Microbial Decolorization of Triazo Dye, Direct Blue 71: An Optimization Approach Using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). (18th February 2020)

• Record Type: Journal Article
• Authors: Zin, Khairunnisa' Mohd; Effendi Halmi, Mohd Izuan; Abd Gani, Siti Salwa; Zaidan, Uswatun Hasanah; Samsuri, A. Wahid; Abd Shukor, Mohd Yunus
• Other Names: Pollice Alfieri Academic Editor.
• Is Part Of: BioMed research international. Volume 2020(2020)
• Publication Date: 2020-02-18
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2020/2734135
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : The release of wastewater from textile dyeing industrial sectors is a huge concern with regard to pollution as the treatment of these waters is truly a challenging process. Hence, this study investigates the triazo bond Direct Blue 71 (DB71) dye decolorization and degradation dye by a mixed bacterial culture in the deficiency source of carbon and nitrogen. The metagenomics analysis found that the microbial community consists of a major bacterial group of Acinetobacter (30%), Comamonas (11%), Aeromonadaceae (10%), Pseudomonas (10%), Flavobacterium (8%), Porphyromonadaceae (6%), and Enterobacteriaceae (4%). The richest phylum includes Proteobacteria (78.61%), followed by Bacteroidetes (14.48%) and Firmicutes (3.08%). The decolorization process optimization was effectively done by using response surface methodology (RSM) and artificial neural network (ANN). The experimental variables of dye concentration, yeast extract, and pH show a significant effect on DB71 dye decolorization percentage. Over a comparative scale, the ANN model has higher prediction and accuracy in the fitness compared to the RSM model proven by approximated R 2 and AAD values. The results acquired signify an efficient decolorization of DB71 dye by a mixed bacterial culture.