## 3 Results and Discussion
### Verification  
The final phase of the experiment involved verification of the model by comparing the predicted response values with the actual values obtained from the analyses. The data, along with the optimal proportion of components obtained in the model, are shown in Table 3.  
In order to obtain a high-quality product, it was determined that parameters such as efficacy, content of polyphenols, flavonoids, \(\beta\)-glucan, vitamin C, total antioxidant capacity, and sensory acceptability should present the highest possible value. Viscosity, hardness, porosity, and volume should be as close as possible to the properties of the control sample. Meanwhile, the color difference and the distances of volatile compounds should be as low as possible so that there is no difference between the final and the control product. A formulation with an optimized proportion of ingredients was developed. The optimized levels of contribution were 4.60% sour fermented beetroot juice, 6.29% \(\beta\)-glucan concentrate, and 2.77% microencapsulated polyphenols. The prognosed and actual parameters are presented in Table 3, and are comparable in most cases. The viscosity was 1689.21 Pas and was close to the expected value (1717.68). These values were much higher than the value for the control bread, indicating that the used ingredients had a strong influence on the dough's viscosity. The efficiency was also close to the expected value (76.56 vs. 79.73%). This value is in line with the typical yield of baked goods. The color difference was higher than prognosed (21.56 vs. 19.09). However, according to the guidelines, that low level of distinction means that the color difference could be noticed by consumers but not cause deteriorations in product acceptance [56]. Hardness was also similar to the expected level (4.22 vs. 4.51 N), and it would be higher relative to the control bread. This indicates the great influence of ingredients on the hardness of bread. In the case of microencapsulated polyphenols, this may be related to the used matrix material, which was soy protein isolate. Both soy protein and \(\beta\)-glucan have a high water-binding capacity, which is why they compete for water in bread with proteins, including gluten proteins. Limited access to water in gluten may cause deterioration of the gluten network, which is associated with a decrease in the volume of bread. As a consequence, this can cause an increase in bread hardness [20]. The porosity of the bread was close to expected (23.89 vs. 21.88%) and was characteristic of this type of bread. This is evidenced, in particular, by the high similarity to the porosity of the control sample, which was 21.15%. TPC (64.78 vs. 61.58 mg GA/100 g), TAC (52.12 vs. 53.69%), TFC (26.98 vs. 27.05 mg/100 g), and beta-glucan content (3.11 vs. 3.25 g/100 g) were close to prognosed values. The vitamin C content was higher than predicted (15.21 vs. 13.31 mg/100 g). The content of bioactive compounds was higher than in the control sample, which did not contain sources of these compounds. Thus, it can be concluded that the use of microencapsulated polyphenols, \(\beta\)-glucan concentrate, and sour fermented beetroot juice increased the content of  
\begin{table} \begin{tabular}{c c c} \hline \hline
**Design Factors** & \multicolumn{2}{c}{**Optimal Amount in Formulation**} \\ \hline \hline \multicolumn{1}{c}{Sour fermented beetroot juice [\%]} & 4.60 \\ \(\beta\)-glucan concentrate [\%] & 6.29 \\ \multicolumn{1}{c}{Polyphenyl microcapsules [\%]} & 2.77 \\ \hline \hline \end{tabular} 
\begin{tabular}{c c} \hline \hline \multicolumn{1}{c}{Predicted values} & \multicolumn{2}{c}{Experimental values} \\ \hline \hline \multicolumn{1}{c}{\(\mathrm{l}\)\(\mathrm{  
bioactive compounds in the product. The volume of the product was close to expected (240,989.01 vs. 241,323.29 mm\({}^{3}\)). Furthermore, it was also characteristic of this type of bread, comparable to the volume of the control sample (284,453.26 mm\({}^{3}\)).