STUDY OF FISH FARMERS SOURCE OF AQUACULTURE INFORMATION IN GHANA Kwamena Quagrainie Purdue University, USA Steve Amisah Kwame Nkrumah University of Science & Technology, Ghana
Aquaculture in Ghana • Main species are tilapia (Oreochromisniloticus) and catfish (Clariasgariepinus) • Total production about 950 mt/year • Farms concentrated in Ashanti region • Majority of farmers are small-scale operators using extensive fish farming practices
Purpose of Study • In 2005 Government took steps to support and accelerate aquaculture development by providing • extension services • training in fish farming techniques • training in basic bookkeeping & business plan preparation • fingerlings for sale to fish farmers
Other agencies involved in aquaculture • Government parastatals • Non-Governmental Organizations – GTZ, FAO, WorldFish Center, etc • Universities • Farmer groups
Questions? • Where do farmers obtain information about fish farming? • What is the source of technical assistantship on fish farming? • What factors influence farmers’ choice of information source?
Methodology • Questionnaire solicited information on: • Source of information for aquaculture • Demographics • General Farm operations • Fish Farm operations
Results - Demographics • Regional responses • Ashanti = 72% • Brong-Ahafo = 28% • Males = 91% • Average age = 53yrs • Years farming = 20yrs • Literacy rate = 84% • Primary = 13% • Secondary = 35% • Adult Ed = 11% • Post-Sec = 33%
Results - Demographics • Average agricultural farm size = 44 acres • Average pond acreage = 1 acre
Multinomial Logit Analysis • Dependent Variable (Aqua Info Source) • Y0 = Government Y1 = NGOs • Y2 = Other Farmers Y3 = University • Y4 = Other • Explanatory variables • Region; Ashanti=1, otherwise=0 • Number of years farming • Educational level; Read/write=1, otherwise=0 • Total pond acreage
Interpretation of Results • Ashanti Region farmers • Farmers have increasing probability of sourcing information from NGOs (7%), university (2%) and other sources (27%) • But a declining probability of obtaining aquaculture information from the government (-27%) and other farmers (-8%) • (Relative to Brong-Ahafo farmers)
Interpretation of Results • Number of years farming • With more experience in farming, there is increasing probability of farmers seeking aquaculture information from the government (8%) and other farmers (10%) • But a decreasing probability of sourcing information from NGOs (-5%), university (-1%) and other sources (-12%)
Interpretation of Results • Literacy • Literate farmers have an increasing probability of obtaining aquaculture information from the government (43%) • But a decreasing probability of sourcing information from all others • (Relative to Illiterates)
Interpretation of Results • Pond Acreage • With larger pond acreage, there is increasing probability of farmers seeking aquaculture information from the government (34%), NGOs (3%), other farmers (0.4%), and other sources (5%). • But a decreasing probability of sourcing information from university (-41%).
Implications of Results • Government support for aquaculture development is critical since most factors indicated a positive effect on probability of sourcing from government (literacy 48%; Acreage 34%). • Ashanti region farmers have a 27% probability of obtaining aquaculture information from other sources (Previous knowledge from schooling, self-education, etc). Reveals the impact of aquaculture curriculum in schools. • Except for being in Ashanti region (2%), literacy (-2%), experience (-1%) and farmers with larger acreages (-41%) have a decreasing probability of seeking aquaculture information from the university. Suggest that outreach activities of universities, e.g. KNUST should go beyond Ashanti region.
Implications of Results • The impact of factors indicated a low effect on probability of sourcing from NGOs (Ashanti 7%; Experience -5%; literacy -10%; Acreage 2%). NGOs usually provide one-time assistance during the project period and do not have field personnel to offer continuous assistance. • The impact of factors indicated a low effect on probability of seeking information from other farmers (Ashanti -8%; Experience -6%; literacy -6%; Acreage 0.4%).
Acknowledgement This study was sponsored by the Aquaculture & Fisheries Collaborative Research Support Program (AquaFish CRSP) funded under USAID Grant No. EPP-A-00-06-00012-00 and by Purdue University, USA and Kwame Nkrumah University of Science and Technology, Ghana.
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