Mastitis is one of the most prevalent and costly diseases in dairy cattle. Key components for adequate mastitis control are the detection of early stages of infection, as well as the selection of appropriate management interventions and therapies based on the causal pathogens associated with the infection. The objective was to characterize the pattern of electrical conductivity (EC) in milk during intramammary infection, considering specific mastitis-causing pathogen groups involvement. Cows (n = 200) identified by an in-line mastitis detection system with a positive deviation ≥15% in the manufacturer's proprietary algorithm for EC (high electrical conductivity (HEC)) were considered cases and enrolled in the study at the subsequent milking. One control (CON) cow, within normal ranges for EC, was matched to each case. A composite milk sample was collected aseptically from each cow for bacteriological culture. Milk yield (MY) and EC were recorded for each milking during ±7 days relative to enrollment. Milk cultures were categorized into gram positive (GP), gram negative (GN), other (OTH) and no growth (NOG). Data were submitted for repeated-measures analysis with EC as the dependent variable and EC status at day -1, bacteriological culture category, parity number, stage of lactation and days relative to sampling as main independent variables. Average (± standard error (SE)) EC was greater in HEC than in CON cows (12.5 ± 0.5 v. 10.8 ± 0.5 mS/cm) on the day of identification (day -1). Milk yield on day -1 was greater in CON than in HEC (37.6 ± 5.1 v. 33.5 ± 5.2 kg). For practical management purposes, average EC on day -1 was similar for the different bacteriological culture categories: 11.4 ± 0.6, 11.7 ± 0.5, 12.3 ± 0.8 and 11.7 ± 0.5 mS/cm in GN, GP, OTH and NOG, respectively. Parity number was only associated with day -1 EC in HEC group, with the greatest EC values in parity 3 (12.3 ± 0.3 mS/cm), followed by parity 2 (11.9 ± 0.2 mS/cm), parity >3 (11.6 ± 0.5 mS/cm) and primiparous cows (11.2 ± 0.2 mS/cm). An effect on EC for the interaction of day relative to identification by pathogen gram category was observed. The same interaction effect was observed on daily MY. Overall, the level of variation for MY and EC between- and within-cows was substantial, and as indicated by the model diagnostic procedures, the magnitude of the variance in the cows in the CON group resulted in deviations from normality in the residuals. We concluded that characteristic temporal patterns in EC and MY in particular pathogen groups may provide indications for differentiation of groups of mastitis-causing pathogens. Further research to build detection models including EC, MY and cow-level factors is required for accurate differentiation.

中文翻译：

---

使用牛奶电导率区分荷斯坦奶牛乳腺炎病原体。

乳腺炎是奶牛中最普遍和最昂贵的疾病之一。充分控制乳腺炎的关键组成部分是检测感染的早期阶段，以及根据与感染相关的致病病原体选择适当的管理干预措施和疗法。目的是在考虑特定的引起乳腺炎的病原体群参与的情况下，表征乳房内感染期间牛奶中的电导率 (EC) 模式。由在线乳腺炎检测系统识别的奶牛（n = 200）在制造商的专有 EC（高电导率 (HEC) 算法）中的正偏差 ≥ 15% 被视为病例，并在随后的挤奶时被纳入研究。在 EC 正常范围内的一头对照 (CON) 母牛与每个病例相匹配。从每头奶牛无菌收集复合牛奶样品用于细菌培养。相对于入组，在 ±7 天内记录每次挤奶的产奶量 (MY) 和 EC。乳培养物分为革兰氏阳性 (GP)、革兰氏阴性 (GN)、其他 (OTH) 和无生长 (NOG)。提交数据进行重复测量分析，EC 作为因变量，第-1 天的 EC 状态、细菌学培养类别、胎次、泌乳阶段和相对于采样的天数作为主要自变量。在鉴定当天（第-1 天），HEC 中的平均（±标准误差 (SE)）EC 高于 CON 奶牛（12.5 ± 0.5 v. 10.8 ± 0.5 mS/cm）。CON 组第 -1 天的产奶量高于 HEC 组（37.6 ± 5.1 对 33.5 ± 5.2 kg）。出于实际管理目的，对于不同的细菌培养类别，第 -1 天的平均 EC 相似：GN、GP、OTH 和 NOG 分别为 11.4 ± 0.6、11.7 ± 0.5、12.3 ± 0.8 和 11.7 ± 0.5 mS/cm。HEC组胎次仅与第-1天EC相关，第3胎EC值最大（12.3±0.3 mS/cm），其次是第2胎（11.9±0.2 mS/cm），胎次>3（11.6± 0.5 mS/cm) 和初产奶牛 (11.2 ± 0.2 mS/cm)。观察到相对于病原体克类别鉴定的日相互作用对 EC 的影响。在每日 MY 上观察到相同的交互作用。总体而言，奶牛之间和奶牛内的 MY 和 EC 变异水平很大，并且如模型诊断程序所示，CON 组奶牛的变异幅度导致残差偏离正态性。我们得出结论，特定病原体组中 EC 和 MY 的特征性时间模式可能为区分引起乳腺炎的病原体组提供指示。为了准确区分，需要进一步研究建立检测模型，包括 EC、MY 和奶牛水平因素。