NMR-based metabolic profiling and differentiation of ginseng roots according to cultivation ages

https://doi.org/10.1016/j.jpba.2011.09.016Get rights and content

Abstract

Ginseng is an important herbal resource worldwide, and the adulteration or falsification of cultivation age has been a serious problem in the commercial market. In this study, ginseng (Panax ginseng) roots, which were cultivated for 2–6 years under GAP standard guidelines, were analyzed by NMR-based metabolomic techniques using two solvents. At first, ginseng root samples were extracted with 50% methanol, and analyzed by NMR with D2O as the NMR dissolution solvent. The 2-, 3-, 4-, and 5/6-year-old ginseng root samples were separated in PLS-DA-derived score plots. However, 5- and 6-year-old ginseng roots were not separated by the solvent system. Therefore, various solvents were tested to differentiate the 5- and 6-year-old ginseng root samples, and 100% methanol-d4 was chosen as the direct extraction and NMR dissolution solvent. In the PLS model using data from the 100% methanol-d4 solvent, 5- and 6-year-old ginseng roots were clearly separated, and the model was validated using internal and external data sets. The obtained RMSEE and RMSEP values suggested that the PLS model has strong predictability for discriminating the age of 5- and 6-years-old ginseng roots. The present study suggests that the age of ginseng could be successfully predicted using two solvents, and the developed method in this study can be used as a standard protocol for discriminating and predicting the ages of ginseng root samples.

Highlights

► Adulteration or falsification of ginseng cultivation age has been a serious problem in the commercial market. ► NMR-based metabolic profiling method was employed to differentiate ginseng root samples of various cultivation ages. ► For the differentiation of ginseng roots according to cultivation ages, various solvents for extraction and NMR measurement were tested. ► The cultivation age of ginseng could be successfully differentiated and predicted using selected two solvents, and the developed method in this study can be used as a standard protocol for discriminating and predicting the ages of ginseng root samples.

Introduction

The roots of Panax ginseng C.A.Meyer (Araliaceae) have been used as a traditional medicinal herb worldwide. P. ginseng roots have been reported to include amino acids, fatty acids, carbohydrates, alkaloids, triterpene saponins, polysaccharides, sesquiterpenes, polyacetlyenes, peptidoglycans, minor elements, vitamins, and phenolic compounds [1], [2]. The major biochemical and pharmacological activities of P. ginseng have been attributed to triterpene saponins such as ginsenosides [3], and it was reported that the content of ginsenosides in root and root-hair increases with increasing age of P. ginseng from one to five years [4]. P. ginseng roots exhibit a wide variety of pharmacological effects, such as cardiovascular control of blood pressure [5], increasing learning [6], increasing cognitive performance [7], antiaging [8], antioxidative [9], anticancer [10], [11], and immunestimulating activities [12].

In recent years, the adulteration of ginseng cultivation age has been a major problem in ginseng commercial markets, because the 5- and 6-year-old ginseng root price is 30 and 60% higher than that of 4-year-old ginseng root [13], which has encouraged adulteration or falsification practices. However, the differentiation of ginseng according to cultivation age is mainly performed by visual inspection, such as morphological characteristics of the head part of ginseng and the number of branched roots. Therefore such differentiation has been rather subjective and relies on a few experts in the field. Nowadays, metabolomics techniques combining spectrometric methods and multivariate statistical analysis such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), hierarchical cluster analysis (HCA), and partial least squares projections to latent structures (PLS) [14]. Those multivariate statistical analysis techniques coupled with NMR analysis using various extraction protocols were used for metabolic profiling and characterization of various types of plants, foods, and tissues [15], [16], [17], [18].

There are a few previous reports regarding fingerprinting or metabolic profiling of ginseng by various analytical methods, such as nuclear magnetic resonance spectroscopy (NMR), 2D J-resolved NMR, UPLC-qTOF-MS, and GCxGC-TOF-MS [19], [20], [21], [22], [23], [24]. However, there are no reports regarding the metabolic differentiation and prediction of cultivation age using ginseng samples cultivated under standardized protocols or guidelines. Most of the previous fingerprinting analysis or metabolic profiling studies of ginseng was performed using ginseng roots purchased or obtained from commercial markets [20], [21], [24], [25]. Thus, metabolic profiling and development of a cultivation age prediction model for ginseng cultivated under standard conditions is very crucial for detecting and preventing adulteration or falsification. In this study, we cultivated ginseng root samples in a restricted and controlled area according to standardized cultivation protocols, and then the ginseng samples were analyzed by two-dimensional NMR-based metabolomics techniques using various solvents to develop a differentiation method for ginseng cultivation age.

Section snippets

Solvents and chemicals

First-grade methanol, D2O [99.9%, containing 0.05% 3-(trimethylsilyl)-propionic-2,2,3,3-d4 acid sodium salt (TSP) as an internal standard], acetone-d6 [99.9%, containing 0.1% (v/v) tetramethylsilane (TMS)], acetonitrile-d3 [99.8%, containing 0.05% (v/v) TMS], pyridine-d5 [99.5%, containing 0.03% (v/v) TMS], and DMSO–d6 [99.9%, containing 1% (v/v) TMS] were purchased from Sigma (St. Louis, MO). Methanol-d4 [99.8%], and methanol-d4 [99.8%, containing 0.05% (v/v) TMS] were obtained from Cambridge

1H NMR spectra and assignment of the peaks in ginseng root samples

The signal overlap was an obstacle to identifying individual metabolites in complex samples from 1H NMR spectra. This problem could be solved by using 2D J-resolved spectra. Spectral data of J-resolved NMR provided supplementary information and a splitting pattern for each signal with the accurate coupling constant. In addition, the 2D NMR techniques including 1H–1H COSY and 1H–13C HSQC can be useful for peak assignment.

Figs. 1, S1 and S2 showed the representative 1H NMR spectrum (Fig. 1a), 2D J

Conclusions

In this study, we differentiated ginseng roots of various cultivation ages using 1D and 2D NMR-based metabolomics techniques with two step solvent systems. We used ginseng root samples cultivated according to standard cultivation guidelines, while most of the previous research has been performed using purchased ginseng root samples from commercial markets or farms. Through PLS-DA model obtained by 50% methanol and D2O as an extraction and dissolution solvent for NMR analysis, 2-, 3-, 4-, and

Acknowledgments

This work was supported by a grant from the BioGreen 21 Program (No. 20070501034007), Rural Development Administration, Republic of Korea.

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    These authors contributed equally to this work.

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