No abstract

Eye temperature (ET) has long been used for predicting or indicating heat stress in dairy cows. However, the region of interest (ROI) and temperature parameter of the eye have not been standardized and various options were adopted by previous studies. The aim of this study was to determine the best ROI for measuring ET as the predictor of heat stress in dairy cows in consideration of repeatability and validity. The ET of 40 lactating Holstein dairy cows was measured using infrared thermography. The mean and maximum temperature of five ROIs—medial canthus (MC), lateral canthus, eyeball, whole eye (WE), and lacrimal sac (LS)—were manually captured. The results show that the ET of left eyes was slightly higher than that of right eyes. The ET taken in MC, WE, and LS within 2 min had a moderate to substantial repeatability. The maximum temperature obtained at the LS had the highest correlation coefficients with respiration rate and core body temperature (all p < 0.001). Therefore, the maximum temperature of LS should be considered by future studies that want to use ET as the predictor or indicator of heat stress in dairy cows.

This study aimed to better understand environmental heat stress and physiological heat strain indicators in lactating dairy cows. Sixteen heat stress indicators were derived using microenvironmental parameters that were measured at the surrounding of cows and at usual fixed locations in the barn by using handheld and fixed subarea sensors, respectively. Twenty highproducing Holstein-Friesian dairy cows (> 30.0 kg/day) from an intensive dairy farm were chosen to measure respiration rate (RR), vaginal temperature (VT), and body surface temperature of forehead (FT), eye (ET), and muzzle (MT). Our results show that microenvironments measured by the handheld sensor were slightly warmer and drier than those measured by the fixed subarea sensor; however, their derived heat stress indicators correlated equally well with physiological indicators. Interestingly, ambient temperature (T a ) had the highest correlations with physiological indicators and the best classification performance in recognizing actual heat strain state. Using segmented mixed models, the determined T a thresholds for maximum FT,