Author
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Wiggans, George |
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Submitted to: Interbull Annual Meeting Proceedings
Publication Type: Proceedings Publication Acceptance Date: 10/22/2000 Publication Date: N/A Citation: N/A Interpretive Summary: Genetic evaluation systems provide the basis for genetic improvement programs. National evaluations are combined into an international evaluation for use worldwide. An evaluation model partitions phenotypic records into genetic and environmental effects. Some influences on lactation records may be removed by adjustments before analysis. Some data may be excluded from the analysis because they are affected by factors that are not adequately accounted for by either adjustment before analysis or by the model. National evaluation systems have been tailored to the dairy industries in particular countries. Differences include type of model used, adjustments before analysis, effects included in the model, assumed parameters, solution methods, and reported results. The design goal is to avoid biases by accounting for effects that would influence the estimates of genetic merit. With the increasing importance of international use of evaluations, emphasis is placed on harmonization. Knowledge of practices worldwide can lead to adoption of the best practice for a specific situation as systems are modified to accommodate changes in milk recording and dairy husbandry and advances in computing power and algorithms. Technical Abstract: Genetic evaluation systems provide the basis for genetic improvement programs. National evaluations are combined into an international evaluation for use worldwide. An evaluation model partitions phenotypic records into genetic and environmental effects. Some influences on lactation records may be removed by adjustments before analysis. Some data may be excluded from the analysis because they are affected by factors that are not adequately accounted for by either adjustment before analysis or by the model. National evaluation systems have been tailored to the dairy industries in particular countries. Differences include type of model used, adjustments before analysis, effects included in the model, assumed parameters, solution methods, and reported results. The design goal is to avoid biases by accounting for effects that would influence the estimates of genetic merit. With the increasing importance of international use of evaluations, emphasis is placed on harmonization. Knowledge of practices worldwide can lead to adoption of the best practice for a specific situation as systems are modified to accommodate changes in milk recording and dairy husbandry and advances in computing power and algorithms. |
