Scotland UKWith large number of animals per generation, and high genetic diversity, selective breeding programmes can deliver large returns on investment , even for modestly sized aquaculture producers. Genetic gain can be influenced by many factors including : candidate numbers; evaluation group sizes; selection intensity and trait weighting in the selection index. In addition , financial returns from the breeding programme will be influenced by the economic values of the traits being selected. Recent a dvances in genetic technology (particularly the cost of genotyping) have offered additional opportunities for investment in selective breeding with genomic selection becoming standard in many sectors within aquacultire.
With realised genetic gains taking up to 4 years to observe and only being available following a significant financial investment, accurate decision making tools are necessary for the design of an optimised breeding programme.
By combining high resolution genetic simulation software, with realistic aquaculture breeding programme constraints, we have been able to simulate multiple generations of selective breeding under realistic genetic parameters , allowing the effect of multiple selection strategies to be evaluated prior to committing time and resources.
By combing commercial economic data (e.g. production costs and market value) with realistic growth models, the outputs of genetic simulations can be expressed in financial units, allowing informed decisions aimed at maximising economic return.