Rapid detection of adulteration in by near-infrared spectroscopy coupled with chemometric methods.

To determine the authenticity of , this study presents an application of near-infrared spectroscopy and chemometric methods for evaluating adulteration of with two cheaper adulterants, i.e. C. and . Partial least squares discriminant analysis models were built for the accurate classification of authentic and adulterated at 5-100% (w/w) levels. Partial least squares regression models were used to predict the level of adulteration in the . After by compared different spectral pretreatment methods, and using interval PLS and synergy interval PLS for variable selection, optimum models were developed. These results show that the NIR spectroscopy combined with chemometric methods offers a simple, fast, and reliable method for classifying and quantifying the adulteration of .