Abstract
Characterization and production of efficient lignocellulytic enzyme cocktails for biomass conversion is the need for biofuel industry. The present investigation reports the modeling and optimization studies of lignocellulolytic enzyme cocktail production by Cotylidia pannosa under submerged conditions. The predominant enzyme activities of cellulase, xylanase and laccase were produced in the cocktail through submerged conditions using wheat bran as a substrate. A central composite design approach was utilized to model the production process using temperature, pH, incubation time and agitation as input variables with the goal of optimizing the output variables namely cellulase, xylanase and laccase activities. The effect of individual, square and interaction terms on cellulase, xylanase and laccase activities were depicted through the non-linear regression equations with significant R(2) and P-values. An optimized value of 20 U/ml, 17 U/ml and 13 U/ml of cellulase, xylanase and laccase activities, respectively, were obtained with a media pH of 5.0 in 77 h at 31C, 140 rpm using wheatbran as a substrate. Overall, the present study introduces a fungal strain, capable of producing lignocellulolytic enzyme cocktail for subsequent applications in biofuel industry.