Journal: iScience

Article Title: Identification of superior rice donors with enhanced nitrogen use efficiency using a comprehensive multivariate genotype selection strategy

doi: 10.1016/j.isci.2025.113280

Figure Lengend Snippet: Principal component analysis, scree plot and biplot of 11 stress indexes calculated using 300 diverse rice genotypes (A) Scatterplots visualize the distribution of sample values in the reduced-dimensional spaces, highlighting clusters and separation patterns based on the principal components of stress indexes. The percentage of total phenotypic variance explained by the first four PCs is 99.17. (B) Scree plot (right panel) showed the % of phenotypic variance explained by the first ten principal components. A sharp decline (angled elbow) in variance after PC2 indicates that the first two components capture most of the data’s variability and the presence of three major clusters within the studied population group. (C) Biplot showed the first two dimensions represent the first (64.2%) and second (30.2%) principal components, capturing most of the variance in the dataset. Arrows represent individual variables, with their direction indicating the correlation with the principal components and their length reflecting the strength of the contribution. The color gradient (ranging from 5.5 to 8.0) indicates the magnitude of each variable’s contribution, with warmer colors (e.g., red) signifying higher contributions.

Article Snippet: AMMI biplot showing the mean yield performance of fifteen rice genotypes in three locations AMMI biplot (Additive Main effects and Multiplicative Interaction model) illustrates the interaction between genotypes and environments based on two principal components, PC1 (56.9%) and PC2 (43.1%) represent the first two interaction principal component axes (IPCA), together explaining 100% of the genotype × environment interaction variance.

Techniques:

Journal: iScience

Article Title: Identification of superior rice donors with enhanced nitrogen use efficiency using a comprehensive multivariate genotype selection strategy

doi: 10.1016/j.isci.2025.113280

Figure Lengend Snippet: AMMI biplot showing the mean yield performance of fifteen rice genotypes in three locations AMMI biplot (Additive Main effects and Multiplicative Interaction model) illustrates the interaction between genotypes and environments based on two principal components, PC1 (56.9%) and PC2 (43.1%) represent the first two interaction principal component axes (IPCA), together explaining 100% of the genotype × environment interaction variance. Green points and lines represent environments (E1, E2, E3). Blue points and dashed lines represent genotypes (G1 to G14). The proximity of genotypes to environments indicates their specific adaptability, while genotypes near the origin are considered more stable across environments.

Article Snippet: AMMI biplot showing the mean yield performance of fifteen rice genotypes in three locations AMMI biplot (Additive Main effects and Multiplicative Interaction model) illustrates the interaction between genotypes and environments based on two principal components, PC1 (56.9%) and PC2 (43.1%) represent the first two interaction principal component axes (IPCA), together explaining 100% of the genotype × environment interaction variance.

Techniques:

Journal: iScience

Article Title: Identification of superior rice donors with enhanced nitrogen use efficiency using a comprehensive multivariate genotype selection strategy

doi: 10.1016/j.isci.2025.113280

Figure Lengend Snippet: GGE biplot showing the relationship between environment and yield performance of 15 rice genotypes in three locations GGE biplot in the “Which-won-where” view is used to visualize the performance of genotypes across multiple environments, identify mega-environments and the best-performing genotypes within each, supporting genotype selection and recommendation. The x axis (PC1: 65.5%) and y axis (PC2: 22.81%) represent the first two principal components derived from genotype and genotype × environment interaction effects. Points labeled G1 to G16 represent different genotypes. Points labeled E1 to E3 represent different environments. Polygons connect the outermost genotypes, forming sectors that help identify which genotype performed best in which environment. Dotted lines (rays) divide the plot into sectors, each associated with a specific environment. The genotype at the vertex of each sector is considered the “winner” in that environment.

Article Snippet: AMMI biplot showing the mean yield performance of fifteen rice genotypes in three locations AMMI biplot (Additive Main effects and Multiplicative Interaction model) illustrates the interaction between genotypes and environments based on two principal components, PC1 (56.9%) and PC2 (43.1%) represent the first two interaction principal component axes (IPCA), together explaining 100% of the genotype × environment interaction variance.

Techniques: Selection, Derivative Assay, Labeling

Journal: BMC Plant Biology

Article Title: Delineation of genotype × environment interaction and identifying superior red sorghum [ Sorghum bicolor L. Moench] genotypes via multi-trait-based stability selection methods

doi: 10.1186/s12870-025-06188-4

Figure Lengend Snippet: AMMI I biplot of 27 red sorghum genotypes (blue dots) tested in three environments (green dots) from summer–2024: A PW: panicle weight, B YIELD: single-plant yield, C Fe: iron content, D Zn: zinc content. PC: principal component

Article Snippet: The AMMI I exploratory graph or biplot was designed with the X-axis representing the trait's mean across environments, highlighting the principal effects [ ], whereas the Y-axis displayed the first interactive principal component axis (IPCA 1) score, addressing the multiplicative effects (Fig. ).

Techniques:

Journal: BMC Plant Biology

Article Title: Delineation of genotype × environment interaction and identifying superior red sorghum [ Sorghum bicolor L. Moench] genotypes via multi-trait-based stability selection methods

doi: 10.1186/s12870-025-06188-4

Figure Lengend Snippet: AMMI II biplot developed using the PC I and PC II values of 27 red sorghum genotypes (blue dots) evaluated in three environments (green dots) from summer–2024: A PW: panicle weight, B YIELD: single-plant yield, C Fe: iron content, D Zn: zinc content

Article Snippet: The AMMI I exploratory graph or biplot was designed with the X-axis representing the trait's mean across environments, highlighting the principal effects [ ], whereas the Y-axis displayed the first interactive principal component axis (IPCA 1) score, addressing the multiplicative effects (Fig. ).

Techniques: