Building the Oolong Tea Grade Judgement Model Based on Interior Quality Parameters

Tea grade evaluation is an important technical method to test the quality of tea, and scientifically building the tea grade evaluation model has an important significance. This paper took 102 Oolong teas as research object and built the Oolong tea grade evaluation model based on interior quality parameters with various characteristic value screening methods in combination with support vector machine algorithm. Meanwhile, by combining hyperspectral technology with chemometrics, this paper built the quantitative forecast model of particle swarm optimization back propagation neural network (PSO-BP) based on characteristic wavelength and sparrow search algorithm optimization least squares support vector machine (SSA-LSSVM) for characteristic quality parameters, and finally verified the chemical value model of quantitative forecast. The results showed that in case of parameter combination of ester catechin, simple catechin, tea polyphenol, aqueous extract, caffeine and epigallocatechin gallate (EGCG), the Oolong t