Detection of tea adulterants using Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics

Food adulteration is a major global concern due to its economic implications and potential health risks. This study aimed to develop and validate a rapid and reliable method to quantify sugar adulteration in black tea representing the major tea-growing regions of Sri Lanka, as well as to qualitatively identify maltodextrin adulteration using Fourier transform near-infrared spectroscopy (FT-NIR). Partial least squares regression models were established for sugar quantification, while high-performance liquid chromatography was used as the reference method for quantitative sugar analysis and qualitative detection of maltodextrin. The developed models demostrated strong predictive performance, with coefficients of determination of 0.89 for fructose, 0.90 for sucrose, and 0.93 for glucose, and residual predictive deviation values exceeding 2.5 for sugars. Furthermore, principal component analysis clearly differentiated maltodextrin-adulterated tea from pure samples, explaining 89% of the total variance, demonstrating the suitability of FT-NIR spectroscopy for rapid adulteration detection in black tea.