Value Chain Analysis of Carps (Fish) in Rupandehi, Nepal
Rinu Chaudhary1*, Chandra Kishor Chaudhary1, Sandeep Lamichhane1, Homnath Dhakal1
1Agriculture and Forestry University (AFU), Rampur, Chitwan, Nepal
Int. J. Grad. Res. Rev. Vol 9(1-2): 19-31.
Copyright (c) 2023 International Journal of Graduate Research and Review
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A survey was conducted to analyze the value chain of carps among 80 respondents in Rupandehi district. The study was conducted among 80 respondents of which 60 were fish farmers, 10 were traders and 10 were consumers. Data were collected by using a semi-structured questionnaire for household survey, focus group discussion, and key informant interview. Descriptive statistics on socio-demographic and economic variables, SWOT (Strength Weakness Opportunity and Threat) analysis, benefit-cost ratio analysis, value chain map, volume map were used to analyze gathered data. The average family size per household in the study site was 7.40. The average age of the respondents was 40 years and most of the respondents were Madhesi. The majority of the respondents (38.3%) had 5-10 years of fish farming experience. The majority of input costs were feed (71%), pond maintenance (16%), labor (7%), fingerlings (2%), fuel (1%), fertilizer (2%) and lime (1%). The average benefit-cost (B/C) ratio was 1.77. The majority of fish produced in Chhapiya (Rupandehi) was marketed to four places- Chhapiya, Bhairahawa, Butwal, and Parasi. A higher volume of the produced fish went to Bhairahawa and Butwal. The producer share percentage was higher in the National marketing channel; Butwal (60%) than Bhairahawa (59.9%) & Parasi (55.71%) and other local marketing channel (57.35%). The price spread percentage was found higher in Parasi (44.28%) than other regional and local marketing channel. The marketing efficiency value of Butwal (7.07) is highest among Parasi (3.20) and Bhairahawa (4.01). Feed cost & flood for producer and ice availability & transportation problem for the traders were ranked as a major problem.
Keywords: Fish farming; Rupandehi; Value chain analysis.