Improved Production of Multi-component Cellulolytic Enzymes Using Sweet Sorghum Bagasse and Thermophilic Aspergillus terreus RWY Through Statistical Process Optimization

Purpose The study was conducted to improve the productivity of the multi-component cellulolytic enzymes using thermophilic Aspergilus terreus strain and sweet sorghum bagasse as substrate. One of the major objectives was to study the interactions between different operating parameters and appraise the potential of the optimized process for validation studies. Methods Response surface methodology (RSM) based on central composite design (CCD) was used to optimize the process parameters for cellulase production by thermophilic Aspergillus terreus via a solid-state fermentation (SSF) process. A set of 50 experiments in triplicate with five factors (moisture content, inoculum level, pH, temperature and incubation period), three levels with six axial points (α ± 1.68) and five replications at the central point were conducted in this study with filter paper (FP) cellulase and β-glucosidase as output parameters. Results Micrographs and scanning electron microscopy (SEM) of A. terreus RWY revealed a chain of conidia in a columnar arrangement with an average size of conidium being 2.12 µ. Statistical process optimization suggested temperature of 45 °C, pH of 5.8, incubation time of 72 h, inoculum concentration of 10% and initial moisture content of 80% ( w/w ) as optimum for conducting validation studies. Validation studies showed comparable FP and β-glucosidase activities as predicted by the model equations. In addition to FP and β-glucosidase, A. terreus RWY also produced endoglucanase (EG), β-xylosidase, α- l -arabinofuranosidase, CBHI, xylanase and xylan esterase of 149.54, 26.94, 183.16, 17.52, 1264.47 and 1106.46 U/gds, respectively during the validation process. Response surface optimization also led to a nearly two-fold increase in FP and β-glucosidase activities. Conclusion Coupled with the use of thermophilic strains which confer specific benefits during industrial applications, statistical process optimization holds potential for scale-up studies for cellulase production using the optimized parameters, SSB as substrate and thermophilic A. terreus RWY.