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Elsevier, Ecological Engineering, (70), p. 183-188, 2014

DOI: 10.1016/j.ecoleng.2014.05.009

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An approach to the metabolic degradation of diethylketone (DEK) by Streptococcus equisimilis : effect of DEK on the growth, biodegradation kinetics and efficiency

Journal article published in 2014 by Filomena Costa, Cristina Quintelas ORCID, M. Teresa Tavares
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract The degradation of diethylketone by Streptococcus equisimilis was evaluated. The toxicity of diethylketone was assessed evaluating the growth of the bacteria for the range of diethylketone concentration between 0 and 6.4??g??L???1. The maximum specific growth rate achieved is 0.555??h???1 at 3.2??g??L???1 of initial diethylketone concentration, followed by a slight decrease, suggesting that higher concentrations of diethylketone negatively affect the growth. The biodegradation efficiency (%) obtained was approximately 95%, for all the initial concentrations tested. The kinetic parameters were estimated using Monod, Powell, Haldane and Loung models. The experimental data is well fitted by the Loung and Haldane models, R2??=??0.98 for both, as compared to Monod model (R2??=??0.79) and Powell model (R2??=??0.72). Once the previous intrinsic functions were established, a set of assays was also performed to evaluate the biodegradation of diethylketone using concentrated biomass for initial diethylketone concentrations ranging from 0.8 to 3.9??g??L???1 in a bioreactor operating in batch mode with recirculation. These concentrated biomass assays aimed the optimization of operational conditions. The removal percentages obtained were approximately 100%, for all the initial ketone concentrations tested and the biodegradation rate followed the pseudo-second order kinetics. The mechanism involved in the degradation of diethylketone by this microorganism is not completely understood, but an approach to the metabolic degradation pathway was established by the identification of the metabolites involved on the process.