[PDF][PDF] Dynamics of the adoption of improved aquaculture technologies among fish farmers in Lagos State, Nigeria

OJ Olaoye, GNO Ezeri, Y Akegbejo-Samsons… - Croatian Journal of …, 2016 - sciendo.com
OJ Olaoye, GNO Ezeri, Y Akegbejo-Samsons, JM Awotunde, WG Ojebiyi
Croatian Journal of Fisheries, 2016sciendo.com
The study assessed the adoption of improved aquaculture technologies among fish farmers
in Lagos State, Nigeria. A total of 90 fish farmers were sampled through the multistage
sampling technique. A validated and pretested interview schedule was used to obtain
primary information from the fish farmers. Obtained data were analyzed using descriptive
and inferential statistics. Results obtained revealed that more than half and about one-third
of the fish farmers sourced credit facilities from cooperative societies and Esusu …
Abstract
The study assessed the adoption of improved aquaculture technologies among fish farmers in Lagos State, Nigeria. A total of 90 fish farmers were sampled through the multistage sampling technique. A validated and pretested interview schedule was used to obtain primary information from the fish farmers. Obtained data were analyzed using descriptive and inferential statistics. Results obtained revealed that more than half and about one-third of the fish farmers sourced credit facilities from cooperative societies and Esusu, respectively, while almost all sold their fishes as smoked fish. Higher proportions of the fish farmers were aware, tried and adopted most of the improved aquaculture technologies with some of the fish farmers also discontinuing most of the previously adopted technologies. The findings of the study also reported that the fish farmers had positive attitude towards the adoption of improved aquaculture technologies. Results of regression analysis revealed that secondary occupation of the fish farmers (β=-0.324, p< 0.01), annual income level (β=-0.471, p< 0.05), cost of pond construction (β= 0.477, p< 0.05) and total profit realized (β=-0.466, p< 0.05) were significant predictors of the adoption of improved technologies by the fish farmers with an R2 implying that 46.0% of the variability in the fish farmers’ adoption of improved aquaculture technologies is explained by the socio-economic and production characteristics of the fish farmers. The study concluded that the adoption of improved aquaculture technologies is dynamic and highly influenced by the socio-economic characteristics of the fish farmers which also change with time. It is therefore recommended that technologies that received low level of adoption or which discontinued after earlier adoption should be worked on so that the adoption of those technologies would translate to increased income level of fish farmers, reduced cost of pond construction and increased profit of the fish farmers.
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