Isolation and Screening of Trichosporon Asahii for Biosurfactant Production and Optimization

L. Ohalete, S.O. Umeh and F.O. Nwajiobi
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L. Ohalete: Department of Applied Microbiology and Brewing, Faculty of Biosciences, Nnamdi Azikiwe University, Awka, Nigeria.
S.O. Umeh: Department of Applied Microbiology and Brewing, Faculty of Biosciences, Nnamdi Azikiwe University, Awka, Nigeria.
F.O. Nwajiobi: Department of Applied Microbiology and Brewing, Faculty of Biosciences, Nnamdi Azikiwe University, Awka, Nigeria.

International Journal of Research and Innovation in Applied Science, 2024, vol. 9, issue 4, 413-424

Abstract: Biosurfactant are biomolecules compounds produced by microorganisms that have desirable characteristics such as being easily degradable and low toxicity over chemical surfactants. Despite their desired properties, their use industrially is limited due to production cost. In this study, optimization of biosurfactant production by Trichosporon asahii isolated from some mechanic workshops was carried out. Enrichment technique was used for the isolation of the organism while response surface methodology was used to optimize the production parameters to ensure cost-effective production. Four independent variables were optimized: carbon source (Rice bran), Nitrogen source (Cow dung), pH and inoculum size with the emulsification index as the response. Three biochemical test such as phenol-sulphuric, phosphate and biuret tests were used to characterize the produced biosurfactant. The result indicated that Trichosporon asahii isolated from oil contaminated soil can produce biosurfactant with emulsification index of 52.2% under optimized cultural conditions of 13.6 g/L of rice bran, 10.25 g/L of cow dung, 7 ml inoculum size and pH of 8.84 in 250 ml conical flask. Lowest surface tension reduction activity of 34.29 ± 0.10 and critical micelle concentration was attained at 6.4 mg/ml. The biochemical characterization showed that the produced biosurfactant was glycophospholipid. The regression coefficient (R2) value of 56.5% implied good fitness of the model design used in the experiment. The study shows that the use of agro industrial waste and response surface methodology is efficient for the production and optimization of biosurfactant.

Date: 2024
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