Application of Artificial Intelligence, Machine Learning and Deep Learning in Food Safety Analysis and Quality Control
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".
Deadline for manuscript submissions: 28 July 2026
Special Issue Editors
Interests: food quality control; quality management engineering; quality detection and evaluation; machine learning; chemometrics; intelligent data processing; spectroscopy; nanomaterials
Special Issues, Collections and Topics in MDPI journals
Interests: food science; instrument analysis; pattern recognition; computer science; food rapid detection technology; food quality evaluation technology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Food safety, quality control, and sample authenticity are lifelines for safeguarding public health and industrial credibility. In recent years, artificial intelligence and its core branches (such as machine learning and deep learning) have evolved into a powerful methodological toolkit in this field, providing novel, efficient, and intelligent solutions to complex analytical problems.
To systematically review and showcase innovative applications of intelligent computing technologies across a broader spectrum of samples, this Special Issue extends its research focus from traditional foodstuffs to medicinal and edible homologous samples of significant health value (e.g., dual-purpose medicinal and food herbs, functional food ingredients). We invite scholars worldwide to submit their original research achievements utilizing artificial intelligence/machine learning/deep learning methods in areas such as food safety analysis, quality control, authenticity identification, and efficacy component evaluation.
Scope and Topics (including but not limited to):
- Automated grading of food appearance quality based on image recognition/computer vision;
- Food quality inspection based on deep learning (especially Convolutional Neural Networks, Transformers);
- Quality prediction of characteristic food components (including nutritional indicators, functional components, contaminants, sensory attributes);
- Novel algorithms/strategies/application scenarios for food adulteration detection, origin traceability, and authenticity verification;
- Mining of food quality markers and construction of comprehensive evaluation models based on multi-omics data;
- Trustworthy traceability systems integrating blockchain and artificial intelligence;
- Edge artificial intelligence computing and lightweight model deployment for quality control;
- Explainable artificial intelligence for resource-constrained scenarios/small-sample data.
This Special Issue will establish an interdisciplinary exchange platform, focusing on the practical implementation of intelligent computing methods within an expanded sample scope;
Our goal is to gather cutting-edge ideas, promote the translation from algorithmic innovation to industrial applications, and jointly enhance food safety assurance capabilities and product quality control levels, thereby serving the health industry and public welfare.
We look forward to receiving your submissions.
Dr. Zhengyong Zhang
Dr. Min Sha
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 250 words) can be sent to the Editorial Office for assessment.
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
- machine learning
- deep learning
- medicinal and edible homologous samples
- computer vision
- adulteration detection
- origin traceability
- predictive modeling
- attention mechanism
- explainable artificial intelligence
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