Characterization, evaluation and multivariate analysis of sunflower germplasm under semi-arid environments of three locations in two sunflower growing states in India

Aim : The present study aimed at identifying high yielding genotypes through principal component analysis and cluster analysis by utilizing multilocation data generated by growing 32 germplasm accessions under semi-arid environments of Telangana and Maharashtra states. Methodology : The evaluation trial was conducted in two Indian states Telangana (Hyderabad) and Maharashtra (Solapur and Savalvihir). R software 3.1.3 package was used to determine the major descriptive statistics, cluster analysis, principal component analysis (PCA) and correlations among the yield contributing traits. Results : Wide range of genetic variation for seed yield and its components were recorded in the accessions studied. Principal component analysis disclosed that the first four components with eigen values greater than 0.43 contributed about 93.3% of total variability in the studied germplasm involving all the seven characters. The genotypes analysed were grouped into eleven clusters, out of which cluster IX was the largest having six genotypes indicating genetic similarity among them. Character association indicated that among the seven agromorphological traits, five traits viz., days to flowering, days to maturity, head diameter, 100-seed weight and volume weight had significant and positive correlation with seed yield. Interpretation : Based on PCA and cluster analysis, eight accessions GMU189, GMU799, GP(2)1217, GP(6)271, GMU440, GP(6)211, GP(6)286 and DRSF113 were identified as high yielding which can be widely utilised for the development of new diverse varieties/hybrids for enhanced seed yield under semi-arid conditions.