Clostridium tyrobutyricum (C. tyrobutyricum) is a fermentation strain used to produce butyric acid. A promising new biofuel, n-butanol, can be produced by catalysis of butyrate, which can be obtained through microbial fermentation. Butyric acid has various uses in food additives and flavor agents, antiseptic substances, drug formulations, and fragrances. Its use as a food flavoring has been approved by the European Union, and it has therefore been listed on the EU Lists of Flavorings. As butyric acid fermentation is a cost-efficient process, butyric acid is an attractive feedstock for various biofuels and food commercialization products. 12C6+ irradiation has advantages over conventional mutation methods for fermentation production due to its dosage conformity and excellent biological availability. Nevertheless, the effects of these heavy-ion irradiations on the specific productiveness of C. tyrobutyricum are still uncertain. We developed non-structured mathematical models to represent the heavy-ion irradiation of C. tyrobutyricum in biofermentation reactors. The kinetic models reflect various fermentation features of the mutants, including the mutant strain growth model, butyric acid formation model, and medium consumption model. The models were constructed based on the Markov chain Monte Carlo model and logistic regression. Models were verified using experimental data in response to different initial glucose concentrations (0-180 g/L). The parameters of fixed proposals are applied in the various fermentation stages. Predictions of these models were in accordance well with the results of fermentation assays. The maximum butyric acid production was 56.3 g/L. Our study provides reliable information for increasing butyric acid production and for evaluating the feasibility of using mutant strains of C. tyrobutyricum at the pre-development phase.
Keywords: Clostridium tyrobutyricum; MCMC model; butyric acid; fermentation; logistic regression; luedeking—piret model.
Copyright © 2021 Cao, Gao, Wang, Shu, Hu, Xie, Cui, Guo and Zhou.