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- W3042305534 abstract "Identification of compounds in food residues from archaeological samples is important to determine their origin. However, high-throughput and accurate identification of compounds in archaeological samples is challenging. In this work, we propose the use of gas chromatography–mass spectrometry (GC–MS) combined with the recently developed chemometric tool autoGCMSDataAnal to identify compounds in archaeological samples. Samples excavated from a tomb of the Xihan dynasty about 2000 BP were used to demonstrate the performance of our proposed methodology. Under the optimized GC–MS instrumental conditions, more than 300 total ion chromatogram peaks were automatically extracted for each sample. Coeluted components were automatically resolved and registered to construct respective mass spectra, based on which compounds were accurately identified. Finally, more than 70 compounds were identified, among which more than 57% were confirmed by standards. A comparison with the automated mass spectral deconvolution and identification system indicates that the combination of GC–MS with autoGCMSDataAnal is suitable for compound identification in archaeological samples." @default.
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- W3042305534 date "2020-11-01" @default.
- W3042305534 modified "2023-10-16" @default.
- W3042305534 title "High-throughput identification of volatile and semi-volatile organic compounds in archaeological samples by gas chromatography–mass spectrometry combined with advanced chemometrics methodology" @default.
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- W3042305534 doi "https://doi.org/10.1016/j.microc.2020.105289" @default.
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