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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Genetics and Animal Breeding » Research » Publications at this Location » Publication #174842
Title: GENETIC EVALUATION OF DAIRY CATTLE WITH TEST DAY MODELS WITH AUTOREGRESSIVE COVARIANCE STRUCTURES

Author
item SAWALHA, RAMI - UNIV. OF NEBR.-LINCOLN
item KEOWN, JEFFREY - UNIV. OF NEBR.-LINCOLN
item KACHMAN, STEPHEN - UNIV. OF NEBR.-LINCOLN
item Van Vleck, Lloyd

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/6/2005
Publication Date: 9/1/2005
Citation: Sawalha, R.M., Keown, J.F., Kachman, S.D., Van Vleck, L.D. 2005. Genetic evaluation of dairy cattle with test day models with autoregressive covariance structures. Journal of Dairy Science 88:3346-3353.

Interpretive Summary: The ranks of the top 100 sires and top 100 cows based on predicted breeding value for lactation yields of Holstein cows were similar with different test-day models. The correlations between predicted breeding values with test-day models and a traditional 305-d lactation model were generally smaller than the larger correlations among predicted breeding values with test-day models. Test-day and 305-d models appear to result in different genetic evaluations and rankings of both sires and cows. The use of test-day models for genetic evaluation of dairy sires and cows may result in more accurate predictions of breeding values compared with traditional 305-d lactation models. These results were based on analyses of first lactation yields (milk, fat, protein) of 12,071 Holstein cows with 106,472 test-day records.

Technical Abstract: This study compared genetic evaluations from three test-day (TD) models with different assumptions about the environmental covariance structure for test-day records and with genetic evaluations from 305-d lactation records for dairy cows. Estimates of genetic values of 12,071 first lactation Holstein cows were obtained with three test-day models using 106,472 TD records. Model I (CS Model) was a simple test-day repeatability animal model with compound symmetry covariance structure for test-day environmental effects. Model II (AR(pe) Model) and Model III (AR(e) Model) also used test-day records but with a first order autoregressive covariance structure among either permanent (AR(pe) Model) or residual (AR(e) Model) test-day environmental effects. Estimates of genetic values with test-day models were also compared with those from a model using 305-d lactation records (Model IV). Cows were genetically evaluated for milk, fat and protein yields and somatic cell score (SCS). Predicted breeding values with the three test-day models were highly correlated (0.98 to 1.00). Predicted breeding values with 305-d lactation records were moderately correlated with those with test-day models (0.71 to 0.87 for sires and 0.80 to 0.87 for cows). The CS and AR(e) Models resulted in the largest estimates of correlations between lactation records of cows and averages of predicted breeding values of their parents. More genetic improvement might be possible by using test-day models to select for animals for higher yield and lower SCS than by using models with 305-d lactation records.