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Frontiers of Chemical Science and Engineering

ISSN 2095-0179

ISSN 2095-0187(Online)

CN 11-5981/TQ

邮发代号 80-969

2019 Impact Factor: 3.552

Frontiers of Chemical Science and Engineering  2011, Vol. 5 Issue (4): 463-470   https://doi.org/10.1007/s11705-011-1112-1
  RESEARCH ARTICLE 本期目录
Application of statistical design for the production of inulinase by streptomyces sp. using pressmud
Application of statistical design for the production of inulinase by streptomyces sp. using pressmud
M. DILIPKUMAR1(), M. RAJASIMMAN1, N. RAJAMOHAN2
1. Department of Chemical Engineering, Annamalai University, Annamalainagar-608002, Tamilnadu, India; 2. Department of Chemical Engineering, Sohar University, Sohar, Sultanate of Oman
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Abstract

A Plackett-Burman design was employed for screening 18 nutrient components for the production of inulinase using streptomyces sp. and pressmud as the substrate via solid-state fermentation (SSF). From the experiments, three nutrients viz. yeast extract, FeSO4·7H2O, and NH4NO3 were found to be the most significant components. Hence these three components were selected and optimized using Response Surface Methodology (RSM). The optimum conditions are: yeast extract 0.00274 g/gds, FeSO4·7H2O 0.00011 g/gds and NH4NO3 0.00772 g/gds. The effect of the substrate concentration and initial moisture content were also studied. A substrate concentration of 12 g and an initial moisture content of 65% are optimum for the maximum production of inulinase (89 U/gds).

Key wordsinulinase    pressmud    Response Surface Methodology (RSM)    streptomyces sp
收稿日期: 2011-03-29      出版日期: 2011-12-05
Corresponding Author(s): DILIPKUMAR M.,Email:mdilip_kumar@yahoo.co.in   
 引用本文:   
. Application of statistical design for the production of inulinase by streptomyces sp. using pressmud[J]. Frontiers of Chemical Science and Engineering, 2011, 5(4): 463-470.
M. DILIPKUMAR, M. RAJASIMMAN, N. RAJAMOHAN. Application of statistical design for the production of inulinase by streptomyces sp. using pressmud. Front Chem Sci Eng, 2011, 5(4): 463-470.
 链接本文:  
https://academic.hep.com.cn/fcse/CN/10.1007/s11705-011-1112-1
https://academic.hep.com.cn/fcse/CN/Y2011/V5/I4/463
NutrientsComposition
Organic carbon20%-25%
Nitrogen0.90%-1.25%
Phosphorus2.50%-3.00%
Potassium1.00%-1.50%
Calcium11.00%
Magnesium1.65%
Sulfur0.23%
Copper52 ppm
Zinc69 ppm
Manganese898 ppm
Iron2000 ppm
Moisture70%
Tab.1  
VariableLevels/g·((10 gds)-1)
Nutrient codeNutrientLow ( - 1)High ( + 1)
AYeast extract0.010.05
BBeef extract0.050.15
CMnSO4·7H2O0.10.5
DK2HPO40.020.07
ESoya bean cake0.40.8
FMgSO4·7H2O0.0020.012
GNH4Cl0.010.03
HKCl0.0050.015
J(NH4)2HPO40.050.3
KNH4NO30.050.1
LZnSO4·7H2O0.10.5
M(NH4)2SO40.060.1
NCorn steep liquor0.40.8
OPeptone0.050.15
PDextrose0.10.3
QFeSO4·7H2O0.00050.002
RKH2PO40.10.6
SUrea0.10.3
Tab.2  
Run No.ABCDEFGHJKLMNOPQRSInulinase activity /(U·gds-1)
11- 11- 11111- 1- 111- 111- 1- 1- 156.74
21- 11111- 1- 111- 111- 1- 1- 1- 1161.51
3- 1- 1- 1- 11- 11- 11111- 1- 111- 1151.12
4- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 1- 140.53
5- 1- 1- 11- 11- 11111- 1- 111- 11131.44
611- 111- 1- 1- 1- 11- 11- 11111- 165.31
7- 1- 111- 111- 1- 1- 1- 11- 11- 111151.42
8- 11- 11111- 1- 111- 111- 1- 1- 1- 130.51
91- 1- 1- 1- 11- 11- 11111- 1- 111- 151.41
10- 11- 11- 11111- 1- 111- 111- 1- 162.30
111- 111- 1- 1- 1- 11- 11- 11111- 1- 171.81
12- 11111- 1- 111- 111- 1- 1- 1- 11- 131.30
13111- 1- 111- 111- 1- 1- 1- 11- 11- 162.61
1411- 1- 111- 111- 1- 1- 1- 11- 11- 1172.71
151- 1- 111- 111- 1- 1- 1- 11- 11- 11151.10
161111- 1- 111- 111- 1- 1- 1- 11- 1141.66
17- 1- 11- 11- 11111- 1- 111- 111- 121.14
1811- 1- 1- 1- 11- 11- 11111- 1- 11150.19
19- 111- 1- 1- 1- 11- 11- 11111- 1- 1120.78
20- 111- 111- 1- 1- 1- 11- 11- 1111173.43
Tab.3  
VariableCodeLevels /(g·(10 gds) -1)
- 1.68- 10+ 1+ 1.68
Yeast extractX10.010.020.030.040.05
FESO4·7H2OX20.00050.00080.00120.00160.002
NH4NO3X30.050.0620.0750.0870.1
Tab.4  
Run No.X1X2X3Inulinase activity /(U·gds-1)
ExperimentalPredicted
101.6803333.84
21115149.09
31- 1- 15246.02
40007881.05
500- 1.684449.67
60008181.05
70007881.05
80008581.05
90008281.05
10- 1- 1- 16265.16
111- 115558.78
120008281.05
130- 1.6806259.40
1411- 13632.82
15- 1114148.23
16001.687163.57
17- 11- 14744.46
181.68004347.93
19- 1.68007063.30
20- 1- 116165.42
Tab.5  
Fig.1  
SourceCoefficient factorSum of squaresDFFP>F
Model81.05045100.12916.10<0.0001
X1-4.56975285.1918.100.0174
X2-7.59853788.51122.400.0008
X34.13041232.9916.620.0278
X1 × X21.8750028.1310.800.3924
X1 × X33.1250078.1312.220.1672
X2 × X30.875006.1310.170.6854
X1 × X1-8.991341165.07133.090.0002
X2 × X2-12.17332135.60160.66<0.0001
X3 × X3-8.637791075.24130.540.0003
Residual352.08108.780.0162
Lack of fit316.085
Pure error36.005
Cor total5452.2019
Tab.6  
Fig.2  
Fig.3  
Fig.4  
Fig.5  
Fig.6  
Fig.7  
SubstrateMicroorganismActivity /(U·gds-1)Ref.
Wheat bran and rice huskCryptococcus aureus436.2[28]
Dry bagasseKluyveromyces marxianus19.4[29]
Wheat branStaphylococcus sp.107.64[30]
Kluyveromyces marxianus122.88
Sugarcane bagasseKluyveromyces marxianus250[31]
Wheat bran and Rice branPichia guilliermondii,291.0[32]
Pichia guilliermondii M-30455.9
PressmudStreptomyces sp.89This work
Tab.7  
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