four important

1.2 Climate Change and Food Security

dimensions of food supplies: availability, stability, access, and utilization (Schmidhuber and Tubiello, 2007). The “availability” refers to the availability of food of appropriate quality in sufficient quantities, supplied either through domestic production or imports. The “stability” relates to the stable access to food as per the demand because to be food secure, a population, household or individuals must have access to adequate amounts of food at all times. The third dimension, “access”, involves access by individuals to adequate resources in order to acquire appropriate foods in sufficient quantity for a nutritious diet. Finally, “utilization” encompasses all food safety and quality aspects of nutrition. In other words, utilization of food through adequate diet, clean water, sanitation, and health care to reach a state of nutritional well-being where all physiological needs are met. Agriculture is not only a source of the food but also a source of income for the majority of the population. Therefore, the critical point for food security is not whether food is available in sufficient quantity but the monetary and non-monetary resources at the disposal of the population that are sufficient to allow everyone access to adequate quantities of quality food. Climate change will affect all four dimensions of food security such as food availability or food production, access to food, stability of food supplies, and food utilization (FAO, 2006). About 2 billion out of the global population of over 7 billion is food insecure because they fall short of one or several of FAOs dimensions of food security. However, the overall impact of climate change on food security differs from region to region and over time, and also on the overall socioeconomic conditions of the population (IPCC, 2001). 1.2.1

Climate Change and Food Availability

Climate change affects agriculture and food production in complex ways. It affects food production directly through changes in agroecological conditions and indirectly by affecting growth and distribution of incomes, and thus demand for agricultural produce. The response of crop yield to climatic variations depend mainly on the species, cultivar grown, soil conditions, direct effect of CO2 on plants, and other location specific factors. The climatic changes such as atmospheric concentrations of CO2 and O3 and temperature and rainfall pattern are projected to directly influence the rates of improvement in agricultural productivity and food availability and thereby global food security in the future. Rosenzweig and Parry (1994) found that enhanced concentrations of atmospheric CO2 increase the productivity of most crops through increasing the rate of leaf photosynthesis and improving the efficiency of water use. According to them, there is a large degree of spatial variation in crop yields across the globe. In general, yields increased in Northern Europe but decreased across Africa and South America (Parry et al., 2004). Crop yields are also more negatively affected across most tropical areas than at higher latitudes and impacts become more severe with an increasing degree of climate change. Furthermore, large parts of the world where crop productivity is expected to decline under climate change coincide with countries that currently have a high burden of hunger (World Bank, 2010). Wheeler and Braun (2013) concluded that there was a robust and coherent pattern of the impacts of climate change on crop productivity globally and hence, on food availability. They projected that climate change will exacerbate food insecurity in areas that already have a high prevalence of hunger and under nutrition. A recent systematic review of changes in the

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yields of the major crops grown across Africa and South Asia under climate change found that average crop yields may decline across both regions by 8% by the 2050s (Knox et al., 2012). Across Africa, yields are predicted to change by –17% (wheat), –5% (maize), –15% (sorghum), and –10% (millet) and across South Asia by –16% (maize) and –11% (sorghum) under climate change. No mean change in yield was detected for rice. Knox et al. (2012) concluded that evidence for the impact of climate change on crop productivity in Africa and South Asia is robust for wheat, maize, sorghum, and millet, and inconclusive, absent, or contradictory for rice, cassava, and sugarcane. 1.2.2

Climate Change and Stability of Food Production

The stability of food production ensures supply of food in sufficient quantity as per the demand at all the time. Global climatic conditions are expected to become more variable than at present, with increases in the frequency and severity of extreme weather events such as cyclones, floods, hailstorms, and droughts. Such extreme weather events can adversely affect the stability of food production and therefore food security by bringing greater year-to-year fluctuations in crop yields. It is projected that the areas subject to high climate variability are likely to expand in future, whereas the extent of short-term climate variability is likely to increase across all regions globally. Droughts and floods are the dominant causes of short term fluctuations in food production in semi-arid and sub-humid areas of the world. If climate fluctuations become more pronounced and more widespread, such extreme events will become more and more severe and more frequent. In semi-arid areas, droughts can drastically reduce crop yields and livestock numbers and their productivity (IPCC, 2001). The sub-Saharan Africa and parts of South Asia are more prone to such climatic variations, meaning that the poorest regions with the highest level of chronic undernourishment in the world will also be exposed to the highest degree of instability in food production (Bruinsma, 2003). 1.2.3

Climate Change and Access to Food

Access to food refers to the ability of individuals, communities, and countries to purchase sufficient quantities of quality food as per their demand. Over the last 30 years, falling real prices for food and rising real incomes have led to substantial improvements in access to food in many of the developing countries. This increased purchasing power has allowed a growing number of people to purchase not only more food, but also more nutritious food with higher contents of protein, micronutrients and vitamins (Schmidhuber and Shetty, 2005). East Asia and to a lesser extent the Near-East/North African region have particularly benefited from a combination of lower real food prices and robust income growth (FAO, 2006). In both regions, improvements in access to food have been crucial in reducing hunger and malnutrition. Fischer et al. (2005) discussed the impact of climate change on agricultural gross domestic product (GDP) and prices. At global level, the impacts of climate change are likely to be very small; the estimates range from a decline of -1.5% to an increase of +2.6% by 2080. At regional level, the importance of agriculture as a source of income can be much more important. In these regions, the economic output from agriculture itself will be an important contributor to food security. The strongest impact of climate change on the economic output of agriculture is expected for sub-Saharan Africa, which means that the poorest and already most

1.2 Climate Change and Food Security

food-insecure region is also expected to suffer the largest contraction of agricultural incomes due to climate change. Agriculture is the main source of food as well as income in many developing regions of the world. Climate change poses a serious threat to food access for both rural and urban populations by reducing agricultural production and incomes, increasing risks and disrupting markets (Olsson et al., 2014). 1.2.4

Climate Change and Food Utilization

A proper utilization of food required for attaining nutritional well-being that depends upon water and sanitation will be affected by any impact of climate change on the health of the environment (Wheeler and Braun, 2013). Climate change will affect the ability of individuals to utilize food effectively by altering the conditions for food safety and changing the disease pressure from vector, water, and food-borne diseases (Schmidhuber and Tubiello, 2007). Climate change directly affects safety of the food. The changing climatic conditions can initiate a vicious circle where infectious disease causes or compounds hunger, which in turn, makes the affected populations more susceptible to infectious disease. The result can be a substantial decline in labor productivity and an increase in poverty and even mortality. The increased frequency and severity of extreme weather events due to climate change such as drought, higher temperatures, or heavy rainfalls have an impact on the disease pressure, and there is growing evidence that these extreme changes affect food safety and food security (IPCC, 2007). The report also emphasizes that increases in mean daily temperatures will increase the frequency of food poisoning, particularly in temperate regions. The rising temperatures are reported to be strongly associated with increased incidences of diarrheal disease in adults and children. Similarly, extreme rainfall events can increase the risk of outbreaks of water-borne diseases particularly where traditional water management systems are insufficient to handle the climate extremes (IPCC, 2007). The impacts of heavy precipitations and flooding will be felt more strongly in environmentally degraded areas and where sanitation and hygiene is lacking. All these events will raise the number of people exposed to different diseases and thus lower their capacity to utilize food efficiently. Wheeler and Braun (2013) proposed six general rules on the impact of climate change on food security and actions to address hunger: 1) Climate change impacts on food security will be worst in countries already suffering high levels of hunger and will worsen over time. 2) The consequences for global under nutrition and malnutrition of doing nothing in response to climate change are potentially large and will increase over time. 3) Food inequalities will increase, from local to global levels, because the degree of climate change and the extent of its effects on people will differ from one part of the world to another, from one community to the next, and between rural and urban areas. 4) People and communities who are already vulnerable to the effects of extreme weather now will become more vulnerable in the future and less resilient to climate shocks. 5) There is a commitment to climate change of 20 to 30 years into the future as a result of past emissions of greenhouse gases that necessitates immediate adaptation actions to address global food insecurity over the next two to three decades. 6) Extreme weather events are likely to become more frequent in the future and will increase risks and uncertainties within the global food system.

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All of these general rules support the need for considerable investment in adaptation and mitigation actions to prevent the adverse impacts of climate change on food security and eradicating global hunger and under nutrition.

1.3 Predicted Impacts of Climate Change on Global Agriculture, Crop Production, and Livestock The agricultural sector is directly affected by changes in temperature, precipitation, and CO2 concentrations in the atmosphere, but it also contributes about one-third to total GHG emissions, mainly through livestock and rice production, nitrogen fertilization, and tropical deforestation. Agriculture currently accounts for 5% of world economic output, employs 22% of the global workforce, and occupies 40% of the total land area. In the developing countries, about 70% of the population lives in rural areas, where agriculture is the largest supporter of livelihoods. This sector accounts for 40% of gross domestic product (GDP) in Africa and 28% in South Asia. However, in the future, agriculture will have to compete for scarce land and water resources with growing urban areas and industrial production (Campen, 2011). Creating more options for climate change adaptation and improving the adaptive capacity in the agricultural sector will be crucial for improving food security and preventing an increase in global inequality in living standards in the future (Smith, 2012). Droughts and floods have always occurred at local level, but they are predicted to increase in intensity and frequency over this century. Severe events can devastate agricultural environments, economies, and livelihoods of millions globally. Climate change and disaster risk management are not confined to only some geographic regions. Wheeler and von Braun (2013) point out that the patterns of models on climate change impacts on crop productivity and production have largely remained consistent over the past 20 years, with crop yields expected to be most negatively affected in tropical and subtropical regions and to overlap with countries that already carry a high burden of malnutrition. Projections for the near term (20–30 years) predict that climate variability and extreme weather events will increase and affect all regions with increasing negative impacts on growth and yield, leading to increased concerns about food security, particularly in sub-Saharan Africa and South Asia (Burney et al., 2010; SREX, 2012). Major climate change impacts by 2030 are expected for maize with a 30% yield reduction in South Africa as well as reductions in China, South, and Southeast Asia (Lobell et al. 2008). Production of wheat, rice, millet, and Brassica crops are predicted to be reduced in these regions, by up to 5% in South Asia, with severe impacts in India because of less food per capita (Population Reference Bureau, 2007; Knox et al., 2012). Desert encroachment is expected in the West African Sahel with reduced production of sorghum, although millet and cowpea production may rise. In tropical West Africa, yields of peanuts, yams, and cassava are likely to decline. Central Africa may see reduced production of both sorghum and millet. East Africa may have an increase in yield for barley but a reduction for cowpea (Redden et al., 2014a) In the Pacific Islands and other low-lying island areas, the impacts of erosion, increased contamination of freshwater supplies by saltwater incursion, increased

1.3 Predicted Impacts of Climate Change on Global Agriculture, Crop Production, and Livestock

cyclones and storm surges, heat, and drought stress are all expected to have a negative toll on food production (Barnett, 2007). The growing season is likely to lengthen at high boreal latitudes such as in Nordic Europe, Siberia, Greenland, and Canada. This will result in widening agricultural opportunities, albeit with possible extreme weather fluctuations. Such changes could provide opportunities for underutilized and semi-domesticated local crops, for example, fruit species from Siberia will have the opportunity to be more widely grown in new cultivation niches and also provide benefits for their health food properties (Holubec et al., 2015). Such changes may result in the changing or developing of markets for novel crops and new utilization. 1.3.1

Climate Change Mitigation, Adaptation, and Resilience

The following paragraphs on climate change mitigation, adaptation, and resilience has been reproduced by the author from Chapter 1 on Impact of Climate Change on Agriculture Production, Food, and Nutritional Security (Yadav et al., 2015) in the book on Crop Wild Relatives and Climate Change, First Edition Edited by Redden, Yadav, Maxted, et al. © 2015 John Wiley & Sons, Inc. Published 2015 by John Wiley & Sons, Inc. Never before in the history of humanity has there been such focus by the world scientists and farmers on securing future food production. Poor people and farming communities living in regions already being impacted by climate change are already developing effective community-based adaptation strategies (Ensor and Berger, 2009; IFAD, 2010; Conway, 2012).In other areas identified as being at high risk from the effects of climate change, farmers communities, and villages are being assisted in the development of Climate-Smart Villages (http://ccafs.cgiar.org/climate-smartvillages# Uxl8JreYbcs), while yet others are working to achieve more resilient landscapes by strengthening technical capacities, institutions, and political support for multi-stakeholder planning and governance for Climate-Smart Landscapes (Scherret al., 2012). The challenge is to actively seek strategies to adapt to climate change and ensure that productivity can keep pace with the demand of a growing population within a finite natural resource base (Reynolds and Ortiz, 2010). This will require a holistic and integrated approach, which, among other things, will benefit from the availability of stress-tolerant germplasm. Such strategies need to be linked to more efficient and sustainable crop and natural resource management enabled by effective policy support. This will require a worldwide concerted effort by scientists, farmers, development agencies, and donors, if we are to meet the growing demand for food by ensuring resilient agricultural and food systems Closing the yield gap and increasing crop production will play a pivotal role with greater access to the worlds genetic resources and their enhanced utilization by farmers and breeders of genetic methods worldwide. A better understanding of crop physiology and genetic sequencing technology means that a more targeted approach to selection across multiple traits is now possible, leading to the development of new crop varieties for future challenging environments (Godfray et al., 2010). This will necessitate much greater utilization and sharing of the plant genetic diversity that currently exists in the more than 1700 gene banks globally by the worlds plant breeders (Guarino and Lobell, 2011; McCouch et al., 2013).

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1.3.2

Mitigation

Reynolds and Ortiz (2010) and Cribb (2010) highlight that crop production mitigation strategies include improved soil management practices; mulch and cover cropping; conservation tillage; more efficient N utilization, improved rice cultivation techniques, and improved manure management practices that will reduce methane and nitrous oxide emissions. These will require new crop varieties and different crop combinations and management systems where agronomic practices have been modified (Hodgkin and Bordoni, 2012). Crop production systems may be able to mitigate climate change through the breeding of crop varieties with reduced carbon dioxide and nitrous oxide emissions (Reynolds and Ortiz, 2010). 1.3.3

Adaptation and Resilience

The increased use of agricultural biodiversity, especially plant genetic resources, will play an important role in improving both adaptability and resilience of agricultural systems (Lin, 2011; Hodgkin and Bordoni, 2012). Lin (2011) highlights that crop diversification can increase adaptation and resilience in a range of ways, including enhanced capacity to suppress pest and disease outbreaks, as well as buffering crop production from the impacts of greater climatic variability and extreme weather events. Areas with greater diversity were found to be more resilient and to recover more rapidly in Honduras following recent hurricanes (Hodgkin and Bordoni, 2012). A recent worldwide review of 172 case studies and project reports demonstrate that agricultural biodiversity contributes to adaptation and resilience through a range of strategies, often integrated, that include protection and restoration of ecosystems, the sustainable use of soil and water resources, agroforestry, diversification of farming systems, adjustments in cultivation practices, and the use of crops with various stress tolerances and crop improvement (Mijatovic et al., 2013). While certain levels of adaptation will be achieved by moving new crops and crop varieties to more favorable environments, crop improvement through plant breeding and the incorporation of new genes will be as important (Guarino and Lobell, 2011). Hodgkin and Bordoni (2012) highlight crop traits for adapting to changing climate and changing production environments: pollination and the setting of seed under elevated temperatures and enhanced resilience and adaptability in the face of increasingly variable production conditions and increased frequency of extreme events. We must make much better use of the genetic diversity that currently exists, both in gene banks and in situ. It will require global efforts to secure and safeguard the large amount of crop wild relatives (CWR) (and other Plant Genetic Resources (PGR)) not already in storage and improved availability of prebreeding/germplasm enhancement efforts that can develop novel genetic material (with resistances to changing distributions and populations of insect pests/diseases and tolerances to drought, flooding, salinity, heat, and cold), with systems such as GENESYS to link gene banks and users so information on Plant Genetic Resources (PGR) is more readily available (Guarino and Lobell, 2011; Hodgkin and Bordoni, 2012). Burke et al. (2009) have examined the likely future shifts in crop climates in sub-Saharan Africa and explore what might be the priorities for crop breeding and the conservation of crop genetic resources for agricultural adaptation. They conclude that

1.3 Predicted Impacts of Climate Change on Global Agriculture, Crop Production, and Livestock

most African countries will have novel climates in at least 50% of their current cropping area by 2050. Often, there will be analog climates already existing in the current climates of at least five other countries, this highlights the key role for international movement of germplasm in future adaptation. However, the few existing climate analogs for some countries were largely clustered in the Sahel. Reliance on just three cereals (rice, maize, wheat) and a few other carbohydrate-rich staples might be sufficient to attain food security, but if nutritional security is to be addressed as well, diverse diets that include a range of grains, pulses, fruit, and nutrient-dense vegetables constitute a common-sense approach to good health (Fanzo et al., 2013). The neglected and underutilized species diversity and the range of adaptive traits and characteristics they possess represent an important resource for climate change adaptation. Unfortunately, they remain largely ignored by researchers and policymakers. Increased efforts will be needed to secure diversity of crops and their wild relatives. Climate change threats posed to crop diversity and CWR will require enhanced complementary actions for both in situ and ex situ conservation, which will need to be adapted to face the growing threats posed by environmental and climate change (Hodgkin and Bordoni, 2012). 1.3.4 Policies, Incentives, Measures, and Mechanisms for Mitigation and Adaptation It is likely that future international agreements and collaboration will become even more important between countries and their genetic resources. Future climate scenarios are likely to make countries even less reliant on their own national genetic resources and more dependent on those of other countries. The role of the International Treaty for Plant Genetic Resources for Food and Agriculture (ITPGRFA) and its Multilateral System (MLS) mechanism is therefore likely to become even more important in facilitating this interdependence and collaboration, though a major question remains as to whether the list of crops currently addressed by the treaty is sufficient under changing climate (Hodgkin and Bordoni, 2012). Further, although the treaty has been in force since 2004 and has 121 contracting parties, bottlenecks to facilitated access still remain and will need to be addressed if future access and sharing is expected to intensify (Bjornstad et al., 2013). Regulations and financial incentives to facilitate efforts to improve land management, maintain soil carbon content, and make more efficient use of agricultural inputs, especially fertilizers and irrigation, will be required (Cribb, 2010; Wreford et al., 2010). Lin (2011) points out improvements are urgently required to the policy realm if crop diversification strategies are to be adopted more widely, stressing that to date efforts to promote greater adoption of crop diversification has been slow and attributes this to market incentives only for select few crops, the drive for biotechnology strategies, and a commonly held belief that monocultures are more productive than diversified systems. Financing mechanisms to fund the response to climate change will run into billions of dollars requiring huge transformations in investments across many sectors (IFAD, 2010). Climate change will add dramatically to the cost of doing “development” with between US$49 billion and US$171 billion per year, estimated as required for adaptation alone by 2030. Carbon markets, relevant national policies, multilateral financial institutions, bilateral and multilateral aid agencies all have important roles to play in helping to mobilize the resources required (Wreford et al., 2010).

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1.4 Impact of Divergent & Associated Technologies on Food Security under Climate Change At global level it is not only the research organizations and governmental bodies who are exploring various approaches to increase food production, safe storages of argo-products, divergent utilization of food items, and quality seed production and distribution, etc. Scientific communities are adopting different technologies for maintaining regular and sustainable market supply for consumer satisfaction. Such associated technologies which are in use at different levels and are under development needs a brief discussion at this stage in this chapter. It is important to mention such technologies viz crop rotational impact on crop productivity, sustainable quality seed production and distribution of new varieties of different field crops, sustainable research and development system in field crops, cereals are deficient in amino acids which is compensated by proteins of legumes and vice-versa, seed certification system and seeds legislation, role of improved crop varieties under climate change, role of plant quarantine in agriculture, precision agriculture practices for quality seed production, nutrient and weed management during crop production, etc. are vital for future agriculture production system under climate change globally. Moritz Reckling et al. (2015) suggested that methods are needed for the design and evaluation of cropping systems, in order to test the effects of introducing or reintroducing crops into rotations. The interaction of legumes with other crops (rotational effects) requires an assessment at the cropping system scale. They experimented the integration of legumes into crop rotations and to demonstrate its application. The framework consists of a rule-based rotation generator and a set of algorithms to calculate impact indicators. It follows a three-step approach: (i) generate rotations; (ii) evaluate crop production activities using environmental, economic and phytosanitary indicators; and (iii) design cropping systems and assess their impacts. It was observed that cropping systems with legumes reduced nitrous oxide emissions with comparable or slightly lower nitrate-N leaching and had positive phytosanitary effects. In arable systems with grain legumes, gross margins were lower than in cropping systems without legumes despite taking pre-crop effects into account. Forage cropping systems with legumes had higher or equivalent gross margins and at the same time higher environmental benefits than cropping systems without legumes. Given the negative side-effects of many current agricultural practices, along with changes in both climate and international trade conditions, novel and resource-efficient production methods are needed. In Europe, less than 30% of the plant-based protein supplement fed to livestock is produced within the continent (Bouxin, 2014; Bues et al., 2013). Moreover, rotations have become very narrow and their sustainability is often questioned (Tilman et al., 2002). In order to design more sustainable cropping systems, new methods are required. Interactions between crops are an important component of how changes in cropping systems impact on their agro-economic and environmental performance. Fertilization, nitrogen mineralization, nitrate leaching, greenhouse-gas emissions, infestations with pests, diseases and weeds, and eventual crop yield are all affected not only by the management of the individual crops but also by long-term processes that are influenced by crop sequence (Bachinger and Zander, 2007; Detlefsen and Jensen, 2007; Dogliotti et al., 2003).

1.4 Impact of Divergent & Associated Technologies on Food Security under Climate Change

Sain Dass et al. (2017) in a personal communication observed that the paradigm shift in global agriculture is bound to come when combination of crop productivity positively linked with soil fertility including health, crop growing environment and nutritional security. The favorable combination of all these factors during cropping season will provide a path to sustainable agriculture production system under climate change. To achieve the proposed shift, the role of quality seeds is extremely important to maintain the seed replacement ratio in the agriculture production system and in achieving the higher productivity of different field crops globally. They feel that the combined and integrated approaches during crop cultivation system involving improved crop varieties, maintenance of good soil health, favorable crop-growing environment, appropriate management of plant nutritional security, and planting of quality seed by farming communities under climate change is needed for sustainable agriculture production system to meet the future challenges of food security. Reardon (2016) suggested that the supply chain transformation can move the world toward greater food security. For small-scale farmers and rural entrepreneurs, the road to alleviating poverty and increasing incomes will increasingly run through cities. To meet urban food needs and realize the promise of agriculture for reducing global poverty, it is critical that the development of food systems includes small farmers and the small rural enterprises along the supply chain. 1.4.1

Integrated Pest Management (IPM)

“a strategy which combines all practical methods of managing pests including biological, cultural, physical and chemical methods in a manner that attains the producer’s production goals while minimizing economic, health and environmental risks” For example, approximately 18% crop yield loss occurs annually due to pest incidence in India alone, and the situation at global level is not much different than India. In a personal communication and discussion with D.B. Ahuja, Director, National Centre for Integrated Pest Management, Indian Agricultural Research Institute, New Delhi, India, (Email:deshbandhu4@rediffmail.com Web: www.ncipm.org.in) such damages were discussed, which suggested that these crop yield losses are of high order but differ, however from place to place and year to year. Under climate change such losses needs to be minimized so that the potential crop yield can be harvested and can be utilized to meet the food security challenges globally. 1.4.2

Technological Options for Boosting Sustainable Agriculture Production

It is now clearly understood that under climatic change there will be a great demand for quality and for nutritive food products to meet the challenges of food security at global level. Thus, technological options which have been developed internationally should be explored for public adoption globally. The major technologies involve those targeting hybrid, quality seeds, climate smart production technologies like conservation agriculture, water efficient technologies like drip/sprinkler irrigation and laser levelling, crop intensification and diversification like cropping and farming systems, Biofortified food like quality protein maize (QPM) and micronutrient enriched food, food processing and value chain management like silos, storage infrastructure and their maintenance, food processing, cold chain management, etc. All such technologies are potential source for increased agriculture production and food security under climate change.

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1.4.3

Mechanization in Agriculture Sector

The labor requirement in agriculture is a big challenge among farming communities to carry out the various field operations during cropping season at global level. These challenges under climate change will create more and more difficulties in field operations for increased food production. Thus, it is important to understand the nature of these challenges for the production systems of various field crops. If these challenges worked out scientifically and adopted at village levels systematically then food production can be sustained successfully under climate change. Thus, farm machineries for land preparation, planting operations, intercultural, harvesting, threshing, seed processing, seed storages, transportation, etc. are important for small and large holding farmers separately. With the utilization of suitable farm machineries at village levels, the labor cost can be minimized, optimization in various field operations can be achieved, farm efficiency can be increased manyfold, irrigation system can be efficiently improved, and crop diversification can be achieved. All such activities will promote a sustainable agriculture production system including productivity, profitability, and stability at farm level and will enhance the food and nutritional security under climate change. 1.4.4

Food Processing and Quality Agro-Products Processing

Under climate change it is imperative that postharvest technologies including food processing and development of value addition chain of agro-products is important for food security. The life style is changing globally, rapid urbanization is happening, while increased literacy, women in the workforce, rising per capita income, etc. are leading to rapid growth and new opportunities in the agriculture sector globally. With these changes the challenges in the food sector are increasing day by day. Thus, it is imperative to bring rapid transformational changes in the food processing sector and in establishing the value addition chain of various quality agro-products globally to meet the big challenges of food and nutritional security under climate change. The transformational changes are more relevant during storages of such agro-products and distribution among consumers at city and village levels throughout the world. Additional financial obligations and resources are needed for the establishment of new processing and storage facilities which should be ensured by the world leaders in respective countries in each continent. This will ensure sustainable food and nutritional security under climate change at global level in the years to come. Judith Ann Francis and Arnold van Huis (2016) suggested that the task of achieving sustainable intensification of agriculture is now one of the greatest intellectual, social and economic challenges to feeding a world population that is projected to reach 9 billion by 2050. While yields can be increased using available technologies (e.g. certified seeds, irrigation and small-scale machinery) – for example cereals in Sub–Saharan Africa (SSA) under traditional low-input production systems yield less than 1 t/ha – the reality is that this will not be simple. Success will depend on the nature of the policy and institutional framework, the physical and human infrastructure, as well as the ease with which knowledge, financing and markets can be accessed, and the assurance that remunerations for public and private investors, including smallholder farmers, will be attractive under internationally accepted trading norms. To achieve the goal of inclusive development, the various options (technological, social, environmental

1.5 The Government of India Policies and Programs for Food Security

and economic) will have to be assessed rigorously through the active engagement of multiple stakeholders and by embracing different perspectives. 1.4.5 Planning, Implementing and Evaluating Climate-Smart Agriculture in Smallholder Farming Systems Rioux et al. (2016) under mitigation of climate change in agriculture for a FAO book series wrote on planning, implementing, and evaluating Climate Smart Agriculture (CSA) in Smallholder Farming Systems (SFS) and suggested imported ideas. Many smallholder farmers in developing countries are facing food insecurity, poverty, the degradation of local land and water resources, and increasing climatic variability. These vulnerable farmers depend on agriculture both for food and nutrition security and as a way of coping with climate change. If agricultural systems are to meet the needs of these farmers, they must evolve in ways that lead to sustainable increases in food production and at the same time strengthen the resilience of farming communities and rural livelihoods. Bringing about this evolution involves introducing productive climate-resilient and low-emission agricultural practices in farmers’ fields and adopting a broad vision of agricultural development that directly connects farmers with policies and programs that can provide them with suitable incentives to adopt new practices. The term “climate-smart agriculture” (CSA) has been coined to describe the approach that aims to achieve global food security and chart a sustainable pathway for agricultural development in a changing climate. CSA seeks to increase farm productivity in a sustainable manner, support farming communities to adapt to climate change by building the resilience of agricultural livelihoods and ecosystems, and, wherever possible, to deliver the co-benefit of reduced GHG emissions. CSA is an approach that encompasses agricultural practices, policies, institutions and financing to bring tangible benefits to smallholder farmers and provide stewardship to the landscapes that support them. On the ground, CSA is based on a mix of climate-resilient technologies and practices for integrated farming systems and landscape management. The evidence base and knowledge to determine the practices that work best in a given context continue to be expanded through the testing and implementation of a broad range of practices. This work is creating a better understanding about the trade-offs that may need to be made when striving to meet the interconnected goals of food security, climate change adaptation and climate change mitigation, and about the synergies that exist between these.

1.5 The Government of India Policies and Programs for Food Security To achieve stable food and nutritional security in India, the government of India has implemented various policies and options from time to time. The major policies are (i) National Food for Work Programme (NFFWP); (ii) Antyodaya Anna Yojana (AAY); (iii) Village Grain Banks Scheme; (iv) Integrated Child Development Scheme (ICDS); (v) Essential Commodities Act – 1955; (vi) National Food Security Mission (NFSM) – 2007; (vii) National Food Security Mission–Rice (NFSM–Rice);

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(viii) National Food Security Mission–Wheat (NFSM–Wheat); (ix) National Food Security Mission – Pulses (NFSM Pulses); (x) minimum support price for different field crops; (xi) grain procurement of major field crops by government of India; and (xii) public distribution of major food grains at low cost to the public at national level, etc. In achieving stable food & nutritional security under climate change it is suggested that internationally such policies can be implemented by various governments at world level.

1.6 Conclusions Keeping in view the various situations of climatic changes and their implications on agriculture production, food, and nutritional security at global level, it is evident that climate change will bring a major change around the world. Climate change will affect not only the food supply and nutritional availability to humans, but also the sustainability of crop production, standards in livestock production, and harmony of socioeconomic environments. Future increase in agriculture production, productivity, and profitability is extremely important to maintain harmonies among different stakeholders at village, district, province, national, and international levels. Utilization of available genetic diversity in general and CWR specifically has not been used extensively and intensively to raise the genetic yield potential of different field crops globally. Importantly, CWR possess hardy gene pools for survival in adverse and harsh environmental conditions. CWR need to be utilized as a priority in crop breeding improvement programs internationally. Climate change and biodiversity are closely linked and each impacts the other. Biodiversity is threatened by human-induced climate change, but biodiversity reduces the impact of climate change. The presence of healthy biodiversity builds natural resilience to climate extremes: for example, forests are nature’s social security check in times of disaster and crisis; they also act as a sink for harmful GHG emissions. In years to come, it is important that the increasing world population get the sufficient nutritive food for the survival of mankind. It is possible only when the genetic yield potential of future varieties is increased significantly by crop professionals, sustained by farming communities, and supported by cropping managers globally. In this dynamic and innovative system, there is a need for strong linkages between national and international research organizations, crop improvement managers, policy makers, crop management specialists, national and international traders, and farming communities at global level. Keeping in mind the sustainability of food production the various approaches like (i) efficient and prudent use of inputs and judicious use of pesticides, herbicides and fertilizers may be advocated; (ii) adapting to climate change using ecological, genetic, and socioeconomic approaches; (iii) minimizing emissions of greenhouse gases like methane, nitrous oxide, and carbon dioxide (CO2 ); (iv) strengthening resilience; (v) reducing environmental impact; and (vi) soil moisture and natural enemies of pests shall be protected.

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Long, S.P., Zhu, X., Naidu, S.L. et al. (2005) Limits to efficiencies of primary production: constraints and opportunities. In Yields of farmed species (eds R. Sylvester-Bradley and J. Wiseman), pp. 167–191. Nottingham, UK, Nottingham University Press Magliulo, V., Bindi, M. and Rana, G. (2003) Water use of irrigated potato (Solanumtuberosum L.) grown under free air carbon dioxide enrichment in central Italy. Agriculture Ecosystem and Environment, 97, 65–80. Manderscheid, R., Pacholski, A. and Weigel, J. (2010) Effect of free air carbon dioxide enrichment combined with two nitrogen levels on growth, yield and yield quality of sugar beet: evidence for a sink limitation of beet growth under elevated CO2 . European Journal of Agronomy, 32, 228–239. McCouch, S., Brute, G.J., Bradeen, J. et al. (2013) Feeding the future. Nature, 499, 23–24. McGrath, J.M., Betzelberger, A.M., Wang, S. et al. (2015) An analysis of ozone damage to historical maize and soybean yields in the United States. Proceedings of the National Academy of Sciences, USA, 112:14390–14395. Mijatovic, D., Van Oudenhoven, F., Eyzaguirre, P. and Hodgkin, T. (2013) The role of agricultural biodiversity in strengthening resilience to climate change: Towards and analytical framework. International Journal of Agricultural Sustainability, 11, 95–107. Misselhorn, A., Aggarwal, P., Ericksen, P. et al. (2012) A vision for attaining food security. Current Opinion in Environmental Sustainability, 4, 7–17. Monks, P.S., Archibald, A.T., Colette, A. et al. (2015) Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer. Atmospheric Chemistry and Physics, 15, 8889–8973 Nelson, G.C., Rosegrant, M.W., Koo, J. et al. (2009) In Climate change: impact on agriculture and costs of mitigation. Washington, DC: International Food Policy Research Institute. Olsson, L. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects (eds Field, C. B. et al.) 793–832 (IPCC, Cambridge Univ. Press, 2014). Parry, M. L., Rosenzweig, C., Iglesias, A. et al. (2004) Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Global Environmental Change—Human Policy Dimensions, 14, 53–67. Ramankutty, N., Evan, A.T., Monfreda, C., and Foley, J.A. (2008) Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles, 22, 1003. Reardon, T.A. (2016) Suggested that the supply chain transformation can move the world toward greater food security, Progress report on GROWING FOOD FOR GROWING CITIES by The Chicago Council on Global Affairs, 332 South Michigan Avenue, Suite 1100, Chicago, Illinois 60604–4416. Access at thechicagocouncil.org/ globalagedevelopment. Reckling, M., Hecker, J.-M., Bergkvist, G. et al. (2015). A cropping system assessment framework—Evaluating effects of introducing legumes into crop rotations, European Journal of Agronomy, 12 pp. Access www.elsevier.com/locate/eja. Redden, B., Yadav, S.S., Hatfield, J.L. et al. (2014a) Global climate change and food security, Chapter 8. In “Temperature and Plant Development”. Eds K.A. Franklin, P.A. Wigge. Wiley Blackwell & Sons, Inc. Ames Iowa, USA) pp. 181–202. Reynolds, M.P. & Ortiz, R. (2010) Adapting crops to climate change: a summary. In: Reynolds, M.P. (ed), Climate change and Crop Production. CABI, pp. 1–8.

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World Bank (2010) World Development Report 2010: Development and Climate Change. World Bank, Washington, DC Yadav, S.S., Hunter, D., Redden, R. et al. (2015) Impact of Climate Change on Agriculture Production, Food, and Nutritional Security, Crop Wild Relatives and Climate Change, Eds R. Redden, S.S. Yadav, N. Maxted et al. (2015) John Wiley & Sons, Inc. pp. 1–23.

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2 Changes in Food Supply and Demand by 2050 Timothy S. Thomas 1 1

International Food Policy Research Institute (IFPRI), Washington, DC, USA

2.1 Introduction With global population projected to grow by close to 2.3 billion people between 2010 and 2050, demands on the food system will be great. The number of mouths to feed will grow by a third in that 40-year period, and they will have to be fed with little expansion in cultivated land — most of the growth in food production will need to come by increasing productivity. With the effects of climate change already being felt, and with much greater effects projected by 2050, will the challenges be too great? Will there be enough food to feed the planet? In particular, will the poorest people be able acquire enough food when demand will be great, and the expansion of supply somewhat limited? On the other hand, global per capita income is expected to rise by more than 150% between 2010 and 2050, suggesting that consumers will have a much greater ability to purchase food, if the real prices (adjusted for inflation) do not rise too drastically. Furthermore, agricultural productivity growth between 1970 and 2010 was quite robust, and it will be important to discover whether losses from climate change will negate gains from technological development (genetic improvement) and yield growth brought about by targeted fertilizer use and better agronomic practices. Changes between 2010 and 2050 will not be uniform throughout the globe. First of all, rates of growth in population and GDP will differ markedly across regions. Secondly, climate change will affect different regions in different ways. Temperature changes are projected to be very different depending upon where one lives. The impact of a rising temperature is also inconsistent across regions. Areas that are already relatively hot will likely experience reduction in agricultural productivity due to increased heat stress, among other stresses. But cooler climates at present might benefit from a little more warmth — a rise in temperatures might actually boost agricultural productivity. Precipitation will also change with many complex regional variations which are much more difficult to characterize than for temperature. This chapter will answer some of the questions posed in this introduction, with regional differentiation of the effect of climate change on agricultural production and food security. A bioeconomic model is applied to consider the countervailing forces of increased demand for food from population and income growth, on the one Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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2 Changes in Food Supply and Demand by 2050

hand, and changes in supply from modest changes in cultivated area, increases due to technological improvements in farming, and decreases (in most cases) due to climate change.

2.2 Model Description The International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) is a global, partial equilibrium, multi-market model focusing on food and agriculture (Robinson et al., 2015). It includes 159 countries that are intersected with major river basins to form the 320 units of analysis called FPUs (food production units). IMPACT has 62 commodities (39 crop, 6 livestock, and 17 processed). The IMPACT model uses the GAMS program (General Algebraic Modeling System) to solve a system of supply and demand equations for equilibrium world prices for commodities. IMPACT incorporates alternate assumptions on changes in population and GDP from the IPCC AR5 report (O’Neill et al., 2012), along with elasticities of supply and demand, and assumptions about agricultural productivity growth for each country. It is important to remember that with any model, the results are driven by the inputs, and so the IMPACT model will be sensitive to the selection of elasticities and exogenous productivity growth. However, the parameters for IMPACT have been carefully selected, and the model has been calibrated and compared against results from other models, so there is reason to trust the projections given by IMPACT. Essential inputs into IMPACT include distribution of harvested areas for each crop from Map-SPAM You, Wood, Wood–Sichra, and Wu (2014), a water model which focuses on availability of water for irrigation, and inputs from a biophysical analysis done on the world’s leading crops using the Decision Support System for Agro technology Transfer (DSSAT) software (Jones et al., 2003) to simulate yields at each half degree square for the climate circa 2000 and the climate circa 2050. The yields for the two years are compared, and these changes provide IMPACT the climate effects that it incorporates within the broader economic and demographic context. IMPACT generates results for agricultural yields, area, production, consumption, prices and trade, as well as indicators of food security. While the IMPACT model produces results at the FPU and country level, space does not permit us to report results for every country. Instead, we choose to aggregate the results by region, and highlight particularly significant countries. In particular, we focus much attention in this chapter on China and India, as the world’s two most populous countries, and ones with great economic significance, as well.

2.3 Model Assumptions 2.3.1

Economic and Demographic Assumptions

In the analysis presented in this chapter, we use the shared socioeconomic pathway (SSP) 2 from the IPCC AR5. This is the ‘middle of the road’ scenario from among the five IPCC socioeconomic scenarios, and has moderate growth in both GDP and population, and with trends of recent decades continuing (O’Neill et al., 2012). Choosing a middle of the

2.3 Model Assumptions

27

road socioeconomic pathway allows us to focus the analysis on the impacts of climate change. Table 2.1 shows the main assumptions for SSP2 for the regions of the world, highlighting India and China. In 2010, the table shows how concentrated the world’s population is in Asia and the Pacific, especially in the world’s two most populated countries, China and India, with the two representing more than 46% of the global total. By 2050, this is projected to fall to just under a third of the world’s population, with China projected to decrease in size and India’s percentage growth between 2010 and 2050 being less than half of what is projected for Sub-Saharan Africa, which is expected to more than double in size, thus adding more than 900 million people to the planet. In comparison India is expected to add 509 million people. We also see in Table 2.1 that in 2010, Asia and the Pacific is responsible for the highest percentage of the world’s GDP, with 35%. The Americas come in second at just under 30%, and Europe and the Former Soviet Union (FSU) third at almost 26%. China itself generated 15% of the GDP, while India generated just over 5%. With the projections of SSP2, however, things will change considerably by 2050. At that point, Asia and the Pacific are projected to generate almost half of the global GDP, with China generating almost a quarter of the world’s GDP itself, and India generating close to an eighth, slightly higher than that projected for the United States. Sub-Saharan Africa is projected to more than double its GDP share by 2050, rising from 2.5% to 6.0%. Table 2.1 GDP, GDP per capita, and population in 2010 and growth in 2010–2050. Population

World

GDP

GDP per capita

Millions

Growth, percent, 2010–2050

Dollars (billions)

Growth, percent, 2010–2050

Dollars

Growth, percent, 2010–2050

2010

SSP2

2010

SSP2

2010

SSP2

6875.0

33.4

67 550.8 242.4

9826 156.7

East Asia

1550.8

−6.1

15 465.6 302.9

9973 328.9

China

1348.9

−5.6

10 190.3 424.0

7554 455.2

South Asia

1629.9

45.6

4461.0 638.4

2737 407.2

India

1224.6

41.6

3653.1 653.8

2983 432.5

633.0

27.0

3769.5 370.8

5955 270.8

239.9

Southeast Asia & Pacific

19.9

929.9 581.3

3877 468.4

Sub-Saharan Africa

Indonesia

858.9 106.8

1695.6 714.1

1974 293.7

Middle East & North Africa

457.1

56.5

4550.5 309.4

9956 161.6

Latin America & the Caribbean

584.7

26.8

5834.4 228.5

9978 159.0 10 093 139.9

Brazil North America USA Former Soviet Union Russia Europe

194.9

18.9

1967.5 185.3

344.5

30.6

14 291.1 109.4

41 489

60.3

310.4

29.6

13 087.1 108.5

42 164

60.8

278.9

−0.6

2854.6 214.7

143.0

−4.4

537.2

7.4

2015.1 180.7 14 628.5

89.9

10 234 216.6 14 096 193.5 27 230

76.8

28

2 Changes in Food Supply and Demand by 2050

Table 2.2 Climate impacts on temperature: base level and projected changes to mean daily maximum temperature for the warmest month, 0 C. 2000

Change, 2000–2050

Base

GFDL

Had-GEM

IPSL

MIROC

25.6

2.0

3.8

3.3

3.9

25.0

2.1

3.7

3.1

4.5

China

25.1

2.2

3.7

3.1

4.5

South Asia

35.6

2.5

3.1

3.4

3.7

India

36.8

2.2

2.9

3.1

3.4

33.1

2.4

2.9

3.1

2.4

30.2

1.5

2.4

2.3

2.0

World East Asia

Southeast Asia & Pacific Indonesia Sub-Saharan Africa

34.4

2.4

3.3

2.9

3.1

Middle East & North Africa

37.9

3.0

4.3

3.8

4.0

Latin America & the Caribbean

30.1

2.3

3.5

3.0

3.8

31.9

2.2

4.1

2.7

4.7

North America

16.4

1.6

3.6

3.2

3.5

United States

26.4

2.6

4.7

3.5

4.6

Former Soviet Union

21.2

1.6

4.4

3.7

5.0

Russian Federation

19.6

1.4

4.2

3.7

5.1

21.0

2.1

4.6

3.6

4.8

Brazil

Europe

While Europe and North America are projected to continue growing, their shares in total global GDP which each fall by 40% or more. The FSU and Latin America and the Caribbean (LAC) will not change much in their shares, and the Middle East and North Africa (MENA) will grow modestly, from 6.7% to 8.1%. In terms of GDP per capita, China and India are both projected in the SSP2 to have phenomenal growth, exceeding 400% in the 2010 to 2050 period. In comparison, the United States and Europe are projected to have growth of less than 80%. Sub-Saharan Africa is projected to have growth at just under 300%, indicating significant catching up being done, yet their GDP per capita will still lag significantly behind LAC and even South Asia. Russia and the rest of FSU are projected to make significant progress in reaching parity with European countries.

2.4 Climate Assumptions General circulation models (GCMs) are developed by climate scientists to determine how climate might change in response to greenhouse gas (GHG) accumulation in the upper atmosphere. In this chapter, we will sometimes write "climate models" when we are referring to GCMs. The IPCC has a process by which teams submit models for use in their assessment reports. In the AR4, there were 24 models. In the AR5, this grew to 61 models. We chose four GCMs developed for the IPCC’s AR5 report. They were chosen primarily because they were used by the AgMIP GGCMI and included in the data (in addition

2.4 Climate Assumptions

to temperature and precipitation) were values for changes to solar radiation — a variable that is required by the DSSAT crop model that we used to generate the estimates of the direct climate impact on agricultural productivity. • GFDL-ESM2M. Produced by the National Oceanographic and Atmosphere Administration General Fluid Dynamics Laboratory (Dunne et al., 2012; Dunne et al., 2013); • HadGEM2-ES. Data from the Met Office Hadley Centre (Collins et al., 2011; Martin et al., 2011); • IPSL-CM5A-LR. Generated by the Institut Pierre-Simon Laplace (Dufresne et al., 2013); • MIROC-ESM-CHEM. From the Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies (Sakamoto et al., 2012). Table with temperature and precipitation changes, and perhaps baseline temperature. The IPCC established four Representative Concentration Pathways, which are a set of assumptions about the pattern and quantity of GHG emissions to 2100. In this chapter, we focus on the high emissions case, which is RCP8.5, to provide a sense of the full range of possible climate change impacts. Table 2.2 shows an overview of an important temperature variable by region, and how the different climate models suggest that will change by 2050. This particular variable is the mean daily maximum temperature of the warmest month. The warmest month often encompasses the growing season, and since high temperatures are known to limit yields (see, for example, Lobell et al., 2011), and since climate change will almost always lead to even higher temperatures and hence an increase in constraints to productivity growth, this is generally an important variable. One difficulty, however, in interpreting the table is that the base values include areas that are currently too cold for cultivation: much of Alaska, for example, in the case of the United States. For this reason, the values do not necessarily reflect temperatures for currently cultivated areas. Nonetheless, the temperature changes will give us some indication of the type of stress that each country and region might face. Table 2.2 reveals that on average, the GFDL climate model projects the lowest warming of the four, with the global increase being only 2.0 degrees. MIROC and HadGEM, on the other hand, project almost twice that, at 3.9 and 3.8 degrees. IPSL is the moderate projection, at 3.3 degrees. Not all regions will warm at the same rate. FSU is projected to increase by 5.0 degrees between 2000 and 2050, in the MIROC GCM. Close behind are Europe, Brazil, the U.S., and China at 4.8, 4.7, 4.6, and 4.5 degrees. The HadGEM GCM projects a slightly lower increase for FSU, at 4.4 degrees, but has the US showing a higher 4.7 degrees increase. Even the IPSL suggests that the US, FSU, MENA, and Europe will have the largest warming. Sub-Saharan Africa (SSA) is projected to receive below average warming in all but the GFDL model, yet the projected warming for SSA in the GFDL model is still lower than what is projected for SSA in the other three GCMs. Table 2.3 shows the projected changes in annual precipitation from the four GCMs. As with temperature, globally, the projected changes are smallest for the GFDL GCM. The IPSL GCM seems to show sizeable increases in precipitation for India, Indonesia, and Brazil. But the climate models differ significantly for key countries. Brazil, for example, despite having a very large projected increase in the IPSL model, is projected to actually

29

30

2 Changes in Food Supply and Demand by 2050

Table 2.3 Climate impacts on annual precipitation: base level and projected, mm. 2000 Base

World East Asia

Change, 2000–2050 GFDL

Had-GEM

IPSL

MIROC

698

17

39

56

48

560

30

63

28

36 34

China

557

30

67

30

South Asia

908

−18

157

242

64

India

1119

−40

235

338

93

1240

−45

14

55

19

2641

2

85

391

156

Southeast Asia & Pacific Indonesia Sub-Saharan Africa

825

−1

15

79

53

Middle East & North Africa

140

−17

−9

−14

−12

Latin America & the Caribbean

1440

18

−11

67

−64

1743

−16

−42

297

−157

North America

555

33

71

56

96

United States

680

29

6

14

42

Former Soviet Union

406

45

55

47

81

Russian Federation

422

51

65

56

93

742

9

−9

46

61

Brazil

Europe

decrease in the other three models, with the MIROC model showing a decrease that is half the magnitude of the increase projected by the IPSL. Projections for India are very diverse, ranging from a 40 millimeter decrease to a 338 millimeter increase, and the other values spaced relatively evenly in between. Indonesia ranges from a 2 millimeter increase to a 391 millimeter increase. China has much more modest increases projected, and the four models are similar to each other in projecting Chinese rainfall. The same may be noted for the US and FSU, and only slightly less so for Europe.

2.5 Results 2.5.1

Production

Global productivity (yield/ha) of almost every crop has risen over the past 40 years, in some cases at quite large and sustained rates. Maize productivity has risen at above 1.9% per year for both the 1970 to 1990 period and the 1990 to 2010 period. Rice and wheat productivities, on the other hand, while showing positive growth throughout, grew much faster in the 1970 to 1990 period than in the 1990 to 2010 period, with both growing above 2.0% (wheat above 2.5%) in the former period, while both were under 1.2% in the latter period (FAO, 2013). While there might be reason to believe that the rate of growth globally might slow as more nations catch up to the productivity possibility frontier, apart from shocks from climate change, we would expect that agricultural productivity will continue to increase.

2.5 Results

31

Table 2.4 shows results projected by the IMPACT model for changes in wheat production between 2010 and 2050 (given the assumptions specified earlier in this chapter). Globally, we note that under this particular scenario (SSP2, RCP8.5), climate change is expected to give a small but positive boost for wheat production across all four climate models that we used. The rule of thumb appears to be that for wheat production, temperate countries will benefit from climate change while tropical countries will be hurt. Just because the impact of climate change on global wheat production is positive does not mean that climate change will not adversely impact production in key locations. India, in particular, a key producing nation for wheat, will suffer yield/ha reductions from climate change of 15% to around 20% relative to levels projected for 2050 in the absence of climate change. Nevertheless, growth in productivity (due to technological and agronomic improvements, and response to prices) is projected to be highest in India — at just over 80% — so that even factoring in climate change, wheat productivity growth should still be above 50%. Table 2.4 Changes in Wheat Production from 2010 to 2050. Yield 2010

% change, 2010–2050

Production Productivity effect of climate change, 2050

With Without climate tons / climate change, hect change median Min

World

Median Max

2010

2010– 2050

Harvested area 2010

2010– 2050

hect, megatons % chg millions % chg

3.0

36.6

39.9

1.2

2.4

2.7

648.5

43.5 218.2

4.6

8.9

27.4

11.7

16.9

20.4

105.9

11.4

23.2

−12.9

China

4.6

8.9

27.2

11.7

16.9

20.3

104.7

11.4

22.7

−12.7

South Asia

2.7

74.4

45.7

−20.2 −16.5

−15.2

104.3

64.9

38.8

13.0

India

2.8

84.2

51.6

−20.2 −17.7

−15.7

76.4

85.1

26.9

21.5

1.6

57.9

0.4

−43.3 −36.4

−2.0

19.7

−11.3

12.7

−11.6

−24.1 −16.3

East Asia

SE Asia & Pacific

2.3

SSA

2.2

68.5

41.0

−6.5

6.8

80.2

3.1

27.8

MENA

2.5

50.1

56.5

2.5

4.3

4.7

69.7

61.5

27.9

3.0

LAC

2.7

42.9

36.9

−11.4

−4.2

−1.8

27.3

64.1

10.0

19.8

2.0

52.1

22.6

−26.3 −19.4

−7.9

4.7

35.6

2.4

10.2

2.9

48.5

74.1

9.2

17.3

20.1

84.5

70.8

29.5

−3.1

2.9

36.8

52.2

9.8

11.3

14.6

57.0

40.0

19.9

−8.8

Brazil North America USA

Former Sov. Union 1.9 Russia Europe

34.1

51.9

11.5

13.2

15.4

87.5

66.5

46.0

9.1

1.9

36.3

50.9

6.4

10.8

12.9

45.8

68.9

23.7

12.5

5.3

19.0

25.9

2.9

5.8

8.7

142.7

15.5

27.0

−8.0

Notes: Data for 2010 is based on modeling projections from FAOSTAT data averaged over a 3-year period to remove year-to-year variations, and is meant to be used as a reference level. Production and harvest area changes show the combined effect of productivity enhancements and climate impacts, and are calculated at the median level across the four climate models used.

32

2 Changes in Food Supply and Demand by 2050

Table 2.5 shows that unlike for wheat as a winter/cool season crop, climate change will have unequivocally negative impact on productivity of rice as a summer crop which is more exposed to heat stress, though the level of change is projected to be less than 10% even for the most negative model. Rice productivity losses in China should be more modest, at around 2% (range −5.3% to +0.7%). However, as for wheat, reductions in yield for India should be larger than most nations, with projected climate impacts ranging from 18.9% to 21.7%. Growth in agricultural productivity (Due to technical and agronomic gains and response to price changes) is projected to be more modest than for wheat at the global level, at 26.3%. Gains for India are much lower for rice than for wheat, at 30.9%. But gains for China (due to technical and agronomic gains but ignoring the effect of climate change) are modestly higher for rice than wheat, 11.3% to 8.9%, while production is projected to drop by less than 1% at the median climate change, and this because declines in harvested area should offset gains in yields. A number of currently small producers of rice — Sub-Saharan Africa, Europe, and the Former Soviet Union — are projected to have their cultivated areas increase by larger Table 2.5 Changes in Rice Production from 2010 to 2050. Yield

2010

% change, 2010–2050

Production Productivity effect of climate change, 2050

With Without climate tons / climate change, hect change median Min

World

Median Max

2010

2010– 2050

Harvested area

2010

2010– 2050

hect, megatons % chg millions % chg

2.9

26.3

16.2

−8.9

−8.0

−5.9

435.3

4.1

12.2

10.8

−4.5

−1.2

1.0

129.2

0.6

31.8

−9.3

China

4.1

11.3

9.4

−5.3

−1.8

0.7

117.4

−0.6

28.6

−9.1

South Asia

2.3

32.5

8.5

−19.2 −18.1

−15.8

132.0

11.1

57.7

1.6

India

2.2

30.9

4.3

−21.7 −20.3

−18.9

92.0

3.7

41.9

−1.0

East Asia

SE Asia & Pacific Indonesia

17.9 152.8

1.5

2.8

32.2

25.0

−7.8

−5.5

−5.2

126.2

24.4

44.8

−0.2

3.2

40.6

38.5

−3.0

−1.5

0.5

37.9

38.0

11.7

−0.4 48.7

SSA

1.3

98.5

97.4

−1.8

−0.6

0.7

11.2

193.1

8.4

MENA

4.7

17.2

20.7

2.4

3.0

4.3

7.2

39.2

1.5

14.6

LAC

3.0

24.2

26.1

−0.3

1.6

1.9

19.1

16.4

6.4

−7.7

−7.5

Brazil

2.6

28.2

25.8

−1.9

0.6

9.5

9.0

3.6

−13.4

5.5

43.5

25.1

−19.9 −12.8

−7.8

7.2

47.4

1.3

17.8

5.5

43.5

25.1

−19.9 −12.8

−7.8

7.2

47.4

1.3

17.8

Former Sov. Union 2.9

70.9

73.9

−0.2

1.8

6.5

1.2

131.0

0.4

34.4

3.2

34.3

27.2

−7.3

−5.3

0.2

0.5

55.3

0.2

22.3

4.6

46.4

50.8

0.8

3.0

5.6

2.0

121.9

0.4

46.1

North America USA Russia Europe

Notes: Data for 2010 is based on modeling projections from FAOSTAT data averaged over a 3-year period to remove year-to-year variations, and is meant to be used as a reference level. Production and harvest area changes show the combined effect of productivity enhancements and climate impacts, and are calculated at the median level across the four climate models used.

2.5 Results

33

percentages (34.4% to 48.7%) — but some of the larger producers like China, India, and countries in the Southeast Asia and Pacific region, are projected to have their rice areas decline slightly. Table 2.6 shows that relative to what we observed with rice and wheat, global maize productivity is projected to be more adversely affected by climate change between 2010 and 2050, with the median loss projected to be more than 20%. Also relative to rice and wheat, the range of projections of the climate impact on productivity is much larger, ranging from a loss of 9.4% to a loss of 24.2%. Another notable difference between the three grains is that global maize area is projected to rise by almost 25%, while the area change for both wheat and rice is near 2%. Climate change is projected to have a more negative effect on maize yields in temperate countries (except Europe) than for tropical countries. This reflects the sensitivity of maize to heat and the fact that maize in temperate countries is generally grown in the summers for which temperatures can get quite high.

Table 2.6 Changes in Maize Production from 2010 to 2050. Yield

2010

% change, 2010–2050

Production Productivity effect of climate change, 2050

With Without climate tons / climate change, hect change median Min

World

Median Max

2010

2010– 2050

Harvested area

2010

2010– 2050

hect, megatons % chg millions % chg

5.1

41.3

12.2

−24.2 −20.6

−9.4

754.9

41.7 149.3

5.4

40.3

17.0

−23.8 −16.6

−7.1

147.3

49.1

27.3

26.8

China

5.4

40.2

16.8

−23.8 −16.7

−7.1

145.4

49.9

26.8

27.6

South Asia

2.2

67.1

37.4

−28.5 −17.8

−9.0

21.5

87.0

9.9

36.7

India

2.0

80.8

56.0

−26.7 −13.7

−10.0

15.2

119.0

7.7

40.3

3.3

30.2

2.9

−23.9 −21.0

−17.4

29.2

21.0

8.7

19.7

3.6

18.4

−5.4

−26.6 −20.1

−16.1

12.3

0.9

3.4

9.9

East Asia

SE Asia & Pacific Indonesia

24.8

SSA

1.6

49.7

29.8

−15.4 −13.2

−10.6

44.8

47.6

27.6

15.6

MENA

6.5

41.4

19.2

−17.9 −15.7

−11.4

14.1

57.8

2.2

32.3

LAC

3.5

54.5

31.3

−16.5 −15.0

−12.5

98.2

89.5

28.1

46.6

3.4

60.9

23.4

−28.0 −23.3

−20.0

43.9

91.2

12.8

56.8

10.0

39.1

7.2

−32.0 −22.9

−9.0

310.8

29.1

31.0

20.4

Brazil North America USA Former Sov. Union Russia Europe

10.1

39.5

6.4

−32.7 −23.7

−9.5

302.0

28.1

30.0

20.4

4.1

59.9

27.0

−31.5 −20.6

−16.3

16.0

57.3

3.9

23.6

4.4

75.9

34.3

−34.5 −23.6

−17.5

4.2

80.9

1.0

33.5

6.8

25.8

12.5

−25.3 −10.6

−9.3

72.8

12.4

10.6

0.8

Notes: Data for 2010 is based on modeling projections from FAOSTAT data averaged over a 3-year period to remove year-to-year variations, and is meant to be used as a reference level. Production and harvest area changes show the combined effect of productivity enhancements and climate impacts, and are calculated at the median level across the four climate models used.

34

2 Changes in Food Supply and Demand by 2050

Table 2.7 shows changes the IMPACT model projects for soybean production between 2010 and 2050. We note a more modest growth in TFP and price responsiveness than for any of the three grains we have considered, with global production increasing by 20.6% in that timeframe. The climate models give conflicting projections for impact on soybean productivity globally, with the median value being negative, but the most optimistic projection being positive. At the median value for climate impact, yields/ha for the world are projected to increase by only 12.8%. Climate change is projected to help China’s soy crop production, increasing it by 13.4% more than without climate change. India, on the other hand, is projected to be adversely impacted in regard to their soy crop production, losing 12.2% as a result of climate change, which is large enough to overwhelm the positive change in TFP, resulting in a net decline in productivity between 2010 and 2050.

Table 2.7 Changes in Soybean Production from 2010 to 2050. Yield

2010

% change, 2010–2050

Production

Productivity effect of climate change, 2050

With Without climate tons / climate change, hect change median Min

World

Median Max

2010

2010– 2050

Harvested area

2010

2010– 2050

hect, megatons % chg millions % chg

2.4

20.6

12.8

−9.3

−6.5

3.0

231.6

49.5

96.9

1.7

11.1

25.7

9.1

13.1

14.7

18.4

45.9

10.8

17.9

China

1.7

10.6

25.5

9.2

13.4

14.9

17.7

46.5

10.3

18.7

South Asia

1.0

10.8

−2.7

−14.3 −12.2

−11.6

8.6

30.5

8.3

35.4

India

1.0

10.9

−2.6

−14.4 −12.2

−11.6

8.6

30.9

8.3

35.6

East Asia

SE Asia & Pacific Indonesia

32.6

1.4

2.0

−8.5

−20.9 −10.3

−2.4

1.7

5.1

1.2

15.4

1.3

5.9

−5.4

−17.6 −10.7

−3.7

0.8

14.4

0.6

20.9 −4.8

SSA

1.1

29.1

28.3

−0.6

3.3

1.3

22.6

1.2

MENA

2.9

9.2

−2.9

−13.7 −11.0

−8.9

0.3

26.8

0.1

32.0

LAC

2.5

20.7

13.9

−14.2

−5.6

7.4

102.7

66.2

41.9

46.0

2.5

22.0

8.8

−21.2 −10.8

1.3

57.5

63.0

23.1

49.6

Brazil North America USA

3.0

23.4

15.4

−15.5

−6.5

−2.4

95.0

35.7

31.4

22.4

3.0

24.1

15.6

−15.6

−6.9

−2.5

91.6

37.0

30.2

23.3

Former Soviet Union 1.3 Russia Europe

−4.1

19.3

33.9

7.4

12.3

17.9

1.6

24.3

1.2

−4.6

1.1

21.4

39.3

13.6

14.8

20.2

0.8

35.3

0.7

−2.9

2.9

23.1

17.8

−12.5

−4.3

0.4

1.9

29.4

0.7

10.6

Notes: Data for 2010 is based on modeling projections from FAOSTAT data averaged over a 3-year period to remove year-to-year variations, and is meant to be used as a reference level. Production and harvest area changes show the combined effect of productivity enhancements and climate impacts, and are calculated at the median level across the four climate models used.

2.5 Results

Soybean area is different than most of the other crops, in that most of its growth in production comes from an increase in area rather than from productivity increases. It is projected to grow globally more than any of the three grains considered, to 32.5% more area in 2050 than in 2010. Together with the positive yield/ha change, this should result in almost a 50% increase in global production. It is, however, important to keep in mind that IMPACT considers total harvested area, and the earlier comment about limited expansion of agricultural land was referring to physical area. In many countries, increasing harvested area will come about as a result of increasing the cropping intensity (having more than one planting per year on a given piece of land, such as a rotation of maize in the summer and wheat in the winter). Table 2.8 shows the changes in production by commodity group and region. Overall, oil crops and sugar crops are projected to increase in production by the highest percentage from 2010 to 2050. As we saw from Table 2.7, soybean production increase will be at a much smaller rate that the 90% increase projected for oil crops, which points to the fact that most of the expansion in production will come from oil palm production, which is projected to grow by 174% between 2010 and 2050. Much of that growth will come from Southeast Asia and the Pacific, including Indonesia, which produces roughly half of the region’s oil crops. By 2050, the region will produce almost 50% of the world’s oil crops. We have already considered three grains in detail, but it would be important to mention that the fastest growth rate for grain production is projected for Sub-Saharan Africa, which is projected to more than double its production in that period. They are followed closely by the Former Soviet Union (especially Russia) and LAC, including Brazil. SSA is projected to become the leading producer of pulses by 2050, not only because they are a major producer now, but also because they are projected to have the highest growth rate of any region. The United States and Brazil are also projected to grow at a fast rate between 2010 and 2050 in their production of pulses, but together they had less than 10% of global production in 2010, while SSA had 17.6% in the same year. China and the rest of East Asia is also projected to grow rapidly in their pulse production. India and SSA are projected to more than double their production of roots and tubers (which includes potatoes, cassava, sweet potatoes, and yams), though in 2010, SSA produced 28.7% of the world’s total, while India produce only 5.0%. By 2050, SSA is project to grow 42% of the world’s roots and tubers. All regions will expand their production of sugar crops, though the most rapid expansion will more than double production in LAC, MENA, and FSU. But while MENA and FSU have only slightly above 3% of global production of sugar crops each, LAC has more than 40%, and is the prime reason global sugar production will likely expand so rapidly. In Table 2.8, "Other crops" includes coffee, cocoa, tea, and cotton. The table shows global production is projected to grow by 50% between 2010 and 2050. Expansion is projected to be most rapid in SSA and MENA. Production is projected to decline in India by 34.4%. This result is driven primarily by cotton and other crops besides tea, coffee, and cocoa. The decline is caused more by a reduction in projected cultivated area than by a decline in yield/ha. Global production of fruits and vegetables is projected to increase by more than 80% between 2010 and 2050. China is already a major producer, with over a third of the global production. It is projected to increase at a slower pace than the rest of the world, at just over 50%. On the other hand, in 2010, India produced less than a quarter of the fruits and vegetables that China produced, but is projected to grow at almost 3 times the rate

35

36

2 Changes in Food Supply and Demand by 2050

Table 2.8 Patterns of Global Production by Commodity Group, from 2010 to 2050. Cereals Production, kilotons 2010

World East Asia

2050

2157.6 3052.3 394.3

484.2

Pulses

Production, kilotons % change, 2010– 2010 2050 2050

Oil crops Production, kilotons % change, 2010– 2010 2050 2050

% change, 2010– 2050

41.5

66.3

118.6

78.7

673.3

1280.6

90.2

22.8

5.8

11.8

102.2

49.1

69.7

41.8 42.0

China

378.7

466.9

23.3

5.4

10.6

95.0

48.3

68.6

South Asia

279.1

375.9

34.7

15.6

22.8

45.8

41.1

51.8

26.1

India

203.6

285.7

40.3

13.9

20.1

44.7

36.8

46.4

26.3

SE Asia & Pacific

186.7

226.7

21.4

6.9

7.5

8.8

231.5

586.8 153.4

Indonesia

50.1

64.6

28.9

0.4

0.4

23.2

113.9

293.3 157.5 113.6 115.0

Sub-Saharan Africa

114.4

239.3 109.2

11.7

27.6

135.4

52.8

MENA

114.6

180.0

57.1

4.0

6.3

56.9

8.5

13.2

LAC

164.3

286.4

74.3

6.9

14.2

105.6

125.7

211.3

68.1

61.8

109.7

77.6

3.7

8.1

119.0

62.5

104.7

67.5

Brazil North America USA Former Sov. Union Russia Europe

436.1

637.9

46.3

6.9

12.9

85.8

109.7

149.6

36.4

382.9

506.6

32.3

2.6

5.6

113.9

96.0

133.3

38.9

157.2

279.4

77.7

3.3

5.6

68.2

14.5

24.0

65.4

79.3

151.4

91.0

1.9

3.3

75.7

7.4

12.8

73.9

311.0

354.1

13.9

5.1

9.5

84.8

40.3

59.5

47.6

Roots and tuber Production, kilotons

World East Asia

54.6

Fruits and vegetables

Production, kilotons % change, 2010– 2010 2050 2050

Sugar crops

Production, kilotons % change, 2010– 2010 2050 2050

% change, 2010– 2050

2010

2050

779.8

1142.2

46.5

180.8

186.6

3.2

607.4

925.3

52.3

115.2

171.6

49.0

177.3

1591.7 2894.9

81.9

1810.8 3347.5

84.9

China

173.0

2.5

569.1

861.2

51.3

109.0

159.9

46.7

South Asia

50.3

103.2 105.3

157.8

377.4 139.1

330.9

526.1

59.0

India

39.2

83.5 113.0

132.5

330.1 149.0

267.1

399.3

49.5

67.3

74.5

10.6

100.9

167.9

66.5

202.9

339.2

67.2

25.7

29.1

13.4

26.7

49.6

85.5

32.9

57.1

73.7

479.3 114.0

101.4

298.1 193.9

81.8

161.1

96.8

55.5

121.3 118.5

SE Asia & Pacific Indonesia

Sub-Saharan Africa 224.0 MENA

21.2

29.6

40.0

150.9

377.8 150.4

LAC

59.9

100.3

67.6

164.3

281.1

71.1

750.1 1522.4 103.0

30.6

40.4

31.9

53.0

90.3

70.2

502.0 1058.7 110.9

Brazil North America USA Former Sov. Union Russia Europe

26.2

36.1

38.0

91.0

138.8

52.5

65.7

130.4

98.4

21.2

30.8

45.5

87.6

125.3

43.0

64.9

128.8

98.6

121.1 108.0

82.3

83.2

1.1

62.0

103.6

67.1

58.2

40.3

32.0 −20.5

21.5

37.9

76.1

30.2

59.1

95.8

67.9

51.5 −24.2

155.9

231.1

48.2

150.4

258.0

71.6 (continued)

2.5 Results

37

Table 2.8 (Continued) Other crops Production, kilotons 2010

World East Asia

2050

116.7 175.0

% change, 2010– 2050

50.0

Meats Production, kilotons 2010

2050

274.1 456.2

Milk and eggs

% change, 2010– 2050

66.4

Production, kilotons 2010

2050

773.4 1215.6

% change, 2010– 2050

57.2

21.9

31.4

43.8

78.6

91.7

16.6

79.4

157.0

China

21.4

30.9

44.2

73.2

83.3

13.8

64.4

137.8 113.8

South Asia

24.4

19.2

−21.5

9.9

30.8

210.6

154.7

350.1 126.3

India

16.7

10.9

−34.4

5.9

19.9

234.9

115.4

295.9 156.3

16.3

20.3

24.9

20.5

42.5

107.5

34.6

5.2

7.4

43.5

2.8

7.2

160.7

2.3

SE Asia & Pacific Indonesia Sub-Saharan Africa MENA LAC Brazil North America USA Former Sov. Union Russia Europe

52.1

97.7

50.8

4.7 104.3

12.5

28.1

124.8

10.9

34.4

217.0

29.1

62.2 113.6

7.3

16.2

121.2

10.8

31.1

188.5

42.0

90.7 115.9

13.4

22.5

67.9

44.1

84.0

90.6

81.7

120.9

47.9

7.9

13.8

74.3

22.6

41.5

83.8

30.4

49.8

63.9

11.9

22.9

92.4

45.2

72.5

60.4

100.0

122.0

22.0

11.8

22.7

92.1

40.5

66.1

62.9

90.9

107.8

18.6

5.9

8.2

40.8

10.0

13.5

34.6

70.8

61.2 −13.6

0.1

0.1

−6.8

5.2

5.6

8.7

34.0

25.7 −24.4

3.1

5.1

67.9

44.2

55.8

26.2

181.1

199.5

10.2

Notes: Data for 2010 is based on modeling projections from FAOSTAT data averaged over a 3-year period to remove year-to-year variations, and is meant to be used as a reference level. Values for 2050 are from the IMPACT model and represent the median value across four GCMs.

of China — nearly 150%. SSA is projected to become the fastest growing region for food and vegetable production, almost tripling between 2010 and 2050. China produces over a quarter of the world’s meats, but expansion of meat production there will be relatively slow at 13.8% relative to the increase for the world, which is projected to be 66.4% between 2010 and 2050. India produces only a small portion of the world’s meat, at just over 2%, but it is projected to grow very rapidly. In fact, South Asia and Sub-Saharan Africa are projected to more than triple their meat production. Still, by 2050, East Asia and the Americas will lead global production, with Europe trailing somewhat behind, not keeping base with growth in the Americas. South Asia is currently the leading region for production of milk and eggs, and the projection from modeling indicates that this dominance will actually increase through to the middle of the century. Chinese production of milk and eggs has been relatively modest compared to their production of meat, but they are projected to more than double production by 2050. SSA and MENA are also projected to more than double their production.

38

2 Changes in Food Supply and Demand by 2050

2.6 Underutilized Crops As climate change challenges the ability of scientists to adapt varieties of major grains and pulses to heat, drought, floods, and salinity stresses, and as nations endeavor to increase cropping intensity so that land can produce more food, there appears to be opportunity for currently underutilized crops, many of which have thrived for millennia and can do well in harsher environmental conditions. Underutilized crops have been defined as “minor crops that are already cultivated, but are underutilized regionally or globally given their still relatively low global production and market value” (Ebert, 2014). There are several crops that are of primarily regional use, but which might be expanded to other regions. Teff, for example, is grown in Ethiopia and is the mainstay of their diet, but is now even grown in parts of the United States as a rainfed crop that can be cultivated in places where maize and other grains would have required irrigation. There are also crops like the azuki beans, grown in East Asia; bambara groundnuts, grown in West Africa; tepary beans in the United States; lima beans, from Peru and the United States; and rye, principally grown in Northern Europe. In addition to adapting species to new locations, there would also be a need to help the species become better developed for the region which is currently using it, especially as it pertains to helping the underutilized species adapt to climate change. These changes will not likely come about unless there is investment in research to expand the use of these crops in other areas, and in breeding tolerances to abiotic stresses in new varieties of these crops. It is even possible that the underutilized crops will decrease in use rather than increase. As climates change, the niche that they currently fill may disappear. In such a case, if there is continued desire to use the crop, investment in developing new varieties will be required. While it would be difficult to call millet underutilized in some regions, in other regions it is, and might be a viable substitute for maize in places like East and Southern Africa if scientists are unable to breed maize better adapted to the changing climate there. Millet is also known for its high nutritional content and could prove to be a good supplement to many diets. In fact, most underutilized crops have higher nutritional content than standard crops, either in regard to vitamins or minerals or amino acids. As incomes of households rise throughout the world, the importance of quality diets rises — with quality referring to nutritional content, as well as to diversity, taste, and texture of the food. One of the characteristics of an underutilized species is that the scientific community has devoted little attention to the crop, so there has been little or no work in developing varieties with improved yield/ha. That may create a steeper learning curve for plant breeders, especially if they are trying to adapt a variety to a different soil or climate than the crop originally was used for. Finally, underutilized species serve to provide plant diversity that is an insurance against new diseases developing and spreading to significantly reduce the productivity on one of the major species used by the global food system.

2.7 Consumption Now that we have examined projections for agricultural production, it is time to turn our attention to consumption, which includes the use of agricultural products for food for

2.7 Consumption

people, for use in producing biofuels, and for livestock feed. Since this chapter focuses on food security, we will not focus on biofuels, but rather on food and feed (since livestock and livestock products are consumed by people). Table 2.9 shows the composition of food consumption by region in 2010 and projection for 2050. Grains are a critical part of diets in many regions. Globally, consumption (by weight) is projected to grow by a third. Among the regions, the largest percentage growth in consumption of grains is projected for Sub-Saharan Africa, which is projected to grow by 127% between 2010 and 2050. It is also the largest quantitative increase in consumption of any region, growing by more than 135 megatons per year. India is projected to increase consumption by 44%, which is an increase of almost 107 megatons per year. China is actually projected to drop in consumption of grains by almost 8%, as they diversify consumption into other commodities. By weight, in 2010 consumption of pulses globally is less than a fifth of the consumption of grains, yet they are an important component of the human diet, since they provide vegetable protein. South Asia, led by India, is the leading region for pulse consumption, consuming almost 36% of the global total. By 2050, global consumption of pulses should grow by close to 90%, led by SSA, which will grow by 187% and increase by 16.8 megatons. South Asia will grow by 12.0 megatons, a 78% increase over 2010. China will grow at a more modest rate of around 35% from 2010 to 2050, but it consumes so few pulses — less than 2% of the global total — that the quantitative increase is extremely small. On the other hand, China is one of the leading consumers of oil crops, at almost a third of the global consumption. Global consumption is projected to rise by almost 50% by 2050, led by SSA, which should see increases of around 178%. Both MENA and South Asia, especially India, will also likely experience significant increases in food consumption. Roots and tubers can be a significant portion of a person’s diet in many countries. SSA is not only the largest global consumer of roots and tubers, with more than 28% of the world’s roots and tubers being consumed there, but it is also projected to be the fastest growing region, more than doubling its consumption of roots and tubers. South Asia, Including India, is projected to grow and a rapid rate, though it only has a small portion of the global total now. Global consumption of fruits and vegetables as food is projected to increase by more than 82%, though not all regions project this. Both South Asia and Sub-Saharan Africa are projected to grow the fastest between 2010 and 2050, each growing at around 300%. East Asia, led by China, currently consumes 40% of the world’s fruits and vegetables, but with a relatively small growth rate of 16% projected between now and 2050. While India represents a relatively small share in global fruit and vegetable consumption, by 2050 it will have almost a quarter of the global consumption. According to the IMPACT model, the world will increase by almost 67% in its consumption of meats and will grow by 56% in its consumption of milk and eggs. This is a positive sign that because the economy is projected to keep improving globally, households will be able to include more proteins in their diets. While the average person will have more protein, it is important to keep in mind that the model does not tell us anything about how these changes are distributed in a country. That is, if a higher portion of the protein is consumed by the segment of population that had the lowest protein consumption (i.e. the poorest), then this would be an even better result from a nutritional perspective. But, as may well be the case, it could be that the increase will

39

40

2 Changes in Food Supply and Demand by 2050

Table 2.9 Patterns of Global Food Consumption by Commodity Group, from 2010 to 2050. Cereals megatons 2010 2050

World East Asia

Pulses

megatons % change, 2010– 2010 2050 2050

Oil crops megatons % change, 2010– 2010 2050 2050

% change, 2010– 2050

989.3 1321.5

33.6

42.8

81.0

89.5

46.7

69.9

49.6

225.3

206.9

−8.2

2.4

3.0

26.7

16.9

21.2

25.2

34.9

15.1

19.4

28.6

5.8

9.4

63.5

China

201.0

185.7

−7.6

1.8

2.5

South Asia

242.1

349.0

44.2

15.3

27.3

India

176.0

242.8

37.9

13.0

22.5

72.9

4.2

7.8

84

100.2

127.6

27.4

2.0

3.1

56.6

8.3

11.3

36

32

0.3

0.5

67.1

3.8

4.4

15.6

9.0

25.8

187.1

5.1

14.3

178.3

SE Asia & Pacific Indonesia

43.4

57.2

78

Sub-Saharan Africa

106.5

242.0 127.3

MENA

92.1

136.0

47.6

3.8

7.1

90.1

2.2

4.0

86.5

LAC

74.9

92.0

22.9

6.6

10.1

51.9

3.9

4.2

7.6

22.6

26.3

16.8

3.3

4.7

43.2

2.7

2.7

2.4

Brazil North America USA

37.3

47.1

26.4

1.6

2.2

36.2

2.4

3.1

26.6

33.3

41.1

23.5

1.4

1.8

34.3

2.2

2.8

25.4

Former Soviet Union 45.2 Russia Europe

47.6

5.3

0.4

0.5

8.7

0.3

0.3

3.5

21.2

20.4

−3.9

0.3

0.3

8.2

0.2

0.2

−2.1

65.8

73.3

11.4

1.7

2.0

17.2

1.8

2.0

12.1

Roots and tubers megatons 2010 2050

World

Fruits and vegetables

megatons % change, 2010– 2010 2050 2050

kilotons % change, 2010– 2010 2050 2050

46.1

110.7 103.7

−6.3

544.7

628.4

15.4

4018

4151

3.3

China

103.9

97.6

−6.1

504.6

589.3

16.8

2610

2855

9.4

South Asia

44.4

85.4

92.2

167.6

660.3 294

4722

8129

72.1

India

34.9

66.0

89.4

142.1

578.3 306.9

3649

5628

54.2

23.7

31.5

32.8

84.8

161.1

89.9

3026

4864

60.7

12.6

83.3

SE Asia & Pacific Indonesia

82.5

31 411 46 116

% change, 2010– 2050

447.5 653.7

East Asia

1349.5 2462.4

Other crops

46.8

15.2

20.6

24.6

54.9 123.5

1008

1848

Sub-Saharan Africa

126.5 273.5

116.3

84.2

333.6 296.4

2133

5924 177.7

MENA

17.8

27.4

53.7

123.6

206.9

2946

4760

LAC

29.9

34.6

15.8

93.3

147.6

58.2

3008

4296

42.8

12.0

12.2

1.5

30.6

44.4

45.1

1150

1535

33.5

Brazil North America USA Former Sov. Union Russia Europe

67.4

61.6

21.8

26.6

22

80.5

118.7

47.4

3592

4678

30.2

19.2

23.1

20.6

72.3

106.8

47.8

3200

4151

29.7

32.2

29.4

−8.6

50.7

66.3

30.9

1341

1983

47.8

18.9

17.3

−8.3

24.8

32.9

32.8

811

1187

46.4

40.5

41.5

2.6

120.1

139.5

16.2

6623

7332

10.7 (continued)

2.7 Consumption

41

Table 2.9 (Continued) Meats megatons 2010

World East Asia China

2050

Milk and eggs

% change, 2010– 2050

megatons 2010

2050

% change, 2010– 2050

56.2

Sugar megatons 2010

2050

% change, 2010– 2050

271.2 451.5

66.5

649.6 1015.0

142.7 255.9

79.4

87.6 117.9

34.5

84.7

180.2 112.8

13.3

20.8

56.3

78.9 106.4

34.9

70.1

166.7 137.9

10.1

17.4

73.1

South Asia

9.6

40.2 317.9

127.6

235.0

84.2

30.7

70.7 130.6

India

5.8

27.9 383.3

92.3

169.2

83.3

24.1

55.7 131.6

18.2

39.8 118.2

18.9

32.9

74.1

12.4

23.1

2.9

8.1 180.1

3.6

SE Asia & Pacific Indonesia

7.2 101.5

3.8

86.6

7.8 105.1

Sub-Saharan Africa

11.2

47.9 326.5

32.0

80.9 152.9

9.7

28.6 193.6

MENA

13.0

30.2 133.1

40.5

65.1

60.7

13.0

29.3 125.4

LAC

35.9

56.5

57.3

70.6

104.5

47.9

22.9

33.4

46.1

16.0

23.6

47.6

27.0

46.6

72.9

8.1

10.3

27.7

Brazil North America USA Former Soviet Union Russia Europe

40.5

54.0

33.3

93.1

120.6

29.5

11.6

16.1

38.1

37.3

49.2

32.2

85.8

110.4

28.7

10.3

14.1

37.9

12.8

16.5

28.2

48.4

48.3

−0.2

10.4

12.7

21.7

7.6

8.9

17

24.4

23.8

−2.4

6.4

7.5

16.6

42.2

48.5

14.8

133.8

147.5

10.2

18.6

21.2

14.0

Notes: Data for 2010 is based on modeling projections from FAOSTAT data averaged over a 3-year period to remove year-to-year variations, and is meant to be used as a reference level. Values for 2050 are from the IMPACT model and represent the median value across four GCMs.

only benefit the wealthiest or those who already had enough protein in their diets. In fact, one of the problems associated with increasing incomes is the higher incidence of obesity, while in many cases, the same country continues with high incidence of household food insecurity. Consumption of meats is projected to more than quadruple in South Asia and Sub-Saharan Africa, but both consume right around 4% each of meats globally, so the fast rise doesn’t cause the entire global consumption to grow by a similar percentage. Meat consumption in China is projected to grow modestly, increasing by just over one third between 2010 and 2050, similar to projections for North America. Human consumption of sugar and edible oils will also grow globally, with oil consumption increasing by about two-thirds, and sugar by just under 80%. Sub-Saharan Africa is projected to lead the way by almost tripling consumption of both oils and sugar. Currently India consumes almost one-sixth of the world’s sugar, and it is projected to grow to almost 22% by 2050. Table 2.10 shows changes in global livestock feed components between 2010 and 2050. Some of the largest changes will come about because of climate change, which is projected to have a larger negative impact on global maize productivity than on the productivity of most other crops. In 2010, the amount of maize used for feed was greater than for the next four feed components combined.

42

2 Changes in Food Supply and Demand by 2050

Table 2.10 Changes in Components of World Livestock Feed, from 2010 to 2050. % change, 2010–2050

Tons

2010

Productivity effect of climate change, %, 2050

Without climate change

With climate change, median

Min

Med

Max

−12.7

Maize

458 261

89.7

47.3

−28.1

−22.4

Wheat

106 748

22.6

70.3

15.8

38.9

65.2

Barley

101 380

53.4

72.7

9.3

12.6

16.4

Soybean meal

149 488

45.7

43.1

−2.6

−1.8

−0.1

79 973

47.6

42.0

−7.0

−3.8

−3.5

Cassava

Ignoring climate change, maize usage in feed would grow quite a bit faster than any of the other big 5 components in livestock feed. However, with climate change, growth in maize for livestock feed will be about half of what it would be without climate change, and will grow slower than both wheat and barley, and about the same pace as soybean meal and cassava.

2.8 Trade and Prices Results from the IMPACT model on net trade (i.e. exports minus imports) are contained in Table 2.11 (positive numbers are net exports and negative are net imports). Just as in the other tables showing IMPACT model results, the 2010 figures are "modeled" data rather than actual data. That is, the IMPACT model is based on 2005 data, and then models each year thereafter until 2050, solving for what the production and consumption of each country and region should have been, given the assumptions concerning GDP, population, climate and weather, and development of agricultural technology. The 2010 data should be close to the 2005 data, which is not data for a single year, but instead is an average over adjacent years, to smooth out year-to-year variation. The column which has "% of cons / prod" is a measure of how important trade of the commodity is for the country or region. It is simply a percentage showing the net imports (exports) divided by total consumption (production). For cereals, we see that in the base year, North America is a huge exporter, and the MENA, East Asia (but not China), and Sub-Saharan Africa are the leading importers. IMPACT projects much of that to shift by 2050. While North America will continue to be the lead exporter, the former Soviet Union will also be a major exporter of cereals. MENA and SSA will be virtually tied for the leading importers, but East Asia will be a net exporter instead of importer, though most of that will be due to a large increase in cereal exports from China. While India’s net trade of cereals was practically nil in 2010, but 2050, it is projected to be a major importer of cereals, leading South Asia to come in a close third for the region with the largest cereal imports. What is also noteworthy about the modeled results for 2050 is the increase in the importance of trade for the world. The ratio of trade to either consumption or

2.8 Trade and Prices

43

Table 2.11 Net trade, 2010 and 2050. Cereals

Pulses

2010 % of cons / prod

Net trade

East Asia China

2050

−42 485

9.8

2010 % of cons / prod

Net trade

1779

0.4

2050 % of cons / prod

Net trade

448

7.7

% of cons / prod

Net trade

5522

46.8 47.5

1427

0.4

54 062

11.6

735

13.5

5042

South Asia

−5247

1.9

−114 421

23.8

−2866

15.5

−10 644

31.9

India

−497

0.2

−64 964

18.7

−1933

12.2

−7670

27.5

8439

4.5

−19 589

8.1

1929

28.0

−365

4.6 33.7

SE Asia & Pacific

−8656

14.8

−20 336

23.9

−33

8.5

−216

Sub-Saharan Africa

Indonesia

−33 734

23.7

−130 198

35.6

−881

7.1

−8666

23.9

MENA

−59 242

35.0

−132 096

43.0

−996

20.3

−3218

34.4

LAC

−23 390

12.5

−45 032

13.8

−679

9.0

2664

18.8

Brazil North America USA Former Soviet Union Russia Europe

−5722

8.5

−29 711

21.5

93

2.5

2967

36.5

124 078

28.5

293 536

46.0

3853

55.7

8760

68.1

103 517

27.0

206 848

40.8

1037

39.4

3557

63.2

22 806

14.5

141 053

50.5

433

13.1

2858

51.2

12 485

15.7

90 722

59.9

149

8.0

1697

51.8

8775

2.8

−10 415

3.0

−1241

20.9

2920

30.7

Roots and tubers 2010 Net trade

East Asia China

−18 555

Fruits and vegetables

2050 % of cons / prod

9.3

2010 % of cons / prod

Net trade

8250

Net trade

4.4

−21 958

2050 % of cons / prod

3.5

% of cons / prod

Net trade

176 918

19.1 18.3

−15 552

8.2

8674

4.9

−15 453

2.6

157 371

South Asia

−6257

11.1

−24 830

19.8

−26 686

14.5

−340 409

47.6

India

−5607

12.5

−19 552

19.4

−24 635

15.7

−298 906

47.7

19 863

29.5

11 009

14.8

5177

5.1

−15 483

8.5 19.3

SE Asia & Pacific Indonesia Sub-Saharan Africa MENA LAC Brazil North America USA Former Soviet Union Russia Europe

1856

7.2

−1392

4.5

−379

1.4

−11 741

−1079

0.5

−27 182

5.4

−3100

3.0

−116 113

28.2

−796

3.6

−4596

13.3

4071

2.7

131 963

34.9

241

0.4

27 374

27.3

46 340

28.2

94 595

33.7 38.3

188

0.6

7581

18.8

15 127

28.5

34 603

−456

1.7

2964

8.2

2650

2.9

7711

5.6

−1979

8.5

2198

7.1

7934

9.1

6860

5.5

8543

10.4

19 538

23.5

221

0.4

22 008

21.2

3137

7.8

26

0.1

−8106

28.0

−1424

3.7

−1504

2.2

−15 185

23.0

−6716

4.1

40 964

17.7

(continued)

44

2 Changes in Food Supply and Demand by 2050

Table 2.11 (Continued) Meats

Milk and eggs

2010

Net trade

East Asia

2050

% of cons / prod

Net trade

2010 % of cons / prod

Net trade

2050 % of cons / prod

Net trade

% of cons / prod

−9189

10.5

−26 390

22.3

−12 757

13.9

−35 120

18.3

−5758

7.3

−23 170

21.7

−10 972

14.6

−37 901

21.6

South Asia

280

2.8

−9455

23.5

−3678

2.3

36 835

10.5

India

162

2.7

−8041

28.8

−1334

1.1

61 777

20.9

China

SE Asia & Pacific Indonesia Sub-Saharan Africa MENA LAC Brazil North America USA Former Soviet Union Russia Europe

1979

9.7

2219

5.2

10 215

29.6

10 727

20.6

−129

4.5

−899

11.2

−1634

41.8

−3452

42.6

−392

3.5

−13 548

28.3

−5702

16.4

−26 212

29.7

−2320

17.7

580

1.9

−6519

13.5

9337

10.3

7133

16.2

25 354

30.2

−1583

1.9

−2910

2.4

6609

29.3

17 911

43.2

−188

0.6

−2467

4.7

4353

9.6

18 097

25.0

−501

0.5

−8446

6.5

3095

7.6

16 573

25.1

−458

0.5

−9875

8.4

−3008

23.2

−3225

19.4

2950

4.2

−4276

6.5

−2497

32.8

−3341

37.5

−990

2.8

−6527

20.2

1164

2.6

6339

11.4

17 574

9.7

20 193

10.1

Notes: Values for 2050 are from the IMPACT model and represent the median value across four GCMs. "% of cons / prod" is calculated as 100 times the absolute value of net trade divided by total consumption if net trade is negative (i.e. net importer) and as net trade divided by total production (i.e. net exporter). In the former, it is the percent of consumption that is imported, and in the latter, the percent of production that is exported.

production increased in every region except East Asia. For places like LAC, the increase was modest, but for places like the former Soviet Union and South Asia, it was a very large percentage increase. Trade in pulses seems modest in 2010 relative to trade in cereals, but that is largely because the consumption and production of pulses is also modest in comparison. North America is the leading exporter, and in addition to the leading quantity of pulses exported, it also leads in percentage of production that is exported. South Asia, led by India, is the leading importer of pulses. By 2050, the percentage of pulse production exported by North America will have grown to the point that over two-thirds of its production will be sent abroad. Importation of pulses will be led by South Asia (including India) and SSA. China will have greatly increased its exportation of pulses, exporting almost 50% of its production by 2050. For roots and tubers, Southeast Asia and the Pacific is the leading exporter, followed by the former Soviet Union. The leading importer is East Asia (particularly China), followed by a large margin by South Asia, led by India. By 2050, China will be a net exporter, while India will increase their imports of roots and tubers. But despite a large increase there, Sub-Saharan Africa will increase even more, and become the world’s leading importer.

2.8 Trade and Prices

Also, LAC will become the world’s leading exporter of roots and tubers, followed by the former Soviet Union. Southeast Asia and Pacific will still export, but not nearly as much as in 2010. In 2010, both China and India were leading importers of fruits and vegetables, though China’s imports were less than 3% of their total consumption of fruits and vegetables. By 2050, however, China will become the world’s leading exporter of fruits and vegetables, exporting almost 20% of its production, while India will have greatly expanded its importing of fruits and vegetables, to almost 50% of its total consumptive needs. In 2010, Latin America and the Caribbean led the world in exports of fruits and vegetables. By 2050, they will expand to double the quantity of total production, and have increased the percent of production which is exported. Still, it will be second to East Asia in exports. Europe will go from a net importer to a net exporter, and SSA will grow to the second leading importing region by 2050. Trade in meats appears to be modest in 2010. The leading export region is LAC, exporting almost a sixth of its production, and led by Brazil, which exports just under 30% of its production. East Asia is the leading importer of meats, led by China. India and South Asia are net exporters of meats, though only a small percentage of world production. The former Soviet Union is the second leading importer of meats by volume, and the leading importer by percent of consumption. By 2050, exports of meats will grow in both LAC and North America. Chinese imports of meats will quadruple, and India will become a significant importer of meats, though not as much as Sub-Saharan Africa, which will be second only to East Asia. In regard to livestock products other than meat — in the IMPACT model, these consist of milk and eggs — Europe is the world’s leading exporter, followed by Southeast Asia and the Pacific. China (along with East Asia) is the world’s leading importer, followed by MENA and SSA. India is a very modest importer. By 2050, India will be among the world’s leaders of milk and egg exports, and South Asia, as a region, will lead the world. Europe’s exports will not change much, so is projected to be the second leading region. China is projected to increase its imports of milk and eggs, and SSA will more than quadruple its imports. To summarize the findings from Table 2.11: apart from milk and eggs, India will rely on imports to supply a higher share of its consumptive needs by 2050 than other regions do (e.g. 29% in the case of meat). China, on the other hand, is projected to be able to supply most of its crop demands for food, but not its food from livestock (i.e. meat, milk, and eggs). Sub-Saharan Africa in 2010 imported modest quantities of each of the commodity groups in Table 2.11, but by 2050, will increase imports dramatically. We observed early that agricultural production will grow there, but both population and income will grow so rapidly there that demand growth will exceed productivity growth, especially when climate change is accounted for. Table 2.12 shows changes in the world prices of various commodities in real terms. The first column of percentages shows the effect of changing incomes, population, tastes, and productivity between 2010 and 2050 without considering climate change. The second column of percentages shows the median impact of climate change along with the other effects between 2010 and 2050. The last column isolates the climate effect only between 2010 and 2050. We see in the table that excluding climate change, there is modest price growth expected for all commodities, with sugar, coffee, and maize leading the way (though

45

46

2 Changes in Food Supply and Demand by 2050

with many commodities not far behind). However, the productivity shocks brought about by climate change will lead to an additional price effect that is higher than 40% for maize and groundnuts. Rice and soybeans trail much further back as the only other two that are above 20%. Earlier, we saw that Table 2.1 shows that most regions will have incomes more than double by 2050 (except for North America and Europe). However, we also see now that the welfare gains from rising incomes will be offset by significant increases in the price of food – particularly for the poorest, who spend a disproportionate share of their incomes on food. As the baseline increases in price are combined with the increases from climate change, real maize prices are projected to almost double in 2050 relative to current levels. Rice and groundnut prices are projected to increase by nearly 60%. Despite income growth, if income inequality increases in a particular country, it is possible that the risk of hunger would grow for the poorest segments of that population.

2.9 Food Security For a measure of food security, we will use share of the population at risk of hunger (Fischer et al. 2005). The results for these statistics from the IMPACT model are in Tables 2.13 and 2.14. In 2010, Table 2.13 tells us that there were 922.7 million at risk of hunger. Of this number, almost a third are from South Asia, with India representing almost a quarter of the global total. Sub-Saharan Africa came in second behind South Asia, with 21.8% of the world’s at risk population. East Asia was third with 18.9 % of the world’s at-risk population, with China representing one-sixth of the world’s total. Table 2.12 Changes in global prices of commodities, 2010 to 2050.

Commodity

% chg, no clim chg

median % chg with clim chg

median effect of clim chg

Beef

14.7%

18.2%

3.0%

Pork

28.3%

34.2%

4.5%

Poultry

23.9%

32.0%

6.4%

Eggs

5.9%

10.4%

4.2%

Milk

12.5%

13.8%

1.1%

Maize

31.8%

94.0%

49.2%

Millet

20.0%

41.2%

15.5%

Rice

26.1%

59.6%

25.9%

Sorghum

12.5%

31.4%

16.6%

Wheat

21.1%

32.1%

9.3%

Potatoes

21.2%

41.0%

16.5%

Sugar

33.4%

42.5%

7.1%

Groundnuts

10.0%

58.0%

43.3%

Soybeans

17.9%

41.7%

21.0%

Cocoa

28.4%

38.5%

7.8%

Coffee

32.0%

54.3%

17.4%

Cotton

26.9%

43.4%

12.9%

Notes: Values from the IMPACT model.

2.9 Food Security

By 2050, under all scenarios, the number of people at risk of hunger throughout the world will fall to no more than 545.5 million people, as listed for the maximum value of at risk people under climate change. Without climate change, this number would be much lower, at 451.8 million people — less than half of the number in 2010. This is primarily the result of higher incomes throughout the world. Surprisingly, not all regions will experience a reduction in the number of people at risk of hunger — not even under the no climate change scenario. Both MENA and North America show projected increases. This is a response to a combination of relatively fast population growth combined with relatively modest income growth and rising food prices. (Also, the fact that they have low initial levels of hunger, which tend not to fall below 3-5%, and thus numbers rise with population. Check with Tim Sulser on this.) When we focus on the median results accounting for climate change, we note that by 2050, Sub-Saharan Africa will have the largest population at risk of hunger, with 27.4% of the world’s total. South Asia will have dropped to second, but with a much lower percent of the world’s at risk population, with 23.1%. Surprisingly, Southeast Asia and the Pacific will have passed East Asia for third place, with 11.9% of the worlds at risk population. In Table 2.14, we see the share of each region that is at risk of hunger. In 2010, 13.5% of the world’s population was at risk of hunger. SSA had the highest percentage among regions, with 23.5%. South Asia came in second at 18.4%, including India, which had 17.8%. Southeast Asia and Pacific came in third with 16.6% at risk. China had 11.4%. Table 2.13 Population at Risk of Hunger in millions, 2010 and 2050. 2010

World East Asia

2050 With climate change

No climate change

Minimum

Median

Maximum

922.7

451.8

486.1

510.5

545.5

174.1

54.1

55.4

56.9

58.0

China

154.4

38.2

38.2

38.2

38.2

South Asia

299.7

107.6

111.1

118.0

136.2

India

218.4

52.0

52.0

54.9

68.3

104.0

48.1

57.4

60.5

63.3

SE Asia & Pacific Indonesia

40.4

8.6

13.0

13.4

13.9

200.9

118.3

131.6

139.8

148.8

MENA

35.3

43.8

46.1

47.0

48.5

LAC

53.3

34.6

37.3

39.8

41.4

7.2

7.0

7.0

7.0

7.0

Sub-Saharan Africa

Brazil North America USA Former Soviet Union Russia Europe

11.1

13.5

13.5

14.4

14.4

9.3

12.1

12.1

12.1

12.1

17.8

9.6

9.6

9.7

9.8

6.4

4.1

4.1

4.1

4.1

26.7

22.3

24.1

24.5

25.1

Notes: Values from the IMPACT model.

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2 Changes in Food Supply and Demand by 2050

Table 2.14 Share of Population at Risk of Hunger, 2010 and 2050. 2010

World East Asia

2050 With climate change

No climate change

Minimum

Median

Maximum

13.5

4.9

5.3

5.6

6.0

11.2

3.7

3.8

3.9

4.0

China

11.4

3.0

3.0

3.0

3.0

South Asia

18.4

4.5

4.7

5.0

5.7

India

17.8

3.0

3.0

3.2

3.9

16.6

6.0

7.2

7.6

8.0

16.8

3.0

4.5

4.7

4.8

SE Asia & Pacific Indonesia Sub-Saharan Africa

23.5

6.7

7.4

7.9

8.4

MENA

7.7

6.1

6.4

6.6

6.8

LAC

9.2

4.7

5.1

5.4

5.6

3.7

3.0

3.0

3.0

3.0 3.2

Brazil North America USA Former Soviet Union Russia Europe

3.2

3.0

3.0

3.2

3.0

3.0

3.0

3.0

3.0

6.4

3.4

3.5

3.5

3.5

4.5

3.0

3.0

3.0

3.0

5.0

3.9

4.2

4.2

4.3

Notes: Values from the IMPACT model.

By 2050, every region is projected to have improved, except that North America, under the median and maximum results from the climate scenarios, will have maintained the same share as in 2010. But this is somewhat misleading, because it is also true that North America had the lowest percent of the population at risk of hunger in 2010, and will maintain that lead in 2050 under all scenarios. Globally, the share of people at risk of hunger will be less than half, even under the worst-case scenario. Under the median result for the climate change scenarios, Sub-Saharan Africa will still have the highest share at risk of hunger among all of the regions of the world, but their share will have dropped from 23.5% in 2010 to 7.9% in 2050, lowering the share by two thirds. India is projected to drop from 17.8% to 3.2%, and China is projected to drop from 11.4% to 3.0%. In all cases, the impact of climate change on share of population at risk of hunger is projected to be modest, making at most 2 percentage point’s difference in any region when comparing the median climate change result to the no climate change scenario.

2.10 Conclusion Using the moderate-scenario projections for population and income from the latest IPCC assessment, together with results from our biophysical analysis of the impact of

2.10 Conclusion

climate change on crop productivity (assuming a relative high emissions pathway of RCP 8.5) and assumptions about the rate of technological progress in crop productivity growth, the IFPRI IMPACT model shows that the growth in production will be such that while food prices will rise in the coming decades, they should not rise high enough that hunger will grow. In fact, the share of the world’s population that is at risk of hunger should shrink by more than 60%, and the number of people at risk of hunger should shrink by more than 44%, between 2010 and 2050. While at the global level, climate change effects on food security (risk of hunger in 2050) increases the population at risk by around 13%, indications are that beyond 2050, the effects could be potentially devastating i.e. temperature stresses in 2100 could dwarf those of 2050, which would potentially devastate crop production. While our analysis did not endeavor to analyze changes in wider nutritional components such as protein consumption or vitamin and mineral consumption, over that period, global consumption of meat, milk, eggs, and vegetables will grow faster than the population, which is a hopeful indicator of at least the improved availability of these important nutritional components. Generally, farmers will be hurt by lost productivity from climate change, which will be partially offset by rising prices. However, we found significant variation across commodities as well as between and within countries, and therefore there will be very diverse effects on farmers depending upon their location and crops suitable for that area. Generally, farmers in tropical/developing regions will be more vulnerable to climate change than those in temperate regions. We pointed to the potential for currently underutilized crops that have served, nonetheless, a historically important role in the diets of various groups of people and suggested that they could serve an important role in the future. First, this would be as crops that might be more suited to the warmer climate of the future which will also likely have more variable rainfall and second, as nutritious components of household diets. But in order for these crops to be used more in the future, there needs to be a supporting research component, both to adapt to new regions and adapt to new climates of regions where they are currently cultivated. Much of the analysis that we presented was predicated upon the assumption that there would be continued development of crop varieties, and that these new varieties would be reasonably adapted to the changing climate. This built-in assumption points to the need for continued investment in agricultural research, lest the productivity growth rates of the model be proved to be too optimistic. In our analysis, we did not account for other effects of climate change such as sea-level rise, increases in crop and livestock pests and diseases, and increases in extreme weather events (like super-typhoons and extended droughts), and these caveats could increase the real cost of climate change to agriculture beyond what we estimated here. Another caveat is for continued world political stability. Pressures could arise in areas of large population growth, India, SE Asia, SSA and MENA, and lead to massive disruption of food production. Beyond 2050, the effect of climate change on production — both through the avenues we controlled for in the IMPACT model, as well as for those that we did not control for — will be much more severe, presenting possibly insurmountable challenges in a number of locations that are currently cultivated. It is also urgent to begin now the necessary genetic and agronomic transformations to enable agriculture to be resilient to the abiotic and biotic stresses of climate change. These are likely to be more extreme beyond

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2050. Reducing greenhouse gas emissions now in order to limit the magnitude of climate change may prove critical to the hope for food security for future generations.

References Collins, W., Bellouin, N., Doutriaux-Boucher, M. et al. (2011) “Development and Evaluation of an Earth–System Model—HadGEM2”, Geoscience Model Development, 4 (4): 1051–1075. Dufresne, J.-L., Foujols, M.-A., Denvil, S. et al. (2013) “Climate Change Projections Using the IPSL–CM5 Earth System Model: From CMIP3 to CMIP5”, Climate Dynamics, 40 (9/10): 2123–2165. Dunne, J., John, J., Adcroft, A. et al. (2012) “GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models Part I: Physical Formulation and Baseline Simulation Characteristics”, Journal of Climate, 25 (19): 6646–6665. Dunne, J., John, J., Shevliakova, E. et al. (2013) “GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part II: Carbon System Formation and Baseline Simulation Characteristics”, Journal of Climate, 26 (7): 2247–2267. Ebert, A.W. (2014) “Potential of Underutilized Traditional Vegetables and Legume Crops to Contribute to Food and Nutritional Security, Income and More Sustainable Production Systems”, Sustainability, 6, 319–335. Fischer, G., Shah, M., Tubiello, F.N., and van Velhuizen, H. (2005) “Socio-economic and Climate Change Impacts on Agriculture: An Integrated Assessment”, Philosophical Transactions of the Royal Society B, 360, 2067–2083. http://rstb.royalsocietypublishing .org/content/360/1463/2067.full. Jones, J., Hoogenboom, G., Porter, C. et al. (2003). “The DSSAT Cropping System Model”, European Journal of Agronomy, 18 (3–4), 235–265. Lobell, David B., Marianne Bänziger, Cosmos Magorokosho, and Bindiganavile Vivek (2011). “Nonlinear heat effects on African maize as evidenced by historical yield trials”, Nature Climate Change, 1 (April), 42–45. Martin, G., Bellouin, N., Collins, W. et al. (2011). “The HadGEM2 Family of Met Office Unified Model Climate Configurations.”, Geophysical Model Development, 4: 723–757. O’Neill, B.C., Carter, T.R., Ebi, K. et al. (2012). Meeting Report of the Workshop on The Nature and Use of New Socioeconomic Pathways for Climate Change Research, Boulder, CO, November 2–4: 2011. Available at: http://www.isp.ucar.edu/socioeconomicpathways. Robinson, S., Mason d’Croz, D., Islam, S. (2015) The International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT): Model description for version 3. IFPRI Discussion Paper 1483. Washington, D.C.: International Food Policy Research Institute (IFPRI). http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/129825 You, L., Wood, S., Wood–Sichra, U. , and Wu, W. (2014) “Generating Global Crop Distribution Maps: From Census to Grid.” Agricultural Systems, 127 (May), 53–60. Sakamoto, T., Komuro, Y., Nishimura, T. et al. (2012). “MIROC4h: A New High-Resolution Atmosphere–Ocean Coupled General Circulation Model.”, Journal of Meteorology Society of Japan, 90 (3): 325–359.

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3 Crop Responses to Rising Atmospheric [CO2 ] and Global Climate Change Pauline Lemonnier and Elizabeth A. Ainsworth USDA ARS Global Change and Photosynthesis Research Unit, Urbana, USA

3.1 Introduction 3.1.1

Rising Atmospheric [CO2 ] and Global Climate Change

The concentration of CO2 in the atmosphere ([CO2 ]) has been continually rising as a consequence of anthropogenic CO2 emissions, which started slowly after the industrial revolution and then increased dramatically after ∼1950 (Figure 3.1a). Prior to the pre-industrial revolution, atmospheric [CO2 ] averaged ∼280 parts per million (ppm) for at least 650,000-800,000 years (Lüthi et al., 2008). In May 2013, the Mauna Loa Observatory in Hawaii registered a daily average [CO2 ] exceeding 400 ppm (http://www.esrl .noaa.gov/gmd/ccgg/trends/) for the first time. The increase in [CO2 ] varies from year to year mostly due to small changes in the balance of photosynthesis and respiration on land. Indeed, the average [CO2 ] growth rate was 1.7 ppm year-1 between 1980 and 2011 but the annual increase fluctuated between 0.7 ppm year-1 in 1992 and 2.9 ppm year-1 in 1998. More recently, atmospheric [CO2 ] has been increasing at 2 ppm year-1 between 2001 and 2011 (Hartmann et al., 2013). Depending on the emissions scenario, atmospheric [CO2 ] is projected to reach between 443 and 541 ppm in 2050. The predictions for 2100 are more variable with a wider range of concentrations from 421 to 936 ppm (Meinshausen et al., 2011), although immediate and dramatic global efforts to reduce emissions are needed to keep atmospheric [CO2 ] at the lower end of that range. Emissions from combustion of fossil-fuels (coal, oil, natural gas) and cement use are the main contributors to rising atmospheric [CO2 ] (Figure 3.1b). From 1870 to 2014, the cumulative CO2 emissions from coal, oil, and gas combustion and cement production represented 189 ppm (Figure 3.1b). In 2014, these emissions were 61% greater than in 1990, with a current rate of increase of 2.3% per year (http://cdiac.ornl.gov/trends/emis /meth_reg.html"cdiac.ornl.gov/trends/emis/meth_reg.html). If this rate continues, CO2 emissions could exceed 100 Gt CO2 year-1 by 2100, approximately three times the current level of 36 Gt CO2 year-1 , possibly resulting in an atmospheric [CO2 ] higher than 1000 ppm (Fuss et al. 2014). An additional factor contributing to rising atmospheric [CO2 ] is the change in land use, mainly deforestation, with a cumulative contribution of 69 ppm from 1870 to 2014 (Figure 3.1b). All CO2 emitted to the atmosphere over the past 145 years has not remained there because the ocean and land are sinks for CO2 (Figure 3.1a). From 1870 to 2014, land has absorbed 75 ppm and oceans 73 ppm Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

3 Crop Responses to Rising Atmospheric [CO2 ] and Global Climate Change

(a)

Data: CDIAC/NOAA–ESRL/GCP/Joos et al 2013/ Khatiwala et al 2013 40

CO2 flux (Gt CO2/yr)

30 Fossil fuels and industry

20 10

Land–use change

0

Land sink

–10 –20

Atmosphere

–30

Ocean sink

–40 1880 1900 1920 1940 1960 1980 2000 14 Global Carbon Project

Data: CDIAC/NOAA–ESRL/GCP/Joos et al 2013/ Khatiwala et al 2013

(b) 550 CO2 concentration (ppm)

52

500 450

Oil

400

+67 ppm Coal

350

Gas Cement +28 +5 ppm ppm

Land use

Land sink

+69 ppm

–75 ppm Ocean sink –73 ppm 397 ppm

+89 ppm

300 288 ppm

250 200

Atmosphere in 1870

Atmosphere in 2014

Global Carbon Project

Figure 3.1 Global carbon budget from 1870 to 2014, reprinted from the Global Carbon Project 2015. (a) Partitioning of CO2 emissions from fossil-fuel combustion and land-use change between the atmosphere, land and ocean sinks. Data are shown in gigatons (Gt) of CO2 per year. (b) Cumulative contributions to the global carbon budget from 1870 to 2014. Data are shown in parts per million of CO2 (ppm).

CO2 , and both of these sinks have grown since the 1950s when CO2 emission rates increased (Figure 3.1a). The increase in CO2 fixation in oceans is mainly governed by physio-chemical processes, while growth of the land surface sink may be explained by an increase in photosynthesis at higher [CO2 ] and longer growing seasons under mid to high latitudes due to global warming (Ciais et al., 2013). CO2 and other greenhouse gases (GHGs) present in the atmosphere are the drivers of global warming, which then results in altered precipitation patterns in some regions of the world and sea level rise. Although some countries contribute more than others to

3.1 Introduction

the total amount of CO2 emissions, this gas is well-mixed in the atmosphere resulting in a global and uniform increase across the world. On the contrary, other aspects of the global change (temperature, precipitation, air pollution) are more variable spatially, temporally and in magnitude. Crops will undoubtedly be growing at increasing [CO2 ] over this century, and at higher temperatures and under more variable and extreme precipitation patterns. It is against this backdrop of global change that we consider food crop responses to rising [CO2 ] in this chapter. We describe how crop responses to rising [CO2 ] are experimentally tested, the fundamental, physiological responses of crops to rising [CO2 ], and then examine how crop productivity and crop quality are impacted by rising [CO2 ], rising temperatures and increasing moisture stress. Finally, we discuss different strategies to improve crop production in a high [CO2 ] world. 3.1.2

Measuring Crop Responses to Rising [CO2 ]

The response of crops to rising atmospheric [CO2 ] has been measured in growth cabinets or controlled environments, in greenhouses, in closed and open top chambers in the field, and using Free Air CO2 Enrichment (FACE) technology. FACE technology uses a horizontal or vertical array of pipes to release either pure CO2 or air enriched with CO2 across plots of vegetation under fully open-air conditions (Hendrey and Miglietta, 2006; Figure 3.2a). CO2 is released into the wind on the upwind side of a plot (typically a circle or octagon), with the rate of release determined from measurements of wind speed, wind direction and concentration of CO2 at the center of a plot. This information is relayed to a computer which uses fast feedback proportional-integral-differential algorithms to provide a relatively stable elevated concentration of CO2 in the center of each plot. FACE technology enables growth of crops in large plots (8-30 m diameter) and avoids nearly all of the artifacts associated with enclosures, including edge effects and alterations to the microclimate, such as temperature, precipitation, and wind or plant-atmosphere coupling (Long et al., 2004). FACE technology has some disadvantages, including the dependence on continuous air movement for treatments, dilution gradients across the plots, and periodic high frequency variation in [CO2 ] (Long et al., 2004; Hendrey and Migietta, 2006). Still, the need to understand how crops respond to elevated [CO2 ] and other aspects of global climate change in the field necessitated the development of FACE technology, and it has been widely recognized as the gold standard for examining crop responses to elevated [CO2 ] (Figure 3.2b). Large-scale FACE experiments have been implemented on five continents with a variety of crops (Table 3.1; Figure 3.2b). Wheat has been the most critically examined species, having been grown at elevated [CO2 ] in the USA, Germany, China, and Australia. Maize has been studied in the USA and Germany, and rice has been studied at two locations in both Japan and China. Other crops including soybean, cassava, coffee, canola, sugar beet, field pea, mustard, barley, and potato have been investigated at a single FACE site (Table 3.1). All of the FACE experiments have examined crop responses to elevated [CO2 ] between 525 ppm and 645 ppm, which is the concentration roughly expected for ∼2050-2075 if current emission trends continue. Although there has not been a formal network to link these experiments, the results from the FACE studies have been synthesized in a number of meta-analyses, providing mean crop physiological and productivity responses to elevated [CO2 ] (e.g. Kimball et al., 2002; Long et al., 2004; Ainsworth & Long, 2005; Bishop et al., 2014).

53

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3 Crop Responses to Rising Atmospheric [CO2 ] and Global Climate Change

(a)

temperature drought

CO2 enrichment

(b)

30.9 °C –27.9 ° C

4,600 Kilometers

Figure 3.2 (a) Image of a Free Air CO2 Enrichment (FACE) plot from the SoyFACE experiment in Illinois, USA. The large size of each FACE plot (∼20 m in diameter) allows for interactive treatments that intercept rainfall and reduce soil moisture as well as infrared heaters that increase canopy temperatures. Photograph provided by Dr. A.D.B. Leakey. (b) Global distribution of large-scale FACE experiments that have investigated crop response to elevated [CO2 ]. Figure redrawn from Leakey et al. 2012.

The rise in atmospheric [CO2 ] will not occur in isolation of other global climate changes, so it has been of interest to investigate the interactive effects of elevated [CO2 ] with rising temperature, air pollution, and altered water availability. This has been done by investigating responses of crops to [CO2 ] over multiple years that vary in climate conditions (e.g. Hasegawa et al., 2013; Bishop et al., 2015) or varying sowing dates to alter growing season temperature environments (e.g. O’Leary et al., 2015). The size of the FACE plots also allows for additional climate change treatments within the plots, including canopy warming using infrared heating arrays (Ruiz-Vera et al., 2013) or rainfall exclusion awnings (Erbs et al., 2012; Gray et al., 2013). These experimental results can then be used to test crop simulation models, which enable broader investigation of crop responses to global climate change. 3.1.3

Physiological Responses to Rising [CO2 ]

Rising atmospheric [CO2 ] directly and instantaneously affects two physiological processes of crops, photosynthetic C assimilation (A), and stomatal conductance (g s ).

3.1 Introduction

Table 3.1 Location and experimental details of Free Air CO2 Enrichment (FACE) sites studying crop responses to elevated [CO2 ].

FACE Site

Years of Experiment

Crops Studied

Elevated [CO2 ] (ppm)

Maricopa, AZ, USA

1993−1997

Wheat, Sorghum

550−570

Champaign, IL, USA

2001−2015

Soybean, Maize, Cassava

550−600

Jaguariuna, Brazil

2011−2013

Coffee

550

Braunschweig, Germany

2001−2005

Wheat, Maize

550

Barley,

550

Stuttgart, Germany

2003−2008

Sugarbeet

550

Wheat,

525

Canola

525

RapolanoTerme, Italy

1995−1999

Potato

550

Wuxi, China

2002

Wheat,

550−575

Rice

550−575

Yangzhou, China

2004−2006

Rice

564−575

New Delhi, India

2010−2013

Mustard

585

Shizukuishi, Japan

1998−2004

Rice

550−645

Tsukubamirai City, Japan

2010

Rice

584

Horsham, Australia

2008−2010

Wheat

550

Walpeup, Australia

2008−2009

Wheat

550

As the concentration of [CO2 ] surrounding a leaf increases from pre-industrial levels (i.e. 280 ppm), there is an immediate increase in the rate of photosynthesis in C3 crops including rice, wheat, and soybean, and in C4 crops such as maize or sorghum (Figure 3.3a). However, the concentration at which photosynthesis is saturated by CO2 is much lower in C4 species (close to today’s ambient [CO2 ] of 400 ppm) than C3 species (approximately 1000 ppm depending on species and growth conditions). This results from the CO2 concentrating mechanism of C4 plants, which divides photosynthesis between two cell types. In mesophyll cells, phosphoenolpyruvate carboxylase (PEPcase) initially fixes bicarbonate to oxaloacetate, which is subsequently converted to malate (or aspartate). The 4-carbon organic or amino acid diffuses to the bundle sheath cells where it is de-carboxylated, releasing CO2 around Ribulose-1,5-bisphosphate (RuBP) carboxylase/oxygenase (Rubisco) and saturating or nearly saturating the carboxylation reaction of Rubisco and largely eliminating the oxygenation reaction (Furbank & Hatch, 1987). Under favorable growing conditions and current atmospheric [CO2 ], A is CO2 -saturated in C4 crops (Figure 3.3a). Therefore, the increase in atmospheric [CO2 ] from ∼400 ppm today to ∼500-1000 ppm expected by the end of this century is unlikely to stimulate A in C4 crops (Figure 3.3a; Leakey 2009). Photosynthesis in C3 crops will benefit directly from an increase in atmospheric [CO2 ] over this century because Rubisco is not currently CO2 -saturated and because increasing [CO2 ] competitively inhibits the oxygenation reaction of the enzyme (Long et al., 2004). The Farquhar et al. (1980) biochemical model of C3 photosynthesis provides the theoretical basis for C3 photosynthetic response to rising intercellular [CO2 ] (ci ). At low intercellular [CO2 ] (50-280 ppm), A is limited by Rubisco carboxylation rate, and there

55

3 Crop Responses to Rising Atmospheric [CO2 ] and Global Climate Change

60

(a)

A (µmol m–2 s–1)

50

40

30

20

10

0 0

200

0

200

400

600

800

1000

400

600

800

1000

50

(b)

40 A (µmol m–2 s–1)

56

30

20

10

0 Intercellular [CO2] (ppm)

Figure 3.3 Response of photosynthesis to [CO2 ]. (a) Example response of photosynthesis (A) to intercellular [CO2 ] (ci ) for a typical C4 crop (dashed line) and C3 crop (solid line). (b) Illustration of typical reduction in photosynthetic capacity of a C3 crop grown for its lifetime at an elevated [CO2 ] of ∼550 ppm (dashed lines) compared to ambient [CO2 ] (∼400 ppm, solid lines). The figure shows a decrease in maximum Rubisco carboxylation capacity (initial slope of the CO2 response) of ∼10% and a decrease in RubP regeneration capacity (after the inflection point) of 5%. Although the supply of [CO2 ] from the atmosphere to the intercellular compartment of the leaf is reduced at elevated [CO2 ] because of lower stomatal conductance (dotted lines indicate that supply function) and photosynthetic capacity is reduced at elevated [CO2 ], A measured at growth [CO2 ] is still ∼15% greater in plants acclimated to elevated [CO2 ] (arrows to y axis).

3.1 Introduction

is a rapid increase in A as [CO2 ] increases (Figure 3.3a). In C3 plants, ci is typically ∼0.7 times atmospheric [CO2 ], so a ci of 280 ppm would be typical for plants growing at 400 ppm or approximately today’s atmospheric [CO2 ]. Many C3 plants are limited by Rubisco at current [CO2 ], as indicated by the intersection of the supply function (grey dotted line in Figure 3.3b) with the initial slope of the A/ci response curve. At higher [CO2 ] (above ∼280 ppm) electron transport capacity supporting RuBP regeneration limits A. Above 280 ppm, A still increases with increasing [CO2 ] because of competitive inhibition of the oxygenation reaction of Rubisco and reduction of subsequent photorespiration (Figure 3.2a). It is the fundamental response of photosynthesis to elevated [CO2 ] in C3 crops that provides the carbon backbones for greater growth and yield, but when crops are grown at elevated [CO2 ] in the longer term, there is also potential for down-regulation of photosynthetic capacity, or photosynthetic acclimation to an elevated [CO2 ] environment. Commonly, investment in Rubisco is decreased when C3 crops are grown at elevated [CO2 ] in the long term, especially when N is limited (Ainsworth & Long, 2005). Maximum Rubisco activity decreased by ∼18% in crops grown at elevated [CO2 ] in the field, while maximum electron transport capacity decreased by 14% (Ainsworth & Rogers, 2007). Decreased investment in Rubisco or electron transport capacity means that crops grown at elevated [CO2 ] may not have the same stimulation of photosynthesis as the instantaneous response predicts (Figure 3.3b), but crops grown at elevated [CO2 ] may also use N more efficiently (Drake et al. 1997). Even with acclimation of photosynthetic capacity at elevated [CO2 ], light-saturated rates of photosynthesis were increased by ∼24% when C3 crops were grown at elevated [CO2 ] (∼550 ppm) in the field (Bishop et al., 2014). A second physiological response of both C3 and C4 crops to elevated [CO2 ] is a reduction in g s . Across all species, plants grown at elevated [CO2 ] (∼550 ppm) reduce g s by 22% (Ainsworth & Rogers, 2007). Stomatal closure results from depolarization of the guard cell membrane, which occurs following activation of K+ channels and S-type anion channels, and Cl- release from guard cells. The precise signal transduction pathways functioning upstream of the ion channels is an area of active study, but it has recently been suggested that the CO2 signaling pathway converges with the abscisic acid (ABA) signaling pathway, and that carbonic anhydrases play a role in regulating CO2 responses (Engineer et al. 2015). A decrease in g s at elevated [CO2 ] does not ensure that total canopy evaporation will be lower, but results from field experiments with diverse crops have measured significantly lower canopy evapotranspiration at elevated [CO2 ] (Bernacchi and VanLoocke, 2015) and greater soil moisture content under crop canopies exposed to elevated [CO2 ] (Bernacchi et al., 2007; Markelz et al., 2011). While understanding the physiological responses of crops to rising [CO2 ] provides a strong theoretical basis for modeling and projection of crop yield responses to rising [CO2 ], it is important to consider that atmospheric [CO2 ] is increasing in combination with rising temperature, increasing water stress, and other environmental changes that can alter the magnitude and direction of crop responses to rising [CO2 ]. For example, reduced g s and canopy evapotranspiration at elevated [CO2 ] can be reversed, as a result of greater leaf area index (LAI) in elevated [CO2 ] and therefore greater water demand (Franzaring et al., 2010; Gray et al. 2016). It is for this reason that research efforts to understand how crops respond to elevated [CO2 ] also need to consider other aspects of environmental change.

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3.2 Crop Production Responses to Rising [CO2 ] Stimulation in A in C3 crops and reduction in g s in all crops at elevated [CO2 ] are well-conserved responses, which can lead to greater biomass production and economic yield at elevated [CO2 ]. On average across large-scale FACE experiments, stimulation of light-saturated photosynthesis by elevated [CO2 ] in C3 crops is ∼24%, leading to greater above-ground biomass production of ∼16% and economic yield increases of ∼19% (Bishop et al., 2014). By contrast, the C4 crops (maize and sorghum) investigated to date do not show consistent increases in above-ground biomass production and economic yield. Maize has been investigated for [CO2 ] response in Illinois, USA and Germany, and when grown with ample water availability, showed no response of photosynthesis, above-ground biomass, or kernel yield to elevated [CO2 ] (Leakey et al., 2004; 2006; Markelz et al., 2011; Manderscheid et al., 2014). Similarly, sorghum grown at elevated [CO2 ] with ample water availability showed no yield response to elevated [CO2 ] (Ottman et al., 2001). However, both maize and sorghum showed significantly higher yields at elevated [CO2 ] when exposed to strong drought stress (Ottman et al., 2001; Manderscheid et al., 2014), consistent with greater water conservation at elevated [CO2 ] and delayed onset and extent of drought stress. There has been one experiment to date investigating the interactive effects of rising [CO2 ] and temperature on maize productivity in the field. A season-long increase in canopy temperature of 2.7∘ C reduced photosynthesis and seed yield, and there was no interaction with growth [CO2 ], suggesting that elevated [CO2 ] will not mitigate the detrimental impacts of rising temperature in maize (Ruiz-Vera et al., 2015). The mechanistic understanding of C3 crop responses to rising [CO2 ] predicts that stimulation in photosynthesis, biomass production, and yield will be greater when water availability is limited (Mooney et al., 1991) and at higher temperatures (Long, 1991). Supporting these predictions, the percent stimulation in daily photosynthetic C assimilation at elevated [CO2 ] was positively correlated with temperature and negatively correlated with water availability in soybean (Bernacchi et al., 2006). Bishop et al. (2014) used the global FACE dataset to test these predictions for crop biomass and yield, and found that across FACE experiments and C3 crops, there was little evidence that biomass or yield showed a greater response to elevated [CO2 ] in sites and regions with higher temperatures, but there was a negative correlation between yield response to elevated [CO2 ] and water supply (precipitation and irrigation), supporting the hypothesis that elevated [CO2 ] protects from moderate drought stress. Results from individual experiments and crops show mixed support for the theoretical interaction of CO2 response and water availability. For example, wheat grown under ample irrigation in Arizona, USA only showed a 10% stimulation in yield, but under limited water availability showed a 23% stimulation in yield (Kimball, 2006). In contrast, in Australia, stimulation of wheat yields at elevated [CO2 ] was significantly greater under irrigated (30-37%) than rainfed conditions (10-22%; O’Leary et al., 2015). An eight-year analysis of soybean response to elevated [CO2 ] offered mechanistic insights into the discrepancies that have been reported about the interactive effects of elevated [CO2 ] and drought stress (Gray et al., 2016). In approximately half of the years, greater soil moisture resulted from reduced g s at elevated [CO2 ]. However, in years when ample early season water availability greatly stimulated LAI at elevated [CO2 ], there was significantly greater demand for soil moisture late in the season. If drought occurred in those years, then soil moisture was more depleted at elevated [CO2 ], limiting the seed yield response. Further investigation of soybean response to drought and elevated [CO2 ] using awnings

3.2 Crop Production Responses to Rising [CO2 ]

to intercept rainfall showed that elevated [CO2 ] enhanced the sensitivity of g s and A to soil drying via a more sensitive ABA response, and that nitrogen fixation may have been impaired to a greater degree by drought at elevated [CO2 ] (Gray et al., 2013, 2016). These experiments have revealed that the degree of stimulation of crop productivity by growth at elevated [CO2 ] has a complex, but predictable dependency on water availability. The response of C3 photosynthesis to elevated [CO2 ] is predicted to be greater at higher temperatures because the increase in [CO2 ] counteracts greater rates of Rubisco oxygenation and subsequent photorespiration at higher temperatures (Long, 1991). Whether or not this prediction holds for biomass and economic yield responses of crops to elevated [CO2 ] may depend upon the difference in optimum temperature for photosynthesis vs. crop yield, and the sensitivity of reproductive processes to temperature (Bishop et al., 2014). The yield response of the brown rice cultivar Akitakomachi was negatively correlated to growing season temperature (Hasegawa et al., 2013), perhaps due to heat stress effects on reproductive growth. A field study with soybean which analyzed the combined effects of elevated [CO2 ] and temperature using infrared heaters reported greater stimulation in photosynthesis under the combined elevated [CO2 ] and temperature treatment. However, this only translated to greater yields in the cooler of the two growing seasons. In a warmer than average growing season, biomass and seed yield were negatively impacted by elevated [CO2 ] and temperature, perhaps from increased respiration or damage to reproductive processes (Ruiz-Vera et al., 2013). Both of these experiments suggest that elevated [CO2 ] will not consistently protect from the damaging effects of higher temperatures on crop yields, and that improving high temperature tolerance is an important target for future crop improvement. Nitrogen fertilization application is another important determinant of the yield response to elevated [CO2 ] with the general result that low N fertilization eliminated economic yield increases at elevated [CO2 ] (Ainsworth & Long, 2005). For example, grain yields of rice were stimulated by elevated [CO2 ] by 15% under high N fertilization treatments, but only by 5% under low N fertilization (Kobayashi et al. 2006). Similarly, wheat yields were stimulated by 16% on average under ample N fertilization and elevated [CO2 ], and by only 8.5% under low N and elevated [CO2 ] (Kimball, 2006). A recent FACE experiment in Beijing, China did not show a significant interaction between N application and [CO2 ] treatment, and wheat grain yield was increased to a similar degree (∼11%) at both high and low N application rates (Han et al., 2015). However, in the Chinese study there was no significant effect of N fertilization rate independent of the [CO2 ] treatment, suggesting that N may not have been limiting yield even in the low N application treatment. 3.2.1

Effects of Rising [CO2 ] on Food Quality

The stimulation of crop yield by elevated [CO2 ] has been accepted for decades (Kimball and Idso, 1983; Long et al., 2006) and incorporated into models of future crop production and food security (Parry et al., 2004). Recently, there has been a growing awareness of the negative effects of rising atmospheric [CO2 ] on seed, grain, and tuber quality (Taub et al. 2008; Högy et al., 2009; Erbs et al., 2010; Loladze, 2014; Myers et al., 2014). Field-based elevated [CO2 ] experiments have reported decreased protein and mineral content in a wide variety of crops. A recent analysis investigated protein, zinc, and iron content in the edible portion of six crops (wheat, rice, field peas, soybean, maize and sorghum) grown at elevated [CO2 ] in FACE experiments (Myers et al., 2014). Protein content decreased by 6% in wheat and 8% in rice, while zinc decreased by 9% in wheat

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and ∼4% in rice, and iron decreased by ∼5% in both wheat and rice. Although protein content was less affected by elevated [CO2 ] in C3 legumes, zinc and iron content were reduced in elevated [CO2 ] in field peas and soybean (Myers et al., 2014). Similarly, protein concentration in barley grains was reduced by 12% at elevated [CO2 ] (Erbs et al., 2010) and protein content of potato tubers was reduced by 14% (Taub et al. 2008). In wheat grains, the decrease in protein was correlated with an overall reduction in non-essential amino-acids (Högy et al., 2009). Other essential minerals including sulfur, magnesium, and copper were also significantly reduced in the edible tissues of plants grown at elevated [CO2 ], and these reductions in the nutritional value of foods could have profound impacts on human health (Erbs et al., 2010; Loladze, 2014). Variation in the response of grain protein to elevated [CO2 ] among different functional groups is generally consistent with differences in physiological responses to elevated [CO2 ] with C4 species showing less response than C3 species. Different explanations for the decrease in nutrient content in plants have been proposed and reductions in different nutrients may result from a combination of several physiological processes. The most obvious is the growth dilution or carbohydrate dilution theory, which posits that non-carbohydrate compounds (proteins, minerals) are diluted by an increase in carbohydrate concentrations and biomass due to greater photosynthesis which is commonly observed under elevated [CO2 ] (Gifford et al., 2000; Poorter et al., 1997). Protein dilution would result from a greater increase in biomass than in N acquisition (Loladze, 2002). In wheat, Pleijel and Uddling (2012) confirmed that growth dilution plays a role by showing a negative correlation between elevated [CO2 ] on grain yield and grain protein yield. They found a negative effect of elevated [CO2 ] on grain protein content even when grain yield did not change, suggesting other mechanisms are also important. Myers et al. (2014) corroborate the interaction of several mechanisms since different nutrients within the same crop showed distinct changes. They hypothesized that the mechanisms could vary depending on the species. In addition to growth dilution, leaf and shoot nitrate assimilation can be inhibited by elevated [CO2 ] (Bloom 2015). There can also be a reduced nutrient uptake by roots at elevated [CO2 ], the rationale being that elevated [CO2 ] decreases stomatal conductance and transpiration in plants at the leaf and canopy scales (Ainsworth and Rogers, 2007; Bernacchi et al., 2007; Leakey et al., 2009). Many soluble nutrients are translocated to the roots by water flow, and reduced transpiration may result in a decreased uptake of these nutrients. In a recent meta-analysis, this idea was validated by showing that nutrients acquired by mass-flow decreased more than nutrients acquired by diffusion to the roots (McGrath and Lobell, 2013). This study also suggested that some physiological changes that occur under elevated [CO2 ], such as reductions in chlorophyll and Rubisco content might alter specific nutrient allocation and demand (McGrath and Lobell, 2013). If the predicted reduction in mineral and protein contents in edible portions of food crops occurs over this century, there could be significant consequences for human nutrition and health. The World Health Organization estimates that 2 billion people already suffer from mineral and vitamin deficiencies, primarily iron, zinc, iodine, and vitamin A (Tulchinsky, 2010), which causes a collective loss of 63 million life-years annually (Myers et al., 2014). Most people suffering from vitamin and mineral deficiency rely on C3 grains and legumes as their source of zinc and iron. Therefore, a decrease in zinc and iron content in four major C3 food crops (wheat, rice, soybean and field peas) in the future elevated [CO2 ] environment would exacerbate the mineral deficiencies which

3.2 Crop Production Responses to Rising [CO2 ]

already exist (Myers et al., 2014). Reductions in protein content of food crops would also disproportionately affect food insecure people. For example, in India, 60% of dietary proteins come from consumption of C3 grains, and one-third of the rural population may be at risk of not meeting this requirement (Swaminathan et al., 2012). This risk will increase if protein content diminishes in C3 grains with rising atmospheric [CO2 ]. Wheat, rice, barley grains, and potato tubers provide respectively 21%, 13%, 0.3%, and 2% of proteins in the human diet (FAO STAT 2013). Based on these figures and experiments showing an average decline of 8% in the protein content of these crops under elevated [CO2 ], Bloom et al. (2014) estimated that the quantity of proteins available for human nutrition would decrease by 3% in the next three to four decades. The consequence of lower quality food supply at elevated [CO2 ] has been broadly studied in insect herbivores (DeLucia et al., 2012). Compensatory feeding has been observed among herbivores fed with plants grown under elevated [CO2 ], which typically have increased total nonstructural carbohydrate (TNC) concentrations and lower protein and N content (Robinson et al., 2012; Stiling and Cornelissen, 2007). Loladze (2014) suggested that humans as well as insect herbivores will suffer the dietary consequences of eating food with increased TNC:protein and TNC:mineral content. TNCs accumulate from 1 to 8 g per 100 g of dry plant tissue at elevated [CO2 ] while mineral content decreases by 8% and protein by 10-15% at elevated [CO2 ] (Loladze, 2014; Taub et al., 2008). Such a change in the consumption of sugars vs. proteins and minerals is suggested to be a potential trigger for obesity, and it is argued that the rise in atmospheric [CO2 ] in the past 250 years and the associated decrease in food quality is one contributor to the weight gain reported in humans, wild mammals, and lab animals over the last several decades (Klimentidis et al., 2011). In addition to a decrease in the nutritional quality of cereal grains at elevated [CO2 ], other characteristics affecting quality of flour can be impacted. For instance, the industrial processing quality for bread-making and brewing (e.g. activity of β-amylase, single kernel hardness, viscosity of the water extract, gluten resistance) of wheat and barley flour was adversely altered by elevated [CO2 ] (Erbs et al., 2010; Högy et al., 2009). Additionally, wheat grains size decreased by elevated [CO2 ] in some studies, which might decrease their market value (Högy et al., 2009; Pleijel and Uddling, 2012). While it is possible that the expected decrease in yield quality on human nutrition could be partly compensated by the predicted increase in yield quantity under higher atmospheric [CO2 ], more research in this area is needed to provide better understanding of the effects of past and future changes in atmospheric [CO2 ] on human health. However, there may be several strategies to counter the reductions in mineral and protein content in crop quality, including supplementation, biofortification, crop breeding, and altered fertilization methods. Unfortunately, all of these solutions might not be readily accessible to the populations in developing countries who need them the most. 3.2.2

Strategies to Improve Crop Production in a High CO2 World

Due to the additional 2 billion people expected by 2050, the world will need 70% more primary foodstuffs according to the United Nations Food and Agricultural Organization (FAO, 2009). However, the land available for cultivation is expected to decrease, along with the rates of yield improvement as global change intensifies (Long, 2014; Ziska et al., 2012). Thus, increasing productivity to meet future food demands represents a

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major challenge for plant scientists. One aspect of addressing this challenge is adapting, breeding and engineering plants to maximize production and maintain food quality in an atmosphere with increased [CO2 ]. 3.2.2.1 Genetic Variability in Elevated [CO2 ] Responsiveness: The Potential and Challenges for Breeding

Several studies have found different cultivars within crop species significantly vary in yield response to elevated [CO2 ]. The average enhancement of yield in 8 inbred japonica rice cultivars grown at elevated [CO2 ] in Japan was 19%, but varied significantly across the cultivars, ranging from 3 to 36% (Hasegawa et al., 2013). Rice cultivars which showed the greatest yield enhancement due to elevated [CO2 ] were usually higher-yielding cultivars in ambient [CO2 ]. Additionally, the yield components related to sink size, including panicle density and spikelets per panicle, contributed most to the yield enhancement under elevated [CO2 ] (Hasegawa et al. 2013). This suggests genetic variation in CO2 response in rice could be partially explained by differences in sink capacity. Another recent study reported genetic variation of yield response to higher [CO2 ] in soybean (Bishop et al., 2015). In 18 genotypes grown at SoyFACE, an average increase of 8% in seed yield was observed under elevated [CO2 ], but the response varied among genotypes from no significant increase to >20% increase in yield. Moreover, 9 genotypes showed consistency in the variation of their yield response to elevated [CO2 ] when grown for 4 consecutive years, suggesting that [CO2 ] response could be a heritable trait (Bishop et al. 2014). In soybean, harvest index, an indicator of the sink capacity of a plant, was positively correlated to the yield response to elevated [CO2 ], supporting the observation in rice and wheat (Aranjuelo et al., 2013; Hasegawa et al., 2013) that high sink capacity is a critical determinant of maximum yield response to elevated [CO2 ]. As previously noted, maintaining food quality is another future challenge since elevated [CO2 ] decreased protein and mineral contents in several crops. Genetic variability in iron and zinc contents under elevated [CO2 ] has been observed in rice cultivars (Myers et al., 2014) suggesting there is genetic variation in the response of food quality to elevated [CO2 ], and promising lines for future selection may exist. Nevertheless, there may also be trade-offs between yield food quality and quantity characteristics that need investigation. Our current understanding of genetic variability with crop species in response to elevated [CO2 ] is still limited to 10 to 20 genotypes at best within a crop species. This is not sufficient to rapidly advance and translate physiological understanding to crop improvement. For that, we need a more comprehensive strategy combining physiological and genetic approaches (Edmeades et al., 2004; Ziska et al., 2012). Studies conducted to date suggest crop breeding programs have not incidentally selected for genotypes with improved responsiveness to elevated [CO2 ] as the concentration has risen over the past 150 years, and the opposite scenario may even have occurred (Leakey and Lau, 2012; Ziska et al., 2012). For example, old and new cultivars of oat show similar biomass responses to elevated [CO2 ], and there is evidence that the [CO2 ] response of wheat yield is less in modern varieties compared to older ones (Ziska et al., 2012). Despite the fact that there is genetic variation in cultivar responses to elevated [CO2 ] and that breeders do not appear to be inadvertently selecting for [CO2 ] response, there has been little effort to date to breed explicitly for lines that will maximize either yield quantity or quality in elevated [CO2 ]. There are a number of reasons for this, including the challenge of growing high crop populations at elevated

3.2 Crop Production Responses to Rising [CO2 ]

[CO2 ] that would enable quantitative genetics, and the challenge of identifying traits underlying greater responsiveness to elevated [CO2 ] (Ainsworth et al., 2008; Ziska et al., 2012). Recent advances in meeting these challenges include spatial design of FACE experiments to incorporate up to 150 genotypes and identifying other treatments that would favor selection for elevated [CO2 ]. Shimono (2011) hypothesized that rice genotypes with the greatest response to elevated [CO2 ] would show a similar response to low planting density, and showed a strong positive correlation between response to elevated [CO2 ] and response to low planting density for total grain weight per plant. This result was confirmed in a larger follow-up study and offers a potential alternative strategy for pre-screening for [CO2 ] response (Shimono et al., 2014). 3.2.2.2

Strategies for Genetic Engineering

In addition to breeding for [CO2 ] response using genetic selection, with modern molecular tools, it may also be possible to genetically engineer crops to maximize yields in elevated [CO2 ] (Leakey and Lau, 2012). Today, tremendous research efforts are addressing the potential to increase photosynthesis in crops in order to improve crop yields (Zhu et al., 2010). Photorespiratory CO2 loss in C3 crops is equivalent to ∼20% of net photosynthesis under moderate conditions (Bauwe et al., 2010), so a number of targets for increasing photosynthesis are aimed at reducing photorespiratory losses. These include the substitution of native Rubisco proteins with better performing enzymes from different species, the conversion of C3 photosynthesis into C4 , the introduction of cyanobacterial carbon-concentrating mechanisms (CCMs) into C3 plants, and the creation of photorespiratory by-passes (Zhu et al., 2010). Potential negative side effects of incorporation of CCMs into C3 crops that might limit increased seed yields include decreased nitrate metabolism, slower recovery from drought stress and increased sensitivity to low temperature stress (Driever and Kromdijk, 2013). Additionally, as [CO2 ] increases in the atmosphere, Rubisco will be less likely to limit photosynthesis under light-saturating conditions, so the benefit from strategies to reduce photorespiration may be less than under current atmospheric [CO2 ]. Under future atmospheric [CO2 ], it may be more promising to increase investment in capacity to regenerate the CO2 acceptor, RuBP, in order to increase photosynthesis and crop yields. Modeling suggests that the current N partitioning among the enzymes of carbon metabolism is not optimal to maximize light-saturated photosynthetic rates (Zhu et al., 2007). It is suggested that C3 plants over-invest in enzymes involved in photorespiration processes and under-invest in Rubisco, sedoheptulose-1,7-bisphosphatase, and fructose-1,6-bisphosphate aldolase. In support of this model, there is evidence that some plants increase the levels of enzymes involved in the regenerative phase of the Calvin cycle under elevated [CO2 ] (Rogers et al., 1998; Geiger et al., 1999). In addition, transgenic tobacco plants overexpressing sedoheptulose-1,7-biphosphatase showed greater photosynthesis and productivity (Lefebvre et al., 2005). Thus, manipulation of the N partitioning in favor of a faster regeneration of RuBP without increasing the total protein-nitrogen investment in the photosynthetic carbon metabolism could enhance crop yield under future [CO2 ]. Another consideration for maximizing yields at elevated [CO2 ] is minimizing the gap between C gain and N acquisition. Even if elevated [CO2 ] enhances N use efficiency, due to reallocation of some nitrogen resources from Rubisco for other processes (Leakey et al., 2009), greater N supply may be required to meet the additional demand of crops

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grown under elevated [CO2 ]. Enhanced fertilization would increase the N supply but the economic and environmental costs could outweigh the benefits. Thanks to their N-fixing nodules, legumes can maintain tissue C:N ratio under elevated [CO2 ] (Rogers et al., 2009), so introducing this capacity into non-leguminous plants could be highly valuable to stabilize or increase yield and food quality in future crops (Delaux et al., 2015). Alternatively, increased use of legumes in rotations or intercropping could improve soil N and offset the need for greater fertilization under elevated [CO2 ]. Another approach, ectopic expression of amino-acid transporters, showed a beneficial effect on overall plant N metabolism and greater N acquisition (Yadav et al., 2015). Thus, engineering N transport might have a positive impact under elevated [CO2 ]. Under elevated [CO2 ], carbohydrate accumulation is usually observed in photosynthetic leaves leading to a negative feedback on photosynthesis (Leakey et al., 2009). As mentioned above, a crop’s ability to use these carbohydrates in different processes (growth, storage) is associated with sink capacity which is crucial to avoid photosynthetic downregulation and maximize yield response to elevated [CO2 ] (Ainsworth and Bush, 2011). Therefore, increasing sugar transport from source to sink tissues may be an effective strategy to prevent the long-term decrease of photosynthetic rate expected under elevated [CO2 ]. Engineering “push and pull mechanisms” may be a way to achieve this purpose via over expression of major sugar transporters and regulation by heterologous promoters (Ainsworth and Bush, 2011; Yadav et al., 2015). However, manipulating carbon partitioning could also have undesirable consequences such as an increase in plant phosphorus needs (Dasgupta et al., 2014). A number of strategies for maximizing crop yields in an elevated [CO2 ] atmosphere have been proposed and many are currently being tested. Some of the strategies may have negative consequences that need to be thoroughly investigated, in particular where there is the potential for interaction with rising temperatures and drought stress. With atmospheric [CO2 ] exceeding 400 ppm for the first time in at least the past 650000 years and the potential for already negative consequences of changes in food quality on human health, adapting crops to rising [CO2 ] and global climate change is an urgent priority.

Acknowledgements We thank Dr. Andrew Leakey for providing the photograph for Figure 3.2a and Kristen Bishop for assistance with Figure 3.2b. We acknowledge funding from USDA NIFA Grant No. 2015-67013-22836.

References Ainsworth, E.A. and Bush, D.R. (2011). Carbohydrate export from the leaf: a highly regulated process and target to enhance photosynthesis and productivity. Plant Physiology 155: 64–69. Ainsworth, E.A. and Long, S.P. (2005). What have we learned from 15 years of free air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2 . New Phytologist 165: 351–372.

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Long, S.P. (1991). Modification of the response of photosynthetic productivity to rising temperature by atmospheric CO2 concentrations: has its importance been underestimated? Plant Cell & Environment 14: 729–739. Long, S.P. (2014). We need winners in the race to increase photosynthesis in rice, whether from conventional breeding, biotechnology or both. Plant Cell and Environment 37: 19–21. Long, S.P., Ainsworth, E.A., Leakey, A.D.B. et al. (2006). Food for thought: lower-than-expected crop yield stimulation with rising CO2 concentrations. Science 312: 1918–1921. Long, S.P., Ainsworth, E.A., Rogers, A., and Ort, D.R. (2004). Rising atmospheric carbon dioxide: Plants FACE the future. Annual Review of Plant Biology 55: 591–628. Lüthi, D., Le Floch, M., Bereiter, B. et al. (2008). High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453: 379–382. Manderscheid, R., Erbs, M., and Weigel, H.J. (2014). Interactive effects of free-air CO2 enrichment and drought stress on maize growth. European Journal of Agronomy 52: 11–21. Markelz, R.J.C., Strellner, R.S., and Leakey, A.D.B. (2011). Impairment of C4 photosynthesis by drought is exacerbated by limiting nitrogen and ameliorated by elevated [CO2 ] in maize. Journal of Experimental Botany 62: 3235–3246. McGrath, J.M. and Lobell, D.B. (2013). Reduction of transpiration and altered nutrient allocation contribute to nutrient decline of crops grown in elevated CO2 concentrations. Plant Cell and Environment 36: 697–705. Meinshausen, M., Smith, S.J., Calvin, K. et al. (2011). The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109: 213–241. Mooney, H.A., Drake, B.G., Luxmoore, R.J. et al. (1991). Predicting ecosystem responses to elevated CO2 concentrations. Bioscience 41: 96–104. Myers, S.S., Zanobetti, A., Kloog, I. et al. (2014). Increasing CO2 threatens human nutrition. Nature 510: 139–142. O’Leary, G.J., Christy, B., Nuttall, J. et al. (2015). Response of wheat growth, grain yield and water use to elevated CO2 under a Free-Air CO2 Enrichment (FACE) experiment and modelling in a semi-arid environment. Global Change Biology 21: 2670–2686. Ottman, M.J., Kimball, B.A., Pinter, P.J. et al. (2001). Elevated CO2 increases sorghum biomass under drought conditions. New Phytologist 150: 261–273. Parry, M.L., Rosenzweig, C., Iglesias, A. et al. (2004). Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Global Environmental Change-Human and Policy Dimensions 14: 53–67. Pleijel, H. and Uddling, J. (2012). Yield vs. quality trade-offs for wheat in response to carbon dioxide and ozone. Global Change Biology 18: 596–605. Poorter, H., VanBerkel, Y., Baxter, R. et al. (1997). The effect of elevated CO2 on the chemical composition and construction costs of leaves of 27 C3 species. Plant Cell and Environment 20: 472–482. Robinson, E.A., Ryan, G.D., and Newman, J.A. (2012). A meta-analytical review of the effects of elevated CO2 on plant-arthropod interactions highlights the importance of interacting environmental and biological variables. New Phytologist 194: 321–336. Rogers, A., Ainsworth, E.A., and Leakey, A.D.B. (2009). Will elevated carbon dioxide concentration amplify the benefits of nitrogen fixation in legumes? Plant Physiology 151: 1009–1016.

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4 Adaptation of Cropping Systems to Drought under Climate Change (Examples from Australia and Spain) Garry J. O’Leary 1 , James G. Nuttall 1 , Robert J. Redden 4 , Carlos Cantero-Martinez 2 , and M. Inés Mínguez 3 1 Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources, Horsham, Victoria, Australia 2 Department of Crop and Forestry Science, Agrotecnio, Universitat de Lleida, Lleida, Spain 3 Centre for The Management of Agricultural and Environmental Risk (CEIGRAM-ETSIAAB-UPM), Technical University of Madrid, Madrid, Spain 4 RJR Agricultural Consultants, Horsham, Victoria, Australia

4.1 Introduction The effects of drought on agricultural production are well known, reducing not only food production, but if prolonged then potentially upsetting economic stability (e.g. Luedi, 2016). The uncertainty of rainfall distribution and amounts as our climate changes has led to emphasis on the more certain aspects of rising global atmospheric CO2 concentrations and temperatures (e.g. Asseng et al., 2014; O’Leary et al., 2015). While irrigation water solves a significant limitation to productivity in those dry areas where it can be delivered, it is not widely possible due to infrastructure and resource constraints. Instead, water conservation methods are utilized within rainfed systems to reduce the impacts of low and unreliable water supply (O’Leary et al., 2011a). Therefore, in the context of global climate change and increasing variability in water supply, local and regional changes are likely to range from increasing to less frequent rainfall across contrasting agro-ecological zones and in the latter case to longer rainless periods. Because of these extremes, water availability is truly the "thousand-pound gorilla" in the climate change agenda, that few authors address (Sinclair, 2011). The biggest challenge comes from areas that are already dry and are continuing to dry further. Within cropping regions throughout the world, where climate is currently marginal in terms of extremes of temperature and water availability during crop maturation, further rises in temperature and reductions in water availability will make cropping highly vulnerable (Conroy et al., 1994). Our adaptation to dryer conditions is expected to build on what has already been achieved in the dryer regions where crops are grown (Connor 2004). Some areas of the world, which are experiencing increased rainfall amid increasing weather volatility, will also require management changes to achieve the best production and productivity outcome. But this Chapter does not address this. High temperature and heat waves can also significantly reduce grain production and quality of rainfed cropping systems. Combined with global increases in atmospheric Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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CO2 concentration and average ambient temperature within a changing climate, there is an expected increase in the frequency of heat waves combined with increasingly severe terminal droughts for many arable regions (IPCC, 2012). Wheat is a significant staple grain with worldwide production of 672 million tonnes in 2012 (FAOSTAT, 2014) providing an important source of human nutrition. Production could be significantly affected by climate change because it is the main crop in dryland areas, as in Australia and Mediterranean regions including Spain. Sustaining productivity of wheat into the future will require continuing adaption of cropping systems through breeding and appropriate agronomic strategies that limit the impact of abiotic stresses associated with increasing weather variability and climate change (Sadras and Dreccer, 2015). This chapter discusses the importance of the management of water supply within rainfed agricultural productions systems in already dry regions that face the prospect of further decreasing rainfall from climate change. It examines the interactive effects of water supply with high temperature and rising atmospheric CO2 concentrations on grain production and quality. It also explores the use of simple models of transpiration efficiency and radiation use efficiency and how phenotypic crop ideotypes might help achieve the breeding and agronomic management objectives of maximizing the available water resources to maintain crop productivity. It draws examples from Australian and Spain.

4.2 Water Supply 4.2.1

Changing Patterns of Rainfall

Examples of changing patterns of rainfall vary from drying to increasingly wetter conditions. Whereas rainfall is seen to be decreasing in parts of Australia (Nicholls, 2004; Lobell et al., 2015) areas in India and the United States of America are experiencing higher rainfall (O’Leary et al., 2018). In Australia, average temperatures are projected to increase in all seasons. Trends of decreasing winter and spring rainfall are projected but there is no clear signal with regard to changes to summer and autumn rainfall. Increased intensity of extreme rainfall events is projected (http://www.bom.gov.au). In Spain, climate projections for the Mediterranean-type areas suggest that earlier dry spells in spring and/or reduced early autumn rainfall (Sánchez et al., 2011; López-Franca et al., 2015). In north-east Spain, a study from 1947 to 1997 (Austin at al. ,1998) showed that agronomic management and wheat and barley yields were highly influenced by changing seasonal rainfall in autumn and spring. In two locations, water use efficiency of wheat and barley increased between 4.3 to 9.0 kg ha−1 mm−1 from September to May rainfall. Such examples are complicated because of the wide geographic spread and diversity of production systems, nevertheless they show that attention to water supplies and its management will be increasingly important as our climate changes. In Australia cereal grain production occurs in three regions, north-eastern sub-tropical with production of hard wheats, south-eastern temperate, and western temperate regions. The National Grains Research and Development Corporation (GRDC http://www.grdc.com.au/) allocates research and development funding based on these regions because of significant differences in their grains production systems (Figure 4.1). Taken together, these regions provide a large gradient in climate and productivity levels. The important primary weather variables are rainfall and temperature but secondary

4.2 Water Supply

Northern Territory Queensland

Western Australia South Australia New South Wales

Victoria

Australian Capital Territory

Bulk wheat export terminals Australian premium white wheat area Predominantly Australian premium white and hard wheat area

Tasmania

Predominantly hard white wheat area

Figure 4.1 Map of the primary grain production zones in Australia showing the premium white quality grading dominant in Western Australia and Victoria with the hard quality dominant in New South Wales and Queensland. Source: Australian Bureau of Agricultural and Resource Economics and Sciences.

variables such as vapor pressure deficit and rising atmospheric CO2 concentrations will interact to reduce and/or increase grain yield and quality. These four weather variables also have important implications for disease, pest and weed ecology within cropping systems. The two main cereal producing areas in Spain (Figure 4.2) are the northern (mean elev. 850 m) and central (mean elev. 550 m) plateaux (I and II) where currently sown wheat (and barley) cultivars have a significant vernalisation requirement. In addition, there are areas at lower elevation in the river basins of the Ebro (north-east, III) and Guadalquivir (south west, IV) where bread wheats with little or no vernalisation requirement are sown along with significant areas of durum wheat. In all regions the combination of seasonal rainfall, frost incidence during flowering and heat and water supply during grain filling dictates cultivar choice (GENVCE: http://www.genvce.org/; MAGRAMA: http://www.magrama.gob.es/es/agricultura/temas/producciones-agricolas/cultivosherbaceos/cereales/default.aspx). Four principal spatial patterns of Spanish long-term temperature variability (1901–2005) have been determined, viz. Northern Spain,

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SiSTEMAS Y PAISAJES AGRARIOS

II

I

III

IV

Figure 4.2 Map of the four main grain production zones in Spain. Northern Central Plateau (I); Ebro Valley (II); Central Plateau (III); Guadalquivir Valley (IV). Libro blanco de la Agricultura y Desarrollo Rural (MAPA 2003, https://www.ign.es/espmap/rural_bach.htm).

South-eastern and Eastern Spain, and South-western Spain (Brunet et al., 2007). The extent to which these regional and seasonal changes in temperature and rainfall will continue is unknown. The response of farmers, however, will be to adopt more suitable cultivars and adapt management practices concerning sowing dates, N fertilization strategies, pest, diseases and weed management. It is expected that future cropping systems will be at least equally diverse as those at present (Figure 4.2). 4.2.2

Rotations, Fallow, and Soil Management

Lack of water has been identified in a worldwide comparison of 13 rainfed wheat producing areas as the single most important factor determining yield. In that study, Australia had the third highest variability in wheat yield after Algeria and Morocco (Russell, 1980). Because of interactions between water supply and other factors such as nutrient supply and disease management, careful experimentation and analysis is essential for the development of enduring agronomic strategies that optimize the use of available resources. One study over a 76-year period in Australia was able to resolve the effects of water supply from those of crop rotation and management. While highlighting the dominant role of water supply it revealed the strong benefits of other crops and fallow, the latter primarily for weed control and water conservation for subsequent crops (e.g. Hannah and O’Leary, 1995). Similar conclusions were reached in central Spain where differences in yield between cereal/legume rotations, with and without fallow, were small and mainly a response to weather of individual cropping years. Cereal yields were, however, higher in the legume

4.2 Water Supply

rotations than in cereal monoculture, probably due to other factors (weeds, pests and disease) (Díaz-Ambrona and Mínguez, 2001), but not so after sunflower, where cereal yields were smaller than after grain legumes, wheat or fallow (López-Bellido et al., 2007). Such water-dependent responses have also been seen in wheat after periods of 3–4 years of lucerne where the profile at sowing was on average 48 mm drier than after annual cropping and it was calculated that the soil profile would fully recharge within 5 years (McCallum et al., 2001). Crop simulation modeling provides a robust tool for untangling the interactive effects of water and nitrogen supply and extreme temperature effects on crop production in variable and changing climatic environments. It can also help clarify new directions in tillage and crop residue management and evaluate potential off-site effects such as runoff and deep drainage. These mechanistic models are built with routines that estimate crop yield components, grain number, grain size and yield, typically calculated on a daily time-step basis. There is a large range of models available with varying designs and methods of computation and aggregation. The most common models are those that calculate daily biomass growth from intercepted solar radiation and radiation-use efficiency. Typically, such mechanistic models are robust in their performance for predicting wheat yield in rainfed cropping systems. The analysis presented in Figure 4.3, for example, demonstrates the good agreement between measured yield and water use (evapotranspiration) and the strong association of yield with transpiration obtained by a crop simulation model. These diagrammatic relationships support the summary equation (Eqn. 4.1) (Tanner and Sinclair, 1983; Sinclair et al., 1984) that operates at the core of these simulation models. Y = kT = k(ET-E)

(4.1)

y = 0.0107x R2 = 0.54

5 4 3

y = 0.0104x R2 = 0.63

2 1 0 0

100

200 300 Water use (mm) (a)

400

Wheat grain yield (Mg ha−1)

Wheat grain yield (Mg ha−1)

where Y is grain yield (kg ha−1 ), ET is crop evapotranspiration (mm) while T and E are its two component, transpiration and soil evaporation, respectively. k is the transpiration efficiency (kg ha−1 mm−1 ) that can also be expressed as k’/Δe where k’ (kg ha−1 mm−1 Pa) is k adjusted for saturation pressure deficit (Δe, Pa) to generalize the yield-water 5 4 3 2 y = 0.0172x R2 = 0.89

1 0 0

100 200 300 Transpiration (mm) (b)

400

Figure 4.3 A strong positive linear relationship between crop water use and wheat yield (a) from 16 years of experimental results (•, —) and simulation modeling of water use (○, − −) in southern Australia and the close tighter relationship (b) between the simulated seasonal transpiration and wheat grain yield by excluding evaporation and drainage through modeling. Source: Reprinted with permission from Latta and O’Leary 2003.

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use relationship across environments of differing evaporative potential (Kemanian et al., 2005; Sinclair, 2012; Vadez et al., 2014a). This equation shows how various agronomic practices can increase yield in water-short environments. The objective is to make the most efficient use of as much water as possible that can be directed to crop transpiration. First, selection of cultivars with high intrinsic k and deep root systems and their use in environments with low Δe will make most efficient use of given quantities of water. Second, practices that reduce water loss by runoff or drainage can increase yield through increasing ET as can also pre-crop fallows that preserve previous rainfall. Third, the important role of soil surface management is seen not only in the performance of weed free fallows (chemical or cultivated), but also in the retention of stubbles to reduce direct loss of water to evaporation in fallows, with benefits to soil water storage and to in-crop transpiration. Fallows are implemented to conserve rainfall as soil water for the following crop (increase ET), but the efficiency (storage/rainfall) of clean fallows (weed growth controlled) is variable and often low. The additional water stored typically represents an efficiency of rainfall capture around 25–35% (40–50 mm) but can exceed 100 mm in any year (Cantero-Martinez et al., 1995). Critical factors are rainfall amounts and distribution relative to evaporation, surface residues and soil water-holding capacity. Stubble retention is a key component for success but in semi-arid environments it is a challenge to retain sufficient crop residue during all fallow months, particularly if grazing animals are present (López and Arrué, 1997; Austín et al., 1998; Lampurlanés et al., 2002). Under those conditions a minimum tillage strategy may be the best conservation practice. However, stubble retention under continuous cropping, with both no tillage or minimum tillage is in general a beneficial soil management strategy to promote the effective accumulation of soil water, reduce evaporative losses and provide a buffer when growing season rainfall patterns are erratic, thus improving yield stability and crop water use efficiency (WUE)/water productivity (Cantero-Martínez et al., 2007; Morell et al., 2011a; Lampurlanés et al., 2016). Some studies in north-east Spain showed that WUE can be higher under conservation management systems due to better root growth, both in shallow and deep soil profile layers that maintained water supply during grain filling period, amid terminal drought (Lampurlanés et al., 2001; Lampurlanés et al., 2002; Morell et al., 2011b). There has been a wide range of modeling studies undertaken across the Australian grain belt and in the cereal growing areas in Spain to assess the likely impacts of a changing climate (Hammer et al., 1987; Wang and Connor, 1996; Guereña et al., 2001; Asseng et al., 2004; Howden and Jones, 2004; Howden and Crimp, 2005; Anwar et al., 2007; Crimp et al., 2008; Ruiz-Ramos and Mínguez, 2010; Sprigg et al., 2015). Together they have employed a range of suitable models (e.g. APSIM, DSSAT, CROPSYST) with a much larger range of assumptions of a future climate. There is, however, an underlying concern that the non-linear and non-stationery nature of climate change will make reliance on crop performance from past climates insufficient. The recent use of standardized climate scenarios has helped by removing effects of otherwise differing baseline conditions. The key findings are for higher grain yields but lower grain nitrogen concentrations from the elevated CO2 and inconsistent effects of elevated temperature and lower rainfall. Such variability has been recently reported by Asseng et al. (2014) with a renewed interest in responses to extreme temperature.

4.3 Interactions of Water with Temperature, CO2 and Nutrients

There is however a clear need for new cultivars with both more heat tolerance and slower development compared to present day cultivars/climate (Wang and Connor, 1996). The extent that phenology of a cultivar should be changed was the subject of a recent study by Sylvester-Bradley et al. (2012) who proposed a phenological wheat ideotype for a new high-rainfall Australian cropping area. Promising genetic variation for longer phenophases has been identified (Botwright-Acuna et al., 2015). Clearly, the impact of climate change on more variable weather patterns and a global increase in atmospheric CO2 across arable cropping regions, challenges our current ideas of production stability particularly with respect to water supply in already semiarid areas. At the same time, however, it offers opportunities to maintain or increase global production through adaptation (agronomic and breeding) and shifting land use.

4.3 Interactions of Water with Temperature, CO2 and Nutrients The changing climate is one significant factor that is forcing agricultural industries to find ways to reduce the deleterious impact of weather on farming. While the increased water supply in some regions provides the opportunity to boost production, there is concern that higher ambient temperatures will reduce yield through accelerated crop development, that reduces the time that crops can accumulate biomass and yield (Lobell et al., 2012). At Horsham, the Australian Government, Victorian State Government and The University of Melbourne conducted a large field experimental programme where free-air atmospheric CO2 levels are increased to levels expected by 2050 (viz. 550 ppm). This Australian Grains Free Air CO2 Enrichment Experiment (AGFACE) assessed possible genetic and agronomic solutions to maintain crop productivity under high CO2 levels, high temperature (simulated heat waves) and drought. The work was integrated with experiments on soils (Butterly et al., 2015), pests and disease (Trebicki, 2015) as well as on grain quality (Fernando et al. 2012, 2014; Panozzo et al., 2014). Consistent increases in growth and grain yield of dryland crops have been measured in elevated CO2 fertilization experiments throughout the world. The ACFACE responses are among the largest so far reported at around 25% increase at 550 ppm CO2 (O’Leary et al., 2015; Fitzgerald et al., 2016) over present day levels of 400 ppm. This yield increase is, however, associated with significant and consistent declines in grain quality (6% reduction in grain protein) (Panozzo et al., 2014) that have become a particular focus of the AGFACE project. The yield increase from rising atmospheric CO2 concentration is considered beneficial to agriculture but the confounding influence of water supply and high temperature, including extreme heat spikes, can limit the advantage on crop growth and yield. The reduced protein observed under elevated CO2 is of concern, particularly because this was not remediated by additional nitrogen (N) fertilization (Myers et al., 2014; Panozzo et al., 2014). 4.3.1

High Temperature Response of Wheat

Wheat production is affected by temperature through plant response to both above optimum temperature for an extended period and/or heat shock which is characterized by shorter periods of very high temperature (>33∘ C (Stone and Nicolas, 1994; Wardlaw and Wrigley, 1994), >35∘ C (Blumenthal et al., 1993)). Optimum temperature

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for grain development ranges from 15 to 25∘ C (Porter and Gawith, 1999), and although greater photosynthesis at ∼ 25∘ C boosts assimilate supply to filling grains this does not compensate for the shortened period of starch deposition. Overall higher temperature produces smaller grains, increases heterogeneity of grain size and limits yield (Andrew, 1987; Spiertz et al., 2006). Wheat exposed to heat shock will respond through early senescence, decreased chlorophyll of leaves, lower CO2 assimilation and increased photorespiration (Farooq et al., 2011). Importantly high temperature coinciding with crop flowering can cause a non-recoverable reduction in yield potential by adversely effecting ovary development, pollen and floret viability, resulting in significantly reduced grain number (Pradhan et al., 2012). This step reduction in grain number may only be partially compensated by greater allocation of assimilate to the remaining kernels (Jenner et al., 1991). For a range of studies, wheat grain viability was most severely affected when exposed to temperatures above 25∘ C for two days immediately prior to anthesis but was less sensitive two days afterwards (Tashiro and Wardlaw, 1990) and largely unaffected 10 to 30 days after anthesis (Stone and Nicolas, 1994). Wheat yields were reduced by 18–35% for 35∘ C heat stress imposed over a single day (Alexander et al., 2010; Talukder et al., 2010). For wheat exposed to 3 to 5 consecutive days of high temperatures between 30 and 42∘ C, at anthesis, the overall decline in grain number was 7% per degree above 30∘ C, which translated to a yield reduction of 6% per degree above 30∘ C (Nuttall et al., 2018). For a simulated heat wave (36∘ C for three days) applied five days prior to anthesis to field grown wheat, under adequate water supply, grain set and yield was reduced by 18% which equated to a grain number decline of 0.21% per ∘ C hr (>32∘ C), and yield decrease of 0.22% per ∘ C hr (>32∘ C) (Nuttall et al. 2015). Reduced water availability at anthesis also appears to exacerbate the impact of high temperature with substantially greater grain loss under water stressed conditions during pre-anthesis growth (Nuttall et al., 2018). Heat shock after anthesis produces wheat kernels that are small and pinched through reduced activity of starch synthesis and translocation to developing grains (Jenner et al., 1991; Jenner, 1994). Small and damaged grains have been observed due to heat stress 2–10 days after anthesis (Tashiro and Wardlaw, 1990). Exposure to chronic temperatures up to 30∘ C commencing six days after anthesis reduced kernel size by between 20 and 30% across two wheat cultivars (Wardlaw et al., 2002). Similarly, for wheat a simulated heat wave of 38∘ C for three days for 15 days after anthesis reduced kernel size by 5% which equated to a reduction of 0.04% per ∘ C.hr (>32∘ C) (Nuttall et al., 2015). For crops under high temperature stress, adequate water supply helps to maintain grain-filling rate, duration and size (Altenbach et al., 2003), although high temperature where water supply is non-limiting has also been shown to cause a reduction in average grain weight by as much as 4% for every 1∘ C rise in temperature beyond 18∘ C (McDonald et al., 1983). Nevertheless, in Mediterranean-type environments, the potential benefit of adequate water to mitigate heat stress effects to rainfed crops is likely to be limited because rainfall is scarce at that time and crops usually mature under conditions of terminal drought. On the other hand, modeled simulations Mínguez et al. (2007) that compared yields of wheat over 30 yr periods of control (1960–1990) versus the A2 future (2070–2100 with 635–856 ppm CO2 ) climate identified areas in southern Europe at 600 m above mean sea level (AMSL) with the greatest probability of a positive yield response of autumn-sown crops to climate change. In this case, the response was with autumn sown spring wheats (no vernalization) that experienced less limitation to winter growth in the future climate

4.3 Interactions of Water with Temperature, CO2 and Nutrients

(Ruiz-Ramos and Mínguez, 2010). In addition, more rapid crop development served to escape heat effects and terminal water deficit during crop maturation. 4.3.2

High Temperature and Grain Quality of Wheat Chronic high temperatures (up to 30∘ C) and heat shock (greater than 30∘ C) during the grain filling phase impact protein content (percentage) and the composition of both protein and starch to the detriment of end-use properties such as dough strength, extensibility and loaf volume (Blumenthal et al., 1993; Jenner, 1994; Farooq et al., 2011). At temperatures above 30○ C grain protein is increased because while starch accumulation decreases (Jenner 1994), protein accumulation remains similar (Altenbach et al., 2003). Although higher grain protein content is usually linked with improved end-use properties, the high temperature effects on the compositional and functional properties of both starch and protein are adversely altered (Blumenthal et al., 1993; Jenner, 1994; Corbellini et al., 1997; Farooq et al., 2011). Heat stress increases the ratio of amylose/amylopectin ratio in starch with a resultant reduction in dough elasticity. For protein composition, high temperature during grain filling reduces the synthesis of glutenin and alter the glutenin/gliadin ratio (Blumenthal et al., 1991; Panozzo and Eagles, 2000) which impacts on dough strength and loaf volume. 4.3.3

Atmospheric CO2 Concentration and Crop Growth

The anticipated rise in average global atmospheric CO2 concentration linked with climate change provides a very real possibility of increasing plant growth by CO2 fertilization. Typically, the effect of elevated CO2 on C3 plants is to increase photosynthesis and growth due to higher leaf CO2 assimilation rates while reducing transpiration (Conroy et al., 1994). For grain crops this equates to an increase in WUE and production (Kimball and Idso, 1983), inferring that increasing CO2 concentrations may provide an advantage to crops, especially those growing in environments of marginal water availability. A review of 430 yield observations of 37 plant species grown under an elevated CO2 environment showed that average yield increased by 36% (Kimball and Idso, 1983) and for C3 crops (such as wheat) this increase was 32%. Elevated CO2 concentration (eCO2 ) increased wheat yield in southern Australia by 26% (2.3 to 2.9 t/ha) (O’Leary et al., 2015), and by 10% in other free-air carbon dioxide enrichment (FACE) studies (Hogy et al., 2009). Although production is likely to be increased under eCO2 , the effect on grain quality is variable but usually adversely affected (Kimball et al., 2001; Hogy et al., 2009). Increasing atmospheric carbon dioxide is a global phenomenon, whereas the shift in other abiotic stress factors such as temperature and rainfall pattern will be region specific. The likely increase in heat waves and increasingly limited water supply across many arable cropping regions underline the importance of understanding the interactive effects of these various climatic and weather variables. A simulation study of wheat growth, determined that greater pre-anthesis growth and yield potential due to elevated CO2 combined with increasing water stress during the grain filling phase translated to greater incidence of ‘haying off’ in some environments (Nuttall et al., 2012). The question of combined conditions of elevated atmospheric CO2 and heat waves is also important. Crops grown under elevated CO2 have greater water use due to greater leaf area

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production but also greater water use efficiency linked to reduced transpiration. This leads to an issue of the role of greater or smaller transpirational cooling under combined effects of higher CO2 and higher temperature. An experimental programme which applied artificial heat wave conditions to crops around flowering within an irrigated FACE facility found no apparent interactive effect of these factors on wheat yield or its components (Nuttall et al., 2015). In one season, however, there was significantly less small grain in treatments grown at high CO2 level compared with ambient CO2 (Fitzgerald et al., 2016). This suggests that a high atmospheric CO2 environment may reduce the impact of a heat wave, even though yield across the CO2 environment was not significantly different. 4.3.4

Elevated Atmospheric CO2 and Grain Quality

Elevated CO2 universally causes a reduction in grain protein concentration. A review of a range of grain crops grown at 550 ppm CO2 concentration in open top chambers, closed chambers and FACE experiments reduced grain protein concentration by 4.2, 3.9 and 2.3%, respectively, relative to 380 ppm CO2 (Hogy and Fangmeier, 2008). More recent FACE experiments in Australia and Germany also reported an overall reduction in grain protein concentration of 3.7% and 7.4%, respectively, due to elevated CO2 (Hogy et al., 2009; Panozzo et al., 2014). For end use properties, elevated CO2 caused a 34% reduction in dough resistance in one study (Hogy et al., 2009), however, remained unchanged in another (Panozzo et al., 2014). For these studies there was a consistent reduction in loaf volume of between 6 to 10 %. This highlights that within a CO2 -rich world a universal reduction of grain protein content and composition may translate to an increase in wheat yields per unit area but with protein below the minimum quality standard for bread making, and the need for the commercial bread making process to be adapted to account for lower protein wheat.

4.4 Matching Genetic Resources to The Environment and the Challenge to Identify the Ideal Phenotype Genetic variation in cultivars and other crop species may hold an important key to increasing adaptation of crops to future weather and climatic conditions across many arable cropping regions. In the case of improving adaptation of crops to dryland regions in southern Australia, breeding for tolerance to subsoil physicochemical constraints such as boron, and salinity on alkaline soils has shown benefit for improving water use and yield (Cartwright et al., 1983; Cartwright et al., 1986; Incerti and O’Leary, 1990; Nuttall et al., 2010). Looking forward, beneficial traits such as greater stem carbohydrate reserves at flowering and more efficient water use may be advantageous in the context of adaptation to climate change impacts (Tausz-Posch et al., 2012). Wheat crops growing under higher levels of CO2 use water more efficiently at 30% more at 550 ppm (O’Leary et al., 2015) so if water supplies can be increased with careful agronomic management (e.g. stubble retention, weed control, plus early vigor) the effects of rising temperatures and lower growing season rainfall can be reduced. A better understanding of water use and water use efficiency will help build enduring agronomic strategies in Australia’s low rainfall dry areas (O’Leary et al., 2011a; Vadez et al., 2014a; Yang et al., 2015).

4.4 Matching Genetic Resources to The Environment and the Challenge to Identify the Ideal Phenotype

The dry nature of the Australian environment translates to the issue of water supply and efficiency being strong features in crop modeling in Australia (e.g. French and Schultz, 1984; O’Leary et al., 1985; Hammer et al., 1987; O’Leary and Connor, 1996). Crop modeling in Australia is now common at the agronomic level with special versions for farmers (e.g. "Yield Prophet" is the farmers’ version of APSIM, Robertson et al., 2015). Such engagement of modeling with farmers has meant that farm productivity on some farms has been maintained at the highest possible level despite the exceptional dry periods associated with the millennium drought (Hochman et al., 2009). The primary features of an environment (e.g. low rainfall) ultimately dictates the range of available adaptation strategies. An example is the response to a change in sowing time and heat tolerant cultivars in a future climate scenario in Victoria (Figure 4.4). Computer modeling allows realistic location-specific solutions to be examined. In addition to field and controlled environment experiments computer simulation studies are also used to complement that detailed work (Chapman, 2008; Hall and Richards, 2013). Computer simulation allows the methodical extrapolation of known science to other locations and the exploration of new ideas in a low risk research environment. Such locations go from one extreme to the other. For example, if the known response to elevated CO2 at Horsham, Victoria over a 3 years period is 25% a model can examine what the response should be at a drier or wetter site that is also warmer. The experimental data is encouraging with signs of positive gains even under quite dry conditions (O’Leary et al., 2015). Without a robust model, the alternative extrapolation methods become unscientific and not generally repeatable. In this way, both modeling and field experimentation contributes to the development of enduring solutions to challenging weather conditions. Because of wide genetic variation it is difficult to find parents that produce an optimal combination of traits to comprise the ideal phenotype in any environment. To capitalize on the environmental resource constraints in any locality the ideal phenotype needs to be articulated. Examples have been proposed that include various plant and crop traits. Such traits include stay green and higher TE characteristics (Fischer et al., 1998; Bänziger et al., 2006). Once such phenotypes can be identified the more difficult task is N

Crop yield stil increasing by year 2070

Decreasing crop yield by year 2070

Decreasing crop yield by year 2050

Decreasing crop yield by year 2030

0

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Decreasing crop yield by year 2015

kilometres

Figure 4.4 Computer modeling analysis of an adaptation to a warmer and drier climate for Victoria showing the direction of productivity increases and decreases employing more heat tolerant cultivars and changed sowing times (Reprinted with permission from O’Leary et al. 2011b).

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to identify genotypes that when crossed will segregate and approximate the phenotype needs to be progressed. One of the difficulties is that there may be various physiological, biochemical and genetic pathways dynamically interacting with the environment to approximate optimal grain yield, and not necessarily one optimum genotype for a given environment scenario, and with seasonal variability various drought mitigating traits may assume importance. Early maturity combined with a high rate of grain filling may be advantageous depending on seasonal distribution of rainfall, and the importance of deep rooting capacity may depend on the availability of subsoil water. For example, barley has been shown to be superior to wheat in water use efficiency in dry environments (Siddique et al., 1990), so different species offer clues to matching phenotypes to specific environments. Cultivar architecture features may range from increased dominance of primary tillers, more erect flag leaves, increased number of surviving florets per spike both within spikelets and with increased number of spikelets per spike. Hybrid wheat could provide such scope for altering wheat architecture, especially with combinations of different gene pools, such as between winter and spring wheat (Whitford et al., 2013), coupled with directional selection in the target environment (Reynolds et al., 2016).

4.5 Changing Climate and Strategies to Increase Crop Water Supply and Use In regions of the world where agricultural systems are rainfed the changing climate raises difficulties and opportunities. A general strategy in those areas has been to match crop growth and development to the patterns of water supply and use (Giménez et al., 1997). The difficulties include even lower rainfall and increasing variability in amount and distribution. Such scenarios might lead to the desertification of already marginal lands. There are, however, important opportunities where the overall rainfall becomes greater and seasonality shifts open new agronomic exploration. A recent study in Australia by Yang et al. (2015) evaluated some climate change scenarios on the water balance and WUE of dryland wheat. They concluded that by 2021–2040 wheat yields are expected to decrease despite slight increases in WUE from reduced overall rainfall and ET. Both transpiration and soil evaporation are expected to decrease with no change in runoff. It was noted that advantages associated with the small gain in crop WUE was limited by the large reduction in water supply. Management systems, therefore should focus on yield per se and water supply (T) rather than measures of efficiency of either T or ET. Partitioning ET in favor of more T through faster early growth enhancing soil cover to result in more light interception and acceleration to full canopy cover. Early crop vigor has been suggested as a trait to select for higher growth and yield in warmer and drier climates (Ludwig and Asseng, 2006; Richards et al., 2014). Whether this can be achieved through improved canopy architecture and higher early light extinction coefficients (e.g. −0.5 −> −0.85) or just by shifting up the present light extinction curve faster (e.g. from elevated atmospheric CO2 concentration) remains to be demonstrated. Shifting the emphasis of early growth to cover the soil faster to boost light interception in the incomplete cover phase will help overcome the primary limitations of water use to growth in semi-arid regions and offers opportunities to maximize yield and profits in drying environments.

4.5 Changing Climate and Strategies to Increase Crop Water Supply and Use

Various agronomic strategies have been shown to increase the supply of water in many semi-arid environments. These include soil water conservation strategies involving reduced or no tillage, stubble or crop residue retention (Mathews and Marcellos, 2003; Elias and Herridge, 2014). These increase soil water reserves by different mechanisms. Stubble or residue retention primarily reduces evaporative losses and increases organic matter, whereas reduced tillage or zero tillage increases the infiltration rate of water into the soil (O’Leary et al., 1997a). If both residues and reduced tillage are applied together the benefits of both often occur (see above, Lampurlanés et al., 2001; Lampurlanés et al., 2002; Morell et al., 2011a). Other benefits of minimum tillage or no-tillage systems is the enhancing of soil structure which may provide more effective infiltration of water to depth, and the protection of this water from evaporative loss. Another method of concentrating water over time is forgoing a crop, applying weed control methods to reduce transpiration losses to carry over water to the subsequent crop (Connor et al., 2011). This practice is called fallowing and has provided from 30 to 60 mm additional water for subsequent use by crops in Australia (Cantero-Martinez et al., 1995a). The length of the fallow period ranges from 3 to 18 months and methods of weed control vary from shallow to deep tillage with disks or tines to chemical herbicides and even grazing, with economics driving the ultimate practice applied by farmers in various countries. This fallow supplied water being typically stored deep in the soil profile is used at a higher water use efficiency than surface applied water (Kirkegaard et al., 2007). If reduced tillage and stubble retention systems are also applied the water storage has been doubled to over 120 mm on clay soils in southern Australia (O’Leary et al., 1997b). Similarly, in Spain, stubble retention under both no-tillage or reduced tillage demonstrate to be a main strategy to better water accumulation and WUE. (Cantero-Martínez et al., 2007; Lampurlanés et al., 2016). Adequate N-fertilization management is also important and, in some cases, a moderate reduction of N-fertilization could led to a higher yields and improved water use and WUE than conventional higher doses, both in Spain and Australia (Cantero-Martínez et al., 1995a; 1995b; Cantero-Martínez et al., 1999). Optimization of N-fertilization together with soil management that promotes early growth of the crop and better partitioning of the water use between pre- and post-anthesis periods produces better overall water use and WUE. (Cantero-Martínez et al., 2003; Angás et al., 2006). Also, crop rotations may help to improve water use and efficiency of barley, wheat and sunflower in combination with other crops (Fereres et al., 1993; Lopez-Bellido et al., 2007; Alvaro-Fuentes et al., 2009). Early planting, theoretically, should contribute to increased transpiration efficiency and promote a higher yield. However, in some cases an early sown crop is more affected by weeds (Recasens et al., 2016) and possibly by pest and diseases. In a study in north-east Spain, a delay of sowing time with an adjusted cycle cultivar could make better use of the water supply improving the WUE and Nitrogen use efficiency (Plaza-Bonilla, unpublished data). Promoting an extensive root system is advantageous in dryland systems as it provides a means of ensuring water supply to crop in the post-anthesis phase, when rainfall is particularly unreliable (Elhers et al., 1991), although the soil profile must have the opportunity to accrue water, or else this benefit may be lost (Nuttall and Armstrong, 2010). Moreover, the capacity for crops to extend roots into the subsoil may be reduced by subsoil physicochemical constraints. For example, for many alkaline soils in southern Australia, the high levels of subsoil boron, salinity and sodicity can limit root growth and water extraction (Nuttall et al., 2003). Again, breeding can offer a partial solution

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for adaptation of crops to subsoil physicochemical constraints, where pyramiding of tolerances can improve crop subsoil water use (Nuttall et al., 2010). In some studies in Northeast Spain, conservative systems such as no tillage and minimum tillage promoted better root systems that allowed higher water extraction by the crop (Lampurlanés et al., 2001; Lampurlanés et al., 2003).

4.6 Beyond Australia and Spain The examples of adaptation strategies to drought and water conservation issues from Australia and Spain are representative of typical dry and semi-arid regions where cropping is a dominant and economically important activity. Other regions of the world that also suffer drought (southern and eastern Africa, China, South Asia, and north and south America and even parts of New Zealand) will also benefit from the general principles highlighted here. The simple definition of water-use efficiency of a crop (i.e. biomass per unit of water used) is easy to understand but also easy to misinterpret. Different terminologies also exist (e.g. water productivity) and also care is needed, particularly when considering the methods of measurement used (Kukal et al., 2014). Studies of its component transpiration and soil evaporation have been the subject of many studies in the dry areas. These extend to genetic efficiency factors (e.g. measurements of carbon isotope discrimination 13 Δ) and to environmental effects of VPD (Tanner and Sinclair, 1983; Sinclair et al., 1984). The simplest interpretation leads one to accept that increasing either or both water supply and its raw efficiency of use can lead to increased production. But what can be practically achieved is the more important question. Whilst increasing water supply is an obvious solution (Figure 4.3) significant effort has been made to distil the basic efficiency fundamentals (e.g. Richards et al., 2014; Valdez et al., 2014b) that are attractive to breeders seeking genetic advancement. This genetic focus however, downplays the importance and scope that water supplies can be increased practically. Clearly, both approaches are complementary, crop breeding needs to be conducted in environments with water conservation and sowing time agronomic managements that anticipate climate change. Moreover, global increases in atmospheric CO2 and increasing volatility in weather patterns provide the incentive for developing joint agronomic and breeding strategies for maintaining grain production and quality, to limit the impact to human nutrition and market value of staple grains in a high CO2 world. Numerous challenges have been noted in the quest to adapt to dryer conditions. These include the need to adapt cultivars to multiple and conflicting conditions (e.g. high temperature stress under dry conditions). Despite the dominating role that water plays there is still some uncertainty about the role that water supply plays in determining subsequent growth, yield and end-use quality of crops because of the unclear interacting factors (e.g. high temperature, high CO2 and higher water supply). Whilst a shortage of water has been shown to be linearly related to daily and accumulated growth, its linkage to solar radiation as the primary driver of growth is less clear, with different models describing this relationship from tight to loose. Most of the water transpired by a crop is not used at all in photosynthesis but rather to cool the crop through energy exchange by advection and vaporization of water (Connor et al., 2011). Because of this, contemporary models are being challenged in all locations

Acknowledgments

to include the effects of canopy temperature and cooling particularly under higher atmospheric CO2 concentrations where reduced stomatal conductance and transpiration and higher canopy temperatures are known to be substantial (Kimball, 2011; Webber et al., 2016). Access of farmers to a choice of cultivars that can allow them a year-by-year response depending on the onset of rainfall (e.g. autumn rains for cereals), and to more informed weather predictions, could optimize the match of the crop cycle to the water supply. An example would be the choice of cultivars with or without vernalisation requirements if the onset of rainfall is significantly late. While this has not been addressed here because it is a production cost issue, that also relates to supply by seed companies; it is nevertheless an example of response agriculture or climate smart agriculture that will be needed to be considered along with the biophysical needs of our future farming systems.

4.7 Conclusions Water is essential for crop production and its shortage significantly limits the productive levels that can be achieved. Its role is often confused between water use and water-use efficiency, typically and incorrectly assuming they are the same thing. Irrespective of the resultant effects of a change in rainfall amount and distribution as the climate changes the management of water supply to a crop, its conservation and use will be central to the maintenance of crop production and regional food security from the dryland areas. Cultivar adaption to the expected warmer conditions, higher atmospheric CO2 and more extreme climatic events around flowering is also needed. Strategies that maximize the use of the available scarce water resources are already known. These include agronomic practices of fallowing, stubble retention, reduced or zero tillage. The response of crops to water is tempered by the other critical factors such as high temperature and heat waves that can cause dramatic yield loss. The rising atmospheric CO2 concentration is expected to reduce such loss but poor grain quality arising directly from elevated atmospheric CO2 levels is an emerging worry. A renewed focus is needed to better manage our scarce water resources in concert with the positive and negative effects noted above.

Acknowledgments This work has been funded by the Australian Grains Research and Development Corporation, the Australian Government Department of Agriculture and Victorian Department of Economic Development, Jobs, Transport and Resources, and by MULCLIVAR project CGL2012-38 923-C02-02 funded by The Spanish Ministry of Economy and Competitiveness. Other significant collaboration has occurred with The University of Melbourne, CSIRO, The University of Florida, the USDA and NASA in a world-wide model comparison project (AgMIP). We thank Prof David Connor for helpful comments on an earlier manuscript but the views expressed here are those of the authors and do not necessarily reflect those of the funding agencies or institutions supporting our research.

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5 Combined Impacts of Carbon, Temperature, and Drought to Sustain Food Production Jerry L. Hatfield National Laboratory for Agriculture and the Environment, USDA–ARS, Ames, Iowa, USA

5.1 Introduction Climate change is a reality with changing CO2 , temperature, and precipitation regimes around the world. These changes are not uniform either in space or time, and this variation adds to the challenge of being able to provide for a food secure world. The interactions among CO2 , temperature, and water availability reveal that the positive impacts of increasing CO2 on crop productivity are offset by increasing temperatures and drought stress. Temperature and drought stress effects have their greatest effect during the reproductive stage of development; however, the effect may have been established during the formation of the number of grain or fruit. There is genetic variation in the response across different germplasm, and one of the challenges will be to determine why these differences exist and how they can be exploited in order to not only develop germplasm capable of being tolerant to these increasing stress levels but also to develop cultural practices that will allow the germplasm to perform at its genetic potential. 5.1.1

Need for Food to Feed the Nine Billion by 2050

Coupling the projections of the required food needs to feed the world population of nine billion by 2050 and beyond, projections of a changing climate increase the uncertainty about the stability of agricultural production and creates a scenario requiring an understanding of the impacts of the changing climate on agricultural crops. Estimates of the increase in global food production required by 2050 range from 60 to 110% above current levels (Tilman et al., 2011; Alexandratos and Bruinsma, 2012). Projections by Alexandratos and Bruinsma (2012) assumed no change in population growth rate, food consumption patterns, or food waste management and estimated that cereals must increase by 940 million tons to reach 3 billion tons; meat production must increase by 196 million tons to reach 455 million tons; and oil crops must increase by 133 million tons to reach 282 million tons by 2050. Analyses by Ray et al. (2013) suggested that the current rate of increase in production for maize (Zea mays L.) of 1.6%, rice (Oryza sativa L.) - 1.0%, wheat (Triticum aestivum L.) - 0.9%, and soybean (Glycine max L. Merr.) - 1.3% are inadequate to satisfy 2050 demands. To counteract these deficiencies, Ray et al. (2013) stated production must increase by 67% (maize), Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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42% (rice), 38% (wheat), and 55% (soybean) by 2050. Hubert et al. (2010) suggested that the required increase for global maize production from 2000 to 2050 would be more than 450 million tons or nearly 30%. These increases in production would be a result of increasing land productivity or available land resources, and increasing the available land resource is not a viable option (Sakschewski et al., 2014). These production increases will be disrupted by the changing climate, and Hatfield et al. (2014) summarized as part of the United States climate assessment that “Climate disruptions to agricultural production have increased in the past 40 years and are projected to increase over the next 25 years. By mid-century and beyond, these impacts will be increasingly negative on most crops and livestock.” These disruptions will come from the increased temperatures and variability in precipitation.

5.2 Changing Climate Changes in the temperature regime will have a significant impact on plant growth and development. Temperatures are projected to increase in the near-term by a mean global average of 1∘ C for the period from 2016 to 2035 compared to the 1850–1900 period but not more than 1.5∘ C (Kirtman et al., 2013). The projection is that the winter temperatures will increase more than summer temperatures, and near-term increases in seasonal and annual mean temperatures are expected to be larger in the tropics and subtropics than in mid-latitudes (Kirtman et al., 2013). However, estimates from multi-model ensembles show summer temperatures over the mid-latitudes would increase between 1–1.5∘ C with the potential for more extreme events as suggested by Hansen et al. (2012). In the long-term, Collins et al. (2013) estimates that global mean temperatures will continue to increase because of greenhouse gases in the atmosphere and are likely to exceed 2∘ C. Their projections include an increase in the frequency, duration, and magnitude of hot extremes coupled with heat stress; however, there remains the potential for cold winter extremes to occur (Collins et al., 2013). Increases in the mean temperatures will affect agricultural production as shown by Porter et al. (2013). Precipitation is required to supply water for crop use to meet atmosphere demand. There are two general trends present in the precipitation signal for the globe; increase in annual precipitation and a shift in the seasonality of precipitation. In the near-term, Kirtman et al. (2013) projected precipitation to increase in the high to mid-latitudes with a concurrent increase in evaporative demand and specific humidity. In the long-term projections of climate, Collins et al. (2013) found that precipitation would increase concurrent with the increasing mean global temperatures at the rate of 1–3% C-1 due to the increase in water vapor pressure and increased evaporation to place more water vapor into the atmosphere. In the short- and long-term both studies projected an increase in spatial variation in precipitation along with an increasing difference between wet and dry seasons (Collins et al., 2013, Kirtman et al., 2013). Toward the end of the 21st century, evaporation trends will continue to increase because of the increasing temperatures (Collins et al., 2013). The projected differences between wet and dry seasons would signal increased variation within the season and among years with the potential for more extreme events in precipitation. Hao et al. (2013) evaluated the combination of extreme temperature and precipitation events from observations derived from ground-based stations and a suite of climate

5.3 Carbon Dioxide And Plant Growth

models. They used a combination of temperature and precipitation: warm/wet (high temperature/high precipitation), warm/dry (high temperature/low precipitation), cold/wet (cold temperatures/high precipitation), and cold/dry (cold temperatures/low precipitation). These analyses compared 1978–2004 with the 1951–1977 period on a global scale and found warm/wet and warm/dry extremes increased. Warm/wet extremes increased in the high latitudes and tropics while the warm/dry extremes increased in many areas, e.g. central Africa, eastern Australia, northern China, parts of Russia, and the Middle East (Hao et al., 2013). Conversely, the extremes in the cold/wet and cold/dry combinations decreased over most of the globe. The increase in the warm/wet and warm/dry extremes over agricultural areas will have a negative impact on agricultural productivity and change the distribution of viable crop production. The effects of extreme temperatures and precipitation, especially drought, have been related to reductions in crop yields (Moriondo et al., 2011; Lobell et al., 2013; Porter et al., 2013). In the assessment for the 5th Intergovernmental Panel on Climate Change, Porter et al. (2013) found that production of maize, rice, and wheat would be negatively impacted in the temperate and tropical regions by increasing temperatures unless adaptation strategies were adopted. Changes in climate have already begun to impact crop productivity around the world, and understanding the interactions between carbon dioxide (CO2 ), temperature, and water on plant phenology and productivity will provide a basis for the development of effective adaptation strategies.

5.3 Carbon Dioxide And Plant Growth 5.3.1

Responses of Plants to Increased CO2

Concentrations of CO2 in the atmosphere have increased from an average of 325 μmol mol−1 from the early 1970’s to nearly 400 μmol gmol1 in the present with projections of 550 μmol mol−1 by mid-century and over 700 μmol mol−1 by 2100. These changes in CO2 concentration have many positive impacts on plant growth and productivity. These studies have been conducted in a variety of chambers where the CO2 concentration could be controlled relative to the current ambient condition with the most popular technique being the free air carbon dioxide experiment (FACE) with this technology being utilized for over 39 years (Kimball, 1983; Kimball and Mauney, 1983; Kimball et al., 1999, 2001, 2002; Ainsworth and Long, 2005; Ainsworth and Rogers, 2007; Kimball, 2010). The impacts of increasing CO2 vary among plants with C4 (maize; sorghum, Sorghum biocolor L. Moench) showing a smaller response than C3 plants (barley, Hordeum vulgare L.; beans, Phaseolus vulgare L.; cotton, Gossypium hirsutum L.; peanut, Arachis hypogea L.; rice; soybean; sugarbeet, Beta vulgaris L.; wheat) for a number of physiological parameters including grain quality (Table 5.1). Overall, the response of plants to increasing CO2 is positive in the absence of temperature stress and even more positive when plants are subjected to water stress because of the impact on water use efficiency (Wu and Wang, 2000; Bernacchi et al., 2007; Chun et al., 2011; Abebe et al., 2016). The positive effect on growth and yield occurs concurrently with a decrease in conductance and crop evapotranspiration. These processes were summarized by Hatfield et al. (2011) to show how stomatal conductance is affected by increased CO2 (Table 5.1). Development of models to account for the role of CO2 concentration on photosynthetic

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Table 5.1 Response of plant physiological variables to a doubling of CO2 concentrations from research studies. Leaf Photosynthesis

Crop

Total Biomass

Grain Yield

Grain Quality

Leaf Stomatal Conductance

41, 4

−11 (protein)7

−341

Canopy Evapotranspiration

% Change 31, 2, 3

Maize

2, 7, 8

Sorghum

9

Bean

5011

Cotton

12, 13

33

11

41, 4, 5, 6 9

9

3

7

0 ,8

3011

4412, 13

36

11

−3612, 13

036 , −814

11

27

36

30

Rice

3615

3015

3015, 16

−1017,18

2219

Sorghum Wheat

−1310

2711

12, 13

Peanut

Soybean

−378

20

35

26

35

3720

2521 3422 −3820 26, 27

15−27

28, 27

31

−4020 −9 to −12 (protein)27, 29, 30, 31

−923 −1224, 25 32

−33 to −43

−833, 34, 35

Source: 1 Leakey et al. (2006), 2 Allen et al (2011), 3 Chun et al. (2011), 4 King and Greer (1986), 5 Ziska and Bunce (1997), 6 Maroco et al. (1999), 7 Abede et al. (2016), 7 Prasad et al. (2006a), 8 Wall et al. (2001), 9 Ottman et al. (2001), 10 Triggs et al. (2004), 11 Prasad et al. (2003), 12 Reddy et al. (1995), 13 Reddy et al. (1997), 14 Reddy et al. (2000), 15 Horie et al. (2000), 16 Baker and Allen (1993a),17 Baker et al. (1989), 18 Yoshimoto et al. (2005),19 Manalo et al (1994), 20 Ainsworth et al. (2002),21 Li et al. (2013), 22 Allen and Boote (2000), 23 Allen et al. (2003), 24 Jones et al. (1985), 25 Bernacchi et al. (2007), 26 Long (1991), 27 Lawlor and Mitchell(2000), 27 Mishra et al. (2013), 28 Amthor (2001), 29 Erbs et al. (2010), 30 Kimball et al. (2007), 31 Fernando et al. (2013), 32 Wall et al.(2006), 33 Andre and duCloux (1993), 34 Kimball et al. (1999), 35 Hunsaker et al. (1994), 36 Hunsaker et al. (2000).

activity show that in C3 plants photosynthesis can be limited by three different processes: 1) maximum Rubisco carboxylation capacity (V c,max ); 2) the rate in which the light reactions generate ATP and NADPH for use in the photosynthetic reduction cycle (J max ); and 3) the rate in which inorganic phosphate is released during triose phosphate utilization (Bernacchi et al., 2013). A model of photosynthesis for C4 plants shows model photosynthetic response to CO2 concentrations is limited initially by PEP carboxylase activity (V pmax ) and by Rubisco activity at higher [CO2 ] (V max ) (von Caemmerer et al. 2000). Increasing CO2 will have more of an effect on C3 plants because these limiting factors are overcome by the increased internal concentration of CO2 . In contrast, C4 plants have a saturation of CO2 at the reaction sites and don’t exhibit a photosynthetic response to increasing CO2 . These effects lead to an increase in all of the physiological parameters and translate into reduced stomatal conductance and water use leading to improved water use efficiency (Table 5.1). The increase in water use efficiency presents an advantage for plants in water-stressed environments. Leakey (2009) proposed that improved photosynthesis in C4 plants would occur under water stress conditions based on a conceptual model that the decreased stomatal conductance would reduce transpiration from the leaves and improve the internal water status of the plant. The increased gradient of CO2 because of the enhanced CO2 in the atmosphere would maintain the intercellular CO2 concentration. Allen et al. (2011) confirmed this conceptual model for maize and grain sorghum and found relatively high canopy photosynthetic rates even with decreased

5.3 Carbon Dioxide And Plant Growth

transpiration rates that resulted in enhanced water use efficiency when both plants were grown at elevated [CO2] of 720 μmol mol−1 , but not at 360 μmol mol−1 . The mechanism for smaller impact of drought on growth under increased CO2 was that the lower transpiration rate resulted in a higher leaf water potential under the higher CO2 concentrations, which created more rapid leaf area expansion leading to increased photosynthesis (Allen et al., 2011; Chun et al., 2011). Bunce (2010) showed differences among maize hybrids in their response to water stress under CO2 concentrations. These findings would suggest that the advantage C4 plants would have under marginal soil water conditions would result from their ability to maintain leaf growth, and suggested that under future conditions with higher CO2 concentrations and more variable water supply, C4 plants would have an advantage. In C3 plants, elevated CO2 increased photosynthetic rates and were limited by the Vc max under high light conditions (Bunce, 2014). Although there is an increase in photosynthesis under increased CO2 , the impact on plant growth is the observable growth parameters. Ewert and Pleijel (1999) observed in spring wheat that elevated CO2 increased the number of tillers and ears per plant by 13% at the beginning of stem elongation. Leaf area was increased throughout the growth cycle of the wheat (Ewert and Pleijel, 1999). Manalo et al. (1994) increased CO2 from 330 to 660 μmol mol−1 under three temperature regimes, 29/21, 33/25, and 37/29∘ C for rice and found tiller number and total dry weight was increased with CO2 across all temperature regimes. Different species exhibit different reactions to elevated CO2 and Franzaring et al. (2008) found for oilseed rape (Brassica napus var. Campino) this resulted in an early transition from vegetative to reproductive and earlier senescence. In their experiment, there was an increase in vegetative biomass at the cessation of flowering, but at harvest there was no difference between CO2 concentrations on seed yield. An interesting observation in this experiment on yield components was that increased CO2 was associated with an increase in the pod walls, but seed size was not affected nor was seed oil content or total oil yields (Franzaring et al., 2008). This is in contrast to the observations on oilseed rape by Frenck et al. (2011) who found that increased CO2 did not compensate for the negative yield impacts induced by high temperatures and O3 . Water stress reduces both Vc max and Jmax, while increased CO2 offsets this effect. However, continual exposure to water stress creates an acclimation effect caused by water availability (Aljazairi and Nogués, 2015). They proposed a linkage between changes in the Rubisco protein content at both low and high CO2 concentrations, under increased CO2 there was a reallocation of nitrogen from the leaf to other plant parts; however, this did not increase the sink strength for C. The implication of this research is that the accumulation of photosynthate in the leaves due to higher CO2 may not be effectively translocated to the sinks for grain development leading to a limitation in grain production. There are interactions of CO2 with O3 , and Mishra et al. (2013) showed two different wheat cultivars showed different responses to changing concentrations of both gases. There was an increase in yield of both cultivars due to a greater grain mass with no change in grain number; however, the difference between cultivars in their interaction with CO2 and O3 suggested that breeding plants to cope with climate stresses needs to consider the interactions with multiple stresses (Mishra et al., 2013). In soybean, the interaction of the rising temperatures with increasing CO2 showed that higher CO2 produced more vigorous growth at 20/15∘ C but at higher temperatures (30/25∘ C) there was a reduction in seed yield even at 700 μmol mol−1 due to a reduction in seed

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size (Heinemann et al., 2006). Li et al. (2013) observed for soybean grown at 740 μmol mol−1 compared to 380 μmol mol−1 that plant height was increased by 25.4%, leaf area by 15.8%, shoot dry weight by 33.4%, and seed yield by 25.3% under normal water and high CO2 at the seed-filling stage. Under drought conditions, the additional CO2 had no significant effect on plant height, leaf area, and seed yield, although shoot dry weight was increased by 56%. The authors attributed this effect to greater biomass allocation toward the stems. As projected by the photosynthesis models for increased CO2 , photosynthetic rates were increased by 21.7–43.3% compared to ambient CO2 levels under normal water. One of the assumptions is that there will be a positive response of plants to increasing CO2 ; however, Xu (2015) showed a differential response to increasing CO2 in wheat. The optimum photosynthetic rate occurred at 970 μmol mol−1 , Vc max at 900 μmol mol−1 , stomatal conductance at 444 μmol mol−1 and stomatal density decreased linearly above 400 μmol mol−1 (Xu, 2015). There is an up-regulation of photosynthesis by the positive changes in the biochemical processes; however, the down-regulation is related to reduced nitrogen availability, reduced stomatal conductance, and carbohydrate accumulation in leaves. Managing plants under increasing CO2 will require a greater attention to water and nutrient management to ensure the needed productivity increases required to create food security. 5.3.2

Effect of Increased CO2 on Roots

Attention has been directed on the plant shoot and yield components in response to increasing CO2. In a recent review by Madhu and Hatfield (2013) on the effect of increasing CO2 on root growth, they found across a number of species that the increased allocation of C to roots may stimulate lateral rooting and root branching. Water relations of the plants will be improved by the change in root density and proliferation that will allow to exploration of the soil to extract adequate nutrients even with reduced water use. Enhanced root growth and biomass production from increasing CO2 has the potential to increase C into the soil profile and stimulate root activity. These summaries were recently confirmed by Pacholski et al. (2015) with observations for barley, sugar beet, and wheat grown under ambient and 550 μmol mol−1 . They found increasing CO2 increased root biomass by 54% during the early vegetative period; however, there was a change in the root/shoot ratio during the growing season with differences among the species. In this study, they did not observe any significant effect of nitrogen in the soil profile on any of the root parameters other than the C:N ratio. The increased allocation of C to the roots does increase the biomass with greater partitioning into roots early in the growing season and then decreases for the remainder of the growing season. Understanding the root system response and the interactions with water and nutrients in the soil profile could help provide strategies to increase resilience to climate change. 5.3.3

Effect of Increased CO2 on Quality

Food security is not only a result of increasing the amount of production but also the quality of the grain or produce. Recent studies have shown that increasing CO2 has a potential negative effect on the quality of the grain or produce (Table 5.1). Increasing CO2 in wheat reduces the protein content in the grain (Conroy and Hocking, 1993;

5.3 Carbon Dioxide And Plant Growth

Kimball et al., 2001; Erbs et al., 2010; Fernando et al., 2012). Conroy and Hocking (1993) observed a steady decline in grain protein from 1967 to 1990 in wheat grown in Australia; however, they did not attribute this decline solely to CO2 changes but suggested that CO2 had a role. Erbs et al. (2010) evaluated CO2 enrichment and N management on grain quality in wheat and barley and found that increasing CO2 to 550 μmol mol−1 with two rates of N, adequate and half N rate, affected crude protein, starch, total and soluble В-amylase, and single kernel hardiness. They observed increasing CO2 reduced crude protein by 4 to 13% in wheat and 11 to 13% in barley but increased starch by 4% when half-rate N was applied. They concluded that nutritional and processing quality of flour will be diminished for cereal grown under elevated CO2 and low N fertilization. There was an interaction of planting date with increased CO2 in a Mediterranean environment on grain protein, S, Zn, and Fe in the grain of wheat (Fernando et al., 2012). The nutrient concentration in the grain was increased with later sowing dates. Fernando et al. (2012) showed a positive correlation between grain protein and the S, Fe, and Zn concentrations and suggested that any strategies to increase grain yields also consider protein and nutrient concentrations as part of food security. Changes in grain quality may not only be due to increased concentrations of CO2 . Increased temperatures were found to decrease grain protein content with differences between wheat varieties in their gluten response to changing temperatures (Molestad et al., 2014). Abebe et al. (2016) observed that increased CO2 (530 μmol mol−1 ) in maize not only had a large effect on grain yield but decreased the grain N content by 11%, P by 19%, and increased the K content by 5% while increasing temperatures reversed the K response. The combination of increasing CO2 and rising temperatures will affect the grain quality of plants and will need to be considered when examining adaptation strategies for climate resilience. These effects are not consistent across cultivars. Mishra et al. (2013) found an interaction between exposure of different wheat cultivars to increased CO2 and O3, with protein and total free amino-acids decreased with increasing CO2 and O3 . Total soluble sugars and starch content increased when the wheat plants were exposed to increased CO2 but decreased when only exposed to increased O3 , and reducing sugars showed an opposite trend. These observations would suggest that attention be given to cultivar differences and the background levels of O3 in future studies. In rice, Goufo et al. (2014) observed a change in the C:N ratio and total non-structural carbohydrates were increased by elevated CO2 in plant tissues while total phenolic and total flavonoids were reduced during vegetative growth and increased at maturity. These responses were due to the partitioning of photosynthetic products into proteins in the early growth stages and into phenolic compounds at maturity (Goufo et al., 2014). These findings would suggest we focus on the partitioning of photosynthates at different growth stages to more completely understand how climate change affects grain quality. These effects are not isolated to grain. In fresh vegetables there have been few observations on the expected response to increasing CO2 or temperature. Zhang et al. (2014) observed in greenhouse tomatoes (Solanum lycopersicum L.) at 800–900 μmol mol−1 CO2 enhanced health-promoting compounds in the fruit, including lycopene, b-carotene, and ascorbic acid, as well as color, firmness, flavor, aroma, and sensory attributes. To achieve food security, a focus on the quality of the grain or produce and differences among varieties is needed to understand the interactions occurring among the changing CO2 , temperature, soil water, and O3 regimes along with the

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nutrient status of the soils (Tausz et al., 2013). The current evidence suggests that these interactions will disrupt the physiological processes related to quality.

5.4 Temperature Effects on Plant Growth 5.4.1

Responses of Plants to High Temperatures Temperatures are projected to increase by 1∘ C by 2050 and as much as 5∘ C by 2100 with an increase in extreme temperature events. Each crop species will respond to this change in temperature differently depending across their life cycle upon their temperature range. Each species has a defined range of maximum and minimum temperatures within which growth occurs and an optimum temperature at which plant growth progresses at its fastest rate. Hatfield et al. (2011) provided a summary of these temperature limits for different species. Growth rates slow as temperature increases above the optimum and cease when plants are exposed to conditions in excess of their maximum temperature (Atkinson and Porter, 1996). Vegetative development (node and leaf appearance rate) hastens as temperatures increase up to the species optimum temperature and then begins to decline (Atkinson and Porter, 1996, White et al., 2013). Vegetative development usually has a higher optimum temperature than reproductive development and exposure of plants to supraoptimal temperatures during this stage can lead to decreased productivity. Progression of a crop through phenological phases is accelerated by increasing temperatures up to the species-dependent optimum temperature. Bahuguna and Jagadish (2015) described the processes through which temperature affects specific plant responses that offers a framework for assessing how changing temperatures under climate change would be realized (Figure 5.1). Temperature stresses on plants affects phenology, growth, and yield (Fuhrer, 2003) along with other ecosystem functions dependent upon temperature. Recent reviews by Hatfield et al. (2011) and Rezaei et al. (2015b) on the temperature effects on plants and reveal that as air temperatures continue to warm, the optimum temperatures are exceeded more often during the growing season and further increases in temperature will reduce yields even more than what has been observed in several studies (Lobell and Gourdji, 2012). Assessments of the magnitude of the impact of high temperature on crop yields have been determined through empirical studies (Reidsma et al., 2009; Schlenker and Roberts, 2009: Mishra and Cherkauer, 2010; Hatfield et al., 2011; Lobell et al., 2013, Tack et al., 2015; Ceglar et al. 2016). Evaluation by Lobell and Field (2007) showed that maize yields were projected to decrease 8.1% per 1∘ C and Mishra and Cherkauer (2010) showed a decrease in maize yields with increases in maximum temperatures over the Midwestern United States. These observations have been conducted using long-term records on maize and wheat (Lobell and Field, 2007; Mishra and Cherkauer, 2010; Hawkins et al., 2013; Tack et al., 2015) to show that maximum temperatures explain as much of the variation in production as precipitation. Production impacts on these crops occur when the crop is exposed to temperatures >32∘ C for maize and 28∘ C for wheat. These effects of temperature interact with drought stress, and Lobell et al. (2011) found the impact of high temperatures was 1% per degree day with no water stress and 1.7% per degree day with water stress. This effect was observed earlier when Runge (1968) observed maize yields were responsive to interactions of

5.4 Temperature Effects on Plant Growth

Tissue temperature Nutrient absorption Stomatal conductivity

Light

RH

Temperature

Minimum (Night)

Amplitude

Germination Photosysthesis Flowering time Dormancy

Maximum (Day)

Thermal perception

Signaling

Reproductive development

Source-sink regulation

Seed development and quality

Carbon use efficieny and growth

Flowering and seed set

Figure 5.1 Overview of temperature and meteorological parameters (relative humidity and solar radiation) on key physiological processes in plants. Differential plant responses with absolute minimum and maximum values and amplitude of diurnal temperature variation. Broken arrows indicate unknown or insufficient information on the mechanism regulated by a specific physiological response. Source: Reprinted with permission from Bahuguna and Jagadish. 2015. Environ. Expt. Botany. 111:83–90.

daily maximum temperature (Tmax ) and rainfall 25 days prior and 15 days after anthesis. These interactions revealed when rainfall was low (zero to 44mm per 8 days), yield was reduced by 1.2 to 3.2% per 1∘ C rise. Conversely, when temperatures were warm (Tmax of 35∘ C), yield was reduced 9% per 25.4 mm decline in rainfall. Hatfield (2016) showed through experimental evidence that growing maize varieties under normal Ames temperatures compared to normal + 4∘ C throughout the growing season increased the rate of phenological development and greatly reduced grain yield. Exposure to high temperature didn’t affect the vegetative portion of the growth cycle because leaf areas and dry weights were identical between environments; however, grain yields were reduced by over 50%. The major impact was due to the increased minimum temperatures and more rapid phenological development during the grain-filling stage. The exposure to temperatures which exceed the optimum growth temperature or the maximum temperature for significant portions of the growing season will have impacts on crop productivity. The increase in minimum temperatures has been shown to have a major impact on productivity of wheat, rice, and maize (Peng et al., 2004; Tao et al., 2006, Tebaldi et al., 2006, Peraudeau et al., 2015, Hatfield, 2016). This effect is related to the increase in respiration rates and increase in the rate of plant senescence. The rice crop has had the most extensive measurements and Tebaldi et al. (2006) suggested that night-time temperatures would have the most effect on grain yield. Nagarajan et al. (2010) found minimum

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temperatures had the greatest environmental impact on rice yield in India while Peng et al. (2004) observed 10% reduction in yield for every degree C increase above 22–24∘ C (Peng et al., 2004). To provide for food security will require we begin to understand how and why both maximum and minimum temperatures are having an impact in order to develop adaptation strategies to cope with climate change.

5.4.2

Mechanisms of Temperature Effect on Plants

Temperature has a major role in all aspects of crop growth and development from the photosynthetic process, respiration, transpiration, dry matter partitioning, development, and root growth. Barlow et al. (2015) and Rezaei et al. (2015b) provide a detailed summary of the effects of high temperatures on plant growth and development and Hatfield et al. (2011) provided a synthesis of the temperature effects on individual crop species, and these summaries are instructive to help guide future efforts in adaptation to the changing temperature regime. In general, photosynthetic rates increase linearly as the temperature increases from the base to the optimum temperature and then declines sharply as the temperatures increase above the optimum (Sage and Kubien, 2007). They found most C3 plants from high latitudes exhibited photosynthetic activity between 0 and 30∘ C while C4 plants adapted to warm or summer season were between 7 and 40∘ C. As temperatures increase above the optimum, there is a rapid decline in the photosynthetic rate that has been linked to changes in the metabolic efficiency of ribulose-1,5-biphosphate carbozylase/ozygenase (Rubisco) process and the ability to efficiently absorb light (Crafts-Brandner and Salvucci, 2002). Net assimilation in plants is a function of both photosynthetic gains and respiration losses and+ determines both growth and maintenance processes. Temperature impacts on respiration as a direct function of enzyme activity which is directly related to temperatures between 0 and 40∘ C with the Q10 of the temperature response declining from 3 to 1 as the temperature increases (Atkin and Tjoelker, 2003). Peraudeau et al. (2015) showed that under both greenhouse and field conditions in higher nighttime temperatures between 3.5 and 5.4∘ C in the greenhouse and 1.9∘ C in the field there was an increase over the growth cycle of the rice by 17–20% in the field and 8–18% in the greenhouse in potential shoot dry matter. An interesting observation in this study was that the increased respiration was between 1–7% of the potential shoot dry matter at maturity, which was not a significant loss in dry matter (Peraudeau et al., 2015). Maintenance respiration increases as temperature increases, and De Vries (1975) observed as the temperature increased from 18 to 35∘ C, maintenance respiration rates in maize increased by 80%. If we combine all of these results, one avenue for adaptation would be to more fully understand the impacts of high nighttime temperatures on the photosynthetic-respiration balance in plants. Rising CO2 concentrations increase the photosynthetic rate and also increase water use efficiency in both C3 and C4 plants. A part of the increase in water use efficiency and temperature effects on transpiration will change this balance because of the cooling effect on the actual leaf temperature that will impact both photosynthesis and respiration. The rate of transpiration from a leaf or a canopy is a function of the radiation input, vapor pressure deficit, and windspeed and can be described in this form. LE =

𝜌Cp [es (Tl ) − ea ] 𝛾 ra + rs

(5.1)

5.4 Temperature Effects on Plant Growth

With LE being the rate of water loss (transpiration of a leaf ), ρ the density of air, Cp the specific heat capacity of air, γ the psychrometric constant, es (Tl ) the saturation vapor pressure at the leaf temperature, ea the actual vapor pressure of the air surrounding the leaf, ra the aerodynamic conductance, and rs the stomatal conductance, we can utilize Eq. 1 to evaluate the linkages between different properties of the air and transpiration rate. The rs terms links the plant leaf to the environment and serves as the gateway for CO2 and water vapor to enter and exit the leaf. Hatfield et al. (2011) provided a detailed explanation of the physical and physiological processes and their interactions. Canopy temperatures of well-watered plant canopies are often much cooler than air and over the past 40 years there have been several different approaches developed to quantify crop water stress indices based on canopy temperature. The most adopted form of these indices has been the crop water stress index (CWSI) with an empirical form proposed by Idso (1982) and the theoretical form developed by Jackson et al. (1981). When water is supplied to the leaf, the leaf temperature is cooler than air because of the evaporation rate, and when the leaf begins to be subjected to water deficits then it begins to warm because the evaporation begins to decline. Both the photosynthetic and respiration processes occur within the leaf and a more accurate representation of the actual temperature determining these processes during the day would be the leaf or canopy temperature. This cooling effect would have a large impact on respiration rates projected under high air temperatures since the actual rates may be much lower because of a cooler leaf (Siebert et al., 2014). Leaf temperatures are not often measured, and physiological relations to temperature utilize air temperature because of the more available data. Higher temperatures will increase the rate of plant development causing plants to decrease their time between phenological stages and increase the rate of root development. Siebert and Ewert (2012) observed that the growing season for oats (Avena sativa L.) had decreased by nearly two weeks from 1959 through 2009 because of the increased air temperatures. Exposure to colder temperatures for vernalization is critical to flowering on winter cereals and fulfilling chilling requirements for perennial tree crops. As the temperatures exceed the optimum there is an increase in the rate of biochemical reactions causing an acceleration of crop development to maturity. This increased rate of development is the primary factor for the yield reductions found in many studies (Peng et al., 2004; Tao et al., 2006; Tebaldi et al., 2006; Lobell and Field, 2007; Mishra and Cherkauer, 2010; Hawkins et al., 2013; Tacarindua et al., 2013; Barlow et al., 2015; Peraudeau et al., 2015; Tack et al., 2015) Heinemann et al. (2006) and Tacarindua et al. (2013) found warmer temperatures increased the developmental rate in soybeans, and the yield decrease was primarily due to decreased seed size. Devasirvatham et al. (2015) observed in chickpeas (Cicer arietinum L.) that there were genetic differences in response to high temperature for phenology, growth, yield components, and grain yield. Exposure of the different genotypes to temperatures above 35∘ C had yield losses up to 39% (Devasirvatham et al., 2015). An interesting observation in this study was that cooler canopy temperatures based on canopy temperature depressions were not related to grain yield. There are several mechanisms associated with the yield reduction of crops when exposed to high temperatures during grain filling ranging from a reduction in photosynthetic efficiency, increased nitrogen and non-structural carbohydrate remobilization from plant tissue, degradation of thylakoid components, and reduction of carbon exchange rate per unit of leaf area

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(Rezaei et al., 2015b). Any one of these factors will have a negative impact on grain or fruit production. The effects described above are critical to the growth and development and production of a plant; however, one aspect of exposure of plants to high temperature is the sensitivity of the pollen to temperature stress. Temperature effects on pollination and kernel set in maize may be one of the critical responses related to climate change. Pollen viability decreases with exposure to temperatures > 35∘ C (Dupuis and Dumas, 1990). The critical duration of pollen viability (prior to silk reception) is a function of pollen moisture content and strongly dependent on vapor pressure deficit and plant water status (Fonseca and Westgate, 2005). The effects of temperature at pre-anthesis can affect the sensitivity of flowering, pollen viability, fertilization, and grain abortion (Barnabás et al., 2008). One of the suggestions for the sensitivity of pollen to temperature stress is that pollen does not produce heat shock proteins and thus lack protection against heat stress (Mascarenhas and Crone, 1996). Prasad et al. (2006a) suggested that the high temperature impacts on pollen viability and grain production in grain sorghum may be enhanced by the increased CO2 levels because these plants exhibit higher leaf temperatures. They evaluated grain sorghum grown at four temperature combinations, 32/22, 36/26, 40/30 and 44/34 ∘ C, at 350 and 700 μmol mol−1 and observed that plants grown at 40/30 and 44/34 ∘ C inhibited panicle emergence. When grown at 36/26 ∘ C compared to 32/22 ∘ C there was a decrease in pollen production, pollen viability, seed-set, seed yield, and harvest index with the decreases greater at the elevated CO2 levels. When coupled with the higher temperatures the negative effects on reproductive growth were more severe under the elevated CO2 and negated the beneficial effects of increased CO2 with higher temperature regimes. The net effect of higher temperatures on yield is due to the shortening of the grain-filling or fruit growth period even though there is an increased grain-filling rate (Dias and Lidon, 2009; Hatfield and Prueger, 2015). Rezaei et al. (2015a) suggested that shifts in phenological development for winter wheat in Germany would prevent exposure to high temperature events at anthesis; however, would not offset the detrimental impacts of high temperatures on grain yield due to the shortening of the grain-filling period. Increasing temperatures will have a detrimental impact on crop production because optimum temperatures will be exceeded more often with the potential exposure to extreme heat events during the growing season. Evidence already collected has shown temperature change is impacting productivity across crops around the world. To reduce this effectively, temperature impact will require understanding the responses of different genetic material to temperature stresses and the accompanying cultural practices that can be utilized to reduce temperature stress.

5.5 Water Effects on Plant Growth Water is essential for all life, and extremes of water availability has potential negative consequences on growth and productivity. Effects of drought on crop plants have shown that the lack of water greatly reduces crop yields and often completely destroys the crop. The projections that precipitation will become more variable with climate change will impact agricultural productivity throughout the world (Collins et al., 2013). Historically, crop losses were assumed to be due to drought stress, and Boyer (1982) found 41% of

5.5 Water Effects on Plant Growth

crop losses in the United States were caused by drought, while excess water causes crop losses of 16% of the yield losses. Potop et al. (2012) extended this type of analysis to vegetable crops in the Czech Republic and found root vegetables had reduced yield with dry summers, Brassica vegetable yields were reduced from frequent dry occurrences during growing season, fruit vegetables were affected by drought during flowering and fruit formation. However, yield reductions in fruit vegetables occurred with wet periods during June (Potop et al., 2012). The mechanisms of plant response to water stress have been detailed in a review by Hsiao (1973) in which he explained the impacts of water deficits on plant functions and revealed that in order for plants to function at their highest level they needed to have adequate water content in their cells. Water deficits in the field can cause reductions in growth and productivity of all crop species, and significant reductions in productivity can occur (Kang et al., 2009). Water stress effects can occur as a result of excess water as well as deficient water supplies and under climate change both of these extremes should be considered in discussions of changing precipitation since extreme events can occur at both the low and high end of the precipitation range. 5.5.1

Mechanisms of Water Stress

Drought stress limits crop productivity in many agroclimatic regions of the world, and improving yield under drought is the focus of many plant breeding efforts (Cattivelli et al., 2008). Drought stress in plants is first detectable as a reduction in leaf water potential or changes in cell turgor, and the visible indicator is leaf wilting or rolling (Hsiao, 1973). These changes lead to stomatal closure because of abscisic acid production affecting the guard cells (Davies and Zhang, 1991). Once the stomatal conductance decreases this reduces the intercellular CO2 concentration, a decreased mesophyll conductance affects photosynthetic metabolism (Pinheiro and Chaves, 2011), and increased leaf temperatures causing increased respiration rates (Siebert et al., 2014). The end result is a reduction in photosynthesis and a decrease in cell and plant growth (Boyer and Westgate, 2004). Wang et al. (2016) found across the Midwestern United States maize yields between 1991 through 2010 were positively correlated with drought stress in the early and middle reproductive growth stages because these stages are related to grain yield. They evaluated the difference between drought stress and aeration stress and found drought stress was the dominant factor even though the Midwest is subjected to large precipitation amounts in the spring. In a recent review of climate adaptation strategies for European agriculture, Semenov et al. (2014) proposed that a better understanding of higher temperatures and drought stresses during the booting and flowering periods would provide guidance on how to reduce losses in grain numbers and potential grain weight. One method of avoiding drought stress would be to improve water availability through more extensive root system and changes in root architecture. In wheat, Lizana and Calderini (2013) showed grain numbers and grain weight were most susceptible to reductions in water availability. Fracasso et al. (2016) in screening grain sorghum varieties for drought tolerance found differences among genetic material in the ability to maintain biomass production and tolerance indices. This resulted in a lower threshold of transpirable soil water and higher capacity to recover leaf functions after a drought stress. The ability of a plant to endure stress to reduce the effects of stress on grain yield in drought environments has been evaluated by Cattivelli et al. (2008) who proposed there were three different

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approaches with potential to increase our knowledge of drought resistance in plants. They stated these approaches were:” (i) plant physiology has provided new insights and developed new tools to understand the complex network of drought-related traits, (ii) molecular genetics has discovered many QTLs affecting yield under drought or the expression of drought tolerance-related traits, (iii) molecular biology has provided genes useful either as candidate sequences to dissect QTLs or for a transgenic approach.” Selection of genetic material capable of showing drought tolerance will provide opportunities to ensure production under increasing stressful conditions. Efeo˘glu et al. (2009) compared three maize cultivars to drought stress and observed relative water content, fresh and dry weight, and reductions in all chlorophyll forms with differences among the three cultivars. Chołuj et al. (2014) compared genetic crosses for sugarbeets (Beta vulgaris L.) for their response to imposed drought compared to full water treatments for three months of the growth cycle. Their observations revealed a differential response of the genetic material for their physiological changes that included a reduction in osmotic potential, leaf area index, efficiency of the photosynthetic process, and the absorption of the photosynthetically active radiation by the leaves. These responses were affected by leaf wilting, changes in leaf specific weight, succulence index, leaf senescence rate, and damage to the leaf membrane (Chołuj et al., 2014). Across the genetic material studied in these examples, there was a reduction in physiological functions in response to drought and changes in the leaf wilting or morphology; however, there were differences within the genetic resources that need to be more fully understood in order to screen genetic material. Since many of the drought impacts affect the physiology of the plant, attempts have been made to impart drought tolerance through changing the abscisic acid availability (Hossain et al., 2015) or phenolic content of the cell walls (Hura et al., 2012). Both of these approaches act as protectors of the photosynthetic systems and also preventing water loss from the cell wall. Avoiding drought stress on plants could be a result of selecting genetic material with greater drought tolerance or by applying chemicals to the crop that would provide some degree of protection to the physiological processes in the plant.

5.6 Interactions of Carbon Dioxide, Temperature, And Water in a Changing Climate Carbon dioxide is projected to continue to increase in the atmosphere and plants will be subjected to a fairly consistent concentration within their life cycle; however, temperature and precipitation will become more variable during and among growing seasons (Collins et al., 2013). If only one parameter were changing, then developing adaptation strategies will be more simplistic but the interactions among CO2 , temperature, and water availability induce a series of complex physiological and biochemical interactions with differential responses across phenological stages. Overall, the vegetative stage of development exhibits less sensitivity than the reproductive stage to stresses. Plant response to increasing CO2 is relatively positive in terms of growth and water use efficiency with C3 plants showing a comparative advantage over C4 plants. These increases in biomass or yield range from 10 to 40% (Table 5.1); however, for many of the crops this increase in productivity comes at the expense of decreased grain or forage

5.6 Interactions of Carbon Dioxide, Temperature, And Water in a Changing Climate

quality. Increased CO2 also benefits root growth leading to a greater exploration of the soil resource for water and nutrients and potentially increasing resilience to climate variation. The largest challenge to continue to understand in response to CO2 is how to increase grain, fruit, and forage quality and the intersection with nutrient management of the crop. Increasing temperatures have a negative impact on crop productivity and there are several reports detailing the magnitude of this impact (Lobell and Field, 2007; Reidsma et al., 2009; Schlenker and Roberts, 2009: Mishra and Cherkauer, 2010; Hatfield et al., 2011; Lobell et al., 2013, Tack et al., 2015; Ceglar et al. 2016). The impact of high temperatures on plants are most detectable during the reproductive stage of development and increase the speed of grain or fruit development at the expense of fruit size with the mechanisms shown in Figure 5.1. Rezaei et al. (2015b) outlined seven areas where our knowledge base about the effects of high temperatures needed to focus: 1) improve our understanding of the relationship between air temperature and canopy temperature relative to the temperature thresholds derived from air temperature; 2) quantify the interactions among CO2 , heat, and water stresses throughout the growing season and across genetic differences; 3) quantify the effects of within canopy temperature gradients on the temperature of the developing fruit organs; 4) determine the most appropriate representation of heat stress at larger spatial scales that include soil water status and varietal differences; 5) evaluate the interactions among cultural practices (nutrient availability, planting density, canopy architecture) and heat stress throughout the growing season; 6) quantify the time scale for heat stress accumulation; and 7) provide a more systematic comparison of heat stress across genetic material to quantify differences in heat tolerance. Adaptation strategies require a framework to assess their potential impact on the ability of the crop to remain productive under stress conditions and the development of the crop status indicator by Banerjee et al. (2015) may provide such a framework. The crop status index was developed for semi-arid wheat based on biophysical, physiological, and biochemical indicators and related to productivity (Banerjee et al., 2015) and could easily be adapted to other crops and growing regions. Variation in precipitation coupled with high temperatures lead to increasing occurrence of drought, and this effect is the dominant factor in reducing crop productivity (Kang et al., 2009). Semenov et al. (2014) presented several challenges to enhance our understanding of the water and temperature interactions. These included an improved understanding of the mechanisms through which higher temperatures and drought stress reduce sink size by reducing fruit numbers or fruit size, breeding for improved stress tolerance and screening of genetic material for drought and heat tolerance, and understanding the role of cultural practices to supply water and nutrients through more efficient root systems and root architecture. There is no single adaptation strategy that will impart resilience to climate stresses. Our understanding of the physiological and biochemical responses across species and among varieties within a crop provides a framework for how we can provide food security in the midst of increasing climate variation. This should be viewed as an opportunity to advance our understanding of the soil-plant-atmosphere interactions and embrace transdisciplinary research teams to explore these interactions across crops, environments, and cultural practices. In the end, we will develop even more robust adaptation practices to ensure food security.

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6 Scope, Options and Approaches to Climate Change Increase Crop Yield Potential Through the Understanding of Genetic Control of Plant Responses to Increased Carbon Dioxide S. Seneweera 1,3 , Kiruba Shankari Arun-Chinnappa 1 , and Naoki Hirotsu 2 1

Centre for Crop Health, University of Southern Queensland, Toowoomba, Australia Tokyo University, Japan 3 National Institute of Fundamental Studies (NIFS), Kandy, Sri Lanka 2

6.1 Introduction Carbon dioxide [CO2 ] concentration in the atmosphere increased from less than 300 μmol CO2 mol−1 before the industrial revolution to 387 μmol CO2 mol−1 by 2009, further increasing at a rate of 1.9 μmol CO2 mol−1 per year since 2000 (IPCC, 2007). This increase in atmospheric [CO2 ], along with other greenhouse gases such as methane, nitrous oxide, and halocarbons, is likely to increase the atmospheric temperature (Carter et al., 2007). The IPCC 2007 emissions scenario A1B predicts that the atmospheric [CO2 ] concentration could reach 550 μmol CO2 mol−1 by 2050 (Carter et al., 2007). For a similar increase in radiative force, the atmospheric temperature is expected to increase by 1.4 to 4.5∘ C in 2100 (IPCC, 2007). The climatic perturbations that result from the changes in the atmospheric composition are expected to have strong regional effects (Carter et al., 2007; Vadez et al., 2012). There is growing evidence suggesting that many plants of the C3 biochemical type will respond positively to increased atmospheric CO2 concentration under optimum growth conditions (Fitzgerald et al., 2016; Long et al., 2004; Sankaranarayanan et al., 2010; Seneweera et al., 2005), but the beneficial effect of elevated CO2 could be offset by other climatic stress factors, such as high temperatures and periodic drought (Ahuja et al., 2010; Fernando et al., 2014; Fitzgerald et al., 2016). Plant growth at elevated CO2 is mediated through increase in photosynthetic capacity (increased carbon gain) and reduction in stomatal conductance (improved plant water use efficiency) (Ainsworth and Rogers, 2007; Thilakarathne et al., 2015). Increased photosynthesis at elevated CO2 is largely due to a reduction in photorespiration and is directly associated with decrease in O2 /CO2 ratio at the site of the CO2 fixation (Bowes, 1991). Elevated CO2 also reduces the stomatal conductance by 30-40% at double the CO2 concentration, which leads to improved efficiency of plant water use (Leakey et al., 2012; Seneweera et al., 2001). Elevated CO2 also substantially increases radiation use efficiency by reducing photorespiration, which is likely to offset the yield loss resulting from high temperature and drought stress. For C4 plants, elevated CO2 is likely to have a much lesser impact on photosynthesis. However, C4 crops benefit from elevated CO2 under water stress conditions because stomatal conductance is reduced which leads to reduced transpiration (McMurtrie et al., 2008; Seneweera et al., 2001). Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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There is a significant amount of literature available on plant response to elevated CO2 and its influence on plant growth, productivity, and physiological and biochemical processes. Elevated CO2 also influences the changes in the biochemical composition of grains and their nutritional quality (Conroy et al., 1998; Hogy et al., 2009; Seneweera et al., 1996). Fundamental understanding of these responses is essential to improve grain quality under future climate change conditions. Crop production needs to be increased by 60% in order to sustain a global population increase from today’s 7 billion to 9 billion by 2050 (Rosegrant and Cline, 2003). Thus, feeding the growing population will be the biggest challenge in the 21st century. Simultaneously, changes in the atmospheric composition will be an additional challenge for crop production, as it will significantly modify the crop production environment. Therefore, the challenges that arise from climate change provide opportunities to apply biotechnology to improve crop yield and quality. In plant breeding or genetic engineering programs for increased crop production, photosynthesis will be one of the key targets, as the main resource for photosynthesis, CO2 , will increase unless consistent effort is tended by the global community to reduce carbon emissions. Three major targets identified for photosynthesis improvement are: the increase in efficiency of photosynthetic radiation us; reduction of photorespiration; and redesigning C3 photosynthesis with C4 traits. If Ribulose bisphosphate carboxylase/oxygenase (RuBisCO) can be engineered to completely suppress photorespiration, theoretically, the potential yield of C3 crops can be increased by up to 45% (Long et al., 2006). There have been a number of attempts to introduce more efficient C4 photosynthetic traits into C3 plants; though the progress has been limited (Matsuoka et al., 1994; Miyao and Fukayama, 2003; Sheehy et al., 1996). In this paper , an overview of plant responses to elevated CO2 concentrations, as well as the underlying causes of those responses will be discussed. Possible strategies that can be adopted to address global food security under a changing climate will also be discussed.

6.2 Impact of CO2 and climate stress on growth and yield of agricultural crop The increase in CO2 concentration to 550 μmol CO2 mol−1 , as projected to occur by the middle of the 21st century (IPCC, 2007), is likely to increase the essential resources for plant growth and development as never experienced in the recent past (Pearson and Palmer, 2000). Using over 400 experimental findings, (Kimball and Idso, 1983) Kimbal and Idso (1983) have shown that elevated CO2 can increase the yield of agricultural crops. The mean stimulation of C3 plant growth was 26% for an increase in the CO2 concentration from 340 to 660 μL CO2 L-1 . In contrast, (Ainsworth et al., 2008) Ainsworth et al. (2008) showed a 14% grain yield increase in the Free AIR CO2 Enrichment (FACE) experiment as compared to a 31% increase in enclosure studies when CO2 was raised from 373 to 570 μmol CO2 mol−1 . These responses are much lower than previously estimated. It is still unclear whether FACE studies are underestimating or enclosure systems are overestimating the response to elevated CO2 . Thus, the true magnitude of the positive “fertilization” effect of elevated CO2 is still uncertain. It has also been demonstrated that there is a large intra-specific variability in growth response to elevated CO2 . For example, plants that have large vegetative sink strength, such as woody crops have showed a 42% biomass enhancement at elevated CO2 , while wheat and rice

6.4 Interaction of Rising CO2 With Other Environmental Factors – Temperature and Water

yield will be increased only by 15%. Understanding the physiological and molecular basis of these discrepancies in response to elevated CO2 is essential in order to prepare effectively for the inevitable future changes in climate.

6.3 The Primary Mechanisms of Plants Respond to Elevated CO2 The direct response of plants to elevated CO2 results from an increase in the photosynthetic rate and a reduction in stomatal conductance. Increases in photosynthetic rates occur only in C3 species. This response to elevated CO2 is partly due to an increase in CO2 concentration at the site of fixation and the suppression of photorespiration. These responses can be easily explained by the kinetic data of RubisCO, which is the rate-limiting enzyme in the photosynthetic carbon reduction cycle (Bowes, 1991; Long et al., 2006). Meta analysis of a large number of FACE experimental data shows a 31% increase in light-saturated leaf photosynthesis and a 28% increase in diurnal photosynthetic carbon assimilation (Ainsworth and Long, 2005). However, the initial stimulation of C3 photosynthesis is not always maintained. Long-term exposure of plants to elevated CO2 reduces the potential photosynthetic rates, an adjustment known as “photosynthetic acclimation” (Moore et al., 1998; Seneweera et al., 2005; Seneweera and Norton, 2011). The majority of vascular plants uses the C3 carbon assimilation pathway and respond well to elevated CO2 . About 2–3% of plants, such as maize, sorghum, and sugar cane, belong to the C4 type, while 6–7% use Crassulacean Acid Metabolism (CAM). For C4 and CAM plants, the plant-water use efficiency is improved at elevated CO2 through the lowering of the stomatal conductance. However, the physiological mechanism of this response is still not well understood (Keel et al., 2007; Seneweera et al., 2001).

6.4 Interaction of Rising CO2 With Other Environmental Factors – Temperature and Water The positive gain from rising CO2 could be negated by rising atmospheric temperature and thereby compromise, and challenge, global food security. To address this issue, it is important to understand the interactions of these environmental signals both at the cellular and whole plant level. It has been widely reported that the optimum growth temperature for several plants has already been shown to substantially increase at elevated CO2 (Taub et al., 2000; Zhu et al., 1999). For example, optimum growth temperature will increase by 5∘ C when plants are grown at 700 μmol CO2 mol−1 concentration (Long, 1991). The underlying physiological mechanism that improves the temperature tolerance of plants under elevated CO2 is likely to be directly or indirectly linked to photosynthesis and photorespiration (Sage and Kubien, 2007). Improved kinetic properties of RuBisCO due to increases in temperature at elevated CO2 can also contribute to increased photosynthesis (Sage and Kubien, 2007). For example, in an oxygen (O2 ) rich atmosphere, as at present, the specificity of RuBisCO for CO2 is relatively low. However, under elevated CO2 conditions, the oxygenation of RuBisCO decreases as a result of the decrease in the O2 /CO2 ratio at the in-site of the CO2

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fixation, leading to a significant reduction in photorespiration. Photorespiration is a wasteful reaction and hence, the suppression of this reaction at elevated CO2 can further improve photosynthetic carbon gain, translating into increased growth and yield. Most of the C3 plants, which account nearly 95% of the plant species on earth, will increase their photosynthetic capacity and biomass production in future CO2 rich atmosphere. However, water stress will be common under climate change conditions and thus future crop productivity will depend on the availability of soil water (Ghannoum, 2009; Lawlor and Tezara, 2009). At elevated CO2 , plants produce large root volumes, an adaptive response to access more water at elevated CO2 . For example, (Wechsung et al., 1999) Wechsung et al. (1999) observed a 70% increase in the dry weight of water-stressed wheat when the plants are exposed to 550 μmol CO2 mol−1 . With C4 species, the growth response to elevated CO2 concentrations is usually maintained or even increased under mild water stress (Samarakoon and Gifford, 1996, Seneweera et al., 2001), but under severe drought, the response is much smaller (Seneweera et al., 2001). Other interactions, such as nutrient cycling, set the ultimate limit to a carbon driven, long-term stimulation of plant production (Finzi et al., 2006, Hungate et al., 2006). Increasing evidence shows that progressive nitrogen (N) limitation (i.e. mineral N declining over time) is one of the key responses to elevated CO2 concentrations. No new N input can lead to dynamic changes in both natural and managed ecosystems. It is likely that elevated CO2 can change the dynamics of nutrient turnover; thus, interdisciplinary approaches that manage this nutrient are essential, particularly to ensure food and ecosystem security in the future.

6.5 Impact of Climate Change on Crop Quality Rising CO2 concentration effects crop and pasture quality by changing the plant metabolism of carbon and nitrogen at both cellular and whole plant level (Seneweera et al., 2005). As wheat and rice are the world’s most important food sources, special focus will be given to these two crops. For rice, it is generally consumed as a cooked whole grain, the properties of the grain itself, rather than the flour, determine the quality. The main quality traits in rice are average grain weight, amylose concentration, relative paste viscosity, and nutrient concentration. The other major characteristics of rice are the appearance, milling, and cooking quality (Juliano, 1992). An increase in the atmospheric CO2 is likely to increase the firmness of the cooked grain because elevated CO2 increases the grain amylose content of rice (Seneweera et al., 1996). The amylose content in rice endosperm, one of the key traits that determine the grain firmness, is closely linked to the post-transcriptional regulation of the waxy (Wx) gene. Rice cultivars with higher amylose content produce large amounts of Wx mRNA and Wx protein (Wang et al., 1995); thus, an understanding of the regulation of the waxy gene under elevated CO2 is important to maintain the cooking quality of rice in future climate. In addition, elevated CO2 reduces a wide range of nutrients that are essential for human and animal health (Seneweera, 2011, Seneweera and Conroy, 1997). These nutrients include protein, micronutrients, amino acids, fatty acids, carbohydrate and phytate (Högy and Fangmeier, 2008; Seneweera and Conroy, 1997). In fact, zinc (Zn) and iron (Fe) deficiency has been recognized as one of the major risk factors by the World Health Organization, with Zn being the fifth leading risk factor for disease in

6.6 Climate Change, Crop Improvement, and Future Food Security

the developing world. One-third of the world’s population is at risk of Zn deficiency, ranging from 4 to 73% of a country’s population, depending on the area. Detailed understanding of the impact of elevated CO2 on grain protein and micronutrients, such as Zn and Fe is essential, in order to improve the nutrient quality of grain. Unlike rice, wheat is mainly consumed as a processed product; thus, its nutritive value and rheological characteristics determine wheat quality. Elevated CO2 increases grain starch content, which is closely associated with improved carbohydrate translocation to the grain. Similar to rice, changes in the amylose-amylopectin ratio are documented at elevated CO2 levels (Blumenthal et al., 1996; Hoegy and Fangmeier, 2008). Lipid concentration, which plays an important role in bread making, is also reduced at elevated CO2 . Reduction in the protein concentration at elevated CO2 is also significant, with the quality of gluten proteins being largely affected (Fernando et al., 2015). These proteins are closely associated with the binding of gliadin and glutenin in gluten, as well as the binding of gluten to starch in the dough, ultimately determining the rheological characteristics of the flour. Similar to rice, mineral nutrients such as Zn and Fe are also significantly reduced in grain produced at elevated CO2 , suggesting that climate change could lead to a hidden global famine of micronutrients, unless otherwise if we do not address these issue immediately.

6.6 Climate Change, Crop Improvement, and Future Food Security Rising CO2 concentrations are likely to improve the potential grain yield of most of the C3 crop plants, but accompanying changes in atmospheric temperature and periodic drought are likely to have a negative impact on the growth and yield of crops (Ghannoum, 2009; Seneweera et al., 1994; Seneweera et al., 2002). Based on the current growth rate, the world population is expected to reach 9 billion by 2050. To meet the higher food demands, crop production will need to be increased by at least 50%. Over the past decade, annual grain yields from cereal breeding programs have reached a plateau (FAO-Stat, 2008). This yield stagnation is exacerbated by population growth, land limitation, and the uncertainty of climate change, all of which are likely to lead to a global food production crisis. To address this problem, it is necessary to understand the underlying cause of this yield stagnation. There is mounting evidence that yield potentials of many crops are limited by the capacity to exploit sufficient carbon during their lifecycles (Fischer et al., 1998). In the past, higher grain yield was achieved through the introduction of semidwarf “Green Revolution” gene that encodes a mutant enzyme involved in Gibberellic Acid (GA) synthesis (Fischer et al., 1998; Okawa et al., 2002). For rice, it is very clear that source capacity is the limiting factor for high yield (Peng et al., 2008), as shown by the higher number of unfilled grains in new breeding lines. There is strong evidence that photosynthesis source capacity is strongly correlated with yield potential (Fischer et al., 1998; Poorter, 1993; Thilakarathne et al., 2015). It has been suggested that photosynthetic carbon gain can be improved by engineering rate-limiting steps in photosynthesis, thereby increasing the photosynthesis per unit leaf area. For this, it is necessary to understand the major factors controlling the photosynthetic carbon flux. The major limitations identified in C3 photosynthesis are limitations by RuBisCO and

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its kinetic properties; limitations by “regeneration,” the rate of recycling of the sugar phosphate acceptor, Ribulose bisphosphate (RuBP), (or sugar synthesis and export limitation). Improvement in photosynthesis could also be achieved by introducing a CO2 concentrating mechanism to C3 plants. In addition, there is a considerable genotypic variation in photosynthetic capacity and the maximum photosynthetic rate in leaf material at a given phonological stage under well-watered conditions. However, only a limited number of studies have been conducted regarding the breeding of crop lines for increase in photosynthesis in source organs. Thus, an understanding of the function of the photosynthetic machinery and its environmental interactions will help to manipulate plants under a changing climate in the future.

6.7 Intra-specific Variation in Crop Response to Elevated [CO2 ] - Current Germplasm Versus Wild Relatives The responsiveness to elevated [CO2 ] is varied with crop species and even within the species and considerable variation is observed. A large intra-specific variation has been reported in many economically important C3 crop species such as rice (Krishnan et al., 2011; Mohammed and Tarpley, 2010; Yang et al., 2009) and wheat (Tausz et al., 2013; Thilakarathne et al., 2012; Ziska, 2008). Thus, there is an intense interest in understanding mechanisms of how elevated [CO2 ] mediates such differential growth response within same crop species. Plant growth and yield response to elevated [CO2 ] is also dependent on the environmental and genotype interaction. Basic understanding of interaction between environment and genotype has been extensively used in plant breeding programs to increase crop yield potential (Tausz et al., 2013). This led to make major breakthrough in crop yield barriers in the recent past when background [CO2 ] was rapidly increasing (Parry and Hawkesford, 2012; Seneweera and Norton, 2011). In general, to increase the yield potential, appropriate characteristics must be selected from broad genetic background. Broadly, morphological/growth, biochemical and molecular and eco-physiological traits should be considered for such breeding experiments. These traits can be targeted to improve various component of plant process, e.g. improving yield potential (Reynolds et al., 2011), quality (Shewry et al., 2009), nutrient use efficiency (Foulkes et al., 2009), or transpiration efficiency (Richards et al. 2010). Therefore, identification of new physiological traits that can capture the response to CO2 and other environmental factors are immensely important to increase the crop productivity or improve crop quality under changing climate conditions.

6.8 Identification of New QTLs for Plant Breeding Crop yield and stress responsiveness are complex traits and normally controlled by quantitative trait loci (QTLs), and are strongly influenced by the environment. Understanding the mechanisms of plant responses to elevated [CO2 ] are important and QTL analysis is a powerful tool to dissect complex traits into single chromosome loci and to characterize them. Genotypic (based on molecular markers) and phenotypic data from a segregating population derived from experimental crosses of contrasting lines are used for QTL analysis. Coarse QTLs are mapped by identifying marker loci correlating with the phenotype. After this primary mapping, QTL will be identified

6.10 Genetic Engineering of CO2 Responsive Traits

within a chromosome region of 10-30 cM, which usually contains several hundred genes. To characterize the function of coarsely mapped QTL and to proceed for fine mapping, selection of near isogenic lines (NILs), that harbors only target QTL allele at the short chromosome segment on a single chromosome, will be required. NILs allow physiological testing evaluating the precise effect of target QTL without the effect of other segregating QTLs. Further, NILs suitable for fine-mapping of QTL region after backcrossing with parental line, called advanced backcross QTL analysis (AB-QTL). After this step, QTL will be finely mapped within a chromosome region of 1000 products in India and >3000 products in the world are being made by using maize as one of the ingredients: • • • •

Food: corn flakes, chapattis, porridge, chips and other value-added products; milk: Used to feed cattle and thus makes it as indirect part of it; chocolates/Biscuits: To give crispiness in these products corn starch used; clothes & shoes: To give smoothening and softness to clothes and leather products corn starch (malt) is used;

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• paper: Corn starch used to give strength to the paper we read and use in our daily life. • medicines: The various forms of corn starch used as constituents as well as coating agent of medicines and syrups; and • eggs and chicken: The more than 70% of the chicken food comes from maize and thus it becomes an indirect constituent for these products.

12.4 Maize Improvement Several breeding methods have been developed for maize improvement such as recurrent selection procedures and several variant of recurrent selection (RS) namely full-sib RS, half-sib RS, RS for general combining ability (gca), RS specific combing ability (sca), reciprocal RS, S1 , S2 , ear-row selection, mass selection, etc. Many of the above methods have been extensively used in the past and the literature has documented the use of the above methods (Hallauer and Miranda, 1988). Similarly, many hybrids methods have also been developed like single cross, double cross, three-way cross, double-top cross, top-cross, etc. have been developed to exploit the heterosis. Even though the single cross hybrids proposed by East (1908) and Shull (1908) has the highest yield potential but could not become practical due to the very low yield potential of inbred lines resulting in uneconomical seed production. Therefore, it remained as a concept until the availability of productive inbred lines for economical seed production. In order to exploit heterosis, Jones’s (1927) concept of double cross hybrid was practiced to produce the first double cross hybrid in the USA. The productivity of USA remained 1.88 t/ha during1865 to 1935. However, in 1935, USA switched over to double cross hybrids from open pollinated varieties. After the introduction of double cross hybrids, productivity jumped from 1.88 to 3.5 t/ha during 1935 to 1960. Thus, the double cross hybrid played an important role in doubling the USA productivity. The double cross hybrid cultivation in USA was due to poor productivity of inbred lines for promoting the single cross hybrid technology. Due to their continuous efforts in improving the productivity of inbred lines, during 1960 the USA has shifted from double cross hybrids to single cross hybrids. However, in many countries including India the double cross hybrid concept is still being practiced to exploit heterosis, which is better than the composites or open pollinated varieties (OPVs).

12.5 Single Cross Hybrids The single cross hybrid technology has advantages over the other types of cultivars developed by different breeding approaches: • To promote Mechanization: Single cross hybrids being uniform in grain size, maturity, ear placement, and plant height promotes mechanization of maize cultivation from sowing to harvesting. Further, it also helps in reducing post-harvest losses. This helps in timely operations which avoid risks associated with the vagaries of climate, saves labour, and reduces the cost of cultivation; • to reduce the operational cost: In general, single cross hybrid seed is relatively smaller and more resistant to most of the pests and diseases than other types of cultivars,

12.6 Pedigree Breeding for Inbred Lines Development

•

• •

•

•

•

which to that extent reduces seed rate, chemical required for seed treatment, seed packing material, storage space, transportation cost, etc., ultimately reducing the chemical load in the soil thus, maintaining the soil micro flora and water quality; farmers acceptance: Being uniform with respect to all the traits of maize, plant farmers cannot be cheated either by the dealers or by the marketing agencies, since even farmers can identify SCH just by seeing the seed size during sowing and plant uniformity during flowering; therefore, the SCH technology is farmer-friendly; enhances the productivity: Maize has the highest yield potential compared to any other types of cultivars; easy hybrid seed production: The single cross hybrid seed production is easy; requires less labour, low cost. It requires only two parents, three isolations for hybrid seed production, and also the maintenance of the parents as compared to other types of cultivars; to address intellectual property rights (IPR) issues and promote public private partnership (PPP): In the era of double cross, most of the indigenous companies were dependent on bigger companies in the absence of IPR. SCH technology is being commercialized by entering MoUs with the Institutions for doing fair business by paying little royalty to Institutes to strengthen their on-going programme. At the same time, the private sector benefited in saving money required for creating big R&D infrastructure. The PPP mode helps in increasing the seed of the public sector hybrid, which will make available a sufficient quantity of quality hybrid seed to farmers at affordable prices in time to cover a larger area under hybrid cultivation in order to increase the production and farm profitability. Wider adoptability: In general, hybrids are heterotic/vigorous in nature, and therefore they have wider adoptability. The hybrids developed at one location can be acceptable across different locations, thus benefitting the larger farming community. Because of a better root system, SCHs efficiently utilize the nutrient and moisture; the situation is more pronounced under erratic rainfed cultivation and prolongs the life cycle of the plant under stress. SCH research requires less resource: The SCH is homogeneous in nature unlike multi-parent cross and OPVs. Therefore, it does not need larger population to evaluate in breeding and agronomy performance, thus saving resources and efforts and improving the efficiency of the experiments.

12.6 Pedigree Breeding for Inbred Lines Development Inbred line development is achieved by continuous inbreeding. Productive inbred lines are the main strength of the single cross hybrids. The base germplasm for the development of inbred lines may be either heterozygous, heterogeneous, or heterozygous homogeneous. The type of base germplasm may be local varieties, landrace population, pools, segregating population, hybrids or open pollinated varieties (OPVs), or composites or synthetics, etc. In the present chapter, the details of the pedigree breeding method are discussed. The pedigree breeding method involves crossing two elite inbred lines followed by continuous inbreeding till phenotypic uniformity is achieved. The chromosomal crossing over and recombination are a major genetic mechanism that provides an opportunity to combine different traits in different combinations, such that the

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most desirable trait combinations may be selected in segregating populations. The F2 generation provides the first opportunity for selection by the breeder. The inbreeding from the base population may be carried out through individual plant selections for at least F7 or S8 to F8 or S9 generations, respectively, which may need 7–8 generations depending upon the genetic diversity between the inbred lines used in pedigree crosses. As a consequence of inbreeding, the percentage of homozygosity increases and subsequently the individual families will lead inbred lines. In pedigree method, the records of the ancestry or pedigree of each progeny is maintained and it is easy to trace the parentage and selection. In F2 , selection is limited to individuals. In F3 and subsequent generations, until a reasonable level of genetic homozygosity is reached, selection is practiced both within and between families. It is also called combination breeding, and provides an opportunity to generate new genetic variability for different desirable traits. The pedigree method has been proven to be the most economical and efficient method of deriving inbred lines. Pedigree breeding is practiced extensively and it is applied to combine different desirable traits, thus provides an opportunity to select plants with desirable features of both parents in the segregating progenies. The inbred lines will be grouped into male and female parents depending on the combination of desirable traits they possess. In single cross hybrid development programme, the inbred lines with most heterotic in nature will be used extensively to develop productive hybrids. Thus, the inbred-hybrid technology has become more popular and has become one of the most economical, less time and labour consuming method of maize breeding. This method (single cross hybrid) has highest yield potential as compared to all the other methods of maize breeding. The major pollination control method in maize for hybrid seed production is through removal of tassel, i.e. detasseling. 12.6.1

Seed multiplication

Inbred lines are multiplied by adopting ear-to-row method, the individual plants of an inbred line are harvested separately and grow each ear in one row by taking 20–30 seeds from each ear in the next season and keep the remnant seeds. Then each ear-to-row is evaluated for phenotypic uniformity and all those ears/rows of an inbred line are rejected which are outcross or segregated. In the next season, remnant seeds of the ears that are phenotypically uniform are collected in bulk and multiplied in isolation. 12.6.2

Single Cross Development

Although the concept of heterosis breeding or hybrid development started in the beginning of the 20th Century, its systematic application started in maize improvement from the early 1940s. In India its application commenced in the late 1990s. Hybrid breeding involves crossing between two inbred lines (synonymous to pure lines of self-pollinated crop plants), evaluation of hybrids, and identification of best hybrid combinations. It was observed across the globe that the higher the genetic differences between the inbred lines the greater will be the heterosis of the hybrids. The term heterosis refers to the superior performance of hybrids over their parental lines. The choice of parents involved in hybrid development is critical for the development of new and improved hybrids; thus, critical evaluation of potential parents for various attributes, such as performance, resistance to various biotic stresses, tolerance to different abiotic stresses as well as other quality traits is required before their consideration for hybrids development.

12.7 Preferred Characteristics for Good Parent

12.7 Preferred Characteristics for Good Parent 12.7.1

Female or Seed Parent

The selected parents should be nutrient responsive with strong roots system having stay-green trait, erect leaves, be resistant/tolerant to biotic and abiotic stresses including lodging resistance. The seed parent should be productive with long cobs having medium placement with complete exertion of cobs. The female and seed parent should have the lax tassel with a shorter anthesis-silking interval (ASI). The lax tassel, a long main branch with few secondary branches having longer pollen shedding duration, is desirable for the male parent. It is always desirable that the male parent should be taller than the female. The seed color of the parent should be attractive and decipherable. The selected parents should have high yield potential. 12.7.2

Development of Specialty Corn Schs

Due to the increase of urbanization, change in food habit, and improved economic status, the specialty corn has gained significant importance in peri-urban areas of the country. The demand of baby corn, sweet corn, and popcorn is increasing every year. With the development of specialty corn single cross hybrid (Sweet corn, Baby corn, QPM, etc.) in the public and private sector has made specialty corn cultivation very remunerative particularly in peri-urban area of India, and now there much less import of baby corn and sweet corn. Rather, India is exporting baby corn. Baby corn and sweet corn is also helping in meeting the Green Fodder requirement for the growing livestock. The country’s first baby corn (HM-4), sweet corn (HSC-1), and popcorn (BPCH-1) hybrids have been released; there are very good sweet corn hybrid in Private sector, e.g. Sugar-75 (Syngenta) is a popular sweet corn hybrid among the people. The peri-urban belt of India is emerging as a potential baby corn-producing belt. The cultivation of maize as baby corn and sweet corn has increased the income of the farmer many fold in Aterna and Manoli villages of Haryana respectively. India’s strategic location and its low cost of production as compared to many other countries will be a boon for India to export to many Asian, European and Gulf countries. One of the baby corn processing industries in India, Fresh Field, is exporting worth $1–3 million. This will help to earn foreign exchange, generate employment, and engage rural masses. Baby corn has played a significant role in ensuring livelihood security and augmenting income level of farmers in peri-urban areas. The cultivation of maize for the above purposes will not only provide year-round employment but also ensure employment to all age groups from children to age-old people. This not only checks rural to urban migration but will also absorb rural youth by providing them suitable employment by preventing them from involving in antisocial activities. This will ensure the rural masses social and livelihood security. 12.7.3

Baby Corn and Sweet Corn

Baby corn and sweet corn cultivation in the peri-urban pockets of the country will ensure livelihood security and cater to the need for green fodder for livestock promotion without any additional land. It will also reduce our dependence on the import of sweet corn and baby corn and will provide opportunity for export due to the low cost of production. Speciality corn cultivation helps the livestock industry in meeting the regular

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supply of green fodder for the growing dairy industries to increase the milk production of the country. There is 63% shortage of green fodder in the country, and cultivation of baby corn and sweet corn will help to fill this gap. 12.7.4

Quality Protein Maize (QPM)

The Productivity of QPM maize is on par with normal maize, but the biological value of QPM maize is double than the normal maize, higher than wheat and rice, and matching with milk for true protein digestibility, which helps to reduce feed requirement. The expenditure index on per unit protein production in QPM is much lower when compared to animal protein. This QPM can be used as food for nutritionally disadvantageous population of the country, especially tribal and hilly regions whose primary food is maize. Additionally, QPM can be used as nutritionally superior food for children, pregnant and lactating women, adolescent, and old age population of the country. This also provides low cost, quality feed for the promotion of the poultry industry, and in the future, 50% of the world hatcheries are likely to be shifted into India. Thus, QPM ensures food and nutritional security in India. 12.7.4.1

Improvement of Inbred Lines

If an elite line is lacking some desirable trait, it can be improved through introgressing desirable traits or gene(s) through the backcross breeding method. In maize, the backcross method has been used to transfer QTLs in order to determine yield and yield component traits. The backcross-derived inbred lines are expected to be superior over their earlier version, this method is extensively used for complimenting the specific weakness of the inbred/hybrid developed through them. In order to sustain the hybrid development program, improvement of base population through introgression of new and exotic germplasm is required, which provides a long-term breeding strategy to derive diverse and broad genetic-based superior inbred lines/ parental lines of hybrids. 12.7.4.2

Improvement of Inbred Lines through MAS

The marker assisted selection (MAS) is employed to improve the target traits through backcrossing. The MAS has several advantages over conventional backcross breeding. These advantages of MAS include that (i) it is possible to select the quantitative / semi-quantitative trait with low heritability in early stage of the crop, (ii) the selection efficiency will not be affected by G×E interactions, (iii) it avoid phenotypic evaluation in early stage of backcross breeding for some qualitative traits like provitamin A, high-lysine, and trytptophan which are quite difficult to evaluate phenotypically, (iv) reduces the backcross generations by half when the gene(s) are recessive in nature, and (iv) it will not be affected by confounding effects of gene(s) when gene pyramiding is desired. However, with the advent of new theories, markers have now been extended to select quantitative traits as well as population improvement, i.e. marker assisted recurrent selection. Marker assisted selection is employed in a stepwise manner viz., foreground selection and background selection (Figure 12.5). 12.7.4.3

Foreground selection

The term marker-assisted foreground selection was proposed by Tanksley in1983 and investigated in the context of introgression of resistance genes by Melchinger in 1990.

12.7 Preferred Characteristics for Good Parent

Recurrent Parent (P1)

Donor Parent (P2)

F1

Recurrent Parent (P1)

Figure 12.5 Schematic diagramme showing marker assisted selection.

In foreground selection, a marker either around a target gene, which is tightly linked, or within the gene (in that case, gene-assisted selection like in case of o2 locus of maize where polymorphic markers are located within the gene) is used to identify and select an individual carrying the gene to be introgressed. Marker assisted selection is very effective while transferring recessive genes, since their transfer through traditional backcrossing requires additional selfpollination after every backcrossing to recover the recessive homozygotes only then it is possible to select the desired plants carrying trait of interest, which prohibitively slow down the conventional backcross breeding program. Establishment of the marker-gene association is the first requirement in exercising the marker assisted selection for the gene of interest. Initially, morphological and isozyme markers were used to tag the gene of interest. However, with the availability of a large number of DNA based markers and the dense molecular genetic maps in most of the cultivated crop plants, the MAS has become possible for both simply inherited and quantitative traits. Successful applications of MAS in various crop plants, including maize, have been reported. The success of MAS depends upon several factors including the genetic base of the trait, the degree of the association between the molecular marker and the target gene, the number of target traits to be introgressed, the number of individuals that can be analysed, and the genetic background in which the target gene has to be transferred, etc. In India, nutritionally superior maize inbred lines have been developed by using an SSR marker, that has been located within opaque2 gene through marker assisted backcross breeding. However, with the identification of single nucleotide polymorphisms (SNPs) as well as association mapping studies in most of the crop plants, SNPs may become routine in the near future, aiding MAS very efficiently. 12.7.4.4

Background selection

In backcross breeding, selection based on the phenotype for “good agronomic type” has always been practiced along with backcrossing, but employing molecular markers

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for recurrent parent genome selection has greatly enhanced the progress of recovering the recurrent parent genome much faster than the conventional backcrossing. The objective of the background selection is to accelerate the recovery of recurrent parent genome outside the target gene so as to reduce the length of the intact chromosomal segment of the donor type dragged around the target gene on the carrier chromosome, as well as to reduce donor genome on the non-carrier chromosomes to the maximum extent. Several parameters need to be optimized in a marker assisted background selection program viz., optimal distance between target locus and flanking markers for a given population size; minimum number of individuals for detecting recombinants in a given marker interval; minimum number of data points to achieve fast completion of backcross program; allocation of marker analyses to different backcross generations. 12.7.4.5

Marker Assisted Backcross Breeding strategies (MABB)

A practical MABB scheme might differ from the basic design consisting of foreground selection and background selection: i) When the donor is an elite line, a two-step strategy involving foreground selection and background selection for marker alleles, irrespective of their position, should be considered. This strategy maximizes the recurrent parent genome recovery by BC3 with limited population size. ii) Alternately, when the introgression programme involves unadapted germplasm, emphasis should be on the elimination of linkage drag in the early backcross generations even though it may stretch the backcrossing to BC4 . iii) When the target trait is easily scorable, then phenotypic selection coupled with background selection may prove more economical. iv) When simultaneous introgressions in a number of recipient parents are desired, restricting the background selection in the advanced generation (BC3 ) may be a good option. v) Finally, when multiple target QTLs are to be introgressed, developing lines carrying individual QTLs and their subsequent inter crossing would be effective in recovering the recurrent parent genotype. Thus, the decision regarding the appropriate MABB scheme should be taken on a case-by-case basis. 12.7.4.6

MABB at What Cost?

This is the issue to be addressed in the context of developing countries like India. The most significant cost prior to MABB is the development of a genetic linkage map for the species of interest and identifications of associations between genes or Quantitative Trait Loci and economically important traits. For the last decade, many studies have been carried out in this direction (Singh and Singh 2015). Presently, for many species the above information is already available and they are in the public domain (http://www .gramene.org; http://www.maizegdb.org etc.). Other issues are funding, the development of infrastructure, the availability of expertise, the timely purchase and acquisition of consumables for molecular laboratories, and various academic formalities. It is hoped that developing countries may benefit from MABB in the near future in applied breeding schemes either by manipulating “classical” genes between elite lines or from genetic resources, or by integrating transgenic plants in the normal breeding because the benefits outweigh the cost concerns. Furthermore, by regular practicing MABB, the costs will be reduced in the end.

12.7 Preferred Characteristics for Good Parent

12.7.5

Doubled Haploid (DH) Technique

The systematic hybrid maize breeding program involves four major steps viz., the development of inbred lines, the generation and evaluation of hybrids, and the identification and subsequent release of the best performing hybrids for commercial cultivation. During this process, a breeder devotes more than 80% of his time for the development of inbred lines through the conventional approach, which is a time consuming and slow process. However, in the last couple of years doubled haploid technology has been adopted in some advanced countries like Germany, USA, etc for the rapid development of inbred lines. This technology is now being considered as promising for use in India in the future as well as for the faster progress of single cross hybrid development programme. Doubled haploid is an individual with the doubled chromosome number of the haploid. In the doubled haploid process, the offspring containing one copy of genome (haploid) will get doubled (doubled haploid) through chemical (Colchicine) treatment. Then the plants will have two identical genomes. This allows maize breeders to quickly produce inbred lines to use in the hybrid breeding program. Doubled Haploids can be produced either in-vitro and in vivo, however, the in vitro method, which is tissue culture dependent, has several inherent limitations that do not allow the practice to be utilized in large scale breeding programs. On the contrary, in-vivo haploid induction in maize was successfully demonstrated by Rober et al in 2005. By following this, the University of Hohenheim, Germany has developed haploid inducer lines viz., RWS and UH400. Thus, in vivo haploid induction and derivation of doubled haploid lines has become a widely used tool in maize. 12.7.5.1

Steps Involved In Vivo DH Inbred Lines Development

There are four steps involved in the realization of in vivo DH inbred lines (i) Development of cross by using inducer as one of the parents (ii) Selection of haploid seeds (iii) Chromosome doubling of haploid seeds/seedlings though Colchicines treatment (iv) Selfing of the diplodized individuals to obtain DH inbred lines (v) Identification and multiplication of stable doubled haploid plants. i) Development of cross by using inducer as male parent: the objective of crossing with the inducer is to obtain haploid seeds in the cross. Inducer is a genotype which selectively eliminates the complete haploid complement of the paternal chromosomes (Figure 12.6). Thus, the seed produced are haploids. Efficient production of haploids is necessary for its commercial practice; therefore, now there are efficient inducers available viz., RWS and UH400. ii) Identification of haploid kernels: The key to successful commercial application of the in vivo doubled haploid technique is a system for the efficient selection of the haploid seeds from diploid seeds. A screening system for separating the kernels with a haploid embryo from those with a regular diploid embryo has been accomplished through dominant kernel, embryo, and stem morphological markers (presence of deep purple pigmentation in the crown of the kernel and in the scutellum-embryo tissue). This has become possible because inducer lines viz., RWS and UH400 carry a dominant purple embryo & endosperm color marker (R1-nj) in their genome. R1-nj gene belongs to a family of genes that regulate the expression of anthocyanin pigment. The R1-nj allele produces a phenotype with scutellum and purple aleurone

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grains. These two features can be used as marker in the embryo and the endosperm (Figure 12.7). However, depending on the intensity of the expression of color in the embryo associated with the phenotypic marker, it is sometimes not possible to distinguish haploid embryo seeds from diploid seeds. In that case haploid plants can be distinguished from the rest of haploid plants by their weak phenotype and sterility during flowering. iii) Chromosome doubling of haploid seeds/seedlings though Colchicine treatment: Colchicine is an alkaloid which can be used for doubling the chromosome’s number of the cells because haploid chromosomal complement is most unstable during meiosis, which will lead to sterile gametes due to uneven movement of chromosomes. Therefore, artificial chromosome doubling of haploid complement before meiosis is necessary for obtaining normal diploid plants. This is accomplished by treating haploid seeds germinated for 2–3 days with colchicine (0.06%) and DMSO (0.05%) solution for 12 hrs at 18∘ C. The tip of the coleoptiles should be cut while treating with Colchicine. The mechanism of Colchicine is well understood as Colchicine prevents the formation of microtubules during cell division. In this way, the chromosomes in cells will be duplicated but not be divided. Care should be taken after Colchicine treatment by washing with water. Subsequently, the seedlings can be grown in the greenhouse with high humidity up to 5 to 6 leaf stages later can be transferred to the field. iv) Selfing of the diplodized individuals to obtain DH inbred lines: The plants developing from seeds treated with Colchicine are called the D0 generation. The diplodized plants should be fertile and should give diploid seeds after selfing but, generally, treatment with Colchicine will not double the chromosomes in all the cells, i.e. sometimes only the number of chromosomes in the ear is doubled and sometimes only the female inflorescence. Therefore, not all diplodized plants (D0 ) may give normal diploid seeds (D1 ). However, one more generation is needed to evaluate the uniformity and stability of the DH inbred lines developed (Fig. 12.8). v) Identification and multiplication of stable doubled haploid plants: the normal diplodized plants obtained will be multiplied and they will be incorporated in the ongoing hybrid breeding program. The flow chart of the use of haploid technology for line development and its integration in subsequent maize hybrid breeding program is given below. Figure 12.6 The schematic diagram shows the method of haploid induction using haploid inducer.

Female

Inducer

Maize ear with haploid and diploid kernels

12.7 Preferred Characteristics for Good Parent

Figure 12.7 Haploid kernel identification (adopted from lecture notes of George Mahuku). Donor

Outcross

Figure 12.8 Flow chart of hybrid maize breeding scheme using doubled haploid lines. Source: modified from (Robert et al, 2005).

Lethal

Inducer

Haploid Embryo

Normal F1

Season 1st

X

Inbred 1

2nd

F1

Inbred 2

Inducer

Haploid Seed Chromosome doubling 3rd

Do Selfing Evaluation of doubled haploid line for uniformity and other desirable traits (D1L) Selfing

4th 5th

6th

D2L

Tester/Line

Production of experimental hybrids Evaluation of hybrids in yield trials and identification of superior hybrids

12.7.5.2

• • • •

Advantages of DH Lines over Conventional Inbred Lines

DH method provide an opportunity to increase the efficiency of line development; DH lines are fixed for all the loci of the genome i.e. 100% homozygosity; DH lines are stable in expression over a generation; DH lines show no inbreeding depression over generations; It is envisaged that the DH technique will allow developing inbred lines/hybrid/ cultivar more rapidly than the conventional method. However, spontaneous mutation or genomic changes caused by transposable elements cannot be avoided.

12.7.6

Transgenic Maize and its Potential

In India the scarcity of labor for agriculture operation is increasing, so therefore there is a need to develop herbicide tolerant GM maize. Currently, more than 120 plant species,

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including agronomically important crops like maize, wheat, oat, barley, sorghum, pearl millet, soybean, tobacco, cotton, etc., have been transformed with the number of markers as well as agronomically important genes. Transformation of crop genomes is desirable for many purposes: increased nutritive value, plant disease resistance, insect resistance, herbicide resistance, and production traits. Presently, more than 25 countries are growing genetically modified (GM) maize across the globe with more than 42 million ha maize area is under GM category which constitutes about 26% of the total maize area of the globe. USA has the highest acreage of GM maize with almost 30 million ha i.e. >85% of USA maize is GM. Similarly, in Canada and Argentina also >85% of maize is GM maize. Other front-runner countries in commercial cultivation of transgenic maize are Brazil and South Africa. Presently GM maize is being cultivated mainly against insect/herbicide tolerance or staking of transgenes for both the traits in different countries of the World. In the recent past, SCH, coupled with herbicide tolerant (HT) and insect tolerant (IT) technologies, has revolutionized maize production in major countries like the USA (Figure 12.9), Brazil, and Argentina, etc. SCH + HT + IT technologies have significantly increased productivity in USA to the tune of 198 kg/ha/annum (1997–2009) while SCH adoption alone increased the productivity by 89 kg/ha/annum (1990–1997). HT and IT technologies have not only increased production but reduced the inoculums of weeds, pests, diseases, etc. as some of the weeds are host of pests and diseases. These technologies have also reduced the cost of cultivation and improved the farm profitability. 12.7.6.1

Abiotic Stresses

Approximately 75% of maize area in India is under rainfed conditions that depend only on rainfall received during Monsoon season. The inherent feature of the Monsoon is spatial, temporal, and intensity variabilities with respect to rainfall, temperature, and vapor pressure deficit affecting the maize production, productivity, and quality. The major abiotic stress that affects maize productivity, production, and quality is moisture stress (for example, drought and water logging). Breeding efforts are required to address these issues under climate change in the future. 120.00

HT and IT maize Intervention

100.00

Yield (q/ha)

95.91

80.00 1998–2010 Average = 91.46

60.00 40.00 20.00

79.53

1985–1997 Average = 73.55 1960–1984 Average = 52.79

After 13 yrs of intervention

Before 13 yrs of intervention

0.00 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

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Figure 12.9 Impact of GM maize in maize productivity in USA.

12.7 Preferred Characteristics for Good Parent

12.7.6.2

Drought Tolerance

Optimum growing conditions are important for normal growth and development to achieve the potential yield of any genotypes. However, drought stress seriously affects the growth and development of maize. Maize crop is highly sensitive to drought caused by deficits in moisture content in soil. It affects overall translocation of nutrients, nutrient uptake, and several other metabolic processes. Critical Stages Maize crop may get exposed to drought at any of the following growth

stage viz., seedling, vegetative stage, flowering, grain-filling, etc. The most sensitive stage for drought stress is flowering followed by grain filling. Anthesis Silking Interval (ASI) Drought condition during the flowering stage affects anthe-

sis silking interval (ASI), which leads to an increase in ASI; thus, it affects overall pollination and fertilization. Due to increased ASI, seed setting is affected thus severely reducing the yield. The moisture stress at both flowering and grain-filling stages can have a severe impact on yield where losses up to as high as 95% yield have been observed. In India, the Kharif maize often faces mid-season, i.e. flowering stage moisture stress. However, the extent of yield losses due to drought stress depends on the stage of the crop and the timing, duration, and severity of drought stress. In order to minimize the adverse effects of drought, shorter ASI is preferred. Role of Root Architecture Root architecture plays an important role in drought tolerance

mainly because roots play a critical role in sensing drought stress. The root system of maize comprises axillary and lateral roots. Axillary roots are further composed of primary, seminal, nodal or crown roots. Primary and seminal roots are collectively known as embryonic roots. Seminal roots are permanent and have a functional role in the growth and development of a plant. The mild drought stress actually stimulates root growth like elongation of root hairs. However, the severe drought stress affects and reduces the major features of roots like root length, root volume, root density and number of roots. Consequently, the above ground part of the maize plant shows symptoms of drought stress viz., leaf senescence, leaf firing, tassel firing, stomata closure due to reduced osmotic pressure, etc. Additionally, these roots play an important role in the uptake of nutrients and moisture as well as in increasing the duration of the life of the plant. Deeper and profuse lateral branches are always preferred to minimize the effects the drought stress and prolong the life of the plant. 12.7.6.3

Screening Techniques

Several screening techniques have been developed to identify drought-tolerant genotypes especially at flowering and grain-filling stage of drought stress. The most important and widely used technique is identification of genotypes with short ASI under moisture stress conditions. There are genotypes that maintain higher leaf water potential under drought stress through drought avoidance or tolerance mechanism. The other traits like erect leaves and low canopy temperature depression are other important criterion considered for identification of drought tolerant genotypes; the resistance mechanisms involved in this would be drought avoidance. The other traits like leaf erectness would reduce transpiration loss, thus provides an inherent mechanism to reduce effect of drought stress. In addition, per cent reduction in grain yield under managed

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moisture stress (drought) condition can also be an important criteria which can be considered for identification of resistant genotypes. igher yield under drought stress condition could be related to several drought adaptive traits through proper statistical analysis thus a selection index could be used for selection for drought tolerance. In addition, stay-green trait is also an ideal trait for drought tolerance, which can be exploited for breeding drought tolerance. The other management techniques are early maturing maize varieties, which mainly escape the drought stress. Hybrid maize exhibit better performance under drought stress as compared to local varieties. Thus, identification of parental lines for drought tolerance is the pre-requisite for development of drought tolerant hybrids. Since drought tolerance is a complex trait, conventional approaches required several years to develop drought tolerant hybrids. However, with the advances in molecular technologies, identification of genetic loci determining adaptive traits of drought tolerance will accelerate the process of drought tolerant cultivar development. 12.7.7

Hybrid Seed Production

Single cross hybrid seed production technology is easy, and the demand for hybrid seed will continue to increase. The cost of single cross hybrid seeds in India is lowest in the world. Large demand for single cross hybrid seed is an opportunity for seed industry growth. They will not only meet the increasing demand of the Indian farmer but can export to the neighboring countries. Due to low freight charges, India has great potential for seed export. In the year 2008–09 India has exported >12000 tons of seeds, worth US $400 million. 12.7.7.1

Pre-requisites of Single Cross Hybrid Seed Production

The most important pre-requisite for hybrid seed production is selection of ideal season as well as geographical sites/locations suitable for quality seed production of hybrid maize. The location should be free from any endemic diseases or insect pests, selection of field is very crucial to avoid voluntary plants and maintain highest genetic purity. The fertile field with assured availability of good quality irrigation water is most suitable. Usually the field where preceding crop like maize and sorghum was grown is not preferred for quality seed production. The hybrid seed production requires technically sound manpower to ensure quality seed production. The productive, uniform and genetically diverse inbred lines must be used for economical seed production. Maintain proper isolation distance is one of the most important pre-requisite to ensure highest genetic purity in hybrid seed production. 12.7.8 12.7.8.1

Important Considerations for Hybrid Seed Production Isolation Distance

If possible, the hybrid seed production should be conducted where no other maize variety/hybrid is planted nearby with the seed production plot at least 400–500 meter distance between two maize genotypes to maintain the genetic purity. The time isolation of 15 days early or later planting than other commercial maize fields helps in maintaining the genetic purity in seed production. This is mainly possible under “Seed Village Concept” by taking seed production of one hybrid in one village, which is most convenient for producing the quality seed. The “Seed Village” concept facilitates

12.7 Preferred Characteristics for Good Parent

in: overcoming isolation problems, ease in monitoring, maintaining genetic purity of seed, reduction in production cost, timely seed availability, reduction in transportation cost, improving farm profitability, employment generation to rural masses, and earning foreign exchange due to lowest seed production cost because of cheaper labor in India. 12.7.8.2

Male:female Ratio

The male to female ratio depends on pollen shedding potential of male parent and male:female synchrony (Figure 12.10). For better seed setting, either the flowering of the female should be earlier than that of the male, or the male’s pollen dehiscence should coincide with the female’s silking. In general, the male to female ratio should be 1:3:1:3:1, 1:4:1:4:1 or 1:5:1:5:1. Planting of two rows of male seed around the field avoids contamination from foreign pollens. Placing a marker in front of the male (or planting wheat or another crop’s seed in front of the male to act as marker) helps to de-tassel only the female plants, as males need not be de-tasseled. 12.7.8.3

How to Bring Male: female Synchrony?

The male to female synchrony can be brought about by staggered planting of male and female lines. The manipulation in plant distance by spaced and narrow planting, irrigation along with fertilizer application, and the application of FYM in either male or female to induce earliness and vigor also helps in bringing synchrony in parents where male anthesis happens at the time of silking in females. 12.7.8.4

Hybrid Seed Production Technology

• Soil type: fertile sandy loam to clay. • Site selection: The site should be on the main road. If it is not, then frequent monitoring during flowering (which affects genetic purity and hybrid stability due to pollen contamination) should be done. • Seasons: Weather should not be cloudy when commencing seed production. Therefore, the Rabi sowing season is preferred in different parts of the country. • Sowing time: The coincidence of extreme (either high or low) temperature or rainy period during flowering should be avoided. These conditions affect seed setting due to pollen wash caused by rain. Extreme low temperatures affect anther mortality; whereas high temperatures affect pollen viability caused by the blasting of pollen

(a)

Figure 12.10 (a). 1:3 Male–Female rows. (b). 1:2 Male-Female rows.

(b)

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•

•

•

•

•

• •

grains, which reduces the hybrid seed yield. Again, harvesting also should not coincide with the rainy period as it affects drying, shelling and viability. Seed treatment: Since each seed contribute in the final yield, seed treatment practice(s) is required for plant establishment. Timely weed management is very much required for achieving the optimum yield and to overcome competition between crop and weeds for moisture and nutrients. Nicking of parental lines: It is one of the important requirement, relatively taller and early flowering male as compared to female is selected for proper fertilization and seed setting. Wherever, there is a problem of nicking, farmers can even go for paired rows of male, which is also suggested if female parent is tall and male parent is dwarf. The other requirement for increased seed yield and seed setting: the lax type of tassel in male line, which facilitates pollen dispersal in larger area; longer pollen shedding duration etc.. In general, coincidence of complete silk emergence in female with the peak pollen shedding period of male increasesseed setting complete, i.e. up to tip. Cylindrical ear with uniform row length is preferred for higher seed yield. Female with erect leaves are preferred for proper penetration of sunlight and better photosynthesis for increased productivity. Maintaining quality hybrid seed: complete and strong husk covering is desirable which avoid moisture penetration, bird damage, discoloration and mould development. Thinning: thinning done 10–15 DAS for providing each plant with equal opportunity for proper growth, each plant will be allowed the same distance, which gives no opportunity for confusion while rouging. Improper spacing will lead to unnecessary rouging of right plants, which in turn increase the labor, cost of seed by reducing the yield due to decreases in the plant population. While grading seed size will not be same that affect the uniformity of the seed size and the seed test weight. Fertilization: Proper growth of the plants is very important; therefore, proper fertilization is very much required to reduce the soil heterogeneity. Monitoring: Monitoring should be done 2–3 times during the knee-high stage. Leaves of different angles, leaf width, leaf colour, stem colour, etc. should be rouged out. Before flowering, any plant with variation in height and vigour (either female or male) should be removed. Seed production should be avoided in order to reduce rouging efforts in cases where the previous crop was maize. Male and female rows can be clearly marked and possible intermixing of rows avoided. Detasseling: The removing of tassels row-wise should be done continuously to avoid possible escape when the tassels are at the green stage and before pollination. No tassel part in the female should be left, otherwise the commercial yield will be reduced. Any male tassels with variations in branches, length, shape, glume, glume base colour, should removed before anthesis. If ever there is any doubt for uniformity of the line, the plant should be removed in order to avoid contamination. After pollination, green cobs and green fodder can be harvested from male lines. This is possible if the male parent is productive, otherwise the green fodder is nutritious. This also solves the green fodder scarcity problem, as green fodder availability in India is a problem benefitting the livestock industry. Further, it also helps female for better growth with better light penetration. Reduces the further possibility of contamination so that it ensures there is no mixing during harvesting.

12.7 Preferred Characteristics for Good Parent

• Irrigation: After first thing (15–20 DAS), flowering, grain filling are most critical for irrigation. Mild irrigation and mild fertilization rule in hybrid seed production. Avoid seed production in poor soil, brackish soil, and water. • Monitoring: To protect the crop from bird damage it is required at least for few days. • Harvesting: it can be done either dehusked cobs, which can be dried through a mechanical drying process, otherwise the normal conventional drying process. Sun drying done up to 20% moisture content. Cobs should be covered with turpentine during the night and then kept open during day. Sorting of the cobs is required to remove variable, infested with pests and diseases, discoloured cobs. For shelling moisture at 14–15%. However, seeds will be dried up to 11–12% for storage. Grading of seeds based on size and bagging in waterproof bags is very must to maintain the viability of seeds as well as its quality. Weighing and seed treatment is also required before bagging. Specifications must be mentioned on the bags before marketing. • Increasing the seed of parental lines and maintenance of their high genetic purity: ear-to-row testing, bulking of uniform ears, and multiplication in isolation is best strategy. • Male:Female ratio: Generally it varies from 1:2 to 1:3 to 1:4 depending upon the types of parental lines used in the cross combination, the site of seed production, season etc. Even farmers can go for 1:5 to 1:6 ration if they go for paired male rows so that pollen load can be maintained for proper pollination and seed setting. Wherever there is female prolificacy then also it is necessary to go for paired male rows by planting in different dates of first and second row so that the second cob can also be get pollinated. If male is dwarf, we can go for more fertilizer application and also increase the density of male parent because closer spacing and more fertilizer application will increase the height of the male parent. If male parent height is more, then we can reduce the plant density by increasing the spacing between plants so that height can be reduced to some extent. • Advantages of applications of FYM: Increases the height, enhances the germination percentage, helps in substituting the micronutrients, and helps in uptaking of micronutrients by holding more nutrients in the root zone. Enhances the root development, retention of moisture for long time, helps in faster growth, decreases the lodging by making the plant strong and also improves soil health and fertility. • Major Diseases and Pests: If diseases appear, it can be controlled by using chemicals. In case of Fusarium stalk rot avoid sowing in the infected fields, for bacterial stalk rot, avoid water logging areas. However, resistant inbred lines can overcome the losses due to pests and diseases. The area of hot spots for pests and diseases can be avoided for hybrid seed production, because inbred lines are more sensitive to incidence of pests and diseases. Avoid previous inoculums. • Management of abiotic stresses: To maintain the humidity during pollination irrigation is required to prolong the viability of the pollen grains. • Cost of cultivation: varies from place to place, land lease cost and land preparation costs etc. • How to increase the hybrid seed yield: selection of right seed production site, by practicing proper seed production technology and by maintaining the high genetic purity.

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12.7.8.5

Hybrid Seed Production Sites

India is the country with diverse ecologies and sophisticated network of seed production agencies like NSC, SFCI, NGOs, and Private Seed Companies supported research institutes like ICAR, SAUs and favourable government policies, the task of availability sufficient quantity of quality seed to farmers does not seems difficult to achieve. Almost 90% of the total hybrid seed production of the country is confined to South India (Andhra Pradesh and Karnataka). Further, these states are covered with 100% area under hybrid cultivation with high productivity. Therefore, several alternative seed production sites viz., E. India: WB – Midnapur, Krishna Nagar, Bihar – Muzaffurpur, Begusarai, Somastipur etc (Rabi); W. India: Gujarat-Panch mahal, Dahud, Rajasthan-Baawada (Rabi); C. India: MP – Chindwada, Indore, Ratlam, Chhattisgarh – Chhattisgarh (Rabi); S. India: MS – Aurangabad, Ahmednagar, Kt – Bellary, Raichur, Shimoga (Rabi); N. India: Pb-Hr-E.UP in Rabi, Uk in Spring, J&K – Jammu, Himachal – Unnawere also identified to achieve the availability of hybrid seed at local places (Fig. 12.11). This not only increases the access to quality seed but also reduces the huge cost involved in transportation and storage. Single cross hybrid seed production also creates a win-win situation to all the stakeholders in seed chain like farmer, companies/agencies and dealers. In this context, the seed village concept can be of great use as it helps in maintaining the genetic purity of hybrid seed along with several managerial, social advantages. There are several success stories existed for seed village concept for example AP for normal maize, QPM hybrid seed production success story in West Bengal and Rajasthan. The hybrid seed production has brought favourable changes in social life of the farmers of the region by uplifting the livelihood and purchasing power of the local villagers. There is need to replicate such success stories across different states of the country. The low cost of SCH seed production increases the profit margin of the framers. Thus, encouraging the farmers to produce more and more hybrid seed, the surplus seed can be exported to neighbouring countries like Sri Lanka, Bangladesh, Myanmar, Bhutan and many African countries. India being located at strategic position in the globe the seed export brings large foreign exchange because of low cost of hybrid seed as India is near to many counties who import hybrid seed (Figure 12.11). 12.7.9 12.7.9.1

Crop Production Cropping System Optimization

Maize has wider adaptability and compatibility under diverse soil and agro-climatic conditions and hence it is cultivated in sequence with different crops under various seasons and agro-ecologies of the country. Therefore, it is considered as a potential driver of crop diversification under different agro-ecologies. The selection of the suitable crop is the key for remunerative crop production. The selection should be made on the basis of available resources and the profitability of crop production. For example, in recent years due to rising temperature at grain filling period of wheat causing terminal heat stress in central and eastern Indian states covering parts of Bihar, Gujarat, Madhya Pradesh, Rajasthan, Jharkhand and Chhattisgarh, which force to select an alternative crop that may be maize during rabi season. The less remunerative sorghum production area in Maharashtra is also shifting under maize. In Odisha, during kharif season maize is coming up as a potential alternative crop in upland area of rice cultivation. Likewise, the rice following rice areas in winter season in the states of Odisha, West Bengal, Karnataka,

12.7 Preferred Characteristics for Good Parent

Figure 12.11 SCH seed production – alternate sites.

Andhra Pradesh and Tamil Nadu facing the problem of ground water decline/shortage and in these area the maize is coming up as a potential crop. The cultivation of spring maize after harvest of potato and sugarcane has become reality in some of the states (Punjab, Haryana, western UP, lower valley of Uttrakhand) and emerged as an alternative profitable crop replacing summer rice. 12.7.9.2

Crop Sequence

Beside the selection of the suitable crop, selection of appropriate crop rotation is the key to sustainability and improving farm profitability. Among different maizebased

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cropping systems, maize-wheat system ranks first having a 1.86 million hectare area (Jat et al., 2014) mainly concentrated in rainfed ecologies and is the third most important cereal based cropping system in India. The other major maize systems in India are maize-mustard, maize–chickpea, maize–maize, cotton–maize, etc. Recently, due to changing scenario of natural resource base, rice–maize has emerged a potential maize–based cropping system in peninsular and eastern India. In peri-urban interface, maize based high value intercropping systems are also gaining importance due to market driven farming. Further, maize has compatibility with several crops of different growth habit that led to development of various intercropping systems in our country. Studies carried out under various soil and climatic conditions in different agro-ecologies of India, under All India Coordinated Research Project on Cropping Systems revealed that compared to existing predominant cropping systems like rice-wheat and rice–rice, the maize based cropping systems are better user of available resources and also at different locations the water use efficiency of maize-based cropping systems was about 100 to 200% higher. Suitable maize-based cropping and intercropping systems (Parihar et al., 2011) for various parts of the country are given in Table 12.3 and 12.4. 12.7.9.3

Best Management Practices (BMP) for Crop Establishment

12.7.9.4

Crop Establishment

The optimum temperature requirement for maize growth and development is 18–32∘ C. Temperatures above 30∘ C with very low humidity considered inhibitory for maize, but the temperature above 30∘ C with high humidity does not affect the maize. The optimum soil temperatures requirement for germination and early seedling growth is 12∘ C or greater, and at tasselling stage 21 to 30∘ C temperature is considered ideal. At flowering the noon temperature above 35∘ C with low humidity destroys pollen due to tassel blasting, which ultimately results in poor seed setting and drastically reduced yields. However, in rainfed agro-ecologies/areas, the sowing time should be coincided with onset of monsoon and it can be predicted on the basis of the figure given as below (Figure 12.12). Maize can be grown in all seasons viz; kharif (monsoon), post monsoon, Rabi (winter) and spring. During Rabi and spring seasons to achieve higher yield at farmer’s field assured irrigation facilities are required. During kharif season it is desirable to complete the sowing operation 12–15 days before the onset of monsoon. The optimum time of sowing are given Table 12.5.

Soil texture and crop rotations are the dominant factors in determining the tillage need for successful cultivation of maize in different agro-ecologies/conditions. Optimum tillage can increase spring soil dry-down rates by loosening the soil as well as improves drainage and/or reduces residue cover, which increases rates of soil moisture/water evaporation. Tillage and crop establishment is the key for achieving the optimum plant stand and is the main driver for determining the crop yield. Though the crop establishment is a series of events (seeding, germination, emergence and final establishment) that depends on interactions of seed, seedling depth, soil moisture, method of sowing, machinery, etc. but, the method of planting plays a vital role in better crop establishment under a set of growing conditions/situations. Maize is mainly sown directly through seed under different tillage and establishment methods but during winters in the areas where it was not possible to vacate the fields in time (till

12.7 Preferred Characteristics for Good Parent

Table 12.3 Maize based sequential cropping systems in different ago-climatic zones of India. Agro-climatic region

Cropping system Irrigated

Rain-fed

Western Himalayan Region

Maize–wheat Maize–potato–wheat Maize–wheat–mungbean Maize–mustard Maize–sugarcane

Maize–mustard Maize–legumes

Eastern Himalayan Region

Summer rice–maize–mustard Maize–maize Maize–maize–legumes

Sesame–Rice + maize

Lower Gangetic Plain region

Autumn rice–maize Jute–rice–maize

Rice–maize

Middle Gangetic Plain region

Maize–early potato–wheat–mungbean Maize–wheat Maize–wheat–mungbean Maize–wheat–urdbean Maize–sugarcane–mungbean

Maize–wheat

Upper Gangetic Plain region

Maize–wheat Maize–wheat–mungbean Maize–potato–wheat Maize–potato–onion Maize–potato–sugarcane–ratoon Rice–potato–maize

Maize–wheat Maize–barley Maize–safflower

Trans Gangetic Plain region

Maize–wheat Maize–wheat–mungbean Maize–potato–wheat Maize–potato–onion Mungbean–maize–toria–wheat Maize–potato–mungbean

Maize–wheat

Eastern plateau and hills region

Maize–groundnut–vegetables Maize–wheat–vegetables

Rice–potato–maize Jute–maize–cowpea

Central plateau and hills region

Maize–wheat

Maize–groundnut

Western plateau and hills region

Sugarcane + Maize

Southern plateau and hills region

Rice–maize Maize–rice

Sorghum–maize Maize–sorghum–Pulses Maize–potato–groundnut

East coast plain and hills region

Rice–maize–pearl millet Maize–rice Rice–maize Rice–rice–maize

Maize–maize–pearl millet Rice–maize + cowpea

West coast plain and hills region

Maize–pulses Rice–maize

Rice–maize Groundnut–maize (continued)

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Table 12.3 (Continued) Agro-climatic region

Cropping system Irrigated

Rain-fed

Gujarat plains and hills region

Maize–wheat

Rice–maize

Western dry region

Maize–mustard Maize–chickpea

Maize+legumes

Island region

Rice–maize

Maize–rice Rice–maize + cowpea Rice–maize–urdbean Rice–rice–maize

Table 12.4 Maize based intercropping systems. Intercropping systems

Suitable area/situation

Maize + Pigeon pea; Maize + Cowpea; Maize + Mungbean; Maize + Urdbean ; Maize + Sugarcane ; Rice + Maize ; Maize + Soybean

All maize growing areas

Maize + high value vegetables; Maize + flowers; Baby corn + vegetables; Sweet corn + vegetables

Peri-urban interface

Maize + turmeric; Maize + ginger; Maize + mungbean; Maize + Frenchbean

Hilly areas

November), transplanting can be done successfully by raising the nursery. However, the sowing method (establishment) mainly depends on several factors viz; the complex interaction over time of seeding, soil, climate, biotic, machinery and management season, cropping system, etc. Recently, conservation agriculture based resource conservation technologies (RCTs) that includes several practices viz; zero tillage, minimum tillage, surface seeding, etc. had come into practice under various maize based cropping systems and these are cost effective and environment friendly. Therefore, it is important that different situations require different sowing methods for achieving higher yield as described below: 12.7.9.5

Raised Bed / ridge and Furrow Planting

Under moisture stress condition (limited / excess moisture), in winter season and brackish water / soil condition, the raised bed / ridge and furrow planting method is considered as best planting method for maize cultivation. Sowing/planting should be done on the southern side of the east–west ridges/beds in winter season, which helps in optimum germination. Planting should be done at proper spacing depending upon the season, growing condition, plant type of genotype. The spacing may be 60–75 cm between rows and 20–25 between plants. The depth of seed should be 4–5 cm for normal maize and 2–3 cm for sweet corn if manual dibbling is done.

12.7 Preferred Characteristics for Good Parent

Bikaner

Delhi Lucknow

Guwahati

15 July Ahmedabad

1 July

Bhopal

Kolkata

15 June Mumbai 10 June

Hyderabad Goa

5 June Indian Ocean

Thiruvananthapuram 1 June

25 May

20 May

Figure 12.12 The onset of monsoon in India across different states. Table 12.5 Optimum times for sowing crops. Season

Optimum time of sowing

Kharif

Last week of June to first fortnight July

Rabi

Last week of October for inter cropping and up to 15th of November for sole crop

Spring

First week of February

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If it is machine sowing, then the raised bed planter having inclined plate, cupping or roller type seed metering systems should be used for planting that facilitates in proper placement of seed and fertilizers at proper place in one operation and that helps in getting good crop stand, higher productivity and resource use efficiency. Using raised bed planting technology, saves 20–30% irrigation water with higher crop productivity. Moreover, under temporary excess soil moisture/water logging situations due to heavy rains, the furrows formed in between the ridges will act as drainage channels and crop can be saved from excess soil moisture stress. For realizing the full potential of the bed planting technology, permanent beds are advisable wherein sowing can be done in a single pass without any preparatory tillage. Permanent beds are more beneficial under excess soil moisture situations as the infiltration rate is much higher and crop can be saved from the temporary water logging injury. 12.7.9.6

Zero-till Planting

Maize can be successfully grown without any primary tillage under no-till situation with less cost of cultivation, higher farm profitability and better resource use efficiency (Parihar et al. 2016)). Under such conditions at the time of sowing proper soil moisture should be ensure and seed and fertilizers should be placed in band using zero-till seed-cum-fertilizer planter with furrow opener as per the soil texture and field conditions. The technology is in place with large number of farmers particularly under rice–maize and maize–wheat systems in peninsular and eastern Indian agro-ecologies. However, use of appropriate planter having suitable furrow opener and seed metering system is the key for success of the no-till technology.

12.7.9.7

Conventional Till Flat Planting

Under heavy weed infestation where chemical/herbicidal weed management is uneconomical in rainfed areas where survival of crop depends on conserved soil moisture, in such situations flat planting can be done using seed-cum-fertilizer planters.

12.7.9.8

Furrow Planting

To prevent evaporative losses of soil moisture/water during spring season under flat as well as raised bed planting is higher and hence crop suffers due to moisture stress.

12.7 Preferred Characteristics for Good Parent

Under such situations/conditions, it is always advisable to grow maize crop in furrows for proper growth, seed setting and higher productivity.

12.7.9.9

Transplanting

Under intensive cropping systems where it is not possible to vacate the field on time for planting of succeeding winter maize, the chances of delayed planting exists and under delay planting crop establishment may not be proper due to low temperature so under such conditions transplanting is an alternative and well established technique for winter maize. Therefore, under the situations where fields can be vacated during December to January, it is advisable to grow nursery for transplanting the seedlings at 4–6 leaf stage in furrows and apply irrigation for optimum crop establishment. The transplanting should be done in the evening followed by immediate irrigation. Add FYM in the furrows, apply light irrigation, and then do transplanting in the furrows. This will help in accelerating the root development, increasing the water holding ability, quick establishment of the seedlings and reducing the mortality and maintaining the plant stand. For high value crops like sweet corn, seed production, the transplanting is also possible to have it as time and space isolation in seed production of parental lines / hybrid seeds which helps in production of pure and good quality seed. For planting of one hectare, 700 m2 nursery area is required and the nursery should be raised during mid-December to first week of January under protected condition to save the crop from cold and frost. It should be covered at night. The age of seedlings for transplanting should be after proper root development of 2–3 cm (4–6 leaf stage depending on the crop growth) and transplant in the month of January–February depending upon the climatic conditions in the areas.

12.7.9.10

BMP for Water Management

The irrigation water management depends on season as about 80% of maize is cultivated during monsoon season particularly under rainfed conditions. However, in the areas with assured irrigation facilities, depending upon the rains and moisture holding capacity of the soil, irrigation should be applied as and when required by the crop and first irrigation should be applied very carefully wherein water should not overflow on the ridges/beds. In general, the irrigation should be applied in furrows up to 2/3rd height of the ridges/beds. Young seedlings, knee high stage (V8 ), flowering (VT ), and grain filling (GF) are the most sensitive stages of maize crop for water stress and hence irrigation should ensured at these stages. In raised bed planting system and limited irrigation water availability conditions, the irrigation water can also be applied in alternate furrow to save the irrigation water. In rainfed areas, tied-ridges are helpful in conserving the rainwater for its availability in the root zone for longer period. For winter maize, it is advisable to keep soil wet (frequent and mild irrigation) during 15 December to 15 February to protect the crop from frost injury. Maize is sensitive to both moisture stress and excessive moisture; hence regulate irrigation according to the crop requirement with proper drainage facilities in the field. Ensure optimum moisture availability during the most critical phase (45 to 65 days after sowing); otherwise yield will be reduced to a considerable extent.

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Regulate Irrigation According to the Following Growth Phase of the Crop Germination and establishment phase

1 to 14 days

Vegetative phase

15 to 39 days

Flowering phase

40 to 65 days

Maturity phase

66 to 95 days

In the irrigated areas, the irrigation may be given as per the soil type and crop stages mentioned as below: Number of irrigation

Days after sowing

Germination and establishment

3

After sowing, 4th , 12th day

Vegetative

2

25th , 36th day

Flowering

2

48th , 60th day

Maturity phase

2

72nd , 85th day

Germination and establishment

3

After sowing, 4th , 12th day

Vegetative Phase

3

22nd , 32nd and 40th day

Flowering phase

3

50th , 60th and 72nd day

Maturity phase

2

85th , 95th day

Crop stage

Heavy soils

Light soils

Drip Irrigation in Maize: The crop must be planted in paired rows (60/90 × 30 cm) for drip irrigation to reduce cost of drippers and laterals (Fig. 12.13). Irrigation is provided once in 2 days based on climatological approach for higher water-use efficiency which is described as follows: Irrigation volume = Pe x Kp x Kc x A x Wp – Re • Pe – Pan evaporation rate (mm/day) • Kp – Pan co-efficient (0.75 to 0.80) • Kc – Crop co-efficient (0.4 – Vegetative stage; 0.75 – Flowering stage; 1.05 – Grain formation stage) • A – Area (75 x 30 cm) • Wp – Wetted percentage (80% for maize) • Re – Effective rainfall (mm) Figure 12.13 Drip Irrigation in Maize.

12.7 Preferred Characteristics for Good Parent

Table 12.6 Duration of irrigation requirement.

Irrigation duration =

Water requirement per plant once in 2 days No. of dripper / plant x Discharge rate (lph)

The duration of the irrigation can be calculated from the formula shown in Table 12.6. The more advantage of the drip irrigation will be realized when the fertilizers are applied along with the irrigation water.Ventury assembly (3/4”) with injector pump (0.5 HP) required for the drip based fertigation system. (Source: http://agritech.tnau.ac.in/ agriculture/agriirrigationmgt_maize.html). 12.7.9.11

BMP for nutrient management

Among all the cereals, maize in general and its hybrids in particular are responsive to applied nutrients either through organic or inorganic sources. The recommended fertilizer application rates depend on a number of factors and the most important ones are discussed below: 1) Cultivar and yield potential: Varieties differ in their response to applied fertilizers depending on their yield potential. Improved hybrids of maize with high yield potential will require more nutrients in order to achieve their attainable yield potential. The yields of maize cultivars will be significantly reduced if fertilizer application rates will be low. Moreover, the nutrient use efficient cultivars may require less external inputs for same yield level compared to less efficient genotypes. On the other hand, application of higher nutrient doses in low yielder composites maize cultivars will decrease nutrient-use efficiency and farm profitability. 2) Crop rotations: The continuous cereal based rotation like maize–wheat requires higher amount of nutrients compared to inclusion of legume/s in rotation with maize. The inclusion of legumes as intercrops (like soybean, mungbean, urdbean, pigeonpea, groundnut, etc) or in rotation considerably reduces N requirement in maize as carry over legume effect. Moreover, it recycles other macro and micronutrients from lower sub-soil layers to upper root zone in the form of leaf falls and thus helps in enhancing applied nutrient-use efficiency. The green manuring of legumes like dhaincha/sunhemp also reduces the nitrogen requirement in maize crop substantially. If the previous crop is cereal like wheat than full recommended dose of fertilizer is needed to get even same levels of yield. 3) Crop management: Efficient use of applied nutrients depends on soil and crop management practices and fertilizer application methods and timing affect nutrient availability. Timely weeding reduces competition for nutrients by weeds which otherwise removes large amount of nutrients. Availability of moisture/water both in terms of amount and timing also influences nutrient movement in the soil and the uptake by crop in synergistic manner. 4) Soil type: Soil fertility is determined by soil type, which in turn is based upon its depth, organic matter content and texture. N, P and S reserves are poor in soils with low organic matter content; coarse texture and a history of continuous cropping for many years are usually very low while there may be sufficient K for crop needs. Coarse texture soil with higher sand proportions requires higher nutrients to produce same yield levels compared to those with fine textured clay soils.

281

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12 Crop Production Management to Climate Change

5) Soil reaction: Essential nutrients are maximum available at pH 6.0–7.0. Thus, the differed pH may require higher amount of the nutrient to be supplied and added. A sufficient supply of all nutrients (including micronutrients) is important for a good, healthy crop and the efficient use of each applied nutrient. If the soil nutrient is present in insufficient in quantity, the plant growth and uptake of other nutrients will be limited. Soil with higher organic matter requires less external nutrients input to achieve the higher yields. 6) Climatic conditions: Response of rainfed crops to applied fertilizers is also depends on soil moisture and its availability during critical crop growth stages like seedling, knee high and reproductive. The erratic rainfall patterns make optimum yield and fertilizer requirements difficult to predict, so fertilizer use is a risky investment. When risk of drought is high, split applications of nitrogen fertilizers is advisable, with adjustments throughout the season based upon the weather conditions. Generally phosphorus (P) applied in the previous season retains some residual availability for the succeeding crop because it is not easily leachable, if prolong drought occurs after fertilizer application resulted in crop failures. 7) Residue management: Maize with the grain yield potential of 6.3 t/ha removes approximately 178 kg/ha of NPK in its straw beside sizeable quantity of other nutrients. With the introduction of improved high yielding hybrids/cultivars, the maize productivity has increased up to 5.0 t/ha in some of the Indian states like Tamil Nadu and Andhra Pradesh. Maintaining proper crop residues in the field contributes to natural cycle of nutrients and reduces the need for fertilizer nutrients specially K, Mg, Mn and Zn (Table 12.7). Thus, the fertilizer requirement will be different in residue incorporated field compared to residue removed field. The straw which is generally 4 to 5 times of the maize grain produced in the field, if it is not required for cattle feeding than it can be used for nutrient recycling in field itself under conservation agriculture-based management practices. The straw retention in filed will be beneficial for potassium management also. Table 12.7 Nutrient uptake by maize crop. Macronutrient uptake (kg/ha) Grain yield (t/ha)

Part

6.3

Grain

100

40

29

9.3

1.5

7.8

Stover

63

23

92

28

15

9

Total

163

63

121

37.3

16.5

16.8

N

P2 O5

K2 O

MgO

CaO

Micronutrient uptake (g/ha) Grain yield (t/ha)

Part

6.3

Mn

Cu

Grain

70

40

110

Stover

940

30

200

Total

1010

70

310

(Source: Aldrich et al., 1986)

Zn

S

12.8 Nutrient Management Practices for Higher Productivity and Profitability in Maize Systems

12.8 Nutrient Management Practices for Higher Productivity and Profitability in Maize Systems Maize is grown in almost all states of the countries in different seasons. The crop is largely grown under rainfed conditions where soils are not only thirsty but also hungry for nutrient too. The less consumption of fertilizer in maize with traditional varieties was one of the major reasons for low maize productivity and profitability in these ecologies. The better nutrient management will synergistically act with water to improve the maize productivity in the country. Moreover, with the adoption of single cross hybrid technology there is need for proper nutrition of the maize to harnessing the maximum benefits of these hybrids at farmers’ field. The application of organic and organic nutrient sources in right amount, at right time, right place with right method will further enhance the maize productivity in different soil types and agro-ecologies. 1) NPK Recommendation: Among all the cereals, maize in general and hybrids in particular are responsive to applied nutrients either through organic or inorganic sources. Blanket nutrient recommendation packages for different agro-ecological zones based on a normal season’s yield potential are available from most national agricultural research institutions. For raising good kharif season crop the application 150:75:50 kg/ha of N:P2 O5 : K2 O required for hybrids of medium and late duration while for early duration hybrids and composites can be grown with 100:40:25 kg/ha of N:P2 O5 : K2 O. During rabi season for cultivation of medium and late duration maize hybrid, it requires180:80:60 kg/ha of N:P2 O5 : K2 O. However, these recommendations vary in different agro-ecological situations as given in Table 12.8 Table 12.8 Recommended dose of nutrients for maize cultivation in various states. Source: Jat et al., 2014.

S. No.

Season

Recommended dose of nutrients (N: P2 O5 :K2 O kg/ha)

States

Odisha, Bihar and Madhya Pradesh

1.

Kharif

100:60:40

2.

Kharif

120:40:0

Rajasthan and Gujarat

3.

Kharif

120:60:40

Himachal Pradesh, Maharashtra, Punjab, Uttar Pradesh and Uttarakhand

4.

Kharif

150:80: 60

Chhattisgarh, Haryana, Karnataka, Jammu and Kashmir, West Bengal and Tamil Nadu

5.

Rabi

120:75:50

Bihar and Rajasthan

6.

Rabi

175:60:50

West Bengal

7.

Rabi

225:80:80

Andhra Pradesh and Tamil Nadu

8.

Spring

80:40:30

Bihar

9.

Spring

120:75:50

Punjab and Uttar Pradesh

283

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12 Crop Production Management to Climate Change

12.8.1

Timing and method of fertilizer application

One of the most important aspects of fertilizer usage is to know when, how, how much, and where fertilizers should be applied to improve the efficiency of the applied nutrients. It primarily depends on the mobility of the particular nutrient applied to soil. With nutrients that are stored efficiently in soil (i.e. P, K, S), fertilizers can be applied before planting, or banded below/side of the seed. P is immobile in soil and it should therefore be applied into the root zone during sowing. N application should be timed to coincide with periods of peak demand and rates adjusted according to rainfall received during the season via split application to reduce leaching losses. Important points for NPK management in maize cultivation: Apply NPK fertilizers as per soil test recommendation as far as possible. If soil test recommendation is not available than only adopt a blanket recommendation. The 20% N in irrigated and 34% N in rainfed conditions with full dose of P2 O5 and K2 O should be applied as basal before sowing. Nitrogen is the most important in maize production but its losses due to leaching, volatilization and fixation results in lower use efficiency. So, studies on N scheduling in maize were carried out at Delhi, Karnal, Pantnagar, Udaipur, Bahraich, Chhindwara and Srinagar Arbhavi. Results revealed that the application of N in 5-split (20% Basal, 25% V4, 30% V8, 20% VT and 5% GF) resulted significantly higher yield of QPM, sweet corn and popcorn over to 3-splits (33% at basal, 33% at V8 and 33% at VT) at Srinagar. However, the degree of yield increase varied across locations (2.5 to 22%) being lowest at Karnal and highest at Arbhavi. So, this can be used as strategy for enhancing N-use efficiency. Apply 20% N as basal and rest 80% N in four splits as top dressing varying proportions as shown in Table 12.9. If N will be applied in three splits only than apply 33% as basal and remaining as top dressing in two equal splits under rainfed conditions at around knee high and tasselling stage of the crop according to the moisture availability in the field. 12.8.2

Integrated Nutrient Management (INM)

The application of the organic manure enhances soil fertility and improves water retention besides supplying the vital macro and micronutrient for crop growth. All type of maize responds well to organic manuring and it is recommended to apply 10 to 15 tonnes/ha of organic manures before planting of crop to enhance the maize productivity and profitability. This is very much necessary for seed production plots as inbred are lesser nutrient use efficient due to their weak root system. Table 12.9 Requirements of top dressing application. S. No.

Crop Stage

Nitrogen rate (%)

1

V4 (four leaf stage)

25

2

V8 (eight leaf stage)

30

3

VT (tasseling stage)

20

4

GF (grain filling stage)

5

12.8 Nutrient Management Practices for Higher Productivity and Profitability in Maize Systems

INM is the best way of utilization of the farm waste and the enhancement in fertilizer nutrient-use efficiency apart from providing good soil health. Studies on INM in quality protein maize (QPM) and other specialty corn (Baby Corn and Sweet Corn) were conducted at various locations involving varying levels of organic and inorganic sources of nutrients. Integration of FYM and 100 to 125% recommended doses on nutrients through chemical fertilizers resulted in significantly higher yields of QPM, Baby Corn and Sweet Corn almost at all the locations. Application of FYM @ 6 ha resulted in 3 to 20% higher grain yield of QPM at different locations. 12.8.3

Biofertilizers

The seed treatment with Azotobacter/Azospirillium @ 600 g/ha found beneficial in maize production. When biofertilizer alone or cocktail is used for seed treatment in maize and soil application, 10 to 15% reduction in the total N is recommended. 12.8.4

Micronutrient Application

Zinc is the major limiting factors for maize production in India and 25 kg/ha zinc sulphate is recommended as basal application for higher maize productivity. Beside this maize crop also respond to sulphur application @ 30 kg/ha and boron application @ 1.5 kg/ha in deficient soils. 12.8.5

Slow Release Fertilizers

The one time or split application strategies of the fertilizers like neem/sulphur coated urea are having potential for decreasing the labour cost incurred in fertilizer application. Further, these products will help greatly under zero-till maize cultivation as portion of the split applied urea remained on the surface of the residue which may volatilize or immobilized. An improvement of 18% in the agronomic nitrogen-use efficiency was found with application of sulfur coated urea over prilled urea application. 12.8.6

Precision Nutrient Management

There is huge variation in Indian soil w.r.t the nutrient various nutrients content and the respond to varied fertilizer application. The 4R principles of applying right nutrient source, at right rate, at right time and at right place is expected to increase nutrient use efficiency, productivity and farm profit from maize production and provides opportunity for better environmental soundness. In-season N application adjustments of maize can be done by using leaf colour charts (LCC), SPAD and Green-Seeker sensors, etc. The crop N requirement at initial growth stage (V3 in maize) is comparatively less. It has been well established that maize starts to rapidly take up N after V6 stage, with the maximum uptake rate near silking and the diagnostic techniques such as the chlorophyll meter (SPAD-502) to monitor crop N status, were found to be good for N management. As an in-season crop N management strategy, skipping basal application and application of nitrogen as per critical SPAD values was found beneficial for improving the crop productivity.

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12 Crop Production Management to Climate Change

The SSNM can be adopted instead of blanket recommendation of nutrients application for higher resource-use efficiency. In this connection, a farmer and extension worker friendly tool “Nutrient Expert on Hybrid MaizeTM ” is being developed by International Plant Nutrition Institute which is under validation stage through AICRP on Maize. It will give the nutrient recommendation for field specific in absence or presence of the data on soil nutrient availability. This software of nutrient expert can be freely access from http://seap.ipni.net. Maize was traditionally grown as subsistence crop in rainfed ecologies until 2000, and hence there are large management yield gaps in which large proportion was contributed by imbalance and inappropriate plant nutrition with multiple nutrient deficiencies. After 2005, maize grew at very faster rate in terms of area expansion in non-traditional assured ecologies by replacing less remunerative crop/s due to its higher productivity. In this context, for enhancing and sustaining higher maize productivity and profitability will be based on balance and adequate fertilization in maize systems using all available organic and inorganic sources with proper crop rotations and application timing. 12.8.7

Conservation Agriculture and Smart Mechanization

Long-term basic and strategic research experiments were started during 2008–09 at Directorate of Maize Research, New Delhi to evaluate conservations tillage practices for improving resource use efficiency in maize based intensive cropping systems. After five years of continuous experimentation, zero tillage out yielded over permanent bed planting and conventional tillage systems in maize–chickpea–Sesbania, maize–mustard–mungbean and maize–maize–Sesbania cropping sequences. However, in maize–wheat–mungbean permanent bed planting was the best method. Soil microbial properties like higher alkaline phosphatase, dehydrogenase activity and microbial carbon in soil were also found under zero tillage compared to permanent bed and conventional tillage practices. Among the different systems under study, maize–wheat–mungbean gave the highest productivity. The soils under zero-tillage and permanent beds showed less resistance compared to conventional tillage and resulted in enhanced infiltration rate of water in the soil due to less trafficking. Among all cropping systems under investigation, maximum system productivity (maize equivalent yield) was recorded under maize–mustard–mungbean, which was followed by maize–wheat–mungbean. This may be due to inclusion of grain yield of mungbean while in Sesbania based cropping systems only dry matter was taken into consideration while the crop was used for green manuring. Therefore, to increase the monetary benefits and to maintain the soil nutrient status farmer may include legumes like mungbean, etc in their cropping sequence and to sustain the soil health Sesbania can be included as a green manure crop in their cropping sequence. Adoption of conservation agriculture based resource conservation practices like permanent beds and zero till resulted in higher carbon based sustainability index (CSI) in various maize based cropping systems. Further, it was also observed that sowing of two maize crops in sequence of any cropping system also resulted in higher CSI due to its efficient photo system being a C4 plant as compared to other C3 crops grown in the various cropping systems. The experiments on different tillage, crop establishment, residue management, tillage x weed control practices and tillage x genotype interactions in different maize

References

systems were also conducted at Pantnagar, Udaipur, Banswara, Dholi and Delhi centers. The performance of different tillage and crop establishment techniques varied across locations, but the yield at most of the locations was on par in bed planting and conventional tillage practices. However, the performance of zero-tillage across the locations was non-consistent as it recorded higher or equal yields at Dholi, Udaipur and Delhi but lower at Pantnagar compared to conventional tillage. However, due to residue retention maize yield was higher over without residue treatment. The performance of two genotypes was also evaluated at Udaipur and it was found that tillage and crop establishment techniques influenced the performance of genotypes and significantly higher yield was obtained with “HQPM 1, over “Pratap Hybrid 2” Under rice–maize system, the rice yield with conventional tillage was on par compared to zero till at Dholi and Banswara while at Hyderabad yield was significantly higher with conventional tillage over to zero tillage. In rabi the maize yield in rice–maize system under conventional tillage was significantly higher compared to zero tillage and on par with permanent bed at Banswara. Moreover, the CA based management practices involved crop production without any tillage practices hence these are helpful in reducing major cost of agriculture and can reduce up to rupees US $40 per ha a cost of the input in the scenario of escalating fuel prices. So, based on these research findings it can be said that conservation agriculture-based management practices proved beneficial in maize systems in terms of economic and environmental sustainability.

References East, E. (1908). Inbreeding in corn, pp. 419–428 In: Reports of the Connecticut Agricultural Experiment Station for Years 1907–1908. In: Connecticut Agricultural Experiment Station. New Haven: CT. Hallauer, A.R. and Miranda, F.O. (1988). Quantitative Genetics in Maize Breeding, 468. USA: Iowa State University Press. doi: 10.1007/978-1-4419-0766-0_6. Jat, M.L., Bijay-Singh, Gerard, Bruno (2014) Nutrient Management and Use Efficiency in Wheat Systems of South Asia. Adv. Agron., 125, 171–259. Jones, D.F. (1927). Double crossed Burr-Leaming seed corn. Conn. Ext. Bull. 108. Parihar, C.M., Jat, S.L., Singh, A.K. et al. (2016). Conservation agriculture in irrigated intensive maize-based systems of north-western India: Effects on crop yields, water productivity and economic profitability. Field Crops Res. 193: 104–116. Röber, F.K., Gordillo, G.A., and Geiger, H.H. (2005). In vivo haploid induction in maize – performance of new inducers and significance of doubled haploid lines in hybrid breeding. Maydica 50: 275–283. Shull, G.H. (1908). The composition of a field of maize. Am. Breeders Assoc. Rep. 4: 296–301. Singh, B.D. and Singh, A.K. (2015). Marker-assisted plant breeding: principles and practices. New Delhi: Springer.

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13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change Andreas W. Ebert Freelance International Consultant in Agriculture and Agrobiodiversity, Schwaebisch Gmuend, Germany

13.1 Introduction Vegetables can be defined as the edible portion of usually herbaceous plants. They are commonly grouped according to the part of the plant that is eaten such as leaves (lettuce), stem (celery), roots (carrot), tubers (potato), bulbs (onion) and flowers (broccoli) (UC Davis, 2014). Vegetables comprise a broad range of genera and species and are an important component of a healthy diet, providing vitamins, antioxidants, minerals, fiber, amino acids and other health-promoting compounds for nutritional security (Tenkouano, 2011). The assignment of crops into the vegetable commodity group is not easy and often confusing. Green chilies and peppers are eaten fresh in relatively large quantities and are therefore considered vegetables, while milled chili products fall into the category of spices and condiments. Similarly, garlic is treated as a vegetable in Asia, given its significant consumption in Asian dishes, while in other parts of the world it would be considered as a spice or medicinal plant. Some leguminous species grown mainly for their dry seeds constitute an important source of vegetables when harvested and consumed at the immature stage, such as seeds, green pods, and leaves. This applies to vegetable soybean (Glycine), common bean (Phaseolus), winged bean (Psophocarpus), garden pea (Pisum), mungbean (Vigna radiata), Azuki beans (Vigna angularis), cowpea (Vigna unguiculata), yard-long bean (Vigna unguiculata subsp. sesquipedalis), and black gram (Vigna mungo). Cassava leaves (Manihot esculenta) are an important leafy vegetable in many countries and should, therefore, be considered as such, although its edible starchy root constitutes the primary use of this crop. This chapter provides an overview of global vegetable production and highlights the role of genetic resources for sustainable production systems. A major focus is on ex situ and in situ conservation of vegetable genetic resources and related portals to access information on global germplasm holdings, including trait mining portals. Crop wild relatives (CWR) and landraces are highlighted, given their increasingly important role for breeding resilient varieties with multiple disease and insect pest resistance and tolerance to abiotic stresses – the foundation for sustainable vegetable production and food and nutrition security under climate change. Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

13.2 Global vegetable production From the consumption point of view, melons and watermelons in the Cucurbitaceae family normally fall under the category of fruit. However, due to their annual growth pattern and type of cultivation, which is similar to the squashes and pumpkins, these are classed as vegetables in the Food and Agriculture Organization’s (FAO) Production Statistics. Although the FAO production statistics differentiate between primary vegetables (item code 1735) and total vegetables & melons (code 1800), the production values of the two categories are the same (FAO, 2016). Primary global vegetable production reached over 1.1 billion tons in 2013-14, about 41% of total global cereal production (2 759 005 787 metric tons) (FAO, 2016). Global vegetable production is clearly on the rise, with an increase of 11% between 2009 and 2013/14 (Table 13.1). Vegetable production data are only partially available for 2014 in the FAO statistics. Hence the average of 2013/14 data is presented here. The top five global producers in 2013-14 were: China (51.3% of world production), India (10.7%), USA (3%), Turkey (2.5%, and Iran (2.1%). Regionally, more than 77% of vegetables are produced in Asia, followed by Europe, the Americas, Africa and Oceania with a comparably tiny share (Table 13.1). In 2013-14, the top 10 vegetable commodities were: fresh vegetables, not elsewhere specified, followed by tomatoes, watermelons, dry onions, cabbages and other brassicas, cucumbers and gherkins, eggplants/aubergines, carrots and turnips, green chilies and peppers, and other melons, including cantaloupes (Table 13.1). This order has not changed compared to 2009. China dominates global production of all top ten vegetable commodities with a share ranging from 26.3% (dry onions) to 76.1% (cucumbers and gherkins). From 2009 to 2013/14, global production of these ten commodities increased in the range of 5.9% for tomatoes to 17.8% for cucumbers and gherkins. Asia is dominating production of the top ten vegetable commodities with a share ranging from 60.7% for tomatoes to 94.5% for eggplants (Table 13.1). Many of the globally grown vegetable crops no longer have clear climate zone boundaries. Several crops that originated in temperate climates (leek, shallot, onion, headed cabbage, cauliflower, broccoli, Chinese cabbage, radish, bell pepper) are now grown in tropical and subtropical countries. This change was made possible by selection and breeding, as well as evolutionary adaptation processes. Similarly, vegetables of tropical origin, such as eggplant, are now successfully grown in more temperate climates.

13.3 The Role of Genetic Diversity to Maintain Sustainable Production Systems Under Climate Change Production systems and the genetic resources upon which they are based are severely threatened (Nelson et al., 2009; Lobell and Gourdji, 2012; Jackson et al., 2013). Climate change is already affecting the distribution of species, their population sizes, their behavior, and their life cycles (Pearson and Dawson, 2003; Kelly and Goulden, 2008). Potential consequences include asynchrony between the life cycles of pollinators and the flowering periods of crop plants, enhanced pathways for invasive alien species, and improved conditions for the spread of insect pests and diseases (Newton et al., 2011;

Table 13.1 Production of primary vegetables and the ten major vegetable commodities in 2009 and 2013/14, worldwide and leading countries.

Commodity

Primary vegetables

Vegetables fresh (not elsewhere specified)

Rank Leading Item 2013– country/ code 2014 World

1735

463

1

Rank 2013– Production 2014 (tons)

%

2009

Average 2013–2014

2013–14 51.27

China

1

520 084 842

580 702 354

India

2

90 634 813

121 015 200

10.68

United States of America

3

37 289 389

34 279 961

3.03

Turkey

4

26 701 516

28 280 809

2.50

Iran 5 (Islamic Republic of )

18 454 097

23 651 582

2.09

Others

326 329 873

344 669 608

30.43

World

1 019 494 530 1 132 599 514

100.00

China

1

148 000 000

161 000 000

57.55

India

2

28 006 300

33 213 000

11.87

Vietnam

3

6 500 000

12 500 531

4.47

Nigeria

4

4 536 383

6 180 000

2.21

Philippines

5

4 382 818

5 000 000

1.79

Others

56 506 966

61 846 509

22.11

World

247 932 467

279 740 040

100.00

Percent increase Yield 2009– 2013/ 2013/14 2014 Hg/ha

Production shared by region (%); 2013–14

Total (%)

Asia Africa Americas Europe Oceania

11.09

195 301 77.4 6.5

8.5

7.3

0.3

100

12.83

141 862 86.7 6.4

2.6

4.1

0.2

100 (continued)

Table 13.1 (Continued)

Commodity

Item code

Rank 20132014

Tomatoes

388

2

Watermelons

567

3

Leading country/ World

Rank 20132014

China

1

45 266 000

50 552 200

30.93

India

2

11 148 800

18 227 000

11.15

United States of America

3

14 181 320

12 574 550

7.69

Turkey

4

10 745 572

11 820 000

7.23

Egypt

5

10 278 539

8 533 803

5.22

Others

62 786 235

61 726 488

37.77

World

154 406 466

163 434 041

100.00

Production (tons)

%

China

1

64 784 679

72 943 838

66.96

Iran (Islamic Republic of )

2

3 074 581

3 947 057

3.62

Turkey

3

3 810 215

3 887 324

3.57

Brazil

4

2 065 167

2 163 501

1.99

Egypt

5

288 492

1 894 738

1.74

Others

24 625 023

24 096 109

22.12

World

98 648 157

108 932 567

100.00

Percent increase 20092013/14

Yield 2013/ 2014

Production shared by region (%); 2013-14

5.85

348 597

60.7

11.1

15.1

12.8

0.3

100

10.43

313 833

83.7

5.3

5.8

5.1

0.2

100

Total (%)

Onions, dry

Cabbages and other brassicas

Cucumbers and gherkins

403

358

397

4

5

6

China

1

21 000 000

22 300 000

26.31

India

2

12 158 800

19 299 000

22.77

United States of America

3

3 429 100

3 159 400

3.73

Iran (Islamic Republic of )

4

320 790

2 381 551

2.81

Russian Federation

5

1 601 550

1 984 937

2.34

Others

35 264 642

35 633 303

42.04

World

73 774 882

84 758 191

100.00

China

1

29 625 000

31 700 000

44.38

India

2

6 869 600

8 534 000

11.95

Russian Federation

3

3 312 090

3 328 876

4.66

Republic of Korea

4

2 848 009

2 434 415

3.41

Japan

5

2 309 100

2 356 862

3.30

Others

21 272 594

23 079 927

32.31

World

66 236 393

71 434 080

100.00

China

1

44 204 000

54 315 900

76.14

Turkey

2

1 735 010

1 754 613

2.46

Iran (Islamic Republic of )

3

1 603 737

1 570 078

2.20

Russian Federation

4

1 132 730

1 068 000

1.50

Ukraine

5

883 000

1 044 300

1.46

Others

10 997 095

11 580 522

16.23

World

60 555 572

71 333 413

100.00

14.89

193 333

67.6

10.2

11.0

10.9

0.4

100

7.85

292 378

74.5

5.8

3.4

16.2

0.2

100

17.80

337 201

88.0

1.7

2.8

7.5

0

100

(continued)

Table 13.1 (Continued)

Commodity Eggplants (aubergines)

Carrots and turnips

Item code

Rank 20132014

Leading country/ World

Rank 20132014

Production (tons)

399

7

China

1

25 885 000

28 433 500

India

2

10 377 600

13 444 000

27.25

Iran (Islamic Republic of )

3

862 159

1 354 185

2.74

426

8

%

Percent increase 20092013/14

Yield 2013/ 2014

Production shared by region (%); 2013-14

14.89

264 807

94.5

3.3

0.5

1.7

0

100

10.80

310 652

62.3

5.2

8.9

22.7

1.0

100

Total (%)

57.63

Egypt

4

1 290 190

1 194 115

2.42

Turkey

5

816 134

826 941

1.68

Others

3 713 129

4 086 993

8.28

World

42 944 212

49 339 734

100.00

China

1

15 057 000

16 829 000

45.23

Uzbekistan

2

995 000

1 641 842

4.41

Russian Federation

3

1 518 650

1 604 656

4.31

United States of America

4

1 626 830

1 290 285

3.47

Ukraine

5

686 400

930 100

2.50

Others

13 697 845

14 913 587

40.08

World

33 581 725

37 209 470

100.00

Chillies and peppers, green

Other melons (including Cantaloupes)

401

568

9

10

China

1

14 500 000

15 800 000

50.78

9.62

Mexico

2

1 941 564

2 994 400

Turkey

3

1 837 003

2 159 348

6.94

Indonesia

4

1 378 727

1 726 382

5.55

Spain

5

932 191

999 600

3.21

Others

7 481 366

7 437 214

23.90

World

28 070 851

31 116 944

100.00

12 153 387

14 336 814

48.77

China

1

Turkey

2

1 679 191

1 699 550

5.78

Iran (Islamic Republic of )

3

1 278 542

1 501 411

5.11

Egypt

4

918 360

1 020 679

3.47

India

5

812 895

1 000 000

3.40

Others

8 660 320

9 836 088

33.46

World

25 502 695

29 394 542

100.00

10.85

161 130

68.7

9.2

12.7

9.3

0.1

100

15.26

248 831

72.5

6.8

13.6

6.8

0.3

100

Source: Statistics Division of FAO. Available at: http://faostat3.fao.org/home/E (accessed 05 March 2016).

296

13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

Keatinge et al., 2014). Efficient adaptation strategies for a changing climate require, among other measures, the preservation of the remaining biodiversity, both in situ as well as in genebanks, and access to genetic resources of crops and their wild relatives (HPLE, 2012). The foundation of the current world food supply is based on thousands of years of crop selection, and improvement carried out on wild and semi-domesticated species (crop wild relatives) and landraces (McCouch, 2004). Present-day cultivated varieties are descendants of those crop wild relatives; the wild species often had low yields and poor taste but were adapted to marginal environments. These wild genes strongly influence agronomic characteristics such as phenology, growing seasons, sensitivity to inputs such as fertilizer and water, resistance to disease and insect pests and tolerance to heat, drought, and salinity. The availability and accessibility of high genetic diversity thus are critical for plant breeding when environmental conditions are changing. The diversity of plant genetic resources provides farmers and plant breeders with the necessary genetic base to enhance crop performance of cultivated varieties under climate change scenarios. Moreover, genetic diversity gives rise to the multitude of characteristics that enable plants and animals to fulfill different roles in the environment. Such diversity will ensure the continued functioning of the ecosystem and the provisioning of ecosystem services because different genotypes perform slightly different functions and occupy different environmental niches (Newton et al., 2011). This is why the conservation and sustainable utilization of genetic resources for food and agriculture is key to maintaining and enhancing the efficiency and the resilience of agroecosystems. The increased environmental variability that is expected to result from climate change implies that in the future, farmers and plant breeders will need access to an even wider range of plant genetic resources for food and agriculture (PGRFA) than today (FAO, 2010; Khoury et al., 2015).

13.4 Ex Situ Conservation of Vegetable Germplasm at The Global Level There is a considerable overlap of genetic resources of vegetables and melons with other commodity groups such as cereals (Amaranthus), food legumes (Phaseolus, Psophocarpus, Glycine, Pisum, Vigna radiata, V. unguiculata, V. angularis, V. mungo), and fiber crops (Corchorus). Taking this overlap into consideration, there are approximately one million accessions of vegetables and melons conserved ex situ worldwide (Ebert, 2013). In a narrower sense, as reviewed by FAO in the second report on the state of the world’s plant genetic resources for food and agriculture, the genetic resources of vegetables conserved ex situ comprise about 503 000 accessions representing 7% of the globally held 7.4 million accessions of plant genetic resources (FAO, 2010). The figures presented in this chapter on vegetable germplasm collections held ex situ worldwide (Table 13.2) are restricted to the top ten primary vegetable commodities, except the diverse group of fresh vegetables, not elsewhere specified (Table 13.1; FAO, 2016). The important group of cucurbits (pumpkins, squashes, gourds) currently ranked 12th in the FAO statistics has been included as well. The data were extracted from the FAO database World Information and Early Warning System (WIEWS) on Plant Genetic Resources for Food and Agriculture (PGRFA) (WIEWS, 2016). The WIEWS

13.4 Ex Situ Conservation of Vegetable Germplasm at The Global Level

Table 13.2 Major ex situ vegetable germplasm collections of the top ten commodity groups (see Table 13.1) held worldwide. Genus

Crop group

Allium

Onion, garlic, shallot, etc.

Genebank

Country

Accessions

Institute code Acronym

Onion, garlic, shallot, etc.

No.

(%)

IND1457

NRCOG

India

2050

6.98

RUS001

VIR

Russia

1888

6.42

JPN003

NIAS

Japan

1352

4.60

USA003

NE9

USA

1304

4.44

DEU146

IPK

Germany

1264

4.30

TWN001

AVRDC

Taiwan

1129

3.84

GBR004

RBG

UK

1100

3.74

USA022

W6

USA

1066

3.63

GBR165

SASA

UK

1005

3.42

Others

Others

17 229

58.63

Total

World

29 387 100

NBPGR

India

10 140

9.92

CHN001

ICS-CAAS

China

9769

9.56

IND073

AICRP-Rapeseed India

7314

7.16

IND1453

NRCRM

India

5440

5.32

CHN003

Inst. Oil C. Res.

China

5168

5.06

n/a

AGG

Australia

4060

3.97

JPN003

NIAS

Japan

3987

3.90

RUS001

VIR

Russia

3503

3.43

GBR006

HRIGRU

UK

3355

3.28

CHN004

BVRC

China

3101

3.03

GBR165

SASA

UK

2901

2.84

DEU146

IPK

Germany

2210

2.16

USA003

NE9

USA

2167

2.12

Allium Brassica

Cabbages, broccoli, rape…

IND001

BGD028

BINA

Bangladesh

2100

2.05

DEU271

IPK

Germany

2069

2.02

USA020

NC7

USA

2002

1.96

TWN001

AVRDC

Taiwan

1939

1.90

FRA215

GEVES

France

1396

1.37

NLD037

CGN

Netherlands 1386

1.36

ETH085

EIB

Ethiopia

1332

1.30

VNM006

FCRI

Vietnam

1300

1.27

FRA010

INRA-RENNES

France

1215

1.19

IND218

IARI

India

1200

1.17

(continued)

297

298

13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

Table 13.2 (Continued) Genus

Brassica

Crop group

Cabbages, broccoli, rape…

Genebank

Country

BGR001

IPGR

Bulgaria

1207

1.18

CAN004

PGRC

Canada

1157

1.13

PAK001

PGRP

Pakistan

1013

0.99

CZE065

OSEVA-OPAVA

Czech Rep.

973

0.95

PRT001

BPGV-DRAEDM

Portugal

939

0.92

BRA012

CNPH

Brazil

934

0.91

Others

Others

16 916

16.55

Total Capsicum

Sweet & hot pepper

Sweet & hot pepper

TWN001 AVRDC

Watermelon

World

102 193 100

Taiwan

8263

11.27 6.41

USA016

S9

USA

4698

MEX008

INIFAP

Mexico

4661

6.36

IND001

NBPGR

India

3835

5.23

MEX003

CIFAP-CEL

Mexico

3590

4.90

MEX009

INIA

Mexico

3590

4.90

BRA006

IAC

Brazil

2321

3.17

JPN003

NIAS

Japan

2271

3.10

BRA012

CNPH

Brazil

2000

2.73

PHL130

CSC-IPB,UPLB-CA Philippines

1880

2.56

TWN005 TSS-PDAF

Taiwan

1800

2.46

DEU146

IPK

Germany

1526

2.08

CHN004

BVRC

China

1394

1.90

FRA011

INRA-UGAFL

France

1371

1.87

TUR001

AARI

Turkey

1334

1.82

RUS001

VIR

Russia

1273

1.74

MEX005

INIA

Mexico

1200

1.64

IND063

NBPGR

India

1200

1.64

CRI001

CATIE

Costa Rica

1163

1.59

PER002

UNALM

Peru

1157

1.58

ESP026

BGUPV

Spain

1074

1.47

HUN001

VEGTBUD

Hungary

1069

1.46

HUN003

RCA

Hungary

1048

1.43

NLD037

CGN

Netherlands 1008

1.38 25.34

Others

Others

18 579

Total

World

73 305

100

RUS001

VIR

Russia

2412

15.93

USA016

S9

USA

1841

12.16

CHN001

ICS-CAAS

China

1197

7.90

Capsicum Citrullus

Accessions

13.4 Ex Situ Conservation of Vegetable Germplasm at The Global Level

Table 13.2 (Continued) Genus

Crop group

Genebank

Watermelon

Cucumis

Other melons & cucumber

Cucumis

Cucurbita

Other melons & cucumber

Pumpkins, squash, gourds

Accessions

ISR002

IGB

Israel

840

5.55

UZB006

UzRIPI

Uzbekistan

805

5.32

BRA017 Citrullus

Country

USA020

CPATSA

Brazil

753

4.97

Others

Others

7296

48.18

Total

World

15 144

100

NC7

USA

4878

10.99

JPN003

NIAS

Japan

4242

9.55

RUS001

VIR

Russia

2998

6.75

CHN001

ICS-CAAS

China

2892

6.51

BRA012

CNPH

Brazil

2400

5.41

KAZ004

RIPV

Kazakhstan

2377

5.35

CHN004

BVRC

China

1927

4.34

FRA215

GEVES

France

1399

3.15

DEU146

IPK

Germany

1154

2.60

IND001

NBPGR

India

1070

2.41

IRN029

NPGBI-SPII

Iran

1046

2.36

BGR001

IPGR

Bulgaria

1006

2.27

ESP026

BGUPV

Spain

983

2.21

TUR001

AARI

Turkey

971

2.19

CZE061

RICP

Czech Rep.

950

2.14

NLD037

CGN

Netherlands

934

2.10

Others

Others

13 175

29.67

Total

World

44 402

100

RUS001

VIR

Russia

5771

14.41

CRI001

CATIE

Costa Rica

2612

6.52

BRA003

CENARGEN

Brazil

1897

4.74

CHN001

ICS-CAAS

China

1767

4.41

MEX008

INIFAP

Mexico

1580

3.94

JPN003

NIAS

Japan

1332

3.33

USA016

S9

USA

1276

3.19

TWN001

AVRDC

Taiwan

1116

2.79

DEU146

IPK

Germany

1042

2.60

USA020

NC7

USA

993

2.48

UZB006

UzRIPI

Uzbekistan

926

2.31

HUN003

RCA

Hungary

924

2.31

TUR001

AARI

Turkey

907

2.26

BGD186

EWS R&D

Bangladesh

850

2.12 (continued)

299

300

13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

Table 13.2 (Continued) Genus

Cucurbita

Daucus

Crop group

Pumpkins, squash, gourds

Carrot

Daucus

Carrot

Lycopersicon/ Solanum

Tomato

Genebank

Country

Accessions

BRA017

CPATSA

Brazil

829

2.07

USA003

NE9

USA

822

2.05

ESP026

BGUPV

Spain

818

2.04

CZE061

RICP

Czech Rep.

715

1.79

Others

Others

13 878

34.65

USA020

Total

World

40 055

100

NC7

USA

1126

12.15

GBR006

HRIGRU

UK

1094

11.81

RUS001

VIR

Russia

1001

10.80

GBR165

SASA

UK

883

9.53

POL030

SKV

Poland

541

5.84

DEU146

IPK

Germany

488

5.27

CHN004

BVRC

China

407

4.39

FRA215

GEVES

France

384

4.14

CZE061

RICP

Czech Rep.

366

3.95

JPN003

NIAS

Japan

342

3.69

UKR021

IOB

Ukraine

320

3.45

Others

2313

24.96

Total

World

9265

100

AVRDC

Taiwan

8566

10.80

USA003

NE9

USA

6516

8.22

USA094

DHSNYST

USA

4850

6.12

PHL130

IPB-UPLB

Philippines

4751

5.99

USA117

Campbell Inst.

USA

4572

5.77

DEU146

IPK

Germany

4062

5.12

USA176

GSLY

USA

3443

4.34

RUS001

VIR

Russia

2540

3.20

JPN003

NIAS

Japan

2428

3.06

CAN004

PGRC

Canada

2137

2.70

COL004

ICA/REGION 5

Colombia

2018

2.55

TWN001

ESP026

BGUPV

Spain

1927

2.43

HUN003

RCA

Hungary

1749

2.21

IND001

NBPGR

India

1694

2.14

BRA006

IAC

Brazil

1688

2.13

KAZ004

RIPV

Kazakhstan

1500

1.89

BRA003

CENARGEN

Brazil

1440

1.82

NLD037

CGN

Netherlands

1306

1.65

FRA215

GEVES

France

1254

1.58

13.4 Ex Situ Conservation of Vegetable Germplasm at The Global Level

Table 13.2 (Continued) Genus

Lycopersicon/ Solanum

Solanum

Solanum

Crop group

Tomato

Eggplant

Eggplant

Genebank

Country

Accessions

FRA011

INRA-UGAFL

France

1246

1.57

BGD186

EWS R&D

Bangladesh

1235

1.56

CZE061

RICP

Czech Rep.

1232

1.55

BGR001

IPGR

Bulgaria

1128

1.42

n/a

AGGa)

Australia

1074

1.35

Vietnam

1000

1.26

Others

Others

13 936

17.58

Total

World

79 292

100

TWN001 AVRDC

Taiwan

3727

24.59

IND001

NBPGR

India

2752

18.16

IND063

NBPGR

India

1300

8.58

JPN003

NIAS

Japan

1090

7.19

USA016

S9

USA

769

5.07

BGD186

EWS R&D

Bangladesh

826

5.45

PHL130

CSC-IPB, UPLB-CA Philippines

642

4.24

IND231

IARI

India

450

2.97

ARM008

SC VIC

Armenia

430

2.84

NLD037

CGN

Netherlands 373

2.46

Others

Others

2798

18.46

Total

World

15 157

100

Grand Total

World

40 8200

VNM006 FCRI

a) Institute code not yet assigned for AGG (Australian Grains Genebank Source: Data derived from the WIEWS database (http://www.fao.org/wiews-archive/germplasm_query .htm). For the WorldVeg (TWN001) data, the AVGRIS database (http://203.64.245.49/AVGRIS/) was used; databases accessed on 7 March 2016. See Annex 1 for full names of genebanks.

database was established by FAO to serve as a global mechanism for information exchange among member countries and as an instrument for the periodic assessment of the state of the world’s PGRFA. The ex situ germplasm collections listed in Table 13.2 comprise 408 200 accessions and thus are already close to the total vegetable germplasm holdings worldwide (503 000 accessions) reported by FAO (2010). Brassicas (102 193 accessions), tomatoes (79 292), and sweet and hot pepper (73 305) comprise the largest ex situ collections at the global level (Table 13.2). Cucurbits, watermelons and other melons, and alliums are also well represented globally, while the global eggplant and carrot germplasm holdings are comparably small. The World Vegetable Center (WorldVeg) plays a major role in the conservation and distribution of vegetable germplasm held in the public domain. Initially set up in 1971 as the Asian Vegetable Research and Development Center with headquarters in Taiwan, the Center began expanding its geographical reach in the 1990s. It now operates

301

302

13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

regional offices in East and Southern Africa (established in 1992 in Tanzania), West and Central Africa (established in 2007 in Mali), East and Southeast Asia/Oceania (established in 1992 in Thailand), South Asia/Central Asia and the Caucasus (established in 2006 in India). As of March 2016, the Center maintains 61 854 accessions of vegetable germplasm comprising 172 genera and 442 species from 156 countries of origin, including some of the world’s largest vegetable collections held by a single institution, such as Capsicum, tomato, and eggplant (Table 13.2). Annually, WorldVeg distributes 6000 to 8000 unique germplasm accessions and materials derived from its breeding programs to the world community.

13.5 Access to Information on Ex Situ Germplasm Held Globally Consumer preference for more diverse diets and exotic food, global warming, and increased environmental variability imply that plant breeders and farmers will need to be able to access a wider range of PGRFA than in the past to adapt to these changes (Khoury et al. 2015). As a precondition, the agricultural community needs ready access to information that enables the most efficient and economical choice of appropriate diversity to address these challenges. As we have seen in the previous section, considerable amounts of diversity are stored in the more than 1750 individual genebanks worldwide. About 130 of those genebanks hold at least 10 000 accessions each (FAO, 2010). Poor documentation on much of the world’s ex situ PGRFA is a considerable obstacle to the increased use of PGRFA in crop improvement and research. In many cases where documentation and characterization data do exist, users encounter frequent problems in standardization and data accessibility, even for basic passport information (FAO, 2010). Unfortunately, a vast majority of countries still do not maintain an integrated national information system on germplasm holdings. Important ex situ holdings in at least 38 countries are still documented only on paper (16 countries) and in spreadsheets (32 countries). Only 60% of countries that reported on documentation are using a dedicated information management system to deal with passport and characterization data on ex situ collections, while generic database software is used in about 34 percent of countries (FAO, 2010). The lack of a freely available, flexible, up-to-date, user-friendly, and multi-language system has constrained improvement of germplasm documentation in many countries. Until recently, it had been impossible to genetically and phenotypically characterize genebank holdings on a large scale. The tremendous technological advances in sequencing and the dramatic decrease in the cost of sequencing have resulted in a massive increase in data generation. Thanks to these sequencing advances, the complete genomes of individuals of more than 180 organisms have been sequenced since 1995 (Ruder and Winstead, 2016). In genomic approaches, sequencing efforts primarily focus on the identification of genomic loci that affect variations in traits of interest. To identify genomic variation, multiple individuals of organisms with the previously established draft or reference genome sequence are being resequenced. To relate the wealth of sequencing data to trait variation, the development of high throughput, high quality, and reliable phenotypic data has become another bottleneck

13.5 Access to Information on Ex Situ Germplasm Held Globally

(Cobb et al., 2013). Innovations in bioinformatics are mandatory for the analysis and management of the massive amounts of sequencing data (Lee et al., 2011). These recent developments have led to the creation of some information tools and platforms as well as crop trait data mining portals. 13.5.1 SINGER: Online Catalog of International Collections Managed by the GCIAR and WorldVeg CGIAR centers that have genebanks and WorldVeg developed customized documentation systems that make characterization data accessible and include, in most cases, an online ordering system. The CGIAR centers have placed their collections under the Governing Body of the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), which means that the diversity they conserve is held in the public domain and available for distribution based on the terms set forth by ITPGRFA. The CGIAR centers and WorldVeg shared their data with the System-wide Information Network for Genetic Resources (SINGER), a portal established in 1994 providing public access to the germplasm resources held by the CGIAR and WorldVeg. Collectively, the 11 CGIAR centers that have genebanks maintain a total of about 741 319 accessions of crop, forage and tree germplasm of major importance for food and agriculture, comprising 3446 species of 612 different genera (FAO, 2010). WorldVeg holds 61 854 accessions of vegetable germplasm. The Directory Interchange Format (DIF) of SINGER was last revised on 19 December 2011 (NASA, 2016) and currently, SINGER is no longer accessible. Data from SINGER have been migrated to the new GENESYS portal. 13.5.2

EURISCO: the European Genetic Resources Search Catalog

The European Cooperative Programme for Plant Genetic Resources (ECPGR), founded in 1980, aims to facilitate the long-term cooperative conservation and utilization of plant genetic resources in Europe (ECPGR, 2016). The program is financed by the participating countries and is coordinated by a Secretariat hosted by Bioversity International. It operates through working groups dealing with groups of crops or general themes related to plant genetic resources. The European Internet Search Catalogue (EURISCO) provides information about ex situ plant collections maintained in Europe. It is based on a European network of 43 ex situ National Inventories (NIs) and 375 participating institutes. Currently, EURISCO comprises passport data of about 1.8 million samples covering 6233 genera and 41 637 species (EURISCO, 2016). Between the years 2003 and 2014, EURISCO was hosted and maintained by Bioversity International, Rome, Italy. Since April 2014, these responsibilities have been moved to the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. EURISCO is maintained in collaboration with and on behalf of the National Focal Points for the NIs. To strengthen the coordination of conservation activities throughout Europe, the ECPGR started in 2004 to work towards a European Genebank Integrated System (AEGIS) for PGRFA. AEGIS entered into force in 2009 with the signature of the Memorandum of Understanding by ten ECPGR member countries. By January 2016, 34 member countries and 58 Associate Member institutions had joined AEGIS (AEGIS, 2016). Membership is open to all European countries that are members of ECPGR

303

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13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

and willing to make PGRFA available under the conditions of the International Treaty. Within the framework of AEGIS, plant accessions are registered in EURISCO by holding countries to be part of the collection of unique and valuable European accessions maintained for the long term. Among the 1.8 million samples in EURISCO, 365 015 accessions belong to the multilateral system of the ITPGRFA, but only 28 686 have been provided by 15 countries to AEGIS (EURISCO, 2016).

13.5.3

GRIN of USDA-ARS

The United States National Plant Germplasm System (NPGS), administrated by the US Department of Agriculture-Agricultural Research Service (USDA-ARS), is a cooperative effort by US public and private organizations to preserve the genetic diversity of agriculturally important plants and encourage their use. Many NPGS genebanks are located at state land-grant university sites, which contribute lab, office, greenhouse, and field space for operations, as well as staff for technical and support services. The private sector is a major user of the NPGS collections and is the primary means by which new and improved plants are commercialized. The NPGS aids the global agricultural community by acquiring, preserving, evaluating, documenting, and distributing crop germplasm to improve the quality and productivity of crops. The Germplasm Resources Information Network (GRIN) web server of USDA-ARS provides germplasm information about plants, animals, microbes, and invertebrates. Currently, 217 families, 2393 genera, 15 091 species, and 574 764 accessions are described in GRIN (USDA-ARS, 2016). Despite its great success over the past 25 years, the full version of GRIN has only been adopted by Canada. This is due to its inherent complexity and licensing fees, which prevented other countries and international genebanks from adopting it for routine use. USDA-ARS, Bioversity International and the Global Crop Diversity Trust (GCDT) partnered under an international project to develop a scalable genebank information management system called GRIN-Global. The GCDT provided a US$1.4 million grant for the development of GRIN-Global and its international deployment to support effective PGR conservation and international genebank information management needs. GRIN-Global is multilingual by design to facilitate adoption by genebanks throughout the world. Initially, GRIN-Global will support French, Spanish, Russian, Arabic, and English. Bioversity will assist in deploying the software in genebanks that request it.

13.5.4

GENESYS: the global gateway to plant genetic resources

GENESYS, a global gateway to plant genetic resources, was developed by Bioversity International in collaboration with GCDT and the Secretariat of ITPGRFA and launched in 2011. It provides accession-level information pooled from a range of different portals such as SINGER, EURISCO, and GRIN, and also strives to incorporate in the future data from national genebanks (Alercia and Mackay, 2010; Arnaud et al., 2010). This ambitious undertaking aims to provide not only passport data but also characterization and evaluation data as well as access to millions of records of environmental information associated with accession collecting sites.

13.5 Access to Information on Ex Situ Germplasm Held Globally

GENESYS is designed for breeders and other scientists and includes GIS and mapping functions, allows queries across all data for accession-specific traits, and has a built-in automated ordering system. As of March 2016, GENESYS comprises information on 2 580 174 accessions belonging to 447 institutes (GENESYS, 2016). Each of the participating networks has access to a centralized data warehouse, allowing it to publish data of interest to the respective community on their customized web portals (Nawar and Mackay, 2010). GENESYS enables users to search global genebank holdings using any combination of passport, environmental, and trait scores. It also provides a function for fast mapping of accessions for visualizing the topology of collecting sites. Furthermore, it has a “tracking” function to find related accessions across genebanks. GENESYS will be the entry point for users to mine genetic variation by using combinations of data on the characteristics, environment and other aspects of genetic diversity to identify accessions of interest and order them online. 13.5.5

The Crop Wild Relatives Portal

The increasing genetic uniformity of crop varieties combined with climate change makes crops more vulnerable to stress. Crop wild relatives (CWR) are important for maintaining genetic diversity and preventing crop losses, which may have grave consequences for food and nutrition security. A well-known example is the famine of the 1840s, caused by large-scale potato crop failures as a result of genetic vulnerability to the late potato blight epidemic, which wiped out a large proportion of the susceptible potato varieties grown at that time in Ireland, Europe, and North America. Genes derived from CWR may have considerable economic value. To provide an example, one wild tomato variety has contributed to a 2.4 percent increase in soluble solids contents worth US$250 million to the tomato industry (Bioversity International, 2016). The Crop Wild Relatives Global Portal was created within the framework of the UNEP-GEF supported project “In situ conservation of crop wild relatives through enhanced information management and field application” (2004-2010). It provides information on CWR that are at particular risk from climate change and allows users to access 15 national portals for CWR, which are available online or have been published as PDF. Moreover, the portal provides access to CWR conservation strategies developed for Europe, Spain, Finland, Italy, and Cyprus. 13.5.6

Crop Trait Mining Platforms

Assessing and identifying new sources of genetic variation is a critical part of any long-term strategy to enhance the productivity, sustainability, and resilience of crop varieties and agricultural systems. Lack of easy access to information relating to agronomically relevant traits of plant genetic resources is the primary limitation to the effective and efficient identification and deployment of novel genetic variation to address pressing production challenges under climate change. 13.5.6.1

Crop Trait Mining Informatics Platform

Australia is building on the GENESYS platform by adding significant Australian generated unique data to develop a Crop Trait Mining Informatics Platform (Crop TMIP) (Mackay and Taylor, 2014). The data will initially be sourced from Grains

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Research and Development Corporation projects. A list of relevant projects can be found at the CIMMYT Australia ICARDA Germplasm Evaluation (CAIGE) portal (http://caigeproject.org.au/). In a next step, the data collection will be used to develop further the Agricultural Information Management Standards (AIMS) issued by FAO and Bioversity International in 2012 as the second version of the international standards on multi crop passport descriptors (MPCD) (AIMS, 2016). These standards aim to facilitate germplasm passport information exchange by defining the descriptors necessary to describe crop species and create respective passports. For each MCPD, a brief explanation of content, coding scheme and suggested field name are provided to assist in the electronic exchange of crop passport data. The new MCPD standards were developed to ensure compatibility with the descriptors used in the WIEWS database for PGRFA, future Bioversity crop descriptor lists, and popular portals such as GENESYS, EURISCO, GRIN, and GRIN-Global. Australia is also planning to develop online tools, including a decision support system, to assist researchers and plant breeders in the identification of genotypes that most likely possess the desired genetic variation, or alleles, for target traits (Mackay and Taylor, 2014). One such approach is the Focused Identification of Germplasm Strategy (FIGS) developed by ICARDA for the rapid mining of genebanks for traits of interest (ICARDA, 2016). 13.5.6.2

The Diversity Seek Initiative

The 7.4 million accessions of plant genetic resources held globally (FAO, 2010) represent an immense, largely untapped resource with great opportunities for accelerating yield gains and overcoming emerging crop productivity constraints. Full characterization of all accessions is required to access the wealth of diversity of this material successfully. This can be achieved via the application of state-of-the-art genomic, phenomic and molecular technologies, and the release of the subsequent data via an online, open-access portal. The Diversity Seek initiative (DivSeek) was launched during a workshop held in San Diego, the USA in January 2014 with the aim to assess how best to harness the untapped potential of genetic diversity stored in genebanks to make plant breeding faster, more efficient and more cost-effective. The workshop brought together 90 experts from 63 institutions and 21 countries (DivSeek, 2016). DivSeek will work with existing, emerging and future initiatives to characterize crop diversity and develop a unified, coordinated and cohesive information management platform to provide easy access to genotypic and phenotypic data associated with genebank germplasm. This initiative is trying to bridge the gap between the information requirements of genebank curators, plant breeders and more targeted upstream biological researchers, to support applied germplasm curation, modern breeding programs, and strategic research. The Global Crop Diversity Trust hosts and implements the facilitation unit jointly with the Secretariat of the International Treaty on Plant Genetic Resources for Food and Agriculture, and operates it on a day-to-day basis with additional inputs provided by the CGIAR consortium, the Global Plant Council and other experts/organizations. Initially, DivSeek will develop a system of internationally agreed-upon standards, protocols, tools, resources and best practices for generating, organizing, structuring, indexing, retrieving, sharing and analyzing genotypic and phenotypic data related to

13.5 Access to Information on Ex Situ Germplasm Held Globally

genebank holdings (DivSeek, 2016). This will be a collaborative approach together with existing networks and projects to avoid duplication. After that, DivSeek will build an information platform that provides access to genotypic, phenotypic, and other types of information linked to physical germplasm in genebanks as well as to ‘digital genomes’ that represent an essential tool for linking genotype with phenotype. This platform is intended to provide access to an array of genotypic and phenotypic datasets. The datasets will be complemented by a range of computational tools and resources that allow users to visualize and analyze the data in the course of their work. DivSeek is pursuing two complementary strategies (DivSeek, 2016): (1) preparing genebank collections effectively to promote their use and to facilitate comprehensive genotypic and phenotypic analyses; and (2) performing a detailed characterization of the diversity that exists in genebanks so that it can be targeted for use in crop breeding programs. The initiative intends to provide a powerful link between different communities of experts, especially those whose work is focused on the physical germplasm and those whose work centers on digital information and cyber infrastructure. In the context of these ongoing discussions, genebanks may need to provide innovative services that may include the introduction of specific user-oriented collection types (van Treuren and van Hintum, 2014). Those may include mapping populations (recombinant inbred lines, near-isogenic lines, and multi parent advanced generation inter-crosses) and genetically purified lines that are preferred for re-sequencing experiments for allele mining purposes. To unambiguously relate phenotypic and genotypic data, purified seed stocks are more reliable than heterogeneous genebank accessions. By establishing a well-coordinated, international effort, based on experience and knowledge of a multitude of stakeholders, projects, and partner consortia, Div Seek will contribute to the generation of high-quality reusable data and promote access to currently mostly untapped genetic diversity that will facilitate the development of crop varieties that are more resilient to current global challenges. 13.5.7 Trait information portal for CWR and landraces and crop-trait ontologies Breeders typically use their own lines and stocks of crop seed to generate novel crop varieties, but these materials are relatively uniform and lack the genetic diversity required to meet the novel challenges presented by climate change and changing consumer demands. CWR and landraces offer the breadth of genetic diversity required by breeders and, therefore, the PGR Secure project under the EU Seventh Framework project is researching novel characterization techniques, and conservation strategies for European CWR and landrace diversity to enhance crop improvement by breeders and ensure European food security in the face of climate change. To achieve these goals, PGR Secure has four research themes (PGR Secure, 2016): 1) Investigation of novel characterization techniques, including genomics, phenotyping and metabolomics; transcriptomics; and Focused Identification of Germplasm Strategy (FIGS); 2) CWR and landrace conservation, including a Europe-wide CWR inventory and exemplar national CWR inventories; a European CWR strategy; a Europe-wide landrace inventory and exemplar national landrace inventories; and European landrace strategy;

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3) facilitating breeders’ CWR and landrace use, including identifying and meeting breeders’ needs; integration of conservation and user communities; and channeling potentially valuable germplasm into commercial breeding programs (pre-breeding); and 4) informatics development, including the availability of CWR and landrace inventory information and unique characterization information on the web, and, finally, interinformation system operability. To address the informatics development component under the PGR Secure project, a Trait Information Portal (TIP) is currently under development to include trait information on accession and population data generated under the project, in addition to existing data. External sources of TIP include the Crop Wild Relative Information System/Population Level Information System (CWRIS/PLIS), EURISCO and relevant European Central Crop Data Bases (ECCDBs) and the European Molecular Biology Laboratory (Dias, 2012). TIP is promoting the use of ontologies for traits, CWR, landraces, and crop-specific data to support the user community. The Plant Ontology (PO) is a controlled vocabulary (ontology) that describes plant anatomy and morphology and stages of development for all plants. The goal of the PO is to establish a semantic framework for meaningful cross-species queries across gene expression and phenotype data sets from plant genomics and genetics experiments (Plant Ontology Consortium, 2016). Originally, there existed two ontology files: (1) the ‘Plant Anatomical Entity’ containing botanical terms describing plant structures and other anatomical entities (plant organs, plant cells, vascular system) and the relationships between them, and (2) the ‘Plant Structure Development Stage’ with a controlled vocabulary of terms describing the various stages of plant structure development, such as plant tissue development, leaf development, seed development stages, etc. In 2011, the two files were merged into a single ontology file. Instead of generating a quantitative assessment of environmentally dependent characters in the form of trait scores provided by common germplasm descriptors, trait ontology terms associate a gene, genetic locus, protein or pathway with a character (Ougham and Thomas, 2014). The TIP concept is contemplating the use of ‘Triontology,’ namely CWR, landrace and crop-trait ontologies (Dias, 2012). It aims to (1) develop an ontology that describes the crops, traits, anatomical and morphological structures, and growth and development stages; (2) establish a semantic framework to query across crops, inventories and traits—genotype and phenotype datasets; and (3) describe crops, CWR and landraces data structures and the relationship among them. The TIP will include information on traits, locations, trial sites, georeferences and geographical information and will be searchable through ontology-driven views. It will use web scraping to include external data sources, molecular data, bibliography, characterization and evaluation data and images and will provide data analysis output options. 13.5.8

Summary and Outlook

Until recently, it had been impossible to genetically and phenotypically characterize genebank holdings on a large scale. Today, it is both feasible and necessary if we wish to

13.5 Access to Information on Ex Situ Germplasm Held Globally

unlock the widely untapped genetic diversity to improve crops for the benefit of human society. Innovations in bioinformatics are mandatory for the analysis and management of the massive amount of sequencing data, and to link them with phenotypic data and genebank information. Recent technology advances and developments have led to the creation of several information tools and platforms as well as crop trait data mining portals that have briefly been described in this section. Unfortunately, most of these new platforms and portals are still under development and comprise only partial information of the global situation. If we take the tomato crop, for example, which ranks second in world vegetable production, and wish to get an overview of global germplasm holdings, we obtain the following figures among major data portals: EURISCO - 21 332 accessions (Lipman, 2014); GENESYS – 31 263 accessions (GENESYS, 2016); WIEWS –79 292 accessions (Table 13.2; WIEWS, 2016). Although the WIEWS database shows the highest record for the global tomato germplasm holdings, a slightly higher figure of 83 720 accessions held globally can be found in the second report on the state of the world’s PGRFA (FAO, 2010). FAO has established the WIEWS database as a global mechanism to foster information exchange among member countries and as an instrument for the periodic assessment of the state of the world’s PGRFA. This database is not very user-friendly, but it is the most representative portal of global germplasm holdings. Therefore, this portal has been used to extract the global germplasm holdings of the main vegetable crops, listed in Table 13.2. In contrast to the WIEWS database, which is built on crop/germplasm statistics provided by each country at certain intervals, the GENESYS portal operates with actual accession passport data and is regularly maintained in close collaboration with the holding institutes. Unfortunately, GENESYS does not have accession-level data from all the genebanks around the globe, most of which are listed in the WIEWS database. This is evident from the fact that the tomato germplasm resources listed in GENESYS make up only 39.4% of the resources reported in the WIEWS database. Although GENESYS makes it easy to conduct crop-based searches, when searching for the crop ‘tomato,’ only germplasm resources listed by the holding institutes as Solanum species are retrieved. Other tomato germplasm resources classified by the holding institutes under ‘Lycopersicon’ or ‘Lycopersicum’ amount to another 17 952 accessions, but those cannot be retrieved when searching for germplasm resources for tomato. This fact can mislead users when conducting crop-based searches for global tomato germplasm resources within the GENESYS portal. However, there is no doubt that portals currently under development, such as GENESYS and TIP, are the portals of choice for breeders and other researchers who are interested in retrieving trait-based information of accessions including environmental data and making use of mapping tools. Plant/Crop and Trait ontologies are another step to bring the communities of molecular and bioinformatics scientists, plant breeders and genebank managers closer together for better and more efficient exploitation of the wealth of genome and marker data and associated germplasm resources. The use of Crop and Trait ontologies, currently under development, is envisioned to be employed in the next iteration of the GENESYS platform.

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13.6 In Situ and On-farm Conservation of Vegetable Resources In situ conservation can be defined as ‘the preservation of ecosystems and natural habitats and the maintenance and recovery of viable populations of species in their natural surroundings and, in the case of domesticated or cultivated species, in the surroundings where they have developed their distinctive properties’ (CBD, 2016). In situ conservation is often envisaged as taking place in protected areas or habitats and can either be targeted at the species level or the ecosystem in which they occur. On-farm management of PGRFA is concerned with the use and maintenance of landraces—farmers’ crops and varieties—grown in agricultural systems and home gardens. Considerable progress has been made in the development of tools and techniques to assess and monitor PGRFA within agricultural production systems. Countries now report a greater understanding of the amount and distribution of genetic diversity in farmers’ fields, as well as the value of local seed systems in maintaining such diversity (FAO, 2010). Several countries are now paying more attention to increase genetic diversity within production systems as a way to reduce risk, particularly in light of changes in climate, and incidence of pests and diseases. New legal mechanisms have been put in place in several countries to enable farmers to market genetically diverse varieties. In situ conservation is a particularly valuable conservation method for species that are difficult to conserve ex situ, such as those known as CWR. CWR represent species that are closely related to crops, including crop progenitors. They are primary sources of traits beneficial to crops, such as pest or disease resistance, abiotic stress tolerance, and yield improvement or stability (Ebert and Schafleitner, 2015). With the development of new biotechnological methods, CWR are gaining vital importance in crop genetic improvement. The trait information portal for CWR and landraces described in the previous section will be a useful tool to find germplasm with the required traits for crop improvement. Taking a broad definition of CWR as any taxon belonging to the same genus as a crop, it has been estimated that there are 50-60 000 CWR species worldwide. Of these, approximately 700 are considered of highest priority, being the species that comprise the primary and secondary gene pools of the world’s most important food crops (Maxted and Kell, 2009). Despite their fundamental importance as genetic resources for food and agriculture, CWR have received relatively little systematic conservation attention. Many CWR species—and the breadth of genetic diversity they contain—are under increasing threat from habitat loss and fragmentation and climate change; few protected areas or management plans address these threats (Akhalkatsi et al., 2012). Given the importance and value of CWR, a global strategy for CWR conservation and use has been drafted. Protocols for the in situ conservation of CWR are now available, and a new Specialist Group on CWR has been established under the name Species Survival Commission (SSC) within the International Union for Conservation of Nature (IUCN). The number and coverage of protected areas have expanded by approximately 30 percent over the past decade, and this has indirectly led to a greater protection of CWR (FAO, 2010). Unfortunately, relatively little progress has been achieved in conserving wild PGRFA outside protected areas or in developing sustainable management techniques for plants harvested from the wild (FAO, 2010). There is a need for more effective national policies,

13.7 Summary and Outlook

legislation and regulations governing the in situ and on-farm management of PGRFA, both inside and outside protected areas, and closer collaboration and coordination are needed between the agriculture and environment sectors. Many aspects of in situ management still require further research. More research capacity is needed in such areas as the taxonomy of CWR and the use of molecular tools to conduct inventories and surveys. In August 2015, the secretariats of the Convention on Biological Diversity (CBD), the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), the FAO’s Commission on Genetic Resources for Food and Agriculture (CGRFA), and Bioversity International notified the respective focal points in each country, as well as the Programme of Work on Protected Areas (PoWPA), and the CGRFA of opportunities to further strengthen the in situ conservation and sustainable use of PGRFA (CBD, 2015). Particular attention should be given to CWR in protected area networks and through other effective area-based conservation measures aimed at CWR. Among vegetable crops, indigenous or traditional vegetables have great potential to combat malnutrition, improve the income of the poor, preserve indigenous biodiversity, enhance sustainable agriculture, and mitigate the risks of climate change for farmers in the developing world. Many of these crops are hardy, adapted to specific marginal soil and climatic conditions, and can be grown with minimal external inputs (de la Peña et al., 2011). This is the case, for example, in the southern part of Rajasthan, India, where due to the harsh climatic conditions only hardy, drought-tolerant traditional vegetables with short growth cycles such as Cucumis melo var. agrestis (kachri) can survive and produce food (Maurya et al., 2007). Greater diversity, which builds spatial and temporal heterogeneity into the cropping system, will enhance resilience to abiotic and biotic stresses (Newton et al., 2011). Crop diversification and greater resilience of production systems could be achieved by using more resilient indigenous vegetables and other underutilized food crops that easily adapt to degraded, drought-prone, or saline areas (Ebert, 2014). With the rapid advance of modern vegetable varieties, indigenous crops and associated landraces are threatened by extinction, and a combination of in situ and ex situ conservation efforts might be the best strategy to preserve these valuable genetic resources for use in breeding and research.

13.7 Summary and Outlook Vegetables comprise a broad range of genera and species and are an important component of a healthy diet. Primary global vegetable production reached over 1.1 billion tons in 2013-14, about 41% of total global cereal production. Asia dominates production of the top ten vegetable commodities with a share ranging from 60.7% for tomatoes to 94.5% for eggplants. The diversity of plant genetic resources provides farmers and plant breeders with the necessary genetic base to enhance crop performance of cultivated varieties under climate change scenarios. The conservation and sustainable utilization of genetic resources for food and agriculture is key to maintaining and improving the efficiency and the resilience of agro-ecosystems and also contributes to the continued functioning of the ecosystem and the provision of ecosystem services.

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According to the FAO, vegetable genetic resources conserved ex situ amount to approximately 503 000 accessions, about 7% of the germplasm resources held ex situ worldwide. Major vegetable germplasm collections held ex situ, and respective holding institutes of the top 10 vegetable commodities plus the cucurbit group are presented in this chapter and amount to approximately 408 000 accessions. WorldVeg is a primary source of vegetable germplasm maintaining close to 62 000 accessions comprising 172 genera and 442 species from 156 countries of origin, including some of the world’s largest vegetable collections held by a single institution, such as Capsicum, tomato, and eggplant. Searching for the right germplasm sources in the more than 1700 individual genebanks worldwide is not an easy task. The agricultural community needs ready access to information that enables the most efficient and economical choice of appropriate diversity to address global challenges. For this purpose, some information platforms and data mining portals have been created. Among those, SINGER, EURISCO, GRIN, GENESYS, the Crop Wild Relatives Portal, the Crop Trait Mining Information Platform, the Diversity Seek Initiative and the Trait Information Portal for CWR and landraces are described in this chapter. Furthermore, Plant/Crop and Trait ontologies are currently under development to bring the communities of molecular and bioinformatics scientists, plant breeders and genebank managers closer together for better and more efficient exploitation of the wealth of genome and marker data and the associated germplasm resources. In situ conservation is a particularly valuable conservation method for species that are difficult to conserve ex situ, such as those known as CWR, which represent species that are closely related to crops. Approximately 700 CWR species are considered of highest priority for in situ and ex situ conservation. They constitute the species that comprise the primary and secondary gene pools of the world’s most important food crops. CWR are primary sources of traits beneficial to crops, such as pest or disease resistance, abiotic stress tolerance, and yield improvement or stability. Among vegetable crops, indigenous or traditional vegetables have great potential to combat malnutrition, improve the income of the poor, preserve indigenous biodiversity, enhance sustainable agriculture, and mitigate the risks of climate change for farmers in the developing world. These highly threatened genetic resources deserve special protection through a combination of in situ and ex situ conservation efforts.

Acknowledgment The author wishes to express his sincere thanks to Maureen Mecozzi for the careful editing of this manuscript.

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Annex 1 Genebank Acronyms Used in Table 13.2

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Annex 1 Genebank Acronyms Used in Table 13.2 AARI (TUR001)

Plant Genetic Resources Department (Turkey)

AGG

Australian Grains Genebank (Australia)

AICRP-Rapeseed & Mustard(IND073) All India Coordinated Research Project on Rapeseed and Mustard AVRDC (TWN001)

World Vegetable Center (former Asian Vegetable Research and Development Center (Taiwan)

BGUPV (ESP026)

Generalidad Valenciana, Universidad Politécnica de Valencia. Escuela Técnica Superior de Ingenieros Agrónomos, Banco de Germoplasma (Spain)

BINA (BGD028)

Bangladesh Institute of Nuclear Agriculture

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13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

BPGV-DRAEDM

Portuguese Bank of Plant Germplasm (Portugal)

BVRC (CHN004)

Beijing Vegetable Research Centre (China)

Campbell Inst. (USA117)

Campbell Institute for Agricultural Research, Campbell Soup Company (USA)

CATIE (CRI001)

Centro Agronómico Tropical de Investigación y Enseñanza (Costa Rica)

CENARGEN

Embrapa Recursos Genéticos e Biotecnologia (Brazil)

CGN (NLD037)

Centre for Genetic Resources (Netherlands)

CIFAP-CEL (MEX003)

Centro de Investigaciones Forestales y Agropecuarias, INIFAP (Mexico)

CNPH (BRA012)

EmbrapaHortaliças (Brazil)

CPATSA (BRA017)

Embrapa Semi-Árido (Brazil)

CSC-IPB, UPLB-CA (PHL130)

Crop Science Cluster-Institute of Plant Breeding, College of Agriculture, University of the Philippines, Los Baños College (Philippines)

DHSNYST (USA094)

Horticultural Sciences Department, New York State Agricultural Experiment Station (USA)

EWS R&D (BGD186)

East West Seed Research and Development Division (Bangladesh)

EIB (ETH085)

Ethiopian Institute of Biodiversity

FCRI (VNM006)

Food Crops Research Institute (Vietnam)

GEVES (FRA215)

Unité Expérimentale d’Angers, Groupe d’Étude et de contrôle des Variétés et des Semences (France)

GSLY (USA176 )

C.M. Rick Tomato Genetic Resources Center, Department of Vegetable Crops, University of California (USA)

HRIGRU (GBR006)

Warwick Genetic Resources Unit (UK)

IAC (BRA006)

Instituto Agronómico de Campinas (Brazil)

IARI (IND2018)

Indian Agricultural Research Institute, Division of Genetics (India)

IARI (IND231)

Indian Agricultural Research Institute, Division of Vegetable Crops (India)

ICA/REGION 5

Centro de Investigación El Mira, Instituto Colombiano Agropecuario El Mira (Colombia)

ICS-CAAS (CHN001)

Institute of Crop Science, Chinese Academy of Agricultural Sciences (China)

IGB (ISR002)

Israel Gene Bank for Agricultural Crops, Agricultural Research Organization, Volcani Centre (Israel)

INIA (MEX005)

Centro de Investigaciones Agrícolas del Golfo Norte, INIA (Mexico)

INIA (MEX009)

Unidad de Recursos Genéticos, Centro de Investigación Agrícola Bajío (Mexico)

INIFAP (MEX008)

Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias (Mexico)

INRA-RENNES

Station d’Amélioration des Plantes, INRA (France)

INRA-UGAFL

Unité de Génétique et Amélioration des Fruits et Légumes (France)

Annex 1 Genebank Acronyms Used in Table 13.2

Inst. Oil C. Res. (CHN003)

Institute of Oil Crops Research, Chinese Academy of Agricultural Sciences (China)

IOB (UKR021)

Institute of Vegetable and Melon Growing (Ukraine)

IPB-UPLB

Institute of Plant Breeding, College of Agriculture, University of the Philippines, Los Baños College (Philippines)

IPGR (BGR001)

Institute for Plant Genetic Resources “K.Malkov” (Bulgaria)

IPK (DEU146)

Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (Germany)

IPK (DEU271)

External Branch North of the Department Genebank, IPK, Oil Plants and Fodder Crops in Malchow

NBPGR (IND001)

National Bureau of Plant Genetic Resources (India)

NBPGR (IND063)

Regional Station Hyderabad, National Bureau of Plant Genetic Resources (India)

NC7 (USA020)

North Central Regional Plant Introduction Station, United States Department of Agriculture, Agricultural Research Services (USA)

NE9 (USA003)

Northeast Regional Plant Introduction Station, Plant Genetic Resources Unit, United States Department of Agriculture, Agricultural Research Services, New York State Agricultural Experiment Station, Cornell University (USA)

NIAS (JPN003)

National Institute of Agrobiological Sciences (Japan)

NPGBI-SPII (IRN029)

National Plant Gene Bank of Iran, Seed and Plant Improvement Institute (Iran)

NRCOG (IND1457)

National Research Centre for Onion and Garlic (India)

NRCRM (IND1453)

National Research Centre on Rapeseed –Mustard (India)

OSEVA-OPAVA (CZE065)

OSEVA PRO Ltd. Research Institute of Oilseed Crops (Czech Republic)

PGRC (CAN004)

Plant Gene Resources of Canada, Saskatoon Research Centre, Agriculture and Agri-Food Canada (Canada)

PGRP (PAK001)

Plant Genetic Resources Program (Pakistan)

RBG (GBR004)

Millennium Seed Bank Project, Seed Conservation Department, Royal Botanic Gardens, Kew, Wakehurst Place (United Kingdom)

RCA (HUN003)

Institute for Agrobotany (Hungary)

RICP (CZE061)

Genebank Department - Vegetable Section Olomouc, RICP Prague (Czech Republic)

RIPV (KAZ004)

Research Institute of Potato and Vegetables (Kazakhstan)

S9 (USA016)

Plant Genetic Resources Conservation Unit, Southern Regional Plant Introduction Station, University of Georgia, United States Department of Agriculture, Agricultural Research Services (USA)

SASA (GBR165)

Science and Advice for Scottish Agriculture, Scottish Government (United Kingdom)

SC VIC (ARM008)

Scientific Center of Vegetables and Industrial Crops (Armenia)

SKV (POL03)

Plant Genetic Resources Laboratory, Research Institute of Vegetable Crops (Poland)

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13 Vegetable Genetic Resources for Food and Nutrition Security under Climate Change

TSS-PDAF (TWN005)

Taiwan Seed Service, Provincial Department of Agriculture and Forestry (Taiwan)

UNALM (PER002)

Universidad Nacional Agraria La Molina (Peru)

UzRIPI (UZB006)

Uzbek Research Institute of Plant Industry (Uzbekistan)

VEGTBUD (HUN001)

Vegetable Crops Research Institute, Station of Budapest (Hungary)

VIR (RUS001)

N.I. Vavilov All-Russian Scientific Research Institute of Plant Industry (Russian Federation)

W6 (USA022)

Western Regional Plant Introduction Station, United States Department of Agriculture, Agricultural Research Services, Washing State University

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14 Sustainable Vegetable Production to Sustain Food Security under Climate Change at Global Level Andreas W. Ebert 1 , Thomas Dubois 2 , Abdou Tenkouano 3 , Ravza Mavlyanova 4 , Jaw-Fen Wang 5 , Bindumadhava Hanumantha Rao 6 , Srinivasan Ramasamy 7 , Sanjeet Kumar 7 , Fenton D. Beed 8 , Marti Pottorff 9 , Wuu-Yang Chen 10 , Ramakrishnan M. Nair 11 , Harsh Nayyar 12 , and James J. Riley 13 1

Freelance International Consultant in Agriculture and Agrobiodiversity, Schwaebisch Gmuend, Germany World Vegetable Center, Eastern and Southern Africa, Duluti, Arusha, Tanzania 3 CORAF/WECARD, Dakar-RP, Senegal 4 World Vegetable Center, Central Asia and the Caucasus, Tashkent, Uzbekistan 5 Department of Agronomy, National Taiwan University, Taipei, Taiwan 6 World Vegetable Center South Asia, Greater Hyderabad, Telangana, India 7 World Vegetable Center, Shanhua, Tainan, Taiwan 8 Food and Agriculture Organization of the United Nations (FAO), Rome, Italy 9 Department of Botany and Plant Sciences, University of California, Riverside, USA 10 World Vegetable Center, Shanhua, Tainan, Taiwan 11 World Vegetable Center South Asia, Greater Hyderabad, Telangana, India 12 Department of Botany, Panjab University, Chandigarh, India 13 College of Agriculture and Life Sciences, University of Arizona, Tucson, USA 2

14.1 Introduction This chapter focuses on approaches to sustainable vegetable production systems for food and nutrition security under climate change in sub-Saharan Africa and Asia. Such approaches include the conservation and use of vegetable genetic resources with a broad genetic base to enable effective breeding and deployment of varieties with multiple disease- and pest resistance and tolerance to abiotic stresses, crop production technologies including integrated pest and disease management, and grafting technologies to overcome biotic and abiotic production constraints. Climate change is predicted to have a major impact on agriculture and horticulture, consequently affecting the world’s food supply. Expected shifts in ecological and agro-economic zones, land degradation, reduced water availability, elevated CO2 , sea level rise and salinization will pose a severe threat to sustainable cultivation of staple crops as well as vegetables and fruit, the latter being of prominent importance for nutrition security and balanced diets. Water shortages aggravated by climate change will be felt in crop production, given the fact that agriculture accounts for 70% of water use worldwide (Johkan et al., 2011; Bhardwaj, 2012; Chatterjee and Solankey, 2015). Greenhouse gas emissions may lead to increased precipitation in high latitudes and decreased precipitation in subtropical areas, such as the southwest USA, Central America, southern Africa and the Mediterranean basin, i.e. southern Europe and Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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northern Africa (Meehl et al., 2007). However, soil moisture and surface runoff may be of more direct relevance to agriculture rather than absolute precipitation values. Higher temperatures will increase evapotranspiration rates. If this is coupled with more intense storms and associated higher surface runoff, significant drying trends in soil moisture and an increased risk of agricultural drought may be the consequence in many agricultural land areas in the coming century (Dai, 2011). As concluded by Lobell and Gourdji (2012), climate change represents a credible threat to sustaining global productivity growth of food production at rates necessary to keep up with growing demand. Increasing the scale of investments in crop improvement and sustainable production technologies, given global climate change and other factors will help to sustain significant yield growth on limited land resources over the next few decades.

14.2 Regional Perspective: Sub-Saharan Africa Most of the farmland in sub-Saharan Africa is cultivated by smallholder farmers in rain-fed systems. Climate change is expected to have a major impact on those farming systems and solutions must be found to assist the poor and marginalized groups of the population—largely dependent on the agricultural sector for their livelihood—to cope with climate change. 14.2.1

The Effects of Climate Change in Sub-Saharan Africa

Agriculture and horticulture are the primary sources of employment and income for most of the rural population of sub-Saharan Africa. Most of the arable land is allocated to cereals, especially maize, sorghum, and millets or root and tuber crops, predominantly cassava, yams and various types of bananas. Except for South Africa and Zimbabwe, where well-developed commercial farming is present, agriculture in the rest of sub-Saharan Africa is mostly conducted by smallholder farmers in a rain-fed system (Cervantes-Godoy et al. 2013, Hachigonta et al., 2013; Waithaka et al., 2013). In West and Central Africa, smallholder farmers also make use of semi-irrigated systems using residual moisture along river banks, notably the “Fadama” systems in Nigeria (Bature et al., 2013) and the transplanted “Muskwari” systems in the Lake Chad basin (Saïdou et al., 2015). These systems are highly vulnerable to climate change and variability, often manifested as recurrent droughts and floods as well as unpredictable variation in length of growing season (Thornton et al., 2009). As such, climate change will have far-reaching consequences for smallholder farmers in sub-Saharan Africa. For effective adaptation to climate change, it becomes essential that smallholder farmers, who are often the poor and marginalized groups in communities, are empowered and become less vulnerable to the frequency and severity of climate change events. Under climate change, many areas in Southern Africa and the Sahel are likely to experience accelerated phenological crop development because of increased annual temperatures, resulting in a shortening of the growing season. Precipitation during the growing season will decrease, leading to a higher risk of water stress. However, in some highland areas, especially in Eastern Africa, increases in precipitation during the growing season may result in prolongation of the same (Thornton et al., 2006; Waha et al., 2013). Climate

14.2 Regional Perspective: Sub-Saharan Africa

change will also lead to increases in atmospheric CO2 (Tubiello et al., 2007), which may lead to yield increases of up to 20% of C3 vegetable crops, such as solanaceous African vegetables. 14.2.2 Interactions Between Climate Change and Other Factors Driving Vegetable Production and Consumption in Sub-Saharan Africa Climate change is not the only driver for vegetable production and consumption in sub-Saharan Africa. Africa is currently mostly rural with only 40% of the population living in urban areas, but the continent is set to urbanize the fastest in the coming decades, becoming 56% urban by 2050 (United Nations, 2014). Medium-sized cities in Africa (>1 million inhabitants) will become important, as they are among the fastest growing urban agglomerates. As a result, the importance of peri-urban and especially urban vegetable production will increase in sub-Saharan Africa. In Dar es Salaam, for example, between 1967 and 1991, the percentage of households practicing urban agriculture rose from 18% to 67%. In 1999, an estimated 90% of leafy green vegetables consumed within the city were produced locally in urban and peri-urban areas (Lwasa et al., 2015). Peri-urban and urban agriculture offer high employment and income possibilities for the urban population, but where these cities are left unmanaged, urbanization goes hand in hand with pollution and environmental degradation, together with unsustainable vegetable production and consumption patterns. Climate change exacerbates the barriers to sustainable urban and peri-urban agricultural systems. Flood risk, for example, increases because permeable land is being replaced by concrete (Sy et al., 2014). On the other hand, urban vegetable farming can make substantial contributions to the city beyond the provision of livelihoods and food, such as buffering and flood control (Danso et al., 2006), which will become increasingly common with climate change. Sub-Saharan African countries have some of the highest population growth rates in the world, which increases the severity of food insecurity. Tanzania’s population, for example, will double over the next four decades, increasing the competition for agricultural land and other resources, making the effects of climate change worse (Waithaka et al., 2013). However, income levels are also rising (Hachigonta et al., 2013). As vegetables, especially in urban areas, are more expensive than staples, higher income levels may provide an opportunity to increase vegetable farming and make more diversified diet options available to the growing population. In brief, population growth, urbanization, and income will increase in sub-Saharan Africa, intensifying pressure on natural resources needed to produce food. Climate change is an additional factor that may increase these pressures. Vegetable production and consumption patterns will undoubtedly change, and some implications are mentioned below. 14.2.3 Implications of Climate Change and Other Factors on Vegetable Production and Consumption in Sub-Saharan Africa Water is an essential component for vegetable production in sub-Saharan Africa, and will increasingly become a major limiting factor due to its increasing scarcity and irregular availability. The distinction between rain-fed and irrigated vegetable production is crucial, because rain-fed and irrigated agricultural production face different climate risk

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levels. While changes in precipitation directly impact rain-fed production, changes in river flow are directly related to irrigated production. Irrigated production is less vulnerable to changes in water resources (Calzadilla et al., 2010). Only a few factors influence whether farmers change crop types, but access to irrigation water is a significant determinant of changing crop type, with farmers that have access to irrigation water switching to high-value crops such as vegetables (Bryan et al., 2013). Where water is available, pressure will mount to increase production in decreasing land holdings. As a result, innovations in water management are needed for vegetable production. For example, investments for the recycling of wastewater may become necessary. Multiple cropping systems are an intrinsic component of agriculture in sub-Saharan Africa. However, they mostly consist of cereal–legume mixed cropping dominated by maize, millet, sorghum and wheat in Eastern and Southern Africa (Van Duivenbooden et al., 2000) and also with a major presence of root and tuber crops in West and Central Africa (Jalloh and Macauley, 2011). Waha et al. (2013) identified the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8,600 households. When testing different management scenarios for their susceptibility and adaptation to climate change, they found that aggregated mean crop yields in sub-Saharan Africa will decrease by 6% to 24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. By the end of the 21st century, crop calorific yields in single cropping systems will only reach 40–55% of crop calorific yields obtained in sequential cropping systems. For example, in Southern Africa, wild vegetable species play a major role in household food security in maize-based subsistence cropping systems (Mavengahama et al., 2013). These insights suggest that resilient and diverse cropping systems, including traditional African vegetables, are necessary components to buffer against climate change. Farmers’ choices of adequate crops and cropping systems will be another important adaptation strategy. The increasing scarcity of water sources may increase pollution, which is especially worrisome for vegetables. Leafy green vegetables are identified as the fresh produce commodity group of highest concern from a microbiological safety perspective (Liu et al., 2013). Because of increased temperatures, pathogens associated with leafy vegetables will enhance their growth and survival. Hence, the likelihood of leafy green vegetable contamination is strongly related to climate change, and the contamination risks are likely to increase. Food safety management of vegetables will become even more important. Farmers producing vegetables for export will find it increasingly difficult to comply with good agricultural practices (GAP) and maximum residue limits (MRL) and food safety standards within sub-Saharan Africa. These are currently lacking or poorly implemented and will need to be tackled soon, as regional trade within the region will gain in importance as a means of offsetting food shortages. Based on existing crop models, in some countries, increased temperature or precipitation will present opportunities to grow crops in areas where they could not previously be grown (Waithaka et al., 2013). Farmers’ choice of adequate crops and crop cultivars, especially in precipitation-limited areas, might be an important adaptation strategy to changing climate conditions (Thomas et al., 2007). Climate change will also drive the need to find more diverse crops. Wider use of today’s underutilized minor crops provides more options to build temporal and spatial heterogeneity into uniform cropping systems and will enhance resilience to both biotic and abiotic stress (Ebert, 2014). Many

14.2 Regional Perspective: Sub-Saharan Africa

traditional vegetables (e.g. amaranth, moringa) and underutilized legume crops (e.g. mung bean) have shown resilience to climate change and are essential sources of vitamins, micronutrients, and protein and, thus, a valuable component to attain food and nutritional security. The World Vegetable Center (WorldVeg) holds the largest public vegetable genebank, with close to 62 000 accessions from 440 species, in which various beneficial traits such as drought resistance and high yield have not been discovered and are waiting to be identified and used. Many poor households in sub-Saharan Africa have limited capacity to adapt to climate change, mainly consisting of small adjustments to their farming practices such as changing planting decisions. Few households can make more costly investments, such as implementing irrigation schemes, although there is a desire to invest in such measures. For example, in Kenya, irrigation and water harvesting schemes were ranked at the top among priority adaptations expressed by individual households, regardless of gender or agroecological area (Bryan et al., 2013). For many of the novel approaches related to climate-smart agriculture, sustainable scaling approaches are needed to address the challenges of poverty and climate change meaningfully. Based on 11 case studies, Westermann et al. (2015) concluded that multi-stakeholder platforms and policy-making networks are key to effective upscaling, especially if paired with capacity enhancement, learning, and innovative approaches to support farmers’ decision making. Global warming may lead to migration rates much faster than those observed during post-glacial times and hence has the potential to reduce biodiversity by selecting for highly mobile and opportunistic species (Malcolm et al., 2002). Invasive species and other species with high fertility and dispersal capabilities are highly adaptive to variable climatic conditions (Beddington et al., 2012). As a result, such species may rapidly disseminate in the region as evidenced by the rapid spread of the tomato pinworm, Tuta absoluta (Desneux et al., 2011). Similarly, diseases such as bacterial wilt caused by Ralstonia solanacearum will increase in incidence and severity. Grafting vegetables is an old horticultural technology utilized over an extended period of time in East Asia to improve plant production, to reduce susceptibility to a range of soil-borne diseases, and to increase soil utilization. WorldVeg has developed effective grafting techniques for tomato, eggplant, chili, sweet pepper and several cucurbits to control soilborne diseases such as bacterial wilt, Fusarium wilt, root-knot nematodes and abiotic stresses like flooding and salinity. Grafting is routinely used in Southeast Asia and offers great opportunities to pre-empt pests and diseases in sub-Saharan Africa. Women are essential actors in vegetable value chains in sub-Saharan Africa, and major custodians of vegetable household consumption and nutrition. In Mozambique, several drivers for the success of projects aimed at climate change adaptation have been identified, which include empowering women, water harvesting and small-scale irrigation, horticulture development, and tried and tested options for livelihood diversification (Midgley et al., 2012). Because irrigation is the most time-consuming aspect of urban and peri-urban vegetable farming, labor requirements will increase (Tallaki, 2005), which may add additional burdens for women. Climate change will have enormous implications for nutrition. A study in Uganda found that the relationship between nutrition and weather is inversely correlated and is strongest where households are isolated. The strongest negative correlation was discovered in environments prone to drought (Shively, 2015). These findings illustrate the importance of focusing on gender-sensitive approaches for rural populations when implementing climate adaptation strategies.

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There is a need to strengthen dissemination and use of indigenous knowledge and to integrate it in modern approaches to climate change adaption. Vegetable production is increasingly embraced by young professionals, partly because of the potential for high income. Low mastery of indigenous knowledge practices by these younger community members has challenged community resilience for climate change adaptation. An example of the use of indigenous knowledge in Uganda is the harvesting of wild fruits and vegetables in the event of intense drought (Egeru, 2012). It is clear that increased investments will be needed, including investments in irrigation and seed, but also in extension services, rural infrastructure and input access through lower transport and marketing costs. Ideally, these investments should target smallholders, and allow farmers to apply relatively cheap and low-tech adaptation options on a farm level. Investment in novel research is also needed. Some of the unfavorable effects of climate change can be removed altogether. Vertical vegetable gardens, for example, eliminate the challenges of infertile or saline soil, flooding, waterlogging, and land and water constraints (WorldFish, 2014). Novel schemes are emerging that can help smallholder farmers mitigate the risks of climate change. For example, insurance coverage can be based on weather indices correlating with factors such as rainfall during a specific timeframe, and payouts are triggered when this index falls above or below a pre-specified threshold. The Agriculture and Climate Risk Enterprise (ACRE) program has recently scaled up to reach close to 200,000 farmers across Kenya, Rwanda, and Tanzania, with payouts provided through mobile banking services (Greatrex et al., 2015). Reduction of loss and waste in food systems is one of the key recommendations made by FAO (2011) to combat the effects of climate change in sub-Saharan Africa. Vegetable production results in huge postharvest losses of up to 40%. The demand for food will increase with population growth, while the supply may decrease with climate change, but the amount of food production per person can be brought down by eliminating waste in vegetable supply chains. Efforts to lower food loss also may increase the overall efficiency of food supply chains and thereby reduce unnecessary use of energy, water, fertilizer, and land, reducing the effects of climate change. Activities to raise awareness of food waste and to promote the use of efficient strategies among food businesses, retailers and consumers will be needed (Beddington et al., 2012). For example, in Mozambique, growing less perishable and easily marketable vegetable crops seems to be the best solution. To help overcome marketing difficulties for farm products where road access is poor and distances long, simple preservation and processing techniques for vegetables should be promoted, including sun-drying of vegetables (Midgley et al., 2012). In one of their recommendations for sub-Saharan Africa, FAO (2011) also advocates a move toward more resource-efficient and healthier vegetable-rich diets. In emerging and urbanizing economies, dietary patterns are shifting away from nutritious food, including vegetables. ‘Westernization’ of eating patterns is expected to accelerate exponentially in sub-Saharan Africa, putting an even higher burden on the population (e.g. through the increase of non-communicable diseases) under stress of climate change and other factors. A better understanding of the diversity of vegetables and their importance in a nutritionally appropriate yet environmentally low-impact diet would be highly beneficial.

14.3 Regional Perspective: South and Central Asia

14.3 Regional Perspective: South and Central Asia Freshwater availability and agricultural biodiversity, which are already under pressure due to population growth and land use change, will be further impacted by climate change in Asia. In South Asia alone, 2.5 billion people will likely be affected by water stress and water scarcity by the year 2050. 14.3.1

The Effects of Climate Change in South Asia

South Asia is highly sensitive to the consequences of climate change. It is one of the most disaster-prone regions of the world, supporting a vast population of more than 1.7 billion (The World Bank, 2016). Climate predictions for the future indicate an increase in frequency and intensity of extreme weather events like droughts and floods (IPCC, (2014b)), thus likely exposing and affecting a significant portion of the population in the region. Analysis of rainfall data for India reveals an increase in the frequency of severe rainstorms over the last 50 years. The number of storms with more than 100 mm of rainfall a day increased by 10 % per decade (UNEP, 2007). On the other hand, many regions in Asia also have been affected by drought and rapid depletion of water resources, which is a cause for concern in many countries. In South Asia alone, 2.5 billion people will likely be affected by water stress and water scarcity by the year 2050 (UNDP, 2006). While estimating these numbers, likely changes in climatic conditions have not been considered. Meltwater from high altitude glaciers of the Himalayan range replenishes many major rivers in Asia. These rivers are the source of water for more than half of the world’s population. Accelerated glacial melt is likely to have huge implications on water availability for agricultural purposes in the region. Melting glaciers may fill glacial lakes in Nepal and Bhutan beyond their capacities, contributing to glacial lake floods (UNEP, 2007). Ice melt currently accounts for most of the observed sea level rise that is not attributable to expansion from ocean warming. At least 60% of ice melt is from glaciers and ice caps, rather than from the two ice sheets (Meier et al., 2007). The contribution of these glaciers and ice caps to sea level rise has accelerated since the late 1990s, due in part to extensive thinning and retreat of glaciers that terminate in the ocean (UNEP, 2007). This acceleration of glacier melt may cause 0.1–0.25 meters of additional sea level rise by 2100, beyond the increase estimated by the IPCC (2007). Agriculture is the backbone of several economies in Asia and a large source of employment. The sector continues to be the single largest contributor to the GDP in the region (Kelkar and Bhadwal, 2007). Bhutan and Nepal have fragile mountainous ecosystems, while Bangladesh and Sri Lanka have low-lying coastal areas. Tropical cyclones combined with sea-level rise will result in enhanced risk of loss of life, properties, and livelihoods in low-lying coastal areas of cyclone-prone countries. Increased precipitation intensity, particularly during the summer monsoon, can contribute to an increase in flood events. India and Pakistan depend on cultivation in arid and semi-arid lands. Drier summer conditions in these areas may lead to more severe droughts. With three-fifths of the cropland being rain-fed, the economy of South Asia depends critically on the annual monsoon rains. Agriculture contributes 19% to India’s GDP,

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employs two-thirds of the national workforce, and caters to the needs of agro-processing industries that form a major pillar of the Indian economy (Kelkar and Bhadwal, 2007). Agriculture is also the largest consumer of water in the region with more than 85 % of the water used for irrigation purposes in India. Agriculture and horticulture, therefore, are highly sensitive to the consequences of a changing climate. 14.3.2

The Effects of Climate Change in Central Asia

The World Bank has given the highest vulnerability rank to four of the five Central Asia countries among the 28 nations of Europe, the Caucasus and Central Asia. The most vulnerable are Tajikistan and Kyrgyzstan (Zoï Environment Network, 2009). Climate change scenarios for Central Asia suggest a 1∘ C to 3∘ C increase in temperature by 2030-50. Higher surface temperatures will result in increased evaporation and reduced soil moisture content, especially during the dry summer months. This scenario may amplify the risk of drought. Global climate phenomena such as the El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) are linked to climatic conditions and trends prevailing in Central Asia. Strong El Niño events are likely to enhance the risk of drought in the southern part of Central Asia and around the Caspian Sea, while a strongly negative NAO causes more precipitation in the south of Europe, the Mediterranean basin and Central Asia (Zoï Environment Network, 2009). Glaciers cover an area of 12 000–14 000 km2 within Central Asia (Zoï Environment Network, 2009). However, they are continuously shrinking. Those in the Tien Shan, Gissaro-Alai, Pamirs, and Dzhungarskiy and Zailiyskiy Alatau mountain ranges have been decreasing by about 1% each year in recent decades (ADB, 2010). Meltwater arising from snow, glaciers and permafrost supplies around 80% of the total river runoff in Central Asia (Zoï Environment Network, 2009). Glaciers are crucial to the agricultural economy of the region. They produce water in summer during the hottest and driest period of the year and compensate for generally low precipitation. Due to the shrinking glaciers, water availability in the major rivers (the Syr Darya and the Amu Darya) may decline by up to 30–40 % in the future (ADB, 2010). Climate change is contributing to the risk of floods and mudflows in Central Asia. There has been a series of glacial outburst floods in the mountains of Tajikistan, Uzbekistan, and Kyrgyzstan in recent years. With glaciers melting, glacial lakes appear every summer in the mountains, and, if contained by unstable moraines, they occasionally burst, causing destructive flash floods. 14.3.3

Climate Change Adaptation Options in South and Central Asia

Integrated water resource management (IWRM) is regarded as the most efficient way to manage water resources in a changing environment with competing demands (Kelkar and Bhadwal, 2007). Rainwater harvesting and integrated watershed management in rain-fed areas would help increase agricultural and horticultural resilience to increased climate variability. An integrated approach would involve modifying or extending infrastructure to collect and distribute water, the adoption of decentralized rainwater harvesting programs, and the implementation of water pricing policies to tame end-user demand. For the Central Asian countries, especially those dominated by deserts—Kazakhstan, Turkmenistan, and Uzbekistan—adaptation to climate uncertainty will require many

14.3 Regional Perspective: South and Central Asia

changes in agricultural practices (ADB, 2010). Existing ways of combating drought and desertification must be strengthened. The Zoï Environment Network (2009) suggests the following measures to enhance efficient water use: (1) Improved climate and water monitoring and forecasting; (2) IWRM; (3) broad introduction of efficient irrigation technologies; (4) water reuse and recycling, and drainage water management; (5) improved water quality control and pollution prevention; (6) water-saving incentives and training of farmers; and (7) rehabilitation of water pipelines and canals. Agricultural and horticultural performance can be enhanced through: (1) Improved agrometeorological and veterinary services, training, scientific and technical support for farmers; (2) conservation of valuable agrobiodiversity; (3) selection and introduction of drought- and pest-resistant and low water consumption crops, and appropriate crop protection methods; (4) water storage for reliable water supply in dry years; (5) crop rotation and shifting production to more suitable areas; (6) rehabilitation of degraded pastures and cropland; (7) remote sensing and mapping of pasture conditions; and (8) insurance, strategic food and forage reserves (Zoï Environment Network, 2009). There is potential to address many of the factors threatening production in changing environments by tapping into the rich storehouse of agrobiodiversity found in crops grown in South and Central Asia. The region is both a center of origin for many crop species and close relatives, and many varieties are adapted to a range of climates, environmental stresses, and other constraints. Maintaining the plant genetic resources of South and Central Asia is vital to realizing this potential. Plant genetic resources for food and agriculture (PGRFA) play a major role in food security and economic development worldwide, and in Central Asia and the Caucasus (CAC) in particular. Indigenous or traditional species are important food sources, particularly for people living in distant mountainous and steppe provinces where other vegetables cannot be grown or delivered, and where homesteads tend to be self-sufficient. As an integral component of agricultural biodiversity, these resources are crucial for sustainable intensification of agricultural production and to ensure the livelihood of a significant proportion of the population, mainly depending on agriculture and horticulture. Scientific understanding of the on-farm management of genetic diversity has increased. While this approach to the conservation and use of PGRFA is becoming mainstreamed within national programs, further efforts are needed to safeguard farmer-managed agricultural biodiversity (FAO, 2010). There is limited involvement from both public and private sectors in developing vegetable crops essential to the economic, food and nutritional security in the CAC region. These activities require strong government commitment and public support. National capacities in plant breeding and seed production and distribution in the region vary widely, and insufficient capacity in these areas often limits the efficient use of PGRFA (Mavlyanova, 2006). Measures for enhanced use of plant genetic resources for climate change adaptation include developing appropriate strategies and policies for the collection, conservation and efficient use of PGRFA. It is necessary to conduct collection missions to rescue valuable agricultural biodiversity threatened by genetic erosion, improve genebank management, and screen and use PGRFA in research programs for the development of new heat-, drought- and salt-tolerant varieties. WorldVeg deployed 1750 genebank accessions and breeding lines of 26 vegetable species for regional testing and state variety trials in eight CAC countries (Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan,

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and Uzbekistan). Many of these varieties adapted well to the local growing conditions. Forty-six new WorldVeg varieties of 14 vegetable crops are currently under state variety trials. From 2006 to 2015, 52 new varieties of 15 vegetable crops supplied by WorldVeg have been released and registered in the State Registries in eight CAC countries. Out of these, 46 % of released varieties have been selected, based on germplasm accessions supplied by the WorldVeg genebank, without undergoing further breeding. In summary, agriculture and aquaculture in Asia will be threatened by a combination of thermal and water stresses, sea level rise, increased flooding, drought, dry winds, and the occurrence of tropical cyclones. Freshwater availability and agricultural biodiversity, which are already under pressure due to population growth and land use change, will be further impacted by climate change. Prolonged or extreme climate stress can drive processes of impoverishment by affecting the livelihoods of poor people, while poverty increases vulnerability to climate change by limiting available options.

14.4 The Role of Plant Genetic Resources for Sustainable Vegetable Production Vegetable improvement depends on accessibility to a range of genetic diversity and the ability to use new genetic variation in plant breeding programs. Modern cultivars represent a limited range of available genetic variability to combat the effect of climate change. Crop wild relatives are often well adapted to marginal environments and can withstand biotic and abiotic stresses better than elite varieties. Since ancient times, they have served as the basis for crop domestication and improvement. Today, crop wild relatives that are prone to genetic erosion in the wild and are only partially conserved in genebanks have been rediscovered as essential resources for crop improvement programs to adapt staple crops as well as vegetables to climate change. However, interspecific hybridization poses severe challenges, including cross incompatibility, sterility, reduced recombination, and tight linkages to negative traits (de la Peña et al., 2011). Despite these difficulties, and through advances in breeding technologies, wild vegetable germplasm has been exploited for crop improvement and as a source of abiotic stress tolerance. Molecular markers provide a powerful tool to discover valuable traits tucked away in wild species and to move these traits into modern varieties (Ebert and Schafleitner, 2015). Marker-assisted selection in backcrossing programs has facilitated the transfer of genes from wide crosses involving crop wild relatives. The increasing ability to move genes from wild relatives into cultivated elite varieties coupled with the precision afforded by the use of modern molecular tools will accelerate the development of innovative vegetable varieties that will thrive in a changing environment. The dependence of countries on crops that originated in other parts of the world has increased over the past 50 years due to the economic and agricultural development and the globalization of food systems. As economies develop, there is an increasing demand for diversified diets and enhanced intake of protein derived from animal products (Keyzer et al., 2005). Moreover, there is a greater emphasis on nutritional quality of foodstuffs today, as well as the need for more resilient production systems in the face of climate change and natural resource limitations. This scenario will certainly increase the need for diverse germplasm in crop breeding, further accelerating global interdependence in plant genetic resources. Most countries need to access genetic resources

14.5 Microbial Genetic Resources to Boost Agricultural Performance of Robust Production Systems

from elsewhere for their agricultural production and food security and, hence, have to be regarded as interdependent in their use of genetic resources. It is expected that the challenges posed by climate change will increase interdependence among countries and will require greater efforts in the international exchange of PGRFA. Global interdependence in plant genetic resources provides a strong rationale for proactively conserving and facilitating access to this diversity worldwide. Therefore, Khoury and co-workers (2015) recommended in their policy brief a more comprehensive participation of countries in the multilateral system of access and benefit sharing of the International Treaty for PGRFA. Furthermore, they proposed the widening of the multilateral approach to the exchange of plant genetic diversity by considering all crops of present and future international importance for food and agriculture. PGRFA also are important in cross-cutting regional programs related to ecosystems, climate change, biodiversity, and invasive species. The number of on-farm management projects carried out with the participation of local stakeholders has slightly increased over the past decades, and new legal mechanisms have been put in place in several countries to enable farmers to market genetically diverse varieties (FAO, 2010). Countries now report a greater understanding of the amount and distribution of genetic diversity in the field, as well as the value of local seed systems in maintaining such diversity.

14.5 Microbial Genetic Resources to Boost Agricultural Performance of Robust Production Systems and to Buffer Impacts of Climate Change The performance of vegetables across contrasting and changing environments due to shifts in climate is inextricably linked to ecological interactions with other organisms in the ecosystem. Microorganisms are diverse and can be largely divided into five functional groups—soil inhabitants, plant and rhizosphere inhabitants, plant pathogens, biological control agents, and food production/preservation microorganisms (Beed et al., 2015). While some interactions, both antagonistic and beneficial to crop productivity, are specific to individual vegetable species, others perform more general functions in the environment. For example, the performance of grain legume vegetables is dependent on their symbiotic association with root-nodulating Rhizobia bacteria that fix nitrogen in the soil. Conversely, free-living and rhizosphere-associated organisms are key players in the creation and maintenance of soil and its structure, and nutrient cycling; they act to stabilize ecosystems and to ensure the provision of clean water and air (Wall et al., 2015). As humanity modifies natural habitats to produce food from more intensified systems involving limited numbers of crops, the pathogen populations of those crops are actively selected. If agronomic practices are deployed that enhance microbial diversity, these emerging plant pathogens will be suppressed through biological control (Beed et al., 2015). Similarly, soil-borne human pathogens are suppressed by increased soil biodiversity (Wall et al., 2015). As crop species and varieties are moved to new locations to adapt to changes in climate, mutualistic associations with microbes will need to be encouraged through appropriate land management practices. If absent in certain environments, then microbes that confer critical functional roles in sustainable crop production will need to

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be introduced. Such an approach requires global databases and archived living reference collections combined with an enabling policy and technical environment to facilitate characterization, access, and sharing of these organisms (Beed, 2011). While certain climate changes will make some environments more conducive to pests and diseases, others will promote the proliferation of their natural enemies and management through biological control, so there is need to remain vigilant and to monitor profile changes in organisms systematically and not to rely on assumed generalizations. This can be illustrated through a historical study of the need to study plant pathogens in association not only with their crop hosts but also within their natural environments, where other organisms act to increase or reduce their abundance. Henry (1932) showed that when wheat was grown in sterilized soil and inoculated with the fungal pathogen Gaeumannomyces graminis—the causal agent of take-all disease—the severity of the disease increased with temperatures from 13 to 27 ∘ C. However, in natural, unsterile soil, the severity of the disease declined when the temperature exceeded 18 ∘ C. This is due to the fact that higher temperatures promote other microorganisms that are antagonistic to the take-all fungus. Increased temperature will affect the ripening of vegetables, causing a shift in the life cycles of the microorganisms naturally resident on the surfaces of these crops. Many surface-borne microorganisms can potentially protect against microorganisms that are harmful to vegetable quality—e.g. soaking in suspensions of yeast reduces the effects of spoiling microorganisms (Zhao et al., 2010).

14.6 Physiological Responses to a Changing Climate: Elevated CO2 Concentrations and Temperature in The Environment Global climate models predict a gradual increase in atmospheric CO2 concentration ∘ and global temperatures to as much as 700 ppm and 2.2 C, respectively by 2100 (IPCC, (2014a)). As CO2 is known to be the principal driver of climate change (Bhardwaj, 2012), it is imperative to assess the effect of such a change on plant growth and development (Šigut et al., 2015; Peet and Wolfe, 2000). We summarize below the likely physiological effects of increased CO2 levels in plants. 14.6.1

CO2 and Photosynthesis

CO2 is a key molecule for photosynthesis. In plants, photosynthesis occurs mainly in the leaves. The resulting carbohydrates are used for plant growth and provide the necessary energy source under ‘normal’ conditions with current atmospheric CO2 concentrations of ∼400 ppm (IPCC, (2014a)). The CO2 concentration limits the photosynthetic reactions under high temperatures and high light intensities. Therefore, photosynthesis is enhanced under increased CO2 levels, resulting in higher dry matter production (Taiz and Zieger, 2015). This phenomenon is known as the ‘CO2 fertilizer effect’, which is used to stimulate crop growth in greenhouses and plant factories (Lobell and Gourdji, 2012). This effect is more pronounced in C3 crops, such as rice, wheat, and legumes (e.g. soybean, mungbean) but less so in C4 crops (e.g. maize, millet, and

14.6 Physiological Responses to a Changing Climate: Elevated CO2 Concentrations

sugarcane). As the present atmospheric CO2 level limits photosynthesis in C3 plants, higher CO2 concentrations will activate the rate limiting enzyme of carboxylation, RuBisCO, which leads to accelerated biochemical reactions (Bindumadhava et al., 2011; Sheshshayee et al., 1996). This initial ‘jump’ is temporary due to subsequent feedback inhibition imposed by ineffective functional sinks. C4 plants elude this effect with the built-in maintenance of CO2 in mesophyll cells (Taiz and Zeiger, 2015). If the CO2 level is doubled, the net photosynthesis (Pn) rate of many C3 plants increases by 30–55% (Johkan et al., 2011). However, in several C3 plants, these promotional effects are temporary and often disappear over the long-term. It is assumed that changes in the photosynthetic apparatus or other factors that occur during short-term responses differ from those during prolonged exposure, which is often the case when photosynthetic production exceeds plant growth (Nakano et al., 1997; Šigut et al., 2015). However, plants that have separate storage organs for assimilates such as radish and potatoes appear to be unaffected (Usuda and Shimogawara, 1998). 14.6.2

CO2 and Stomatal Transpiration

In most crops, increased CO2 levels improve water use efficiency (WUE) due to higher carbon fixation functions triggered by photosynthesis and declined stomatal conductance, potentially decreasing drought susceptibility and reducing input water requirements. When substrate CO2 is high, it precludes stomatal control of its diffusivity between outside and inside of the leaves (Bindumadhava et al., 2011). Nevertheless, the effect of decreased transpiration on vegetable crop yields is unlikely to be large because vegetables are irrigated in most production areas. However, physiological disorders such as tip burn in lettuce, blossom-end rot in tomato and bell pepper, are sometimes associated with excessive transpiration and tissue water deficits (Rogers and Dahlman, 1993). 14.6.3

Dual Effect of Increased CO2 and Temperature

Temperature increases from global warming will occur concurrently with the rise in CO2, and they both interact closely (Idso et al., 1987). High temperature affects the photosynthetic functions and causes irregularities of physiological machinery associated with CO2 . For instance, in tomato, overall productivity is reduced by high temperatures due to bud drop, abnormal flower development, dehiscence and viability, ovule abortion, poor viability, and reduced carbohydrate availability. Some universally drawn strategies to ameliorate the effects of global warming on food production include development and use of heat-tolerant varieties, proper nutrient and water management, coordination of growing periods, and control of pests/diseases. In particular, use of heat-tolerant crops and pest/disease control are perhaps the most promising approaches (Johkan et al., 2011). Largely, the useful effect of elevated CO2 might be offset by the adverse global warming effect. Increased temperatures accelerate the rate of many physiological processes viz., photosynthesis to an upper limit. Extreme temperature can be harmful beyond physiological limits of a plant (Lynch and Lande, 1993). High temperature distresses vegetable crops in several ways by influencing crop duration, flowering, fruit growth, ripening, and quality. Since vegetables usually consist of at least 90% of water, drought stress, mostly at critical periods of growth, would drastically reduce productivity and

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quality (Chatterjee and Solankey, 2015). Forecasting which vegetable types are most vulnerable to high temperatures is difficult. Nonetheless, it is suggested that indeterminate types are less sensitive to periods of heat stress since flowering occurs over an extended period, compared with determinate types that flower all at once (Hall and Allen, 1993). Under heat stress, the reported effect of elevated CO2 on photosynthesis and growth are highly variable and differ among plant types (Wang et al., 2012; Šigut et al., 2015). 14.6.3.1

High Temperature (HT) Effect on Mungbean

Mungbean is cultivated on over six million ha in warmer regions of the world and is one of the important food legumes in South and Southeast Asia, mainly in the Indian sub-continent, which accounts for 45% of global production. Mungbean is a short duration (60–65 days) legume crop and has wide adaptability with low input requirements (Nair et al., 2012). However, its productivity is very low in tropical and sub-tropical regions of Asia, such as India and Pakistan, due to harsh growing conditions compounded by abiotic stresses, such as increasing CO2 levels, high temperatures, and salinity. Heat stress has detrimental effects at several plant levels leading to drastic reductions in growth and yield (Wahid et al., 2007). HT results in a scorching effect leading to marginal (mild) to complete (severe) browning of leaves. Leaf damage intensifies due to oxidative damage and reduction in anti-oxidative defense (Kumar et al., 2011, 2013). The roots, flowers, and seeds depend on the leaves to supply sucrose and other molecules for nodulation growth, reproductive function, and seed filling. Maintenance of the photosynthetic role of the leaves is vital under heat stress to sustain synthesis and transport of sucrose to these organs (Awasthi et al., 2014). Sucrose decreases in leaves and seeds owing to heat stress conditions, which may be linked to reduced RuBisCO activity and sucrose synthesizing enzymes. Heat stress affects sucrose production in leaves and impairs its transport to developing reproductive sinks (Kaur et al., 2015). It also reduces the ability of nitrogen fixation by heating up the soil surface, which hampers the nodulation process and affects rhizosphere activity, thus reducing the nodules in mungbean roots (Kumar et al., 2013). Photosynthesis may be inhibited as a result of the loss of chlorophyll, disruption of electron flow and reduced CO2 assimilation (Sinsawat et al., 2004). At a cellular level, heat stress leads to membrane damage, enzyme inactivation in mitochondria and chloroplasts, impaired protein synthesis and carbon metabolism (Hasanuzzaman et al., 2013). 14.6.3.2

Current and Proposed Mungbean Physiology Studies at Worldveg South Asia

WorldVeg South Asia initiated a study on mungbean to explore the dual effect of high temperatures with increasing CO2 levels. Forty-five elite mungbean accessions (a collective pool representing varieties/genotypes from different sources/partners from India) were used for this purpose, and relevant agronomic and physiological traits were assessed along with final pod and seed yields in both managed walk-in growth houses and under field conditions. Plants of 45 different mungbean accessions were grown in containers on sandy-loam soil mixed with sand in a 3:1 ratio and placed outdoors in a walk-in mesh house (summer 2015, Punjab, India) and under field conditions (summer 2015, Hyderabad, India). Day/night temperatures during the larger part of the reproductive phase on average

14.6 Physiological Responses to a Changing Climate: Elevated CO2 Concentrations

were >40/25∘ C. Sets of accessions were sown at two planting times, the first batch during the last week of March (normal-sowing), and the second batch during the last week of April (late sowing). This was meant to expose the plants to heat stress at reproductive stages. Seeds were treated with Rhizobium culture, and the plants were irrigated daily to avoid any possible water deficits, which may occur to a larger extent in a field-grown crop. Daily max/min temperature, RH, photoperiod, PAR and photosynthetic efficiency were recorded from sowing to final maturity stage to relate the weather conditions with yield. The response of these accessions to higher temperatures (43–44∘ C) during peak growth and reproductive stages in late sowing season was determined during the full growth and production cycles. Based on sustained growth (plant height, functional leaf area, biomass accumulation), physiology (photosynthetic efficiency, chlorophyll function, stomatal and transpiration efficiency, functional water relations), reproductive status (flowering initiation, effective number of flowering clusters, resistance to flower abortion, pollen germination and viability, stigma receptivity) and final yield traits (number of pods, pod setting, pod and seed yield/plant) (Fig. 14.1), ten putative high temperature tolerant accessions have been identified for further investigation. From a future climate change prospect, an attempt also was made by subjecting these identified accessions to elevated CO2 environments to determine growth and yield responses. They were grown under increased CO2 concentrations in Open Top Chambers (OTC) at the controlled climate management facility of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Hyderabad, India. Briefly, CO2 enriched air was distributed through air blowers within the OTC. The designated concentration of CO2 within the OTC was measured by a CO2 analyzer. Potted plants of ten mungbean accessions were placed randomly inside OTCs (maintained at three CO2 concentrations: 390 ppm – ambient, 550 ppm and 700 ppm). Growth, intrinsic physiological efficiencies, and yield traits were measured regularly, up to final harvest. Single leaf level photosynthesis and transpiration efficiencies were recorded in plants of Normal sown genotypes

VC6173 8–10

EC 693369

VC6372(45-8-1)

EC 693370

ML 818

Late sown genotypes

Figure 14.1 Pod morphology of a few selected mungbean accessions from normal and late sowing summer season (please note heat induced changes in pod shape, size and length in late-sown genotypes).

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Table 14.1 Range values of photosynthesis and transpiration efficiencies, measured at single leaf level, of selected mungbean accessions grown in OTC with different CO2 concentrations. Physiological traits

Amb. CO2

Photosynthetic rate (μmol m−2 s−1 )

550 ppm CO2

700 ppm CO2

Min

Max

Min

Max

Min

Max

24.0

33.6

32.1

50.1

30.2

48.3

0.3

0.9

0.8

2.3

0.4

1.6

5.1

9.2

7.1

13.2

6.1

12.2

Stomatal conductance (μmol m−2 s−1 ) −2 −1

Transpiration rate (mmol m s )

all treatments (Table. 14.1) using a portable photosynthesis system (LI-6400XT, LiCOR systems, USA). Preliminary results indicated that the photosynthetic rate increased in elevated CO2 conditions by 40–45%, stomatal efficiency by 90–100% and transpiration rate by 20–22%, respectively over ambient (control) conditions. Among the accessions, an appreciable increase in growth traits (plant height, leaf area, total dry matter) in the range of 78–125%, under both elevated levels of CO2 (550 and 700 ppm) was observed along with increased yield traits (number of pods, pod fresh and dry weights, pod and seed yield) ranging from 47 % to 111% (Fig. 14.2). Interestingly, exposure of mungbean accessions to 550 ppm CO2 resulted in a gain in early maturity of about 12 to 14 days in a few accessions. The second level of confirmatory experiments is underway. This report is perhaps the first information on mungbean about exploiting promising heat- tolerant accessions under elevated CO2 conditions for their growth and yield responses. From these experiments, we expect useful clues towards developing a much-needed strategy for future climate change challenges. 14.6.4

Conclusion

Knowing the likely impact of increases in atmospheric temperature and CO2 on vegetable crops would constitute a first step in developing comprehensive adaptation 140.0

125.1

120.0

% Increase

334

100.0

102.4

111.1 97.9 83.5

80.8

80.0 60.0

78.2

47.2

40.0 20.0 0.0 # Pods

LA (cm2)

PDW (g/pl)

TDM (g/pl)

Traits 550 ppm

700 ppm

Figure 14.2 Percent increase in growth and yield traits of CO2 fertilized plants compared with ambient CO2 (control) conditions across all mungbean accessions (LA – Leaf Area, PDW – Pod Dry Weight, TDM – Total Dry Weight of the whole plant).

14.7 Plant Breeding for Sustainable Vegetable Production

strategies to address the adverse effects of climate change and global warming, as most of the vegetables—being annual crops—are deprived of any carbon sequestration potential. In the present study, among the mungbean pool evaluated, we found 10–12 accessions showing intrinsic tolerance to high-temperature stress. When they were further exposed to different elevated CO2 levels, 6–8 accessions showed intrinsically higher adaptive (physiological) abilities compared to the rest. Hence, these genotypes can be categorized as promising elite candidates for subsequent analysis to detect useful information regarding their mechanism for climate resilience. Mungbean has a distinct advantage of being a short-duration crop that can be grown in a wide range of environments. Exploring fundamental physiological mechanisms and phenotypic traits (either acquired or adapted) that impart tolerance to adverse climate conditions (water deficits, heat stress, and salinity) is of paramount significance. Further, we plan to use higher CO2 influx at different growth stages for developing a mungbean model for varied and diverse growth conditions. The present studies and the associated learning process can empower us to develop a low-cost, feasible field module to effectively capture the benefits of elevated CO2 in C3 plants like mungbean in particular, and vegetables in general, as almost all vegetable crops are C3 species requiring more substrate CO2 to run their photosynthetic machinery effectively.

14.7 Plant Breeding for Sustainable Vegetable Production Vegetable breeding has significantly contributed to global food, nutrition, and income security through intensification, diversification, and industrialization of the horticultural sector. The excitement after the rediscovery of Mendel’s laws of inheritance at the beginning of the 20th century led to a series of scientific and technological advancements (Table 14.2). Both private and public sectors invested heavily in these emerging new breeding tools to enhance vegetable breeding programs. Improved vegetable seeds, especially hybrid seeds, constitute a major market segment that generates a high return on investment compared with old, open-pollinated crop seeds and planting materials. This section focuses on vegetable breeding perspectives for sustainable vegetable production in changing small-scale farming systems in Asia and Africa in response to ongoing socio-economic and climatic changes. Examples from WorldVeg’s international breeding programs, especially of tomato and pepper, showcase the impact of the availability of improved seeds to the livelihoods of smallholder farmers and households in Asia and Africa. 14.7.1

Formal Vegetable Seed System –Lessons Learned

The existence of a formal seed sector is a prerequisite to harness the full potential of professional plant breeding programs. Among developing countries, India has witnessed the development of a sophisticated private seed industry over the past 20 years. This is attributed to deregulation of the seed policy in 1987, leading to substantial investments and the initiation of new seed companies (Pray et al., 2001). Liberalization eliminated significant restrictions on the import of vegetable seeds, including seeds of hybrid cultivars developed by multinationals. The combination of proper incentives, access to better germplasm and qualified human resources led to

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Table 14.2 Major scientific discovery, technological advancements, and events in genetics and plant breeding. Period

Major breakthroughs

1865–1900

Mendel proposed laws of heredity. This led to active research in this area by some groups worldwide.

1900–1935

The rediscovery of Mendel’s laws and the establishment of chromosome theory of inheritance; the term “genetics” was coined. The linkage between the genes was explained, which led to the concept of indirect selection of a trait by selection of other characters (i.e. application of morphological markers in breeding).

1935–1970

Discovery of DNA as genetic materials and totipotency of cells; application of tissue culture techniques in plant breeding. Discovery of cytological, biochemical (protein/isozyme) markers; use of morphological markers (dwarf plants) in breeding, leading to Green Revolution.

1970–2005

Discovery/invention of restriction enzymes, Southern blotting, Taq polymerase and polymerase chain reaction (PCR) machine. Extensive use of non-PCR markers, PCR based markers, computer robotics, microarray, genetic transformation (both nuclear and organelle) techniques.

2005 to date

Rapid and highly cost effective sequencing of whole plant genomes; use of high throughput genotyping by sequencing, large-scale phenotyping, bioinformatics, targeted genome editing, metabolic profiling of crops.

commercialization of improved vegetable cultivars, which benefited farmers. However, there is considerable variation in vegetable seed R&D with a fledgling private vegetable R&D sector arising in a few countries (e.g. Bangladesh, Kenya, Senegal), but relatively little development in other Asian and African countries. 14.7.2

Role of WorldVeg’s International Breeding Programs

Breeding for the development of new vegetable cultivars with multiple disease- and insect pest resistance and tolerance to abiotic stresses can make a substantial contribution toward sustainable vegetable production. Tomato, peppers, cucurbits, onion, legumes, some traditional vegetables (e.g. amaranths, African eggplant) and mungbean are WorldVeg’s principal breeding crops. WorldVeg breeders envision seed companies, NGOs, and community-based organizations as major vehicles to deliver improved seeds to the local farmers. The production of vegetable seed is an essential component of business for the private seed sector. Long-term research such as identification and introgression of resistance genes from wild relatives usually requires an investment of decades to complete. This is a timeframe beyond the willingness and capacity of most small seed companies. Hence, WorldVeg’s approach to heavily invest in pre-breeding is logical. WorldVeg has proven expertise in the development of traits such as resistance to several diseases, insect resistance, and flavonoids in tomato (Hanson et al., 2013; Kadirvel et al., 2013; Rakha et al., 2015; Hanson et al., 2016) and introgression of anthracnose resistance genes from two different Capsicum species into commonly cultivated C. annuum hot pepper (Gniffke et al., 2013, Suwor et al., 2015). Over 22 thousand seed samples of tomato and over 33 thousand seed samples of pepper were supplied to institutions in 138 countries from 2001 to 2013 (Ebert and Chou, 2015). For both species,

14.7 Plant Breeding for Sustainable Vegetable Production

80 % of the seed shipments were improved breeding lines and 20 % were germplasm accessions (Ebert and Chou 2015). These materials have and are going to benefit mainly small and medium seed companies, which compete with each other to better satisfy the expectations of their customers and other stakeholders. WorldVeg assists such companies with breeding materials to develop cultivars quickly, and the resulting seed sales can provide revenue to these private sector enterprises to support their R&D activities. This approach has proven to be successful in India and East and Southern Africa. 14.7.3

Impact of WorldVeg’s Breeding Programs

Over the last 25 years, more than 500 cultivars based on WorldVeg’s developed and supplied vegetable germplasm have been released in more than 35 countries worldwide. An analysis of pepper seed dissemination efforts revealed that since 2005, 30 pepper lines provided by WorldVeg had been released as open-pollinated varieties (OPVs) for commercial cultivation in eight countries (Lin et al., 2013). Also, 34 hybrids developed using WorldVeg materials as parental inbreds were commercialized in six other countries. Most of these hybrids were commercialized by seed companies (Reddy et al., 2015). Despite the major shift from OPVs to hybrid seed in recent years, international germplasm provided by WorldVeg continues to play a significant role in varietal development by seed companies. A survey undertaken by Schreinemachers et al. (2017) in India, showed that 11.6 t or 14 % of the total market of hybrid tomato seed and 15.0 t or 13% of hybrid chili pepper seed sold by Indian seed companies in 2014 still contained WorldVeg germplasm in its pedigree. The authors estimated that over half a million farmers use such seed. In East and Southern Africa, an analysis of improved open-pollinated varieties supplied by private seed companies in Tanzania revealed that in 2014, 50% of tomato and 98% of African eggplant commercial seed production in the region was based on varieties developed by WorldVeg (Schreinemachers et al., 2017). For Tanzania alone, investment in crop improvement generated economic gains of US$ 255 million for tomato and US$ 5 million for African eggplant up to 2014. Replication of this kind of larger impact is possible in many African and Asian countries but requires creating a critical mass of breeders, plant protection specialists, entrepreneurs and an enabling policy framework. 14.7.4

Future Outlook

In recent years, private plant breeding programs have increased in size and number (Silva, 2010). Public sector breeding must remain vigorous, especially in areas where the private sector does not function (Silva, 2010). WorldVeg, in partnership with several National Agricultural Research and Extension Systems (NARES), is working to improve traditional vegetables which, in general, are considered to be highly nutritious. Active connections between the private and public breeding sectors and better use of germplasm conserved in national, regional and international genebanks are mandatory. Improved open-pollinated and hybrid vegetable varieties are, and will continue to be, the most effective, environmentally safe, and sustainable way to ensure global food security in the future (Silva, 2010). Under normal circumstances of a functioning formal seed system, crop breeding, seed production and marketing of improved seeds of OPVs and hybrid varieties provide incentives to all stakeholders. Thus improved

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seeds are available on a sustainable and competitive basis. Many factors such as increasing pressure from diseases and insect pests, urbanization, shortages of agricultural labor, shrinking cultivable land, increasing risks of crop failure due to unpredictable climate, and growing demand for more nutritious and safer foods will drive changes in vegetable crops and production systems. Sustainable agricultural production systems will require new cultivars with enhanced traits, improved production technologies, and better marketing strategies. These adjustments and advancements will affect all stakeholders.

14.8 Management of Bacterial and Fungal Diseases for Sustainable Vegetable Production Plant diseases caused by fungal and bacterial pathogens impose a significant threat to vegetable production. Plant diseases can occur when susceptible host plants, virulent pathogens, and conducive environments co-exist. Environmental conditions such as temperature, moisture levels, and atmospheric composition play a major role in the development of fungal and bacterial diseases. The expected climate change predictions by 2100 include an increase in global mean temperatures of 0.9 to 3.5∘ C (Chakraborty et al., 2000; IPCC, 2007) and a projected doubling of CO2 to greater than 700 μmol mol−1 (IPCC, 2007). Whether climate change will enhance, reduce, or not affect the manifestation of crop diseases is largely determined by the plant-pathosystem and the environmental factors expected to occur (Chakraborty et al., 2000). Moreover, extensive research on increased levels of CO2 has been shown to enhance photosynthesis and water use efficiency. This, in turn, may lead to higher biomass and yield (Kimball, 1983; Rogers and Dahlman, 1993; Amthor, 1995; Drake et al., 1997; Kimball et al., 2002; Ziska and Bunce, 2007) and an increase of canopy size in most crop plants (Pangga et al., 2013). An increase of canopy size has a large impact on the microclimate within the plant canopy, such as a decrease in light levels, reduction of air circulation and an increase in relative humidity, which can enhance the proliferation and spread of many fungal diseases (Pangga et al., 2004, 2013). While higher temperatures can affect many aspects of the physiology of crop plants, of particular concern, are the possible adverse effects on host disease resistance. For example, several genes involved in host defense responses have been shown to be negatively regulated by higher temperatures increasing disease severity (de Jong et al., 2002; Romero et al., 2002; Sun et al., 2011). In general, plants that are subjected to stress will be more susceptible to pathogens, particularly to unspecialized necrotrophic pathogens (Desprez-Loustau et al., 2006). An increase in rainfall can enhance the development of certain bacterial and fungal pathogens. For example, increased duration of surface wetness of leaves and canopies in addition to warm temperatures could increase the severity of fungal diseases such as anthracnose caused by Colletotrichum spp. The addition of wind and water runoff can promote the dispersal of pathogens leading to larger infectious areas and survival of the pathogens (Luck et al., 2011). Research approaches for predicting climate change on plant disease is still an evolving field, with the challenge of finding causal relationships separated from crop management practices that may influence the observed pathogen distribution (Juroszek and Tiedemann, 2013). However,

14.8 Management of Bacterial and Fungal Diseases for Sustainable Vegetable Production

each plant-pathosystem must be evaluated for risk under the projected climate changes to design strategies for managing the disease. Climate change combined with globalization, increased human mobility, and pathogen and vector evolution have increased the spread of invasive plant pathogens. Early and accurate diagnoses and pathogen surveillance on local, regional, and global scales are necessary to predict outbreaks, allowing for timely development and application of mitigation strategies. Plant disease diagnostic networks have been developed worldwide to address the problem of efficient and effective disease diagnosis and to promote cooperation of institutions and experts (Miller et al., 2009). Among the networks, the Global Plant Clinic, a consortium of CABI Bioscience, Rothamsted Research, and Central Science Laboratory, has trained local extension staff to become plant doctors and to set up mobile plant clinics in developing countries to provide diagnostic service and management advice to farmers. On-site symptom-based diagnoses should be followed up with laboratory assays to confirm the identification of the pathogen. Paper-based molecular diagnostic methods are ideal, due to the ease of collecting DNA samples from pure cultures or diseased plant tissues, and transportation and storage of field samples (Ndunguru et al., 2005). Following this approach, collaboration among WorldVeg, the Secretariat of the Pacific Community, and the Fiji Ministry of Agriculture utilized the Whatman FTA card technology to identify the causal agent of re-emerging chili anthracnose as Colletotrichum acutatum (Wang et al. unpublished data). Linking sampling and field diagnosis with efficient pathogen identification is the key to effective disease surveillance and downstream management practices. Approaches to the sustainable management of plant diseases include the following principles: (1) preventing the contact of the pathogen and the plants; (2) reducing the pathogen population size; (3) utilizing host resistance; and (4) direct protection of plants from pathogens (Maloy, 2005). Preventing the entry of exotic plant pathogens with high risk is the first line of defense for disease management. National plant protection organizations are responsible for establishing effective quarantine regulation, including a list of quarantined organisms that should be restricted from entering the country or from further spreading within the country. At the same time, vegetable farmers can apply practices to reduce or avoid the risk of disease outbreak. Such practices include using pathogen-free planting materials such as seeds, seedlings or other propagating materials, selecting a plot that is pathogen-free or without disease history, applying netting to protect seedlings from insect vectors, and planting in a season that is not favorable to the disease occurrence. Wei et al. (2015) demonstrated that by shifting the transplanting time earlier in the spring crop and later in the autumn crop for tomato significantly reduced the incidence of bacterial wilt due to the lower mean maximum air temperature. With the trend of global climate change, farmers may need to adjust production periods to reduce or avoid endemic diseases. Eradicating or reducing a pathogen population present in an area, a plot, a plant, or plant parts, such as seeds, is a critical component in a sustainable disease management package. Based on the mode of action, the methods can be grouped into three categories, i.e., cultural (rotation and sanitation), physical (soil solarization, heat treatment of planting materials, etc.), chemical (soil fumigation, seed treatments and soil amendments, etc.) or biological (use of biocontrol agents or compost). Although many of these methods may not bring immediate or complete control, reducing the

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pathogen population size could prevent the disease resurgence in the next season, which could have a positive impact over the long term. Control efficacy of soil treatments may vary from location to location. Michel and Mew (1998) found that the effect of urea and calcium oxide amendment on the survival of Ralstonia solanacearum, a soil-borne bacterium that causes bacterial wilt, is dependent on the interaction of the pH and nitrite accumulated during urea hydrolysis of the treated soils. The suppressive effect of nitrite was observed only under acidic conditions. An incubator test was designed to conduct a preliminary evaluation of the suppressive effects of soil amendments on R. solanacearum for field application (Lin et al., 2008). Use of resistant cultivars is the least expensive, easiest, and safest control method for small-scale vegetable farmers. Moreover, diseases caused by soil-borne pathogens often cannot be controlled adequately by other means. However, in some cases, the performance of resistant cultivars can vary in different locations, or the cultivars can become susceptible after some time. Pathogens that pose the greatest risk of breaking down resistance genes have a mixed reproduction system, a high potential of genotypic flow, large effective population size, and high mutation rates (McDonald and Linde, 2002). It has been observed that the aggressiveness of Erysiphe cichoracearum on the model plant Arabidopsis increased with higher stomatal density, guard cell length, and trichome number on newly developed leaves under elevated CO2 conditions (Lake and Wade, 2009). It is likely that the evolution of plant pathogens could be affected by climate change, which, in turn, could have an impact on the durability of resistant cultivars. WorldVeg has focused on breeding for resistance against a few important pathogens with large evolutionary potential, such as chili anthracnose caused by several species complexes of Colletotrichum, and tomato bacterial wilt caused by the species complex of R. solanacearum. Approaches taken for developing durable, resistant cultivars include: (1) monitoring pathogen spatial and temporal variation; (2) identifying durable, resistant sources with suitable evaluation methods; and (3) identification of markers associated with multiple resistant loci for gene pyramiding. Fruit anthracnose of Capsicum spp. can be caused by several Colletotrichum species. The nomenclature for the Colletotrichum species has been under constant reassessment (Hyde et al., 2009). C. acutatum has been reported to infect pepper and chili fruits in Taiwan (Sheu et al., 2007), Thailand (Than et al., 2008) and Korea (Kim et al., 2008). However, the taxonomy of C. acutatum has been reassessed and revised. Shivas and Tan (2009) recognized three distinct groups within C. acutatum strains from Australia and established two new species, C. simmondsii and C. fioriniae, for molecular groups A2 and A3, respectively. A recent study further separated 29 species within the complex of C. acutatum sensu lato (Damm et al., 2012), indicating the complexity of the species. Following the latest classification, Kanto et al. (2014) confirmed that the causal agent of an outbreak of anthracnose on sweet pepper in Japan to be C. scovillei. Adopting a common and robust classification system is important to reveal the distribution of different species or pathogen types, which would enable breeding resistant cultivars against the predominant pathogen species or type in a region. Broad spectrum resistance against many species of Colletotrichum was reported for Capsicum chinense accession ‘PBC932’ (AVRDC, 1999). However, the resistance has been overcome by new pathotypes of C. acutatum in Thailand and Taiwan (Than et al., 2008; Mongkolporn et al., 2010; Gniffke et al., 2013). In addition to pathogen isolates, disease reactions on chili pepper could vary, depending on the inoculation methods and fruit stage (Mahasuk et al., 2009;

14.8 Management of Bacterial and Fungal Diseases for Sustainable Vegetable Production

Lin et al., 2007). WorldVeg is currently coordinating research to identify suitable artificial inoculation methods with good correlation with field reactions and to determine resistant sources with stable performance against anthracnose over different locations in Southeast Asia. Considering the complexity of the Colletotrichum species infecting pepper, more and diverse resistance genes are required for future gene pyramiding. Investigating resistance in other closely related species to C. annuum, such as C. chinense and C. frutescens as well as C. baccatum, can achieve this goal. Bacterial wilt caused by Ralstonia solanacearum is hard to manage due to its soil-borne nature, ability to survive for extended periods of time under a wide range of environmental conditions, and wide host range covering more than 200 monocotyledonous and dicotyledonous species (Denny, 2006). Traditionally, R. solanacearum has been classified into five races and six biovars according to host range and biochemical properties, respectively. Genetic and phylogeny studies conclude the presence of four different phylotypes related to the geographical origin of the strains, namely Asiaticum (phylotype I), Americanum (phylotype II), Africanum (phylotype III), and Indonesian (phylotype IV) (Fegan and Prior, 2005). Variation in virulence of R. solanacearum strains within phylotypes has been observed, and tomato has a high susceptibility to diverse R. solanacearum strains (Lebeau et al., 2011). Resistance to bacterial wilt in tomato can be location-specific (Hanson et al., 1996) and strain-specific (Prior et al., 1990). ‘Hawaii 7996’ (Solanum lycopersicum) is one of the most stable sources of resistance against R. solanacearum in tomato, exhibiting a high survival rate (97 %) over 12 field trials conducted in 11 countries (Wang et al., 1998). Two major QTLs were identified with stable resistance in ‘Hawaii 7996’ by evaluating a set of recombinant inbred lines in several field locations and against different strains (Wang et al., 2013). Bwr-12, located in a 2.8-cM interval of chromosome 12, controlled 17.9–56.1 % of the total resistance variation. The main function of Bwr-12 was associated with the suppression of the bacteria multiplying in the stem. However, this QTL was not associated with resistance against race 3-phylotype II strain. Bwr-6, which was distributed along a 15.5-cM region on chromosome 6, explained 11.5–22.2 % of the phenotypic variation. Bwr-6 and Bwr-12 are commonly present in known resistant tomato lines developed by different breeding programs (Ho and Wang, 2013). An examination of the population structure of R. solanacearum phylotype I in Taiwan revealed that the local population is homogeneous, while mutations and adaptation to local specific ecological niches keep shaping the population (Lin et al., 2014). Searching for new resistance should be continued for stacking multiple resistance QTLs to generate resistant cultivars against different pathogen strains. Application of chemical agents could protect vegetables from endemic diseases that commonly occur at a certain season or plant stage. Selection of chemical agents should be based on accurate diagnoses and local recommendations and regulations. Timely application following regular field scouting is the key to effective control. Since the introduction of site-specific fungicides in the 1960’s, fungicide resistance in phytopathogenic fungi has become a major problem in plant protection. Alteration of the biochemical target sites of fungicides is the common mechanism of resistance to site-specific fungicides (Ma and Michailides, 2005). A variety of abiotic and biotic inducers have been applied to enhance the resistance to pathogen infection (Walters et al., 2005). Biotic inducers include infection by necrotic pathogens and plant-growth promoting rhizobacteria, and treatment with non-pathogens or cell wall fragments. Abiotic

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inducers include chemicals that act at various points in the signaling pathways involved in plant defense, as well as water stress, heat shock, and pH stress. Resistance induced by these agents, also known as resistance elicitors or plant activators, is broad spectrum and long lasting, but rarely provides complete control of infection. For example, Acibenzolar-S-methyl, a plant activator that induces systemic acquired resistance in many different crops, could manage tomato bacterial spot and bacterial speck similar to standard copper compounds (Louws et al., 2001). Phosphorous acid has been found to be able to suppress diseases caused by oomycete pathogens (Grant et al., 1990). A simple method to prepare neutralized phosphorous acid salt for controlling Phytophthora disease has been developed (Ann et al., 2009), which is easy for small-scale vegetable farmers to adopt. Results of field trials conducted in Bali, Indonesia showed neutralized phosphorous acid salt can control tomato late blight as efficiently as chemical fungicides currently used by farmers (WorldVeg, unpublished data). Enhancing the capacity of small-scale vegetable farmers on disease diagnostics and integrated disease management is the best way to reduce their vulnerability to climate change. Such capacity would allow early and accurate disease diagnosis, and to apply appropriate control methods before, during and after the cropping season. Adequately trained farmers could adapt their local vegetable production systems to become more resilient to the uncertain effects of climate change on plant disease outbreaks.

14.9 Management of Insect and Mite Pests Insect and mite pests are a major biotic constraint limiting the productivity of vegetable crops in the tropics and sub-tropics. They cause serious damage at various growth stages of a vegetable crop starting from the seedling stage until the final harvest. Besides causing direct damages, some insects also act as vectors of viral diseases. If the crop is left unprotected, the damage can lead to complete crop failure. For instance, according to a review by Srinivasan (2013), the legume pod borer (Maruca vitrata) can cause up to 80% yield losses in vegetable and grain legumes in different parts of the world. The yield reduction in eggplant due to fruit and shoot borer (Leucinodes orbonalis) and in tomato due to fruit worm (Helicoverpa armigera) can be as high as 70%. Complete crop failure is possible with diamondback moth (Plutella xylostella) on vegetable brassicas. The extent of losses due to melon fly (Bactrocera cucurbitae) varies between 30% and 100%, depending on the cucurbit species and season. Climate change, especially the rise in carbon dioxide (CO2 ) concentration, and temperature, substantially alters the pest status. For instance, the common army worm (Spodoptera litura) increased its feeding on mungbean plants grown under elevated CO2 because of increased sugar levels (Srivastava et al., 2002). Reproduction of green peach aphid (Myzus persicae) on Brassica oleracea plants was substantially increased under elevated CO2 (Bezemer et al., 1999). Increases in temperature also increased the number of generations in whitefly (B. tabaci) biotypes (Muniz and Nombela, 2001). Vegetable growers face serious challenges from exploding pest populations, especially under changing climates, and resort to indiscriminate and unsustainable applications of hazardous and broad-spectrum chemical pesticides, which destabilize the production system due to the adverse effects on above-ground as well as soil-dwelling beneficial

14.9 Management of Insect and Mite Pests

organisms. Different components of integrated pest management strategies have been effective in regulating the sustainability of production systems, in part due to the enhanced ecosystem services they provide. This section exemplifies the roles of different pest management components in sustainable vegetable production systems. In general, pest management practices can be broadly grouped into two categories: preventive measures and curative measures. Preventive pest management measures include the use of resistant or tolerant varieties, cultural practices which prevent, delay or reduce the onset of harmful pest species, and protective cultivation. Curative measures include pest management interventions such as the use of pheromones and attractants, botanical and microbial pesticides, and conservation and augmentation of generalist as well as species-specific natural enemies. When carefully chosen and deployed, these component technologies sustainably regulate pest populations at levels below the point of causing economic damage to various vegetable crops. As eggplant fruit and shoot borer is practically a monophagous pest feeding only on eggplant, discontinuation of eggplant cultivation in a community for few seasons will significantly reduce populations of this pest. Eggplant seedlings should not be grown near fields with previous or existing crops, or near dried eggplant heaps (Alam et al., 2003). Various cultural practices such as ridging of young plants, planting of legumes after a green manure crop, crop rotation, and mulching with paddy straw enhance tolerance to bean fly damage in vegetable and grain legumes (review by Srinivasan, 2013). The seedling production of various vegetable crops can be carried out under 32-mesh nylon net to reduce the infestation of lepidopteran pests or 60-mesh nylon net to reduce the sucking pests early in the season, which would lessen the amount of chemical pesticides used at the beginning of the crop cycle, and thus help protect natural enemies. Although resistant or tolerant varieties may differ in their performance depending on the strains or biotypes of the target pest species in a region, they still have the potential to reduce the pest damage significantly. For instance, different eggplant varieties were shown to be tolerant or resistant to fruit and shoot borer across locations in South Asia (review by Srinivasan, 2013). High levels of fruit borer and whitefly resistance have been reported in close as well as distant relatives of tomato (Talekar et al., 2006; Rakha et al., 2015). Mungbean accessions that are resistant to legume pod borer are also available (review by Srinivasan, 2013). However, some of these accessions or varieties may not be used directly, since they may possess some undesirable agronomic traits. Care must be taken when choosing an accession or variety to be incorporated into an IPM strategy. Intercropping, trap cropping, and barrier (border) crops are also useful in preventing or reducing the incidences of insect pests on target vegetable crops. When eggplant was grown with intercrops such as coriander, mint and marigold and maize as the border crop, the diversity of natural enemies was significantly higher compared to the sole crop (Sujayanand et al., 2015). African marigold can be planted as a trap crop to reduce fruit worm attacks on tomato (review by Srinivasan, 2013). Recent studies have indicated that tropical soda apple (Solanum viarum) can be used as an effective ‘dead-end’ trap crop to manage tomato fruit worm (Srinivasan et al., 2013). Dead-end trap crops do not require any pesticide treatment to prevent the pest population from moving onto the main crop. The dead-end trap crop should be planted in field borders, where it can intercept pest adults and thus reduce damage to the main crop (Shelton and Badenes-Pérez, 2006). Sequential trap cropping with Indian mustard is an effective

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way of reducing diamondback moth damage. Also, studies have indicated that yellow rocket (Barbarea vulgaris var. arcuata) can be used as a dead-end trap crop for the management of diamondback moth (Shelton and Badenes-Pérez, 2006). Insect pheromones including sex and aggregation pheromones are extensively used not only for monitoring but also for mass-trapping of insect pests. Besides suppressing the pest population, the use of pheromone traps also enhances biodiversity because fewer applications of chemical pesticides are needed to keep pests in check, allowing natural enemies to flourish. For example, a pheromone-based IPM strategy reduced pesticide abuse in eggplant production systems and enhanced the activities of natural enemies, especially Trathala flavoorbitalis, a larval parasitoid of fruit and shoot borer in the Indo-Gangetic plains of South Asia. The parasitism rate during the production period was considerably higher (40–50%). If this level of parasitism is sustained over larger areas throughout the year, it will reduce the pest population on a sustainable basis, thus reducing the need for pesticide use in combating this pest (Alam et al., 2003). Similarly, bio-pesticides complement the performance of natural enemies against key insect pests on vegetable crops, which was evident in the management of diamondback moth. Bacillus thuringiensis-based bio pesticides and parasitoids of diamondback moth (Diadegma semiclausum and Diadromus collaris) act synergistically to suppress major lepidopteran pests on vegetable brassicas in tropical Asia (Srinivasan, 2012). Additive effects were also found on the mortality of diamondback moth when entomopathogenic fungi were combined with the parasitoid, Oomyzus sokolowskii (dos Santos Jr. et al., 2006). Experiments have confirmed the plausible synergism between Maruca vitrata multiple nucleopolyhedroviruses (MaviMNPV) and the parasitoid Apanteles taragamae against legume pod borer in West Africa (Srinivasan et al., 2009). Besides microbial pesticides, botanical pesticides are an effective component of IPM strategies. Among the botanical pesticides, neem (Azadirachta indica) is widely used, and several formulations containing the active component azadirachtin are commercially available. A recent study has confirmed that Melia azedarach extracts and commercial neem formulations can be employed together for the sustainable management of Oriental fruit fly (Bactrocera dorsalis), tomato fruit worm and legume pod borer (Srinivasan et al., 2015). The evidence is available for the synergistic action of neem with microbial pesticides such as NPVs and entomopathogenic fungi against tomato fruit worm, common army worm (Spodoptera litura) and legume pod borer (Srinivasan, 2012; Sokame et al., 2015).Thus, biopesticides and natural enemies either alone or in combinations can play a significant role in sustainable pest management in vegetable production systems.

14.10 Grafting to Overcome Soil-borne Diseases and Abiotic Stresses The soil is the matrix in which crops grow. It is a complex environment incorporating inorganic matter, organic matter, and microorganisms. Pathogens of soil-borne diseases such as bacterial wilt (Ralstonia solanacearum), fusarium wilt (Fusarium oxysporum f. sp. lycopersici), and root-knot nematodes (Meloidogyne spp.) survive in the soil and are difficult to control. These soil-borne diseases are major constraints to the production of tomato and other vegetable crops. The fumigant methyl bromide, widely

14.10 Grafting to Overcome Soil-borne Diseases and Abiotic Stresses

used for controlling soil-borne diseases, was phased out in 2015, and grafting is now one of the recommended alternatives to methyl bromide, according to the United Nations Environment Programme (UNEP) (Schafer, 1999). Under the effect of climate change and human activities, abiotic stresses such as flooding, drought, salinity, and extreme temperature are becoming more severe. Those unfavorable abiotic stresses are threatening crop production and thus food security, which can be alleviated by the use of grafting technology. Grafting technology combines different genotypes for use as a scion and rootstock to form a new plant. The rootstock is the base portion of the grafting union that provides the root system, while the scion is the upper portion that produces the harvestable yield (Genova et al., 2013). In the last four decades, grafting has been a common practice to overcome such stresses to plant growth, especially in East Asia, in both the Solanaceae and Cucurbitaceae (Schwarz et al., 2010; Keatinge et al., 2014). In the late 20th century grafting was introduced to Europe and other countries for commercial vegetable production (Kubota et al., 2008). From Europe, grafting was introduced to North America and is now enjoying growing interest by greenhouse growers and organic farmers. Vegetable grafting can provide a high level of control of soil-borne diseases, but also increases tolerance to abiotic stresses (Schwarz et al., 2010) and productivity while maintaining high fruit quality. However, the degree of tolerance varies with the type of rootstock used. Using the right rootstock can help overcome abiotic stressors, such as high salinity, flooding, and soil temperature extremes, even allowing the extension of the growing season. Also, grafted vegetables have resulted in increased yields and shown increased water and nutrient uptake (Rivard and Louws, 2011; Genova et al., 2013). Bacterial wilt (R. solanacearum) research has been conducted by the World Vegetable Center since the establishment of the Center in 1973 and grafting research began in 1992 to develop quick and inexpensive grafting procedures as a way to control bacterial wilt. The tube splicing method was found to be the most successful method for tomato grafting. The tomato rootstock VI043614 (Hawaii 7996) and eggplant rootstocks VI034845 (TS03), VI046101 (EG190), VI046103 (EG195), VI045276 (EG203) and VI046104 (EG219) were found to be resistant to bacterial wilt, Fusarium wilt, root-knot nematodes, and flooding to different degrees. These rootstocks are currently being recommended by WorldVeg scientists (see WorldVeg website at: avrdc.org; Genova et al., 2013). As the tolerance/resistance of the recommended rootstocks might be overcome by pathogens with time and given the impact of climate change and the evolution and aggressiveness of pathogens, screening of new rootstock sources and rootstock-scion combinations is currently in progress (Fig. 14.3; Fig. 14.4). For this purpose, germplasm of solanaceous and cucurbit crops conserved in the WorldVeg genebank is screened for tolerance/resistance to biotic and abiotic stresses. Compatibility testing between scions and rootstocks is undertaken as well. Grafting provides a stronger root system (rootstock) for the scion to produce a good harvest, even under stress conditions. It is a technique that can be used both in protected or open field vegetable production. It is not only an alternative to methyl bromide, but also facilitates sustainable agriculture by reducing the application of chemicals (fumigants, pesticides, and fertilizer). It can effectively control soil-borne diseases and overcome abiotic stresses. For smallholder farmers or women farmers, grafting provides a method to overcome several crop production constraints. Production and sale of grafted

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Figure 14.3 A tunnel type grafting/healing chamber developed by the World Vegetable Center.

Figure 14.4 Grafted tomato plant transplanted to the field.

seedlings to neighboring communities may be an alternative income source for better livelihoods. A successful example is the introduction of the grafting technique by WorldVeg to Vietnamese scientists in September 1998 during a one-month training course. Following this training, grafting was introduced in Lam Dong province in southern Vietnam, in collaboration with the Potato, Vegetable and Flower Research Center from 2002 to 2006. An evaluation study was undertaken recently—ten years after the introduction of the grafting technology in Vietnam—to assess the impact of tomato grafting on the tomato industry. Farmers adopted tomato grafting to control soil-borne diseases, such as bacterial wilt (R. solanacearum), to overcome abiotic stress, such as an excess of soil moisture (waterlogging) during the hot-wet summer season, as well as to extend the growing season. Based on the average difference in profits between grafted and non-grafted tomato, and considering the 100% adoption rate and the total area under tomato cultivation in Lam Dong province, the estimated total profit for tomato farmers was US$ 41.7 million higher than if the same area had been planted with non-grafted tomato (Genova et al., 2013). Recent grafting experiments conducted in Uzbekistan with the local variety Gulkand revealed that grafted plants flowered and ripened earlier, had higher yield compared to non-grafted plants and—depending on the rootstock used—higher soluble solid and ascorbic acid content (Mavlyanova, pers. comm.). Climate change adds pressure to vegetable production systems. Grafting is a promising technique to tackle both biotic and abiotic stresses and is now receiving more attention worldwide to overcome some production constraints. In 2014, researchers

Acknowledgment

began screening germplasm from WorldVeg’s extensive genebank collections for alternative rootstock sources. Resulting promising accessions with biotic and abiotic stress resistance/tolerance can then be used in rootstock breeding to develop rootstocks with desired horticultural traits. This may enhance and strengthen sustainable horticulture and food security.

14.11 Summary and Outlook Climate change is predicted to have a major impact on agriculture and horticulture, consequently affecting the world’s food supply. Many factors such as expected shifts in ecological and agro-economic zones, land degradation, reduced water availability, elevated CO2 , strong winds, typhoons and cyclones, sea level rise and salinization will pose a severe threat to sustainable cultivation of staple crops as well as vegetables and fruit. The latter are of prominent importance for nutrition security and balanced diets. Population growth, urbanization, and income will further increase in sub-Saharan Africa and Asia. These factors will increase pressure on the natural resources needed to produce sufficient, nutritious and healthy food, and climate change is an additional critical factor threatening sustainable food production and nutrition security. Smallholder farmers in the tropics and subtropics, in particular, will be affected by climate change. The challenges posed by climate change will increase interdependence among countries on plant genetic resources for food and agriculture and will require greater efforts in sustainable conservation and international exchange. Microbial genetic resources can boost the agricultural performance of robust production systems and serve as a buffer to the impact of climate change. WorldVeg researchers identified a set of promising mungbean accessions performing well under high temperature and elevated CO2 conditions. Climate change combined with globalization, increased human mobility, and pathogen and vector evolution have increased the spread of invasive plant pathogens. Approaches to the sustainable management of plant diseases and insect pests include: (1) preventing the contact of the pathogen/insect with the crop plants; (2) reducing the pathogen/insect population size; (3) utilizing host resistance; and (4) direct protection of plants from pathogens/insects. Use of resistant cultivars is the least expensive, easiest, and safest control method for small-scale vegetable farmers. Over the last decades, WorldVeg breeders have embarked on breeding for multiple disease resistance against a few important pathogens of global relevance and with significant evolutionary potential, such as chili anthracnose, tomato bacterial wilt, and Tomato yellow leaf curl virus. Agronomic practices that enhance microbial diversity may suppress emerging plant pathogens through biological control. Biopesticides and natural enemies either alone or in combination can play a significant role in sustainable insect pest management in vegetable production systems. Grafting can effectively control soil-borne diseases and overcome abiotic stress. WorldVeg’s grafting technology is routinely used in Southeast Asia and offers great opportunities to pre-empt pests and diseases in sub-Saharan Africa and Central Asia and to combat abiotic stress.

Acknowledgment The authors wish to thank Maureen Mecozzi for the careful editing of this manuscript.

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Srinivasan, R., Su, F.C., and Huang, C.C. (2013) Oviposition dynamics and larval development of Helicoverpa armigera on a highly preferred unsuitable host plant, Solanum viarum. Entomologia Experimentalis et Applicata 147(3): 217–224. Srinivasan, R., Lin, M.Y., Yule, S. et al. (2015) Effects of botanical extracts and formulations against fruit fly, fruit and pod borers on tomato and yard-long bean. Biological Agriculture & Horticulture: An International Journal for Sustainable Production Systems, 31(4): 254–264. Srivastava, A.C., Tiwari, L.D., Madan P., and Sengupta, U.K. (2002) CO2–mediated changes in mungbean chemistry: Impact on plant- herbivore interactions. Current Science, 82: 1148–1151. Sujayanand, G.K., Sharma, R.K., Shankarganesh, K. et al. (2015) Crop diversification for sustainable insect pest management in eggplant (Solanales: Solanaceae). Florida Entomologist, 98: 305–314. Sun, Y., Yin, J., Cao, H. et al. (2011) Elevated CO2 influences nematode-induced defense responses of tomato genotypes differing in the JA pathway. PLoS ONE, 6, e19751. Suwor, P., Thummabenjapone, P., Sanitchon, J. et al. (2015) Phenotypic and genotypic responses of chili (Capsicum annuum L.) progressive lines with different resistant genes against anthracnose pathogen (Colletotrichum spp.). European J. Plant Pathology, 143: 725–736. Sy, M., Khouma, M., Diagne, M.O. et al. (2014) Building Urban Resilience: Assessing urban and Per-Urban Agriculture in Dakar, Senegal. United Nations Environmental Program, Nairobi, Kenya. 47p. Taiz, L. and Zeiger, E. (2015) Plant physiology (6th edition). Sinauer Associates Press, Sunderland, MA, USA. Talekar, N.S., Opeña, R.T., and Hanson, P. (2006) Helicoverpa armigera management: a review of AVRDC’s research on host plant resistance in tomato. Crop Protection, 25(5): 461–467. Tallaki, K. (2005) The pest control systems in the market gardens of Lomé, Togo. AGROPOLIS The social, political and environmental dimensions of urban agriculture, IRDC, Ottawa, Canada, pp. 51–67. Than, P.P., Jeewon, R., Hyde, K.D. et al. (2008) Characterization and pathogenicity of Colletotrichum species associated with anthracnose on chili (Capsicum spp.) in Thailand. Plant Pathology, 57: 562–572. The World Bank, 2016. Data South Asia. http://data.worldbank.org/region/SAS (accessed 8 February 2016) Thomas, D.S.G., Twyman, C., Osbahr, H., and Hewitson, B. (2007) Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa. Climatic Change, 83: 301–322. Thornton, P.K., Jones, P.G., Owiyo, T.M. et al. (2006) Mapping Climate Vulnerability and Poverty in Africa. Report to the Department for International Development, Nairobi. ILRI, Nairobi, Kenya. 173p. Thornton, P.K., Jones, P.G., Alagarswamy, G., and Andresen, J. (2009) Spatial variation of crop yield response to climate change in East Africa. Global Environmental Change, 19(1): 54–65.

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Tubiello, F.N., Amthor, J.S., Boote, K.J. et al. (2007) Crop response to elevated CO2 and world food supply: a comment on “food for thought…” by Long et al., Science 312: 1918–1921, 2006. European Journal of Agronomy, 26: 215–223. UNDP (United Nations Development Programme) (2006) Human Development Report 2006. Beyond scarcity: Power, poverty and the global water crisis. http://hdr.undp.org/ sites/default/files/reports/267/hdr06-complete.pdf (accessed 9 February 2016). UNEP (United Nations Environment Programme) (2007) GEO Yearbook 2007: An overview of our changing environment. Nairobi: UNEP. 86 pp. United Nations (2014) World Urbanization Prospects. 2014 Edition. Highlights. United Nations, New York, USA. 27p. Usuda, H. and Shimogawara, K. (1998) The effects of increased atmospheric carbon dioxide on growth, carbohydrates, and photosynthesis in radish, Raphanus sativus. Plant and Cell Physiology, 39(1): 1–7. Van Duivenbooden, N., Pala, M., Studer, C. et al. (2000) Cropping systems and crop complementarity in dryland agriculture to increase soil water use efficiency: a review. Netherlands Journal of Agricultural Science, 48: 213–236. Waha, K., Müller, C., Bondeau, A. et al. (2013) Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa. Global Environmental Change, 23: 130–143. Wahid, A., Gelani, S., Ashraf, M., and Foolad, M.R. (2007) Heat tolerance in plants: an overview. Environ. Exp. Bot., 61: 199–223. Waithaka, M., Nelson, G.C., Thomas, T.S., and Kyotalimye, M. (2013) East African Agriculture and Climate Change: A Comprehensive Analysis. IFPRI, Washington DC, USA. 387p. Wall, D.H., Nielsen, U.N., and Six, J. (2015) Soil biodiversity and human health. Nature, DOI: 10.1038:nature15744. Walters, D., Walsh, D., Newton, A., and Lyon, G. (2005) Induced resistance for plant disease control: Maximizing the efficacy of resistance elicitors. Phytopathology, 95: 1368–1373. Wang, D., Heckathorn, S.A, Wang, X, and Philpott, S.M. (2012) A meta-analysis of plant physiological and growth responses to temperature and elevated CO2 . Oecologia, 169: 1–13. Wang, J.F., Hanson, P.M., and Barnes, J.A. (1998) Worldwide evaluation of an international set of resistance sources to bacterial wilt in tomato. In: P. Prior, C. Allen, and J. Elphinstone (eds). Bacterial wilt disease: molecular and ecological aspects. Springer, Berlin, pp. 269–275. Wang, J.F., Ho, F.I., Truong, H.T.H. et al. (2013) Identification of major QTLs associated with stable resistance of tomato cultivar ‘Hawaii 7996’ to Ralstonia solanacearum. Euphytica, 190: 241–252. Wei, Z., Huang, J.-F., Hu, J. (2015) Altering Transplantation Time to Avoid Periods of High Temperature Can Efficiently Reduce Bacterial Wilt Disease Incidence with Tomato. PLoS ONE, 10(10): e0139313. doi:10.1371/journal.pone.0139313. Westermann, O., Thornton, P., and Förch, W. (2015) Reaching More Farmers – Innovative Approaches to Scaling Up Climate Smart Agriculture. CCAFS Working Paper No. 135. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Copenhagen, Denmark. 110p.

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WorldFish (2014) Vertical agriculture: Suspended Horticulture in Towers. WorldFish, Dhaka, Bangladesh. 7p. Zhao, Y., Tu, K., Tu, S. et al. (2010) A combination of heat treatment and Pichia guilliermondii prevents cherry tomato spoilage by fungi. International Journal of Food Microbiology, 137: 106–110. Ziska, L.H. and Bunce, J.A. (2007) Predicting the impact of changing CO2 on crop yields: some thoughts on food. New Phytologist, 175: 607–618. Zoï Environment Network (2009) Climate Change in Central Asia: a visual synthesis. Imprimerie Nouvelle Gonnet, F-01303 Belley, France; 80 p.

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15 Sustainable Production of Roots and Tuber Crops for Food Security under Climate Change Mary Taylor 1 , Vincent Lebot 2 , Andrew McGregor 3 , and Robert J. Redden 4 1

University of the Sunshine Coast, Queensland, Australia CIRAD-AGAP, Vanuatu 3 Koko Siga Pacific, Fiji 4 RJR Agricultural Consultants, Horsham, Victoria, Australia 2

15.1 Introduction Root and tuber crops, including cassava (Manihot esculenta), sweet potato (Ipomoea batatas), yams Dioscorea spp.), potato (Solanum tuberosum), edible aroids such as taro (Colocasia esculenta), cocoyam/tannia (Xanthosoma sagittifolium), giant taro (Alocasia macrorrhizos) and swamp taro (Cyrtosperma merkusii) are important to agriculture and food security of many countries, ranging from the tropics through to temperate countries for potato. They are the second most important group of food crops in developing countries after cereals (Lebot, 2009). These crops contribute to the diet of approximately 2.2 billion people as well as to animal feeds and industry. The annual world production of root and tuber crops is about 765 million tonnes (mt) consisting of potatoes (333 mt), cassava (237 mt), sweet potatoes (130 mt), yams (53 mt), and taro and other aroids (12 mt). Globally around 110 kg tropical root and tuber crops are consumed per capita on a yearly basis. Cassava, sweet potatoes, yam, taro and other aroids are largely consumed in the developing world with most of the potato production consumed in the developed countries. Despite their importance, however, investment in root and tuber crops has been much lower than in the cereal crops. Reasons include low levels of productivity often as a result of pests and diseases, bulky nature of the crops, high water content and a relatively short shelf-life. Value chain development and the expansion of production and delivery at scale to processors and markets can be problematic (Chandra, 2015). Climate change research has mainly considered and evaluated the impact on major food crops grown in continental environments. Climate model-based studies show that climate change will fundamentally alter global food production patterns and that negative yield impacts for wheat, rice, maize, sorghum and millet are expected in low latitude and tropical regions (Rosenzweig et al., 2014; Frieler et al., 2015). Analysis of past climate trends reveals that negative impacts are more common than positive ones, for example, there is evidence that climate change has already negatively affected

Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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wheat and maize yields in many regions and also at global level (Lobell, Schlenker and Costa-Roberts, 2011; Porter et al., 2014). Knox et al. (2012) conducted a systematic review of model-based studies of future yields of major staples in South Asia and Africa. Under high greenhouse gas (GHG) emissions, significant yield variation is indicated with maize (–16%) and sorghum (–11%) in South Asia and wheat (–17%), maize (–5%), sorghum (–15%) and millet (–10%) in Africa. Meta-analysis of data in Europe showed extensive impacts of climate change on yield for wheat, maize, sugar beet and potato, but limited for barley, rice and rye (Knox et al., 2016). The impact on other crops, such as roots and tubers, has been much less studied (HLPE, 2012a), despite their importance for nutrition and livelihood opportunities. Model limitations have precluded the study of mixed systems and minor crops (Challinor et al., 2014b; Thornton and Herrero, 2015). A review of crop models for potato, sweet potato and yam found that crop physiological knowledge, detailed field experimental data and agronomic research are rare for these crops, especially for sweet potato and yam; and that major field experimentations for modelling improvements are needed for potato, sweet potato and yam (Raymundo et al., 2014). However, climate change impact studies for root and tuber crops do exist, based on an application of climate models, knowledge of climate projections combined with an understanding of the crop’s physiology and optimum growing conditions, and expert (farmer and researcher) opinion; such studies suggest that root and tuber crops generally will be less affected by climate change than the staple cereal crops (Adhikari et al., 2015; McGregor et al., 2016). It is suggested that cassava could benefit as it is characterized by high optimum temperature for photosynthesis and growth and shows a positive response to CO2 increase (Porter et al., 2014). Tuber crops, generally, appear to be more stimulated by elevated CO2 levels than grain crops (Miglietta et al., 1998; Rosenthal et al., 2012). Ayanlade et al. (2010) found that tuber yield of cassava and yam was significantly affected by rainfall variation (550–2987 mm) depending on the genotype under cultivation and the production system. Projections of climate change impacts on crop production are largely based on modelling– using climate and crop models. But as noted by Lebot (2013), the temperature and rainfall operate within a microclimate where the crops are grown, and this can change significantly between different locations, for example, between the windward and leeward sides of the same island, e.g. in the Pacific and Caribbean regions. For agricultural impacts research, regional- to local- scale projections of climate variables, such as seasonal temperatures, seasonal rainfall, and frequency of both temperature and rainfall extremes are key requirements in understanding the potential impacts on agricultural productivity (Ramirez-Villegas et al., 2013). The following sections consider the optimum growing conditions for root and tuber crops and their tolerances to abiotic and biotic stress, and based on this information discuss the potential vulnerability of these crops based on climate change projections. The observations of farmers and researchers working with the crops are also considered as the resilience of any crop to climate change cannot be separated from their cropping systems and from the farmers and communities who manage those systems. Potato is discussed separately because more research has been conducted on this crop.

15.2 Optimum Growing Conditions for Root and Tuber Crops

15.2 Optimum Growing Conditions for Root and Tuber Crops 15.2.1

Sweet Potato

Optimum temperatures for growth should be 24∘ C or more (Lebot, 2009). The greatest increase in storage root weight occurs when the crop is grown at a constant soil temperature of 30∘ C and night air temperature of 25∘ C (Spence and Humphries, 1972). Tuber formation is impaired when air temperature exceeds 34∘ C (Bourke, 2013), with a lower night-time temperature required for tuber formation and a higher day temperature for vegetative growth (Adhikari et al., 2015). Optimum rainfall for sweet potato is in the range of 900 to 1300 mm (Nelson and Elevitch, 2011), but farmers can grow sweet potato in locations with high to very high rainfall, (up to 5000 mm/year), using mounds or drains to reduce soil water levels (Bourke and Harwood, 2009). Well distributed rainfall of 1000 to 2000 mm and high levels of sunshine are required to obtain the highest yield potential (Lebot, 2009). Genetic variation for salinity tolerance has been demonstrated in Vietnam (van Kien et al., 2013), China (Gui Ling et al., 2011), and when cultivated hydroponically (Begum et al., 2015). 15.2.2

Cassava

The optimum temperature for growth for cassava is 25∘ –29∘ C but the crop will tolerate a wide temperature range of 12∘ –40∘ C. Cassava thrives with annual rainfall of between 1500–2000 mm/year and maximum solar radiation (Lebot, 2009). Higher rainfall levels can reduce root growth, but despite this, it remains an important food crop in some very high rainfall locations. Cassava is considered to be a crop that is highly tolerant to drought and can be grown where precipitation is as low as 500 mm/year (FAO, 2010). Stomata in cassava are very sensitive to changes in atmospheric humidity as well as in soil water. Cassava close stomata under water stress and can remain photosynthetically active at reduced rates, over most of its life cycle. A further advantage is the deep rooting capacity of cassava enabling water to be extracted at a slow rate to a depth of 2m. Finally, leaf canopy is much reduced under prolonged stress, contributing to lower crop water consumption. Post water stress, cassava rapidly forms new leaves with higher photosynthetic rate compensating for the yield reductions of prolonged stresses (El-Sharkawy, 2006). Drought can however, reduce yield by up to 60% if a prolonged drought period (>2 months) falls during the root thickening initiation state (Jarvis et al., 2012). Water stress can impact on starch quality, depending on the severity of the conditions and stage of plant maturity (Lebot, 2009) and the cyanogen levels in the plant (Taylor et al., 2016). High concentrations of cyanogens associated with drought can be reduced by cooking and boiling and by watering plants for two weeks after the drought period (Vandergeer et al., 2013). Drought can also exacerbate micronutrient deficiency (e.g. zinc) due to reduced transpiration rates, and also mineral toxicity, such as boron and salinity (Reynolds et al., 2010). Cassava is particularly susceptible to water logging and to high winds (>30 knots) which can cause lodging of the plants. Farmers anticipating the arrival of a

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cyclone/hurricane can cut off the stems above ground level, reducing the damage to the roots. Cassava has the added advantage over many crops in that it can be planted at any time of the year and some varieties can be stored in the ground for two to three years, providing some insurance against more intense storms (McGregor et al., 2016). Studies carried out on cassava varieties obtained from different regions of Africa (arid, saline zone compared with high rainfall areas) showed that some genotypes were more sensitive to salinity than others (Carretero et al., 2007). 15.2.3 15.2.3.1

Edible Aroids Taro

Taro is an important edible aroid in many parts of the world, especially the Pacific. The preferred temperature for maximum photosynthesis is 25∘ –35∘ C, with 30∘ C as optimum. Aroids, in general, have relatively high water requirements, with taro being particularly demanding. High rainfall is required during the first 20 weeks after planting (WAP), corresponding to maximum leaf development (Lebot, 2009). Taro is susceptible to cyclone damage, particularly when there is associated flooding. A mature corm growing in standing water for a few days will rot. Six months after Cyclone Val (1992) struck Samoa in the Pacific a severe outbreak of taro caterpillar or armyworm (Spodoptera litura) occurred; disruption to the ecological balance by Cyclone Val is also likely to have contributed to the rapid spread of taro leaf blight (TLB) caused by Phytophthora colocasiae (McGregor et al., 2011). TLB is a disease of major importance for taro crops in many regions of the world. Serious outbreaks of TLB in Samoa in 1993 (Chan et al., 1998), the Caribbean in 2004 (Rao et al., 2010), Cameroon (Mbong et al., 2013), Ghana (Omane et al., 2012), and Nigeria (Bandyopadhyay et al., 2011) demonstrated the devastating impact of this disease on the food security of small farmers / rural communities dependent on taro. Chemical and cultural control is largely ineffective and breeding for disease resistance is the most sustainable approach to manage the disease (Singh et al., 2012). Climate change poses a challenge to the control and severity of this disease as favourable temperatures and regular periods of leaf wetness, particularly in the humid tropics promote TLB epidemics by favouring pathogen dispersal, infection, and disease development (Thankappan, 1985; Trujillo, 1965; Putter, 1976). Further, in Papua New Guinea (PNG), TLB is less severe a few hundred meters above sea level and is rarely found above the altitude of 1300 m (Bourke, 2010), suggesting sensitivity of the oomycete to a small rise in minimum (night) temperature. 15.2.3.2

Cocoyam

Cocoyam can be cultivated across a wide temperature range, 13∘ –29∘ C. In Puerto Rico, 24∘ C is suggested as the mean annual temperature for successful cultivation. Optimum rainfall is given as 1500–3000 mm per year with an absolute minimum of 1000 mm and an absolute maximum of 5000 mm (Manner, 2011b). Cocoyam is less susceptible to high winds than taro; the cormels will remain edible for up to four weeks after harvesting. The crop can be harvested after 6 to12 months, or left standing in the ground for up to 20 months. Cocoyam is more tolerant to drought than other aroids, and is also more resistant to pests and diseases. Taro beetles do not dig into the soil to reach the cormels (Lebot, 2009).

15.2 Optimum Growing Conditions for Root and Tuber Crops

Cocoyam root rot disease (CRRD) is the most important disease of cocoyam in West and Central Africa (WCA), favored by high rainfall, high relative humidity and high soil water content. Molecular characterization has identified Pythium myriotylum as the causal agent of CRRD in Cameroon (Onyeka, 2014). Recently CRRD has spread to the savannah ecological zones of Nigeria. It is not yet clear whether this is due to increased virulence of the pathogen, or poor cultural practices of the farmers (Onyeka, 2014). In WCA, both CRRD in cocoyam and TLB in taro are negatively impacting the productivity of these important food crops. These diseases are also of importance in East Africa – 45% of cocoyam farmers interviewed in the East African countries of Tanzania, Uganda and Kenya identified diseases as one of their main constraints (Talwana et al., 2009). 15.2.3.3

Giant Taro

15.2.3.4

Swamp Taro

Optimum temperature range for giant taro is stated as 23∘ –31∘ C, most likely as for taro, with 30∘ C being the optimum temperature. The lower limit for mean annual rainfall is 1500 mm with 5000 mm as the upper limit, although it is not tolerant of water logging (Manner, 2011a). In PNG, giant taro is grown successfully across locations with rainfall of 2000–4000 mm per year. Giant taro is susceptible to cyclone damage, the plants collapse, but the corms will support new vegetative growth. Giant taro can be quite tolerant of extended periods of drought. A reduction in leaf area occurs but the plant will resume growth when rainfall resumes (McGregor et al., 2016). Swamp taro can be cultivated between 23∘ –31∘ C, although temperatures of 38∘ C (the maximum temperature of the hottest month) have been recorded. For rainfall, a mean annual range is not really applicable; a continuous water supply is required either from rain or other sources to maintain the marshy, swampy land preferred by swamp taro (Manner, 2011c). Swamp taro can survive a cyclone with limited wind damage but is susceptible to saltwater intrusion. Swamp taro pits are usually in low lying atoll locations and therefore highly vulnerable to sea-level rise and extreme high tides. Drought will also exacerbate the impact from salinity. Rao (2010), in Tuvalu, indicated that some varieties of swamp taro were less susceptible to salinity than others, but as pointed out by Webb (2007) the response of swamp taro to salinity is very complex. 15.2.4

Yams

Warm temperatures promote vegetative growth in yams, but a marked reduction in mean temperature, which usually occurs in the cool season, is required to promote tuber bulking. Yams are tolerant of dry conditions hence planting usually occurs during the dry season. However, well-distributed rainfall of around 1500 mm during the total growth cycle (approximately 8–10 months) is required to achieve optimum yields. Anthracnose (Colletotrichum gloeosporioides) is the major disease impacting the growth of Dioscorea alata, the greater yam, the most widely distributed yam species worldwide. Serious outbreaks of anthracnose, especially during the warm wet season can suddenly destroy the aerial parts of the plant and reduce yields up to 80%. The disease can be spread with planting material as the oomycete is tuber borne but major weeds are also natural hosts. Therefore, good crop maintenance is a required for disease

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control. Resistant varieties exist and conventional breeding can produce interesting hybrids (Lebot, 2009). Cultivated yams are trained to grow over trellises and supports and thus are highly susceptible to strong winds. Tubers will quickly rot if broken or damaged prior to maturity. Loss of planting material is the major impact with a gap of two to three years needed to get back into full production, although the good storability of yams does help to minimise this impact. Wild yams, in contrast, are resistant to cyclones, with their strong fibrous vines using the forest canopy for support. Wild yams, unlike their domesticated cousins, if left un-harvested will regenerate and thus provide a food bank at the time of disasters (McGregor et al., 2016).

15.3 Projected Response of Root and Tuber Crops to Climate Change 15.3.1

Sweet Potato

Based on an understanding of the crop’s cultivation requirements and expert opinion, McGregor et al. (2016) projected that beyond 2050, the food security implications under all emission scenarios except RCP2.61 could be serious. Extreme heat events above 34∘ C would be expected to have impact in countries where temperatures for sweet potato production are currently around 32∘ C. Impact would depend on the timing and duration of the event, as well as soil moisture levels. Depending on whether temperature increases favour or disadvantage virus vectors, yields could be negatively affected. Susceptibility of sweet potato to high temperatures at night and climate-induced water stress suggests that the crop might be negatively impacted in the future in East Africa (Adhikari et al., 2015). Increase in mean annual rainfall might cause some reductions in sweet potato tuber yield, particularly on heavy clay soils. Excessively high soil moisture, however, particularly during initiation (6–10 weeks after planting) reduces tuber yield and has been a major cause of food shortages in the PNG highlands (Bourke, 1988). In countries where rainfall is already very high, growers are likely to find it difficult to counter a significant rainfall increase. A wetter climate could also increase problems with sweet potato scab (Elsinoe batatas) (McGregor et al., 2016). 15.3.2

Cassava

Cassava is often described as the crop ‘suited’ for a future with elevated CO2 (eCO2 ), increased temperature and variable rainfall patterns. Evidence suggests that tuber crops are more stimulated by eCO2 than grain crops (Miglietta et al., 1998). A field study of cassava showed roughly a doubling of dry mass for a CO2 increase from 385 to 585 μL L−1 (Rosenthal et al., 2012). Cassava shows better yield gain than grain crops at higher 1 RCPs are concentration pathways used in the IPCC AR5. They are prescribed pathways for greenhouse gas and aerosol concentrations, together with land use change, that are consistent with a set of broad climate outcomes used by the climate modelling community. They include one mitigation scenario leading to a very low forcing level (RCP2.6), two medium stabilisation scenarios (RCP4.5 and RCP6) and one very high baseline emission scenario (RCP8.5) http://sedac.ipcc-data.org/ddc/ar5_scenario_process/RCPs.html.

15.3 Projected Response of Root and Tuber Crops to Climate Change

CO2 concentrations, can recover from very long drought periods, and exhibits increases in optimum growth temperature under eCO2 levels (Rosenthal and Ort, 2012). Increases in average temperature, even up to 2∘ C and beyond, are not expected to have a significant impact on cassava production, given its wide temperature range. Extreme heat days would also be expected to have little impact, but as with all crops the ability to manage heat stress will be influenced by precipitation (McGregor et al., 2016). With the likelihood that cassava cultivation will continue to expand because of its resilience to environmental change, studies are needed on the parameters that affect the growth, nutrition and cyanogenesis of cassava, and importantly the influence of the interactions between these factors (Burns et al., 2010). Even with cassava varieties that are low in cyanogen content, such as those found in the Pacific Islands, there is the possibility that a combination of drought and eCO2 could raise linamarin (the predominant cyanoglycide) levels significantly. An unpublished study by Bain (2010) indicated that the high cyanogen levels were connected to a redistribution of metabolites within the plant rather than an actual increase in cyanogens. Recent studies conducted by Gleadow et al. (2013) at Monash University, Australia, suggest that the concentration of linamarin in cassava tubers does increase with eCO2 . Increases in levels are found in both the leaves and the tubers, but the effect is more pronounced in the leaves (Steven Crimp pers. comm.). 15.3.2.1

Edible Aroids

Modelling studies suggest that projected changes in mean climate conditions will have little effect on the yield of taro and other edible aroids production in general, with the exception of extremely low rainfall; taro generally prefers a wet, humid environment and most varieties do not tolerate drought therefore low rainfall would negatively impact production (Wairiu et al., 2012). The vulnerability of susceptible taro varieties to taro leaf blight disease will be increased if higher levels of humidity are associated with higher night temperatures. Increased rainfall would also favour the spread of Pythium (which would affect both taro and cocoyam) and probably taro armyworm or caterpillar (McGregor et al., 2016). Cocoyam and giant taro are more tolerant of drought than taro; farmers in the Pacific Island countries are planting more cocoyam in response to drought conditions (McGregor et al., 2016). However, preliminary results of screening of local (Macaronesian taro gene pool) and elite taro cultivars (Pacific genepool) has shown significant differences in the ability to cope with drought stress among elite and local varieties (Ganança et al., 2015). Some upland South African taro landraces have also demonstrated drought tolerance and adaptation to low levels of water use (Mabhaudhi et al., 2013; Mabhaudhi et al., 2014). In the long term, as 30∘ C is the optimum temperature for taro, temperature increases of 2∘ C and beyond could impact on production, and similarly with the other edible aroids, possibly with the exception of swamp taro (McGregor et al., 2016). 15.3.2.2

Yam

Yams require a marked reduction in mean temperature for tuber bulking, therefore the projected temperature increases in the long term and extreme heat events, depending on timing and duration could be significant (Lebot, 2009). Data from the south-eastern rainforest zone of Nigeria, indicated that yam production would become increasingly

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difficult if the trends of decreasing rainfall and relative humidity and increasing temperature and sunshine hours evident over the past 30 years (1978– 2007) continued (Nwajiuba and Onyeneke, 2010). Overall, it could be expected that a wetter environment would favour yam production compared with other root crops. However, based on experience of yam production in wetter climates in Pacific Island countries, higher rainfall will increase the incidence and intensity of anthracnose disease (caused by the fungus Colletotrichum gloeosporioides) on D. alata. Increasing rain intensity and waterlogging can also lead to rot and potentially death of the plant (Lopez-Montes, 2012).

15.4 Climate Change and Potato Production Night temperatures of over 25∘ C, traditionally, affect the growth of potatoes. With projections of global rises in temperatures of 1.1∘ to 6.4∘ C over the next 50 years, current areas of potato production could no longer support growth of the crop. High temperatures have been shown to slow tuber growth and reproduction, increase physiological damage to tubers and shorten tuber dormancy, which makes the tubers sprout too early2 . Hijmans (2003) predicted, based on the climate change projections at the time, that at high latitudes, global warming will likely lead to changes in the time of planting, the use of later-maturing cultivars, and a shift of the location of potato production. In many of these regions, changes in potato yield are likely to be relatively small, and sometimes positive. In contrast, shifting planting time or location is less feasible at lower latitudes, and in these regions global warming could have a strong negative effect on potato production. Heat tolerant cultivars are the option for such environments. The effects of global warming on potato production have been predicted to decrease global yields by 10%–19% in 2010–39, and by 18%–32% in the 2050s, when actually more production is needed to feed the world’s growing population.3 Jarvis et al. (2012), using 20 Growth Crop Models (GCM) under the A1B storyline, projected about 15% reduction in potato yield in Africa by 2030. Similarly, Tatsumi et al. (2011), with five GCM models projected a 17% decline in potato yield in eastern Africa from the 1990s to the 2090s. As a consequence of climate change, potato yield in most of East African countries (except Rwanda) will decrease due to heat and water stress (Adhikari et al., 2015). Potato is currently grown with constant irrigation. Climate projections for precipitation stress variability and increased severity of extreme events could pose a challenge for potato production but at the same time, potato requires far less water to grow than the world’s other major crops – wheat, maize, and rice. If grown with care, the potato can grow with very little water, or in an abundance of water4 . Because of its high water use efficiency, potato is being considered as a substitute for the less water efficient cereal crops. The International Potato Center (CIP) is working to develop potatoes that offer late blight resistance, increased water efficiency, with high bio-availability of iron and zinc, which also meet consumer preferences5 . 2 http://cipotato.org/press-room/blogs/potato-faces-up-to-climate-change-challenges/ 3 http://www.hutton.ac.uk/news/heat-stress-study-could-protect-potato-yields 4 http://cipotato.org/press-room/blogs/potato-faces-up-to-climate-change-challenges/ 5 http://cipotato.org/research/potato-in-temperate-areas/development-of-high-yielding-diseaseresistant-and-drought-and-heat-tolerant-varieties-for-long-day-conditions/

15.5 Sustainable Production Approaches

Potato late blight (caused by the oomycete Phytophthora infestans) is generally recognized as the most important potato disease. In more humid mountainous areas, late blight disease is leading to reduced yields and profitability. Late blight resistance is frequently not present in popular varieties (Forbes, 2012), so disease management is often dependent on pesticides, which can be too costly for resource-poor farmers (Kromann et al., 2009; Blandon-Diaz et al., 2011) and can affect non-target species (Cheatham et al., 2009). Sparks et al (2014) examined the global effect of climate change on potato late blight using a meta-model and three GCMs for the A2 GHG emission scenario for three time-slices (2000–2019; 2040–2059; 2080–2099). Five regions, where potato is an important crop, were evaluated and the authors found that the average global risk of potato late blight increases initially, when compared with historic climate data, and then declines as planting dates shift to cooler seasons. However, the limitations of the analysis were recognized, such as the predicted effects of climate change are not equal across geographic locations, the potential effect of weather extremes and weather variability, and the increasing strength of the inoculum during the growing season. With this in mind, the authors stressed the importance of agronomic practices to manage the disease.

15.5 Sustainable Production Approaches Climate change impact on crop production will be determined by the extent of climate change, the responses of the crops themselves (physiological thresholds) and the physical environment in which the crops are grown. The nature of this physical environment is affected by how the crop and soil conditions are managed by farmers. Pretty (2008) described systems high in sustainability as ‘those that aim to make the best use of environmental goods and services, while not damaging those assets’ and highlighted that agricultural sustainability does not mean a net reduction in input use, rather an intensification of resources so that there is better use of existing resources, such as land, water, biodiversity and technologies. A recent review of the vulnerability of Pacific agriculture and forestry to climate change highlighted the relative resilience of the staple food crops, such as the root and tuber crops, compared to some global staples such as wheat and rice (McGregor et al., 2016). But the review emphasized the need to improve production systems to make them more resilient, recommending a focus on the aspects of traditional farming systems that contribute to sustainability. Three approaches were highlighted – the cultivation of trees and crops, that is, agroforestry systems; crop and tree diversity; and soil fertility management. 15.5.1 15.5.1.1

Agroforestry Systems Combining Tree Crops and Roots and Tubers

Although maximum achievable yields of root and tuber crops may be lower than that achieved in a monocrops situation with high inputs of water and nutrients, the understory crops in an agroforestry (AF) system will receive some protection from drying winds and excessive heat, and their yields may in practice not be much lower, on a per plant basis, than those achieved by most farmers in open fields (McGregor et al., 2016).

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Further, because of the complementary architecture of the plants, the total per hectare return to the farmer is likely to be higher, as in the banana/coffee system from Uganda (van Asten et al., 2011). In Tanzania, a study of agroforestry plots ranging from 0.04 ha to 1.0 ha and covering 103 households engaged in AF and non-AF illustrated the diversity of benefits available to the AF farmers through increased food production and income, increasing the farmer’s resilience during environmental extremes and climate variability (Charles, 2015). As demonstrated for coffee in Mexico, the understory crops experience less water and heat stress (Lin, 2007). 15.5.2

Soil Health Management

Soils that are repeatedly cropped under humid tropical conditions show very low levels of organic matter with correspondingly low levels of nutrient retention, water infiltration and retention and biological activity. Preliminary data from the Pacific Islands indicates that increasing the soil organic matter (SOM) content rapidly restores all dimensions of soil function (McGregor et al., 2016). Improving the SOM content benefits water retention capacity and stabilizes soil aggregation which enhances drought tolerance of the crop (Altieri et al., 2015). Organically rich soils usually contain symbiotic mycorrhizal fungi, such as arbuscular mycorrhizal (AM) fungi. AM fungi improve plant water relations and can thus increase the drought tolerance of host plants (Garg and Chandel, 2010). Conservation agriculture (CA) which comprises minimum soil disturbance, retention of crop residues and crop diversification is promoted as an approach for making farming systems more resilient to climatic changes as well as mitigating climate change through soil carbon sequestration. Meta-analysis of CA impacts on soil carbon (C) in two tropical regions showed that increases in SOM concentration (as opposed to stock) in near-surface soil from CA resulted in improvements in soil physical conditions. Such improvements are expected to contribute to climate change adaptation, though not necessarily leading to consistently increased crop yields (Powlson et al., 2016). Zougmoré et al. (2014) analysed traditional agronomic practices in semi-arid West Africa with a focus on sustainably increasing productivity and resilience and at the same time, reducing GHG emissions. They found that the most successful systems were those that provided water, nutrients and a supportive soil structure in a synergistic manner. Incentive measures to encourage adoption of the techniques were also noted as important. Bryan et al. (2011) examined what agricultural strategies would help smallholder farmers to mitigate and adapt to climate change, strengthen food security and improve livelihoods. Several practices were identified as triple wins in terms of climate adaptation, GHG mitigation, and productivity and profitability, with integrated soil fertility management providing multiple benefits across the agro-ecological zones examined. 15.5.3

Utilizing Diversity

Farmer access to and availability of diversity is crucial in the management of climate change. In the early 1990s cassava was very important for farmers’ income in Thailand but at the same time the crop was gaining a reputation for eroding and degrading soil at higher altitudes. Breeders crossbred the most popular Thailand variety with varieties

15.6 Optimization of Root and Tuber Crops Resilience to Climate Change

collected from Venezuela in 1967 – today Thailand is the world’s largest exporter of the crop, cornering 70% of the dried cassava market and 90% of the cassava starch market6 . To develop improved varieties, plant breeders require a diverse pool of genetic resources. Crop wild relatives (CWR) are widely recognized as one of the most important resources available to plant breeders in the fight against climate change. But many CWR have not been collected and conserved in genebanks, meaning breeders are unable to use them. In addition, many of their habitats are under threat from urbanization, pollution, deforestation, climate change and war. A number of CWR of sweet potato are potentially distributed in regions with low precipitation and high heat; such species could be good candidates for exploration for these traits (Khoury et al., 2015). A recent study found that wild yams are highly contaminated by crop-to-wild gene flows, highlighting the need for collecting CWR of yam to support breeding for climate change resilient traits (Scarcelli et al., 2017). CWR of cassava are also in need of collection and conservation7 . CWR of potato are already widely used in global breeding programs; some CWR are sources of valuable traits offering resistance to frost and late blight. The crop is vulnerable to climate change, with growing areas moving upwards in the Andes, and a potential increase of pests and diseases due to rising temperatures. A gap analysis has identified gaps in genebanks and 32 species were assigned high priority for collecting (Castañeda-Álvarez et al., 2015).

15.6 Optimization of Root and Tuber Crops Resilience to Climate Change Breeding crops to resist biotic and abiotic stresses will be an essential tool in managing climate change impacts. The CGIAR Roots, Tubers and Bananas (RTB)8 programme has been focusing efforts on the latest advances in gene sequencing, metabolite profiling and bioinformatics to better understand the genes and cellular processes responsible for traits such as drought tolerance, nutritional content and resistance to pests and diseases. The primary goal of the programme is to complete genome-wide association studies (GWAS) of the main RTB crops. Undertaking GWAS for RTB crops has only become possible in recent years, since the first genome sequences for potato were completed (Potato Genome Sequencing Consortium, 2011). The cassava genome is currently the focus of a more comprehensive mapping by the Next Generation Cassava Breeding Project (http://www.nextgencassava.org/). Genome sequences for sweet potato and yam have yet to be completed (RTB, 2015). Gene sequencing has been achieved for nearly 6500 RTB crop varieties and metabolic profiling has resulted in the identification of 7000 metabolic features per RTB crop. High quality phenotypic data for heat and drought tolerance were generated for potato and metabolomic analysis resulted in the calibration of 20 metabolites found to increase during drought stress. Field screening of 1973 sweet potato accessions from the CIP 6 https://blogs.scientificamerican.com/guest-blog/crop-diversity-is-key-to-agricultural-climate-adaptation/ 7 http://blog.ciat.cgiar.org/over-70-of-essential-crop-wild-relative-species-in-urgent-need-of-collectionsays-new-research/ 8 Programme researches on bananas, cassava, potato, sweet potato and yam

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genebank in the lowlands of northern Peru identified 146 accessions which performed well under heat-stress conditions with at least 21 of the accessions showing high yields and early bulking under heat-stress conditions. Further, the test site was characterized by poor, sandy soil highlighting the potential of the accessions that performed well to have real potential for production on marginal lands (RTB, 2015). Okogbenin et al. (2012) discuss phenotypic approaches to drought in cassava. CIAT and other breeding programmes in Latin America and the Caribbean, as well as institutes in Africa, such as the National Root Crops Research Institute in Umudike, Nigeria, are screening germplasm for tolerance to extended water shortages, either natural or imposed, and to low-fertility soils. The authors suggest that complementary phenotyping strategies such as metabolite profiling used in combination with conventional cassava drought phenotyping traits will further enhance understanding of drought tolerance in cassava. Yam crop improvement generally seems to be focused on tuber yield, tuber quality, and resistance to yam mosaic virus (YMV) in white yam (Dioscorea rotundata) and yam anthracnose disease (YAD) in water yam (D. alata). To this end, at IITA the whole genome draft sequencing of D. rotundata is under way along with re-sequencing of 10 elite parental lines. This information is being integrated with phenotyping and genotyping data of the breeding collections to assess genetic diversity and identification of marker(s) associated with targeted traits for marker-assisted selection or genomic selection9 . High temperature is one of the most significant uncontrollable factors affecting potato yield. Work at the James Hutton Institute, UK, is focusing on developing heat-tolerant potato cultivars. Physiological, biochemical and molecular analyses have been combined with a detailed time series of transcript and metabolite profiles in both the leaves and tubers. This analysis has led to insights into the thermal signalling pathway that suppresses tuber formation10 . The crops – potato, cassava, sweet potato and yams are well supported through the CGIAR system, both by the Centres themselves and also through the RTB programme. The situation regarding edible aroids is not so favourable. Fortunately, the International Network for Edible Aroids (INEA)11 , an EU funded five-year programme, is focusing on the two major edible aroids – taro and cocoyam. The overall objective of the breeding programme is to develop TLB-tolerant varieties with drought resistance and good quality corms and then to facilitate exchange to assist farmers in climate change adaptation. The aim is for all country partners to exchange true taro seed (TTS) in order to initiate an international convergent-divergent breeding scheme (exchange of TTS and recurrent selection), introduce allelic diversity and strengthen the position of taro towards forthcoming climate change. Easy to use and 9 http://www.iita.org/c/document_library/get_file?p_l_id=45268&folderId=7172121&name=DLFE-8904 .pdf 10 http://www.hutton.ac.uk/news/heat-stress-study-could-protect-potato-yields 11 INEA brings together scientists and farmers into a global network to exchange germplasm and relevant information under the auspices of international treaties. The countries involved are: Burkina Faso, CARDI, Costa Rica, Cuba, Ghana, India, Indonesia, Kenya, Madagascar, Nicaragua, Nigeria, the Philippines, Papua New Guinea, Samoa, South Africa and Vanuatu. INEA is also supported by four European institutes (in France, Germany, Portugal and Slovenia) which will backstop the work, together with Bioversity International. INEA is led by the Secretariat of the Pacific Community (SPC), Fiji, and the Centre de Cooporation Internationale enRecherche Agronomique pour le Developpement (CIRAD), France and Vanuatu.

References

reliable production protocols for TTS are available for taro, the greater yam (D. alata), cassava and sweet potato. Within the INEA programme, Cuba and Vanuatu are working on aroids, other than taro, in particular, cocoyam – selections are being evaluated for a wide range of characteristics and traits including drought, water logging and root rot disease (INEA, 2014).

15.7 Conclusion The nature of climate change and the lack of data that exist regarding its impact, for example, on pests and diseases, and the time lag from research to widespread application, mean that action will need to be linked with new knowledge, with implementation regularly reviewed on the basis of emerging research and consensus. Hence, the importance of recognizing and addressing the problems that exist with current production systems, such as declining soil health and fertility, lack of diversity, etc., and ensuring that any new initiatives are developed around sustainable, climate-smart practices. The approach has to be learning by doing, putting in place ‘no/low regrets’ actions that will reduce risks now and promote future adaptation. At the same time, the need to ‘produce’ crops ready for change has to be addressed and achieving this for vegetatively propagated crops is not easy. For crops other than the edible aroids, which do have the support of the CGIAR system, progress in genomics will continue to reap the benefits but it should not be the only approach. New adapted varieties must be available to smallholder farmers to strengthen their adaptation to forthcoming challenges. True seeds from genetically diverse parents, rather than clones selected within a narrow range of agro-ecological conditions, provides an approach that can achieve this aim.

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Spence, J.A. and Humphries, E.C. (1972) Effect of moisture supply, root temperature, and growth regulators on photo-synthesis of isolated rooted leaves of sweet potato. Annals of Botany, 36: 115–121. Talwana, H.A.L., Serem, A.K., Ndabikunze, B.K. et al. (2009) Production status and prospects of cocoyam (Colocasia esculenta (L.)) in East Africa. Journal of Root Crops, 35(1): 98–107. Tatsumi, K., Yamashiki, Y., da Silva, R.V. et al. (2011) Estimation of potential changes in cereals production under climate change scenarios. Hydrol. Process., Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/hyp.8012.https://www .researchgate.net/profile/Roberto_Silva24/publication/230249789_Estimation_of_ potential_changes_in_cereals_production_under_climate_change_scenarios/links/ 540a03ae0cf2df04e7491f57.pdf. Taylor, M., Lal, P., Atumurirava, F. et al. (2016) Agriculture and climate change: An overview. In: Vulnerability of Pacific Agriculture and Forestry to Climate Change (ed. M. Taylor, A. McGregor, and B. Dawson). Noumea: Secretariat of the Pacific Community. Thankappan, M. (1985) Leaf blight of taro–a review. J. Root Crop., 11: 1–8. Thornton, P.K. and Herrero, M. (2014) Climate change adaptation in mixed crop–livestock systems in developing countries. Global Food Security, 3(2): 99–107. Trujillo, E.E. (1965) Effects of humidity and temperature on zoosporangia production and germination of Phytophthora colocasiae. Phytopathology, 55(2): 126. Van Asten, P.J.A., Wairegi, L.W.I., Mukasa, D., and Uringi, N.O. (2011) Agronomic and economic benefits of coffee–banana intercropping in Uganda’s smallholder farming systems. Agricultural Systems, 104(4): 326–334. Vandergeer, R., Miller, R.E., Bain, M. et al. (2013) Drought adversely affects tuber development and nutritional quality of the staple crop cassava (Manihot esculenta Crantz). Functional Plant Biology, 40: 195–200. vanKien, N., Hoanh, M.T., and Hue, N.T. (2013) Using salt-tolerant sweet potato varieties in Than Hoa Province. Vietnam Discussion Paper Series – Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), (2013–3) Los Bãnos. Wairiu, M., Lal, M., and Iese, V. (2012) Climate Change Implications for Crop Production in Pacific Islands Region. In: Agricultural and Biological Sciences "Food Production – Approaches, Challenges and Tasks" (ed. A. Aladjadjiyan). ISBN: 978-953-307-887-8, http://www.intechopen.com/books/food-production-approacheschallenges-and-tasks/climate-change-implications-for-crop-production-in-pacificislands-region. Webb, A. (2007) Tuvalu Technical Report: Assessment of salinity of groundwater in swamp taro (Cyrtospermachamissonis) ‘pulaka’ pits in Tuvalu. EU-EDF8-SOPAC Project Report 75. Zougmoré, R., Jalloh, A., and Tioro, A. (2014) Climate-smart soil water and nutrient management options in semiarid West Africa: a review of evidence and analysis of stone bunds and zaï techniques. Agriculture & Food Security, 3(1): 16.

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16 The Roles of Biotechnology in Agriculture to Sustain Food Security under Climate Change Rebecca Ford, Yasir Mehmood, Usana Nantawan, and Chutchamas Kanchana-Udomkan Environmental Futures Research Centre, Griffith University, Nathan, Queensland, Australia

16.1 Introduction The production of crop-derived food is intricately linked to environmental conditions, particularly those conducive to optimal crop yield and quality. Climate change directly threatens all basic environmental requirements for crop food production (i.e. water, temperature and nutrient availability), with even greater risk from more frequent predicted occurrences of extreme weather events (i.e. floods, dust storms, cyclones and fires; IPCC 2013). Climate change poses major challenges to the future productivity of both temperate and tropical agricultural crops. Steadily rising temperatures have already been witnessed and are further expected in most global climate zones (IPCC, 2007). Surface temperatures have been forecast by many climate models to increase 1 to 2o C by 2050, and by 2 to 7∘ C by 2100 (IPCC, 2007; IPCC, 2013; Smith et al., 2007; Lean and Rind, 2009). The current rate of climate change is unlikely to provide sufficient evolutionary time for natural adaptation of many food crop species and/or the relocation of production systems to cooler, wetter or more predictable climes (Lloyd and Farquhar, 2008). However, our awareness of the fragility of our food systems to weather extremes and climatic fluctuations is growing rapidly. Addressing food security under climate change includes evolving scientific and technical understanding to enable eco-friendly solutions with climate-proofing of crops. As such, we are reaching to new scientific knowledge and innovation through a myriad of biotechnology approaches for future food security. This chapter reviews significant biotechnology advances towards improving the resilience of food production systems to major climate impacts. We will discuss specific examples of the gains already made or yet to be proven under climates more extreme than those in which crops were domesticated within the last 12000 years. We will highlight examples in both temperate and tropical crops where biotechnology enables a step-change in food production and availability under changed climates.

Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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16.2 Reduced Water Availability and Drought Climate change in many semi-arid and arid temperate regions of the world is altering patterns, frequencies and volumes of rainfall. Together, with warmer and longer lasting changes in average air and soil temperatures, this has led to increased frequencies and prolonged periods of drought, which in agricultural terms “is any situation when the amount of water available to the plant is less than what is required to sustain maximum growth and productivity” Deikman et al. (2012). By 2025, close to 2 billion people are expected to have absolute water shortage with 65% of the population living in water-stressed environments (Nezhadahmadi et al., 2013). Drought has caused particularly serious and long-term damages to food supply in regions with fragile soil structures that have poor water-holding capacities and little tolerance for reduced precipitation. The FAO estimates that US$4.9b was lost in crop and livestock production between 2003 and 2013 due to droughts in the Horn of Africa, equivalent to 20% of all production losses in Sub-Saharan Africa during that period (FAO 2015). Severe drought is estimated to directly cause an annual reduction of 3–36% of the average value of rice production in Asia (Pandey and Bhandari, 2007). Drought and water stress are known to induce a period of growth cessation and changes in endogenous hormonal levels which influence flowering time in tropical crops such as mango (Sthapit et al., 2012). Ramirez et al. (2011) have predicted a decrease in banana/plantain production in most global growing regions towards the end of the 21st century due to a combination of high temperature and drought impacts on flowering and fruit development. As a consequence, much research has been conducted towards drought-proofing the most vital staple food crops in the highest risk regions. Much effort has been made in the conventional selection and breeding of varieties with drought tolerance, however, progress is limited by the substantial time and cost involved in breeding based on solely phenotypic assessment and recurrent selection. Improved selection with the applications of marker-assisted selection, and genetic modification via introgression of proposed candidate genes, have been applied with excellent results. The identification of the key functional drought tolerance genes is complicated by co-expression of many quantitatively expressed genes operating in concerted and/or independent manners under differing environmental conditions. Hence the heritability of the contributing genetic factors has generally been found to be low (Blum 2011). However, detection of genes that are expressed during water stress is crucial to uncovering those underpinning the drought tolerance mechanisms. Today, there are a plethora of drought-tolerant varieties of many staple food crops either already being adopted or under adaptation assessment in agricultural regions around the globe.

16.3 Drought-proofing Wheat and Other Cereals Drought tolerance in cereals can be divided into mechanisms that are physiologically or biochemically-derived. Physiological responses include decreased photosynthesis, stomatal closure for reduced transpiration, oxidative stress response and cell wall alterations. Foundation studies have highlighted the importance of physiological changes such as cuticular fortification for reduced permeability and cell membrane stability

16.3 Drought-proofing Wheat and Other Cereals

(Blum and Ebercon, 1981). Whereas, biochemical responses have included reduction in rubisco, reduction in photo chemicals and up regulation of various stress-related metabolites. The expressions of various enzymes, hormones, carbohydrates and amino acids have been investigated as biomarkers for association with drought tolerance (Yang et al., 2010). Determining which responses are most influential in reducing plant harm and hence seed production, is pivotal for a strategic biotechnology approach towards drought tolerance breeding in grain crops. Several promising sources of drought tolerance genes/alleles have been detected in land races and wild relative species (Dodig et al., 2012; Nevo and Chen, 2010). To determine the drought tolerance gene-targets, several methods have been employed and since plants use an array of mechanisms for their response to drought stress, many candidate genes and pathways have been uncovered and investigated. A summary of the initial studies to uncover the genome sequences governing the molecular basis of dehydration tolerance in plants was provided by Ingram and Bartels (1996). These included genes involved in general metabolism, osmotic adjustment, structural adjustment, degradation and repair, toxin removal, maturity and seed development and soluble sugars. Specific studies have been aimed at uncovering genes involved in drought-escape, such as adaptive changes in root architecture via abscisic acid signalling (Xiong et al., 2006) and acceleration to reproductive status, including flowering and seed-set (Neumann, 2008). Due to the large and complex hexaploid nature of the wheat genome of approximately 17 Gbp (Brenchley et al., 2012) and the previously mentioned polygenic nature of the drought trait, genetic gain through traditional breeding approaches has been slow. To dissect drought tolerance traits and their complex related contributing genetic factors, genomic approaches to assess functionally-relevant sequences have been applied. Most recently, a whole genome transcriptomics approach in hexaploid one-week-old wheat seedlings revealed genes differentially transcribed in response to 1 or 6 h of drought stress (Lui et al., 2015). This approach uncovered a large number of differentially expressed sequences (∼2000), including some with large variation among treatments. However, caution must be applied regarding the interpretation of these results for selective breeding purposes since the stress applied was very short and likely instigated a shock rather than an adaptive response. Hence the temporal changes in gene expressions require validation in a field situation and in older plants over a longer period of water holding treatment, to determine their adaptive drought tolerance. Also, differences in tolerance mechanisms among species and source genomes must be expected. Aprile et al. (2009) uncovered vastly differential transcriptomic responses among bread and durum wheats to terminal drought stress, suggesting different genome organizations and presence/absence of the D genome in particular. Genes found up-regulated by drought stress included those involved in ABA, proline, glycine-betaine and sorbitol pathways. Meanwhile, analyses of the transcription factor (TF) families that were differentially transcribed during seedling drought shock treatment (Lui et al., 2015) have revealed an up-regulation of several TFs known to play key roles in drought tolerance pathways (Akhtar et al., 2012). TF families previously assessed for involvement in various drought-tolerance pathways include; AP2/EREBPs (e.g. DRE binding protein/CRT binding factor), basic leucine zippers (e.g. ABA responsive element binding protein/ABRE

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binding factor), CCAAT-binding (e.g. nuclear factor Y) and zinc-finger (e.g. C2 H2 zinc finger protein) families (Zhu, 2002; Shinozaki et al., 2003). Lui et al. (2015) demonstrated that HSF and DREB TFs have complex and overlapping expression control within the pathways for both drought and heat tolerance in wheat, with potential for induction of multiple stress tolerance through strategic manipulation of target sequences. Following the break-through study that showed a massive improvement in drought tolerance from expression of a single dehydration responsive element DREB1A in the model crop Arabidopsis (Kasuga et al., 1999), a multitude of transgenic studies have been performed with candidate drought tolerance-related TFs to identify those with functional promise (Gosala et al. 2009). The transgenic expression of members of various TF families has also resulted in improved drought tolerance in other food crop species (Hu et al., 2006; Nelson et al., 2007; Xiao et al., 2009).

16.4 Drought Tolerance in Temperate Legumes Of the commonly grown temperate legume food crops, chickpea requires more soil moisture for germination than lentil, faba bean or field pea (Siddique, 1999; Siddique et al., 1999). Up to 60% yield losses occur in chickpea and up to 50% yield losses in lentil and field pea occurred due to terminal drought. Faba bean is also considered highly sensitive to drought (McDonald and Paulsen, 1997; Amede et al., 2003). Variation in the reaction to drought is present among chickpea germplasm and tolerance has been detected (Toker et al., 2007). Line ICC4958 has a particularly deep and extensive root system and was identified as a potential donor of drought tolerance (Sarker et al., 2005). Molecular markers have been identified for QTL controlling root traits related to a long fibrous roots system (Gaur et al. 2008). Many chickpea drought-tolerance related genes have been uncovered through differential expression studies. A microarray approach detected more than twofold changes in transcription of 109 genes following drought treatment (Mantri et al., 2007). Subsequently, Jain and Chattopadhyay (2010) uncovered 53 ESTs that were associated with drought tolerance and a further suit of ESTs were identified as differentially transcribed among ICC4958 (tolerant) and ICC1882 (susceptible) in response to drought stress of which >50% were associated with drought. A relative expression study of 10 selected genes through qPCR determined that; 1-aminocyclopropane-1-carboxylate synthase (HO062180), alkaline alpha galactosidase (HO062433), leucine-rich repeat protein (HO062474), MADS box protein (HO062366), protein kinase (HO062281), esterase lipase thioesterase family protein-1(HO062244), yippee family protein (Putative zinc binding protein) (HO062242), esterase lipase thioesterase family protein-2 (HO062386), calcium ion binding (HO062250) and GDP dissociation inhibitor (HO062555), were all significantly associated with the tolerance trait (Deokar et al., 2011). Further evidence for the functionality of candidate tolerance genes is provided by recent mapping of chickpea populations segregating for drought tolerance-related root traits, with identification of nine tolerance QTLs. A “hot spot” on linkage group 4 accounted for 48% of the tolerance trait variation and contained seven SSR markers that will potentially be useful for selective breeding strategies (Varshney et al., 2013). Another physiological trait strongly linked to drought tolerance in chickpea is early flowering which is controlled by a single locus, and genotypes with homozygous

16.5 Drought Tolerance in Tropical Crops

recessive alleles at the flowering locus are able to escape drought (Kumar and Rheenen et al., 2000). Several transcription factor families have been implicated in drought tolerance in legume crop species. In particular, a NAC transcription factor (CarNAC3) was proposed as an important regulator of drought stress in chickpea (Peng 2009, Meng et al. 2009). Peng et al. (2009) suggested that CarNAC5 acts as a transcription activator when chickpea plants are under drought and heat stress. A CarNAC3 homolog was recently transformed into a hybrid poplar plant and the resultant transformant lines performed well in glasshouse trials when under salinity and drought stress, able to maintain normal root and stem growth (Movahedi et al., 2014). The identification of predicated drought tolerance genes and their controllers (including microRNAs; Mantri et al., 2013) is now feasible with the availability of the complete genome sequences for chickpea and many other food legumes (Varshney et al., 2012, 2013), to enable acceleration breeding applications of drought tolerance mechanisms.

16.5 Drought Tolerance in Tropical Crops Severe drought can cause 3–36% in production loss of tropical crops across Asia (Pandey and Bhandari, 2007). Rice, one of the world’s most important crops, is sensitive to decreases in soil water content since they have historically been grown under flood irrigation where the soil matric potential is zero. Ray et al. (2011) reported that genes responsive to drought stress conditions significantly overlap with those expressed during panicle and seed development. Maize (Zea mays) is also very sensitive to water-deficit stress (Boyer and Westgate, 2004), as its pollination and embryo development during and post flowering are greatly affected by soil water supply (Bolaños and Edmeades, 1996; Grant et al. 1989). Anthesis-silking interval (ASI) for successful pollination shows a high correlation with grain yields and is highly heritable under drought stress (Bolaños and Edmeades, 1996). Reviews in drought response were published by Yang et al. (2010), and for particular crops such as rice (Leung, 2008; Todaka et al., 2015) and maize (Bruce et al., 2002). The low heritability of grain yield under stress has been the main argument for screening of component traits in breeding programs (Yang et al., 2010). Bernier et al. (2007) identified a major QTL for grain yield under drought stress in rice. They detected a large QTL, which accounted for 47% of the average yield under stress, or 51% of the genetic variance, defined by two markers spanning 10.2cM on chromosome 12. This QTL accounted for an increase in grain yield, harvest index, and biomass yield under stress. Kumar et al. (2007) also reported a QTL on chromosome 1 that accounted for 32% of the variation in yield under drought stress in rain fed lowland rice. In maize, there have been several reports of QTLs associated with specific phenotypes observed under drought stress in diverse mapping populations (Veldboom and Lee, 1996; Frova et al., 1999; Ribaut et al., 1996, 1997; Tuberosa et al., 2002). Individual drought-associated QTL generally explain less than 10% of phenotypic variance for grain yield, ASI or barrenness under stress (Campos et al., 2004). The development of consensus QTL maps generated from a number of crosses is beginning to reveal regions that are commonly associated with drought (Ribaut et al., 2002), thus reducing the need to map each specific cross. Ho et al. (2002) identified QTLs for grain yield, grain moisture,

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and plant height. Also, BC3 containing an introgression at two QTL loci significantly outperformed non-carrier entries. Gene targets for drought tolerance can be divided into functional genes (abscisic acid (ABA)-dependent signalling pathway) and regulatory genes (ABA-independent regulatory network mediated by dehydration responsive element-binding (DREB)-type transcription factors (Bhatnagar-Mathur et al., 2013; Takoda et al., 2015). The introduction of some stress-inducible genes via gene transfer has significantly improved plant stress tolerance (Shinozaki and Yamaguchi-Shinozaki 2007). The utilisation of transcription factors (TF), such as bZIP, NAC, MYB, MYC, zinc-finger, WRKY and ethylene response factor (ERF), which regulate multiple genes involved in the stress tolerance, may be far more effective than single gene manipulations (Bhatnagar-Mathur et al., 2013). In rice, more than 5000 genes were up-regulated and more than 6000 down-regulated by drought stress (Maruyama et al., 2014). The study demonstrated that different metabolites accumulate under the stress conditions among rice and Arabidopsis. Several studies have been conducted in an effort to uncover the sequences that govern these responses, including much work on determining functionally relevant transcription factors. The rice genome contains at least 139 Ethylene Responsive Factor (ERF) family genes (Nakano et al., 2006) and many have been shown to be inducible by environmental stimuli including drought (Dubouzet et al., 2003; Liu et al., 2007). The AP2 ERF-like transcription factor HARDY (HRD gene), isolated from Arabidopsis improved water use efficiency in rice (Karaba et al., 2007). Subsequently, constitutive expression of the ERF gene AP37 was found to not only enhance drought tolerance at the vegetative stage, but also to increase the grain yield under drought conditions in rice (Oh et al., 2009). Quan et al. (2010) then reported that the ERF member, TSRF1, improved the osmotic and drought tolerance of rice seedlings without growth retardation. Also, transcripts of the rice gene OsDREB2B2 containing anAP2/ERF DNA binding domain accumulated following heat, cold, drought, or high salinity stress treatments. Subsequently, OsDREB2B2 was found to regulate the abiotic stress responses through alternative splicing (Matsukura et al., 2010). Previously, OsDREB1F and OsDREB1G were found to be upregulated by water deficit stress (Chen et al., 2008; Wang et al., 2008). Many drought-responsive genes have been identified through whole-genome expression analyses including NAC (SNAC1) which was upregulated 5.6-fold by drought stress in microarray analysis in rice (Hu et al., 2006). In rice, 140 putative NAC, or NAC-like genes are predicted according to sequence analysis, of which 40 are likely to be responsive to drought and/or salt stresses (Kikuchi et al. 2000; Fang et al., 2008). Several rice NACs such as SNAC1 (Hu et al., 2006), SNAC2 (Hu et al., 2008), OsNAC6 (Nakashima et al., 2007), ONAC045 (Zheng et al., 2009), and soybean GmNACs (Tran et al., 2009) are induced by drought and other abiotic stresses, demonstrating cross-talk among the stress responsive pathways. Over-expression of SNAC1 in transgenic rice improved drought tolerance under field conditions (Hu et al., 2006). Overexpression of another NAC transcription factor (OsNAC6) increased tolerance to dehydration and salinity stress through growth retardation (Nakashima et al., 2007). Tomato plants transformed with interfering RNA (RNAi) at the SlNAC4-gene locus, which functions as a stress-responsive transcription factor, were less tolerant to salt and drought stress in soil than the wild type (Zhu et al., 2014). The transformants had lower

16.6 Rainfall Intensity, Flooding and Water-logging Tolerance

leaf chlorophyll and higher water loss rate. Furthermore, the expressions of multiple other stress-related genes were downregulated in SlNAC4-RNAi plants under both control and salt-stressed conditions, indicating the importance of the SINAC4 locus for regulating many responses to the drought stress.

16.6 Rainfall Intensity, Flooding and Water-logging Tolerance Heavy rains during flower development may affect pollinator activity, causing poor fruit or grain set as well as grain water-marking and fruit blemishing (Ploetz, 2003; Lim and Khoo, 1985). Additionally, unseasonal rains provide an epidemiological advantage for several crop pests and diseases which damage yield and quality. This may occur through increases in crop population and changes in distributions of existing pests, weeds and diseases (Rosenzweig and Liverman, 1992). Warmer conditions and flooding may assist diseases, pests and weeds to invade previously uninhabited regions, and floods may facilitate the spread of water-borne pathogens and weaken plants to increase susceptibility to infection and other abiotic stresses. Increased frequency and higher storm/cyclone intensities will lead directly to foliar and flower injuries, and cause the erosion of soil content and structure. Periods of increased rainfall intensity will lead to flooding and water logging of root systems and crop submergence. The combined extreme water availability stresses of flood and drought were responsible for over USD $3.0b in insurance payouts in the United States in 2011, and > 70% reduction in crop production (Bailey-Serres et al. 2012). Many agricultural regions of the world are affected by flooding with 59.6% of global crop production estimated to be lost on annual average (FAO, 2015). The biological impacts and consequences of flooding on crops are many, dependant on the type of water (fresh, saline, stagnant = ability to transfer light), intensity of water arrival (force of downpour) and length of time of flooding. The impacts include reduction in gaseous diffusion, limiting O2 and CO2 exchange needed for respiration and photosynthesis, with reduced carbohydrate production and nutrition in grain crops (Pedersen et al., 2013). Pucciariello et al. (2014) highlighted the potential for whole crop loss in rice and soybean under flooding scenarios. The biological impacts also include changes in soil ecology that affects rhizobia and subsequent nitrogen and nutrient availability, as well as accumulation of toxic substances in flooded soils such as salinity and toxic sulphide (Lamers et al., 2013; Watanabe et al., 2013). Also, changes in soil pH that causes disassociation of bound ions, may increase the availability of heavy metals, such as Pb and Cd, to uptake by the plant and potential for direct human ingestion (Albering et al., 1999; Bailey-Serres et al., 2012). Physiological and molecular studies have uncovered two major flood survival strategies in crop species. These are 1) adaptive changes that enable plants to survive short periods of deep submergence through general cellular metabolic and growth decreases; and 2) changes that enable plants to survive longer periods of submergence in shallower water through root elongation and the formation of aerenchyma (cortical air spaces) to increase O2 access (Drew et al., 1979). Sachs et al. (1996) identified a set of an aerobically-induced proteins in maize involved in glycolysis including a novel

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xyloglucan endotransglycosylase thought to be involved in aerenchyma formation during flooding (Saab and Sachs 1996). Subsequent gene expression studies on arrowhead (Sagittaria pygmaea Miq.) tubers, a common weed in Japanese rice fields, by Ookawara et al. (2005) concluded that five xyloglucan endotransglycosylase/hydrolase SpXTH genes are differentially regulated in response to anoxia and are involved in anoxic shoot elongation through modification of cell wall architecture. These and other cell wall modifiers are discussed in depth regarding their involvement in flood, drought and other stresses in Sasidharan et al. (2011). Several of the major genes governing water logging tolerance have been identified and studied in various crop species. Initially this was achieved through quantitative trait loci (QTL) mapping, and development of loci-associated markers for selective breeding purposes. This has been achieved for the Rps locus in soybean (Cornelious et al., 2005; Vantoai et al., 2001), the Sub1A locus in rice (Xu et al., 2006), and the Qwt and tfy loci in barley (Li et al., 2008). As genome sequences have become more available genome framework markers (i.e. SNPs) may be strategically applied to produce dense genome maps. A far greater depth of understanding of the complex multi-genic nature of the waterlogging tolerance trait has become apparent in several species. For example, 36 QTL were identified for waterlogging tolerance on 18 chromosomes in wheat using the International Triticeae Mapping Initiative (ITMI) population, which explained from 0.8 to 28.2% of the tolerance trait (Yu and Chen 2013). In maize, five QTL were detected to explain 30% in total of the tolerance trait and another 13 QTL were identified conditioning secondary traits associated with waterlogging tolerance such as brace roots, chlorophyll content and % stem and root lodging, each able to explain from 3 to 14% of the trait. From these, 22 candidate sequences were characterised, several with previously reported function in the tolerance trait. Flanking SNP markers were developed to each QTL and a high-throughput genotyping assay was developed for tropical maize breeding programs (Zaidi et al., 2015). Xu and Mackill (1996) mapped a major QTL, which was designated as SUB1, associated with submergence tolerance on chromosome 9 in rice, accounting for 70% of the phenotypic variance in this population. As mentioned, submergence tolerance is a main flood survival strategy employed by crops. A major breakthrough in the understanding of the genetic control for this trait occurred with the discovery of the Sub1 region found in rice (Oryza sativa) able to withstand 10–14 days of complete submergence. The Sub1A gene was determined to be an ethylene-response-factor (ERF) like gene (Xu et al. 2006). The transcriptional changes associated with the Sub1A-1 ERF transcriptional regulator allele were subsequently uncovered through transcriptional analysis. In total 898 genes and 13 pathways were associated with Sub1A-1-dependant regulation. Of these, there were 16 members of the AP2/ERF transcription factor superfamily significantly implicated, 10 of the ERF and 6 of the DREB subfamily. Homologs of these were previously associated with a range of functions including delayed senescence through anaerobic respiration and ethylene accumulation during submergence mediated by cytokinin, negative feedback regulation of ethylene-responsive genes and inhibition of gibberellin (GA), restricting GA-mediated shoot elongation (Jung et al., 2010). In addition to submergence tolerance, SUB1A also improves survival of rice following de-submergence and during drought (Fukao et al., 2011) making it an ideal candidate for genetic manipulation for improving tolerance to multiple water constraints in rain-fed food production systems. A Sub1A submergence tolerance gene was first transferred into a high yielding cultivar using

16.8 Thermo-tolerance and Heat Shock Proteins in Food Crops

marker-assisted selection (Xu et al. 2006), and in 2013 the International Rice Research Institute (IRRI) estimated that the released Sub1A varieties had reached more than 4 million rice farmers. The ethylene respond factors (ERF) proteins SNORKEL1 and SNORKEL2 (SK1 and SK2) promote GA accumulation and fast stem elongation, known as an escape strategy, in deep-water rice (Hattori et al. 2009).

16.7 Heat Stress And Thermo–tolerance Globally, periods of high temperature stress during the cropping season are predicted to become more frequent with future average temperature rises of up to 2.50 C (IPPC, 2007). In general, high temperatures can affect the components of leaf photosynthesis, reducing vegetative and productive growth. Species that are sensitive to high temperatures and require cool-induced fruit setting are likely to be most affected by predicted climate change, including mangosteen, lychee and longan (Sthapit et al., 2012). Heat stress affects ripening and post-harvest quality (Moretti et al. 2010) with the impact dependant on the combination of heat-intensity, heat duration and the day-night temperature differential. Pollen viability of rice and production declines in response to high temperature stress (Kim et al., 1996; Prasad et al., 2006; Shah et al., 2011). Similar negative impacts have been detected in peanut, sorghum and maize showing low fertility of flowers and the downgrading of product quality (Commuri and Jones, 2001; Prasad et al., 2001; Singh et al., 2015). Several studies have determined the effects of high temperatures on flowering and fruit development of tropical crops such as banana, mango, papaya and passion fruit (Bhriguvanshi, 2010; Ramirez et al., 2011; Sthapit et al., 2012). Air temperatures > 38∘ C and bright sunshine have resulted in sunburn of exposed banana fruit, especially on the top hands of the bunch, directly impacting production (Deuter et al., 2012).

16.8 Thermo-tolerance and Heat Shock Proteins in Food Crops The effects of heat stress are generally of greater consequence on reproductive than vegetative tissues and organs of cereals, particularly on pollen germination at anthesis which leads to decreased seed set (Barnabas et al., 2008). Variation in responsiveness and some thermo-tolerance at these critical developmental stages has recently been detected through germplasm screening in sorghum (Singh et al., 2015). A thorough understanding of the major genetic components and molecular mechanisms that operate in the reproductive tissues to underpin the thermo-tolerance trait is a necessary first step towards effective selective tolerance breeding strategies for stable and improved productivity under elevated temperatures. The genetic components underpinning the thermo-tolerance trait in cereals were initially uncovered through QTL mapping. In maize, six QTL were identified that conveyed tolerance through cellular membrane thermo-stability (Ottaviano et al., 1991). Using the same very small RIL population, a further five QTL for ability of pollen to germinate and six QTL for pollen tube growth at high temperature were identified (Frova, 1996;

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Frova and Sari-Gorla, 1993;). Early protein expression studies in roots of several cereals exposed to heat at 400 C revealed the involvement of several classes of heat shock proteins (HSP) (Necchi et al., 1987). Variation in protein expression levels of different HSP was subsequently associated with acquired thermo-tolerance although specific function was unknown (Krishnan et al., 1989). Further detailed genomics studies have determined the involvement of many heat stress transcription factors (HSTF) that act as regulators for metabolic responses and HSP as molecular chaperones, which bind and stabilize proteins at intermediate stages of folding, assembly, degradation, and translocation across membranes during a heat event (Hong et al., 2009). Using a hexaploid wheat genome array, 6560 probe sequences were differentially transcribed in response to heat treatment. The majority were HSP, heat shock factor (HSF) genes and HSTFs as well as proteins involved in phyto-hormone biosynthesis/signalling, calcium and sugar signal pathways, RNA and other metabolisms (Qin et al., 2008). In another study, 3516 reliable ESTs were differentially expressed in bread wheat (Triticum aestivum) in response to heat shock at 37 and 42∘ C for 2 h. These included HSP and signalling molecules with expression associated with developmental stage and other abiotic stress responses (Chauhan et al., 2011). Additionally, several small (15–30 kDa) heat shock proteins (sHSP), such as HSP70 and HSP 90-100, have been implicated in thermo-tolerance (Gurley, 2000; Ouyang et al., 2009; Yang et al., 2006). Among staple foods, these have been isolated from pea (Lee et al., 1997), rice (Sato and Yokoya, 2008; Chen et al., 2014; Murakami et al., 2004), carrot (Malik et al., 1999) and soybean (Jinn et al., 1995). In particular, HSP70 functions as a molecular chaperone for membrane transport and prevents the aggregation of denatured proteins (Lee and Schöffl, 1996). Higher levels of HSP70 and genes related to metabolism and stress defenses were observed in several tolerant grape genotypes under elevated temperatures (Zhang et al., 2005). HSP100 also operates as a chaperone and functions to re-solubilize other HSPs linked to temperature stress (Gurley, 2000; Glover and Lindquist, 1998). Studies of transgenic Arabidopsis with a mutated hot1 gene for HSP101 have reported that lowering HSP101 increases susceptibility to heat stress (Hong and Vierling, 2000), while over expression of HSP101 enables normal germination and seedling development under high temperatures (Queitsch et al., 2000). Expression of HSPs is generally associated with specific cell structures such as nuclease, cell wall, mitochondria, chloroplasts, ribosomes and endoplasmic reticulum (Barua et al., 2008; Frank et al., 2009; Yang et al., 2006). Many proteomic studies in major crops investigated localization of these HSPs for example mitochondrial sHSPs (28, 23, 22, 20 and 19 kDa) in maize (Korotaeva et al., 2001); mitochondrial HSP68 in tomato (Neumann et al., 1993); mitochondrial HSP70 in rice (Qi et al., 2011) and chloroplast-localized HSP26 in rice (Lee et al., 2000). The genes encoding heat-response protiens have been identified, for example a nuclear-encoded HSP in tomato (has32) encoding a 32 kDa protein (Liu et al., 2006) and Oshsp26 genes encoding sHSP in rice chloroplast (Lee et al., 2000). Functions of HSPs genes in response to heat stress are complex and are still not yet well studied. The finding revealed relationship among HSPs encoding genes, HSFs and HSTFs. In most cases constitutively active HSFs and HSTFs express as transcriptional activators in plants which leads to an increase in amount of HSPs synthesis (Lee and Schöffl, 1996; Banti et al., 2010), hence higher level of thermos-tolerance. In contribution to the development of heat tolerant crops, the transgenic approach

16.8 Thermo-tolerance and Heat Shock Proteins in Food Crops

has been utilized for gene characterization and functional analysis. Over expression of TaHsfC2a and TaHsfA6f was reported as determinants of thermos-protective processes, activating the expression of reporter HSP genes in wheat (TaHSP16.8, TaHSP17, TaHSP17.3, and TaHSP90.1-A1) (Xue et al., 2014; 2015). Expression of SlHsfA3, a heat stress transcription factor from tomato, directly activates expression of SlHsp26.1-P and SlHsp21.5-ER which prevent heat stress damage during Arabidopsis seed germination (Li et al., 2013). Also, genetic engineering for over expression of soybean GmHsf-34 gene can improved the tolerances to drought and heat stresses in transgenic Arabidopsis (Li et al., 2014). Introduction of the carrot sHSP17.7 gene to transgenic potato can enhance thermos-tolerance by affecting cellular membrane stability (Hu et al., 2010). Recent findings on plant adaptation to thermos-tolerance point also to the involvement of other non-HSP mechanisms (Gao et al., 2008; Sakuma et al., 2006; Wu et al., 2009), such as membrane lipids (Horváth, 2012), osmolystes (Diamant et al., 2001; Kishitani et al., 2000) and antioxidants (Mittal et al., 2012; Panchuk et al., 2002). As examples, regulation and functional analysis of maize ZmDREB2A (Qin et al., 2007) and rice OsDREB2B (Matsukura et al., 2010) indicated their roles in mediating the expression of genes responsive to heat stress. A membrane-associated TF, bZIP28, was determined to be involved in heat stress sensing in Arabidopsis (Gao et al., 2008) and rice (Qian et al., 2015). Furthermore, members of the WRKY gene family have been extensively utilized for enhancing high temperature tolerance in transgenic plants, including thein rice (WRKY11; Wu et al., 2009), pepper (WRKY40; Dang et al., 2012) and banana (MusaWRKY71; Shekhawat et al., 2013). Accumulation of saturated fatty acids in membrane lipids has also been shown to promote thermo-tolerance (Horváth, 2012). Murakami et al. (2000) revealed that transgenic plants with silencing of the gene encoding fatty acid desaturase had significantly lower levels of trienoic fatty acids, which resulted in increased thermo-tolerance. Also, the increased content of dienoic fatty acids was reported to co-suppress fatty acid desaturase, consequently leading to improved high temperature tolerance in rice (Sohn and Back, 2007). The genes related to specific metabolic proteins that were identified and utilized for transformation applications included the ω-3 fatty acid desaturase genes; FAD7,FAD8 [localized in chloroplasts] and FAD3 [localized in the endoplasmic reticulum] (Arondel et al., 1992; Iba et al., 1993). Thermo-tolerance may also be enhanced in plants through the deployment of compatible osmolytes to balance intracellular osmotic status and protect protein structures (Gargv et al., 2002; Kishitani et al., 2000). Heat tolerance in transgenic wheat T6 line was improved by inducing the gene encoding betaine aldehyde dehydrogenase from Atriplex hortensis (Wang et al., 2010). Transgenic rice plants that overexpressed spinach choline monooxygenase gene, which catalyzes conversion of betaine aldehyde dehydrogenase to glycinebetaine, had enhanced thermo-tolerance (Shirasawa et al., 2006). Plant adaptation to thermo-tolerance also involves reactive oxygen species (ROS) scavenging, which is activated by ROS-scavenging enzymes such as superoxide dismutase (SOD) and superoxide reductase (SOR). Expression of tomato glutathione peroxidase (LePHGPx), cytosolic peroxidase (cAPX) and peroxidase protein (TtAPX) in tobacco showed increased thermo-tolerance (Chen et al., 2004; Sun et al., 2010; Wang et al., 2006). The over expression of another ROS-scavenging enzyme, monodehydroascorbate reductase (LeMDAR), in transgenic tomato plants also resulted in higher

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thermo-tolerance (Li et al., 2010). Kim et al. (2011) enhanced high temperature stress tolerance in potato by inducing expression of the Arabidopsis 2-cys-peroxiredoxin (At2-Cys Prx) gene.

16.9 Heat Stress Tolerance in Temperate Legumes Optimal growth and productivity temperatures for cool season legume crops range from 10∘ C to 30∘ C. However, a daily maximum temperature above 25∘ C is considered to cause heat stress and with climate change increasing heat stress events during flowering and pod set are predicted to become a major issue for maintaining the productivity of these staple food sources. Tolerant sources have been identified and the genetic components underpinning the tolerance traits have been investigated, particularly in chickpea whereby 167 genotypes were screened against heat stress under field conditions and genetic variation was confirmed by the heat tolerance index and canopy temperature depression (GRDC report 2014). Diversity Array’s Technology (DArT) markers were then used to understand the genetic variation linked to the tolerance and 44 DArT sequences were associated with grain yield and characteristics such as total pod number, filled pod number and seed number under the heat stress conditions (GRDC report 2014). In another approach, association mapping using over 300 chickpea accessions was used determine the genetic components conditioning heat tolerance in chickpea. The phenotypic data was collected over multiple seasons and locations, and the resultant 312 trait-associated markers included 18 SNPs from 5 genes significantly related to productivity traits (Thudi et al., 2014).

16.10 Salinity Stress, Ionic and Osmotic Tolerances The major causes of salinity in our food production agro-geographical zones are from rising water tables in low lying areas, derived from ancient sea water inundation, or from reduced rainfall and subsequent top soil erosion that exposes saline subsoils and leads to dryland desertification. Saline stress environments have high concentrations of soluble salts with electrical conductivity (ECe) of more than 4 dSm–1. Among the soluble salts, NaCl is the major component contributing to salinity. At the physiological level, salinity imposes an osmotic stress that limits water uptake and ion toxicity can cause nutrition (N, Ca, K, P, Fe, Zn) deficiency and oxidative stress (Munns 2002). Plant responses to salinity can vary with the degree and duration of stress imposed as well as plant development stage (seedling, flowering, maturity) when the stress is applied (Munns, 1993). Germination may be delayed or may not be affected at low salinity but be affected above a tolerance threshold. At the seedling stage, germplasm response can be quite variable to salt stress (Ashraf et al., 1994). Therefore, stability in salt tolerance must be sought at all growth stages of a crop species. Salt tolerant plants are generally categorized as either halophytes or glycophytes. Halophytes grow and survive best at high salinity (200–400 mM NaCl), conversely glycophytes cannot survive under high saline conditions and almost all commercial field crops are glycophytes as they are susceptible to salinity greater than 4 dSm-1 (Rengasamy, 2006). The main adaptive strategies of salt-tolerant plants exposed to

16.11 Salinity Tolerance in Rice

salinity are 1) osmotic stress tolerance; 2) avoidance through ion exclusion, potentially as a result of low membrane ion permeability; and 3) tolerance, through ion inclusion and possible compartmentalization, which enables the plant to remain functional despite internal ionic stress (Blumwald et al., 2004; Munns, 2005; Munns and Tester, 2008). Adaptive physiological and biochemical tolerance responses are controlled by interactions of hundreds of salt responsive genes (Sahi et al., 2006). These include processes such as ion homeostasis (membrane proteins involved in ionic transport), osmotic adjustment and water regime regulation (osmolytes), as well as, toxic scavenging of toxic compounds (Blumwaldet et al., 2004). The regulatory molecules, conditioning these responses, have been found to be cellular signal pathway components and transductors of long distance response co-ordination, such as hormones, mediators, transcription factors and regulatory genes (Mishraet et al., 2006). Salt tolerance is attained through three interrelated characteristics; avoidance of salt injury, reestablishment of homeostatic conditions and resumption of growth in the new, stressful environment (Zhu, 2001). Several genes involved in the MAP kinase pathways are known to control osmoregulation, cell growth and differentiation during salinity stress(Mishra et al., 2006; Pitzschke et al., 2009). Many other genes have been identified through expression studies to regulate salt tolerance in sugarcane (Tammisola, 2010), rice (Asano et al., 2012; Zou et al., 2009, 2012), barley (Li et al., 2010) and soybean (Li et al., 2012). Also, salinity-inducible TFs have been identified based on interactions with promoters of osmotic/salt stress–responsive genes, and most are involved in the downstream activation of other stress-inducible genes (Huang et al., 2012; Zou et al., 2012). A very recent example is GmbZIP110 a member of the bZIP TF family found responsive to and regulating salinity stress in soybean (Xu et al., 2016). Several transgenics are under field evaluation including sugarcane that contains OsDREB1A (Tammisola, 2010).

16.11 Salinity Tolerance in Rice Many salt-tolerant rice varieties have been developed worldwide through conventional breeding, molecular-assisted selection and genetic transformation approaches (Shahbaz and Ashraf 2013). Similar to other crops, the response to salt stress in rice is often dependent on the developmental stage and other factors (Flowers, 2004). The major characteristics contributing to salinity tolerance in rice are leaf stomata, leave structure, tilling date and Na+ uptake in shoot and root, and heading date (Ashraf and Harris, 2004; Koyama et al., 2001; Lin et al., 2004; Pride et al., 1997; Yeo et al., 1990). A number of salt-tolerant rice varieties have been developed through conventional and marker-assisted breeding with limitations related to growing region, climatic condition or soil texture. Mishra et al. (2003) identified several lines, CSR 10, CSR 13, CSR 27, Narendra Usar 2, Narendra Usar 3, and basmati CSR 30, able to maintain salt-tolerance in various environmental conditions. Meanwhile, genome mapping studies have identified QTL associated with traits related to salinity tolerance in rice (Lee et al., 2007; Lin et al., 2004; Prasad et al., 2000; Pride et al., 1997; Sabouri et al., 2009; Thomson et al., 2010). Lin et al., 2004 identified eight QTL controlling rice tolerance, of which, three were associated with shoot and five were associated with roots characteristics. Two QTL were identified with large effect, qSNC-7 for shoot

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Na+ concentration and qSKC-1 for shoot K+ concentration. These explained 48.5% and 40.1% of the total phenotypic variance, respectively (Lin et al., 2004). Ghomi et al. (2012) identified 41 QTL for 12 traits related to salinity tolerance at the seedling stage in an F2:4 population of rice derived from a cross between a salt-tolerant variety, Gharib (indica), and a salt-sensitive variety, Sepidroud (indica), These QTL were specific to stage of development (Shahbaz and Ashraf, 2013). Transgenic approaches have been effectively employed for improving the salt tolerance trait in rice. Through the use of high density genetic and physical maps (Goff, 1999; Tao et al., 1994; Umehara et al., 1995), knowledge of gene expression (Jamil et al., 2011) and well-established protocols for genetic engineering, salinity tolerant transformants have been produced (Asona et al., 2012; Verma et al., 2007, Zou et al., 2009, 2012). The types of genes employed have included vascular transporters genes (OsNHX1, SOD2, PgNHX1) to improve shoot and root system and increase accumulation of various ions e.g. Na+ K+ , Ca2+, Mg2+ (Ohta et al., 2002; Fukuda et al., 2004; Zhao et al., 2006 and Verma et al., 2007). The resultant survival rate of rice seedling under salinity stress conditions increased from 50–81% to 100% (Ohta et al., 2002). Other approaches have been to reduce accumulated trehalose (using the genes TSP1 and TPSP) and proline (using the gene P5CS) (Garg et al., 2002; Jang et al., 2003; Su and Wu, 2004) and transformation with the gene OPBP1 from tobacco (Chen and Guo, 2008).

16.12 Salinity Tolerance in Legumes Recently, RNA sequencing was carried out to profile the transcriptome of root and shoot tissues of chickpea seedling subjected to salinity, desiccation and cold stress (Garg et al., 2015). A significant fraction (34%) of the Transcriptome was found to be affected with the expression of the largest proportion of genes affected by salinity (5321) (Garg, 2015). The relative differential expressions of nine candidate salinity-tolerance genes were assessed using quantitative PCR among tolerant and susceptible genotypes. Of these, CapLEA-1 (late embryogenesis abundant), LTP (Nonspecific LTP precursor) H1 and 219 cDNA sequences, Cu/Zn SOD (Cu/Zn superoxide dismutase) and PK (protein kinase) were significantly up regulated only in the tolerant genotype and will be targets for further investigation for use in selective breeding strategies (Arefain and Saeid, 2015). Most recently, whole-genome resequencing of soybean has identified allelic variation and three major structural variants within a GmCHX1 gene previously related to salinity tolerance. Subsequently, KASP assays were designed with the discovery of associated SNPs, markers that have been validated to precisely identify salt tolerant genotypes (Patil et al., 2016).

16.13 Transgenics to Overcome Climate Change Imposed Abiotic Stresses Plant genetic engineering and transformation techniques have been developed across many staple food crops using electroporation of protoplasts, Agrobacterium-mediated

16.13 Transgenics to Overcome Climate Change Imposed Abiotic Stresses

391

Table 16.1 Examples of transgenic staple food crops with tolerances to many of the current and predicted climate change imposed abiotic stresses. Enhanced tolerance

Crop

Transgene

Gene function and change in expression

Wheat

AtNHX1

Encoding vascular Na+ /H+ antiporter gene

Salinity

Xue et al., 2004

P5CS

Encoding Δ1 pyrroline-5- carboxylate synthetase, over-accumulated proline

Salinity

Sawahel and Hassan, 2002

VaP5CS

Encoding Δ1 pyrroline-5- carboxylate synthetase, proline synthesis

Drought

Vendruscolo et al., 2007

mt1D

Encoding mannitol-1-phosphate dehydrogenase, mannitol synthesis

Drought and salinity

Abebe et al., 2003

BADH-1

Encoding glycine-betaine, over-production

Drought, heat and cold

Wang et al., 2010

OsNHX1

Encoding vascular Na+ /H+ antiporter gene

Salinity

Fukuda et al., 2004

SOD2

Encoding vascular Na+ /H+ antiporter gene

Salinity

Zhao et al., 2006

PgNHX1

Encoding vascular Na+ /H+ antiporter gene, well developed shoot and root system

Salinity

Verma et al., 2007

P5CS

Encoding Δ1 pyrroline-5- carboxylate synthetase, over-accumulated proline

Salinity

Su and Wu, 2004

OsHsp17.0 and OsHsp23.7

Over-expression heat shock proteins HSP17.o and HSP23.7

Drought and salt tolerance

Zou et al., 2012

SAMDC

Encoding S-adenosylmethioninedecarboxylase, polyamine synthesis

Drought

Peremarti et al., 2009

OsHSP70 (mitochondrial)

Over-expression HSP70 protein, suppressed Heat programmed cell death

Qi et al., 2011

OsNHX1

Encoding vascular Na+ /H+ antiporter gene

Chen et al., 2007

Rice

Maize

1

Salinity

Reference

P5CS

Encoding Δ pyrroline-5- carboxylate synthetase, proline synthesis

Osmotic stress, De Ronde et al., heat and drought 2004

Chickpea P5CS

Encoding Δ1 pyrroline-5- carboxylate synthetase, proline synthesis

Salinity

Ghanti et al., 2011

Potato

TSP1

Encoding trehalose-6-phosphate synthase 1 gene

Drought

Stiller et al., 2008 and Kondrak et al., 2012

codA

Encoding choline oxidase

Drought

Ahmad et al., 2008 and Cheng et al., 2013

Drought

Shin et al., 2011

Soybean

StMYB1R-1 Over-expression of StMYB1R-1, MYB-like domain transcription factor AtNHX1

Encoding vascular Na+ /H+ antiporter gene

Salinity

Wang et al., 2010

AtP5CS

Encoding Δ1 pyrroline-5- carboxylate synthetase, over-accumulated proline

Salinity

Hmida-Sayaria et al., 2005

StDREB1

Over-expression of StDREB1 transcription factor

Salinity

Bouazi et al., 2013

Oxidative and heat

Kim et al., 2011

At2-cys Prx Encoding 2-cysteine peroxiredoxin

(continued)

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Table 16.1 (Continued)

Crop

Transgene

Tomato SlNAC3

Banana

Gene function and change in expression

Overexpression of NAC family genes

Enhanced tolerance

Reference

Drought and salinity

Al-Abdallat et al., 2015

SlHSP21

Over-expression of sHSP, accumulation of Heat carotenoids

Neta-sharir et al., 2005

SAMDC

Encoding S-adenosyl-l-methionine decarboxylase, polyamine, enhancing antioxidant enzyme activity and CO2 assimilation

Heat

Cheng et al., 2009

MusaDHN-1

Over-expression of dehydrin gene, a broader class of LEA proteins

Drought and salinity

Shekhawat et al., 2011a

Multiple abiotic stress

Shekhawat et al., 2011b

Multiple abiotic

Sreedharan et al., 2012

MusaWRKY71 Encoding WRKY transcription factor protein MusaSAP1

Encoding A20/AN1 zinc finger protein and stress associated proteins

MusaPIP2;6

Over-expression of native aquaporin gene Salinity

Sreedharan et al., 2015

transformation or particle bombardment to develop plants that are able to tolerate the various adverse environmental consequences of climate change. The possibility to predict transgene expression and understand functional genomic impacts in planta remains a challenge to the development of transgenic crops. However, combining transformation with gene silencing and gene knock out will allow researchers to determine exact functional relationships between genotype and stress-tolerance phenotype. Despite their massive advantages for sustained and increased productivity under adverse growing environments, many hurdles remain in the challenge towards public acceptance of transgenic crops. Transformation is often seen as a means to grossly simplify the complex nature of plant breeding and an erratic approach to pump out material claimed to be useful for sustainable agriculture (Simmonds, 1997; Simoens and Van Montagu, 1995). Also, the transformation targets are often limited by the scarcity of useful genes, the lack of understanding of the energetic cost associated with the insertion of certain genes, and of the complex gene interactions. Even greater hurdles exist over sovereignty of sequence and technology ownership, food chain control and the underpinning governmental regulations around risk assessments and release of transformed materials. Despite these hurdles, many examples of functionally validated and potentially useful transgenic and stress-tolerant varieties exist and are awaiting implementation. Some of the diverse sources of genes utilized and the traits improved are listed in Table 16.1.

16.14 Conclusion Following clarification of the underlying physiological mechanisms for tolerances to the current and predicted abiotic stresses that are conferred by climate changes, it is clear

References

that biotechnology approaches offer great potential to provide us with knowledge to develop food sources that are tolerant. Already, the genomic signallers and sequences together with functional key tolerance genes have been uncovered for abiotic tolerances in many staple crops. Several have been transferred into elite varieties and validated for function in the field, representing a massive opportunity for future-proofing our food sources in preparedness (Castiglioni et al., 2008; Oh et al., 2005; Vendruscolo et al., 2007). The uptake of these food sources will be pivotal to our ability to meet the predicted food demands under the constraints of the climates we have scientifically predicted to likely occur.

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17 Application of Biotechnologies in the Conservation and Utilization of Plant Genetic Resources for Food Security Toshiro Shigaki Laboratory of Plant Pathology, University of Tokyo, Tokyo, Japan

17.1 Introduction The elevating level of greenhouse gases in the atmosphere is causing a rapid rise of the atmospheric temperature in every part of the world. Surprisingly, this trend of climate change was confirmed only recently. In fact, in the 1970s, global “cooling” was the main concern even among climate scientists. This view is now confirmed wrong, and focused strategies can be made against global warming, rather than a once anticipated ice age. Still, it is an enormous challenge for the conservation of plant genetic resources and for food security, as the temperature rise is faster than plants can possibly cope with by their innate adaptability. Healthy plant genetic resources are the centrepiece of the very survival of the human race. They provide materials for breeding new varieties that address food security problems. It is argued that modern lifestyle is giving an illusion that technology allows us to live in a completely artificial environment. However, our life is sustained only by consuming plants, and animals that are fed with plants. Preservation of plant genetic resources therefore literally defines our survival, and biotechnology holds the key to address it. Biotechnology requires plant genetic resources as much as plant genetic resources need biotechnology for their preservation. In this sense, they are mutually dependent on each other for their own survival. Advances in biotechnology provide powerful tools for the management of plant genetic resources conserved in situ, ex situ, and in vitro. Biotechnology is becoming critically important as one of the most effective tool in the face of rapid loss of plant genetic resources. The erosion of plant genetic resources is caused by interrelated factors including climate change, urbanization following rapid population increase, and vandalism.

17.2 Climate change Release of greenhouse gases into the atmosphere is constantly raising the temperature world over. Many plants cannot adapt to such a new environment and simply disappear from the surface of the planet. The change in temperature also results in the shifting of pest and disease epidemiology, which has a negative impact on the survival of Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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Figure 17.1 Farmland lost due to the flooding following a La Niña event in Morobe Province, Papua New Guinea.

wild and cultivated plants. Heightened global temperatures may result in more frequent appearance of El Niño and La Niña events. These conditions cause flooding and droughts depending on the geographical regions. Germplasm preserved in farmers’ gardens can be easily lost during such extreme weathers (Figure 17.1). 17.2.1

Population Explosion

According to the United Nations statistics, the world population in 2015 was estimated to be 7.349 billion. This figure is projected to reach 9.7 billion by 2050. Food production must increase to meet the demand by this increasing population. However, rapid climate change may negatively affect agricultural production. Enhanced food production can be achieved by developing enhanced varieties of crops using breeding technologies. The parent varieties of the breeding populations must come from germplasm collections with useful genetic traits. Biotechnology can help identify and transfer these traits to the new varieties. 17.2.2

Vandalism

Vandalism has been a major cause of the loss of genetic collections in politically unstable countries. For example, in 2002, Taliban fighters looted the national seed bank in Abu Ghraib in Afghanistan (Nature Editorial, 2005). Sadly, they took only the empty plastic bottles that contained the seeds and discarded the contents. Fortunately, in this case, International Center for Agricultural Research in the Dry Areas (ICARDA) in Aleppo, Syria managed to receive a copy of the seeds from Afghan scientists. Ironically, as of this writing, Syria itself is in crisis and ICARDA has been operating from Beirut, Lebanon since 2012. With unpredictable weather becoming common, and crop failures increasing, such vandalism may become more commonplace.

17.4 Conservation

Biotechnology provides remedies to these risks by accelerating the development of enhanced varieties, safeguarding the germplasm for breeding, and, making long term storage of germplasm possible. This chapter discusses the contributions of biotechnology to the preservation, exchange, and utilization of plant genetic resources and suggests future directions to be made. Biotechnology refers to any technological tools applied to biological systems. Although our focus is on the modern applications of molecular biology and tissue culture technologies, related topics such as international treaties surrounding germplasm exchange will also be discussed.

17.3 Collecting Germplasm Germplasm is collected from the populations in natural habitats or in the agricultural fields. The form of germplasm can be seeds, or vegetative propagules. However, this is not easy when the seeds are large and difficult to transport, or the seeds remain viable only for a short time. An example for the former case is coconut (Cocos nucifera). Due to the large size of the seed, small pea size embryos can be collected instead in the field and transported in sterile conditions to the tissue culture laboratory. The embryos can then be germinated in vitro in a specialized medium (Assy-Bah et al., 1989; Ashburner et al., 1996). Sago palm (Metroxylon spp.) is an example of the latter case. Sago is an efficient producer of starch and a staple food in some regions such as Sepic and the Gulf Provinces in Papua New Guinea. In Bougainville Island, Papua New Guinea, sago fronds are an important material for the thatching of houses. However, the sago stands are in decline and preservation of sago germplasm is urgently required. The sago seeds lose their viability rapidly when stored, and do not tolerate dry conditions (McClatchey et al., 2006). The in vitro technique developed for coconut may be adapted to sago palm to allow efficient preservation.

17.4 Conservation 17.4.1

In situ Collection

Preserving plant germplasm in the locations where they are cultivated or naturally grow is the best and most inexpensive way for germplasm conservation. However, without monitoring, and in the case of cultivated crops, without the understanding and cooperation from farmers, the germplasm preserved this way is quickly lost. There are a number of reasons for this. First, climate change is negatively affecting the health of the natural habitat of the plants. Second, population growth and resultant urbanization is destroying the habitat of the plants. Besides, cultivated varieties and landraces may be given up by farmers for more profitable varieties. The role of biotechnology may seem limited. However, biotechnology can help identify key varieties and species that represent the genetic diversity. Simultaneously, important germplasm preserved in situ can be transferred to ex situ or in vitro collections for safekeeping.

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17.4.2

Ex situ Collection

Whether it is an ex situ or an in vitro collection, maintaining a germplasm collection is a costly exercise (Figure 17.2). Ideally, a germplasm collection should represent the diversity of the population from which the samples are collected. Unnecessary duplication of samples must be avoided to reduce the size of the collection for cost efficient maintenance. This “core collection” is easier to manage than the larger but highly redundant collections. Traditionally, this has been done using morphological characteristics. However, morphology often misrepresents the true genetic distances among different accessions, because environmental influences often greatly alter the morphology. Since the advent of molecular technologies, various methods have been developed to accurately estimate the evolutionary distances among species or varieties within a species. Such methods include DNA fingerprinting, and more recently, genotyping by sequencing using next generation sequencing machines. These technologies will be described later in this chapter in detail. The phenotypical and the genetic fingerprinting data can be used to reduce the size of the germplasm collections by eliminating identical duplicates or closely related accessions. 17.4.3

Slow Growth in Tissue Culture

In order to store growing germplasm in tissue culture for an extended period of time, the growth can be slowed using (1) low light intensity, (2) low temperature, or (3) reduced carbon sources and/or minerals. The exact conditions must be determined for each species. In general, organized cultures such as shoots are used for slow growth storage

Figure 17.2 Sweet potato conserved ex situ at the Miyakonojo Sweet Potato Germplasm Collection. Such a collection is costly to maintain. Source: National Agricultural Research Center for Kyushu Okinawa Region, Miyazaki, Japan.

17.4 Conservation

Figure 17.3 Germplasm conserved in tissue culture at the Secretariat of the Pacific Communities laboratory in Suva, Fiji. The accessions are donated by and distributed to Pacific and other countries according to the international seed treaty.

(Figure 17.3) since undifferentiated tissues such as callus are vulnerable to somaclonal variation (Rao, 2004). Slow growth protocols have been developed for a wide range of crops. However, the technology is generally used for the conservation of only a small number of species such as temperate tree species, Musa spp., Irish potato, sweet potato, cassava, yam, and Allium spp. (FAO, 1996). 17.4.4

Cryopreservation

Properly desiccated seeds of most non-tropical plants can be stored at low temperature for a long period of time. It is the most convenient way to preserve germplasm adopted in many seed banks (Figure 17.4). However, vegetatively propagated plants, or seeds that cannot withstand cold storage (recalcitrant seeds, for example, those of most tropical trees) must be maintained either in the field or in tissue culture. These collections are subject to loss for natural and human causes. Maintenance of field collection is also labour intensive and therefore expensive. In tissue culture, genetic properties of the plants may change over time due to the mutations that occur during repeated subculturing (somaclonal variation). Currently, only long-term conservation of vegetatively propagated plants is achieved by cryopreservation. In this method, plant material is immersed in liquid nitrogen at -196∘ C, at which temperature all the biochemical functions of the cell are arrested. Unlike tissue culture, it is highly unlikely that any change occurs during the storage, and therefore it is an ideal method of preservation of the species for which alternative mode of storage is either not possible or impractical. The critical factor for the successful cryopreservation is to avoid the formation of intracellular ice crystals. This would cause the irreversible

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Figure 17.4 Seeds stored in cold at National Institute of Agrobiological Sciences, Tsukuba, Japan. Seed retrieval is automated in this facility.

destruction of cell membranes, where cell’s most important biochemical reactions and transportation of ions and biomolecules take place. There are a number of protocols for cryopreservation. The most widely used method is by using a process termed vitrification. In this process, cytosol can be made amorphous, rather than forming crystals upon freezing. The use of vitrification in cryopreservation of plant tissues was first reported in 1989 (Langis et al.; Uragami et al.). In this protocol, plant tissues are treated with a concentrated vitrification solution and then immersed in liquid nitrogen. An example of vitrification solution, termed PVS2 (for “Plant Vitrification Solution 2”) consists of glycerol (30%), ethylene glycol (15%), dimethyl sulphoxide (15%), and sucrose (400 mM) (Sakai et al., 1990). Cryopreservation can be cost effective because it requires minimum maintenance and takes up only a small space for storage. Contamination is also unlikely. However, it does require regular replenishment of liquid nitrogen. This last requirement is often the bottleneck in resource poor countries where the supply of liquid nitrogen is either non-existent or unreliable. The ice crystal formation that prevents preservation of plant tissues in cold storage is also a problem in preservation of foods. As widely known, when fresh foods such as vegetables, meat, or fruits are frozen, the ice crystals in the cells alter the texture, reducing the value of the foods significantly. To address this, a new technology termed CAS (Cells Alive System) was developed by ABI Company in Japan. In CAS, ice crystal formation is minimized by using electromagnetic fields and mechanical vibrations. This technology can be potentially applied to improve cryopreservation of plant genetic resources as well. In the future, as space transportation becomes more common and cost-effective, it may become possible to preserve plant genetic resources in space by natural

17.4 Conservation

cryopreservation. This is considered an extreme version of Svalbard Global Seed Vault, which will be described later in this chapter. For example, locations may exist on the moon that never receive the sun’s light. In such locations, the temperature may remain low enough to be suitable for cryopreservation. The relative inaccessibility of such a location and the freedom from any weather, unlike on the Earth, is also ideal to prevent damage to the germplasm. However, careful cost-benefit analysis must be done, and the effects of and the protection from cosmic radiation must be studied before such programmes can be seriously considered. 17.4.5

Herbarium

Herbariums have been in existence for many centuries and important resources for reference plant specimens. (A herbarium dedicated for cultivated plants is called a hortorium.) Recently, herbariums are recognized as an important source of DNA for phylogenetic studies. A herbarium itself is not a repository of live genetic materials, but it is nonetheless a good practice to preserve all accessions as herbarium specimens. These specimens serve as references when variety identification is necessary. Accessions preserved in situ, ex situ, or in vitro should be deposited in herbarium for this purpose to avoid any future confusion. Most herbariums were established long before the knowledge of DNA, and therefore the collectors were not obliged to employ specimen preparation techniques that preserve the integrity of DNA. For this reason, the DNA in herbarium samples is often partially degraded. Many protocols to isolate DNA of reasonable quality from herbarium specimens have been developed to address this (for example, Costa and Roberts, 2014). 17.4.6

Svalbard Global Seed Vault

In situ, ex situ, and even in vitro conservation are not immune to the loss of plant genetic resources. Climate change and urbanization have been two of the major causes of the loss of germplasm preserved in situ. Natural disasters such as drought, flooding, and pest and disease outbreak can destroy in situ and ex situ germplasm collections preserved in the field. Even in vitro collections are not protected from funding shortage and sabotage. In 2008, a seed bank, with a concept never imagined before, started its operation. This new facility is called Svalbard Global Seed Vault, located on a remote Spitsbergen Island in the Svalbard Archipelago in the Arctic Norway. The storage facility is located 120 metres inside a sandstone mountain under the permafrost cover, with no known tectonic activity. The stored seeds are stably maintained at -18∘ C by power generated from locally mined coal. The beauty of the Arctic location of this seed bank is that even if the power fails, the low temperature is still maintained for at least several weeks before it reaches the natural temperature of the sandstone mountain, -3∘ C. The location is also far from any potential conflict, and vandalism or terrorism is unlikely. The risk of vandalism is high in certain politically unstable areas. In the past, important seed banks have been destroyed, as mentioned earlier. With Svalbard Global Seed Vault, even if a major world war breaks out and most of the human population is wiped out from the surface of the planet, the surviving humans can make use of the seeds for their dietary needs.

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Operated by Global Crop Diversity Trust and Norwegian Government, Svalbard Global Seed Vault is run on a non-profit basis. Existing seed banks can send their duplicate seeds to the Seed Vault for safekeeping. The seeds stored in the Seed Vault remain the property of the donors and there is no fee to end users to deposit seeds. In order to preserve seeds at low temperature, the physiology of seeds must be understood first. There are two types of seeds in terms of cold storability: orthodox and recalcitrant. Orthodox seeds can survive subfreezing temperature and can stay viable for up to hundreds of years, while recalcitrant seeds are intolerant to low temperature. Unfortunately, most tropical seeds are thought to be recalcitrant, although the orthodox/recalcitrant status of many tropical seeds is unknown. Therefore, it will be necessary to assess the cold storability of all such seeds before the seeds are sent to Svalbard. In a strict sense, Svalbard Global Seed Vault is not a biotechnological application, but nonetheless, it is based on a modern concept not imagined in the past. It is a biological technology to extend the shelf life of preserved germplasm.

17.5 Characterization of Germplasm It is critically important to assess the genetic variation of the germplasm for the effective management and utilization of the collection. Before the advent of modern biotechnology, the genetic diversity was recorded by using phenotypic characters, such as leaf shape, flower color, yield, and pest and disease resistance. However, many of such parameters are influenced by external factors such as climate and biotic/abiotic stresses. Therefore, to assess the genetic diversity per se, biochemical and molecular markers are preferred. First such markers were enzymes that occur in the plant tissues. Isolated enzyme proteins (allozymes and isozymes) were electrophoresed and their molecular sizes were separated on the gel for visualization to determine the differences among different varieties. However, the variation among such proteins revealed by this method is often limited. In this regard, DNA-based technologies provide greater polymorphism and prove useful to assess the diversity of germplasm with better accuracy. Besides, DNA can be isolated at any stage of growth and development, and only a small quantity of the sample is required for analysis. DNA is also very stable, unlike protein or RNA, and stores well for repeated analyses. Development of FTA cards even eliminates tedious process of DNA isolation. In this technology, plant tissues are simply macerated on the special filter paper and stored at room temperature until analysis. FTA cards are especially useful in remote locations or resource-poor countries where biochemical reagents and equipment are not readily available for conventional DNA extraction. 17.5.1

Early Developments

In the 1990s, two PCR-based DNA technologies were commonly used to identify differences (polymorphism) among different samples. They were restriction fragment length polymorphism (RFLP), and randomly amplified polymorphic DNAs (RAPD). 17.5.1.1

RFLP

RFLP was the first technique that allowed inexpensive DNA genotyping of plant germplasm (Lodish et al., 2000). In this technique, DNA samples are digested by

17.5 Characterization of Germplasm

appropriate restriction enzymes. The numerous fragments of various sizes that are produced by digestion are separated according to their length by gel electrophoresis. The separated DNA fragments are then transferred to a membrane by a process named Southern blotting. The blot is then hybridized to a radiolabeled DNA probe, which visualizes the length of the fragments that are complementary to the probe. In the genomes of different samples, restriction sites occur at different loci. This produces fragments of different sizes detected by the probe. Southern blotting is a time-consuming process and can limit the utility of this technique. 17.5.1.2

RAPD

RAPD (commonly pronounced “rapid”) is a method of genotyping using PCR (Williams et al., 1990). Unlike regular PCR with different forward and reverse primers, RAPD utilizes single primer of random sequence, typically ten nucleotides long. Because such a primer is annealed at different loci on the genome of different plant varieties, it can produce polymorphic DNA band patterns when amplified by PCR and visualized on an electrophoresis gel. An advantage of RAPD is that it does not require prior knowledge of sequence, and the procedure is straightforward. The main limitation of RAPD is its reproducibility. RAPD performed on identical samples may produce different results that can arise from different PCR conditions, such as template concentration, DNA quality, concentration of PCR reagents, and thermocycling program. Therefore, for validity, RAPD data must generally be confirmed by another method. Another disadvantage is that most RAPD markers are dominant markers, meaning that it cannot distinguish between homozygous and heterozygous loci. 17.5.2

New Developments

More advanced techniques later became available and widely used. These include microsatellite (or simple sequence repeats) analysis and amplified fragment length polymorphism (AFLP). Recently these two techniques are commonly employed or characterization of plant genetic resources. 17.5.2.1

Genotyping by Simple Sequence Repeats (SSR)

Plant germplasm can be genotyped by using a DNA marker termed simple sequence repeats, which is also called microsatellites. It is a repetitive DNA sequence widely found in plant genomes. The repeats consist of DNA motifs ranging in length from one to five base pairs, and typically repeated 5-50 times (Turnpenny and Ellard, 2005). The length of the repeat region is detected by PCR with specific primers developed for SSR. It is a highly reproducible method, but the development of SSR markers tends to be time consuming and expensive. 17.5.2.2

Amplified Fragment Length Polymorphism (AFLP)

AFLP-PCR or simply AFLP is a highly sensitive method to detect DNA polymorphism by PCR (Zabearu and Vos, 1993; Vos et al., 1995). In this technique, genomic DNA is digested by restriction enzymes and then adaptors are ligated to the sticky ends of the DNA fragments. Primers are designed so that only a subset of the DNA fragments is amplified to produce polymorphism. The amplified fragments are separated and

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visualized on denaturing polyacrylamide gels. To perform AFLP, no prior sequence information is required. Therefore, AFLP has been used in the taxonomical studies of bacteria, fungi, and plants, where the genomic makeup of these organisms are still largely unknown. 17.5.3

Recent Developments

Technologies have been developed to sequence DNA fast and inexpensively, and they are generally referred to as next generation sequencing. In this technology the sequence is read at the time of DNA synthesis by detecting the light emitted upon the addition of a nucleotide to DNA. Numerous synthesis-reading events are performed simultaneously, and the parallel sequencing can yield several 100s of millions to several 100s of billions of DNA bases per run (Shendure and Ji, 2008). Next-generation sequencing can be applied to plant genotyping. 17.5.3.1

Genotyping by Sequencing (GBS)

GBS was first described first in Elshire et al. (2011), and it is lately gaining popularity. In GBS, genomic DNA is digested with a selected restriction enzyme, and ligated to adapters. Selected library fragments are then amplified using primer sequences common to the restriction sites. This “reduced representation library” is used for discovering and scoring polymorphism such as single nucleotide polymorphisms (SNPs). GBS has been used for genome-wide association studies, genomic diversity studies, genetic linkage analyses, molecular marker discovery, and genomic selection under a large scale plant breeding programs (He et al., 2014). 17.5.4

Future Prospects

In the future, it is expected that the cost of whole genome sequencing become affordable to justify the sequencing of all accessions in germplasm collections. Data processing will also become more efficient. At that point, any form of DNA fingerprinting will become obsolete, and genetic characterization will be based simply on the complete DNA sequence of individual accession.

17.6 Germplasm Exchange When desired crop varieties are not available locally, germplasm can be sourced from gene banks located in different parts of the world. In fact, no country is self-sufficient in terms of plant genetic resources, and agriculture is dependent on germplasm introduced from elsewhere in the world in the past. For example, now widely cultivated in Africa, cassava is originated from South America (Shigaki, 2016). Before the germplasm is exchanged, it must be certified to be free of pathogen as part of the quarantine requirements, because infected germplasm has inferior vigour and can serve as a source of new pathogens when introduced to a new location. A traditional method utilized at quarantine facilities to test the seeds for the presence of pathogen infection, the grow-out test is a time-consuming way. It also may not be able to detect a low level of infection. Biotechnology provides tools to assess the health of the

17.6 Germplasm Exchange

germplasm and largely replaced the traditional method. Sophisticated biotechnological methods are now being developed to ensure the quality of the planting materials that are exchanged beyond political and geographical borders. As the volume of the germplasm traffic increases, the role of molecular assays is becoming increasingly important. Some examples of pathogen assay are described. 17.6.1

Bioassay

Before the 1970s, pathogen testing was done largely by grow-out tests aimed mostly at detecting the infection of seeds by fungal pathogen. It is a time-consuming method, and often misses symptomless pathogens such as viruses and viroids, although viruses can be tested by grafting to indicator plants. To overcome the lengthy process of bioassay, biotechnological methods have been developed for fast and sensitive pathogen detection. 17.6.2

Enzyme-Linked Immunosorbent Assay (ELISA)

The development of ELISA in 1971 (Engvall E and Perlmann P, 1971; Van Weemen BK and Schuurs AHWM, 1971) made highly sensitive and specific detection of even symptomless pathogens possible, notably viruses. It has become a standard method used by quarantine authorities around the world. Conventional ELISA employed chromogenic reporters and substrates that generate colour change which must be visually read, or quantified by spectrophotometer. Newer techniques use fluorogenic, electrochemiluminescent, and quantitative PCR reporters. However, ELISA requires specific antiserum or antibody raised against each pathogen or strain of pathogen, which can be costly and time consuming. Many antibodies react with non-target antigens and specificity must be carefully assessed before they are used for assays for valid results. Recent advancement in ELISA technology includes the detection of attogram levels of antigens, developed by de la Rica (2012), in which blue colour appears for positive results and red colour for negative. 17.6.3

PCR

In this regard, more recent technology of polymerase chain reaction (PCR) is used as a versatile method. Insofar as some sequence information is available for the target pathogen, it is possible to design specific primers to amplify pathogen DNA, or in the case of most plant pathogenic viruses, RNA (following complementary DNA synthesis by reverse transcription). An application of PCR, real time PCR (or quantitative PCR, or qPCR) can even detect the copy number of DNA in the sample and more accurately detect the pathogens in the sample. PCR and qPCR require a laboratory facility and dedicated equipment, such as thermocycler, electrophoresis units, and gel documentation system. 17.6.4

Loop-mediated Isothermal Amplification (LAMP)

LAMP is a relatively new patented technology that utilizes a DNA amplification chemistry distinct from PCR. It is claimed to be more sensitive and cost effective than

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PCR. Similar to PCR, it can be performed in a dedicated thermocycler-like machine. Alternatively, many LAMP kits have been developed, which eliminated the need of a dedicated machine. This technology brings the accuracy and sensitivity of sophisticated molecular laboratory testing to practically anywhere where the samples are collected. It can potentially become a method of choice for plant disease diagnosis, especially in resource poor countries and regions. There are internationally agreed protocols to follow for the exchange of germplasm. Plant genetic resources, and any other genetic resources, were, until recently, recognized as a common property shared by all humans, regardless of political boundary where the materials were originated. Many crops cultivated in the world were introduced from other parts of the world this way. Countries or regions of their origin were not compensated in any way. However, this understanding has changed as countries started to claim their genetic resources and associated traditional knowledge as part of their intellectual property. This trend is clearly against efficient exchange and thus effective utilization of plant genetic resources. To address this, United Nations World Food Organization (FAO) coordinated to establish an international treaty termed International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA). Under this treaty, member countries can import accessions preserved in gene banks by signing a streamlined agreement (standard material transfer agreement, or SMTA). When the user wants access to seeds donated by multiple countries, the user does not need to negotiate with each country of origin. Rather, a simple SMTA will allow the user to import them. The SMTA states that when the user receives monetary gains arising from the seeds, a small fraction of the profit must be paid to the pool of funds within the treaty (benefit sharing funds). The benefit sharing funds are used to fund projects aimed at promoting world food and nutritional security. The amount of money received by the funds arising from the usage of the germplasm is far from sufficient to cover necessary activities by ITPGRFA and its member countries. Revision to the mechanism of fundraising is being considered, including the adoption of a subscription-based fee system. Currently, only the crops specified in Annex I of ITPGRFA can be exchanged using the SMTA. The list covers many important crops. However, many other crops are not listed in Annex I. Expansion of Annex I to include all crops is currently under consideration by the governing body of ITPGRFA. Donor countries must ensure that the genetic materials they export are free from any pest and disease. This requires gene banks to test their germplasm with sophisticated biotechnological tools, such as ELISA and PCR. This is especially difficult for small developing countries which do not have critical mass of population and scientific capacity. Regional cooperation and assistance from developed countries are important in this regard. Potentially less expensive technologies such as LAMP can be also considered. The crops not covered by ITPGRFA must be handled by another treaty termed Nagoya Protocol for Access and Benefit Sharing. It is a bilateral agreement, rather than multilateral as in ITPGRFA, meaning that the exchange must be negotiated individually between the donor and the recipient. These treaties have been signed by a majority of the countries and are becoming the standard protocols when germplasm is exchanged, and biotechnological methods are now indispensable as the standard test for phytosanitary status of the germplasm exchanged.

17.7 Germplasm Utilization

17.7 Germplasm Utilization In order to justify the high cost of maintenance, germplasm should not be preserved for the sake of preservation alone. Rather, preserved germplasm should be actively utilized as a coping strategy in times of needs and for breeding new varieties to address the changing environment and nutritional and culinary requirements by people. This is often called the “Use it or lose it principle.” Germplasm preservation is costly as it often requires a sophisticated facility. As the number of maintained germplasm increases, this cost can be prohibitive for gene banks. Benefits coming out of the utilization will justify this cost, or the cost may be covered by fees paid by users. Recent advances in biotechnology widened the scope of the improvement of plant genetic resources beyond conventional breeding methods. For example, advanced tissue culture techniques have overcome sexual incompatibility. Genetic engineering even crosses the family and kingdom barriers to develop previously unimaginable crops that can resist pathogens and pests, have enhanced nutritional traits, or tolerate herbicide application. A few examples are listed here.

17.7.1

Embryo Rescue

Embryo rescue is an in vitro tissue culture technique used to “rescue” a developing embryo that may not survive to become viable plant without technical intervention (Sage et al., 2010). This technique is typically used to produce hybrids between two closely related species. In this technique, which has become an important plant breeding tool, embryos are excised and transferred to the media before the embryos are otherwise aborted. The composition of the media varies depending on the species and the developmental stage of the embryo. Many hybrids have been successfully developed using the embryo rescue. Some examples are hybrids between Arachis hypogaea and closely related but incompatible species A. paraguariensis and A. Appressipila, both of which are resistant to early leaf spot (Rao et al., 2003). Arguably, most celebrated interspecific hybrid that was developed by embryo rescue may be NERICA (for New Rice for Africa) rice. This new hybrid rice, developed by the Africa Rice Center (formerly WARDA [West Africa Rice Development Association]) is a cross between two Oryza species, namely O. sativa and O. glaberrima. O. glaberrima is still cultivated in some African countries. Although its yield is lower than that of O. sativa, it is highly tolerant to low rainfall, a condition typical in Africa. It is also resistant to many pests and diseases and competes well with weeds. Besides, it has higher protein content than O. sativa, which is a desirable trait in African countries. Combining the high yield potential of O. sativa and drought tolerance and other desirable characters of O. glaberrima, is not possible through conventional crosses but was achieved by the embryo rescue technique. It should be stressed that this was possible only because O. glaberrima seeds were preserved in the gene bank of Africa Rice Center. NERICA helps reduce the importation of rice by allowing African countries to produce their own harvest. Considering that more than half of the world’s population increase is occurring in Africa, NERICA has a potential to play a key role to achieve food security of African countries.

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NERICA’s potential is not limited to Africa. For example, occasional drought conditions are common in the Pacific. In Papua New Guinea, NERICA was introduced in 2011 to prepare for El Niño induced drought conditions, which is becoming more common in recent years, possibly due to climate change. Currently, evaluation of the newly introduced hybrid is ongoing. 17.7.2

Somatic Hybridization

Somatic hybridization and protoplast fusion have been particularly useful to transfer beneficial traits from wild relatives of cultivated species to cultivated varieties. The membrane of protoplast has strong negative charges. Therefore, fusion of protoplast must overcome the repulsion by the charges. This can be accomplished by adding polyethylene glycol (PEG) or calcium ions, or by using electric fields. An example of somatic hybridization is the late blight resistance transferred from Solanum nigrum into S. tuberosum (Horsman et al., 1997; Zumnoch-Guzowska, 2003). 17.7.3

Molecular Breeding

Molecular-based markers freed the selection of lines with target traits from phenotypic observations, thus dramatically accelerating the speed of the development of new lines and varieties. This technology, marker-assisted selection (MAS) has produced many commercially successful varieties of crops. An example is PureHeart seedless mini watermelon, that has a very thin rind and a mini size that can fit into a home refrigerator easily. The reason why MAS has gained popularity is that the products of MAS are not genetically modified organisms (GMOs). Environmental advocates, who are against genetic engineering, support MAS as an environmentally friendly way of breeding (for example, see Greenpeace, 2009). Therefore, the new crops developed by MAS are readily accepted by these groups and consumers in GMO-sensitive countries, especially in Europe. As next-generation sequencing and processing become increasingly powerful, more markers associated with tolerance to climate change stresses will become available for the breeding of enhanced crops. 17.7.4

Genetic Engineering

Genetically engineered crops are now widely grown (Table 17.1). However, despite the initial excitement about the promises of genetic engineering, the world became wary of its dangers. Many of the concerns are based on misunderstanding of the science, but some are real. An example is the possibility of contaminating the gene pool if genetically engineered plants are grown in the open field. Such risks must be carefully evaluated before GMOs are released into the environment. The first genetically engineered plant (tobacco plant with an antibiotic resistant gene) was developed in 1983 (Fraley et al.). Since then, many crops have been modified genetically with added traits such as herbicide resistance (James, 1996) and pest resistance from Bacillus thuringiensis (Bt) (Vaeck et al., 1987). In 1994, a genetically modified tomato named FlavrSavr, which was made to have a longer shelf life, was developed (Bruening and Lyons, 2000). It was the first genetically modified crop approved for sale. In 1995, a potato engineered with the Bt gene

17.7 Germplasm Utilization

Table 17.1 Major countries with genetically modified crops in terms of planted area.

Rank

Country

Area (million hectares)

1

USA

73.1

Maize, soybean, cotton, canola, sugarbeet, alfalfa, papaya, squash

2

Brazil

42.2

Soybean, maize, cotton

3

Argentina

24.3

Soybean, maize, cotton

4

India

11.6

Cotton

5

Canada

11.6

Canola, maize, soybean, sugar beet

Biotech Crops

Source: International Service for the Acquisition of Agri-biotech Applications (ISAAA) Brief 49-2014: Executive Summary.

was approved by the US Environmental Protection Agency. Other crops such as canola, maize, and cotton with Bt were also developed. In 2000, beta carotene (a precursor of vitamin A) enriched rice termed golden rice was announced (Ye et al., 2000). The nutritionally improved GMO crops such as golden rice lacked rigorous clinical study performed in humans when it was developed. The first such study was carried out by Morris et al. (2008) at Baylor College of Medicine. The group developed carrots with enhanced calcium content, by inserting a calcium transporter (CAX) in the genome. In their clinical study, 30 adults ate the genetically engineered carrots one day, and control carrots on another day. The participants absorbed 41% more calcium from the engineered carrots than from the control. Although the commercial availability must await further studies, the carrots may one day help alleviate osteoporosis problems. There are now three categories in GMO crops, transgenic, cisgenic, and subgenic. Transgenic plants are “conventional” genetically modified plants. They have foreign genes or genetic elements inserted into their genome. The insertion of foreign genetic elements cross the natural boundary of cross breeding, and can be selected from the same kingdom (plant to plant) or from other kingdoms (often from bacteria). In most cases, along with the main genes, a tissue or developmental stage specific promoter, and a marker gene (e.g. antibiotic or herbicide resistance) are also transferred for efficient expression and selection. Due to the incorporation of completely foreign elements in the crop’s genome, it has been a target of environmental activists, making the commercialization of GMOs financially too risky. Cisgenic plants are developed with only the DNA elements from the same or closely related species. Such genetic alteration can occur through conventional breeding. It is argued that cisgenic plants are natural, thus they should not be regulated by the same laws as transgenic plants. In 2014, Wan and colleagues reported the deletion of wheat genes that code for proteins that repress defences against powdery mildew, making the wheat resistant to the pathogen. In this process, no DNA elements were added, yet it created a new trait. This type of “genetically engineered” plant is called subgenic plant. This approach is similar to mutation breeding, which is not considered genetic engineering. Cisgenic and subgenic crops do not contain any foreign genetic elements in the genome, and therefore many concerns surrounding transgenic crops do not apply. In

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fact, such genetic alteration could occur in nature. Although they must go through careful trials, these crops may be more readily accepted by consumers. 17.7.5

Biosafety

Biosafety is the prevention of loss of human and ecological health, and usually refers to the safety against genetically engineered organisms. Considering the widespread use of transgenic animals and plants both in the commercial sectors and research, legislation on biosafety should be an essential installation. In 2000, the Convention on Biological Diversity (CBD) established a protocol on biosafety (“Cartagena Protocol”). It covers “the transboundary movement, transit, handling and use of all living modified organisms that may have adverse effects on the conservation and sustainable use of biological diversity, taking also into account risks to human health.” Considering the clear benefits as coping strategy against climate change, the biosafety legislation must be in place before the technology adoption. The most important and urgent need in developing countries is the human capacity to understand the increasingly rapid development of biotechnology, biosafety, and intellectual property issues, and to solve the problems arising from these. Currently, most countries in the developing world lack even the most basic higher education institutes. Therefore, the training of the staff concerned is typically outsourced to developed countries. Local capacity building, through training courses held at local institutes, is of utmost importance. The biotechnology has advanced at an alarming speed for the past few decades and branched out into unexpected areas. Unfortunately, many developing countries are on the receiving end of the technology and this makes the countries vulnerable to adverse changes resulting from the technological advancement, because adaptation to the changes tends to be slow. For example, the assessment of Bt technology may require equipment and human resources beyond the ability of most developing countries. Fast developing technology necessitates swift regulatory response, and any delay will endanger the countries economically and environmentally, and will result in missed opportunities. The controversies surrounding GMOs concern their safety to humans and the environment. Potential risks are not always examined to address the questions from consumers and environmental activists. It is essential to remove such obstacles for the acceptance of GMOs. If there is any real risk in GMOs, it should be banned according to domestic biosafety laws and international treaties. To cope with rapid climatic change, the development of climate-change ready crops may be too slow if only conventional (including MAS) technologies are used. Genetic engineering, thus, will be an essential tool to feed the increasing population. Rigorous scientific standards must be applied to warrant the safety of GMOs.

17.8 Future Strategies and Guidelines for the Preservation of Plant Genetic Resources Genetic resources are being lost at an alarming rate due to climate change and rapid urbanization following population increases. Gene banks are therefore important back up centers of the natural reserves of the genetic resources, whether they are natural

17.8 Future Strategies and Guidelines for the Preservation of Plant Genetic Resources

or selected by humans throughout the history by artificial selections and breeding. Biotechnology contributes to both the preservation itself and the assessment and utilization of the preserved germplasm. Centers of diversity of many plant species are often located in developing countries in the tropics and more often than not, they are not well equipped with biotechnological capacity. Advancement of biotechnology is expected to make sophisticated preservation techniques more accessible to these regions. For example, LAMP, a molecular assay based on a novel molecular amplification chemistry, is recognized as a more sensitive yet less expensive method, than conventional methods such as PCR or ELISA. The test can be performed on site without a laboratory facility. Therefore, it is ideal for countries that cannot justify the need for dedicated laboratories. Seeds are probably the best form of germplasm preservation. In the tropics, the status of the seeds for cold storability is not well understood, although tropical seeds are probably recalcitrant. The status has to be tested before resorting to other methods, as cold storage is the easiest and most inexpensive method. If the seed are proven recalcitrant, then the preservation requires alternative methods such as tissue culture or cryopreservation. Unfortunately, both these technologies are currently prohibitively expensive in many developing countries to be used as the standard mode of preservation. Lowering the cost depends on the future advancement of the technologies. The most serious obstacle to the use of biotechnology, including genetic engineering may not be technological at all, but it may come from its unacceptance by consumers and activists. In the future, if the environment becomes harsher for agriculture, this may change, as many African countries now accept transgenic crops. In the meantime, technologies to engineer new lines without any foreign genetic elements have been developed and is termed “cisgenic” and “subgenic” as opposed to “transgenic” plants. Although these are also products of genetic engineering, they are expected to be more readily acceptable by the public. Together with more rigorous studies to prove the safety of GMOs, the development of minimally altered crops may prove successful. At the same time, marker development for molecular selection must be accelerated and more markers should be made freely available to breeders, especially in developing countries. It is currently an expensive exercise to develop markers for unconventional and neglected crops. Technological advancement should contribute to lower the cost of maker development for such crops. Svalbard Global Seed Vault provides a new and secure way to preserve germplasm. It acts as a backup facility of gene banks around the world. This author’s opinion is, if funds are identified, the Global Seed Vault itself can be duplicated in the future elsewhere in a similar natural and social environment, after sufficient experience is gained from Svalbard. This will further safeguard genetic resources. To develop crops that can adapt well to the changing climate, understanding of plants’ cell physiology is the key. Discovery of molecular pathways for heat, drought, salinity, and pest/disease tolerance will lead to the breeding of enhanced crops. Non-transgenic approach, if necessary, will facilitate its acceptance by the public. Biotechnology can even take advantage of the excess carbon dioxide by converting C3 plant rice to adopt the C4 pathway. This will boost yield, as well as help reduce the carbon dioxide in the atmosphere. The world population will reach the 10 billion mark around 2055–2056 (medium variant estimate, United Nations, 2015). Over half of the population increase will occur

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in Africa, where climate change has direct effects on food production. It is therefore understandable that genetic engineering is generally viewed in a positive light in Africa. The raw material for genetic engineering is genetic resources. To prepare for the climate change and population explosion, it is crucial to identify efficient and cost-effective ways to conserve plant genetic resources. Biotechnology should hold the most promising key to achieve this goal.

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18 Climate Change Influence on Herbicide Efficacy and Weed Management Mithila Jugulam, Aruna K. Varanasi, Vijaya K. Varanasi, and P.V.V. Prasad Department of Agronomy, Kansas State University, Manhattan, USA

18.1 Introduction Climate change refers to a change in the climate system that persists for long periods of time, irrespective of the cause. Since the industrial revolution, climate change has been more often associated with a rise in the concentration of greenhouse gases such as carbon dioxide (CO2 ), methane, nitrous oxide, and halocarbons. The concentration of atmospheric CO2 is steadily rising and is expected to reach ∼1000 μmolmol−1 by the year 2100 with a simultaneous increase of 2–4∘ C in the earth’s annual surface temperature (IPCC, 2013). Human activities such as the burning of fossil fuels and deforestation have contributed to a large extent to the emission of greenhouse gases (IPCC 2013, MacCracken et al., 1990). Continued emission of these gases may lead to unprecedented climate changes involving high global temperatures, erratic precipitation and wind patterns, and weather extremities such as droughts, floods, and severe storms (Tubiello et al., 2007; Robinson and Gross, 2010; Gillett et al., 2011; Coumou and Rahmstorf, 2012). Such extreme weather events and rapid climatic changes will have major impacts on the stability of ecosystems; consequently influencing plant life and agriculture (Dukes and Mooney, 1999). Crop production and agronomic practices involving weed management and pest control may be severely affected by these altered abiotic conditions primarily caused by changes in climate and climate variability (Dukes et al., 2009, Singer et al., 2013). Warmer and wetter climates not only affect weed growth but also change chemical properties of certain herbicides; thereby altering their performance on weeds and their control (Poorter and Navas, 2003; Dukes et al., 2009). Determining the response of weeds and herbicides to increased CO2 levels and associated changes in other climate variables is critical to optimize weed management strategies in the context of climate change. This chapter provides an overview of the impacts of climate change factors on weed growth and herbicide efficacy, particularly focusing on the impacts of climate factors on the underlying physiological mechanisms that determine herbicide performance.

Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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18.2 Herbicides in Weed Management Agricultural production strongly depends on crop protection measures. Insects, pathogens, weeds, and other pests can adversely affect agricultural yields, if left uncontrolled. Outbreaks of pests and diseases may be random and irregular but weeds are relatively constant and cause severe negative effects on agriculture and other natural resources (Kostov and Pacanoski, 2007). Weeds cause extensive damage to cropland and non-cropland areas, and to public health. Weed management has become the primary focus for farmers and weed scientists around the world. Weeds cause yield losses by competing with crops for essential resources such as light, water, nutrients, and space. Weeds also interfere with harvest operations and contaminate the seed, thereby lowering the value of harvested crops. Furthermore, weeds are known to produce harmful chemicals and serve as hosts for several insect pests and diseases (Swinton et al., 1994; Boydston et al., 2008). Hence, weed control is critical for profitable crop production. Weeds can be controlled through cultural, mechanical, biological, and chemical methods. However, chemical weed management through the use of herbicides is widespread in developed countries such as the US, where labor is limited and expensive. Use of herbicides is also increasing in developing countries. Herbicides are routinely applied for weed control in more than 90% of US crop acreage (Gianessi and Sankula, 2003) because of their simplicity in use and greater efficacy (McErlich and Boydston, 2013). Furthermore, weed control through herbicides offers many advantages to farmers by enabling timely weeding, early planting, reducing tillage and soil erosion, and lowering control costs. Despite the concerns of environmental pollution and toxicity to living organisms, their regulated use is essential to sustain the quantity and quality of current agricultural yields. Selective control of weeds through the use of herbicides in several cropping systems has tremendously improved crop yields and quality of the produce. Selective action of herbicides largely depends on interaction with the plant and the environment. Environmental conditions such as light, temperature, relative humidity, and wind velocity at the time of herbicide application determine herbicide’s performance and effectiveness on weeds. Furthermore, climate change associated with increasing temperatures may alter physiology and growth characteristics of weeds, as well as the efficacy of herbicides that currently are fatal to these weeds. Given the importance of herbicide use in sustainable crop production, it is essential to understand if and how climate change influences the efficacy of herbicides to control weeds in current and future climates.

18.3 Climate Factors and Crop-Weed Competition Agriculture has considerable impact on climate change and is accountable for about 30% of greenhouse gas emissions (Nitze et al., 2008). Some modern agricultural practices do contribute to the emission of greenhouse gases, such as CO2 , nitrous oxide, and methane. Examples include the use of farm machinery, fertilizer applications, and the practices necessary for livestock production. Deforestation and other agricultural processes, such as wetland rice cultivation, are also major sources of gases such as methane. Nonetheless, most of the negative impacts of agriculture on climate can be counteracted to a large extent through appropriate and timely measures by improving

18.3 Climate Factors and Crop-Weed Competition

best management practices (BMPs). Examples of some BMPs that can be considered are using precision agriculture, efficient use of resources, diversification of farming systems, agricultural intensification on existing land, and other technological advancements (Tilman et al., 2011; Mueller et al., 2012; Johnson et al., 2014). On the other hand, since agriculture is highly dependent on specific climate conditions, it is very important to give attention to understanding the impact of climate change factors on farming practices and agricultural output. The effects of climate change on agriculture will be very complex. Besides directly influencing crop growth and productivity, climate change may also affect crop-weed-pest interactions, and livestock farming systems. Higher CO2 concentrations and subsequent rise in temperatures will result in erratic weather patterns and extreme weather events such as droughts, floods, heat stress, and freeze events increasing climate variability, which will have considerable negative impacts on the productivity of agro-ecosystems. Conversely, anticipated climate changes, especially elevated CO2 levels, will probably have positive effects on the yield and quality of some crops (C3 crops such as wheat, Triticum aestivum; rice, Oryza sativa; barley, Hordeum vulgare; and soybean, Glycine max). Higher CO2 levels have been predicted to increase the yields of some of these crops by as much as 13% by 2050 (Jaggard et al., 2010). However, increasing CO2 concentration also leads to partial closure of stomata leading to an increase in plant tissue temperature, which will negatively influence plant growth and productivity. In addition, other directly associated factors such as unpredictable rainfall patterns and high temperatures during the growing cycle may reduce yield and quality of crops (Hartfield et al., 2011; Mahajan et al., 2012; Singh et al., 2013; Kadam et al., 2014). For most food crops the positive impacts of elevated CO2 on growth and yield are more than negated by negative impacts of associated increases in temperatures (Prasad et al., 2001, 2005). Furthermore, rapidly changing climate is a major concern for management of agricultural pests and weeds, as it may affect weed, pest, and disease infestations in uncertain ways (Field et al., 1999; Scherm, 2004). Weeds tend to have higher genetic diversity and physiological plasticity than crops. For this reason weeds adapt quickly to resource changes and have a greater ability to survive and flourish in different environmental conditions. It is predicted that climate change could lead to higher competition from weeds, and without proper weed management it could result in greater yield losses (Miri et al., 2012; Valerio et al., 2013). Many weed species will be able to take advantage of increased CO2 levels and warmer conditions and will grow faster and better than most crops (Hartfield et al., 2011). Higher CO2 levels will directly affect photosynthesis in plants and influence the ability of crops to compete with weed species (Chandrasena, 2009). Previous research has demonstrated that C3 and C4 weeds show significant increases in plant growth as a result of increased CO2 and higher temperatures. For example, at elevated CO2 concentrations, a 65% increase in the biomass of a C3 weed, common lambsquarters (Chenopodium album) was observed which resulted in the seed yield reduction of soybean by 39% (Ziska, 2000). Similarly, a 3∘ C rise in temperature was found to increase the growth rate of itch grass (Rottboelliacochin chinensis), a highly competitive C4 weed in many cropping systems–including sugarcane, corn, cotton, soybean, grain sorghum, and rice systems–and is projected to invade further into the central Midwest and California (Patterson et al., 1999). Elevated CO2 (800 μmolmol−1 ) and high temperatures (26/18∘ C; daytime maximum/nighttime minimum; d/n) have

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been reported to intensify competition to tomato crops from both C3 (common lambsquarters) and C4 (redroot pigweed; Amaranthus retroflexus) weeds (Valerio et al., 2013). In general, C3 and C4 plants have different abilities for temperature acclimation of photosynthesis. In C3 plants, carboxylation of ribulose biphosphate (RuBP; first acceptor of CO2 ) is favored at higher CO2 levels. But when temperatures rise above 25∘ C, oxygenation of RuBP is favored which increases photorespiration and inhibits CO2 assimilation (Jorden and Ogren 1984). Conversely, in C4 plants, temperature effect is negligible as lower photorespiration rates are maintained at all times, because CO2 pumps in mesophyll cells (Hatch 1987). As a result of these differences in the photosynthetic pathways, C3 plants typically have a greater ability to respond positively to rising CO2 levels, whereas C4 plants are better adapted to heat stress and drought (due to higher water use efficiency) (Osmond et al., 1982; Long, 1999; Morgan et al., 2001). Since the majority of agricultural weeds have a C4 photosynthetic pathway, weeds will have an advantageous position over crops (mostly C3 plants) under higher temperatures and limited water availability. Furthermore, the differential impacts of climate change variables–such as moisture regimes, CO2, and temperature levels–on weeds and crops allows weeds to compete well and thrive even in unpredictable environments (Hartfield et al., 2011). Hence, there could be serious implications of increasing the temperature and CO2 concentration on crop–weed interactions and therefore, needs greater attention. Climate change factors such as elevated CO2 , increased temperature, and water stress may also affect the availability of nutrients for plant growth and development in future. Root growth and volume plays an important role in nutrient acquisition in most plants. Plants that are under nutrient stress generally increase their root biomass to enhance physiological capacity of roots for nutrient uptake from deeper layers of soil (Bassirirad et al., 2001). Besides increasing shoot growth and photosynthetic activity, elevated CO2 can also stimulate root biomass in many plants (Adair et al., 2009; Anderson et al., 2010; Dijkstra et al., 2010). Fine roots and its associated mycorrhizas, which form the primary pathways for nutrient uptake, are stimulated to increase nutrient-use-efficiency (Bassirirad, 2000; Gifford et al., 2000). Root growth at elevated CO2 was found to increase by 50% and 57% in an evergreen dwarf shrub (Calluna vulgaris) and perennial grass (Deschampsia flexuosa), respectively (Arndal et al., 2013). Studies on root growth and nutrient uptake responses to elevated CO2 and other climate factors in plants are limited and have shown highly inconsistent patterns among different species (Beier, 2004; Bielenberg and Bassirirad, 2005; Gutschick and Pushnik, 2005). With increases in CO2 levels, some plants showed a decline in the tissue concentrations of major nutrients like N and P; whereas in other cases, leaves and roots had negligible effects on their P concentrations (Gifford et al., 2000; Taub and Wang, 2008). Assimilation of N by roots may decrease under elevated CO2 due to inhibition of photorespiration, resulting in decreased carbohydrate accumulation in roots compared to shoots, particularly in C3 plants (Reich et al., 2006; de Graaff et al., 2006; Rachmilevitch et al., 2004; Bloom, 2009). At higher temperatures nutrient uptake is expected to increase due to longer growing seasons that create a wider window of opportunity for mineralization processes that increase nutrient availability to plants (Beier, 2004; Schmidt et al., 2002). Under prolonged drought conditions, dehydration of roots and reduced soil nutrient mobility impede root activity and nutrient uptake (Hinsinger et al., 2009). In some cases, water scarcity may increase root length while decreasing the density (Staddon et al.,

18.3 Climate Factors and Crop-Weed Competition

2003). Elevated CO2 also influences nutrient dynamics between crops and weeds. In a rice-barnyard grass competition scenario, rice was able to increase uptake and tissue concentrations of C, N, P, and K nutrients compared to barnyard grass, resulting in enhanced tillering and greater biomass in rice (Zeng et al., 2011). Climate change is also speculated to be one of the most important determinants for the distribution of many weed species including the invasive and noxious weeds (McDonald et al., 2009; Pautasso et al., 2010). Climate change directly affects the composition and habitable range of both annual and perennial weed species. Global warming will result in longer growing seasons in temperate regions which will increase weed infestations, creating more challenges for weed management (Hartfield et al., 2011; Hakala et al., 2011). For example, survival of some winter annual weeds could be greater in wetter and milder winters, whereas summer annuals may start showing up in regions further north due to warmer summers and longer growing seasons (Walck et al., 2011; Hanzlik and Gerowitt, 2012). The geographical range of some weed species typically found in southern regions (e.g. Palmer amaranth; Amaranthus palmeri) may expand to northern regions as early spring and warmer winters make higher latitudes more conducive to plant growth. Invasive weeds such as kudzu (Pueraria lobata) may also expand their habitat range to new areas and higher latitudes and are projected to cause greater losses to crop, rangeland, and forest productivity (Blaustein, 2001; Ziska and George, 2004). Over the last decade, invasive plants have been reported to cause significant negative impact on agroecosystems including agriculture, forestry, rangelands and other human activities such as transportation, public health, recreation, and tourism (Pimentel et al., 2000; EEA, 2012; Sheppard and Stanley, 2014). These changes in weed distribution can incur greater losses to the US economy both in the newly infested areas and in their current habitat, if conditions become more favorable. On the other hand, traditionally problematic weeds will probably become less challenging in certain regions as higher temperatures create more unfavorable growth conditions (McDonald et al., 2009). Enhanced greenhouse effects associated with rise in CO2 concentration and temperature levels can lead to changes in precipitation patterns and water availability that will significantly impact plant growth and propagation (Rodenburget et al., 2011). Most weeds have prolific seed production and rapid seed dispersal mechanisms, which enable them to spread quickly and establish in new territories. Consequently, weeds may have greater advantage with variable precipitation patterns resulting in migrations to new territories and altering the composition and integrity of ecosystems. For example, under prolonged drought conditions, cheatgrass (Bromus tectorum) and yellow star thistle (Centaurea solstitialis) are known to outgrow other species leading to a shift in the vegetation (Vollmer and Vollmer, 2006, Hartfield et al., 2011). Robinson and Gross (2010) studied the impact of variable precipitation on common lambsquarters and giant foxtail (Setaria faberi) and found that common lambsquarters was more tolerant to dry soil conditions than giant foxtail. Climate change will impose new limitations on essential resources required for plant growth and may change the dynamics of crop-weed competition in several cropping systems. Therefore, it becomes imperative to expand our knowledge on how weeds and crops respond to climate change factors on a case-by-case basis. Extensive research is needed to identify the weeds that may become problematic in future climates to devise specific management strategies that are efficient in managing these weeds under such contexts.

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18.4 Climate Change Factors, Herbicide Efficacy and Weed Control Herbicides are important tools for weed management and offer several benefits to growers by being cost-effective and more reliable than any other methods of weed control. But the chemical properties of herbicides are as much liable to climate change factors as plant growth and development. Weed resistance to herbicides will probably increase due to more aggressive growth of weeds in future climate conditions, which can cause a decline in the efficacy of routinely used herbicides. This may necessitate increased use of herbicide mixtures and integrated weed management strategies (Rosenzweig et al., 2001; Bailey, 2003). Environmental conditions at the time of herbicide application significantly impact herbicide efficacy on weeds. Herbicide efficacy in susceptible plants is determined by many factors including herbicide absorption and translocation, herbicide metabolism, and herbicide binding with the target site in the plants. Each one of these factors may be influenced by environmental conditions such as light, moisture, humidity, temperature, and wind velocities at the plant level (microclimate). Changes in climate factors such as increased CO2 levels and high temperatures may alter the physicochemical properties of the herbicide, thereby affecting the penetration and translocation of herbicides in the plants. In addition, changes in growth and physiology of plants will determine the ability of herbicide to interact with the plant surface and also the target site, once it is translocated inside the plant (Steurbaut, 2009; Keikotlhaile, 2011). Climate change impacts on foliar- and soil-applied herbicides depend on the specific environmental conditions, and can also vary among the different herbicide chemistries. Climate change factors can impact the underlying physiological mechanisms through which herbicide is absorbed and translocated in the plant to reach the target site and cause the lethal effect on the plant. It is important to critically examine the effects of major climate change variables such as rising CO2 levels, high temperatures, moisture availability, and solar radiation on potential mechanisms that alter herbicide efficacy. 18.4.1

Effects of Elevated CO2 and High Temperatures

Optimum concentrations of CO2 and temperature are important not only for plant growth and development, but also for sustaining the chemical properties of herbicides. An increase in CO2 and temperature will cause substantial effects on photosynthetic activity and stimulate overall plant growth (Gutierrez et al., 2008). Increase in aboveground plant growth can dilute the amount of foliar-applied herbicides absorbed in plants, thereby decreasing the herbicide residue that binds to the target site and kills the plant (Holland and Sinclair, 2004). An increase in plant biomass and leaf area resulted in lowering the efficacy of glyphosate in invasive weeds such as Rhodes grass (Chloris gayana) and dallisgrass (Paspalum dilatatum) at elevated CO2 levels (Manea et al., 2011). Similarly, roots are also stimulated to grow more and may reach deeper soil layers at elevated CO2 levels. This prevents the uptake of soil-applied herbicides, which are generally present in the top layers. Ziska et al. (2004) reported high root:shoot ratio of field-grown Canada thistle (Circium arvense) under elevated CO2 levels, which reduced the efficacy of glyphosate due to the dilution effect caused by large volume of roots. However, in some cases, high temperatures could enhance root uptake of herbicides

18.4 Climate Change Factors, Herbicide Efficacy and Weed Control

due to a decrease in soil organic matter and high evaporation rates (Miraglia et al., 2009). Another prominent effect of elevated CO2 is the reduction in stomatal conductance by 50% in some plants (Bunce, 1993), which can alter the transpirational flow and reduce the efficacy of both foliar- and soil-applied herbicides. Furthermore, due to leaf thickening, stomata may remain closed, thereby reducing the amount of foliar-applied herbicide that is directly absorbed by plants. This has shown to protect the weeds from damage by post-emergence herbicides (Ziska, 2008; Jackson et al., 2011). Quackgrass (Elymus repens) exposed to high CO2 concentration (720 μmolmol−1 ) was found to be more tolerant to glyphosate compared to plants exposed to ambient CO2 concentration of 380 μmolmol−1 . It was suggested that a reduction in stomatal conductance or increase in leaf starch concentrations may have decreased glyphosate absorption in these plants (Ziska and Teasdale, 2000). On the other hand, high temperatures can change the amount of herbicide diffused by altering the viscosity of cuticle waxes and physicochemical properties of spray solutions (Price, 1983). Higher temperatures have been shown to lower the viscosity of cuticular lipids, thereby increasing the permeability and diffusion of herbicides through the cuticle (Fausey and Renner, 2001). Changes in other temperature-dependent processes such as phloem translocation, respiration, and protoplasmic streaming in plants exposed to high temperatures will also change herbicide performance. For instance, 14 C-glyphosate translocated more to meristematic tissues of roundup ready soybean at 35∘ C than at 15∘ C, possibly suggesting higher glyphosate injury when there is an increase in temperature (Pline et al., 1999). In some cases, high temperatures were also found to induce rapid metabolism of parent herbicide molecules and increase the activity of some antioxidant enzymes that help in the detoxification of reactive oxygen molecules, thus reducing herbicide activity on target plants. In a recent study by our group (Godar et al., 2015), the efficacy of mesotrione (HPPD-inhibitor) significantly decreased when palmer amaranth plants were exposed to a high d/n temperatures of 40/30∘ C. At these temperatures, although absorption of mesotrione was higher, the amount of herbicide translocated to the growing tissues was significantly lower compared to plants grown at optimum (32.5/22.5∘ C; d/n) or low temperatures (25/15∘ C; d/n). Furthermore, Palmer amaranth plants under high temperatures rapidly metabolized mesotrione molecules and had increased expression of target (HPPD) gene, possibly diluting the mesotrione toxicity in the treated plants. This suggests that weeds such as Palmer amaranth could be less sensitive to mesotrione under increased temperatures via multiple mechanisms. Temperature also can influence germination and seedling growth of plants, which, in turn, determine the sensitivity of plants to herbicide application (Hull et al., 1975). Due to their direct impacts on photosynthetic activity, elevated CO2 concentrations and high temperature could have pronounced effects on the efficacy of herbicide chemistries such as Photosystem II inhibitors (PSII) and pigment inhibitors that interfere with photosynthesis. Efficacy of linuron was reduced by 15% in wild buckwheat (Polygonum convolvulus) at double-ambient CO2 levels (Archambault et al., 2001). In contrast, high air temperatures maximized the control of velvet leaf and common ragweed after atrazine application (Stewart et al., 2009). High soil temperatures primarily affect the efficacy of soil-applied herbicides by decreasing permeability and increasing volatility and microbial breakdown. At a high soil temperature (25∘ C), volatilization of herbicide, triallate was increased from 14 to 60% and 7 to 41% in sandy and loamy soils, respectively (Atienza et al., 2001). Herbicides that inhibit amino acid

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biosynthesis (e.g. ALS inhibitors) were effective in controlling cheat grass, wild oat, jointed goat grass (Aegilops cylindrica), when temperatures were 25/23∘ C (d/n) after application compared to 5/3∘ C (d/n) (Olson et al., 2000). High temperatures may also have variable effects on the efficacy of some other herbicides, such as synthetic auxins. While temperature increase had no effect on the efficacy of dicamba/diflufenzopyr providing >95% control of common ragweed, common lambs quarters, and redroot pigweed; however, control of velvetleaf was reduced by 7% to 15% at low temperature (Stewart et al., 2009). Ou and Jugulam (unpublished) observed increased translocation of Dicamba resulting in improved kochia control at 17.5/7.5∘ C; d/n or 25/15∘ C; d/n temperatures compared to 32.5/22.5∘ C. In case of PPO inhibitors such as Flumiclorac and Fluthiacet, which are contact herbicides, high temperature increased herbicide diffusion as a result of reduction in the viscosity of cuticular waxes on the plant leaf surface (Fausey and Renner, 2001). Overall, the outcome of these studies suggests that there may be a need for increased dose and/or number of applications of some herbicides in future climate conditions to sustain the current efficacy of these herbicides (Rosenzweig et al., 2001; Noyes et al., 2009). 18.4.2

Effects of Precipitation and Relative Humidity

Precipitation and relative humidity (RH) are the other important climate factors that mainly influence herbicide retention on the leaf surface, as well as absorption and translocation inside the plant. Precipitation also influences the availability of soil moisture for plant growth. Variable precipitation likely accompanied by warmer temperature will lead to weather extremities such as droughts and floods affecting overall plant growth and development (Clements et al., 2014). In such scenarios, weeds again tend to fare better showing greater survival and tolerance mechanisms and even sustaining herbicide applications. In addition, intense rainfall immediately after herbicide application could result in washing-off of spray droplets from the plant surfaces and/or diluting the herbicide concentration applied to the plants, thus reducing herbicide retention time and uptake. Conversely, lower precipitation amounts will enhance herbicide uptake by rewetting dried spray droplets on the leaf surface (Olesen and Kudsk, 1987). Water stress caused by low amounts of precipitation also significantly affects herbicide activity due to lower translocation and decreased transpiration within the plant (Zanatta, 2008; Keikotlhaile, 2011). Activity of Acetyl CoA Carboxylase (ACCase) inhibitors was significantly lower in plantain signal grass (Urochloa plantaginea) when plants were grown under water stress (Pereira, 2010). Furthermore, under limited water availability, solubility and movement of soil-applied herbicides were decreased resulting in lower root uptake (Dao and Lavy, 1978; Moyer, 1987). All pre--emergence herbicides require optimum soil moisture for movement within the soil and active absorption by plant roots (Olson et al., 2000). Jurisk et al. (2013) reported a decrease in the activity of pethoxamid (seedling growth inhibitor) applied as PRE-emergence under dry soil moisture conditions. While dry soil conditions increase herbicide adsorption to soil particles, heavy rainfall immediately after the application may result in herbicide loss due to leaching (Soukup et al., 2004). Plant modifications, such as upright or downward orientation of leaves, in dry conditions lower retention of foliar-applied herbicides (Levene and Owen, 1995). Leaves of velvetleaf plants tilt downwards during drought conditions, which decreases glyphosate uptake and lower its efficacy on the plants

18.4 Climate Change Factors, Herbicide Efficacy and Weed Control

(Zhou et al., 2007). These studies indicate that changes in precipitation patterns may benefit herbicide dissipation rather than persistence, and that herbicide efficacy varies with the timing and intensity of rainfall (Bailey, 2003; Stenrod et al., 2008). Drought conditions during autumn and intense precipitation in humid regions can hinder field operations such as weed scouting and herbicide application for early weed control (Chen and McCarl, 2001; Miraglia et al., 2009). Precipitation and RH are interdependent climate variables. While precipitation largely influences soil moisture availability, RH is a measure of atmospheric moisture content. Optimum RH is required for the herbicide spray droplet to interact with leaf cuticle and gain entry into the plant system before it starts drying on the leaf surface, at which point it cannot be absorbed by the plant (Muzik, 1976; Price, 1983). Research has shown that RH could exert greater influence on the uptake of foliar-applied herbicides than temperature (Devine et al., 1993, Anderson et al., 1993). Optimum levels of RH at the time of spraying will increase herbicide uptake and subsequently may lead to greater translocation inside the plant. RH has higher impacts on water-soluble herbicides such as glyphosate, bentazon, paraquat, and nicosulfuron compared to lipophilic herbicides (such as pendimethelin, atrazine, fluazifop, and carfentrozone). At plant level, high RH stimulates stomata to remain open, thus allowing more herbicide to be absorbed into the leaf surface (Kudsk et al., 1990). Ramsey et al. (2002) studied the efficacy of glufosinate ammonium on wild oat plants grown at high (>95%) and low RH (40%). Uptake and efficacy of glufosinate ammonium increased significantly in plants exposed to high RH for 30 min prior to and after herbicide application compared to those left continuously at low RH. High air temperature accompanied with high RH is beneficial for weed control by some herbicides like amino acid inhibitors, which show improved efficacy under these conditions (Stopps et al., 2013).

18.4.3

Effects of Solar Radiation

Solar radiation or light is the most important determinant for photosynthesis in plants. Growth rate in plants is proportional to the amount of solar radiation intercepted, if all other conditions are favorable. Solar radiation affects herbicide activity primarily through changes in plant anatomy and growth. As light intensity increases, the rate of photosynthesis and phloem translocation increase which facilitates the movement of foliar-applied systemic herbicides within the plant and to the growing point/target sites for action. High light intensity also improves herbicide uptake as more stomata remain open. Herbicides such as Bentazon, Clethodim, and Talkoxydim showed higher efficacy on weeds as light intensity increased (McMullan, 1996, Hatterman-Valenti et al., 2011). In some cases, solar radiation may directly affect the chemical properties of herbicides through photo-degradation. For example, efficacy of CHD herbicides (ACCase inhibitors) decreased at low light intensity (UV light) due to photo-degradation (McMullen, 1996). For some herbicides such as cell membrane disrupters, which are contact herbicides, light is needed for activation to generate lethal symptoms in the affected plants (Wright et al., 1995). Paraquat is a contact herbicide belonging to this group which had decreased efficacy on velvetleaf and large crabgrass as UV radiation increased. The authors suggest a possible increase in the leaf wax content of these species at high UV radiation, resulting in lower absorption and efficacy (Wang et al., 2006).

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18.5 Concluding Remarks and Future Direction Several climate factors that can influence weed growth and herbicide efficacy have been presented. The projected increase in CO2 levels and elevated temperatures will have a direct impact on weeds. Changes in future climate is expected to make some weeds more aggressive and tolerant to herbicide applications besides directly influencing herbicidal properties and its absorption and translocation within plants. In addition, climate change factors may lead to significant changes in the weed distribution patterns and cause shifts in the composition of weed species. Based on the information from existing studies, proactive steps are needed to restrict the potential spread of invasive weeds to new areas in the impending climate change conditions. Seasonal precipitation and temperature fluctuations will strongly influence the timing of herbicide applications and other weed management decisions. Overall, research suggests that higher volumes of different types of herbicides may need to be used at frequent intervals. However, such applications will have negative impacts on environment and will not be sustainable and benefit agricultural production. Further, under such situations, a greater number of weeds may evolve herbicide resistance at a faster rate, creating further challenges for weed management. This projected scenario is of major concern and will require extensive research to understand this delicate balance in using herbicides for weed control in future climates and environmental sustainability. High priority should be given for research on a critical case-by-case analysis of climate change impacts on different crop-weed competition at multiple locations with diversified cropping systems. Comprehensive research efforts that include ecological, physiological, and molecular analyses are needed to study the interactive effects of different climate variables on plant growth and herbicide performance rather than basing conclusions from single factor experiments. There is a strong need for research on development of integrated and more sustainable weed management practices in current and future climates for minimizing risk of weeds, safeguarding the environment, and finding sustainable practices.

Acknowledgments We thank the Department of Agronomy for supporting the Weed Physiology program. This manuscript is approved for publication as Kansas Agricultural Experiment Station Contribution No. 16-188-B.

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19 Farmers’ Knowledge and Adaptation to Climate Change to Ensure Food Security Lois Wright Morton Department of Sociology, Iowa State University, Ames, Iowa

19.1 Farmers and Climate Change One of the greatest challenges to local and global food security is the impact that an increasingly variable climate has on agricultural animal and crop productivity and soil and water resources. Farmer willingness and capacity to re-evaluate their systems of farming and continuously adapt will affect how well we are able to meet this challenge (Morton, 2014a). A number of social and economic factors influence farmer motivation and ability to address extreme weather and climate uncertainty. These include individual and collective community experiences and indigenous knowledge about climate and their agroecosystems, values and beliefs, social networks, access to scientific knowledge and technologies, policies and institutional support (Morton and Rudel, 2014). Patterns of adaptation to climate change vary greatly from modern to subsistence farming systems and among scales of agriculture. These variations are evident within and among developed, developing, and underdeveloped countries reflecting huge differences in experiences and knowledge, in individual and institutional capacities to manage, and in decisions to develop coping strategies (or not). High levels of poverty, limited resources, ecosystem degradation, social and political conflicts, and weak institutions plague many rural communities especially (but not limited to) those in underdeveloped countries, amplifying the impacts of climate change (Hisali et al., 2011; Morton and Rudel, 2014). Food security at the micro household and village levels as well as for many regions and nation-states is a major concern worldwide. Further, loss and degradation of agricultural soil and water assets due to increasing extremes in precipitation affect both rainfed and irrigated agriculture, threatening capacities to sustainably continue to feed growing populations (Melillo et al., 2014; Sjogersten et al., 2013). Understanding how farmers experience and make sense of climate is key to developing on-farm, watershed level, regional, and global strategies to ensure agricultural productivity, long term integrity of soil and water assets, and resilience of rural landscapes and livelihoods. Climate and weather are experienced and understood locally. It is through weather that the farming community has a “…daily, personal and visceral encounter with climate. The seasonal ritual of planting, harvesting and cultivating the farm create a climate imaginary based on the structure of the agrarian year. Farmers Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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notice when the weather and the micro-climate of their farm changes, discerning rather than recording or quantifying changes in temperature, precipitation and the onset of the seasons” (Geoghegan and Leyson, 2012:58). The diverse spatial geographies in which climate change manifests itself implies that the relevant responses to the adverse impacts (as well as the opportunities) arising from climate change tend to be context specific and highly localized (Hisali et al., 2011). Research on human–agroecosystem processes and relationships is limited and there are more questions than answers. Social scientists are exploring farmers’ beliefs, perceptions, past experiences, and current practices to discover patterns of adaptation and the narratives farmers are using to interpret and give meaning to their farming practices and climate impacts on their immediate and the larger environment. In this chapter research on farmers’ perspectives on climate change, experiences with extreme weather and perceived risks, and confidence they have in technologies and their own skills are presented. Despite differential impacts of climate and weather on geographies around the world and substantial differences in scale of agriculture, farming practices, cultural patterns, and resources, research on farmers and climate change reveal a number of common themes. First, the experience of weather and climate is local and specific to each farm enterprise (Hisali et al., 2011; Basannagari and Kala, 2013; Sjogersten et al., 2013; Morton, 2014a; Morton et al., 2015). Secondly, farmers (as do all humans) give preference to intuitive and experiential information processing over analytical and abstract information (Slovic, 2009; Burns and Slovic, 2012; van der Linder, 2015). Third, the linking of local indigenous knowledge to scientific information is central to the creation of new knowledge that farmers trust and are willing to apply as they consider whether and how to adapt (Wolf et al., 2013; Wike and Morton, 2015a). Fourth, water and soil resources are deeply affected by climate variability and their degradation can be accelerated or reduced by management practices and changes in crops (Hatfield and Morton, 2013; Olson and Morton, 2012; Olson et al., 2015). Fifth, conservation and adaptive management programs and policies must be flexible so that farmers can tailor new science and technologies to their own local conditions (Seo and Mendlsohn, 2008; Seo, 2010; Arbuckle et al., 2014). This suggests research that examines a suite of possible management practices, crop responses to too much or too little precipitation and temperature variations, and an increase in crop choices will be valuable resources in support of adaptation. Sixth, one-crop farms and regions seem to be most vulnerable to variable conditions (Sjogersten et al., 2013). A number of studies find that diversified agricultural enterprises and regions may have greater capacity to better manage uncertainty and risks over time (Seo and Mendlsohn, 2008; Seo, 2010; Sjogersten et al., 2013). Case studies from around the world help us to better understand how farmers are experiencing and view climate change; how they individually and collectively value the water, soil and natural resources that sustain their way of life; how they are changing (or not) their management practices, and how they view the future of continuing to farm the land. There are many reasons why it matters how farmers view climate change and how/whether they respond to a changing climate. Food and water security are essential to human survival and capacity to thrive (Morton, 2014a, b). Climate and weather have consequences for food security and employment, affecting crop yields, food prices, and the value chain of food processing, storage, transportation, and retailing. Availability and distribution of food and water affect population migration and settlement patterns,

19.2 Knowledge About Climate

economic and political stability, and social health and well-being. On a very personal scale, managing the land, farming and food production are not just about livelihoods, but also individual and cultural identities that ensure people of rural places survive, thrive, and have capacity to plan forward into the future (Wolf et al., 2013).

19.2 Knowledge About Climate Temperature change, or global warming, is what people most commonly associate with climate change. IPCC scientists report that the numbers of cold days and nights have decreased and numbers of warm days and nights have increased on a global scale (IPCC, 2014). The United States (US) 3rd National Climate Assessment presents scientific assessments that the US average temperature has increased by 1.3∘ F to 1.9∘ F since record keeping began in 1895 (Melillo et al., 2014). Yet many farmers in the Midwestern US have commented, “Our summers haven’t gotten any hotter from what I’ve been able to see.” And they would be absolutely correct! Midwestern US temperatures have been quite different in terms of summer warming patterns compared to the rest of the country. The Southeastern US extending up into the Midwest is one of the only land areas on Earth that hasn’t warmed appreciably over the past century. Global and even statistical averages are only averages which mask individual observations. California farmers in western US who have experienced higher temperatures and multiyear drought are adapting to reduced water availability. However, a 2012 study finds that 71% of California farmers are unconvinced that climate change poses more risks than benefits to agriculture in their county (Prokopy et al., 2015a). Experiences with increased temperatures and changes in precipitation do not automatically lead to perceptions of risk and vulnerability and adaptive management. US farmers are not alone in their mixed reviews and skeptical approach to climate change and what it might mean for agriculture. Farmers in dryland north Shaanxi and Ningxia (China) perceptions of climate change and levels of anxiety to these changes vary by region based on aridity. In highly arid Yanchi County, 73% of farmers report they have noticed changes in climate in their lifetime and 45% were very concerned (Sjogersten et al., 2013). However, in a less arid, wetter region of China, 66% farmers reported they noticed recent changes in their climate but were generally unconcerned and thought these changes had no impact on their farming. In North Central Namibia (Africa) farmers have faced highly variable and an uncertain climate for hundreds of years and farm with the expectation that their climate will continually change. Over time these Namibia farmers have used their local knowledge to construct a land classification system to decide the type of crop to plant and where based on expected conditions in a given growing season (Newsham and Thomas, 2011). Scientists are discovering this indigenous classification system has permitted farmers to build an enduring resilience to variability in their local climate. A farmer from Amstetten, Austria listening to a preliminary forecast of 2040 average maize yields decreasing up to 20% because of changes in precipitation and extreme weather events says, “I would rather trust my own experience than any such forecast” (Schiemeir, 2015). Local weather and climate vary by geography—latitude and longitude–and microclimate conditions are what farmers experience and use to gauge how “real” climate change is and how they should respond, if at all.

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19.3 Weather and Climate Weather is the temperature, wind, cloudiness, precipitation, and humidity at a given point in time at a specific location. Climate refers to average weather conditions in a specific location over long periods of time. Farmers don’t directly experience global warming, they experience local and regional temperatures not the global average (Sarewitz and Pielke, 2000; Geoghegan and Leyson, 2012). Climate science gathers and analyzes many kinds of weather data over long periods of time to understand multi-year, multi-decade patterns. Discovery of climatic changes are analytical and statistical in nature (Wilke and Morton, 2015a,b). While climate patterns are not readily apparent to the non-scientist, extreme weather events, disorderly seasons, and changes in the growth cycles of flora and fauna are often visible and intuitive to those who are observant (Geoghegan and Leyson, 2012; Slovic, 2009). Research indicates that to some extent people are able to accurately detect broad changes in local weather such as seasonal precipitation and temperatures (Geoghegan and Leyson, 2012; Basannagari and Kala, 2013; van der Linder et al., 2015). Although awareness of weather is common, there is mounting evidence that most people regard changes in climate as psychologically distant and non-urgent (van der Linden et al., 2015). Furthermore, farmers in many regions of the world are even more skeptical than the general public about the immediate risk of climate change. This does not mean farmers are not intimately aware of the environment around them. Local knowledge is constructed from everyday encounters with weather and the land in the way it is felt and observed (Geoghegan and Leyson, 2012). Farmers form and accumulate knowledge about local changes on their landscape and on their farm by observing the weather, animals and plants over the time span of a few years or decades. It is these observations that help them make sense of their own environment in the context of their farming operation. How this information is synthesized affects how these observations are translated into information that can be used to develop a set of practices (e.g. crop selection, input timing and crop harvesting, planning for wet seasons and drought) (Geoghegan and Leyson, 2012; Morton, 2014a). Farmers around the world are aware of weather and climate differently and interpret how they should respond based on their geographies and agricultural systems. Shortand long-term weather experiences, historical narratives, and knowledge of their effects on their topography, soils and production systems are factored into decisions about workloads, available labor, markets for products, skills and the range of alternative solutions available to adapt to changing conditions. Farming is complex and variability in weather extremes often drives concerns and decision-making. For example, heavy rains and an intemperate winter can stress housing and feeding of animals requiring immediate action to protect animal safety, health and well-being. In the longer term, trampling of wet soil by cattle leads to damaged vegetation, soil erosion and compaction, an immediate and future problem on productivity of fields that are constantly wet. Even within the same region farmers often make sense of their climate differently. In a study by Basannagari and Kala (2013), Himalayan (India) apple farmers perceived the effects of climate change along an altitudinal gradient. The majority of apple farmers at all elevation ranges (low hills 3000m) reported an increase in atmospheric temperature and decrease in snowfall. Low hill farmers (72%) thought this increase in temperature was responsible for decline in fruit

19.4 Values and Beliefs About Climate Change

size and quality. However, 35% of high hill and 30% of mid hill farmers’ perceived frost as the major cause for damage to apples whereas low hills farmers (24%) viewed hailstorm as the major issue. All farmers admitted delaying apple harvests and experienced decreased quality affects because of weather. However, mid hills farmers reported apple scab and low hills farmers considered pest attacks on apple crops as the indicator which made climate change apparent to them. Farmers in the Nile Basin of Ethiopia have observed increasing temperature over the past 20 years; and 53% have observed decreasing rainfall (Deressa et al., 2009). Chinese research in7? dryland north Shaanxi and Ningxia revealed profound variation in knowledge about climate change, commodity prices, and social change which influenced lives and decisions about their futures (Sjogersten et al., 2013). North Central Namibia (Africa) local knowledge about their agroecological system was found to be evenly distributed among men and women (Newsham and Thomas, 2011). Understanding local agroecological dynamics allowed farmers to adapt crop-livestock strategies to as much as a 40-50% variation in annual rainfall. This study revealed a division of expertise and labor in agriculture, with men tending the livestock and women cultivating crops. This gender specialization and cultural norms make women more vulnerable to crop failure than men. Cattle are a source of wealth, providing food security and access to cash. Widows who lose cattle to relatives when their husbands die have a greatly reduced household wealth and food sources and decreased flexibility when crop yields are reduced. Wealth, farm size and a variety of different land units (different soil types and position in the landscape) within a single farm were found to be associated with Namibian farmer flexibility to tailor growing strategies to fit with weather conditions of any given growing season (Newsham and Thomas, 2011). Farmers in developed countries also are observing variable and uncertain weather conditions. A US Midwest survey of almost 5000 farmers in 11 states found that 74% of farmers reported experiencing problems with saturated soils or ponding in the last five years (2008-2011) (Arbuckle et al., 2014 JSWC). A much lower percentage had experienced stream or river flooding on their lands (37%), significant soil erosion (39%), or drought (30%). And about 56% were concerned about longer dry periods and drought in the future and 51% were concerned about increased heat pressure on their maize and soybean crops.

19.4 Values and Beliefs About Climate Change A growing body of literature finds that farmers’ strategic responses to external change such as climate is not entirely explained by profit-maximization considerations but also by attitudes, values, beliefs, and social identities (Arbuckle et al., 2013a,b; Arbuckle, Morton and Hobbs, 2015; Wheeler et al., 2013; McGuire et al., 2013, 2015). These individual and social characteristics are often associated with how experiences and knowledge of agroecosystems and climate are framed. The interpretation and integration of these experiences and knowledge with external scientific knowledge and technologies seem to influence adaptive management behaviors (Wolf et al. 2013; Wheeler et al., 2013; McGuire et al., 2013, 2015). Values are enduring beliefs about the world and how it works that influence attitudes and personally or socially preferable actions and behaviors. Although there are many definitions of values, all conceptions

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include i) beliefs ii) about desirable end states or behaviors iii) that transcend specific situations iv) are used to guide evaluation of behaviors and events and v) are ordered by relative importance (Wolf et al., 2013). Values and beliefs are part of how farmers define their farmer role in society, that is, they underlie the prioritization of characteristics that are expressed which identify the farmer as a unique person (McGuire et al., 2015). In the US, many farmers express their identities by claims they feed the world and/or are good stewards of the land. Research has shown that individual farmers have several identities which are activated and given priority by different experiences; which can lead to a reordering of importance of beliefs and values (McGuire et al., 2015; Wolf et al., 2013). In this context, farmer values and beliefs about climate, farming, and agroecological systems can influence whether and how they respond to climate change. Social science research that connects values and beliefs to farming systems and climate has led to mixed findings and is only beginning to understand how beliefs about climate change affect agricultural adaptive management. Some types of adaptation seem to be occurring without engaging beliefs about climate change causality (Wheeler et al., 2013; Arbuckle et al., 2015). Adaptation can range from minor adjustments such as changing planting dates or fertilizer rates to transformation of farmland into an entirely different land use (e.g. reservoirs, wetlands, trees, development). One might speculate that incremental adaption is a short-term problem solving response quite different from transformational adaptation that requires a higher level of decision-making and more active engagement of values and beliefs. A look at what farmers from different parts of the world believe about climate change offers insights into how farmers are framing the global and local issue of climate change.

19.5 Farmer Climate Beliefs Australia has been on the front lines of experiencing and adapting to climate change (Wheeler et al., 2013). Yet, Australian farmers are far more skeptical than the general Australian public (77% in 2010) with different studies reporting from 25% (2009) to 55% (2008) of farmers believing that climate change is occurring. Some research finds that farmers who are convinced that climate change is occurring (without regard to causality) are more likely to plan on adapting (Wheeler et al., 2013). However, these adaptations are more likely to be accommodations or incremental adjustments rather than transformational. Other research suggests that believing climate change is occurring was a more important factor in driving transformational change rather than incremental adaptation (Park et al., 2012). Younger Australian farmers, farmers that are more productive, have identified successors and are more innovative traditional and/or environmentally focused farmers were found to more likely incrementally adapt (Wheeler et al., 2013). A cross national comparison of beliefs in high income countries (Scotland, US, Australia and New Zealand) between 2010–2012 reveals that over half (ranging from 51% to 68%) of farmers at six study sites believed that the climate is changing (Prokopy et al., 2015a). However, scientists found a wide range of beliefs regarding causality of climate change. Only in the Australian site did a majority (59%) of farmers believe that climate change is anthropogenic. The Scotland site had the lowest percent of farmers (25%) that believed human activities were a cause of climate change compared to the

19.5 Farmer Climate Beliefs

other sites (California (35%), US Midwest (41%), and two New Zealand sites (46%; 37%)). The majority of farmers in these industrialized agricultural systems did not believe that climate change is a threat to local agriculture (US Midwest 78%; California 71%; New Zealand-Marlborough 68%; Australia 60%; New Zealand Hawkes Bay 59%; and Scotland 55%). Even within a particular region there can be significant variations in climate causality beliefs among agricultural scientists, climatologists, extension educators, agricultural advisors and farmers (Prokopy et al., 2015b). Over half of agricultural scientists (50–67%) and climatologists (53%) in the US Midwest (2011–2012) reported they believed that climate change is caused mostly by human activities. In contrast about 19% of extension educators, 12% of agricultural advisors, and 8% of farmers thought climate change was primarily caused by humans. Extension and crop advisors are often the intermediary information sources that bridge science and practical applications to farmers. It is noteworthy that these intermediaries are more closely aligned in their perceptions of climate change causality with farmers they work with rather than the agricultural science community in their universities where they receive their training and information. Chinese farmers in dryland north Shaanxi and Ningxis (China) overwhelming accept that their climate and environment is changing (Sjogersten et al., 2013). They perceived that their climate has become generally warmer (hotter summer with less cold winters), summers drier, that their water table has fallen, and biodiversity much reduced. These dryland north China farmers’ perceptions of climate change were linked to microclimate aridity levels in their area. In areas of higher aridity, 73% farmers said they noted changes in their climate and 45% percent were very concerned about perceived increase in drought. Some of these farmers had changed crops and others were questioning the long-term viability of continuing to farm in the area. However, 66% of Chinese farmers in a less arid part of the region perceived recent changes in climate but were generally unconcerned about climate change and reported no impacts on their farming practices. Similarly, in another part of the region, 28% of farmers reported drier conditions and warmer winters but were generally not concerned. Northern China livestock farmers seemed to accept the new norm that water is in short supply and they must work with what they have. This was in contrast to farmers in southern region who were just recently becoming concerned about falling precipitation rates and rising temperatures. Some farmers looked on the positive side by noting that reduced rainfall could lead to less soil erosion (Sjogersten et al., 2013). A 2012 survey of almost 5000 famers in a region of the US that produces more than half of the nation’s maize and soybean crop revealed that 66% of farmers believed climate change is occurring (Arbuckle et al., 2013a, 2015). However, 31% of farmers were uncertain and 3.5% did not believe that climate change is occurring. While most of these Midwestern farmers perceived that the climate was changing, very few believed it was mostly anthropogenic (8%) and about 1/3 were willing to concede it was equally from human and natural causes. A quarter believed climate change was mostly natural. Belief in human causality was more likely to be associated with higher levels of concern about longer dry periods and drought (66–65%), increased heat stress on crops (60–62%), more frequent extreme rains (60–57%) and increases in saturated soils/ponding (51–47%). This compares to one-third of farmers who were uncertain about the cause of climate change or believed there was insufficient evidence

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and reported low levels of concern about longer dry periods and drought (52%), increased heat stress on crops (45%), more frequent extreme rains (44%) and increases in saturated soils/ponding (38%). In general farmers around the world seem to recognize that their weather patterns are changing. However, much of the research on farmer values and beliefs seems to find that a changing climate is not necessarily perceived as a risk to agriculture nor seen as a reason to adapt or mitigate. Findings are mixed as to the roles religious beliefs, identity, a valued lifestyle and social values play in shaping perceptions of risk and vulnerability (Wolf et al., 2013; Arbuckle et al., 2015). There is a need for additional benchmark and follow-up studies on farmer beliefs and values to discover how enduring beliefs affect social norms, identity, worldviews and lifestyle preferences that influence adaptation and mitigation efforts. The activation of values has been found to influence perceptions and interpretations of situations that in turn lead to planned actions (Wolf et al., 2014). This suggests that perceptions of vulnerability can be understood as shaped by interior and subjective assessments of risk (Wolf et al., 2014) as well as external experiences and observations with weather and climate. Those farmers most concerned about climate risks are likely to be experiencing aridity and drought. It is not known to what extent increased farmer hazard experiences and observations about climate conditions over time could realign beliefs and values about climate and agro ecosystem relationships. Very few studies ask about farmer causality of climate beliefs. Longitudinal studies could inform the enduring nature and directionality of climate beliefs and whether the intensification of weather experiences increase adaptation responses.

19.6 Vulnerability, Experiences of Risk, Concern About Hazards and confidence Exposure to extreme weather events and climate conditions as well as attribution of the significance of local exposure influence perceptions of risk and vulnerability, concerns about future conditions, and confidence in addressing variability (Howe et al., 2014). Vulnerability to climate change can be defined as the degree of inability to cope with adverse climate effects as a function of exposure, sensitivity and adaptive capacity (Below et al., 2012). Exposure, sensitivity and adaptive capacity are linked to livelihoods and economic risk in much of the climate change literature (Wolf et al., 2013; Howe et al., 2014). Exposure represents the occurrence of a climate hazard; and sensitivity refers to the magnitude of the effect. Howe et al. (2014) report that rural Indian respondents were more sensitive to actual local changes in precipitation than urban respondents. Further, they find a pattern of higher social vulnerability associated with perceptions of deceasing rainfall including low perceived adaptive capacity and greater food and livelihood dependence on local weather (Howe et al., 2014). Estimates of climate sensitivity of agriculture in two developing countries, Brazil and India, are measured by Sanghi and Mendelsohn (2008) by examining how net farm income and property values vary with climate and farmer reactions and adaptations. Drought and pest and disease outbreaks affect agricultural production in both these countries with large impacts on the volatility of global markets and food prices. Predictions of future consequences using alternative climate scenarios show annual damages in Brazil between 1% and 39% and; 4% and 26% in India. Models show that

19.6 Vulnerability, Experiences of Risk, Concern About Hazards and confidence

differences in farmer net revenue reduction (7–17% in India and 10–30% in Brazil) can be explained by adaptation. This work posits that farmers make planting adjustments in suboptimal climate conditions to increase net revenue and the combination of adjustments leads to net revenue reductions that are smaller than predicted reductions in yields. For example, climate sensitivities are thought to be influenced by irrigation making India slightly less sensitive than Brazil because it has more irrigated farmlands (Sanghi and Mendelsohn, 2008). Researchers also suggest some of the effect may be offset by carbon fertilization but note that climate-induced extreme weather events are not factored into these models. Crop switching is an adaptation strategy that reduces sensitivity to precipitation and temperatures and vulnerability to reduced yields and income. Research in seven South American countries modeled 949 farmer adjustments to climate and finds that farmers move away from crops with low yields and substitute new crops that are more likely to perform better (Seo and Mendelsohn 2008). In South America these farmers choose fruits and vegetables in warmer locations and wheat and potatoes in cooler places. Farms located in wetter regions were more likely to grow rice, fruits, potatoes, and squash; with maize and wheat grown in dryer locations. The probability of selecting soybean and potatoes declines the wetter the farm. However, maize which is grown throughout South America, is more of a generalist and does not seem to be sensitive to climate conditions. This may be because of there are a large number of maize varieties that grow well in a many different climate zones. Agriculture is the mainstay of economies in most African countries providing employment to 70% of the population on average (Hisali et al., 2011). Research on African farmers ‘economic vulnerability examines net revenues from 9000 farm surveys in 10 countries (Niger, Burkina Faso, Senegal, Ghana, Cameroon, Kenya, Ethiopia, South Africa, Zambia, Egypt). Integrated crop-livestock, livestock-only, and crops-only systems are compared in light of current climate and future (2060) predictions (Seo, 2010). African livestock net revenues are highly sensitive to climate variations and farmers select primary livestock species based on local climate conditions. African farmers in this study preferred a mixed farm over a specialized farm when the climate is hot. In the short term, models of increasing temperatures found that the net revenues of specialized crop and mixed farms decreased while specialized livestock farm net revenues increased. In wet climates, farmers were projected to more often choose crops over livestock; and net revenue of crops-only farms increased with higher precipitation while mixed farms and livestock-only farms decreased. In the long term, models show integrated farms more likely to be profitable over specialized farms a half century into the future with climate impacts ranging from 9% loss to 27% gain depending on climate scenarios (Seo, 2010). These climate sensitivity studies suggest that estimates of climate economic impacts will be more accurate if they reflect not just changes in yields per crop but also crop switching, changes in farm systems and adaptive management strategies. Seo (2010) models find that African crop-only farms could lose up to 75% of their annual income with significant implications for food security. The vulnerability of one crop only farms is a concern not only in Africa but also China. The increasing specialization of high value crops under the Chinese ‘one village, one crop’ policy has increased farm income over that last decade in some regions (Sjogersten et al., 2013). However, farmers report two major concerns related to changing climate conditions and this

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policy: many of these cash crops have high water requirements and household incomes are dependent on one crop. Shifts in timing and frequency of precipitation as well as the increasingly silted Yellow River which limits irrigation capacities make farmer incomes vulnerable to water availability. Further, specialization often means that households do not grow their own food but must purchase family food on the market. This policy leaves some farming communities vulnerable to food insecurity when pest and diseases destroy cash crops, water availability and access are limited, and/or market saturation reduces crop prices below input costs and decrease farmer net revenues. Chinese farmers in this study recognized the increased long-term vulnerability of the one crop policy and expressed concern for the limited agrodiversity in their villages (Sjogersten et al., 2013).

19.7 Climate Related Hazards More than three quarters of the disasters that have occurred globally over the past decade have been triggered by climate and climate related hazards such as drought, storms, and floods (Gopalakrishnam, 2013). Flooding of agricultural lands along river systems are often due to prolonged high flood stages and unusually large runoff in systems cut off from historical flood plains by levees and floodwalls (Olson et al., 2016; Morton and Olson, 2014). The 2008 IPCC report concluded that current water management practices may not be robust enough to cope with impacts of climate change and draws specific attention to flooding risk in agriculture and ecological systems (Romero-Lankao et al., 2014). This is illustrated by shrimp farmers on the east coast of India who are highly vulnerable to cyclones, floods, sea-level rise and change in monsoon patterns (Nagothu et al., 2012). Shrimp farmers rated floods and cyclones as the highest risks associated with climate and weather they were concerned about. Their experiences with changing weather and climate have been quite dramatic and they report one of their greatest needs is for advance warning on cyclones and floods. Levee breaching, flooding of agricultural fields, soil losses, and gully formation that take fields out of production are found along the US Mississippi River and its tributaries as a result of extreme precipitation in 2008, 2009, and 2011 (Olson, 2009; Olson and Morton, 2012; Olson et al., 2015). The 2011 Len Small levee breach in southern Illinois (US) flooded farmland in much of Alexander County (Olson and Morton, 2013). Illinois agricultural statistics recorded 1800 fewer ha (4500 ac) of maize and 2600 less ha (6500 ac) of soybeans were harvested in 2011 compared to 2010. This resulted in production losses with 1570000 bu of maize produced in 2010 dropping to 710000 bu in 2011 and the 1200000 bu 2010 soybean production decreasing to 865000 bu due to flooding, crop, and soil damage. In southeast Missouri, the induced breaching and floodway activation by US Army Corps of Engineers in May, 2011 to manage Mississippi river flooding and downriver breaching resulted insubstantial crop losses in much of the area. A 31% change in land use to wetlands and 44% loss of agricultural productivity in one 195 ac (78 ha) soybean field was lost as of 2013 due to erosion phase changes and reshaping of the gully side slopes and soil reconstruction (Olson et al., 2015). Additional efforts in 2014 affected the land use and restored some of the soil productivity and yield capacity of the tract to 70%, but there was still a 30% permanent productivity loss.

19.7 Climate Related Hazards

Although flooding can do a great deal of damage to crops and farmland, farmers often perceive that drought is more problematic (Newsham and Thomas, 2011; Arbuckle et al., 2013). Water scarcity and security is a local and global problem and there are very few adaptive measures available to address multi-year drought (Morton, 2014b). Water limitations in dryland northern China are the biggest constraints on crop production along with access to affordable fertilizer. Aridity and increasing salinity are limiting factors for Ningxia (China) farmers with implications for whether farming can even be continued in this region (Sjogersten et al., 2013). Namibian farmers after two years of floods in 2008 and 2009 worried that drought was next and were concerned increased frequency of dry years could make crop farming impossible (Newsham and Thomas, 2011). Further, many farmers had lost confidence in the accuracy of their early warning ecological indicators for wet or dry rainy seasons; and lamented that TV and radio weather forecasts were too general for use in cropping and livestock decisions. In Uganda (Africa) up to 34% of crop damage has been estimated to be caused by climate induced stimuli such as rainfall shortage, crop diseases and insect damage. Crop pests and disease are major constraints to agricultural production according to Uganda community leader interviews in the 2005–6 national household survey (Hisali et al., 2011). In the US Great Lakes region, fruit, vegetable and specialty crop growers report that their greatest vulnerability to a changing climate is pest and disease (Johnson and Morton, 2015). Perceptions of vulnerability and risk, beliefs about climate, personal experiences with different climate hazards, and confidence in capacity to adjust to expected and unexpected change can vary a great deal among farmers. Research on almost 5000 US Midwest farmers reveals heterogeneous perspectives and support for adaptive management (Arbuckle et al., 2014). A latent class analysis based on responses to a farmer survey in 2012 identified six distinct classes of farmers (Figure 19.1). These six classes were labeled: the concerned (14%), the uneasy (25%), the uncertain (25%), the unconcerned (13%), the confident (18%), and the detached (5%). Only 18% of farmers were highly confident that some combination of practices, knowledge and technical skills, financial capacities, human ingenuity, and government programs such as crop insurance would reduce threats to the viability of their farm enterprise. About 60% of farmers claimed some level of “efficacy” or confidence (Figure 19.1) that they will be able to deal with increases in weather variability. Although, these findings are specific to US maize and soybean growers in 2012, they offer a visual representation of the variations in farmers’ beliefs, experiences, perceptions of risk, and efficacy associated with support for adaption. Much more work is needed to understand what the distribution of these categories of farmers might look like in developed, developing and underdeveloped countries with different climate hazards, geographic and cultural contexts. It is also not known how differences in farm systems such as specialty crops, livestock (or even type of livestock), and mixed systems or scale of the farm enterprise would affect the distributions of these categories in a region or nation-state. Hisali et al. (2011) report that farmers in rural Zimbabwe did not move to adaption because they perceived the risk, as well as their capacity to adapt to be rather low. More international research is needed to better understand the relationships among beliefs, hazard vulnerability, risk perceptions, efficacy, and support for adaption.

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Figure 19.1 US Midwest farmers have different beliefs, risk perceptions, hazard experiences, confidence (efficacy) and support for action in response changing climate conditions. Radar charts show class rank for each category of variables by standardized mean values: (a) class 1, the concerned (14%); (b) class 2, the uneasy (25%), (c) class 3, the uncertain (25%); (d) class 4, the unconcerned (13%), (e) class 5, the confident (18%), and (f ) class 6, the detached (5%). Source: Reprinted with permission: Arbuckle, J.G., Hobbs, J., Loy, L.W., et al. (2014). Understanding farmer perspectives on climate change: Toward effective communication strategies for adaptation and mitigation in the Corn Belt. Journal of Soil and Water Conservation, Nov/Dec 69:6:505–516..

19.8 Adaptation Factors Adaptations to climate change are adjustments in natural and human systems made in response to actual or expected climatic stimuli or their effects (Deressa et al., 2009). The intent of adaption is to moderate harm or exploit beneficial opportunities.

19.8 Adaptation Factors

Adaptation can be classified from no action to incremental adaption to transformational actions (Walthall et al., 2012; Wheeler et al., 2013; Melillo et al., 2014). No adaption responses are essentially current status quo management, with farmers making no adjustments or very limited adjustments in response to climatic conditions. Incremental adaption can run from expansive actions designed to expand infrastructure and production to capture economies of scale, to accommodating change such as changing water management practices, to reducing the farm effort, investments and resource ownership. Incremental adaption usually involves increased investments in time, equipment, and changes in management but seldom entail major decision-making. Transformational actions can involve changing land use such as major shifts from agriculture to wetlands or forests, or discontinued farming. Transformation occurs when economic, ecological or social conditions make the current system untenable and represent a major change in livelihood, location and/or identity (Wheeler et al., 2013). The decision to adjust or substantively adapt agriculture practices in response to changes in precipitation, temperatures, humidity and extreme weather events are affected by institutional infrastructures and policies at national and district levels; market signals for land, agricultural raw commodities and finished products; social norms and relationships; individual/household wealth, skills, information and technology resources and perceptions of the urgency and critical nature (risk) associated with doing something versus doing nothing (Below et al. 2012). Below et al. (2012) in their work in Tanzania find that rural infrastructure (primarily rural road construction) efficient use of inputs, women’s education level, social capital, agricultural extension and micro credit access influenced adaptation. Australian accommodation strategies are primarily focused on improving irrigation infrastructure and management practices with emphasis on more water efficient crops (Wheeler et al., 2013). There is substantial evidence that farmers’ response to changing climate and choice of adaptation strategies entails more than net farm revenues. Social and environmental factors, public policies, technology development, matching scientific investigations with farmer needs, and expanded information and financial resources are all factors that have been found to influence farmer willingness and capacity to adapt. Other social and economic factors found to be significant are gender, age, wealth of head of household, farm ownership, household size, farmer’s current position in the life cycle, experience, education, health status, distance to markets, access to credit, availability of resources including extension as well as social capital (Hisail et al., 2011; Deressa et al., 2009). The asset value of livestock to the farm household is a widely recognized reason to keep livestock in African and other developing countries (Rufino et al., 2011). An important source of family wealth, livestock provide animal power, manure for soil fertility maintenance and a store of cash value (Deressa et al., 2009; Seo, 2010; Seo et al., 2010). Social capital represented by private social networks and information institutions have three distinct roles in adoption of the agricultural technologies. These networks are conduits for financial transfer, exchange of information about new technologies, and facilitation of cooperative collective efforts. In many developing countries agriculture is a main sector of the economy. Agriculture in Ethiopia represents 52% of GDP and 85% of foreign exchange earnings and employs about 80% of the population 2004) (Deressa et al., 2009). Research in the Nile Basin of Ethiopia finds farmer responses to climate change range from no adaption (42%), tree planting (21%), soil conservation (15%), change to different crop varieties

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(13%); change planting dates-early or later (5%) and irrigate (4%) (Deressa et al., 2009). Farmers who did not adapt offered a number of reasons: lack of information, lack of money, shortage of labor, shortage of land and poor potential for irrigation. Newsham and Thomas (2011) report short-term strategies to address food insecurity varied in undeveloped countries and were less effective as population density increased. These short-term coping strategies involved sharing food with family and neighbors, selling cattle, hunting wild animals, increasing consumption of hardier wild resources such as leaves, digging wells for water, applying for government assistance, and purchase of food to compensate for shortfall. Farming experience and membership in a shrimp farmer association had a significant influence in improving technical and economic efficiencies in India shrimp farmers adapting to climatic factors (Nagothu et al., 2012). Fuel used for electricity production and changes in shrimp feed are adaptive management efforts found to improve technical and economic efficiency. Larger Indian shrimp farmers (above 2ha) had more professional advisors and put in place management that increased production efficiencies (Nagothu et al., 2012). Electricity in some agricultural systems can make a big difference in productivity. Electricity increased farm profits of mixed farm and livestock-only farms but not cultivated crop farms in South America (Seo, 2010). Tropical underdeveloped nations are particularly vulnerable to climate impacts. Common adaptation strategies in Uganda were the utilization of improved crop varieties, shifts to crops more suited to climate conditions and diversification of the crop portfolio (Hisali et al., 2011). Seo (2010) finds that the ecological characteristics of place influence farmers’ systems of agriculture and selection of a specific livestock species or combination of species that suit the existing climate condition best. Almost 80% of Africa agricultural lands are grazing lands. In South America land use is four to eight times more likely to be pasture rather than cropland (Seo, 2010). South American farmers tend to favor beef cattle, Egyptians raise chickens, and West African farmers are more likely to raise goats and sheep since they endure heat better. Livestock consumption in developing countries is projected to increase about 40% in the next two decades offering important diversified markets. Surveys of 1300 farmers who own some livestock from seven South American countries find that climate and soil are major factors in choice of livestock (Seo et al., 2010). Summer temperatures affected choice of dairy cattle; winter precipitation affected the choice of cattle and sheep and; summer precipitation the choice of sheep. Temperature variability affected choice of beef cattle while precipitation influenced choice of sheep. As temperature increased farmers chose livestock over crops more often. As rainfall increased farmers initially adopted livestock but after rainfall passed 150mmper month, livestock adoption decreased (Seo et al., 2010).

19.9 Water is the Visible Face of Climate Securing water resources by addressing scarcity, access, and quality is a major ongoing effort in regions of the world experiencing aridity and drought (Wheeler et al., 2013; Morton, 2014b). Intra season as well as annual variations in the hydrological cycle marked by high increases of extreme rain events or decreased precipitation leading to drought have seen an increase in irrigation and drainage, sometimes in the same field. The timing, amount and intensity of precipitation during the growing season has large effects on whether a crop can be established, grow and develop, and reach its full grain

19.10 Making Sense of Climate: Local, Indigenous and Scientific knowledge

yield potential (Morton et al., 2015). Excess water or too little water compromises crop productivity and influences nutrient uptake or off-farm loss in runoff. Farmers in India who overcame flooding and cyclone events were those with the highest efficiency levels (Nagothu et al., 2012). In the Nile Basin of Ethiopia higher levels of precipitation appeared to decrease the likelihood of implementing new adaptation techniques. Increased precipitation seems to relax the constraints imposed by increased temperature on soil moisture and crop growth. Conversely decreases in precipitation significantly increased the likelihood of putting in place soil conservation practices, changing crop varieties, shifting planting dates and adding or increasing irrigation (Deressa et al., 2009). Investments in irrigation can buffer farmers from dependence on food aid in times of crop failure due to drought (Dresser et al. 2009). Australian farmers are responding to water scarcity by buying more land and water, increasing irrigated acres, changing crop mix and adopting more efficient water infrastructure (Wheeler et al., 2013). Morton et al. (2015) report US Midwest farmers experience with saturated soil was significantly associated with increased use of artificial drainage and less use of no-till, cover crops and planting on highly erodible land (HEL). Farmers in Midwest counties with a higher percent of soils considered marginal for row crops were more likely to use no-till, cover crops and increase planting on HEL. Farmers who sold their maize crop through multiple markets were more likely to have planted cover crops and planted on HEL. Iowa farmers’ trust in environmental or agricultural interest groups as sources of climate information, climate change beliefs, and perceptions of climate risk were found to be associated with support for adaptation and mitigation (Arbuckle et al. 2015). Beliefs about climate change causality varied with their trust in their social network. Those who trusted environmental interest groups were positively associated with climate causality beliefs and supported adaptation and mitigation. Those who trusted agricultural interest groups were less likely to engage their climate beliefs but moved directly to perceived risks and support for adaptation. Upper US Midwest maize farmers are most likely to use a suite of practices to help them better address management issues associated with too much water on the landscape (Morton et al. 2015). Households in developing countries often seek to reduce their vulnerability not by maximizing income but by diversifying their portfolio of capital assets so as to increase capacity to trade income for security (Below et al., 2012). Assumptions that a large number of effective and feasible practices are more effective than one or two in responding to climate variability needs to be carefully applied (Below et al., 2012). Farm size and wealth may be critical variables in which adaptive measures are best suited to meet economic, social, and ecological needs. In developing countries, a household which practices several adaptive practices on a very small scale may not be better adapted to climate than a household that uses one single effective practice to its full extent (Below et al., 2012)

19.10 Making Sense of Climate: Local, Indigenous and Scientific knowledge Adaptation derived from a combination of local, indigenous knowledge and scientific knowledge seems to create new knowledge that farmers more readily uptake (Newsham and Thomas, 2011; Wilke and Morton, 2015). What is considered successful

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and legitimate adaptation is determined in part by what farmers perceive to be worth achieving, protecting, and preserving. Definitions of successful and legitimate adaptive management responses hinge on farmers and their rural communities’ underlying values and objectives (Wolf et al., 2013). When Namibian farmers understand their agro ecosystem dynamics, they seemed to be better able to adapt cropping and livestock strategies to highly variable climatic conditions from one rainy season to the next (Newsham and Thomas, 2011). Northern dryland Chinese farmer adaption to new technologies depended on funding and expertise available to support changes in practices (Sjogersten et al., 2013). Chinese farmers consistently linked training with practical applications of knowledge and the importance of adaptations appropriate to their local context. Learning from neighbors was a key method of knowledge transfer with the Chinese village leader often viewed as a champion of farmer innovation (Sjogersten et al., 2013). Early adapters were those who had access to additional information and technical support as well as higher income to take advantage of government programs and funding schemes. Farmers around the world have different ways of knowing and different ways of framing personal, social and institutional information that affect their views of increasingly variable weather and how they ought to respond (or not). Climate change is “a reality, an agenda, a problem, a context, a narrative and a discourse” (Geoghegan and Leyson, 2012:58). Although climate change is one of the most important societal issues of the 21st century, farmers continue to be cautious about what it means and what they should do. Psychological science finds there are at least three human predispositions that explain this skepticism (van der Linder et al., 2015). First, the human brain privileges experience over analysis. Thus, personal experiences with local weather and climate are valued and used to guide decisions over scientific information that presents statistics and facts that do not reflect their own experiences. Second, people are social beings who respond to group norms. Personal beliefs and values often reflect the values, beliefs, attitudes and social norms of the local farm community. Farmer to farmer exchanges increase the speed of knowledge transfer and what is learned. Crop advisors and extension specialists that are trusted and respected in the community can increase adoption of new practices (Haigh et al., 2015; Prokopy et al., 2015b). Third, issues that are not visible or do not need immediate attention are out of sight and out of mind. Climate change happens over time, putting considerable psychological distance between today’s experiences with precipitation and temperatures and that of next year or 50 years into the future. When these predispositions are combined, local norms associated with agricultural practices which are generally focused on short-term rather than long-term privilege the current growing season over long-term weather patterns making climate less relevant. Weather is the phenomena which farmers use to narrate climate and the ways they might respond to what they have learned (Geoghegan and Leyson, 2012; Wilke and Morton, 2015a,b). Efforts to communicate climate science have been found to be most effective if the language focuses on weather and climate and the ways it may change and not insisting on particular beliefs about causality (Arbuckle et al., 2013b; Wilke and Morton, 2015a,b). This approach acknowledges understanding that climate change is conjoined with other kinds of knowledge about the local environment and farming, and allows different ways of knowing to be legitimate in the framing of climate change (Arbuckle et al., 2013b; Geoghegan and Leyson, 2012). The challenge is to

19.11 System Adaptation or Transformation

design strategies in support of local farmer adaptation through appropriate public policy, investment and collective actions so as to reduce the negative consequences of predicted future climate conditions (Hisali et al., 2011).

19.11 System Adaptation or Transformation While variations in climate and extreme weather events will continue to be experienced locally in different ways, there is strong evidence that future local and global climates will become increasingly uncertain and unpredictable in comparison to past years (Melillo et al., 2014; IPCC, 2014). Snowmelt-dominated watersheds are seeing shifts in seasonal runoff with more in winter. There is increased regional and seasonal variability in water resources and changes in pressures associated with weeds, diseases, and insect pest as well as the timing and coincidence of pollinator lifecycles. Prolonged exposure to extreme temperature increase production costs and loss of productivity in animal husbandry. These changes, some incremental press processes and some pulse events that transform through shocks will continue to affect the agro ecosystem and the human-social functions that are the foundation of food security (Morton and Rudel, 2014). Agricultural scientists, farmers, agribusiness, and policymakers are challenged to understand these patterns, adjust and adapt technologies as well as management practices, and develop appropriate public policies in timely ways. Weather and climate and their impacts on soil, water, and vegetation are central to agriculture everywhere. All successful farmers know the characteristics of the climate they live in and pay close attention to weather patterns as they make daily and longer-term decisions. Adaptive management responses can delay and reduce some of climate and variable weather impacts. Individual farmers and agricultural regions in many places have adapted in incremental ways to current changing conditions. Yet farmers in many parts of the world do not view their climate as changing sufficiently for them to substantially alter the way they currently manage their agricultural lands. Delayed or non-response by farmers to a changing climate presents a major threat to food production and food security long term. It is not known whether current rates of adaption and social-economic systems will keep pace with the rate of climate change in the coming decades. Changing climatic conditions are exposing farm households and their communities to ever increasing risk and threaten the resources of livelihoods around the world that depend on agriculture for both food security and income (Hisali et al., 2011). Poor farm households with limited knowledge and financial resources are highly vulnerable to food insecurity. Many contextual objective factors and subjective internal beliefs and perceptions of risk shape vulnerability and barriers to adaption. The challenge is to not replace a bottom up-extension and local knowledge with top down approaches that push for rapid modernization that displace local knowledge with technicians, at the cost of reducing farmers’ personal agro ecosystem knowledge and confidence (Newsham and Thomas, 2011). Traditional knowledge, land skills and codes of behavior based on values and historical experience and practice play roles in capacity and willingness to adapt. Scientific and indigenous knowledge as well as farmer and community values, beliefs and practices must be considered legitimate for adaption to happen. Food security and threats to livelihoods are tangible vulnerabilities. Loss of tradition, culture, and community

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unity that underpin food security are social, intangible, and subjective but emotionally real and implicit influences on behaviors and adaptation (Wolf et al., 2013). National and global climate change policies need to address these values explicitly if efforts for planned adaption are to be perceived as legitimate and effective by those affected. A number of research centers in Africa, South America, and Asia are linking research on crop varieties and management to local variations in culture, climate, traditional knowledge and practices to improve food security in their regions. CGIAR Consortium Research Centers such as CIAT (International Center for Tropical Agriculture), CIMMYT (International Maize and Wheat Improvement Center), ICRISAT (International Crops Research Institute for the Semi-Arid Tropics), ILRI (International Livestock Research Institute), and IITA(International Institute for Tropical Agriculture) are focused on equipping and providing access to rural poor farmers information, seeds, technologies, and technical support to reduce climate related crop failures and improve economic livelihoods. The CCAFS (CGIAR Research Program on Climate Change, Agriculture and Food Security) https://www.cgiar.org/.../climate-change-agricultureand-food-security is conducting gender analysis and research to discover mechanisms that would improve gender related acceptance and use of new information. The gender strategy initiative acknowledges the cultural variations among different rural peoples and provides tools and processes for each region to develop gender appropriate resources in conjunction with crop and livestock knowledge useful for effective adaptation to changing weather and climate conditions. A global effort to mobilize Climate Smart Agriculture (CSA) is being seeded by local NGOs that connect local farmers, farm organizations, agribusiness, academic institutions, seed companies, foundations, and other NGOs. Promotion of CSA is taking hold in many parts of the world, from Climate Smart Villages in developing countries to a newly formed North America Climate Smart Agriculture Alliance in the United States. In 2011, a Climate Smart Village project was launched involving 15 climate-smart villages in West and East Africa and South Asia; with more villages in Latin American and Southeast Asia added in recent years. The intent of this initiative is to leverage local values and indigenous knowledge with science and technology tools to help small holder farmers take practical steps to change their agricultural practices in ways that increase dependable flood supplies and improve livelihoods. Workshops and town hall meetings are a first step to getting local villagers involved. Partner organizations and researchers work side-by-side with villagers to provide valuable and essential resources to help the village identify appropriate and acceptable climate smart options for themselves. For example, in Kenya’s Lower Nyando valley farmers are experimenting with alley cropping of maize, sorghum and other cultivated crops planted between rows of multi-purpose trees (ccafs.cigar.org/climate-smart-villages). Processes are designed to be participatory and inclusive of women and vulnerable groups. A growing body of literature argues that trade policies have weakened agricultural capacity in developing countries. The push to sell produce on international markets ties livelihoods to highly volatile international food prices and can lead farmers to abandon crops better adapted to their local conditions in favor of cash crops (Newsham and Thomas, 2011). Farmers need accessible, affordable scientific information and technology resources to combine with their own knowledge. Context specific, real time advice will become even more important as farmers try to keep up with new weather patterns (Morton et al., 2015; Schiermeier, 2015). Global, national, and even regional forecasts

References

often do not reflect local conditions. “Agricultural forecasts are notoriously difficult because they face multiple tiers of uncertainty: in how climate will change regionally, in assumptions about what crops might be planted, in the availability of fertilizers and in economic projects” (Schiermeier, 2015:397). Global circulation models (GCM) have difficulty predicting precipitation on a country basis (Sanghi and Mendelsohn, 2008). Among farmers’ greatest needs is for downscaled, local forecasts to guide short and medium term decision-making. US and international social science findings suggest that farmers benefit when they have a variety of effective and feasible adaptive management practices appropriate to their locale and the farm enterprise from which to choose (Morton et al., 2015; Below et al., 2012). Much more research in this area is needed if we are to understand the motivations and abilities of farmers to adapt and the keystone factors that are driving capacity to change. There is also a great need for coupled human-agroecosystem research if we are to concurrently increase productivity and protect soil and water resources needed for future productivity. One of the big questions each agroecological region faces is will their incremental adjustments to current farming practices be sufficient to ensure long term agricultural system resilience under changing climate? Or will the necessary adaptations need to be much more significant to produce sufficient food for a rapidly increasing population? What is the appropriate mix among shifts to significantly different crops better suited to local climates, even more agricultural intensification, more narrow income distributions among populations, and transformation of the land uses? And what are the mechanisms and resources farmers, scientists, and policy makers need to continually assess and effectively adapt as conditions change? Transformations that lead to increased numbers of farmers leaving the land and exiting out of agriculture entirely may not solve the food security problem. Livelihood diversification away from agriculture could reduce food production and place many low-income households at risk of food insecurity. It may solve individual household income needs but increase dependence on markets and volatile food prices.

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Basannagari, B. and Kala, C.P. (2013). Climate change and apple farming in Indian Himalayas: a study of local perceptions and responses. PLoS ONE, 8(10): e77976. doi: 10.1371/journal.pone.0077976. Below, T.B, Mutabazi, K.D., Kirschke, D. et al. (2012). Can farmers’ adaption to climate change be explained by soico-economic household-level variables? Global Environmental Change 22: 223–235. Burns, W.J. and Slovic, P. (2012). Risk Perception and Behaviors: Anticipating and Responding to Crises, Risk Analysis 32 (4): 579–582. Deressa, T.T., Hassan, R.M., Ringler, C. et al. (2009). Determinants of farmers’ choice of adaptation methods to climate change in the Nile Basin of Ethiopia. Global Environmental Change 19: 248–255. Geoghegan, H. and Leyson, C. (2012). On climate change and cultural geography: farming on the Lizard Peninsula, Cornwall, UK. Climatic Change 113: 55–66. Gopalakrishnam, C. (2013). Water and Disasters: A Review and Analysis of Policy Aspects. International Journal of Water Resources Development 29: 250–271. Haigh, T., Morton, L.W., Prokopy, L.S. et al. (2015). Agricultural Advisors as Climate Information Intermediaries: Exploring Differences in Capacity to Communicate Climate Weather, Climate and Society 7 (1): 83–93. doi: 10.1175/WCAS-D-12-00036.1. Hatfield, J. and Morton, L.W. (2013) Chapter 2 Marginality Principle. Pp19–55.In: R. Lal and B.A. Stewart (Eds), Principles of Sustainable Soil Management in Agroecosystems. Advances in Soil Science. New York: Taylor & Francis, CRC Press. Hisali, E., Birungi, P., and Buyinza, F. (2011). Adaptation to climate change in Uganda: Evidence from micro level data. Global Environmental Change 21: 1245–1261. Howe, P.D., Thaker, J., and Leiserowitz, A. (2014). Public perceptions of rainfall change in India. Climatic Change 127: 211–225. Doi: 10.1007/s10584-014-1245-6. Johnson, A. and Morton, L.W. (2015) Midwest Climate and Specialty Crops: Specialty crop leader views and priorities for Midwest Specialty crops. Iowa State University, Department of Sociology Technical Report 1039. McGuire, J., Morton, L.W., and Cast, A. (2013). Reconstructing the Good Farmer Identity: Shifts in Farmer Identities and Farm Management Practices to Improve Water Quality. Agriculture and Human Values 30 (1): 57–69. doi: 10.1007/s10460-012-9381-y. McGuire, J., Morton, L.W., Cast, A., and Arbuckle, J.G. (2015). Farmer identities and responses to the social-biophysical environment. Rural Studies 39: 145–155. IPCC (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (ed. C.W. Team, R.K. Pachauri and L.A. Meyer). Geneva, Switzerland: IPCC 151pp. Melillo, J.M., Richmond, T.C., and Yohe, G.W. (eds) (2014). Highlights of Climate Change Impacts in the United States: The Third National Climate Assessment. Washington, DC.: US Global Change Research Program US Government Printing Office. Morton, L.W. (2014a). The science of variable climate and agroecosystem management. Journal of Soil and Water Conservation 69 (6): 2017A–212A. Morton, L.W. (2014b). Achieving water security in agriculture: the human factor. Agronomic Journal 106: 1–4. doi: 10.2134/agronj14.0039. Morton, L.W., Hobbs, J., Arbuckle, J., and Loy, A. (2015). Upper Midwest Climate Variations: Farmer Responses to Excess Water Risks. Journal Environmental Quality 44: 810–822. doi: 10.2134/jeq2014.08.0352.

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Morton, L.W. and Rudel, T. (2014). Impacts of climate change on people and communities of rural America. Chapter 9. In: Rural America in a Globalizing World (ed. C. Bailey, L. Jensen, and E. Ransom). Morgantown: West Virginia University Press. Morton, L.W. and Olson, K.R. (2014) Addressing soil degradation and flood risk decision making in levee protected agricultural lands under increasingly variable climate condition. Journal of Environmental Protection, Published online September 2014. Vol. 5:1220–1234dx.doi.org/10.4236/jep.2014.512117 Nagothu, U.S., Muralidhar, M., Kumaran, M. et al. (2012). Climate change and shrimp farming in Andhra Pradesh, India: Socio-economic and vulnerability. Energy and Environment Research 2 (2): 137–148. Newsham, A.J. and Thomas, D.S.G. (2011). Knowing, farming, and climate change adaptation in North-Central Namibia. Global Environmental Change 21: 761–770. Olson, K. (2009). Impacts of 2008 flooding on agricultural lands in Illinois, Missouri, and Indiana. Journal of Soil & Water Conservation 64 (6): 167A–171A. Olson, K.R. and Morton, L.W. (2012). The impacts of induced levee breaches on agricultural lands of the Ohio and Mississippi River Valleys. Journal of Soil and Water Conservation 67 (1): 5A–10A. Olson, K.R. and Morton, L.W. (2013). Impacts of 2011 Len Small levee breach on private and public Illinois lands (July/August). Journal of Soil & Water Conservation 68 (4), 89A–95A. doi: 10.2489/jswc.68.4.89A. Olson, K.R., Matthews, J., Morton, L.W., and Sloan, J. (2015). Impact of levee breaches, flooding, and land scouring on soil productivity. Journal of Soil and Water Conservation 70 (1): 5A–11A. Olson, K.R., Morton, L.W., and Speidel, D. (2016). Missouri Ozark Plateau Headwaters Diversion Engineering Feat. Journal of Soil and Water Conservation 71 (1): 20A–26A. Park, S.E., Marshall, N.A., Jakku, E. et al. (2012). Informing adaptation responses to climate change through theories of transformation. Global Environmental Change 22: 115–126. Prokopy, L.S., Arbuckle, J.G., Barnes, A.P. et al. (2015a). Farmers and climate change: A cross-national comparison of beliefs and risk perceptions in high-income countries. Environmental Management doi: 10.t /s00267-015-0504-2. Prokopy, L.S., Morton, L.W., Arbuckle, J.G. et al. (2015b). Agricultural stakeholder views on climate change: Implications for conducting research and outreach. Bulletin of Atmospheric Meteorological Society doi: 10.1175/BAMS-D-13-00172.1. Romero-Lankao, P., Smith, J.B., Davidson, D. et al. (2014) North America. In: Climate Change 2014: Impacts Adaptation and Vulnerability, Volume II: Regional Aspects Ch 26, IPCC 5th Assessment Report WG11 AR 5. Rufino, M.C., Reidsma, P., and Nillesen, E.E.M. (2011). Comments to “is an integrated farm more resilient against climate change? A micro-econometric analysis of portfolio diversification in African agriculture”, Food Policy 36: 452–454. Sanghi, A. and Mendelsohn, R. (2008). The impacts of global warming on farmers in Brazil and India. Global Environmental Change 18: 655–665. Sarewitz, D. and Pielke, R.A., Jr. (2000). Breaking the global warming gridlock. The Atlantic Monthly, July 54–64. Schiermeier, Q. (2015). Quest for climate-proof farms. (July 23). Nature 523: 396–397. Seo, S.N. and Mendelsohn, R. (2008). An analysis of crop choice: adapting to climate change in South American farms. Ecological Economics 67: 109–116.

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Seo, S.N. (2010). Is an integrated farm more resilient against climate change? A micro-econometric analysis of portfolio diversification in African agriculture. Food Policy 35: 32–40. Seo, S.N., McCarl, B.A., and Mendelsohn, R. (2010). From beef cattle to sheep under global warming? An analysis of adaptation by livestock species choice in South America. Ecological Economics 69: 2486–2494. Sjogersten, S., Atkin, D., Clarke, M.L. et al. (2013). Responses to climate change and farming policies by rural communities in northern China: a report on field observation and farers’ perception in dryland north Shaanxi and Ningxia. Land Use Policy 32: 125–133. Slovic, P. (2009). The Perception of Risk. Sterling, VA: Earthscan Publications. Van der Linder, S., Maibach, E., and Leiserowitz, A. (2015). Improving public engagement with climate change: five “best practice” insights from psychological science. Perspectives on Psychological Science 10 (6): 758–763. doi: 10.1177/1745691615598516. Walthall, C.L., Hatfield, J., Backlund, P. et al. (2012). Climate Change and Agriculture in the United States: Effects and Adaptation. Washington, DC: USDA Technical Bulletin 1935. Washington, DC. 186 pages. Wheeler, S., Zuo, A., and Bjornlund, H. (2013). Farmers’ climate change beliefs and adaptation strategies for a water scarce future in Australia. Global Environmental Change 23: 537–547. Wilke, A.K. and Morton, L.W. (2015a). Climatologists’ patterns of conveying climate science to the agricultural community. Agriculture & Human Values 32 (1): 99–110. doi: 10.1007/s10460-014-9531-5. Wilke, A.K. and Morton, L.W. (2015b). Communicating climate science: Components for engaging agricultural audiences. Communication Science, Doi: 10.1177/ 1075547015581927. Wolf, J., Allice, I., and Bell, T. (2013). Values, .climate change, and implications for adaptation: evidence from two communities in Labrador, Canada. Global Environmental Change 23: 548–562.

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20 Farmer and Community-led Approaches to Climate Change Adaptation of Agriculture Using Agricultural Biodiversity and Genetic Resources Tony McDonald 1 , Jessica Sokolow 2 , and Danny Hunter 3 1

Institute of Land Water and Society, Charles Sturt University, Australia The Cabrera Research Lab, Ithaca, New York and The College of Human Ecology, Cornell Institute of Public Affairs, Cornell University, Ithaca, New York 3 Healthy Diets from Sustainable Food Systems Initiative, Bioversity International, Rome, Italy and Healthy Food Systems node, Charles Perkins Centre, University of Sydney, Australia 2

20.1 Introduction Communities around the world are already experiencing the effects of climate change. While these effects vary over space and time, they include rises in temperature and changes in rainfall amount, distribution and timing (FAO, 2014). Further, extreme weather events, such as droughts and floods, are expected to increase in frequency, further affecting agricultural production systems around the world (ibid; Jarvis et al., 2008). These changes are expected to have a wide range of impact on agricultural production, particularly as temperature and water availability are key in determining crop productivity (Alteri et al., 2015). Climate changes will not only affect abiotic factors influencing agricultural systems, such as solar radiation, water and temperature, but also biotic factors, such as pollination, pest and pathogens (Lin, 2011). The population dynamics of pest, pathogens and weed populations, including range extensions and phenological changes, is expected to have an effect on agriculture systems (Alteri et al., 2015; Lin, 2011). Changes in these factors are expected to have enormous impact on production systems worldwide. Conservation and utilization of a broad range of genetic resources in agriculture is an essential element of strategies for coping with the effects of climate change. To adapt to and build resiliency against such impacts, strategies at the local, regional and national level are needed that involve the development of new crop varieties and crops, as well as a consistently wider use of more diverse crops and species in production systems (Hodgkin and Bordoni, 2012). However, the role of genetic resources for food and agriculture, especially in terms of adaptation, has received little attention (Mijatovic et al., 2013). High genetic diversity, and the redundancy of this diversity, will allow for continued functioning of the ecosystem and ecosystem services because different phenotypes perform slightly different roles and occupy different environmental niches (Hodgkin and Bordoni, 2012; Jarvis et al., 2008; Padulosi et al., 2011). Thus, diversity of genetic resources is necessary to maintain and enhance the efficiency and resilience of agro-ecosystems. Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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This chapter will explore briefly (i) how climate change is impacting farming communities around the globe, as well as the genetic resources that are an essential resource to these farmers. We will then look forward to (ii) how genetic resources can be an invaluable resource to communities, and (iii) how farmer-led approaches are utilizing these resources to adapt to climate change and then (iv) their barriers to implementing these initiatives.

20.2 Impact of Climate Change on Farming Communities It is well recognized that climate change will directly affect the agriculture sector due to changes in temperature, precipitation, and increased carbon dioxide in the atmosphere (Yadav et al., 2015). The effects of climate change on farming communities, particularly traditional and indigenous communities, are often coupled with an array of outside pressures affecting the livelihood and food security of these communities, such as population growth and urbanization, social conflict, extreme poverty that affects the wellbeing of the human and natural world (Hunter and Fanzo, 2013). These factors are threatening the wellbeing of nearly 70% of the world’s marginalized individuals, who often live in remote, rural areas and depend on agriculture production for their livelihoods and food security (World Bank, 2016). Climate change is expected to have an incredible impact on agricultural production systems (Hodgkin and Bordoni, 2011) causing systemic shifts in the social and ecological aspect of agroecosystems worldwide (Ahmed and Stepp, 2016). A 2014 IPCC report stated that “People who are socially, economically, culturally, politically, institutionally, or otherwise marginalized in society are often highly vulnerable to climate change and climate change responses” (IPCC, 2014, p. 7). Rural and indigenous communities living in harmony with their environment are deeply threatened by, and in some cases are already impacted by, the changing climate and their stories and experiences shed light on the dramatic impacts of climate change (The Christensen Fund, 2014).1 Indigenous communities often live in sensitive natural regions—from the circumpolar Artic to desert landscapes—and have been using traditional ecological knowledge to understand the ecological changes and how to adapt (ibid). International institutions have recognized the threats and challenges facing communities in this ever-changing world, and have identified the empowerment of local communities and connecting farmers with external knowledge as effective tools for meeting these challenges (IAASTD, 2009). Bioversity International conducted research with 2400 smallholder farmers across Bolivia, India and Nepal to understand their perceptions of climate change and their coping strategies to gain insight into the adaptive capacity of their production systems and opportunities to enhance their resilience (Meldrum et al., 2013)2 . Of the farmers interviewed, 89% recognized changes in weather conditions over time, with many recognizing the unpredictability of the weather and the negative impact of its 1 https://www.christensenfund.org/issues/indigenous-peoples-climate-change/ 2 Bioversity International’s research was conducted in partnership with M. S. Swaminathan Research Foundation (MSSRF), Local Initiative for Biodiversity, Research and Development (LI-BIRD) and FundaciónPromoción eInvestigación de ProductosAndinos (PROINPA).

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changing patterns on yield and food security (ibid). Unstructured research during project implementation with subsistence and transition (or subsistence-plus) farming communities in Laos, Cambodia and Myanmar found similar findings where increasing impact of uncharacteristic weather events were having impacts upon farming (McDonald, 2017). Seeds for Needs, an initiative of Bioversity International (see Box 20.1), works closely with Ethiopian wheat farmers who are experiencing changing climatic conditions that drier weather and shorter cultivation seasons. A third of the farmers surveyed reported a reduction in are affecting production systems. Farmers in the research area reported a trend towards hotter and yields as a result of climate change (Bioversity International, 2015). There are seven case-studies which demonstrate farmer led initiatives which are highlighted by use of dedicated boxes throughout the chapter. The relationship between each of these case-studies is illustrated in Figure 20.2. Box 20.1 Seeds for Needs: Participatory Variety Selection for Climate Change Adaption in Ethiopia Bioversity International’s Seeds for Needs initiative works with over 20000 smallholder farmers in over 11 countries to research how agricultural biodiversity can minimize the risks associated with climate change. The initiative uses a participatory approach, where the farmers are directly involved in the research. Farmers evaluate and select varieties throughout the growing season, and provide feedback on their preferred traits to Bioversity scientists. Additionally, the initiative uses a crowdsourcing approach where farmers conduct small-scale trials where they compare three randomly-assigned varieties (out of a larger selection) and one control to their own. This method disseminates seeds farmers need in a short period time. While farmers collect qualitative data, Bioversity scientists also collect quantitative agronomic and morphological data to better understand famer’s priority traits and better inform breeders, who take into account preferences and identify accessions for distribution to farmers. Since the projects start in Ethiopia in 2009, the initiative now takes place in eleven countries, with each country focusing on different species. The countries and corresponding species include: Cambodia (rice, sweet potato); Colombia (beans); Ethiopia (barley); Honduras (beans); India (rice, wheat); Kenya and Tanzania (sorghum, pigeon pea, cowpea); Laos (cucumber, long bean, rice sweet corn, watermelon); Papua New Guinea (taro, sweet potato); Rwanda and Uganda (beans). The aim of these trials is to develop resilience and climate-adapted solutions at scale, while maximizing use of agricultural biodiversity, to benefit more farmers and their communities. Starting in 2009, Seeds for Needs engaged wheat-growing farmers in Ethiopia over a 2-year period. These farmers recognized the climatic changes impacting productivity, included increasing temperatures, and lower amounts of rainfall, including erratic rainfall and a shorter rainy season. Bioversity worked with the farmers to identify seeds from the national genebank that can help them adapt their production systems to conditions of drought and elevated temperatures. Of the 25000 varieties of durum wheat and barley available in the national genebanks, 500 landraces and improved varieties were short-listed (and made available to farmers through established or new community seedbanks), farmers and scientists then selected 50 varieties to test for local adaptation in the field. Field experiments collected data on eight agronomic (Continued)

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Box 20.1 (Continued) and morphological traits (including flowering components, yield components and plant structure), which was complemented by information from farmers on four additional traits: earliness (fast-maturing), tiller capacity (capacity to generate extra shoots from one seed), spike morphology and an ‘overall’ trait that represents a general appreciation for each variety. The initiative also shared information with farmers and decision makers about the risks of climate change and how the use of better-adapted varieties can help to protect livelihoods and ensure food security. Additionally, Seeds for Needs produced a Crop Atlas to help determine which accessions, or group of accessions, can be used under particular climate conditions to help farmers plan for adaptation of their production systems. Seeds for Needs shows that existing landraces have the potential to provide immediate options to farmers for managing climate-related risks. The initiative also demonstrates that re-introducing selected varieties conserved in national genebanks to farming communities can provide small-scale farmers with concrete options to adapt to a changing climate. Source: Bioversity International.

20.3 Inequity of Climate Change across Farming Communities Climate change does not affect members of communities equally. There is a complex relationship between the social and ecological systems that will be touched upon further in this chapter (Mijatovic et al., 2013). Gender can be an important dimension to consider when investigating how a community is impacted by the changing climate. Women’s activities of providing for their families, by gathering, preparing and providing food and water, can be particularly vulnerable to these changes (ibid). For this reason, when implementing adaptation strategies, such as diversifying production systems (as will be discussed), it is important for those involved to consider the consequences on all community stakeholders, such as the workload of women in the community (Bhattarai et al, 2015). For example, in Nepal fox tail millet (Kauno) was a traditional crop abandoned due to a decline in crop yields during prolonged dry seasons (Bhattarai et al, 2015). However, upon further investigation, there were other reasons for the crop’s abandonment related to the women’s workload, as Kauno is incredibly labor-intensive and a burden on a women’s workload (ibid). Thus, as institutions support communities adapting to climate change through the use of genetic resources, the social implications of a species or variety must be taken into account. Additionally, the effects of climate change are often location-specific, thus requiring local, tailored approaches to adaption and resilience building (PAR, 2009). Indigenous communities have voiced a need for this locally-driven approach to climate change, using their agrobiodiversity and social systems (ibid). It is important this local agency and traditional knowledge is paired with institutional insight and guidance, bringing forward outside perspectives and new research and tools. Many traditional and indigenous communities use farming approaches which are built upon a highly diverse and prevalent foundation of genetic resources (Alteri et al., 2015). These approaches help communities to adapt to climate change, while ensuring

20.5 Monocultures

food security and also lowering greenhouse gas emissions (FAO, 2015). However, genetic resources—including underutilized species such as crop wild relatives and landraces which bring more genetic diversity to an agricultural system than advanced germplasm (Heisey and Rubenstein, 2015)—and agricultural biodiversity are under threat of the impacts of climate change (FAO and PAR, 2011; Jarvis et al., 2008; Padulosi et al., 2011).

20.4 Impact of Climate Change on the Many Elements of Genetic Resources and Agricultural Biodiversity Agricultural biodiversity and genetic resources are threatened by biotic and abiotic factors resulting from climate change (Lin, 2011; Jarvis et al., 2008). By 2030, Southern Africa could lose more than 30% of its maize crop (the staple crop in the region), while in South Asia, rice, millet and maize (regional staples), could endure losses exceeding 10% (Lobell et al., 2008). In mid-to-high latitudes, crops may initially benefit from the warming of the climate (approximately +2∘ Celsius), but crop health will decline as the climate continues to warm (FAO and PAR, 2011). Climate change can also pose challenges for the livestock and fishery production systems. For example, heat stress and limited water availability may affect the health of animals (FAO, 2015) and incidences of diseases and algal blooms can affect the health of aquatic genetic resources. Broadly, vegetation belts are expected to move towards the poles, with more localized shifts towards higher altitudes (Box 20.3; Padulosi et al., 2011). Evidence exists that plants adapted to specialized ecological niches may have difficulty migrating to new climatic environments (Heywood, 2011a). In coastal areas, sea level rise could dramatically affect species’ environments due to the change in salinity, dramatically effecting the survival of important species, such as rice (Khatavkar 2010) (Box 20.2).3

20.5 Monocultures These effects on the agricultural system are coming at a time when the system is particularly vulnerable. Monocultures have increased dramatically worldwide, thus narrowing plant diversity and increasing crop genetic uniformity (Alteri et al., 2015). The intensification of agricultural systems has resulted in reduced genetic diversity of domesticated plants and animals (Hunter and Fanzo, 2013). FAO (2010) estimates that of a total of 300 000 plant species, 10 000 have been used for human food since the origin of agriculture. Out of these species, only 150–200 have been commercially cultivated (ibid). Historical events demonstrate the pernicious nature of this uniformity, such as events as the widespread Irish Potato Famine causing an 80% yield reduction, millions dead and a mass migration out of Ireland; or, the great Bengal famine of 1943 that nearly decimated rice production (Alteri et al., 2015). This issue of the narrow window within which intensification of agricultural systems operate will be dealt with again, where the complexity of barriers faced by farmers is discussed. 3 http://practicalaction.org/region_south_asia_agriculture_casestudy

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Box 20.2 Farmers Use of Traditional Rice Varieties to Adapt to Saline Conditions As sea levels rise, rice farmers in coastal communities must find ways to adapt to saltier conditions. Currently saline stress is a major limiting factor to crop productivity. Practical Action works with rice farmers in Sri Lanka to adapt to these conditions using indigenous rice varieties. Some traditional rice varieties can resist high salinity in soil and water. Farmers, with support from Practical Action, selected and trailed different traditional varieties of rice from National Federation of Traditional Seeds. In Dehigahalanda, Sri Lanka, farmers chose 10 varieties and scored them according to plant height, duration, grain quality and yield. Out of the ten varieties, four scored the highest and were consequentially promoted through farmer organizations as salient-tolerant, high quality rice varieties. Farmers have also found that using traditional varieties paired with the application of organic fertilizer helped to ease the soil salinity issue. While some farmers have found that the traditional varieties do not produce the yield of the hybrid varieties, they continue to achieve high profits, as consumer demand for these rare rice varieties is often high. During these trails, Practical Action invites farmers from the surrounded areas, whose cropping activities similarly affected by saline stress, to visit the trial plots to observe the crop growth and engage in discussion with the farmers conducting the trials. This process helps to share knowledge between the farmers, thus raising awareness about the role traditional varieties can play in adapting to climate change conditions. Source: Practical Action 2010 https://practicalaction.org/blog/where-we-work/sri-lanka/environment-lagoons-andsri-lanka/and Khatavkar, 2010

20.6 Wild Species Wild species may be particularly vulnerable to climate change because they do not receive attention from management interventions that can support their adaptation to changing conditions (Jarvis et al., 2008). Overall, less is known about the potential impact of climate change on wild, underutilized species. Such changes may include: their adaptive and resilience capacities, ability to migrate, and dispersal capacity; the nature and ecology of their new bioclimatic envelopes and their ability to survive in them and spread; the availability of pollinators and dispersal agents; and the environment and the management practices that might be associated with the species (Padulosi et al., 2011). Species distribution models can serve as useful tools to predict and prepare for the impacts of climate change on the distribution of species. These models can estimate if a species’ habitat will decrease or if new areas will become available under climate change conditions (Cobben et al., 2013). Modelling efforts, using approaches such as climate envelope, bioclimatic and ecological niche modelling help to anticipate the response of species to climate change, but the information about trends for underutilized species is still piecemeal. Some bioclimatic models—which compares bioclimatic and locality data to understand the relationship between species and the climate and future changes (Havens et al., 2015; Beaumont et al., 2007)—suggests that many crop wild relatives will be at risk if they fail to migrate to new climatic envelopes (Padulosi et al., 2011). The ecological niche model (ENM) by Russell et al. (2014) predicts some future losses of genetic diversity in wild barley midterm future climate change. Further, Ostrowski et al.

20.7 Role of Genetic Resources and Agricultural Biodiversity in Coping with Climate Change

(2016) used an ENM to project that gene flow from cultivated wheat to wild relatives (Aegilops species) would lead to a general decline in suitable climatic conditions for Aegilops species. Estimates of the number of underutilized wild species that will be lost as a result of climate change are currently not available as they are such a numerous and diverse array of species. There is still a great way to go to improve the modelling of crop wild relatives in the face of climate change. Firstly, more accurate climate and country-level data is needed to build the models (Maxted et al., 2014). Additionally, many models do not include species’ dispersal capacity (i.e., its capability of reaching new habitat areas) or founder effects (i.e., whether species loses genetic diversity while tracking suitable climate conditions), which can limit the accuracy of the models and potentially underestimating the threat to distribution of many species, particularly CWRs (Cobben et al., 2013). Modelling results cannot yet direct specific coping strategies to respond to this biodiversity loss, making best use of the biodiversity and underutilized species (Padulosi et al., 2011). Further model development is crucial for a better understanding of how genetic diversity and agricultural biodiversity may be affected by climate change, and how ex situ and in situ conservation methods can best preserve these genetic resources.

20.7 Role of Genetic Resources and Agricultural Biodiversity in Coping with Climate Change Climate change brings forth new challenges and barriers to managing and preserving the world’s genetic resources and agricultural biodiversity, however it also brings to the spotlight their importance (FAO 2015). Agricultural biodiversity contributes species and genotypes to an agroecosystem that have different ecosystem roles and niches (Vandermeer et al., 1998). A diverse agricultural system often has many more species than ecosystem functions, thus building redundancy and resilience—an insurance of sorts (Alteri et al., 2015). This insurance ensures that the ecosystem continues to function in face of the abiotic and biotic effects of climate change (ibid). Additionally, genetic diversity adds a buffer in the event a species fails to survive the environmental changes, allowing the other species to serve their role (Lin, 2011). Communities around the world realize the role of genetic resources and agricultural biodiversity in adapting to climate change. A review by Mijatovic et al. (2013) of 172 case studies and project reports from around the world that describe the use of agricultural biodiversity and associated knowledge in strengthening resilience to climate change-related stresses demonstrates that traditional farmers use agricultural biodiversity to promote resilience (Mijatovic et al., 2013). This approach is implemented by farmers through a number of—often interconnected—strategies, such as the protection and restoration of ecosystems, the sustainable use of soil and water resources, agroforestry, diversification of farming systems, various adjustments in cultivation practices, and the use of stress-tolerant crops and crop improvement (Mijatovic et al., 2013). These approaches are not new, as smallholder farmers have historically responded to environmental changes by gradually modifying their management practices based on their indigenous knowledge and experience, such as improving their selection of adapted cultivars and mixing crops with trees and livestock to reduce risks of crop failures (Bedmar Villanueva et al., 2015) More recently, farmers use crop diversification

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strategies, taking into consideration a diversity of traits and characteristics among existing species, to respond to the effects of climate change, including the use of short-maturing and stress-tolerant crops varieties, wild plant gathering and mixedcropping production systems (ibid). While traditional and indigenous farmers around the world realize the incredible tool genetic resources and agricultural biodiversity can be, international and national climate change arenas have given them little attention. The United Nations Framework Convention on Climate Change (UNFCCC) acknowledges the role of ecosystems in addressing climate change, but has not specifically recognized the role of genetic resources and agricultural biodiversity in adapting to climate change (FAO, 2015). Adaption strategies were not put on the UNFCC agenda until 2001, when the need was recognized for least developed countries and nine years later adaption was given the same priority as mitigation (ibid). National Adaption Programmes of Action (NAPA), initiated by the UNFCCC Adaption Committee, creates a formal process to identify and plan for medium- and long-term adaption needs (ibid). Based on a review of the NAPAs, Bedmar Villanueva et al. (2015) found that agrobiodiversity was not incorporated comprehensively or systematically (Bedmar Villanueva et al., 2015). This may in part be due to few established precedents or models for scaling-up agricultural biodiversity strategies at the national level (ibid). There is an urgent need to establish such models and provide policymakers with the tools and resources needed to effectively incorporate agricultural biodiversity and genetic resources into national climate change policies, such as NAPAs, as well as international guidance and policies. Top-down approaches can provide essential frameworks and infrastructure to support the activities driven by communities and farmers on the ground.

20.8 Brief Overview of Approaches Using Genetic Resources and Agricultural Biodiversity to Cope with Climate Change The use of genetic diversity to cope with climate change has thus far focused on localized interventions for single crops, animals or aquatic species, or specific components such as enhanced soil management or pollinator availability, with has resulted in small-scale effects (PAR and FAO, 2011). Instead, approaches targeting agricultural biodiversity should include a variety of integrated components to promote resilience, such components may include: inter- and intra-specific diversity of plants and animals, ecological interactions between wild, cultivated, above-ground, below-ground and aquatic diversity and the resulting ecosystem services (ibid). This leads us to discuss the need for an integrated, whole system approach for using agricultural biodiversity to cope with climate change. FAO (2015) refers to this an ecosystem approach, or a strategy for the integrated management of land, water and living resources that promotes conservation and sustainable use in an equitable way. This approach focuses on the management response aimed at preserving and promoting the services provided by genetic resources, not on a single species, breed or variety, but also on the surrounding ecosystem (FAO, 2015). For example, crop pollination is essential for the agricultural production system, but requires not only

20.8 Brief Overview of Approaches Using Genetic Resources

Community

Protection

Ecosystem/landscape Adjustment Restoration

Conservation

Agriculture

Links between natural and cultivated landscapes

Adaptation

Inter-and intra-species diversity

Maintenance of species and genetic diversity

Figure 20.1 Platform for Agrobiodiversity’s Whole System Approach, highlighting adaptation dynamics.

the presence of pollinator species, but also synchrony with the flowering period of the plant, which could be affected by climate change (ibid). The Platform for Agrobiodiversity Research (PAR) offers a similarly holistic approach to maintain species and genetic diversity to help farmers adapt to a changing climate (see Figure 20.1). The approach highlights how adaptation strategies contribute to the resilience of the whole system at different levels: i) the links between natural and cultivated landscapes; ii) the role of agriculture in the protection and restoration of ecosystems; and iii) the maintenance of species and genetic diversity (PAR, 2010 a,b). To understand the farmer’s approach to using agrobiodiversity to cope with climate change, and support the development of the model (see Figure 20.1), the Platform analyzed more than 300 different case studies from around the world and found that adapting agriculture systems to climate change involved three different levels of action (Hodgkin and Bordoni, 2011): 1) Ecosystem or landscape; 2) farm or agricultural system; and 3) inter- and intra-specific diversity. Additionally, the study recognized that farmer innovations were based both on their traditional knowledge as well as new information and research; and social, cultural and political dimensions played an important role in shaping the innovations (Hodgkin and Bordoni, 2011). Finally, the use of traditional crop and livestock species and varieties,

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Importance of Agro-Biodiversity (Box 20.4) Range of climate Change Impacts (Box 20.1) Uncharacteristic weather events (Box 20.1)

Temperature increase; Drought; Intense Rains

Farmer Knowledge and Resourcefulness (Box 20.5)

Specific planting zone impacts (Box 20.3). Inundation and salinity in lowland tropics (Box 20.2)

Farm-based diversity diminishing (Box 20.7) Relationships / Trust and Confidence (Box 20.6) Figure 20.2 Summary of Relationship between the Text boxes. Table 20.1 Barriers and/or qualifying factors which act as barriers to farmer-led adaptation. Farmers & their Communities

Institutional & Collaborative mechanisms

Contextual & Background

Farmer Groups

Resource availability

Geography / Topography / Geology /

Trust

Leadership style

Top-down tendency

Literacy levels

Message digestibility

Bio-physical

Population Characteristics

Long timelines involved

Climatic & weather patterns

Farming System X type

Donor commitment

Pest & disease dynamics

Farm ready

Time dedication

Socio-political

Contradictory policy intentions Source: Contributing author.

along with new genetic material, was crucial to coping with climate change (ibid). This research highlights the importance of supporting community-led approaches through assisting the maintenance of traditional materials and the transfer of new information and genetic resources to the communities (see Box 20.3 for an example from Potato Park, Peru). Gene banks will need to meet the demand for new genetic resources, which can help to breed new species adapted to the changing environment (Hodgkin and Bordoni, 2011). Crop varieties, such as crop wild relatives and landraces, are important resources that can contain beneficial traits for climate change adaptation (Heisey and Rubenstein, 2015).

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Box 20.3 Quechua Farmers Leverage Genetic Diversity and Institutional Partnerships to Adapt to Climate Change The effects of climate change are drastically clear in the Peruvian highlands, where farmers in Potato Park, a valley outside Cusco, have had to adapt to the changing planting zones due to the warming climate. In a time period of only 30 years, farmers had had to move their cultivation of native potato varieties up the valley by 200 meters due to the warming temperatures. It is expected that farmers will be progressively pushed up the mountain due to the changing climate until there is no more land left to farm. Quechua farmers, with the support of the International Potato Center (known as CIP), are adapting to this change beyond simply moving their fields up the mountain, but by testing and using different traditional potato varieties. The participating farming communities cultivate and monitor more than 1440 native cultivars, which include their own varieties and cultivars provided to the communities (including those from CIP). The participatory process in Potato Park harnesses indigenous farmers’ knowledge of genetic resources. The farmers monitor the varieties for their diversity and changes over time. This effort, which can be considered a landscape-based gene bank, has re-introduced varieties previously collected from communities in the 1960s that were since lost (i.e., seed repatriation). Seed repatriation is one in-situ approach to recover once lost genetic biodiversity, putting access to the genetic resource back in the hands of the community. This process of expanding upon the intra-specific diversity available also provides farmers with a form of insurance to protect their staple crop in the face of climatic uncertainty. The fostering of this biodiversity in Potato Park, Peru not only benefits the Quechua farmers in the community, but mountain communities around the globe. The 2014 Bhutan Declaration on Climate Change and Mountain Indigenous Peoples aims to initiate responses to the impact of climate change of indigenous people in mountain regions. This Declaration in part established an international seed exchange program between Potato Park in Peru, the communities in Yunnan, China and the Ura and Jangbi communities in Bhutan to expand the use of genetic resources to an international scale to help farmers in these regions adapt to climate change. Source: International Institute for Environment and Development, 2014 and 2015

Rippke et al. (2016), recognize that with climate change will require some communities to transform their production systems from, for example, annual to perennials, shifting crop types or moving out of agriculture. However, they offer that biodiversity continues to play an important part in this process, as before a community, region or nation transforms its process to adapt to a changing climate, they should go through an incremental adaptation phase. This phase includes modification to crops and management practices, including crop improvement for key traits (e.g., drought or heat tolerance; Rippke et al., 2016). These crop improvements should be the first priority as they require a significant lead time (15 or more years) and can delay or avoid transformations (ibid). As seen from the results of the PAR case studies, social, cultural and political dimensions can play a role in the use of genetic resources and agricultural biodiversity in the adaption of agricultural production systems to climate change. Farmers make decisions regarding intra- and inter-species diversity based on these dimensions, which thus dictate the effects the climate change variables will have on their agricultural ecosystem (Ahmed and Stepp, 2016). A study by Mwongera et al. (2014) reflects the importance

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of socio-cultural dimensions when adapting to a new environment. The study involved two different communities moving along the slope of Mount Kenya in Eastern Africa, the Mwimbi farmers moving from a higher to a lower altitude and the Tharaka farmers moving from semi-arid lowlands to a higher altitude (in this case, the movement of these groups was a result of policy implications (Mwongera et al., 2014). Each group made use of their crop genetic resources, knowledge and practices adapted from their time in the previous climatic zone (ibid). The study found that both communities endured the drought conditions differently, with the Tharaka seeds better enduring the drought in part due to the farmers’ historical experience and knowledge from the semiarid lowlands (ibid). One may be surprised that the two communities did not exchange seeds, however it was found that seed exchange was restricted due to social barriers and limited intermarriage (ibid). As we continue through the chapter we will discuss a spectrum of farmer-led approaches. Through this discussion, particularly when considering scaling these approaches to broaden their reach, it is important to keep in mind barriers farmers—like the Mwimbi on Mount Kenya—may face when using genetic resources and agricultural biodiversity to adapt to climate change. It can also be argued that the speed of Climate Change in some farming systems and biomes suggests that the collective response, both formal and informal, be under pressure to accelerate. As will be discussed further, the needs are clear but the barriers to this acceleration are considerable.

20.9 Identification of a Spectrum of Examples of Farmer-led Approaches This chapter includes seven text boxes which aim to link together the major field-based findings. The relationship between these findings are summarised in the graphic 20.2. The text boxes offer case study examples of (i) the range of climate change impacts and farmer response (Box 20.1), (ii) intrinsic farmer knowledge and resourcefulness (Box 20.5), (iii) critical impact planting zones and the response in mountain areas (Box 20.3), and (iv) tropical coastal regions where increased salinity presents a challenge (Box 20.2). All this is occurring amidst a sizeable trend where, (v) the importance of agro-biodiversity maybe theoretically understood (Box 20.4), (vii) but farm-based diversity is rapidly diminishing (Box 20.7). A pertinent summary box highlights that the starting point to facilitate action with farmers is to establish two-way relationships, trust and confidence by identifying immediate and pressing needs and helping farmers to successfully address them (Box 20.6). Box 20.4 Importance of Agrobiodiversity Farmers in the Northwestern Ghats Embrace Traditional Varieties and Farming Approaches: The Platform for Agrobiodiversity Research (PAR), hosted by Bioversity International, brings together researchers, civil society, international organizations and others under the premise that sharing knowledge (new and traditional) and experiences improve and maximize the use of agrobiodiversity. PAR commits to agendas and efforts based on the needs of poor farmers, local communities and indigenous peoples. PAR, with support of The Christensen Fund, has undertaken an effort

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to understand how rural and indigenous communities around the world use agrobiodiversity to cope with the effects of climate change on agriculture. Part of this work involved workshops, which helped to share information about these strategies and initiatives, including a 2009 workshop on “The use of agrobiodiversity by indigenous peoples and rural communities in adapting to climate change” held in Chiang Mai, Thailand. Presentations shared knowledge of activities and research taking place around the world. The northwestern Ghats in India is one such region discussed, which is particularly importance as its considered a global biodiversity hotspot. Many rural farmers in this region practice rotational farming (or dongarsheti). The impacts of climate change, as seen from changing monsoon patterns reducing water availability, in conjunction with the effects of fertilizer overuse has decreased the productivity of the agriculture land. As a result, farmers have begun to adapt to these changes by drawing upon the plant genetic resources of traditional crops like finger millet (Eleusinecoracana) and little millet (Panicummilliare) that are resistant to drought and require less water, in addition to the practice of dongarsheti farming. This adaptation approach is not without its challenges, as farmers have difficulties obtaining adequate seeds of local cultivars. Reviving traditional agricultural practices is also threatened by land-use pressures from non-agricultural pressures, such as tourism and urbanization projects. It is important for local, regional and national-level institutions to continue to support farmers’ use of agrobiodiversity and traditional practices to adapt to climate change, particularly in the face of mounting socio-economic and climate-related pressures threatening the livelihoods and food security of traditional and indigenous farmers. Source: Platform for Agrobiodiversity Research (PAR) 2010

20.10 Examination of Barriers to Implementation of Farmer-led Approaches Examples taken from the field in this chapter highlight that individual farmers have demonstrated intelligent adaptation across different farming systems, agro-geography and climatic zones. The various text boxes indicate the emergence through observation and skilful adaptation over time, the response by farmers attuned to the variables of plant response and how to work with it. Table 20.1 offers a spectrum of barriers and qualifying factors which can negatively impact on farmer led adaptation. These specific factors fall into categories that can be either outside the control of farmers and institutions (e.g. geography, climatic & weather patterns), or can be facilitated by increased donor activity (e.g. increase in projects exploring a diversity in farming systems). However, the largest barriers to deploying farmer and community led approaches concern: • The fact that the lead-times involved in rigorously building a varietal response to emerging conditions can be can be long and not necessarily linear; • climate change impact is proving to be highly dynamic and the best of predicted scenarios are regularly being reviewed; • the difficulty in spawning the pre-conditions of effective collaboration; • the rapid pace of change which has been thrust upon farmers, particularly cropping farmers in the wet/dry monsoon tropics by climate change;

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• the inadequacy of the mainstream mechanism used for communication and connection with farmers and which could be potentially harnessed foster greater communication; • the dimensions of the socio-economic, political, and cultural conditions which are increasingly under pressure of change; and while change and the challenges it brings can be supportive of new thinking, the examples cited are routinely the product of long-term processes. Source: Contributing author observations Questions that arise having read these case studies include whether such initiatives could be fostered and cultivated in greater number, but also query if the existing predominant systems of engagement with farmers could actually be harnessed to promote and stimulate farmer-led approaches. The assumptions behind farmer and community involvement in climate change adaption can be extensive and the scenarios sketched out in the examples highlight that farmers and communities that can contribute to climate change adaptation, either in a passive or active manner, have time, inclination and access to land, as well as the knowledge, motivation and appropriate attitude which drives them, and possibly a track record of previous success at modifying their farming practices and achieving positive outcomes. Box 20.5 Intrinsic farmer knowledge and resourcefulness There are major areas of naturally occurring diversity in wheat species and Afghanistan is recognised as one of them, most particularly across the northern provinces where the topography and thus the profusion of micro climatic variance provides by default a range of challenging ‘nursery’ conditions for wheat to adapt. Wheat is the staple crop of the region and for thousands of years the land has provided inviting conditions for endemically occurring wild relatives and landraces to evolve in a unique biome. These genetic relatives can exhibit a host of well sought after attributes including drought tolerance, early maturing cycles, shortened growth habit, root system variance, endurance against long periods of flooding, resistance to evolving pathogens and stresses including some rust etc. Farmers in Afghan cropping fields will enthusiastically offer a wealth of knowledge concerning different varieties. Over 84% of those farmers see saving their own seed to be their best source of seed (Jilani et al., 2013). The farmer fields and the surrounding hills have been seen as a resource by numerous international seed collectors, perhaps the most famous being N. I. Vavilov, the Russian research scientist who interpreted the Afghan region as the site of one of the first centers of farming, and Central Asia’s hub of crop origin and diversity; collections of some of these wild relatives are to be found in various global gene banks (Mitrofanova et al. 2013). Research has revealed that although it is recognized that improved varieties can give a better yield, popularity of traditional seed varieties is demonstrated by many farmers who prefer to grow both the traditional with the improved (ACIAR 2013). The phenomena of ‘wild relatives’ is highly dynamic and new generations have evolved emerging as volunteers in situ. Against this backdrop there are still land races used in Afghanistan (ibid), and while Afghan government agencies supported by donors have initiated many programs to promote improved seed, there is still tendency to choose to grow a healthy percentage of old varieties. In a unique agro-geographic area such as Afghanistan with topographical barriers and a highly compromised footprint of government activity, there are many examples where farmers in the

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remote and secluded valleys take leadership and demonstrate a keen eye and knowledge of their annual crops, identify the values of specific specimens which have developed in situ rather than thru a gene bank, and are engaged with demonstrating their knowledge that a diversity will offer resilience against highly variable growing conditions. Another favoured Afghan staple is Millet, a highly drought tolerant and valuable crop utilized for both fodder and human consumption. Farmers are fully acquainted with how vulnerable their annual crops can be and millet is commonly planted with numerous varieties, a strategic move by farmers as insurance against weather variables. A recent field trip (by an author colleague) to a village in the northern Jawsjan Province to witness a field with many different varieties of millet growing. The farmer was asked which one he liked the best and, he went through the crop and picked out 8 lines – explaining the varying characteristics and qualities of each. From a climate change resilience perspective, such farmer knowledge indicates both a canny skill to know his varieties and its qualities, and to harness brilliant planning to achieve a strong heterogeneous mix. In conventional agriculture there is a high value placed upon the importance of mono crop regimes, with the corollary marketing and branding of single varieties. In the push for greater productivity monoculture systems are mainstream practice, but to have a built-in insurance and resilience against climate change, some traditional farmers can show the benefits of other ways. These farmers intuitively place a high value on simply maintaining diversity! Source: Co-author – personal field-work observations.

For any area of inquiry, multiple models may exist, and in many respects, particularly at the farm level, no two models will be the same. For all sorts of reasons, adult approaches to inquiry and thus learning are not linear, and are best understood through the theories of ‘andragogy’ and ‘appreciative inquiry’, which both highlight the fact that the adult learner is likely to be self-directed, experience-rich, theory-poor, and will expect to take responsibility for his/her decisions (Knowles 1984 ). To be successful, adult learning programs associated with agriculture must therefore accommodate this fundamental dimension.4 As formal Extension programs are considered to be the major ‘vehicle’ for intersection with farmers, and seen as the collective noun for agricultural education with farmers, the following section draws upon observations of the barriers in extension impact, and for the most part rules out any potential fostering of farmer and community-led thru the predominant existing orthodox approaches. The corollary of this is that perhaps contemporary farmer–led activities with the potential to contribute to climate change adaptation could be seen to predominantly occur in spite of formal extension. Prospective impacts of climate change on the food security of subsistence farmers is an uneasy issue (Shrestha, 2012) and extension for heterogeneous farming systems is a challenge in developing countries (Chatterjee et al., 2015). A wide range of measures could be taken to amend this situation and strengthen farmer resilience against the impact of climate change, but there are numerous barriers which can hinder fruitful and collaborative extension with farmers. These barriers to delivering effective and sustainable extension, especially to subsistence farmers, can be profound, but to some 4 Knowles, M (1984) Andragogy in Action. San Francisco: Jossey-Bass.

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degree these obstructions resonate across the spectrum of farming typologies around the globe. There is a scale and variety of extension typologies ranging from the natural and informal ‘farmer to farmer’ models through more formal publicly funded government agencies, bilateral and multilateral donor initiatives, NGO’s working as agents of change, and private companies aiming to support farmers in promotion of their product and cultivation technologies. Strategies of extension are also as diverse as national political philosophies and goals, from very centralized and top down, to decentralised and more farmer group driven.5 The most common and favoured method thru which farmers tend to initially become aware and are inclined to adopt new ideas comes thru family and from fellow farmers, due in considerable part to the presence of informal closeness, shared common attributes and most importantly, trust (Vanclay, 2004). Fundamentally this has been the primary method of handing on acquired knowledge and learnt skills to the next generation; a cumulative body of information and wisdom which can reflect experiences and adaptations of the generations gone before. There are a number of assumptions which offer context to the range of barriers that work against a proliferation of farmer and community led contributions to climate change adaptation. These assumptions revolve around issues associated with (i) farmers and the communities of which they are members, (ii) the existing resources and the incremental pressures upon them, (iii) the role of government and associated institutions including donors, research bodies, and (iv) the complex role played by the private sector. Impact from these barriers can manifest in a multitude of ways, sometimes arrived at through contradictory policies, are commonly unintentional and, as a result, occur mostly by default. While many stakeholders can claim some involvement in the broad practices and production from farming, ultimately it is individual farmers and potentially the immediate community in which they live, who are key players in the day to day cycle of annual cropping systems. There is no doubt that the profile of an innovative farmer engaging in independent inquiry can be strengthened, supported and both lead and be led by his/her community. While no development issue exists in isolation, some recent field work has strengthened the hypothesis that there can be a strong correlation between the incidence of isolation of a farming community, and its ability to look for answers from within. The major theory to draw on to explain adult learning processes is that of andragogy (Knowles, 1984) which espouse that (i) adults need to be involved in the planning and evaluation of their instruction, (ii) their experience (including mistakes) provides the basis for learning activities, (iii) that adults are most interested in learning subjects which have immediate relevance to their livelihood or personal life, and (iv) that adult learning is problem-centred rather than content-oriented. Sadly, few agricultural Extension programs targeting developing world scenarios are neither synthesised, structured, nor delivered using these primary and logical principles of andragogy. Basically, inspired extension could promote learning by doing and the learning might exist where low literacy and numeracy levels prevail, where government services are minimal to zero, where subsistence farming is dominant, and where schools, health, sanitation, clean water, roads, utilities etc. have an inadequate profile. 5 http://www.fao.org/docrep/t8654e/t8654e05.htm

20.10 Examination of Barriers to Implementation of Farmer-led Approaches

Subsistence and subsistence plus agriculture approximately involves anywhere between 50 to 90% of developing country’s farming populations. Due to greater ease of movement across borders for work, global trends suggest that those same communities will, on average, be experiencing a loss of population due to labour migration and urban drift, and an aging farming population, a situation which has fast tracked change in farming models towards mechanisation and larger land units. Globally, there is an emerging picture of fewer farmers needing to produce more. Added to this is the variance of farmers. Associated with types of farmers is the issue of land ownership, either through traditional / cultural systems or contemporary formal and ‘title’ based systems. Farmers who have ownership have an understandable greater chance of engaging in practises associated with successful resource stewardship, long-term improvement and the like.6 One Indian government initiative to plausibly categorise and describe ‘farmer’ differences is based upon the size of land holding (Singh undated).7 Such a definition may demonstrate that an increase in property dimensions gives a farming family options and latitude to enquire and build upon knowledge. Farmers and families of small land holdings, where the annual cycle is a unvarying risky gamble, can understandably be time poor and not well placed when it comes to improving the outcomes of their labour. This Indian categorization of farmers also include the ‘landless’, which is a group that can commonly be excluded from crop improvement Extension. A second ‘barrier to fostering farmer-led adaptation include the characteristics and pre-ordained direction of the institutions; government agencies, publicly funded donors, multilaterals, national and international agricultural research organisations. These institutions are routinely guided by national and global needs. The issues and topics they face are addressed from a myriad of funding resources and staff limitations, as well as a philosophical position which historically has delivered with a top down approach.8 Collectively national Government policy and intention tend to be focused on long term programs to promote agricultural production and feed ever growing populations but commonly many governments struggle to fully implement policy ideals. The globe presently has an annual growth of a steady 1.1%, a number which translates to an estimated 80 million people per year. This growth is compounded by the phenomena of urban agglomeration and the massive food demands that are required to feed people removed from land and living in cities. It is expected that 70% of the world population will be urban by 2050, and that most of this shift will occur in less developed countries. Between 1950 and 2010 farmers as a percentage of population have decreased from 81 to 48.2% in developing countries, and from 35 to 4.2% in developed nations.9 As a result of this dramatic shift, agricultural programs have invariably aimed to increase and accelerate production output; a process which logically promotes the shift to broad acre systems that promote efficient and high yielding varieties as monocultures, and, as one end result, precludes by default the profile and potential contribution of the individual curious farmer who’s expectations for answers will be pursued and arrived at via a very different route. 6 http://www.fao.org/docrep/005/y4307e/y4307e05.htm 7 Shiv Pratap Singh -⋅ Indian Agricultural Research Institute https://www.researchgate.net/post/What_ should_be_the_criteria_to_classify_a_farmer_into_landless_marginal_small_medium_and_large 8 http://ag4impact.org/sid/socio-economic-intensification/building-human-capital/agricultural-extension/ 9 IFAD and International Labor Organization (ILO)

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Public Private Partnerships have surfaced as major trend in governance and service delivery over recent decades, driven by the user pays principle. Examples of such partnership in agriculture in rice milling processes witnessed in Khammouane Province of Lao PDR (Shrestha, 2012), where processing efficiencies have been achieved, and dedicated Extension staff have been engaged to solely promote improvements in rice production by contract suppliers to the mill.10 Where private investment and collaboration with Public institutions in agriculture can have positive outcomes in research (Spielman et al.2009), there tends to be a focus on an attractive business opportunity (ACIAR, 2014), which is commonly focused towards post-harvest activities rather than the equally important “inputs” end a value-chain. From an inputs perspective, overall the transition from multiple varieties of rice to less than a handful in number has been driven by productivity and varietal characteristics, including the capacity to withstand impact of long periods of inundation predicted as a potential long-term effect of climate change in the region. In Khammouane province some farmers and rice millers report that less than 15 years ago up to 20 varieties were available, whereas now farmers are sourcing from from only two or three varieties only (McDonald, 2017). There are barriers in developing countries to overcoming information and technological gaps and government provided agricultural Extension services have been widely criticized for their limited scale, sustainability and impact (Aker, 2012). However, regardless of these challenges, it is frequently acknowledged that over the last 60 years huge amounts have been accomplished by way of increased productivity, working with farmers to offer them greater opportunity although each new decade brings new challenges (Chimhowu, 2013). It is globally recognised that success in Research and Extension programs helped to deliver the ‘green revolution’, a process which frequently worked in tandem with international “development assistance” programs promoting change in farming on many levels. Ironically, it can be argued that the success of this Green Revolution has contributed to greater numbers of food secure populations, an increase in the area of agricultural activity and thus threats to biodiversity in the form of conversion of land, along with the deforestation which accompanies it, biomass loss and habitat-fragmentation which in turn cumulatively contribute as major drivers of climate change. Additional blockages or barriers can include a lack of understanding of the thinking and rationale for many existing practices and traditions. The maxim of “starting where the farmers are” was popularized through the work of Robert Chambers and colleagues11 during the 1990’s. In the simple rush to improve basic household food supply, the bulk of Extension effort which has had impact has been perhaps too busily promoting change rather than starting off with the conviction that it was worthwhile understanding the potentially high-value integrations of traditional farmer coping mechanisms; in short, “starting where the farmers are”! Due to competition for resources, few Extension programs can concern themselves with accessing and carefully documenting, acknowledging and potentially utilizing these existing practices of farmers. One reason for this is that it is seen as a process which can commonly be seen to be more about ‘Research’ than ‘Extension’, a distinction which is commonly reinforced as funding invariably comes 10 http://www.snv.org/public/cms/sites/default/files/explore/download/biie_report_jan_to_june_final.pdf http://www.bdsknowledge.org/dyn/bds/docs/821/Aker_A_for_Agriculture_FINAL.pdf 11 1989

20.10 Examination of Barriers to Implementation of Farmer-led Approaches

from differing sources. On the other hand, if farmer-led practices have the potential to contribute to greater knowledge concerning locale and biome value, wild genetic resources along with clever, traditional farming practices, then to explore and document what for farmers may be just normal everyday observation and practice, dedicated field research which openly collaborates with farmers is required. While there is no one Extension model, shortcomings in delivery of a range of initiatives include the fact that messages tend to be supply rather than demand driven, adopting a more top-down, more pedagogically (Knowles, 2015) orientated approach. Demand driven collaboration will be associated with and presumably grow out of situations where farmers are engaged with problems and know where solutions are available. Commonly in “supply” situations, farmers simply may not be aware that there could be alternatives to explore, and/or solutions to problems. Players involved in the supply end of extension; government, academic research, private enterprise system and the NGO system – all have different positive and negative characteristics, and still collectively efforts have not been adequate in numbers nor resourced to adequately access anywhere near the majority of farmers. The cumulative numbers of staff involved and their collective capacity is simply not sufficient to reach farmers across the world, whose productivity and thus food security could benefit considerably if appropriately delivered programs were to productively reach them. In the vast majority of farming and rural livelihood settings, most especially in the developing world, women comprise the quiet majority yet they receive only a fraction of the land, credit, inputs (such as improved seeds and fertilizers), agricultural training and information compared to men.12 Extension programs have seldom effectively focused upon a gender equity approach, with the result that 70% of farmers can be argued to have been excluded from programs. In addition, research findings are clear that women, more than men, are exposed to a range of challenges that prevent them from accessing existing Extension programs. Success of any delivery process will depend largely on approaches and strategies being promoted for reaching women and men farmers on an equal basis. Delivering extension can seldom be a one size fits all program, and by far, a global minority of farmers have access to extension that offers all the appropriate answers to their daily and future challenges. While the developed world ‘north’ models can commonly assume a computer literate and well-resourced market orientated client/farmer, at the other end of a scale in the developing ‘south’ there is often a lack of appropriate resources and informed staff. These two worlds, the south and the north, can be additionally described as the ‘lean majority’ in the former and the ‘fat minority’ the later,13 a very tidy and convenient way to highlight the discrepancies faced by the public sector and farmers in many countries. Public extension in such situations can be limited to zero mobility with which to visit farmers, and for many remote communities it is common that well-intentioned but under-skilled, and inadequately resourced volunteers who actually interface with farmers, invariably with second-hand word-of-mouth messages from the district agricultural officer. It may come as a surprise to some readers that civil servants in some countries, including those in extension roles, may be obliged to “buy” their position.14 As a result they become part of a patronage system which includes their clients – the farmers; in such 12 http://www.farmingfirst.org/women_infographic/ 13 http://www.npr.org/sections/goatsandsoda/2015/01/04/372684438/ 14 https://www.jstor.org/stable/4190505?seq=1#page_scan_tab_contents

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situations if farmers cannot pay, they do not benefit from extension, regardless of the quality of its messages. Conventional, government-run agricultural extension services to the ‘lean majority’ have, in some notable situations, particularly where they are driven with large and grandiose parameters, failed to deliver the expected improved agricultural productivity and standards of living. This is especially true in remote and marginal upland areas. Orthodox approaches have also been criticized for promoting chemical-intensive, standardized, and often inappropriate packages of farming practices (Scarborough, 1997). In the judgement of many subsistence plus rice farmers, these practices are simply not sustainable (McDonald, 2017). One of the most difficult things to attempt with subsistence farming communities is to aim to introduce new crops and thus a change in cuisine, regardless of the efficacy of the crop. In such a situation change is being sort where the annual cropping gamble will be at its greatest, and no farmer is such a situation wants to take on more risk! Before adoption of extension ideas occur, there are antecedents or precursors, the absence of which can act as barriers to adoption. Without part or all of these important conditions being in place, extension can struggle to succeed. The way that programs, messages and services are developed, scripted, staffed, delivered, monitored and evaluated can and do differ such that they can be lacking in appropriate tailoring to the situation, and can be influenced by current trends rather than “a best fit” scenarios (Woods 2008). A number of precursors can present a challenge for Extension agencies operating with the ‘lean majority’. The barriers that both work against orthodox extension models successfully promoting change and effectively facilitate farmer led approaches can be itemised these under three categories, (i) the farmers and their communities, (ii) Institutional & Collaborative mechanisms and (iii) Contextual & Background issues. 20.10.1

Farmers & their Communities

• Farmer Groups: While the support required to embrace new ideas and innovate will vary across communities, a group of farmers, either in “fat majority” or “lean minority” communities will engage, investigate, discuss, analyse, absorb and adopt through mutual support more quickly, and will invariably benefit and approach adoption from a more positive perspective as members of a support group, either formal or informal (Pretty, 2003). • Trust: Trust in the collaborative process based on whether previous efforts have been positive is a critical element (see Box 20.6). To facilitate trust and thus confidence, the deliverables and timelines involved need to be appropriate to match and support farmer needs and expectations. • Literacy: The profile of literacy, numeracy and of “technacy”15 in a community will influence the ability to deal with new information. It follows from this that engagement with the processes of formal education modulates the brain and assists the capacity to interact with the environment (Baltes et al., 2006). Farmer expectation 15 Technacy is defined as the ability to understand, communicate and exploit the characteristics of technology to discern how human technological practice is necessarily a holistic engagement with the world that involves people, tools, and the consumed environment, driven by purpose and contextual considerations (Seemann 2009).

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and the ability to seek to improve practices and outputs can therefore be significantly influenced by levels of literacy within a community. • Population: Characteristics including numbers as well as density of population, culture, religion, economy, politics, and the role of gender and aspirational values of farmers can all play a positive and/or negative facilitation role.16 • Farming System dynamics: The farming system involved and the graduation from subsistence to “subsistence plus” (with the subsequent need to adopt more market orientated farming practices) can present challenges which will make obvious change attractive to farmers. • Farm Size: As previously noted from the Indian categorization system, dimensions of land contribute by default to the ability of farmers to choose and adopt (Kumar, 2007). Box 20.6 Establishing trust over rust with Afghan farmers! In 2010 collective donor concern to assist Afghan wheat farmers saw a massive import of UG99 resistant wheat variety and made available for planting. Distribution of the seed presented enormous challenges, similar indeed to the annual program of improved seed distribution for which a small team regularly contributed. While the UG99 is understood globally to have the potential to devastate staple crops, and it has been found in both Yemen and Iran, it is the common yellow rust, otherwise known as Stripe Rust (Pucciniastriiformisf.sp. tritici) that farmers in Afghanistan need resistance to. Annually there are major losses from this rust. In this case, the imported UG99 variety was not resistant to the common yellow rust and, as a result, the donor supported and imported UG99 resistance was not subsequently regarded by farmers as a sensible contribution, as it missed first base! Source: Contributing author field experience.

20.10.2

Institutional & Collaborative mechanisms

• Resource Availability & Access: Appropriate software and hardware to facilitate Extension processes including skilled staff, appropriate and operational mediums to promote the messages (e.g. radio, theatre groups), equipped vehicles supported with dedicated time and fundamentals such as mobility, fuel and maintenance all require steady budgets. In this regard, is fair to say that for reach-out programs servicing the “lean-majority” who may need it the most, are the very ones who have the greatest need. • Leadership styles: There are leadership approaches which facilitate success and while they may reflect or be influenced by cultural difference, universally farmers will respond to messages and assistance delivered in participative, collaborative, advisory and empowering styles as opposed to methods which are top-down, and a “one-way” process. In such situations it can be individual and personal qualities which make a difference. Team or staff skills are therefore critical, as is the successful contribution of the messages and technologies that they bring. 16 http://collections.infocollections.org/ukedu/en/d/Jsk16ae/8.10.html

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• Message digestibility: Extension messages match both a resource threshold and capacity of male and female farmers. The message and the actions need to be targeted at the right time and be within the grasp of farmers. • Long-time lags involved in “Research and Development” and Extension formulation as well as appropriate technology generation and adoption is a constant difficulty as lead times can be considerable and commonly underestimated. • Donor Commitment: In many scenarios, the ability of the public Extension service is dependent upon the cash flow from sources beyond government or the private sector. Commonly donor programs play a critical role in such scenarios. • Institutional Time dedication: If it is to make a difference, working with farmers, developing trust and benefitting from sharing their perspective takes time, and the more time the better. • Contradictory Policy Intentions: Unless well thought thru, institutional / government policy can generate unhelpful and opposing constructs. 20.10.3

Contextual & Background

• Agro-geography/Topography/Geology: Accessible topography whereby remote communities and farmers have ease of access to the world outside combined with agro-geographical features including soils and water availability can combine to influence both in a positive and negative manner. • Biophysical: The proximity of intact forest representing healthy and representative biodiversity contributes many ecological services to farming, a scenario highlighted by traits involved in “integrated pest management” approaches.17 • Climatic: Climatic variance can present huge challenges to farming, and in many cases, CC is increasing the dimensions of these challenges. • Co-evolving pests and diseases: The evolving biological response of pests and disease can work on a much more efficient competitive and generational timeline than that of the farming adaptation and response. • Socio-Political: Just as is cited above at the farm community level, the external social and political forces can considerably influence potential of collaboration. Box 20.7 Farm based Diversity Diminishing Recent rapid survey work across three countries in Southeast Asia included specific questions on choice of rice varieties for sowing by farmers. The survey aimed to answer questions regarding farmer variety choice and what influences that choice and the speed of adoption new varieties. Farmers can point to traditional varieties which are preferred for taste and cooking purposes, genotypes which perform well over long periods of inundation, others which maybe tall growing and offer stalk fodder, or varieties which can tolerate a build-up of surface salts. The list goes on and on. However, in response to impacts of change in wet season arrival and length, farmers have rapidly adopted higher yielding 90 day growing varieties as opposed to the traditional 150 day or more. This shift has seen farmers rapidly move to growing rice they may not like to eat, but farming communities of the region are rapidly graduating from subsistence to ‘subsistence

17 http://www.cdpr.ca.gov/docs/specproj/h2o/workbook/appendix/page111-115.html

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plus,’ whereby yield and efficient growth time lines have seen a quick demise of the number of varieties grown to two or three maximum. In Cambodia the IR504 variety is a good example and in the Mekong delta country there is virtually now a monocrop of the one variety. Source: Co-author personal observation.

20.11 Systems that are working A summary of the solution to many of these difficulties, to overcome many of these barriers and facilitate greater farmer engagement in climate change adaptation is the resourcing and application of suitable programs. The table and summaries which follow it above highlight that initiative require time, patience, appropriate resourcing and institutional commitment to seek new answers as the world faces climate change realities. Operational models which have proven to be a positive departure from the norm, and which philosophically aim to combine many of the qualities listed above are sadly few and far between. However, theoretically the approach taken by the following two examples is important: • Krishi Vigyan Kendra (KVK), is a front-line agricultural extension centre financed by the Indian Council of Agricultural Research. KVK primarily works to exert a powerful influence on the other extension system of the district, caters to the training needs of the farmers and extension functionaries, and facilitates the spread of technologies tailored to the diverse environment of farmers. There are currently 651 KVK offices across 8 agro-geographic zones of India.18 These KVK’s perform as an integral part of the National Agricultural Research System (NARS) program, aiming at assessment of location specific technology modules in agriculture and allied enterprises, through technology assessment, refinement and demonstrations. Theoretically the KVK model is an enlightened two way process cooperatively enabling skills and resources to address farmer problems. The KVKs have been functioning as knowledge and resource centres of agriculture technology since their initiation in Kerala southern India in 2004. Their laudatory role is to support initiatives of public, private and voluntary sector to improve the agricultural economy of the district, and they link the NARS with Extension systems and farmers. The quintessential aspects of the KVK which make them different is that they aim to marry in a collaborative manner the skills of science graduates with that of the farmer problems, working together in a collaborative manner at the village and district level. • The Bioversity International “Seeds for Needs” (see Box 20.1) pursues successful collaboration with farmers along a very similar philosophical position as does the KVK’s. • The Farmer Field School (FFS) technique, a term initially coined and given high profile from FAO promoted IPM work in Indonesia during the late 1980s,19 was synonymous with fostering dynamic synergies between farmers and research scientists and cultivating an adult learning environment whereby the players involved 18 http://www.icar.org.in/en/krishi-vigyan-kendra.htm 19 http://www.fao.org/docrep/006/ad487e/ad487e02.htm

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saw themselves as equals. Sadly, the term FFS has become diluted in its meaning through misuse, such that it is now frequently used to describe any type of gathering where messages are handed to farmers. In essence, the original FFS approach took as its starting point the assumption that regardless of schooling, farmers have similar intelligent potential as that of a research scientist and by fostering a collaborative approach can nurture positive collaborative outcomes for all concerned; farmers as well as research scientists. Many contemporary models are commonly nothing more that top-down pedagogical approaches “filling the vessel” with enlightenment from the outside, as opposed to strengthening the farmer ability to enthusiastically observe for example agronomic dynamics in crops, to seek answers and to have a collaborative forum whereby he or she can benefit. • Scholarship with Farmers The challenges to feed a steadily growing global population amidst the challenges of climate change is considerable and to facilitate greater farmer and community led engagement in adaptation is not so much a side-line issue but more so a critically important step. More than anything else, what is required is a minor revolution in the way that knowledge about farming and farming systems are propagated. The term FFS could be dispensed with by something more akin to “Scholarship with Farmers”, where the combined aspirations are towards regional and agro-geographical models which can offer support for the positive steps necessary at farmer and community level.

20.12 Conclusion This chapter has shown that there are highly relevant examples of what can occur when farmers, either through their own conviction or with the support of collaboration, are engaged in or focused on research activities which improve the adaptive capacity and integrity of their crops, specifically where they can see the impact of climate change. The examples cited indicate that this a process that does not follow a prescriptive “one-size-fits-all” approach, but more issue and site specific in character. To some extent there is a serendipitous dimension to the engaging of farmers and community-led approaches to climate change adaptation in so far as there are considerable barriers which are the products of the context within which orthodox agricultural Extension operates. In the light of these barriers, the chapter calls for a new approach in the relationship with farmers, particularly concerning the need for collaborative engagement on genetic adaptation. Whereas an appropriate approach and a collaborative parity has been cultivated between farmer and technical support, it has been seen that farmers and communities with enquiring minds can enthusiastically support the important task of varietal adaptation.

References Abdu-Raheem, K.A. and Worth, S.H., (2013) Food security and biodiversity conservation in the context of sustainable agriculture: the role of agricultural extension. South African Journal of Agricultural Extension, Ext.Vol.41 n.1 Pretoria Jan. 2013

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ACIAR (2014) The role of the private sector in promoting economic growth and reducing poverty in the Indo-Pacific region. Submission 21, Department Of Foreign Affairs And Trade, Canberra, Australia. Ahmed, S. and Stepp, J.R. (2016) Beyond yields: Climate change effects on specialty crop quality and agroecological management. Elementa: Science of the Anthropocene, 4(March), 000092. http://doi.org/10.12952/journal.elementa.000092 Aker, J.C., “Dial “A” for Agriculture: A Review of Information and Communication Technologies for Agricultural Extension in Developing Countries.” CGD Working Paper 269. Washington, D.C.: Center for Global Development. http://www.cgdev.org/content/ publications/detail/1425497 Altieri, M., Nicholls, C.I., Henao, A., and Lana, M.A. (2015) Agroecology and the design of climate change-resilient farming systems. Agronomy for Sustainable Development, 35(3), 869–890. http://doi.org/10.1007/s13593-015-0285-2 Beaumont, L.J., Pitman, A.J., Poulsen, M., and Hughes, L. (2007) Where will species go? Incorporating new advances in climate modelling into projections of species distributions. Global Change Biology, 13(7), 1368–1385. http://doi.org/10.1111/j.13652486.2007.01357.x Bioversity International (a). Seeds for Needs: Policy Brief No. 1 through 4. Rome, Italy. Bioversity International (b). The “Seeds for Needs” initiative in Ethiopia: Integrating farmer and scientist knowledge. Rome, Italy Bioversity International (c). Seeds for Needs: Overview. Rome, Italy Bioversity International (d). Seeds for Needs Factsheet 1: A Participatory Approach for Landrace Evaluation. Rome, Italy Bioversity International (e). Seeds for Needs Factsheet 2: A Crowdsourcing Approach. Rome, Italy. Bioversity International (f ). Seeds for Needs Factsheet 3: Strengthening the Informal Seed System through Community Seedbanks. Rome, Italy. Chambers, R., Pacey, A., and Thrupp, L.A. (eds) 1989 Farmer First: Farmer Innovation and Agricultural Research, London: IT Publications, Chatterjee, S., Goswami, R., and Bandopadhyay, P. (2015) Methodology of Identification and Characterization of Farming Systems in Irrigated Agriculture: Case Study in West Bengal State of India, Journal of Agricultural Science and Technology, 17(5), 1127–1140. Chimhowu, A. (2013) Aid for agriculture and rural development in the global south; A changing landscape with new players and challenges. UNU-WIDER Working Paper No. 2013/014, United Nations University. Christensen Fund (2014) “Indigenous Peoples and Climate Change: from Recognition to Rule of Law”. Available at: https://www.christensenfund.org/2014/01/13/indigenouspeoples-climate-change/. Accessed on June 8, 2016. Cobben, M.M.P., van Treuren, R., and Hintum, T.J.L. van. (2013) Climate change and crop wild relatives: can species track their suitable environment, and what do they lose in the process? Plant Genetic Resources: Characterization and Utilization, 11(3), 234–237. http://doi.org/10.1017/S1479262113000087 Food and Agriculture Organization of the United Nations (FAO) (2010) The State of Food Insecurity in the World, FAO, Rome, Italy. FAO and PAR (2011) Workshop Outcomes: Biodiversity for Food and Agriculture—Contributing to food security and sustainability in a changing world. Rome.

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FAO (2014) Lessons Learned about Ways and Means to Consider and Use Genetic Diversity to Build Resilience to Climate Change in Food and Agriculture Systems, Survey Report. CGRFA-15/15/Inf.16. Rome, Italy. FAO (2015). Coping with Climate Change—The Roles of Genetic Resources for Food and Agriculture. Rome. Havens, K., Vitt, P., Still, S. et al. (2015) Seed Sourcing for Restoration in an Era of Climate Change Seed Sourcing for Restoration in an Era of Climate Change. Natural Areas Journal, 35(1), 122–133. http://doi.org/10.3375/043.035.0116 Heisey, P.W. and Rubenstein, K.D. (2015) Using Crop Genetic Resources To Help Agriculture Adapt to Climate Change: Economics and Policy, EIB-139, U.S. Department of Agriculture, Economic Research Service, April 2015. Heywood, V.H. (2011a) An outline of the impacts of climate change on endangered species in the Mediterranean region. Naturalistasicil, 35(1): 107–119. Hunter, D. and Fanzo, J. (2013) Agricultural biodiversity, diverse diets and improving nutrition. In: Fanzo, J., Hunter, D., et al. (eds), Diversifying Food and Diets: Using Agricultural Biodiversity to Improve Nutrition and Health. Issues in Agricultural Biodiversity. Earthscan, UK, pp. 1–13. Hodgkin, T. and Bordoni, P. (2012) Climate Change and the Conservation of Plant Genetic Resources. Journal of Crop Improvement, 26, 329–345. IAASTD (International Assessment of Agricultural Knowledge, Science and Technology for Development) (2009) Agriculture at a crossroads, international assessment of agricultural knowledge, science and technology for development, synthesis report. Washington, DC: Island Press. International Institute for Environment and Development (2014) Return of potatoes from CIP to Andean farmers proves critical for climate adaptation. Available at: http://www .iied.org/return-potatoes-cip-andean-farmers-proves-critical-for-climate-adaptation. Accessed on: June 08, 2016. International Institute for Environment and Development (2015) Mountain communities rebuild diverse, climate-resilient crops. Available at: http://www.iied.org/mountaincommunities-rebuild-diverse-climate-resilient-crops. Accessed on: June 08, 2016. IPCC (2014) “Climate change 2014: Impact, adaptation and vulnerability.” In: Technical summary report., ed. V. Braun. Jilani A., Pearce D., and Bailo, F. (2013) ACIAR wheat and maize projects in Afghanistan. ACIAR Impact Assessment Series Report No. 85. Australian Centre for International Agricultural Research: Canberra. 158 pp. Khatavkar, A. (2010) Adapting Rice to Saltier Conditions. Practical Action, 44. Knowles, M. (1984) Andragogy in Action. San Francisco: Jossey-Bass. Knowles, M. S., Holton, E. F., Swanson, R. A., (2015 Ed), The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development. Routledge. Abington, Oxon UK. Kumar, P., (2007) Farm Size and Marketing Efficiency: Pre and Post-Liberalization, Concept Publishing Company, New Delhi. Lin, B. B. (2011). Resilience in Agriculture through Crop Diversification: Adaptive Management for Environmental Change. BioScience, 61(3), 183–193. http://doi.org/10.1525/bio.2011.61.3.4 Lobell, D.B., Burke, M.B., Tebaldi, C. et al. (2008) Prioritizing climate change adaptation needs for food security in 2030. Science, 319 (5863): 607–610.

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Maxted, N., Kell, S., and Magos Brehm, J. (2014) “Crop Wild Relatives and Climate Change.” In Plant Genetic Resources and Climate Change, M. Jackson, B. Ford-Lloyd, and M. Parry (eds). CABI International, UK, pp. 114–135. McDonald, T., Thirthon, A. (2017) Promoting Synergy between Sustainable Agriculture and Food Safety: Experiences on Green Water Management and Nitrogen Use Efficiency in the Greater Mekong Subregion. Discussion Paper Series of the Greater Mekong Subregion’s (GMS) Core Agriculture Support Program for the Working Group of Agriculture. Asia Development Bank, Manila. Mbo’o-Tchouawou, M. and Colverson, K. (2014) Increasing access to agricultural extension and advisory services: How effective are new approaches in reaching women farmers in rural areas? Nairobi, Kenya: International Livestock Research Institute (ILRI). Meldrum, G., Sthapit, S., Rojas, W. et al. (2013) Agricultural biodiversity enhances capacity to adapt to climate change. New Agriculturist, 13(6), 20–22. Available at: http://www .new-ag.info/en/focus/focusItem.php?a=3154. Accessed on June 8, 2016. Mitrofanova, O.P., Strelchenko, P.P., Zuev, E.V. et al. (2013), Genetic diversity of bread wheat landraces collected by scientific expeditions in Afghanistan. Russian Journal of Genetics: Applied Research, January 2013, Volume 3,Issue 1,pp 1–11. Musa, Y.N, Aboki, E., and Audu, I., (2013) The Limitations and implications of Training and Visit Extension System in Nigeria. Journal of Agriculture and Sustainability, ISSN 2201-4357 Volume 4, Number 1, 2013, 67–76. Ostrowski, M.F., Prosperi, J.M., and David, J. (2016) Potential implications of climate change on aegilops species distribution: Sympatry of these crop wild relatives with the major European Crop triticumae stivum and conservation issues. PLoS ONE, 11(4), 1–19. http://doi.org/10.1371/journal.pone.0153974 PAR 2010 (a). Coping with Climate Change: The Use of Agrobiodiversity by Indigenous and Rural Communities. Rome: Platform for Agrobiodiversity Research. PAR 2010 (b). The Use of Agrobiodiversity by Indigenous and Traditional Agricultural Communities in: Adapating to Climate Change. Rome: Platform for Agrobiodiversity Research. PAR (2009) Workshop report: experiences, knowledge gaps and opportunities for collaboration. The use of agrobiodiversity by indigenous peoples and rural communities in adapting to climate change. Rome: Platform for Agrobiodiversity Research. Padulosi, S., Heywood, V., Hunter, D., and Jarvis, A. (2011) Underutilized Species and Climate Change: Current Status and Outlook. Crop Adaptation to Climate Change, 507–521. http://doi.org/10.1002/9780470960929.ch35 Practical Action. Adapting rice to saltier water. Available at: http://practicalaction.org/ adapting-rice-to-saltier-water-1. Accessed on: 8 June 2016. Pretty J. 2003. Social capital and the collective management of resources. Science 302, 1912–1915 Reuter-Lorenz, P.A., Baltes, P.B., and Rosler, F., (Eds) (2006) Lifespan Development and the Brain: The Perspective of Biocultural Co-Constructivism. Cambridge University Press Russell, J., van Zonneveld, M., Dawson, I.K. et al. (2014) Genetic Diversity and Ecological Niche Modelling of Wild Barley: Refugia, Large-Scale Post-LGM Range Expansion and Limited Mid-Future Climate Threats? PLoS ONE, 9(2): e86021. doi: 10.1371/journal.pone.0086021 Seemann, K.W. (2009) Technacy Education: Understanding Cross-cultural Technological Practice, Work, Learning and Sustainable Development. In: Technical and Vocational

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Education and Training: Issues, Concerns and Prospects, vol.8 pp. 117–131. Desert Knowledge Co-operative Research Centre in Sustainable Desert Settlements, Southern Cross University Shrestha, R, (2012) Building Independence, Income and Empowerment. SNV, Netherlands Development Organisation (http://www.snv.org/public/cms/sites/default/files/explore/ download/biie_report_jan_to_june_final.pdf) SKAT (1994) Agricultural Extension: Guidelines for Extension Workers in Rural Areas298 pages) Spielman, D.J., Hartwich, F., and von Grebmer, K. (2009) Public-private Partnerships and Developing-country Agriculture: Evidence from the International Agricultural Research System. IFPRI discussion paper no. 00708. Washington, D.C.: IFPRI. Vanclay, F. (2004) Social Principles for agricultural extension to assist in the promotion of natural resource management. Australian Journal of Experimental Agriculture, CSIRO Publishing, Vol 44, 213–222 Vandermeer, J., van Noordwijk, M., Anderson, J. et al. (1998) Global change and multi-species agroecosystems: concepts and issues. Agric. Ecosyst. Environ., 67:1–22. doi:10.1016/S0167-8809(97) 00150-3 Vernooy, R., Otieno, G., Bessette, G. et al. (2015) A novel strategy to discover and use climate-adapted germplasm. Bioversity International, Rome, Italy. Woods, N. (2008) Whose aid? Whose influence? China, emerging donors and the silent revolution in development assistance, Blackwell Publishing Ltd/The Royal Institute of International Affairs, International Affairs, 84: 6 (2008) 1205–1221. World Bank (2016) “Data: Agriculture & Rural Development.” Available at: http://data .worldbank.org/topic/agriculture-and-rural-development. Accessed on: June 13, 2016. Yadav, S.S., Hunter, D., Redden, B. et al. (2015) “Impact of Climate Change on Agriculture Production, Food, and Nutritional Security” In: Crop Wild Relatives and Climate Change, R. Redden, S.S. Yadav, N. Maxted et al. (eds). John Wiley & Sons, Inc., 1–23.

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21 Accessing Genetic Diversity for Food Security and Climate Change Adaptation in Select Communities in Africa Otieno Gloria Bioversity International Regional Office of Uganda, Kampala, Uganda

21.1 Introduction Climate change continues to be a challenge for global food production and agricultural ecosystems. Since the 1950s, surface temperatures have increased by 0.5 to 2∘ C, temperature increases coupled with the increased frequency of extreme weather events such as droughts and floods (UNEP, 2008) show just how pressing addressing climate change is. The fifth Inter-governmental Panel on Climate Change (IPCC, 2014) report indicates that climate change will result in an increase in temperatures of between 1.4 to 5.8∘ C in the 2100s, rainfall will become more erratic and seasons will shift (CDKN, 2014). These patterns interfere with cropping systems, impacting yields and food security (Otieno et al., 2013). The populations most vulnerable to these shifts are the poor, especially rural farmers (Schmidhuber and Tubiello, 2007). In particular, crop yield losses will be more severe in the tropics than in temperate areas, including many regions in Africa. Agriculture is a key component for economic growth and development in Africa. The population relying on agriculture1 directly or indirectly accounts for 48% of the total (almost 70% in East Africa) (NEPAD, 2013). Major food crops in Africa are cereals such as maize and rice, and to a lesser extent sorghum and millets. Root crops such as yams, cocoyam, sweet potatoes and cassava also play an important role in providing food security. Perennial crops such as bananas provide between 20–30 per cent of daily caloric requirements, especially in the Eastern and Western parts of the continent (Chauvin et al., 2012). Africa will be severely affected by temperature changes (between 2 and 5.8∘ C) and extreme weather events caused by climate change and resulting in a loss in agricultural productivity. Some regions may benefit from more favorable climate conditions for production, while others will face increased climate change-related biotic and abiotic stresses by the mid-century (IPCC, 2007). Estimates indicate that between 75 million and 250 million people in Africa will be affected by water shortages caused by climate change and increased incidences of both crop and livestock pests and diseases (Niang et al., 2014). As in any situation of economic imbalance, the poor and especially those rural communities that rely on agriculture will 1 Agriculture supports food security and livelihoods of most rural populations in Africa, it is also an important source of food for urban populations and a source of employment for agro-industries and hence a very important sector for economic growth and development in Africa (Otieno et al., 2013). Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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be the most affected–losing livelihood opportunities and facing increasing food and water insecurity. Many mitigation and adaptation measures are beyond the reach of countries with severe resource constraints, such is the case with the majority of African countries (ibid, pp. 1023). According to the IPCC’s fifth assessment report, increasing temperatures and changes in precipitation are very likely to reduce cereal crop productivity and high value perennial crops in Africa. Suitable agro-climatic zones for growing economically important perennial crops are estimated to significantly diminish, largely because of the effects of rising temperatures. For example, in the case of maize-based systems in East Africa, where there will be overall warming and increased precipitation increased production may result (Thornton et al., 2009). In the Southern African region, maize production is likely to experience a reduction in yields of up to 30% (Ibid). Furthermore, pest, weed, and disease pressure on crops and livestock is expected to increase in most parts of Africa due to climate change and other factors related to human activities (FAO, 2009). It is estimated that by the 22nd century agriculture losses in Africa will contribute to between 2–7% of the GDP in parts of the Sahara, 2–4% in central Africa, and 0.4–1.3% in western Africa1 . These will be coupled with an expansion of arid and semi-arid lands by 60–80 million hectares; decreasing productivity by up to 50–60% (Ibid). Finally, climate change is projected to affect individual species and population distribution through increases in temperature and precipitation or through extreme weather events such as floods, droughts and wildfires, leading to a possible increase in the rate of extinction. Rural households that rely heavily on climate sensitive resources will be more affected including loss of biodiversity. In fact, some communities are already experiencing a loss in the number of varieties of crops, limiting their ability to cope with climate change and meet their food security needs (Halewood et al., 2017). In regards to strategies based on use, conservation and management of genetic resources for climate change adaptation, IPCC’s fifth assessment report recognizes their importance and provides several recommendations. Among its recommendations, the report highlights the importance of improving crop tolerance to new conditions. Specifically, the report suggests improving access to gene banks to develop varieties with appropriate adaptive characteristics while incorporating indigenous knowledge (IK) to identify adaptive strategies, contributing to food security in many parts of the world2 (IPCC, 2014). Rural communities can rely on three main sources of Plant Genetic Resources for Food and Agriculture (PGRFA): international gene bank collections that are in the multilateral system of access and benefit sharing (MLS), national gene bank collections and collections within communities in-situ or through collective gene banks such as community seed banks. Access to these resources depends on different access and benefit sharing regimes as determined by international laws, treaties and conventions (Halewood et al., 2017 pp 6–7). The International Treaty for Plant Genetic Resources for Food and Agriculture (ITPGRFA) establishes a multilateral system of access and benefit sharing (MLS) through which countries create an international pool of PGRFA for 64 priority crops and forages of global importance for food security, to be used for research, training and breeding purposes. In exchange for putting their own PGRFA in the pool, countries obtain access to PGRFA of all other countries, along with those in the collections held by international organizations that have signed agreements with the Governing Body

21.2 Methodology

of the ITPGRFA. Some materials are not in the MLS and not freely accessible, for instance in-situ collections held by farmers and collections held by countries that are not signatory to the ITPGRFA would to be accessed through negotiations that follow the provisions of the Convention on Biological Diversity’s (CBD) Nagoya Protocol where prior informed consent (PIC) is obtained and access and benefit conditions set under Mutually Agreed Terms (MAT). This chapter’s main objective is to identify present and future climate-related challenges in the communities of Southern and Western Africa, specifically addressing communities in Benin. Zambia and Zimbabwe, with a view to finding relevant and potentially adaptable plant genetic material from local, national and international pools of genetic resources that can be used by communities and national breeding programs to adapt to climate change. It is based on the hypothesis that migrating climates lead to an increased possibility of using adapted germplasm/traits/populations/varieties which were developed in other areas, countries, continents, which might already have faced similar climate changes. Species and variety diversification can be effective in strengthening farmers’ capacity to adapt to climate change, therefore the introduction of gene-based traits from ‘foreign’ germplasm can also enhance adaptive capacity, and access and benefit sharing laws influence how adapted germplasm is accessed/provided (Halewood et al., 2017). The first section of this paper introduced the topic of climate change in different communities in Southern and Western Africa and the challenges it presents to agriculture in the region. The second section of this paper provides a summary of the methodologies used to identify climate related changes and determine potentially adaptable material that can be accessed by the communities and national research organizations through various access and benefit sharing regimes. Section three provides a synopsis of the results, starting with a summary of the present and future climate related challenges faced by these communities and a presentation of the potentially suitable PGRFA from national gene banks and international collections for each of the communities. The final section concludes with a look at the policy implications for access and benefit sharing (ABS).

21.2 Methodology The study draws upon case studies of communities in Benin, Zambia and Zimbabwe. These case studies look at how climate change drives the interdependence and exchange of genetic resources and how they may affect access and benefit sharing of the resources. The research strategy involved a step-by-step methodology combining various approaches such as GIS and crops suitability modelling to select suitable varieties for climate change adaptation (Vernooy et al., 2016). 21.2.1

Reference Sites and Crops

National research partners comprised of breeders, national gene banks and extension workers in Zambia, Zimbabwe, and Benin were engaged in the selection of reference sites and crops based on their experience working in these communities. The selection of the crops was based on their relevance for food security and livelihoods and importance of the crops for climate change adaptation (Table 21.1).

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Table 21.1 Summary reference sites and selected crops.

Country

Site name

Zambia

Chikankata 16∘ 13′ 41′′ S, 28∘ 8′ 38′′ E

Rufunsa

Zimbabwe Tsholotsho

Benin

GIS location

Precipitation Temperature Altitude (mm per (MinimumReference (masl) annum) Maximum (∘ C) crop Agro-ecology

1264

782

18−26

Maize

Mixed crop and livestock with maize as a staple crop

15∘ 4′ 52′′ S, 29∘ 38′ 8′′ E

872

825

9−34

Sorghum Semi-arid mixed crop and livestock, maize, sorghum and millet are major cereals

19∘ 46′ 0′′ S, 27∘ 45′ 0′′ E

1093

564

6−30

Sorghum Arid to semi-arid mixed crop and livestock systems with sorghum, pearl millet and finger millet grown

Uzumba Maramba –Pfungwe (UMP)

17∘ 4′ 37′′ S 1∘ 941 56′ 50′′ E

600

8−32

Finger millet

Arid to semi-arid with mixed crop and livestock systems. Sorghum, pearl millet, finger millet cow peas are predominantly grown

Bonou

6∘ 53′ 59′′ N 2∘ 26′ 59′′ E

10

1099

22−35

Cow peas

Sub-equatorial climate with two rainy seasons, farmers practice mixed crop and livestock farming

42

1081

22−33

Maize

Sub-equatorial climate with mixed crop and livestock systems

Tori-Bossito 6∘ 30′ 11′′ N, 2∘ 8′ 42′′ E

Source: Authors’ compilations.

21.2.2

Data and Methods

The first step involved carrying out an analysis of the community’s past and future climate challenges. Climate and weather changes between 2008–2015 were obtained using data from a Where2 weather data and this was corroborated with information from focus group discussions (FGDs) held with farmers in the referenced communities. Farmers pointed out the most prominent observations in terms of temperature and

2 This is an online resource where daily weather of sites can be accessed using their GPS coordinates. It is available at www.awhere.com and is free for sub-Saharan Africa only.

21.2 Methodology

precipitation changes: shifting seasons and extreme weather events. Farmers also gave an account of their coping strategies and desired traits for climate change adaptation. Future climate projections of the selected sites were obtained using 2050s projections from WorldClim3 . The second step involved using GIS-based selections of crop varieties from different sources that have been collected in climatic conditions that are similar/analogous to the new and future climate conditions at the selected sites. Databases with accessions from different sources such as GENESYS4 and national gene banks were used. Genesys is a global portal with information about plant genetic resources for food and agriculture. It is a source from which germplasm accessions from gene banks around the world can easily be found and ordered. It is comprised of collections held by national gene banks (these are already in the MLS), CGIAR centers, European gene banks, the USDA and some universities and research organizations. It is freely available for use and contains relevant passport data for each of the accessions. Varieties of the selected crops were screened using a combination of GIS and climate datasets (current and future) from WorldClim to develop climate profiles (both current and 2050s) for each accession,5 in order to develop a predictive tool to identify suitable varieties. A total of 19 bioclimatic climatic variables were extracted using the BIOCLIM algorithm at 2.5 arc minutes6 resolution using the program DIVA-GIS7 . Most of these variables were associated with different precipitation and temperature regimes characteristic of the different habitats of the selected crops. Agro-ecological variables at each locality were extracted using ArcGIS 10. Each accession had a unique agro-ecological zone. Since the accessions have been clustered together based on three variables (annual average temperature, annual precipitation and agro-ecological zone), calculations were made for the annual average temperature and annual precipitation variables using the formulas ((tmin1+tmax1)/2+ (tmin2+tmax2)/2+(tminn +tmaxn )/2)/12 and (prec1+prec2+precn ), respectively. Finally, the selected accessions from the national gene banks and international sources were mapped to provide a visualization of the change in the number and geographic spread of accessions at present and in the 2050s. It is important to note that this methodology has its limitations in that it only considers variables such as temperature, precipitation yet other variables such as soil characteristics or the epidemiology of crop pests and diseases may vary and influence the growth and development of crops. However, further observations can be made by obtaining and testing the relevant varieties with farmers in the field.

3 WorldClim is a set of global climate layers (climate grids) with a spatial resolution of about 1 square kilometer. The data can be used for mapping and spatial modeling in a GIS or with other computer programs. 4 Genesys is a free data portal that collates collections from international gene banks such as the USDA; European gene bank; the national gene bank material that has been declared in the MLS; 5 This exercise in effect allows each accession to have a unique climate profile based on temperature and precipitation over the growing season 6 An arc minute is a unit of angular measurement equal to one sixtieth (1/60) of one degree 7 DIVA-GIS is a free computer program for mapping and geographic data analysis (a geographic information system. It is used to map out and combine GIS based accessions with climate data so that each accession has a unique climate with a set of 19 bioclimatic variables.

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21.3 Results and Discussion 21.3.1

Summary of Climate Change in Selected Sites

Climate trends in Africa indicate that most regions have experienced temperature increases between 1 and 2 degrees Celsius. Precipitation on the other hand is less clear with large temporal and spatial variability, precipitation has decreased in some regions, especially Northern and Sahelian regions of Africa, and increased in some regions, such as Southern Africa, causing floods. Eastern Africa has experienced extreme variability in rainfall with long dry spells and floods. Looking at the selected sites, past trends in temperature and precipitation in Zimbabwe indicate an increase in temperature and precipitation and increased variability in rainfall amounts over time. Trends in precipitation and temperatures from 2008 to 2015 in Tsholotsho and Uzumba Maramba Pfumbwe (UMP) indicate that maximum temperatures have been increasing slightly since 2008 and there has been increased variation in rainfall patterns. In Zambia, past trends also indicate an increase in temperature and a decrease in precipitation in both sites of Rufunsa and Chikankata. The two sites in Benin, have similar trends, maximum temperatures have been constant since 2008 while minimum temperatures have shown a slight increase, and precipitation has been variable over time. High variability in rainfall coupled with shifting planting seasons and increased temperatures in most of the selected sites have led to losses in productivity and yields. In some cases, the prevalence of diseases and pests have increased. There have also been losses in genetic diversity resulting in a lower number of varieties that farmers can grow, affecting cropping patterns and food and livelihood security in these communities (Table 21.2). Other factors not related to climate change have also led to loss of some varieties grown by farmers as they are no longer suitable for the market or home consumption, in many cases these preferences have resulted in narrowing the varietal base available for farmers and lowering their ability to cope with climate change. As a result of these factors, farmers have tended to rely on varieties with traits such as drought tolerance and early maturity. In some areas farmers have switched to more resilient crops such as cassava, millet and sorghum as a strategy for coping with food insecurity resulting from climate change. Future trends on climate change vary from site to site. Comparing the present and the predicted climate of the 2050s, Eastern and Southern Africa would in the 2050s experience higher precipitation rates and higher temperatures but rainfall patterns will be erratic leading to further losses in productivity. Due to these increased temperature and precipitation regimes, disease prevalence would also be increased further; in particular, aflatoxins will increasingly affect post-harvesting and agro-processing of food, worsening food insecurity. Temperatures in Western Africa are predicted to rise and the increase in precipitation will result in the shifting and shortening of seasons. In most of the communities, early maturing, drought tolerant and disease resistant varieties will be needed for breeding and use by farmers (Table 21.2). 21.3.2 Finding Potentially Adaptable Accessions from a Pool of National and International Plant Genetic Resources Using climate and GIS modelling, accessions with the potential to adapt to the climatic conditions were identified from a pool of national gene bank collections. The same was

21.3 Results and Discussion

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Table 21.2 Summary effects of climate change and coping strategies 2008–2015.

Country

Site

Temperature changes in 2050s (∘ C)

Zambia

Chikankata

+1.4

314

Loss of diversity (3 varieties), increased incidences of pests and diseases

Farmers identified 3 drought tolerant varieties for use

Rufunsa

+1.5

427

Shifting seasons, loss of diversity and yield losses

Switching to more drought tolerant crops i.e pearl millet, finger millet, cassava; and early planting

Tsholotsho

+1.3

286

Shifting seasons, loss of diversity,food insecurity, increased incidences of pests and disease and reduction

Reliance on 3 main varieties of sorghum, using earlier maturing varieties

Uzumba Maramba Pfungwe

+1.2

316

Shifting seasons, loss of diversity (5 varieties lost), yield losses, increased pests and diseases

Early planting, use of early maturing varieties

Bonou

+0.6

193

Loss of diversity, yield loss and food insecurity

Early maturing varieties

Tori-Bossito

+0.8

252

Loss of 3 varieties of maize, yield losses, food insecurity

Switching to other crops, use of early maturing varieties

Zimbabwe

Benin

Precipitation changes

Climate change effects on cropping systems

Coping strategies

Source: Weather data analysis and information from FGDs with farmers.

done from a pool of international gene bank collections for each site as summarized below: 21.3.2.1

Zambia

Predictions for the 2050s climate and temperature for Zambia suggest that temperatures will experience an increase of 1.5∘ C in both sites and an increase of precipitation by 250–320 mm per annum. Based on the predicted increase of temperatures, potentially adaptable accessions of sorghum and maize were identified for the present and 2050s climate conditions of Chikankata and Rufunsa. The two sites are depicted in Figures 21.1 and 21.2 respectively. In Chikankata, the potentially adaptable accessions of maize for present and future climate conditions were assessed. Out of the 300 maize accessions currently available in the National gene bank (Figure 21.1) only 48 and 11 of them were found to be potentially adaptable for present and 2050s climate conditions, respectively (Figure 21.1). Likewise, when the germplasm available in the international sources of PGRFA were assessed, out of 2800 accessions in international collections, 125 maize accessions were assessed as being potentially adaptable for present conditions. The number of accessions adaptable to the predicted climate conditions of the 2050s was reduced to 87 (Figure 21.2). The limited options demonstrate that in the 2050s there will be less gene bank material that is suited for the climate and therefore Zambia will have to

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Figure 21.1 Potentially adaptable maize accessions for present and 2050’s climate conditions in Chikankata, Zambia.

21.3 Results and Discussion

Figure 21.2 Potentially adapted accessions of maize from international collections for Chikankata Zambia.

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look further afield to identify material that is potentially suitable for climate change adaptation. For Rufunsa, the sorghum accessions identified from the national gene banks again experience a reduction in the 2050s climatic scenarios, illustrating the need to look beyond domestic materials for germplasm that is potentially adaptable to present and future climate change (Figure 21.3). Looking at international sorghum collections, out of 300 potentially adaptable accessions for present climate conditions, 242 are held by ICRISAT while 51 accessions are held by the USDA (Figure 21.4). ICRISAT accessions are freely available through the multilateral system of access and benefit sharing, however, since the US is not party to the international treaty for plant genetic resources (ITPGRFA) the accessions held at the USDA have to be accessed through the Nagoya Protocol. 21.3.2.2

Zimbabwe

For the study site of Tsholotsho, 31 sorghum accessions (out of the total 178 sorghum accessions available in the National genebank) were identified as being potentially adaptable for the present climate conditions. Under the predicted conditions, the number of sorghum accessions was reduced to 20 (Figure 21.5). The number of potentially adaptable sorghum accessions for present climate conditions available from international sources was also assessed and it was found that the 514 accessions suitable and available for present conditions would be reduced to 242 under the predicted climatic conditions of 2050 (Figure 21.6). For the Uzumba Maramba Pfungwe site, 29 out of 90 accessions available in the national gene bank are deemed adaptable to present climate conditions, with six of these accessions being deemed adaptable for the 2050s (Figure 21.7). This reduction in the number of accessions shows that the national gene banks collections in Zimbabwe will not be sufficient to meet the genetic resources needs of communities and breeders alike. International collections will be needed in order to find suitably adapted materials for communities to use (Figure 21.8). For example, 36 accessions identified for present climate conditions are available in India and parts of East Africa. The seven accessions identified adaptable to the 2050s climate conditions are held India. All the accessions are held by ICRISAT and available in the MLS. 21.3.2.3

Benin

An analysis of the accessions of cowpea available in national collections reveals that out of 360 accessions, 157 are potentially suitable for present climate conditions in Bonou, and 46 accessions for future climate conditions. Similar to the sites above, suitability of gene bank accessions is reduced due to changes in temperature and precipitation in 2050s (Figure 21.9). A look at the international collections shows that most of the potentially adapted accessions are available in the Sahel region with 861 accessions in the present and 502 in the 2050s (Figure 21.10). For Tori-bossito, the trends are similar to the other sites; out of 225 national collections 137 are suitably adapted for Benin under present climate conditions and 37 for 2050s conditions (Figure 21.11). International gene bank collections show an increase in the number of potentially adaptable accessions of maize for future climatic conditions, due to a combination of the temperature and precipitation regimes in the 2050s that would be favorable for maize. The geographic spread of collections being from central and South America and Asia (Figure 21.12).

21.3 Results and Discussion

Figure 21.3 Potentially adaptable accessions of sorghum from the national gene bank for present and 2050’s climate conditions.

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Figure 21.4 Potentially adaptable sorghum accessions from international gene bank collections for Rufunsa.

21.3 Results and Discussion

Figure 21.5 Potentially adaptable sorghum accessions from National gene bank for present and 2050’s climate conditions in Tsholotsho, Zimbabwe.

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Figure 21.6 Potentially adaptable sorghum accessions from international sources for present and 2050’s climate conditions in Tsholotsho, Zimbabwe.

21.3 Results and Discussion

Figure 21.6 (Continued)

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Figure 21.7 Potentially adaptable gene bank accessions of finger millet for present and 2050’s climate conditions in UMP, Zimbabwe.

21.3 Results and Discussion

Figure 21.8 Potentially adaptable international gene bank accessions of finger millet for present and 2050’s climate conditions for UMP.

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Figure 21.9 Potentially adaptable national collections of cowpeas for present and 2050’s climate conditions in Bonou, Benin.

21.3 Results and Discussion

Figure 21.10 Potentially adaptable international gene bank accessions of cow peas for present and 2050’s climate conditions in Bonou, Benin.

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Figure 21.11 Potentially adaptable accessions of maize from national gene bank collection for Tori-Bossito, Benin.

21.3 Results and Discussion

Figure 21.12 Potentially adaptable international gene bank collections of maize for present and 2050’s climate conditions for Tori-bossito, Benin.

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21.4 Conclusions and Policy Implications Climate related challenges continue to determine present and future food security globally. However, the challenges presented are exacerbated in developing countries, whose resources for mitigation and adaptation is limited. Preliminary analysis on climate change in selected sites indicate that farmers are already experiencing climate related challenges, losing diversity of crops and facing imminent food insecurity. The climate of the 2050s in all of the sites studied in this chapter indicate an increase in temperature and precipitation, erratic and unreliable rainfall patterns and a shortening of the growing season, all of which would affect cropping patterns, productivity and food security in future. One of the main strategies for climate change adaptation identified by the IPCC’s fifth assessment report is to utilize gene bank material that would provide a diverse range of genetic resources, which can be used to improve productivity under changing climate. As temperature and precipitation regimes change, there will be climate change winners and losers in terms of the suitability of the genetic resources used by the communities in in Benin, Zambia and Zimbabwe. Some countries will experience temperature and precipitation regimes that are favorable and lead to an increase in genetic resources available from national and international collections; however, in most cases the genetic resources held by national gene banks are becoming increasingly insufficient to provide this needed genetic diversity. Despite the lack of genetic diversity at the national level, international gene bank collections have a wide range of materials collected from other countries that are potentially adaptable for present and future climate challenges. These materials also have the potential to provide important traits that can be used for breeding new crop varieties. These findings highlight the interdependence of countries on PGRFA for climate change adaptation (Lopez Noriega et al., 2012) and emphasizes the need to have policies both at the global and national levels that support and improve the access and exchange of information and genetic resources. Most of the materials identified in this study are held by CGIAR research centers such as CIAT for beans; ICRISAT for finger millet and Sorghum; and IITA for cowpeas and are easily accessible through the MLS. The MLS of access and benefit sharing provides for facilitated access of PGR for countries that are signatory to the treaty (Halewood et al., 2017). Communities can therefore request material from the holding institutions at no cost with the support of national gene banks or research institutions. Some of the materials identified are held by institutions such as USDA in countries that are not signatory to the Treaty, accessing these materials would require negotiations between respective countries for their access through provisions of the Nagoya Protocol involving Prior Informed Consent (PIC) and Mutually Agreed Terms (MATs). It is therefore important that countries though implementation of the Treaty and the CBD-NP put in place mechanisms through which PGRFA and related information is available and can be accessed by recipients. Breeding of new crop varieties with desirable traits for climate change is essential for the development of resilient seed systems. Breeders need not only capacity to identify accessions with potential traits, but also to have information on the traits. These requirements emphasize the need for characterization, evaluation and information sharing mechanisms to be improved so that breeders and other researchers working with these communities can access and assess the useful traits required for climate change adaptation.

References

Finally, improving countries’ capacities (both technical and financial) to be able to assess their current and future PGRFA needs is essential. National gene banks also require capacity to manage and conserve genetic resources and to compile and share information related to PGRFA characterization and traits identification.

References Chauvin, N.D., Mulangu, F., and Porto, G. (2012) Food consumption and production trends in Sub Saharan Africa. Prospects for the transformation of the Agricultural Sector. UNDP Working Paper Number 2012–011 available at: http://www.undp.org/content/ dam/rba/docs/Working%20Papers/Food%20Production%20and%20Consumption.pdf Climate Development and Knowledge Network (CDKN) (2014) IPCC’s Fifth Assessment Report, What’s in it for Africa? Available at: http://cdkn.org/wp-content/uploads/2014/ 04/AR5_IPCC_Whats_in_it_for_Africa.pdf FAO, (2009) The International Treaty for Plant Genetic resources for Food and Agriculture available at: http://www.fao.org/3/a-i0510e.pdf FAO (2009) Climate Change in Africa: The threats to Agriculture Produced by the FAO regional Office for Africa available at ftp://ftp.fao.org/docrep/fao/012/ak915e/ak915e00 .pdf Halewood M., Otieno, G., Nkhoma, C. et al. (2017) Access and benefit sharing for climate resilient seed systems. ISSD synthesis report 2017. IPCC (2007) Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, UK and New York, NY, USA IPCC (2014) Climate change 2014: Synthesis Report. Contribution of working Groups I, II, III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Core Writing team, R.K. Pachauri & L.A. Meyers (eds)). IPCC, Geneva Switzerland, 151 pp. López-Noriega, I., Galluzzi, G., Halewood, M. et al. (2012) Flows under stress: availability of plant genetic resources in times of climate and policy change. Working paper no.18. Copenhagen, Denmark. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Available online at: http://ccafs.cgiar.org/ Lobell D.B, Schlenker, W. & Costa-Roberts, J. (2011) Climate trends and global crop production since 1980. Science, 333 (6042) (2011), pp. 616–620, 10.1126/science. 1204531. NEPAD (2013) Agriculture in Africa Outlook available at: http://www.un.org/en/africa/ osaa/pdf/pubs/2013africanagricultures.pdf Niang, I., Ruppel, O.C., Abdrabo, M.A. et al. (2014) Africa. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken et al. (eds)]. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp. 1199–1265. http://ipcc-wg2.gov/ AR5/images/uploads/WGIIAR5-Chap22_FINAL.pdf Otieno G., Mungai O., and Ogalo V. (2013) Climate, Food, Trade: Where is the Policy Nexus in Kenya? Eds CUTS INTERNATIONAL ISBN 978-81-8257-177-8

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Thornton, P.K., Jones, P.G., Alagarswamy, G., and Andresen, J. (2009) Spatial variation of crop yield response to climate change in East Africa. Global Environmental Change, 19(1), 54–65. UNEP (2008) Agriculture, Agro-biodiversity and Climate Change. COP 9, MOP 4, Bonn Germany. http://www.un.org/en/ecosoc/docs/pdfs/agriculture.pdf Schmidhuber, J., and Tobiello, F.N. (2007) Global food security under climate change. PNASJ, 104 (50):19703–10708. Vernooy, R.; Bessette, G.; Rudebjer, P.; Otieno, G. (eds) (2016) A Resource Box for Resilient Seed Systems Handbook. Available at https://www.bioversityinternational.org/e-library/ publications/detail/resource-box-for-resilient-seed-systems-handbook/

523

Index a AAY. See Antyodaya Anna Yojana ABA. See Abscisic acid Abiotic stress adaptation to 150, 176–77 biotechnology in 391t–92t, 392 breeding and 149–53, 162–63, 266–68 germplasm and 170–74, 171t–72t grafting and 344–47, 346f heat tolerance 149, 173–74, 388 mitigation of 131, 133, 137–38 rainfall in 72–74, 72f–73f, 96–97 RH in 440–41 in wheat 160–61 AB-QTL. See Advanced backcross QTL analysis Abscisic acid (ABA) 57, 107–8 phenotyping 149 signalling 379, 382 synthase 162 ACCase. See Acetyl CoA carboxylase Access, in food security 7–9 Acetyl CoA carboxylase (ACCase) 176, 440 Acibenzolar-S-methyl 342 ACRE. See Agriculture and Climate Risk Enterprise Acyrthosiphon pisum 232 Adaptation, of crops abiotic stress and 150, 176–77 approaches to 131–41, 134f to drought conclusions on 85 introduction 71–72 temperature and 77–80

water conservation 82–85 water supply in 72–77, 73f–75f systems and 465–67 technology and 131–41 Adaptation factors 460–62 Advanced backcross QTL analysis (AB-QTL) 125 Aegilops cylindrica 440 Aegilops kotchyii 165 Aegilops spp. 477 Aegilops tauschii 159, 162, 165 Afghanistan 414, 484b–85b, 491b AFLP. See Amplified fragment length polymorphism Africa. See also Sub-Saharan Africa Benin 501, 505t, 508, 516f–19f, 520 GDP of 10 genetic diversity in discussion on 520–21 introduction of 499–501 methodology in 501–3, 502t summary on 504–8, 505t, 506t–7t, 509t–19t genetic resources of 166–68, 167t NERICA 425–26 water conservation in 84–85 Zambia 501, 502t, 504t, 505, 506t–7t, 520 Zimbabwe 501, 508, 511f–12f, 514f, 520 AGFACE. See Australian Grains Free Air CO2 Enrichment Experiment Agooecosystem 449–50, 453, 467 Agricultural Information Management Standards (AIMS) 306

Food Security and Climate Change, First Edition. Edited by Shyam S. Yadav, Robert John Redden, Jerry L. Hatfield, Andreas W. Ebert, and Danny Hunter. © 2019 John Wiley & Sons Ltd. Published 2019 by John Wiley & Sons Ltd.

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Index

Agriculture. See also Conservation agriculture; Food security CGRFA 311–12 in China 131–37, 134f CO2 impact on 4 CSA 17, 466 FAO 6–7, 17, 189, 290 IARI 201, 211, 215–16 IITA 160, 166, 167t, 168, 178 infrastructure management 137 ITPGRFA 13, 303, 424, 500–501 mechanization in 16 NARES 337 NARS 493 O3 impact on 5–6 PGRFA 327, 329, 500 technology and 131–37, 134f temperature impact on 6 Agriculture and Climate Risk Enterprise (ACRE) 324 Agrobacterium 163 -mediated transformation 390–92 Agrobiodiversity 482, 482b–83b Agroforestry systems 367–68 Agro-product processing 16–17 Ahuja, D. B. 15 AIMS. See Agricultural Information Management Standards Algeria 74 Allopolyploidy 159, 163 Alocasia macrorrhizos 359 Aluminum toxicity 174 Amino-acid transporters 64 Amplified fragment length polymorphism (AFLP) 421–22 Amylose/amylopectin ratio 79, 122–23 Andes 161, 369 Andragogy 485–86 Anhui province 133 Anthesis-silking interval (ASI) 259, 267, 381 Anthracnose 173t, 339–41, 363, 366, 370 Anti-oxidant enzymes 162 Antyodaya Anna Yojana (AAY) 17 Apanteles taragamae 344 Aphis gossypii 232 Apples 163, 343

weather and 452–53 Appreciative inquiry 485 Arabidopsis 340, 380, 386–87 Arachis hypogaea 97, 425 Arbuscular mycorrhizal fungi 368 ArcGis 133, 503 Arctic 2, 164, 419 Argana spinosa 163 Argentina 199, 252, 266 Army worm 342, 362, 365 Aroids 362–63, 365 Ascorbic acid 101, 173, 346 ASI. See Anthesis-silking interval Asia climate change and 325–28 IMPACT and GDP and 27–28, 27t trade and prices 42–45, 43t–44t O3 impact on 5 vegetable production in 290, 291t, 301–2, 311 Asiatic citrus psyllid 233 Australia drought in 71–85, 73f–75f, 81f farmer knowledge in 454–55 GRDC in 72, 73f O3 impact on 5 pests in 230, 233–40, 234f water strategies in 82–85 water supply in 72–77, 73f–75f wheat production in 77–82, 81f Australian Grains Free Air CO2 Enrichment Experiment (AGFACE) 77 Austria 451 Autopolyploidy 159 Availability, of food 7–8. See also Food security Avena sativa 105 Azadirachta indica 344 Azospirillium 285 Azotobacter 285 Azuki beans 38, 289

b Baby corn 259–60 Bacillus subtilis 153 Bacillus thuringiensis (Bt) 344, 426–28

Index

Backcrossing 148, 161, 178, 260–62 Background selection 261–62 Bacterial disease of vegetables 338–42 wilt in 153, 170, 344 Bactrocera cucurbitae 342 Bactrocera dorsalis 344 Bactrocera tyroni 233 Bajra-wheat 211 Bambara groundnut 38, 166–68, 167t Banana 320, 368, 378, 385, 387, 499 germplasm of 167t RTB and 369 transgenics of 392t Bangladesh 272, 325 Banswara 287 Barley 360, 384, 389, 435 CO2 effects and 53, 55t, 60–61 water use and 72–73, 82 Barley yellow dwarf virus (BYDV) 232, 235–38, 237f B-carotene 101 Bean, CO2 impact on 97–100, 98t. See also Legumes Beijing province 133, 138 Bengal famine 475 Benin 501, 505t, 508, 516f–19f, 520 Bentazon 441 Best management practices (BMP) for crop-weed competition 434–35 for water 279–81, 280f, 281t Beta carotene 427 Beta vulgaris 97, 109 Bhutan 272, 325, 481 BIoassay 423 BIOCLIM algorithm 503 Biodiversity Bioversity International 472–73, 473b–74b, 482b, 493 community-led efforts and 477–82, 479f–80f, 480t, 481b–83b Seeds for Needs 473, 473b–74b, 493 Biofertilizers 285 Biofuel 39, 190, 252 Biological nitrogen fixation (BNF) 139–40 Biotechnology abiotic stresses and 391t–92t, 392

AFLP in 421–22 bIoassay in 423 biosafety in 428 Bt in 426–28 CBD and 428 climate change and 413–15, 414f conclusion on 392–93 conservation in 415–20, 416f–18f crop varieties and 135–36 ELISA in 423 embryo rescue in 425–26 flooding tolerance and 383–85 GBS in 422 germplasm and 415 characterization of 420–22 exchange of 422–24 future strategies for 428–30 utilization of 425–28, 427t GMO and 426–27, 427t heat shock proteins and 385–88 heat stress and 385, 388 introduction to 377, 413 LAMP in 423–24 MAS in 125, 260, 261f, 426 PCR in 423 RAPD in 420–21 RFLP in 420–21 salinity tolerance and 388–90 SSR in 421 in temperate legumes 380–81, 388 in tropical crops 381–83 water availability and 378 wheat and 378–80 Biotic stress 172t–73t Bioversity International 472–73, 473b–74b, 482b, 493 Bird cherry-oat aphid 232–36, 234f, 240 Black gram 289 BMP. See Best management practices BNF. See Biological nitrogen fixation Bolivia 163, 472 Boron 83 Brassica 107, 132, 301 crop production of 10, 162, 290, 297t–98t Brassica napus 162 Brassica oleracea 342

525

526

Index

Brazil 146, 456–57 IMPACT and food security and 46–48, 47t–48t temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t maize production 252, 252t O3 impact on 5 Bread-making, grain quality 61, 80, 123 Breeding. See Crop production; Plant breeding Brevicoryne brassicae 232 Bromus tectorum 437 Bt. See Bacillus thuringiensis BYDV. See Barley yellow dwarf virus

c C3 crops CO2 impact on 4, 97–100, 98t, 120–22 O3 impact on 5–6 photosynthesis and 330–31 rising CO2 and 55–57, 56f weed competition and 435–36 C4 crops CO2 impact on 4, 97–100, 98t, 120–22 O3 impact on 5–6 photosynthesis and 330–31 rising CO2 and 55–57, 56f weed competition and 435–36 CA. See Conservation agriculture Cactoblastis cactorum 231 Cajanus acutifolius 175 Calcium transporter 427 California, US 451 Calluna vulgaris 436 Calvin cycle 63 CAM. See Crassulacean acid metabolism Cambodia 473, 473b, 493b Cameroon 363 Canada 11, 132, 266, 298t, 304, 427t Canada thistle 438 Canopy temperature 85, 105, 109, 149, 170, 179, 238 Cantaloupe 290, 295t Capsicum 336–37 Capsicum chinense 340 Carbon based sustainability index (CSI) 286

Carbon-concentrating mechanism (CCM) 63 Carbon dioxide (CO2 ) atmospheric rise in crop responses to 58–64 food quality and 59–61 introduction to 51–53, 52f measuring 53–54, 54f, 55t physiological responses to 54–57, 56f FACE technology and 53–54, 54f, 55t development of 138–39 grain quality and 79–80, 100–102 impact on agriculture 4 IPCC estimates of 2 photosynthesis and 330–31 roots and 100 stomatal transpiration and 331 temperature and 330–35, 333f, 334t, 438–40 water interactions and 77–80, 108–9 WUE and 4 Carbon markets 13 Carbon:Nitrogen ratio (C:N ratio) 64, 100–101 Caribbean 360, 362, 370. See also Latin America and Caribbean Carrots 290, 294t, 300t, 301, 386 CAS. See Cells Alive System CASS. See Chinese Academy of Agricultural Sciences Cassava 289, 361–62, 364–65, 422 Cauliflower 146 CBD. See Convention on Biological Diversity CCM. See Carbon-concentrating mechanism Cells Alive System (CAS) 418 Centaurea solstitialis 437 Central and West Asia and North Africa region (CWANA) 166 Centre for Study of Developing Societies (CSDS) 191 Cereals, trade in 42–45, 43t Cereal yellow dwarf virus (CYDV) 235 CFFRC. See Crops For Future Research Centre

Index

CGRFA. See Commission on Genetic Resources for Food and Agriculture Chambers, Robert 488 Cheatgrass 437 Chenopodium album 435 Chenopodium pallidicaule 163 Chicken food 256 Chickpea 105, 380 abiotic stress and 170–74, 171t–72t genetic resources of 162–63, 168–73, 169t, 172t maize-chickpea cropping sequence 274, 276t, 286 transgenics of 391t China climate change technologies in 131–41, 134f FACE experiment in 59 germplasm in 297t–300t IMPACT and food security and 46–48, 47t–48t GDP and 27–28, 27t temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t maize production in 252, 252t meat consumption in 41, 41t milk and egg production in 37, 37t O3 impact on 5 rice production in 32–33, 32t soybean production in 34, 34t vegetable production in 290, 291t–95t water conservation in 84–85 Chinese Academy of Agricultural Sciences (CASS) 134 Chloris gayana 438 Chlorophyll 60, 78, 108, 153, 332–33 meter of 149, 170, 285 Chlorophyll a/b binding protein 173, 176 The Christensen Fund 482–83 Chromosome doubling 264 Cicer arietinum 105 Cicer reticulatum 163 CIMMYT. See International Centre for Wheat and Maize Improvement CIP. See International Potato Center Circium arvense 438 Clethodim 441

Climate change awareness of 138 climate-crop modeling in 140 CO2 impact and 4, 58–59, 95–100, 98t, 120–22 crop production and genetic control and 119–26 impact mitigation on 10–13 divergent technologies and 14–17 drought and 71–85, 73f–75f, 81f farmers knowledge 449–67, 460f financing incentives and 13 food quality and 59–61, 138–39 food security 1–10 genetic resources and 413–15, 414f herbicide efficacy in 438–41 India government policies and 17–18 IPM and 15 mitigation and technology 131–41, 134f nitrogen fixation and 139–140 O3 impact of 5–6 population explosion and 414 positive impacts of 3 predicted impact of 10–13 research on 138 techniques for 137–41 temperature and 330–35, 333f, 334t temperature impact in 6 vegetables and in Asia 325–28 in SSA 320–24 water use changes and 82–84 Climate-crop modeling 140 Climate Smart Agriculture (CSA) 17, 466 Climate-Smart Landscapes 11 Climate-Smart Villages 11 C:N ratio. See Carbon:Nitrogen ratio CO2 . See Carbon dioxide Cocoa 35, 36t, 46t Coconut 415 Cocoyam 359, 362–63 Cocoyam root rot disease (CRRD) 363 Coffee prices of 45–46, 46t production of 35, 36t, 55t Colchicine 263–64

527

528

Index

Cold shock protein B (CspB) 153 Coleoptile 202–4, 204f Colletotrichum gloeosporioides 366 Colletotrichum spp. 338, 340 Colocasia esculenta 359 Combine harvester 200 Commission on Genetic Resources for Food and Agriculture (CGRFA) 311–12 Common lambsquarters 435–37 Community-led efforts barriers to 480t, 483–92, 491b biodiversity and 477–82, 479f–80f, 480t, 481b–83b climate impact and 472–73, 473b–74b, 475, 476b conclusions on 494 diminishing diversity and 492b–93b inequity and 474–75 introduction to 471–72 monocultures and 475 trust in 490, 491b wild species and 476–77 working systems in 493–94 Compensatory feeding 231 Computer simulations, of crop yield 81–82, 81f Conservation agriculture (CA) breeding methodology in 215–16 challenges of changing climate 196–98, 196f–97f depleting resources 193–95, 194f–95f profit decline 191–92, 192f conclusion on 220–21 genotypes adapted for 202–13, 204f–9f, 211f–13f introduction to 189–91 in Northern India 214–19, 215f, 219t–20t, 221f technology gaps of 199–202, 201t WUE and 218–19, 219t, 220f, 220t Convention on Biological Diversity (CBD) 428, 501 Cost-benefit analysis 140 Cotton 46t, 266 canopy temperature 238 CO2 impact on 97–100, 98t cotton-wheat cropping system 206

GMO of 427, 427t IMPACT prediction of 35, 36t Cotton bollworm 231 Cowpea 10, 473b, 520 in Benin 508, 516f–17f collection of 166–67, 167t, 178 maize-cowpea cropping system 275t–76t production of 289 Crassulacean acid metabolism (CAM) 121 Crateagus sp. 163 Crop Altas 474b Cropping systems cotton-wheat 206 maize-chickpea 274, 276t, 286 maize-cowpea 275t–76t rice-wheat 189–90, 195, 214, 215f Crop production atmospheric CO2 and 79–80 BMP for 274 CA breeding methodology of 215–16 computer simulations of 81–82, 81f DH technique 263–65, 264f–65f fallow land and 74–77, 75f genetic control and 119–26 grain quality and 79–80, 100–102 heat shock proteins and 385–88 management of introduction to 251 maize scenario 251–56, 252t–53t, 253f–55f nutrients in 281–87, 282t, 283t–84t pedigree breeding 257–58 single cross hybrids 256–66 sowing time in 276–78, 277f, 277t system optimization 272–76, 273f, 275t–76t tilling in 278 transplanting in 279 water in 279–81, 280f, 280t–81t microbial resources in 329–30 pests and 232–40, 234f, 237f QPM in 260–62, 261f rotations 74–77, 75f vegetables 290, 291t–95t breeding of 335–38, 336t sustainability 328–29, 367–69

Index

water BMP in 279–81, 280f, 281t watermelon 290, 292t weed competition in 434–37 WUE in 76, 79, 82–83 Crops For Future Research Centre (CFFRC) 168 Crop Trait Mining Platforms 305–7 Crop water stress index (CWSI) 105 Crop wild relatives (CWR) as genetic diversity 161–62, 174–76 germplasm and 124 portal of 305 of roots and tubers 369 Crop Wild Relatives and Climate Change 11 Crossbreeding 147–48, 177, 260–62. See also Plant breeding CRRD. See Cocoyam root rot disease Cryopreservation 417–19, 418f CSA. See Climate smart agriculture CSDS. See Centre for Study of Developing Societies CSI. See Carbon based sustainability index CspB. See Cold shock protein B Cuba 371 Cucumbers 290, 293t, 299t CWANA. See Central and West Asia and North Africa CWR. See Crop wild relatives CWSI. See Crop water stress index CYDV. See Cereal yellow dwarf virus Cyrtosperma merkusii 359 Czech Republic 107, 317

d Dallisgrass 438 DArT. See Diversity Array’s Technology Decision Support System for Agro-technology Transfer (DSSAT) software 26, 29 Deforestation 10, 51, 369, 433, 434, 488 Deoxynivalenol 239 Deschampsia flexuosa 436 DH. See Doubled haploid Diabrotica virgifera virgifera 231 Diamondback moth 342, 344 Diaphorina citri 233

Dienoic fatty acids 387 DIF. See Directory Interchange Format Dioscorea rotundata 370 Dioscorea spp. 359 Dioxide. See Carbon dioxide Directory Interchange Format (DIF) 303 Diseases Anthracnose 173t, 339–41, 363, 366, 370 BYDV 232, 235–38, 237f fungal pathogens 238–40, 338–42 grafting and 344–47, 346f pests and bird cherry-oat aphid 232–36, 234f, 240 host plant distribution and 240–41 insects 342–44 plant viruses and 235–38, 237f of vegetables 338–42 DIVA-GIS 503, 503n5 Diversity Array’s Technology (DArT) 388 Diversity Seek initiative (DivSeek) 306–7 DNA markers 147, 151–52, 421 Doubled haploid (DH) technique 263–65, 264f–65f Downy mildew 172t–73t, 239 Drosophilia melanogaster 233 Drought in Australia 71–85, 73f–75f, 81f CO2 and 77–80, 108–9 food security and 8 germplasm and 170–73, 172t–73t nutrients and 77–80 in Spain 71–85, 73f–75f, 81f stress, genetics of 119, 126 technology adaptations to 131–41 temperature and 77–80, 102–6, 103f tolerance in corn 136, 266–67 in temperate legumes 380–81 in tropical crops 381–83 in wheat 378–80 water availability and 378 water conservation and 82–85 water effects and 106–8 water interactions in 77–80 DroughtGardTM hybrid maize 153

529

530

Index

Drought tolerant maize for Africa (DTMA) 167 Dryland expansion 3 DSSAT. See Decision Support System for Agro-technology Transfer DTMA. See Drought tolerant maize for Africa Dwarf shrub 436

e East Asia 42–45, 43t–44t. See also Asia ECCDB. See European Central Crop Data Base Ecological niche model (ENM) 476–77 Ecotilling 163 ECPGR. See European Cooperative Programme for Plant Genetic Resources EFP. See Epidermal patterning factor EFSA. See European Food Safety Authority Eggplant 290, 294t, 301, 301t rootstock 345 Eggs consumption of 39, 41t IMPACT predictions on 37, 37t trade in 42–45, 44t Egypt 462 EI Niño weather 136–37 Electrical penetration graph (EPG) 232 Electrophoresis gel 421, 423 ELISA. See Enzyme-linked immunosorbent assay El Niño Southern Oscillation (ENSO) 326 El Niño weather 414 Elsinoe batatas 364 Elymus repens 439 Embryo rescue 425–26 ENM. See Ecological niche model ENSO. See El Niño Southern Oscillation Enzyme-linked immunosorbent assay (ELISA) 423 EPG. See Electrical penetration graph Epidermal patterning factor (EFP) 126 ERF. See Ethylene responsive factor Erysiphe cichoracearum 340 Essential Commodities Act 17 Ethiopia 38, 177, 453, 461–62

Seeds for Needs and 473, 473b–74b, 493 Ethylene 149 Ethylene responsive factor (ERF) 382, 384–85 EU. See Europe EURISCO. See European Internet Search Catalogue Europe (EU) crop protection system of 137 food security and 46–48, 47t–48t growing season of 11 rice production in 32–33, 32t temperature 28–30, 28t, 30t European Central Crop Data Base (ECCDB) 308 European Cooperative Programme for Plant Genetic Resources (ECPGR) 303–4 European Food Safety Authority (EFSA) 153 European Internet Search Catalogue (EURISCO) 303–4, 306, 308–9 Ex situ conservation 166, 416 Ex situ germplasm 296–309, 297t–301t

f FACE. See Free Air CO2 Enrichment Fadama wheat 160–61 systems 320 Fallow land 74–77, 75f FAO. See Food and Agriculture Organization Farmer Field School (FFS) 493–94 Farmer knowledge. See also Community-led efforts adaptation factors 460–62 beliefs in 453–56 climate change and 449–53 climate hazards 458–59, 460f indigenous 463–65 resourcefulness and 484b–85b risk experience and 456–58 system adaptation and 465–67 transformation and 465–67 water and 462–63 weather and 452–53

Index

Faulkner, Edward 199 Fe. See Iron Fertilizer application of 284 biofertilizers 285 nitrogenous 4, 59, 190 FFS. See Farmer Field School FIGS. See Focused Identification of Germplasm Strategy Financing incentives 13 Finger millet 171t–73t, 483b, 514f–15f Finland 132 FlavrSavr 426 Flooding tolerance 383–85 Floods, food security and 8 Flumiclorac 440 Fluthiacet 440 Focused Identification of Germplasm Strategy (FIGS) 165, 165t, 306 Food and Agriculture Organization (FAO) 189, 290 CGRFA 311–12 food security and 6–7, 17 Food processing 16–17 Food production units (FPU) 26 Food quality, protein content 138–39 Food security access in 7–9 adaptation approaches to 131–41, 134f availability and 7–8 biotechnology and 377–93, 391t–92t CO2 impact on 4 crop improvement and 123–24 CSA and 17 disease and 229–41, 230f, 234f, 237f divergent technologies and 14–15 FAO and 6–7 farmer knowledge in 449–67, 460f food processing and 16–17 genetic resources abiotic stress adaptation and 176–77 climate change and 159–60 CWR and 161–62, 174–76 forage and range species 166 germplasm and 170–74, 171t–73t in humid tropics 166–68, 167t nutritional quality and 174

plant phenomics in 168–70 strategic overview of 177–78 summary of 179 temperate crop zone 164–66, 164t–65t under-utilized species 163–64 IMPACT model climate assumptions 28–30, 30t conclusions to 48–50 consumption 38–42, 40t–42t description of 26 food security 46–48, 47t–48t introduction to 25–26 production and 30–37, 31t–34t, 36t–37t trade and prices 42–46, 43t–44t, 46t underutilized crops 38 India government policies and 17–18 IPCC and 1–9 IPM and 15 mechanization and 16 mitigation to 11–13, 131–41, 134f O3 impact on 5–6 pests and 229–41, 230f, 234f, 237f policies on 13 predicted impacts on 10–13 root and tubers 359–71 SFS and 17 in SSA 8–9 stability and 7–8 sustainable production and 15 utilization and 7, 9–10 vegetable production in Asia 290, 291t, 301–2, 311 in China 290, 291t–95t in India 290, 291t–95t, 297t–301t resources of 289–312, 291t–95t, 297t–301t in USA 290, 291t–95t, 298t–301t Foreground selection 260–61 Former Soviet Union (FSU) food security and 46–48, 47t–48t GDP and 27–28, 27t grain production in 35, 36t rice production in 32–33, 32t temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t

531

532

Index

Fossil fuels 51, 52f Foxtail millet 171t–73t, 177 FPU. See Food production units Free Air CO2 Enrichment (FACE) 4, 79–80, 97, 120 pests and 230 technology of 53–54, 54f, 55t test device development 138–39 Fructose-1,6-bisphosphate aldolase 63 Fruit borer 342 Fruits consumption of 39, 40t IMPACT prediction of 35–37, 36t–37t trade in 42–45, 43t Fruit worm 342 FSU. See Former Soviet Union Fukuokain, Masanobu 199 Fungal pathogens 238–40, 338–42, 366 Furrow planting 276–79 Fusarium 271 Fusarium pseudograminearum 239 Fusarium wilt 344

g GA. See Gibberellic acid Gaeumannomyces graminis 330 Galactosidase 380 GAMS. See General Algebraic Modeling System Gansu province 133 GAP. See Good agricultural practices GBS. See Genotyping by sequencing GCDT. See Global Crop Diversity Trust GCM. See General Circulation Model GDP. See Gross domestic product Genebank accession 152, 166, 307, 327 General Algebraic Modeling System (GAMS) program 26 General Circulation Model (GCM) 28–29, 467 GENESYS 12, 303–6, 309, 312, 503, 503n4 Genetically modified organism (GMO) 426–27, 427t maize 266, 266f Genetic engineering 63–64. See also Biotechnology

of CO2 responsiveness 125–26 Genetic resources. See also Community-led efforts abiotic stress and 160–63, 176–77 in Africa 166–68, 167t Bioversity International 472–73, 473b–74b, 482b, 493 of chickpea 162–63, 168–73, 169t, 172t climate change and 159–60, 413–15, 414f Crop Trait Mining Platforms 305–7 cryopreservation of 417–19, 418f CWR and 161–62, 174–76, 305 EURISCO 303–4, 306, 308–9 ex situ collection 416 ex situ germplasm 296–309, 297t–301t forage and range species 166 GENESYS 304–5 germplasm and 170–74, 171t–73t biotechnology 415–20, 416f–18f future strategies for 428–30 utilization of 425–28, 427t herbarium in 419 in humid tropics 166–68, 167t ICRISAT and 159, 168–70, 169t, 177–79 in situ collection 310–11, 415 introduction to 159 of microbes 329–30 nutritional quality and 174 PGRFA 327, 329, 500 plant phenomics in 168–70 semi-arid tropics and 168, 169t SGSV in 419–20 SINGER 303 stability and 290–96 strategic overview of 177–78 summary of 179 temperate crop zone 164–66, 164t–65t of tomato 300t–301t, 301–2 under-utilized species 163–64 vandalism and 414–15 of vegetables stocks in 289–312, 291t–95t, 297t–301t in sustainable production 328–29 watermelon 298t–99t, 301

Index

WIEWS 296–301, 306, 309 Genetic Resources Center (GRC) 166 Genome wide association study (GWAS) 125 of roots and tubers 369 Genotypes in CA 202–13, 204f–9f, 211f–13f GBS in 422 rising CO2 and 62–63 Genotyping by sequencing (GBS) 422 Geographic information systems 152 Germany 80, 106, 132, 263 Germplasm. See also Genetic resources abiotic stress and 170–74, 171t–72t of banana 167t characterization of 420–22 collecting of 415 cryopreservation of 417–19, 418f drought tolerance 170–73 enhancement of 148 exchange of 422–24 FIGS 165, 165t future strategies for 428–30 GRIN 304–6 heat tolerance in 173–74 multiple stress tolerances 170, 171t–73t SGSV in 419–20 soil nutrient imbalance and 174 of tomato 309, 311 utilization of 425–28, 427t vandalism and 414–15 Germplasm Resources Information Network (GRIN) 304, 306 Gherkins 290, 293t GHG. See Greenhouse gas Giant foxtail 437 Giant taro 359, 363 Gibberellic acid (GA) 123 in CA 202 plant breeding and 149 Global Carbon Project 2015, 52f Global Crop Diversity Trust (GCDT) 304 Gluten 61, 79, 123 Glycine max 95, 167t, 435. See also Soybean Glyphosate 438–41 GM. See Genetically modified

GMO. See Genetically modified organism Goat grass 440 Good agricultural practices (GAP) 322 Gossypium hirsutum 97. See also Cotton GRACE. See Gravity Recovery and Climate Experiment Grafting 323, 344–47, 346f Grain quality 61, 79–80, 100–102, 123 Grains Research and Development Corporation (GRDC) 72, 73f Gravity Recovery and Climate Experiment (GRACE) 193 GRC. See Genetic Resources Center GRDC. See Grains Research and Development Corporation Green chili 289–90 Greenhouse gas (GHG) 52–53 food security and 1, 10, 17–18 Greenland 11 Green peach aphid 342 Green-Seeker sensors 285 GRIN. See Germplasm Resources Information Network Gross domestic product (GDP) in Africa 10 climate change impact on 8 IMPACT and 27–28, 27t Groundnut 168, 169t, 170, 171t–72t, 176 Guard cells 57, 107 GWAS. See Genome wide association study

h Halocarbon 119, 433 Haploid induction 263, 264f Haryana, India rice-wheat cropping in 214, 215f water in 193–95, 194f–95f wheat cultivation in 192, 192f, 205–6, 206f Hawkmoth 231 Heat shock proteins 385–88 Heat stress 385 Heat tolerance. See also Abiotic stress germplasm and 173–74 in temperate legumes 388 in wheat 149 Heat wave damage 1

533

534

Index

Hebei province 133 HEL. See Highly erodible land Helicoverpa armigera 175, 231, 342 Hemipteran insects 231–33 Herbarium 419 Herbicides efficacy of 438–41 solar radiation and 441 in weed management 343 Herbicide tolerant (HT) 266 Heterologous promoter 64 Hexaploid wheat 148, 159, 162, 165, 386 Highly erodible land (HEL) 463 High throughput phenotyping 150–51 Himalaya 325, 452 Honduras 12, 473b Honeysuckle berry 164 Hordeum vulgare 97, 166, 435. See also Barley HT. See Herbicide tolerant Huang-Huai-Hai area 134, 134f Hunan province 133 Hunger, IMPACT model of 46–48, 47t–48t Hybrid DroughtGardTM 153 maize seed 269–72 SCH in 256–66, 272, 273f wheat 82

i IARI. See Indian Agricultural Research Institute ICARDA. See International Center for Agricultural Research in Dry Areas ICDS. See Integrated Child Development Scheme ICRISAT. See International Crops Research Institute for Semi-Arid Tropics IITA. See Institute for Tropical Agriculture IMPACT. See International Model for Policy Analysis of Agricultural Commodities and Trade Impact of Climate Change on Agriculture Production, Food, and Nutritional Security (Yadav) 11

India conservation agriculture in challenges of 191–98, 192f, 194f–97f genotypes adapted for 202–13, 204f–9f, 211f–13f introduction to 189–91 in Northern India 214–19, 215f, 219t–20t, 221f technology gaps of 199–202, 201t depleting resources of 193–95, 194f–95f food security and 46–48, 47t–48t GDP and 27–28, 27t government policies and 17–18 maize in 251–56, 252t–53t, 253f–55f NFFWP 17 NFSM 17–18 O3 impact on 5 rice production in 32–33, 32t root and tuber production in 35, 36t severe weather in 1–2 temperature 28–30, 28t, 30t tillage in 199–200 trade and prices 42–46, 43t–44t vegetable production in 290, 291t–95t, 297t–301t water in 193, 194f–95f Indian Agricultural Research Institute (IARI) 15, 201, 211, 215–16 Indian mustard 139 Indonesia food security and 46–48, 47t–48t oil production in 35, 36t temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t INEA. See International Network for Edible Aroids INM. See Integrated nutrient management Inner Mongolia province 133 Insect pests 231–34, 234f. See also Diseases of vegetables 342–44 In silico breeding 149 In situ collection 310–11, 415 Institute for Tropical Agriculture (IITA) 160, 166, 167t, 168, 178

Index

Institut Pierre-Simon Laplace (IPSL) 29–30, 30t Integrated Child Development Scheme (ICDS) 17 Integrated nutrient management (INM) 284–85 Integrated pest management (IPM) 15 Integrated water resource management (IWRM) 326–27 Intellectual property rights (IPR) 257 Interfering RNA (RNAi) 382–83 Intergovernmental Panel on Climate Change (IPCC) 131, 499–500 climate change definition of 2 SRES 4 International Center for Agricultural Research in Dry Areas (ICARDA) 160, 164–65, 164t, 178–79 International Centre for Wheat and Maize Improvement (CIMMYT) 161–62, 165–66, 169 International Crops Research Institute for Semi-Arid Tropics (ICRISAT) 159, 168–70, 169t, 177–79, 333, 466 International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) assumptions of 26–28, 27t–28t climate assumptions of 28–30, 30t conclusions to 48–50 consumption and 38–42, 40t–42t description of 26 food security and 46–48, 47t–48t introduction to 25–26 production and 30–37, 31t–34t, 36t–37t trade and prices 42–46, 43t–44t, 46t underutilized crops 38 International Network for Edible Aroids (INEA) 370 International Potato Center (CIP) 366, 481b International Rice Research Institute (IRRI) 385 International Treaty for Plant Genetic Resources for Food and Agriculture (ITPGRFA) 13, 303, 424, 500–501

trade and prices 42–46, 43t–44t International Triticeae Mapping Initiative (ITMI) 384 International Union for Conservation of Nature (IUCN) 310 Iodine 60–61 Iowa 463 IPCC. See Intergovernmental Panel on Climate Change IPM. See Integrated pest management Ipomoea batatas 359 IPR. See Intellectual property rights Iran 290, 291t–95t, 299t Irish Potato Famine 475 Iron (Fe) content 59–61, 101 deficiency of 122–23 IRRI. See International Rice Research Institute Irrigation management 279–81, 280f, 280t–81t ISPL. See Institut Pierre-Simon Laplace Itch grass 435 ITMI. See International Triticeae Mapping Initiative ITPGRFA. See International Treaty for Plant Genetic Resources for Food and Agriculture IUCN. See International Union for Conservation of Nature IWRM. See Integrated water resource management

j Japan 418 Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute 29 Japonica rice cultivar 62–63 Jawsjan province 485b Jiangsu province 133, 137

k Kañiwa 163 Kenya 135, 322–24, 336, 466, 473b Kerala state 192, 493 Khammouane province 488

535

536

Index

Kharif

252, 255, 277f, 277t. See also Monsoon nutrient management and 283, 283t Krishi Vigyan Kendra (KVK) 493 Kudzu 437 KVK. See Krishi Vigyan Kendra Kyrgyzstan 326–27

l LAC. See Latin America and Caribbean LAI. See Leaf area index Lam Dong province 346 LAMP. See Loop-mediated isothermal amplification Land use 51, 52f, 77, 325, 328. See also Community-led efforts urban competition for 132 La Niña 414, 414f Laos 473, 473b Latin America and Caribbean (LAC) CA in 190 GDP and 27–28, 27t sugar production in 35, 36t temperature 28–30, 28t, 30t LCC. See Leaf colour chart Leadership style 491 Leaf area index (LAI) 57 Leaf colour chart (LCC) 285 Leaf senescence 108, 267 Leaf stomatal conductance 98t LeasyScan 169 Legume pod borer 342, 344 Legumes 388 biotechnology and 380–81 nitrogen fixation and 139–40 rotational effects and 14 salinity tolerance and 390 Lepidoptera 231, 233 Leucine zippers 379–80 Leucinodes orbonalis 342 Liaoning province 133 Lima beans 38 Literacy, in farming 490–91 Little millet 483b Livestock feed components of 41–42, 42t forage and range species 166

predicted climate impact on 10–13 Lonicera caerilea 164 Loop-mediated isothermal amplification (LAMP) 423–24, 429 Lycopene 101

m MABB. See Marker assisted backcross breeding strategies Magnesium 60, 282, 282t Maize by area of world 252, 252t in Benin 518f–19f cotton-wheat cropping system 206 DH technique in 263–65, 264f–65f DroughtGardTM hybrid 153 DTMA project 167 haploid induction in 263, 264f hybrid seed 269–72 IMPACT predictions on 33, 33t improvement of 256 in India 251–56, 252t–53t, 253f–55f irrigation in 280–81, 280f, 281t MABB 262 maize-chickpea cropping sequence 274, 276t, 286 male:female synchrony in 269, 269f management of 251–56, 252t–53t, 253f–55f nutrient BMP for 281–82, 282t O3 impact on 5 prices of 45–46, 46t QPM in 15, 260–62, 261f, 285 sequential cropping in 275t–76t transgenic development of 136, 265–68, 266f, 391t Male:female ratio 271 Male:female synchrony 269, 269f Managed environment facility (MEF) 151 Manduca sexta 231 Manihot esculenta 289, 359 MAP kinase pathway 389 Marker assisted backcross breeding strategies (MABB) 262 Marker assisted selection (MAS) 125, 260, 261f, 426 Marker trait association (MTA) 176

Index

Maruca vitrata 342, 344 MAS. See Marker assisted selection Mauna Loa Observatory, Hawaii 51 Maximum residue limits (MRL) 322 Meats consumption of 41, 41t IMPACT predictions on 37, 37t trade in 42–45, 44t Mechanization, in agriculture 16 Mediterranean region 72, 78, 101, 319, 326. See also Spain MEF. See Managed environment facility Mekong delta 493b Melia azedarach 344 Melon fly 342 MENA. See Middle East and North Africa Mendel’s laws 335, 336t Mesophyll cells 331 Methane 5, 12, 18, 119, 145, 433–34 Met Office Hadley Centre 29 Metroxylon spp. 415 Mexico 205, 210 coffee in 368 maize production in 252t vegetable production in 295t, 298t–99t Microbial resources 329–30 Middle East and North Africa (MENA) IMPACT and temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t O3 impact on 5 sugar production in 35, 36t Milk consumption of 39, 41t IMPACT predictions on 37, 37t trade in 42–45, 44t Millet 38, 132, 134–35 MIROC model 28t, 29–30, 30t Mites 342–44 Mitigation, of climate change 10–13 Mitochondria 332, 386 MLS. See Multilateral System Mobile banking services 324 Moisture stress 135, 151, 266–68, 278–79 CO2 rise and 52–53 Monsoon 201, 211, 483 plant tolerance to 266

Morocco 74 Mozambique 323–24 MRL. See Maximum residue limits MTA. See Marker trait association Multilateral System (MLS) 13 Multi-objective analysis 140 Multiple stress tolerance 170 Mungbean 289 physiology and 332–34, 333f, 334t seed yield of 332–34 temperature and 332 Myanmar 272, 473 Mycotoxin 239 Myzus persicae 342

n Nagoya Protocol for Access and Benefit Sharing 424, 501, 508 Namibia 451, 453, 464 NAO. See North Atlantic Oscillation NAPA. See National Adaption Programmes of Action NARES. See National Agricultural Research and Extension Systems NARS. See National Agricultural Research System National Adaption Programmes of Action (NAPA) 478 National Agricultural Research and Extension Systems (NARES) 337 National Agricultural Research System (NARS) 493 National Climate Assessment 451 National Food for Work Programme (NFFWP) 17 National Food Security Mission (NFSM) 17–18 National Sample Survey Organization (NSSO) 191–92 Near isogenic line (NIL) 125 Neem 344 Nepal 472 Nepal fox tail millet 474 NERICA. See New Rice for Africa Nevada desert 161, 178 New Rice for Africa (NERICA) 425–26 New Zealand 84, 454–55

537

538

Index

NFFWP. See National Food for Work Programme NFSM. See National Food Security Mission NF-Y. See Nuclear factor Y Nigeria 320, 365–66 Night-time temperatures 103–4, 361 NIL. See Near isogenic line Ningxia province 133, 137, 451, 453, 455 Nitrogen fixation 139–40 Nitrogenous fertilizer 4, 59, 190 Nitrous oxide 12, 18, 119, 145, 433–34 Nivalenol 239 Nordic Europe 11 North America food security and 46–48, 47t–48t O3 impact on 5 temperature 28–30, 28t, 30t trade and prices 42–45, 43t–44t North Atlantic Oscillation (NAO) 326 Norway, SGSV and 168, 419 NSSO. See National Sample Survey Organization Nuclear factor Y (NF-Y) 153 Nutrients, in soil BMP for 281–82, 282t in crop production 283–87, 283t–84t water interactions and 77–80 Nutrition, of crops CO2 rise and 59–61 deficiency estimates of 122–23 food access and 8–9 INM and 284–85 quality decline in 174

o O3 . See Ozone Oats 105 Odisha 272–73 Oil crop 95 consumption of 39, 40t IMPACT prediction of 35, 36t One Straw Revolution (Fukuokain) 199 Oomycete pathogen 342, 367 Oomyzus sokolowskii 344 Open pollinated varieties (OPV) 256–57, 337 Open Top Chambers (OTC) 333

OPV. See Open-pollinated varieties; Open pollinated varieties Oriental fruit fly 344 Orissa state 192, 254 Oryza sativa 95, 384, 435. See also Rice Osmotic tolerance 383–85, 388–89 OTC. See Open Top Chambers Ozone (O3 ) on agriculture 5–6 mitigation and 131, 139

p Pacific Islands 10 Pakistan 1, 198, 218, 298t, 325, 332 Palmer amaranth 439 Papua New Guinea 362, 414f, 415, 426, 473b PAR. See Platform for Agrobiodiversity Research Paraquat 441 Parasitic weed 166–67 Paris Agreement on Climate Change 3 Participatory plant breeding (PPB) 146–47 Paspalum dilatatum 438 PB. See Permanent raised bed PCR. See Polymerase chain reaction Peanut 97 Pearl millet 172t, 176, 211 PEG. See Polyethylene glycol Perennial grass 436 Permanent raised bed (PB) 217 Peru 38, 163, 481b Pests bird cherry-oat aphid 232–36, 234f, 240 BYDV 232, 235–38, 237f fungal pathogens 238–40 host plant distribution and 240–41 insect pests 231–34, 234f introduction to 229–31, 230f plant viruses and 235–38, 237f of tomato 342–43 of vegetables 342–44 PGR. See Plant genetic resources PGRFA. See Plant Genetic Resources for Food and Agriculture Phaseolus vulgare 97

Index

Phenomics 150–51 Phenotype matching to environment 80–82 phenotyping 149–51 Phosphorous deficiency 174 Photoperiod sensitivity genes 208 Photorespiration 63, 119–22, 126, 436 Photosynthesis CO2 and 330–31 in mungbean 332–34, 334t temperature effects on 104–6 Photosystem II inhibitors (PSII) 439 Physiology-facilitated breeding 149 Phytophthora colocasiae 362 Phytophthora disease 342 Pigeon peas 160, 171t–72t Plantain signal grass 440 Plant breeding. See also Crop production abiotic stress and 149–53, 162–63 backcrossing in 148, 161, 178, 260–62 CA breeding methodology 215–16 crossbreeding in 147–48 CWR and 161–62 DNA markers in 147, 151–52, 421 domestic diversity in 146–47 GA in 149 genetic control and CO2 impact and 120–21 conclusions on 126 crop quality and 122–23 CWR and 124 food security and 123–24 genetic engineering and 125–26 introduction to 119–20 QTLs and 124–25 temperature effects on 121–22 water effects on 121–22 germplasm enhancement in 148 GWAS in 125 high throughput phenotyping 150–51 omics-led 151–52 pedigree breeding in 257–58 phenomics in 150–51 phenotyping in 149–51 physiology-facilitated 149–51 PPB in 146–47 pre-breeding in 148

QTLs and 124–25 temperature effects on 102–6, 103f trait introgression 151–52 transgenic breeding and 152–53 of vegetables 335–38, 336t water stress and 106–8 Plant genetic resources (PGR) 12. See also Genetic resources Plant Genetic Resources for Food and Agriculture (PGRFA) 327, 329, 500 Plant-microbe interaction 220–21 Plant Ontology (PO) 308 Plant phenomics 168–70 Platform for Agrobiodiversity Research (PAR) 479, 482b–83b Plutella xylostella 342 PO. See Plant Ontology Pod borer 175 Poland 236 Polar ice sheets 2 Polyethylene glycol (PEG) 426 Polygonum convolvulus 439 Polymerase chain reaction (PCR) 423 Polyphagous insect 231 Population genomics 151 Potato 331, 359 climate change and 366–67 CO2 impact on 4 late blight of 367 transgenics of 391t Potato Park 481b Powdery mildew conidia 240 PoWPA. See Programme of Work on Protected Areas PPB. See Participatory plant breeding PPP. See Public private partnership Practical Action 476b Pre-breeding 148 Precipitation. See also Rainfall mitigation of 131, 133, 137–38 RH in 440–41 Prickly pear moth 231 Programme of Work on Protected Areas (PoWPA) 311 Proline 390 Promopsis spp. 163 Protein content 138

539

540

Index

PSII. See Photosystem II inhibitors Public private partnership (PPP) 257, 488. See also Community-led efforts Pueraria lobata 437 Pulses consumption of 39, 40t global production of 35, 36t, 38, 139–40 NFSM of 18 trade in 42–45, 43t Punjab 189–90 government of 200 rice-wheat cropping in 214, 215f water in 193–95, 194f–95f wheat cultivation in 192, 192f, 205–6, 206f, 208f Pythium 365 Pythium myriotylum 363

q Qinghai province 133 QPM. See Quality protein maize QTL. See Quantitative trait locus Quackgrass 439 Quality protein maize (QPM) 15, 260–62, 261f, 285 Quantitative trait locus (QTL) 152 in CO2 responsiveness 124–25 in legumes 380 MABB and 262 in tropical crops 381–82 Quechua, Peru 481b Queensland fruit fly 233

r Rabi (winter) 274, 277f, 277t rice 254, 254f Radish 290, 331 Rainfall changing patterns of 72–74, 72f–73f climate change and 96–97 tolerance 383–85 Rajasthan 272 Ralstonia solanacearum 323, 340–41, 344 Randomly amplified polymorphic DNA (RAPD) 420–21 RCT. See Resource conservation technologies

Reactive oxygen species (ROS) 162, 387, 439 Recurrent selection (RS) 256, 260 Relative humidity (RH) 440–41 Representative Concentration Pathways 29 Residue management 282, 282t Resilience 11–13, 369–71 Resource conservation technologies (RCT) 276 Restriction fragment length polymorphism (RFLP) 420–21 Reverse transcription quantitative PCR (RT-qPCR) 236, 237f RFLP. See Restriction fragment length polymorphism RH. See Relative humidity Rhizobia bacteria 329 Rhizobium culture 333 Rhodes grass 438 Rhopalosiphum padi 232–36, 234f, 240 Rht gene 203, 204f Ribulose-1,5-bisphosphate (RuBP) 55–57, 56f, 124, 436 Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) 55–57, 56f, 98, 331 crop improvement and 120, 123–24 engineering of 126 Rice China production of 32–33, 32t CO2 impact on 4, 97–100, 98t EU production of 32–33, 32t FSU production of 32–33, 32t IMPACT predictions on 32–33, 32t India production of 32–33, 32t IRRI and 385 japonica cultivar 62–63 NFSM of 18 prices of 45–46, 46t protein kinase 177 Rabi rice 254, 254f rice-wheat cropping system 189–90, 195, 214, 215f salinity tolerance and 389–90, 475, 476b SSA production of 32–33, 32t transgenics of 391t

Index

waterlogging and 149 Risk-benefit analysis 140 Risk experiences 456–58 RNAi. See Interfering RNA Roots architecture of 267, 379 CO2 effects on 100 Roots and tubers cassava 361–62, 364–65 consumption of 39, 40t edible aroids 362–63, 365 food security and conclusion on 371 introduction 359–60 optimum conditions for 361–64 potato production 366–67 projected responses of 364–66 resilience of 369–71 sustainable production of 367–69 sweet potato 364 IMPACT prediction of 35, 36t soil health and 368 trade in 42–45, 43t tree crops and 367–68 yams 363–66 Rootstock. See Genetic resources ROS. See Reactive oxygen species Rotational effects 14. See also Cropping systems Roundup ready 439 RS. See Recurrent selection RT-qPCR. See Reverse transcription quantitative PCR Rubisco. See Ribulose-1,5-bisphosphate carboxylase/oxygenase RuBP. See Ribulose-1,5-bisphosphate Russia 132. See also Former Soviet Union heat wave damage in 1 temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t Rwanda 324, 373b Rye 38

®

s Sago palm 415 Salinity tolerance osmotic stress and

388–89

in rice 389–90, 475, 476b Saltwater incursion 10–11 SCH. See Single cross hybrids Scotland 454–55 Scutellum 263–64 Sea level rise 2 Sedoheptulose-1,7-bisphosphatase 63 Seed multiplication 258 parent 259 setting 197 size 99–100, 105, 202, 270 yield breeding and 62–63 CO2 impacts on 58–59, 99–100 hybrid technology and 270–71 of mungbean 332–34 stress tolerance on 170 temperature and 106 Seeds for Needs 473, 473b–74b, 493 Seed Village Concept 268–69 Semi-arid tropics environment of 76, 82–84, 109 genetic resources and 168, 169t Senescence, of leaves 108, 267 Septoria brown spot 239 SFS. See Smallholder farming systems SGSV. See Svalbard global seed vault Shaanxi province 133, 451, 453, 455 Shanxi province 133 Shared socioeconomic pathway (SSP) 26–28, 31 Siberia 11 Simple sequence repeats (SSR) 421 SINGER. See System-wide Information Network for Genetic Resources Single cross hybrids (SCH) 253, 256–66 seed production 272, 273f Single nucleotide polymorphism (SNP) 125, 162, 422 Sitobion avenae 232 SLA. See Specific leaf area Smallholder farming systems (SFS) 17 SNP. See Single nucleotide polymorphism SOC. See Soil organic carbon Soil 282 diseases and grafting 344–47, 346f

541

542

Index

Soil (contd.) management 74–77, 75f nutrient management 174 quality 193–95 Soil organic carbon (SOC) 195 Soil organic matter (SOM) 368 Solanum lycopersicum 101, 341. See also Tomato Solanum tuberosum 359 Solanum viarum 343 Solar radiation 441 SOM. See Soil organic matter SOR. See Superoxide reductase Sorghum biotic stress of 173t CO2 impact on 97–100, 98t in Zimbabwe 511f–12f Sorghum biocolor 97 South Africa 10, 132, 266, 320, 322 drought tolerant corn 136 South America 2, 422, 457, 462, 502 water conservation in 84–85 South Asia crop yield in 131–32 GDP of 10 IMPACT and food security and 46–48, 47t–48t trade and prices 42–45, 43t–44t oil production in 35, 36t water conservation in 84–85 WorldVeg in 327–28, 332–34, 333f, 334t Southern blotting 421 Soybeans CO2 impact on 4 IMPACT predictions on 34–35, 34t O3 impact on 5 prices of 45–46, 46t Roundup ready 439 transgenics of 391t SoyFACE experiment 54f, 62 Spain drought in 71–85, 73f–75f, 81f grain production in 72–75, 74f Special Report on Emissions Scenarios (SRES) 2, 4 Species Survival Commission (SSC) 310

®

Specific leaf area (SLA) 170 Spodoptera litura 342, 344, 362 SRES. See Special Report on Emissions Scenarios Sri Lanka 272, 325, 476b SSC. See Species Survival Commission SSP. See Shared socioeconomic pathway SSR. See Simple sequence repeats Stability, of food production 7–8 Stanford University 135 Stomata CO2 and 331 conductance 54–55, 98–100, 98t, 119 herbicides and 441 transgenic breeding and 153 Striga weed 166–67 Stripe Rust 491b Stubble-borne fungal pathogen 239 Sub-Saharan Africa (SSA) crop climates in 12–13 food-insecurity and 8–9 genetic resources of 166–68, 167t IMPACT and food security and 46–48, 47t–48t GDP and 27–28, 27t temperature 28–30, 28t, 30t trade and prices 42–45, 43t–44t rice production in 32–33, 32t vegetables in 320–24 Succulence index 108 Sugar consumption of 41, 41t IMPACT prediction of 35, 36t prices of 45–46, 46t Sugar-75 259 Sugarbeet 55t, 97, 108, 427t CO2 impact on 4 Sunflower 75, 83, 139 Superoxide reductase (SOR) 387 Surveillance system 137 Svalbard global seed vault (SGSV) 168, 419–20 Swamp taro 359, 363 Sweet corn 259–60 Sweet potato 364, 416f System-wide Information Network for Genetic Resources (SINGER) 303

Index

t Taiwan 340 Tajikistan 326–27 Talkoxydim 441 Tamil Nadu 252, 273 Tamil Nadu state 192, 252, 254f Tanzania 321, 324, 337, 363, 368 Taro leaf blight 362 Tasmania 160 Tea production 35, 36t Technacy 490–91, 490n15 Technology, in CA 199–202, 201t. See also Biotechnology Teff 38 Temperate crops biotechnology of legumes and 380–81 heat tolerance in 388 vegetable production of 290 zone of 163–66, 164t–65t Temperature 6 of canopy 85, 105, 109, 149, 170, 179, 238 CO2 interactions and 108–9, 331–32 CO2 rise and 52–53, 438–40 IMPACT model and 28–30, 28t, 30t mungbean and 332 of night-time 103–4, 361 plant growth effects 102–6, 103f water interactions and 77–80 wheat quality and 79 wheat response to 77–79 wheat yield and 197, 197f TF. See Transcription factor Thailand 340, 368–69 Tillage crop establishment and 274–76 in India 199–200 zero-till condition 199–204, 201t, 209, 212f, 217 Tilling, transgenic technique of 163 TNC. See Total nonstructural carbohydrate Tomato breeding programs for 335–42 FlavrSavr 426 gemplasm of 309, 311 genetic resources of 300t–301t, 301–2 insect pests of 342–43

production of 290, 292t rootstock of 344–46, 346f transgenics and 382, 386–88, 392t Tomato yellow leaf curl virus 347 Total nonstructural carbohydrate (TNC) 61 Trait introgression Crop Trait Mining Platforms 305–7 MTA and 151–52, 176 Transcriptional regulation 151 Transcription factor (TF) 379–82, 384, 386–87, 391t Transgenic breeding 152–53 abiotic stresses and 391t–92t, 392 in maize production 265–68, 266f Tilling 163 Translational regulation 151 Transplanting 279 Trathala flavoorbitalis 344 Tree crops 367–68 Trehalose 390 Triticum aestivum 95, 435. See also Wheat Triticum durum 162 Tropical crops biotechnology in 381–83 drought tolerance in 381–83 IITA 160, 166, 167t, 168, 178 Tropospheric ozone 5–6 True taro seed (TTS) 370–71 Trust, in farming 304, 490, 491b TTS. See True taro seed Tubers. See Roots and tubers Turkey 290, 291t–95t, 298t–99t Turnip 290, 294t Tuta absoluta 323

u Udaipur 287 Uganda 136, 177, 323–24, 363, 368 farmer knowledge in 459 UK. See United Kingdom UMP. See Uzumba Maramba Pfumbwe Underutilized crops 38, 163–64 UNEP. See United Nations Environment Programme UNFCC. See United Nations Framework Convention on Climate Change

543

544

Index

United Kingdom (UK) 132, 135, 191 United Nations 414 United Nations Environment Programme (UNEP) 345 United Nations Framework Convention on Climate Change (UNFCC) 2, 478 United States (USA) Army Corps of Engineers 458 IMPACT and food security and 46–48, 47t–48t GDP and 27–28, 27t temperature 28–30, 28t, 30t trade and prices 42–46, 43t–44t livestock in 14 midwest 5, 453, 455, 459, 460f O3 impact on 5 surveillance system of 137 transgenics from 136 USDA-ARS 304, 306 vegetable production in 290, 291t–95t, 298t–301t Ura 481 Urban competition 132 Urochloa plantaginea 440 USA. See United States Utilization, in food security 7, 9–10 Uttar Pradesh 192f, 193, 254, 254f, 283t Uzbekistan 346 Uzumba Maramba Pfumbwe (UMP) 504, 508

v Vandalism 414–15 Vanuatu 371 Vapor pressure 73, 96, 104–6, 266 Vector-borne disease 3, 229–41, 230f, 234f, 237f Vegetables bacterial diseases and 338–42 breeding of 335–38, 336t climate change and 319, 347 in Asia 325–28 in SSA 320–24 consumption of 39, 40t EURISCO 303–4, 306, 308–9 fungal disease 338–42 genetic resources of

ex situ germplasm in 296–309, 297t–301t in situ conservation of 310–11 introduction to 298 on-farm conservation of 310–11 role in stability 290–96 summary on 311–12 in sustainable production 328–29 global production of 290, 291t–95t grafting and 344–47, 346f insect pests of 342–44 microbial resources and 329–30 mites and 342–44 production of in Asia 290, 291t, 301–2, 311 in China 290, 291t–95t IMPACT prediction of 35–37, 36t–37t in Iran 290, 291t–95t, 299t in Mexico 295t, 298t–99t in Turkey 290, 291t–95t, 298t–99t in USA 290, 291t–95t, 298t–301t trade in 42–45, 43t Venezuela 369 Vernalization 73, 85, 105 in CA 206, 207f Vietnam 346 Vigna mungo 289 Vigna unguiculata 289 Village Grain Banks Scheme 17 Vinegar fly 233 Vitamin A 60–61

w Water availability 378 CO2 interactions 77–80, 108–9 conservation efforts of 82–85 farmer knowledge and 462–63 in India 193–95, 194f–95f management of 279–81, 280f, 280t–81t nutrient interactions and 77–80 plant breeding and 121–22 saltwater incursion 10–11 supply strategies of 82–84 temperature interactions 77–80 vapor pressure of 73, 96, 104–6, 266

Index

Water-borne disease 3 Waterlogging rice production and 149 tolerance 383–85 transgenic wheat and 135 Watermelon genetic resources of 298t–99t, 301 production of 290, 292t Water stress 107–8 Water use efficiency (WUE) 331 in CA 218–19, 219t, 220f, 220t CO2 impact on 4 in crop yield 76, 79, 82–83 Weather 1–2. See also Climate change EI Niño 136–37, 414 farmer knowledge and 452–53 Weeds 433, 442 management of 190–91, 204–5 crop competition in 434–37 herbicides efficacy in 438–41 herbicides in 434 parasitic 166–67 West African Sahel 10 West African sorghum 177 Western corn rootworm beetle 231 Wheat. See also Conservation agriculture abiotic stress tolerance of 135, 160–61 bajra-wheat 211 biotechnology and 378–80 CO2 impact on 4, 97–100, 98t drought tolerance 378–80 Haryana production of 196, 196f hexaploidy of 148, 159, 162, 165, 386 ICIMMYT 161–62, 165–66, 169 IMPACT predictions on 30–31, 30t maize-wheat cropping sequence 276t, 278, 281, 286 NFSM-Wheat 18 in Northern India 214, 215f O3 impact on 5 quality of 79 rice-wheat cropping system and 189–90, 195, 214, 215f rust 490, 491b temperature and 77–79, 197, 197f transgenics of 391t zinc content in 59–60

Whitefly 342 White yam 370 Whole System Approach 478–79, 479f WIEWS. See World Information and Early Warning System Wild buckwheat 439 Wilt 153, 170, 344 Winged bean 289 Women 474, 489 in food security 16 in SSA 323 World Bank 326 WorldClim 503, 503n3 World Health Organization crop nutrition and 60–61 nutrient deficiency estimates of 122–23 World Information and Early Warning System (WIEWS) 296–301, 306, 309 World Vegetable Center (WorldVeg) 301–3, 312 bacterial disease and 339–42 breeding programs and 335–37 soil-borne disease and 345–47 South Asia and 327–28, 332–34, 333f, 334t in SSA 323 WRKY gene family 387 WUE. See Water use efficiency

x Xanthosoma sagittifolium 359 Xyloglucan endotransglycosylase

383–84

y Yadav, S. S. 11 Yam mosaic virus (YMV) 370 Yams 167, 167t, 363–66 Yangtze 138 Yangtze-Huai plain 134, 134f Yellow star thistle 437 Yield. See also Crop production computer simulations of 81–82, 81f of mungbean seed 332–34 stress tolerance on 170 temperature and 106, 197, 197f

545

546

Index

Yield. See also Crop production (contd.) WUE and 76, 79–83, 218–19, 219t–20t, 220f YMV. See Yam mosaic virus

z Zambia 501, 502t, 504t, 505, 506t–7t, 520 Zero-till condition 199–204, 201t, 209, 212f, 217, 278

Zhejiang province 133 Zimbabwe 501, 508, 511f–12f, 514f, 520 Zinc 59–60, 101, 282, 282t, 285 deficiency of 122–23 Zinc-finger proteins 380, 382 Zizyphus spp. 163 Zoï Environment Network 327

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