## 2 Materials and Methods
### Independent Validation  
If the same crops are planted on the same land every year, the soil will become less fertile. Therefore, secondary rotation combination design experiments are rarely continuously conducted in the same experimental field to determine the best cultivation measures of corn. Two groups of public experimental data with the same experimental location and experimental design as the JLASTU experiment were selected to verify the GDM-DEA method. The experiments were named the Anshun Pan experiment and the Anshun Tang experiment, respectively [54; 55]. The cultivation measures and yield production are shown in Tables S1-S4. As is the case with the JLASTU experiment, the two experiments also have twelve control groups. The Chifeng Zheng experiment [56] with different regions and experimental designs was also selected for verification. The experimental data were collected with the four-factor five-level quadratic general rotation combination design method in the experimental site of Chifeng Academy of agricultural and animal husbandry sciences (Table S5). In contrast to the quadratic regression orthogonal rotation combination design method, the quadratic general rotation combination design method has 31 experimental groups in this study. In the Chifeng Zheng experiment, the cultivation measures of group codes 25-31 are the control group. The cultivation measures, as well as the yield production of the Chifeng Zheng experiment can be found in Table S6. Figure 1 is the flow chart of the full text, which is divided into the following two parts: the corn planting experiment and corn production performance evaluation. The experiment adopts the quadratic regression orthogonal rotation combination design, and the evaluation method adopts the CCR model that can evaluate the relative effectiveness of multiple decision-making units. Based on this model, a new evaluation model is proposed, which is easier to determine the optimal cultivation measures in corn from the evaluation results. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Variable (\(X_{i}\))**} & \multirow{2}{*}{**Changes in Pitch**} & \multicolumn{6}{c}{**Design Level (\(r\))**} \\ \cline{3-6}  & & \(-\)**2** & \(-\)**1** & **0** & **1** & **2** \\ \hline Density (\(X_{1}\)) & 1 (10,000 plants/ha) & 5 & 6 & 7 & 8 & 9 \\ \hline N (\(X_{2}\)) & 40 (kg/ha) & 160 & 200 & 240 & 280 & 320 \\ \hline P\({}_{2}\)O\({}_{5}\) (\(X_{3}\)) & 20 (kg/ha) & 80 & 100 & 120 & 140 & 160 \\ \hline K\({}_{2}\)O (X\({}_{4}\)) & 30 (kg/ha) & 60 & 90 & 120 & 150 & 180 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Decisive variety \(x\) and linear coded data. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Group Code** & \(x_{1}\) & \(x_{2}\) & \(x_{3}\) & \(x_{4}\) & **Production (kg/ha)** \\ \hline  
\hline \end{tabular}
\end{table} 
Table 2: Experiment structural matrix of the JLASTU experiment. The current research methods used to determine the efficiency mainly include the parametric method and non-parametric method. The parametric method includes the deterministic parameter method and non-deterministic parameter method. The deterministic parameter method has some defects with no explicit assumption for the error term. Thus, the non-deterministic parameter method has received increasing attention. At present, the probability frontier construction method and stochastic frontier analysis are the most common methods. The non-parametric method originates from production frontier research methods based on the relative measurement of economic efficiency proposed by [PERSON]. It does not limit the shape of the efficiency frontier and does not require a clear definition for the basic production function but locates relatively efficient points on the production frontier based on the observation of a large number of actual data and particular production effectiveness standards. Currently, the most popular non-parametric method is the DEA Method. DEA is an efficiency evaluation method based on the concept of relative efficiency.