Work

MULTIVARIATE ANALYSIS OF GENERAL COMBINING ABILITY EFFECTS IN LINSEED (Linum usitatissimum L.) USING PRINCIPAL COMPONENT ANALYSIS AND HIERARCHICAL CLUSTERING

Year: 2026

Type: article

Abstract: Principal Component Analysis (PCA) and Ward's hierarchical clustering were applied to the General Combining Ability (GCA) matrix of 10 linseed (Linum usitatissimum L.) parents (4 lines × 6 testers) across 15 agronomic and oil-quality traits (rabi 2024–25). Three principal components explained 81.86% of total variance: PC1 (47.60%) represented a yield–agronomic axis, PC2 (21.55%) captured a fatty-acid axis reflecting Δ-15 desaturase antagonism and PC3 (12.71%) separated palmitic acid from seeds per capsule. SHA-7 exhibited the highest yield-GCA (PC1 score +4.93), while Varsa Alsi showed unique high-ω-3 GCA (PC2 score −4.19). Four parent clusters and four trait clusters were identified. The MGIDI ranked Varsa Alsi first (1.295) and SHA-7 second (4.633), confirming SHA-7 × Varsa Alsi as the optimal cross for simultaneous yield and ω-3 improvement

Source: PLANT ARCHIVES

DOI: 10.51470/plantarchives.2026.v26.supplement-2.257