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

Molecules

Dong-Kyu Lee⁵  Dong Kyu Lim⁵  Jung A. Um⁵  Chang Ju Lim⁵  Ji Yeon Hong⁵  Young A Yoon⁷  Yeonsuk Ryu⁷  Hyo Jin Kim¹  Hi Jae Cho⁶  Jeong Hill Park⁵  Young Bae Seo²  Kyunga Kim⁴  Johan Lim³  Sung Won Kwon⁵ 

[1] College of Pharmacy, Dongduk Women’s University, Seoul 136-714, Korea; E-Mail:;Department of Herbology, College of Oriental Medicine, Daejeon University, Daejeon 300-716, Korea; E-Mail:;Department of Statistics, Seoul National University, Seoul 151-742, Korea; E-Mail:;Department of Statistics, Sookmyung Women’s University, Seoul 140-742, Korea; E-Mail:;College of Pharmacy, Seoul National University, Seoul 151-742, Korea; E-Mails:;Korea Promotion Institute for Traditional Medicine Industry, Gyeongsan 712-260, Korea; E-Mail:;School of Pharmacy, Sungkyunkwan University, Suwon 440-746, Korea; E-Mails:

关键词: traditional medicine;    Gastrodia elata;    Rehmannia glutinosa;    plant metabolomics;    origin discrimination;    multivariate statistical analysis;   

DOI  :  10.3390/molecules19056294

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.