Abstract: Objective: In order to construct a quantitative evaluation model of Baoqing Guiding black tea based on chromatic aberration. Methods: Baoqing Guiding black tea were used as materials. On the basis of sensory evaluation, the chromatic aberration value of dry tea, tea infusion and infused leaf were measured respectively. The correlation between chromatic aberration value and tea quality were analyzed, and the quality evaluation model were constructed by GA-BP neural networks. Results: The quality of Baoqing Guiding black tea was extremely significant correlated with the Lab value of tea infusion and leaves (P<0.01), and significantly correlated with the a value of dry tea (P<0.05). The introduction of genetic algorithm (GA) obviously improved the fitting accuracy of BP neural network, the coefficient of determination (R²) of GA-BP model was obviously higher than BP model. By comparing different hidden layer structures, the GA-BP neural network with structure of 9-5-1 were selected. The determination coefficients (R²) of training, verification, test and prediction of optimized GA-BP model were 0.988, 0.976, 0.933 and 0.95 respectively. Conclusion: The quantitative quality evaluation method of Baoqing Guiding black tea based on chromatic aberration and GA-BP neural network was feasible.