Toward the automated detection of behavioral changes associated with the post-weaning transition in pigs

Abstract

We modified an automated method capable of quantifying behaviors which we then applied to the changes associated with the post-weaning transition in pigs. The method is data-driven and depends solely on video-captured image data without relying on sensors or additional pigmarkings. It was applied to video images generated from an experiment during which post-weaned piglets were subjected to treatments either containing or not containing in- feed antimicrobials (ZnO or antibiotics). These treatments were expected to a􀀀ect piglet performance and health in the short-term by minimizing the risk from post-weaning enteric disorders, such as diarrhea. The method quantified total group feeding and drinking behaviors as well as posture (i.e., standing and non-standing) during the first week post-weaning, when the risk of post- weaning diarrhea is at its highest, by learning from the variations within each behavior using datamanually annotated by a behavioral scientist. Automatically quantified changes in behavior were consistent with the e􀀀ects of the absence of antimicrobials on pig performance and health, and manifested as reduced feed e ciency and looser feces. In these piglets both drinking and standing behaviors were increased during the first 6 days post-weaning. The correlation between fecal consistency and drinking behavior 6 days post weaning was relatively high, suggesting that these behaviors may have a diagnostic value. The presence or absence of in-feed antimicrobials had no e􀀀ect on feeding behavior, which, however, increased over time. The approach developed here is capable of automaticallymonitoring several di􀀀erent behaviors of a group of pigs at the same time, and potentially thismay be where its value as a diagnostic tool may lie.