Advances in the Application of Artificial Intelligence in Food Quality and Safety Analysis
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Analytical Methods".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 28
Special Issue Editors
Interests: non-destructive testing of food; spectroscopy and spectral analysis; applications of biosensors; intelligent processing of food; applications of deep learning in food; applications of machine vision
Interests: electrochemical micro-nano sensing; portable food analytical methods; monitoring and control of food safety risk factors; development and application of biomimetic nano-probes; rapid detection of food quality
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue will focus on the transformative role of artificial intelligence (AI) in advancing food quality and safety analysis. AI technologies, including machine learning, computer vision, and predictive modeling, are reshaping traditional approaches by enabling rapid, non-destructive, and high-throughput detection of contaminants, adulterants, and nutritional components. Contributions are invited to explore AI-driven innovations such as real-time quality monitoring (e.g., automated texture/color analysis via hyperspectral imaging), risk prediction (e.g., microbial spoilage models, allergen detection), and authenticity verification (e.g., deep learning for fraud detection in supply chains). Submissions should emphasize algorithmic breakthroughs or innovative applications (e.g., explainable neural networks, reinforcement learning for multi-parameter optimization), and practical implementations (e.g., IoT-integrated sensors, edge computing devices for on-site testing). Emerging topics include AI-enhanced spectral data interpretation, blockchain–AI synergy for traceability, and scalable solutions for industrial compliance. Challenges such as dataset standardization, model generalizability, and cost-effective deployment in resource-limited settings will also be addressed. This collection aims to bridge gaps between computational research and real-world applications, fostering AI adoption to ensure safer, transparent, and sustainable global food systems.
Dr. Yongqiang Shi
Dr. Xinai Zhang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- food quality and safety analysis
- machine learning
- computer vision
- predictive modeling
- real-time quality monitoring
- risk prediction
- authenticity verification
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