Fermentative production and kinetics of cellulase protein on Trichoderma reesei using sugarcane bagasse and rice straw

Cellulase a multienzyme made up of several proteins finds extensive applications in food, fermentation and textile industries. Trichoderma reesei is an efficient producer of cellulase protein. The comparative study was made on various carbon sources on the production of cellulase using strains of T. reesei QM 9414, 97.177 and Tm3. Pretreatment of sugarcane bagasse and rice straw offers very digestible cellulose and potentially less inhibition. Cellulase production was enhanced by multiple carbon sources because of diauxic pattern of utilization of substrates. This is the first attempt of combining the synthetic substrate (xylose, lactose) with natural substrate (sugarcane bagasse, rice straw). The mixture of substrates produced the highest maximal enzyme activity on cellulose with xylose, cellulose with lactose, bagasse with xylose, bagasse with lactose, rice straw with xylose and rice straw with lactose. In addition Monod growth kinetics and Leudeking piret product formation kinetics were studied using T. reesei with optimized medium under optimized conditions of inoculum concentration, D.O. level, agitator speed, temperature and pH

Optimization and modeling of cellulase protein from Trichoderma reesei Rut C30 using mixed substrate

Bioethanol from cellulosic raw material has proved to be the best alternative renewable energy source. Cellulase is a multienzyme complex catalyses the bioconversion of cellulose to glucose, which can beused for ethanol production. The objective of this research is to reduce the cost of cellulase production by optimization of fermentation conditions and modeling of the fermentation process. Research surface methodology was suggested for optimization of process conditions of cellulase biosynthesis.Logistic kinetic model was the best model for the mixed substrates. A conceptual Artificial Neural Network (ANN) model was well incorporated in the fermentative production of cellulase. By adopting these models high yield of cellulase was obtained

Response surface optimization of medium composition for xylitol production by Debaryomyces hansenii var hansenii using corncob hemicellulose hydrolysate

Optimization of the culture medium for xylitol production using Debrayomyces hansenii var hansenii was carried out. The optimization of xylitol production using corncob hemicelluloses hydrolysate as substrate was performed with statistical methodology based on experimental designs. The screening of nine nutrients for their influence of xylitol production to achieved using a Plackett-Burman design. MgSO4.7H2O, KH2PO4, (NH4)2SO4, yeast extract were selected for based on their positive influence on xylitol production. The selected components were optimized using Response Surface Methodology (RSM). The optimum conditions are: MgSO4.7H2O - 1.02 g/l, (NH4)2SO4 - 3.94 g/l, KH2PO4- 2.74 g/l and yeast extract - 3.45 g/l. These conditions are validated experimentally which revealed an enhanced xylitol yield of 0.76 g/g

Enhanced Production of Xylitol from Corncob by Pachysolen tannophilus Using Response Surface Methodology

Optimization of the culture medium and process variables for xylitol production using corncob hemicellulose hydrolysate by Pachysolen tannophilus (MTTC 1077) was performed with statistical methodology based on experimental designs. The screening of nine nutrients for their influence on xylitol production was achieved using a Plackett-Burman design. Peptone, xylose, MgSO4·7H2O, and yeast extract were selected based on their positive influence on xylitol production. The selected components were optimized with Box-Behnken design using response surface methodology (RSM). The optimum levels (g/L) were peptone: 6.03, xylose: 10.62, MgSO4·7H2O: 1.39, yeast extract: 4.66. The influence of various process variables on the xylitol production was evaluated. The optimal levels of these variables were quantified by the central composite design using RSM, for establishment of a significant mathematical model with a coefficient determination of . The validation experimental was consistent with the prediction model. The optimum levels of process variables were temperature (36.56°C), pH (7.27), substrate concentration (3.55 g/L), inoculum size (3.69 mL), and agitation speed (194.44 rpm). These conditions were validated experimentally which revealed an enhanced xylitol yield of 0.80 g/g