Resumen

FONSECA, E. F.; ALVES, T. L. M.; LIMA, E. L.  y  DE SOUZA JR., M. B.. A hybrid neural model for the production of sorbitol and gluconic acid using immobilized Zymomonas mobilis cells. Lat. Am. appl. res. [online]. 2004, vol.34, n.3, pp.187-193. ISSN 0327-0793.

Only ten years were enough for hybrid neural network-first principle models (HNM) reach a status of a standard industrial tool. This modeling strategy is employed here to represent the production of sorbitol and gluconic acid from glucose and fructose, using permeabilized and immobilized Zymomonas mobilis cells. Mass component balances are derived for the substrate concentrations. A multilayered neural network is used to represent the reaction rate. Experimental results were used to develop and validate the model. The HNM allows the elucidation of the phenomena involved in the process. It is observed from the results that the resistance for mass transfer from the liquid to the particles is increased at higher substrate concentrations and that the reaction rate depends on the concentrations of substrate and product in the particles. Additionally, it may be stated that the flexibility of the HNM allows the development of a model that would otherwise be difficult, if based solely on phenomenological principles.

Palabras clave : Hybrid Modeling Methods; Neural Networks; Enzymatic Reaction; Basket Reactor.

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