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Recently, extensive attention and interest have been focused on the polysaccharides prepared from fungi for their various biological activities, such as immunomodulating effects of the polysaccharides from
Endophytic fungus
Currently, a large number of studies have been reported to optimize the medium for production of desired products in the fermentation process of microorganisms by employing different kinds of statistical experimental design techniques and analytical methods [
The fractional factorial design (FFD) enables the identification of the main effect of each variable upon response, which is estimated as the difference between both averages of measurements made at the high and low levels of that factor [
The analysis of variance (ANOVA) of the FFD experiments is summarized in
Based on the results and analyses of FFD experiments, the concentrations (g/L) of glucose, peptone and MgSO_{4}·7H_{2}O in medium were determined as the critical factors on EPS production. Hence, the equally spaced locations of each variable singlefactor experiments were carried out to further optimize the three factors, while the concentrations of KH_{2}PO_{4} and FeSO_{4}·7H_{2}O were fixed at 2.0 g/L and 0.05 g/L, respectively.
The effects of the concentration of glucose ranged from 10 to 80 g/L on EPS production are presented in
The effects of the concentration of MgSO_{4}·7H_{2}O on EPS production are shown in
According to the results of FFD and singlefactor experiments, the suitable concentrations of glucose, peptone and MgSO_{4}·7H_{2}O in medium for EPS production were determined for further CCD experiments. Five levels of each variable were set by software of Design Expert, which are presented in
in the Equation,
In order to determine whether the quadratic regression model was significant or not, the ANOVA analysis was conducted, which is summarized in
The coefficients of the quadratic polynomial model, along with their corresponding
The threedimensional (3D) response surface and twodimensional (2D) contour plots are the graphical representations of the quadratic polynomial regression equation [
The response surface plot in
By analyzing the 3D response surface and 2D contour plots, the corresponding point to the maximum of EPS yield should locate on the peak of the response surface, which projected in the smallest ellipse in the contour diagram [
By solving the inverse matrix of the regression polynomial equation (
The endophytic fungus
Exopolysaccharide (EPS) was prepared from fermentation broth of
The carbohydrate content of EPS was measured spectrophotometrically by the method of anthronesulfuric acid [
Fractional factorial design (FFD) was initially employed to identify the major components of medium affecting the producing of EPS, which was very practical, especially when the investigator is faced with a large number of factors and is unsure which settings are likely to be close to optimum responses [
By analyzing the results of factorial design experiments, three main components having significant effects on EPS production were determined as glucose, peptone and MgSO_{4}·7H_{2}O. Singlefactor experiments of the three major factors were carried out to determine their optimal ranges for EPS production, when the concentrations of KH_{2}PO_{4} and FeSO_{4}·7H_{2}O were fixed at 2.0 g/L and 0.05 g/L, respectively.
Based on the results of fractional factorial and singlefactor experiments, central composite design (CCD) experiments and response surface methodology (RSM) were employed to optimize the concentrations of glucose, peptone and MgSO_{4}·7H_{2}O in the fermentation medium for realizing the maximization of EPS yield by the software of DesignExpert. In recent years, both CCD and RSM technologies have been widely applied to optimize the medium composition for production of different metabolites from fungi, which have also been proved to be efficient, practical and precise [
where
CCD in this experimental design consisted of 20 trials which were carried out in a random order in triplicate that was necessary to estimate the variability of measurements, which are presented in
Based on the CCD experimental data, a secondorder polynomial model was established, which correlated the relationship between EPS yield and the independent variables. The relationship could be expressed by the following equation (
where
The fitness of the secondorder polynomial model equation was evaluated by the coefficient (
The medium composition (
The authors wish to thank the Program for Changjiang Scholars and Innovative Research Team in University of China (IRT1042) and the National Natural Science Foundation of China (31071710) for their financial support in this research.
Effects of the concentrations (g/L) of glucose (
The 3Dresponse surface and 2Dcontour plots of EPS yield (g/L)
The matrix of fractional factorial design (FFD) and the experimental results.
Run  Glucose (g/L)  Peptone (g/L)  KH_{2}PO_{4} (g/L)  MgSO_{4}·7H_{2}O (g/L)  FeSO_{4}·7H_{2}O (g/L)  EPS Yield (g/L) 

1  30  10  0.5  0.5  0.05  1.20 
2  60  10  0.5  0.5  0.01  1.42 
3  30  20  0.5  0.5  0.01  2.80 
4  60  20  0.5  0.5  0.05  3.67 
5  30  10  2.0  0.5  0.01  1.12 
6  60  10  2.0  0.5  0.05  2.36 
7  30  20  2.0  0.5  0.05  3.85 
8  60  20  2.0  0.5  0.01  6.62 
9  30  10  0.5  2.0  0.05  2.82 
10  60  10  0.5  2.0  0.01  5.37 
11  30  20  0.5  2.0  0.01  5.08 
12  60  20  0.5  2.0  0.05  13.63 
13  30  10  2.0  2.0  0.01  2.97 
14  60  10  2.0  2.0  0.05  6.84 
15  30  20  2.0  2.0  0.05  5.57 
16  60  20  2.0  2.0  0.01  10.89 
Analysis of variance (ANOVA) of the fractional factorial design (FFD) experiments.
Source  Sum of squares  d.f.  Significance  

Glucose  40.29  1  12.67  0.0052  
Peptone  49.04  1  15.42  0.0028  
KH_{2}PO_{4}  1.12  1  0.35  0.5664  
MgSO_{4}·7H_{2}O  56.74  1  17.84  0.0018  
FeSO_{4}·7H_{2}O  1.84  1  0.58  0.4641 
significance of the variable:
Coded values (
Variable (g/L)  Symbol  Coded level  


 
Uncoded  Coded  −1.682  −1  0  1  +1.682  
Glucose  43.18  50  60  70  76.82  
Peptone  21.59  25  30  35  38.41  
MgSO_{4}·7H_{2}O  1.66  2  2.5  3  3.34 
CCD experimental matrix and the results.
EPS Yield (g/L)  

 
Run  Experimental 
Predicted 

1  0  −1.682  0  6.07  6.23  −0.17 
2  0  0  1.682  9.30  9.59  −0.29 
3  0  1.682  0  10.22  9.99  0.23 
4  −1  −1  −1  2.71  2.45  0.26 
5  −1  1  1  7.89  7.52  0.36 
6  −1  1  −1  7.32  7.81  −0.49 
7  1  1  1  10.01  10.31  −0.30 
8  0  0  0  13.43  12.52  0.91 
9  0  0  0  11.95  12.52  −0.57 
10  1  −1  −1  4.47  4.88  −0.41 
11  1  1  −1  6.01  6.00  0.01 
12  0  0  −1  4.87  4.52  0.35 
13  1.682  0  0  8.51  8.39  0.13 
14  −1  −1  1  4.12  4.18  −0.06 
15  0  0  0  12.09  12.52  −0.43 
16  0  0  0  12.73  12.52  0.21 
17  −1.682  0  0  3.94  4.00  −0.06 
18  1  −1  1  11.64  11.20  0.44 
19  0  0  0  13.02  12.52  0.50 
20  0  0  0  11.89  12.52  −0.43 
Analysis of variance (ANOVA) for the fitted quadratic polynomial model.
Source  Sum of squares  d.f.  Mean square  Probability  

Model  228.02  9  25.34  78.46  <0.0001 
Lack of fit  1.20  5  0.24  0.59  0.71 
Pure error  2.03  5  0.41  
Corrected total  231.25  19 
Regression coefficient and their significance test of the quadratic polynomial model.
Model term  Coefficient estimate  Standard error  Sum of squares  d.f.  Mean square  Probability  

Intercept  12.52  0.23  
1.30  0.15  23.18  1  23.18  71.79  <0.0001  
1.12  0.15  17.06  1  17.06  52.83  <0.0001  
1.51  0.15  31.12  1  31.12  96.36  <0.0001  
−1.06  0.20  8.96  1  8.96  27.75  <0.0001  
1.15  0.20  10.58  1  10.58  32.76  0.0004  
−0.50  0.20  2.01  1  2.01  6.24  0.0002  
−2.24  0.15  72.04  1  72.04  223.09  0.0316  
−1.56  0.15  34.99  1  34.99  108.36  <0.0001  
−1.93  0.15  53.80  1  53.80  166.61  <0.0001 
The coded and actual values in the 2^{51} FFD experiments.
Variable (g/L)  Level  

 
−1  +1  
Glucose  30  60 
Peptone  10  20 
KH_{2}PO_{4}  0.5  2.0 
MgSO_{4}·7H_{2}O  0.5  2.0 
FeSO_{4}·7H_{2}O  0.01  0.05 