Farmer Perception of Technology and its Impact on Technology Uptake: The Case of Fodder Legume in Central Kenya Highlands.

Technology adoption by farmers is crucial to increasing agricultural productivity hence meeting food and nutrition challenges in Africa. Economists investigating consumer demand have accumulated considerable evidence showing that consumers generally have subjective preferences for product attributes. However, when investigating adoption of new agricultural technologies, economists have lagged behind in analysing how farmers' (the consumer of agricultural technologies) subjective perceptions of technology characteristics affect their adoption decisions. Focusing on farmer perceptions of technologies may provide a better understanding of technology adoption since they deal with the technologies and probably perceive technologies differently from researchers and extension agents. The objective of this paper is to investigate farmers' perception of technology and its impact on adoption using a case study of legume forages in central Kenya highlands. Data from a random sample of 131 farm households in four districts in central Kenya was used. Using participatory techniques, four most important fodder legume attributes to farmers in their adoption decision were identified. These were then used in conjoint analysis. An ordered probit model was estimated to assess relative importance of each attribute to the farmer. A tobit model was also estimated to show the effect of farmers' perception of calliandra and desmodium on probability and intensity of adoption. Results showed that dry season tolerance and economy on land are most important characteristics of fodder legumes to the farmers. It was also found that Calliandra and desmodium were more relevant to the farmers in the area than other fodders. Farmers' perception of the two fodders had a significant impact on their adoption. Consequently, it was recommended that before introducing a technology in an area, it is necessary that the farmers' perception of the technology be analysed Conjoint analysis, ordered probit and tobit estimates, fodder legume adoption