Genetic Evaluation Systems

Accurate methods for evaluating genetic merit of bulls and cows for economically important traits are needed to identify those animals that are best suited to be parents of the next generation. The degree of system sophistication needed depends partially on effectiveness of the sampling program in randomizing bull daughters across herds that represent various management levels. If randomization is

Fig. 1 Numbers of U.S. cows and mean milk yield by year. (Source: Animal Improvement Programs Laboratory, Agricul tural Research Service, U.S. Department of Agriculture, Belts ville, MD; http://aipl.arsusda.gov [accessed Sept 2003].)

Fig. 2 Mean milk yield, genetic merit (breeding value), and sire genetic merit of U.S. Holstein cows with national genetic evaluations by birth year. (Source: Animal Improvement Programs Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD; http://aipl.arsusda. gov [accessed Sept 2003].)

Fig. 1 Numbers of U.S. cows and mean milk yield by year. (Source: Animal Improvement Programs Laboratory, Agricul tural Research Service, U.S. Department of Agriculture, Belts ville, MD; http://aipl.arsusda.gov [accessed Sept 2003].)

Fig. 2 Mean milk yield, genetic merit (breeding value), and sire genetic merit of U.S. Holstein cows with national genetic evaluations by birth year. (Source: Animal Improvement Programs Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD; http://aipl.arsusda. gov [accessed Sept 2003].)

equitable for all bulls, less sophisticated procedures are needed. In the United States, methodology for national evaluations has progressed from daughter-dam comparison (1936) to herdmate comparison (1960) to modified contemporary comparison (1974) and finally, to an animal model (1989).[1] The most recent development in genetic evaluation systems is the use of test-day models, which have been adopted by several countries. Because test-day models account better for environmental effects and variations in testing schemes, they can provide more accurate estimates of genetic merit than do lactation models; however, test-day models are statistically more difficult and computationally more intensive.1-3-1 Once evaluations are released to the dairy industry, dairy farmers have an opportunity to select among the best bulls for their needs and to purchase semen marketed by AI organizations. Mating decisions for specific animals can be based on estimated genetic merit for individual traits or selection indexes that combine traits of economic interest.

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