Emerging Approaches for the Detection of Food Fraud and Adulteration
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Quality and Safety".
Deadline for manuscript submissions: 20 March 2026 | Viewed by 4
Special Issue Editors
Interests: food; detection; fraud; chemometrics; artificial inteligence
Special Issues, Collections and Topics in MDPI journals
Interests: advanced analytical techniques for food fraud detection; rapid screening methods; chemometric modeling; digital traceability systems; AI-based authenticity verification
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Food fraud and adulteration have become increasingly significant threats to global food safety, quality, and consumer trust. The unfair practices (e.g., dilution, substation of raw materials with cheaper ones, mislabelling, addition of undeclared substances) influence the perception of the consumer towards the food industry and may pose risks to public health (e.g., addition of substances with negative effects on human health).
This Special Issue aims to showcase recent advances in analytical and digital methodologies designed to identify, monitor, and mitigate food fraud and adulteration.
The Special Issue welcomes contributions on, but not limited to, the following themes:
- Development and application of new techniques such as advanced spectroscopic, chromatographic, proteomic, and metabolomic methods for detecting adulterants and verifying authenticity.
- Molecular and DNA-Based Tools: Use of barcoding, next-generation sequencing, and other molecular biology techniques for species identification and fraud detection.
- Rapid and On-Site Detection Methods: Portable and high-throughput screening technologies suitable for real-time monitoring along the supply chain.
- Nanotechnology and Biosensors: Design of nanosensors and smart biosensing devices offering enhanced sensitivity, selectivity, and speed in fraud detection.
- Digital and Data-Driven Approaches: Integration of artificial intelligence, chemometrics, blockchain, and big data analytics to improve traceability and strengthen predictive capabilities.
Through this Special Issue, we aim to advance the scientific dialogue on safeguarding food authenticity and provide innovative tools that reinforce consumer confidence, regulatory compliance, and global food security.
Prof. Dr. Mircea Oroian
Dr. Anca Becze
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
- food
- adulteration
- spectroscopy
- chromatography
- chemometrics
- artificial intelligence
- traceability
- DNA-based methods
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