IMPACT OF SCIENCE ON AFRICAN AGRICULTURE AND FOOD SECURITY This page intentionally left blank IMPACT OF SCIENCE ON AFRICAN AGRICULTURE AND FOOD SECURITY Edited by P Anandajayasekeram Manager, Capacity Strengthening Unit International Livestock Research Institute, ILRI, Addis Ababa M Rukuni Regional Director for African Programmes W.K Kellogg Foundation S Babu Senior Research Fellow, Training Programme International Food Policy Research Institute, Addis Ababa F Liebenberg Project Leader, ARC C.L Keswani Consultant CABI is a trading name of CAB International CABI Head Office Nosworthy Way Wallingford Oxfordshire OX10 8DE UK Tel: +44 (0)1491 832111 Fax: +44 (0)1491 833508 E-mail: cabi@cabi.org Website: www.cabi.org CABI North American Office 875 Massachusetts Avenue 7th Floor Cambridge, MA 02139 USA Tel: +1 617 395 4056 Fax: +1 617 354 6875 E-mail: cabi-nao@cabi.org © CAB International 2007 All rights reserved No part of this publication may be reproduced in any form or by any means, electronically, mechanically, by photocopying, recording or otherwise, without the prior permission of the copyright owners A catalogue record for this book is available from the British Library, London, UK A catalogue record for this book is available from the Library of Congress, Washington, DC ISBN: 978 84593 267 Typeset by AMA DataSet Ltd, UK Printed and bound in the UK by Biddles Ltd, King’s Lynn Contents Contents Contributors Biography of Authors viii x Foreword xiii Preface xiv Part I Challenges Facing African Agriculture S.C Babu, P Anandajayasekeram and M Rukuni The Role of Impact Assessment in Evaluating Agricultural Investments in Eastern and Southern Africa P Anandajayasekeram, S Babu, M Rukuni and S Workneh 13 Part II Economics of Wheat Research in Kenya David W Makanda and James F Oehmke Impact of Sorghum Research and Development in Zimbabwe: the Case of SV P Anandajayasekeram, D.R Martella, J Sanders and B Kupfuma Ex-ante Analysis of the Sorghum and Millet Improvement Program P Anandajayasekeram, D.R Martella, J Sanders and B Kupfuma 34 46 57 v Contents vi Impact of Pearl Millet Research and Development in Namibia: the Case of Okashana P Anandajayasekeram, D.R Martella, J Sanders and B Kupfuma 68 74 Economic Impact of Maize Research in Tanzania A.J Moshi, P Anandajayasekeram, A Kaliba, D Martella, W Mwangi and F.M Shao Economic Returns from Livestock Research and Development in Tanzania: 1966–1995 R.M Kaliba Aloyce, Sean Fox and David Norman 83 Impact of the Russian Wheat Aphid Control Programme in South Africa Carissa N Marasas 91 10 The Impact of Public Investment in Maize Research in Kenya Daniel D Karanja 103 11 Impact of Maize Technology Development and Transfer in Ethiopia T Zegeye, G Tesfahun and P Anandajayasekeram 116 12 Evaluating Agricultural Research and Extension in Tanzania: the Production Function Approach A.C Isinika 13 Impact Assessment of Sorghum Research in Zambia Medson Chisi 14 The Economic Impact of Investments in Cassava Research in Uganda A Bua, G Acola, R.L Adupa, G.W Otim-Nape, Y.K Baguma, D Sserunkuma, V Manyong and O Coulibaly 15 Impact Assessment of Groundnut Research in Zimbabwe E Mazhangara, P Anandajayasekeram, M Mudhara, D Martella and M Murata 16 The Rate of Return to Wine Grape Research and Technology Development in South Africa Rob Townsend and Johan van Zyl 127 137 147 152 161 17 Socio-economic Impact of Lachenalia Research in South Africa J.G Niederwieser 171 18 Impact Assessment of Sunflower in Zimbabwe M Murata, P Anandajayasekeram, M Mudhara, D Martella and E Mazhangara 184 19 Impact Assessment of Cotton Research in Zimbabwe: 1970–1995 M Mudhara, P Anandajayasekeram, B Kupfuma and E Mazhangara 192 Contents vii 20 21 22 23 The Socio-economic Impact of Proteaceae Research and Technology Development in South Africa J.M.C Esterhuizen 199 Impact Assessment of the Biological Control of Prosopis Species in the Britstown–De Aar District, South Africa J.M.C Esterhuizen 210 Socio-economic Impact of the Control of Ticks and Tick-borne Diseases in South Africa R Randela 221 Impact of Investments in Livestock Research and Development Programmes in South Africa M.R Mokoena 236 Part III 24 An Overview of Impact Assessment Methods P Anandajayasekeram, S Babu and M Rukuni Overview of Impact Assessment Methodologies P Anandajayasekeram and S Babu Index 249 300 Contributors Contributors P Anandajayasekeram, International Livestock Research Institute, ILRI, Manager, Capacity Strengthening Unit (CaSt), PO Box 5689 Addis Ababa, Ethiopia, Tel: +251 11 6463215 Ext 2481, Fax +251 11 646 1252/646 4645, E-mail: p.anandajayasekeram@cgiar.org S.C Babu, Senior Research Fellow, International Food Policy Research Institute, 2033 K Street, Washington, DC 20006, USA, Tel: + 202 8625618, E-mail: s.babu@cgiar.org A Bua, Principal Research Officer, National Crop Research Institute, Namulonge, PO Box 7084, Kampala, Uganda, Tel: 256-772-461950, E-mail: abua@naro-ug.org Medson Chisi, Golden Valley Agricultural Research Trust, PO Box 54, Fringilla, Zambia, E-mail: smip@zamnet.zm or medsonchisi@hotmail.com J.M.C Esteurhuizen, Agricultural Economist, Agricultural Research Council, PO Box 8783, Pretoria 0001, South Africa, Tel.: 27 12 4279700, Fax: 27 12 342 3948 A.C Isinika, Institute of Continuing Education, Sokoine University of Agriculture, PO Box 3044, Morogor, Tanzania, E-mail: isinika@suanet.ac.tx, aidaisinika@yahoo.co.uk R.M Aloyce Kaliba, Research Associate/Policy Analyst, Aquaculture/Fisheries Center, University of Arkansas at Pine Bluff, 1200 North University Drive, Mail Slot 4912, Pine Bluff, AR 71601, USA, Tel: 870 575 8108; Fax: 870 575 4637; E-mail: akaliba@uaex.edu Daniel D Karanja, Senior Fellow, Partnership to Cut Hunger and Poverty in Africa, 499 S Capitol Street SW, Suite 500B, Washington, DC 20003, Tel: 202-479-4501; Fax: 202-488-0590, E-mail: karanjad@msu.edu, www.africanhunger.org Carissa N Marasas, APHIS-PPQ-CIAO, 4700 River Road Unit 133, Riverdale, MD 20737, USA, E-mail: Carissa.Marasas@aphis.usda.gov E Mazhangara, 5684 Shaw Street, Haslett, MI 48840, USA, E-mail: emazhangara@yahoo.com M.R Mokoena, Deputy Director, Commodity Marketing Directorate, National Department of Agriculture, Private Bag X15, Pretoria, 0007 South Africa, Tel: (012) 319 8080, Fax: (012) 319 8077, E-mail: MadimeM@nda.agric.za A.J Moshi, Zonal Director Research and Development, Eastern Zone, Ilonga Agricultural Research Institute, PO Box 33, Kilosa, Tanzania, Tel: + 255-023-2623201, Fax/Tel: + 255-023-2623284 M Mudhara, Farmer Support Group, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, Pietermaritzburg, South Africa, E-mail: mudhara@ukzn.ac.za; mudhara@yahoo.co.uk M Murata, Project Monitoring and Evaluation Officer, Implementation and Coordination of Agricultural Research and Training (ICART) Project in the SADC Region, Food, Agriculture and Natural Resources viii Contributors ix Directorate, SADC Secretariat, P/Bag 0095, Gaborone, Botswana, Tel: (267) 3951863 ext 5094, Fax: (267) 3924099, E-mail: mmurata@sadc.int J.G Niederwieser, Plant Breeder, ARC – Vegetable and Ornamental Plant Institute, Private Bag X293, Pretoria 001, South Africa, Tel: 27 12 8419611, Fax: 27 12 808 1127 James F Oehmke, Professor and Liberty Hyde Bailey Scholar Department of Agricultural Economics, 317 AgH, East Lansing, MI 48824-1069, USA, Tel: 1-517-353-2981, E-mail: oehmke@msu.edu R Randela, National Treasury, Director: Justice and Secret Services, Pretoria, South Africa, E-mail: Rendani.randela@treasury.gov.za Rob Townsend, Agricultural Economist, The World Bank, 1818 H Street, NW Washington, DC 20433, USA, E-mail: rtownsend@worldbank.org T Zegeye, Agricultural Socio-economics Research Department, PO Box 2003, Addis Ababa, Ethiopia, Tel: 251 11 6454434, Fax: 251 11 6461294, E-mail: socio_economics@eiar.gov.et P Anandajayasekeram and S Babu 296 Good practices for estimating benefits: ● ● ● ● Good practices in data analysis and calculating returns to investment: ● ● ● ● ● Study the market situation of the commodities affected by R&D and determine tradable status appropriate for estimating total surplus Use economic prices that are appropriately adjusted to reflect policy distortions in the output market All monetary values should be expressed in real terms Estimate of research benefits should be disaggregated by commodities, production environment or geographical basis if the parameter estimates are different for different components of the research programme Ensure that spill-over effects are included Create a different spreadsheet template for each of the commodity/products/zones affected by the R&D programme Document the logical structure of the model/method used for calculating the benefit and cost stream, including clear specification of assumptions and sources of data used to derive the various model parameters Calculate both summary measures, i.e NPV and IRR to indicate the profitability of R&D investment Carry out appropriate sensitivity analysis by varying some of the critical assumptions made in the model When evidence of research spill-outs and spill-ins exists, good practice for ex-post impact assessment is to conduct spatially disaggregated analysis that explicitly treats spill-outs and spill-ins General procedure: ● ● ● ● ● ● ● ● Define the minimum data set and collect them on a regular basis Collecting panel data on a regular basis is cost-effective Combine both qualitative and quantitative assessment Build in-house capacity for ongoing evaluation Develop mechanisms to integrate information with decision-making If the institute is genuinely interested in improving its quality, relevance and effectiveness, sampling of ‘failures’ as well as ‘successes’ may offer more insight Establishing baseline conditions is a prerequisite to providing credible evidence of impact in terms of measuring the people-level impacts of R&D investment Instil impact culture at all levels, i.e institute, programme and project This simply means having an impact orientation so that research is continuously conducted in relation to specific goals As the payoffs from research are long term and inherently uncertain, in using impact assessment as a planning tool one must allow a certain margin of failure if innovation is not to be interrupted Impact assessment needs to be driven by internal consideration of research efficiency, i.e to generate feedback on research impact for purposes of project guidance, priority setting and resource allocation The external (accountability) and internal (research efficiency) dimensions of impact assessment should be seen as complementary Whether it is done by internal staff or outside experts, it is important to ensure that project assessment follows an accepted standard of good practices and produces credible results It is a well-known fact that the investors in public R&D are no longer satisfied with activitybased progress reports They in fact expect outcome and impact evaluation, i.e an objective assessment of the actual effects of the funded programme on the target populations Now there Overview of Impact Assessment Methodologies 297 is also general consensus that no single method or data set is capable of capturing what is necessary to understand complex systems involving policies, organizations, institutions, programmes and people through which goals are achieved In order to ensure an adequate coverage of the information universe, both qualitative and quantitative data are required and multiple methods and approaches are advocated (Greene and Caracelli, 1997) Retrospective narratives are an essential component of the former and indeed provide the basis for quantitative estimates and the related issue of attribution Case studies are essential for further refining approaches and methodologies and learning lessons, which can enhance the future impacts and help define ‘best practices’ Use of independent evaluators in the process offers the advantage of objectivity and lend credibility to the impact evaluation, although the cost often means that only a small number of projects and programmes can be subjected to this type of evaluation Notes Accountability can cover: impact accountability, coverage accountability, service delivery accountability, efficiency accountability, fiscal accountability and legal accountability For details of the functional form and its derivatives please refer to: Alston et al (1995); Anandajayasekeram et al (1996); Masters et al (1996); Akino and Hayami (1975) A number of impact studies conducted by CSIRO in Australia used this approach For more details see Johnson et al (1992) References Akino, M and Hayami, Y (1975) Efficiency and equity in public research: rice breeding in Japan’s economic development American Journal of Agricultural Economics 57, 1–10 Alston, J.M., Norton, G.W and Pardey, P.G (1995) Science under scarcity Principle and Practice for Agriculture Cornell University Press, 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Organized by the Standing Panel on Impact Assessment (SPIA) of the Technical Advisory Committee (TAC), 3–5 May 2000 FAO, Rome, pp 7–27 Weiss, C.H and Bucavalas, M.J (1980) Social Science Research and Decision Making Colombia University Press, New York Williams, D (1993) Methods for assessing the socio-economic impacts of Government S&T Report prepared under contract ARA Consulting Group, Inc Canada Ottawa, Canada Winpenny, J (1991) Values for the Environment: a Guide to Economic Appraisal HMSO/ODL, London Index Index Abstract of Agricultural Statistics, South Africa 238–239 accountability 13 activity 291 adoption 111, 114, 121, 125, 141, 148–155, 253 ceiling 143–144, 269 cost 155, 157, 267–268 development and transfer costs 97 path 144 profile 141 rate 74, 125, 137, 159 survey 142 adjusted R2 96, 130 AES 106, 113 Africa 1–3, 5–6, 147 African agriculture 1–2, 6, 9, 103, 107 African farmers 107, 110 African farming 110 African food crisis African Land Development Board 111 African Land Utilization and Settlement Board 111 African Leadership African nations 103 African Union African Union Commission on Rural Economy and Agriculture Botswana 24, 60–62, 65, 145 Burkina Faso 10 Central Africa 300 Eastern Africa 8, 13–14, 107, 123–124 Eastern and Southern Africa (ESA) 3–14, 18, 28, 30, 287 Egypt 3, 24 Ethiopia 2, 19, 24, 26, 116–118, 120–121, 123–124 Amhara 117, 122, 125 Oromiya 117, 122, 125 Southern Region 117, 122, 125 Kenya 3, 19, 24, 103–105, 113–114 Lesotho 24, 60 Malawi 3, 10, 60 Mali Mozambique 24, 60, 145 Namibia 19, 24, 69, 145 Nigeria 3–5 North Africa 16 Rwanda South Africa 19, 21–24, 91, 107–108, 161–163, 171, 210 Southern Africa 8, 13–14 Southern Africa Development Community (SADC) 6, 24, 57–60 sub-Saharan Africa 1–2, Sudan 10 Swaziland 60 Tanzania 2, 19, 26, 60, 74–80, 83–89, 127–129, 131–132 Uganda 3, 10, 19, 26, 147, 149–150 Index 301 West Africa 3, Zambia 19, 24, 60, 137–138, 140–145 Copperbelt 137 Eastern Province 137–139 Northern Province 137 Northwestern Province 137 Zimbabwe 19, 21, 24, 46–51, 54–55, 60, 145–192 agrarian economy 116 agricultural credit 11 Agricultural Credit – Land Bank 108 agricultural extension programme 106, 110, 130 agricultural field 119 Agricultural Finance Corporation 108–109 Agricultural Information Centre 111 agricultural marketing 111 agricultural officers 110 agricultural production 117 Agricultural Production Marketing Act 107–108 agricultural research and development (R&D) 13, 26, 249 Agricultural Research Trust 152 agricultural research 74 agricultural research and extension 19 Agricultural Research, Tanzania 128 AGRITEX 48, 53–54, 156–157 agro-climatic regions 138 agro-ecological zone 6, 118, 125, 129, 141–143 Agronomy Institute of Crop Management 154, 156, 158 agronomic recommendations 119 agronomists 124 agronomy 119, 123 Akino–Hyani (A & H) method 52, 57, 62, 65, 269, 271–276 Alemaya College of Agriculture 117 Almon lag 135 Ambo Research Centre 124 annual net returns 144 anti-poverty programme 26 Apac 148 appropriate price 120 Arab traders 107 assistant agricultural instructors 110 attribution 288 average prices 120 average total costs 97 Awassa Research Center 117 Bako, Ethiopia 117 banana 3, 117 weevil and diseases Bandahe 159 baseline conditions 296 beans 129 before and after comparison 255 benefit cost method 77, 147 analysis 142, 149–150, 154–155, 171, 186, 192, 223, 244, 269 approach 79, 140, 150, 156, 178, 265, 269, 276 ratio 229, 234, 268–270 benefit flow period 269 benefits 118, 120, 122 benefits to livestock improvement research 240 best bet practices 279, 294–295, 297 Birr 116 biological control 19, 91–92 blight 117 boundary partners 263 breeding 123, 124 British Government 110 brown grain varieties 139 MMSH-375-H 139 MMSH-413-H 139 budget 123 bulb 177 Bureau of Agriculture, Ethiopia 122, 124 CAADP capacity 284 effectiveness 284 efficiency 284 external environment 285 operational environment 284 organizational 284–285 program theory 284 relevance 285 sustainability 284 capacity strengthening Caribbean 16 case studies 261, 293, 297 cassandra problems 280 cassava 3, 19, 147–150 adoption of cassava varieties 148 cassava mosaic virus 147–148 National Cassava Program, Uganda 150–151 Index 302 causality 281, 287 central highlands 110 Central Statistics Authority (CSA), Ethiopia 117 cercospora disease 154, 159 cercospora leaf spot disease 154 certified maize seed 111 challenges facing African agriculture challenges to increase agricultural productivity chemical control 91, 96–97 cherry picking approach 294 chingungwana 159 chitununu 159 chlorpyrifos 94 CIMMYT 123–124, 253 CIMMYT/SIDA 124 CMD 149–150 Cobb-Douglas type 128, 274 coefficient of variation 253 coffee 129 collaborative activities 258 colonial government 110 commercial demand 141 commercial farmers 159 Commercial Farmers’ Union 153 commercialization 177 Commercial Oilseed Producers’ Association 153, 156 common units 140 communal areas 159 compounding 267 comprehensive framework 249 consumers 122 consumers and producers surplus 240, 243 consumer price index (CPI) 85, 120, 129, 150, 155 consumer surplus 266–267 conservation, soil and water 26 contribution analysis 289 control practice 94 control strategy 226 correlation 95 correlation multiple regression analysis 91, 96 cost–benefit 96–97, 140, 200, 226, 233 cost effectiveness analysis 261 cost of technology development 121 cost of technology transfer 12, 21 cost saving method 271, 276 cotton 3, 19, 127, 154, 192 cotton bollworms 3, 19, 127, 154, 192 coverage accountability 297 cowpea pod borer cross boundary 146 cross commodity 146 cross cutting method 148 cultivars 148 cultural practices 117 data 120 Dalgety Ltd 111 decentralization 10 demand 114, 120, 265 demeton-S-methyl 94 demonstrations 111 demonstration trials 108 Department of Agriculture, Kenya 110 Department of Agriculture, South Africa 215 depreciation 122 depreciation of capital 142 determination of ROR 56 diffusion ceiling 143–144 diffusion phase 269 diffusion process 145–150, 239 direct foreign subsidy 113 direct product 16, 249, 254 discount rate 80, 116, 122–123, 131, 155, 178, 187–189, 194, 204 discounted benefit 268 discounted cost 268 discounted incremental net profit 187 discounting 267 diseases 119 disease control programme 20 divisia index 133–134 divisia productivity indices 134 domestic price 120 ‘do nothing’ strategy 225 downstream effects 277 downy mildew 117 DR & SS 157–158 drought tolerance 145 dummy variable 105 early warning unit 156 East Coast Fever 221, 224, 226 economic analysis 104, 171, 178 Index 303 economic approach 119, 273 economic assessment 147 economic costs and benefits 225 economic impact of research 155, 186 economic pay off 113 economic reforms 112 economic return 83–84, 149 economic surplus 164, 243, 258, 267, 281 econometric analysis 281 econometric problems 275 econometric surplus 265, 273 education 26 effectiveness analysis 140, 158, 203, 254–255 efficiency 127, 158, 204 efficiency accountability 297 efficiency analysis 140, 203, 255, 265–266 egret 154, 159 elasticities 265 elasticity of demand and supply 271 elasticity of maize output 105 elasticity of production 130–131 electricity 26 empirical model 134 enterprise budgets 97 entomology 123 environmental effects 184, 207 error correction model 20 error terms 274 estimated rate of return 116 estimate of costs and benefits 226 Ethiopian Grain Trade Agency 120 Ethiopian Institute of Agricultural Research (EIAR) 120, 123–124 Ethiopian Seed Enterprise 120, 121, 124 European settlement 108 evaluation 294 evaluation planning 264–265 outcome journal 265 performance journal 265 strategy journal 265 exchange rate 113 exogenous variables 105 Expanded NCPB 109 expert opinion 293 extension 103–104, 152 extension costs 157, 267 extension programme 112 extension services 113 extension workers external environment 285 factors contributing to limited use of impact assessment 27 factor productivity 127, 130 famine FAO 2, 224, 129 FAO-sponsored fertilizer trials 108 FARA farmers 78 farm gate prices 148–150 farm-level 232 field price 273 fertilizer 118 Fertilizer Industry Agency 120 financial and economic analysis 199, 204 financial burden of dipping 223 fiscal accountability 297 fixed inputs 274 flamingo 154 floriculture industry 171 flower bulb market 174 food security 1, 116, 125, 147–149 foreign exchange 113 foreign exchange protection 113 foreign grain varieties 139 Forum for Agricultural Research in Africa Free State Department of Agriculture 97 functional form 133 F value 96 general equilibrium model 254 General Gowan General Olusegun Obasanjo general procedure 296 genotypes 148 gestation period 127 GM crops GMR 111 Golden Valley 145 good practices 295–296 grain markets 113 Green Revolution 1–4 gross benefits 77, 97, 150, 155, 158, 195 gross domestic product 74, 127 groundnut 19, 152–154, 157–158 groundnut and investment 152 groundnut production 159 groundnut R & D programme 156, 158 groundnut research 156, 159–160 groundnut research and complementarity 152 Index 304 groundnut research and extension 152–153 guaranteed minimum returns (GMP) 107 guaranteed government prices 107 H511 112 H512 112 H611 112 H611C 112 H622 112 H625 112 H626 112 health 26 high protein maize 109 human capacity 10 human capital Hi-breed Private Seed Company 124 hybrids 111, 114, 116, 118, 125, 138 Beletech 118 BH-140 118 BH-530 118 BH-540 118 BH-660 118 hybrid maize 121 hybrid plateau 107–108 hybrid revolution 107–108 IDS IFPRI impact 1, 116, 122–123, 156, 171, 185 accountability 297 assessment 13–14, 27, 116–118, 192, 200, 249–250 agricultural R& D programme 14 comprehensive framework 251, 254 conceptual framework 15 guidelines, environmental 278 methodologies 249 results 29 chains 258 economic 18, 122–123, 137–142, 152–156, 179–255 environmental 16, 159, 174, 186, 195–256 evaluations 14, 16, 200, 297 ex ante 14, 17, 57, 63, 140, 190, 200, 253–281 ex post 14, 17, 117, 120, 139, 199, 246, 281 intersectoral 249–250 institutional 252 investments 236 linkages 124 logical flow of impacts 282 market impacts 276–277 off-site 276–277 on-site 276–277 organizational impacts 207, 284 people level 16, 139, 156, 194–195, 243, 249–255 policy research 279 production 139, 252 purpose of impact 253 social 179, 203, 208 socio-economic 75, 117–118, 138, 159, 173, 182, 200–280 socio-cultural 16, 23, 139–159, 184, 252–256 IDRC 150 imports 113 imidacloprid insecticide 94 income distribution 120 IITA 150 IRR 158 income effects 186 incrementality 288 incremental net benefit 186 Increased Production of Crops Ordinance 107–108 independent variable 130 index number approach 266–269 index of input 129 indigenous commercial farmers 152 infrastructure infrastructure investments inflation 120 innovation systems 10, 148 input prices 113 institutions changes 16 impact 251–252 institutionalization 24, 29 institutional analysis 106–108 institutional collapse 107 strengthening 28 IHB stream 241 integrated partial indicators 259 intermediate product 249 international design 263–264 inter-academy council Index 305 intercropping 124 inter disciplinary 145 interest rate 273 ICRISAT 46, 48, 52–53, 57 ICRISAT Groundnut Program 158 International Monetary Fund (IMF) 112 Jimma, Ethiopia 125 Jimma College of Agriculture, Ethiopia 117 Jimma Research Centre, Ethiopia 124 Kabowe 159 Kassawaya 159 Kenya Agricultural Research Institute (KARI) 112–113 Kenya Farmers’ Association 107 Kenya Flat White Complex 110 Kenya hybrid maize 110 Kenyan economy 112 KFA 108, 110–111, 114 KGGCU 109 Kitale Research Station 110 KSC 105, 108–113 Lachenalia R&D programme 19, 21, 171–182 land resettlement programme 110 land tenure system 110, 149 large scale farmers 96, 111, 141–142 Latin America 1, 16–17, 154 Brazil 10 legal accountability 297 liner regression analysis 274 livestock 236 Animal Improvements Institute 237–238 Animal Products and Animal Nutrition Institute 237 National Beef Cattle Performance and Progeny Testing Scheme (NBCPPTS) 237–243 National Dairy Cattle Performance and Progeny Testing Scheme (NDCPPTS) 237–244 National Mutton Sheep Performance and Progeny Testing Scheme (NMSPPTS) 237–244 National Wooled Sheep Performance and Progeny Testing Scheme (NWSPPTS) 237–243 National Poultry Performance Testing Scheme (NPPTS) 240–241 Range and Foreign Institute for Exotic Diseases 237 livestock research expenditures 246 lira 148 Loan and Land Bank 110 logical chart 289 logical framework 254, 289 low risk technological component 74 mail survey 155 maize 3, 19, 74–90, 103, 107, 112–113, 117–119, 128 maize system borers Maize and General Produce Board 111 Maize Control Unit 107 Maize Control Committee 108 Maize Marketing Board 107 maize output 104, 106, 117 maize price 120 maize production 111, 113, 117 maize in Tanzania 21, 75 maize research in Kenya 15, 103–104, 106 maize research and development 75, 112–114 maize research expenditure 106, 112 maize technology development and transfer 74, 108, 110, 116 maize sub-sector 117 maize support systems 108 maize varieties 104, 112–114 maize yield 79, 114 Makulu Red 152–154, 159–160 malnutrition marginal physical product 275 marginal product of research (MPR) 131 marketable surplus 79, 125 marketing systems and trade liberalization 6–7 mathematical programming 259–266 Mau-Mau Rebellion 107 medium-scale farmers 141 Melkasa 124 meta analysis 24 methodological issues 28 Index 306 mevinphos 94 mid-altitude maize research 108 millet 19–20, 46–47, 61, 64 mini green revolution 103 Ministry of Agriculture, Ethiopia 121, 124, 128–129 Ministry of Agriculture, Food and Fisheries, Tanzania 139–141 Ministry of Agriculture, Kenya 105–106, 121 Ministry of Economic Development and Cooperation (MEDAC), Ethiopia 121 Ministry of Finance, Planning and Economic Development, Uganda 150 Ministry of Natural Resources and Tourism, Tanzania 128 MMB 114 modified peer review 260 monitoring and evaluation systems for NARIs 29, 190, 197, 246 monocrotofos 94 morbidity 226 mortality 226–228 motivation 284 Mubende 148 multi-criteria analysis 30, 258 multi stage sampling 74, 77, 137, 141, 156, 187 multiple lines of evidence 293 Natal Common 154, 159 National Agricultural Research Institutes (NARIs) 28–29 National Agricultural Research Systems (NARS) 10, 58, 66–68, 70 National Maize Research Programme (NMRP) 74 National Variety Release Committee 121, 124 NCPB 109, 111 NEP-Pilot Project, 1981 109 net benefit 122, 158, 195, 267, 272 net incremental benefit 240 net social benefit 140 net present value (NPV) 64, 71, 78, 88, 97, 116, 122–296 NEPAD 9, 13–14 Nigeria’s First Development Plan nitrogen use efficiency 145 Njoro breeding station 110 nominal values 128–129 non-adoption rate 137 non conventional inputs 134 non-governmental organizations (NGOs) 54, 138, 141, 155 non-traded goods 148 nutritional approach 266 objective assessment 249 operational environment 284 opportunity cost 122, 129, 149 option and existence value 278 OECD 17 Ondersterpart Veterinary Institute 224 on-farm research 108, 155 open pollinated maize varieties 111, 116, 125 A-511 118 Abo-Bako 118 ACV-3 118 ACV-6 118 Alemaya 118 Composite 118 Guto 118 Katumani 118 Kuleni 118 UCB 118 Operation Feed the Nation ordinary least squares 135 organizational motivation 285 organizational performance 263, 284–285 outcome 249, 290 challenge 263 immediate outcome 262, 290–291 intermediate outcome 262, 290–291 mapping 263–265 performance monitoring 264 ultimate outcome 261–262, 291 Pacific 16 paddy 129 panel data 296 parathion 94 partial budget 91 partial equilibrium analysis 122, 140, 265–266 partial indicators 259 Index 307 participatory research appraisal techniques 118 pathology 123 pay offs to investment 240 pearl millet 68 perfectly inelastic supply 269 perfectly elastic demand curve 269 Pearson’s Correlation Coefficient 95 Pioneer Hi Breed Seed Private Company 120–121 planning 197 Plant Protection Research Institute 154, 156–159 plover 152 political 112 policy environment 108 potato potato tuber moth poverty 1–2 pre-hybrid era 107–108 prices 113, 120 price elasticity 140 demand and supply 244 process benefit 279 producer and consumer surplus 265, 267 producer prices 104, 113 production and function approach 127–129, 132, 164, 274 production systems 141 approach 260 profit function 164 programme files 293 programme theory 284 progress markers 263 protection recommendations 119 public research 154, 185 Proposis 210 analytical framework and methodology 213 benefit and costs 216–218 biological control in Brits town 210 biological control in South Africa 210–212 cost–benefit framework 215, 210 economic analysis 217–218 effectiveness analysis 213 effectiveness of biological control 214 efficiency analysis 213, 215–218 environmental impact 218–219 financial analysis 216–219 impact assessment 210–221 logic model 215 logical framework analysis 214, 210 Plant Protection Research Institute, South Africa 215 problems related to biological control 214 Proposis species 210–212 rates of return 217–218 profitability 151 production cost 97 provincial marketing 111 Proteaceae research 19, 21 public–private partnerships 10 public sector investments 91 questionnaires 141, 149 Qwa Qwa 92–93 R factor 134, 272 Rakai 148 ranking principles 270 rationalizing 249 rate of return (ROR) 16–17, 19–20, 24, 27–30, 47–75, 103–254 average rate of return (ARR) 75, 265, 273 internal rate of return (IRR) 46, 56, 66, 186, 196–197, 268–273, 296 marginal rate of return (MIRR) 245, 265–275 rate of return analysis 140, 150 real interest rate 122, 186 real value 120 return to investment 1–2 random variables 274 reconnaissance surveys 120 recommendations 91, 110, 121 reduced gestation period 179 regression analysis 103, 127, 130 regression coefficient 104 Regional Bureau of Agriculture, Ethiopia 121 Relative Performance of Public Sector Agriculture (R&D) 25 research 114, 117 research advice 280 research benefits 296 research costs 97, 121 research and extension 194 Index 308 research and extension, Tanzania 127 research expenditure 103–105, 240, 246 research phase 269 research and development 28, 46, 68, 83–89, 142, 195–249 costs 268 elasticity 274 investments 117, 120, 251 R&D impact assessment 249 research and technology 161 systems 13 retrospective narratives 297 review and synthesis of impact assessment studies 15 roads 26 Rockefeller Foundation 110 rust 117 RWA-ICP 97 RWA insecticides 94 RWA insecticide costs 94 RWA-resistant cultivars 92, 94, 97 sample size 222 sample survey 141 sampling procedure 156–222 S&T 10 Sasakawa Global-2000 120, 121, 124 scaling up Science and Technology Act of 1979 112 screen project 294 scoring model 266 secondary data 120 seed 111–114 seed cost 142 seed markets 113 seed multiplication and distribution programme (SMMP) 106 seed stock 111 selection principles 270 semi-arid tropics 46 service delivery accountability 297 Shedu Shagari sensitivity analysis 55, 65, 72, 155, 158, 178, 193–195, 197–230 sensitivity test 122, 130, 143 Sima 144 simple benefit–cost method 144 simulation method 259, 266 site-specific agronomic research 145 site-specific recommendations 145 smallholder sector 6, 77, 85, 96, 128, 141, 144, 159 Small Grain Institute (ARC–SGI) 91–92 small-scale irrigation Spearman’s correlation coefficient 95 socially profitable 208 soil scientists and economists 124 social rate of return 127, 131 social time of preference 143, 160, 188 Sokoine University of Agriculture 128 sorghum 19–20, 46–47, 57–58, 60, 64, 127, 141 Department of Research and Specialist Services (DR-SS) 47–48, 51–54 development and diffusion of SV 47–51 impact of assessment of sorghum research, Zambia 137 importance of sorghum and millet 47 on-farm trial results 48–49 returns to SV 54 sensitivity analysis 55–56 social benefit of SV 51 Sorghum & Millet Improvement Programme (SMIP) 48–49, 51–54, 57, 62, 66, 68, 71–72 sorghum production sector 47 sorghum research programme 138, 145 SV adoption costs 52–53 SV research and extension costs 53 spacing 118 spill-ins 23, 257–258, 296 spill-outs 23, 257 spill-overs 23, 75, 250, 258, 296 benefits 63 economic 257–258 effects 145–146, 208, 249, 256 impacts 92 inter-commodity 257 inter-locational 256 inter-sectoral 257 knowledge 258 technological 257 Soroti 148 stalk borer 117, 119 storage pests 119 standard pre-tested questionnaires 92 staple food 75 stepwise adoption behavior 77, 142 Index 309 streak virus 117 striga 117 structured surveys 293 study design 222 subsistence demand 141 subsistence production 116 surplus approach 19–20 susceptible cultivars 93 supply 120, 265 supply response approach (model) 19, 83–89 Swynnerton Plan 108, 110 swallow 154 Swedish International Development Authority 137 sweet potato feathery mottle virus target versus achievement comparison 255 technology development & dissemination (TDD) 266, 273 technology development and transfer (TDT) 25, 29, 74, 125, 153, 199, 200, 252 technology generation and development technology package 114 technology productivity 272 telecommunications 26 temporal distribution of benefits 128 Thaba Nchu 92 tick control 221 ticks and tick borne diseases 221–222, 232–233 tobacco 154 time series analysis 273 total cost 142 total factor productivity 128, 131, 133–134, 164 tracking performance 292 training and visit system 112–113 training impact 282 trans log model 128, 133 Trans Nzoia district 110, 114 transfer costs 63, 157 Tugela–DM 92 Tumba 159 types of impact evaluation 14 Ukiriguru in Western Tanzania 128 uncertainty 278 unit cost of saving 91, 96–97, 272 UN Millennium Project 14 USA Valencia R2 154 value added 116 value of livestock 223 value of marginal product 273, 275 variable inputs 274 varieties in Zambia 145 Venda Department of Agriculture 223 wheat research in Kenya 34–45 East African Agriculture & Forestry Research 37 East African Veterinary Research Organization 37 environmental concerns 43 financial and economic profitability 41–42 International Maize & Wheat Improvement Center 42 Kenyan Wheat Sector 34 policy implications 40–43 rate of returns on investments in wheat research 38 research policy and research targets 42 Russian Wheat Aphid Control Programme in South Africa 21 smallholder or commercial farms 42 trends in wheat yields and research expenditure 37 wheat self sufficiency 40–43 white grain varieties 138 FSH-22 139 MMSH-375 139 MMSH-413 139 MMSH-928 138 MMSH-1256 138 MMSH-1324 138 WP-13 138 WSH-287 138 WSV-187 138 WSV-387 138 ZSV-12 138 ZSV-15 138 wine grapes 20, 162, 164, 166, 168 with and without scenarios 155, 186, 193, 226, 229, 246–255 Index 310 without dipping scenario 226 without technology scenario 156 women World Bank 112–113, 129 World War II 107 yield (YD) 105, 112, 116, 148–149 Zambia Seed Company 138, 141 ZAMSEED 144–145 .. .IMPACT OF SCIENCE ON AFRICAN AGRICULTURE AND FOOD SECURITY This page intentionally left blank IMPACT OF SCIENCE ON AFRICAN AGRICULTURE AND FOOD SECURITY Edited by P Anandajayasekeram... effects of food policy on household food security and nutrition, and monitoring the impact of food and nutrition programmes on the nutritional status of the beneficiaries Dr Babu has conducted... UNICEF/Cornell Food and Nutrition Policy Programme He has also been a senior food and nutrition policy advisor to the Government of Malawi and conducted evaluation of food and nutrition interventions as