CoChat
Sign Up
Cited by 37Food Supply Chain TraceabilityFood Safety and HygieneArtificial Intelligence Applications

Harnessing Artificial Intelligence to Safeguard Food Quality and Safety

Open access
Singh, Diwakar·2025·Journal of Food Protection
DOI 10.1016/j.jfp.2025.100621
Open this paper in CoChat — free account

Abstract

Artificial Intelligence (AI) is reforming the food industry, particularly in food safety and quality control, by enhancing detection, predicting shelf life, and optimizing production processes. This review explores the innovative role of AI, focusing on the integration of machine learning (ML), computer vision, and natural language processing (NLP) in food safety systems. AI is transforming food safety by enabling real-time monitoring, predictive analytics, rapid contaminant detection, and automation throughout the food supply chain. These technologies reduce human error and allow quicker responses to safety threats, ultimately preventing foodborne illnesses and improving product quality. AI also helps to predict and manage climate-induced risks, such as chemical and microbiological hazards linked to extreme weather and temperature shifts. The review outlines the integration of digital tools such as biosensors and Internet of Things (IoT) devices and examines AI's convergence with blockchain and process analytical technologies to enhance traceability and strengthen food safety management systems. Despite its potential, the widespread adoption of AI is hindered by challenges such as data privacy concerns, workforce adaptation, and regulatory barriers, while critical gaps in digital infrastructure, data standardization, and policy support also need to be addressed to enable effective implementation. The review highlights the importance of ethical frameworks and interdisciplinary collaboration to guide responsible AI deployment. Emerging tools like neural networks and behavior-based safety assessments can boost food system resilience. The review concludes by calling for enhanced regulatory cooperation and technological investment to realize AI's full potential in creating safer, more sustainable, and efficient food systems.

Integrity signals

Registry

Crossref · 10.1016/j.jfp.2025.100621

Cites

129 of 129 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Real-time monitoring technologies integrating bioinformatics with multi-omics and digital health data are starting to allow long-term tracking of probiotic strains and host responses, especially in translational and post-market settings.

    “Simultaneously, real-time monitoring technologies integrating bioinformatics with multi-omics and digital health data are starting to allow for the long-term tracking of probiotic strains and host responses, especially in translational and post-market settings [159,160].”

    From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [160]

Cites

1 retracted

Flagged first, then by citations

Cited by

Sorted by citations

  • Current Concepts in Probiotic Safety and Efficacy

    Churin, A. A., Sokolyanskaya, L. O., Lukina, A. P., & Karnachuk, O. V. (2026) · Nutrients · doi:10.3390/nu18040696 · Cited by 31 · see citing works

    “Simultaneously, real-time monitoring technologies integrating bioinformatics with multi-omics and digital health data are starting to allow for the long-term tracking of probiotic strains and host responses, especially in translational and post-market settings [159,160].”

Authors
Singh, D.
Corresponding author
Singh, Diwakar
ORCID
Singh, Diwakar
Venue
Journal of Food Protection
Publisher
Elsevier BV
Published
2025-10
Volume
88
Issue
11
Pages
100621
ISSN
0362-028X (ISSN-L)
DOI
10.1016/j.jfp.2025.100621
OpenAlex
W4414223706
Cited by
37
References
129
Citations by year
2026: 36 · 2025: 1
FWCI
3.00
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Food Protection (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Food Supply Chain Traceability
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Food Safety and Hygiene
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
food quality control, machine learning, computer vision, natural language processing, contamination detection, shelf life prediction, food supply chain monitoring, foodborne illness prevention, biosensors, Internet of Things, blockchain traceability, process analytical technology, data privacy, AI regulation, responsible AI, food system resilience
MeSH terms
Artificial Intelligence, Food Contamination, Humans, Food Safety, Food Quality

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review