Introduction
The multigenic and environmentally sensitive nature of drought tolerance presents significant challenges for the selection and breeding of superior genotypes in oilseed sunflower. Effective evaluation of drought tolerance relies on the simultaneous assessment of multiple traits across various environments, necessitating robust multi-trait selection methods.
 Materials and Methods
The study evaluated 100 oilseed sunflower genotypes for 13 agronomic and physiological traits under both normal and limited irrigation (drought stress) conditions, employing a simple 10×10 lattice design during the 2013 and 2014 growing seasons in Qezeljeh village, Salmas. Drought stress was imposed at the 8-leaf stage using a class A evaporation pan: plots received irrigation after 90 mm (normal) or 10 mm (drought) of evaporation. The measured traits included plant height (cm), leaf length (cm), leaf width (cm), petiole length (cm), stem diameter (cm), head diameter (cm), number of leaves, greenness index (SPAD), days to flowering, days to maturity, relative water content, seed oil content, and seed yield per plant.  The multi-trait genotype-ideotype distance index (MGIDI) was employed for selection, and data were analyzed using the metan package in R.
 Results and Discussion
Multivariate analysis of variance revealed significant effects of environment, genotype and their interaction under both irrigation regimes, indicating broad genetic diversity. Factor analysis identified five principal factors (eigenvalues >1) under normal conditions, and four under drought, explaining 75% and 69.1% of total trait variation, respectively.
Under normal irrigation, the first factor (eigenvalue:  4.8) included leaf length, leaf width, petiole length, stem diameter, head diameter and seed yield. Subsequent factors were associated with relative water content, flowering and maturity timing, greenness index, leaf number, plant height, and oil content. Under drought stress, the first factor (eigenvalue: 4.45) comprised similar morphological and yield traits, with other factors grouping relative water content, phenological traits, oil content, leaf number, plant height, and greenness index.
Principal component analysis of genotype-by-environment interaction revealed three and four components (eigenvalues >1) under normal and drought stress, explaining 62.3 and 71.4% of the variation, respectively. Under normal conditions, the eigenvalues of the first three factors were 1.81, 1.07, and 1.03, respectively, and under drought stress conditions, the eigenvalues of the first four factors were 4.5, 2.24, 1.23, and 1.06, respectively. The MGIDI index identified five genotypes (254-ENSAT), (AS3232), (ENSAT699), (HA304), and (SDB1) exhibited the greatest genetic distance, indicating their potential for breeding drought-tolerant hybrids through heterosis.
 Conclusion
The MGIDI provides a comprehensive approach for multi-trait selection and clustering of sunflower genotypes under both normal and drought conditions. The identification of genotypes with high genetic divergence offers valuable material for developing drought-tolerant hybrids, leveraging the benefits of heterosis for improved crop resilience.