Evaluation of Four Thermal Comfort Indices and Their Relationship with Physiological Variables in Feedlot Cattle

Climatic data from different years and experiments conducted in Nebraska were used to estimate four comfort thermal indices and to predict the risk of heat stress and its relationship with pen surface temperature (PST). These included the temperature-humidity index (THI), the adjusted THI (THIadj), the heat load index (HLI), and THIPST using pen surface temperature instead of air temperature. Respiration rates (RR), tympanic temperatures (TT), and panting scores (PS) were also collected in each year and from each location. During 2007, mean values of soil temperature, PST, outgoing shortwave radiation, and TT were greater than in 2008 (p < 0.011). However, HLI, relative humidity, and incoming and outgoing long-wave radiation were greater during 2008 (p < 0.012). The TT was positively correlated with THIPST and THIadj (0.75 and 0.70, respectively), whereas RR had a moderate correlation with THI, THIadj, and HLI (0.32, 0.27, and 0.34, respectively; p < 0.001). Thermal comfort indices showed a positive correlation with TT, especially the THIPST. These relationships vary with location. However, all of the thermal indices showed weak relationships with the observed RR. This would confirm the different roles that TT and RR have as indicators of heat stress. The THIPST was the best index for predicting TT across years.

Automated summary

This study used climatic data from different years and experiments conducted in Nebraska to estimate comfort thermal indices and predict the risk of heat stress. The results showed correlations between tympanic temperature (TT) and THIPST and THIadj, as well as correlations between respiration rate (RR) and THI, THIadj, and HLI. Thermal comfort indices were positively correlated with TT, especially THIPST. However, weak relationships were observed between thermal indices and RR, confirming the different roles of TT and RR as heat stress indicators. THIPST was found to be the best index for predicting TT.