Quality assessment of Fritillariae cirrhosae using portable NIR spectrometer

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. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This study examined the feasibility of rapidly identifying Fritillariae cirrhosae varieties, distinguishing authenticity, and detecting components using a portable NIR spectrometer. LDA and PLSR algorithms were utilized to achieve high accuracy and prediction determination coefficients in relating sample spectra to reference values.