An Economic Assessment of Banana Genetic Improvement and ...

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168 APPENDIX A Table A.1 (continued) Cultivar name Synonyms Genomic group Common use Household share (percent) Cultivar share (percent) 62 Muvubo Saga saga Muzhuba Muzubwe Mujuba 1 1 22.44 1.70 63 Nabusa Enyeru Enyarweru 1 1 22.63 6.04 64 Nakabinyi Kakono 1 1 3.09 0.14 65 Nakabululu Mbululu Embururu Butende Enyigit 1 1 43.52 6.39 66 Nakamali Malira Omutono Malira Nakangu 1 1 6.96 1.48 67 Nakasabira — 1 1 1.55 0.05 68 Nakawere Karinga Kasenene Musenene 1 1 2.13 0.15 69 Nakinyika Kifuba Kafuba Enzuma 1 1 19.92 2.53 70 Nakitembe Entaragaza Enshembashembe Malira Omunene Malira 1 1 57.83 9.18 71 Nakyetengu Kitetengwa Kitika 1 1 5.22 0.49 72 Nakyewogoola — 1 1 0.19 0.00 73 Nalugolima Nyarugoroma 1 1 0.39 0.02 74 Nalukira Enyarukira 1 2 1.35 0.30 75 Nalwesaanya — 1 2 0.19 0.01 76 Nalyewurula — 1 1 1.16 0.04 77 Namadhi Nalusi 1 1 1.35 0.01 78 Namadhugudha Namunwe Nyeko-ger 1 1 7.54 0.66 79 Namafura — 1 1 0.19 0.00 80 Namaliga Namalevu Kyanakyandiga Kiriga Rwakashita 1 1 4.06 0.28 81 Nambi — 1 1 0.97 0.08
BANANA TAXONOMY FOR UGANDA 169 Table A.1 (continued) Cultivar name Synonyms Genomic group Common use Household share (percent) Cultivar share (percent) 82 Namwezi Serunjogi 83 Nandigobe Enjagata Ngalodabha Mbedha 1 1 5.03 0.36 Nyarwanda 84 Ndyabalangira Enzirabushera Ntinti 1 1 18.96 1.55 Mulangira Muzirankanja Muziranyama Katetema 1 1 25.73 3.89 85 Nfuuka Nyakahangazi 1 1 6.00 1.07 86 Njoya — 1 1 2.13 0.83 87 Nkago Ikago 1 1 3.09 0.10 88 Nsabaana — 1 1 0.19 0.00 89 Ntujo — 1 1 0.19 0.00 90 Okiteng — 1 1 0.19 0.01 91 Oringoi — 1 1 0.19 0.01 92 Shombobureku — 1 1 0.39 0.01 93 Siira — 1 1 12.38 0.95 94 Ssalalugazi — 1 1 0.39 0.01 95 Sukali Ndiizi Kabaragara Osukari Epusit Kapere 22 (AAB) 3 60.74 6.71 Notes: Genomic groups are defined as 1 = endemic (AAA-EA), 2 = nonendemic, 22 = exotic, and 23 = hybrid. Common uses are 1 = cooking, 2 = beer brewing, 3 = dessert, 4 = multiuse, and 5 = roasting. Household share is the proportion of households that grow this cultivar out of 517 households in the sample. Cultivar share is the proportion of mats planted to this cultivar out of 52,321 mats in the sample. — indicates a cultivar without a synonym. References Karamura, D. A. 1998. Numerical taxonomic studies of the East African highland bananas (Musa AAA-East Africa) in Uganda. Ph.D. thesis, University of Reading, Reading, England. Karamura, D. A., and B. Pickersgill. 1999. A classification of the clones of East African highland bananas (Musa) found in Uganda. Plant Genetic Resources Newsletter 119: 1–6.
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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
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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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Page 142 and 143: 126 CHAPTER 8 Table 8A.3 Production
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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
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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 178 and 179: 162 CHAPTER 11 4. 5. for which the
Page 181 and 182: APPENDIX A Banana Taxonomy for Ugan
Page 183: BANANA TAXONOMY FOR UGANDA 167 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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