The use of principal component analysis (PCA) in the selection of bread wheat (Triticum aestivum L.) genotypes under kahramanmaraş conditions

Abstract:

In this study, grain yield and yield-contributing agricultural traits of 50 different bread wheat genotypes (1 standard cultivar Germenicia and 49 advanced lines) were investigated, and the relationships between traits and genotypes were evaluated using Principal Component Analysis (PCA) and correlation analysis. The research was conducted during the 2024-2025 growing season at the experimental fields of the Eastern Mediterranean Transitional Zone Agricultural Research Institute in Kahramanmaraş, Turkey. Results showed significant variations among genotypes: plant height ranged from 84.00 to 106.33 cm, spike length from 8.78 to 12.88 cm, number of spikelets from 16.00 to 22.00, number of kernels per spike from 30.80 to 91.40, grain weight per spike from 1.50 to 2.81 g, and grain yield from 416.42 to 632.49 kg/da. Correlation analysis revealed a statistically significant positive relationship (r=0.416) between grain yield and plant height, while spike characteristics exhibited high internal correlations ranging from r=0.478 to 0.683. Principal Component Analysis indicated that 71.35% of the total variance was explained by the first two principal components. The First Principal Component (F1), explaining 46.97% of the variance, was defined as the "Spike Yield Components", whereas the Second Principal Component (F2), explaining 24.38%, was designated as the "Total Yield and Vegetative Growth" axis. As a result of the research, lines 208 and 209 demonstrated superiority in terms of spike size and architecture. Conversely, lines 244, 225, 233, and 207 stood out regarding maximum grain yield per unit area, manifesting excellent adaptation to the transitional zone ecology and highlighting their potential as strong cultivar candidates for future breeding programs.