An Economic Assessment of Banana Genetic Improvement and ...

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Summary This research report highlights findings from a set of studies undertaken by applied economists on the impact of improved banana cultivars and recommended management practices in the East African highlands. A particular focus of the analysis is genetic transformation of the cooking banana. Genetic transformation to achieve pest and disease resistance of the cooking banana is a promising strategy for smallholder farmers in this region. Biotic constraints are severe and not easily addressed through conventional breeding techniques or control methods. Exports on the world market are currently negligible, so that the risks of reduced exports due to policies against genetically modified foods are low. The crop is both an important food source and a significant generator of rural income, which means that improving productivity could have great social benefits. Findings demonstrate the potentially pro-poor application of transgenic cooking varieties and the likely social consequences of the choice of host cultivar for trait insertion. Simulations illustrate the extent to which supporting public investments in education, market infrastructure, and extension would augment farmer demand for new planting material. Demand for planting material of potential host varieties for gene insertion varies according to household and physical farm characteristics, markets, and the attributes of varieties. In particular, farmers demand material with lower expected yield losses to black Sigatoka and weevils. The evidence also confirms that adoption of Fundación Hondureña de Investigación Agrícola (FHIA) hybrids reduces the vulnerability of Tanzanian households to yield losses from pests and disease. For farmers with few nonfarm sources of income, reducing production risk can smooth both consumption and income from local sales. In addition, it is evident that social capital plays a significant role in the use of recommended practices for managing soil fertility in banana production in Uganda. Most of the villages in the banana-producing areas foster active social organization, although membership in economic associations is more exclusive. Village social characteristics will likely have especially important implications for planting-material systems of East African highlands bananas. For this crop, transfers of planting material and related information are heavily farmer based, compared to the more formal seed distribution systems of some cereal crops. Analysis of banana productivity confirms its dependence on the economic, climate, and soil characteristics of subregions. Evidence suggests that the efficiency of banana production can be improved, particularly in the Central Region of Uganda, where labor productivity is higher than elsewhere in the country. Soil pH and the application of manure have positive and significant effects on productivity, especially in southwest Uganda and the Central Region. The critical importance of labor in productivity is evident in findings regarding the age of the household head and family size. The analysis of production efficiency reveals the presence of surplus labor in banana production in the highlands, while access to farm labor is a constraint in the lowlands. Wages are higher for casual labor in the lowlands, where a more developed market for unskilled labor exists. Investment in technology development could shift banana productivity in the highlands. In the lowlands, both technology development and extension education have positive effects on productivity. Investing in human capital––especially wom- xii
SUMMARY xiii en’s education––and enabling more access to input and credit markets could improve banana production, and investments in the paved road network would improve the comparative advantage of the lowlands in banana production. Simulations of the gross economic benefits that could be generated by a set of technology options indicate that more widespread adoption of current best practices is likely to generate the greatest investment payoffs in Uganda. Yet the authors argue that the longer-term strategy endorsed by the National Agricultural Research Organization of Uganda, which combines conventional and transgenic approaches to mitigate the biotic pressures that cause major economic losses, is essential for sustaining banana-production systems. The results of this study have implications for research and development (R&D) policies according to five categories: 1. Developing Improved Banana Genotypes. Findings confirm the vulnerability of the cooking banana, as well as other types grown in the region, to pests/diseases and the need for a research policy to commit long-term investments in the development of resistant genotypes. The choice of host cultivar and use group will have social consequences in terms of which farmers will be most likely to use and benefit from improved cultivars. In general, however, greater social costs are likely to be caused by delays in banana improvement than by choice of any host cultivar or technology set. Time lags in research and adoption have often been shown to be the single-most important determinant of the social payoff to investment. 2. Enhancing Demand and Supply of Improved Germplasm. A policy supporting investments in agricultural education, extension, marketing infrastructure, and access to good roads will enhance demand and supply of improved banana cultivars and, in turn, raise banana productivity and efficiency. We predict a demand for pest- and disease-resistant material, given the evidence that farmers value these traits, but demand will be much greater if other supporting investments in education, extension, and market infrastructure are made. 3. Designing Effective Dissemination Mechanisms. Findings support the current policy of the Government of Uganda, which emphasizes farmer association and human capital development as pillars of technology and knowledge dissemination. Farmers are price responsive, adopting new technologies at greater rates when output prices are high relative to input prices. The high rates of dissemination of improved practices for managing soil fertility are promising, despite the labor these practices demand. Farmer- and socially based mechanisms appear to be a crucial factor in the dissemination of both planting material and technologies. This finding reflects, in part, the clonally propagated nature of the banana plant. 4. Scaling Up Genotype Adoption. A demand-driven strategy for scaling up farmer use of approved banana varieties is needed. Widespread adoption of FHIA hybrids occurs in Tanzania. The analysis suggests that higher adoption rates in Tanzania relative to Uganda result from greater disease pressures, heavy dissemination efforts, and the fact that historically farmers have actively sought out planting material that is free of pests and diseases. Adoption definitely shows an impact on vulnerability to disease losses. Further analysis is needed over time to determine whether diffusion and benefits have been sustained, and whether incomes have been affected. The examples of farmer-tofarmer exchanges described in the report for Uganda, though limited in their impact in terms of numbers of farmer and communities, warrant closer examination as models for more structured and decentralized diffusion mechanisms. We recommend a farmer- and socially based network design, with farmer-supplied planting material, possibly scaling
Page 1 and 2: An Economic Assessment of Banana Ge
Page 3 and 4: Contents List of Tables List of Fig
Page 5 and 6: Tables 3.1 Net marketing margins pe
Page 7 and 8: TABLES vii 6.5 Characteristics of h
Page 9 and 10: Figures 2.1 Sample domain: Elevatio
Page 11: Acknowledgments The International F
Page 15 and 16: Acronyms and Abbreviations AGT ARDI
Page 17: Part I. Research Methods
Page 20 and 21: 4 CHAPTER 1 practices in Africa are
Page 22 and 23: 6 CHAPTER 1 periment station. Not a
Page 24 and 25: 8 CHAPTER 1 niques (based on seed p
Page 26 and 27: 10 CHAPTER 1 Cohen, J. I., and R. P
Page 28 and 29: CHAPTER 2 Elements of the Conceptua
Page 30 and 31: 14 CHAPTER 2 ples of adoption disco
Page 32 and 33: 16 CHAPTER 2 transgenic bananas cur
Page 34 and 35: 18 CHAPTER 2 Figure 2.2 Sites sampl
Page 36 and 37: 20 CHAPTER 2 Figure 2.4 Time profil
Page 39: Part II. Research Context
Page 42 and 43: here> 1near 3. 26 CHAPTER 3 major f
Page 44 and 45: 28 CHAPTER 3 disease, which affects
Page 46 and 47: here> 1near 3. 30 CHAPTER 3 Table 3
Page 48 and 49: 32 CHAPTER 3 Table 3.2 Banana produ
Page 50 and 51: 34 CHAPTER 3 would only be able to
Page 52 and 53: 36 CHAPTER 3 Nkonya, E., J. Pender,
Page 54 and 55: here> 1near 4. 38 CHAPTER 4 cash ne
Page 56 and 57: 40 CHAPTER 4 Figure 4.1 Introductio
Page 58 and 59: 42 CHAPTER 4 Research Introductions
Page 60 and 61: 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
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112 CHAPTER 8 inputs or implement c
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114 CHAPTER 8 Crop output is determ
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116 CHAPTER 8 Table 8.1 Variable de
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here> 8.6near here> 8.2near 8.3nea
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120 CHAPTER 8 Table 8.4 Production
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122 CHAPTER 8 during the SOM decomp
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124 CHAPTER 8 Supplementary Tables
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126 CHAPTER 8 Table 8A.3 Production
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128 CHAPTER 8 Thomas, G. W. 1982. E
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130 CHAPTER 9 (Nkuba et al. 1999).
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132 CHAPTER 9 be reduced through la
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134 CHAPTER 9 Table 9.2 Summary sta
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136 CHAPTER 9 Table 9.3 Coefficient
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138 CHAPTER 9 Table 9.4 Mean compar
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140 CHAPTER 9 References Anandajaya
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142 CHAPTER 10 Table 10.1 Ugandan c
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144 CHAPTER 10 (Kangire and Rutherf
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146 CHAPTER 10 Table 10.4 Predomina
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here> 7near 10. 148 CHAPTER 10 Tabl
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150 CHAPTER 10 Table 10.8 Present v
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152 CHAPTER 10 In terms of specific
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Part IV. Conclusions
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158 CHAPTER 11 in cooking, brewing
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160 CHAPTER 11 sumption and income
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162 CHAPTER 11 4. 5. for which the
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APPENDIX A Banana Taxonomy for Ugan
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BANANA TAXONOMY FOR UGANDA 167 Tabl
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BANANA TAXONOMY FOR UGANDA 169 Tabl
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BANANA TAXONOMY FOR TANZANIA 171 Ta
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BANANA TAXONOMY FOR TANZANIA 173 Ta
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APPENDIX C Use of Improved Banana V
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DETAILS OF SAMPLE SURVEY DESIGN 177
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VILLAGE SOCIAL STRUCTURE IN UGANDA
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List of Principal Authors and Contr
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ABOUT THE AUTHORS 187 rigation, and
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