ArticleScientific reports2024
Detecting tail biters by monitoring pig screams in weaning pigs.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- A Conformer-Based Time-Frequency Decoupling Network for Pig Vocalization Behavior Classification.Animals : an open access journal from MDPI · 2026Article
- Feeding of Undocked Pigs: Effects of Feed Components and Feed Composition.Animals : an open access journal from MDPI · 2026Review
- Advances in Audio Classification and Artificial Intelligence for Respiratory Health and Welfare Monitoring in Swine.Biology · 2026Review
- BCST-GCN: a skeleton-based spatiotemporal graph convolutional network with bidirectional cross-attention for pig behavior recognition.Frontiers in veterinary science · 2026Article
- Framework for Classification of Fattening Pig Vocalizations in a Conventional Farm with High Relevance for Practical Application.Animals : an open access journal from MDPI · 2025Article
- Review: Gut Microbiota-A Powerful Tool for Improving Pig Welfare by Influencing Behavior Through the Gut-Brain Axis.Animals : an open access journal from MDPI · 2025Review
- The Economic Implications of Phasing Out Pig Tail Docking: A Pilot Study in Italy.Animals : an open access journal from MDPI · 2025Article
- A review of sound-based pig monitoring for enhanced precision production.Journal of animal science and technology · 2025Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Early identification of tail biting and intervention are necessary to reduce tail lesions and their impact on animal health and welfare. Removal of biters has become an effective intervention strategy, but finding them can be difficult and time-consuming. The aim of this study was to investigate whether tail biting and, in particular, individual biters could be identified by detecting pig screams in audio recordings. The study included 288 undocked weaner pigs housed in six pens in two batches. Once a tail biter (n = 7) was identified by visual inspection in the stable and removed by the farm staff, the previous days of video and audio recordings were analyzed for pig screams (sudden increase in loudness with frequencies above 1 kHz) and tail biting events until no biting before the removal was observed anymore. In total, 2893 screams were detected in four pens where tail biting occurred. Of these screams, 52.9% were caused by tail biting in the observed pen, 25.6% originated from other pens, 8.8% were not assignable, and 12.7% occurred due to other reasons. In case of a tail biting event, screams were assigned individually to biter and victim pigs. Based on the audio analysis, biters were identified between one and nine days prior to their removal from the pen after visual inspection. Screams were detected earlier than the increase in hanging tails and could therefore be favored as an early warning indicator. Analyzing animal vocalization has potential for monitoring and early detection of tail biting events. In combination with individual marks and automatic analysis algorithms, biters could be identified and tail biting efficiently reduced. In this way, biters can be removed earlier to increase animal health and welfare.
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Registered trials
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