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Open AccessArticle

Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome

1
Department of Chemistry, Tufts University, Medford, MA 02155, USA
2
Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, 10125 Turin, Italy
*
Author to whom correspondence should be addressed.
Molecules 2019, 24(20), 3757; https://doi.org/10.3390/molecules24203757
Received: 29 July 2019 / Revised: 4 September 2019 / Accepted: 15 October 2019 / Published: 18 October 2019
(This article belongs to the Special Issue (Mass Spectrometric) Non Target Screening–Techniques and Strategies)
Identifying all analytes in a natural product is a daunting challenge, even if fractionated by volatility. In this study, comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-MS) was used to investigate relative distribution of volatiles in green, pu-erh tea from leaves collected at two different elevations (1162 m and 1651 m). A total of 317 high and 280 low elevation compounds were detected, many of them known to have sensory and health beneficial properties. The samples were evaluated by two different software. The first, GC Image, used feature-based detection algorithms to identify spectral patterns and peak-regions, leading to tentative identification of 107 compounds. The software produced a composite map illustrating differences in the samples. The second, Ion Analytics, employed spectral deconvolution algorithms to detect target compounds, then subtracted their spectra from the total ion current chromatogram to reveal untargeted compounds. Compound identities were more easily assigned, since chromatogram complexities were reduced. Of the 317 compounds, for example, 34% were positively identified and 42% were tentatively identified, leaving 24% as unknowns. This study demonstrated the targeted/untargeted approach taken simplifies the analysis time for large data sets, leading to a better understanding of the chemistry behind biological phenomena. View Full-Text
Keywords: tea; metabolomics; GC/MS; software; database; MS subtraction; spectral deconvolution; 2DGC; volatilomics tea; metabolomics; GC/MS; software; database; MS subtraction; spectral deconvolution; 2DGC; volatilomics
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Morimoto, J.; Rosso, M.C.; Kfoury, N.; Bicchi, C.; Cordero, C.; Robbat, A., Jr. Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome. Molecules 2019, 24, 3757.

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