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This study aimed to focus on applying near-infrared (NIR) spectroscopy to identify the adulteration of traditional Thai medicine products (TTM) with steroids. One hundred and ten samples were prepared with pure TTM and ten different steroid concentrations (0.25-5 mg steroid/g TTM). Fourier transform near-infrared (FT-NIR) spectrometer was used to scan TTM samples. The partial least squares (PLS) regression was used for the NIR spectroscopic model development to predict the level of steroid adulteration in TTM. For classification analysis, the principal component analysis (PCA) was used to discriminate 11 groups of raw TTM spectra (220 spectra). The developed PLS model accompanied by 3 latent variables (LVs) could predict the steroid content in TTM accurately with the coefficient of determination of prediction (r2) of 98.20%, root mean square error of prediction (RMSEP) of 0.22 mg steroid/g TTM, and residual prediction deviation (RPD) of 7.46. Furthermore, the PCA approach was possible to discriminate among the groups of TTM. The study showed NIR spectroscopy's capability to be used as a powerful technique to evaluate the steroid adulterated in TTM. This report is useful for food and drug association, patients, pharmaceuticals, and medical sectors.
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