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Automated detection and scoring of pleurisy in Norwegian slaughtered pigs: a field trial

AI-driven tools have the potential to enhance disease surveillance, reduce observer variability, and facilitate large-scale data collection in slaughterhouse environments.

26 March 2026
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Abattoirs provide a valuable opportunity to assess the impact of porcine pleuropneumonia, as lesions caused by Actinobacillus pleuropneumoniae remain visible at postmortem inspections.

Objective: This study evaluated an artificial intelligence (AI)-based system for scoring pleurisy in slaughtered pigs under field conditions.

Methods: The trial was conducted in a Norwegian abattoir, where a collaborative robot automatically captured carcass images. A convolutional neural network assessed pleurisy according to the “Pleurisy Evaluation on the Parietal Pleura” method. In parallel, veterinarians and meat inspectors from the Norwegian Food Safety Authority scored pleurisy using a binary system, based on the presence or absence of lesions exceeding 15 cm. Moreover, a subset of 500 images were scored by two academic veterinarians (one has been working for decades in farm animals' pathology, and the other is a PhD student studying farm animals’ respiratory pathology) using the “Pleurisy Evaluation on the Parietal Pleura” method. The same veterinarians recorded lesions larger than 15 cm.

Results: The AI system detected pleurisy in 9.80 % of pigs, demonstrating high specificity and sensitivity (>95 %) compared with veterinary assessments of digital images. Norwegian meat inspection staff reported pleurisy in 5.18 % of pigs, showing a moderately strong correlation with the AI system (Spearman's ρ = 0.67). Very large lesions were identified in 3.4–4.6 % of digital images by veterinarians. Prevalence results aligned with historical data, being consistent with the high health status of Norwegian pig herds. Lesions were mainly located on the caudal chest wall, supporting Actinobacillus pleuropneumoniae as a major causative agent.

Conclusion: This study highlights the potential of AI-driven tools to enhance disease surveillance, reduce observer variability, and facilitate large-scale data collection in slaughterhouse environments.

Romano A, Golunova E, Marruchella G, Dondona AC, Bernabò N, Del Negro E, Pettinella S, Naadland SS, Jensen AD, Alvseike OA, Nagel-Alne GE. Automated detection and scoring of pleurisy in Norwegian slaughtered pigs: a field trial, Food Control, Volume 178, 2025, 111514, ISSN 0956-7135. https://doi.org/10.1016/j.foodcont.2025.111514.

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