及时准确地识别乳房内感染的奶牛对于最佳乳房健康管理至关重要。已经开发了各种传感器系统来提供乳房健康信息,这些信息可以用作农民的决策支持工具。在这些传感器中,利拉瓦尔在线细胞计数器(利拉瓦尔,汤巴,瑞典)提供了每次奶牛挤奶的体细胞计数。我们的目的是描述和评估这些在线细胞计数(OCC)的诊断传感器特性,以检测乳房内感染。定义为亚临床乳腺炎发作或临床乳腺炎的新病例。单个OCC值的预测能力,OCC值的滚动平均值,和升高的乳腺炎风险(EMR)变量在识别具有亚临床乳腺炎发作或临床乳腺炎新病例的奶牛中的准确性进行了比较。通过OCC在2个不同的乳腺炎病原体组中进行亚临床乳腺炎发作的检测,Pat1和Pat2,按其已知的增加体细胞计数的能力分类。这项研究的数据是在挪威生命科学大学的乳牛群进行的田间试验中获得的。总之,在17个月的研究期间,对173头母牛进行了至少一次采样。四分之一奶培养物的总数为5,330。最常见的Pat1病原体是表皮葡萄球菌,金黄色葡萄球菌,和乳酸链球菌。最常见的Pat2病原体是牛棒状杆菌,葡萄球菌色基因,和溶血葡萄球菌.在研究期间,成功记录了96,542次挤奶中的82,182次挤奶的OCC。对于亚临床乳腺炎发作,滚动7天平均OCC和EMR方法在检测Pat1亚临床乳腺炎发作方面比单个OCC值表现更好。EMR方法在检测Pat2亚临床乳腺炎发作方面优于OCC方法。对于2个病原体组,检测亚临床乳腺炎发作的灵敏度为69%(第1页)和31%(第2页),分别,在预定义的特异性为80%(EMR)。所有3种方法在检测临床乳腺炎的新病例方面同样出色,最佳灵敏度为80%,特异性为90%(单一OCC值)。
Timely and accurate identification of cows with intramammary infections is essential for optimal udder health management. Various sensor systems have been developed to provide udder health information that can be used as a decision support tool for the farmer. Among these sensors, the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) provides somatic cell counts from every milking at cow level. Our aim was to describe and evaluate diagnostic sensor properties of these online cell counts (OCC) for detecting an intramammary infection, defined as an episode of subclinical mastitis or a new case of clinical mastitis. The predictive abilities of a single OCC value, rolling averages of OCC values, and an elevated mastitis risk (EMR) variable were compared for their accuracy in identifying cows with episodes of subclinical mastitis or new cases of clinical mastitis. Detection of subclinical mastitis episodes by OCC was performed in 2 separate groups of different mastitis pathogens, Pat 1 and Pat 2, categorized by their known ability to increase somatic cell count. The data for this study were obtained in a field trial conducted in the dairy herd of the Norwegian University of Life Sciences. Altogether, 173 cows were sampled at least once during a 17-mo study period. The total number of quarter milk cultures was 5,330. The most common Pat 1 pathogens were Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae. The most common Pat 2 pathogens were Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus. The OCC were successfully recorded from 82,182 of 96,542 milkings during the study period. For episodes of subclinical mastitis the rolling 7-d average OCC and the EMR approach performed better than a single OCC value for detection of Pat 1 subclinical mastitis episodes. The EMR approach outperformed the OCC approaches for detection of Pat 2 subclinical mastitis episodes. For the 2 pathogen groups, the sensitivity of detection of subclinical mastitis episodes was 69% (Pat 1) and 31% (Pat 2), respectively, at a predefined specificity of 80% (EMR). All 3 approaches were equally good at detecting new cases of clinical mastitis, with an optimum sensitivity of 80% and specificity of 90% (single OCC value).