Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron
The present study was conducted to evaluate 30 rice genotypes at three different locations in eastern Uttar Pradesh during the Wet- 2020–21 and determine the impact of GEI on grain yield (tha-1), days to 50% flowering, grain Fe content (PPM), and grain Zn content (PPM). The study also aimed to ident...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/177970 |
| _version_ | 1855529846410575872 |
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| author | Singh, Akansha Singh, Dhirendra Kumar Singh, Shravan Kumar Singh, Vikas Kumar Kumar, Arvind |
| author_browse | Kumar, Arvind Singh, Akansha Singh, Dhirendra Kumar Singh, Shravan Kumar Singh, Vikas Kumar |
| author_facet | Singh, Akansha Singh, Dhirendra Kumar Singh, Shravan Kumar Singh, Vikas Kumar Kumar, Arvind |
| author_sort | Singh, Akansha |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The present study was conducted to evaluate 30 rice genotypes at three different locations in eastern Uttar Pradesh during the Wet- 2020–21 and determine the impact of GEI on grain yield (tha-1), days to 50% flowering, grain Fe content (PPM), and grain Zn content (PPM). The study also aimed to identify the genotypes that displayed the best performance according to the multi-trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), and factor analysis and ideotype-design (FAI-BLUP) index. AMMI analysis demonstrated significant variation for environment (E), genotype (G), and genotype-by-environment interaction (GEI) (P < 0.01) for all the studied traits. The AMMI1 biplot showed that PC1 explained the majority of the variation for GY (77.6%), DTF (90.5%), Fe (73.5%), and Zn (86.8%), helping to identify stable and high-performing genotypes. AMMI2 biplot further resolved complex GEI patterns, highlighting genotypes with specific adaptability to individual environments. The GGE biplot revealed clear “which-won-where” patterns for GY, DTF, Fe, and Zn, explaining 94.37%, 99.71%, 83.49%, and 96.93% of GEI variation, respectively. BLUP analysis using a linear mixed model revealed significant GEI effects for GY, DTF, Fe, and Zn across 30 rice genotypes in three environments. Low heritability was observed for Fe (28.2%) and moderate for GY (54.4%) and Zn (56.4%), while DTF showed high heritability with strong genotypic accuracy. Genotype G7 was identified as stable, early, high-yielding, and rich in Fe based on HMGV, RPGV, and HMRPGV indices. The MTSI, MGIDI and FAI-BLUP analysis revealed that BHU-SKS-1 (G15) and IR105696 -1–2-3–1-1–1 -B (G9) were the most stable and best mean performer for high grain yield and high grain Fe & Zn content, while IR 108,195–3-1–1-2 (G7) was the most stable and best mean performer for high grain yield and high grain Fe content with early flowering. |
| format | Journal Article |
| id | CGSpace177970 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1779702026-01-08T16:13:44Z Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron Singh, Akansha Singh, Dhirendra Kumar Singh, Shravan Kumar Singh, Vikas Kumar Kumar, Arvind rice crop yield zinc iron trace elements The present study was conducted to evaluate 30 rice genotypes at three different locations in eastern Uttar Pradesh during the Wet- 2020–21 and determine the impact of GEI on grain yield (tha-1), days to 50% flowering, grain Fe content (PPM), and grain Zn content (PPM). The study also aimed to identify the genotypes that displayed the best performance according to the multi-trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), and factor analysis and ideotype-design (FAI-BLUP) index. AMMI analysis demonstrated significant variation for environment (E), genotype (G), and genotype-by-environment interaction (GEI) (P < 0.01) for all the studied traits. The AMMI1 biplot showed that PC1 explained the majority of the variation for GY (77.6%), DTF (90.5%), Fe (73.5%), and Zn (86.8%), helping to identify stable and high-performing genotypes. AMMI2 biplot further resolved complex GEI patterns, highlighting genotypes with specific adaptability to individual environments. The GGE biplot revealed clear “which-won-where” patterns for GY, DTF, Fe, and Zn, explaining 94.37%, 99.71%, 83.49%, and 96.93% of GEI variation, respectively. BLUP analysis using a linear mixed model revealed significant GEI effects for GY, DTF, Fe, and Zn across 30 rice genotypes in three environments. Low heritability was observed for Fe (28.2%) and moderate for GY (54.4%) and Zn (56.4%), while DTF showed high heritability with strong genotypic accuracy. Genotype G7 was identified as stable, early, high-yielding, and rich in Fe based on HMGV, RPGV, and HMRPGV indices. The MTSI, MGIDI and FAI-BLUP analysis revealed that BHU-SKS-1 (G15) and IR105696 -1–2-3–1-1–1 -B (G9) were the most stable and best mean performer for high grain yield and high grain Fe & Zn content, while IR 108,195–3-1–1-2 (G7) was the most stable and best mean performer for high grain yield and high grain Fe content with early flowering. 2025-11 2025-11-17T17:25:13Z 2025-11-17T17:25:13Z Journal Article https://hdl.handle.net/10568/177970 en Open Access Springer Singh, Akansha; Singh, Dhirendra Kumar; Singh, Shravan Kumar; Singh, Vikas Kumar; and Kumar, Arvind. 2025. Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron. Scientific Reports 15(1): 39586. https://doi.org/10.1038/s41598-025-11748-7 |
| spellingShingle | rice crop yield zinc iron trace elements Singh, Akansha Singh, Dhirendra Kumar Singh, Shravan Kumar Singh, Vikas Kumar Kumar, Arvind Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron |
| title | Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron |
| title_full | Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron |
| title_fullStr | Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron |
| title_full_unstemmed | Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron |
| title_short | Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and iron |
| title_sort | multivariate stability analysis to select elite rice oryza sativa l genotypes for grain yield zinc and iron |
| topic | rice crop yield zinc iron trace elements |
| url | https://hdl.handle.net/10568/177970 |
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