Alvarado, Kelly | 2022-06-23
Crude oil and its derivatives have high application in different industries, and unforeseen spills or overexploitation generate a significant threat in ecosystems, causing negative impacts on soil, water, and air. There are microorganisms capable of metabolizing hydrocarbons through the bioremediation process with biosurfactant production, but large-scale culturing and technification are still a significant challenge due to their high costs and optimization stage requirement. An unstructured kinetic model provides crucial information regarding improvements and process optimization at the first stages. Thereof prediction of bioprocess kinetic behavior is expected from mathematical expressions. Considering the above, biosurfactants’ bioprocess modeling tends to be an essential tool to increasingly focus on the efficiency and profitability of oil industries. That is why biosurfactant kinetics production from Bacillus subtilis is investigated in this research, implementing a mathematical model. Previous studies refereed experimental data to integrate into Monod, Contois, Haldane, Moser, Powell, Tessier, Aiba-Edward, Luong, Yano-Koga, and Chen-Hashimoto equations. Therefore, a nonlinear regression parameterization procedure is applied using the Matlab Fmincon Function. The best accuracy found between experimental and simulated data was achieved using the Chen-Hashimoto kinetic model with μmax, kd and ks values of 2.3239 d− 1 , 0.3748 d− 1 and 1.1619 g/L, respectively. This research suggests that biosurfactant production occurs under anaerobic conditions where hydrolysis controls microbial growth. These research results are a promising aim related to industrial biotechnology since computational modeling is essential for process efficiency from a technical and economic perspective.
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