Impact Of Soil And Crop Management Technologies Promoted Through Farmer Field Schools On Farming Systems And Productivity Among Smallholder Farmers In North Rift Valley, Kenya

ABSTRACT

Conventional Extension Approaches used over decades achieved minimal successes in creating impact in terms of agricultural production and improved livelihood of smallholder farmers in Kenya. The Participatory Extension Approaches, in particularly the Farmer Field School (FFS) approach have been tried widely and created positive impact in Asian countries. Kenya Agricultural Research Institute (KARI) introduced FFS approach in 2001 as an alternative to conventional approach to promote dissemination of Soil and Crop Management Technologies (S&CMT). Since the introduction of the FFS approach in the study locations, no impact studies have been undertaken to document its importance in comparison with the conventional extension approach. The purpose of this study was to determine the impact of the S&CMTs disseminated through FFSs on the Farming Systems (FS) and productivity among the smallholder farmers in North Rift, Kenya. A survey methodology with an Ex-post facto research design was used with a sampling frame consisting of 6,560 small-scale farmers. A sample of 180 FFS and 180 Non-FFS farmers (360 persons) was chosen for the study, using random sampling. The dependent variable for the study was impact of Soil and Crop Management Farmer Field Schools (S&CMFFSs) and was operationalised into the FS and productivity variables. The FS variables were the level of change in farm practices, knowledge and skills acquired in S&CMTs and level of household income. The productivity variables included the level of soil and crop management reflected in the level of production per unit area for maize. The independent variables were the S&CM FFS and conventional extension approaches used in farmer training and dissemination of S&CMTs. Moderator variables were socio-economic factors of the respondents. Data was collected through interview schedules administered to FFS and Non FFS farmers. Descriptive statistics was used to compute percentages, means and standard deviations. Inferential statistics used included multiple regression, t-test and one way analysis of variance. Hypotheses were tested at α 0.05. Data was analysed using Statistical Package for Social Scientists (SPSS). The results indicated that there were significant differences (P