基于BP神经网络结合响应面法优化香芹菜叶总黄酮提取工艺及其应用

Based on the BP Neural Network Combined with Response Surface Optimization Celery Leaf Flavonoids Extraction Technology and Its Application

以宁波当地四季小香芹菜叶为原料,采用超声辅助乙醇-硫酸铵双水相提取法,借助响应面分析法(RSM)和BP神经网络相结合的手段优化芹菜叶中黄酮提取工艺。研究4个主要因素对总黄酮提取率的影响,采取中心组合设计试验,以响应面输出的数据样本作为BP神经网络的输入样本,利用其交互算法具有的特点进行优化拟合,达到BP神经网络与响应面相结合优化其提取工艺的目的。结果表明,在超声时间52.25 min,超声温度52.5℃,料液比1∶44,乙醇质量分数61.47%条件下芹菜叶总黄酮提取率可达6.62%,芹菜叶总黄酮对DPPH·、·OH和·O^(2-)有清除作用,最大清除率分别达88.2%,86.1%,84.3%,且对细菌的抑制效果良好,尤其对单核细胞增生李斯特菌抑制效果显著,可作为一类细菌抑制剂。经LC-MS分析,样品提取物中木犀草素和芹菜素含量相对较高。

The ultrasonic assisted ethanol ammonium sulfate aqueous two-phase extraction method was used to optimize the extraction process of flavonoids from celery leaves by response surface methodology(RSM)and BP neural network.The effects of four main factors on the extraction rate of total flavonoids were studied.The central composite design experiment was adopted.The data sample output from response surface was used as the input sample of BP neural network,and the characteristics of its interactive algorithm were used to optimize the fitting,so as to achieve the purpose of optimizing the extraction process by combining BP neural network with response surface.The results showed that under the conditions of ultrasonic time of 52.25 min,ultrasonic temperature of 52.5 ℃,solid-liquid ratio of 1 ∶ 44 and ethanol content of 61.47%,the extraction rate of total flavonoids from celery leaves could reach 6.62%.Total flavonoids from celery leaves had scavenging effects on DPPH·,·OH and ·O^(2-),and the maximum scavenging rates were 88.2%,86.1% and 84.3%,respectively.It could be used as a kind of bacterial inhibitor.The content of luteolin and apigenin in the sample extract was relatively high by LC-MS analysis.