Influence of Information and Crop Management Practices on Productivity among Smallholder Potato Farmers in North Rift Kenya - Kamuren, Charles K. (African Journal of Education,Science and Technology (AJEST), 2022)
Potato (Solanum tuberosum L) tuber, is a major food whose demand is increasing worldwide. Its value-chain in Kenya generates employment for approximately 800,000 farmers and 3.3M citizens. Nonetheless, in spite of dissemination of appropriate technologies, innovations, and management practices (TIMPs), Kenya’s productivity has persisted at lows of 9-15t/Ha compared to Netherland’s 36-42t/Ha. Implementation of field-specific decision support system (DSS) has been proposed as a possible intervention. However, no studies exist showing the influence of prevailing information management (IM) practices on crop management practices. Therefore, in the context of precision agriculture (PA) and the theory of the firm, this study sought to assess, subject to farming duration, the influence of information sources on crop spacing and resultant effect on productivity among smallholder potato farmers in Kenya’s North-Rift highlands. Using stratified random sampling, a survey was conducted on 353 households of whom potato was the main crop and whose farms were located at least 2300masl. Descriptive statistics, linear regression and post-estimation data analysis techniques were employed. Extension services, radio, farmer groups, Internet and telephone usage stood at 62%, 45%, 18%, 6% and 3% respectively while 11% possessed an email address. Regardless of farming duration, in decreasing order, radio and Internet (implicitly) showed positive aggregate influence while farmer groups and extension services showed negative aggregate influence. Notably, all information sources were significantly associated with ‘not known’ seed spacing response with corresponding significant negative effect on productivity. The results demonstrate poor IM and imprecise crop management practices thereby validating the necessity for entrenchment field-specific DSS