Aquaculture: A hidden goldmine for the rural poor—A cost–benefit analysis of fish farming for sustainable development and food security in Vihiga County, Kenya

Author:

Syanya Fredrick Juma12ORCID,Harikrishnan Mahadevan1,Simiyu Naomy Nasambu3,Khanna A. R. Nikhila1,Litabas Joel Anyula2,Mathia Wilson Munala2

Affiliation:

1. School of Industrial Fisheries Cochin University of Science and Technology Kochi India

2. Government of Kenya Ministry of Agriculture Livestock and Fisheries, Department of Agriculture livestock and fisheries Vihiga County government Vihiga County Kenya

3. School of Management Studies, Cochin University of Science and Technology Kochi Kerala India

Abstract

AbstractIn Kenya, aquaculture plays a significant role in enhancing the livelihoods of rural communities by boosting the local economy and diversifying protein sources. Although Vihiga County in Western Kenya boasts considerable potential for aquaculture, it paradoxically experiences some of the highest levels of poverty and malnutrition in the country. The profitability of fish farming has also been affected by inefficiencies and poor resources, disproportionately affecting the income and nutritional value of rural poor who rely on Aquaculture as a source of cheap protein. The study was conducted in Vihiga County to assess the cost–benefit of aquaculture production, selecting 100 fish farmers through a stratified random sampling technique from five sub‐counties. A descriptive research design was employed, and data analysis was conducted using correlation and regression analysis with SPSS. Budgetary techniques were used for the cost–benefit analysis. Data presentation was by comparing the mean and standard deviation in US dollars of different pond size production. The research findings indicated that the size and type of pond do not have a significant correlation and differences in production (p‐value >.05). There is a strong positive correlation between the size of the pond and the stocking density. The variable cost (VC) has a positive correlation with pond productivity meaning that an increase in VC leads to an increase in production. And is not statistically significant (p‐value = .21827, p‐value >.05). Moreover, the total cost (TC) correlation is statistically significant (p‐value = .0351, p < .05). Larger ponds are more profitable but require higher costs production than smaller ponds. The study concludes that pond size significantly impacts productivity, advocating for smaller ponds to achieve higher net returns with lower production costs. Major challenges include high costs of feeds, inputs, fish diseases, and post‐harvest losses. Key policy variables influencing aquaculture in Vihiga County include infrastructure, fish feed production, capital, and fisheries extension services. Adequate financial support from both National and County governments is crucial for sustainable aquaculture in alignment with Kenya's Vision 2030 and Global Sustainable Development Goals. Policymakers are urged to assist small‐scale farmers with financing, training, and market information to optimize returns on investment.

Publisher

Wiley

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