The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The difference in variance component estimates between the two. ![]() The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. hierarchical generalized linear models (DHGLM) to derive an estimation algorithm. Estimation using ASReml took less than 7 d on a Linux server. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. ![]() These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. ![]() Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance.
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