## 3 Results and Discussion  
### Modeling and Optimization of the Malt Mixture  
#### 3.1.1 Modeling of the Malt Mixture  
Three malt types, Pilsner malt (P), Caramel Pils malt (CP) and Caramel Munich type 2 malt (CM2), were selected for the present study on the basis of previous studies. The choice was also based on existing recipes for the production of lager beer. The malt mixture was modeled using a special cubic simplex-lattice design with two replications. The choice of an estimation method was related to the possibility of exploring a larger part of the factor space due to the small number of independent variables. The results of the options  
Figure 2: Scheme for the mashing mode optimization. (S: sample point). presented in Table 1 have been shown in Table 2. The response surfaces for the investigated indicators have been summarized in Figure 3. The mathematical models obtained have been presented in Equations (1) to (7). The data from the statistical processing of the models have been presented as Supplementary Material. All mathematical models described the experimental data with very high accuracy, with correlation coefficients ranging from 72% to 99% (see Equations (1) to (7)). The extract of the obtained word changed within relatively narrow limits, following a tendency to decrease with an increase in the CM2 malt content in the mixture. This was due to the lower enzyme activity of the special malts due to their production method [30]. The color of the word obtained increased with the increase in the content of CP and CM2 malts in the mixture. CP and CM2 have higher color intensity, which is also reflected in the color of the resultant word. The trend observed was due to the higher initial color of both malt types, with CM2 malt (with a higher color intensity) having a stronger influence. Similarly, the trends observed here can be explained by the CM2 malt production method [30]. As is known from the literature, word has significant biological potential, which is due to a number of components extracted from malt: phenolic compounds, melanoidins, reductones and others [30; 31]. In the present study, we analyzed the content of phenolic compounds, determined by the Folin-Ciocalteu method, as well as the word antioxidant potential, using four main methods: DPPH, FRAP, CUPRAC and ABTS. The data in Figure 3c show that the phenolic compound content increased linearly with the increase in the amounts of CP and CM2 malts in the blend. In most cases, malt drying at high temperatures, or malt roasting aimed at higher color intensity, leads to the release of phenolic compounds from the matrix and their easier extraction into the word. This, together with the melanoidins, which also have antioxidant potential, increases the word biological activity [30; 31]. In the present study, the data showed that the word had high antioxidant potential, which followed the analogous trend for phenolic compounds: an increase in the biological activity with the increase in the CP and CM2 amounts. In terms of biological activity, CM2 malt had stronger influence, since it was more heavily roasted and therefore contained more melanoidins, which had a direct impact on the activity. Analogous trends were found in [PERSON] et. al., 2022 [34]. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Variant**} & **Extract** & **Color** & **FC** & **DPPH** & **FRAP** & **CUPRAC** & **ABTS** \\  & \({}^{\circ}\)**P** & **EBC Units** & **mg/dm3** & & & **\(\boldsymbol{\um}\)****prod** & **TROLOX/dm3** & \\ \hline
1 & 13.070 & 247.500 & 1274.080 & 781.910 & 1313.540 & 5621.670 & 7783.310 \\
2 & 13.590 & 5.750 & 397.600 & 333.360 & 688.540 & 1682.780 & 2266.760 \\  
Figure 3: Response surface for different target functions, “,” denotes decimal point. Investigation of the Effect of the Addition of Acidulated Malt, Lactic Acid and CaCl\({}_{2}\) on the Extract Yield  
As a fully enzymatic process, mashing is affected by factors such as temperature, pH and substrate concentration.