Adjusting for heterogeneity of variance for carcass traits affects single and multiple trait selections in genetic evaluation of Japanese Black cattle

Hirofumi Nakaoka, Claude Gaillard, Takayuki Ibi, Yotaro Sasae, Yoshiyuki Sasaki

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Heterogeneity of variance among subclasses of an effect is a potential source of bias in genetic evaluation. Degrees of the heterogeneity of variance among farm-market-year-sex (FMYS) subclasses for carcass weight, beef marbling standard number, rib-eye area, rib thickness and subcutaneous fat thickness were investigated in Japanese Black cattle. Consequences of adjusting for the heterogeneity on the predicted breeding values (PBVs) or on the genetic indexes derived from the PBVs of the five carcass traits were assessed. A total of 57 461 records were collected between 1997 and 2002 from steers and heifers fattened at farms across Japan. These records were grouped into 1591 FMYS subclasses. Bartlett's test showed that the degree of the heterogeneity of variance among the FMYS subclasses was sizeable in all traits (P < 0.0001). By applying a two-step adjustment procedure it was possible to reduce the standard deviation, the coefficient of variation and the Gini coefficient of the phenotypic variances by 67.5% to 75.0% in the different traits. The applied adjustment caused a substantial re-ranking of elite dams in the PBV for each trait as well as in the genetic index. This study provided evidence that the applied adjustment reduces the bias in the PBVs due to heterogeneous variances and increases the accuracy of bull-dam selection.

Original languageEnglish
Pages (from-to)645-654
Number of pages10
JournalAnimal Science Journal
Volume79
Issue number6
DOIs
Publication statusPublished - Dec 2008
Externally publishedYes

Keywords

  • Beef cattle
  • Genetic evaluation
  • Heterogeneity of variance
  • Model selection
  • Multiple trait selection

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)

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