两类红花和牛黄的太赫兹光谱法真伪鉴别分析

doi:10.3964/j.issn.1000-0593(2019)01-0045-05

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Abstract Saffron and natural bezoar are two traditional Chinese medicines widely used in clinical practice. Due to their lower yields, high medicinal value and price, market demand and other factors, more and more adulteration and counterfeit goods not only seriously damage the health of patients but also hinder market normal operation. However, the empirical methods based on observation, smell and soak have become increasingly difficult to distinguish high imitation counterfeits. In addition, the traditional physical and chemical detection techniques through chemical extraction, chromatography and mass spectrometry are cumbersome and time-consuming, and have high requirements and reliance on testing environments, professional ability and equipment. They cannot meet the actual needs of on-site, rapid and simple identification. Thus, it is urgent to explore new and effective detection methods and identification techniques. Terahertz radiation has very low energy and terahertz time-domain spectroscopy (THz-TDS) possesses not only the high specificity of pure compounds but also the “macroscopic fingerprint characteristics” of the hybrid system to identify the diversity and complexity of the chemical composition in the mixture. In addition, as a common statistical analysis method, principal component analysis (PCA) mainly replaces the original variables with a few comprehensive variables that can explain the variance of the original data to the greatest extent and can perform pattern recognition on different kinds of samples. In this work, 18 pieces of saffron and safflower samples as well as 20 groups of natural and artificial bezoar were respectively compressed by using pellet compression. The absorption spectra of two kinds of valuable Chinese medicinal materials and their counterfeit products, saffron and safflower as well as natural and artificial bezoar, were measured using THz time-domain spectroscopy in the range of 0.3~2.5 THz. Finally, the principal component analysis (PCA) was used to identify the obtained data set. In order to improve the identification ability of PCA, on one hand, the data set was mapped to a set of bases (feature vectors) for simplification, and larger eigenvalues were selected instead of describing the original main spectral information; on the other hand, in order to eliminate the impact of noise on the classification process, we adopted Savitzky-Golay(S-G)smoothing before PCA to remove the redundant and irrelevant spectral features; the discriminant analysis was then performed using Fisher’s diagnostic line. Comparing the principal component scores with and without S-G smoothing, classification results with S-G smoothing were obviously distinguished and the first two principal components could basically reflect the differences between spectra. It could be clearly seen that in the unprocessed score plots, the overlapping of the two types of samples is severe, whereas only a relatively small number of sample points overlap in the smoothed score plots, indicating the role of SG smoothing in spectral identification. The classification results showed that the saffron and safflower had obvious clustering trends, and the accuracy of classification identification of saffron and safflower were both 100%; while there was a slight overlap of artificial bezoar and natural bezoar even though the intra-class samples basically gathered together, and the classification accuracy was 100% and 90%, respectively. Furthermore, the principal component score of the sample can also reflect the internal characteristics of the sample and the clustering information. Among them, the saffron sample contains higher compounds of crocin, crocetin and other content, so that better degree of polymerization has been obtained and the distribution is relatively concentrated; on the other hand, the compounds contained in the natural bezoar are more complex. Consequently, the clustering effect is poor and the distribution range is wide. The reliable results based on the THz-TDS and PCA not only distinguish between saffron and safflower as well as natural and artificial bezoar, but also provide the means and theoretical basis for enriching the quality standard of Chinese herbal medicine.

Key words：Terahertz time-domain spectroscopy; Principal component analysis; Saffron; Bezoar

Received: 2018-01-19 Accepted: 2018-05-06

ZTFLH:

O434.3

Corresponding Authors: ZHANG Zhen-wei E-mail: zhangzw_cnu@163.com

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2019)01-0045-05 OR https://www.gpxygpfx.com/EN/Y2019/V39/I01/45