A deterministic model for the optimization of dairy cattle breeding based on BLUP breeding value estimates

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Abstract
A deterministic model was developed to examine the optimization of open nucleus breeding schemes in order to maximize the rate of genetic response in dairy cattle. By changing the parameters, the model was able to simulate both a closed nucleus and a progeny testing scheme. The model implicitly optimized the generation interval and the selection across tiers by means of truncation across age classes and tiers respectively. The effects of size of the progeny test group and the nucleus size were assessed by comparing alternative plans. It is possible to optimize a breeding plan given the reproduction rates of the animals, the availability of different sources of information, the age distribution of the animals (survival rates) and the phenotypic and genetic parameters of the trait.The steady state selection response was assessed by calculating the genetic progress year after year until it stabilized. The genetic gain was corrected for the effects of reduced variances due to previous selections and increased variances due to genetic differences between parental age classes.In an example, the model was used to predict the improvement in milk yield in a closed artificial insemination breeding scheme. The genetic gain of a conventional progeny testing scheme was about one-third lower than the genetic gain of the optimized breeding plan. The variance reduction due to selection decreased the steady state genetic gain by a factor 0·3

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