Phytoextraction potential of water fern (Azolla pinnata) in the removal of a hazardous dye, methyl violet 2B: Artificial neural network modelling. Issue 5 (16th April 2018)

• Record Type: Journal Article
• Authors: Kooh, Muhammad Raziq Rahimi; Lim, Linda B. L.; Lim, Lee-Hoon; Malik, Owais Ahmed
• Is Part Of: International journal of phytoremediation. Volume 20:Issue 5(2018)
• Page Start: 424
• Page End: 431
• Publication Date: 2018-04-16
• Subjects: Methyl violet 2b -- phytoextraction -- water fern (Azolla pinnata); Phytoremediation -- Periodicals; 628.5
• DOI: 10.1080/15226514.2017.1365337
• Languages: English
• ISSNs: 1522-6514

Abstract

ABSTRACT: This study investigated the potential of Azolla pinnata (AP) in the removal of toxic methyl violet 2B (MV) dye wastewater using the phytoextraction approach with the inclusion of an Artificial Neural Network (ANN) modelling. Parameters examined included the effects of dye concentration, pH and plant dosage. The highest removal efficiency was 93% which was achieved at a plant dosage of 0.8 g (dye volume = 200 mL, initial pH = 6.0, initial dye concentration = 10 mg L −1 ). A significant decrease in relative frond number (RFN), a growth rate estimator, observed at a dye concentration of 20 mg L −1 MV indicated some toxicity, which coincided with the plant pigments studies where the chlorophyll a content was lower than the control. There were little differences in the plant pigment contents between the control and those in the presence of dye (5 to 15 mg L −1 ) indicating the tolerance of AP to MV at lower concentrations. A three-layer ANN model was optimized (6 neurons in the hidden layer) and successfully predicted the phytoextraction of MV ( R = 0.9989, RMSE = 0.0098). In conclusion, AP proved to be a suitable plant that could be used for the phytoextraction of MV while the ANN modelling has shown to be a reliable method for the modelling of phytoextraction of MV using AP.