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African Journal of Biotechnology

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Optimization of chloroxylenol degradation by Aspergillus niger using Plackett-Burman design and response surface methodology

Khaled M. Ghanem, Fahad A. Al-Fassi, Nuha M. Al-Hazmi

Abstract


Chloroxylenol is a very toxic phenolic derivative and it represents potential hazard towards human health and to the environment. Aspergillus niger, local isolate, is an efficient fungus to degrade 99.72% of 2 mg/L of chloroxylenol after 7 days of fermentation. It also has a high capacity to degrade 91.83% of higher chloroxylenol concentration of 20 mg/L after 6 days of incubation on mineral medium amended with 2 g/L of glucose. Statistical experimental designs were used to optimize the process of chloroxylenol degradation by the fungus. The most important factors influencing chloroxylenol degradation, as identified by a two-level Plackett-Burman design with 11 variables, were NaCl, (NH4)2SO4, and inoculums size. Response surface analysis was adopted to further investigate the mutual interactions between these variables and to identify their optimal values that would generate maximum chloroxylenol degradation. Under the optimized medium compositions and culture conditions, A. niger was able to degrade completely (100%) chloroxylenol (20 mg/L) after 134.6 h of fermentation. The predicted values of Plackett-Burman conditions and response surface methodology were further verified by validation experiments. The excellent correlation between predicted and experimental values confirmed the validity and practicability of this statistical optimum strategy. Optimal conditions obtained in this work laid to a solid foundation for further use of A. niger in treatment of high strength chloroxylenol polluted effluents. So, the optimized conditions were applied to bioremediate crude sewage containing 27.8 mg/L of chloroxylenol by A. niger. The fungus efficiently degraded chloroxylenol after 8 days of fermentation.

Key words: Chloroxylenol degradation, Aspergillus niger, Plackett-Burman design, Response surface methodology.




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