Bio-statistical approach for optimization of cold-active α-amylase production by novel psychrotolerant M. foliorum GA2 in solid state fermentation

Abstract

Abstract Cold-active enzymes along with their producing microbes are of commercial value and find multiple applications in various industrial and biotechnological sectors. In this study, production optimization of cold active α-amylase from cold-adapted Microbacterium foliorum GA2 was carried out. The aim of the present work was to use economical agro-substrate for increasing cold-active α-amylase production and to optimize the fermentation parameters in SSF (Solid state fermentation) using two statistical experimental designs. Plackett–Burman design and response surface methodology was used to determine key ingredients for the best media composition and optimal concentration of these components, respectively. The screening result of Plackett–Burman design showed bagasse, lactose and pH had significant effects ( p -value≤0.05) on cold-active α-amylase production. Maximum α-amylase production (6610 units) was observed through response surface methodology in medium having 40% bagasse, 0.003 M lactose, and pH 8.0 at 20 °C when incubated for 5 days in static conditions. The closeness of optimized values ( R 2 =92.26%) to experimental values ( R 2 =96.28%) proved the validity of the statistical model. Under these experimental designs, the α-amylase yield increased three-fold in comparison to control and was much efficient and economical than “one-variable-at-a-time” methodology. Thus, cold-adapted M. foliorum GA2 could be exploited for industrial production of α-amylase using bagasse at relatively low temperatures.