{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T19:00:32Z","timestamp":1790190032393,"version":"4.1.0"},"reference-count":55,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T00:00:00Z","timestamp":1781136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Research, Development and Innovation Office (NKFIH), Budapest, Hungary","award":["2024-1.1.1-KKV_F\u00d3KUSZ-2024-00072"],"award-info":[{"award-number":["2024-1.1.1-KKV_F\u00d3KUSZ-2024-00072"]}]},{"award":["2024-1.1.1-KKV_F\u00d3KUSZ-2024-00072"],"award-info":[{"award-number":["2024-1.1.1-KKV_F\u00d3KUSZ-2024-00072"]}],"id":[{"id":"https:\/\/ror.org\/03g2am276","id-type":"ROR","asserted-by":"publisher"}]},{"name":"the Strategic Research Fund of the University of Veterinary Medicine Budapest, Hungary","award":["SRF-003"],"award-info":[{"award-number":["SRF-003"]}]},{"award":["SRF-003"],"award-info":[{"award-number":["SRF-003"]}],"id":[{"id":"https:\/\/ror.org\/03vayv672","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Veterinary Sciences"],"abstract":"<jats:p>Background: Artificial intelligence (AI) is increasingly being proposed for postharvest food-safety control of animal-source foods, but its practical value depends on whether models can support real decisions rather than only report high accuracy. Methods: This narrative review used a structured literature mapping of peer-reviewed work, mainly from 2020 to 2025, identified through database searches and citation tracking using combined terms for artificial intelligence, machine learning, animal-source foods, postharvest food safety, slaughterhouse inspection, cold-chain monitoring, traceability, authenticity, HACCP, validation, and regulatory applicability. Results: The most implementation-proximate applications are computer vision prescreening in slaughterhouses and processing plants, sensor- and IoT-based cold-chain surveillance, freshness and adulteration screening, and digital traceability systems. Across these areas, stronger evidence is associated with clearly defined control points, transparent reference methods, external or temporal validation, auditable data flows, and documented human oversight. The main weaknesses are single-site datasets, retrospective designs, incomplete reporting of reference methods, limited workflow testing, and insufficient attention to false alerts, fallback procedures, and governance. Conclusions: AI should be viewed as targeted decision support, not as a replacement for established food-safety control. Future studies should prioritize prospective, multi-site, workflow-embedded validation and show how alerts lead to documented corrective or verification actions.<\/jats:p>","DOI":"10.3390\/vetsci13060574","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T06:53:10Z","timestamp":1781247190000},"page":"574","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Artificial Intelligence in Postharvest Food Safety Control of Animal-Source Foods: Evidence Thresholds, Validation, and Regulatory Applicability"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7410-9354","authenticated-orcid":false,"given":"Andr\u00e1s","family":"Bitts\u00e1nszky","sequence":"first","affiliation":[{"name":"Department of Food Hygiene, Institute of Food Chain Science, University of Veterinary Medicine Budapest, Istv\u00e1n u. 2., H-1078 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7793-2661","authenticated-orcid":false,"given":"Vilmos","family":"Bilicki","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Institute of Informatics, University of Szeged, H-6720 Szeged, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gerg\u0151","family":"Sud\u00e1r","sequence":"additional","affiliation":[{"name":"CERES Holding Ltd., 7030 Paks, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikl\u00f3s","family":"S\u00fcth","sequence":"additional","affiliation":[{"name":"Department of Food Hygiene, Institute of Food Chain Science, University of Veterinary Medicine Budapest, Istv\u00e1n u. 2., H-1078 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5441-5303","authenticated-orcid":false,"given":"Szilvia","family":"Kusza","sequence":"additional","affiliation":[{"name":"Centre for Agricultural Genomics and Biotechnology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Egyetem t\u00e9r 1, H-4032 Debrecen, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8176-7013","authenticated-orcid":false,"given":"Andr\u00e1s J.","family":"T\u00f3th","sequence":"additional","affiliation":[{"name":"Department of Food Hygiene, Institute of Food Chain Science, University of Veterinary Medicine Budapest, Istv\u00e1n u. 2., H-1078 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Havelaar, A.H., Kirk, M.D., Torgerson, P.R., Gibb, H.J., Hald, T., Lake, R.J., Praet, N., Bellinger, D.C., de Silva, N.R., and Gargouri, N. (2015). World Health Organization Global Estimates and Regional Comparisons of the Burden of Foodborne Disease in 2010. PLoS Med., 12.","DOI":"10.1371\/journal.pmed.1001923"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1475","DOI":"10.1007\/s12571-023-01391-3","article-title":"Burden of Foodborne Disease in Low-Income and Middle-Income Countries and Opportunities for Scaling Food Safety Interventions","volume":"15","author":"Grace","year":"2023","journal-title":"Food Secur."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.bj.2018.03.003","article-title":"Food Safety in the 21st Century","volume":"41","author":"Fung","year":"2018","journal-title":"Biomed. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"110575","DOI":"10.1016\/j.foodcont.2024.110575","article-title":"Phenotypic and Genotypic Patterns of Antimicrobial Resistance in Livestock and Poultry in South Asia: A Systematic Review and Meta-Analysis","volume":"164","author":"Harun","year":"2024","journal-title":"Food Control"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.tifs.2019.11.002","article-title":"Internet of Things in Food Safety: Literature Review and a Bibliometric Analysis","volume":"94","author":"Bouzembrak","year":"2019","journal-title":"Trends Food Sci. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Donaghy, J.A., Danyluk, M.D., Ross, T., Krishna, B., and Farber, J. (2021). Big Data Impacting Dynamic Food Safety Risk Management in the Food Chain. Front. Microbiol., 12.","DOI":"10.3389\/fmicb.2021.668196"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s12393-024-09386-2","article-title":"Application of Artificial Intelligence in Food Processing: Current Status and Future Prospects","volume":"17","author":"Bidyalakshmi","year":"2025","journal-title":"Food Eng. Rev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"12513","DOI":"10.1080\/10408398.2022.2103086","article-title":"A Perspective on Data Sharing in Digital Food Safety Systems","volume":"63","author":"Qian","year":"2023","journal-title":"Crit. Rev. Food Sci. Nutr."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"105153","DOI":"10.1016\/j.tifs.2025.105153","article-title":"Artificial Intelligence for Food Safety: From Predictive Models to Real-World Safeguards","volume":"163","author":"Balakrishnan","year":"2025","journal-title":"Trends Food Sci. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"110952","DOI":"10.1016\/j.foodcont.2024.110952","article-title":"Towards Digitalisation of Food Safety Management Systems\u2014Enablers and Constraints","volume":"168","author":"Sartoni","year":"2025","journal-title":"Food Control"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"109768","DOI":"10.1016\/j.foodcont.2023.109768","article-title":"Applications of Computer Vision Systems for Meat Safety Assurance in Abattoirs: A Systematic Review","volume":"150","author":"Sandberg","year":"2023","journal-title":"Food Control"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Revelou, P.K., Tsakali, E., Batrinou, A., and Strati, I.F. (2025). Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods. Foods, 14.","DOI":"10.3390\/foods14060922"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"105161","DOI":"10.1016\/j.tifs.2025.105161","article-title":"Artificial Intelligence in Smart Seafood Safety across the Supply Chains: Recent Advances and Future Prospects","volume":"163","author":"Jiao","year":"2025","journal-title":"Trends Food Sci. Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"105154","DOI":"10.1016\/j.tifs.2025.105154","article-title":"Agri-Food Traceability Today: Advancing Innovation towards Efficiency, Sustainability, Ethical Sourcing, and Safety in Food Supply Chains","volume":"163","author":"Rossi","year":"2025","journal-title":"Trends Food Sci. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1111\/j.1471-1842.2009.00848.x","article-title":"A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies","volume":"26","author":"Grant","year":"2009","journal-title":"Health Inf. Libr. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.jbusres.2019.07.039","article-title":"Literature Review as a Research Methodology: An Overview and Guidelines","volume":"104","author":"Snyder","year":"2019","journal-title":"J. Bus. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/s41073-019-0064-8","article-title":"SANRA\u2014A Scale for the Quality Assessment of Narrative Review Articles","volume":"4","author":"Baethge","year":"2019","journal-title":"Res. Integr. Peer Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"111292","DOI":"10.1016\/j.foodcont.2025.111292","article-title":"The Role of Artificial Intelligence in Advancing Food Safety: A Strategic Path to Zero Contamination","volume":"175","author":"Naseem","year":"2025","journal-title":"Food Control"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"104855","DOI":"10.1016\/j.tifs.2024.104855","article-title":"Research Progress on the Artificial Intelligence Applications in Food Safety and Quality Management","volume":"156","author":"Yu","year":"2025","journal-title":"Trends Food Sci. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"109552","DOI":"10.1016\/j.foodcont.2022.109552","article-title":"Risk Based Meat Safety Assurance System\u2014An Introduction to Key Concepts for Future Training of Official Veterinarians","volume":"146","author":"Ferri","year":"2023","journal-title":"Food Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e13403","DOI":"10.1111\/1541-4337.13403","article-title":"Risk Factors Affecting the Food Safety Risk in Food Business Operations for Risk-Based Inspection: A Systematic Review","volume":"23","author":"Ze","year":"2024","journal-title":"Compr. Rev. Food Sci. Food Saf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"110604","DOI":"10.1016\/j.foodcont.2024.110604","article-title":"Effectiveness of Machine Learning Algorithms as a Tool to Meat Traceability System. A Case Study to Classify Spanish Mediterranean Lamb Carcasses","volume":"164","author":"Teixeira","year":"2024","journal-title":"Food Control"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"110574","DOI":"10.1016\/j.foodcont.2024.110574","article-title":"A Comprehensive Review of the Dairy Pasteurization Process Using Machine Learning Models","volume":"164","author":"Singh","year":"2024","journal-title":"Food Control"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"110495","DOI":"10.1016\/j.foodcont.2024.110495","article-title":"XAI-Empowered IoT Multi-Sensor System for Real-Time Milk Adulteration Detection","volume":"164","author":"Goyal","year":"2024","journal-title":"Food Control"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"65660","DOI":"10.1109\/ACCESS.2021.3076373","article-title":"Secure Identification, Traceability and Real-Time Tracking of Agricultural Food Supply during Transportation Using Internet of Things","volume":"9","author":"Bhutta","year":"2021","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.tifs.2022.08.011","article-title":"Rapid Freshness and Survival Monitoring Biosensors of Fish: Progress, Challenge, and Future Perspective","volume":"129","author":"Xiong","year":"2022","journal-title":"Trends Food Sci. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"139230","DOI":"10.1016\/j.foodchem.2024.139230","article-title":"Development of Machine Learning-Based Shelf-Life Prediction Models for Multiple Marine Fish Species and Construction of a Real-Time Prediction Platform","volume":"450","author":"Cui","year":"2024","journal-title":"Food Chem."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"101287","DOI":"10.1016\/j.cofs.2025.101287","article-title":"Digital Transformation of the Agri-Food System","volume":"63","author":"Vahdanjoo","year":"2025","journal-title":"Curr. Opin. Food Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"111378","DOI":"10.1016\/j.foodcont.2025.111378","article-title":"Smart Technology for Public Health: Reshaping the Future of Food Safety","volume":"176","author":"Liberty","year":"2025","journal-title":"Food Control"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Dodero, A., Escher, A., Bertucci, S., Castellano, M., and Lova, P. (2021). Intelligent Packaging for Real-Time Monitoring of Food-Quality: Current and Future Developments. Appl. Sci., 11.","DOI":"10.3390\/app11083532"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"110113","DOI":"10.1016\/j.foodres.2021.110113","article-title":"A Critical Review on Intelligent and Active Packaging in the Food Industry: Research and Development","volume":"141","author":"Omid","year":"2021","journal-title":"Food Res. Int."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1080\/09537287.2021.1882691","article-title":"Improving Food Safety through Data Pattern Discovery in a Sensor-Based Monitoring System","volume":"33","author":"Jacobsen","year":"2022","journal-title":"Prod. Plan. Control"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"e70120","DOI":"10.1111\/jfpe.70120","article-title":"Smart Sensors in Food Packaging: Sensor Technology for Real-Time Food Safety and Quality Monitoring","volume":"48","author":"Mani","year":"2025","journal-title":"J. Food Process Eng."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Sobhan, A., Hossain, A., Wei, L., Muthukumarappan, K., and Ahmed, M. (2025). IoT-Enabled Biosensors in Food Packaging: A Breakthrough in Food Safety for Monitoring Risks in Real Time. Foods, 14.","DOI":"10.3390\/foods14081403"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Wang, K., Lin, X., Zhang, M., Li, Y., Luo, C., and Wu, J. (2022). Review of Electrochemical Biosensors for Food Safety Detection. Biosensors, 12.","DOI":"10.3390\/bios12110959"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Chen, Y., Wang, Y., Zhang, Y., Wang, X., Zhang, C., and Cheng, N. (2024). Intelligent Biosensors Promise Smarter Solutions in Food Safety 4.0. Foods, 13.","DOI":"10.3390\/foods13020235"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s10479-023-05169-w","article-title":"A Critical Analysis of the Integration of Blockchain and Artificial Intelligence for Supply Chain","volume":"327","author":"Charles","year":"2023","journal-title":"Ann. Oper. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"e16526","DOI":"10.1016\/j.heliyon.2023.e16526","article-title":"Blockchain Technology in Food Safety and Traceability Concern to Livestock Products","volume":"9","author":"Patel","year":"2023","journal-title":"Heliyon"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s43069-025-00511-3","article-title":"Transforming Agrifood Supply Chains with Digital Technologies: A Systematic Review of Safety and Quality Risk Management","volume":"6","author":"Plakantara","year":"2025","journal-title":"Oper. Res. Forum"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"104800","DOI":"10.1016\/j.tifs.2024.104800","article-title":"Advances in Smart Food Authentication for Enhanced Safety and Quality","volume":"155","author":"Bhat","year":"2025","journal-title":"Trends Food Sci. Technol."},{"key":"ref_41","first-page":"101429","article-title":"Leveraging Blockchain to Tackle Food Fraud: Innovations and Obstacles","volume":"18","author":"Duan","year":"2024","journal-title":"J. Agric. Food Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1007\/s12393-023-09354-2","article-title":"Food Quality 4.0: Sustainable Food Manufacturing for the Twenty-First Century","volume":"15","author":"Velebit","year":"2023","journal-title":"Food Eng. Rev."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.tifs.2022.01.020","article-title":"Digitalisation and Artificial Intelligence for Sustainable Food Systems","volume":"120","author":"Marvin","year":"2022","journal-title":"Trends Food Sci. Technol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"e24924","DOI":"10.2196\/24924","article-title":"Machine Learning Prediction of Foodborne Disease Pathogens: Algorithm Development and Validation Study","volume":"9","author":"Wang","year":"2021","journal-title":"JMIR Med. Inform."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e078378","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI Statement: Updated Guidance for Reporting Clinical Prediction Models That Use Regression or Machine Learning Methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.tifs.2022.04.025","article-title":"Artificial Intelligence and Ethics within the Food Sector: Developing a Common Language for Technology Adoption across the Supply Chain","volume":"125","author":"Manning","year":"2022","journal-title":"Trends Food Sci. Technol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1017\/err.2023.1","article-title":"Risk Management in the Artificial Intelligence Act","volume":"15","author":"Schuett","year":"2024","journal-title":"Eur. J. Risk Regul."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"103702","DOI":"10.1016\/j.compind.2022.103702","article-title":"Cybersecurity in the Food and Beverage Industry: A Reference Framework","volume":"141","author":"Latino","year":"2022","journal-title":"Comput. Ind."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s12117-023-09516-y","article-title":"The Threat of Ransomware in the Food Supply Chain: A Challenge for Food Defence","volume":"29","author":"Manning","year":"2023","journal-title":"Trends Organ. Crime"},{"key":"ref_50","first-page":"102245","article-title":"A Review of Cybersecurity Incidents in the Food and Agriculture Sector","volume":"23","author":"Kulkarni","year":"2025","journal-title":"J. Agric. Food Res."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Ahmad, A., Liew, A.X.W., Venturini, F., Kalogeras, A., Candiani, A., Di Benedetto, G., Ajibola, S., Cartujo, P., Romero, P., and Lykoudi, A. (2024). AI Can Empower Agriculture for Global Food Security: Challenges and Prospects in Developing Nations. Front. Artif. Intell., 7.","DOI":"10.3389\/frai.2024.1328530"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"111050","DOI":"10.1016\/j.foodcont.2024.111050","article-title":"A Risk-Based Approach to Meat Inspection: How European Official Veterinarians Perceive Their Work and Training","volume":"170","author":"Cardoso","year":"2025","journal-title":"Food Control"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.foodcont.2018.03.014","article-title":"Developing Official Control in Slaughterhouses through Internal Audits","volume":"90","author":"Luukkanen","year":"2018","journal-title":"Food Control"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"100196","DOI":"10.1016\/j.jfp.2023.100196","article-title":"Official Control in Slaughter and Game Handling: Expectations and Prerequisites for Implementation of Remote Meat Inspection in Sweden","volume":"87","author":"Hunka","year":"2024","journal-title":"J. Food Prot."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"111128","DOI":"10.1016\/j.foodcont.2024.111128","article-title":"Official Food Control Inspectors\u2019 Perceptions of Remote Food Control in Finland","volume":"171","author":"Piira","year":"2025","journal-title":"Food Control"}],"container-title":["Veterinary Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-7381\/13\/6\/574\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T08:25:31Z","timestamp":1781252731000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-7381\/13\/6\/574"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,11]]},"references-count":55,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["vetsci13060574"],"URL":"https:\/\/doi.org\/10.3390\/vetsci13060574","relation":{},"ISSN":["2306-7381"],"issn-type":[{"value":"2306-7381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,11]]}}}