响应面结合数学模型优化提取黑灵芝三萜成分

Extraction of Triterpenoids from Ganoderma atrum Optimized by Response Surface Enzyme and BP Neural Network Combined with Genetic Algorithm

采用单因素试验和Box-Behnken试验,考察乙醇体积分数、酶解时间、加酶量和料液比对黑灵芝中三萜类成分提取率的影响。运用响应面和BP神经网络结合遗传算法对超声辅助酶法提取黑灵芝中三萜类成分的工艺条件进行优化。结果表明,各因素对黑灵芝中三萜类成分的提取率影响明显。采用优化后的超声辅助酶法提取黑灵芝中三萜类成分的工艺条件:乙醇体积分数83.16%、酶解时间49.89 min、加酶量4.02%、料液比1∶25.85 g/mL。在此工艺条件下预测的三萜提取率理论值为21.11 mg/g。

Single factor experiment and Box-Behnken experiment were conducted to investigate the effects of ethanol concentration, enzymatic hydrolysis time, enzyme dosage and solid-liquid ratio on the extraction yield of triterpenoids from Ganoderma atrum. Response surface and BP neural network combined with genetic algorithm were used to optimize the ultrasonic assisted enzymatic extraction of triterpenoids from Ganoderma atrum. The results showed that the extraction rate of triterpenoids from Ganoderma atrum was significantly affected by various factors. The optimized ultrasonic assisted enzymatic extraction conditions of triterpenoids from Ganoderma atrum were as follows: ethanol concentration 83.16%,enzymatic hydrolysis time 49.89 min, enzyme dosage 4.02%, solid-liquid ratio 1∶25.85 g/mL. The predicted extraction yield of triterpenoids was 21.11 mg/g under this condition.