AI-Powered Innovations in Food Safety from Farm to Fork
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| Publicado en: | Foods vol. 14, no. 11 (2025), p. 1973 |
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| Autor principal: | |
| Otros Autores: | , , , |
| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 003 | UK-CbPIL | ||
| 022 | |a 2304-8158 | ||
| 024 | 7 | |a 10.3390/foods14111973 |2 doi | |
| 035 | |a 3217731503 | ||
| 045 | 2 | |b d20250601 |b d20250614 | |
| 084 | |a 231462 |2 nlm | ||
| 100 | 1 | |a Yin Binfeng |u School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China; creatgang@163.com (G.T.); chemistwindow@gmail.com (R.M.); 18205073638@163.com (J.B.) | |
| 245 | 1 | |a AI-Powered Innovations in Food Safety from Farm to Fork | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Artificial intelligence is comprehensively transforming the food safety governance system by integrating modern technologies and building intelligent control systems that provide rapid solutions for the entire food supply chain from farm to fork. This article systematically reviews the core applications of AI in the orbit of food safety. First, in the production and quality control of primary food sources, the integration of spectral data with AI efficiently identifies pest and disease, food spoilage, and pesticide and veterinary drug residues. Secondly, during food processing, sensors combined with machine learning algorithms are utilized to ensure regulatory compliance and monitor production parameters. AI also works together with blockchain to build an immutable and end-point traceability system. Furthermore, multi-source data fusion can provide personalized nutrition and dietary recommendations. The integration of AI technologies with traditional food detection methods has significantly improved the accuracy and sensitivity of food analytical methods. Finally, in the future, to address the increasing food safety issues, Food Industry 4.0 will expand the application of AI with lightweight edge computing, multi-modal large models, and global data sharing to create a more intelligent, adaptive and flexible food safety system. | |
| 653 | |a Artificial intelligence | ||
| 653 | |a Quality control | ||
| 653 | |a Control systems | ||
| 653 | |a Food contamination & poisoning | ||
| 653 | |a Food processing industry | ||
| 653 | |a Safety systems | ||
| 653 | |a Industry 4.0 | ||
| 653 | |a Edge computing | ||
| 653 | |a Nutrition | ||
| 653 | |a Food spoilage | ||
| 653 | |a Data integration | ||
| 653 | |a Pesticide residues | ||
| 653 | |a Food processing | ||
| 653 | |a Machine learning | ||
| 653 | |a Farms | ||
| 653 | |a Food quality | ||
| 653 | |a Innovations | ||
| 653 | |a Food industry | ||
| 653 | |a Food sources | ||
| 653 | |a Spoilage | ||
| 653 | |a Food chains | ||
| 653 | |a Traditional foods | ||
| 653 | |a Sensors | ||
| 653 | |a Food systems | ||
| 653 | |a Food supply | ||
| 653 | |a Industrial applications | ||
| 653 | |a Food safety | ||
| 653 | |a Food contamination | ||
| 653 | |a Safety | ||
| 653 | |a Supply chains | ||
| 700 | 1 | |a Tan, Gang |u School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China; creatgang@163.com (G.T.); chemistwindow@gmail.com (R.M.); 18205073638@163.com (J.B.) | |
| 700 | 1 | |a Rashid, Muhammad |u School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China; creatgang@163.com (G.T.); chemistwindow@gmail.com (R.M.); 18205073638@163.com (J.B.) | |
| 700 | 1 | |a Liu, Jun |u Suqian Product Quality Supervision and Inspection Institute, Suqian 223800, China; ljljljlj1982@163.com | |
| 700 | 1 | |a Bi Junjie |u School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China; creatgang@163.com (G.T.); chemistwindow@gmail.com (R.M.); 18205073638@163.com (J.B.) | |
| 773 | 0 | |t Foods |g vol. 14, no. 11 (2025), p. 1973 | |
| 786 | 0 | |d ProQuest |t Agriculture Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3217731503/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3217731503/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3217731503/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |