ISSN: 0973-7510

E-ISSN: 2581-690X

Research Article | Open Access
V. Dhanya
Department of Biotechnology, Al-Ameen College, Edathala, Aluva, Ernakulam – 683 564, Kerala, India.
J. Pure Appl. Microbiol., 2019, 13 (4): 2251-2260 | Article Number: 5780
https://doi.org/10.22207/JPAM.13.4.39 | © The Author(s). 2019
Received: 12/08/2019 | Accepted: 22/09/2019 | Published: 18/12/2019
Abstract

The population rise and industrialization has resulted in the uncontrolled and untreated discharges of various toxic chemicals from different industries and these toxic chemicals cause’s very serious pollution problems. Microbial degradation of toxic pollutants is one of the important way to remove the environmentally harmful compounds. The microorganisms metabolize or enzymatically transform the chemicals to less toxic metabolites. The present research emphasized on the biodegradation of mono-aromatic pollutants like Benzene, Toluene, Xylene and Phenol (BTXP) by a formulated microbial consortium constituted by Alcaligenes sp d2, Enterobacter aerogenes, Raoultella sp and Bacillus megaterium. Statistical design tools have been used for the optimization of different parameters which influencing BTXP biodegradation. The influencing parameters pH, concentration of BTXP and inoculum formulation was identified using Plackett-Burman design and was fine- tuned with Response Surface Methodology. The results specified that pH 6.25 and 250µl of 5% BTXP with the consortium formulated by mixing equal proportions ie, 3 ml of all the four bacterial isolates with OD 1,were found to be optimum for biodegradation. The degradation efficiency of the formulated consortium at its optimized condition was analyses by Fourier Transform Infrared Spectroscopy (FT/IR). About 96% of BTXP was degraded from the medium at the optimized condition and the spectral changes in FT/IR also recommended the effective removal of toxic chemicals from the medium.

Keywords

Biodegradation, Fourier Transform Infrared Spectroscopy, Microbial consortium, Plackett-Burman design, Response Surface Methodology.

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