Discrimination and quantification analysis of Acorus calamus L. and Acorus tatarinowii Schott with near-infrared reflection spectroscopy

A rapid near-infrared reflection (NIR) spectroscopy analysis method was developed for discrimination of the dried rhizome part of Acorus calamus L. and Acorus tatarinowii Schott, two kinds of traditional Chinese herbs that are sometimes mixed or used interchangeably, and the simultaneous determination of their main components beta-asarone and alpha-asarone. The NIR spectra of 25 Acorus calamus L. samples and 25 Acorus tatarinowii Schott samples were collected in integrating-sphere diffused reflection mode and pre-processed with different methods. Principal component analysis (PCA) and discriminant partial least squares (DPLS) were applied to discriminate Acorus calamus L. from Acorus tatarinowii Schott, and the latter method proved better, more visual and effective. The quantitative models of beta-asarone and aasarone were developed using partial least squares regression (PLSR) as multivariate regression method with optimum spectral pre-processing method, wavenumber range and latent variables (LV) numbers, and the results from ultra performance liquid chromatography (UPLC) analysis were taken as reference values. The correlation coefficients of the quantitative models of beta-asarone and alpha-asarone are all above 0.98 while the root mean square errors of prediction (RMSEP) are all below 0.6%, indicating that the models we established have good predictive ability. The results demonstrate that NIR spectroscopy could be used to solve analogous problems for the safety of clinical medication, and can also be applied in the medical industry for the quality control of Acorus calamus L. and Acorus tatarinowii Schott.