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首页> 外文期刊>Turkish Journal of Veterinary and Animal Sciences >The prediction of the prevalence and risk factors for subclinical heifer mastitis in Turkish dairy farms
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The prediction of the prevalence and risk factors for subclinical heifer mastitis in Turkish dairy farms

机译:土耳其奶牛场亚临床小母牛乳腺炎的患病率和危险因素预测

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The aim of this study was to determine the risk factors for subclinical heifer mastitis and to create a model that can predict the prevalence of subclinical mastitis of pregnant heifers in farms in Turkey. Lacteal secretion samples were taken from 439 pregnant (6-9 months) heifers and bacteriological analyses were performed. In this study, 37.47% of the samples were determined to be infected. In lacteal secretion samples, the isolation rate of coagulase-negative staphylococci and Staphylococcus aureus was 44.83% and 35.71%, respectively. The incidence of mastitis was calculated as 42.87 +/- 4.12%. An eight-question survey was conducted. Using the data collected, a multiple linear regression analysis using backward stepwise method was used to predict the incidence of mastitis. According to the multiple regression model, the number of animals, well-balanced ration, separating the cows in dry periods into different boxes, and contact of heifers with older cows significantly contributed to the model (P < 0.05). Coefficient of determination (R-2) for the model was estimated at 93.8%. Today, with the knowledge of risk factors for pregnant heifers, changes in management would be beneficial to prevent mastitis. Additionally, this study showed that predictive models for the incidence of mastitis could be conducted through comprehensive future studies.
机译:这项研究的目的是确定亚临床小母牛乳腺炎的危险因素,并创建一个可以预测土耳其农场的怀孕小母牛亚临床乳腺炎患病率的模型。从439个怀孕的母牛(6-9个月)中采集乳酸分泌样品,并进行细菌学分析。在这项研究中,确定有37.47%的样本被感染。在乳汁分泌样品中,凝固酶阴性葡萄球菌和金黄色葡萄球菌的分离率分别为44.83%和35.71%。乳腺炎的发生率经计算为42.87 +/- 4.12%。进行了八个问题的调查。使用收集到的数据,使用后向逐步方法进行多元线性回归分析来预测乳腺炎的发生率。根据多元回归模型,动物数量,均衡的日粮,将干旱时期的母牛分为不同的箱体以及小母牛与年长母牛的接触对模型产生了显着影响(P <0.05)。该模型的测定系数(R-2)估计为93.8%。如今,有了怀孕小母牛的危险因素的知识,改变管理方式将有助于预防乳腺炎。此外,这项研究表明,可以通过全面的未来研究进行乳腺炎发病率的预测模型。

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