# Design and Evaluation of Vacuum Central Drum Seed Metering Device
## 4 Seed Performance Test
### Multivariate Test
#### 4.4.2 Test Results Analysis  
Due to the strong tiller capacity of hybrid rice, 2 \(\pm\) 1 seeds per hole is generally more appropriate for field direct seeding, so 2 \(\pm\) 1 seeds per hole is defined as qualified, 0 seeds per hole is defined as missing, and \(\geq\)4 seeds per hole is defined as re-seeding. 1. Influence on seeding qualified rate  
From the analysis of Table 5, the R-values indicate that the order of influence on the pass rate indicators was A \(>\) C \(>\) B. For the analysis of increasing the pass rate, A\({}_{1}\)B\({}_{1}\)C\({}_{2}\) is the best combination. From the ANOVA in Table 6, factors A and C have a significant effect on the pass rate compared to factor B. 2. Influence on the missing rate  
From the analysis of Table 7, the R-values indicate that A \(>\) C \(>\) B in the order of priority for the indicators of sowing failure, and that A\({}_{2}\)B\({}_{3}\)C\({}_{2}\) was the best combination for increasing the sowing failure rate. From the ANOVA in Table 8, factors A and C are more significant than factor B in influencing the sowing rate. 3. Influence on the rate of re-seeding  
From the analysis in Table 9, the R-values indicate that the main order of influence on the reseeding rate indicators was A \(>\) C \(>\) B. The analysis for increasing the reseeding rate indicates that A\({}_{3}\)B\({}_{1}\)C\({}_{1}\) was the best combination. From the ANOVA in Table 10, the factors ABC did not have a significant effect on the reseeding rate. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Source** & **Type III Sum of Squares** & **df** & **Mean Square** & **F** & **Sig.** \\ \hline Correction model & 11,129.028a & 9 & 1236.559 & 11.100 & 0.001 \\ Intercept distance & 79,507.427 & 1 & 79,507.427 & 713.716 & 0.000 \\ A & 8279.023 & 5 & 1655.805 & 14.864 & 0.001 \\ B & 6.524 & 2 & 3.262 & 0.029 & 0.971 \\ C & 2843.481 & 2 & 1421.741 & 12.763 & 0.003 \\ Error (Inaccuracy) & 891.194 & 8 & 111.399 & & \\ Total & 91,527.650 & 18 & & \\ Total corrected & 12,020.223 & 17 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The variance analysis for the qualification rate. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Factor** & **A** & **B** & **C** \\ \hline \(k_{1}\) & 488.58 & 199.50 & 215.28 \\ \(k_{2}\) & 498.18 & 197.04 & 235.5 \\ \(k_{3}\) & 482.4 & 161.19 & 147.33 \\ \(k_{4}\) & 400.02 & & \\ \(k_{5}\) & 372.36 & & \\ \(k_{6}\) & 131.76 & & \\ \(\overline{k}_{1}\) & 84.30 & 66.55 & 71.76 \\ \(\overline{k}_{2}\) & 83.03 & 65.68 & 78.50 \\ \(\overline{K}_{3}\) & 80.40 & 53.73 & 49.11 \\ \(\overline{k}_{4}\) & 66.70 & & \\ \(\overline{k}_{5}\) & 62.06 & & \\ \(\overline{k}_{6}\) & 21.96 & & \\ \(R\) & 62.34 & 12.82 & 29.39 \\ Factor Priorities & A & C & B \\ Optimization options & A\({}_{1}\)B\({}_{1}\)C\({}_{2}\) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The intuitionistic analysis for qualified rate. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Factor** & **A** & **B** & **C** \\ \hline \(k_{1}\) & 25.40 & 200.40 & 215.28 \\ \(k_{2}\) & 15.90 & 177.70 & 173.70 \\ \(k_{3}\) & 55.50 & 164.30 & 268.50 \\ \(k_{4}\) & 99.60 & & \\ \(k_{5}\) & 112.8 & & \\ \(k_{6}\) & 233.2 & & \\ \(\overline{k}_{1}\) & 8.47 & 33.40 & 35.88 \\ \(\overline{k}_{2}\) & 5.30 & 29.62 & 28.95 \\ \(\overline{k}_{3}\) & 18.50 & 27.38 & 44.75 \\ \(\overline{k}_{4}\) & 33.20 & & \\ \(\overline{k}_{5}\) & 37.60 & & \\ \(\overline{k}6\) & 77.73 & & \\ \(R\) & 72.43 & 6.02 & 15.8 \\ Factor Priorities & A & C & B \\ Optimization options & A\({}_{2}\)B\({}_{3}\)C\({}_{2}\) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: The intuitionistic analysis for the missing rate.