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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 #174755

Title: EVALUATION OF AUTOREGRESSIVE COVARIANCE STRUCTURES FOR TEST DAY RECORDS OF HOLSTEIN COWS; ESTIMATES OF PARAMETERS

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: 3/31/2005
Publication Date: 3/31/2005
Citation: Sawalha, R.M., Keown, J.F., Kachman, S.D., Van Vleck, L.D. 2005. Evaluation of autoregressive covariance structures for test day records of holstein cows; estimates of parameters. Journal of Dairy Science 88:2632-2642.

Interpretive Summary: Test-day records of lactation yields at approximately 30-d intervals provide basic information for genetic evaluation of dairy sires and cows for milk, fat, and protein yields. The traditional method has been to sum the test-day records to obtain a 305-d lactation yield. The test-day records can be used directly with more sophisticated statistical procedures. Proper use of test-day records requires knowledge of correlations among the test-day records. One method is to treat each test-day as a separate trait which would require a 10 by 10 correlation matrix which would be termed the "unstructured" correlation structure. The other extreme is to consider the correlation to be the same for each pair of test-day records (termed the "compound symmetry" correlation structure). An intermediate approach tested here is to consider what is called an "auto-regressive" correlation structure by which the correlation changes by the power of the interval between the test-days with rho the correlation between adjacent test-day records and rho-squared for test-days two intervals apart, etc. Thus only one parameter (rho) is needed to characterize the correlation among test-day records. The "auto-regressive" approach has many computational advantages over the "unstructured" approach and some advantages over the "compound symmetry" approach. This study of 106,472 first lactation test-day records of milk, fat, and protein yield of 12,071 Holstein cows compared these three approaches. The conclusion was that the "autoregressive" approach may be a reasonable approximation for modeling environmental effects among test-day yields of Holstein cows.

Technical Abstract: The objective of this study was to compare test day (TD) models with autoregressive covariance structures for the estimation of genetic and environmental components of variance for milk, fat and protein yields and somatic cell score (SCS) in Holstein cows. Four models were compared: Model I (CS Model) was a simple test day repeatability animal model with compound symmetry covariance structure for environmental effects, Model II (AR(pe) Model) and Model III (AR(e) Model) had a first order autoregressive covariance structures for test day permanent or residual environmental effects, respectively, and Model IV (305-d Model) was a simple animal model using 305-d records. Data were 106,472 first lactation test day records of 12,071 Holstein cows calving from 1996 through 2001. Likelihood ratio tests indicated that AR(pe) and AR(e) Models fit the data significantly better than the CS Model. The AR(e) Model resulted in slightly smaller estimates of genetic variance and heritability than the CS Model. Estimates of residual variance were always smaller with the CS Model than with the AR(e) Model with the autoregressive covariance structure among TD residual effects. Estimates of heritability with different TD models were in the range of 0.06 to 0.11. The 305-d Model resulted in estimates of heritability in the range of 0.11 to 0.36. The autoregressive covariance structure among TD residual effects may help to prevent overestimation of heritability for milk, fat and protein yields and SCS.