MATHEMATICAL MODELING OF CELLULASE ENZYME PRODUCTION IN A SOLID STATE FERMENTATION BIOREACTOR AND IT’S EFFECT ON PRETREATMENT

Abstract

Solid-state fermentation (SSF) is the process which involves microbial growth in limited presence of water using a solid substrate. Generally funguses are the preferred organisms for this as it resembles the natural habitat of the organisms. Recent demand for large quantities of enzymes and other biologically active secondary metabolites has given a lime light to the technology of solid state Cellulase is the third largest industrial enzyme after Amylase and Proteases, which covers almost 20% of the total enzyme market. Cellulase hydrolyzes β-1,4 glycosidic linkage in cellulose. It comprises endoglucanase, exoglucanase, and β- glucosidase. Cellulases are produced generally by submerged fermentation using genetically modified organisms. But large-scale production of cellulase has not been exploited much because of lack of proper bioreactor facility with control system. Mathematical modeling is a powerful device for the designing, scaling-up and controlling of bioreactors. A mathematical model plays a great role in summarizing our knowledge about the proper operation and functioning of a reactor system summarizes our knowledge about how a system operates. In this thesis, sorghum was pretreated with alkali and steam explosion to check its effect on the increase in activity. Pretreatment here was not successful, but the steam explosion gave some good results at 60 min. Even though activity increased in the steam explosion, but for large scale reactor run it may not be feasible because of biomass loss and degradation of sugars into inhibitory compounds during pretreatment. That’s why we have gone for untreated biomass for SSF and also estimated the kinetic and transport parameters. A new packed bed SSF bioreactor with intermittent mixing was set up.. For modeling, existing equation from the literature Ranjbar et al., (2019), have been used. Using logistic growth model kinetic parameters µm and Xm have been calculated. Measurement of cell biomass is a crucial factor in SSF as the filamentous fungi remains attached to the solid biomass and it becomes difficult to separate them. So, the alternate method of biomass estimation which involves respiratory data gives information regarding the real time monitoring of microbial biomass production. In our system,CO2 production rate(CPR) and oxygen uptake rate(OUR) has been performed in the solid state fermentation and those data has been fitted using existing design equation mathematical modeling. Model parameter were taken from literature and fitted in the heat transfer design equation, along with the values of other parameters and operating variables, which gave prediction of rate of change of water in bed and temperature change with respect to bed height, radius in different time interval during the fermentation process. These equations can be used for other organisms too and can be used for scaling up in future.