| This study applied a technology-characteristic approach to the adoption of improved rice varieties in Southern Senegal. The objective was to test the hypothesis that both farm, farmers' characteristics, and farmers' perceptions of technology-specific characteristics significantly condition the technology adoption decision. Earlier studies have not incorporated the characteristics of the technology in the analysis of adoption. Different measures of performance were used to evaluate the behavior of the improved varieties, and seven characteristics elicited from farmers were used to measure the extent to which the improved varieties meet the expectations of farmers. A Tobit model was used to test the hypothesis, using a stratified random sample of 400 farmers. The results reveal that the application of fertilizer is the major determinant of the Yield Gap. Most of the improved varieties are superior to the local in better environments, but do not perform well in poor environments. One of the causes of slow progress in rice production is the undue attention given to developing technologies for physical favorable environments. Improved and local varieties have different responses to fertilizer, and under the farm level conditions, response curve cross-over does occur for many varieties. Hence, the ordering of varieties with respect to yield will vary at high and low management levels. The results also show that farmers use different criteria to discriminate among varieties. Farmers demand rice varieties with short maturation period, tall stature, good resistance to soil-related constraints, and good cooking quality. The study finds that farmer-specific variables (information, participation in village-level organization, access to credit, age) and technology-specific factors (cycle, resistance to stress, height, cooking quality) are significant in explaining farmers' adoption of improved varieties.;The model results show that farmer perceptions of the technology-specific attributes of the varieties are the major factors determining adoption. The response to changes in these attributes is relatively more elastic than the response to changes in the farmer-specific factors. Therefore, research and extension that shape the adoption of improved technologies, need to consider farmers' perceptions of technology-specific attributes in their programs. |
