Next-Generation Chemometric and Spectroscopic Strategies for Food Safety and Authenticity: Toward Faster and More Reliable Detection
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 542
Special Issue Editor
Interests: multivariate data analysis; spectroscopy; qualitative performance parameters; food fraud; data fusion
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The increasing complexity of global food supply chains, combined with recurring cases of food fraud and contamination, has intensified the need for rapid, robust, and interpretable analytical tools. Spectroscopic techniques, especially when integrated with chemometrics, machine learning, or deep learning, offer non-destructive, sustainable, and high-throughput solutions for food safety and authenticity assessment.
This Special Issue invites original research and reviews focused on developing and applying innovative spectroscopic and chemometric methodologies for real-time or near-real-time food analysis. Emphasis will be placed on defining, estimating, and validating performance parameters—critical aspects that remain underexplored and that are currently lacking in regulatory consensus. Submissions addressing these challenges through new protocols, benchmarking approaches, or validation frameworks will be highly valued.
We are particularly interested in contributions that considering the following:
- Present novel chemometric workflows for multivariate calibration, classification, or detection;
- Explore spectral preprocessing and data fusion techniques to enhance model robustness;
- Propose standardized strategies for reporting accuracy, precision, sensitivity, specificity, and model transferability;
- Demonstrate the real-world applicability of these methods through case studies on food fraud, adulteration, or contamination.
By addressing both methodological innovation and performance validation, this Special Issue will advance the field toward reliable, transparent, and regulatory-ready solutions for ensuring food integrity.
Join us in shaping next-generation tools for food safety, which will be faster, smarter, and scientifically rigorous.
Prof. Dr. Itziar Ruisánchez Capelastegui
Guest Editor
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 safety
- food authenticity
- chemometrics
- spectroscopy
- multivariate analysis
- machine learning
- rapid detection
- non-destructive analysis
- model validation
- food fraud
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