Abstract：
\"India is the world\'s leading producer of milk\" and demands a non-invasive diagnostic tool like infrared thermography (IRT) to identify the costliest production disease, mastitis. It can form the basis of precision dairy farming. Therefore, the present study focuses on thermal imaging of the udder and teat quarters of Sahiwal cows during different seasons to identify subclinical (SCM) and clinical mastitis (CM) cases using the Darvi DTL007 camera. A total of 24-69 lactating Sahiwal cows were screened out using IRT regularly throughout the year. The intramammary infection status was further assessed using the CMT. The receiver operating characteristic analysis was carried out to develop the current study\'s cut-off for various thermographic parameters. The incidence for SCM and CM ranged from 26.47 to 38.75% and 17.83-22.79%, respectively during different seasons in Sahiwal udder quarters. The thermogram analysis revealed a significant difference (p < 0.01) in the mean values of the udder and teat surface temperature of Sahiwal cows between healthy, SCM, and CM during different seasons. The mean values of udder skin surface temperature (USST) during different seasons ranged between 29.07 and 36.91 °C, 31.51 to 37.88 °C and 32.42 to 38.79 °C among healthy, SCM, and CM-affected quarters, and correspondingly, the mean values of teat skin surface temperature (TSST) were 28.28 to 36.77 °C, 30.68 to 37.88 °C and 31.70 to 38.73 °C, respectively. Further results revealed an increase (p < 0.01) in the mean values of USST during winter, summer, rainy, and autumn as 2.44, 3.35; 0.97, 1.88; 1.06, 1.83; 1.29, 2.39 °C and TSST as 2.4, 3.42; 1.11, 1.96; 1.21, 2.19, 1.3, 2.4 °C of SCM, CM-affected quarters to healthy quarters, respectively, in Sahiwal cows. Thermograms showed a strong positive correlation with the CMT scores of SCM, CM cases, and healthy samples. Henceforth, irrespective of the seasons studied in the present work, IRT is an efficient, supportive tool for the early identification of subclinical mastitis.
摘要：
“印度是世界领先的牛奶生产国”，需要一种非侵入性诊断工具，如红外热成像(IRT)来识别最昂贵的生产疾病，乳腺炎.它可以形成精准奶牛养殖的基础。因此,本研究的重点是使用DarviDTL007相机对不同季节的Sahiwal奶牛的乳房和乳头区域进行热成像，以识别亚临床（SCM）和临床乳腺炎（CM）病例。全年定期使用IRT筛选出总共24-69头泌乳Sahiwal母牛。使用CMT进一步评估乳房内感染状态。进行了接收器工作特性分析，以开发当前研究的各种热成像参数的截止值。SCM和CM的发生率为26.47至38.75％和17.83-22.79％，分别在Sahiwal乳房区的不同季节。热谱图分析显示，健康的Sahiwal奶牛乳房和乳头表面温度的平均值存在显着差异（p<0.01）。SCM,和CM在不同的季节。不同季节乳房皮肤表面温度（USST）的平均值介于29.07和36.91°C之间，健康者为31.51至37.88°C和32.42至38.79°C，SCM,和受CM影响的季度，相应地，乳头皮肤表面温度（TSST）的平均值为28.28至36.77°C，30.68至37.88°C和31.70至38.73°C，分别。进一步的结果表明，冬季USST的平均值增加（p<0.01），夏天,下雨,秋季为2.44、3.35；0.97、1.88；1.06、1.83；1.29、2.39°C，TSST为2.4、3.42；1.11、1.96；1.21、2.19、1.3、2.4°C，受CM影响的季度到健康的季度，分别,在Sahiwal奶牛。热谱图与SCM的CMT评分呈较强的正相关,CM案例，和健康样本。从今以后,不管在目前的工作中研究的季节，IRT是一种高效的，早期识别亚临床乳腺炎的支持工具。
