Measuring the Effectiveness of Crop Improvement Research in Sub-Saharan Africa from the Perspectives of Varietal Output, Adoption, and Change: 20 Crops, 30 Countries, and 1150 Cultivars in Farmers’ Fields July 2014 CGIAR INDEPENDENT SCIENCE AND PARTNERSHIP COUNCIL Synthesis Report for Objectives 1 and 2 of Bill & Melinda Gates Foundation’s Diffusion and Impact of Improved Varieties in Africa (DIIVA) Project Measuring the Effectiveness of Crop Improvement Research in Sub-Saharan Africa from the Perspectives of Varietal Output, Adoption, and Change: 20 Crops, 30 Countries, and 1150 Cultivars in Farmers’ Fields Tom Walker, Arega Alene, Jupiter Ndjeunga, Ricardo Labarta, Yigezu Yigezu, Aliou Diagne, Robert Andrade, Rachel Muthoni Andriatsitohaina, Hugo De Groote, Kai Mausch, Chilot Yirga, Franklin Simtowe, Enid Katungi, Wellington Jogo, Moti Jaleta and Sushil Pandey Prepared for the Standing Panel on Impact Assessment (SPIA) CGIAR Independent Science & Partnership Council (ISPC) July 2014 The CGIAR Independent Science and Partnership Council encourages fair use of this material provided proper citation is made. Walker, T., Alene, A., Ndjeunga, J., Labarta, R., Yigezu, Y., Diagne, A., Andrade, R., Muthoni Andriatsitohaina, R., De Groote, H., Mausch, K., Yirga, C., Simtowe, F., Katungi, E., Jogo, W., Jaleta, M. & Pandey, S. 2014. Measuring the Effectiveness of Crop Improvement Research in Sub-Saharan Africa from the Perspectives of Varietal Output, Adoption, and Change: 20 Crops, 30 Countries, and 1150 Cultivars in Farmers’ Fields. Report of the Standing Panel on Impact Assessment (SPIA), CGIAR Independent Science and Partnership Council (ISPC) Secretariat: Rome, Italy. Contents Tables and figures iv Acronyms and abbreviations vi Acknowledgements vii Foreword xi Executive summary 1 Introduction 6 1. Crop and country coverage 8 2. Scientific strength in crop improvement 10 Scientific staff strength by research program in 2010 10 The congruence rule: How many full-time equivalent (FTE) scientists are desirable? 13 Differences in scientific strength over time 14 Other aspects of scientific capacity: age, education, experience, and area of specialization 17 FTE scientists in the CGIAR 19 Agreement between the DIIVA and the Agricultural Sciences and Technology Indicators Initiative (ASTI) FTE estimates 21 Summary 23 3. Varietal output 25 Findings on varietal output in 1998 26 Updating varietal output in 2010 26 Varietal output over time 28 The historical record on CGIAR contributions to varietal output 30 The maturity of crop improvement programs over time 32 Summary 34 4. Varietal adoption 37 Defining modern varieties (MVs) and estimating adoption 37 Adoption levels of improved varieties by crop in 2010 39 Adoption rates by country 43 Named MVs in the adoption database 44 Spillovers in adoption 46 IARC-related adoption 47 Comparing adoption levels between 1998 and 2010 48 Summary 51 5. Varietal change 53 The importance of estimating varietal change 53 The velocity of varietal turnover in 2010 by crop 53 Varietal change and adoption by crop-by-country observations 55 The vintage of adopted varieties 56 Comparing levels of varietal change in 1998 and 2010 57 Summary 58 6. Validating adoption estimates generated by expert opinion from survey estimates 59 Validating expert opinion on adoption and the protocol used to elicit estimates from experts 59 Describing the validation surveys on the diffusion of MVs 61 Validating expert opinion with the survey estimates 62 Focusing on challenges in nationally representative adoption surveys 66 Summary 68 7. Conclusions 70 References 74 Annex: Summary data on FTE scientists, varietal release, and adoption of improved varieties by crop and country 79 Synthesis Report for Objectives 1 and 2 of Bill & Melinda Gates Foundation’s DIIVA Project — iii Tables and figures Table 1.1. Area coverage in SSA in 2010 by crop 9 Table 1.2. The number of crop-by-country observations in the DIIVA Project by type of data 9 Table 2.1. FTE scientists by crop improvement program in SSA in 2010 11 Table 2.2. Estimated research intensities by crop in SSA in 2010 from the perspectives of area, production, and value of production 12 Table 2.3. Comparing the actual allocation of FTE scientists to a normative allocation by crop 14 Table 2.4. Differences in estimated FTE scientists and research intensities between 1998 and 2010 by crop based on 65 paired comparisons 15 Figure 2.1. Change in scientific staff strength in food crop improvement programs between 1997/98 and 2009/10. 16 Table 2.5. Educational level of scientists in crop improvement programs by region in SSA 17 Table 2.6. Relative allocation of scientists by disciplinary specialization across roots and tubers, grain legumes, and cereals in SSA in 2010 in % shares 18 Table 2.7. Relative allocation of scientists by disciplinary specialization in SSA in 2010 in % shares 19 Figure 2.2. Number of PhD scientists working in the groundnut, pearl millet, sorghum and pulse improvement programs in ICRISAT by location for selected years in 1978–2010 20 Figure 2.3. Comparing ASTI and DIIVA estimates of scientific strength 22 Table 3.1. Counting the number of cultivars in the varietal release database by crop in SSA from before 1970 to 2011 27 Table 3.2. The frequency of cultivar release by decade by crop in SSA 28 Table 3.3. Performance in varietal release from 1999 to 2011 29 Figure 3.1. Crop-by-country observations with more releases in the 1980s than in the 2000s 31 Table 3.4. The contribution of IARCs of the CGIAR to varietal output output in SSA, 1980–2011 32 Figure 3.2. Number of improved maize varieties released by decade and by origin 33 Table 3.5. IARC-related percent share estimates over time with and without maize in ESA 33 Figure 3.3. Trend in the release of bean varieties by germplasm source, 1970–2010 34 Figure 3.4. Trend in cassava variety releases by IITA content, 1970–2010 35 iv — Synthesis Report for Objectives 1 and 2 of Bill & Melinda Gates Foundation’s DIIVA Project Table 3.6. Trend in the number of sorghum, pearl millet and groundnut varieties released by germplasm origin, 1970–2010 35 Figure 3.5. Trend in cowpea varietal releases by germplasm content, 1970–2010 35 Table 4.1. Source of the national adoption estimates by number of observations 39 Table 4.2 Adoption of MVs of food crops in SSA in 2010 40 Table 4.3. Weighted area adoption levels by country in SSA in 2010 44 Table 4.4. Top-ranked varieties by commodity and country by area and value of production 45 Table 4.5. The contribution of the CG Centers to MV adoption in SSA in 2010 48 Table 4.6. Change in MV adoption between 1998 and 2010 in ten food crops in SSA 49 Figure 4.1. Change in the estimated level of adoption of improved maize and cassava varieties between 1998 and 2010 50 Figure 4.2. Change in the estimated level of adoption of improved bean, groundnut, pearl millet, potato, rice, sorghum and wheat varieties between 1998 and 2010 51 Table 5.1. The velocity of varietal turnover of improved varieties in farmers’ fields in SSA by crop 54 Figure 5.1. Distribution of crop-by-country improvement level of adoption and the mean 55 Figure 5.2. The distribution of country by crop improvement level of adoption and mean age of varieties in farmers’ fields 56 Table 5.2. Genetic improvement programs with higher adoption and more rapid varietal turnover by crop and country 57 Table 5.3. The vintage of varieties contributing to adoption in 2010 by criterion and by release period 57 Table 6.1. Description of the sampling features of the diffusion MV validation surveys conducted by participants in the DIIVA Project 62 Table 6.2. Validating adoption estimates from expert opinion with survey results by crop 63 Table 6.3. Agreement between expert and survey estimates of specific varieties by expert interval 65 Table 6.4. Distribution of rice by variety planted during major growing season in 2012 67 Table 6.5. Comparison of village-level and household-level interview data on varietal adoption using area grown under these varieties for rice in Nigeria 68 Annex Table 1: Summary data on FTE scientists, varietal release, and adoption of improved varieties by crop and country 79 Synthesis Report for Objectives 1 and 2 of Bill & Melinda Gates Foundation’s DIIVA Project — v Acronyms and abbreviations ASTI Agricultural Sciences and IFPRI International Food Policy Technology Indicators Research Institute BMGF Bill & Melinda Gates Foundation IITA International Institute of Tropical BSc Bachelor of Science Agriculture CATIE Centro Agronómico Tropical de INTSTORMIL International Sorghum and Millet Investigación y Enseñanza (Costa Collaborative Research Project of Rica) USAID CAR Central African Republic IRAT Institut de Recherches CIAT Centro Internacional de Agronomiques Tropicales Agricultura Tropical (Inter national IRRI International Rice Research Center for Tropical Agriculture) Institute CIMMYT Centro Internacional de ISNAR International Service for National Mejoramiento de Maiz y Trigo Agricultural Research (International Center for the IVT Institute of Horticultural Plant Improvement of Maize and Breeding Wheat) JICA Japan International Cooperation CIP Centro Internacional de La Papa Agency (International Potato Center) MAPE Mean Absolute Percent Error CIRAD Centre de Coopération MAS Marker-assisted selection Internationale en Recherche MDV Millennium Development Goals Agronomique pour le MSc Master of Science Développement (Agricultural MV Modern variety Research for Development) NARO National Agricultural Research