Kyriazakis, IliasAlameer, AliBucková, KatarínaMuns, Ramon2023-02-022023-02-022023-01-04Kyriazakis, I., Alameer, A., Bučková, K. and Muns, R. (2023) ‘Toward the automated detection of behavioral changes associated with the post-weaning transition in pigs’, Frontiers in Veterinary Science. Frontiers Media SA. Available at: https://doi.org/10.3389/fvets.2022.1087570.2297-1769 (electronic)https://doi.org/10.3389/fvets.2022.1087570Publication history: Accepted - 7 December 2022; Published - 4 January 2023.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.en© 2023 Kyriazakis, Alameer, Buˇcková and Muns. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.behaviordrinkingearly warningfeedingmachine learningpigspost-weaning diarrheaswineArticle