Central Composite Design Optimization of Biological Dye Removal in the Presence of Macroalgae Chara sp.

Abstract

Central Composite Design Optimization of Biological Dye Removal in the Presence of Macroalgae Chara sp.Response surface methodology (RSM) was employed to investigate the effects of different operational parameters on the biological decolorization of a dye solution containing malachite green (MG) in the presence of macroalgae Chara sp. The investigated variables were the initial pH, initial dye concentration, algae amount, and reaction time. Central composite design (CCD) was used for the optimization of biological decolorization process. Predicted values were found to be in good agreement with experimental values (R 2 ¼ 0.982 and Adj-R 2 ¼ 0.966), which indicated suitability of the employed model and the success of RSM. The results of optimization predicted by the model showed that maximum decolorization efficiency was achieved at the optimum condition of the initial pH 6.8, initial dye concentration 9.7 mg/L, algae amount 3.9 g, and reaction time 75 min. UV-VIS spectra and FT-IR analysis showed degradation of MG.

Coagulation–flocculation of marine Chlorella sp. for biodiesel production

“…The P value (probability) with 95% confidence level (P value < 0.05) was used as a tool to check the significance of each coefficient. The smaller P value is the more significant corresponding coefficient (Khataee et al, 2010;Bhornsmithikun et al, 2010). The coefficient of variance (CV) is a ratio of the standard error of estimate to the mean value of the observed response and defines reproducibility of the model.…”

Optimization of sample preparation method of total sulphur measurement in mine tailings

“…Now adding the values of regression coefficients for the intercept, linear, quadratic and interaction terms from Table 6 to Eq. 3, an empirical second-order relationship between the dependent (%S CCD ) and independent (B and C) variables can be derived (Khataee et al 2010), No. of all experiments is n = 2 All independent variables in Eq.…”

“…The F tests, F critical values (Montgomery et al 2006) and P (probability) values are presented in the same table. High values of F(F [ F cr ) and low values of P (P \ 0.05) of the regression model of %S CCD for KZK-1 indicate that all variable terms (linear, quadratic and interaction) are statistically significant and the model is adequate for prediction (Khataee et al 2010;Chang et al 2011). …”

“…Then, the optimum conditions are attained by using response surface methodology (RSM), which is predominantly of four types, three level full factorial design (FFD), Doehlert design, central composite design (CCD) and Box-Behnken design Ferreira et al 2007). The RSM provides an extra advantage of measuring the quadratic effects of factors compared to the FFD, which is limited to the linear and interaction effects (Khataee et al 2010). This quadratic effect helps to analyse the curvature of experimental data (Lima et al 2007).…”

Effects of Operational Parameters on Decolorization of C. I. Acid Red 88 by UV/H2O2 Process: Evaluation of Electrical Energy Consumption

“…The release of wastewaters containing organic dyes into the environment is undesirable, not only because of their color, but also because many dyes from wastewater and their breakdown products are toxic to life 1, 2. A number of methods including electrochemical treatment 3 and response surface methodology 4 have been employed to investigate the decolorization process.…”