Authentication and classification of black tea from narrow-geographic origins based on the combination of UV-Vis fingerprinting and chemometric methods

Tea is the second most consumed beverage in the world, and its characteristic flavor is due to the chemical components such as catechins, vitamins, amino acids, caffeine, and volatile aroma components derived from tea leaves. The chemical composition of tea leaves determines their quality characteristics. The geographical features and environmental factors such as slope aspect, altitude, soil characteristics, temperature, rainfall, and sun exposure mainly influence this parameter [1]. The combination of UV-Vis spectrophotometry by multivariate data analysis methods for authentication of food products has been recently proposed as an efficient technique in food science and technology [2]. This study investigates the feasibility of UV-Vis spectroscopy coupled with chemometric methods to authenticate tea samples based on their geographical origins in a narrow longitudinal strip (200 km). Black tea samples were obtained from five geographical areas in the Northern provinces of Iran, including Ramsar, Lahijan, Shaft, Leilakooh, and Oshiyan. Samples of 0.1 g of tea were used to perform the extraction process. 40.0 mL of 20% methanol aqueous solution was added to a 0.1 g tea sample and then heated at 80 °C for 20 min in a sealed beaker. The sample was heated on a hot-plate magnetic stirrer equipped with a thermometer. The spectrum of each sample was immediately recorded using a UV–Vis spectrophotometer. Several preprocessing methods, such as standard normal variate (SNV), auto-scaling, multiplicative scatter correction (MSC), mean centering (MC), first derivative, and their combinations, were applied to eliminate the noninformative information. The partial least squares-linear discriminant analysis (PLS-LDA) model using first derivative spectra represented the following results, including 98.0% of sensitivity, 99.6% specificity, and a mean accuracy of 98.0%. The satisfactory results of the models depicted that the chemical components of tea, such as polyphenols, chlorogenic and fatty acids that absorb UV radiation, are the chemical markers that can discriminate tea samples based on their geographical origin. Therefore, UV-Vis spectral fingerprinting combined with chemometrics could be a practical, feasible, and simple method for classifying tea based on their geographical origins in a narrow longitudinal strip.