Tail Biting In Pigs Research Articles

Prevalence of tail damage and ear lesions in docked and undocked pigs during trials to find alternatives to tail docking on Spanish commercial farms.

Tail docking is widely used to control tail biting in pigs, but it is a painful and stressful procedure. The impact of non-docking trials on tail damage (TD) and ear lesions (EL) from weaning to slaughter was assessed on four commercial farms. A total of 898 docked pigs (396 DP) or undocked pigs (502 UP) were assessed for tail damage and ear lesions at the beginning and end of the weaner stage, during fattening and at the abattoir during slaughter. The percentage of UP with shortened tails increased significantly from weaning to fattening, but the percentage of non-inflamed tails and tails without fresh lesions increased. In terms of severity of lesion, a lower percentage of pigs scored as 'no visible lesion' at the end of weaning compared to fattening, both for UP and DP (p<0.05). DP always had a lower percentage of TD, whereas UP had a lower percentage of EL at the end of weaning. It was not possible to statistically compare different preventive strategies trialed on farms as alternatives to docking. This study highlights that combining tail length and lesion score at slaughter could be a reliable on-farm welfare indicator.

Assessing Decision Support Tools for Mitigating Tail Biting in Pork Production: Current Progress and Future Directions.

Tail biting (TB) in pigs is a complex issue that can be caused by multiple factors, making it difficult to determine the exact etiology on a case-by-case basis. As such, it is often difficult to pinpoint the reason, or set of reasons, for TB events, Decision Support Tools (DSTs) can be used to identify possible risk factors of TB on farms and provide suitable courses of action. The aim of this review was to identify DSTs that could be used to predict the risk of TB behavior. Additionally, technologies that can be used to support DSTs, with monitoring and tracking the prevalence of TB behaviors, are reviewed. Using the PRISMA methodology to identify sources, the applied selection process found nine DSTs related to TB in pigs. All support tools relied on secondary information, either by way of the scientific literature or expert opinions, to determine risk factors for TB predictions. Only one DST was validated by external sources, seven were self-assessed by original developers, and one presented no evidence of validation. This analysis better understands the limitations of DSTs and highlights an opportunity for the development of DSTs that rely on objective data derived from the environment, animals, and humans simultaneously to predict TB risks. Moreover, an opportunity exists for the incorporation of monitoring technologies for TB detection into a DST.

Impact of feed, light and access to manipulable material on tail biting in pigs with intact tails

BackgroundTail biting (TB) is a welfare issue with economic consequences due to infections and ill-thrift. This study aimed to reduce tail injuries in a high-performing non-tail-docking pig herd.ResultsDuring eleven years preceding the trial, the annual incidence of tail injuries registered at slaughter in pigs from the herd increased from 3% (equivalent to the national mean) to 10%. It was positively correlated to a high weight gain and negatively correlated to daylight length.The overall incidence of tail injuries during the four years preceding the trial was 9.2% with significant differences between four identically structured buildings for fatteners (I < II < III < IV).The feed was enriched with amino acids, minerals and fibres. The buildings used different illumination strategies, I: standard fluorescent tubes with an invisible flickering light of 30–40% for 14 h daily, II: non-flickering led light for 14 h daily, III (control) and IV: standard fluorescent tubes for 2 h daily. IV had free access to manipulable material (hay-silage), while I–III was offered 100–200 g daily.During the adaptation period (6 months), the incidence of tail injuries decreased significantly in all buildings to a mean of 5.4%. The largest decrease (from 11.4 to 4.3%) was obtained in IV.During the trial period (12 months), the mean incidence of tail injuries decreased in all groups to a mean of 3.0%. There were no differences in treatment incidences of individual pigs due to TB between groups, but the use of enriched pellets due to TB in pens was lowest in II. The low incidence of tail injuries was retained during the post-trial period (6 months) when all buildings used artificial illumination for two hours per day.ConclusionsThe incidence of TB in fast growing non-tail-docked pigs in the herd was successfully reduced by supplementing the feed with amino acids, minerals, vitamins and fibres. Additional manipulable material accelerated that process and non-flickering illumination may have had an impact in preventing TB.The results obtained do not support the need for tail-docking of pigs, provided that the needs of the pigs in terms of feed ingredients, stocking density and access to manipulable materials are fulfilled.

Evaluation of a scheme to identify risks for tail biting in pigs.

The study aimed to assess the effectiveness of a tail-biting risk assessment scheme. The scheme consisted of trained private veterinary practitioners (assessors) applying a risk assessment tool on commercial pig farms to six pens per farm. The assessment tool included animal and non-animal-based observations which were used to determine the perceived risk of tail biting for each pen. For this study 27 farms were assessed, and a subsequent batch of pigs from each farm underwent post-mortem tail lesion scoring at the abattoir. The assessments revealed that a high percentage of pens had fully slatted flooring (92%) and mixed-sex populations (84%), with a significant proportion of pens containing pigs which were all tail docked (92%). Most pens (86%) did not allow all pigs simultaneous access to feeders. Enrichment was present in 88% of the pens, but most (46%) were supplied with only one item, and only 15% offering multiple enrichment types. The study found no significant associations between the risk of tail biting and visible injuries, dirty flanks, or tucked tails, as assessed by the assessors (P > 0.05). Similarly, the risk of tail biting reported per pen was not associated with aggressive, damaging, or exploratory behaviours (P > 0.05). At the abattoir, 96% of pigs' tails exhibited minor skin damage, with only 4% showing moderate to severe damage. Furthermore, no links were found between the scores obtained during slaughter and the risk of tail biting, as reported by the assessors (P < 0.05). Although the tool was useful in identifying several improvements that could be made at farm level in areas such as stocking density, enrichment provision and reducing tail docking, overall the results underscored the need for improved training of assessors, and the challenge of associating management practices and animal based measures with tail-biting risk.

Prediction of tail biting in pigs using partial least squares regression and artificial neural networks

Tail biting in pig farming causes economic losses as well as pain and suffering to the affected pigs. The aim of the study was to predict tail lesions to provide the farmer with the opportunity to intervene early. To do this, tail lesions were recorded during rearing (REA) and fattening (FAT) on two farms (Farm 1: 10 batches REA, 5 batches FAT; Farm 2: 7 batches REA, 4 batches FAT). In addition, tail posture, skin lesions, musculoskeletal system issues, treatment index for suckling, weight at weaning, water consumption, activity time, humidity, NH3 and CO2 concentrations were observed. Processed to daily values forming a time series, these data was used to predict the prevalence of tail lesions per pen using partial least squares (PLS) regression models, focused time-delay neural networks (FTDNN) and nonlinear autoregressive neural networks with exogenous inputs (NARX). After training, validating and testing the methods for Farm 1, the respective methods were applied to the data of Farm 2. In addition, it was investigated whether the prevalence of tail lesions per pen could be predicted for an offset of one to five days before with PLS. The networks were used to test whether a delay of one to five days before should be included for prediction. NARX achieved the best prediction performance on both farms in REA and FAT: accuracy between true and estimated values (R 0.85–0.97), recall (REC 0.63–0.97), false positive rate (FPR 0.01–0.27), precision (PRC 0.43–0.92), F1-score (0.54–0.94) and area under the precision-recall curve (AUPRC 0.66–0.97). PLS (R 0.49–0.81, REC 0.32–0.86, FPR 0.02–0.36, PRC 0.42–0.70, F1-score 0.40–0.77, AUPRC 0.43–0.85) and FTDNN (R 0.45–0.90, REC 0.19–1.00, FPR 0.00–0.97, PRC 0.30–0.84, F1-score 0.28–0.75, AUPRC 0.30–0.86) performed less accurately than NARX but still with sufficient prediction performance, whereby the results for Farm 2 were worse than for Farm 1. Therefore, a generalisation of the methods to other farms is possible. No noticeable difference was observed between offsets 1 to 5 and delays 1 to 5. PLS, FTDNN and NARX with all offsets and delays are suitable for predicting the prevalence of tail lesions per pen in several farms as well as in REA and FAT.

Amino acid supplementation counteracts negative effects of low protein diets on tail biting in pigs more than extra environmental enrichment

Low protein (LP) diets may increase the occurrence of damaging behaviours, like tail biting, in pigs. We investigated the effect of supplementing a LP diet with indispensable amino acids (IAA) or environmental enrichment on tail biting. Undocked pigs (n = 48 groups of 12) received either a normal protein diet (NP), a LP, LP with supplemented IAA (LP+), or LP diet with extra environmental enrichment (LP-E+) during the starter, grower, and finisher phase. Performance, activity, behaviour, and body damage were recorded. LP and LP-E+ had a lower feed intake, growth, and gain-to-feed ratio, and were more active than NP and LP+ pigs. LP-E+ pigs interacted most often with enrichment materials, followed by LP, LP+, and NP pigs. LP pigs showed more tail biting than all other groups during the starter phase and the finisher phase (tendency) compared to NP and LP+ pigs. Thus, LP-E+ only reduced tail biting in the starter phase, whereas LP+ tended to do so throughout. Tail damage was more severe in LP pigs than in NP and LP+, with LP-E+ in between. In conclusion, IAA supplementation was more effective than extra environmental enrichment in countering the negative effects of a low protein diet on tail biting in pigs.

13. Decision support tools for mitigating tail biting in pigs: Analysing methodologies and predictive outputs

13. Decision support tools for mitigating tail biting in pigs: Analysing methodologies and predictive outputs

The importance ofslaughterhouses inmonitoring the occurrence oftail biting inpigs - Review.

Tail biting inpigs represents avery serious problem inmodern pig farming, particularly with the intensification ofthe industry. Itis considered amultifactorial syndrome and can becaused byvarious factors, leading tosignificant economic losses through reduced weight gain and partial ortotal condemnation ofslaughtered carcasses due tosecondary bacterial infections. The aim ofthis article isto summarise the current knowledge regarding tail biting inpigs, with aprimary focus onthe use ofslaughterhouses for evaluating tail lesions and monitoring their prevalence. The introduction addresses the factors influencing the incidence oftail biting inpig farms and prevention strategies. Subsequent sections cover topics such astail docking, the negative effects ofpigtail biting, the advantages and drawbacks ofexamining tail lesions inslaughterhouses, and the methodical procedure for evaluating such lesions. Additionally, the article discusses the relationship between tail lesions and meat inspection findings, aswell asthe prevalence oftail lesions invarious European countries.

Automatic monitoring and detection of tail-biting behavior in groups of pigs using video-based deep learning methods.

Automated monitoring of pigs for timely detection of changes in behavior and the onset of tail biting might enable farmers to take immediate management actions, and thus decrease health and welfare issues on-farm. Our goal was to develop computer vision-based methods to detect tail biting in pigs using a convolutional neural network (CNN) to extract spatial information, combined with secondary networks accounting for temporal information. Two secondary frameworks were utilized, being a long short-term memory (LSTM) network applied to sequences of image features (CNN-LSTM), and a CNN applied to image representations of sequences (CNN-CNN). To achieve our goal, this study aimed to answer the following questions: (a) Can the methods detect tail biting from video recordings of entire pens? (b) Can we utilize principal component analyses (PCA) to reduce the dimensionality of the feature vector and only use relevant principal components (PC)? (c) Is there potential to increase performance in optimizing the threshold for class separation of the predicted probabilities of the outcome? (d) What is the performance of the methods with respect to each other? The study utilized one-hour video recordings of 10 pens with pigs prior to weaning, containing a total of 208 tail-biting events of varying lengths. The pre-trained VGG-16 was used to extract spatial features from the data, which were subsequently pre-processed and divided into train/test sets before input to the LSTM/CNN. The performance of the methods regarding data pre-processing and model building was systematically compared using cross-validation. Final models were run with optimal settings and evaluated on an independent test-set. The proposed methods detected tail biting with a major-mean accuracy (MMA) of 71.3 and 64.7% for the CNN-LSTM and the CNN-CNN network, respectively. Applying PCA and using a limited number of PCs significantly increased the performance of both methods, while optimizing the threshold for class separation did result in a consistent but not significant increase of the performance. Both methods can detect tail biting from video data, but the CNN-LSTM was superior in generalizing when evaluated on new data, i.e., data not used for training the models, compared to the CNN-CNN method.

Identifying Early Indicators of Tail Biting in Pigs by Variable Selection Using Partial Least Squares Regression.

This study examined relevant variables for predicting the prevalence of pigs with a tail lesion in rearing (REA) and fattening (FAT). Tail lesions were recorded at two scoring days a week in six pens in both REA (10 batches, 840 scoring days) and FAT (5 batches, 624 scoring days). To select the variables that best explain the variation within the prevalence of pigs with a tail lesion, partial least squares regression models were used with the variable importance in projection (VIP) and regression coefficients (β) as selection criteria. In REA, five factors were extracted explaining 60.6% of the dependent variable's variance, whereas in FAT five extracted factors explained 62.4% of the dependent variable's variance. According to VIP and β, seven variables were selected in REA and six in FAT with the tail posture being the most important variable. In addition, skin lesions, treatment index in the suckling phase, water consumption (mean), activity time (mean; CV) and exhaust air rate (CV) were selected in REA. In FAT, additional musculoskeletal system issues, activity time (mean; CV) and exhaust air rate (mean; CV) were selected according to VIP and β. The selected variables indicate which variables should be collected in the stable to e.g., predict tail biting.

Can straw based enrichment treat tail biting in pigs?

PICO question&#x0D; Can straw based enrichment be used successfully as a treatment intervention to reduce tail biting injuries in weaner to finisher pigs housed in indoor farming systems?&#x0D; &#x0D; Clinical bottom line&#x0D; Category of research question&#x0D; Treatment&#x0D; The number and type of study designs reviewed&#x0D; Three papers were critically reviewed. All three papers answered the PICO question and matched the inclusion criteria for this Knowledge Summary, providing moderate evidence. One non-randomised controlled trial and two randomised controlled trials.&#x0D; Strength of evidence&#x0D; Moderate&#x0D; Outcomes reported&#x0D; Veit et al. (2016) found that straw based enrichment can reduce tail biting, similarly, Larson et al. (2018) found straw based enrichment could reduce tail biting, however, other factors contribute more so to reducing tail biting. Haigh et al. (2019) did not find evidence to suggest straw-based enrichment could reduce tail biting. Triggers for tail biting injuries are multifaceted, therefore enrichment alone will not eliminate pen mate manipulation&#x0D; Conclusion&#x0D; In view of the strength of evidence and the outcomes from the studies the following conclusions have been made; it is expected that these findings provide enough evidence to encourage farmers to introduce novel straw based enrichment as a treatment measure, however it would be most effective if other husbandry factors could be considered in addition&#x0D; &#x0D; How to apply this evidence in practice&#x0D; The application of evidence into practice should take into account multiple factors, not limited to: individual clinical expertise, patient’s circumstances and owners’ values, country, location or clinic where you work, the individual case in front of you, the availability of therapies and resources.&#x0D; Knowledge Summaries are a resource to help reinforce or inform decision making. They do not override the responsibility or judgement of the practitioner to do what is best for the animal in their care.&#x0D; &#x0D;

Network analysis of tail-biting in pigs – the impact of missed biting events on centrality parameters

AbstractWith social network analysis, group structures of animals can be studied. However, underlying behavioural observations face problems of missing events or deviations between observers. The current study analysed the robustness of node-level network parameters based on tail-biting observations in pigs affected by missed events. Real observations of one observer were used as a gold standard to build true networks and to compare two sets of erroneous networks to them. The first set consisted of networks from different observers of the same data basis. The second set consisted of networks with a fixed error rate (random samples of the gold standard). The stability of the ranking order was used as an indication of accuracy (range 0–1; ≥0.49 good accuracy; ≥0.81 very good accuracy). Comparing observers with true networks yielded overall bad accuracy scores. Generally, outgoing network parameters (active: biting) provided better accuracy scores than ingoing network parameters (passive: being bitten). The results of sampled networks showed decreasing accuracy scores with increasing error rates. At the same error rate, longer observation periods yielded better accuracy scores. For sampled networks, differences between outgoing and ingoing network parameters were more distinct and local parameters (direct contacts) provided better accuracy scores than global parameters (direct and indirect contacts). Overall, sampled networks with 3/10 missed events yielded good to very good accuracy. As networks with more observations handle missed events better, studies of behavioural observations always need to evaluate the required accuracy and feasible workload. The current study gives insights in the accurate estimation of behavioural observations.

Tail-docking and tail biting in pigs: Findings at the slaughterhouse in Portugal

Tail-docking is not accepted by European Union legislation as a routine measure to prevent tail biting in pigs. As part of systematic monitoring of animal welfare there is an increasing interest in recording tail damage in pigs at slaughter to identify problem farms. Tail biting lesions have been associated to causes of total condemnation in postmortem meat inspection. The goals of this study were to assess tail-docking and tail biting in slaughter pigs and to evaluate the association of tail lesions with meat inspection findings. The study was carried out at four pig slaughterhouses in the north of Portugal. Data was collected at the batch level during checks on food chain information, and at ante- and postmortem meat inspection. A total of 196 batches were screened. These batches covered 10,146 pigs: 4090 weaners (132 batches from 62 farms) and 6056 finishing pigs (64 batches from 43 farms). Of all the 196 batches, 88% were classified as tail-docked, corresponding to 100% of batches of finishing pigs and 83% of weaners. Tail lesions were scored according to a 3-level scale. During postmortem inspection, 84% pig carcasses (8566 out of 10,146) presented absence of tail lesions. Mild to moderate tail lesions (13%) were more frequent than severe ones (3%). Tail lesions, both mild and severe, were more prevalent (P>0.001) in weaners (13.1%, 3.5%) than in finishing pigs (12.7%, 2.1%). A total of 169 (1.7%) carcasses were condemned during postmortem inspection with the prevalence being higher in weaners (3.3%) than in finishing pigs (0.6%). The most frequent causes were poor body condition (31.4%), arthritis/polyarthritis (28.4%), and peritonitis (20.1%). No association between severity of tail lesions and postmortem condemnations was observed at the batch level, however a tendency for a higher proportion of postmortem condemnations in docked batches was found among weaners (P = 0.013). Further research with increased sample size and the analysis performed at the animal level is needed in order to confirm the observed tendencies. Recording information on tail lesions at the slaughterhouse is useful to gain information about general herd health, to support risk-based meat inspection and to assist farmers in welfare management plans.

The gut microbiota and microbial metabolites are associated with tail biting in pigs

Tail biting is an abnormal behaviour that causes stress, injury and pain. Given the critical role of the gut-microbiota in the development of behavioural problems in humans and animals, the aim of this study was to determine whether pigs that are biters, victims of tail biting or controls (nine matched sets of pigs) have a different microbiota composition, diversity and microbial metabolite profile. We collected faecal and blood samples from each individual for analysis. The gut microbiota composition was most different between the biter and the control pigs, with a higher relative abundance of Firmicutes in tail biter pigs than the controls. Furthermore, we detected differences in faecal and plasma short chain fatty acids (SCFA) profiles between the biter and victim pigs, suggesting physiological differences even though they are kept in the same pen. Thus, in addition to supporting an association between the gut microbiota and tail biting in pigs, this study also provides the first evidence of an association between tail biting and SCFA. Therefore, further research is needed to confirm these associations, to determine causality and to study how the SCFA profiles of an individual play a role in the development of tail biting behaviour.

Network analysis of tail-biting in pigs – indirect effect on tail posture

Tail-biting in pigs compromises animal health and animal welfare, thus, early indicators of an outbreak must be discovered before severe tail lesions occur. Tail posture is one of these promising indicators. The individual animal's behaviour is affected by the group structure, which can be investigated using social networks. Therefore, this study analysed the effect of the group structure of tail-biting pigs on tail posture using pig-level social network parameters. Detailed behavioural observations of 6 pens with 24 undocked pigs per pen four days before a tail-biting outbreak were the data basis. The effect of ingoing network parameters (weighted in-degree, weighted ingoing closeness) on binary tail posture (0: raised, 1: lowered) was tested as covariates in generalised linear mixed models. The pen (1-6), day (t-1 to t-4), hour (10:00 h – 17:00 h), location (at the trough, not at the trough) and receiver (received tail-directed behaviour in the previous 20 min, received no tail-directed behaviour in the previous 20 min) were used as fixed effects. Additional to the fixed effect receiver (p < 0.05), the probability of a lowered tail posture increased with higher values of weighted in-degree (p < 0.05) if less than 40 min passed between the tail-biting and the tail posture observation. If the tail-biting event was 40 to 120 min before the tail posture observation, the probability of a lowered tail posture increased with higher values of weighted ingoing closeness (p < 0.05). Furthermore, the location in the pen (p < 0.05) and the interaction between pen and day (p < 0.05) affected the tail posture significantly. Thus, the group structure of tail-biting pigs has a prolonged influence on tail posture. For this reason, the tail posture is a practicable indicator of tail-biting if monitored regularly.

Tail-Biting in Pigs: A Scoping Review.

Simple SummaryTail-biting in commercial pig-rearing facilities is a welfare concern. Serious outbreaks may occur sporadically, particularly in the grower-finisher stage of production. A scoping review was undertaken to determine if there is general agreement on the common risk factors and appropriate intervention strategies of tail-biting. Online databases were explored for relevant articles and information was extracted from the articles based on predetermined questions. Important risk factors varied between studies, as did successful interventions. The provision of rooting material to alleviate a pig’s innate exploratory behavior was determined to be a common prevention/intervention strategy. Deciphering between risk factors and interventions in the literature was not always possible. Overall, the cause of tail-biting was determined to be multifactorial.Tail-biting is globally recognized as a welfare concern for commercial swine production. Substantial research has been undertaken to identify risk factors and intervention methods to decrease and understand this vice. Tail-biting appears to be multifactorial and has proven difficult to predict and control. The primary objective of the scoping review was to identify and chart all available literature on the risk factors and interventions associated with tail-biting in pigs. A secondary objective was to identify gaps in the literature and identify the relevance for a systematic review. An online literature search of four databases, encompassing English, peer-reviewed and grey literature published from 1 January 1970 to 31 May 2019, was conducted. Relevance screening and charting of included articles were performed by two independent reviewers. A total of 465 citations were returned from the search strategy. Full-text screening was conducted on 118 articles, with 18 being excluded in the final stage. Interventions, possible risk factors, as well as successful and unsuccessful outcomes were important components of the scoping review. The risk factors and interventions pertaining to tail-biting were inconsistent, demonstrating the difficulty of inducing tail-biting in an experimental environment and the need for standardizing terms related to the behavior.

Understanding the financial impact of tail biting in pigs: a step towards a non-docking policy.

Understanding the financial impact of tail biting in pigs: a step towards a non-docking policy.

Difference in exploration and use of PET bottle and horseshoe for environment enrichment in piglets

Article Details: Received: 2020-10-20 | Accepted: 2020-11-27 | Available online: 2021-01-31 https://doi.org/10.15414/afz.2021.24.mi-prap.62-66 Abstract Attractivity of two different enrichment objects was investigated in paper. Eight piglets were housed in pen with slatted floor. Pen environment was enriched with two hanging objects – PET bottle and horseshoe. Interactions with enrichment objects were evaluated during two consecutive days. PET bottle was more attractive, total number of interactions was 600 on day 1 and 451 on day 2. Horseshoe has very low attractiveness, number of interactions on day 1 was only 64 and 74 on day 2. Exploration of more attractive object was decreasing between days. Exploration of less attractive object was increasing. We recommend use of different enrichment objects for prolonged duration of exploration and occupation by manipulation, but both objects should be attractive for piglets. Keywords: environment, enrichment, piglets, keyword, keyword References Averos, X., et al. (2010). A meta-analysis of the combined effect of housing and environmental enrichment characteristics on the behaviour and performance of pigs. Applied Animal Behaviour Science , 127(3-4), 73–85. https://doi.org/10.1016/j.applanim.2010.09.010 Bolt, S. L. and George, A. J. (2019). The use of environmental enrichment on farms benefits animal welfare and productivity. Livestock, 24(4), 183–188. https://doi.org/10.12968/live.2019.24.4.183 Buijs, S. and Muns, R. (2019). A Review of the Effects of Non-Straw Enrichment on Tail Biting in Pigs. Animals , 9(10), 824. https://doi.org/10.3390/ani9100824 Chen, Ch. et al. (2020). A computer vision approach for recognition of the engagement of pigs with different enrichment objects. Computers and Electronics in Agriculture , 175, 105580. https://doi.org/10.1016/j.compag.2020.105580 Council directive 2008/120/EC of 18 December 2008 laying down minimum standards for the protection of pigs. Available online: http://data.europa.eu/eli/dir/2008/120/2019-12-14 (accessed on 15 October 2020). Elkmann, A. and Hoy, S. (2009). Frequency of occupation with different simultaneously offered devices by fattening pigs kept in pens with or without straw. Livestock Science, 124(1-3), 330–334. https://doi.org/10.1016/j.livsci.2008.12.008 Ernst, K. et al. (2018). Play behavior and environmental enrichment in pigs. Available online: https://www.wur.nl/upload_mm/e/f/b/6af2e2db-430e-4771-8f7d-6f5b974eab5e_final%20report%20ACT%202060%20juli%202018%20op%20website%20.pdf (accessed on 10 October 2020). Godyn, D. et al. (2019). Effects of environmental enrichment on pig welfare-A Review. Animals , 9(6), 383. https://doi.org/10.3390/ani9060383 Jensen, P. (2002). The ethology of domestic animals . New York: CABI Publishing. Wood-Gush, D. G. M. and Beilharz, R. G. (1983). The enrichment of a bare environment for animals in confined conditions. Applied Animal Ethology , 10(3), 209–217. https://doi.org/10.1016/0304-3762(83)90142-6 Young, R. J. (2003). Enrichment for captive animals . Oxford, UK: Blackwell Science Ltd.

Maternal and direct genetic parameters for tail length, tail lesions, and growth traits in pigs.

Tail length and tail lesions are the major triggers for tail biting in pigs. Against this background, 2 datasets were analyzed to estimate genetic parameters for tail characteristics and growth traits. Dataset 1 considered measurements for trait tail length (T-LEN) and for the growth traits birth weight (BW), weaning weight (WW), postweaning weight (PWW), and average daily gain (ADG) from 9,348 piglets. Piglets were born in the period from 2015 to 2018 and kept on the university Gießen research station. Dataset 2 included 4,943 binary observations from 1,648 pigs from the birth years 2016 to 2019 for tail lesions (T-LES) as indicators for nail necrosis, tail abnormalities, or tail biting. T-LES were recorded at 30 ± 7 d after entry for rearing (T-Les-1), at 50 ± 7 d after entry for rearing (end of the rearing period, T-LES-2), and 130 ± 20 d after entry for rearing (end of fattening period, T-LES-3). Genetic statistical model evaluation for dataset 1 based on Akaike's information criterion and likelihood ration tests suggested multiple-trait animal models considering covariances between direct and maternal genetic effects. The direct heritability for T-LEN was 0.42 (±0.03), indicating the potential for genetic selection on short tails. The maternal genetic heritability for T-LEN was 0.05 (±0.04), indicating the influence of uterine characteristics on morphological traits. The negative correlation between direct and maternal effects for T-LEN of -0.35 (±0.13), as well as the antagonistic relationships (i.e., positive direct genetic correlations in the range from 0.03 to 0.40) between T-LEN with the growth traits BW, WW, PWW, and ADG, complicate selection strategies and breeding goal definitions. The correlations between direct effects for T-LEN and maternal effects for breeding goal traits, and vice versa, were positive but associated with a quite large SE. The heritability for T-LES when considering the 3 repeated measurements was 0.23 (±0.04) from the linear (repeatability of 0.30) and 0.21 (±0.06; repeatability of 0.29) from the threshold model. The breeding value correlations between T-LES-3 with breeding values from the repeatability models were quite large (0.74 to 0.90), suggesting trait lesion recording at the end of the rearing period. To understand all genetic mechanisms in detail, ongoing studies are focusing on association analyses between T-LEN and T-LES, and the identification of tail biting from an actor's perspective.

Tail-directed behaviour in pigs – relation to tail posture and tail lesion

Tail-biting in pigs affects the health and welfare of the animals. Different indicators, such as the tail posture, can be used to detect tail-biting at an early stage. The aim of this study was to investigate the effect of tail-directed behaviour, differentiating between tail-biting and tail-in-mouth behaviour, on tail lesions and tail posture of 6 groups of 24 undocked piglets in identical pens using detailed behavioural observations of the four days (t-1 to t-4) before a tail-biting outbreak. Tail lesions were scored twice a week. The tail posture and the tail-directed behaviour were recorded using video observation. Generalised linear mixed models were used separately for tail-biting and tail-in-mouth behaviour to test the influence of the number of receiving (RT) or performing (PT) tail-directed behaviour on the multinomial tail lesions (0: no tail lesion, 1: superficial tail lesion, 2: small or large tail lesion) and to test the influence of RT and PT and the fixed effects of pen (1-6), day (t-1 to t-4), hour (10:00 h – 17:00 h), location (at the trough, not at the trough) and receiver (received tail-directed behaviour in the previous 20 min, received no tail-directed behaviour in the previous 20 min) on the binary tail posture (0: raised tail posture, 1: lowered tail posture). For the tail-biting behaviour dataset, the results showed that piglets with a higher RT had significantly more severe tail lesions (p < 0.05). For the tail-in-mouth behaviour dataset, RT had a significant but reversed effect on tail lesion (p < 0.05). Tail-in-mouth behaviour had no significant influence on tail posture. The probability of a lowered tail posture was significantly higher for piglets that had been tail-bitten in the previous 20 min compared to piglets that had not been tail-bitten (p < 0.05). With an added time offset between the tail-biting behaviour observation and the tail posture observation, the effect of being tail-bitten was still significant for the time offsets of 20–60 min and 100 min (p < 0.05). The day and position in the pen had a significant effect on tail posture as well (p < 0.05). Thus, tail-biting influenced the tail posture and the lasting effect facilitates the use of the tail posture as an indicator for tail-biting.