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Novel Analytical Techniques in Food Chemistry

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 993

Special Issue Editor


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Guest Editor
Laboratory of Food Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Athens, Greece
Interests: food analysis; food safety; chemical contaminants; mass spectrometry; food authenticity; bioactive molecules
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Special Issue Information

Dear Colleagues,

Recent scientific and technological advances are rapidly reshaping the field of food chemistry, developing powerful new tools to investigate food composition, safety, authenticity, and quality. Conventional analytical methods, while still widely used, are increasingly complemented by innovative, high-resolution, and data-rich approaches that offer greater sensitivity, speed, and reliability when working with complex food matrices.

Emerging techniques such as ambient and high-resolution mass spectrometry, advanced chromatographic–MS platforms, and novel spectroscopic and hyperspectral methods are enabling more detailed chemical characterization than ever before. At the same time, significant progress in biosensors, nanomaterial-based detection, microfluidic systems, and portable analytical devices supports rapid, on-site measurement—an essential capability for modern food monitoring. The increasing integration of chemometrics, machine learning, and AI further strengthens these innovations by enabling efficient processing of large datasets, facilitating pattern recognition, and improving decision-making in areas such as food authentication, contaminant detection, foodomics and particularly metabolomics and proteomics, and nutritional profiling.

This Special Issue welcomes original research and review articles showcasing advances in analytical methodologies and their applications in food chemistry. Topics of interest include novel MS and chromatographic techniques, spectroscopy and imaging, sensor technologies, microfluidic platforms, and data-driven analytical strategies aimed at enhancing food safety, quality assurance, and transparency across the food system. This collection will highlight innovative research and reviews that push the boundaries of food analysis, ensuring a safer, more authentic, and higher-quality global food supply.

Dr. Marilena Dasenaki
Guest Editor

Manuscript Submission Information

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Keywords

  • food quality and safety
  • food authenticity
  • food analysis
  • mass spectrometry
  • spectroscopic techniques
  • biosensors
  • chemometrics and machine learning
  • foodomics

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Published Papers (1 paper)

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Research

32 pages, 2400 KB  
Article
Decoding Cretan Wines: Phenolic Profiling of Greek Indigenous Wine Varieties Using LC-QTOF-MS
by Pelagia Lekka, Maria Dimitropoulou, Athanasia Rousali, Ana-Maria Kiose, Marianthi Basalekou, Nikolaos Thomaidis and Marilena Dasenaki
Molecules 2026, 31(5), 815; https://doi.org/10.3390/molecules31050815 - 28 Feb 2026
Viewed by 687
Abstract
Crete’s rich heritage of indigenous wine grapes remains underexplored in terms of chemical composition, with many cultivars yet to be fully characterized. This study presents a comprehensive analysis of the phenolic profile of 67 monovarietal Cretan wines produced by 10 wineries (42 white, [...] Read more.
Crete’s rich heritage of indigenous wine grapes remains underexplored in terms of chemical composition, with many cultivars yet to be fully characterized. This study presents a comprehensive analysis of the phenolic profile of 67 monovarietal Cretan wines produced by 10 wineries (42 white, 25 red) from 12 varieties—eight white (Assyrtiko, Dafni, Malvazia, Melissaki, Moschato Spinas, Plito, Vidiano, and Vilana) and four red (Kotsifali, Liatiko, Mandilaria, and Romeiko). A targeted LC–QTOF–MS workflow covering 45 phenolic compounds (flavonoids and non-flavonoids) was applied. Varietal differences were assessed using heteroscedasticity-robust univariate statistics (Welch’s ANOVA with Games–Howell post hoc comparisons and effect-size estimation) and explored by multivariate analyses (PCA and HCA); cross-validated PLS-DA was used for descriptive classification, and MFA integrated the targeted phenolic matrix with classical indices (e.g., total phenolics, tannins, and color metrics). Red wines exhibited stronger variety-linked phenolic structuring than white wines, whereas white-wine differentiation was driven by a limited subset of marker phenolics. Given the central role of phenolic composition in overall wine quality, this study provides the first detailed phenolic characterization of 12 key indigenous Cretan grape varieties. Full article
(This article belongs to the Special Issue Novel Analytical Techniques in Food Chemistry)
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