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Updated: Jul 19, 2026

Rapid Collection of Floral Fragrance Volatiles using a Headspace Volatile Collection Technique for GC-MS Thermal Desorption Sampling
Published on: December 10, 2019
Metabolomic profiling of natural volatiles: headspace trapping: GC-MS
Yury M Tikunov1, Francel W A Verstappen, Robert D Hall
1Center for BioSystems Genomics, Wageningen, The Netherlands.
Abstract:
Plants are a fabulously rich source of naturally volatile metabolites, which are derived from a range of contrasting biochemical pathways (e.g., mono-, di-, and sesquiterpenoids, benzoates, alcohols, esters). Such volatiles may immediately be released from the plant or they may be stored, e.g., in glycosylated form for release later "on demand." Certain roles for these molecules have already been determined in that they can function as attractants (e.g., to pollinators, seed dispersers, and others) or as protectants (repellants, pathogen inhibitors, and so on). The flavor and fragrance of plant materials to humans and other animals are also, to a great extent, determined by natural volatiles. Other more sophisticated roles have also been elucidated where plant volatiles have been shown to be involved either as signal molecules to attract the predators of damaging herbivorous insects or potentially even as signal molecules warning other plants of imminent danger. As such, detailed knowledge of these components can be valuable in relation to breeding crop varieties for enhanced product quality or for achieving improved resistance to pathogens and insects. Furthermore, knowledge of the metabolites can result in a corresponding knowledge of the genes responsible for their synthesis and this can lead to dedicated strategies for their in vitro production through, e.g., reverse genetics in heterologous microbial expression systems in fermentors for the production of high-value fine chemicals. Various analytical techniques based on gas chromatography-mass spectrometry have been devised for the analysis of this complex group of metabolites. Two of these key methods are detailed in this chapter.
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