Introduction
Wheat is one of the strategic crops worldwide in terms of human food consumption. Improved yield in grain as well as its quality for processing into flour for human consumption are the two major goals of any breeding program for ensuring food security particularly in developing countries. High baking quality is essential for producing acceptable bread and reducing post-baking losses. The use of molecular markers has facilitated the identification of genotypes with superior baking properties. Among these markers, seed storage proteins provide reliable indicators for assessing flour functionality. Gluten, the principal protein complex responsible for wheat dough properties, consists of gliadins and glutenins, which contribute differently to dough behavior. Glutenins primarily determine dough elasticity and strength, whereas gliadins influence viscosity and extensibility. The allelic diversity in gliadin proteins has been used as a marker system to characterize germplasm and to predict the baking quality of wheat. As a result, gliadin markers have become important tools for breeding wheat which has the processing properties and end-use quality that are required by growers and end-users.

Materials and Methods
In this study, gliadin banding profiles of 40 wheat genotypes—including 28 F₆ recombinant inbred lines from the Zagros × Norstar cross and 10 commercial cultivars—were characterized using A-PAGE vertical acrylamide gel electrophoresis. Marquis wheat band no. 50 served as the reference marker for scoring. Protein bands were visually identified, and their presence or absence was recorded as binary data. To determine the functional relevance of gliadin variation, associations between gliadin subunits (ω, γ, β, and α) and key bread-making quality parameters were analyzed. The evaluated traits included hectoliter weight, thousand-grain weight, protein content, Zeleny value, loaf volume, moisture, water absorption, wet gluten, gluten index, SDS sedimentation, and grain hardness. Stepwise linear regression was applied to identify gliadin bands significantly contributing to variation in quality traits. Additionally, Spearman correlation coefficients were calculated to assess relationships among gliadin bands and their potential co-inheritance patterns.

Results and Discussion
The results revealed both significant positive and negative correlations among gliadin protein bands, with several pairs such as 6 and 9, 20.5 and 27.5, 29 and 34.5, and 34.5 and 37 showing complete correlation, indicative of block inheritance within specific gene families. Five bands across the ω, γ, β, and α fractions were significantly associated with grain hardness, loaf volume, wet gluten content, and grain weight. Four bands showed significant relationships with protein percentage and hectoliter weight. Six bands were linked to SDS sedimentation volume, gluten index, and moisture absorption. Furthermore, seven bands exhibited significant associations with Zeleny sedimentation value and grain moisture content at the 5% and 1% significance levels, highlighting the predictive potential of gliadin markers for bread-making quality. Strong and significant correlations were also observed between some gliadin protein bands with several traits and several traits with a specific gliadin band. The existence of such relationships is important in breeding programs.

Conclusion
The findings highlighted the dominant contribution of ω- and α-gliadin fragments to key traits underlying bakery quality, underscoring their value in quality assessment. Several gliadin bands showed simultaneous associations with multiple traits, indicating their pleiotropic effects. These alleles therefore represent reliable molecular indicators for identifying superior genotypes. Consequently, they can be effectively integrated into selection strategies aimed at improving bakery quality.