Abstract
Dendrobium huoshanense (DHS) has long been used to make tea drink, soup, and porridge to protect eye and liver in many Southeast Asian countries for centuries. As a rare and endangered functional food, adulteration in DHS with visually similar but cheaper and more accessible plants such as Dendrobium henanense (DHN) because of their similarities in morphology has become prevalent in the market. In this study, the Attenuated Total Reflectance Fourier transform Infrared Spectroscopy (ATR-FTIR) combined with chemometric methods was established to detect fraudulent addition in DHS with DHN. The partial least squares (PLS) models based on the ATR-FTIR files of DHS mixed with different proportions of DHN were built under cross validation and tested with different independent data sets. To reduce the variables' lack of information and increase the accuracy of the model, different wavelength selection methods including Moving Window Partial Least Squares (MW-PLS), Monte Carlo-uninformative variable elimination (MC-UVE), and interval random frog (iRF) were compared.The results showed that iRF performed the most perfectly with the number of latent variables (nLVs = 7), the lowest Root Mean Square Error of Cross-Validation (RMSECV = 7.37), and the maximum determination coefficients (R(2) = 0.9721). The excellent performance of the model was proved by the low RMSEP value of 6.44% and the high R(2) value of 0.9556. The developed method could rapidly quantify the adulteration DHN in DHS, and our study might provide an efficient and great potential technique tool for the rapid, green, low-cost, and nondestructive identification and quantification for DHS adulterated with DHN.