## 3 Results
### Response Surface Test Results
#### 3.2.1 Analysis of Variance  
The results of response surface analysis of variance are shown in Table 3. The regression analysis of the test results was performed by Design-Expert 10, a software for performing experimental design (DOE) provided by Stat-Ease Inc. (Minneapolis, MN, USA). The regression equation of grain loss rate \(Y_{1}\) and grain damage rate \(Y_{2}\) is as follows:  
\[Y_{1}=1.11+0.0738A+0.0575B+0.0263C-0.015 AB+0.0525 AC+0.04 BC+0.1858A^{2}+0.1433B^{ 2}+0.1907C^{2} \tag{16}\]  
\[Y_{2}=0.154+0.0537A+0.0587B+0.035C+0.005 AB-0.0925 AC-0.0575 BC+0.138A^{2}+0.083B^{ 2}+0.1305C^{2} \tag{17}\]  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Test**} & \multicolumn{3}{c}{**Test Factors**} & \multicolumn{3}{c}{**Test Indicators**} \\ \cline{2-6}  & \multicolumn{1}{c}{**A**} & \multicolumn{1}{c}{**B**} & \multicolumn{1}{c}{**C**} & \multicolumn{1}{c}{**Grain Loss Rate**} & \multicolumn{1}{c}{**Grain Breakage Rate**} \\  & \multicolumn{1}{c}{**A**} & \multicolumn{1}{c}{**B**} & \multicolumn{1}{c}{**C**} & \multicolumn{1}{c}{\(Y_{1}\) **(\%)**} & \multicolumn{1}{c}{\(Y_{2}\) **(\%)**} \\ \hline
5 & 1 & 1 & 0 & 1.56 & 0.48 \\
6 & 0 & 0 & 0 & 1.06 & 0.15 \\
7 & \(-1\) & \(-1\) & 0 & 1.28 & 0.28 \\
8 & 0 & \(-1\) & 1 & 1.38 & 0.26 \\
9 & 1 & 0 & \(-1\) & 1.48 & 0.52 \\
10 & 1 & 0 & 1 & 1.62 & 0.42 \\
11 & \(-1\) & 1 & 0 & 1.43 & 0.35 \\
12 & 0 & 0 & 0 & 1.11 & 0.17 \\
13 & 0 & 1 & \(-1\) & 1.42 & 0.31 \\
14 & 0 & \(-1\) & \(-1\) & 1.35 & 0.32 \\
15 & \(-1\) & 0 & \(-1\) & 1.45 & 0.24 \\
16 & 0 & 0 & 0 & 1.12 & 0.18 \\
17 & 0 & 0 & 0 & 1.15 & 0.16 \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Source of**} & \multicolumn{5}{c}{**Grain Loss Rate \(Y_{1}\) (\%)**} \\ \cline{2-6}  & Sum of & & Mean & & \\  & Squares & & Square & F-Value & \(p\)-Value & Significance \\ \hline Model & 0.5230 & 9 & 0.0578 & 63.3 & \(<\)0.0001 & ** \\ A & 0.0435 & 1 & 0.0435 & 47.63 & 0.0002 & ** \\ B & 0.0264 & 1 & 0.0313 & 34.21 & 0.0006 & ** \\ C & 0.0055 & 1 & 0.0078 & 8.55 & 0.0222 & * \\ AB & 0.0009 & 1 & 0.0009 & 0.9851 & 0.354 & \\ AC & 0.0110 & 1 & 0.011 & 12.07 & 0.0104 & * \\ BC & 0.0064 & 1 & 0.0036 & 3.94 & 0.0875 & \\ A\({}_{2}\) & 0.1453 & 1 & 0.1532 & 167.7 & \(<\)0.0001 & ** \\ B\({}_{2}\) & 0.0864 & 1 & 0.0805 & 88.09 & \(<\)0.0001 & ** \\ C\({}_{2}\) & 0.1532 & 1 & 0.1453 & 159.02 & \(<\)0.0001 & ** \\ Residuals & 0.0055 & 7 & 0.0009 & & & \\ Fail to fit & 0.0010 & 3 & 0.0006 & 0.5531 & 0.6729 & \\ Error & 0.0045 & 4 & 0.0011 & & & \\ Total & 0.5285 & 16 & & & & \\ \hline \hline \multirow{2}{*}{**Source of**} & \multicolumn{5}{c}{**Grain Breakage Rate \(Y_{2}\) (\%)**} \\ \cline{2-6}  & Sum of & & Mean & & \\  & Squares & Freedom & Square & F-Value & \(p\)-Value & Significance \\ \hline Model & 0.3093 & 9 & 0.0344 & 53.52 & \(<\)0.0001 & ** \\ A & 0.0231 & 1 & 0.0231 & 35.99 & 0.0005 & ** \\ B & 0.022 & 1 & 0.022 & 34.34 & 0.0006 & ** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Variance analysis of response surface test. * indicates significant.  
The analysis of variance results indicates that the feeding speed, feeding angle, and stem-pulling roller speed all have significant effects on the two indicators, and there are interactions between some of these factors. The feeding speed and the stem-pulling roller speed had an interactive effect on the grain loss rate and the grain damage rate. The feeding angle and stem-pulling roller speed have an interactive effect on the grain damage rate. The regression models for the two evaluation indicators have a highly significant goodness of fit, with misfit terms of \(p>0.05\), indicating the absence of other factors influencing the evaluation indicators.