Browsing by Author "Manyong, V.M."

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    Adoption of a New Maize and Production Efficiency in Western Kenya
    (2010-09) Mignouna, D.B; Mutabazi, k; Senkondo, E.M; Manyong, V.M.
    Declining yields of maize as a result of Striga infestation has necessitated a new technology known as Imazapyr-resistant maize (IRM) to contain the problem. As a result, research and development initiatives with substantial participation of the private sector to transfer this new technology to farmers have been made in western Kenya. This study therefore assesses the adoption of IRM variety and efficiency levels of farmers in western Kenya. A multi-stage sampling technique was used to select a total of 600 households from Nyanza and Western provinces for this study. Tobit model and stochastic production frontier analysis were the analytical methods. Results show that age, education, maize production gap, risk, contact with extension agents, lack of seeds, membership in social group, effective pathway for IRM dissemination and compatibility of the technology are the variables that were found to be significant (P<0.05) in shaping the decisions of households on whether to adopt or not. The study reveals that the mean technical efficiency of maize production of sampled farmers is 70% indicating some inefficiencies of maize production in western Kenya. Also, adoption of IRM significantly increased frontier maize output (P<0.01); household size decreased inefficiency along with farm size. It was recommended that efforts to increase adoption of IRM for enhanced farm efficiency should focus on farmers’ education, farming experience and access to information and farm basic inputs.
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    Determinants of adopting Imazapyr-resistant maize technologies and its Impact of household Income in Western Kenya
    (AgBioForum,, 2011-01) Mignouna, D.B.; Manyong, V.M.; Rusike, J.; Mutabazi, K.D.S; Senkondo, E.M.
    This study identifies the adoption determinants and causal impact of adoption of imazapyr-resistant maize (IRM) on income and poverty among maize farming households using a logistic model and Heckman selection-correction model. Results from a randomly selected sample of 600 households consisting of 169 adopters and 431 non-adopters reveal that combined specific household, farm, institutional, and technological factors influ- ence the probability of adoption of the technology. The results also showed that adoption of IRM raises farm household income even after controlling for observable and unobservable house- hold characteristics. Conclusions drawn from this study are that the use of IRM for Striga control is a reasonable policy instru- ment to raise small-farm income and reduce poverty among maize farming households.