Work

Rapid Identification of Vicatia thibetica de Boiss and Quantitative Analysis of the Content of Six Chemical Components Based on Near-Infrared Spectroscopy

Year: 2025

Type: article

Abstract: In this study, a rapid, accurate, objective, and cost-effective method for identifying and evaluating the quality of Vicatia thibetica de Boiss (V. thibetica) herbs were established. This study developed and employed a method that integrates near-infrared (NIR) spectroscopy with orthogonal partial least squares-discriminant analysis (OPLS-DA) and artificial neural networks (ANN) to address two major challenges in the origin identification and quality evaluation of V. thibetica rhizome medicinal materials. The results demonstrated that the combination of NIR spectroscopy, OPLS-DA, and ANN successfully and accurately distinguished V. thibetica from three distinct origins. Additionally, combining partial least squares (PLS) and NIR spectroscopy, the contents of chlorogenic acid, isochlorogenic acid A, isochlorogenic acid C, umbelliferolide, senkyunolide I, and ligustilide measured by HPLC-UV were used as reference values to predict the contents of the six chemical components in V. thibetica, and spectral preprocessing methods optimized the model, and the correlation coefficients of the final quantitative model for the contents of the six components in V. thibetica were between 0.7852 ~ 0.9538, the root mean square error of calibration (RMSEC) was between 0.0027 and 0.2530, and the root mean square error of prediction(RMSEP) was between 0.0031 and 0.4240. The results suggest that NIR spectroscopy combined with OPLS-DA and ANN can be used as a rapid and accurate method to evaluate the quality of V. thibetica herbs.

Source: Molecules

DOI: 10.3390/molecules30091867