Evaluation of Autoregressive Covariance Structures for Test-Day Records of Holstein Cows: Estimates of Parameters

Authors

R. M. Sawalha, University of Nebraska-Lincoln
Jeffrey F. Keown, University of Nebraska-LincolnFollow
Stephen D. Kachman, University of Nebraska-LincolnFollow
L. Dale Van Vleck, University of Nebraska-LincolnFollow

ORCID IDs

Stephen D. Kachman

Document Type

Article

Date of this Version

3-31-2005

Comments

Published in Journal of Dairy Science Vol. 88, No. 7, 2005.

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 TD repeatability animal model with compound symmetry covariance structure for environmental effects, model II (AR_pe model) and model III (AR_e model) had first-order autoregressive covariance structures for TD 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 TD 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 did 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 bias in heritability estimates for milk, fat and protein yields, and SCS.