Department of Agricultural Engineering, Universidade Federal do Ceará, 60440900, Fortaleza, CE, Brazil; Center of Environment and Agriculture Science, Universidade Federal do Maranhão, 65500-000, Chapadinha, MA, Brazil.
Department of Agricultural Engineering, Universidade Federal do Ceará, 60440900, Fortaleza, CE, Brazil.
J Therm Biol. 2021 Apr;97:102881. doi: 10.1016/j.jtherbio.2021.102881. Epub 2021 Feb 25.
This study aimed to evaluate the use of thermal imaging obtained by infrared thermography (IRT) to detect cases of subclinical mastitis in dairy cows under commercial conditions of compost barn systems in a region of Brazil with a semiarid climate. Twenty-eight crossbred cows were evaluated twice a day for one week using IRT. Three thermal images were obtained for each cow, referring to the anatomical regions of the right and left fore udder and rear udder. A computer program was used to analyze the images and obtain the right fore udder temperature (RFUT, °C), left fore udder temperature (LFUT, °C), rear udder temperature (RUT, °C), and average udder temperature (AUT, °C). In addition, samples of milk from each quarter of the udder were collected for somatic cell count (SCC) to correlate the diseases observed on the thermal image with any infection in the udder region. The results obtained using IRT were subjected to regression and correlation analyses. It was observed that LFUT, RAQT, RUT, and AUT were adjusted in quadratic polynomial models with good prediction of SCC (i.e., infection) with R = 0.92, 0.97, 0.86, and 0.94, respectively. The region of the anterior quarters of the udder was the most promising for imaging, stronger correlations were obtained between LFUT and RFUT with SCC (r = 0.87 and 0.88, respectively). The IRT is a practical technology capable of detecting cases of mastitis in dairy cows with good precision, especially with thermal images from the anatomical region of the front quarters of the udder. However, more detailed studies are needed to make thermal imaging processing a more useful method for routine activities on farms in compost barn systems.
本研究旨在评估使用红外热成像（IRT）检测巴西半干旱气候地区堆肥仓系统商业条件下奶牛亚临床乳腺炎病例的效果。28 头杂交奶牛每天进行两次 IRT 评估，持续一周。为每头奶牛拍摄三张热图像，分别对应右前乳房和左前乳房及后乳房的解剖区域。使用计算机程序分析图像并获得右前乳房温度（RFUT，℃）、左前乳房温度（LFUT，℃）、后乳房温度（RUT，℃）和平均乳房温度（AUT，℃）。此外，还从每个乳房的四个象限采集奶样进行体细胞计数（SCC），以将热图像上观察到的疾病与乳房区域的任何感染相关联。IRT 获得的结果进行了回归和相关性分析。结果表明，LFUT、RAQT、RUT 和 AUT 均采用二次多项式模型进行调整，SCC（即感染）的预测效果较好，R 分别为 0.92、0.97、0.86 和 0.94。乳房前区是最有希望进行成像的区域，LFUT 和 RFUT 与 SCC 之间的相关性更强（r 分别为 0.87 和 0.88）。IRT 是一种实用技术，能够准确检测奶牛乳腺炎病例，特别是从乳房前区获得的热图像。然而，需要进行更详细的研究，以使热成像处理成为堆肥仓系统农场常规活动中更有用的方法。
