An Economic Assessment of Banana Genetic Improvement and ...

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162 CHAPTER 11 4. 5. for which the “technology” is generated on the farm. Again, farmers are price responsive, undertaking more production when the output price relative to the input price is high. The high rates of dissemination of improved soil fertility practices are promising, despite the labor these practices demand. Labor constraints are less of a problem in the highlands, the more commercially oriented production zone with labor surpluses. Farmer- and association-based mechanisms appear to be a crucial factor in disseminating both planting material and technologies. Scaling up the adoption of genotypes. There is need for a demand-driven strategy for scaling up farmer use of approved banana varieties. There is widespread adoption of FHIA hybrids in Tanzania, given the great disease pressures, extensive dissemination efforts, and the historical practices of farmers in actively seeking pest- and disease-free planting material. Adoption definitely shows an impact on vulnerability to disease losses. Further analysis is needed over time to see whether diffusion is sustained, benefits are sustained, and income effects are observable. The examples of farmerto-farmer exchanges described for Uganda, though limited in their impact in terms of numbers of farmers and communities, warrant closer examination as models for more structured, though more decentralized, diffusion mechanisms. We recommend a farmerbased and socially based network design, with farmer-supplied planting material, possibly scaling up from some of the experiences in Uganda. The strategy of providing large quantities of materials free of charge (a “push” strategy) is not sustainable. Determining R&D strategies for the highlands and lowlands. Strategies for improving productivity in high-elevation areas will necessarily be different from those targeting the low-elevation areas. The highlands require development and promotion of best cultural practice and marketing improvements, whereas lowlands require development and promotion of pest- and/or diseaseresistant endemic varieties together with best cultural practice aimed at reviving productivity. To support the success of these efforts, major investments need to be made in dissemination. Overall, we recommend targeting more than one trait, but not too many simultaneously, because such a strategy could delay transformation, curbing the benefits to be earned by Ugandan society. Technical change is a continuous, multidimensional process. Social science can contribute to the formulation of agricultural research policy during technology development by identifying the social, economic, and institutional impediments that must be addressed to ensure that promising new crop technologies will be adopted by farmers. Once these technologies are in the course of adoption, social science can provide insights into mechanisms that will support adoption rates and enhance the positive impact of technical change on the livelihoods of rural people. The National Banana Research Programme of NARO and IITA, with the support of the INIBAP, have embarked on an ambitious breeding program that employs a range of biotechnologies (embryo rescue and somatic embryogenesis) as well as crossing, propagation, and crop and soil management practices, to address the most debilitating diseases and pests. Some of the improved technology explored in this report already exists and some is emerging from these efforts. The baseline developed here, which represents a single, statistically based “snapshot” in a gradual process of technical change, has been used to predict the ex ante impact of transgenic cultivars. In addition, it has been used to assess the ex post impact
CONCLUSIONS AND IMPLICATIONS FOR RESEARCH POLICY 163 of conventional hybrids, investigate the role of social capital in the adoption of practices to enhance soil fertility, and assess the efficiency of banana production. Later, this same baseline will be available to assess the ex post impacts of emerging technologies. The sector analysis provides an overview of the potential distribution of benefits across the range of technologies currently promoted or under development.
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An Economic Assessment of Banana Ge
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Contents List of Tables List of Fig
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Tables 3.1 Net marketing margins pe
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TABLES vii 6.5 Characteristics of h
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Figures 2.1 Sample domain: Elevatio
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Acknowledgments The International F
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SUMMARY xiii en’s education--and
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Acronyms and Abbreviations AGT ARDI
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Part I. Research Methods
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4 CHAPTER 1 practices in Africa are
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6 CHAPTER 1 periment station. Not a
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8 CHAPTER 1 niques (based on seed p
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10 CHAPTER 1 Cohen, J. I., and R. P
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CHAPTER 2 Elements of the Conceptua
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14 CHAPTER 2 ples of adoption disco
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16 CHAPTER 2 transgenic bananas cur
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18 CHAPTER 2 Figure 2.2 Sites sampl
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20 CHAPTER 2 Figure 2.4 Time profil
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Part II. Research Context
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here> 1near 3. 26 CHAPTER 3 major f
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28 CHAPTER 3 disease, which affects
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here> 1near 3. 30 CHAPTER 3 Table 3
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32 CHAPTER 3 Table 3.2 Banana produ
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34 CHAPTER 3 would only be able to
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36 CHAPTER 3 Nkonya, E., J. Pender,
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here> 1near 4. 38 CHAPTER 4 cash ne
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40 CHAPTER 4 Figure 4.1 Introductio
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42 CHAPTER 4 Research Introductions
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44 CHAPTER 4 Table 4.2 Names of the
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46 CHAPTER 4 The most widely used m
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48 CHAPTER 4 Ortíz, R., and D. Vuy
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here> 5.3near here>
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52 CHAPTER 5 Table 5.4 Percentage o
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54 CHAPTER 5 Table 5.7 Percentage o
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here> 9near 5. here> 10near 5. 56 C
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here> 12near 5. 58 CHAPTER 5 Table
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60 CHAPTER 5 Table 5.14 Number and
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here> 18near 5. 62 CHAPTER 5 Table
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64 CHAPTER 5 Table 5.20 Average num
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66 CHAPTER 5 Table 5.23 Percentage
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68 CHAPTER 5 Table 5.26 Average dis
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70 CHAPTER 5 considerably higher in
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Part III. Economic Assessment of Te
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76 CHAPTER 6 The agricultural house
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78 CHAPTER 6 grow, but have grown i
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80 CHAPTER 6 Table 6.2 Summary stat
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82 CHAPTER 6 tion. More frequent vi
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84 CHAPTER 6 Table 6.4 Prototype ho
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86 CHAPTER 6 Table 6.5 Characterist
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88 CHAPTER 6 References Cameron, A.
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90 CHAPTER 7 by-products of other f
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here> 1near 7. 92 CHAPTER 7 Table 7
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94 CHAPTER 7 ity in the two technol
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96 CHAPTER 7 Table 7.2 Definition o
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98 CHAPTER 7 The direct link betwee
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100 CHAPTER 7 Table 7.3 Factors inf
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102 CHAPTER 7 tive sign but are onl
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104 CHAPTER 7 fertility management
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106 CHAPTER 7 participatory decisio
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108 CHAPTER 7 Stevens, J. P. 2002.
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110 CHAPTER 8 defined as a function
Page 128 and 129: 112 CHAPTER 8 inputs or implement c
Page 130 and 131: 114 CHAPTER 8 Crop output is determ
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Page 136 and 137: 120 CHAPTER 8 Table 8.4 Production
Page 138 and 139: 122 CHAPTER 8 during the SOM decomp
Page 140 and 141: 124 CHAPTER 8 Supplementary Tables
Page 142 and 143: 126 CHAPTER 8 Table 8A.3 Production
Page 144 and 145: 128 CHAPTER 8 Thomas, G. W. 1982. E
Page 146 and 147: 130 CHAPTER 9 (Nkuba et al. 1999).
Page 148 and 149: 132 CHAPTER 9 be reduced through la
Page 150 and 151: 134 CHAPTER 9 Table 9.2 Summary sta
Page 152 and 153: 136 CHAPTER 9 Table 9.3 Coefficient
Page 154 and 155: 138 CHAPTER 9 Table 9.4 Mean compar
Page 156 and 157: 140 CHAPTER 9 References Anandajaya
Page 158 and 159: 142 CHAPTER 10 Table 10.1 Ugandan c
Page 160 and 161: 144 CHAPTER 10 (Kangire and Rutherf
Page 162 and 163: 146 CHAPTER 10 Table 10.4 Predomina
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Page 166 and 167: 150 CHAPTER 10 Table 10.8 Present v
Page 168 and 169: 152 CHAPTER 10 In terms of specific
Page 171: Part IV. Conclusions
Page 174 and 175: 158 CHAPTER 11 in cooking, brewing
Page 176 and 177: 160 CHAPTER 11 sumption and income
Page 181 and 182: APPENDIX A Banana Taxonomy for Ugan
Page 183 and 184: BANANA TAXONOMY FOR UGANDA 167 Tabl
Page 185 and 186: BANANA TAXONOMY FOR UGANDA 169 Tabl
Page 187 and 188: BANANA TAXONOMY FOR TANZANIA 171 Ta
Page 189 and 190: BANANA TAXONOMY FOR TANZANIA 173 Ta
Page 191 and 192: APPENDIX C Use of Improved Banana V
Page 193 and 194: DETAILS OF SAMPLE SURVEY DESIGN 177
Page 199 and 200: VILLAGE SOCIAL STRUCTURE IN UGANDA
Page 201 and 202: List of Principal Authors and Contr
Page 203 and 204: ABOUT THE AUTHORS 187 rigation, and
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