論文

査読有り
2008年12月

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

ANIMAL SCIENCE JOURNAL
  • Hirofumi Nakaoka
  • ,
  • Claude Gaillard
  • ,
  • Takayuki Ibi
  • ,
  • Yotaro Sasae
  • ,
  • Yoshiyuki Sasaki

79
6
開始ページ
645
終了ページ
654
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1111/j.1740-0929.2008.00576.x
出版者・発行元
WILEY

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.

リンク情報
DOI
https://doi.org/10.1111/j.1740-0929.2008.00576.x
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000260544000001&DestApp=WOS_CPL
ID情報
  • DOI : 10.1111/j.1740-0929.2008.00576.x
  • ISSN : 1344-3941
  • eISSN : 1740-0929
  • Web of Science ID : WOS:000260544000001

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