THz-TDS combined with a fuzzy rule-building expert system applied to the identification of official rhubarb samples

Abstract

Terahertz time-domain spectroscopy (THz-TDS) as a new non-destructive testing method has been applied to the identification of 41 official and unofficial rhubarb samples in the present work. The THz time domain spectra of rhubarb samples were preprocessed and then used to establish an identification model by using fuzzy rule-building expert systems (FuRES). The model was validated using a bootstrapped Latin-partitions (BLPs) method with 10 bootstraps and 4 Latin-partitions. The obtained results showed that the model has good predictive ability with respect to the classification accuracy of 94.8 ± 0.5% and 95.2 ± 0.1% by using the preprocessing methods of Savitzky–Golay (S–G) first derivative combined with either one of two orthogonal signal correction (OSC) methods, respectively. The proposed method showed that THz-TDS combined with chemometrics can be used to identify genuine and counterfeit Chinese herbal medicines, as well as official and unofficial rhubarb.