Mate selection in aquaculture breeding using differential evolution algorithm

Abstract

An algorithm to perform mate selection in aquaculture breeding using a computational optimization procedure called “differential evolution” (DE) was applied under optimum contribution selection and mate selection scenarios, to assess its efficiency in maximizing the genetic merit while controlling inbreeding. Real aquaculture data sets with 8,782 Nile tilapias from five generations and 79,144 coho salmon from eight generations were used to optimize objective functions accounting for coancestry of parents and expected genetic merit and inbreeding of the future progeny. The mate selection results were compared with those from the realized scenario (real mates), truncation selection and optimum contribution selection method. Mate selection allowed reducing inbreeding up to 73% for Nile tilapia, compared with truncation selection, and up to 20% for coho salmon, compared with realized scenario. There was evidence that mate selection outperformed optimum contribution selection followed by minimum inbreeding mating in controlling inbreeding under the same expected genetic gain. The developed algorithm was computationally efficient in maximizing the objective functions and flexible for practical application in aquaculture breeding.