The composition of high-molecular-weight-glutenin subunits (HMW-GS) is a key determinant of wheat baking properties. These subunits are encoded by the GLU-A1, GLU-B1, and GLU-D1 loci on the long arm of chromosome 1 and consist of x- and y-type subunits. Allelic variations in composition are a major factor influencing bakery quality. Unlike sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) or ultra-performance liquid chromatography (UPLC), which often fail to resolve closely related allelic variants, PCR-based markers allow for clear and definitive discrimination at the DNA level. Building on the results of a previous study that determined the GLU-B1 allele composition, we aimed to confirm—through the use of PCR markers—the allele compositions of GLU-A1 and GLU-D1 in 44 domestic wheat varieties. The results showed that “Jonong” and “Sinmichal1” contained the Glu-A1b (A1x2*) allele rather than Glu-A1a (A1x1) or Glu-A1c (A1x-null). Additionally, “Jonong” and “Sinmichal1” exhibited the allelic composition Glu-D1a (D1x2+D1y12), rather than Glu-D1d (D1x5+D1y10) or Glu-D1f (D1x2.2+D1y12). These results were compared with those obtained by SDS-PAGE and UPLC. The PCR-based markers used to identify GLU-A1 and GLU-D1 alleles in this study will be valuable for determining the allelic composition at the GLU-A1 and GLU-D1 loci in domestic wheat varieties. Furthermore, the re-evaluated genetic composition is expected to improve the precision of assessments related to the baking quality of domestic wheat.

In common wheat (Triticum aestivum L.), the protein content and glutenin protein composition are the key quality-determining parameters. Allelic variations, especially in high-molecular-weight glutenin subunits (HMW-GSs), affect bread quality significantly. The HMW-GS Glu-1 locus consists of two tightly linked genes encoding x- and y-type subunits that exhibit highly variable frequencies. In this study, we evaluated Glu-B1 alleles using allele-specific PCR markers in 44 domestic wheat cultivars. The composition of Glu-1Bx7+Glu-1By8 in the 24 cultivars was either Glu-1Bx7+Glu-1By8, Glu-1Bx7*+ Glu-1By8, or Glu-1Bx7*+Glu-1Bx8*. In addition, the two cultivars initially identified Glu- 1Bx7+Glu-1By8* were corrected to Glu-1Bx7*+Glu-1By8*. Seven cultivars previously classified as having Glu-1Bx7+Glu-1By9 composition contained Glu-1Bx7*+ Glu-1Bx9. The allele composition of the cultivar was identified as Glu-1Bx20+Glu-1By20 instead of Glu-1By20. The HMW-GSs of 21 wheat varieties were analyzed using ultra-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis. These results will be helpful for evaluating the composition of Glu-B1 alleles in domestic wheat and accurately assessing the quality of domestic wheat flour.

Fusarium head blight (FHB) causes yield reduction, quality deterioration, and mycotoxin contamination in wheat, highlighting the need for resistant wheat varieties. In this study, we evaluated FHB resistance genes and infection rates in 44 domestic wheat varieties. Among them, 42 had the Type I resistance gene Fhb4, 37 had Fhb5, and 35 possessed both. For Type II resistance, 14 had Fhb1, 11 had Fhb2, and five had both. Twenty cultivars had both type I and type II resistance genes, and among them, Chungkye, Dahong, Gobun, Namhae, and Ol had all of the Fhb1, Fhb2, Fhb4, and Fhb5 genes. The average infection rate over three years was 42.6% in cases with both Type I and Type II resistance genes and 44.3% in cases without Type II resistance genes. The infection rate was very high in 2020 and very low in 2021, complicating the analysis of the three-year average. However, when the infection rate was evenly distributed in 2019, there was a tendency for increased resistance among the varieties carrying Type II resistance genes. This suggested that external factors may influence infection rates, emphasizing the need for a precise evaluation system suitable for selecting additional resistance genes. In addition, it is necessary to develop resistant varieties suited to the domestic environment through additional resistance gene selection and integration of resistance genes. This study contributes to understanding FHB resistance genes in domestic wheat varieties and developing resistant domestic wheat varieties.

To stably produce domestic wheat under water-scarce environmental conditions due to climate change, root characteristics with excellent water utilization rates are crucial. In this study, we analyzed the root and grain phenotypes of 37 domestic wheat varieties over a two-year period by combining the results of genetic mutations related to semi-dwarfing and grain size. Root length was positively correlated with maximum root depth (r=0.76**) and total seminal root length (r=0.54**), whereas it was negatively correlated with the number of roots (r=-0.33**) and root angles (r=-0.51**). The thousand-kernel weight was positively correlated with embryo width (r=0.34**) and embryo area (r=0.33**) but was not correlated with other root traits. Embryo length was positively correlated with the number of roots (r=0.34**) and coleoptile length (r=0.42**). Phenotypic analyses of roots and grains, along with genotypic analyses of semi-dwarfing (Rht-B1 and Rht-D1) and grain size (TaCWI-4A, TaCWI-5D, TaGW2-6A, TaSus2-2B) genes, revealed that the Rht-D1b genotype led to reduced root depth, increased root angles, and reduced coleoptile length. TaCwi-A1, TaCWI-5D, TaSus2-2B, and TaGW2-6A, possessing the alleles TaCwi-A1a, Hap-5D-C, Hap-L, and Hap-6A-G associated with a larger grain size, resulted in an increased number of roots and root depth. Domestic wheat varieties were categorized into three clusters based on root, grain, and coleoptile trait characteristics, with 15 varieties in Cluster I, 9 in Cluster II, and 13 in Cluster III. The results of this study can be utilized in basic research to develop varieties that can produce stable domestic wheat by selecting resources with excellent root growth and seed characteristics.

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.