Evaluation of infrared thermography as a diagnostic tool to predict heat stress events in feedlot cattle.

OBJECTIVE To determine whether infrared thermographic images obtained the morning after overnight heat abatement could be used as the basis for diagnostic algorithms to predict subsequent heat stress events in feedlot cattle exposed to high ambient temperatures. ANIMALS 60 crossbred beef heifers (mean ± SD body weight, 385.8 ± 20.3 kg). PROCEDURES Calves were housed in groups of 20 in 3 pens without any shade. During the 6 am and 3 pm hours on each of 10 days during a 14-day period when the daily ambient temperature was forecasted to be > 29.4°C, an investigator walked outside each pen and obtained profile digital thermal images of and assigned panting scores to calves near the periphery of the pen. Relationships between infrared thermographic data and panting scores were evaluated with artificial learning models. RESULTS Afternoon panting score was positively associated with morning but not afternoon thermographic data (body surface temperature). Evaluation of multiple artificial learning models indicated that morning body surface temperature was not an accurate predictor of an afternoon heat stress event, and thermographic data were of little predictive benefit, compared with morning and forecasted weather conditions. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated infrared thermography was an objective method to monitor beef calves for heat stress in research settings. However, thermographic data obtained in the morning did not accurately predict which calves would develop heat stress later in the day. The use of infrared thermography as a diagnostic tool for monitoring heat stress in feedlot cattle requires further investigation.