Application of response surface methodology for the optimization of textile effluent biodecolorization and its toxicity perspectives using plant toxicity, plasmid nicking assays

Jadhav, Shraddha; Chougule, Amit; Shah, Dhawal; Pereira, Cristina Silva; Jadhav, Jyoti P.

doi:10.1007/s10098-014-0827-3

Cited by 34 publications

(13 citation statements)

References 36 publications

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“…A normal probability plot of the residuals (shown in Figure a) is constructed and analyzed to ensure the normality assumption. Furthermore, the internally studentized residuals values of all experimental trails are obtained within the value of 2, which signifies that a transformation of the response could make a better analysis of the model . The graph of actual experimental values versus model predicted values signify a good fit, represented in Figure b.…”

Section: Resultsmentioning

confidence: 82%

“…It is worth noting that the elliptical shape of contour plot signifies the significant interactions between the corresponding variables, while negligible interaction occurs if it is circular in shape. The response surfaces and contour plots are derived from the predicted regression model by keeping one factor constant at its zero level while varying the other two factors within experimental range to investigate their interactive effect on dye decolourization . Figure a represents the significant interactive effect of temperature and pH on decolourization percentage.…”

Section: Resultsmentioning

confidence: 99%

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Process optimization for effective bio‐decolourization of methyl orange by Pseudomonas aeruginosa 23N1 using chemometric methodology

Mishra

Maiti

2019

Can J Chem Eng

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Development of low-cost and efficient treatment processes to remove dyes from dye-laden industrial wastewaters is currently an important topic of research. This study aims to investigate the bio-decolouration of methyl orange (MO) dye by Pseudomonas aeruginosa 23N1 and to optimize the process parameters for efficient removal of MO. The regular two-level factorial analysis technique is used to screen out the operational factors and to select their upper and lower limits for further optimization using central composite design (CCD). The result revealed that the peptone, yeast extract, and salt are the vital nutrients required by the bacteria to achieve high dye decolourization. Analysis of variance (ANOVA) in CCD indicates (correlation coefficient (R 2 ) as 0.999 with predicted R pre 2 ¼ 0.996 and adjusted R adj 2 ¼ 0.998) a strong correlation between the predicted response and the experimental response under identical experimental conditions. ANOVA in CCD exhibits high positive coefficients of estimate, 21.86 and 17.75, for dye and yeast extract concentration, respectively, suggests their major influences on decolourization performance. Higher decolourization is achieved at higher initial dye concentration due to the utilization of dye molecules as a preferable food supplement for bacteria. Model validation analyses show 98.23 AE0.4 %, and 98.60 AE0.5 % decolourization for initial 50 and 150 mg/L dye solution, respectively, which are in agreement with the model predicted dye decolourization percentages of 98.44 and 98.34 %, respectively. The disappearance of the maximum absorption peak of the MO dye in the UV-visible spectra indicates that decolourization of dye is either through the bioaccumulation or biodegradation mechanism.

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Section: Resultsmentioning

confidence: 82%

Section: Resultsmentioning

confidence: 99%

Process optimization for effective bio‐decolourization of methyl orange by Pseudomonas aeruginosa 23N1 using chemometric methodology

Mishra

Maiti

2019

Can J Chem Eng

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“…Statistical significance of the model equation and model terms was evaluated by F-test and ANOVA [33]. Sum of squares (SS), DOF (degree of freedom), mean of square (MS), and associated F-test of importance (F) can be calculated as follows:…”

Section: Anova Testmentioning

confidence: 99%

Optimization of Electrocoagulation Process for the Removal of Binary Dye Mixtures Using Response Surface Methodology and Estimation of Operating Cost

Shah¹,

Tahir²,

Ullah³

et al. 2017

OJAppS

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The study was useful for the treatment of Reactive red 223 (R223) and Coomassie brilliant blue R250 (CBBR250) binary dye system by electrocoagulation process (EC). Moreover, the Al and Fe electrode were used as an anode and cathode, respectively. The response surface methodology (RSM) was adopted by utilizing central composite design to plan the experimental runs. The EC process was preceded under the effect of operating parameters including pH, NaCl, voltage and electrolysis time. The % color and COD removals were examined as response variables. The removal efficiency of RR223 and CBBR250 dye at optimum values was 89% and 94% and COD removal was 100%. The kinetic study was performed to determine the rate and rate constant. First and second order kinetic models were studied to figure out the exact mechanism of the dye removal using EC process. The estimated cost of the experimental design about 4.486 US$/dm 3 was also determined. This study showed that EC process is an economical way for the treatment of waste water.

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“…The optimal values were obtained by solving the regression equation and contour plots were used for analyzing the interactive effect of each variable (Jadhav et al 2013(Jadhav et al , 2014.…”

Section: Experimental Design and Data Analysismentioning

confidence: 99%

Coagulation of landfill leachate by FeCl3: process optimization using Box–Behnken design (RSM)

Kumar

Bishnoi

2015

Appl Water Sci

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FeCl 3 coagulation was used to achieve maximum reduction of COD, phosphate, sulfate and color and process optimization (FeCl 3 dosage, pH, reaction time) was done by BBD-RSM. Responses were recorded in terms of EC, COD, phosphate, color and sulfate removal. Variables A (pH) and B (reaction time) were negatively related to removal of COD and phosphate, whereas, C (FeCl 3 dosage) was positive in case of COD removal and negative for phosphate removal. pH and coagulant dosage had negative relationship with color removal; however, reaction time showed positive relationship. In case of percent sulfate removal, variable A (pH) demonstrated negative relationship whereas B (reaction time) and C (FeCl 3 dosage) were found to be positively related. Numerical optimization of the model revealed a maximum reduction of 71, 93, 86 and 99.6 % COD, phosphate, color and sulfate at optimal FeCl 3 dosage = 3 g/l, pH 8, and reaction time = 95 min.

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Application of response surface methodology for the optimization of textile effluent biodecolorization and its toxicity perspectives using plant toxicity, plasmid nicking assays

Cited by 34 publications

References 36 publications

Process optimization for effective bio‐decolourization of methyl orange by Pseudomonas aeruginosa 23N1 using chemometric methodology

Process optimization for effective bio‐decolourization of methyl orange by Pseudomonas aeruginosa 23N1 using chemometric methodology

Optimization of Electrocoagulation Process for the Removal of Binary Dye Mixtures Using Response Surface Methodology and Estimation of Operating Cost

Coagulation of landfill leachate by FeCl3: process optimization using Box–Behnken design (RSM)

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