Beef sires are sometimes represented in more than one genetic evaluation and may have highly accurate primary genetic evaluations based on progeny data not included in a secondary evaluation. It is dissatisfying to breeders that sires' rankings differ markedly, especially when the secondary evaluations are based on relatively limited data. Bayesian principles provide a framework for incorporating external information into a genetic evaluation. Simplifying assumptions resulted in a practicable procedure where external information is assumed to be contained in the animals' external EPD and accuracies. Parameters were included to account for unknown base differences. The procedure is illustrated with a numerical example and Monte Carlo simulation. The procedure increased the rank correlation between EPD and breeding values and sires with external information are more similar to their primary EPD.

R. L Quaas, Z. Zhang

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume , , 24.12, 2006
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