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<p>The textile dyeing industry’s wastewater is a well-known environmental threat, particularly due to the persistent nature of indigo dye. This study tackles this challenge head on by exploring a novel bacterial consortium approach for effective dye decolourization. Using Response Surface Methodology (RSM), we optimized key factors pH, temperature, inoculum size, glucose, and NH<sub>4</sub>Cl to enhance the decolourization process. A Central Composite Design (CCD) revealed a significant influence of these variables, leading to the development of a robust quadratic model that showed excellent alignment between experimental and predicted values. Our findings demonstrate that under optimal conditions (inoculum size 1.25 ± 0.5% with ~ 10<sup>8</sup> cells/mL, pH 6 ± 0.5, temperature 35 ± 2&#xa0;°C, glucose 1.5 ± 0.5%, and NH<sub>4</sub>Cl 1.8 ± 0.5%), the decolourization rate of 100&#xa0;mg/L indigo dye was significantly enhanced. This study not only underscores the power of statistical tools in optimizing bioremediation processes but also paves the way for more sustainable and cost-effective wastewater treatment strategies. Our results offer promising avenues for tackling industrial effluents laden with persistent dyes, contributing to a cleaner and more sustainable environment.</p>

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Cost-Effective Optimization of Indigo Dye Decolourization by Novel Bacterial Consortium: A Robust Approach Using RSM

  • 期刊论文

  • 发表日期：

    2025年10月4日

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  • Devika P. Vala,
  • Devayani R. Tipre,
  • Shailesh R. Dave,
  • Darshna K. Patel,
  • Shivranjani B. Gajjar

摘要

The textile dyeing industry’s wastewater is a well-known environmental threat, particularly due to the persistent nature of indigo dye. This study tackles this challenge head on by exploring a novel bacterial consortium approach for effective dye decolourization. Using Response Surface Methodology (RSM), we optimized key factors pH, temperature, inoculum size, glucose, and NH4Cl to enhance the decolourization process. A Central Composite Design (CCD) revealed a significant influence of these variables, leading to the development of a robust quadratic model that showed excellent alignment between experimental and predicted values. Our findings demonstrate that under optimal conditions (inoculum size 1.25 ± 0.5% with ~ 108 cells/mL, pH 6 ± 0.5, temperature 35 ± 2 °C, glucose 1.5 ± 0.5%, and NH4Cl 1.8 ± 0.5%), the decolourization rate of 100 mg/L indigo dye was significantly enhanced. This study not only underscores the power of statistical tools in optimizing bioremediation processes but also paves the way for more sustainable and cost-effective wastewater treatment strategies. Our results offer promising avenues for tackling industrial effluents laden with persistent dyes, contributing to a cleaner and more sustainable environment.