# Effect of Deacidification Treatment on the Flavor Quality of Zaosu Pear-Kiwifruit Wine
## 3 Results and Discussion
### Optimization of MLF Parameters for Pear-Kiwifruit Wine
#### 3.1.2 Predictive Model Fitting of Deacidification Efficiency  
According to the results of single-factor tests and estimated production costs, combined with the risk of microbial spoilage, the levels of the three independent variables, initial pH (A), inoculation amount (B), and MLF temperature (C), were subjected to a Box-Behnken design, to maximize the degradation of L-malic acid as the dependent response (Y). A total of 17 experiments were performed (Table 1), and a regression model was obtained to express the relationship between the investigated variables (A, B, and C) and the response value (Y) as follows:  
\[\text{Y}=97.79-1.10\text{A}-0.36\text{B}+0.41\text{C}+0.15\text{AB}-0.31\text{ AC}-0.61\text{BC}-4.73\text{A}^{2}-3.91\text{B}^{2}-1.87\text{C}^{2}. \tag{2}\]  
The _F_-value obtained from ANOVA was 103.36, with a \(p\)-value <0.0001, and this nonsignificant lack of fit implied that the model was very closely related to MLF efficiency, and that the regression analysis was effective (Table 2). Furthermore, the coefficient of determination (\(R^{2}\)), the adjusted \(R^{2}\), and the coefficient of variation (\(CV\)) were 0.9925, 0.9829, and 0.51%, respectively, indicating that the model could accurately predict the percentage degradation of L-malic acid in pear-kiwifruit wine during MLF with _O. oeni_ GF-2. The one-order term coefficient of initial pH (A) and all quadratic term coefficients were very significantly related to deacidification efficiency (\(p<0.01\)), whereas the inoculation amount (C) and its interaction with temperature had a significant effect (\(p<0.05\)) on the  
Figure 1: Effects of malcolate fermentation parameters by _Oenococcus oeni_ strain GF-2 on total conversion of L-malic acid in pear–kiwifruit wine: (**A**) initial pH; (**B**) malcolate fermentation temperature; (**C**) amount of _O. oeni_ inoculum. Error bars indicate the SD (\(n=3\)). Values with different letters are significantly different (\(p<0.05\)) among the samples. percentage degradation of L-malic acid in wine samples (Figure 2C). The other terms were not significantly related to MLF efficiency (Figure 2A,B). The optimal combination of MLF parameters predicted by the regression equation was as follows: initial pH of 3.4, inoculation amount of 5%, and temperature of 20 \({}^{\circ}\)C; under these conditions, the degradation of L-malic acid was predicted to be 97.9%. An 8.0 L-scale MLF confirmatory test was performed in triplicate under the above conditions, achieving an average 98.3% reduction in L-malic acid content, very close to the predicted value. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Independent Variable**} & \multicolumn{1}{c}{**Response**} \\ \cline{2-5}
**Run** & **A** & **B** & **C 1 ** & **Total Conversion** \\  & **Initial pH** & **MLF** & **Inoculation** & **of L-Malic** \\  & **Temperature (1 ** & **Amount (\%, \%)** & **Acid (\%)** \\ \hline
1 & \(-1\) (3.20) & \(-1\) (18) & 0 (5) & 90.78 \\
2 & \(1\) (3.60) & \(-1\) & 0 & 88.42 \\
3 & \(-1\) & 1 (22) & 0 & 89.55 \\
4 & \(1\) & 1 & 0 & 87.81 \\
5 & \(-1\) & 0 (20) & \(-1\) (4) & 91.70 \\
6 & \(1\) & 0 & \(-1\) & 89.96 \\
7 & \(-1\) & 0 & 1 (6) & 93.03 \\
8 & \(1\) & 0 & 1 & 90.06 \\
9 & \(0\) (3.40) & \(-1\) & \(-1\) & 91.19 \\
10 & 0 & 1 & \(-1\) & 91.90 \\
11 & 0 & \(-1\) & 1 & 93.34 \\
12 & 0 & 1 & 1 & 91.60 \\
13 & 0 & 0 & 0 & 98.16 \\
14 & 0 & 0 & 0 & 96.93 \\
15 & 0 & 0 & 0 & 98.46 \\
16 & 0 & 0 & 0 & 97.85 \\
17 & 0 & 0 & 0 & 97.54 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Box–Behnken design and response values for MLF-treated pear–kiwifruit wine.