Full Length Research Paper
Abstract
This study assesses the nexus between livelihood diversification, technology adoption and food security status among rice farm households in the Ogun State. A multistage sampling technique was used to select two Agricultural Development Programme zones (Ikenne and Abeokuta zones) in the state. Purposive selection of two blocks per zone based on the concentration of rice farmers was done. Six farming cells were randomly selected from each block making a total of twenty-four (24) farming cells, seven rice farmers were randomly selected from each farming community giving a sample size of 168 rice farmers. A well-structured questionnaire was used to collect data. Out of the 168-questionnaire administered, 158 of it was gotten and used for the study. The data were analyzed using descriptive statistics, Simpson index for livelihood diversification and logit regression model. From the results, the age group 36 – 45 years is the modal category with 32.9% which was followed by 26 – 35 years with 27.9 percent. A large percentage (32.9) of the farmers had no formal education, 40.5 percent had school certificate, 20.3 percent had primary education, while 6.3 percent had tertiary education. Most farmers in the study area had extension agent at least once in every two months. The coefficients of age and education were found to be significant with the age carrying negative sign. It was concluded that rice farmers education in the study area was one of the major factors needed to improve their skills on other form of livelihood in order to enhance their well-being. It was recommended that young people should be encouraged to diversify their livelihood. The farmers should be educated on ways to diversify their livelihood. Credit facilities should be made available for the farm household either by the government or private parastatals to enhance farming activities. Production assets of the rice farmers in the study area should be improved on.
Key words: Rice farmers, livelihood, diversification, determinants, logit regression.
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