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Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM

Ginseng, which contains abundant ginsenosides, grows mainly in the Jilin, Liaoning, and Heilongjiang in China. It has been reported that the quality and traits of ginsengs from different origins were greatly different. To date, the accurate prediction of the origins of ginseng samples is still a cha...

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Autores principales: Zhang, Chi, Liu, Zhe, Lu, Shaoming, Xiao, Liujun, Xue, Qianqian, Jin, Hongli, Gan, Jiapan, Li, Xiaonong, Liu, Yanfang, Liang, Xinmiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268438/
https://www.ncbi.nlm.nih.gov/pubmed/35807471
http://dx.doi.org/10.3390/molecules27134225
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author Zhang, Chi
Liu, Zhe
Lu, Shaoming
Xiao, Liujun
Xue, Qianqian
Jin, Hongli
Gan, Jiapan
Li, Xiaonong
Liu, Yanfang
Liang, Xinmiao
author_facet Zhang, Chi
Liu, Zhe
Lu, Shaoming
Xiao, Liujun
Xue, Qianqian
Jin, Hongli
Gan, Jiapan
Li, Xiaonong
Liu, Yanfang
Liang, Xinmiao
author_sort Zhang, Chi
collection PubMed
description Ginseng, which contains abundant ginsenosides, grows mainly in the Jilin, Liaoning, and Heilongjiang in China. It has been reported that the quality and traits of ginsengs from different origins were greatly different. To date, the accurate prediction of the origins of ginseng samples is still a challenge. Here, we integrated ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) with a support vector machine (SVM) for rapid discrimination and prediction of ginseng from the three main regions where it is cultivated in China. Firstly, we develop a stable and reliable UHPLC-Q-TOF-MS method to obtain robust information for 31 batches of ginseng samples after reasonable optimization. Subsequently, a rapid pre-processing method was established for the rapid screening and identification of 69 characteristic ginsenosides in 31 batches ginseng samples from three different origins. The SVM model successfully distinguished ginseng origin, and the accuracy of SVM model was improved from 83% to 100% by optimizing the normalization method. Six crucial quality markers for different origins of ginseng were screened using a permutation importance algorithm in the SVM model. In addition, in order to validate the method, eight batches of test samples were used to predict the regions of cultivation of ginseng using the SVM model based on the six selected quality markers. As a result, the proposed strategy was suitable for the discrimination and prediction of the origin of ginseng samples.
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spelling pubmed-92684382022-07-09 Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM Zhang, Chi Liu, Zhe Lu, Shaoming Xiao, Liujun Xue, Qianqian Jin, Hongli Gan, Jiapan Li, Xiaonong Liu, Yanfang Liang, Xinmiao Molecules Article Ginseng, which contains abundant ginsenosides, grows mainly in the Jilin, Liaoning, and Heilongjiang in China. It has been reported that the quality and traits of ginsengs from different origins were greatly different. To date, the accurate prediction of the origins of ginseng samples is still a challenge. Here, we integrated ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) with a support vector machine (SVM) for rapid discrimination and prediction of ginseng from the three main regions where it is cultivated in China. Firstly, we develop a stable and reliable UHPLC-Q-TOF-MS method to obtain robust information for 31 batches of ginseng samples after reasonable optimization. Subsequently, a rapid pre-processing method was established for the rapid screening and identification of 69 characteristic ginsenosides in 31 batches ginseng samples from three different origins. The SVM model successfully distinguished ginseng origin, and the accuracy of SVM model was improved from 83% to 100% by optimizing the normalization method. Six crucial quality markers for different origins of ginseng were screened using a permutation importance algorithm in the SVM model. In addition, in order to validate the method, eight batches of test samples were used to predict the regions of cultivation of ginseng using the SVM model based on the six selected quality markers. As a result, the proposed strategy was suitable for the discrimination and prediction of the origin of ginseng samples. MDPI 2022-06-30 /pmc/articles/PMC9268438/ /pubmed/35807471 http://dx.doi.org/10.3390/molecules27134225 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Chi
Liu, Zhe
Lu, Shaoming
Xiao, Liujun
Xue, Qianqian
Jin, Hongli
Gan, Jiapan
Li, Xiaonong
Liu, Yanfang
Liang, Xinmiao
Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM
title Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM
title_full Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM
title_fullStr Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM
title_full_unstemmed Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM
title_short Rapid Discrimination and Prediction of Ginsengs from Three Origins Based on UHPLC-Q-TOF-MS Combined with SVM
title_sort rapid discrimination and prediction of ginsengs from three origins based on uhplc-q-tof-ms combined with svm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268438/
https://www.ncbi.nlm.nih.gov/pubmed/35807471
http://dx.doi.org/10.3390/molecules27134225
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