偏最小二乘回归
化学计量学
化学
线性判别分析
高效液相色谱法
环烯醚萜
色谱法
数学
有机化学
统计
糖苷
作者
Gang He,Xinyan Zhu,Tao Shen,Yuanzhong Wang
标识
DOI:10.1016/j.infrared.2023.105062
摘要
In recent years, people are paying more and more attention to their nutritional health care, and the demand for medicinal plants is increasing year by year, which has aroused widespread concern about their quality. Therefore, the development of methods that enable rapid evaluation of medicinal plants is necessary. The present study was based on 132 Gentiana rigescens (G. rigescens) plants analyzed for the content of total secoiridoids (gentiopicroside, loganic acid, swertiamarin) in different parts of the plant using high performance liquid chromatography. Fourier transform infrared (FT-IR) spectroscopy was also used to characterize the overall chemical information of different parts of G. rigescens. The use of two-dimensional correlation analysis algorithms further improves the acquisition of spectral information and effectively extracts the more chemically informative bands (1750–400 cm−1). On this basis, FT-IR spectroscopy combined with chemometrics was proposed for the prediction of total secoiridoids content in G. rigescens roots, stems and leaves. The results showed that the content of total secoiridoids showed a pattern of root > stem, leaf and gentiopicroside > loganic acid > swertiamarin. Partial least squares discriminant analysis (PLS-DA) was effective in identifying samples from different parts of the body with 100 % model accuracy. The optimized Partial least squares (PLS) model was able to predict the content of gentiopicroside, loganic acid, and swertiamarin in both roots and leaves with RPD values greater than 1.4. Unfortunately, the model had difficulty in predicting the content of loganic acid and swertiamarin in stems (RPD < 1.4). Overall, the method has good stability and applicability, and provides an effective and rapid analytical method for the quality evaluation of medicinal plants.
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