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Systematic Clinical Examinations for Identification of Latent Udder Health Types in Danish Dairy Herds

机译:鉴定丹麦乳牛群体潜在乳房健康类型的系统临床检查

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A cross-sectional study was conducted to explore the applicability of systematic clinical examinations of udders as an additional tool for the evaluation of udder health status on dairy farms. During 2000, each of the 16 dairy farms was visited 5 times; 20 cows per farm were chosen at random at each visit for clinical udder examination immediately after milking. The clinical examination included both pathological and morphological variables. One examination per cow was included in the analysis (n = 707 cows). Principal component analysis (PCA) was performed in 3 steps. First, 19 variables characterizing udder and teats were analyzed (PCA 1). Second, the variables parity and stage of lactation were included (PCA 2). Finally, somatic cell count (SCO and milk yield (PCA 3) were included. The PCA resulted in 4 components that explained 30% of the variation of the data: 1) small udder, 2) distressed udder, 3) mastitis udder, and 4) soiled udder. Variables with high positive correlation to the "small udder" were small udder shape, short teats, and first parity. Impaired teat surface, hard udder texture, and a long udder shape were related to the "distressed udder." The "mastitis udder" was characterized by the clinical variables asymmetry between front quarters, asymmetry between hind quarters, knotty tissue, and acute clinical mastitis. Reduced milk yield and high SCC were related to the "mastitis udder," whereas low SCC was related to the "small udder." The "soiled udder" was related to early lactation. Including this information in the assessment of udder health may be of substantial value for data analysis in farms with suspected underreporting of clinical mastitis.
机译:进行了一项横断面研究,以探索对乳房进行系统性临床检查的适用性,以此作为评估奶牛场乳房健康状况的附加工具。 2000年期间,对16个奶牛场中的每一个进行了5次访问。每次访视时,随机选择每个农场20头奶牛,以便在挤奶后立即进行临床乳房检查。临床检查包括病理学和形态学变量。分析中每头母牛进行了一次检查(n = 707头母牛)。主成分分析(PCA)分为3个步骤。首先,分析了表征乳房和乳头的19个变量(PCA 1)。其次,包括变量胎次和泌乳阶段(PCA 2)。最后,包括了体细胞计数(SCO和产奶量(PCA 3)。PCA产生了4个成分,这些成分解释了数据的30%的变化:1)小乳房,2)苦恼的乳房,3)乳腺炎的乳房,以及4)乳房变脏。与“小乳房”高度正相关的变量是小乳房形状,短奶头和第一胎。乳头表面受损,乳房硬质感和乳房长形与“受苦乳房”有关。 “乳腺炎乳房”的特征是前四分之一之间的临床变量不对称,后四分之一之间的不对称,结节组织和急性临床乳腺炎。降低的牛奶产量和较高的SCC与“乳腺炎”有关,而较低的SCC与“小乳房”有关。 “烂乳房”与早期哺乳有关。将这些信息包括在乳房健康评估中,对于怀疑临床乳腺炎报告不足的农场进行数据分析可能具有重要价值。

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