Study on Multi-index Comprehensive Optimization of Tea Extraction Process Based on Orthogonal Design and BP Neural Network Genetic Algorithm

OBJECTIVE To optimize the extraction process of tea by orthogonal design and BP neural network-genetic algorithm. METHODS Using caffeine, EGCG and ECG as the indexes, based on the single factor experiment, orthogonal design and BP neural network-genetic algorithm were used to optimize the ultrasonic-assisted extraction process of effective components in tea, and these process by the two methods were validated. RESULTS The optimum extraction conditions were 85% ethanol concentration, 80℃ and 10 min ultrasonic time. The validation score was 99.050. The optimum extraction scheme obtained by BP neural network-genetic algorithm was ethanol concentration 89%, extraction temperature 88℃, ultrasonic time 13 min, network prediction score 100.758, process verification score 99.651, relative error 1.099%. CONCLUSION BP neural network-genetic algorithm mathematical model can be used to predict and optimize the extraction process of effective components in tea, and slightly better than orthogonal design.