ArticleAnimals : an open access journal from MDPI2019
Prediction of Tail Biting Events in Finisher Pigs from Automatically Recorded Sensor Data.
Article in Animals : an open access journal from MDPI, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- A Systematic Review on Validated Precision Livestock Farming Technologies for Pig Production and Its Potential to Assess Animal Welfare.Frontiers in veterinary science · 2021Pooled it
- Feeding of Undocked Pigs: Effects of Feed Components and Feed Composition.Animals : an open access journal from MDPI · 2026Review
- ASAS-NANP Symposium: Mathematical modeling in animal nutrition: revolutionizing animal farming with artificial intelligence: trends, challenges, and opportunities.Journal of animal science · 2026Review
- Risk factors for signs of tail biting in intact-tailed weaner pigs: A cross-sectional study.Animal welfare (South Mimms, England) · 2026Article
- Detecting tail biters by monitoring pig screams in weaning pigs.Scientific reports · 2024Article
- Farmers' Perspectives of the Benefits and Risks in Precision Livestock Farming in the EU Pig and Poultry Sectors.Animals : an open access journal from MDPI · 2023Review
- Machine learning algorithms can predict tail biting outbreaks in pigs using feeding behaviour records.PloS one · 2023Article
- Identifying Early Indicators of Tail Biting in Pigs by Variable Selection Using Partial Least Squares Regression.Animals : an open access journal from MDPI · 2022Article
- Automatic monitoring and detection of tail-biting behavior in groups of pigs using video-based deep learning methods.Frontiers in veterinary science · 2022Article
- Use of drinkers by finisher pigs depend on drinker location, pig age, time of day, stocking density and tail damage.Frontiers in veterinary science · 2022Article
- Understanding German Pig Farmers' Intentions to Design and Construct Pig Housing for the Improvement of Animal Welfare.Animals : an open access journal from MDPI · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Tail biting in pigs is an animal welfare problem, and tail biting should be prevented from developing into tail damage. One strategy could be to predict events of tail biting so that the farmer can make timely interventions in specific pens. In the current investigation, sensor data on water usage (water flow and activation frequency) and pen temperature (above solid and slatted floor) were included in the development of a prediction algorithm for tail biting. Steps in the development included modelling of data sources with dynamic linear models, optimisation and training of artificial neural networks and combining predictions of the single data sources with a Bayesian ensemble strategy. Lastly, the Bayesian ensemble combination was tested on a separate batch of finisher pigs in a real-life setting. The final prediction algorithm had an AUC > 0.80, and thus it does seem possible to predict events of tail biting from already available sensor data. However, around 30% of the no-event days were false alarms, and more event-specific predictors are needed. Thus, it was suggested that farmers could use the alarms to point out pens that need greater attention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.