Sandalwood is one of the most valuable woods in the world. However, today's counterfeits are widespread, it is difficult to distinguish authenticity. In this paper, similar genus ( Dalbergia and Pterocarpus ) and confused species ( Gluta sp .) of sandalwood were quickly and efficiently identified. Rapid identification model based on 1 H NMR and decision tree (DT) algorithm was firstly developed for the identification of sandalwood, and the accuracy was improved by introducing the AdaBoost algorithm. The accuracy of the final model was above 95%. And the feature components between different species of sandalwood were further explored using UHPLC-QTOFMS and NMR spectrometry. The results showed that 183 compounds were identified, among which 99 were known components, 84 were unknown components. The 1 H NMR and 13 C NMR signals of 505 samples were assigned, among them, 14 compounds were attributed, characteristic chemical shift intervals with great differences in the model were analysed. Furthermore, the fragmentation pattern of different compounds from sandalwood, in both positive and negative ion ESI modes, was summarized. The results showed a potential and rapid tool based on DT, NMR spectroscopy and UHPLC-QTOFMS, which had performed great potential for rapid identification and feature analysis of sandalwood.
American ginseng and Asian ginseng products have similar appearance, however, the huge price differences for various species and grades of ginseng lead to the widespread adulteration in the commercial market. We herein reported an efficient colorimetric sensor array for ginseng discrimination through analysis of diols composition (e.g. monosaccharide and ginsenoside). The sensor array was rationally designed based on two mechanisms, changes in pH and indicators displacement assay (IDA), with phenylboronic acid as the receptor to diols. The excellent discrimination capability of the sensor array was validated upon analysis of different species or concentrations of monosaccharides in ginseng hydrolysate. 40 ginseng samples within three categories (cultivated American ginseng, wild American ginseng and Asian ginseng) were successfully classified using the sensor array coupled with a statistical analysis such as hierarchy cluster analysis (HCA) and principal component analysis (PCA). Our work provided a simple and effective method for the fast discrimination and quality control of ginseng products.
危险品化学品经营许可证（带存储）