Factors Influencing Adoption of Improved Groundnut Processing Technology among Rural Women in Kebbi State, Nigeria

Dawa Amina, Umar Sa’adu and Gona Ayuba
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Dawa Amina: Department of Agricultural Economics and Extension, Kebbi State University of Science and Technology, Aliero
Umar Sa’adu: Department of Agricultural Economics and Extension, Kebbi State University of Science and Technology, Aliero
Gona Ayuba: Department of Agricultural Economics and Extension, Kebbi State University of Science and Technology, Aliero

International Journal of Research and Scientific Innovation, 2024, vol. 11, issue 8, 1367-1376

Abstract: The study was carried out to determine the factors influencing adoption of improved groundnut processing technology among rural women in Kebbi State, Nigeria. Primary data were collected through the use of structured questionnaire. A multi-stage sampling procedure was used to select the respondents. First stage involved the purposive selection of 6 LGAs with highest concentration of women groundnut processors in the State. Purposive sampling was used in selecting the communities based on predominance in groundnut processing. Forty (40) respondents were randomly selected from each LGA to obtain a total of 240 respondents. Descriptive statistics such as mean, percentages, frequency distribution and regression analysis were employed used to achieve the objective of the study. The result showed that 32.5% of the respondents were between the ages of 41-50, 87% of the respondents were married, 55% of the respondents had secondary school education, 48% of the respondents had annual income of N501,000-N1000,000, and 54% of the respondents indicated that groundnut processing was their major occupation. The result showed that most (95.8%) of the respondent had access to market and four (4) extension visits in a year. The result showed that majority (68.8%) of the respondents were members of association, while 64.2% of the respondents had access to credit. It was discovered that age, annual income, years of experience in groundnut processing, membership of cooperative society, compatibility and complexity significantly contributed to the model at 5% and 10% levels of probability.

Date: 2024
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