Biomass-degrading enzymes are one of the most costly inputs affecting the economic viability of the biochemical route for biomass conversion into biofuels. This work evaluates the effects of operational conditions on biomass-degrading multienzyme production by a selected strain of Aspergillus niger. The fungus was cultivated under solid-state fermentation (SSF) of soybean meal, using an instrumented lab-scale bioreactor equipped with an on-line automated monitoring and control system. The effects of air flow rate, inlet air relative humidity, and initial substrate moisture content on multienzyme (FPase, endoglucanase, and xylanase) production were evaluated using a statistical design methodology. Highest production of FPase (0.55 IU/g), endoglucanase (35.1 IU/g), and xylanase (47.7 IU/g) was achieved using an initial substrate moisture content of 84%, an inlet air humidity of 70%, and a flow rate of 24 mL/min. The enzymatic complex was then used to hydrolyze a lignocellulosic biomass, releasing 4.4 g/L of glucose after 36 hours of saccharification of 50 g/L pretreated sugar cane bagasse. These results demonstrate the potential application of enzymes produced under SSF, thus contributing to generate the necessary technological advances to increase the efficiency of the use of biomass as a renewable energy source.
-Bioprocess development studies concerning the production of cellulases are of crucial importance due to the significant impact of these enzymes on the economics of biomass conversion into fuels and chemicals. This work evaluates the effects of solid-state fermentation (SSF) operational conditions on cellulase production by a novel strain of Aspergillus oryzae using an instrumented lab-scale bioreactor equipped with an on-line automated monitoring and control system. The use of SSF cultivation under controlled conditions substantially improved cellulase production. Highest production of FPase (0.40 IU g -1 ), endoglucanase (123.64 IU g -1 ), and -glucosidase (18.32 IU g -1 ) was achieved at 28 C, using an initial substrate moisture content of 70%, with an inlet air humidity of 80% and an airflow rate of 20 mL min -1 . Further studies of kinetic profiles and respirometric analyses were performed. The results showed that these data could be very useful for bioprocess development of cellulase production and scale-up.
The major drawbacks in large-scale solid-state fermentation processes are related to difficulty in controlling the medium temperature and moisture content, which are variables that directly affect microbial growth and product formation. Several mathematical models have been developed to describe these effects, although none has simultaneously considered distinct growth phases, growth restrictions caused by large temperature variations at several distinct moisture content conditions, and product formation pathways. In this manner, the objectives of this paper were to develop a mathematical model to represent the process under different operational conditions and a model-based optimization procedure to investigate the effects of varying temperature profiles to maximize a (hemi) cellulolytic enzyme production during cultivation of Aspergillus niger under solid state fermentation. The proposed model correlates fungal growth with the CO 2 production rates and with enzymatic production by the Luedeking-Piret function. It was developed with data acquired in a laboratory-scale column-type bioreactor in controlled conditions of aeration, temperature, and inlet air relative humidity. The developed model accurately predicted the respiration profile responses at all temperatures, under the most productive moisture content conditions. Incubation of the culture with the optimized temperature profile improved the enzymatic production, compared to the estimated optimum static temperature. These findings demonstrate the usefulness of this model for the optimization of larger-scale SSF processes.
The solid-state fermentation (SSF) processes have existed for centuries in Eastern civilizations and have been widely used in the production of foodstuffs. In Western, the industry has worked preferably with the submerged fermentation (SF) processes, because it occurs in aqueous medium and it facilitates the bioreactor control. However, new demands, such as solid waste management, are not fully covered by FS. On the other hand, the processes of FES can be described as the growth of microorganisms on solid substrates in the absence of free water, which can meet this demand. But because of this characteristic, the greater difficulty is the bioreactor's internal variables control and the major one the removal of the heat produced by biological activity. Researches in this field show that removal is easier through air exchange, because of the difficulties of thermal conduction in a solid medium. Therefore, it becomes necessary to develop an aeration control system that allows processes evaluation in bench scale, thereby reducing the number of uncertainties in modeling and simulation process. Thus, facilitating the temperature control of a larger-scale bioreactor's bed. The aim of this work is to apply a robust control technique that guarantees the system's performance indexes throughout the air flow and temperature operational range. The plant was modeled on a first-order system without delay, at nine different conditions of temperature and aeration. These indixes are: settling time less than 12000 seconds and overshoot less than 10%. The controller used was a Proportional Integrative (PI) type. This controller was tuned using the LMI methodology (Linear Matrix Inequalities) through the V-K iterative algorithm restrictions. The implementation results show that the restrictions used in the algorithm are able to tune the controller, even not knowing all the dynamics of the aeration system.
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