EXPERIMENTAL INVESTIGATION OF DIFFERENTIATION STATE MODEL FOR CARBON-LIMITED FED-BATCH PENICILLIN PRODUCTION (FERMENTATION, MORPHOLOGY, FILTRATION)

JUDY LYNN WALKER CAGNEY, Purdue University

Abstract

The development and implementation of control strategies for bioreactor systems require improved predictive models and on-line sensors for important process variables. To this end, a structured model for glucose-limited fed-batch penicillin production has been developed for use in the determination of optimal feeding policies. In the model, cell mass exists in three differentiation states--growing hyphal tips, penicillin producing cell mass, and degenerated, inactive cell mass. Expressions are developed for growth, branching, differentiation and degeneration processes; an expression describing inhibition of penicillin synthesis by high concentrations of glucose is used. Fed-batch data were obtained in a highly automated, computerized bioreactor system which includes a filtration device developed for on-line estimation of mycelial concentrations. Measurement of void cell mass fraction through application of the Kozeny-Carman equation to filtration measurements allows estimation of the amount of degenerated cell mass present. Filtration measurements along with maintenance energy requirements as calculated using off-gas measurements are used to follow the time profiles of the three differentiation states. Model simulations give a good quantitative description of biomass, penicillin, glucose, and differentiation state time profiles obtained over a range of growth and production phase growth rates. An unstructured model, studied for purposes of comparison, is incapable of predicting all of the experimental data, particularly when significant mycelial degeneration has occurred. The structure of the differentiation state model allows interpretation of penicillin production phenomena, such as a minimum growth rate requirement for high synthesis rates and variable maintenance energy requirements, for which the unstructured model does not account. Temperature studies demonstrate the need to develop the temperature dependence of only 4 model parameters--growth, branching, synthesis, and hydrolysis coefficients--before using the model for optimal temperature profile development.

Degree

Ph.D.

Subject Area

Chemical engineering

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