Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity - Rosengart, Stephan; Chuppava, Bussarakam; Trost, Lea-Sophie; Henne, Hubert; Tetens, Jens; Traulsen, Imke; Deermann, Ansgar; Wendt, Michael; Visscher, Christian (Frontiers in Veterinary Science, 2022)
Precision livestock farming can combine sensors and complex data to provide a simple score that is meaningful productivity, pig welfare and farm sustainability which are the main drivers of modern pig production. To take account of these drivers, we assigned 697 hybrid (BHZP db.Viktoria) sows to four parity groups. In addition, by pooling clinical findings from every sow and their piglets, sows were classified into three groups for the annotation: healthy, clinically suspicious and diseased. Besides, the udder was thermographed and performance data were documented. Results showed that the piglets of diseased sows with eighth or higher parity had the lowest daily weight gain (healthy; 192g±31.2, clinically suspicious; 191g±31.3, diseased; 148g±50.3 (p < 0.05)) and sows had the highest number of stillborn piglets (healthy (n); 2.2±2.39, clinically suspicious; 2.0±1.62, diseased; 3.91±4.93). Moreover, all diseased sows showed higher maximal skin temperatures by infrared thermography of the udder (p < 0.05). Thus, thermography coupled with Artificial Intelligence (AI) systems can help in identifying and orienting diagnosis of symptomatic animals to prompt adequate reaction at the earliest. With these insights, precision livestock farming innovations can be developed to enhance animal welfare and animal health care in pig production in the future.