Statistical medium optimization for the production of β-galactosidase from Aspergillus terreus KUBCF1306 using Response Surface Methodology

β-galactosidase is a vital enzyme with diverse applications in food and pharmaceutical industries. Response surface methodology was used to study the effects of fermentation parameters on β-galactosidase enzyme production. The effect of pH, temperature, carbon source, nitrogen source, inoculum size and incubation time on the production of βgalactosidase from Aspergillus terreus KUBCF1306 were studied by employing statistical methods. Objective of the present work is to improve the yield of β-galactosidase activity by using statistical methods like Placket & Burman designs (PBD) and Response surface methodology (RSM). Screening of variables to find their relative effect on βgalactosidase production was done using Plackett-Burman design. Central composite experimental design maximizes the amount of information that can be obtained, while limiting the number of individual experiments. Out of the six factors screened, pH, carbon source and temperature were found to influence the enzyme production significantly. Results of the statistical analysis showed that the lack of fit, of the model was good in all cases. The response surface methodology was found to be useful in optimizing and determining the interactions among process variables in β-galactosidase enzyme production.