星点设计-效应面法优化细辛脑的溶解度

Optimized Solubility of Asarone by Central Composite Design/Response Surface Methodology

目的星点设计-效应面优化法优化细辛脑的溶解度。方法以pH值、烟酰胺和卵磷脂的用量为考察因素,细辛脑的溶解度为考察指标,用线性方程和二次多项式描述细辛脑溶解度和3个考察因素之间的数学关系,根据最佳效应面,选择最佳组成,并进行预测分析。结果细辛脑的溶解度与3个考察因素之间用线性方程拟合效果不好,其相关系数为0.724。用二次多项式拟合效果较佳,其相关系数为0.946,优选的最佳条件为pH值7.8,烟酰胺的用量为7%,卵磷脂的用量为0.25%,最佳条件的细辛脑的溶解度试验值与二次多项式拟合方程预测值的偏差为1.60%。结论所建立的模型预测性良好。

Objective To optimize the solubility of asarone by central composite design/response surface methodology. Methods Independent variables were pH value micotinamide content and lecithine content,and asarone solubility was dependent variable.Linear or nonlinear mathematic models were used to estimate the relationship between independent and dependent variables.According to the best-fit response surface,The optirnum solubility was selected. Results It was showed that the correlation coefficient of linearity equations was very low.The correlation coefficient reached 0.724.But the correlation coefficient of second-order quadratic modal was high,reaching 0.964.The optimum conditions for the asarone solubility were as follows： pH value being 7.8,micotinamide content 7%,lecithine content 0.25%.The deviation between the test value of the asarone solubility at the optimum conditions and the binomial fitting equation forecast value was 1.60%. Conclusion It shows that the optimurn rnathematic mode1 is highly predictive.