Negative relationship between dry matter intake and the temperature-humidity index with increasing heat stress in cattle: a global meta-analysis.

Changes in frequency and severity of heat waves due to climate change pose a considerable challenge to livestock production systems. Although it is well known that heat stress reduces feed intake in cattle, effects of heat stress vary between animal genotypes and climatic conditions and are context specific. To derive a generic global prediction that accounts for the effects of heat stress across genotypes, management and environments, we conducted a systematic literature review and a meta-analysis to assess the relationship between dry matter intake (DMI) and the temperature-humidity index (THI), two reliable variables for the measurement of feed intake and heat stress in cattle, respectively. We analysed this relationship accounting for covariation in countries, breeds, lactation stage and parity, as well as the efficacy of various physical cooling interventions. Our findings show a significant negative correlation (r = - 0.82) between THI and DMI, with DMI reduced by 0.45 kg/day for every unit increase in THI. Although differences in the DMI-THI relationship between lactating and non-lactating cows were not significant, effects of THI on DMI varied between lactation stages. Physical cooling interventions (e.g. provision of animal shade or shelter) significantly alleviated heat stress and became increasingly important after THI 68, suggesting that this THI value could be viewed as a threshold for which cooling should be provided. Passive cooling (shading) was more effective at alleviating heat stress compared with active cooling interventions (sprinklers). Our results provide a high-level global equation for THI-DMI across studies, allowing next-users to predict effects of heat stress across environments and animal genotypes.

The simulation of discrete vessel effects in experimental hyperthermia.

The ability of two simple thermal models to predict experimentally measured in vivo temperature profiles was compared. These comparisons were done both with and without the inclusion of separate, discrete blood vessels. The two tissue models were: 1) Pennes' Bio-Heat Transfer equation (BHTE), and 2) an effective thermal conductivity equation (ETCE). The experimental temperature data were measured (Moros, 1990; Moros et al., 1993) in the thighs of anesthetized greyhound dogs under hyperthermic conditions generated by scanned focused ultrasound. Blood vessels were added to the thermal models in counter-current pairs transiting the model domain. The blood vessels in both models were assumed to have a constant heat transfer coefficient, and an axially varying mixed mean temperature. The vessel locations were determined a posteriori, via inspection of the experimental temperature data. Least square error fits of the predicted model temperatures to the experimental temperature data were obtained by adjusting both (a) the mass flow rate within and (b) the position of each blood vessel, and (c) the value of either the perfusion parameter (W) in the BHTE or the effective thermal conductivity parameter (Keff) in the ETCE. When small numbers (3-4) of blood vessel pairs were included, both of the models showed significant improvement in their ability to predict the experimental temperatures. Although both models performed well in terms of predicting temperatures near large vessels, the BHTE had a statistically significant better ability to predict the complete set of measured temperatures at all locations.