Thermoregulation at birth differs between piglets from two genetic lines divergent for residual feed intake.

Thermoregulation is essential to piglets' neonatal survival. This study used infrared thermography (IRT) to assess thermoregulation abilities of piglets from two lines divergent for residual feed intake (RFI). At birth, morphology (weight, length, width and circumference), vigour (respiration, mobility and vocalisation), and rectal temperature were recorded from piglets of the 11th generation of the low RFI (LRFI, more efficient; n = 34) and the high RFI (HRFI, less efficient; n = 28) lines. Infrared thermography images were taken at 8, 15, 30 and 60 min post partum. Temperatures of the ear base and tip, and of the back (i.e. shoulders to rumps) were extracted (Thermacam Researcher Pro 2.0) and analysed with linear mixed models (SAS 9.4). Piglets had different average hourly weight gain (HRFI = 7.1 ±â€¯1.3 g/h, LRFI = 3.6 ±â€¯1.3 g/h; P < 0,001) but did not differ in morphology or vigour. All temperatures increased overtime. At birth, piglets' rectal temperature was correlated with the initial temperature of the ear base and the maximum back temperature (0.37 and 0.33, respectively; P < 0.05). High residual feed intake piglets had lower ear tip temperatures than LRFI piglets at 15 (24.7 ±â€¯0.37 °C vs. 26.3 ±â€¯0.36 °C, respectively; F1, 63.5 = 9.11, P < 0.005) and 30 min post partum (26.2 ±â€¯0.47 °C vs. 27.6 ±â€¯0.44 °C, respectively; F1, 66.9 = 4.52, P < 0.05). Moreover, thermal pattern of the ear tip differed between the two genetic lines. In conclusion, IRT allowed non-invasive assessment of piglets' thermoregulation abilities and indicated an influence of genetic selection for RFI on neonatal thermoregulation abilities.

Towards the quantitative characterisation of piglets' robustness to weaning: a modelling approach.

Weaning is a critical transition phase in swine production in which piglets must cope with different stressors that may affect their health. During this period, the prophylactic use of antibiotics is still frequent to limit piglet morbidity, which raises both economic and public health concerns such as the appearance of antimicrobial-resistant microbes. With the interest of developing tools for assisting health and management decisions around weaning, it is key to provide robustness indexes that inform on the animals' capacity to endure the challenges associated with weaning. This work aimed at developing a modelling approach for facilitating the quantification of piglet resilience to weaning. A total of 325 Large White pigs weaned at 28 days of age were monitored and further housed and fed conventionally during the post-weaning period without antibiotic administration. Body weight and diarrhoea scores were recorded before and after weaning, and blood was sampled at weaning and 1 week later for collecting haematological data. A dynamic model was constructed based on the Gompertz-Makeham law to describe live weight trajectories during the first 75 days after weaning, following the rationale that the animal response is partitioned in two time windows (a perturbation and a recovery window). Model calibration was performed for each animal. Our results show that the transition time between the two time windows, as well as the weight trajectories are characteristic for each individual. The model captured the weight dynamics of animals at different degrees of perturbation, with an average coefficient of determination of 0.99, and a concordance correlation coefficient of 0.99. The utility of the model is that it provides biologically meaningful parameters that inform on the amplitude and length of perturbation, and the rate of animal recovery. Our rationale is that the dynamics of weight inform on the capability of the animal to cope with the weaning disturbance. Indeed, there were significant correlations between model parameters and individual diarrhoea scores and haematological traits. Overall, the parameters of our model can be useful for constructing weaning robustness indexes by using exclusively the growth curves. We foresee that this modelling approach will provide a step forward in the quantitative characterisation of robustness.