Artificial neural network modeling of biotreatment of malachite green by Spirodela polyrhiza: Study of plant physiological responses and the dye biodegradation pathway

Abstract

Phytoremediation is an environmental friendly and sustainable means of pollutant remediation through the use of plants. The ability of duckweed (Spirodela polyrhiza L.) for decolorization of malachite green was evaluated. Effect of some operational parameters such as initial plant biomass, the reaction time, initial dye concentration, pH and temperature on dye removal efficiency was determined. The importance of each parameter was assessed by artificial neural network (ANN) modeling and the plant initial biomass and pH were found to be the most important factors. The findings indicated that ANN provided reasonable predictive performance (R2=0.98). The metabolic fate of the dye was proposed by identification of 6 intermediate compounds produced during this process by GC–MS technique. Some physiological responses of the plant were studied at 10 and 20mg/L of the dye. The activities of antioxidant enzymes were increased at high concentration of the contaminant but there was a significant decrease in photosynthetic pigments content at 20mg/L of malachite green.