IDENTIFICATION OF FACTORS CAUSING HETEROGENEOUS WITHIN-HERD VARIANCE-COMPONENTS USING A STRUCTURAL MODEL FOR VARIANCES

Many applications of mixed linear statistical models for genetic evalu ation of dairy cattle assume that genetic and residual components of v ariance are each constant across environments. However, this assumptio n is violated for production and conformation traits, which can reduce accuracy of selection and cause biases in the proportions of breeding animals chosen from each environment. Best linear unbiased prediction can accommodate heterogeneous variances if the appropriate variance c omponents are known. Variance components may need to be estimated with in individual herds using Bayesian or empirical Bayes methods, but suc h approaches may not yet be computationally feasible on a national bas is. For this study, a structural log-linear model for sire and residua l variances was used to identify various management factors associated with differences in within-herd variance components. Increases of her d size and within-herd mean were associated with significant increases of within-herd residual variance for milk and fat yields, but residua l variance of milk yield decreased slightly as the proportion of regis tered animals in the herd increased. Type of milking system, silage st orage system, DHI testing program, use or nonuse of a TMR, and use or nonuse of automatic milking machine removal devices also significantly affected residual variances. However, differences in sire variances a cross levels of management factors were not significant.