Introduction
Crop development and breeding are critical for ensuring food security, improving nutritional quality, and mitigating the impact of changing climate. However, these processes are inherently complex, requiring the evaluation and selection of genotypes based on multiple traits. In this context, the Multi-traits Genotype-Ideotype Distance Index (MGIDI) and the Selection Index of Ideal Genotype (SIIG) have emerged as robust and versatile tools for identifying superior genotypes across a range of traits. These multivariate selection indices consolidate information from various agronomic characteristics into a single value, allowing for the effective ranking of genotypes based on their distance from an ideal genotype. The present study aimed to identify promising bread wheat genotypes using the MGIDI and SIIG indices, with a focus on yield and other key agronomic traits.
Material and Methods
 In this study, 14 promising wheat lines - selected from the wheat breeding program of the Rainfed Agriculture Research Institute and provided by the ICARDA international research center – along with two check cultivars, were evaluated using a randomized complete blocks design (RCBD) with three replications. The experiment was conducted at the Sarab-Chengaei research station during the 2021-2023 cropping seasons. Each experimental plot consisted of eight cropping rows, each 6 meters long, spaced 15 cm apart, with a seeding density of 350 seeds per square meter. Fertilization was applied based on soil chemical analysis. The traits measured included days to heading, days to maturity, plant height, 1000-kernel weight, grain filling period, peduncle length, grain filling rate, awn length, number of spikelet per spike, spike density, number of grains per spike, grain weight per spike and grain yield. All plots were harvested using an experimental grain harvester.
Results and Discussion
Combined variance analysis revealed that genotype effects were significant for days to heading, days to maturity, grain filling period, spike length, awn length, spike density and 1000-kernel weight. Genotypes G15, G14, G2, G10, and G8 recorded the highest grain yield, averaging 4169, 3911, 3907, 3870 and 3809 kg ha^-1, respectively. Based on the MGIDI index, lines G2 and G15 were identified as desirable genotypes. Factor analysis extracted five factors that collectively explained 88.9% of the total phenotypic variation among genotypes. According to the SIIG index, genotypes G2, G15 and G9 were superior, exhibiting the highest SIIG values. A positive and significant correlation was observed between grain yield and number of grains per square meter, grain filling rate, and peduncle length, indicating that these traits play a key role in enhancing yield performance. Cluster analysis classified the genotypes into three main clusters: Class 1 included early-maturing genotypes with low yield; Class 2 comprised genotypes with later maturity and low yield; and Class 3 contained early- maturing genotypes with high yield potential.
Conclusion
Line G15 and the Qaboos cultivar, which had the lowest MGIDI values and yields above the average of all genotypes, were identified as ideotypes based on the MGIDI index. According to the SIIG index, lines G15 and G9, along with the Qaboos control cultivar, were recognized as the top-performing genotypes. Therefore, line G15 is recommended for use in future breeding programs or as a promising candidate for cultivar release. The high yield performance of the Qaboos cultivar further supports its suitability for cultivation in regions with climatic conditions similar to those of the experimental site.