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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| Format: | Article |
| Language: | English |
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Semarak Ilmu Publishing
2025
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| 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 |
| _version_ | 1848827200467369984 |
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| author | Jalani, Joyce Cynthia Zatul Iffah, Mohd Arshad Shalyda, Md Shaarani Rohaida, Che Man Yamani, Laura Navika |
| author_facet | Jalani, Joyce Cynthia Zatul Iffah, Mohd Arshad Shalyda, Md Shaarani Rohaida, Che Man Yamani, Laura Navika |
| author_sort | Jalani, Joyce Cynthia |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T03:56:56Z |
| format | Article |
| id | ump-44855 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:56:56Z |
| publishDate | 2025 |
| publisher | Semarak Ilmu Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-448552025-06-18T03:23:13Z http://umpir.ump.edu.my/id/eprint/44855/ Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) Jalani, Joyce Cynthia Zatul Iffah, Mohd Arshad Shalyda, Md Shaarani Rohaida, Che Man Yamani, Laura Navika QA75 Electronic computers. Computer science TD Environmental technology. Sanitary engineering TP Chemical technology 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. Semarak Ilmu Publishing 2025 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/44855/1/Optimization%20of%20victoria%20blue%20r%20dye%20decolorization%20using%20two-level.pdf Jalani, Joyce Cynthia and Zatul Iffah, Mohd Arshad and Shalyda, Md Shaarani and Rohaida, Che Man and Yamani, Laura Navika (2025) Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs). Journal of Advanced Research in Micro and Nano Engineering, 32 (1). pp. 23-33. ISSN 2756-8210. (Published) https://doi.org/10.37934/armne.32.1.2333 https://doi.org/10.37934/armne.32.1.2333 |
| spellingShingle | QA75 Electronic computers. Computer science TD Environmental technology. Sanitary engineering TP Chemical technology Jalani, Joyce Cynthia Zatul Iffah, Mohd Arshad Shalyda, Md Shaarani Rohaida, Che Man Yamani, Laura Navika Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) |
| title | Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) |
| title_full | Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) |
| title_fullStr | Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) |
| title_full_unstemmed | Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) |
| title_short | Optimization of Victoria Blue R dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (GPW-hNFs) |
| title_sort | optimization of victoria blue r dye decolorization using two-level factorial analysis with garbage enzyme pineapple waste hybrid nanoflowers (gpw-hnfs) |
| topic | QA75 Electronic computers. Computer science TD Environmental technology. Sanitary engineering TP Chemical technology |
| url | http://umpir.ump.edu.my/id/eprint/44855/ http://umpir.ump.edu.my/id/eprint/44855/ 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 |