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Product Excellence through Experimental Design
... It also expresses a good enough quadratic fits to navigate the design space. Joglekar and May (1987) suggested that R 2 should be at least 0.80 for a good fit of a model. The R 2 value (0.92) obtained from this study was higher than 0.80, indicating that the regression models explained the process well. ...
Acetobacter xylinum strains are known as efficient producers of cellulose. A. xylinum is an obligate aerobic bacterium that has an oxygen-based metabolism. The dissolved oxygen (DO) concentration in a rotary discs reactor (RDR) is one of the most important factors that need to be observed during the cellulose synthesis by these bacteria. In this study, the effects of different discs rotation speed (5, 7, 9 and 12 rpm) and fermentation period (3, 4, 5 and 6 days) on the DO concentration and production of bacterial cellulose in a 10-L RDR were examined. The highest yield was obtained at 7 rpm with a total dried weight of 28.3 g for 4 days fermentation. The results showed that the DO concentration in the 10-L RDR increased in the range of 13 to 17% with increasing of discs rotation speed from 7 to 12 rpm. However, fermentation with high discs rotation speed at 12 rpm reduced the bacterial cellulose production. Analysis of data using Statistica 8.0 showed a high coefficient of determination value (R2 = 0.92). In conclusion, discs rotation speed gave more significant effect on the DO concentration and production of bacterial cellulose in 10-L RDR compared to fermentation period. This was further combined with synergistic effect from sufficient consumption of oxygen for the enhanced production of bacterial cellulose and providing the controlled environment for encouraging bacterial growth throughout the fermentation process.
... The goodness of fit was checked by the coefficient of determination (R 2 ) [24] . There is no specific rule relating to the minimum value accepted for this coefficient, but 80 % is a commonly accepted limit [25]. Lower values can be tolerated, providing that the quality of the model has been proved [26]. ...
A performant method for the simultaneous quantification of daidzein, genistein, formononetin, and biochanin A in forages using an UPLC®-MS/MS was developed and fully validated. The ultrasound-assisted extraction and enzymatic hydrolysis used in the sample preparation step were optimized using the Box–Behnken experimental design. The optimal extraction conditions used for a representative mix of forage plants were 80 °C, 10 min, and 55 % methanol, and for hydrolysis, they were 20 °C, 18 h, and pH = 6. The chromatographic separation was achieved using an Acquity UPLC® HSS T3 column, with a water/methanol linear gradient containing 0.01 % of formic acid at a 0.55 mL min−1 flow rate. The four isoflavones were detected by ESI mass spectrometry in positive ion MRM mode. The method allows high throughput analyses of samples and showed an adequate linear regression model for all isoflavones over a range from 5 to 125 ng mL−1. There were good intra- and inter-day precisions (≤8.2 and ≤7.6 %) and accuracy (≤11.4 and ≤7.1 %). The recovery rates were in an acceptable range of 70–120 %, except for biochanin A, where the rate was about 50 %. Good method repeatability was also observed, and there was no matrix effect or carryover problem. The sample extracts were stable for at least 6 days of storage at -21 and 6 °C. The method proved to be sensitive, precise, and accurate for discriminating a wide variety of forages likely to be grazed by ruminants according to their isoflavone contents and to observe the impact of storage process on isoflavone content in forages.
... It has been recommended that for a good model fit, R 2 should be !80% [45]. The results of the significance test and ANOVA of the regression equation model are presented in Table 5. Beside the linear term of reaction time (X 3 ) and its quadratic form (X 3 2 ), the p-values of all the model terms were significant at 95% confidence level (p < 0.05). ...
... El tiempo de licuefacción en el sorgo en comparación con las otras dos harinas es mayor, seguido del maíz y la yuca; esto se atribuyó a su mayor contenido de amilopectina, ya que afecta de manera directa el tiempo de hidrólisis y el porcentaje de conversión, porque la alfa amilasa no actúa sobre los enlaces alfa 1-6 de las Según el coeficiente de determinación ajustado (Tabla 3), la enzima y el sustrato explican un 80%, 95%, y 85% del porcentaje de conversión para la yuca, el sorgo y el maíz. Estos valores son aceptables según Joglekar et al., 36 que consideran bueno un R 2 de al menos 0,8, mientras que Henika RG (1982) 37 considera bueno, mínimo un valor de 0,85; teniendo en cuenta los valores del coeficiente de determinación ajustado, los modelos son adecuados para predecir la respuesta. ...
RESUMEN
Existen diversos productos agrícolas con altos contenidos de almidón, como yuca, sorgo y maíz, que pueden ser destinados para la producción de jarabes glucosados. Objetivo: Determinar la producción de jarabes glucosados empleando un complejo enzimático en la hidrólisis de almidón contenido en harinas de yuca, sorgo y maíz.
Materiales y métodos: Las harinas fueron caracterizadas fisicoquímicamente determinándose el peso seco, humedad, fibra, ceniza, proteína, densidad aparente, almidón, temperatura de gelatinización y pH. La hidrólisis se realizó en dos etapas; en la etapa inicial (licuefacción) se empleó la enzima Termamyl® 120 L (pH 5,4, 80°C, 8 µL enzima/g almidón), para la segunda etapa (sacarificación) se empleó la enzima G-zyme® 480 (pH 4,3, 60°C, con dos niveles de concentración 1,5 a 5 µL/g y con el software estadístico Design Expert 7,0 se determinaron los tratamientos para encontrar la mejor relación enzima-sustrato que optimizará el porcentaje de conversión, mediante la metodología de superficie de respuesta (RSM). Resultados: Los tiempos de licuado y sacarificado para yuca y maíz fueron de 30 y 60 min, y para sorgo de 40 y 80 min. Los porcentajes de conversión obtenidos experimentalmente a partir de los modelos (RSM) fueron de 98,40%, 96,52% y 91,04% con una productividad (g azúcares reductores/L.min) de 2,70, 1,69 y 1,04 para yuca, sorgo y maíz,
respectivamente. Conclusión: El tiempo de hidrólisis total en las tres harinas fue igual o inferior a 2 h, se obtuvieron porcentajes de conversión para yuca, sorgo y maíz del 98,4%, 96,52% y 91,04% respectivamente, se demuestra la efectividad de las enzimas empleadas y mediante el modelo RMS se obtiene la optimización del porcentaje de conversión.
... coefficient variation (R 2 ) value (0.5552). An R 2 value greater than 0.80 is desirable in order to obtain a good fit model (Joglekar and May, 1987). The low value of the R 2 may due to the fluctuation of the required pH occurred as NaOH was added for adjustment during the hydrolysis process. ...
The present study aims to optimize the enzymatic hydrolysis condition and determine the functional properties of eel (Monopterus albus) protein hydrolysate (EPH) at different hydrolysate concentrations (0.1%, 0.5%, 1.0%). The enzymatic hydrolysis (using alcalase) condition; namely, temperature (°C), enzyme to substrate concentration (%) and pH on both the yield and degree of hydrolysis (DH), as responses, was optimized using the response surface methodology (RSM) by employing three factors, 3-level, Central Composite Design (CCD). The optimum hydrolysis condition suggested was a temperature of 55.76 °C, enzyme concentration of 1.80% and pH of 9. The experimental result for yield (9.45%) was higher while the experimental result for DH (15.01%) was lower than the predicted values of the responses using the quadratic model, which were 5.67% and 16.73%, respectively. The findings for the functional properties showed that the Nitrogen Solubility Index (NSI) of EPH was 85%. The emulsion stability index (ESI) of EPH was shown to decrease with the increase hydrolysate concentration (0.1%, 0.5%, 1.0%) while the foam expansion of EPH showed an increase with the increase in concentration. High solubility and the ability of EPH to emulsify and form foam show its potential for use as a natural binding and emulsifying agent.
... The coefficient of determination (R 2 ) is a measure of degree of fit [23]. For a good fit of a model, R 2 should be at least 0.80 [24]. In this study, the R 2 values of the second-order polynomial models for TPC, FRAP, and TEAC were 0.9524, 0.9743, and 0.9610, respectively, which implied that 95.24%, 97.43%, and 96.10% of the variations could be explained by the fitted quadratic models, respectively. ...
Sugar apple (Annona squamosa L.) is a popular tropical fruit and its peel is a municipal waste. An ultrasound-assisted extraction method was developed for the recovery of natural antioxidants from sugar apple peel. Central composite design was used to optimize solvent concentration (13.2%-46.8%), ultrasonic time (33.2-66.8 min), and temperature (43.2-76.8 C) for the recovery of natural antioxidants from sugar apple peel. The second-order polynomial models demonstrated a good fit of the quadratic models with the experimental results in respect to total phenolic content (TPC, R2 = 0.9524, p > 0.0001), FRAP (R2 = 0.9743, p < 0.0001), and TEAC (R2 = 0.9610, p < 0.0001) values. The optimal extraction conditions were 20:1 (mL/g) of solvent-to-solid ratio, 32.68% acetone, and 67.23 °C for 42.54 min under ultrasonic irradiation. Under these conditions, the maximal yield of total phenolic content was 26.81 (mg GA/g FW). The experimental results obtained under optimal conditions agreed well with the predicted results. The application of ultrasound markedly decreased extraction time and improved the extraction efficiency, compared with the conventional methods.
... 4.1.1. Coefficient of regression (R 2 ), adjusted R 2 , predicted R 2 , adequacy of precision Coefficient of regression (R 2 ) is an important parameter to check the adequacy of a model.Table 5) should be at least 0.80 for good fitting of a model [48]. In present study, values of R 2 for removal of TPA: 0.96 (A), 0.95 (Fe); COD: 0.96 (Al), 0.98 (Fe) and energy consumption: 0.93 (Al), 0.90 (Fe) show that all values are under satisfactory level which shows good adequacy of the model. ...
... The correlation coefficient (R 2 ) shows how the model accounts for the response. A value of about 0.80 is desired for good fit of model (Joglekar and May, 1987 ). In this study, the correlation coefficient (R 2 ) value of 0.924 is in reasonable agreement with the model. ...
The adsorption capacity of a neglected adsorbent; Ageratum conyzoides leaf powder (ACLP), was investigated in this study for effluent dye removal. The adsorbent was characterized using FESEM, FTIR, BET, XRF, XRD and EDX. The combined effects of three independent variables (pH, dye concentration and adsorbent concentration) were evaluated in a batch study through Box Behnken model of the Response Surface Methodology (RSM) for experimental design, analysis and process optimization. Dye removal efficiency was monitored at a predetermined contact time of 20 minutes. Adsorption kinetics were examined by first and second order rate models, Elovich and Intraparticle diffusion models, while equilibrium study were examined by Langmuir and Freundlich isotherm models. At optimum conditions of pH 4 and adsorbent concentration of 0.06 g, dye removal efficiency exceeded 90% and was successfully optimized by RSM. Adsorption kinetics were described by pseudo second order kinetic model while equilibrium study was represented by Langmuir isotherm with maximum adsorption capacity of 192.4 mg/g. Preconcentration of MB onto ACLP was investigated and a factor of 108.3 was obtained. ACLP was regenerated and could be reused for a minimum of 20 cycles. Thermodynamic studies show that adsorption was spontaneous and exothermic. The results illustrate that Ageratum conyzoides leaf powder could be effectively utilized for effluent dye removal.
... The p values of all regression models were less than 0.0310 indicating the significance of all the models. The R 2 values of the responses to protein, soluble fibre, insoluble fibre, dough hardness, biscuit breaking strength and OAA were found to be 0.9847, 0.9796, 0.9976, 0.9694, 0.9837 and 0.9635 respectively, which is higher than 80% indicating the fitness of polynomial models used for describing the effect of variables on the responses [35] . Ear- lier [14] reported, in optimization of baking parameters of chapathi with respect to vitamin B1 and B2 retention and quality, the polynomial models were fitted as the R 2 value for the responses like hardness, cohesiveness, chewiness, vitamin B1 and B2 were above 80%. ...
2015) Optimization of Multigrain Premix for High Protein and Dietary Fibre Biscuits Using Response Surface Methodology (RSM). Food and Nutrition Sciences, 6, 747-756. http://dx. Abstract In order to improve the nutritional quality of biscuits, a multigrain premix (MGP) was developed by using whole barley, sorghum, chickpea, pea and defatted soya flour, each at 20% level. The developed MGP had 26.28% protein, 10.13% insoluble dietary fiber and 7.38% soluble dietary fiber. The experiment was designed to optimise the MGP and wheat flour concentration for the development of multigrain biscuits with high protein, dietary fibre and to maximize the acceptability by the application of central composite rotatable design (CCRD) of Response Surface Methodology (RSM). The levels of incorporation of MGP and wheat flour were taken as variables whereas protein , soluble, insoluble fibers, biscuit dough hardness, breaking strength and overall acceptability (OAA) as responses. The optimum level of MGP and wheat flour obtained using numerical optimization was found to be 40 g and 60 g respectively. The biscuits prepared using these had 16.61% protein, 2.57% soluble fibre, and 6.67% insoluble fibre which is significantly (p ≤ 0.05) higher than control biscuit. Keywords Multigrain Biscuits, Breaking Strength, High Protein and Fiber, Multigrain Premix, Response Surface Methodology (RSM)
... The value of R 2 gives an indication of consistency between the experimental values and the predicted values. It has been recommended that R 2 should be at least 80% for the good fit of a model [32]. In this study, R 2 of the model obtained was 0.8986, which indicated that the sample variation of 89.86% for GA production was attributed to the independent variables selected and only 10.14% of the total variations were not explained by the model. ...
The study examined the impact and interactions of cashew apple juice (CAJ) concentration, pH, NaNO3 concentration, inoculum size and time on gluconic acid (GA) production in a central composite design
(CCD). The fermentation process and parameters involved were modeled and optimized using artificial neural network (ANN) and response surface methodology (RSM). The ANN model established the optimum levels as CAJ of 250 g/l, pH of 4.21, NaNO3 of 1.51 g/l, inoculum size of 2.87% volume and time of 24.41 h with an actual GA of 249.99 g/l. The optimum levels predicted by RSM model for the five independent variables were CAJ of 249 g/l, pH of 4.6, NaNO3 of 2.29 g/l, inoculum size of 3.95% volume, and time of 38.9 h with an actual GA of 246.34 g/l. The ANN model was superior to the RSM model in predicting GA production. The study demonstrated that CAJ could serve as the sole carbon source for GA production.
... iddle of the asphalt concrete overlay A, n ¼ fracture parameters Table 9also shows predicted service life against reflection cracking for bending fracture models. As can be seen from Fig. 8, the predicted fatigue lives as a function of the applied tensile strain hadbetter correlation (R 2 ¼ 0.926) than modified bending fracture model (R 2 ¼ 0.855).Joglekar and May (1987)suggested that R 2 for a good fitted model should be at least 0.80. Therefore, it is evident that the both predicted models developed in this study for service life of reinforced overlay on bending mode are fair match with the test results. ...
This study examines the influence of the most important parameters on delaying reflection cracking in geogrid reinforced overlay in bending mode, employing a large scale experimental set up. The objective was to investigate the effects of grid stiffness, tensile strength, coating type, amount of tack coat, overlay thickness, crack width and stiffnesses of asphalt overlay and existing asphalt concrete on reinforced asphalt overlay performance with geogrid interlayer. Results indicate that the cracked layer and overlay moduluses have strongest influence on reduction of reflective cracking. Also, two fatigue life estimation models for reflection cracking were developed, one based on initial strain (fatigue model) and the other by modifying Paris law for fracture mechanic model in mode I. It was found that the coefficient of determination of predicted fatigue lives and measured lives for the two developed models were sufficient. Therefore, both service life models can be used to estimate fatigue life of reflection cracking in bending mode (I).
... It showed that the peak for the model equation obtained is 1.56 g of catalyst and the oxidant concentration at 41 g L −1 (optimum ratio). Studies suggest that for a good fit of a model, the correlation coefficient (R 2 ) should be at least 0.80 (Joglekar and May 1987; Fua et al. 2007). The R 2 values for the response variables of design B, shown inTable 7 andFig. ...
This study proposes an improved activation for hydrogen peroxide and persulfate using Fe-modified diatomite (MD) to favorably lead the reaction to generate hydroxyl and sulfate radicals to degrade the contaminants phenanthrene and anthracene. Diatomite was modified by impregnating it with a mixture of ferrous (Fe2+) and ferric (Fe3+) ions in the form of precipitated iron oxides and hydroxides. The raw and synthesized materials were characterized by powder X-ray diffraction (XRD), X-ray fluorescence (XRF), particle size by laser diffraction, chemical microanalysis of the elements by energy-dispersive X-ray, and scanning electron microscopy (SEM). Batch experiments were performed to compare the new activator material (modified diatomite) with traditional methods of activation for these oxidants and to statistically study the optimum ratio between the amount of this material and the concentration of one oxidant to the degradation of the contaminants phenanthrene and anthracene. The characterization results showed that the materials are amorphous and that the Fe ion concentration was 4.78 and 17.65 % for the raw and modified diatomites, respectively. This result shows a significant increase in the amount of iron ions after synthesis. Comparing the traditional activation method with the modified diatomite, the results of batch experiments showed that the synthesized material presents significant catalytic activity for the oxidation of these contaminants, using sodium persulfate and hydrogen peroxide as oxidants. The analysis of the variables results showed that the concentration of the oxidant has higher significance than the amount of the catalyst.
... The regression coefficients obtained for the different responses and ANOVA results for the model responses are presented in Tables S1 and S2, respectively. For the good fit of a model, the R 2 value should be 0.80 (Joglekar & May, 1987). In the present study, R 2 values for the three responses were higher than 0.80 which implies the adequacy of the applied regression model. ...
... The p-values (p < 0.10) were used as a tool to justify the significance of each of the coefficients and to understand the interactions between the significant variables affecting the dye decolorization process [5]. Regression coefficient (R 2 ) should be at least 80% for a good fittest model [20]. The statistical significance of the variable and model was also determined by F-test for analysis of variance (ANOVA) and the variables with higher than 90% confidence level were considered as significant one. ...
Bacterial strain M1 isolated from soil contaminated with dye was found to be a potential dye decolorizer in the screening studies. The strain was identified as Lysinibacillus fusiformis by 16S rDNA sequencing method. While, the bacteria required 72 h to achieve maximum decolorization of dye in yeast extract broth, it needed 48 h of incubation for achieving 97.1% decolorization in Luria Bertani broth. Plackett–Burman design (PBD) was used to study the effect of most important variables that influence the dye decolorization process under static conditions. In PBD model, 12 experiments were made with seven process variables and the remazol golden yellow decolorization was within the range from 1.01 to 69.29%. From statistically analyzed data, lactose, yeast extract, and pH were found as most important variables that influence the dye decolorization process. These three variables and their combined effect of levels was studied by response surface methodology for an optimization of dye decolorization through central composite design and the outcome varied from 2.05 to 83.80%. The optimized level of lactose, yeast extract, and pH was found to be 0.40% (w/v), 1.30% (w/v), and 7.5, respectively, to achieve maximum dye decolorization of remazol golden yellow (89.66%) in validation of model. This study specifically explored factors influencing the dye decolorization through statistical tools and suggests their appropriate level with interactions playing a key role for an effective dye decolorization process.
... The p-values (p < 0.10) were used as a tool to justify the significance of each of the coefficients and to understand the interactions between the significant variables affecting the dye decolorization process [5]. Regression coefficient (R 2 ) should be at least 80% for a good fittest model [20]. The statistical significance of the variable and model was also determined by F-test for analysis of variance (ANOVA) and the variables with higher than 90% confidence level were considered as significant one. ...
Bacterial strain M1 isolated from soil contaminated with dye was found to be a potential
dye decolorizer in the screening studies. The strain was identified as Lysinibacillus fusiformis
by 16S rDNA sequencing method. While, the bacteria required 72 h to achieve maximum
decolorization of dye in yeast extract broth, it needed 48 h of incubation for achieving 97.1%
decolorization in Luria Bertani broth. Plackett–Burman design (PBD) was used to study the
effect of most important variables that influence the dye decolorization process under static
conditions. In PBD model, 12 experiments were made with seven process variables and the
remazol golden yellow decolorization was within the range from 1.01 to 69.29%. From statistically
analyzed data, lactose, yeast extract, and pH were found as most important variables
that influence the dye decolorization process. These three variables and their
combined effect of levels was studied by response surface methodology for an optimization
of dye decolorization through central composite design and the outcome varied from 2.05
to 83.80%. The optimized level of lactose, yeast extract, and pH was found to be 0.40%
(w/v), 1.30% (w/v), and 7.5, respectively, to achieve maximum dye decolorization of remazol
golden yellow (89.66%) in validation of model. This study specifically explored factors
influencing the dye decolorization through statistical tools and suggests their appropriate
level with interactions playing a key role for an effective dye decolorization process.
... EE significantly (p50.05) varied for 15 model liposomes depending on the preparation condition. For instance, the model liposome prepared by the same mixing time, but different shear rate did not show the same EE or vesicle size. As shown inTable 3, a high coefficient of determination (R 2 40.99) was obtained for both polynomial regression models. Joglekar & May (1987) also suggested that R 2 should be at least 0.80 for a good fitness of a model. Thus, these findings indicated the fitness of the final reduced response models for describing the variation of dependent variables. The ANOVA results showed that the second-order response surface equations were found to be significantly (p50.05) fitted for t ...
This study presents the application of the response surface methodology (design) to develop an optimal preparation condition (independent variables) namely shear rate (600–1000 rpm), mixing time (30–60 min), and sonication time (10–20 min) for polyunsaturated fatty acids (docosahexaenoic acid and eicosapentaenoic acid) nanoliposomes. Fifteen lipid mixtures were generated by the Box–Behnken design and nanoliposomes were prepared by the Mozafari (direct hydration and without using organic solvents) method. Nanoliposomes were characterized with respect to entrapment efficiency (EE) and vesicle size as Y1 and Y2 dependent variables, respectively. The results were then applied to estimate the coefficients of response surface model and to find the optimal preparation conditions with maximum EE and minimum vesicle size. The response surface analysis exhibited that the significant (p50.05) second-order polynomial regression equations were successfully fitted for all dependent variables with no significant (p40.05) lack of fit for the reduced models. The response optimization of experiments was the shear rate: 795 rpm; mixing time: 60 min; and sonication time: 10 min. The optimal nanoliposome had an average diameter of 81.4nm and EE of 100%. The experimental results of optimal nanoliposomes characterization confirmed an accurate fitness of the predicted values by reduced response surface models.
... value. According to Joglekar and May (1987), R 2 should be greater than 0.80 in order to obtain a good fit model. The ANOVA results also demonstrate that the linear model terms of (A), (C) and (D) have significant effect (p<0.05) and only (B) is not significant. ...
Fish protein hydrolysate was prepared from tilapia muscle using commercial Alcalase enzyme. Optimization of enzymatic hydrolysis process for preparing tilapia muscle protein hydrolysates (TMPH) was performed by employing central composite design (CCD) method of response surface methodology (RSM). O-phtaldialdehyde (OPA) method was employed to calculate the degree of hydrolysis (DH), which is the key parameter for monitoring the reaction of protein hydrolysis. The suggested model equation was proposed based on the effects of pH, temperature, substrate concentration and enzyme concentration on the DH. Optimum enzymatic hydrolysis conditions using Alcalase enzyme were obtained at pH7.5, temperature of 50oC, substrate concentration of 2.5% and enzyme concentration of 4.0%. Under these conditions, the highest value of the DH was achieved at 25.16% after hydrolysing at 120 min. The TMPH was further assessed for their nutritional value with respect to chemical and amino acid compositions. Molecular weight distributions of TMPH were characterized by SDS-PAGE. TMPH contains moderate amount of protein (28.14%) and good nutritive value with respect to the higher total amino acid composition (267.57 mg/g). Glutamic acid, aspartic acid and lysine were the most abundant amino acids present in TMPH with values 42.68, 29.16 and 26.21 mg/g, respectively. Protein hydrolysates from tilapia muscle containing a desirable peptide with low molecular weight which may potentially to be used as functional food products.
... The p-values (p < 0.10) were used as a tool to justify the significance of each of the coefficients and to understand the interactions between the significant variables affecting the dye decolorization process [5]. Regression coefficient (R 2 ) should be at least 80% for a good fittest model [20]. The statistical significance of the variable and model was also determined by F-test for analysis of variance (ANOVA) and the variables with higher than 90% confidence level were considered as significant one. ...
Bacterial strain M1 isolated from soil contaminated with dye was found to be a potential dye decolorizer in the screening studies. The strain was identified as Lysinibacillus fusiformis by 16S rDNA sequencing method. While, the bacteria required 72 h to achieve maximum decolorization of dye in yeast extract broth, it needed 48 h of incubation for achieving 97.1% decolorization in Luria Bertani broth. Plackett–Burman design (PBD) was used to study the effect of most important variables that influence the dye decolorization process under static conditions. In PBD model, 12 experiments were made with seven process variables and the remazol golden yellow decolorization was within the range from 1.01 to 69.29%. From statistically analyzed data, lactose, yeast extract, and pH were found as most important variables that influence the dye decolorization process. These three variables and their combined effect of levels was studied by response surface methodology for an optimization of dye decolorization through central composite design and the outcome varied from 2.05 to 83.80%. The optimized level of lactose, yeast extract, and pH was found to be 0.40% (w/v), 1.30% (w/v), and 7.5, respectively, to achieve maximum dye decolorization of rem-azol golden yellow (89.66%) in validation of model. This study specifically explored factors influencing the dye decolorization through statistical tools and suggests their appropriate level with interactions playing a key role for an effective dye decolorization process.
... Therefore, the ratio was set at 1: In this study, the adequacy of the obtained model was determined by ANOVA test. Joglekar and May (Joglekar & May, 1987) suggested that for a good fit of a model, R 2 should be at least 0.80. The ANOVA results confirmed a good model with R 2 and R 2 adjusted in the ranges of 0.93–0.96 ...
A reversed-phase high performance liquid chromatographic coupled to ultraviolet detection (RP-HPLC/UV) method was developed for simultaneous determination of 15 phenolic compounds and caffeine in TEAS (green tea, oolong tea, black tea and mate). Furthermore, the extraction process of total phenolic contents (TPC) from TEAS were optimized using response surface methodology (RSM) based on a central composite design (CCD) and then applied to extraction of TEAS. The best conditions obtained using the model were as follow: green tea – extraction time of 123 min, extraction temperature of 70 °C and ethanol concentration of 75%, oolong tea – extraction time of 98 min, extraction temperature of 70 °C and ethanol concentration of 69%, black tea – extraction time of 105 min, extraction temperature of 71 °C and ethanol concentration of 63%, and mate – extraction time of 103 min, extraction temperature of 71 °C and ethanol concentration of 61%. Among the extraction methods used in this study, heat-reflux extraction was found to result in the highest values of TPC. The chromatographic peaks of the 16 studied compounds were successfully identified by comparing their retention time and UV spectra with the reference standards. Method validation was performed by means of linearity, sensitivity, selectivity, accuracy and precision. The developed method was found to be simple, specific and reliable and is suited for routine analysis of phenolic compounds and caffeine in TEAS.
... Determination of coefficient (R 2 ) assisted us to check the model precision, where model R 2 was found to be 0.826 and adjusted R 2 was found to be 0.789. Joglekar and May suggested that R 2 value greater than 0.80 is recommendable (Joglekar and May 1987). Model correlation was found out with experimental values and predicted values from the optimal conditions. ...
Azo dyes comprise largest class of synthetic organics, cementing it with wide commercial applications in various processing and manufacturing industries. Metabolic breakdown products of azo dyes, generates amines, which are found to be carcinogenic and mutagenic by nature, so these components have to detoxified, before its release into water bodies. Existing physic-chemical methods are not cost-effective and eco-friendly; with each methodology have their own limitations. Methyl Red (2-(N, N-Dimethyl-4 aminophenyl) azobenzene carboxylic acid) is our choice of dye under investigation. In our study, strong oxidizing agent such as sodium hypochlorite was used in our study to investigate the decolorizability of azo dyes. Preliminary studies were carried out using five process variables such as pH, temperature (), incubation time (minutes), dye concentration (mM) and sodium hypochlorite concentration (mM), to predict the operating levels and ranges for optimization. A Box-Benkhen Design matrix with seventeen runs was used to study the interaction among three variables such as pH, temperature (°C) and incubation time (minutes). The optimal predicted experimental conditions were found to be pH 3.0, temperature of 50˚C and incubation time of 20 minutes, yielding a maximal decolourization of 87.17% which was found to be in good agreement with that of the predicted conditions (88.92%). As our study is at bench scale, further validation has to be performed U. Arulmozhi et al 198 using analytical tools, assisting us to predict the insights of interaction among the reactant and the oxidizing agent and model mechanism.
... From the equation above, Y is the response which is calculated by the model; B 0 is a constant; b i, b ii and b ij are linear, squared and interaction coefficients, respectively. R 2 with no less than 0.80 indicates a good model fit (Joglekar & May, 1987 ). Larger values of absolute t-value and smaller values of p-value indicate that the variables will be more significant (p < 0.05). ...
This study investigated the possible relationship between the enzyme extraction variables, namely amount of buffer (25–75 ml, X 1), temperature (À20, 25 °C, X 2) and mixing time (1–3 min, X 3) on total protein (Y 1), total activity (Y 2), specific activity (Y 3), storage stability (Y 4), temperature stability (Y 5) and pH stability (Y 6) of serine protease from mango peel. It was found that there was significant (p < 0.05) fit of the response surface models for all the response variables investigated. There was indication of high coefficient of determination (R 2) values (between 0.954 and 1.000) in the regression models describing variations of the response variables. It was found that there was no significant (p > 0.05) difference between the experimental and predicted values. This ensured that the response surface models used to indicate property changes of serine protease as a function of enzyme extraction conditions were sufficient.
A rapid and high-throughput method based on dispersed solid-phase microextraction coupled with GC/MS was developed for the determination of morphine, codeine, and methadone compounds from biological and aqueous samples. Bionanocomposites based on polylactic acid-polycaprolactone/graphene was prepared by melt mixing using an internal mixer with direct feeding method. In general, the weight ratio of the polylactic acid matrix phase to the polycaprolactone dispersed phase of the adsorbent was 70–30, and three weights of graphene (0.5, 1, and 2 wt% by weight of polymer) was used. The bionanocomposites were characterized by SEM, FTIR, and XRD. The XRD results showed that the graphene nanoparticles were well dispersed in the polymer matrix. The main variables with significant influence on extraction efficiency, such as graphene dosage, adsorbent dosage, extraction time, and desorption conditions, were studied by chemometric methods, including Box Behenken design and response surface methods. Under the optimum conditions, good linearity was obtained within the range of 5–2000 ng L−1 for three analytes, with correlation coefficients > 0.9996. The developed method also showed good repeatability, RSD 3–8% (n = 3), for the spiked aqueous solutions at the concentration level of 40 ng L−1.
p>The dye wastewater discharge from the textile industries mainly affects the aquatic environment. Hence, the treatment of this wastewater is essential for a pollutant-free environment. The purpose of this research is to optimize the dye removal efficiency for process influencing independent variables such as pH, electrolysis time (ET), and current density (CD) by using Box-Behnken design (BBD) optimization and Genetic Algorithm (GA) modelling. The electrocoagulation treatment technique was used to treat the synthetically prepared Reactive Black dye solution under batch mode potentiometric operations. The percentage of error for the BBD optimization was significantly greater than for the GA modelling results. The optimum factors determined by GA modelling were CD-59.11 mA/cm2, ET-24.17 minutes, and pH-8.4. At this moment, the experimental and predicted dye removal efficiencies were found to be 96.25% and 98.26%, respectively. The most and least predominant factors found by the beta coefficient were ET and pH respectively. The outcome of this research shows GA modeling is a better tool for predicting dye removal efficiencies as well as process influencing factors.</p
Centrifugal tests provide an efficacious experimental process to predict the behavior of deep excavations, and numerical models are indispensable for demonstrating the test results and analyzing the engineering demand parameters. Uncertainty in material properties can cause simulations to differ from tests; therefore, updating the model becomes inevitable. This study presents a response-surface-based model updating technique for the nonlinear three-dimensional simulation of the centrifugal testing model of strutted deep excavation in sand. An overview of the fundamentals of the response-surface model is provided, including selecting uncertain parameters as input factors, creating a design order for training the model, building a second-order polynomial surface, and updating the input factors through targeted centrifugal results. The bending strains of diaphragm wall panels at multiple points along the depth are used to form the multiobjective function. Response-surface model predictions were well-matched with actual numerical responses, with less than a 0.5% difference. Parametric analyses could be conducted utilizing this updated strutted deep excavation model.
In this work, a novel thin film based on porous polyethersulfone (PES) was designed and prepared applying polyvinyl alcohol (PVA) as a surface modifier and polyvinyl pyrrolidone (PVP) as a pore former. In this regard, after preparing the solution containing the appropriate amounts of PES, PVP, and PVA, the related membrane was prepared using phase inversion method. The characterization of the prepared porous PVA/PVP/PES membrane has been performed using attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), thermogravimetric analysis (TGA), and EDX-mapping. The PVA/PVP/PES monolithic membrane was applied for thin film microextraction (TFME) of bisphenol A (BPA) in bottled water samples followed by spectrofluorimetry determination. The effect of PVA and PVP on the porosity and hydrophilicity of the prepared membrane and also on the extraction capability of the thin film was investigated. The fractional factorial design has been employed to screen essential factors affecting the extraction and desorption steps of TFME. Afterward, the significant factors were optimized applying the Box-Behnken design. The developed method’s limit of detection (LOD) was 0.3 ng mL⁻¹ and its linear dynamic range (LDRs) was 1-1000 ng mL⁻¹. The method repeatability (RSD %) based on intra-day precision, inter-day precision and inter-thin film repeatability with six replicate experiments in each item were 5.1, 8.9 and 9.5%, respectively, using spiked distilled water (100 ng mL⁻¹). The applicability of the developed TFME-FL has been assayed by the determination of BPA in bottled mineral waters and the corresponded relative recoveries were in the range of 83.7 to 95.7 %.
High-intensity ultrasound (HIUS) is one of the physical methods to modify protein functionality. This study aims to improve the functional properties of hemp seed protein isolate (HSPI) based on the solubility and particle size using the Response Surface Methodology. The acoustic intensity of 37 W/cm² and protein concentration of 6.9% for 7.8 min were optimum process conditions that increased HSPI solubility (78%). The functional properties of ultrasound treated isolate (HSPI-HIUS) under the optimal conditions were compared with untreated HSPI. The results revealed that the emulsification, oil absorption, and foaming properties of HSPI-HIUS significantly enhanced after HIUS, whereas gelling concentration significantly decreased. Enhanced functional properties in HSPI-HIUS have been associated with structural changes based on surface hydrophobicity, particle size, and fluorescence intensity. This study indicated that HIUS can increase the functionality and prevalence of hemp seed protein isolate in food products.
Polyaniline nanofiber films were fabricated on the surface of stainless steel wire via a controllable and simple electrophoretic deposition route from nonaqueous colloidal suspension consisting of Polyaniline nanofibers. The prepared coating material was then characterized by field emission scanning electron microscopy equipped with energy dispersive spectroscopy and elemental mapping analysis. The fabricated Polyaniline film‐coated stainless steel wire was then utilized as an effective and novel sorbent phase for solid‐phase microextraction of tamoxifen for subsequent gas chromatography/flame ionization detection of this anti‐cancer drug. Parameters consisting of the temperature, extraction time, salt concentration, agitation speed, pH, temperature, and time of desorption, were studied and optimized by one at a time strategy. Under best conditions, the detection limit (S/N = 3), the limit of quantification (LOQ=10/3 LOD), linear dynamic range, repeatability, and reproducibility values of 0.51 μg L‐1, 1.7 μg L‐1, 2‐1130 μg L‐1, 5.7 and 8.6% were attained, respectively. The prepared fiber can preserve 90% of its efficacy after 20 consecutive cycles, demonstrating the suitable thermal stability and fair cyclability of the proposed SPME coating material for the determination of tamoxifen by GC‐FID. The route was effectively utilized to determine tamoxifen in urine samples, with relative recoveries ranging from 89% to 106%.
In this work, a novel Bacterial NanoCellulose (BNC) producing strain, from Kombucha tea, was isolated and characterized. Based on 16S rRNA analysis the strain was identified as Komagataeibacter rhaeticus. Under static culture, K. rhaeticus K3 produces membranes with a relaxed structure, as observed by Scanning Electron Microscopy (SEM). The addition of 2% (v/v) ethanol to the culture media enhanced by more than 3-fold of the BNC yield.
Response surface methodology (RSM) was performed with K. rhaeticus K3, using a new low cost Eucalyptus Biomass Hydrolysate (EBH). The maximum experimental BNC yield was of 5.46 g/L, obtained with the following composition: 31.4 g/L of EBH; 2.89% (v/v) of ethanol and 10.8 g/L of Yeast extract/peptone.
Texture Profile Analysis (TPA) of BNC membranes obtained using Hestrin-Schramm culture (HS) medium and optimized medium from EBH showed that membranes from EBH had higher resistance to compression, higher cohesiveness and resilience.
Pistacia lentiscus leaves are used in several applications, thanks to their polyphenolic abundance. Thiswork aimed to characterize the polyphenols and to optimize the extraction conditions to shorten the time, decrease the consumption of solvent, and to maximize the yield of different classes of phenolics, which have diverse industrial applications. The variables were optimized by applying a Box-Behnken design. Galloyl and myricetin derivatives were the most abundant compounds, and two new tetragalloyl derivatives were identified by LC-MS/MS. According to the models, the maximum yields of polyphenols (51.3 ± 1.8 mg g −1 DW) and tannins (40.2 ± 1.4 mg g −1 DW) were obtained using 0.12 L g −1 of 40% ethanol at 50 • C. The highest content of flavonoids (10.2 ± 0.8 mg g −1 DW) was obtained using 0.13 L g −1 of 50% ethanol at 50 • C, while 0.1 L g −1 of 30% ethanol at 30 • C resulted in higher amounts of myricitrin (2.6 ± 0.19 mg g −1 DW). Our optimized extraction decreased the ethanolic fraction by 25% and halved the time compared to other methods. These conditions can be applied differently to obtain P. lentiscus extracts richer in tannins or flavonoids, which might be employed for various purposes.
Bael fruit pulp was treated with pectinase enzyme for the easy extraction and high recovery of juice with nutritive properties. The response surface methodology (RSM) and artificial neural network (ANN) modeling were carried out on runs of Box-Behnken design of three variables for the optimization process and identification of the best modeling method. Pectinase concentration of 0.22 g/100 g of pulp, the temperature of 46.20°C, and time of 6.35 hours was found out to be RSM optimized value of variables whereas pectinase concentration of 0.18 g/100 g of pulp, the temperature of 46.81°C and time of 6.09 hours was obtained to be ANN-GA optimized value of variables. From the values of the coefficient of determination (R 2), root mean squared error (RMSE), and mean absolute error (MAE), ANN was found out to be better than RSM. This research would help in the commercial production of bael fruit juice on an industrial scale.
In this study, the response surface methodology (RSM) and desirability function (DF) were utilized to optimize the recycling conditions of aluminum (AA6061) chips, in the presence of particulate alumina (Al2O3), to obtain a metal matrix composite of recycled aluminum (MMC-AlR) using hot press forging processes. The effects of temperature (430–530 °C) and holding time (60–120 min) were investigated. The introduction of 2.0 wt. % of Al2O3 to the aluminum matrix was based on preliminary research and some pilot tests. This study employed the 2k factorial design of experiments that should satisfy the operating temperatures (T) of 430 °C and 530 °C with holding times (t) of 60 min and 120 min. The central composite design (CCD) was utilized for RSM with the axial and center point to evaluate the responses to the ultimate tensile strength (UTS), elongation to failure (ETF), and microhardness (MH). Based on RSM, with the desirability of 97.6%, the significant parameters T = 530 °C and t = 120 min were suggested to yield an optimized composite performance with UTS = 317.99 MPa, ETF = 20.45%, and MH = 86.656 HV. Three confirmation runs were performed based on the suggested optimum parameters, and the error revealed was less than 25%. The mathematical models suggested by RSM could adequately describe the MMC-AlR responses of the factors being investigated.
The present work evaluates and optimizes CO2 absorption in a bubble column for the Pz-H2O–CO2 system. We analyzed the impact of the different operating conditions on the hydrodynamic and mass-transfer performance. For the optimization of the process, variable conditions were used in the multivariate statistical method of response surface methodology. The central composite design is used to characterize the operating condition to fit the models by the least-squares method. The experimental data were fitted to quadratic equations using multiple regressions and analyzed using analysis of variance (ANOVA). An approved experiment was carried out to analyze the correctness of the optimization method, and a maximum CO2 removal efficiency of 97.9%, an absorption rate of 3.12 g/min, an NCO2 of 0.0164 mol/m²·s, and a CO2 loading of 0.258 mol/mol were obtained under the optimized conditions. Our results suggest that Pz concentration, solution flow rate, CO2 flow rate, and speed of stirrer were obtained to be 0.162 M, 0.502 l/h, 2.199 l/min, and 68.89 rpm, respectively, based on the optimal conditions. The p-value for all dependent variables was less than 0.05, and that points that all three models were remarkable. In addition, the experiment values acquired for the CO2 capture were found to agree satisfactorily with the model values (R² = 0.944–0.999).
High fructose syrup is a sweetener widely used as a substitute for sucrose in the food and beverage industry with its current industrial production being carried out in three sequential processes using three different enzymes that operate under different pH and temperature conditions. In this study, a single step synergistic saccharification and isomerization process has been proposed, using the commercial amyloglucosidase from Aspergillus niger immobilized by the CLEA technique (co-aggregated with magnetic nanoparticles and polyethyleneimine), and the commercial immobilized glucose isomerase (IGI) from Streptomyces murinus, Sweetzyme® IT Extra. Immobilization stabilized both enzymes, widening the operation window, thus, by applying a factorial design with a central composite rotatable design it was possible to define an optimal condition of pH and temperature of the process, as well as the best ratio between the two enzymes (pH 5.7, 50 °C and UGI/UAMG ratio of 1.56). Simultaneous saccharification and isomerization of 35% (w/v) dextrin solution produced a Dextrose Equivalent yield over 95%, with a glucose-to-fructose conversion around 48% after 30 h of reaction. In addition, both biocatalysts could be reused for six consecutive cycles, maintaining glucose-to-fructose conversions without loss of activity and with easy recovery of the biocatalysts. Furthermore, because they are of different natures (magnetic CLEA of amyloglucosidase and non-magnetic IGI pellets), if one of these biocatalysts is inactivated, they can be easily separated and reloaded individually.
In this work, recycled paper sludge (RPS), composed of non-recyclable fibres, was used as a carbon source for bacterial nanocellulose (BNC) production. The biomass was enzymatically hydrolysed with Cellic CTec 2 to produce a sugar syrup with 45.40 g/L glucose, 1.69 g/L cellobiose and 2.89 g/L xylose. This hydrolysate was used for the optimization of BNC fermentation by static culture, using Komagataeibacter xylinus ATCC 700178, through response surface methodology (RSM). After analysis and validation of the model, a maximum BNC yield (5.69 g/L, dry basis) was obtained using 1.50% m/v RPS hydrolysate, 1.0% v/v ethanol and 1.45% m/v yeast extract/peptone (YE/P). Further, the BNC obtained was used to produce composites. A mixture of an amino-PolyDiMethylSiloxane-based softener, polyethyleneglycol (PEG) 400 and acrylated epoxidized soybean oil (AESO), was incorporated into the BNC membranes through an exhaustion process. The results show that BNC composites with distinct performances can be easily designed by simply varying the polymers percentage contents. This strategy represents a simple approach towards the production of BNC and BNC-based composites.
The main goals of this research were the chemical and biological characterization of the bitter melon (Momordica charantia) isolate obtained by traditional (maceration) extraction, as well as optimization of this process using response surface methodology (RSM) and artificial neural networks (ANNs). Experiments were performed using Box–Behnken experimental design on three levels and three variables: extraction temperature (20 °C, 40 °C, and 60 °C), solvent concentration (30%, 50%, and 70%) and extraction time (30, 60, and 90 min). The measurements consisted of 15 randomized runs with 3 replicates in a central point. The antioxidant activity of obtained extracts was determined by the 1,1-diphenyl-2-picrylhydrazyl (DPPH), cupric ion reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP) assays while chemical characterization was done in terms of the total phenolic content (TPC). The methodology shows positive influence of solvent concentration on all four observed outputs, while temperature showed a negative impact. RSM showed that the optimal extraction conditions were 20 °C, 70% methanol, and an extraction time of 52.2 min. Under these conditions, the TPCs were 20.66 milligrams of gallic acid equivalents (mg GAE/g extract), DPPH 30.22 milligrams of trolox equivalents (mg TE/g extract), CUPRAC 67.78 milligrams of trolox equivalents (mg TE/g extract), and FRAP 45.48 milligrams of trolox equivalents (mg TE/g extract). The neural network coupled with genetic algorithms (ANN-GA) was also used to optimize the conditions for each of the outputs separately. It is anticipated that results reported herein will establish baseline data and also demonstrate that that the present model can be applied in the food and pharmaceutical industries.
Emulsions are metastable systems typically formed in the presence of surfactant molecules, amphiphilic polymers, or solid particles, as a mixture of two mutually immiscible liquids, one of which is dispersed as very small droplets in the other. These dispersions are unwanted occurrences in some areas, like those formed during crude oil production, but are also put into many other useful applications in the oil and gas industry, food industry, and construction industry, among others. These emulsions form when two immiscible liquids come together in the presence of an emulsifying agent and suicient agitation strong enough to disperse one of the liquids in the other. Thermodynamically, these emulsions are unstable and thus would separate into their individual phases when left alone. To be stabilized, surface-active agents (surfactants) or solids (that act in so many ways like surfactants) ought to be used. Like many commercially available products, several pharmaceutical products are usually supplied in the form of emulsions that must be stabilized before they are being administered. Pharmaceutical emulsions used for oral administration
either as medications themselves or as carriers come in form of stable emulsions. Either water-in-oil (w/o) or oil-in-water (o/w), these emulsions after formulation must be classified, majorly as stable or unstable. Only formulations that give stable emulsions are used, and the unstable ones reformulated or discarded. Classifying such emulsions using results obtained by visual observation in most cases can be very tedious and inaccurate. This necessitates the use of a more scientiic and intelligent method of classiication. The objective of this study is to employ support vector machine (SVM) as a new technique to classify synthetic emulsions. The study will assess the efects of nonionic surfactant (sodium monooleate) and Laponite clay (LC) on the stability of synthetic emulsions prepared using a response surface methodology (RSM) based on a Box-Behnken design. The stability of the emulsions was measured using batch test and TurbiScan, and the SVM was used to classify the emulsions into stable, moderately stable and unstable emulsions. The study showed that an increase in surfactant concentration in the presence of moderate to high concentrations of LC can provide a stable emulsion. Also, a clear classiication of the emulsion samples was provided by the SVM, with high accuracy and reduced misclassiications
due to human error. A higher accuracy in classiication would reduce the risk of using the wrong formulation for any pharmaceutical product.
Keywords: water-in-oil emulsions, oil-in-water emulsions, multiple emulsions, Pickering emulsions, support vector machine, response surface methodology
The cost effective dry regenerable K2CO3/Al2O3 seems to be a promising sorbent for CO2 removal from the flue gas of fossil fuel power plants. In this work, the characterization of carbonation reaction and process optimization were performed in a so-called micro fluidized bed reactor (MFBR), which has recently been applied to study gas-solid reactions. The sorbent was also characterized by BET and SEM techniques. In addition, the most important gas-solid heterogeneous models were evaluated and the kinetic parameters were determined by the model fitting approach. Based on the kinetic study results, the homogeneous model (HM) and the shrinking core model (SCM) were selected as the reaction models. Also, the effects of the independent variables including temperature, gas flow rate, and vapor pretreatment amount on the responses (adsorption capacity and reaction rate constant) were investigated by the response surface methodology (RSM) coupled with Box-Behnken-Design (BBD). Regarding to the analysis of variance (ANOVA) results, the temperature and gas flow rate are the most important factors affecting the adsorption capacity and the reaction rate constant, respectively. In addition, the semiempirical polynomials were developed to find the optimum condition corresponding to the highest adsorption capacity and reaction rate. Consequently, the optimum independent variables were 60 °C, 562 CCM and 22.2 mg H2O condition for the temperature, gas flow rate, and vapor pretreatment amount. The best response values of 65.29 mg CO2/g sorbent and 0.3402 (min-1) were predicted for the adsorption capacity and reaction rate constant at the optimum conditions which were verified experimentally. The presented results are applicable and essential for future simulation and modeling CO2 capture in the fluidized bed reactor.
The objective of this study was to develop sensory accepted low-salt cooked ham by the application of response surface methodology (RSM). A Box-Behnken experimental design was used to assess the effects of the independent factors salt replacer (Artisalt™) (0–100%), high pressure treatment (0.1–600 MPa) and a mix of organic acids (Inbac™) (0.2–0.4%) on hardness, flavour, saltiness and overall sensory acceptability (OSA) of the cooked ham. The main factor that affected all response variables was salt replacement. The optimum parameters to maximise salt reduction and produce hams with similar OSA associated with this type of products were Artisalt™ (53%), HPP (535 MPa) and Inbac™ (0.3%) and the cooked ham manufactured using the optimum parameters contained 1.4% total salt which is a 46% reduction compared to control samples which contained 2.6% total salt. Overall, a combination of salt replacer, HPP and organic acids showed great potential for the development of cooked ham with significantly reduced salt content.
Industrial relevance
Consumer studies have shown that meat consumption is being more and more influenced by health, nutritional and environmental considerations; therefore, companies are constantly searching for new and emerging technologies to reduce salt in meat products and enhance shelf life to reduce food waste. In this study we used a novel approach which showed great potential in salt reduction of ham as the quality and sensory acceptability of the ham were similar and/or better after salt was replaced by 53%. The hurdle approach used in this study is expected to improve the safety and shelf life of the low-salt optimised ham and this confirmatory study is underway.
The low cost of K2CO3/Al2O3 adsorbent is encouraging to use it for CO2 capture from the flue gas of fossil-fuel power plants. In this study, optimization of CO2 capture process using K-based adsorbent in a fixed-bed reactor has been investigated. The sorbent was also characterized by different techniques such as SEM, BET, and XRD analysis before and after the reactions. Response surface methodology (RSM) combined with Box–Behnken design (BBD) was employed to evaluate the effects of the process variables (temperature, mole ratio of H2O/CO2 and vapor pretreatment time) and their interaction on the responses (CO2 capture capacity and deactivation rate constant) to achieve the optimal conditions. In addition to the experiments, the deactivation model in the non-catalytic heterogeneous reaction system was employed to evaluate the kinetic parameters (sorption rate and deactivation rate constants) using nonlinear least square technique. According to the analysis of variance (ANOVA), the vapor pretreatment time and temperature were found to be the most important process variable, which affect CO¬¬2¬ adsorption capacity. Moreover, two quadratic semi-empirical correlations were established to calculate the optimum operating conditions of CO2 capture process. The predicted values of the correlations showed very good agreement with the experimental data. The optimum process variables obtained from the numerical optimization corresponded to 61.3 °C, 1.001 and 9 min for adsorption temperature, mole ratio of H2O/CO2 and min vapor pretreatment time, respectively. Based on the optimal condition, the highest adsorption capacity of 87.71 (mg CO2/g sorbent) in 100% CO2 removal zone (corresponding to 97.82% of theoretical adsorption capacity in the total zone) and the lowest deactivation rate constant of 0.1872 were obtained. Furthermore, additional experiments performed in the optimal conditions resulted in 86.97 adsorption capacity and deactivation rate constant of 0.1874. The results indicate that the presented models could adequately predict the responses and provide suitable information for the process scale-up.
This study describes the optimization of polyphenol extraction from mango seed kernels by using response surface methodology (RSM). In the solid-to-liquid selection, the extraction yield, total phenolic content (TPC), antioxidant activity, and tyrosinase inhibitory activity are all significantly increased with a decrease in the solid-to-liquid ratio (P < 0.05). Between the Nam-Dok-Mai kernel (NDK) and the Tong-Dam kernel (TDK), the TDK was chosen for RSM with a fixed ratio of 1:30 solid-to-liquid. The variables in the independent processing were the concentrations of ethanol, the temperature, and the time applied to RSM. Ethanol concentration, temperature, and duration had significant individual and interactive effects on phenolic yield and antioxidant activities (P < 0.05). The optimized condition that maximized the extraction yields, TPC, and antioxidant activities from TDK was an ethanol concentration of 62 %, a temperature of 63 °C, and a duration of 150 min. The obtained and validated optimized model could be used to describe the effect of these variables on the extraction of phenolic compounds from mango seed kernels.
The effect of pulse protein, egg yolk and oil contents on the physical properties (i.e., static and dynamic rheological behavior, texture) of lentil‐, pea‐ and chickpea‐supplemented salad dressings was studied using a three‐factor central composite design (CCD). Multiple regression equations were developed to describe the effects of the independent variables on several response variables. In general, an increase in oil and emulsifier (pulse protein or egg yolk) contents modified the rheological and textural properties and led to either a linear or a nonlinear increase in several parameters, including , m , η ap , σ 0 , Q (t) % and firmness. Response surface methodology was used to optimize the salad dressing formulations based on selected response variables, which were either maximized or minimized, or targeted using average values of parameters for several commercial salad dressings. The validation test confirmed the overall adequacy of the response surface models in predicting specific properties of the set formulations.
Practical Applications
The use of egg yolk as an emulsifier in the formulation of salad dressings may be a concern for those with high cholesterol. Proteins prepared from pulses may be promising value‐added replacements for such reduced egg‐yolk emulsion‐type food products. We have demonstrated the feasibility of making pulse protein‐supplemented salad dressings with physical properties similar to those of commercial dressings by varying levels of pulse protein, egg yolk and oil in salad dressing emulsion systems.
Results of the interaction of process variables and the consequential mixture of phenolic compounds adsorption study are expected to shed brighter light on the wastewater treatment applications. Accordingly, the aims of this research are to model and optimize the process variables which impinged on the simultaneous adsorption of phenol and 4-chlorophenol (4-CP) in the binary solution by spherical activated carbon (SAC). Batch assessments were designed using response surface methodology software. The process variables, namely SAC dosage and pH were varied over the 1.50–3.50 g/L and 4.00–9.00 g/L ranges, respectively, were experimented. The analysis of variance results showed the significant models could precisely predict the percentage removals of phenol and 4-CP, indicating models reliability. The interaction of process variables was inconspicuous for the case of phenol adsorption. However, increasing the pH would deteriorate the 4-CP adsorption which was partially offset by raising the SAC dosage. Considering the environmental benefits, optimization taken place at the SAC dosage and pH of 3.50 g/L and 7.60 g/L, respectively, was selected. By employing the optimized conditions of SAC dosage of 3.50 g/L at pH 7.60 for the adsorption process, the predicted phenol and 4-CP removal percentages were found to be 85.4 % (73.1 mg/g) and 96.2 % (82.6 mg/g), respectively, which were in agreement with the experimental runs.
The extraction of biologically active compounds from eggplant pulp by modified supercritical CO2 extraction was investigated. Response surface methodology was used to optimize the extraction of phenolic compounds and antioxidant capacity by assessing the pressure, temperature, and cosolvent percentage. The results demonstrated that the maximum phenolic content (3,530.79 mg CAE/100 g extract) and antioxidant capacity (4,593.22 μmol TE/g extract) were observed at 56.8°C, 280 bar, and 1.22% of ethanol and were higher than those obtained by conventional solvent extraction. Four phenolic acids were identified in the supercritical extracts and not in the conventional extracts using HPLC-DAD analysis, suggesting that modified supercritical CO2 extraction is more efficient and selective.
Zearalenone (ZEA) adsorption by a mixture of organic (yeast cell wall) and inorganic (activated charcoal) adsorbents was evaluated by an incomplete Box Behnken (33) statistical design with a quintuplicate at the central point. The variables analysed were different ratios of adsorbents (yeast cell wall and activated charcoal) at 100:0, 87.5:12.5 and 75:25, pH (3.0, 4.5 and 6.0) and ZEA concentrations (300, 750 and 1,200 ng/ml). The adsorbent mixture at 75:25 showed higher efficiency for ZEA adsorption (>96.1%) than the 87.5:12.5 ratio (81.3 to 93.7%) and with the pure yeast cell wall (78.1 to 55.7%). The significant variables were the ratio of adsorbent mixture and ZEA concentration. The effect of pH was not significant (P=0.05), indicating that the binding between ZEA and the adsorbent would be stable at different pH (3.0, 4.5 and 6.0). The quadratic model obtained by the Box Behnken (33) design can be used for predictive purposes, because it showed a non-significant deviation (P=49.54%) and a good correlation coefficient (R2=0.98), suggesting that the ZEA adsorption would be maximum (100%) when the adsorbent mixture is set at 75:25 and the ZEA concentration at 300 ng/ml. Although the predictive model showed that an increase in adsorption efficiency could occur in a smaller ZEA concentration (300 ng/ml), the mixture at the 75:25 ratio presented high efficiency (>98%) in adsorption when high ZEA concentrations were used (1,200 ng/ml), indicating that these mixtures would be able to adsorb a wide range of ZEA concentrations. Therefore, this mixture of yeast cell wall and activated charcoal adsorbents at 75:25 might be a candidate for further in vivo testing.
The degradation of chlortetracycline hydrochloride in aqueous medium (initial concentration of 10 mg/L) has been studied by electrooxidation process using Ti/PbO2 and Ti/IrO2 anode electrodes. The performance of the electrolytic cell resulted from its capability of reacting on pollutants by using both effects of electrolysis. Indeed, the organic pollutants can be destroyed at the electrode surface where hydroxyl radicals are generated (direct effect), and they can be simultaneously oxidized in solution by means of active chlorine (indirect effect). Different operating parameters, such as current density, reaction time, and temperature, were investigated. The optimal experimental parameters for chlortetracycline degradation have been investigated by using a central composite design (CCD) methodology. It has been demonstrated that under the optimal conditions determined by this method, electrooxidation can economically be applied to oxidize chlortetracycline (96% of degradation for a total cost of US$3.23 per gram of chlortetracycline removed).
In a past few decades the variety of hemp Cannabis sativa L. was unfairly neglected because of the similarity with the kind of hemp that is illegal and is used as a narcotic. The objective of this study was to evaluate the oil extraction process from Cannabis sativa seeds by cold pressing followed by extraction with supercritical CO2. In pressing experiments, the response surface methodology was conducted in order to study the effects of temperature, frequency and nozzle size on oil recovery and quality parameters. The optimal condition to obtain the highest oil recovery and the best oil quality within the experimental range of the variables studied was at temperature of 60 °C, frequency of 20 Hz and using nozzle of ID 6 mm. The residual oil in the press cake was totally extracted by supercritical CO2 in newly designed and built supercritical fluid extraction system. The oregano essential oil was the most effective in protecting the oil from oxidative deterioration.
This study assessed the effects and interactions of cashew apple juice (CAJ) concentration, pH, time, methanol concentration, and NaNO3 concentration on oxalic acid fermentation in a central composite design. The efficacies of artificial neural network (ANN) and response surface methodology (RSM) in modeling and optimizing the process were evaluated using correlation coefficient (R), coefficient of determination (R2), and absolute average deviation (AAD). The highest oxalic acid production observed was 120.66 g/L under optimum values of a CAJ concentration of 291 g/L, pH of 6.9, time of 10.82 days, methanol concentration of 2.91% (v/v), and NaNO3 concentration of 1.05 g/L that were numerically predicted by the developed RSM quadratic model. Using the developed ANN model coupled with rotation inherit optimization, the highest oxalic acid production observed was 286.75 g/L under the following optimum values: CAJ of 291 g/L, pH of 6.5, time of 12.64 days, methanol concentration of 3.82% (v/v), and NaNO3 concentration of 2.41 g/L. The results showed that the ANN model (R = 0.9996, R2 = 0.9999, AAD = 0.21%) was better than the RSM model (R = 0.9986, R2 = 0.9973, AAD = 1.00%) for optimizing oxalic acid fermentation. The use of the ANN model led to a 2.4-fold increase in oxalic acid yield over the RSM model.
The purpose of this paper is to present an efficient and most useful experimental design for multiple-factor experimentation. The fired absorptions of a series of whiteware compositions are expressed as a function of the composition variables and temperatures. These variables are X1= clay/ flux, X2= clay/flint, X3= nepheline syenite/ feldspar, and X4= firing temperature. This relationship represents the “best” second-order approximation to the true but unknown relationship between the absorption and the variables. The equation points out the contribution of each variable to the fired absorption as well as the effect of one variable as influenced by a second. The errors associated with each coefficient in the equation are included along with errors of predicted absorptions.
Statistics of Experimenters
- G E P Box
- W G Hunter
- J S Hunter
- GEP Box
Computer-Aided Design of Experiments and Taguchi Techniques Course. 2820 Fountain Lane North
- A M Joglekar
- AM Joglekar
CADE-Discovery and Optimization Software. Int’l Qual-Tech, Ltd., 2820 Fountain Lane North
- A M Joglekar
- A T May
- AM Joglekar
Optimization of white layer formulation by a multiple-factor experimental design
- L T Kissell
- LT Kissell
The Design of Experiments
- R A Fisher
- RA Fisher