OPTIMIZATION OF EXTRACTION CONDITIONS OF SHIKIMIC ACID IN PINE NEEDLES BASED ON ARTIFICIAL NEURAL NETWORK

摘要

In this study, taking ethanol as the solvent and using ultrasonic-assisted extraction method, the authors extracted the shikimic acid in pinus elliottii needles, and measured the content of shikimic acid through high performance liquid chromatography (HPLC). Through single factor experiment and orthogonal experiment, the optimum extraction conditions of ultrasonic-assisted extraction method were defined: the ultrasonic power is 250W; the ethanol concentration is 65%;the ultrasonic-assisted extraction temperature is 60°C;the material-liquid ratio is 1:23; the extraction time is 15 minutes. Then, based on orthogonal experiment, the authors constructed an artificial neural network optimization model: the ethanol concentration is 77.5%;the ultrasonic-assisted extraction temperature is 65°C; the material-liquid ratio is 1:28; the extraction time is 25 minutes. Experiments show that the result obtained through artificial neural network is better than that of orthogonal experiment. The differences between the two results lie in the interaction between multiple factors.