Phenotypic Evaluation of Sunflower (Helianthus Annuus L.) Landraces as a Tool for Conservation and Valorization of Plant Genetic Resources

Abstract

Sunflower yield stagnation driven by genetic erosion threatens edible oil security, necessitates the integration of adaptive genetic resources. This study conducted the phenotypic valorization of 114 Pakistan's indigenous sunflower landraces along with 3 checks to characterize genetic diversity, analyze yield-associated traits, and identify superior genotypes for sunflower improvement programs. The experiment was conducted in an augmented block design using six blocks at the Agriculture Research Farm, Hazara University, Mansehra. Data on 9 morpho-yield related traits were analyzed using Analysis of Variance (ANOVA), principal component analysis (PCA), cluster analysis, and correlation analysis. Highly significant differences (p<0.001) were observed for treatments, and 'Checks vs. Varieties' highlights considerable genetic variability in the germplasm. Adjusted means performance revealed that Atika-09 (1947.5 kg ha^-1), Atika-11 (2427.3 kg ha⁻¹), and Mehraj-10 (1502.4 kg ha^-1) showed superior performance across important yield and adaptive traits. PCA revealed that seed yield (PC1) and disease incidence (PC2) accounted for 49.29% of the variation among genotypes. Cluster analysis grouped the genotypes into two clusters, dividing them into 4 groups and 8 subgroups, with group A1 comprising superior lines for yield stability and resistance. Seed yield showed a strong positive correlation with plant height (r = 0.54**), head diameter (r = 0.36**), and harvest index (r = 0.92**). The results demonstrate that phenotypic selection, supported by multivariate analysis, can effectively accelerate the development of resilient high-yielding sunflower hybrids for Pakistan’s cropping systems. These findings provide a valuable genetic foundation for breeding programs targeting resilience and yield stability in sunflowers.