Optimization of Bioremediation of Crude Oil Polluted Soil through Variation in Moisture Content and Proportion of Augmenting Bacterium and Fungus
Peekate, Lekiah Pedro *
Department of Microbiology, Rivers State University, P.M.B. 5080, Port Harcourt, Nigeria.
Friday, Mdananebari
Department of Microbiology, Rivers State University, P.M.B. 5080, Port Harcourt, Nigeria.
Aleruchi, Owhonka
Department of Microbiology, Rivers State University, P.M.B. 5080, Port Harcourt, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Aim: The aim of this study was to enhance bioremediation of crude-oil polluted soil through optimization procedures.
Study Design: The Box-Benkhen coded values format and experimental design were used in the design of the study.
Place and Duration of Study: The study was carried out in the Microbiology laboratory of the Department of Microbiology, Rivers State University, Nigeria, between February 2024 and July 2024.
Methodology: Hydrocarbon utilizing bacteria (HUB) & fungi (HUF) were isolated from crude-oil polluted soil, and screened for hydrocarbon degrading ability (HCDA). HUB and HUF with the highest HCDA were identified and used for bioremediation optimization experiment. In the experiment, different combination of moisture content (MC), and proportion of HUB (pHUB) & HUF (pHUF) were investigated for their effect on extent of hydrocarbon reduction (EoHR). EoHR obtained from the different combinations were fitted using a generalized polynomial model so as to obtain a polynomial equation for predicting EoHR. The equation was used in generating prediction profiles from which the combined values of the 3 parameters that will lead to the highest EoHR was determined. The predicted combined values were implemented in a new setup. A control and a setup enhanced with fertilizer were also prepared. The setups were maintained for 3 weeks. On day 0, 14, and 21 samples were collected and analyzed for total hydrocarbon concentration (THC).
Results: The results obtained showed that among the coded isolated HUB and HUF, HB5 and HF1 had the highest HCDA; 36.4% and 4.1% respectively, and were identified phenotypically as Klebsiella ornithinolytica and Aspergillus flavus respectively. The results of the optimization experiment and prediction profiles showed that the highest (68.6%) EoHR was achievable at MC = 20%, pHUB = 10%, and pHUF = 1%. The actual EoHR on day 21 in the optimized, enhanced optimized, and control setups were 60.3, 58.9, and 39.9% respectively.
Conclusion: Bioremediation optimization studies is advantageous and should be carried out on crude-oil polluted sites before carrying out bioremediation.
Keywords: Bioremediation, hydrocarbon-polluted soil, hydrocarbon-utilizing microorganisms, box-behnken experimental design matrix, prediction profiles