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Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and Iron

Akansha Singh, Dhirendra Singh, S. K. Singh, Vikas Kumar Singh, Arvind Kumar

2025Scientific Reports6 citationsDOIOpen Access PDF

Abstract

), 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.

Topics & Concepts

BiplotHeritabilityAmmiGenotypePrincipal component analysisBiologyGene–environment interactionMultivariate statisticsVeterinary medicineQuantitative trait locusGenetic variationMultivariate analysisZincBiotechnologyAgronomyPlant breedingBest linear unbiased predictionUttar pradeshAnimal scienceInteractionGrain yieldForensic scienceGenetic variabilityAdaptabilityOryza sativaMathematicsBreeding programMixed modelGenetics and Plant BreedingPlant Micronutrient Interactions and EffectsGenetic Mapping and Diversity in Plants and Animals