IN-POND RACEWAY CATFISH PRODUCTION AND ECONOMIC ANALYSIS

Terry R. Hanson*, Lisa B. Bott, Luke A. Roy and Jesse C. Chappell
 
Auburn University School of Fisheries, Aquaculture and Aquatic Sciences
203 Swingle Hall, Auburn University, Auburn, AL 36849 hansontr@auburn.edu  

A Southern Regional Aquaculture Center (SRAC) funded project (Performance Evaluation of Intensive, Pond-Based Culture systems for Catfish Production) allowed us to monitor the production performance of hybrid catfish grown in in-pond raceways; estimate the cost of production (investment + fixed + variable costs); and identify the relative strengths, weaknesses, and trade-offs of these alternative production systems. An in-pond raceway system (IPRS) in west Alabama housed in a six acre pond was utilized to grow two crops of fish with very different outcomes.  Each raceway was 35' x 16' x 4' with a fish culture area of 1,620 ft3 peer cell.  The production goal in cycle one was to sell fish to a local processor as soon as harvest size was reached at spot market prices ($0.85 to $1.15/lb) and cycle two had the goal of selling to a live hauler on a weekly basis at a set higher price ($1.30/lb).  The production characteristics between the two systems are presented in the table below.  Cycle one produced 55,422 lb from 4 raceway cells over an average of 11 months and resulted in a net return of $10,122 over all expenses or a profit of $0.18/lb sold.  Cycle two produced 43,607 lb from 5 raceway cells over an average of 17 months and resulted in a negative net return of $10,023 or a loss of $0.23/lb.  It appears that the reasons for this difference could be attributed to the longer period of time fish were in the raceways as well as frequent partial harvesting in cycle two which resulted in scrapes, punctures and stress to fish. Disease mortalities occurred in much greater quantities than in cycle one, which began with large stockers which were completely harvested at one time from each raceway cell. IPRS have promise and lessons learned from these economic analyses are providing needed information on how best to utilize and optimize these systems.