College of Agriculture and Veterinary Science (FCAV), São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil.
Embrapa Southeast Livestock (EMBRAPA), São Carlos, São Paulo, Brazil.
Trop Anim Health Prod. 2022 Sep 14;54(5):295. doi: 10.1007/s11250-022-03285-6.
The aim of the present study was to use different models that include body composition phenotypes for the evaluation of residual feed intake (RFI) in Nellore bulls of different ages. Phenotypic and genotypic data of bulls that had participated in feed efficiency tests of a commercial (COM) and an experimental (EXP) herd between 2007 and 2019 were used. The mean entry age in the two herds was 645 and 279 days, respectively. The phenotypes were evaluated: rib eye area (REA), backfat thickness (BFT), residual feed intake (RFI), RFI adjusted for REA (RFI), RFI adjusted for BFT (RFI), and RFI adjusted for REA and BFT (RFI). The (co)variance components and prediction of genomic estimated breeding values (GEBV) were obtained by REML using ssGBLUP in single and two-trait analyses. Spearman's correlations were calculated based on the GEBV for RFI. The RFI phenotypes exhibited moderate heritability estimates in both herds (0.17 ± 0.03 to 0.27 ± 0.04). The genetic correlation between phenotypes was positive and high (0.99) in the two herds, a fact that permitted the creation of a single database (SDB). The heritability estimates of the SDB were also of moderate magnitude for the different definitions of RFI (0.19 ± 0.04 to 0.21 ± 0.04). The genetic correlations were positive and high between RFI traits 0.97 ± 0.01 to 0.99 ± 0.01), and positive and low/moderate between REA and BFT (0.01 ± 0.10 to 0.31 ± 0.12). The selection of animals based on the GEBV for RFI did not alter the ranking of individuals selected for RFI, RFI, and RFI. The results of the present study suggest that records of Nellore bulls of different ages and with different body compositions can be combined in a SDB for RFI calculation. Therefore, young animals can be evaluated in feed efficiency tests in order to reduce costs and the generation interval and possibly to obtain a higher response to selection.
本研究的目的是使用包含身体组成表型的不同模型来评估不同年龄的内罗尔公牛的剩余采食量(RFI)。使用了 2007 年至 2019 年期间参加商业(COM)和实验(EXP)牛群饲料效率测试的公牛的表型和基因型数据。两个牛群的平均进入年龄分别为 645 天和 279 天。评估了表型:眼肌面积(REA)、背膘厚(BFT)、剩余采食量(RFI)、REA 调整的 RFI(RFI)、BFT 调整的 RFI(RFI)和 REA 和 BFT 调整的 RFI(RFI)。使用 REML 通过 ssGBLUP 在单个性状和双性状分析中获得了(协)方差分量和基因组估计育种值(GEBV)的预测。根据 RFI 的 GEBV 计算了 Spearman 相关系数。两个牛群的 RFI 表型均表现出中等的遗传力估计值(0.17±0.03 至 0.27±0.04)。两个牛群的表型之间的遗传相关性为正且高度相关(0.99),这使得可以创建一个单一的数据库(SDB)。对于不同的 RFI 定义,SDB 的遗传力估计值也为中等(0.19±0.04 至 0.21±0.04)。RFI 性状之间的遗传相关性为正且高度相关(0.97±0.01 至 0.99±0.01),而 REA 和 BFT 之间的遗传相关性为正且低度/中度相关(0.01±0.10 至 0.31±0.12)。基于 RFI 的 GEBV 选择动物不会改变个体选择 RFI、RFI 和 RFI 的排名。本研究的结果表明,可以将不同年龄和不同身体组成的内罗尔公牛的记录组合在一个 SDB 中用于 RFI 计算。因此,可以在饲料效率测试中评估年轻动物,以降低成本和世代间隔,并可能获得更高的选择响应。