Detection of the Adulteration of Dendrobium Huoshanense with Dendrobium Henanense by UV-Vis-Shortwave Near-Infrared Diffuse Reflectance Spectroscopy Combined with Chemometrics

J AOAC Int. 2024 Jan 4;107(1):158-163. doi: 10.1093/jaoacint/qsad090.

Abstract

Background: Dendrobium huoshanense (DHS) is a classic traditional Chinese medicine (TCM) with distinctive medicinal benefits and great economic worth; nevertheless, because of similar tastes and looks, it is simple to adulterate with less expensive substitutes (such as Dendrobium henanense [DHN]).

Objective: This work aimed to develop a reliable tool to detect and quantify the adulteration of DHS with DHN by using UV-Vis-shortwave near-infrared diffuse reflectance spectroscopy (UV-Vis-SWNIR DRS) combined with chemometrics.

Methods: Adulterated samples prepared in varying concentrations (0-100%, w/w) were analyzed with UV-Vis-SWNIR DRS methods. Partial least-square-discriminant analysis (PLS-DA) and partial least-squares (PLS) regression techniques were used for the differentiation of adulterated DHN from pure DHS and the prediction of adulteration levels.

Results: The PLS-DA classification models successfully differentiated adulterated and nonadulterated DHS with an over 100% correct classification rate. UV-Vis-SWNIR DRS data were also successfully used to predict adulteration levels with a high coefficient of determination for calibration (0.9924) and prediction (0.9906) models and low error values for calibration (3.863%) and prediction (5.067%).

Conclusion: UV-Vis-SWNIR DRS, as a fast and environmentally friendly tool, has great potential for both the identification and quantification of adulteration practices involving herbal medicines and foods.

Highlights: UV-Vis-SWNIR DRS combined with chemometrics can be applied to identify and quantify the adulteration of herbal medicines and foods.

MeSH terms

  • Chemometrics
  • Dendrobium*
  • Discriminant Analysis
  • Food Contamination / analysis
  • Least-Squares Analysis
  • Plant Extracts
  • Spectroscopy, Near-Infrared / methods

Substances

  • Plant Extracts