Ginseng in the spotlight

Three notable studies on different analytical approaches have been published in 2013 on the subject of ginseng authentication.

Reviewed: Yuk J, McIntyre KL, Fischer C, et al. Distinguishing Ontario ginseng landraces and ginseng species using NMR-based metabolomics. Anal Bioanal Chem. May 2013;405(13):4499-4509. Abstract available at http://link.springer.com/article/10.1007%2Fs00216-012-6582-6.

Yuk et al. used ¹H-NMR [nuclear magnetic resonance]-based metabolomics to distinguish five American ginseng (Panax quinquefolius, Araliaceae) landraces (a landrace is a dynamic population of a cultivated plant that has historical origin, distinct identity, and lacks formal crop improvement, as well as often being genetically diverse, locally adapted, and associated with traditional farming systems)¹ grown in Ontario, Canada, and the two ginseng species, P. quinquefolius and Asian ginseng (P. ginseng). The various landraces were distinguishable on the basis of differences in the methyl ginsenoside region, and in the levels of sucrose and ginsenoside Rb₁. The Ontario P. quinquefolius was also compared with Asian P. ginseng by principal component analysis (PCA), and a clear separation between the two groups was observed due to an increased level of maltose and a decreased level of sucrose in Asian ginseng compared to American ginseng. Lower ginsenoside content, especially ginsenoside Rb₁, was also detected in the Asian ginseng’s metabolic profile. The authors conclude that nuclear magnetic resonance (NMR)-based metabolomics are a powerful high-throughput technique to distinguish closely related ginseng landraces and to identify metabolic differences from American and Asian ginseng.

Comment: In most cases, there is no need to differentiate between the same species growing in different regions. For typical identification purposes, P. quinquefolius growing in Canada, Wisconsin, China, or West Virginia are usually all acceptable as American ginseng. However, e.g., the State of Wisconsin has instituted a “Wisconsin-grown Certification Seal” in the Hong Kong market, to distinguish Wisconsin ginseng from “China white” (Chinese-grown American ginseng), as well as Ontario and British Columbia supply sources. In this situation the technology described in this article is highly relevant. But while this is a very powerful technology, NMR is also an expensive technology so it remains to be seen how extensively it will be integrated into industry GMPs.

Reference

1.       Camacho Villa TC, Maxted N, Scholten M, Ford-Lloyd B. Defining and identifying crop landraces. Plant Genetic Resources: Characterization and Utilization. 2005;3(3):373-384.

Reviewed: Cui S, Wang J, Geng L, Wei Z, Tian X. Determination of ginseng with different ages using a taste-sensing system. Sensors and Materials. 2013;25(4 ):241-255. Abstract available at http://myukk.org/SM0917.html.

The paper by Cui et al. focused on the reported adulteration of P. ginseng root with ginseng root materials of younger age, considered of lesser value. The authors compared results of a sensory evaluation with those obtained using a UV method for total ginsenosides. The taste measurements were carried out using a taste-sensing system with different electrodes to measure sourness, sweetness, saltiness, astringency, umami (a category best described as resembling the taste of monosodium glutamate), and bitterness.

The authors found a linear correlation between the increase in root age, ginsenoside contents, and sourness. The umami and saltiness showed an inverse correlation, which means that both taste attributes were less pronounced in older material. Other taste measures did not correlate with the age of the ginseng materials. The authors suggested that the taste measurement produces more informative quality data than the evaluation of a single class of phytochemicals and propose the use of sensory measurements as an economic alternative to ginsenoside quantification for the detection of ginseng root material of lesser value.

Comment: The paper has a few shortcomings, like an abundance of spelling errors and the use of an ultraviolet (UV) methodology to measure total ginsenosides after derivatization with vanillin-sulfuric acid, which is a non-specific method with many possible interferences. But the idea of an objective evaluation of multiple sensory properties of a medicinal herb has potential merit and the technology may prove to be a valuable addition to the quality control tools available to manufacturers of herbal products. Since in traditional Chinese medicine older roots are considered more desirable than younger roots, this may be of particular interest to manufacturers of Chinese herbal products.

Reviewed: Harnly J, Chen P, Harrington P de B. Probability of identification: Adulteration of American ginseng with Asian ginseng. J AOAC Int. 2013;96(6):1258-1265. Abstract available at http://www.ingentaconnect.com/content/aoac/jaoac/2013/00000096/00000006/art00013?crawler=true.

In the last paper reviewed here, Harnly et al. applied the AOAC International guidelines for validation of botanical identification methods to the detection of P. ginseng as an adulterant to P. quinquefolius using spectral fingerprints obtained by flow injection mass spectrometry (FIMS). Samples of 100% American ginseng and 100% Asian ginseng were physically mixed to provide 90, 80, and 50% American ginseng. According to the authors, the distinction of 100% American ginseng from a 90% American ginseng – 10% Asian ginseng mixture at a 95% confidence level requires the analysis of a minimum of 40 samples with correct results. The multivariate FIMS fingerprint data were analyzed using soft independent modeling of class analogy (SIMCA) based on 100% American ginseng. FIMS was able to discriminate between 100% American ginseng and 100% Asian ginseng, and between 100% American ginseng and 90, 80, and 50% American ginseng. The probability of identification (POI) curve was estimated based on the standard deviation of 90% American ginseng. Two chemometric* modeling methods (SIMCA and fuzzy optimal associative memories) and two classification methods (partial least squares-discriminant analysis and fuzzy rule-building expert systems) were applied to the data. The modeling methods correctly identified the adulterated samples; the classification methods did not.

Comment: Authentication based on statistical methods has established itself as state of the art for raw material identification. As such, the work performed by the authors can be viewed as the “gold standard” for a botanical identification method. The protocol suggested by AOAC makes sense from a mathematical and statistical point of view, and seems to require a reasonable amount of work if there is only one possible adulterant that needs to be included in the test system. However, for certain raw materials, there are many known adulterants, so the workload becomes increasingly heavy, and, depending on the herb in question, finding enough botanically authenticated material of the species in question and its potential adulterants can be a challenging task. The FIMS method combined with statistical data analysis should provide correct results for unknown adulterants as well, if present in significant amounts, but for obvious reasons (it is not possible to make well-defined mixtures of American ginseng and the unknown adulterant), the POI cannot be determined in such cases.

* Chemometrics is the science of relating chemical measurements to the state of the system, e.g., the quality of an herbal material, via statistical methods.