The study examined the resource use efficiency of yam production in Ekiti State, Nigeria. Multistage sampling techniques were used to select 120 respondents and were interviewed using a well structured questionnaire. The study described the socioeconomic characteristics of the farmers; indentify the system of land ownership and the constraints that yam farmers faced; and analyze the technical efficiency of the farmers. Descriptive statistics such as; frequency counts, mean and percentage was used while the inferential statistics used to estimate technical efficiency was stochastic frontier function. The findings revealed that the study area is dominated by male, married, experienced and small holder farmers with almost secondary school level of education. The mean and maximum technical efficiency was 0.87 and 0.99 respectively thus showing a high level of how yam farmers are technically efficient in the study area. The study recommended that government should provide adequate extension and supportive services with a view to improving farming techniques with technological innovation and farm inputs should be made available at highly subsidized rates through adequate and efficient distribution to the farmers.
I S S N 2 3 2 1 -1 0 9 1 V o l u m e 1 0 N u m b e r 2 J o u r n a l o f S o c i a l S c i e n c e s R e s e a r c h 2014 | P a g e c o u n c i l f o r I n n o v a t i v e R e s e a r c h F e b r u a r y 2 0 1 6 w w w . c i r w o r l d . AbstractThis study was carried out on effect of climate change on cocoa production in Ondo State, Nigeria. It specifically identified the socio-economic characteristics, examined the coping strategies adopted by the farmers in adjusting to these problems, determined the factors affecting the coping strategies adopted by the farmers in adapting to climate change, examined the rainfall and temperature patterns of the study area within the period of 1992 -2012 and analyzed the effects of some climatic variables on cocoa production within the period of 1992-2012. Multi-stage sampling technique was employed to obtain data from 180 cocoa farmers that were purposively selected from 3 Local Government Areas in Ondo State being the highest producers it the State, these are; Ondo East, Akure South and Idanre LGA. Descriptive Statistical Analysis, Trend Analysis, Multiple Regression Model and Tobit Regression Modelwere used to analyze the data. About 62% of the cocoa farmers interviewed observed noticeable changes in temperature while 70% and 51% of the farmers reported increased changes in rainfall and sunlight respectively. Among the most prevalent climate change problems reported among cocoa farmers in the study area were; high incidence of black pod disease (80%), death of cocoa trees (75%), increase malaria incidence (65%),reduction in cocoa yield (63%) and inability to dry cocoa pods (61%). The trend analysis of cocoa production in the study area revealed that there was a sharp decrease in the volume of cocoa produced from 1992-2000while fluctuatingoccurrenceswere witnessed in the volume of cocoa produced till 2012. Also, there was variability in the rainfall, relative humidity and temperature patterns examined within the period under the study. The major coping strategies employed by the cocoa farmers in the study area were; use of chemicals (75%), mulching and planting trees (69%) different planting date (63%), monitoring weather (61%) and crop diversification (58%)while factors influencing coping strategies adoption by the cocoa farmers in the study were; level of education, farm size, access to extension service and farming experience.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.