Multi-response central composite design of the mineralization and removal of aniline by subcritical water oxidation method

Catalytic Oxidation of Ponceau 4R in Aqueous Solution using Iron-impregnated Al-pillared Bentonite: Optimization of the Process

The application of the Fenton-like process for the oxidation of an aqueous solution of Ponceau 4R dye, using an aluminum pillared clay impregnated with iron (Fe(wt%)/Al-PILC) as catalyst, was investigated. The Response Surface Methodology (RSM), based on a Central Composite Design (CCD) was used to evaluate and optimize the oxidation process of a Ponceau 4R solution. Three independent variables were studied in the experimental design: the amount of H2O2 expressed in multiples of times of stoichiometry dose, iron concentration incorporated by impregnation onto aluminum pillared clay (Fe(wt%)), and amount of catalyst (Fe(wt%)/Al-PILC). The response variables were decolorization and total organic carbon (TOC) removal. The significance of independent variables and their interactions were tested by means of analysis of variance (ANOVA), with a 95% confidence level. With low stoichiometric dose of H2O2 (0.96 and 1.54 times), medium amount of catalyst (374.4 and 391.3 mg) and high Fe concentration impregnated in pillared clay (9.3 and 7.7 wt%), the total decolorization and high TOC removal were achieved. Under multi-objective optimization conditions (3.0 times the stoichiometric dose of H2O2, 420 mg Fe(wt%)/Al-PILC and 5.5 wt% Fe impregnated in Al-PILC), it was possible to achieve 86.18% decolorization and 66.81% TOC removal after 5 h of reaction at 25 °C, with the additional advantage of showing an iron leaching of less than 0.10 mg/L. The established models' soundness is confirmed by a good fit between predictive models and experimental results. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0). 

Comparative profiling of lactic acid bacteria isolates in optimized and spontaneous fermentation of cowpea leaves

In as much as spontaneous fermentation of cowpea leaves enhances product diversification, the process is rather slow with poor product quality. Limited work has been undertaken to provide input toward standardization of the process and enhancing of product quality. The current study sought to evaluate the in-process fermentative bacteria profile changes due to the effect of optimization of fermentation process of cowpea leaves. Lactic acid bacteria (LAB) isolates from spontaneous and optimized fermentation were characterized using biochemical tests, whereby optimization was done using the Response Surface Methodology model of the central composite design in the Design Expert Software. The RSM models accounted for 89% and 60% variability in the response variables of pH and titratable acidity, respectively (p < .001). Increasing the sugar concentration and period of fermentation significantly (p < .05) increased the titratable acidity, while reducing the pH. The optimal fermentation parameters were established as sugar and salt concentrations of 5% and 2%, respectively, 16 days of fermentation, pH of 3.8 and titratable acidity of 1.22% with a desirability of 0.859. Of the 13 identified LAB isolates, Lactobacillus brevis and Lactococcus lactis dominated the onset stage of spontaneous fermentation whereas only Lactobacillus brevis dominated the onset stage of optimized fermentation. Additionally, the final stage with the dominant isolates of L. plantarum was longer in the spontaneous fermentation process than in the optimized process. Evidently, optimizing the fermentation process resulted in increasing dominance by heterofermenters in the production of soured cowpea leaves, with the yielded product having enhanced acidity.

Application of ultrasound-assisted and subcritical water oxidation methods in the mineralisation of Procion Crimson H-EXL using response surface methodology and artificial neural network

Eco-friendly methods, the ultrasound-assisted oxidation (UAO) and the subcritical water oxidation (SWO) methods, were applied to mineralise the widely used commercial reactive azo dye, Procion Crimson H-EXL in the presence of H₂O₂. 72.20% and 72.86% of total organic carbon removal were achieved in the UAO and SWO methods, respectively. The Box-Behnken design (BBD) was applied to design the experimental processes and optimise both methods. ANOVA and validation tests were performed to assess the employed models. F and P values were obtained as 36.72 and <0.0001 in the UAO method, respectively, and 605.97 and <0.0001 in the SWO method, respectively. The artificial neural network (ANN) was applied in both the UAO and the SWO methods. The predictive performance of the BBD and ANN models were evaluated and compared to each other over R², root mean square error and absolute average deviation values.