RESUMO

Penicillin G acylase (PGA) is one of the most important enzymes for the pharmaceutical industry. Bacillus megaterium has the advantage of producing extra-cellular PGA. This work compares two neural networks (NNs) architectures for on-line inference of B. megaterium cell mass in an aerated stirred tank bioreactor, during the production of PGA. Nowadays, intelligent computing tools such as artificial NNs and fuzzy logic are commonly applied for state inference and modeling of bioreactors. Combining these two approaches in hybrid, neuro-fuzzy systems, may be advantageous. Our results indicate that a neuro-fuzzy inference system showed a better performance to infer cell concentrations, when compared to multilayer perceptrons networks.

Assuntos

Bacillus megaterium/citologia , Bacillus megaterium/enzimologia , Redes Neurais de Computação , Penicilina Amidase/biossíntese , Reatores Biológicos , Contagem de Colônia Microbiana/estatística & dados numéricos , Lógica Fuzzy , Modelos Biológicos , Sistemas On-Line , Biologia de Sistemas

Assuntos

Bebidas Alcoólicas/análise , Bacillus megaterium/citologia , Bacillus megaterium/isolamento & purificação , Bacillus megaterium/fisiologia , México