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Updated: Jul 21, 2025

Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool
Published on: May 25, 2021
A non-target geographical origin screening of botrytized wines through comprehensive two-dimensional gas
Nemanja Koljančić1, Adriano A Gomes1,2, Ivan Špánik1
1Institute of Analytical Chemistry, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Bratislava, Slovakia.
Abstract:
One of the most effective methods for gaining insight into the composition of trace-level volatile organic characteristics of wine products is through the use of a comprehensive two-dimensional gas chromatography-high resolution mass spectrometry (GC × GC-HRMS) technique. The vast amount of data generated by this method, however, can often be overwhelming requiring exhaustive and time-consuming analysis to identify significant statistical characteristics. The use of advanced chemometric software can achieve the same or even higher efficiency. This study aimed to identify differences based on geographical locations by analyzing the volatile organic compounds in the composition of botrytized wines from Slovakia, Hungary, France, and Austria. The volatile organic compounds were extracted by solid-phase microextraction and analyzed using GC × GC-HRMS. The data obtained from the analysis underwent Fisher-ratio (F-ratio) tile-based analysis to identify statistically significant differences. Principal component analysis demonstrated a significant distinction between wine samples based on geographical location, using only 10 statistically significant features with the highest F-ratio. In the samples, the following compounds were analyzed: methyl-octadecanoate, 2-cyanophenyl-β-phenylpropionate, α-ionone, n-octanoic acid, 1,2-dihydro-1,1,6-trimethyl-naphthalene, methyl-hexadecanoate, ethyl-pentadecanoate, ethyl-decanoate, and γ-nonalactone. These, all play an important role in cluster pattern observed on principal component analysis results. Additionally, hierarchical cluster analysis confirmed this.
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