Rapid geographical origin analysis of pure West Lake lotus root powder (WL-LRP) by near-infrared spectroscopy combined with multivariate class modeling techniques

Abstract

A rapid analysis method was proposed for the identification of a popular traditional Chinese food with Protected Geographical Indication (PGI), West Lake lotus root powder (WL-LRP), by near-infrared spectroscopy and chemometric methods. A set of 105 pure and real WL-LRP samples were collected from 9 main producers to obtain a representative training set of the authentic objects. 95 non-WL-LRP samples from 8 different main lotus producing areas of China were analyzed for validation of model specificity. Linear partial least squares class model (PLSCM) and nonlinear support vector data description (SVDD) were used to develop quality control models of authentic and pure WL-LRP objects. Spectral data were preprocessed by taking derivatives and standard normal variate (SNV) transformation. The analysis results indicate performing SNV transformation can obtain more stable and accurate models compared with taking derivatives. The best models were obtained with SNV spectra, the sensitivity and specificity was 0.87 and 0.90 for PLSCM, 0.93 and 0.92 for SVDD, respectively.