Important Variables Influencing Milk Yields on Smallholder Farms in Western Kenya
Keywords:smallholder farms, milk yields, important variables, pair-wise ranking, beta weights, product measure, multiple linear regression
This study sought to assess the most important variables influencing milk yields on smallholder farms in Western Kenya, a region with persistent milk insufficiency. Four approaches were assessed on ranking of important variables: Use of farmer focus groups, key informant interviews (pair-wise ranking of variables), beta weights and Product measure (multiple linear regression). The findings showed that all the four methods produced different ranking order. Using a combined weighting system, the most important variables influencing milk yields on smallholder farms were found to be fodder; dairy meal, credit, Artificial insemination, improved research technologies, group membership, policy and economic returns. Collectively, they explained 63.9% of the variance in milk yields in the area (F8, 291= 65.089, p<0.001).We argue that a combined weighting approach appears to be a sharper ranking method in selecting important variables from many components in a value chain system.
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