支持向量回归和响应面法优化姜黄提取工艺

Extraction Optimization of Rhizome of Curcuma longa by Response Surface Methodology and Support Vector Regression

目的:探究微波辅助提取姜黄药材的最优工艺。方法:在单因素试验基础上,使用经粒子群算法改进的支持向量回归法和响应面设计优化法,以姜黄素、去甲氧基姜黄素和双去甲氧基姜黄素的总量为指标,对乙醇浓度、液料比、微波时间各影响因素进行考察。结果:经两模型筛选得到最优工艺条件为:乙醇浓度69%,液料比21∶1,微波时间55 s。在此工艺条件下,3种姜黄素类化合物的提取总量为28.97 mg/g。结论:响应面模型与支持向量回归机模型的拟合效果良好,相关性均在0.96以上,预测出的最优工艺一致,最优提取率与真实值的偏差均小于1.2%,均可用于优化提取工艺。

Objective： To optimize the optimal microwave-assisted extraction method of curcuminoids from Curcuma longa. Methods： On the base of single factor experiment,the ethanol concentration,the ratio of liquid to solid and the microwave time were selected for further optimization. Support Vector Regression（ SVR） and Central Composite Design-Response Surface Methodology（ CCD） algorithm were utilized to design and establish models respectively,while Particle Swarm Optimization（ PSO） was introduced to optimize the parameters of SVR models and to search optimal points of models. The evaluation indicator,the sum of curcumin,demethoxycurcumin and bisdemethoxycurcumin by HPLC,were used. Results： The optimal parameters of microwave-assisted extraction were as follows： ethanol concentration of 69%,ratio of liquid to solid of 21 ∶ 1,microwave time of 55 s. On those conditions,the sum of three curcuminoids was 28. 97 mg / g（ per gram of rhizomes powder）. Conclusion： Both the CCD model and the SVR model were credible,for they have predicted the similar process condition and the deviation of yield were less than 1. 2%.