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Published in: Forensic Toxicology 2/2018

01-07-2018 | Original Article

VOCs as fingerprints for the chemical profiling of hashish samples analyzed by HS-SPME/GC–MS and multivariate statistical tools

Authors: Roberta Ascrizzi, Guido Flamini, Mario Giusiani, Fabio Stefanelli, Viviana Deriu, Silvio Chericoni

Published in: Forensic Toxicology | Issue 2/2018

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Abstract

Purpose

The statistical evaluation of the chemical profile of seized hashish samples is a valuable tool to aid the estimation of the route through which the material has reached the dealers’ market.

Methods

In this study, the complete volatile organic compound (VOC) emission profiles of 48 seized hashish samples have been analyzed by means of headspace solid-phase microextraction/gas chromatography–mass spectrometry and evaluated with chemometric tools; multivariate statistical analyses, both hierarchical cluster analysis and principal component analysis (PCA) methods have been performed on the results to assess the existence of possible patterns throughout the samples.

Results

The total VOC emission profiles sharply distributed the samples in clusters based on their batches of origin; this trend was also clearly shown in the PCA plot, in which samples coming from the same seizure were grouped together. The Δ9-tetrahydrocannabinol (THC) content analysis did not show a relevant trend in terms of lot of origin of the samples.

Conclusions

The evaluation of the VOCs released into the headspace traced a much more complete chemical profiling of the samples, as compared to the analysis of cannabinoids only, or the THC titration. The multivariate statistical analyses were very useful to estimate the origin of the seized material.
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Metadata
Title
VOCs as fingerprints for the chemical profiling of hashish samples analyzed by HS-SPME/GC–MS and multivariate statistical tools
Authors
Roberta Ascrizzi
Guido Flamini
Mario Giusiani
Fabio Stefanelli
Viviana Deriu
Silvio Chericoni
Publication date
01-07-2018
Publisher
Springer Japan
Published in
Forensic Toxicology / Issue 2/2018
Print ISSN: 1860-8965
Electronic ISSN: 1860-8973
DOI
https://doi.org/10.1007/s11419-017-0398-1

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