Tail biting is a serious animal welfare and economic problem in pig production. Tail docking, which reduces but does not eliminate tail biting, remains widespread. However, in the EU tail docking may not be used routinely, and some ‘alternative’ forms of pig production and certain countries do not allow tail docking at all. Against this background, using a novel approach focusing on research where tail injuries were quantified, we review the measures that can be used to control tail biting in pigs without tail docking. Using this strict criterion, there was good evidence that manipulable substrates and feeder space affect damaging tail biting. Only epidemiological evidence was available for effects of temperature and season, and the effect of stocking density was unclear. Studies suggest that group size has little effect, and the effects of nutrition, disease and breed require further investigation. The review identifies a number of knowledge gaps and promising avenues for future research into prevention and mitigation. We illustrate the diversity of hypotheses concerning how different proposed risk factors might increase tail biting through their effect on each other or on the proposed underlying processes of tail biting. A quantitative comparison of the efficacy of different methods of provision of manipulable materials, and a review of current practices in countries and assurance schemes where tail docking is banned, both suggest that daily provision of small quantities of destructible, manipulable natural materials can be of considerable benefit. Further comparative research is needed into materials, such as ropes, which are compatible with slatted floors. Also, materials which double as fuel for anaerobic digesters could be utilised. As well as optimising housing and management to reduce risk, it is important to detect and treat tail biting as soon as it occurs. Early warning signs before the first bloody tails appear, such as pigs holding their tails tucked under, could in future be automatically detected using precision livestock farming methods enabling earlier reaction and prevention of tail damage. However, there is a lack of scientific studies on how best to respond to outbreaks: the effectiveness of, for example, removing biters and/or bitten pigs, increasing enrichment, or applying substances to tails should be investigated. Finally, some breeding companies are exploring options for reducing the genetic propensity to tail bite. If these various approaches to reduce tail biting are implemented we propose that the need for tail docking will be reduced.

Large-scale phenotyping of animal behaviour traits is time consuming and has led to increased demand for technologies that can automate these procedures. Automated tracking of animals has been successful in controlled laboratory settings, but recording from animals in large groups in highly variable farm settings presents challenges. The aim of this review is to provide a systematic overview of the advances that have occurred in automated, high throughput image detection of farm animal behavioural traits with welfare and production implications. Peer-reviewed publications written in English were reviewed systematically following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After identification, screening, and assessment for eligibility, 108 publications met these specifications and were included for qualitative synthesis. Data collected from the papers included camera specifications, housing conditions, group size, algorithm details, procedures, and results. Most studies utilized standard digital colour video cameras for data collection, with increasing use of 3D cameras in papers published after 2013. Papers including pigs (across production stages) were the most common (n = 63). The most common behaviours recorded included activity level, area occupancy, aggression, gait scores, resource use, and posture. Our review revealed many overlaps in methods applied to analysing behaviour, and most studies started from scratch instead of building upon previous work. Training and validation sample sizes were generally small (mean±s.d. groups = 3.8±5.8) and in data collection and testing took place in relatively controlled environments. To advance our ability to automatically phenotype behaviour, future research should build upon existing knowledge and validate technology under commercial settings and publications should explicitly describe recording conditions in detail to allow studies to be reproduced.

The objective of the study was to estimate genetic correlations between skin lesions and aggressive behavior postmixing and under more stable social conditions as a potential means of selecting against pig aggressiveness. Postmixing aggression in commercial pig production is common, compromises welfare and profitability, and cannot be significantly reduced by low-cost changes to the environment. A genetic component to individual aggressiveness has been described in pigs and other species. Selective breeding against aggressiveness ought to be possible if an easily measured indicator trait can be shown to be genetically associated with aggressive behavior. Aggressive behavior was recorded continuously for 24 h after mixing, and a count of skin lesions (lesion count, LC) was recorded at 24 h and 3 wk postmixing on 1,663 pigs. Two behavioral traits were found to have a moderate to high heritability similar to that of growth traits; duration of involvement in reciprocal fighting (0.43 ± 0.04) and delivery of nonreciprocal aggression (NRA; 0.31 ± 0.04), whereas receipt of NRA had a lower heritability (0.08 ± 0.03). Genetic correlations (r_g) suggested that lesions to the anterior region of the body 24 h after mixing were associated with reciprocal fighting (r_g = 0.67 ± 0.04), receipt of NRA (r_g = 0.70 ± 0.11), and to a lesser extent, delivery of NRA (r_g = 0.31 ± 0.06). Lesions to the center and rear were primarily genetically associated with receipt of NRA (r_g = 0.80 ± 0.05, 0.79 ± 0.05). Genetic correlations indicated that pigs that engaged in reciprocal fighting delivered NRA to other animals (r_g = 0.84 ± 0.04) but were less likely to receive NRA themselves (r_g = −0.41 ± 0.14). A genetic merit index using lesions to the anterior region as one trait and those to the center or rear or both as a second trait should allow selection against animals involved in reciprocal fighting and the delivery of NRA. Positive correlations between LC 24 h and 3 wk after mixing were found, especially for lesions to the center and rear of the body, indicating that postmixing lesions are predictive of those received under more stable group conditions. As well as reducing immediate aggression at mixing, selection on postmixing LC is expected to have a long-term impact on injuries from aggression, even after dominance relationships are established. Copyright © 2009. .

Tail biting is a major welfare and economic problem for indoor pig producers worldwide. Low tail posture is an early warning sign which could reduce tail biting unpredictability. Taking a precision livestock farming approach, we used Time-of-flight 3D cameras, processing data with machine vision algorithms, to automate the measurement of pig tail posture. Validation of the 3D algorithm found an accuracy of 73.9% at detecting low vs. not low tails (Sensitivity 88.4%, Specificity 66.8%). Twenty-three groups of 29 pigs per group were reared with intact (not docked) tails under typical commercial conditions over 8 batches. 15 groups had tail biting outbreaks, following which enrichment was added to pens and biters and/or victims were removed and treated. 3D data from outbreak groups showed the proportion of low tail detections increased pre-outbreak and declined post-outbreak. Pre-outbreak, the increase in low tails occurred at an increasing rate over time, and the proportion of low tails was higher one week pre-outbreak (-1) than 2 weeks pre-outbreak (-2). Within each batch, an outbreak and a non-outbreak control group were identified. Outbreak groups had more 3D low tail detections in weeks -1, +1 and +2 than their matched controls. Comparing 3D tail posture and tail injury scoring data, a greater proportion of low tails was associated with more injured pigs. Low tails might indicate more than just tail biting as tail posture varied between groups and over time and the proportion of low tails increased when pigs were moved to a new pen. Our findings demonstrate the potential for a 3D machine vision system to automate tail posture detection and provide early warning of tail biting on farm.