classification and authentication of iranian tea according to their geographical origin based on uv-vis spectral fingerprinting using pattern recognition methods

Abstract: the chemical composition of tea, as one of the most important quality characteristics, depends on several parameters including the genetic nature of the plant, climatic conditions (temperature, sun exposure time, rainfall), growth altitude, soil and horticultural practices, the plucking time, sorting of the leaves, the processing steps and the storage conditions [1].the reputation of particular countries and farms in producing high quality tea allowed these producers to offer higher prices for their specific product. this may tempt some manufacturers to use a fraudulent label in order to introduce their tea product as the product of these famous areas, so that they can sell their product at a higher price [2]. this has made consumers sensitive and precise to know the exact geographical origin of the tea crop.classification of tea samples based on the geographical origin was investigated using the uv-vis spectra. tea samples from five regions in north of iran were collected during the harvesting period 2018–2019. mean centering (mc), multiplicative scatter correction (msc), standard normal variate (snv) and their combinations, were employed as the spectral pre-processing methods in order to improve the quality of the spectra. principal component analysis (pca), principal component analysis-linear discriminant analysis (pca-lda) and partial least square-linear discriminant analysis (pls-lda) were employed in order to assess the feasibility of discrimination of tea samples. the results showed that the tea samples can be identified based on their geographical regions using uv-vis spectral fingerprints. a high percentage of correct classifications for the training set using cross validation shows the strong relationship between the uv-vis spectral fingerprinting and the geographical region, while the satisfactory results for the prediction set demonstrates the ability to identify the geographical origin of an unknown tea sample based on its uv-vis spectral data.