Crews D H, Pollak E J, Quaas R L
Agriculture and Agri-Food Canada Research Centre, Lethbridge, Alberta T1J 4B1, Canada.
J Anim Sci. 2004 Mar;82(3):661-7. doi: 10.2527/2004.823661x.
This study was conducted to compare carcass EPD predicted using yearling live animal data and/or progeny carcass data, and to quantify the association between the carcass phenotype of progeny and the sire EPD. The live data model (L) included scan weight, ultrasound fat thickness, longissimus muscle area, and percentage of intramuscular fat from yearling (369 d of age) Simmental bulls and heifers. The carcass data model (C) included hot carcass weight, fat thickness, longissimus muscle area, and marbling score from Simmental-sired steers and cull heifers (453 d of age). The combined data model (F) included live animal and carcass data as separate but correlated traits. All data and pedigree information on 39,566 animals were obtained from the American Simmental Association, and all EPD were predicted using animal model procedures. The genetic model included fixed effects of contemporary group and a linear covariate for age at measurement, and a random animal genetic effect. The EPD from L had smaller variance and range than those from either C or F. Further, EPD from F had highest average accuracy. Correlations indicated that evaluations from C and F were most similar, and L would significantly (P < 0.05) re-rank sires compared with models including carcass data. Progeny (n = 824) with carcass data collected subsequent to evaluation were used to quantify the association between progeny phenotype and sire EPD using a model including contemporary group, and linear regressions for age at slaughter and the appropriate sire EPD. The regression coefficient was generally improved for sire EPD from L when genetic regression was used to scale EPD to the appropriate carcass trait basis. The EPD from C and F had similar linear associations with progeny phenotype, although EPD from F may be considered optimal because of increased accuracy. These data suggest that carcass EPD based on a combination of live and carcass data predict differences in progeny phenotype at or near theoretical expectation.
本研究旨在比较使用周岁活体动物数据和/或后代胴体数据预测的胴体预期子代差异（EPD），并量化后代胴体表型与父系EPD之间的关联。活体数据模型（L）包括周岁（369日龄）西门塔尔公牛和母牛的扫描体重、超声脂肪厚度、背最长肌面积以及肌内脂肪百分比。胴体数据模型（C）包括西门塔尔牛所生阉牛和淘汰母牛（453日龄）的热胴体重、脂肪厚度、背最长肌面积和大理石花纹评分。综合数据模型（F）将活体动物数据和胴体数据作为单独但相关的性状。来自美国西门塔尔协会的39566头动物的所有数据和系谱信息均已获取，所有EPD均采用动物模型程序进行预测。遗传模型包括当代组的固定效应、测量时年龄的线性协变量以及随机动物遗传效应。L模型的EPD比C或F模型的方差和范围更小。此外，F模型的EPD平均准确性最高。相关性表明，C和F模型的评估结果最为相似，与包含胴体数据的模型相比，L模型会使公牛排名显著重新排序（P < 0.05）。在评估后收集了胴体数据的后代（n = 824）用于通过包含当代组的模型以及屠宰时年龄和相应父系EPD的线性回归来量化后代表型与父系EPD之间的关联。当使用遗传回归将EPD按适当的胴体性状基础进行缩放时，L模型中父系EPD的回归系数通常会得到改善。C和F模型的EPD与后代表型具有相似的线性关联，尽管由于准确性提高，F模型的EPD可能被认为是最优的。这些数据表明，基于活体和胴体数据组合的胴体EPD能够预测接近理论预期的后代表型差异。
