Technology Training Needs of Women Farmers for Enhancing Value Change in Marketing of Farm Products in Enugu State, Nigeria (original) (raw)
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The survey was conducted to identify constraints to participation of rural women in technology dissemination of Women in Agriculture Program (WIA) in Imo State, Nigeria. Questionnaire was used to collect data from a sample of 60 respondents. Data were analyzed using descriptive statistics such as frequency, percentage and mean score. Results showed that 33.0% of the respondents were aged between 41 and 50 years, majority (75.0%) were married, 88.0% had formal education and 55.3% engaged in farming and trading, while 56.6% had a household size of 6-10 persons. The respondents participated in the activities like processing and utilization of food crops (16.7%), harvesting and storage of food crops (16.7%), dry season vegetable production (13.3%), processing and utilization of livestock products (10.0%), processing and utilization of soya bean into soya milk and soya meal (6.7%). The study recommended that rural women should be encouraged Original Research Article Okeke et al.; ARJA, 11(3): 1-7, 2019; Article no.ARJA.50080 2 to join cooperative societies in order to pull their resources together. It also highlighted the need for promotion of rural women's activities through adequate provision of credit facilities by government at all levels for optimum productivity.
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This study examines the factors that drive technology utilisation, learning and transfer among women farmers in Nigeria. It assesses both modern and indigenous technologies used in farming activities. Three states were purposively selected from the six that comprise the South West geopolitical zone of the country. Structured questionnaire was administered to 180 women smallholder farmers who were randomly selected in equal proportion across the three states. Some 128 copies of questionnaire were retrieved representing a response rate of about 71%. The study reveals that majority of the women (about 67%) use indigenous technologies while only a few (17%) and 16% use modern technologies and a combination of both respectively. Family and friends are the main source of learning indigenous technologies while extension agents are the major source of modern. The study uses spearman correlation to determine the drivers of the dependent variables. Age, level of education, years of experience...
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The mobile phone technology is an important tool to enhance farmers’ access to better paying agricultural markets. The study reports the results of a household study in Mwanza, Dedza and Mzimba Districts of Malawi. The study assesses drivers of adoption of mobile phone technology for agricultural marketing by smallholder farmers. The study used regression techniques to identify drivers and extent of mobile phone use. Results show that use is positively affected by literacy, distance to local market, land size, current value of assets, crop income, and region variations but negatively influenced by access to electricity. Intensity of use is conditioned by gender, participation in agricultural projects, ownership of a mobile phone, current asset value, distance to nearest public phone services, and region variations. Asset endowment plays a critical role in enhancing adoption of mobile phone technology. Gender disparities significantly affect adoption as most women have limited access...
The Impact of Education on Small-scale Farmers’ Use of ICT in Abuja, Nigeria
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The study examined the impact of farmers’ level of education on the use of Information Communication Technologies (ICT) – radio, television, GSM phone video, agricultural books, camera and computer. A multistage technique was adopted for sampling while questionnaire was used for data collection. A total of 320 farmers made up of those who had primary, secondary, post-secondary and no formal school education were interviewed. Data were analyzed using two-way mixed analysis of variance (ANOVA). Results showed that, on average, farmers with post-secondary education significantly (p < .05) used all the types ICT more than those who had at most secondary education. There was no significant difference (p > .05) between farmers who had secondary and primary education in the use of all types of ICT but farmers who had secondary education significantly (p < .05) used ICT more than those with no formal school education. On the contrary, there was no significant difference (p > .05...