Non-targeted metabolomic analysis of variation of volatile fractions of ginseng from different habitats by HS-SPME-GC-MS coupled with chemometrics

Origin differentiation based on volatile constituents of genuine medicinal materials Quisqualis indica L. via HS-GC-MS, response surface methodology, and chemometrics

INTRODUCTION

Quisqualis indica L. (QIL) has a long history as a traditional Chinese herb in China, but the study of volatile components in QIL from different geographical sources has been relatively rare.

OBJECTIVES

To establish an optimal headspace gas chromatography-mass spectrometry (HS-GC-MS) method to comprehensively analyse the volatile component profile and screen quality markers of QIL from different origins.

METHODS

Response surface methodology (RSM) was used to optimise the conditions for headspace analysis. The volatile components of QIL from four main origins of southwest China were analysed and identified by HS-GC-MS. The similarity of all samples of QIL was evaluated by fingerprint. The differences of the volatile components in QIL from different origins were distinguished by chemometrics.

RESULTS

According to the optimal conditions of RSM, a total of 31 volatile components were identified, including fatty acids, aldehydes, alcohols, alkyl pyrazines, and other volatile components. Similarity evaluation presented that there were 26 common volatile components with different contents in all samples. Principal component analysis (PCA) showed that QIL from four different origins could be roughly divided into four categories. Hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) indicated that QIL from different origins had obvious regional characteristics.

CONCLUSION

The optimised HS-GC-MS method provided a strategy to rapidly, effectively, and accurately elucidate the volatile component profile of QIL from different origins, and seven important differential components were screened for quality evaluation and origin traceability.

Development of a variety and quality evaluation method for Amomi fructus using GC, electronic tongue, and electronic nose

Amomi fructus is rich in volatile components and valuable as a medicine and edible spice. However, the quality of commercially available A. fructus varies, and issues with mixed sources and adulteration by similar products are common. In addition, due to incomplete identification methods, rapid detection of the purchased A. fructus quality is still an issue. In this study, we developed qualitative and quantitative evaluation models to assess the variety and quality of A. fructus using GC, electronic tongue, and electronic nose to provide a rapid and accurate variety and quality evaluation method of A. fructus. The models performed well; the qualitative authenticity model had an accuracy of 1.00 (n = 64), the accuracy of the qualitative origin model was 0.86 (n = 44), and the quantitative model was optimal on the sensory fusion data from the electronic tongue and electronic nose combined with borneol acetate content, with R ² = 0.7944, RMSEF = 0.1050, and RMSEP = 0.1349. The electronic tongue and electronic nose combined with GC quickly and accurately evaluated the variety and quality of A. fructus, and the introduction of multi-source information fusion technology improved the model prediction accuracy. This study provides a useful tool for quality evaluation of medicine and food.

Differentiation of Mountain- and Garden-Cultivated Ginseng with Different Growth Years Using HS-SPME-GC-MS Coupled with Chemometrics

Although there are differences in the appearance of Mountain-Cultivated Ginseng (MCG) and Garden-Cultivated Ginseng (GCG), it is very difficult to distinguish them when the samples are processed to slices or powder. Moreover, there is significant price difference between them, which leads to the widespread adulteration or falsification in the market. Thus, the authentication of MCG and GCG is crucial for the effectiveness, safety, and quality stability of ginseng. In the present study, a headspace solid-phase microextraction gas chromatography mass spectrometry (HS-SPME-GC-MS) coupled with chemometrics approach was developed to characterize the volatile component profiles in MCG and GCG with 5-,10-,15-growth years, and subsequently to discover differentiating chemical markers. As a result, we characterized, for the first time, 46 volatile components from all the samples by using the NIST database and the Wiley library. The base peak intensity chromatograms were subjected to multivariate statistical analysis to comprehensively compare the chemical differences among the above samples. MCG_{5-,10-,15-years} and GCG_{5-,10-,15-years} samples were mainly divided into two groups by unsupervised principal component analysis (PCA), and 5 potential cultivation-dependent markers were discovered based on orthogonal partial least squares-discriminant analysis (OPLS-DA). Moreover, MCG_{5-,10-,15-years} samples were divided into three blocks, and 12 potential growth-year-dependent markers enabled differentiation. Similarly, GCG_{5-,10-,15-years} samples were also separated into three groups, and six potential growth-year-dependent markers were determined. The proposed approach could be applied to directly distinguish MCG and GCG with different growth years and to identify the differentiation chemo-markers, which is an important criterion for evaluating the effectiveness, safety, and quality stability of ginseng.