Biodegradation of direct blue 129 diazo dye by Spirodela polyrrhiza: An artificial neural networks modeling

摘要: Phytoremediation potential of the aquatic plant Spirodela polyrrhiza was examined for direct blue 129 (DB129) azo dye. The dye removal efficiency optimized under variable conditions operational parameters including time, initial concentration, pH, temperature and amount plant. study reflected significantly enhanced S. by increasing temperature, concentration Intriguingly, artificial neural network (ANN) predicted time as most dominant parameter on DB129 efficiency. Furthermore, effect treatment some physiologic indices growth rate, photosynthetic pigments content, lipid peroxidation antioxidant enzymes were studied. results revealed a reduction in content multiplication fronds after exposure to solution. In contrast, malondialdehyde well catalase (CAT) peroxidase (POD) activities increased that probably due ability overcome oxidative stress. As result biodegradation, number intermediate compounds identified gas chromatography-mass spectroscopy (GC-MS) analysis. Accordingly, probable degradation pathway postulated.