Genetic diversity and population structure analysis of Asian and African aromatic rice (Oryza sativa L.) genotypes

Rice germplasms collected from different regions could be used as valuable resources for the future breeding programme. For the utilization of such collections, knowledge about the level and distribution of genetic diversity among these collections will facilitate the breeder. In this study, we report the phenotypic correlation, biochemical quality parameters and population genetic analysis of 35 rice accessions including 34 aromatic rice from different countries and a nonaromatic, Nagina 22, a well-known drought resistance variety. Further biochemical quality analysis, gel consistency test, molecular diversity analysis with 55 simple sequence repeat markers, population structure analysis and pair wise FST analysis were also conducted to assess the genetic diversity. The collected rice genotypes showed significant variability in different agronomic traits, i.e. spikelet per panicle, branches per panicle etc. Results obtained from the above tests demonstrated the importance of regional genetic studies for understanding the diversification of aromatic rice in Asian and African rice.

Divergence Analysis for Yield and Quality Traits in Some Indigenous Basmati Rice Genotypes [Oryza sativa L.].

Genetic divergence was assessed among 23 genotypes of basmati rice representing different regions of India on the basis of yield and quality characteristics utilizing Mahalanobis D2 analysis. Based on the genetic distance (D2 values), the rice genotypes were grouped into six clusters. Of the six clusters formed cluster VI consisted of maximum eight genotypes followed by cluster V accommodating six genotypes, cluster I with four genotypes, cluster III and IV with three genotypes each and cluster II with one genotype. The results indicated that there was some degree of similarity of genotypes clustered together on the basis of their origin. However, the pattern of distribution of some genotypes from different eco-geographical regions was found random, indicating that geographical diversity and genetic diversity were not related. The maximum intra cluster distance was observed for the cluster III. The highest genetic divergence was observed between the clusters IV and I exhibiting wide diversity. The genotypes representing cluster VI are more yielding combined with excellent cooking quality. Among different traits, plant height, kernel length, elongation ratio and amylose content had maximum contribution towards total divergence may be used as selection parameters in segregating generations. Intelligent selection of genotypes from the clusters may be used as potential donors for future hybridization programmes to develop varieties and hybrids of high yield without much compromise on quality.