An Economic Assessment of Banana Genetic Improvement and ...

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vi TAbles 5.12 Results of hypothesis tests comparing distributions of expected yield loss due to three constraints, by elevation, across use groups, Uganda 58 5.13 Percentage of farmers growing improved banana cultivars, Uganda 59 5.14 Number and share of banana mats planted to improved banana cultivars, by users, Uganda 60 5.15 Percentage of farmers growing improved banana cultivars, Tanzania 60 5.16 Number and share of banana mats planted to improved banana cultivars, by users, Tanzania 61 5.17 Percentage of farmers adopting selected banana management practices, Uganda 61 5.18 Share of banana mats managed with recommended practices among users, Uganda 62 5.19 Average number of years in use of banana cultivars currently planted, Uganda 63 5.20 Average number of years in use of banana cultivars currently planted, Tanzania 64 5.21 Planting material transfer (supplied and received) for cultivars grown in the survey season, Uganda 65 5.22 Planting material supplied or received, by distance, social relationship, elevation, and exposure, Uganda 65 5.23 Percentage of planting material supplied and received, by type of transaction and stratum, Uganda 66 5.24 Average farm-gate and market bunch prices across banana cultivars (Ush) 66 5.25 Number of banana suckers received, by source and genomic group, Tanzania 67 5.26 Average distance from the source of planting materials, by genomic group and strata, Tanzania (km) 68 5.27 Percentage of improved banana planting materials obtained, by mode of transaction, Tanzania 68 5.28 Percentage of improved banana planting materials received, by social relationship to source, Tanzania 68 5.29 Average number of banana suckers received by farmers per genomic group, by elevation and exposure, Tanzania 69 5.30 Average number of banana suckers per genomic group supplied by farmers to other farmers, by elevation and exposure, Tanzania 69 6.1 Summary statistics for variables defined at the household level 79 6.2 Summary statistics for variables defined at the cultivar level 80 6.3 Zero-inflated Poisson (ZIP) regression results 81 6.4 Prototype households with high and low predicted demands for the potential host variety Nakitembe 84
TABLES vii 6.5 Characteristics of households with high predicted demand for the potential host cultivar Nakitembe, before and after effective insertion of resistance to black Sigatoka and weevils, with supporting public investments 86 7.1 Results of the likelihood ratio test for the null hypothesis that the coefficients on the two management decisions are equal 92 7.2 Definition of variables, hypothesized effects, and the summary statistics 96 7.3 Factors influencing the probability and extent of use of soil fertility management practices 100 8.1 Variable definitions and summary statistics for cooking bananas, productivity and technical efficiency analysis 116 8.2 Results of the frontier function 117 8.3 Cobb-Douglas production estimates for the overall sample (location dummies excluded) 119 8.4 Production elasticities 120 8.5 Test for the null hypothesis that σ u = 0 120 8.6 Factors influencing technical efficiency 121 8.7 Incorporating soil factors in the production frontier function (n = 154) 123 8A.1 Labor demand estimates (first stage of the production function estimation) 124 8A.2 Two-stage least squares estimates of the production function for cooking bananas (endogeneity test) 125 8A.3 Production function estimates, three-stage least squares estimate 126 9.1 Five-year average areas under crop production by district in Kagera Region, 1996/97–2000/01 (ha) 131 9.2 Summary statistics and hypothesized effects of variables used in the analysis 134 9.3 Coefficient estimates for the treatment effects model 136 9.4 Mean comparisons between likely nonadopters and adopters in exposed areas 138 9.5 Mean vulnerability comparisons between farmers in exposed and nonexposed areas (percent) 139 10.1 Ugandan cooking banana production, by production system, 2000 142 10.2 Estimated yield losses caused by priority banana production constraints in each of the six production systems 143 10.3 Annualized banana production costs and returns in each of the six production systems 145 10.4 Predominant management practices, by production system category 146 10.5 Targeting of technologies relevant to industry-scale scenarios 146 10.6 Definition of technology scenarios and selected research parameters 147
Page 1 and 2: An Economic Assessment of Banana Ge
Page 3 and 4: Contents List of Tables List of Fig
Page 5: Tables 3.1 Net marketing margins pe
Page 9 and 10: Figures 2.1 Sample domain: Elevatio
Page 11 and 12: Acknowledgments The International F
Page 13 and 14: SUMMARY xiii en’s education--and
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
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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
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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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Page 199 and 200:
VILLAGE SOCIAL STRUCTURE IN UGANDA
Page 201 and 202:
List of Principal Authors and Contr
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ABOUT THE AUTHORS 187 rigation, and
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