Journal
FOOD AND BIOPRODUCTS PROCESSING
Volume 134, Issue -, Pages 1-18Publisher
ELSEVIER
DOI: 10.1016/j.fbp.2022.04.0020960-3085
Keywords
Dynamic modelling; Mass transfer rate; Clostridium carboxidivorans; Substrate inhibition; Product inhibition; Sensitivity analysis
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A dynamic-kinetic model for gas fermentation of C. carboxidivorans was developed and validated in this study. The model considered gas-liquid mass transfer, carbon monoxide uptake, and multiple conversion pathways of acid/alcohol production. The analysis revealed that adjusting the operating conditions could greatly improve the fermentation performance.
A dynamic-kinetic model for gas fermentation of C. carboxidivorans is presented. The model described the acid/alcohol production in gas-fed stirred tank reactors (GFSTR) and in batch pressurized reactors. The model took into account gas-liquid mass transfer rate, carbon monoxide uptake rate and three conversion paths: cell growth associated with acid/alcohol production, alcohol production by acid conversion and direct alcohol production not associated to cell growth. The assessment of kinetic parameters/yields was carried out by regression of experimental data retrieved from the literature. The model was then used to study the effects of several process conditions on the fermentation performances. The sensitivity was analysed with respect to three operating variables (agitation speed, gas feeding flow-rate and bioreactor filling ratio) and also to the kinetic parameters/yields. The proposed model successfully reproduced the experimental data: the R2 of the investigated variable concentrations ranged between 0.769 and 0.885. Sensitivity analysis pointed out that: i) the model was significantly affected by parameters related to the growth kinetic whereas it was not impacted by parameters related to direct alcohol production; ii) fermentation performances could be improved tuning the operating conditions, in particular, the decrease of the mass transfer rate could increase the cell/metabolite production. (c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
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