摘要
目的采用星点设计-效应面优化法优选干姜提取工艺。方法以药材粉碎粒度、加水量和提取时间为自变量,6-姜酚的提取率为因变量对自变量各水平进行多元线性回归和二项式拟合,通过效应面法优选最佳的提取工艺,并进行预测分析。结果确定的最佳提取工艺为干姜药材粉碎成0.600mm(30目)粗粉,加入10倍量水提取2次,每次10h,提取率预测值与理论值偏差为-0.90%,二项式拟合的相关系数为0.9548。结论星点设计-效应面优化法优选干姜提取工艺,方法简便,预测性良好。
Objective To optimize the extraction process of Rhizoma zingibers by central composite design/response surface methodology. Methods Multiple linear regression and binomial fitting models were performed with grinding size, volume of water added and refluxing time as the independent variables and extraction rate of 6-gingerol as dependent variable. Response surface methodology was used to optimize the extraction process and to predict the values. Results The optimum conditions of extraction process were determined as pulverizing the herbs into 30 meshes powder, adding 10-fold solvent and extracting for 2 times, 10 hours once. The bias between observed and predicted values was -0.90% and the correlation coefficient of binomial fitting complex model was as high as 0. 954 8. Conclusion Central composite design/response surface methodology is convenient and highly predictive for optimizing the extraction process of Rhizoma zingibers.
出处
《医药导报》
CAS
2009年第7期897-900,共4页
Herald of Medicine
基金
军队十五科研基金资助项目(基金编号:01Q136)
军队十一五科研基金资助项目(基金编号:06MA360)
关键词
干姜
6-姜酚
星点设计
效应面优化法
提取工艺
Rhizoma zingibers
6-gingerol
Central composite design
Response surface methodology
Extraction process
