OPTIMIZATION OF BIOPROCESS PARAMETERS FOR THE PRODUCTION OF β-GALACTOSIDASE BY EMPLOYING STATISTICAL METHODS

Abstract

Optimization of medium components or process parameters by the classical method i.e., changing one independent variable (lactose, soya peptone, ammonium di-hydrogen phosphate and agitation) while fixing all other at a fixed level is extremely time consuming and expensive for a large number of variables. To overcome this difficulty, experimental factorial design and response surface methodology can be employed to optimize the medium components and cultural conditions. The marine derived fungus Aspergillus flavus MTCC*9349 has been studied for the production of β-galactosidase. The effect of medium, pH, temperature, carbon source, nitrogen source and incubation time on the production of β-galactosidase was studied by employing statistical methods. Central composite experimental design maximizes the amount of information that can be obtained, while limiting the number of individual experiments. By employing the statistical methods 1.95 times increase in the yield of the enzyme was obtained (499.63 U/gm dry cell weight).