Rapid Identification of Peucedanum praeruptorum Dunn and Its Adulterants by Hand-Held Near-Infrared Spectroscopy

Background Peucedanum praeruptorum Dunn (PPD) is a traditional Chinese medical herb of high medical and economic value. However, PPD is often adulterated by inexpensive plants. Objective In order to establish an integrated and straightforward methodology to identify adulterated PPD products, hand-held near-infrared spectroscopy (NIRS) combined with chemical pattern recognition techniques was employed. Method The standard normal variate (SNV) was used to preprocess the original near-infrared spectra. Principal component analysis (PCA), linear discriminant analysis (LDA), and partial least-squares regression analysis (PLSDA) were used to construct the recognition models. Results PCA analysis could not correctly distinguish PPD from non-PPD. However, based on absorbance in the spectral region of 1405-2442 nm and SNV pretreatment, the accuracy of the LDA model was above 90% at identifying genuine PPD. Compared with the LDA method, the PLSDA model is more stable and reliable, and its model prediction accuracy was 93.4%. Conclusion The combination of NIRS and chemometric methods based on a hand-held near-infrared spectrometer is an efficient, nondestructive, and reliable method for validating traditional Chinese medicine PPD. Highlights: The advanced method based on a hand-held near-infrared spectrometer can be used for rapid identification and quality evaluation of PPD in the field, medicinal material markets, and points of sale.