偏最小二乘回归
线性判别分析
近红外光谱
化学
色谱法
相关系数
数学
分析化学(期刊)
统计
物理
量子力学
作者
Linhong Fan,Shuqin Liu,Wenxiang Fan,Lin He,Chunling Zhang,Chunjie Wu,Yong‐Liang Huang
标识
DOI:10.1016/j.saa.2021.120325
摘要
This paper mainly focuses on the feasibility of rapidly identifying Fritillariae cirrhosae varieties, distinguishing its authenticity and detecting its components by using a portable near infrared (NIR) spectrometer. Five different varieties of Fritillariae cirrhosae, five common counterfeits and two main components (ethanol-soluble extractives and total alkaloids) were studied. The reference values of ethanol-soluble extractives were determined by hot dip method and the reference value of total alkaloid was determined by ultraviolet–visible spectrophotometry (UV–Vis). Linear discriminant analysis (LDA) algorithm was used to identify the sources of different varieties of Fritillariae cirrhosae and the common counterfeits of Fritillariae cirrhosae, respectively. As a result, the best models seemed to be effective, with accuracy of the two models' prediction sets reaches 83.33% and 90.91%, respectively. The partial least squares regression (PLSR) algorithm was used to relate the sample spectra with the reference values of ethanol-soluble extractives and total alkaloid content. Coefficient of determination of prediction (R2p) and root mean square errors of prediction (RMSEP) obtained were 0.8562 and 0.3911; 0.6917 and 0.0117, for ethanol-soluble extractives and total alkaloid content, respectively. The results showed that the portable NIR spectrometer could evaluate the quality of Fritillariae cirrhosae with high efficiency and practicability.
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