Modelagem matemática e desenvolvimento de estratégias de controle automático de biorreator de leito fixo para a produção de celulases fúngicas por cultivo em estado sólido
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Data
2022-08-31
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Universidade Estadual Paulista (Unesp)
Resumo
Nos últimos anos o cultivo em estado sólido (CES) tem sido bastante aplicado para a produção de celulase fúngicas que viabilizam a produção do etanol de segunda geração. Dentre os biorreatores disponíveis para o CES, os biorreatores de coluna apresentam inúmeras vantagens, porém, algumas limitações como o monitoramento das concentrações dos gases impedem a determinação do crescimento microbiano durante a fermentação. Diante desta dificuldade, este trabalho tem como objetivo a modelagem matemática e o desenvolvimento de estratégias de controle automático de temperatura para ampliação de escala para a produção de celulases fúngicas por CES, sendo proposto inicialmente o desenvolvimento de um sistema automático para monitoramento de gases em diversas posições do biorreator de leito fixo empacotado. Foram avaliados em tempo real a taxa de comunicação do sistema, perfis de temperatura, concentrações de CO2 e O2, além dos perfis de umidade e atividade enzimática CMCase no final das fermentações. Para tanto foram realizadas diversas fermentações utilizando o fungo termofílico Myceliophthora thermophila I-1D3b cultivado em bagaço de cana e farelo de trigo (7:3 m/m), na umidade de 75% e temperatura de 45°C variando a taxa de aeração, tamanho do biorreator, e critérios de acionamento de válvulas de amostragem de gases (Casos I a IV). Em relação à taxa de comunicação, observou-se um atraso de 1,6 s/iteração na apresentação dos dados coletados em relação ao tempo de 1 s/iteração configurado, não interferindo nos resultados apresentados. Também foi possível avaliar o efeito da sequência de ativação da válvula na concentração de gases nos módulos fermentativos. No Caso I observou-se uma maior oscilação da temperatura e das concentrações de O2 e CO2, resultando num acúmulo da concentração de CO2 até valores próximos a 9% nos módulos fermentativos. Nos Casos II a IV as condições de temperatura e concentrações de gases se mantiveram mais estáveis, resultando, nestes três últimos casos, em uma concentração máxima de CO2 de 4%, de forma que a atmosfera do meio não fosse prejudicial ao processo. Utilizando como referência um modelo matemático para simulação de biorreatores de leito fixo empacotado a duas fases (balanços energia e água), foi avaliada a sensibilidade de algumas variáveis de processo em dois planejamentos experimentais utilizando Metodologia de Superfície de Resposta (MSR) e dentre os parâmetros avaliados, aeração, temperatura da parede e altura do biorreator apresentaram influência significativa sobre as temperaturas e teores de umidade das fases sólida e gasosa e concentrações de biomassa e substrato. Ao simular um biorreator de escala industrial de 50 m3, obteve-se perfis de temperatura máximas próximas a 53°C, semelhantes aos encontrados nos experimentos de diferentes vazões de aeração para o biorreator largo. Foram avaliadas ainda diferentes estratégias de controle do processo com a inversão do fluxo de ar e com a aeração auxiliar no centro do biorreator, demonstrando que para estes diferentes métodos de controle do processo, os perfis de temperatura e umidade podem ser controlados. Dessa forma, este sistema automatizado de acionamento de válvulas e coleta de dados em tempo real mostrou-se efetivo e permite sua aplicação em conjunto com técnicas de controle automático do processo fermentativo para otimizar as condições de produção enzimática em CES.
In recent years, solid state cultivation (SSC) has been widely applied for the production of fungal cellulase that enable the production of second-generation ethanol. Among the bioreactors available for SSC, column bioreactors have numerous advantages, however, some limitations such as monitoring of gas concentrations prevent the determination of microbial growth during fermentation. Faced with this difficulty, this work aims at mathematical modeling and the development of automatic temperature control strategies to scale up the production of fungal cellulases by SSC, initially proposing the development of an automatic system for monitoring gases in several packed bed bioreactor positions. The communication rate of the system, temperature profiles, CO2 and O2 concentrations, as well as moisture profiles and CMCase enzymatic activity at the end of the fermentations were evaluated in real time. For that, several fermentations were carried out using the thermophilic fungus Myceliophthora thermophila I-1D3b grown on sugarcane bagasse and wheat bran (7:3 w/w), at 75% moisture and 45°C, varying the aeration rate, size of the bioreactor, and criteria for triggering gas sampling valves (Cases I to IV). Regarding the communication rate, there was a delay of 1.6 s/iteration in the presentation of the collected data in relation to the configured time of 1 s/iteration, not interfering with the results presented. It was also possible to evaluate the effect of the valve activation sequence on the concentration of gases in the fermentation modules. In Case I, a greater oscillation of temperature and concentrations of O2 and CO2 was observed, resulting in an accumulation of the concentration of CO2 until values close to 9% in the fermentation modules. In Cases II to IV, the temperature conditions and gas concentrations remained more stable, resulting, in these last three cases, in a maximum CO2 concentration of 4%, so that the atmosphere of the medium was not harmful to the process. Using as a reference a mathematical model for the simulation of two-phase packed bed bioreactors (energy and water balances), the sensitivity of some process variables was evaluated in two experimental designs using Response Surface Methodology (RSM) and among the parameters evaluated, aeration, wall temperature and height of the bioreactor had a significant influence on the temperatures and moisture contents of the solid and gas phases and concentrations of biomass and substrate. When simulating an industrial scale bioreactor of 50 m3, maximum temperature profiles were obtained close to 53°C, similar to those found in experiments with different aeration flow rates for the wide bioreactor. Different process control strategies were also evaluated with air flow inversion and auxiliary aeration in the center of the bioreactor, demonstrating that for these different process control methods, temperature and humidity profiles can be controlled. Thus, this automated system for activating valves and collecting data in real time proved to be effective and allows its application in conjunction with automatic control techniques of the fermentation process to optimize enzyme production conditions in SSC.
In recent years, solid state cultivation (SSC) has been widely applied for the production of fungal cellulase that enable the production of second-generation ethanol. Among the bioreactors available for SSC, column bioreactors have numerous advantages, however, some limitations such as monitoring of gas concentrations prevent the determination of microbial growth during fermentation. Faced with this difficulty, this work aims at mathematical modeling and the development of automatic temperature control strategies to scale up the production of fungal cellulases by SSC, initially proposing the development of an automatic system for monitoring gases in several packed bed bioreactor positions. The communication rate of the system, temperature profiles, CO2 and O2 concentrations, as well as moisture profiles and CMCase enzymatic activity at the end of the fermentations were evaluated in real time. For that, several fermentations were carried out using the thermophilic fungus Myceliophthora thermophila I-1D3b grown on sugarcane bagasse and wheat bran (7:3 w/w), at 75% moisture and 45°C, varying the aeration rate, size of the bioreactor, and criteria for triggering gas sampling valves (Cases I to IV). Regarding the communication rate, there was a delay of 1.6 s/iteration in the presentation of the collected data in relation to the configured time of 1 s/iteration, not interfering with the results presented. It was also possible to evaluate the effect of the valve activation sequence on the concentration of gases in the fermentation modules. In Case I, a greater oscillation of temperature and concentrations of O2 and CO2 was observed, resulting in an accumulation of the concentration of CO2 until values close to 9% in the fermentation modules. In Cases II to IV, the temperature conditions and gas concentrations remained more stable, resulting, in these last three cases, in a maximum CO2 concentration of 4%, so that the atmosphere of the medium was not harmful to the process. Using as a reference a mathematical model for the simulation of two-phase packed bed bioreactors (energy and water balances), the sensitivity of some process variables was evaluated in two experimental designs using Response Surface Methodology (RSM) and among the parameters evaluated, aeration, wall temperature and height of the bioreactor had a significant influence on the temperatures and moisture contents of the solid and gas phases and concentrations of biomass and substrate. When simulating an industrial scale bioreactor of 50 m3, maximum temperature profiles were obtained close to 53°C, similar to those found in experiments with different aeration flow rates for the wide bioreactor. Different process control strategies were also evaluated with air flow inversion and auxiliary aeration in the center of the bioreactor, demonstrating that for these different process control methods, temperature and humidity profiles can be controlled. Thus, this automated system for activating valves and collecting data in real time proved to be effective and allows its application in conjunction with automatic control techniques of the fermentation process to optimize enzyme production conditions in SSC.
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Microbiologia industrial, Fermentação em estado sólido, Enzimas de fungos, Tecnologia de bioprocesso, Modelos matemáticos, Industrial microbiology, Solid-state fermentation, Fungal enzymes, Bioprocess technology, Mathematical models