Characterization of dystocia in a herd of Holstein dairy cows in Brazil

Abstract The objective of this study was to characterize calvings with low and high difficulty based on the productive and reproductive performance of dairy cows. Calvings were grouped in no calving assistance, calving with low assistance, and calving with high assistance. The original data set comprised 1,902 calving records obtained from a large dairy farm in Southeast Brazil. Factor analysis was applied using the SAS® Studio 3.8 statistical program through the factor procedure, considering the Multivariate Analysis category. Milk fat (0.92–0.79) and total solids (0.91–0.80) were strongly correlated with Factor 1. Calving interval (0.87– 0.68) and the number of AI (artificial inseminations) per conception (0.87–0.71) showed high correlations with Factor 2. Milk yield (0.84–0.76) and accumulated milk yield (0.84–0.77) were strongly correlated with Factor 3. Based on the results, we conclude that the three calving scenarios were characterized by well-defined and independent factors. Cows which required a high assistance at calving showed a lower variance explained by the model for milk fat and total solids contents, calving interval, and the number of AIs per conception.摘要：本研究旨在基于奶牛的生产与繁殖性能，对不同难易程度的产犊事件开展特征分析。研究将产犊事件分为无需助产、轻度助产与重度助产三类。原始数据集包含来自巴西东南部一家大型奶牛场的1902条产犊记录。本研究采用SAS® Studio 3.8统计软件的因子分析程序，纳入多元分析范畴开展因子分析。其中，乳脂（0.92–0.79）与总乳固体（0.91–0.80）与因子1呈强相关性；产犊间隔（0.87–0.68）与单次受孕所需人工授精（artificial inseminations, AI）次数（0.87–0.71）与因子2呈高相关性；产奶量（0.84–0.76）与累计产奶量（0.84–0.77）与因子3呈强相关性。基于研究结果，本研究得出结论：三类产犊场景可通过明确且独立的因子实现特征区分。产犊时需要重度助产的奶牛，其乳脂率、总乳固体含量、产犊间隔以及单次受孕所需人工授精次数这几项指标的模型解释方差更低。