Research on Flavonoids Based on Terahertz Time-Domain Spectroscopy
YIN Ming1, WANG Jian-lin1, HUANG Hao-liang1, HUANG Qiu-ping2, YANG Meng-meng1, FU Zheng-ping3, LU Ya-lin2*
1. National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230026, China
2. Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
3. School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China
Abstract：Flavonoids are a large class of polyphenols widely distributed in plants in the form of free or glycoside, which has anti-oxidation, anti-bacterial, anti-viral, anti-tumor growth and other pharmacological effects. As an important active component of traditional Chinese medicine, they have high medicinal value and development prospect. In this paper, the biomolecular properties of eight common flavonoids, including baicalein, quercetin, naringenin, daidzein, baicalin, puerarin, genistein and gastrodin, were studied by terahertz time-domain spectroscopy (THz-TDS) in the 0.2～2.5 THz band. The results showed that these flavonoids have different characteristic absorption peaks in the terahertz band. The terahertz absorption characteristics with temperature variation in the range of 78～320 K were studied. The results showed that the characteristic absorption peaks gradually increased with the decrease of temperature, and the frequency position of absorption peak was blue-shifted. In addition, Qualitative identification and quantitative analysis of flavonoids were carried out by chemometrics combined with terahertz absorption spectra. First, the spectral characteristic variables were extracted by principal component analysis (PCA), then the first five principal components were used as input variables of support vector machine (SVM) to establish a classification model, and the optimal parameters were selected through the optimization model, and finally, the classification accuracy of 100% was obtained. In addition, the partial least squares regression (PLSR) model and the artificial neural network (ANN) model were used to analyze the flavonoids with different concentrations in starch quantitatively. By comparing the two methods, the ANN model obtained the highest prediction accuracy. The correlation coefficients of naringenin and daidzein in the prediction set were R2=0.994 4, R2=0.996 4, and the root means square error was RMSE=1.932 5 and RMSE=1.544 1, respectively. In summary, the biomolecular properties of flavonoids were studied by THz-TDS technology, and a rapid, effective and non-destructive qualitative identification and quantitative analysis of flavonoids were provided. This method has potential application value in the detection of Chinese herbal medicine, and has better reference significance for the study of other biomolecules.
殷 明，王建林，黄浩亮，黄秋萍，杨萌萌，傅正平，陆亚林. 基于太赫兹时域光谱技术的黄酮类化合物研究[J]. 光谱学与光谱分析, 2020, 40(12): 3919-3924.
YIN Ming, WANG Jian-lin, HUANG Hao-liang, HUANG Qiu-ping, YANG Meng-meng, FU Zheng-ping, LU Ya-lin. Research on Flavonoids Based on Terahertz Time-Domain Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3919-3924.
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