Does weight matter? Exploring links between birth weight, growth and pig-directed manipulative behaviour in growing-finishing pigs

Tail status at both individual and pen level affects tail biting victimisation in pigs over the finishing period

Tail biting is a significant welfare problem in commercial pig production. Individual tail health was assessed in non-docked pigs (n = 1 579) on five farms (180-441 pigs and 16-30 pens per farm) at introduction to the finishing unit (W0) and 9 weeks later (W9) to present longitudinal descriptive data, establish risk factors for being tail bitten and investigate possibilities to infer information about W0 tail health based on W9 tail appearance. Tail health was described in terms of posture (hanging), shortening (loss of distal flattening), lesion type (TLT; 0 = no lesion, 1 = minor lesion on intact skin; or with skin penetration 2 = < 0.5 cm, 3 = 0.5-2 cm, or 4 = > 2 cm), length (iL) and change therein from W0 to W9 (ΔL). ΔL may include cumulating information on received tail biting given that the variation was large and negative values were present. The average intact tail measured 22 ± 2.1 and 29 ± 2.3 cm at W0 and W9, respectively, with no effect of sex. Tail lesion prevalence decreased unexpectedly from W0 to W9, possibly due to a docking-like effect in the present population showing a relatively high injury prevalence at W0. Mixed models predicting tail health at W9 were built with pig (n = 1 323-1 492) as statistical unit and pen (n = 94-124) nested within farm as random effects. Pen-level tail appearance at W0 was included as eligible predictors. No model predicted TLT 2,3 or 4 at W9, suggesting that factors other than early tail appearance determined late victimisation. A larger ΔL was predicted by the individual-level factors barrow (vs female), a larger iL, no tail shortening and any other TLT as compared to 4 in the individual at W0; as well as smaller percentage of hanging tails in the pen, a larger average iL in the pen (px̅L) and an interaction between iL and px̅L. According to the interaction effect, two different scenarios predicted a smaller ΔL: smaller iL and px̅L, or especially larger iL and px̅L. The scenarios may be re-targeting of previous victims by individuals accustomed to an environment with tail biting and two-stage tail-biting where the longest tails were the most attractive objects for exploration. We conclude that pigs with better tail health at introduction to the finishing unit receive less injurious biting during 9 weeks. Pen-level tail health has a profound effect that is very different at extremes of tail length. One-fourth of early skin-penetrating tail injuries may not be detectable shortly before slaughter.

Fewer culturable Lactobacillaceae species identified in faecal samples of pigs performing manipulative behaviour

Manipulative behaviour that consists of touching or close contact with ears or tails of pen mates is common in pigs and can become damaging. Manipulative behaviour was analysed from video recordings of 45-day-old pigs, and 15 manipulator-control pairs (n = 30) were formed. Controls neither received nor performed manipulative behaviour. Rectal faecal samples of manipulators and controls were compared. 16S PCR was used to identify Lactobacillaceae species and 16S amplicon sequencing to determine faecal microbiota composition. Seven culturable Lactobacillaceae species were identified in control pigs and four in manipulator pigs. Manipulators (p = 0.02) and females (p = 0.005) expressed higher Lactobacillus amylovorus, and a significant interaction was seen (sex * status: p = 0.005) with this sex difference being more marked in controls. Females (p = 0.08) and manipulator pigs (p = 0.07) tended to express higher total Lactobacillaceae. A tendency for an interaction was seen in Limosilactobacillus reuteri (sex * status: p = 0.09). Results suggest a link between observed low diversity in Lactobacillaceae and the development of manipulative behaviour.

Body Weight Estimation for Pigs Based on 3D Hybrid Filter and Convolutional Neural Network

The measurement of pig weight holds significant importance for producers as it plays a crucial role in managing pig growth, health, and marketing, thereby facilitating informed decisions regarding scientific feeding practices. On one hand, the conventional manual weighing approach is characterized by inefficiency and time consumption. On the other hand, it has the potential to induce heightened stress levels in pigs. This research introduces a hybrid 3D point cloud denoising approach for precise pig weight estimation. By integrating statistical filtering and DBSCAN clustering techniques, we mitigate weight estimation bias and overcome limitations in feature extraction. The convex hull technique refines the dataset to the pig's back, while voxel down-sampling enhances real-time efficiency. Our model integrates pig back parameters with a convolutional neural network (CNN) for accurate weight estimation. Experimental analysis indicates that the mean absolute error (MAE), mean absolute percent error (MAPE), and root mean square error (RMSE) of the weight estimation model proposed in this research are 12.45 kg, 5.36%, and 12.91 kg, respectively. In contrast to the currently available weight estimation methods based on 2D and 3D techniques, the suggested approach offers the advantages of simplified equipment configuration and reduced data processing complexity. These benefits are achieved without compromising the accuracy of weight estimation. Consequently, the proposed method presents an effective monitoring solution for precise pig feeding management, leading to reduced human resource losses and improved welfare in pig breeding.

Effects of Birthweight of Piglets in a Multi-Suckling System on Mortality, Growth Rate, Catch-Up Growth, Feed Intake and Behaviour

Multi-suckling systems aim to improve animal welfare, but in these systems, a large variation is seen in piglet growth rate. Birthweight (BiW) plays an important role in explaining the variation in body weight (BW) gain of piglets. This study aims to investigate the relationships between BiW and piglet traits up to day 44 postpartum (p.p.). A total of 55 sows were used. The growth rate and mortality were assessed for all piglets. Feed and milk intake, behaviours, and skin lesions were assessed in four focal piglets per litter. Focal piglets were divided into four groups based on their BiW class (high BiW (HBiW) vs. low BiW (LBiW)) and growth rate class (fast vs. slow). Results showed that increased mortality was observed in piglets with a BiW below 1.1 kg. Birthweight was positively related with the number of sucklings (β = 2.8 no./kg of BiW per 7.5 h), corresponding to milk intake (β = 102 g/kg of BiW per day), and to a lesser extent, to the intake of sow feed (β = 44 g/kg of BiW per day) in week 6. Birthweight was positively related with the number of skin lesions (β = 4.3 no./kg of BiW) in week 4. We found no indications that fast-growing LBiW piglets differed from fast-growing HBiW piglets, however, fast-growing piglets of both HBiW and LBiW tended to eat more feed (485 ± 18 vs. 420 ± 17 g/day, p = 0.068), were present less often at teats of alien sows (1.1 ± 0.2 vs. 1.8 ± 0.3, p = 0.010), and had more skin lesions (9.0 ± 0.6 vs. 7.4 ± 0.4, p = 0.047), compared to slow growing piglets. Our study, thus, provides little insight into the traits that affect catchup growth in a multi-suckling environment but increases insight into the differences between fast-growing and slow-growing piglets, regardless of their birthweight class.

The Evidence for a Causal Link Between Disease and Damaging Behavior in Pigs

Damaging behaviors (DB) such as tail and ear biting are prevalent in pig production and reduce welfare and performance. Anecdotal reports suggest that health challenges increase the risk of tail-biting. The prevalence of tail damage and health problems show high correlations across batches within and between farms. There are many common risk factors for tail-biting and health problems, notably respiratory, enteric and locomotory diseases. These include suboptimal thermal climate, hygiene, stocking density and feed quality. The prevalence of tail damage and health problems also show high correlations across batches within and between farms. However, limited evidence supports two likely causal mechanisms for a direct link between DB and health problems. The first is that generalized poor health (e.g., enzootic pneumonia) on farm poses an increased risk of pigs performing DB. Recent studies indicate a possible causal link between an experimental inflammation and an increase in DB, and suggest a link between cytokines and tail-biting. The negative effects of poor health on the ingestion and processing of nutrients means that immune-stimulated pigs may develop specific nutrient deficiencies, increasing DB. The second causal mechanism involves tail-biting causing poor health. Indirectly, pathogens enter the body via the tail lesion and once infected, systemic spread of infection may occur. This occurs mainly via the venous route targeting the lungs, and to a lesser extent via cerebrospinal fluid and the lymphatic system. In carcasses with tail lesions, there is an increase in lung lesions, abscessation, arthritis and osteomyelitis. There is also evidence for the direct spread of pathogens between biters and victims. In summary, the literature supports the association between poor health and DB, particularly tail-biting. However, there is insufficient evidence to confirm causality in either direction. Nevertheless, the limited evidence is compelling enough to suggest that improvements to management and housing to enhance pig health will reduce DB. In the same way, improvements to housing and management designed to address DB, are likely to result in benefits to pig health. While most of the available literature relates to tail-biting, we suggest that similar mechanisms are responsible for links between health and other DB.