Department of Environmental Science & Engineering, Guru Jambheshwar University of Science & Technology, Hisar (Haryana), India.
J Basic Microbiol. 2012 Jun;52(3):314-23. doi: 10.1002/jobm.201100060. Epub 2011 Jul 21.
This paper reports the application of experimental design methodology for the optimization of decolourization of azo reactive textile dye Remazol Red RR and reduction of chemical oxygen demand (COD) using fungal isolate Aspergillus foetidus. Response surface methodology (RSM), involving central composite design matrix in three most important input variables; temperature, pH and initial dye concentration was employed. A total of 20 experiments were conducted in the study towards the construction of a quadratic model. This demonstrated the benefits of approach in achieving excellent predictions, while minimizing the number of experiments required. Very high regression coefficient between the variables and the responses indicated excellent evaluation of experimental data. Under optimized conditions fungal isolate was capable to decolourize Remazol Red RR up to 86.21% and COD reduction up to 55.43% was achieved during the experimental setup. Enzymatic activity indicated excellent outcome under the optimal process conditions. The experimental values agreed with the predicted ones, indicating suitability of the model and success of RSM approach in optimizing the process.
本文报告了实验设计方法在优化真菌分离物 Aspergillus foetidus 对偶氮反应性纺织染料 Remazol Red RR 的脱色和化学需氧量（COD）还原中的应用。响应面法（RSM）采用了三个最重要的输入变量（温度、pH 和初始染料浓度）的中心组合设计矩阵。在研究中总共进行了 20 次实验，以构建二次模型。这证明了该方法在实现出色预测的同时，最小化所需实验数量的优势。变量和响应之间的高回归系数表明对实验数据进行了出色的评估。在优化条件下，真菌分离物能够将 Remazol Red RR 脱色至 86.21%，在实验设置期间实现了高达 55.43%的 COD 还原。酶活性在最佳工艺条件下表现出色。实验值与预测值吻合，表明模型的适用性以及 RSM 方法在优化工艺方面的成功。
