Early selection of grain quality traits in rice (Oryza sativa L.), is essential to improve the yield and quality of this staple crop. We analyzed four key traits—protein content, grain filling rate, height, and panicle length—in 85 Korean cultivars. Through whole- genome resequencing we identified 12,718,879 raw single nucleotide polymorphisms (SNPs); after PLINK-based quality control (bi-allelic selection, call rate≥0.90, MAF≥0.03), ~2.20 million high-quality SNPs remained for machine-learning (ML) pre-screening. To rank the features (without marker-level inference), we applied a liberal univariate PLINK case-control scan using the top and bottom 30% per trait. We also analyzed associations with a linear mixed model (GCTA v1.93.2, MLMA; fixed covariates: ecotype, PC1, PC2; random effect: GRM) to verify calibration under population structure; with n=85, no genome-wide significant hits were detected, and QQ-plots indicated adequate calibration (per-trait effective tests m≈1.54-1.57 million under stricter filters). The random forest feature importance prioritized 26, 51, 19, and 20 core SNPs for the four traits, respectively. Across the algorithms, the best models achieved mean accuracies of 81.8% (protein content), 81.0% (grain filling rate), 73.1% (height), and 94.0% (panicle length). All selected SNPs met the Fluidigm array design requirements, supporting its deployment as a compact, genotype-based panel for early selection and a practical step toward digital breeding in rice.

Breeding wheat cultivars with high nitrogen use efficiency is crucial for sustainable agriculture. In this study, 130 durum wheat accessions from 53 countries were cultivated under two nitrogen fertilization levels to investigate variations in agronomic traits and identify accessions suitable for low-nitrogen conditions. Under no nitrogen fertilization, SPAD value (-99.2), flag leaf length (−15.8 mm), grain area (−0.52 mm²), grain length (−0.27 mm), thousand-grain weight (+5.2 g), and grain protein content (−4.2%) showed significant differences compared to that under standard nitrogen fertilization. Among these traits, the SPAD value exhibited a strong positive correlation with protein content in the absence of nitrogen fertilization, suggesting its potential as an indicator for selecting germplasm with superior nitrogen use efficiency. Hierarchical cluster analysis, based on the differences in the six traits under the two nitrogen fertilization levels, classified the 130 durum wheat accessions into three groups (Groups 1, 2, and 3). Accessions in Group 2 exhibited superior adaptability under no nitrogen fertilization compared with those in the other two groups. We identified seven accessions in Group 2 that exhibited minimal decreases in SPAD values and protein content under no nitrogen fertilization for use in wheat breeding programs aimed at developing cultivars with high nitrogen use efficiencies.

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.