Using infrared thermography to detect subclinical mastitis in dairy cows in compost barn systems.

Abstract

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 R2=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.