A hybrid neural model (HNM) for the on‐line monitoring of lipase production by <i>Candida rugosa</i>

Abstract

Abstract A mechanistic model was proposed by Gordillo for the representation of lipase production by Candida rugosa , with the bioreactor in batch and fed‐batch operation. However, the model was not able to represent the lipolytic activity. The objective of the present study is to propose an efficient hybrid neural‐phenomenological model (HNM) for this process. The experimental data used corresponded to fed‐batch operation with constant substrate feed rate at 2.8 × 10 −7 ; 5.6 × 10 −7 and 9.7 × 10 −7 kg s −1 . Artificial neural networks (ANNs) were trained to represent the aqueous and intracellular lipase activity and were further associated with a reduced version of the mechanistic model of the proposed HNM. When compared to the experimental data, the HNM exhibited higher accuracy. The HNM can be employed in process monitoring using only on‐line measurements of CO 2 and substrate feed rate to infer enzyme activities and also substrate and biomass concentrations. Copyright © 2007 Society of Chemical Industry