FACTORS AFFECTING THE ADOPTION OF DISEASE-RESISTANT PLANTAIN AND BANANA (MUSA SPP.) HYBRIDS IN NIGERIA
The study assesses the level of adoption of hybrid cultivars of plantain and banana (Musa spp.), promoted through plantain promotion projects based on farmer-to-farmer diffusion and extension events, and determines the factors affecting their adoption and dissemination in four plantain and banana growing areas of Nigeria.
Data have been analyzed with an econometric Logit model.
The results indicate that the farmer capacity to choose and use planting materials and related production techniques has been significantly improved by training programs over a period of four years.
Farmer awareness has been increased through field days, demonstration plots, farmer exchange visits and a platform for sharing information on hybrids and associated techniques.
Reasons reported by farmers to adopt the hybrids include high yields, resistance to black leaf streak, taste/good cooking quality, and access to planting materials due to the rapid multiplication technique deployed by the project.
Farmers, who participated in on-farm trials, demonstration plots, field days and/or other training programs on hybrids and associated technologies during the five last years, adopted the hybrid cultivars because of their direct participation and contact with breeders and other project partners.
The projects collaboration with the national extension system for the organization of annual training programs with pioneer farmers on hybrid cultivars and associated technologies has highly contributed to the large and effective dissemination and adoption of plantain and banana hybrids by small farmers.
Aïtchédji, C., Tenkouano, A. and Coulibaly, O. (2010). FACTORS AFFECTING THE ADOPTION OF DISEASE-RESISTANT PLANTAIN AND BANANA (MUSA SPP.) HYBRIDS IN NIGERIA. Acta Hortic. 879, 741-748
DOI: 10.17660/ActaHortic.2010.879.80
https://doi.org/10.17660/ActaHortic.2010.879.80
DOI: 10.17660/ActaHortic.2010.879.80
https://doi.org/10.17660/ActaHortic.2010.879.80
binary logit model
English