An Economic Assessment of Banana Genetic Improvement and ...

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70 CHAPTER 5 considerably higher in lowland areas of Tanzania, and differs markedly in pattern between banana-growing households in Uganda and Tanzania. The diversity of banana cultivars is high at the country, village, and household levels across the Lake Victoria region of Uganda and Tanzania. Even the most popular banana cultivars occupy less than 10 percent of the total number of mats grown in Uganda. Cooking bananas are not only the most important food staple for households, but they are also a source of cash in local markets. In Uganda, the findings support banana researchers’ observations that (1) farmers have difficulties recognizing and attributing different disease pressures and (2) farmers consider endemic cooking bananas to be superior in terms of cooking quality compared to hybrid cultivars. Furthermore, use rates for recommended management practices appear to be much higher than for improved banana cultivars, particularly in high-elevation and exposed areas. Transfer of planting material, predominantly between farmers, is evidently more intensive in low-elevation areas, where disease pressures are greater. Village social structures and participation in social organizations emerge as important determinants of use of banana technologies. The number of distinct banana cultivars identified in Tanzania is larger than in Uganda, considering the smaller geographic extent of the Tanzanian sample, and recent introductions of exotic and hybrid bananas have no doubt contributed to the richness of materials grown. A few common characteristics emerge between findings in Uganda and Tanzania, however: (1) the vast majority of the identified cultivars (more than 80 percent) are endemic to the region; (2) on average, households grow numerous distinct cultivars simultaneously in their banana groves; (3) all farms grow at least one cooking cultivar; (4) farmers perceive endemic bananas to be superior in terms of consumption quality; and (5) there is strong evidence of farmer-to-farmer exchange of planting material of both endemic and exotic and/or hybrid cultivars. Adoption of hybrids and exotic cultivars (both endemic to other regions but not this one, and nonendemic) is greater in Tanzania than in Uganda. The relative severity of biotic pressures in Kagera Region is one reason. Data also confirm that farmers in Kagera Region perceive that hybrids are superior to endemic types in terms of yield and resistance to black Sigatoka and weevils, but inferior with respect to Fusarium wilt, as the scientists who recommended the varieties had expected. The same cannot be said for the farmers surveyed in Uganda. Although this result could be an artifact of the relatively small sample of hybrid adopters in Uganda, it is consistent with national researchers’ observations that disease pressures were greater in Tanzania, and Ugandan farmers have difficulty in disease recognition. Clearly, dissemination pathways, both formal and informal, are another major factor that explains differences in adoption between the two countries. The next three chapters investigate the determinants and effects of adoption of cultivars and practices. References Bagamba, F. 2007. Market access and agricultural production: The case of banana production in Uganda. Ph.D. thesis, Wageningen University, The Netherlands. Edmeades, S., M. Smale, M. Renkow, and D. Phaneuf. 2004. Cultivar demand within the framework of an agricultural household model with attributes: The case of bananas in Uganda. Environment and Production Technology Division Discussion Paper 125. Washington, D.C.: International Food Policy Research Institute.
BANANA-GROWING HOUSEHOLDS AND BANANA CULTIVARS 71 Gold, C. S., A. Kiggundu, D. Karamura, and A. Abera. 1998. Diversity, distribution and selection criteria of Musa germplasm in Uganda. In Bananas and food security, ed. C. Picq, E. Fouré, and E. A. Frison. International symposium on the socioeconomics of non-export banana production, Douala, Cameroon, November 10 –14, 1988. Montpellier, France: International Network for the Improvement of Banana and Plantains. Gold, C. S., G. Kagezi, G. Night, and P. Ragama. 2004. The effects of banana weevil damage on highland banana growth, yield and stand duration in Uganda. Annals of Applied Biology 145 (3): 263–269. Hardaker, J., R. Huirne, and J. Anderson. 1997. Coping with risk in agriculture. Wallingford, U.K.: CAB International. Katungi, E. 2006. Social capital and technology adoption on small farms: A case of banana production technology in Uganda. Ph.D. thesis, University of Pretoria, Pretoria, Republic of South Africa. Nkonya, E., J. Pender, C. Kaizzi, K. Edward, and S. Mugarura. 2005. Policy options for increasing crop productivity and reducing soil nutrient depletion and poverty in Uganda. Environment and Production Technology Division Discussion Paper 134. Washington, D.C.: International Food Policy Research Institute. Nkuba, J. 2007. Assessing adoption and economic impacts of new banana cultivars on livelihoods of farmers in Kagera Region, Tanzania. Ph.D. thesis, Department of Agricultural Economics, Sokoine University, Sokoine, Tanzania.
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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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Page 52 and 53: 36 CHAPTER 3 Nkonya, E., J. Pender,
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Page 89: Part III. Economic Assessment of Te
Page 92 and 93: 76 CHAPTER 6 The agricultural house
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Page 98 and 99: 82 CHAPTER 6 tion. More frequent vi
Page 100 and 101: 84 CHAPTER 6 Table 6.4 Prototype ho
Page 102 and 103: 86 CHAPTER 6 Table 6.5 Characterist
Page 104 and 105: 88 CHAPTER 6 References Cameron, A.
Page 106 and 107: 90 CHAPTER 7 by-products of other f
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Page 114 and 115: 98 CHAPTER 7 The direct link betwee
Page 116 and 117: 100 CHAPTER 7 Table 7.3 Factors inf
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Page 120 and 121: 104 CHAPTER 7 fertility management
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Page 124 and 125: 108 CHAPTER 7 Stevens, J. P. 2002.
Page 126 and 127: 110 CHAPTER 8 defined as a function
Page 128 and 129: 112 CHAPTER 8 inputs or implement c
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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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