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

Abstract

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.