Adding value to food chain information: using data on pig welfare and antimicrobial use on-farm to predict meat inspection outcomes

Assessment of pig welfare at slaughterhouse level: A systematic review of animal-based indicators suitable for inclusion in monitoring protocols

Pig welfare constitutes a strategic pillar of sustainability within the pork industry. Consequently, there is a need to identify, develop and/or validate indicators for assessing pig wellbeing under commercial conditions. A systematic review following PRISMA guidelines identified 95 pig welfare indicators (PWIs) categorized into physiological, behavioral, health and post-mortem, and product quality. The review evaluated their validity and feasibility (V&F) for use in abattoirs to measure welfare during transport and slaughter. Thirty V&F indicators were found: one physiological (body temperature), 12 behavioral (human-animal relationship, aggression, falling, vocalization, slipping, panting, lying down, sitting, turning back), 13 health and post-mortem (presence of entry points, hernias, body lesions, ear lesions, tail lesions, pericarditis, pneumonia, bursitis, lameness, dead animals, walking and non-walking animals), and four product quality (pH, bruises, body condition, carcass weight). This information might help to identify the factors that affect the risk level of particular pig welfare problems, thereby aiding in the application of risk-based strategies.

An Integrated Analysis of Abattoir Lung Lesion Scores and Antimicrobial Use in Italian Heavy Pig Finishing Farms

Respiratory diseases significantly affect intensive pig finishing farms, causing production losses and increased antimicrobial use (AMU). Lesion scoring at slaughter has been recognized as a beneficial practice to evaluate herd management. The integrated analysis of abattoir lesion scores and AMU data could improve decision-making by providing feedback to veterinarians and farmers on the effectiveness of antimicrobial treatments, thus rationalizing their use. This study compared lung and pleural lesion scores collected at Italian pig slaughterhouses with on-farm AMU, estimated through a treatment index per 100 days (TI100). Overall, 24,752 pig carcasses, belonging to 236 batches from 113 finishing farms, were inspected. Bronchopneumonia and chronic pleuritis were detected in 55% and 48% of the examined pigs, respectively. Antimicrobials were administered in 97% of the farms during the six months prior to slaughter (median TI100 = 5.2), notwithstanding compliance with the mandatory withdrawal period. EMA category B (critical) antimicrobials were administered in 15.2% of cases (median TI100 = 0.06). The lung score was not associated with the total AMU, but significant, positive associations were found with the past use of critical antimicrobials (p = 0.041) and macrolides (p = 0.044). This result highlights the potential of abattoir lung lesion monitoring to rationalize antimicrobial stewardship efforts, contributing to AMU reduction.

Relationship between animal-based on-farm indicators and meat inspection data in pigs

BACKGROUND

This study aimed to validate slaughterhouse indicators collected during meat inspection as an alternative to on-farm animal welfare indicators. For this purpose, the assessments of twelve on-farm and seven slaughterhouse indicators of 628 pigs from three different farms were combined into three indices, differentiated between on-farm and slaughterhouse: (1) limb health, (2) other organ health, and (3) respiratory health. At first, an assessment at animal-level using agreement parameters was carried out to ascertain whether the same welfare or health issues were identified on-farm and at slaughterhouse, taking the production period (farrowing, rearing and fattening period) and the last weeks before slaughtering into account. Second, the connection of slaughterhouse findings on the individual on-farm health indices was examined using logistic regressions, to determine whether certain welfare issues can be better monitored using slaughterhouse indicators.

RESULTS

Acceptable agreement was determined using the Prevalence-Adjusted Bias-Adjusted Kappa (PABAK) for the farrowing and fattening period, but not for the rearing period. A more detailed analysis of the weeks before slaughter shows that there is still a poor agreement 8 weeks before slaughter and an acceptable agreement 4 weeks before slaughter. This indicated the slaughterhouse indicators pneumonia, pleuritis and pericarditis as possible estimators of fever and deviant behavior on-farm and the slaughterhouse indicators bursitis and joint inflammations as possible estimators of lameness. In the second part of the analysis, the connection of slaughterhouse findings on the individual on-farm health indices was investigated; a significant influence of the farm on the limb and respiratory indices and no significant influence of the slaughterhouse findings could be determined, provided that all weekly assessments during the lifetime of the pigs have been taken into account. However, an influence of the slaughterhouse findings on the respiratory index and on the other organ index could be determined if only the weekly assessments four and eight weeks before slaughter, respectively, were taken into account.

CONCLUSIONS

In general, the possible suitable indicators detected by the PABAK, could replace some health-related indicators but a complete substitution of on-farm welfare assessment is not possible. In addition, the traceability over time must be investigated further.

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.

Combining computer vision score and conventional meat quality traits to estimate the intramuscular fat content using machine learning in pigs

Intramuscular fat content (IMF%) is an important factor that affects the quality of pork. The traditional testing method (Soxhlet extraction) is accurate; however, it has a long preprocessing time. In this study, a total of 1481 photographs of 200 pigs' loin muscles were used to obtain a computer vision score (IIMF %). Then, actual IMF%, meat color, marbling score, pH value, and drip loss of 200 pigs were measured. Stepwise regression (SR) and gradient boosting machine (GBM) were used to construct the estimation model of IMF%. The results showed that the correlation coefficients between IMF% and IIMF%, marbling score, backfat thickness, percentage of moisture (POM), and pH value were 0.68, 0.64, 0.48, 0.45, and 0.25, respectively. The model accuracies of SR and GBM base on residuals distribution were 0.875 and 0.89, respectively. This study presents a method for estimating IMF% using computer vision technology and meat quality traits.