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.

中文翻译：

---

巴西荷斯坦牛纵向生殖性状遗传评估的自回归模型

繁殖效率是奶牛群盈利能力的主要决定因素。因此，繁殖性状已被广泛用作当前奶牛育种计划中的选择目标。我们旨在评估对巴西荷斯坦牛的开放天数 (DO)、产犊间隔 (CI) 和子代妊娠率 (DPR) 建模的策略。通过自回归 (AR) 模型分析这些生殖性状，并分别使用 127,280、173,092 和 127,280 个表型记录与经典重复性 (REP) 模型进行比较。这里使用了来自 1,469 头荷斯坦牛群的前三个产犊顺序。AR 模型报告了所有评估特征的 Akaike 信息标准和均方误差的较低值，以及较大的模型概率。相似地，从 AR 模型估计更大的加性遗传和更低的残差方差。两种模型的遗传性和可重复性估计值相似。DO、CI 和 DPR 的遗传力分别为 0.04、0.07 和 0.04；AR 和 REP 模型分别为 0.05、0.06 和 0.04。从 DO、CI 和 DPR 的 AR 估计的个体 EBV 可靠性平均比从 REP 模型获得的高 0.29、0.30 和 0.29 个单位。考虑到前 10 名公牛，从 AR 和 REP 模型获得的 EBV 之间的等级相关性介于 0.72 到 0.76 之间；前 100 名多头从 0.98 增加到 0.99。从两种方法中选择的公牛之间的重合百分比超过了顶级组中包含的公牛数量。总的来说，模型拟合标准的结果，