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[Optimal extraction of effective constituents from Aralia elata by central composite design and response surface
Shao-Wa Lv1, Dong Liu, Pan-Pan Hu
1College of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin 150040, China. lswa5599@sina.com
Objectives:
To optimize the process of extracting effective constituents from Aralia elata by response surface methodology.
Methods:
The independent variables were ethanol concentration, reflux time and solvent fold, the dependent variable was extraction rate of total saponins in Aralia elata. Linear or no-linear mathematic models were used to estimate the relationship between independent and dependent variables. Response surface methodology was used to optimize the process of extraction. The prediction was carried out through comparing the observed and predicted values.
Results:
Regression coefficient of binomial fitting complex model was as high as 0.9617, the optimum conditions of extraction process were 70% ethanol, 2.5 hours for reflux, 20-fold solvent and 3 times for extraction. The bias between observed and predicted values was -2.41%.
Conclusion:
It shows the optimum model is highly predictive.
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Related Concept Videos
01:28Methods of Medium Optimization
01:16Response Surface Methodology
The process of RSM involves several key steps: