The optimal medium of Phellinus linteus were determined by using the single factor experiment and Response Surface Analysis in the flask,which were composed of sucrose 50.0 g/L,corn steep powder 3.0 g/L,KH2PO410.0 g/L,MgSO41.0 g/L,CaCl23.0 g/L and VB1200μg/L.
Analysis of the response surface showed that dextrose equivalent(DE) 0.75～5.72 were prepared at 95℃ by altering the amount of enzyme(1～3 mL),digested time(10～15 min) and the concentration of starch paste(10%～20%).
The extracting duration, heating temperature, pH value of extracting solution and the ratio of liquid to solid were optimized according to the mathematic model built by Central Composite Design in Design Expert Software(Static Made Easy, Minneapolis, MN, USA. Version 6.0.5, 2001)on the rationale of response surface methodology.
依据响应面法(RSM,Response surface methodology)原理,使用Design Expert(Static Made Easy,Minneapolis,MN,USA.version6.0.5,2001)软件的中心组合设计建立试验数学模型,对微波萃取黄芪多糖的提取时间、加热温度、提取溶液pH值及液料比进行优化组合。
Using the software of Design-Expert 5,a response surface quadratic model in terms of actual factors was obtained based on the experimental data. The optimum FeSO4.7H2O concentration,H2O2/FeSO4.7H2O and pH were found to be 0.013mol/L,4.60,and 4.45 respectively and the highest COD removal efficiency(69.85%) could be achieved.
Response surface methodology(RSM) based on a five-level,four-variable central composite rotatable design(CCRD)was used to evaluate the interactive effects of temperature(30~70 ℃),amount of enzyme(10~30 mg),substrate concentration(vitamin C,9.36~28.07 g/L) and reaction time(24~72 h)on the percentage yield of vitamin C lactate.
The results show that combination of the finite element method, the response surface method and Monte Carlo method is an ideal way for the reliability analysis and probability strength design of the blade.
A gradient-based parameterization analytical method and a response surface method were applied herein for blade optimization.
The response surface method with Reynolds-averaged Navier-Stokes analysis is used for optimization.
solver, a blade parameterization method (BPM), a gradient-based parameterization-analyzing method (GPAM), a response surface method (RSM) with zooming algorithm and a simple gradient method.
The network parameters are optimized by minimizing the training and testing errors using response surface methodology.