Effects of Digital Systems and Climate Smart Agriculture on Domestication and Productivity of Cape gooseberry (Physalis Peruviana L.) Among Farming Families in Baringo County, Kenya

Abstract

Cape Gooseberry fruit has documented nutritional, medicinal and industrial values. In Kenya, the level of domestication of the crop is low, despite the fact that it grows naturally in many parts of the country, including Baringo County. The purpose of this study was to introduce the crop in Baringo County for cultivation, and determine its acceptance levels. The study, also, documented the eco-physiological characteristics of the crop in situ. The study examined the deployment and use of documentary audio-visuals, online training and mobile app on Cape Goosberry productivity. In addition, the study incorporated climate smart agriculture, the selected practices being organic manure and intercropping with beans. The research designs used were quasi-experimental and participatory learning and action research. The sample size for the study was 120. Three Sub-Counties in Baringo County were purposively selected. From each Sub-County, one ward was, also, purposively selected. The sample was distributed equally among the three wards. Random sampling was used to select 40 farming families from each ward. Within each ward, sampled farming families were assigned to four treatments as follows: The first group received crop technologies through digital systems and incorporated climate smart agriculture; the second group received technologies through digital systems; the third group incorporated climate smart agriculture and relied on regular extension services; and the last group relied on regular extension services. The farming families grew the crop and at maturity, they harvested and weighed the fruits. The data collection instruments used were interview schedules, observation schedules and crop productivity templates. Experts examined the validities and reliabilities of the instruments and the recommended improvements effected. Triangulation and KR-21 were used in determining the instrument reliabilities, which yielded a reliability coefficient of 0.94. Productivity data were analysed to determine the effects of digital systems and climate smart agriculture. Content analysis, descriptive and inferential statistics were used in analysis. The inferential statistics used were t-tests and analysis of variance. The tests were at 0.05 level of significance. The major findings are that: Cape Gooseberry performs well under clay loam soil; farmers in Baringo County are willing to engage in production of the crop; and productivity levels improved when technologies were disseminated using digital systems in combination with climate smart agriculture. The conclusions from the study are that: Cape Gooseberry is a viable crop for Baringo County. The study recommends provision of training of extension staff on integration of digital systems and climate smart agriculture on extension systems.