Sample preparation strategies for comprehensive volatile fingerprinting

Dynamic headspace (D-HS); Enrichment; Extraction; Multidimensional comprehensive gas chromatography (GCxGC); Solid-phase microextraction (SPME); Sorptive extraction; Static headspace (S-HS); Thermal desorption tubes (TDT); Analytical Chemistry; Spectroscopy

Abstract :

[en] Comprehensive multidimensional chromatography (GC × GC) has burst the separation capabilities of the classical monodimensional GC. Along with the enhanced separation power, the layers of information that can be extracted from a two-dimensional (2D) plot are significantly increased leading the handling of such complex datasets towards the metabolomics approach. To maximize the output of such a powerful combination, the sample preparation step plays an essential role. This chapter aims to give a detailed overview of the sample preparation techniques used to cover a broad range of volatiles for untargeted GC × GC analysis of odourants. A theoretical insight within the different techniques used will be given, covering both static and dynamic extraction methods with particular emphasis to green sample preparation techniques. Static methods include static headspace (SHS), HS-solid-phase microextraction (SPME), HS sorptive extraction (HSSE), while, dynamic methods include dynamic HS (DHS) using thermal desorption tubes (TDT).

Disciplines :

Chemistry
Food science

Author, co-author :

Franchina, Flavio ; Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique, organique et biologique ; Department of Chemical, Pharmaceutical, and Agricultural Sciences, University of Ferrara, Ferrara, Italy

Purcaro, Giorgia ; Université de Liège - ULiège > TERRA Research Centre > Chimie des agro-biosystèmes

Language :

English

Title :

Sample preparation strategies for comprehensive volatile fingerprinting

Publication date :

2022

Main work title :

Characterization of Odorant Patterns by Comprehensive Two-Dimensional Gas Chromatography

Editor :

Cordero, Chiara Emilia Irma

Publisher :

Elsevier B.V.

ISBN/EAN :

978-0-323-98881-0

Peer reviewed :

Peer reviewed

Additional URL :

https://api.elsevier.com/content/article/PII:S0166526X22000022?httpAccept=text/xml

Available on ORBi :

since 05 July 2022

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