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Cost-benefit analysis of aquaculture breeding programs
Kasper Janssen1,2, Helmut Saatkamp3,4, Hans Komen3,4
1Animal Breeding and Genomics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands. kasper.janssen@wur.nl.
Optimizing aquaculture breeding programs by evaluating different designs, including those with and without multiplier tiers, reveals that programs without multiplier tiers are most profitable long-term. The number of selection candidates should align with the time horizon and production output for maximum profitability.
Area of Science:
- Aquaculture
- Animal Breeding
- Quantitative Genetics
Background:
- Selective breeding programs are crucial for aquaculture profitability, with design choices significantly impacting outcomes.
- Cost-benefit analysis is key to evaluating the economic viability of different breeding program structures.
Purpose of the Study:
- To evaluate various breeding program designs for aquaculture, considering options with and without multiplier tiers.
- To optimize the number of selection candidates within these breeding programs to maximize profitability.
Main Methods:
- Compared a baseline gilthead seabream breeding program with alternatives: annual multiplier tier replacement, annual replacement with multiplier priority, and no multiplier tier.
- Utilized cost-benefit analyses to assess program profitability over time.
- Determined relationships between profitability, number of selection candidates, time horizon, and production output.
Main Results:
- The baseline program was profitable within 5 years. Alternative programs showed higher profitability up to year 17.
- The program without a multiplier tier was the most profitable up to year 22.
- Optimal number of selection candidates positively correlated with time horizon and production output.
Conclusions:
- Breeding programs without multiplier tiers offer superior profitability, especially over longer time horizons.
- Prioritizing multiplier tier improvement is beneficial for short time horizons, while nucleus improvement is better for long horizons.
- Adjusting the number of selection candidates based on time horizon and production output is essential; exceeding the optimum has less negative impact than falling short.
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