## 5 Discussion  
1. Humidity directly determines the friction coefficient \(\mu\) between the straw and straw guide board, and it has a great influence on the PLR, PIR, and PBR of the grain combine harvester. Moreover, it is of great research value to determine whether the influence of the rice humidity on the harvesting effect can be eliminated by adjusting the angle of the straw guide board. However, owing to the difficulty in controlling the rice humidity during the grain combine harvester trials, this study did not consider it as an independent factor involved in the field validation trials and optimization. Otherwise, it would have been a four-factor, three-level trial, and there would have been exceedingly many experimental groups, the observation and statistics would have been difficult, and there would have been many problems in the operability and practical application of the field experiments.
2. The effects of the rice varieties, material characteristics, and agronomy on the threshing equipment were not fully considered in this experiment. To conduct field trials of adjustable straw guide and threshing devices under different crop types, different yield differences, and different operating environments, the next step for the research  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Indicator** & **No.** & **Predicted Value** & **Validated Value** & **Relative Error** & **Absolute Error** \\ \hline \multirow{4}{*}{_PLR_ (\%)} & 1 & & 1.28 & 8.47 & 0.10 \\  & 2 & & 1.23 & 4.24 & 0.05 \\  & 3 & & 1.27 & 7.63 & 0.09 \\  & mean & & 1.26 & 6.78 & 0.08 \\ \hline \multirow{4}{*}{_PIR_ (\%)} & 1 & & 0.71 & 1.39 & \(-\)0.01 \\  & 2 & & 0.70 & 2.78 & \(-\)0.02 \\  & 3 & & 0.75 & 4.17 & 0.03 \\  & mean & & 0.73 & 1.39 & 0.01 \\ \hline \multirow{4}{*}{_PBR_ (\%)} & 1 & & 0.63 & 16.67 & 0.09 \\  & 2 & & 0.61 & 12.96 & 0.07 \\ \cline{1-1}  & 3 & & 0.54 & 0.59 & 9.26 & 0.05 \\ \cline{1-1}  & mean & & 0.61 & 12.96 & 0.07 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of predicted values and validated values.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Constraints**} & \multicolumn{4}{c}{**Solutions**} \\ \cline{2-9}
**Name** & **Goal** & **Lower** & **Upper** & **Lower** & **Upper** & **Importance** & **Optimized** & **Parameter** \\  & **Limit** & **Limit** & **Weight** & **Weight** & **Results** & **Adjustment** \\ \hline \(A\) (r/min) & within range & 500 & 700 & 1 & 1 & 3 & 551.29 & 550 \\ \(B\) (km/h) & within range & 2.5 & 4.5 & 1 & 1 & 3 & 3.14 & 3 \\ C (\({}^{\circ}\)) & within range & 10 & 50 & 1 & 1 & 3 & 28.22 & 28 \\ _PLR_ (\%) & minimize & 0 & 2 & 1 & 1 & 3 & 1.18 & 1.18 \\ _PIR_ (\%) & minimize & 0 & 1.60 & 1 & 1 & 3 & 0.72 & 0.72 \\ _PBR_ (\%) & minimize & 0 & 1.72 & 1 & 1 & 3 & 0.53 & 0.54 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Constraints and solutions.  
team will be to explore the effects of different experimental factors on the grain combine harvester PLR, PIR, and PBR.
3. With the development of science and technology, electromechanical and hydraulic control, sensors, the Internet, machine vision, computer simulation, and other technologies are also widely used in combined harvester research. Advanced technology will inevitably bring complex structures and increase manufacturing costs. High temperature and high humidity operating environments also affect the service life of the equipment. Balancing the ease of operation, stability of use, and economy of purchasing machines will also be a key issue to seriously consider.