TAILIEUCHUNG - Genetic diversity analysis of rice genotypes for yield and yield attributing traits under saline stress condition

The present investigation to assess genetic diversity among 100 rice genotypes including five checks was conducted at Thyavanagi Village of Davanagere, Karnataka during Kharif 2016. Mahalanobis’ D2 statistics is used to quantify the degree of divergence. It is based on second degree statistics and pattern obtained by D2 does not change with number of characters. Mean values of 100 rice genotypes for ten characters were used to assess genetic distance between pair of genotypes. Genotypes were grouped into eleven clusters distribution patterns. Cluster pattern indicated that cluster I consists of maximum of 33 genotypes followed by cluster III (18 genotypes), cluster V (12 genotypes), cluster IV (11 genotypes), cluster II (10 genotypes). Whereas, clusters VIII, IX and XI were clustered as unitary clusters with single genotypes. Maximum intra cluster distance was observed in cluster VII () followed by cluster IV () and cluster VI indicated that the genotypes grouped under these clusters were more diverse. Highest contribution towards divergence was observed by plant height ( %) followed by spikelet fertility ( %). | Genetic diversity analysis of rice genotypes for yield and yield attributing traits under saline stress condition

• Nông nghiệp
• Genetic diversity analysis
• Rice genotypes
• Yield and yield attributing traits
• Saline stress condition
• Assess genetic diversity
• Genetic diversity
• Genetic variability
• Similarity coefficient
• Soybean genotypes
• Molecular marker based genetic diversity
• Brassica compestris
• Genetic diversity analysis based
• Molecular level
• Diversity analysis
• Genetic diversity analysis in sunflower
• Parental lines
• RAPD markers
• Principal component analysis
• Principal component analysis approach
• Brinjal (Solanum melongena L
• Onion genotypes through RAPD
• ISSR markers
• Genetic diversity remarkably
• Genetic improvement
• Sequence related amplified polymorphism
• Simple sequence repeat
• Genetic diversity of watermelon
• Gossypium hirsutum L
• Cotton germplasm
• Agro morphological characterization
• Mahalanobis D2 statistics
• Cluster analysis
• Okra genotypes
• Morphological markers
• Random amplified polymorphic DNA
• Polymerase chain reaction
• Genetic diversity analysis of citrus cultivars
• D2 analysis
• Landraces and salinity
• Genetic diversity in traditional landraces
• Rice for yield
• Acrocarpus fraxinifolius
• ISSR analysis of genetic diversity
• Landscape elements
• Transition forest belt
• Garcinia gummi gutta
• Molecular markers
• ISSR marker based genetic diversity analysis
• Garcinia accessions
• RAPD analysis for genetic diversity
• Hybridity in cowpea
• Primers revealed various levels
• RAPD based genetic diversity analysis
• Genotypes of Withania somnifera (L ) Dunal
• Crop improvement programme
• Twenty five genotypes of Ashwagandha
• Multivariate analysis in mungbean
• Genetic diversity under acidic soils
• Acidic soils of Manipur
• Clustering pattern of the genotypes
• Triticum aestivum
• SSR markers
• Oil palm genotypes
• Genetic diversity in oil palm genotypes
• Multivariate analysis
• Assessment of genetic diversity
• Thirty five genotypes
• Oilseed brassica species
• Genetic diversity in onion
• Short day condition
• Genotypes into three clusters
• Rice landraces
• Rice landraces of NW himalayas
• RAPD and ISSR markers
• Cassava genotypes
• Yield attributes in cassava genotypes
• Genetic diversity studies based
• Labeo rohita
• Hatchery and Dhaura reservoir
• Microsatellite markers
• Diversity analysis of genetic
• Bread wheat
• Quality characteristics of bread wheat
• Black gram
• Genetic diversity for yield
• Yield contributing traits in black gram
• Black gram (Vigna mungo L )
• Genetic diversity for Brinjal
• Future breeding program
• Individual character in Solanum melongena L