Introduction

Iron (Fe) deficiency is a major nutritional constraint in calcareous soils of arid and semi-arid regions, where high soil pH and low iron solubility severely restrict plant iron uptake. This deficiency leads to chlorosis, reduced photosynthetic capacity, and substantial yield losses in cereal crops. Durum wheat (Triticum durum L.) is widely cultivated in dry environments due to its relative tolerance to heat and water scarcity; however, its productivity is still strongly affected by micronutrient limitations, particularly iron deficiency. Considerable genetic variation exists among durum wheat genotypes in their ability to tolerate iron-deficient conditions, which provides an opportunity for genetic improvement through breeding. Selection based solely on grain yield under stress conditions is often inefficient because yield performance varies across environments. Therefore, the use of stress tolerance indices derived from grain yield under both stress and non-stress conditions has been proposed as an effective approach for identifying superior and stable genotypes. The present study aimed to evaluate the response of a diverse set of durum wheat genotypes to iron deficiency stress, to identify the most efficient tolerance indices, and to select superior genotypes suitable for cultivation and breeding programs in arid regions.

Materials and Methods

A total of 121 durum wheat genotypes were evaluated over two consecutive growing seasons (2022–2023 and 2023–2024) at the Agricultural Research Station of Zabol, located in an arid region of southeastern Iran. The experimental site was characterized by calcareous soil with low available iron content. Two contrasting environments were considered: optimal iron supply, achieved by applying 20 kg ha⁻¹ iron chelate at the first irrigation, and iron-deficient conditions without iron application. Experiments were conducted using an augmented design with five check cultivars replicated across blocks in each environment. Genotypes were sown in rows with standard agronomic practices, and grain yield was measured on a per-plant basis at physiological maturity. Sixteen stress tolerance indices were calculated based on grain yield under optimal (Yp) and iron-deficient (Ys) conditions. Statistical analyses included Welch’s t-test for comparing mean grain yield between environments, Pearson correlation analysis to evaluate relationships among indices and yield, three-dimensional Fernandez plots for genotype classification, principal component analysis (PCA) for dimensional reduction, biplot visualization, and hierarchical cluster analysis using Ward’s method. All analyses were performed using R software reduction, biplot visualization, and hierarchical cluster analysis using Ward’s method. All analyses were performed using R software.

Results

Iron deficiency stress caused a significant reduction in grain yield across genotypes, confirming the strong impact of this nutritional stress under arid soil conditions. Despite this reduction, a wide range of variation was observed for grain yield in both environments, indicating substantial genetic diversity among the evaluated genotypes Correlation analysis revealed that several indices were significantly associated with grain yield under both optimal and stress conditions. Among them, geometric mean productivity (GMP), harmonic mean (HM), mean relative performance (MRP), and the modified stress tolerance indices K1STI and K2STI showed strong and positive correlations with grain yield in both environments, indicating their high efficiency for identifying tolerant and high-yielding genotypes. The three-dimensional Fernandez plot classified genotypes into four distinct groups, clearly separating genotypes with high and stable yield in both conditions from sensitive ones. PCA results showed that the first two principal components explained more than 96% of the total variation. The first component was associated with yield potential and simultaneous tolerance, while the second component represented sensitivity to iron deficiency. Biplot analysis confirmed the close association of superior genotypes with GMP, HM, MRP, K1STI, and K2STI. Hierarchical cluster analysis grouped genotypes into four clusters. The fourth cluster, consisting of genotypes G36, G39, G42, G53, G54, and G115, exhibited the highest grain yield under iron-deficient conditions and superior performance across most tolerance indices.

Conclusion

The results of this study demonstrated that iron deficiency significantly reduces grain yield in durum wheat while substantial genetic variation exists for tolerance to this stress. The combined use of stress tolerance indices and multivariate statistical analyses proved to be an accurate and reliable approach for screening iron-deficiency-tolerant genotypes. Among the evaluated indices, GMP, HM, MRP, K1STI, and K2STI were identified as the most efficient for simultaneous selection under optimal and iron-deficient conditions. Based on consistent performance across different analytical methods, genotypes G36, G39, G42, G53, G54, and G115 were identified as superior and stable under iron deficiency stress. These genotypes can be recommended as valuable genetic resources for breeding programs aimed at improving durum wheat productivity and adaptation in arid and calcareous soil conditions.