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J Chromatogr A

Title:		Characterization of volatile organic compounds in Polygonum multiflorum and two of its processed products based on multivariate statistical analysis for processing technology monitoring
Author(s):		Xing Y; Yu Z; Hu X; Yin J; Fan T; Fu Z; Pan G; Liu E; Zhou J; Han L;
Address:		"State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, P.R. China. Second Affiliated hospital of Tianjin University of Traditional Chinese Medicine, 69 Zengchan Road, Hebei District, Tianjin, 300250, P.R. China. Tianjin Institude for Drug Control, 98 Guizhou Road, Heping District, Tianjin, 300070, P.R. China. Electronic address: Zhou_Jian_Peng@hotmail.com. State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, P.R. China. Electronic address: hanlifeng@tjutcm.edu.cn"
Journal Title:		J Chromatogr A
Year:		2022
Volume:		20220819
Issue:
Page Number:		463431 -
DOI:		10.1016/j.chroma.2022.463431
ISSN/ISBN:		1873-3778 (Electronic) 0021-9673 (Linking)
Abstract:		"Herein we describe a comprehensive analysis of the volatile organic compounds (VOCs) of raw Polygonum multiflorum Thunb. (PM) and two of its processed products, as well as an effective and simple method based on volatile markers to determine to which extent the PM had been processed. Sixty-five VOCs were identified by headspace-solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), along with headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). Principal component analysis (PCA) of the HS-SPME-GC-MS spectra and fingerprint analysis of the HS-GC-IMS spectra allowed the identification of raw PM from its processed products based the VOCs identified. Furthermore, the content and distribution of VOCs in the samples were easily analyzed visually based on clustering-kernel density estimation (Cluster-KDE). Finally, exploratory factor analysis (EFA) allowed the screening of significant markers to identify the processing method and consequently distinguish the three studied groups of PM"
Keywords:		*Fallopia multiflora Gas Chromatography-Mass Spectrometry/methods Solid Phase Microextraction/methods Technology *Volatile Organic Compounds/analysis Gas chromatography-ion mobility spectrometry Gas chromatography-mass spectrometry Multivariate statistica;
Notes:		"MedlineXing, Yanchao Yu, Zhenyan Hu, Xiaohan Yin, Jiaxin Fan, Tianci Fu, Zhifei Pan, Guixiang Liu, Erwei Zhou, Jianpeng Han, Lifeng eng Netherlands 2022/08/27 J Chromatogr A. 2022 Sep 13; 1680:463431. doi: 10.1016/j.chroma.2022.463431. Epub 2022 Aug 19"