Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs)

In Malaysia, the textile industry poses a significant environmental challenge with its dye-containing effluents, and the disposal of ash from palm oil mills exacerbates the issue. This study addresses the critical need for efficient and sustainable methodsto treat...

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Bibliographic Details
Main Authors: Jalani, Joyce Cynthia, Zatul Iffah, Mohd Arshad, Shalyda, Md Shaarani, Rohaida, Che Man, Yamani, Laura Navika
Format: Article
Language:English
Published: Semarak Ilmu Publishing 2025
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/44855/
http://umpir.ump.edu.my/id/eprint/44855/1/Optimization%20of%20victoria%20blue%20r%20dye%20decolorization%20using%20two-level.pdf
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Summary:In Malaysia, the textile industry poses a significant environmental challenge with its dye-containing effluents, and the disposal of ash from palm oil mills exacerbates the issue. This study addresses the critical need for efficient and sustainable methodsto treat dye-containing industrial wastewater, focusing on Victoria Blue R (VBR) dye decolorization. The study explores the optimization of the decolorization process using Garbage Enzyme Pineapple Waste hybrid Nanoflowers (GPW-hNFs) through a two-level factorial analysis. The GPW-hNFs, synthesized from garbage enzyme derived from pineapple waste, serve as a promising enzymatic source for dye degradation. By systematically varying factors such as nanoflower amount, initial dye concentration, pH level, sonication time, and temperature, the study identifies key parameters influencing VBR dye decolorization. Employing statistical tools such as ANOVA and predictive modelling, the study reveals the significance of nanoflower amount, initial dye concentration, and their interaction (AC) in achieving optimal decolorization. The predicted optimum condition, validated experimentally, resulted in a remarkable 61.35% dye decolorization. The high accuracy (99.96%) underscores the efficacy of the two-level factorial analysis in optimizing GPW-hNFs for VBR dye decolorization, offering a promising avenue for sustainable wastewater treatment in the textile industry.