EVALUATION OF ELECTRONIC AGRICULTURE PLATFORM TO ACHIEVE FOOD PRODUCTION IN BUSIA COUNTY, KENYA

Abstract

Agricultural production depends on effective dissemination and access to relevant information on new production techniques, application of agricultural input, decision making on markets, prices and methods of conservation of productive resources. The purpose of this study is to evaluate the influence of electronic agriculture platforms in providing information to improve food production in Busia County. The objectives of the study include; To determine and describe the extent to which the use of e-Agriculture resources has been adopted by farmers to increase agricultural production, To identify the agricultural information needs of farmers in Busia County, To describe constraints encountered by small holder farmers’ in accessing and utilization of electronic agriculture resources and to provide policy recommendations on dissemination of e-agriculture information resources in achieving agricultural production in Kenya. The study will adopt a descriptive survey design with a target population of 181,789 small holder farmers from Nambale and Teso North Sub Counties. Random sampling using the balloting technique will be used to select the two wards in each sub county. Sample size of 384 respondents will be selected based on Krejcie and Morgan (1970) formula. A multi stage sampling technique will be used to arrive at the sample which will include; purposive, proportionate and simple random sampling techniques. Data will be collected using a questionnaire designed using Likert scale of 5 to 10 items and will be validated by experts in the department to be administered at house hold level. A pre-test of the research instruments will be done using 20 smallholder farmers from Bukhayo West ward of Nambale Sub-county. Data analysis will be aided by the Statistical Package for Social Science (SPSS) version 17.0 and the Cronbach alpha reliability test will be used to ensure that the results generated from the instruments are consistent. The collected data will be processed and analyzed using both descriptive and inferential statistics. The chi-square test of independence and cross tabulations will be used to measure the relationship between dependent and independent variables. All tests will be done at α = 0.05 level of significance.