## 3 Results and discussion  
### Analysis of the Experiment Results in the Field  
Three-factor and five-level quadratic orthogonal rotation combination experiments were performed, each experiment was repeated three times, and the average value of the experimental results was taken. The experimental scheme and analysis of the results were carried out by Design Expert 8.0 software, as shown in Table 3. The ANOVA table is shown in Table 4. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Source** & **Sum of Squares** & **Degree of Freedom** & **Mean Square** & **F Value** & **\(p\) Valve** \\ \hline Modal & 313.22 & 9 & 34.80 & 30.17 & \textless{}0.0001 ** \\ \(x_{1}\) & 58.87 & 1 & 58.87 & 51.03 & \textless{}0.0001 ** \\ \(x_{1}\) & 147.89 & 1 & 147.89 & 128.20 & \textless{}0.0001 ** \\ \(x_{1}\) & 1.19 & 1 & 1.19 & 1.03 & 0.3282 \\ \(x_{1}\) & 0.070 & 1 & 0.070 & 0.061 & 0.8089 \\ \(x_{1}\) \(x_{2}\) & 12.18 & 1 & 12.18 & 10.56 & 0.0063 ** \\ \(x_{1}\) \(x_{2}\) & 0.24 & 1 & 0.24 & 0.21 & 0.6548 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Analysis of variance table. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**Rotating Speed of the**} & **Weeding** \\
**Level** & **Forward Speed/(m/s)** & **Weeding Wheels/(r/min)** & **Depth/(mm)** \\ \hline \(-1.682\) & 0.43 & 86.4 & 43.2 \\ \(-1\) & 0.5 & 100 & 50 \\ \(0\) & 0.6 & 120 & 60 \\ \(1\) & 0.7 & 140 & 70 \\ \(1.682\) & 0.77 & 153.6 & 76.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Coding table of the experiment factor level. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**Experimental Factors**} & **Experimental** \\ \cline{2-4}
**Level** & **Forward Speed** & **Rotating Speed of the Weeding** & **Weeding Depth** & **Inter Row Weeding** \\  & **x\({}_{1}\)/(m/s)** & **Wheels x\({}_{2}\)/(r/min)** & **x\({}_{3}\)/(mm)** & **Rate \(y\)/(\%)** \\ \hline \(1\) & \(-1\) (0.5) & \(-1\) (100) & \(-1\) (50) & 83.77 \\ \(2\) & \(-1\) & \(-1\) & 1 (70)  
According to the results of the variance analysis in Table 4, the F-value of the regression equation was 2.04, and the \(p\)-value was 0.1774, which means that the difference in lack of fit was not significant, and the fitting degree of the equation was good. The regression equations of the inter row weeding rate and forward speed, rotating speed of the weeding wheels and depth of weeding were established as follows:  
\[y=89.94-2.08x_{1}+3.29x_{2}+0.30x_{3}-0.094x_{1}x_{2}-1.23x_{1}x_{3}+0.17x_{2} x_{3}-1.63x_{1}^{2}-1.46x_{2}^{2}-1.06x_{3}^{2} \tag{33}\]  
The larger the F value is, the greater the influence of the experimental factors on the experimental indexes is [21]. Based on the F value of each factor, the order of the influence of the three factors on the weeding rate is as follows: the rotating speed of the weeding wheels > forward speed > weeding depth. Design Expert 8.0 software was used to analyze the interaction of the forward speed, rotating speed of the weeding wheels and weeding depth. The response surface and contour map are shown in Figures 8-10. The response surface and contour map of the influence of the forward speed and rotating speed of the weeding wheels on the inter row weeding rate are shown in Figure 8. When  
The response surface and contour map of the influence of the forward speed and depth on the inter row weeding rate are shown in Figure 9. When the forward speed was constant, the inter row weeding rate increased slowly with increasing weeding depth. When the weeding depth was constant, the inter row weeding rate increased first and then decreased slowly with increasing forward speed. The response surface changed quickly along the direction of the forward speed and relatively slowly along the direction of the weeding depth, which indicated that the influence of the forward speed on the inter row weeding rate was more significant than that of the weeding depth on the inter row weeding rate.