Submitted to: Journal of Dairy Science
Publication Type: Peer reviewed journal
Publication Acceptance Date: 5/5/2005
Publication Date: 8/1/2005
Citation: Gengler, N., Wiggans, G.R., Gillon, A. 2005. Adjustment for heterogeneous covariance due to herd milk yield by transformation of test-day random regressions. Journal of Dairy Science. 88(8):2981-2990. Interpretive Summary: Heterogeneity of components of variation is a major source of bias in genetic evaluations. An innovative approach based on adjustment of regressions of each test-day yield during lactation was developed to allow extreme flexibility during the modeling process. Preliminary analysis indicated that genetic and nongenetic (co)variance structures differed by herd milk yield. The method developed suggests a number of innovative solutions to issues related to heterogeneous (co)variance. The method allows herd-specific lactation curves based on herd yield level. Multibreed evaluation with accommodation for breed-specific (co)variances (e.g., heritabilities) and inclusion of crossbreds through interpolation based on proportion of genes from ancestor breeds also is possible with this method. Another possibility is to extend the method to produce different bull rankings according to the source of (co)variance differences.
Technical Abstract: A method of accounting for differences in (co)variance components of test-day milk records was developed based on transformation of regressors for random regression effects. Preliminary analysis indicated that genetic and nongenetic (co)variance structures differed by herd milk yield. Differences were found for phenotypic (co)variances and also for heritability, permanent environmental, and herd-time (co)variances. Heritabilities for test-day milk yield were higher (maximum of around 25%) for high-yield herds and lower (maximum of 15%) for low-yield herds. Permanent environmental (co)variances had the opposite trend and averaged 10% lower in high-yield herds. Relative herd-time (co)variances were around 10% at start of lactation and then began to decrease regardless of herd yield; high-yield herds increased in midlactation followed by another decrease, and medium-yield herds increased at end of lactation. Regressors for random regression effects were transformed to adjust for heterogeneity of test-day yield (co)variances. Some animal reranking occurred because of this transformation of genetic and permanent environmental effects. When genetic correlations between environments were allowed to differ from 1, some additional animal reranking occurred. Correlations of (co)variances for genetic and permanent-environmental regression within herd, test-day, and milking frequency class with class mean milk yield were reduced with adjustment for heterogeneous (co)variance. The method suggests a number of innovative solutions to issues related to heterogeneous (co)variance structures, such as adjusted estimates in multibreed evaluation.