Classification of Paris species according to botanical and geographical origins based on spectroscopic, chromatographic, conventional chemometric analysis and data fusion strategy

Abstract

Given that the consumption of pure varieties for Paridis Rhizome was increasing and causing a “ripple effect”, i.e. numerous other unofficial Paris species were harvested and traded as the succedaneum of Paridis. The purpose of this study was to establish an effective strategy to distinguish Paris species and trace geographical origins of pure varieties of Paridis samples. A total of 87 batch samples of wild Paris were analyzed by UPLC and FTIR. Among them, 79 batch samples of five species and 40 batch samples of Paris polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz were used to establish pattern recognition models of PLS-DA, SVM and random forest simultaneously, basing on polyphyllin content, FTIR spectra, UPLC chromatograms, low- and mid-level data fusion strategy. Quantitative analysis results revealed that more obvious fluctuation of polyphyllin content was shown in different species sample than that of pure varieties of Paridis collected from various origins. Pattern recognition models showed that compared with polyphyllin content, FTIR spectra, UPLC chromatograms and low-level data fusion method, mid-level data fusion strategy showed a better accuracy (>92%) in PLS-DA model to classify Paridis samples according to botanical and geographical origins. Similar results were obtained in SVM and random forest models. Thus, the classification of these three pattern recognition models were verified each other and demonstrated that mid-level data fusion strategy combined with chemometrics could recognize different Paris species and trace the pure varieties of Paridis geographical origins, correctly.