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Abstract

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.

Details

1009240
Business indexing term
Title
AI-Powered Innovations in Food Safety from Farm to Fork
Author
Yin Binfeng 1   VIAFID ORCID Logo  ; Tan, Gang 1 ; Rashid, Muhammad 1   VIAFID ORCID Logo  ; Liu, Jun 2 ; Bi Junjie 1 

 School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China; [email protected] (G.T.); [email protected] (R.M.); [email protected] (J.B.) 
 Suqian Product Quality Supervision and Inspection Institute, Suqian 223800, China; [email protected] 
Publication title
Foods; Basel
Volume
14
Issue
11
First page
1973
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
23048158
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-06-02
Milestone dates
2025-04-28 (Received); 2025-05-31 (Accepted)
Publication history
 
 
   First posting date
02 Jun 2025
ProQuest document ID
3217731503
Document URL
https://www.proquest.com/scholarly-journals/ai-powered-innovations-food-safety-farm-fork/docview/3217731503/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-07-23
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  • Coronavirus Research Database
  • ProQuest One Academic