Production and composition of milk per Holstein and Jersey cow from two farms in northwest Rio Grande do Sul

ABSTRACT The aim of the present study was to monitor cow milk quality and composition in two farms in the Noroeste Rio-grandense mesoregion, located in the municipalities of Palmeira das Missões and Pinhal - RS. Both herds were mixed, with animals of the Holstein (70%) and Jersey (30%) breeds. The following overall parameters were evaluated: body condition score (BCS), udder dirtiness, and calving order, and the following milk composition factors were measured: total dry extract (TDE), defatted dry extract (DDE), milk lactose, fat, and protein contents, casein, milk urea nitrogen (MUN), and somatic cell count (SCC). Multivariate statistical analysis was performed, and four factors were identified representing combinations of the measured variables. The first factor comprised negative relationships between milk production and cow breed, milk fat content, and milk protein content. The second factor comprised the positive relationships between lactation days and body condition score and milk protein content. The third factor represented the negative relationships between milk lactose content and SCC score, calving order, and BCS. The fourth factor was composed of the positive relationship between delivery order and udder dirtiness. Cluster analysis revealed that individual cows could be categorized into three groups. Monitoring the breed, calving order, body condition score, lactation days, milk production, fat, protein, and lactose contents, somatic cell counts, and udder dirtiness in cows allows greater control of the herd, allowing potential shortcomings to be rectified quickly and economic losses to production to be minimized.摘要 本研究旨在监测位于南里奥格兰德州帕尔梅拉达斯米索斯市（Palmeira das Missões）与Pinhal市境内的北里奥格兰德宏区域（Noroeeste Rio-grandense mesoregion）内两座牧场的牛乳品质与成分。两个牛群均为混合品种，其中荷斯坦（Holstein）牛占比70%、娟姗（Jersey）牛占比30%。本研究评估的整体参数包括体况评分（body condition score, BCS）、乳房洁净度与产次；测定的乳成分指标涵盖总干提取物（total dry extract, TDE）、脱脂干提取物（defatted dry extract, DDE）、牛乳乳糖含量、乳脂含量、乳蛋白含量、酪蛋白、乳尿素氮（milk urea nitrogen, MUN）以及体细胞计数（somatic cell count, SCC）。采用多变量统计分析后，共识别出4个可代表测定变量组合的因子：第一个因子体现了产奶量与牛品种、乳脂含量及乳蛋白含量间的负相关关系；第二个因子体现了泌乳天数与体况评分、乳蛋白含量间的正相关关系；第三个因子代表了乳糖含量与体细胞评分、产次及体况评分间的负相关关系；第四个因子则由产次与乳房洁净度间的正相关关系构成。聚类分析结果显示，可将个体母牛划分为3个组别。对母牛的品种、产次、体况评分、泌乳天数、产奶量、乳脂、乳蛋白及乳糖含量、体细胞计数以及乳房洁净度进行监测，可实现对牛群的精细化管控，快速修正潜在管理短板，并最大限度降低生产相关经济损失。