Multivariate approach to endogamy and phenotypic value using different crossbreeding strategies

Abstract

Simulation has contributed to the advance of genetic improvement. This study aimed at evaluating selective mating by using the distribution of extremes to maximize the phenotypic increment and slow down the endogamy increment, under a multivariate approach. Simulated data were used to assess mating strategies in different family sizes, over 20 generations. The cluster analysis made possible to distinguish the selective mating from other strategies for each family size. By combining mating strategy and family size, the cluster analysis pointed out the superiority of the selective mating to optimize the phenotypic value and slow down the endogamy increment. The cluster methods showed equivalence in the formation of groups with homogeneous strategies for the estimates of phenotypic mean values and mean endogamy. The multivariate analysis corroborated superior phenotypic increments to the selective mating, as well as lower endogamy levels, over the generations.