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Farmers’ choice among recently developed hybrid banana varieties in Uganda: A multinomial logit analysis

Author

Listed:
  • Tushemereirwe, W.K.
  • Wale, E.
  • Ortmann, G.F.
  • Akankwasa, k.

Abstract

This paper analyses the effect of farmer characteristics, variety attributes and agro-ecological conditions on farmers’ banana variety choice decisions in Uganda. A Multinomial Logit (MNL) model was used to estimate the determinants of variety choice. The results show that M9 was the most preferred hybrid variety, followed by M2 and M14. However, many of the respondents (39.4%) chose Mbwazirume, a local variety, as their most preferred variety. Good taste, large bunch size, soft food and good flavour were the most desirable attributes, while longer maturity period was a notable undesirable attribute. Results from the MNL analysis suggest that small land size, taste and regional location were negatively associated with variety choice, while perceptions that hybrid bananas could reduce food insecurity and tolerance to pests and diseases were positively associated with probabilities of variety choice. Probabilities of choosing hybrids for food security increase in favour of M2 (by 6.13%) and M9 (27.60%), and decrease by 23.05% for M2, 6.89% for M14 and 9.36% for M9 due to taste relative to Mbwazirume. Farmers’ involvement in varietal improvement and development programmes is vital for meeting their preferences. Future breeding efforts should consider attributes such as bunch size, good taste, soft food and agronomic characteristics. Farmers with large land sizes should be targeted for on-farm promotional activities to increase the potential adoption and impact of the hybrids. After the hybrids are popularized and used by farmers, there will be a need for an impact study to evaluate their acceptability in terms of household food security and income.

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  • Tushemereirwe, W.K. & Wale, E. & Ortmann, G.F. & Akankwasa, k., 2013. "Farmers’ choice among recently developed hybrid banana varieties in Uganda: A multinomial logit analysis," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 52(2), March.
    • Handle: RePEc:ags:agreko:345244
    DOI: 10.22004/ag.econ.345244
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