Lactation and Immuno-Physiology Laboratory, Animal Physiology Division, Indian Council of Agricultural Research (ICAR)-National Dairy Research Institute, Karnal, Haryana, India.
Reproductive Biotechnology, School of Life Sciences, Technical University of Munich, Freising, Germany.
J Therm Biol. 2024 Apr;121:103838. doi: 10.1016/j.jtherbio.2024.103838. Epub 2024 Mar 26.
The present study focused on Sahiwal cows, a prominent milch breed in tropical India, to correlate udder temperature with physiological markers of stress and inflammation during subclinical mastitis (SCM). The primary goal was to assess the potential of udder infrared thermography for the early detection of SCM under the semi-intensive production. Cows were categorized based on milk somatic cell counts (SCC), with healthy (H) cows having SCC <2 × 10 cells/mL and no history of mastitis, and cows with subclinical mastitis (SCM) and initial stages of clinical mastitis (CM) having quarter milk SCC of 2-5 × 10 and >5 × 10 cells/mL, respectively. Firstly, udder thermograms were analysed for udder skin surface temperature (USST), teat skin surface temperature (TSST), and teat apex temperature (TAT) using Fluke software to determine the optimal site for temperature measurement during intramammary infection. Secondly, milk samples were collected for automatic estimation of compositional changes, electrical conductivity, and pH. Thirdly, milk whey was separated for quantifying stress and inflammatory indicators, including cortisol, prolactin, and acute-phase proteins (APPs): milk amyloid A and milk haptoglobin using bovine-specific ELISA kits. Significant increases (p < 0.01) in USST, TSST, TAT, cortisol, and APPs were observed in SCM and CM compared to healthy cows, while prolactin levels decreased (p < 0.01). The correlation matrix revealed strong positive correlations of SCC with USST (r = 0.84, p < 0.01). In ROC analysis, USST demonstrated cut-off values of 37.74 and 39.58 °C, with accuracy (p < 0.05) of 98% for SCM and 95% for CM, surpassing both TAT and TSST. Therefore, the combination of these non-invasive methods increases the reliability and accuracy of infrared thermography for early detection of SCM, providing valuable insights for the development of a protocol for routine screening and udder health monitoring in indigenous dairy cows.
本研究聚焦于印度热带地区的主要乳用品种——萨希瓦尔牛，旨在探讨在亚临床乳腺炎（SCM）期间，乳房温度与应激和炎症的生理标志物之间的相关性。主要目标是评估在半集约化生产条件下，通过乳房红外线热成像技术对 SCM 进行早期检测的潜力。根据牛奶体细胞计数（SCC）对奶牛进行分类，健康奶牛（H）的 SCC<2×10 细胞/ml，且无乳腺炎病史，而患有亚临床乳腺炎（SCM）和临床乳腺炎（CM）初期的奶牛的四分位 SCC 分别为 2-5×10 和>5×10 细胞/ml。首先，使用 Fluke 软件分析乳房热图，以确定在发生乳腺炎时进行体温测量的最佳部位，包括乳房皮肤表面温度（USST）、乳头皮肤表面温度（TSST）和乳头尖端温度（TAT）。其次，采集牛奶样本进行自动成分变化、电导率和 pH 值的检测。再次，分离乳清以定量评估应激和炎症指标，包括皮质醇、催乳素和急性期蛋白（APP）：牛奶淀粉样蛋白 A 和牛奶触珠蛋白，采用牛特异性 ELISA 试剂盒进行检测。与健康奶牛相比，SCM 和 CM 奶牛的 USST、TSST、TAT、皮质醇和 APPs 显著升高（p<0.01），而催乳素水平下降（p<0.01）。相关矩阵显示 SCC 与 USST 之间存在强正相关（r=0.84，p<0.01）。在 ROC 分析中，USST 显示出 37.74 和 39.58°C 的截断值，SCM 的准确率（p<0.05）为 98%，CM 的准确率为 95%，均优于 TAT 和 TSST。因此，这些非侵入性方法的结合提高了红外线热成像技术对 SCM 早期检测的可靠性和准确性，为开发用于印度本土奶牛常规筛查和乳房健康监测的方案提供了有价值的见解。
