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Response surface methodology was employed to optimize the degradation conditions of AFB_{1} by
Mycotoxins are secondary metabolites produced by
Response surface methodology (RSM), an experimental strategy for seeking the optimum conditions for a multivariable system, described first by Box and Wilson, is a much more efficient technique for optimization [
The purpose of this study was to screen and to establish the optimum conditions for aflatoxin degradation involving the variable factors: temperature, pH, liquid volume, inoculum size, agitation speed, incubation time and to investigate the application of response surface methodology using central composite design to model the degradation of AFB_{1}.
The bacterial strain (
The ingredients of the ATYP medium for propagating
The aflatoxigenic strain,
The Plackett–Burman (PB) experimental design is widely used as a screening tool [
where y is the response (the degradation rate of AFB_{1}), β_{0} is the model intercept and β_{i} is the linear coefficient and x_{i} is the level of the independent variable [
Range of values for PlackettBurman (PB) ^{a}.
Code  Variables (unit)  Levels ^{a}  

−1  0  +1  
X_{1}  Temperature (°C)  15  25  35 
X_{2}  pH  6.0  7.0  8.0 
X_{3}  Liquid volume (mL/100mL)  10  20  30 
X_{4}  Inoculum size (%)  6  10  14 
X_{5}  Agitation speed (rpm)  160  180  200 
X_{6}  Incubation time (h)  48  72  96 
^{a} x_{1} = (X_{1} − 25)/10; x_{2} = (X_{2} − 7.0)/1; x_{3} = (X_{3} − 20)/10; x_{4} = (X_{4} − 10)/4; x_{5} = (X_{5} − 180)/20; x_{6} = (X_{6} − 72)/24.
A Central composite design (CCD) with five coded levels was used for exploring the subregion of the response surface in the neighborhood of the optimum. The experimental results of the response surface analysis (RSM) were fitted via the response surface exploring the subregion of the response surface in the neighborhood of the optimum. The experimental results of RSM were fitted via the response surface regression procedure, as expressed by the following second order polynomial equation:
Peanuts that reach commercial level of maturity were harvested and used immediately or stored at 4 °C for use within 48 h. For preparation, the peanut kernels were washed with tap water, then surfacedisinfected with 0.1% sodium hypochlorite for 1 min, cleaned with tap water and air dried [
The design matrix selected for the screening of significant variables for the degradation of AFB_{1} and the corresponding responses are shown in
Experimental designs and the results of the PB design.
Run  x_{1}  x_{2}  x_{3}  x_{4}  x_{5}  x_{6}  y (%) 

1  −1  −1  −1  −1  −1  −1  18.1 
2  1  −1  −1  −1  −1  1  10.6 
3  −1  1  −1  −1  −1  1  80.9 
4  1  1  −1  −1  −1  −1  12.6 
5  −1  −1  1  −1  −1  1  75.0 
6  1  −1  1  −1  −1  −1  13.4 
7  −1  1  1  −1  −1  −1  26.2 
8  1  1  1  −1  −1  1  11.8 
9  −1  −1  −1  1  −1  1  51.4 
10  1  −1  −1  1  −1  −1  10.9 
11  −1  1  −1  1  −1  −1  27.2 
12  1  1  −1  1  −1  1  11.3 
13  −1  −1  1  1  −1  −1  49.0 
14  1  −1  1  1  −1  1  9.2 
15  −1  1  1  1  −1  1  90.6 
16  1  1  1  1  −1  −1  34.9 
17  −1  −1  −1  −1  1  1  26.6 
18  1  −1  −1  −1  1  −1  15.8 
19  −1  1  −1  −1  1  −1  14.5 
20  1  1  −1  −1  1  1  12.5 
21  −1  −1  1  −1  1  −1  22.9 
22  1  −1  1  −1  1  1  22.8 
23  −1  1  1  −1  1  1  85.7 
24  1  1  1  −1  1  −1  21.2 
25  −1  −1  −1  1  1  −1  12.2 
26  1  −1  −1  1  1  1  8.7 
27  −1  1  −1  1  1  1  62.8 
28  1  1  −1  1  1  −1  26.7 
29  −1  −1  1  1  1  1  40.3 
30  1  −1  1  1  1  −1  19.8 
31  −1  1  1  1  1  −1  32.3 
32  1  1  1  1  1  1  45.2 
33  0  0  0  0  0  0  79.4 
34  0  0  0  0  0  0  81.4 
35  0  0  0  0  0  0  79.8 
36  0  0  0  0  0  0  80.9 
Identifying significant variables for the degradation of AFB_{1} using Plackett–Burman design.
Variable  Coefficients  

Intercept  31.34688  10.52  <0.0001 
x_{1}  −13.38438  −4.49  0.0001 
x_{2}  5.92813  1.99  0.0578 
x_{3}  6.17188  2.07  0.0489 
x_{4}  1.93438  0.65  0.5223 
x_{5}  −1.97187  −0.66  0.5143 
x_{6}  8.99063  3.02  0.0058 
The results of the
A central composite design (CCD) under RSM was used to analyze the interactive effect of temperature, pH, liquid volume and incubation time to reach an optimum level. The design matrix and the corresponding results of the RSM experiments to determine the effects of four independent variables are shown in
The matrix of the central composite design (CCD) experiment and the corresponding experimental data.
Runs  x_{1}  x_{2}  x_{3}  x_{6}  y (%) 

1  −1  −1  −1  −1  57.6 
2  −1  −1  −1  1  47.8 
3  −1  −1  1  −1  74.9 
4  −1  −1  1  1  80.4 
5  −1  1  −1  −1  64.2 
6  −1  1  −1  1  72.4 
7  −1  1  1  −1  65.3 
8  −1  1  1  1  90.4 
9  1  −1  −1  −1  47.0 
10  1  −1  −1  1  46.3 
11  1  −1  1  −1  64.8 
12  1  −1  1  1  62.0 
13  1  1  −1  −1  54.6 
14  1  1  −1  1  59.7 
15  1  1  1  −1  60.5 
16  1  1  1  1  65.1 
17  −2  0  0  0  68.1 
18  2  0  0  0  53.7 
19  0  −2  0  0  69.1 
20  0  2  0  0  92.2 
21  0  0  −2  0  68.5 
22  0  0  2  0  95.5 
23  0  0  0  −2  60.7 
24  0  0  0  2  95.8 
25  0  0  0  0  82.6 
26  0  0  0  0  84.4 
27  0  0  0  0  83.7 
28  0  0  0  0  83.9 
29  0  0  0  0  83.4 
30  0  0  0  0  82.2 
31  0  0  0  0  84.0 
x_{1} = (X_{1} − 25)/5; x_{2} = (X_{2} − 7.0)/0.5; x_{3} = (X_{3} − 20)/5; x_{6} = (X_{6} − 72)/12.
Experimental data were used in the response surface regression (RSREG) procedure of SAS to find the coefficients of the response function. The coefficients of the response function for the degradation efficiencies are listed in
Regression coefficients of the response function for the degradation of AFB_{1}.
Parameter  DF  Estimate  StandardError  Pr >  


Intercept  1  83.457143  3.273286  25.50  <0.0001 
x_{1}  1  −5.075000  1.767777  −2.87  0.0111 
x_{2}  1  4.066667  1.767777  2.30  0.0352 
x_{3}  1  6.991667  1.767777  3.96  0.0011 
x_{6}  1  4.391667  1.767777  2.48  0.0244 
x_{1} * x_{1}  1  −7.662202  1.619505  −4.73  0.0002 
x_{2} * x_{1}  1  −0.737500  2.165075  −0.34  0.7378 
x_{2} * x_{2}  1  −2.724702  1.619505  −1.68  0.1119 
x_{3} * x_{1}  1  −1.512500  2.165075  −0.70  0.4948 
x_{3 }* x_{2}  1  −3.312500  2.165075  −1.53  0.1456 
x_{3} * x_{3}  1  −2.387202  1.619505  −1.47  0.1599 
x_{6} * x_{1}  1  −1.425000  2.165075  −0.66  0.5198 
x_{6} * x_{2}  1  3.175000  2.165075  1.47  0.1619 
x_{6} * x_{3}  1  1.850000  2.165075  0.85  0.4055 
x_{6} * x_{6}  1  −3.324702  1.619505  −2.05  0.0568 
ANOVA results for central composite design (CCD).
Regression  DF  Type I Sum of Squares  Pr > 


Linear  4  2651.125000  0.4205  8.84  0.0006 
Quadratic  4  1983.513233  0.3146  6.61  0.0024 
Crossproduct  6  469.407500  0.0745  1.04  0.4345 
Total Model  14  5104.045733  0.8096  4.86  0.0017 
The response surface plot showing the effects of temperature (x_{1}) and pH (x_{2}) on AFB_{1} degradation.
The response surface plot showing the effects of temperature (x_{1}) and liquid volume (x_{3}) on AFB_{1} degradation.
The response surface plot showing the effects of temperature (x_{1}) and incubation time (x_{6}) on AFB_{1} degradation.
The response surface plot showing the effects of pH (x_{2}) and liquid volume (x_{3}) on AFB_{1} degradation.
The response surface plot showing the effects of pH (x_{2}) and incubation time (x_{6}) on AFB_{1} degradation.
The response surface plot showing the effects of liquid volume (x_{3}) and incubation time (x_{6}) on AFB_{1} degradation.
According to the canonical analysis, the results predicted by the model showed that the maximum degradation could be achieved when the temperature, initial pH, liquid volume and incubation time were set at 23.2 °C, 7.17, 24.6 mL/100 mL and 81.9 h, respectively. The predicted optimum rate of AFB_{1} degradation was 96.7%. In order to confirm the optimization results, a further degradation test was carried out under the optimal conditions based on the results from the model; the experimentally observed optimum rate of AFB_{1} degradation was 95.8% which was quite in agreement with the predicted value.
The strain of marine
Inhibition of aflatoxin B_{1} by
Control 




Aflatoxin B_{1} (μg/kg) (mean ± SD)  195.69 ± 1.92  178.38 ± 2.47  148.27 ± 3.87  140.80 ± 3.59 
TejadaCastañeda
Plackett–Burman design and central composite design were adopted to screen the key factors and identify the optimal conditions for degradation of AFB_{1}. Using RSM analysis, the four significant variables (temperature, pH, liquid volume and incubation time) selected by the Plackett–Burman design experiment were found to have linear effects on AFB_{1} degradation at significant level. The optimum conditions of each variable were as follows: temperature, 23.2 °C; pH, 7.17; liquid volume, 24.6 mL/100mL; inoculum size, 10%; agitation speed, 180 rpm; and incubation time, 81.9 h. Under these conditions, the AFB_{1} degradation efficiency of
Our result by mathematic modeling has great potential for practical applications. It can be used in aflatoxin removal during industrial fermentation for food processing and fermentation for bioenergy generation such as ethanol production.
This research was supported by National Natural Science Foundation of China (31000823), Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) and a research grant from Qingdao Municipal Science and Technology Commission (081324jch), Shandong Province, People’s Republic of China.
The authors declare no conflict of interest.