BALANCING GAIN AND RELATEDNESS IN SELECTION

A population merit criterion, B-omega, for a set of genotypes, omega, is formulated as B-omega = (g) over bar(omega) - c Theta(omega) where, c is a weighting constant, (g) over bar(omega) is the average of thei r breeding values, and Theta(omega) is the average coancestry of the c onsidered genotypes, which is a measure of their relatedness. The bree ding objective studied here is selecting the set omega that maximises B-omega. An iterative search algorithm is proposed for finding this ma ximum under a given breeding-population size. This algorithm was appli ed to an example using simulation techniques. Results were presented a s graphs where the gain was plotted against the status effective numbe r, which was used to quantify the degree of relatedness as an inverse function of average coancestry. For all except extreme c values the al gorithm gave markedly better combinations of gain and average coancest ry when compared with a conventional method to control relatedness by restricting contributions from individual parents.