Statistical optimization of glucose oxidase production from Aspergillus niger NRC9 under submerged fermentation using response surface methodology

Abstract

Response surface methodology (RSM), employing the fractional factorial design (FFD) was used to optimize the fermentation medium for the production of glucose oxidase (GOD) from a marine isolate (NRC9) of Aspergillus niger under submerged fermentation. The design was employed by selecting glucose, CaCO3, ammonium phosphate and MgSO4 concentrations as model factors by ‘one variable at a time’ experiment. A second-order quadratic model and response surface method showed that the optimum concentrations (g/l) glucose, 100; CaCO3, 25; (NH4)2HPO4, 1.8 and 0.4 of MgSO4, resulted in an improvement of GOD production (170 ± 0.88 U/ml) as compared to the initial level (109.81 ± 1.38 U/ml) after four days of incubation at 200 rpm and 30 °C, whereas its predicted value obtained by the quadratic model was 164.36 U/ml. Analysis of variance (ANOVA) showed a high coefficient of determination value (R 2) of 0.967, ensuring a satisfactory adjustment of the quadratic model with the experimental data. This is the first report on production of glucose oxidase from a marine fungal isolate, Aspergillus niger NRC9, using statistical experimental design and response surface methodology in optimization of its production under submerged fermentation.