The studies on genetic variation, diversity and population structure of rice germplasm of North East India could be an important step for improvements of abiotic and biotic stress tolerance in rice. Genetic diversity and genetic relatedness among 114 rice genotypes of North East India were assessed using genotypic data of 65 SSR markers and phenotypic data. The phenotypic diversity analysis showed the considerable variation across genotypes for root, shoot and drought tolerance traits. The principal component analysis (PCA) revealed the fresh shoot weight, root volume, dry shoot weight, fresh root weight and drought score as a major contributor to diversity. Genotyping of 114 rice genotypes using 65 SSR markers detected 147 alleles with the average polymorphic information content (PIC) value of 0.51. Population structure analysis using the Bayesian clustering model approach, distance-based neighbor-joining cluster and principal coordinate analysis using genotypic data grouped the accession into three sub-populations. Population structure analysis revealed that rice accession was moderately structured based on F_ST value estimates. Analysis of molecular variance (AMOVA) and pairwise F_ST values showed significant differentiation among all the pairs of sub-population ranging from 0.152 to 0.222 suggesting that all the three subpopulations were significantly different from each other. AMOVA revealed that most of the variation in rice accession mainly occurred among individuals. The present study suggests that diverse germplasm of NE India could be used for the improvement of root and drought tolerance in rice breeding programmes.

Multi-parent Advanced Generation Inter-Cross (MAGIC) populations offer high recombination and genetic diversity, providing opportunities for dissecting complex agronomic traits. In this study, 230 MAGIC rice recombinant inbred lines derived from eight indica founders were evaluated at the Assam Rice Research Institute, AAU, Titabor, to assess variation in five key traits: grain weight, grain number per plant, grain length, grain breadth, and 100-grain weight. Analysis of variance (ANOVA) revealed significant genotypic variation (p < 0.001) for grain yield per plant and grain number per plant, while grain size traits showed limited differentiation among genotypes. These traits exhibited high genotypic and phenotypic coefficients of variation (> 50%) and high broad-sense heritability (> 89%), indicating a substantial genetic contribution to phenotypic variation under the experimental conditions. Grain yield per plant showed a strong positive correlation with grain number per plant (r = 0.97), identifying grain number as the primary determinant of yield. Multivariate analyses, including principal component analysis and hierarchical clustering, revealed structured phenotypic variation within the population. A Composite Trait Index (CTI) facilitated the identification of superior lines, with Plots 18, 70, and 85 emerging as promising genotypes. Collectively, these findings demonstrate the phenotypic diversity and breeding potential of the MAGIC population for improving rice yield under rainfed lowland conditions of Northeast India.