Abstract
Dendrobium huoshanense (DHS) is a typical traditional Chinese medicine with unique medical and high economic values; however, it may easily be adulterated with cheaper alternatives (e.g. Dendrobium henanese, DHN), because of their similar appearances and tastes. In this study, adulteration of DHN in DHS was detected by near infrared (NIR) spectroscopy combined with chemometric methods. By performing partial least squares (PLS) analysis, PLS multivariate methods including partial least-squares discriminant analysis (PLS-DA), and partial least-squares regressions (PLSR) were applied to the obtained spectral data to build models. The PLS-DA model was employed to differentiate between pure DHS samples and those adulterated with DHN. The R2 value obtained for the PLS-DA model was 0.4898 with an RMSEP error of 0.1554, resulting in a 100% accuracy of validation sample sets. Similarly, a PLSR model was also developed to quantify the amount of DHN adulterant in DHS samples. Experimental results indicated that the good performance of the multiplicative scattering correction (MSC) model is the better model showing a prediction performance of RMSEP of 2.38 and R2 of 0.9946. These results suggest that the combination of NIR spectroscopy and chemometric method provides a fast, simple and reliable method for detecting adulteration of DHS. The method of classification allowed identification of both authentic and adulterated DHS samples. Comparison of six different techniques for spectra preprocessing to improve quantitative model performance was obtained with MSC derivative spectra. The method can detect most of the current DHS adulterations in the Chinese market.
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