Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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| Data(s) |
01/11/2013
01/11/2013
02/08/2013
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| Resumo |
In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation. INCT-CNPq (Brasilia, DF, Brazil) INCTCNPq (Brasilia, DF, Brazil) FAPESP (Sao Paulo, SP, Brazil) FAPESP (Sao Paulo, SP, Brazil) |
| Identificador |
ENVIRONMENTAL TECHNOLOGY, ABINGDON, v. 33, n. 15, supl. 4, Part 1-2, pp. 1739-1745, DEC, 2012 0959-3330 http://www.producao.usp.br/handle/BDPI/37148 10.1080/09593330.2011.644585 |
| Idioma(s) |
eng |
| Publicador |
TAYLOR & FRANCIS LTD ABINGDON |
| Relação |
ENVIRONMENTAL TECHNOLOGY |
| Direitos |
closedAccess Copyright TAYLOR & FRANCIS LTD |
| Palavras-Chave | #EXPERIMENTAL DESIGN #ARTIFICIAL NEURAL NETWORKS #MICROBIAL CONSORTIUM #PROCESS OPTIMIZATION #PHENOL DEGRADATION #INHIBITORY SUBSTRATE #PSEUDOMONAS-PICTORUM #DEGRADATION #SOIL #TEMPERATURE #SUPPLEMENTS #NUTRIENT #KINETICS #WATER #ENVIRONMENTAL SCIENCES |
| Tipo |
article original article publishedVersion |
