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巴西荷斯坦牛纵向繁殖性状遗传评估的自回归模型。

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.

机构信息

Department of Animal Science, Federal University of Viçosa, Viçosa, Brazil.

Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão, Portugal.

出版信息

Reprod Domest Anim. 2021 Mar;56(3):391-399. doi: 10.1111/rda.13874. Epub 2020 Dec 22.

Abstract

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.

摘要

繁殖效率是奶牛养殖盈利能力的主要决定因素。因此,繁殖性状已被广泛应用于当前奶牛育种计划中的选择目标。本研究旨在评估巴西荷斯坦奶牛的天数开放(DO)、产犊间隔(CI)和女儿妊娠率(DPR)的模型构建策略。使用 127,280、173,092 和 127,280 个表型记录,分别通过自回归(AR)模型和经典重复力(REP)模型分析这些繁殖性状。这里使用了 1,469 个荷斯坦牛群的前三个产犊顺序的奶牛。对于所有评估的性状,AR 模型报告的赤池信息量准则和均方误差值较低,模型概率较大。同样,AR 模型估计的加性遗传和残余方差较大。两种模型的遗传力和重复力估计值相似。DO、CI 和 DPR 的遗传力估计值分别为 0.04、0.07 和 0.04;AR 和 REP 模型分别为 0.05、0.06 和 0.04。从 AR 模型估计的 DO、CI 和 DPR 的个体 EBV 可靠性平均比从 REP 模型获得的 EBV 可靠性高 0.29、0.30 和 0.29 个单位。考虑前 10 头公牛时,AR 和 REP 模型获得的 EBV 之间的秩相关系数范围为 0.72 至 0.76;对于前 100 头公牛,相关系数从 0.98 增加到 0.99。两种方法选择的公牛数量越多,选择的公牛之间的吻合率越高。总体而言,模型拟合标准、遗传参数估计和 EBV 预测的结果对 AR 模型有利,表明该模型可用于巴西荷斯坦奶牛纵向繁殖性状的遗传评估。

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