TAILIEUCHUNG - Assessment of genetic diversity in thirty-five genotypes of oilseed brassica species using principal component analysis

The principal component and factor analyses of 35 genotypes of different Brassica species was carried for pooled data of two years 2015-16 and 2016-17. The PCA indicated that first four principal components showed eigen values more than one and explained more than 80% of total variability in pooled analysis. Based on Varimax Rotation all fourteen characters were grouped in eight principal factors and siliquae per plant, plant height, main shoot length and siliquae on main shoot were the major contributing traits which accounted for of total variation of . The hierarchical cluster analysis divided 35 genotypes into six clusters. The cluster IV appeared as the largest cluster containing maximum numbers of genotypes 23 under pooled analysis. The mean performance of different clusters revealed wide range of differences among clusters. The genotypes V20 (GPM-O-1 X PT-303), V16 (PL-58 X BN-11), V27 (GPM-O-58), V5 (NGM-17 X T-42) and V15 (PL-58 X BN-10) in cluster IV showed very good performance for seed & oil yield per plant. While genotypes V11 (T-42 X NGM-17), V10 (T-42 X GPM-O-58), V19 (T-42 X PL-58) and V33 (T-42) in cluster III, IV and V exhibited very good performance for oil content. | Assessment of genetic diversity in thirty-five genotypes of oilseed brassica species using principal component analysis

• Sinh học
• Assessment of genetic diversity
• Genetic diversity
• Thirty five genotypes
• Oilseed brassica species
• Principal component analysis
• Genetic diversity among fenugreek
• Fenugreek genotypes
• ISSR markers
• Rice bean
• Utilization of molecular
• Morphometric tools for assessment
• Genetic diversity of rice bean
• Genetic diversity in Gangatiri cow
• Gangatiri cow
• Employing RAPD marker
• RAPD marker for the assessment
• Genetic diversity of sesame
• Sesame varieties
• Similarity coefficient level increases
• Molecular characterization
• SSR markers
• Soybean varieties
• Genetic diversity assessment
• Variability of maize
• Maize (Zea mays L ) inbreds
• Genotypes into different clusters
• Genetic variability
• Correlation analysis
• Genetic advances
• Yield traits in cauliflower
• Genetic diversity assessment for growth
• Rice restorer lines
• Eigen values
• New restorer lines
• Hybrid rice
• Genetic diversity analysis
• Cultivated tomato (Solanum lycopersicon L )
• Genotypes using molecular markers
• D2 statistic
• Simple sequence repeats markers
• Indigenous sesame genotypes
• Bottle gourd
• Genetic diversity in bottle gourd
• Yield improvement
• Pigeonpea diversity
• Microsatellite markers
• Microsatellite (SSR) markers
• Pigeonpea cultivars
• Genetic variation
• Genetic advance
• Okra [Abelmoschus esculentus (L
• ) Moench]
• Elite genotypes of okra
• PIC and marker
• Genetic diversity in hybrids of tomato
• Tomato (Solanum lycopersicum L
• Mahalanobis D2 statistics
• Genetic diversity in okra
• West Godavari district during kharif season
• Twenty nine hybrids
• D 2 statistics
• Clustering pattern
• Linseed (Linum usitatissimum L )
• Genetic diversity in linseed
• Cluster analysis
• Genetic diversity for Brinjal
• Future breeding program
• Individual character in Solanum melongena L
• Summer season
• Genetic diversity in blackgram
• Genotypes evaluated
• Different seasons
• Genetic divergence
• Different chilli (Capsicum annuum L )
• Genetic diversity in tomato
• Tomato germplasm
• Kabuli chickpea
• Diversity and cooking quality
• Cooking quality
• Large seeded kabuli chickpea
• Genetic diversity in extra large
• Common bean
• Yield traits
• Large germplasm
• Bread wheat
• Triticum aestivum L
• Genetic diversity in bread wheat
• Genetic polymorphism
• Diverse parents
• Simple sequences repeat
• Rice germplasm using SSR markers
• Genetic diversity in rice