LAUSR

Because of the similar appearance and properties of different quality grades of the product, super Dendrobium huoshanense could be easily adulterated with first-grade D. huoshanense and second-grade D. huoshanense products, thereby affecting its clinical application and causing market distortion. In this study, a combination of hand-held near infrared spectroscopy and chemometrics was used to classify different grades of D. huoshanense. The standard normal variate was employed to preprocess the original near infrared spectra, following which linear analysis models (principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), and a non-linear support vector machine (SVM) model, were utilized to establish the identification models. The results showed that PCA analysis could not identify the three grades of D. huoshanense, and the LDA analysis could distinguish the second-grade from the other two grades. The PLSDA model resulted in prediction accuracies for the calibration cross-validation, and test sets of 91.83%, 83.58%, and 84.29%, respectively. Unfortunately, the super and first-grade D. huoshanense were not identified by the linear analysis model. Further analysis was performed with a non-linear model, where SVM was used to analyze all grades of D. huoshanense. The recognition rate of thel training set and validation set were 88% and 84%, respectively. All in all, the use of a hand-held near infrared spectrometer combined with chemometrics could identify the quality grade of D. huoshanense samples on-site in real-time, and provide a simple, fast, and reliable method for the quality control of the traditional Chinese medicine herb of D. huoshanense.