Mung bean (Vigna radiata) is a rich natural source of vitexin and isovitexin—flavonoids known for their potential anti-inflammatory properties. The aim of this study was to evaluate, through the use of RAW 264.7 macrophages, the anti-inflammatory effects of extracts from mung bean seeds containing vitexin and isovitexin. High-performance liquid chromatography (HPLC) was employed to quantify the levels of these compounds in various mung bean cultivars: “Jinhwang,” “Samhwang,” “Seonhwa,” and “Jangan,” as well as “Dahyeon,” and “Sanpo,” two of the most widely cultivated varieties in Korea. Cytotoxicity assays revealed no significant toxicity at concentrations of 25, 50, and 100 µg/mL, allowing further analysis at these levels. In nitric oxide (NO) inhibition assays, “Samhwang” (10.61 µM) and “Seonhwa” (9.7 µM) demonstrated the highest NO-suppressing activity at 50 µg/mL. Tumor necrosis factor-alpha (TNF-α) levels were significantly reduced by “Seonhwa” (83.6 pg/mL) and “Jangan” (72.3 pg/mL), with “Jangan” showing the strongest inhibitory effect. Interleukin-6 (IL-6) analysis revealed notable suppression in “Samhwang,” “Seonhwa,” and “Jangan” at 50 µg/mL, with “Samhwang” exhibiting the most potent effect (78.6 pg/mL). These findings suggest that the “Samhwang” cultivar, in particular, possesses significant anti-inflammatory potential and may serve as a valuable candidate for the development of natural anti-inflammatory agents.

A comprehensive evaluation of 515 Korean wheat germplasms, including cultivars, experimental lines, and landraces, was conducted over 2 years under upland field conditions to characterize major agronomic and grain traits. Allelic variation at 13 key functional loci was assessed using Kompetitive Allele-Specific PCR (KASP) and PCR-based markers. The winter-type vrn-A1 with a single copy (CNV=1; 40.2%) advanced heading by approximately 5 days compared to multiple-copy genotypes, and winter-type vrn-B1 (88.5%) advanced heading by 2 days compared to the spring-type. The photoperiod-insensitive alleles Ppd-B1a (5.6%) and Ppd-D1a (76.3%) advanced heading by 3 and 4 days, respectively, with a combined effect of up to 6 days. Semi-dwarfing alleles Rht-B1b and Rht-D1b showed reduced culm lengths of 2.1 cm and 4.7 cm, respectively, and the Rht-B1a/Rht-D1b genotype was 6 cm shorter than Rht-B1a/Rht-D1a. The Pina-D1a/Pinb-D1a genotype had the lowest kernel hardness value (32.2), whereas Pina-D1b/Pinb-D1a had the highest (60.5). The thousand kernel weight ranged from 36.1 mg to 42.5 mg depending on the allelic combinations of TaCwi-A1, TaGW2-6A, and TaSus2-2B. Cultivars and experimental lines were clearly distinguished from landraces based on phenotype-based clustering, with the majority of cultivars (81.6%) and experimental lines (68.3%) grouped into cluster III. In contrast, landraces were predominantly distributed in clusters I (55.1%) and II (29.2%). Random forest analysis identified four genes, Ppd-D1, Pina-D1, Pinb-D1, and WAPO-A1, as major contributors to cluster classification. Cluster III was highly enriched with alleles favorable for earliness (Ppd-D1a, 98.3%) and grain hardness (Pina-D1b and Pinb-D1b, 57.9%). WAPO-A1b, an allele associated with an increased spikelet number per spike, was more frequently observed in clusters I (94.6%) and II (79.1%) than in cluster III (58.4%).

In this study, we established a system to analyze and accurately distinguish changes in the metabolite content of mung bean sprouts at various growth stages. Specific regions of the FT-IR spectrum (1700–1500 cm^-1, 1500–300 cm^-1, and 1100–950 cm^-1) reflected qualitative and quantitative changes in key metabolites, such as amino acids, proteins, nucleic acids, lipids, and sugars. These regions play crucial roles in assessing metabolic changes at different growth stages. The results of the PCA revealed that metabolite clusters were distinctly separated according to growth stage, with notable differences observed between days 7, 10, 14, and 17. This indicated significant differences in metabolite changes across growth stages. PLS-DA analysis also confirmed similar results, clearly distinguishing metabolite changes according to growth stage, thus providing valuable information for identifying growth stages. This technique can be an important tool in the selection and breeding of mung bean varieties and can contribute to the development of functional materials. Furthermore, it is expected to contribute significantly to enhancing mung bean productivity and research on functional substances.

This study used perilla seeds produced in 2019, 2020, and 2021 to determine the year of production using multivariate statistical analysis of Fourier-transform infrared (FTIR) spectral data of perilla leaves. Spectral analysis based on multivariate statistical analysis of whole-cell extracts was used to distinguish the perilla leaves at the metabolic level. FT-IR spectral data of the leaves were analyzed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The FTIR spectrum identified spectral differences between the frequency regions of 1,700 to 1,500, 1,500 to 1,300, and 1,100 to 950 cm^-1. This spectral region reflects quantitative and qualitative changes in amides I, II in amino acids and proteins (1,700–1,500 cm^-1), phosphodiester groups from nucleic acids and phospholipids (1,500–1,300 cm^-1), and carbohydrate compounds (1,100–950 cm^-1). PCA revealed separate clusters corresponding to production traceability relationships. Therefore, PCA can be used to distinguish between production in 2019, 2020, and 2021 based on different metabolite contents. PLS-DA showed a similar production traceability classification for the perilla seeds. In addition, this metabolic identification system can be used to rapidly select and classify useful perilla seed varieties.

To better understand the morphological variation in the 189 accessions of cultivated var. frutescens of Perilla crop preserved at the RDA-Genebank in South Korea, morphological characteristics were investigated using seven traits related to leaf quality. In the principal component analysis (PCA), the first and second principal components accounted for 28.9% and 19.7% of the total variance, respectively. In the first component, leaf color (QL1) and stem color (QL3) contributed positively, whereas the flowering period (QL5) and degree of pubescence (QL6) contributed in a negative manner. In the second component, QL5 and QL6 contributed positively, whereas the fragrance of plants (QL7) contributed negatively. The results of PCA showed that the 189 Perilla accessions were clearly divided into three groups based on the 1st axis (X-axis), except for some accessions. However, the Perilla accessions collected in South Korea and abroad did not show a clear geographical distribution between the collection areas. Correlation analysis among the seven traits of 189 Perilla accessions showed a positive correlation coefficient for the combination of QL1 and QL3, and QL5 and QL6, and a negative correlation for the combination of color of the reverse side of the leaf and QL6, and QL5 and QL7. Therefore, the results of this study will provide useful information for the selection of useful resources for the development of leafy vegetable varieties of the Perilla crop and the preservation and management of genetic resources of the Perilla crop preserved at the RDA-Genebank in South Korea.

In this study, 14 agricultural and phenotypic traits were used to analyze morphological variations among 10 near-isogenic lines (NILs) of colored waxy maize and 2 parental lines (HW3 and HW9) of the hybrid cultivar “Mibaek 2.” The results of principal component analysis indicated that on the first principal component axis, seed coat color, R value, V value, days of tasseling, L* value, and days of silking greatly contributed to the positive direction, whereas anthesis–silking interval and leaf width greatly contributed to the negative direction. On the second principal component axis, kernel row number and tassel color contributed to the positive direction, whereas setted ear length, ear length, and 100-kernel weight contributed to the negative direction. Thus, the morphological characteristics that greatly contributed to the first and second principal components might be useful for discrimination among the 10 NILs and 2 parental lines of “Mibaek 2.” Of the 10 NILs analyzed, 16CLP26 and 16CLP16 were considered useful breeding material for the development of colored waxy maize varieties with relatively high amounts of yield and anthocyanin. Collectively, these results are expected to provide useful information for the development and selection of lines for breeding colored waxy corn varieties at the Maize Research Institute, Gangwon-do Agricultural Research and Extension Services.

FT-IR spectroscopy, combined with multivariate analysis, was used to determine whether 67 different wild and rootstock peach accessions could be discriminated from each other. Genomic DNA was isolated from leaves, and the purified genomic DNA was analyzed by FT-IR spectroscopy in the spectral region from 1800 to 800 cm^-1. FT-IR spectra showed that typical spectral differences existed in the frequency regions of N-H stretching (amide I), C=O stretching vibrations (amide II), and PO₂⁻ ionized asymmetric and symmetric stretching. Principal component analysis (PCA) was able to discriminate three groups. The partial least squares discriminant analysis (PLS-DA) yielded more clear discrimination among the three groups of peach accessions. The FT-IR spectral differences might be directly related to subtle changes in the base functional group and backbone structures of genomic DNA. This technique could provide a research foundation for FT-IR spectral-based rapid diagnosis, selection, and discrimination of peach accessions for rootstock.

The International Union for the Protection of New Varieties of Plants (UPOV) promotes an effective system of plant variety protection and encourages the development of new varieties of plants. This international convention was initiated to standardize the system efforts and strengthen policy. The establishment of cultivar discrimination system is very important to distinguish varieties between domestic and foreign agricultural products. It is necessary for the protection of breeders’rights. In addition, it will help for more efficient and quality management of plant breeding. This study was conducted to identify and group rice varieties based on agro-morphological characteristics such as plant height, panicle length, number of tillers, culm length, leaf length, leaf width, leaf pigments and flag leaf angles. Using these parameters, statistical analysis classified a total of 243 rice varieties bred in Korea into four groups. Most rice varieties did not exhibit anthocyanin pigments on the leaves particularly on the first leaf, leaf blade, leaf sheath and auricle, except for varieties classified as black rice. Results of phylogenetic and principal component analysis (PCA) indicated that these varieties formed three largely distinct clusters according to their ecotype and morphological differentiation. This result would be useful in rice varietal identification for the protection of breeders’variety rights.

In order to develop a core set and new corn variety in Korea, we evaluated the morphological characteristics of 194 maize accessions by examining eight quantitative characteristics. On the evaluation of quantitative traits for 194 maize accessions, they showed the morphological variations in tassel length (35.1±5.0 cm), plant height (226.1±33.7 cm), ear height (86.3±22.6 cm), stem diameter (2.3±0.6 cm), leaf width (9.3±1.1 cm), ear length (14.5±2.4 cm), ear row number (14.1±1.9 row), and 100 kernel weight (24.9±4.4 g). The results of principal component analysis (PCA) indicated that the tassel length, plant height, and ear height greatly contributed to positive direction on the first principal component axis. One-hundred kernel weight contributed to negative direction on the second principal component axis. Thus these morphological characteristics, which contributed greatly in the first and second principal components, might be useful for discrimination among 194 maize accessions. In our study, seven accessions, such as IT026357, IT026441, IT027321, IT033271, IT033591, IT033597 and IT124273, particularly were measured high on yield-related traits. Consequently, the 194 maize accessions used in this study could be used as promising materials for maize breeding programs such as development of new hybrid in Korea.