Introduction in 2017–2019 of the new EU legislation on official controls in food production allowed use of computer vision systems (CVSs) as complementary tools in meat inspection of bovines, pigs and poultry. A systematic literature review was performed to identify and analyse relevant articles reporting on the performances of CVSs used in abattoirs for ante- and post-mortem veterinary inspection and meat safety assurance, including systems for detecting carcass/organ contamination and lesions. In this review, 62 articles were identified and analysed. There were 35 articles reporting on CVS performance in the detection of carcass/organ lesions and 27 in the detection of carcass contamination. CVSs for broiler chicken, pig and bovine meat safety assurance were reported in 53, 5 and 4 articles, respectively. Not all developed CVSs were validated, and only three articles reported results from real-time evaluation of CVS performance in an abattoir vs performance of the official veterinarian. Most of the reported CVS performance measures (i.e., sensitivity and specificity) were >80%. A high specificity in detecting lesions and carcass contamination (i.e., a low number of false positives) is of importance for the food business operator in order to minimise food waste, whereas a high sensitivity (i.e., a low number of false negatives) is required for production of wholesome and safe meat. At present, the existing CVSs developed for overall meat safety assurance of broiler chicken carcasses and organs demonstrate very high sensitivities but suboptimal specificities, indicating the need for further CVS development and optimisation.

Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review / Sandberg, M.; Ghidini, S.; Alban, L.; Capobianco Dondona, A.; Blagojevic, B.; Bouwknegt, M.; Lipman, L.; Seidelin Dam, J.; Nastasijevic, I.; Antic, D.. - In: FOOD CONTROL. - ISSN 0956-7135. - 150:(2023), p. 109768.109768. [10.1016/j.foodcont.2023.109768]

Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review

Ghidini S.;Alban L.;Nastasijevic I.;
2023-01-01

Abstract

Introduction in 2017–2019 of the new EU legislation on official controls in food production allowed use of computer vision systems (CVSs) as complementary tools in meat inspection of bovines, pigs and poultry. A systematic literature review was performed to identify and analyse relevant articles reporting on the performances of CVSs used in abattoirs for ante- and post-mortem veterinary inspection and meat safety assurance, including systems for detecting carcass/organ contamination and lesions. In this review, 62 articles were identified and analysed. There were 35 articles reporting on CVS performance in the detection of carcass/organ lesions and 27 in the detection of carcass contamination. CVSs for broiler chicken, pig and bovine meat safety assurance were reported in 53, 5 and 4 articles, respectively. Not all developed CVSs were validated, and only three articles reported results from real-time evaluation of CVS performance in an abattoir vs performance of the official veterinarian. Most of the reported CVS performance measures (i.e., sensitivity and specificity) were >80%. A high specificity in detecting lesions and carcass contamination (i.e., a low number of false positives) is of importance for the food business operator in order to minimise food waste, whereas a high sensitivity (i.e., a low number of false negatives) is required for production of wholesome and safe meat. At present, the existing CVSs developed for overall meat safety assurance of broiler chicken carcasses and organs demonstrate very high sensitivities but suboptimal specificities, indicating the need for further CVS development and optimisation.
2023
Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review / Sandberg, M.; Ghidini, S.; Alban, L.; Capobianco Dondona, A.; Blagojevic, B.; Bouwknegt, M.; Lipman, L.; Seidelin Dam, J.; Nastasijevic, I.; Antic, D.. - In: FOOD CONTROL. - ISSN 0956-7135. - 150:(2023), p. 109768.109768. [10.1016/j.foodcont.2023.109768]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2952993
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