alexa Statistical Enhancement of Cyanide Degradation Using Microbial Consortium
ISSN: 1948-5948

Journal of Microbial & Biochemical Technology
Open Access

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Research Article

Statistical Enhancement of Cyanide Degradation Using Microbial Consortium

Virender Kumar, Vijay Kumar and Tek Chand Bhalla*

Department of Biotechnology, Himachal Pradesh University, Summer Hill, Shimla-05, H.P, India

*Corresponding Author:
Tek Chand Bhalla
Department of Biotechnology
Himachal Pradesh University
Summer Hill, Shimla, India
Tel: +91177-2832153
E-mail: [email protected]

Received Date: September 21, 2015; Accepted Date: October 05, 2015; Published Date: October 12, 2015

Citation: Kumar V, Kumar V, Bhalla TC (2015) Statistical Enhancement of Cyanide Degradation Using Microbial Consortium. J Microb Biochem Technol 7: 344-350. doi:10.4172/1948-5948.1000237

Copyright: © 2015 Kumar V, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Remediation of cyanide contaminated water bodies using microorganisms is a popular alternative over chemical and physical methods of cyanide detoxification. The objective of the present study is to develop a microbial consortium using three bacteria, i.e., Enterobacter sp. RL2a, Serratia marcescencs RL2b and Achromobacter sp. RL2c for effective degradation of simulated cyanide wastewater. In vitro cyanide degradation was optimum with 2% inoculum volume of cells; pH 6.0, 30°C temperature at 20 mM substrate concentration leading to complete cyanide removal in 36 h. Response surface methodology (RSM) approach was used for optimization of reaction conditions for cyanide degradation using 5 mg ml-1 resting cells of microbial consortium. Plackett-burman design depicted that three variables viz. time, resting cells of strain RL2b and pH exhibit positive effect on cyanide degradation. The analysis of the quadratic regression model suggested that the model was very significant as correlation coefficient (0.847) closer to 1 denotes better correlation between the observed and predicted responses. The model was validated by performing the experiment under optimum conditions, which resulted in 63% cyanide degradation in 1 h reaction and complete degradation of 20 mM cyanide in 6 h. By performing factorial design, there was 1.3 fold (33%) increases in cyanide degradation.

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