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Thermostable lipase from a newly isolated Staphylococcus xylosus strain; process optimization and characterization using RSM and ANN Electron. J. Biotechnol.
Khoramnia,Anahita; Lai,Oi Ming; Ebrahimpour,Afshin; Tanduba,Carynn Josue; Voon,Tan Siow; Mukhlis,Suriati.
Normal feed forward back-propagation artificial neural network (ANN) and cubic backward elimination response surface methodology (RSM) were used to build a predictive model of the combined effects and optimization of culture parameters for the lipase production of a newly isolated Staphylococcus xylosus. The results demonstrated a high predictive accuracy of artificial neural network compared to response surface methodology. The optimum operating condition obtained from the ANN model was found to be at 30ºC incubation temperature, pH 7.5, 60 hrs incubation period, 1.8% inoculum size and 60 rpm agitation. The lipase production increased 3.5 fold for optimal medium. The produced enzyme was characterized biochemically and this is the first report about a...
Tipo: Journal article Palavras-chave: Artificial neural network; Characterization; Lipase; Optimization; Response surface methodology; Staphylococcus xylosus.
Ano: 2010 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582010000500015
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