Sharma Praveen, Singh Lakhvinder, Dilbaghi Neeraj
Department of Environmental Science & Engineering, Guru Jambheshwar University of Science & Technology, Hisar, Haryana, India.
J Hazard Mater. 2009 May 30;164(2-3):1024-9. doi: 10.1016/j.jhazmat.2008.08.104. Epub 2008 Sep 6.
Decolorization of textile azo dye Disperse Yellow 211 (DY 211) was carried out from simulated aqueous solution by bacterial strain Bacillus subtilis. Response surface methodology (RSM), involving Box-Behnken design matrix in three most important operating variables; temperature, pH and initial dye concentration was successfully employed for the study and optimization of decolorization process. The total 17 experiments were conducted in the study towards the construction of a quadratic model. According to analysis of variance (ANOVA) results, the proposed model can be used to navigate the design space. Under optimized conditions the bacterial strain was able to decolorize DY 211 up to 80%. Model indicated that initial dye concentration of 100 mgl(-1), pH 7 and a temperature of 32.5 degrees C were found optimum for maximum % decolorization. Very high regression coefficient between the variables and the response (R(2)=0.9930) indicated excellent evaluation of experimental data by polynomial regression model. The combination of the three variables predicted through RSM was confirmed through confirmatory experiments, hence the bacterial strain holds a great potential for the treatment of colored textile effluents.
枯草芽孢杆菌菌株对模拟水溶液中的纺织偶氮染料分散黄211（DY 211）进行了脱色处理。响应面法（RSM），涉及三个最重要的操作变量（温度、pH值和初始染料浓度）的Box-Behnken设计矩阵，成功用于脱色过程的研究和优化。该研究共进行了17次实验以构建二次模型。根据方差分析（ANOVA）结果，所提出的模型可用于指导设计空间。在优化条件下，该菌株能够将DY 211脱色高达80%。模型表明，初始染料浓度为100 mgL⁻¹、pH值为7和温度为32.5℃时，脱色率最高。变量与响应之间的回归系数非常高（R² = 0.9930），表明多项式回归模型对实验数据的评估效果极佳。通过RSM预测的三个变量的组合通过验证实验得到了证实，因此该菌株在处理有色纺织废水方面具有巨大潜力。
