Gluten proteins in wheat grains are generally considered one of the most important factors in determining dough properties and bread quality. In this study, wheat protein quality characteristics were investigated in 607 varieties collected from seven countries grown in a South Korean wheat breeding field for two years. The average protein content was 12.2±1.86%, and the sodium dodecyl sulfate-sediment volume (SDSS) was 46.9±8.39 mL. HI-LINE had the highest protein content (18.3±0.35%) and SDSS (76.7±1.98 mL), while both NE 84557 and Iksan 374 showed small deviations in protein content and SDSS. Protein content and SDSS values were higher in Ax2*+By8 and By9+Dy10 combinations at Glu-A, Glu-B1, and Glu-D1 loci of high molecular weight gluten subunit (HMW-GS) than in other combinations. However, no difference in Glu-A3 and Glu-B3 loci in LMW-GS was observed. Furthermore, in HMW-GS, the composition of Glu-D1 Dy10 and Dy12 had a greater effect on protein quality than Glu-B1 By8 and By9 when the allele of Glu-A1 had Ax2*. Significant differences were found between Dy10 and Dy12 genes of the HMW-GS Glu-D1 and between protein content and SDSS, but not among others. These results suggest that Glu-D1 is extremely important for improving protein quality in HMW-GSs. As a result of this study, HMW-GS allele selection using functional markers, protein content, and SDSS investigation are expected to enable the development of varieties with high protein quality that are stable amid various environmental changes.

Low-temperature damage at the seedling stage is one of the most significant natural obstacles to wheat’s growth. In domestic wheat breeding programs, the selection of cold-tolerant varieties is crucial for the development of superior wheat varieties. Traditionally, the extent of damage caused by freezing wheat is estimated through visual observation. In this study, we compared the RGB image analysis method with conventional visual evaluation and chlorophyll content analysis methods to determine if this method could accurately quantify the cold tolerance discrimination of wheat in the field. First, single-leaf-level RGB image analysis revealed a pattern similar to dead leaf ratio and chlorophyll content in three grades of freezing injury. Next, we compared the significance of plant-level RGB image analysis. The greenness index by RGB image analysis showed a higher correlation with dead leaf ratio by visual evaluation. Finally, 40 wheat varieties were planted in the field and wheat canopy images were collected at the seedling stage after wintering. There was a high correlation between the greenness index and the visual evaluation. However, there was no correlation between dead leaf ratio and visual evaluation or greenness index as determined by RGB image analysis. These findings suggest that using RGB image analysis rather than visual evaluation can be useful in assessing freeze damage in wheat fields.