Effect of temperature in the context of climate change on nutrient requirements of lactating sows
Résumé
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. This also results in a decrease in piglet weight gain and an increase in the mobilization of body reserves, which may impair reproduction after weaning. In the context of climate change which increases average temperature and the frequency of periods of heat stress, the aim of this work was to quantify the relationships between ambient temperature and sow and piglet performance, and to use these relationships in a prediction model of nutrient utilization by sows. A database with 46 publications and 254 observations was built in order to adjust prediction equations for different criteria such as feed intake, respiratory frequency, body temperature, litter growth, and milk production. These equations were then incorporated into a simulation model including (1) a bioclimatic module predicting the effect of outdoor temperature on the indoor temperature perceived by the sow and (2) a nutrition module predicting the effect of temperature on feed intake, milk production, energy and amino-acid utilization, and body reserves. This enabled a decision support tool to be developed for the prediction of performance and nutritional requirement of lactating sows in different climatic conditions. The model was used to simulate the effect of climate change on sow’s and piglets’ performance using CLIMATOR climate database for West and South France. The results show highly significant effects of season and region on animal performance and nutritional requirements. The simulations performed for years 2045-2050 indicate that these effects tend to become more marked with climate change. For instance digestible lysine requirement per kg feed was on average 10% higher during summer than during winter, and the requirement simulated for period 2045-2050 was about 2% higher than for 2000-2005. In practice the model developed should enable feed composition to be better adapted to the season and to the geographical location of farms and to expected changes of climate for the future.