Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study

Chemical profiles of medicinal plants could be dissimilar depending on the cultivation environments, which may influence their therapeutic efficacy. Accordingly, the regional origin of the medicinal plants should be authenticated for correct evaluation of their medicinal and market values. Metabolom...

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Main Authors: Dong-Kyu Lee, Dong Kyu Lim, Jung A. Um, Chang Ju Lim, Ji Yeon Hong, Young A Yoon, Yeonsuk Ryu, Hyo Jin Kim, Hi Jae Cho, Jeong Hill Park, Young Bae Seo, Kyunga Kim, Johan Lim, Sung Won Kwon, Jeongmi Lee
Format: Article
Language:English
Published: MDPI AG 2014-05-01
Series:Molecules
Subjects:
Online Access:http://www.mdpi.com/1420-3049/19/5/6294
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spelling doaj-4a408024fbc04538b1ba0189ed7c76062020-11-25T00:10:18ZengMDPI AGMolecules1420-30492014-05-011956294630810.3390/molecules19056294molecules19056294Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics StudyDong-Kyu Lee0Dong Kyu Lim1Jung A. Um2Chang Ju Lim3Ji Yeon Hong4Young A Yoon5Yeonsuk Ryu6Hyo Jin Kim7Hi Jae Cho8Jeong Hill Park9Young Bae Seo10Kyunga Kim11Johan Lim12Sung Won Kwon13Jeongmi Lee14College of Pharmacy, Seoul National University, Seoul 151-742, KoreaCollege of Pharmacy, Seoul National University, Seoul 151-742, KoreaCollege of Pharmacy, Seoul National University, Seoul 151-742, KoreaCollege of Pharmacy, Seoul National University, Seoul 151-742, KoreaCollege of Pharmacy, Seoul National University, Seoul 151-742, KoreaSchool of Pharmacy, Sungkyunkwan University, Suwon 440-746, KoreaSchool of Pharmacy, Sungkyunkwan University, Suwon 440-746, KoreaCollege of Pharmacy, Dongduk Women's University, Seoul 136-714, KoreaKorea Promotion Institute for Traditional Medicine Industry, Gyeongsan 712-260, KoreaCollege of Pharmacy, Seoul National University, Seoul 151-742, KoreaDepartment of Herbology, College of Oriental Medicine, Daejeon University, Daejeon 300-716, KoreaDepartment of Statistics, Sookmyung Women's University, Seoul 140-742, KoreaDepartment of Statistics, Seoul National University, Seoul 151-742, KoreaCollege of Pharmacy, Seoul National University, Seoul 151-742, KoreaSchool of Pharmacy, Sungkyunkwan University, Suwon 440-746, KoreaChemical profiles of medicinal plants could be dissimilar depending on the cultivation environments, which may influence their therapeutic efficacy. Accordingly, the regional origin of the medicinal plants should be authenticated for correct evaluation of their medicinal and market values. Metabolomics has been found very useful for discriminating the origin of many plants. Choosing the adequate analytical tool can be an essential procedure because different chemical profiles with different detection ranges will be produced according to the choice. In this study, four analytical tools, Fourier transform near‑infrared spectroscopy (FT-NIR), 1H-nuclear magnetic resonance spectroscopy (1H‑NMR), liquid chromatography-mass spectrometry (LC-MS), and gas chromatography-mass spectroscopy (GC-MS) were applied in parallel to the same samples of two popular medicinal plants (Gastrodia elata and Rehmannia glutinosa) cultivated either in Korea or China. The classification abilities of four discriminant models for each plant were evaluated based on the misclassification rate and Q2 obtained from principal component analysis (PCA) and orthogonal projection to latent structures-discriminant analysis (OPLS‑DA), respectively. 1H-NMR and LC-MS, which were the best techniques for G. elata and R. glutinosa, respectively, were generally preferable for origin discrimination over the others. Reasoned by integrating all the results, 1H-NMR is the most prominent technique for discriminating the origins of two plants. Nonetheless, this study suggests that preliminary screening is essential to determine the most suitable analytical tool and statistical method, which will ensure the dependability of metabolomics-based discrimination.http://www.mdpi.com/1420-3049/19/5/6294traditional medicineGastrodia elataRehmannia glutinosaplant metabolomicsorigin discriminationmultivariate statistical analysis
collection DOAJ
language English
format Article
sources DOAJ
author Dong-Kyu Lee
Dong Kyu Lim
Jung A. Um
Chang Ju Lim
Ji Yeon Hong
Young A Yoon
Yeonsuk Ryu
Hyo Jin Kim
Hi Jae Cho
Jeong Hill Park
Young Bae Seo
Kyunga Kim
Johan Lim
Sung Won Kwon
Jeongmi Lee
spellingShingle Dong-Kyu Lee
Dong Kyu Lim
Jung A. Um
Chang Ju Lim
Ji Yeon Hong
Young A Yoon
Yeonsuk Ryu
Hyo Jin Kim
Hi Jae Cho
Jeong Hill Park
Young Bae Seo
Kyunga Kim
Johan Lim
Sung Won Kwon
Jeongmi Lee
Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study
Molecules
traditional medicine
Gastrodia elata
Rehmannia glutinosa
plant metabolomics
origin discrimination
multivariate statistical analysis
author_facet Dong-Kyu Lee
Dong Kyu Lim
Jung A. Um
Chang Ju Lim
Ji Yeon Hong
Young A Yoon
Yeonsuk Ryu
Hyo Jin Kim
Hi Jae Cho
Jeong Hill Park
Young Bae Seo
Kyunga Kim
Johan Lim
Sung Won Kwon
Jeongmi Lee
author_sort Dong-Kyu Lee
title Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study
title_short Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study
title_full Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study
title_fullStr Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study
title_full_unstemmed Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study
title_sort evaluation of four different analytical tools to determine the regional origin of gastrodia elata and rehmannia glutinosa on the basis of metabolomics study
publisher MDPI AG
series Molecules
issn 1420-3049
publishDate 2014-05-01
description Chemical profiles of medicinal plants could be dissimilar depending on the cultivation environments, which may influence their therapeutic efficacy. Accordingly, the regional origin of the medicinal plants should be authenticated for correct evaluation of their medicinal and market values. Metabolomics has been found very useful for discriminating the origin of many plants. Choosing the adequate analytical tool can be an essential procedure because different chemical profiles with different detection ranges will be produced according to the choice. In this study, four analytical tools, Fourier transform near‑infrared spectroscopy (FT-NIR), 1H-nuclear magnetic resonance spectroscopy (1H‑NMR), liquid chromatography-mass spectrometry (LC-MS), and gas chromatography-mass spectroscopy (GC-MS) were applied in parallel to the same samples of two popular medicinal plants (Gastrodia elata and Rehmannia glutinosa) cultivated either in Korea or China. The classification abilities of four discriminant models for each plant were evaluated based on the misclassification rate and Q2 obtained from principal component analysis (PCA) and orthogonal projection to latent structures-discriminant analysis (OPLS‑DA), respectively. 1H-NMR and LC-MS, which were the best techniques for G. elata and R. glutinosa, respectively, were generally preferable for origin discrimination over the others. Reasoned by integrating all the results, 1H-NMR is the most prominent technique for discriminating the origins of two plants. Nonetheless, this study suggests that preliminary screening is essential to determine the most suitable analytical tool and statistical method, which will ensure the dependability of metabolomics-based discrimination.
topic traditional medicine
Gastrodia elata
Rehmannia glutinosa
plant metabolomics
origin discrimination
multivariate statistical analysis
url http://www.mdpi.com/1420-3049/19/5/6294
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