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5.1
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Foods
Special Issues
Emerging Approaches for the Detection of Food Fraud and Adulteration
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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 1221

Special Issue Editors

Prof. Dr. Mircea Oroian

E-Mail Website
Guest Editor
Faculty of Food Engineering, Stefan cel Mare University of Suceava, 13 Universitatii Street, 720229 Suceava, Romania
Interests: food; detection; fraud; chemometrics; artificial inteligence
Special Issues, Collections and Topics in MDPI journals
Dr. Anca Becze

E-Mail Website
Guest Editor
INCDO INOE 2000, Research Institute for Analytical Instrumentation, Donath 67, 400293 Cluj-Napoca, Romania
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 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

  • food
  • adulteration
  • spectroscopy
  • chromatography
  • chemometrics
  • artificial intelligence
  • traceability
  • DNA-based methods

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

9 pages, 5675 KB  
Communication
Development of a Multiplex PCR Assay for Simultaneous Identification of Six Commercially Important Bivalves
by Kang-Rae Kim, Hye-Jin Kim and In-Chul Bang
Foods 2025, 14(22), 3881; https://doi.org/10.3390/foods14223881 - 13 Nov 2025
Viewed by 270
Abstract
Processed bivalve products typically lack diagnostic shell characters, making DNA-based assays essential for reliable species authentication in routine testing. We developed and validated a conventional, COX1-based multiplex PCR for the simultaneous identification of six commercially important food bivalves: Argopecten irradians, Mimachlamys crassicostata [...] Read more.
Processed bivalve products typically lack diagnostic shell characters, making DNA-based assays essential for reliable species authentication in routine testing. We developed and validated a conventional, COX1-based multiplex PCR for the simultaneous identification of six commercially important food bivalves: Argopecten irradians, Mimachlamys crassicostata, Mizuhopecten yessoensis, Scaeochlamys farreri, Atrina pectinata, and Swiftopecten swiftii. The assay yielded robust, single-band amplification across an annealing window of 54–59 °C and maintained reproducible performance over template inputs from 0.1 to 50 ng per reaction. This work provides a practical marker set for simultaneous identification of six bivalve species in freeze foods or tissues where morphological traits are not preserved. Full article
(This article belongs to the Special Issue Emerging Approaches for the Detection of Food Fraud and Adulteration)
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16 pages, 2422 KB  
Article
Cold-Pressed Walnut-Oil Adulteration with Edible Oils Detection Using Vis-NIR Spectroscopy
by Georgiana Fediuc, Mariana Spinei and Mircea Oroian
Foods 2025, 14(22), 3877; https://doi.org/10.3390/foods14223877 - 13 Nov 2025
Viewed by 333
Abstract
The aim of this study is to evaluate the usefulness of UV-Vis-NIR spectroscopy as a tool for detecting the adulteration of cold-pressed walnut oil and other edible oils (rapeseed, sunflower, and soybean oils) at varying percentages. The spectra were recorded between 200 and [...] Read more.
The aim of this study is to evaluate the usefulness of UV-Vis-NIR spectroscopy as a tool for detecting the adulteration of cold-pressed walnut oil and other edible oils (rapeseed, sunflower, and soybean oils) at varying percentages. The spectra were recorded between 200 and 1800 nm, but the analyses focused on 350–1650 nm due to high UV and NIR absorption. Color was determined in CIEL*a*b* coordinates to achieve the differences among the samples. The spectra were submitted to several pre-treatment (none, normalization, SNV, MSC, baseline/detrend, first/second derivative, and 1st-order smoothing) to improve the statistical model’s parameters. The differentiation of the samples was carried out using an unsupervised method (principal component analysis—PCA) and two supervised methods (linear discriminant analysis—LDA and partial least squares linear discriminant analysis—PLS-DA). Partial least squares regression (PLS-R) was used for predicting the degree of adulteration. Separation between the authentic and adulterated samples was visible in the PCA scores plot, primarily along the spectral regions of 420–500 nm (pigment-related absorption band) and 1150–1450 nm (lipid-associated band). PLS-DA was superior to DA for the discrimination of authentic/adulterated samples, with baseline spectra of 350–1650 nm yielding a 100% overall accuracy and near-perfect accuracy with MSC (98.48%). PLS-R was able to predict the adulteration level, depending on the pre-treatment applied. Full article
(This article belongs to the Special Issue Emerging Approaches for the Detection of Food Fraud and Adulteration)
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15 pages, 2888 KB  
Article
Establishing a Detection Method Based on Multiplex PCR for Identification of Sheep Meat, Goat Meat and Common Adulterant Meats
by Yanbing Yang, Kai Quan, Huiguo Yang, Yuxuan Song, Xiyun Zhang, Bo Wang, Xiaoyang Lv and Wei Sun
Foods 2025, 14(22), 3875; https://doi.org/10.3390/foods14223875 - 13 Nov 2025
Viewed by 436
Abstract
This study aimed to establish a multiplex PCR identification system capable of rapidly detecting adulteration in sheep and goat meat, while qualitatively identifying common adulterant meats (pork, chicken, and duck). Species-specific primers targeting mitochondrial DNA sequences were designed after screening for gene fragments [...] Read more.
This study aimed to establish a multiplex PCR identification system capable of rapidly detecting adulteration in sheep and goat meat, while qualitatively identifying common adulterant meats (pork, chicken, and duck). Species-specific primers targeting mitochondrial DNA sequences were designed after screening for gene fragments with intraspecies conservation and interspecies specificity across five target species. The multiplex PCR conditions and system were systematically optimized and evaluated for specificity, reproducibility, sensitivity, and practical applicability using simulated mixed samples and heat-treated products. The results demonstrated that the system could successfully identify sheep meat, goat meat, and adulterant meat components in randomly combined target meat template DNAs with excellent reproducibility. The system maintained a high sensitivity, detecting target species even at low DNA template concentrations and in samples with low adulteration ratios. Moreover, target meat components remained detectable in heat-treated products, confirming the system’s robustness under realistic market conditions. This multiplex PCR identification system demonstrates strong specificity, good reproducibility, high sensitivity, and broad applicability. It provides an important tool for effectively monitoring sheep and goat meat adulteration and offers crucial technical support for ensuring the authenticity of sheep and goat meat. Full article
(This article belongs to the Special Issue Emerging Approaches for the Detection of Food Fraud and Adulteration)
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