On-line prediction of products concentrations in glutamate fermentation using metabolic network model and linear programming

Abstract

The experimental data showed that, in glutamate fermentation with strain Corynebacterium glutamicum S9114, glutamate produced in different ways with different patterns of OUR, CER and lactate accumulation at different DO levels. A metabolic network model combined with the linear programming optimization was thus developed to on-line predict glutamate production under different DO levels, with only OUR and CER be on-line measured. The results indicated the advantages of the metabolic network model over the traditional unstructured models, in terms of easy parameter identification, prediction accuracy, and the universal abilities. The proposed model potentially supplies an alternative way for on-line control and optimization of fermentation processes.