Evidence map›Paper›PMID 40509500›Full record

ReviewFoods (Basel, Switzerland)2025

AI-Powered Innovations in Food Safety from Farm to Fork.

Binfeng Yin, Gang Tan, Rashid Muhammad, Jun Liu, Junjie Bi

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Liquid Metal-Enabled Soft Bioelectronics for Human Health Monitoring.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Binfeng YinSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China.ORCID 0000-0002-0484-4951
Gang TanSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China.
Rashid MuhammadSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China.ORCID 0000-0001-5218-0689
Jun LiuSuqian Product Quality Supervision and Inspection Institute, Suqian 223800, China.
Junjie BiSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China.

Funding

"High-end Talent Support Plan" of Yangzhou UniversityKey Research and Development Program of Suqian L202408Market Supervision Administration Science and Technology Fund of Jiangsu Province KJ2023076Natural Science Foundation of the Jiangsu Higher Education Institutions of China 22KJB150050
6 · The paper itself

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.

Indexed as

AIfood safetyfrom farm to forkfull chainrapid detection

Identifiers

PMID40509500
PMCPMC12154576

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.