Chromatography/Mass Spectrometry for the Determination of Food Authenticity and Food Analysis

A special issue of Separations (ISSN 2297-8739). This special issue belongs to the section "Analysis of Food and Beverages".

Deadline for manuscript submissions: 15 January 2026 | Viewed by 7544

Special Issue Editor


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Guest Editor
European Commission, Joint Research Centre Geel, Retieseweg 111, B-2440 Geel, Belgium
Interests: chromatography; mass spectrometry; sample preparation; chemical analysis; analytical chemistry; LC-MS/MS; LC-MS; gas chromatography

Special Issue Information

Dear Colleagues,

The authenticity of food is a characteristic highly valued by consumers, and for this premium prices will be paid. Food fraud, which refers to the adulteration of food with the fraudulous intention of enhanced financial gain, has become an serious problem. Two examples include honey and wine, where adulteration, due to the large volumes of these products traded and the willingness of the consumer to pay extra for authenticity, can deliver immense illegitimate profits. Therefore, methods of analysis that are able to prove authenticity and detect possible adulterations are in high demand. Liquid and/or gas chromatography and mass spectrometric detection have become essential techniques in food analysis. They enable sensitive targeted analysis to be performed if the markers for specific adulterations are known; if such markers are not known, they faciliate non-targeted analysis (NTA). NTA provides a wealth of information from which multi-variate analysis can filter out possible specific markers or groups of suspicious test samples.

This Special Issue aims to compile papers in which LC- and/or GC-MS have been utilized to analyze food in order to detect adulteration and that exemplify recent advances in food authentication.

Dr. Andreas Breidbach
Guest Editor

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Keywords

  • liquid chromatography
  • gas chromatography
  • mass spectrometry
  • adulteration
  • food fraud
  • multi variate analysis
  • authentication
  • high resolution MS

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Published Papers (4 papers)

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Research

14 pages, 1840 KiB  
Article
Volatilomic Fingerprint of Tomatoes by HS-SPME/GC-MS as a Suitable Analytical Platform for Authenticity Assessment Purposes
by Gonçalo Jasmins, Tânia Azevedo, José S. Câmara and Rosa Perestrelo
Separations 2025, 12(8), 188; https://doi.org/10.3390/separations12080188 - 22 Jul 2025
Abstract
Tomatoes are globally esteemed not only for their nutritional value but also for their complex and appealing aroma, a key determinant of consumer preference. The present study aimed to comprehensively characterise the volatilomic fingerprints of three tomato species—Solanum lycopersicum L., S. lycopersicum [...] Read more.
Tomatoes are globally esteemed not only for their nutritional value but also for their complex and appealing aroma, a key determinant of consumer preference. The present study aimed to comprehensively characterise the volatilomic fingerprints of three tomato species—Solanum lycopersicum L., S. lycopersicum var. cerasiforme, and S. betaceum—encompassing six distinct varieties, through the application of headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC-MS). A total of 55 volatile organic compounds (VOCs) spanning multiple chemical classes were identified, of which only 28 were ubiquitously present across all varieties examined. Carbonyl compounds constituted the predominant chemical family, with hexanal and (E)-2-hexenal emerging as putative key contributors to the characteristic green and fresh olfactory notes. Notably, esters were found to dominate the unique volatile fingerprint of cherry tomatoes, particularly methyl 2-hydroxybenzoate, while Kumato and Roma varieties exhibited elevated levels of furanic compounds. Multivariate statistical analyses, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), demonstrated clear varietal discrimination and identified potential aroma-associated biomarkers such as phenylethyl alcohol, 3-methyl-1-butanol, hexanal, (E)-2-octenal, (E)-2-nonenal, and heptanal. Collectively, these findings underscore the utility of volatilomic fingerprint as a robust tool for varietal identification and quality control within the food industry. Full article
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17 pages, 2019 KiB  
Article
Free Fatty Acid Determination in Alcoholic and Non-Alcoholic Beers via Liquid Chromatography–High-Resolution Mass Spectrometry Analysis
by Christiana Mantzourani and Maroula G. Kokotou
Separations 2025, 12(5), 114; https://doi.org/10.3390/separations12050114 - 1 May 2025
Viewed by 2132
Abstract
In recent years, non-alcoholic beers have been gaining popularity. Among the various components that affect the flavor and sensory characteristics of beers, free fatty acids (FFAs) are minor components. However, due to their involvement in beer quality, fast and simple methods for analyzing [...] Read more.
In recent years, non-alcoholic beers have been gaining popularity. Among the various components that affect the flavor and sensory characteristics of beers, free fatty acids (FFAs) are minor components. However, due to their involvement in beer quality, fast and simple methods for analyzing FFAs in beers are of importance. In this work, we present a liquid chromatography–high-resolution mass spectrometry (LC-HRMS) method for the rapid determination of FFAs in beers, avoiding a tedious sample preparation and derivatization and allowing the simultaneous study of a large set of FAs, including medium-chain, long-chain, saturated, monounsaturated and polyunsaturated FAs. The method was applied in the analysis of twelve non-alcoholic and nine alcoholic beer samples from the local market, permitting the comparison of their FFA profiling. Among the 37 FAs studied, 29 were quantified, and palmitic, stearic, oleic and myristic acids were identified as the predominant FAs in both alcoholic and non-alcoholic beers. The majority of the predominant long-chain FAs, including palmitic, stearic and myristic acids, were found in decreased amounts in non-alcoholic beers, compared to the alcoholic ones, with the marked exception of oleic acid, which was increased in non-alcoholic beers. Among the medium-chain FAs, octanoic acid was found at lower concentrations in non-alcoholic beers, comparing to regular beers, while lauric acid was slightly increased. Principal component analysis (PCA) suggested the correlation of FFAs with the type of beer (alcoholic or non-alcoholic beer). Full article
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10 pages, 1639 KiB  
Article
Detection of Honey Adulteration by Liquid Chromatography—High-Resolution Mass Spectrometry: Results from an EU Coordinated Action
by Viviana Paiano, Andreas Breidbach, Carolin Lörchner, Tereza Ždiniaková, Olivier De Rudder, Alain Maquet, Lourdes Alvarellos and Franz Ulberth
Separations 2025, 12(2), 47; https://doi.org/10.3390/separations12020047 - 13 Feb 2025
Cited by 2 | Viewed by 3632
Abstract
Honey, a sweet and nutritious food produced by honeybees, is extensively consumed by humans due to its potential health benefits. Unfortunately, the adulteration of honey with inexpensive sugar syrups is a prevalent issue. Verifying the authenticity of honey is crucial for maintaining its [...] Read more.
Honey, a sweet and nutritious food produced by honeybees, is extensively consumed by humans due to its potential health benefits. Unfortunately, the adulteration of honey with inexpensive sugar syrups is a prevalent issue. Verifying the authenticity of honey is crucial for maintaining its quality and safety standards. The aim of this study was to identify the illicit addition of sugar syrups to honey imported into the European Union (EU). The European Commission’s Joint Research Centre (JRC) has employed different analytical approaches to detect several markers of adulteration in honey; however, this paper mainly focuses on the use of Liquid Chromatography–High-Resolution Mass Spectrometry (LC-HRMS). Two qualitative methods were developed to detect mannose (Man), difructose anhydride III (DFA III), 2-acetylfuran-3-glucopyranoside (AFGP), and oligo-/polysaccharides with degrees of polymerization (DPs) of 6 to 11. Out of the 320 honey samples provided by the authorities of the participating EU Member States, 147 (46%) were suspicious for non-compliance with the EU Honey Directive 2001/110/EC, mostly due to the presence of mannose and oligo-/polysaccharides. As a result, the development and standardization of sophisticated and universally recognized testing procedures will increase the capability of official control laboratories to detect honey adulteration and will serve as a powerful preventive measure against fraudulent practices in the global honey market. Full article
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15 pages, 2867 KiB  
Article
Rapid Classification of Unroasted Green Coffee Beans and Spices Based on the Tentative Determination of Volatile Compounds by Solid-Phase Dynamic Extraction (SPDE) and Gas Chromatography–Mass Spectrometry (GC–MS) with Supervised Learning
by Dimitrios G. Lazaridis, Evelyna K. Kokkosi, Emmanouela N. Mylonaki, Vassilios K. Karabagias, Nikolaos D. Andritsos and Ioannis K. Karabagias
Separations 2024, 11(12), 351; https://doi.org/10.3390/separations11120351 - 14 Dec 2024
Cited by 2 | Viewed by 1213
Abstract
The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of commercial unroasted green coffee beans, clove, cinnamon–clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing [...] Read more.
The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of commercial unroasted green coffee beans, clove, cinnamon–clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning commercial unroasted green coffee beans, clove, cinnamon, cinnamon and clove mixture (1:1, w/w), and nutmeg fine powders based on multivariate analysis of variance and supervised learning from tentative data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography–mass spectrometry. Results showed that 7 volatile compounds, i.e., ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate, could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of commercial unroasted green coffee beans, cinnamon, clove, cinnamon and clove mixture, and nutmeg, based on selected volatile compounds. In addition, the study provides further support to the literature by means of a possible substitution of these products in rapid analysis tests, given the statistical models developed. Full article
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