Statistical Optimization of Biosurfactant Production from Aspergillus niger SA1 Fermentation Process and Mathematical Modeling

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Abstract

In this study, we sought to investigate the production and optimization of biosurfactants by soil fungi isolated from petroleum oil-contaminated soil in Saudi Arabia. Forty-four fungal isolates were isolated from ten petroleum oil-contaminated soil samples. All isolates were identified using the internal transcribed spacer (ITS) region, and biosurfactant screening showed that thirty-nine of the isolates were positive. Aspergillus niger SA1 was the highest biosurfactant producer, demonstrating surface tension, drop collapsing, oil displacement, and an emulsification index (E24) of 35.8 mN/m, 0.55 cm, 6.7 cm, and 70%, respectively. This isolate was therefore selected for biosurfactant optimization using the Fit Group model. The biosurfactant yield was increased 1.22 times higher than in the nonoptimized medium (8.02 g/l) under conditions of pH 6, temperature 35°C, waste frying oil (5.5 g), agitation rate of 200 rpm, and an incubation period of 7 days. Model significance and fitness analysis had an RMSE score of 0.852 and a p-value of 0.0016. The biosurfactant activities were surface tension (35.8 mN/m), drop collapsing (0.7 cm), oil displacement (4.5 cm), and E24 (65.0%). The time course of biosurfactant production was a growth-associated phase. The main outputs of the mathematical model for biomass yield were Yx/s (1.18), and μmax (0.0306) for biosurfactant yield was Yp/s (1.87) and Yp/x (2.51); for waste frying oil consumption the So was 55 g/l, and Ke was 2.56. To verify the model's accuracy, percentage errors between biomass and biosurfactant yields were determined by experimental work and calculated using model equations. The average error of biomass yield was 2.68%, and the average error percentage of biosurfactant yield was 3.39%.

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APA

Al-Hazmi, M. A., Moussa, T. A. A., & Alhazmi, N. M. (2023). Statistical Optimization of Biosurfactant Production from Aspergillus niger SA1 Fermentation Process and Mathematical Modeling. Journal of Microbiology and Biotechnology, 33(9), 1238–1249. https://doi.org/10.4014/jmb.2303.03005

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