# Extraction Optimization of Water-Extracted Mycelial Polysaccharide from Endophytic Fungus Fusarium oxysporum Dzf17 by Response Surface Methodology

^{*}

## Abstract

**:**

_{1}), 80–100 °C for extraction temperature (X

_{2}), and 20–40 (v/w) for ratio of water volume (mL) to raw material weight (g) (X

_{3}). The experimental data obtained were fitted to a second-order polynomial equation using multiple regression analysis. Statistical analysis showed that the polynomial regression model was in good agreement with the experimental results with the determination coefficient (R

^{2}) of 0.9978. By solving the regression equation and analyzing the response surface contour plots, the extraction parameters were optimized as 1.7 h for extraction time, 95 °C for extraction temperature, 39 (v/w) for ratio of water volume (mL) to raw material weight (g), and with 2 extractions. The maximum value (10.862%) of WPS yield was obtained when the WPS extraction process was conducted under the optimal conditions.

## 1. Introduction

## 2. Results and Discussion

#### 2.1. Effect of Extraction Time on WPS Yield

#### 2.2. Effect of Extraction Temperature on WPS Yield

#### 2.3. Effect of Ratio of Water to Raw Material on WPS Yield

#### 2.4. Effect of Extraction Times on WPS Yield

#### 2.5. Model Building and Statistical Analysis

_{1}), extraction temperature (X

_{2}) and extraction ratio of water volume to raw material weight (X

_{3}) were chosen as the variables to optimize the process of polysaccharide extraction. There were a total of 17 runs performed for optimizing these three variables in the current Box-Behnken design (BBD) [28]. The values of response Y (WPS yield) under the different experimental combinations are presented in Table 1. There was a considerable variation of WPS yield depending upon the different extraction conditions. WPS yield ranged from 7.027 to 10.535%.

^{2}) and the multiple correlation coefficients (R). The value of the determination coefficient adj-R

^{2}(0.9949) suggested that the total variation of 99.49% for WPS yield was attributed to the independent variables and only about 0.51% of the total variation could not be explained by the model. The value of R was closer to 1, the fitness of the model was better [29]. In this research, the value of R (0.9989) indicated a high degree of correlation between the observed and predicted values. The lack-of-fit measured the failure of the model to represent the data in the experimental domain at points which were not included in the regression. The F-value for the lack-of-fit was not significant (p > 0.05), confirming the validity of the model.

_{2}(extraction temperature) and x

_{3}(ratio of water volume to raw material weight).

#### 2.6. Response Surface Plot and Contour Plot Analyses

#### 2.7. Optimization of the Extraction Parameters and Validation of the Model

## 3. Experimental Section

#### 3.1. Cultivation of Fusarium oxysporum Dzf17

_{2}HPO

_{4}(0.6 g/L), and MgSO

_{4}·7H

_{2}O (0.2 g/L). All flasks were maintained on a rotary shaker at 150 rpm and 25 °C for 14 days. The mycelia were collected by filtration of fermentation broth (150 L), and washed twice with deionized water, then lyophilized.

#### 3.2. Extraction of WPS

#### 3.3. Experimental Design

_{1}, x

_{2}, x

_{3}and prescribed into three levels, coded as +1, 0, −1 for high, intermediate and low, successively. The variable levels X

_{i}were coded as x

_{i}according to the following equation (Equation (2)):

_{i}is the coded value of the variable X

_{i}, while X

_{0}is the value of X

_{i}at the center point, and ΔX is the step change of an independent variable, i = 1, 2, 3.

_{0}is the intercept term; x

_{1}, x

_{2}and x

_{3}are independent variables; a

_{1,}a

_{2}and a

_{3}are linear coefficients; a

_{12}, a

_{13}and a

_{23}are cross product coefficients; and a

_{11}, a

_{22}and a

_{33}are the quadratic term coefficients. All of the coefficients of the second polynomial model and the responses obtained from the experimental design were subjected to multiple nonlinear regression analyses.

^{2}) of determination. The analysis of variance (ANOVA) and test of significance for regression coefficients were conducted by F-test. In order to visualize the relationship between the response values and independent variables, the fitted polynomial equation was separately expressed as 3D response surfaces and 2D contour plots [37,38].

## 4. Conclusions

## Acknowledgments

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**Figure 1.**Effects of extraction time (

**A**), extraction temperature (

**B**), ratio of water volume (mL) to raw material weight (g) (

**C**), and number of extractions (

**D**) on water-extracted mycelial polysaccharide (WPS) yield. The error bars represent standard deviations from three independent samples. Different letters indicate significant differences among the treatments at p = 0.05 level.

**Figure 2.**Three-dimensional response surfaces (

**A**,

**C**and

**E**) and contour plots (

**B**,

**D**and

**F**), showing the effects of extraction time (X

_{1}), extraction temperature (X

_{2}), and ratio of water volume (mL) to raw material weight (g) (X

_{3}), and the effect of their their reciprocal interaction on WPS yield (Y).

**Table 1.**Box-Behnken design (BBD) matrix and the response values for water-extracted mycelial polysaccharide (WPS) yield.

Run | x_{1} | x_{2} | x_{3} | WPS Yield (%) | ||
---|---|---|---|---|---|---|

Experimental Y_{e} | Predicted Y | Y_{e} – Y | ||||

1 | 1 | −1 | 0 | 8.162 | 8.207 | −0.045 |

2 | 0 | −1 | −1 | 7.649 | 7.615 | 0.034 |

3 | −1 | −1 | 0 | 7.027 | 6.933 | 0.094 |

4 | 1 | 1 | 0 | 9.318 | 9.352 | −0.034 |

5 | 0 | 1 | −1 | 9.826 | 9.803 | 0.023 |

6 | −1 | 0 | −1 | 8.511 | 8.579 | −0.068 |

7 | 1 | 0 | −1 | 9.695 | 9.684 | 0.011 |

8 | 1 | 0 | 1 | 9.684 | 9.616 | 0.068 |

9 | −1 | 1 | 0 | 9.978 | 9.933 | 0.045 |

10 | −1 | 0 | 1 | 10.077 | 10.088 | −0.011 |

11 | 0 | 1 | 1 | 10.344 | 10.378 | −0.034 |

12 | 0 | −1 | 1 | 8.456 | 8.480 | −0.024 |

13 | 0 | 0 | 0 | 10.437 | 10.437 | 0.000 |

14 | 0 | 0 | 0 | 10.535 | 10.437 | 0.098 |

15 | 0 | 0 | 0 | 10.339 | 10.437 | −0.098 |

16 | 0 | 0 | 0 | 10.388 | 10.437 | −0.049 |

17 | 0 | 0 | 0 | 10.486 | 10.437 | 0.049 |

**Table 2.**Analysis of variance (ANOVA) for the fitted quadratic polynomial model for optimization of WPS yield.

Source | Sum of Squares | d.f. | Mean Square | F-Value | Probability (p) > F |
---|---|---|---|---|---|

Model | 19.24 | 9 | 2.14 | 345.32 | <0.0001 |

Lack of fit | 0.019 | 3 | 6.44 × 10^{−3} | 1.07 | 0.4549 |

Pure error | 0.024 | 4 | 6.00 × 10^{−3} | ||

Corrected total | 19.28 | 16 | |||

R^{2} = 0.9978 | R^{2} _{adj} = 0.9949 | CV (%) = 0.83 |

**Table 3.**Regression coefficient estimates and their significance test of quadratic polynomial model.

Model Term | Coefficient Estimate | Standard Error | Sum of Squares | Mean Square | F-Value | Probability (p) > F |
---|---|---|---|---|---|---|

Intercept | 10.44 | 0.035 | ||||

x_{1} | 0.16 | 0.028 | 0.20 | 0.20 | 32.37 | 0.0007 |

x_{2} | 1.02 | 0.028 | 8.35 | 8.35 | 1348.73 | <0.0001 |

x_{3} | 0.36 | 0.360 | 1.04 | 1.04 | 167.52 | <0.0001 |

x_{1}x_{2} | −0.45 | 0.039 | 0.81 | 0.81 | 130.15 | <0.0001 |

x_{1}x_{3} | −0.39 | 0.039 | 0.62 | 0.62 | 100.45 | <0.0001 |

x_{2}x_{3} | −0.07 | 0.039 | 0.02 | 0.02 | 3.37 | 0.1089 |

x_{1} ^{2} | −0.70 | 0.038 | 2.04 | 2.04 | 329.90 | <0.0001 |

x_{2} ^{2} | −1.12 | 0.038 | 5.28 | 5.28 | 852.41 | <0.0001 |

x_{3} ^{2} | −0.25 | 0.038 | 0.26 | 0.26 | 42.14 | 0.0003 |

Variable | Symbol | Coded Level | |||
---|---|---|---|---|---|

Uncoded | Coded | −1 | 0 | 1 | |

Extraction time (h) | X_{1} | x_{1} | 1 | 2 | 3 |

Extraction temperature (°C) | X_{2} | x_{2} | 80 | 90 | 100 |

Ratio (v/w) of water volume (mL) to material weight (g) | X_{3} | x_{3} | 20 | 30 | 40 |

© 2012 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

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**MDPI and ACS Style**

Li, P.; Lu, S.; Shan, T.; Mou, Y.; Li, Y.; Sun, W.; Zhou, L.
Extraction Optimization of Water-Extracted Mycelial Polysaccharide from Endophytic Fungus *Fusarium oxysporum* Dzf17 by Response Surface Methodology. *Int. J. Mol. Sci.* **2012**, *13*, 5441-5453.
https://doi.org/10.3390/ijms13055441

**AMA Style**

Li P, Lu S, Shan T, Mou Y, Li Y, Sun W, Zhou L.
Extraction Optimization of Water-Extracted Mycelial Polysaccharide from Endophytic Fungus *Fusarium oxysporum* Dzf17 by Response Surface Methodology. *International Journal of Molecular Sciences*. 2012; 13(5):5441-5453.
https://doi.org/10.3390/ijms13055441

**Chicago/Turabian Style**

Li, Peiqin, Shiqiong Lu, Tijiang Shan, Yan Mou, Yan Li, Weibo Sun, and Ligang Zhou.
2012. "Extraction Optimization of Water-Extracted Mycelial Polysaccharide from Endophytic Fungus *Fusarium oxysporum* Dzf17 by Response Surface Methodology" *International Journal of Molecular Sciences* 13, no. 5: 5441-5453.
https://doi.org/10.3390/ijms13055441