The Netherlands.- Cost-benefit analysis in a recent study revealed that a breeding program for gilthead seabream can reach a positive net present value five years after its start. After ten years, the net present value of the studied breeding program was 2.9 million euro. A breeding program can thus be a highly profitable investment for aquaculture companies.
A breeding program improves the genetic level of the animals used in production and thereby increases farm profit. Benefits of a breeding program depend on the rate of increase of the genetic level of animals used in production and production output of the company. In many breeding programs, genetic gain is first obtained in a nucleus and then via a multiplier tier disseminated to production. The ‘genetic lag’ between genetic levels in the nucleus and in production delays the benefits from genetic improvement.
How to improve the profitability of your breeding program
The current study compared multiple alternative breeding program designs to a baseline breeding program that was based on the breeding program of Andromeda SA, one of the major seabream farming companies in the Mediterranean. A comparison between breeding program designs demonstrated that the profitability of a breeding program can be improved by reducing the genetic lag. For example, the profitability increases substantially when production is supplied directly from the nucleus instead of from the multiplier tier. Thus a multiplier tier delays the benefits of genetic improvement.
Analysis of the relation between the number of selection candidates and profitability revealed that an optimum number of selection candidates exists. The optimum number of selection candidates increases with the length of the time horizon and production output. Using too many selection candidates relative to the optimum leads to less reduction in profitability than using too few selection candidates.
Reference (open):
Kasper Janssen, Helmut Saatkamp and Hans Komen. Cost-benefit analysis of aquaculture breeding programs. Genetics Selection Evolution 2018, 50:2
https://doi.org/10.1186/s12711-018-0372-3
https://gsejournal.biomedcentral.com/articles/10.1186/s12711-018-0372-3
Source: Wageningen University and Research
