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  • Title: Optimizing targeted/untargeted metabolomics by automating gas chromatography/mass spectrometry workflows.
    Author: Robbat A, Kfoury N, Baydakov E, Gankin Y.
    Journal: J Chromatogr A; 2017 Jul 07; 1505():96-105. PubMed ID: 28533028.
    Abstract:
    New database building and MS subtraction algorithms have been developed for automated, sequential two-dimensional gas chromatography/mass spectrometry (GC-GC/MS). This paper reports the first use of a database building tool, with full mass spectrum subtraction, that does not rely on high resolution MS data. The software was used to automatically inspect GC-GC/MS data of high elevation tea from Yunnan, China, to build a database of 350 target compounds. The database was then used with spectral deconvolution to identify 285 compounds by GC/MS of the same tea. Targeted analysis of low elevation tea by GC/MS resulted in the detection of 275 compounds. Non-targeted analysis, using MS subtraction, yielded an additional eight metabolites, unique to low elevation tea.
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