## 3 Results
### Biplot Patterns for Multivariate Analysis  
Biplot patterns are divided into three main sections: the \"which-won-where\" pattern, based on the correlation between genotypes and environments; the \"mean vs. stability\" pattern, measured according to the genotype; and the \"discriminative vs. representativeness\" pattern, which evaluates the test environments [11; 18]. These biplot patterns form a two-dimensional visualization matrix on the X and Y axes. Within this matrix, data are centered and then decomposed using singular values (SV) into GE scores (dimensionless) for the principal components, PC1 and PC2. PC1 reflects the level of performance, while PC2 indicates the stability of the genotypes [18]. The GGE biplot (\"which-won-where\") in Figure 2 shows the pattern of test data across multiple environments, where the x-axis PC1 and y-axis PC2 explain 56.51% and 18.26%, respectively, of the total variation (74.77%). The genotypes furthest from the origin in various directions formed a polygon that encompassed all other genotypes, indicating that they were the best varieties in their respective sectors. The polygon was divided into four sectors when a perpendicular line was drawn from the origin to each side of the polygon, dividing the biplot into sectors by year. The 15 environments were grouped into \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Source of** & **Yield (t. ha\({}^{-1}\))** & **SD** & \multicolumn{2}{c}{**Rank by Grand**} & \multirow{2}{*}{**Rank by GGE**} \\
**Variation** & & & & **Mean** & \\ \hline \multicolumn{5}{c}{**Genotypes**} \\ \hline CC-8592 & 76.54 \(\pm\) 0.511 \({}^{\text{c}}\) & 19.63 & 6 & 4 \\ CC93-4181 & 68.67 \(\pm\) 1.845 \({}^{\text{d}}\) & 17.58 & 9 & 6 \\ CLONES & 92.64 \(\pm\) 2.334 \({}^{\text{a}}\) & 22.4 & 1 & 5 \\ CR-74250 & 72.52 \(\pm\) 1.065 \({}^{\text{d}}\) & 16.13 & 7 & 5 \\ EC-02 & 85.27 \(\pm\) 1.301 \({}^{\text{a,b}}\) & 23.83 & 2 & 2 \\ EC-03 & 63.98 \(\pm\) 1.636 \({}^{\text{e}}\) & 15.06 & 10 & 7 \\ EC-05 & 72.63 \(\pm\) 2.026 \({}^{\text{c,d}}\) & 16.13 & 8 & 6 \\ EC-07 & 86.1 \(\pm\) 1.912 \({}^{\text{a,b}}\) & 20.18 & 3 & 1 \\ EC-08 & 83.29 \(\pm\) 1.697 \({}^{\text{b}}\) & 19.47 & 4 & 3 \\ ECU-01 & 82.95 \(\pm\) 0.813 \({}^{\text{b}}\) & 19.72 & 5 & 3 \\ \hline \multicolumn{5}{c}{**Sector**} \\ \hline sector 01 & 75.17 \(\pm\) 0.813 \({}^{\text{c}}\) & 17.17 & 3 & 3 \\ sector 02 & 79.84 \(\pm\) 0.647 \({}^{\text{b}}\) & 19.71 & 2 & 2 \\ sector 03 & 88.44 \(\pm\) 0.799 \({}^{\text{a}}\) & 22.99 & 1 & 1 \\ sector 04 & 70.77 \(\pm\) 0.81 \({}^{\text{c}}\) & 17.56 & 5 & 3 \\ sector 05 & 73.68 \(\pm\) 0.807 \({}^{\text{d}}\) & 18.03 & 4 & 2 \\ \hline \multicolumn{5}{c}{**Years**} \\ \hline
2018 & 68.45 \(\pm\) 0.58 \({}^{\text{b}}\) & 18.42 & 3 & 3 \\
2019 & 82.31 \(\pm\) 0.58 \({}^{\text{a}}\) & 18.95 & 2 & 2 \\
2020 & 83.61 \(\pm\) 0.624 \({}^{\text{a}}\) & 19.52 & 1 & 1 \\ \hline \hline \end{tabular}  
* **Note.** Values indicate the yield mean \(\pm\) SE (standard error); Different letters within a column indicate significant differences according to the Tukey HSD test (\(p<0.05\)).  
\end{table} 
Table 5: Yield and classification of genotypes, sectors and years by [PERSON]’s test and GGE model. different clusters (environment A and C as one group, environments B, K, L as another group, environments E, H, I as a third group, and finally environments F, G and D, J as independent groups), and then the suitable genotypes for each group were identified. The winning genotype, which has the highest yield in all the environments dividing the sector, is located at the vertex. According to [PERSON] and [PERSON], (2006) [27], genotypes located at the vertices of the polygon have had the best or worst performance in one or more environments. There are five sectors with the genotypes \"CLONES\", \"EC-02\", \"EC-03\", \"EC-05\", and \"EC-07\" as corner or vertex genotypes. The analysis showed that the CLONES genotype had the highest yield in environments J and D, while the EC-07 genotype had the highest yield in environment B.