Discrimination of raw and sulfur-fumigated ginseng based on Fourier transform infrared spectroscopy coupled with chemometrics

Abstract

Ginseng (Panax ginseng), as a tonic and functional food in many countries and regions for thousands of years, is often sulfur-fumigated (SF) for storage and protection. However, our previous study indicated sulfur-fumigation could transform ginsenosides, the active components of ginseng, into sulfur-containing derivatives and thus affect the quality and safety of ginseng. In this study, a rapid and efficient method in discrimination of non-fumigated (NF) and SF ginseng was developed using Fourier transform infrared (FT-IR) spectroscopy coupled with multivariate statistical analysis. A total of 240 batches of raw spectra were obtained from NF and SF ginseng by FT-IR spectroscopy. After excluding the outliers, the different performance of 3 spectral signal enhancing methods, 3 modeling evaluation methods, and 4 model evaluation indexes were compared. The results demonstrated the feasibility of using FT-IR spectroscopy between 3650 and 3200 cm−1 for the detection of sulfur-fumigation in ginseng. After sulfur fumigation, the peak areas in fingerprint and functional group area varied significantly. In addition, the parameters of back propagation artificial neural network (BP-ANN) evaluation model are the highest, its accuracy = 91.67%, precision = 89.29%, recall = 96.15%, and F1 = 92.59%. The error rates of 3 models were k-nearest neighbor algorithm (KNN) (25.00%) > logistic regression (LR) (16.67%) > BP-ANN (8.33%). It can be concluded that FT-IR spectroscopy combined with multivariate statistical analysis has great potential in rapid discrimination of NF and SF ginseng, which can provide a valuable reference for the quality and effectiveness of edible and medicinal application of ginseng.