Safety Control and Quality Analysis in Food Processing
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Food Chemistry".
Deadline for manuscript submissions: 28 February 2027 | Viewed by 1
Editors
Interests: agriculture machinery; spectroscopy; precision agriculture; non-destructive analyses
Interests: food analysis; pharmaceutical chemistry; analytical chemistry; high-performance liquid chromatography; antioxidants; food quality; protein-protein interaction; protein characterization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Food safety and nutritional quality remain among the most critical challenges in modern food science. As global supply chains become increasingly complex and consumer demand for authentic, safe, and nutrient-rich products grows, the need for rapid, reliable, and non-destructive analytical tools has never been more urgent. Despite considerable scientific progress, significant gaps persist—particularly in real-time process monitoring, multi-matrix validation, and the transition of laboratory innovations into industry-ready applications.
This Special Issue of Molecules, entitled "Safety Control and Quality Analysis in Food Processing," aims to bring together the latest advances in analytical methodologies and quality monitoring strategies applied across diverse food processing contexts. Fully aligned with the journal's scope in analytical and food chemistry, this Issue seeks to compile a robust collection of high-impact studies that collectively advance the field of precision food quality control.
We welcome original research articles and reviews addressing, but not limited to, the following themes:
- Non-destructive spectroscopic techniques (NIR, FT-NIR, Raman, hyperspectral imaging);
- Chemometric and multivariate analysis (PCA, PLS, ANN) for food quality prediction;
- Detection of adulteration and fraud, and geographic origin authentication;
- Sensor-based and AI-driven tools for real-time process monitoring;
- Effects of processing treatments (drying, fermentation, heat treatment) on nutritional and physicochemical properties;
- Rapid microbiological safety detection platforms.
We warmly encourage contributions from researchers in food science, analytical chemistry, spectroscopy, and data science. We look forward to receiving your contributions.
Dr. Mehmet Burak Büyükcan
Dr. Raffaella Colombo
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules 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 2700 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 quality
- NIR spectroscopy
- FT-NIR
- chemometrics
- food adulteration
- non-destructive analysis
- food processing
- authentication
- multivariate analysis
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