2.3. Statistical Analysis and Estimation of the Adequacy of the Models
The ability of the obtained equations to describe the response’s variability was determined by analysis of variance (ANOVA), and the significance of the regression coefficients was evaluated by their corresponding
p-values, as outlined in
Table 2. The
p-values for all models were less than 0.0001, indicating that all proposed models were statistically significant. The regression coefficients
X1,
X3,
X4,
X1·X1,
X4·X4, and
X2·X3 for TPC,
X3 and
X4,
X1·X1,
X3·X3,
X4·X4, and
X1·X4 for DPPH inhibition,
X3,
X4,
X3·X3, and
X4·X4 for gallic acid concentration, and linear
X4 and quadratic
X4·X4 for catechin and quercetin concentration were significant (
p < 0.05). Since the interactive coefficients generally were not significant except
X2·X3 for TPC and
X1·X4 for DPPH inhibition, this indicates the presence of only a small interaction effect of the studied variables.
The lack-of-fit test for all models showed that there is no evidence that the model does not fit the data since
p-values are larger than 0.05 (
Table 2). Determination coefficients R
2, adjusted R
2, and predicted R
2 were calculated for each model to verify the adequacy of the models to predict experimental data (
Table 3). The values of R
2 and adjusted R
2 for all models are greater than 91% and 80%, respectively, which indicates the adequacy of the models, i.e., indicates that only a small percentage of the variation of experimental data is not explained by the respective models [
31]. The values of the predicted R
2 were higher than 93% for TPC, DPPH inhibition, and quercetin concentration, indicating a good model prediction of the responses for new observations, while predictive R
2 of 54.81% and 75.64% for gallic acid and catechin, respectively, indicates lower predictive abilities of these models.
Residual plots were constructed in order to examine the adequacy of the models (
Figure S1, Supplementary Material). Normal probability plots of residuals are used to verify the assumption that the residuals are normally distributed (
Figure S1(AI–AV)). In the case of normally distributed residuals, that plot should follow a straight line. Since non-normal patterns are observed in normal probability plots of all models, the other residual plots are constructed to test the adequacy of the models. The residuals versus fits plots indicate that the residuals of all models are randomly distributed since they fall randomly on both sides of 0. A constant variance of residuals was observed for all models (
Figure S1(BI–BV)). Moreover, on the residuals versus order plots (
Figure S1(CI–CV)), no trends or patterns were observed, indicating that the residuals are independent of one another.
2.4. Effects of Process Variables
In order to show the relationship between the responses and experimental levels of each variable and to illustrate the interactive effects of independent variables (C (Brij S20), time, pH, and SM ratio) on the response variables (TPC, DPPH radical inhibition, and concentration of gallic acid, catechin, and quercetin) three-dimensional surface plots were generated using Equations (1)–(5) (
Figure 1).
According to
Figure 1A and the ANOVA results (
Table 2), the concentration of surfactant, time, and pH had a positive linear effect on TPC (
p = 0.0106,
p = 0.0813, and
p = 0.0024, respectively), while the SM ratio had a significantly negative linear effect (
p < 0.0001). The most influential factor on TPC was the SM ratio in the linear model (percentage contribution of 88.60%). Quadratic terms of C (BrijS20) and SM ratio were statistically significant (
p = 0.0273 and
p < 0.0001, respectively), indicating curvilinear changes in TPC. The only significant interactive effect was the one between the time and pH (
p = 0.0294). Namely, TPC increased and then slightly decreased with the increase in concentration of surfactant, and the highest TPC values were obtained around the midpoint. Accordingly, in recent research, the concentration of non-ionic surfactant Tween 80 positively affected the extraction of phenolic compounds from apple pomace, while the highest TPC values were observed around the midpoint [
23]. A similar effect of concentration of non-ionic PEG 8000 on the extraction yield of polyphenols in single-factor experiments was observed. The total extraction yield of polyphenols increased when the concentration of surfactant increased from 0.05 mg/mL to 0.25 mg/mL, after which it slightly decreased. However, when the concentration of surfactant is excessive, lower extraction efficiency due to high viscosity and lower mass transfer between the matrix and solution can be expected [
32]. As shown in
Figure 1B, increasing the pH value and decreasing the SM ratio increased the DPPH radical scavenging activity of the obtained extracts. The linear and quadratic terms of pH value and SM ratio were statistically significant (
p < 0.0001) (
Table 2). The highest percentage contribution was observed for the SM ratio (77.54%). Regarding the influence of pH value, the highest DPPH inhibitory activity was observed in the midpoint at a pH of around 5 (
Figure 1B). In
Figure 1B, an increase in DPPH radical scavenging activity is observed with an increase in C (Brij S20) and time. The linear term of C (Brij S20) was negative, but the quadratic term was significantly positive (
p = 0.0714 and
p = 0.0353
, respectively). The linear and quadratic terms of time were also positive, but both were statistically insignificant (
p > 0.07).
Figure 1.
Response surface plots showing the interaction effect of process variables (C (Brij S20), time, pH, and SM ratio) on TPC (
A), DPPH inhibition (
B), gallic acid concentration (
C), catechin concentration (
D), and quercetin concentration (
E). Only the interactive effect between C (Brij S20) and SM ratio was statistically significant (
p = 0.0263) (
Table 2). A study on optimization of the extraction of phenolic compounds from grape juice and wine pomaces using ethanol and acetone showed that four factors were significant for DPPH inhibition, including temperature, time, solvent type, and pomace type [
33].
Figure 1.
Response surface plots showing the interaction effect of process variables (C (Brij S20), time, pH, and SM ratio) on TPC (
A), DPPH inhibition (
B), gallic acid concentration (
C), catechin concentration (
D), and quercetin concentration (
E). Only the interactive effect between C (Brij S20) and SM ratio was statistically significant (
p = 0.0263) (
Table 2). A study on optimization of the extraction of phenolic compounds from grape juice and wine pomaces using ethanol and acetone showed that four factors were significant for DPPH inhibition, including temperature, time, solvent type, and pomace type [
33].
Similarly to DPPH scavenging activity, the concentration of gallic acid in extracts increases with increased pH and decreased SM ratio, with these two linear terms being statistically significant (
p = 0.0186 and
p < 0.0001, respectively) (
Figure 1C,
Table 2). According to ANOVA results, the SM ratio was the most influential factor, with a percentage contribution of 54.81% (
Table 2). Quadratic terms of pH value and SM ratio were also statistically significant (
p = 0.0054 and
p = 0.0042, respectively), explaining the curved response surfaces. Interestingly, it was noticed that C (Brij S20) had negative linear and negative quadratic effects on gallic acid concentration, even though both linear and quadratic terms were statistically insignificant (
p = 0.3304 and
p = 0.9563, respectively). On the other hand, the linear effect of time was negative, while the quadratic was positive but not statistically significant (
p = 0.7152 and
p = 0.2063, respectively). Interaction terms were not significant (
Table 2).
According to ANOVA results, the efficiency of catechin extraction was most influenced by the SM ratio (percentage contribution of 75.66%), where the linear term of SM ratio and the quadratic term for SM ratio were the only statistically significant terms of the model (
p < 0.0001) (
Table 2). It was also observed that all linear terms except time, i.e., C (Brij S20), pH, and SM ratio, had negative effects on the concentration of catechin in the extracts (
Figure 1D,
Table 2).
The most influential factor in the concentration of quercetin in the extracts was the SM ratio (percentage contribution 87.10%) (
Table 2). It can be observed that the SM ratio had a negative linear effect and positive quadratic effect on quercetin concentration, while these terms were the only statistically significant terms in this model (
p < 0.0001) (
Figure 1E,
Table 2). Although statistically insignificant, linear terms such as C (Brij S20) and pH value had a negative effect on quercetin extraction, while time had a positive linear effect (
Table 2).
Therefore, a decrease in the SM ratio led to enhanced TPC, DPPH inhibition, as well as the concentration of gallic acid, catechin, and quercetin, and the term of SM was the most influential and statistically significant in all models (
Figure 1,
Table 2). The SM ratio was the most influential factor in a simple surfactant-mediated extraction of phenolics from apple pomace when an aqueous solution of Tween 80 was applied as an extraction medium (independent variables in the experimental design were concentration range—0.1–1.9%, time—40–80 min, SM ratio—40–120 mL/g, and pH—2.0–6.0). In the mentioned study, an increase in concentration, time, pH, and SM ratio led to an increase in the extraction of phenolic compounds (mg GAE/g dry weight) until reaching certain midpoints. Namely, after reaching the SM ratio of around 100 mL/g, a slight decrease in TPC was observed [
23]. In a microwave-assisted extraction of target polyphenols and furanocoumarins from fig leaves with aqueous solution of non-ionic surfactant PEG 8000 (0.25 mg/mL) as extraction medium, Box–Behnken experimental design revealed that an increase in the liquid/solid ratio from 15 mL/g led to a higher extraction yield of rutin (mg/g dry weight) until reaching the midpoint at around 20 mL/g, and then became lower [
32]. Jeganathan et al. [
34] observed that total phenolic content (mg GAE/100 g) in red grape extracts obtained by simple solid/liquid extraction with acid/ethanol solution decreases significantly with increasing solid/liquid ratio. In another study, the solid/liquid ratio caused a negative effect on the total phenolic content (g GAE/kg dry matter) of grape pomace extracts obtained by glycerol solutions in a homogenizer-assisted extraction [
35]. However, when comparing these results, the way of expressing TPC and the range of the SM ratio must be taken into account. Although its influence can vary depending on the type of extraction, the SM ratio is generally recognized as one of the most influential factors in the extraction processes in different studies. It is also suggested that an increased SM ratio does not increase the total yield due to exceeding the minimum solvent required to dissolve all polyphenols [
32]. Additionally, the negative effect of SM increase on polyphenol extraction could be a consequence of the limited amount of polyphenols present in the extraction material.
Time was generally the least influential factor (except for quercetin concentration, on which it had the second smallest impact) and positively affected all investigated responses except gallic acid concentration (
Figure 1,
Table 2). Similarly, extraction time was one of the factors with the least impact on the recovery of phenolic compounds (mg GAE/g dry grape pomace) from the pomace of Portuguese grape varieties using ethanol and acetone in the experimental design [
36]. In a simple extraction of antioxidant phenolic compounds from grape juice and wine pomaces using ethanol and acetone, longer extraction time had a positive significant effect on DPPH inhibition %, while its effect on TPC (mg GAE/g) was also positive but not significant at level 0.05 [
33]. The mass transfer of compound from matrix to solvent is related to the time. However, the mass transfer increases with time until the maximum extraction is achieved [
33,
37].
Furthermore, it is known that solution pH plays maybe even more important role in the efficient extraction of phenolic compounds. As shown in
Figure 1A–E, TPC, catechin, and quercetin concentrations decrease with an increase in pH. The percent of DPPH radical inhibition and gallic acid concentration increased with an increase in pH, but maximum responses were observed in midpoints at a pH of around 5. Therefore, it can be concluded that extracts rich in antioxidant polyphenols could be obtained in the acidic region, which is in agreement with the literature data [
20,
23,
38,
39]. Namely, simple phenolic compounds are weakly acidic, and therefore, in acidic solutions, they are predominantly present in an undissociated state. Thus, when an aqueous solution of non-ionic surfactant is used as an extraction medium, the undissociated compounds possibly form stronger interactions with the hydrophobic micellar core, resulting in efficient extraction [
20,
23]. Acidic conditions are used for the extraction of polyphenols because they are generally more stable in low pH since hydroxyl groups remain non-ionized, preserving their antioxidant properties and preventing degradation reactions [
40]. Additionally, ionizable species like polyphenols in uncharged form are more soluble due to the reduction of their intermolecular interaction [
41]. Furthermore, some phenolic compounds (like gallic, caffeic, and chlorogenic acid) are not stable at high pH, and it is shown that these transformations are not reversible [
42]. Similarly, medium pH value has an important influence on the degradation of flavonoids like quercetin. It is shown that flavonoids are prone to degradation in basic conditions and that a higher number of hydroxyl groups in a flavonoid molecule leads to their lower stability [
43].
2.5. Selection of Optimal Conditions and Model Validation
Predictive models were used for the theoretical calculation of the optimal set of extraction conditions for obtaining extract with maximal TPC (mg GAE/L), DPPH radical inhibition (%), gallic acid, catechin, and quercetin concentrations (mg/L). The optimum conditions were determined to be a surfactant concentration of 3%, extraction time of 120 min, pH value of 4.06, and SM ratio of 50 mL/g. The predicted results under the optimal conditions obtained by RSM are presented in
Table 4.
For validation of the models, triplicate experiments were performed under the optimized conditions. The mean validated values obtained for TPC, DPPH radical inhibition, gallic acid, catechin, and quercetin concentrations were 968.50 ± 37.06 GAE/L, 61.41 ± 7.13%, 5.10 ± 0.05 mg/L, 10.62 ± 0.79 mg/L, and 6.04 ± 0.10 mg/L, respectively. The experimentally obtained % of DPPH inhibition fell within the CI and PI of predicted values, while TPC value and concentrations of gallic acid, catechin, and quercetin determined in Cabernet Franc extract obtained under optimal extraction conditions were even higher than predicted. This indicates a satisfactory predictive ability of the mathematical model and the suitability for optimizing the extraction of polyphenols from grape pomace using aqueous solutions of non-ionic surfactants.
The application of water solutions of Brij S20 for the extraction of grape pomace polyphenols has several advantages. Preparation of these types of extracts does not require additional equipment or high electrical or thermal energy demands (like microwave-assisted or ultrasound extraction), making them appropriate for scaled-up production. Brij S20 is considered to be nature-friendly and biodegradable, and it is widely used in different types of pharmaceutical and cosmetic products [
44]. Therefore, polyphenol extracts obtained with Brij S20 could be directly used for the preparation of these types of products. For example, emulsions could be suitable carriers for extracts rich in polyphenols. It has been shown that polyphenol extracts from different sources can be successfully incorporated into stable emulsions [
45,
46].
Additionally, surfactant-mediated extracts could facilitate the formulation of the final product due to their increased stability. For example, a stabilization effect was observed in surfactant Tween 20-based anthocyanin extracts of grape pomace [
47]. Therefore, the “leave-in” surfactant in the obtained extract is not only a desirable ingredient of a potential final cosmetic product but also contributes to the overall stability of the extract. Non-ionic surfactants are also known to enhance polyphenol penetration in the skin and their inhibitory effects on certain enzymes involved in the process of senescence [
48]. Moreover, surfactant recovery and reuse in methods such as cloud point extraction opens the possibility of developing even more sustainable and cost-effective methods in the future [
49].