Effect of ambient temperature in lactating sows, a meta-analysis and simulation approach in the context of climate change

Abstract

Because of their intense metabolism, lactating sows are highly sensitive to high ambient temperature which induces a reduction in their voluntary feed intake and milk production, which decreases piglet weaning weight. This also results in an increase in mobilisation of body reserves that may impair reproduction after weaning. The aim of the study was to quantify, on the basis of a quantitative analysis of the literature data, the effect of ambient temperature on the performance and physiology of lactating sows, with the perspective of integrating this knowledge in sow nutrition decision support tools. A literature database with 38 publications and a total of 227 observations was built in order to adjust prediction equations according to temperature, using a Mixed linear or quadratic model with random effect of publication, for different criteria such as feed intake, litter and piglet growth rate, milk production, maternal body reserve mobilisation, respiratory rate (RR) and core body temperature. The first criterion with the highest response to temperature was RR which increased by 175 % between 22 °C and 32 °C. The second most affected criterion was feed intake which was reduced by 36 % between 22 °C and 32 °C, and the third one was milk production which was reduced by 20 % between 22 °C and 32 °C. The equations obtained from the meta-analysis were incorporated into a nutrition model, based on InraPorc®, in order to predict, in the context of climate change, the effect of temperature on feed intake, milk production, energy and aminoacid utilisation, and body reserve mobilisation. The simulations performed using this model clearly indicate that nutrient requirement of sows per kg feed is affected by variation in ambient temperature due to seasons or to expected climate change. In practice, the integration of these new equations in nutritional models will enable feed composition to be better adapted to the season and to the geographical location of farms.