Applying conjoint analysis to match farmer's preferences for cattle traits with those conferred by the improved trypanotolerant Orma Boran cattle in coastal Kenya

Abstract

Bovine trypanosomiasis is a key constraint to increased livestock production across all production systems of Kwale County in coastal Kenya. Genetically controlled trypanotolerance of cattle is regarded as one of the promising methods available to mitigate the impact of this disease, and the improved trypanonotolerant Orma Boran is one of the breeds available in Kenya for this purpose. Conjoint analysis was thus used to match farmer’s preference for cattle traits against those conferred by this breed in three production systems of Kwale County. The study also estimated the transaction costs (TC) that would influence access to breeding services while availing the breed. The aim was to identify production systems where the breed matches well with farmer preferences, as an initial step towards its dissemination. In order of importance, farmers preferred cattle that were resistant to trypanosomiasis, had large body size, exhibited resistance to tick-borne diseases (TBD), and had high milk output. However, there were inter-production system differences in trait preferences, where resistance to TBD was least valued in the agro-pastoral system, with more emphasis put on the size of animal and trypanotolerance respectively. On the other hand, in medium potential and marginal pastoral systems, more emphasis was placed on TBD resistance, followed by trypanosomiasis resistance. The agro-pastoral production system was therefore delineated as a potential area for disseminating the breed. Regarding transaction costs, the price of service was the most important transaction costs element. Furthermore, whereas bull service was preferred over artificial insemination (AI) services in marginal pastoral and medium potential systems, AI was given preference in an agro-pastoral system. It was thus concluded that the Orma Boran dissemination would be successful among agro-pastoral households system, and should be delivered using subsidized AI services.