Was performed based on the experimental data, and second-order polynomial models

Was performed based on the experimental data, and second-order polynomial models representing the recoveries of TPC, TFC, DPPH, and ABTS. The extract radical-scavenging capabilities as response variables are depicted in Table 2. Where possible, models were simplified by elimination of statistically insignificant terms (P.0.05). The quality of the fit of the model was expressed by the R2 correlation coefficient, and its statistical significance was confirmed with an F-test. ANOVA of response values revealed that experimental data were correlated as depicted in Table 2. Calculated models were used to explain 99.37 , 98.77 , 98.22 , and 97.29 of the results with respect to TPC, TFC, DPPH, and ABTS radical-scavenging capabilities, respectively. Generally, fitting of exploration and 35013-72-0 manufacturer optimization response surfaces may cause misleading results, unless the model exhibits a good fit [27]. Results were found to be significant (P,0.001), attesting to the goodness of fit of the models. F-values, which indicate lack of fit, were all insignificant (P.0.05), further confirming model validity. The results indicate that the models could predict recovery rates of TPC, TFC, DPPH, and ABTS radical-scavenging capabilities of C. cyrtophyllum leafs extracts quickly and efficiently when independent variables were within the ranges depicted here.Analyses of the regression coefficients and response surfacesRegression coefficients of the models for TPC, TFC, DPPH, and ABTS radical-scavenging capacities obtained by the multiple linear regressions are shown in Table 2. Variables in their coded form permitted a direct interpretability of variation in the linear, quadratic, and interaction effects of the independent variables. Three-dimensional response surface plots (Fig. 2) were constructed to predict the effects of the independent variables and their mutual interaction on the response variables. The surface plots facilitated the visualization of statistically significant factors derived from the statistical analysis. The plots were generated by plotting the response 18055761 using the z-axis against two independent variables while keeping the remaining independent variable at zero level. Regarding the SIS-3 chemical information ethanol concentration (X1), linear effects were confirmed to be statistically significant for TPC, TFC, DPPH, and ABTS radical-scavenging capacities, as indicated by the P value. A negative quadratic effect of X1 was observed with respect to the response variables, indicating that the response variables peak at a certain ethanol concentration, then started to decrease with further increases in ethanol. As shown in Fig. 2 (A, B), ethanol concentration influenced responses more significantly than temperature and time (optimal ethanol concentration ,50?0 ). This might be due to the solvent polarity which is suitable for phenol-enriched extraction. Similar results [28] have also beenreported for the extraction of phenolic antioxidants from wheat. Maximum recovery was observed at 50 and 60 EtOH. For extraction time (X2), all response variables exhibited significant, linear, negative quadratic effects. The fact that the effects of X2 were statistically significant and linear indicated that increased extraction time improved antioxidant recovery. The fact that the effects of X2 were negative and quadratic confirmed the deceleration in the extraction recoveries after equilibrium was reached. In this way, excessive time was found to be not useful for extraction of more antioxidant.Was performed based on the experimental data, and second-order polynomial models representing the recoveries of TPC, TFC, DPPH, and ABTS. The extract radical-scavenging capabilities as response variables are depicted in Table 2. Where possible, models were simplified by elimination of statistically insignificant terms (P.0.05). The quality of the fit of the model was expressed by the R2 correlation coefficient, and its statistical significance was confirmed with an F-test. ANOVA of response values revealed that experimental data were correlated as depicted in Table 2. Calculated models were used to explain 99.37 , 98.77 , 98.22 , and 97.29 of the results with respect to TPC, TFC, DPPH, and ABTS radical-scavenging capabilities, respectively. Generally, fitting of exploration and optimization response surfaces may cause misleading results, unless the model exhibits a good fit [27]. Results were found to be significant (P,0.001), attesting to the goodness of fit of the models. F-values, which indicate lack of fit, were all insignificant (P.0.05), further confirming model validity. The results indicate that the models could predict recovery rates of TPC, TFC, DPPH, and ABTS radical-scavenging capabilities of C. cyrtophyllum leafs extracts quickly and efficiently when independent variables were within the ranges depicted here.Analyses of the regression coefficients and response surfacesRegression coefficients of the models for TPC, TFC, DPPH, and ABTS radical-scavenging capacities obtained by the multiple linear regressions are shown in Table 2. Variables in their coded form permitted a direct interpretability of variation in the linear, quadratic, and interaction effects of the independent variables. Three-dimensional response surface plots (Fig. 2) were constructed to predict the effects of the independent variables and their mutual interaction on the response variables. The surface plots facilitated the visualization of statistically significant factors derived from the statistical analysis. The plots were generated by plotting the response 18055761 using the z-axis against two independent variables while keeping the remaining independent variable at zero level. Regarding the ethanol concentration (X1), linear effects were confirmed to be statistically significant for TPC, TFC, DPPH, and ABTS radical-scavenging capacities, as indicated by the P value. A negative quadratic effect of X1 was observed with respect to the response variables, indicating that the response variables peak at a certain ethanol concentration, then started to decrease with further increases in ethanol. As shown in Fig. 2 (A, B), ethanol concentration influenced responses more significantly than temperature and time (optimal ethanol concentration ,50?0 ). This might be due to the solvent polarity which is suitable for phenol-enriched extraction. Similar results [28] have also beenreported for the extraction of phenolic antioxidants from wheat. Maximum recovery was observed at 50 and 60 EtOH. For extraction time (X2), all response variables exhibited significant, linear, negative quadratic effects. The fact that the effects of X2 were statistically significant and linear indicated that increased extraction time improved antioxidant recovery. The fact that the effects of X2 were negative and quadratic confirmed the deceleration in the extraction recoveries after equilibrium was reached. In this way, excessive time was found to be not useful for extraction of more antioxidant.

Leave a Reply