This paper presents an approach to the design of breeding programs in which no design is purposefully aimed at. The design emerges as a consequence of a policy implemented at the level of the breeding pair or mating group. The method proposed accounts for both genetic and cost factors in a single index, and uses an algorithm which optimises the mating structure. The method is discussed with particular reference to crossbreeding systems. Stochastic simulation is used to demonstrate the emergence of various designs according to prevailing genetic and cost parameters.

Brian P Kinghorn

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume XII. Biotechnology, selection experiments, parameter estimation, design of breeding systems, management of genetic resources., , 233–244, 1986
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