An Economic Assessment of Banana Genetic Improvement and ...

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48 CHAPTER 4 Ortíz, R., and D. Vuylsteke. 1994. Plantain breeding at IITA. In The improvement and testing of Musa: A global partnership, ed. R. Jones. Montpellier, France: International Network for the Improvement of Banana and Plantains. Rald, J., and K. Rald. 1975. Rural organisation in Bukoba District, Tanzania. Uppsala, Sweden: The Scandinavian Institute of African Studies. Ssebuliba, R. N. 2000. Fertility in East African highland bananas. Ph.D. thesis, Makerere University, Makerere, Uganda. Ssebuliba, R. N., D. Talengera, D. Makumbi, P. Namanya, A.Tenkouano, W. K. Tushemereirwe, and M. Pillay. 2006. Reproductive efficiency and breeding potential of East African highland bananas. Field Crops Research 95 (2–3): 250–255. Tushemereirwe, W. K., A. Kangire, J. Kubiriba, and K. Nowakunda. 2000. Acceptability of Fusarium wilt resistant banana cultivars considered appropriate replacements for a cultivar susceptible to one disease in Uganda. Uganda Journal of Agricultural Sciences 5 (6): 62–64. Tushemereirwe, W. K., I. Kashaija, W. Tinzaara, C. Nankinga, and S. New. 2003. A Guide to Successful Banana Production in Uganda. Second edition. Entebbe, Uganda: National Agricultural Research Organization. Weedrt, J. 2003. Adoption of superior banana cultivars in the Kagera Region: Accomplishment and constraints. Bukoba, Tanzania: Kagera Community Development Programme and Economic Development Initiatives, Limited.
here> 1near 5. CHAPTER 5 Characteristics of Banana-Growing Households and Banana Cultivars in Uganda and Tanzania Svetlana Edmeades, Melinda Smale, Enoch Mutebi Kikulwe, Jackson M. Nkuba, and Mgenzi Said Ramadhan Byabachwezi A first stage of data analysis confirmed few statistical differences between exposed and nonexposed areas in the underlying social and demographic characteristics of households and the physical characteristics of their farms. This result validates the sample design (Chapter 2). In this chapter, selected characteristics of banana-growing households in Uganda and Tanzania are analyzed by elevation, and uses of new banana cultivars, practices, and planting material systems are summarized by exposure and elevation. 1 In general, means, frequencies, or proportions only are reported here, weighted by the inverse probability of selection. Banana-Growing Households Household demographic characteristics in the Lake Victoria region of Uganda and Tanzania are shown in Table 5.1. Household heads averaged 45 years of age with roughly 6 years of education in Uganda, and 49 years of age with 7 years of education in Tanzania. Though the age of the household head and mean years in school are statistically different between the highland and lowland areas of Uganda, the magnitudes of the differences are not meaningful. Roughly a quarter of household heads are reported to be women, with a smaller percentage in highelevation areas in Uganda, and a comparable pattern in Tanzania. In Tanzania, gender of the household head is the only major demographic characteristic that differs statistically by elevation. Clearly, longer-term absence of men is more prevalent in the lowland areas.
Page 1 and 2:
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
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
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
Page 62 and 63: 46 CHAPTER 4 The most widely used m
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Page 68 and 69: 52 CHAPTER 5 Table 5.4 Percentage o
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Page 74 and 75: here> 12near 5. 58 CHAPTER 5 Table
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Page 80 and 81: 64 CHAPTER 5 Table 5.20 Average num
Page 82 and 83: 66 CHAPTER 5 Table 5.23 Percentage
Page 84 and 85: 68 CHAPTER 5 Table 5.26 Average dis
Page 86 and 87: 70 CHAPTER 5 considerably higher in
Page 89: Part III. Economic Assessment of Te
Page 92 and 93: 76 CHAPTER 6 The agricultural house
Page 94 and 95: 78 CHAPTER 6 grow, but have grown i
Page 96 and 97: 80 CHAPTER 6 Table 6.2 Summary stat
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
Page 108 and 109: here> 1near 7. 92 CHAPTER 7 Table 7
Page 110 and 111: 94 CHAPTER 7 ity in the two technol
Page 112 and 113: 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
Page 171:
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
Page 201 and 202:
List of Principal Authors and Contr
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ABOUT THE AUTHORS 187 rigation, and
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