Cargando…

Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis

To characterize the chemical differences of volatile components between crude and processed Baizhu Shaoyao San (BSS), a classical Chinese herbal formula that is widely applied in the treatment of gastrointestinal diseases, we developed a gas chromatography–mass spectrometry-based needle trap device...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Yangyang, Cai, Hao, Cao, Gang, Duan, Yu, Pei, Ke, Zhou, Jia, Xie, Li, Zhao, Jiayu, Liu, Jing, Wang, Xiaoqi, Shen, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030309/
https://www.ncbi.nlm.nih.gov/pubmed/30110475
http://dx.doi.org/10.1098/rsos.171987
_version_ 1783337123144794112
author Xu, Yangyang
Cai, Hao
Cao, Gang
Duan, Yu
Pei, Ke
Zhou, Jia
Xie, Li
Zhao, Jiayu
Liu, Jing
Wang, Xiaoqi
Shen, Lin
author_facet Xu, Yangyang
Cai, Hao
Cao, Gang
Duan, Yu
Pei, Ke
Zhou, Jia
Xie, Li
Zhao, Jiayu
Liu, Jing
Wang, Xiaoqi
Shen, Lin
author_sort Xu, Yangyang
collection PubMed
description To characterize the chemical differences of volatile components between crude and processed Baizhu Shaoyao San (BSS), a classical Chinese herbal formula that is widely applied in the treatment of gastrointestinal diseases, we developed a gas chromatography–mass spectrometry-based needle trap device combined with multivariate data analysis to globally profile volatile components and rapidly identify differentiating chemical markers. Using a triple-bed needle packed with Carbopack X, DVB and Carboxen 1000 sorbents, we identified 121 and 123 compounds, respectively, in crude and processed BSS. According to the results of principal component analysis and orthogonal partial least-squares discriminant analysis, crude and processed BSS were successfully distinguished into two groups with good fitting and predicting parameters. Furthermore, 21 compounds were identified and adopted as potential markers that could be employed to quickly differentiate these two types of samples using S-PLOT and variable importance in projection analyses. The established method can be applied to explain the chemical transformation of Chinese medicine processing in BSS and further control the quality and understand the processing mechanism of Chinese herbal formulae. Besides, the triple-bed needle selected and optimized in this study can provide a valuable reference for other plant researches with similar components. Furthermore, the systematic research on compound identification and marker discrimination of the complex components in crude and processed BSS could work as an example for other similar studies, such as composition changes in one plant during different growth periods, botanical characters of different medicinal parts in same kind of medicinal herbs and quality identification of one species of medicinal herb from different regions.
format Online
Article
Text
id pubmed-6030309
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher The Royal Society Publishing
record_format MEDLINE/PubMed
spelling pubmed-60303092018-07-17 Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis Xu, Yangyang Cai, Hao Cao, Gang Duan, Yu Pei, Ke Zhou, Jia Xie, Li Zhao, Jiayu Liu, Jing Wang, Xiaoqi Shen, Lin R Soc Open Sci Chemistry To characterize the chemical differences of volatile components between crude and processed Baizhu Shaoyao San (BSS), a classical Chinese herbal formula that is widely applied in the treatment of gastrointestinal diseases, we developed a gas chromatography–mass spectrometry-based needle trap device combined with multivariate data analysis to globally profile volatile components and rapidly identify differentiating chemical markers. Using a triple-bed needle packed with Carbopack X, DVB and Carboxen 1000 sorbents, we identified 121 and 123 compounds, respectively, in crude and processed BSS. According to the results of principal component analysis and orthogonal partial least-squares discriminant analysis, crude and processed BSS were successfully distinguished into two groups with good fitting and predicting parameters. Furthermore, 21 compounds were identified and adopted as potential markers that could be employed to quickly differentiate these two types of samples using S-PLOT and variable importance in projection analyses. The established method can be applied to explain the chemical transformation of Chinese medicine processing in BSS and further control the quality and understand the processing mechanism of Chinese herbal formulae. Besides, the triple-bed needle selected and optimized in this study can provide a valuable reference for other plant researches with similar components. Furthermore, the systematic research on compound identification and marker discrimination of the complex components in crude and processed BSS could work as an example for other similar studies, such as composition changes in one plant during different growth periods, botanical characters of different medicinal parts in same kind of medicinal herbs and quality identification of one species of medicinal herb from different regions. The Royal Society Publishing 2018-06-20 /pmc/articles/PMC6030309/ /pubmed/30110475 http://dx.doi.org/10.1098/rsos.171987 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Chemistry
Xu, Yangyang
Cai, Hao
Cao, Gang
Duan, Yu
Pei, Ke
Zhou, Jia
Xie, Li
Zhao, Jiayu
Liu, Jing
Wang, Xiaoqi
Shen, Lin
Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis
title Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis
title_full Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis
title_fullStr Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis
title_full_unstemmed Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis
title_short Discrimination of volatiles in herbal formula Baizhu Shaoyao San before and after processing using needle trap device with multivariate data analysis
title_sort discrimination of volatiles in herbal formula baizhu shaoyao san before and after processing using needle trap device with multivariate data analysis
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030309/
https://www.ncbi.nlm.nih.gov/pubmed/30110475
http://dx.doi.org/10.1098/rsos.171987
work_keys_str_mv AT xuyangyang discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT caihao discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT caogang discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT duanyu discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT peike discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT zhoujia discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT xieli discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT zhaojiayu discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT liujing discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT wangxiaoqi discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis
AT shenlin discriminationofvolatilesinherbalformulabaizhushaoyaosanbeforeandafterprocessingusingneedletrapdevicewithmultivariatedataanalysis