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J. Dairy Sci. 88:3346-3353
© American Dairy Science Association, 2005.

Genetic Evaluation of Dairy Cattle with Test-Day Models with Autoregressive Covariance Structures and with a 305-d Model

R. M. Sawalha1, J. F. Keown1, S. D. Kachman2 and L. D. Van Vleck1,3

1 Department of Animal Science, and
2 Department of Statistics, University of Nebraska, Lincoln 68583-0908
3 Roman L. Hruska U.S. Meat Animal Research Center, Agricultural Research Service, USDA, Lincoln, NE 68583-0908

Corresponding author: Rami M. Sawalha; e-mail: rami.sawalha{at}sac.ac.uk.

This study compared genetic evaluations from 3 test-day (TD) models with different assumptions about the environmental covariance structure for TD records and genetic evaluations from 305-d lactation records for dairy cows. Estimates of genetic values of 12,071 first-lactation Holstein cows were obtained with the 3 TD models using 106,472 TD records. The compound symmetry (CS) model was a simple test-day repeatability animal model with compound symmetry covariance structure for TD environmental effects. The ARs and ARe models also used TD records but with a first-order autoregressive covariance structure among short-term environmental effects or residuals, respectively. Estimates of genetic values with the TD models were also compared with those from a model using 305-d lactation records. Animals were genetically evaluated for milk, fat, and protein yields, and somatic cell score (SCS). The largest average estimates of accuracy of predicted breeding values were obtained with the ARs model and the smallest were with the 305-d model. The 305-d model resulted in smaller estimates of correlations between average predicted breeding values of the parents and lactation records of their daughters for milk and protein yields and SCS than did the CS and ARe models. Predicted breeding values with the 3 TD models were highly correlated (0.98 to 1.00). Predicted breeding values with 305-d lactation records were moderately correlated with those with TD models (0.71 to 0.87 for sires and 0.80 to 0.87 for cows). More genetic improvement can be achieved by using TD models to select for animals for higher milk, fat, and protein yields, and lower SCS than by using models with 305-d lactation records.

Key Words: autoregressive covariance • genetic evaluation • milk yield • test day

Abbreviation key: AR(1) = first-order autoregressive, CS = compound symmetry, PBV = predicted breeding values, TD = test day.




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J Dairy Sci, September 1, 2006; 89(9): 3636 - 3644.
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