Multi-source information fusion strategies of aerial parts in FTIR-ATR spectroscopic characterization and classification of Paris polyphylla var. yunnanensis

Abstract

The rational utilization of aerial parts (stem and leaf) of Paris polyphylla var. yunnanensis (P. yunnanensis) is increasingly being studied, due to the growing scarcity of resources. In our study, the geographical origin and cultivation year classification of 662 cultivated P. yunnanensis rhizome, stem and leaf samples from Yuxi, Lijiang and Honghe cities were analyzed by Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectra using principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), random forest (RF) methods combined with multi-source information fusion strategies. Firstly, samples collected from Honghe procedure among all geographical origins were showed higher consistency by biomass analysis. Besides, the PLS-DA model of leaves part was obtained the better geographical origin classification ability than that of underground part (rhizomes), which demonstrate that leaves can be applied to identify geographical origins of P. yunnanensis effectively. And the geographical origins have a greater influence on the P. yunnanensis samples than the cultivation years. Thirdly, the PLS-DA model based on aerial parts combined with high-level multi-source information fusion strategy and important variables selection method can reach the best classification effect (100%) as same as the models of individual dataset of rhizomes. Our study provides a reference for the rational utilization of aerial parts (stems and leaves) for P. yunnanensis such as in the field of fast and effectively classification researches.