Developing a new thermal comfort prediction model and web-based application for heat stress assessment in dairy cows

Precise evaluation and prediction of heat stress on animals are largely studied, given their importance for reducing economic losses and improving animal welfare. There are serials of thermal comfort index models that attempt to quantify the severity of heat stress imposed on dairy cows. However, few index models involved the heat exchanges between cows and the environment. There is also no relevant online prediction and assessment tool for heat stress in dairy cows. The objective was of this study was to develop a new thermal comfort indicator, referred to as Skin Temperature Index for Cows (STIC), based on the heat balance equations and an integrative tool to predict and assess heat stress in dairy cows. Environmental and physiological data from a previous study was divided into the validation set (N = 902, accounting for 30%) and the evaluation set (N = 2103, 70%). We first derived the explicit expression for the theoretical model (Predicted Skin Temperature, PST) by simplifying the theoretical model and using nonlinear regression analysis. As verified by the validation set, the PST model showed an acceptable accuracy with the root mean square error of 1.165 & DEG;C, the mean absolute error of 0.918 & DEG;C, and the mean absolute percentage error of 2.62%. Then, the STIC model was obtained based on the upper and lower limits of skin temperature and the PST model. The results indicate that the determination of coefficient (R2) of STIC for rectal temperature, respiration rate, skin temperature, eye temperature were 0.48, 0.71, 0.73, and 0.42, respectively. The STIC showed significantly higher prediction with the physiological responses than other thermal comfort indices (p < 0.05) with respect to rectal temperature (r = 0.69), skin temperature (r = 0.86), and eye temperature (r = 0.65). In addition, the STIC thresholds and the adjustments of cow-related factors (body posture, average daily milk yield, and stage of lactation) to the critical threshold were established based on temperature-humidity index thresholds. Further, we developed a web-based application, the Heat Stress Indicator Tool, for thermal comfort index calculation and visualization of the level of heat stress imposed on dairy cows. Overall, the PST and STIC models incorporate air temperature, relative humidity, solar radiation, wind speed and consider the interactions of environmental parameters based on the heat exchange theory. They are powerful in assessing the heat stress of cows and have great potential for serving as precise environmental control criteria in cow buildings. Moreover, the online tool is practical for researchers and dairy farm managers.(C) 2021 IAgrE. Published by Elsevier Ltd. All rights reserved.