Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.
Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Autoregressive repeatability animal models for the analysis of first lactation test day records of Holstein cows
Abstract
Animal models with first order autoregressive (AR(1)) covariance structures for permanent environmental effects (ARpe), residual effects (AR e) or genetic and residual effects (ARae) of test day records (TD) were examined. The models with AR(1) covariance structures were compared together and with a simple test day repeatability model with compound symmetry (CS) covariance structure for TD environmental effects and a 305-day lactation model. Data consisted of 106,472 records (TD data) of 12,071 first lactation Holstein cows (305-day data). Estimates of genetic and environmental components of variance and autocorrelation coefficients were obtained for milk, fat, and protein yields and somatic cell scores (SCS) using ASReml. Likelihood ratio tests indicated that models with the AR(1) covariance structures were significantly more appropriate for the TD data for all traits than the CS model. Estimates of heritability were slightly less with the models with the ARe or ARae covariance structures (0.09) than with the CS model (0.10 to 0.11) for yield traits. All TD models resulted in similar estimates of heritability for SCS (0.06). Estimates of residual variance may have been underestimated with the CS model compared with TD models with the ARe or the ARae covariance structures. Estimates of heritability with the 305-day model for all traits were in the range of 0.11 to 0.36. The predicted breeding values (PBV) with different TD models were highly correlated (0.98 to 1.00). The PBV with the ARae Model were not the same at different test days and tended to decrease with advancement of the lactation for SCS. The smallest estimates of accuracy of PBV were at the beginning and at the end of lactation. The AR(1) covariance structure for TD residual or for both genetic and residual effects may help to prevent overestimation of heritability and repeatability for milk, fat and protein yields and SCS compared with simple repeatability model with the CS covariance structure.
Subject Area
Animal sciences|Genetics
Recommended Citation
Sawalha, Rami M, "Autoregressive repeatability animal models for the analysis of first lactation test day records of Holstein cows" (2004). ETD collection for University of Nebraska-Lincoln. AAI3159560.
https://digitalcommons.unl.edu/dissertations/AAI3159560