This study was conducted from 2021 to 2024 at the Grassland and Forage Division, National Institute of Animal Science, Rural Development Administration, Korea, to develop a high-yielding, medium-maturing Italian ryegrass (Lolium multiflorum Lam.) cultivar. The newly developed cultivar, named ‘Aura’ is a tetraploid type characterized by green leaves, a semi-erect growth habit before winter, and an erect growth habit during spring growth. ‘Aura’ headed on May 11, approximately 10 days later than the check cultivar ‘Kowinearly’, confirming its classification as a medium-maturing cultivar. At the heading stage, plant height reached 105 cm, which was greater than that of the control cultivar. In addition, leaf blade width, spike length, and spikelet number were greater in ‘Aura’ indicating vigorous growth. The average dry matter yield of ‘Aura’ across four regions was 10,535 kg/ha, which was significantly higher than that of ‘Kowinearly’ (p<0.05). The crude protein content of ‘Aura’ was 10.5%, which was 2.2 percentage points higher than that of the check cultivar. In contrast, acid detergent fiber and neutral detergent fiber concentrations were lower in ‘Aura’ resulting in slightly greater total digestible nutrient content and relative feed value. Furthermore, ‘Aura’ maintained stable winter survival across all test locations. These results indicate that ‘Aura’ is a promising medium-maturing cultivar with high productivity, stable winter hardiness, and favorable forage quality for cultivation in Korea.

Alfalfa (Medicago sativa L.) is an important forage legume with high feed value and productivity. Because cultivated alfalfa is an outcrossing autotetraploid species with high heterozygosity, phenotype-based cultivar identification can be limited by environmental variation and within-cultivar genetic diversity. In this study, single nucleotide polymorphism (SNP) markers were developed for the identification of the Korean alfalfa cultivar ‘Alfaking (MSCB07)’. Newly generated genotyping-by-sequencing (GBS) datasets for ‘Vernal 25’ and ‘Common (AF)’ were analyzed together with a previously generated whole-genome sequencing (WGS) dataset of ‘Alfaking (MSCB07)’. After alignment to the reference genome and SNP filtering, 20,375 SNP loci were retained for downstream analysis. Principal component analysis and neighbor-joining tree analysis separated ‘Alfaking (MSCB07)’ from the other analyzed cultivars. Genotype pattern comparison identified two diagnostic barcode groups, and their combined profile distinguished ‘Alfaking (MSCB07)’ as “bb” among the analyzed cultivars. Finally, 54 SNP loci were selected as candidate markers for ‘Alfaking (MSCB07)’ discrimination. These results suggest that the selected SNP markers may be useful for cultivar identification, seed purity control, and cultivar protection of ‘Alfaking (MSCB07)’. Further validation with additional alfalfa cultivars and genetic resources is needed to confirm the broader applicability of these markers.

Molecular markers have been widely utilized in population genetics, diagnostic taxonomy, and genetic mapping, and can be applied to cultivar discrimination during field selection processes for alfalfa. In this study, whole-genome sequencing information was obtained for seven alfalfa lines and cultivars developed in Korea, including ‘Alfaone (MS001)’, using Next-Generation Sequencing (NGS). Single nucleotide polymorphism (SNP) analysis revealed that ‘Alfaone (MS001)’ could be distinguished from other lines and cultivars using six SNP loci. Specifically, only two SNP loci were sufficient to differentiate ‘Alfaone (MS001)’ from major lines and cultivars such as ‘MS002’ and ‘Alfaking (MSCB07)’. This set of SNP barcodes provides a reliable standard for alfalfa cultivar discrimination, contributing to domestic cultivar protection and the advancement of the Korea forage industry. Furthermore, the development of distinguishing markers across alfalfa cultivars will enhance genetic resource identification and support the breeding of high-quality new cultivars.

This study reports the development of a new alfalfa (Medicago sativa L.) variety, ‘Alfaone’, at the Forage Production Systems Division, National Institute of Animal Science, Rural Development Administration, Korea, from 2015 to 2023. The variety originated from an artificial cross between Xun Lu (maternal parent) and RadarⅡ Brand (paternal parent), followed by pedigree selection and performance testing. The elite line ‘MsCB01’ was subsequently released as ‘Alfaone’. Regional adaptability trials were conducted for two years (2022–2023) across four representative sites in Korea (Cheonan, Pyeongchang, Jeongeup, and Jinju) to evaluate agronomic traits, forage yield, and quality. Evaluated characteristics included plant height, regrowth ability, winter survival, and lodging resistance. The average dry matter yield of ‘Alfaone’ was 20,811 kg/ha, approximately by about 3% higher than that of the standard cultivar ‘Vernal’ (20,236 kg/ha). Yield superiority was particularly evident in Pyeongchang, suggesting excellent cold tolerance and winter hardiness. Assessment of forage nutritive traits indicated that ‘Alfaone’ was comparable to ‘Vernal’, demonstrating that its yield advantage did not come at the expense of quality. Overall, ‘Alfaone’ is a promising cultivar that combines high productivity with strong adaptability to unfavorable environments, particularly cold-prone regions. Its release is expected to promote the expansion of alfalfa cultivation, enhance forage self-sufficiency, and reduce dependence on imported hay in Korea.

A new barnyard millet (Echinochloa esculenta L.) cultivar, ‘Da-on’ (line BM3), was developed by the National Institute of Animal Science (NIAS) through pedigree selection using local germplasm collected from Jeju Island in 2016. After four years of line separation (2017–2020), a yield trial (2022), and regional adaptability tests across three sites (2023–2024), its agronomic performance and forage quality were evaluated. ‘Da-on’ is a mid-maturing cultivar with a heading date of August 5, which is 11 days later than the check cultivar ‘Borajik’. It exhibits an erect growth habit, purple panicles, and strong lodging resistance. The average plant height was 178.8 cm, which was 40.8 cm taller than that of ‘Borajik’. The dry matter yield of ‘Da-on’ was 16,858 kg/ha, representing a 130% increase compared with ‘Borajik’. Forage quality traits showed lower ADF (34.0%) and NDF (63.7%) contents, while total digestible nutrients (TDN) were higher (62.0%) than in the check. Crude protein content was comparable between the two cultivars. In addition, ‘Da-on’ showed resistance to lodging and leaf blight during field trials, confirming its stability across diverse environments. These results demonstrate that ‘Da-on’ is a promising summer forage crop cultivar suitable for nationwide cultivation, providing higher productivity and nutritive value to enhance forage self-sufficiency in Korea.

This study explores how to integrate the generative artificial intelligence (AI) tool Midjourney into the fashion design process, emphasizing the visualization of sporty fashion concepts. The research applied Midjourney at every stage of the fashion design process: mood board, fashion sketch, flat drawing, production package, fashion show presentation, and store display and sales. Specifically, sporty fashion was selected as the theme, and customized prompts were developed from prior research and design principles to generate visual outputs for each stage. Furthermore, three apparel design experts evaluated the AI-generated images to assess Midjourney’s practical applicability and effectiveness in each phase of the fashion design workflow. Expert evaluations revealed that Midjourney was particularly effective in the early stages, offering diverse and visually engaging imagery that supported creative ideation and mood expression. The tool allowed quick exploration of different silhouettes during the sketching stage but was imprecise in detailed forms and proportions. Limitations became more evident in the flat drawing and work instruction stages, where outputs failed to accurately reflect material textures and technical construction. Prompt refinements and referencebased prompts were tested but often resulted in inconsistent or stylized outputs. Additionally, continuity between stages was missing. Midjourney shows potential as a creative tool, but experts highlight its limitations for practical industry application. Further research is needed to improve prompt optimization and training data for enhanced accuracy and usability in AI-assisted fashion design workflows.

A new variety of Alfalfa (Medicago sativa L.), named 'Alfaking' was developed between 2015 and 2023 at the Grassland and Forages Division, National Institute of Animal Science, Rural Development Administration, Cheonan, Republic of Korea. The variety was produced through artificial hybridization, with ‘Paravivo’ serving as the maternal line and ‘WL514’ as the paternal line. ‘Alfaking’ underwent field tests across four regions (Cheonan, Pyeongchang, Jeongeup, and Jinju) to evaluate its agronomic characteristics and forage production over two years (2022-2023). The dry matter yield of ‘Alfaking’ reached 22,516 kg/ha, which is 11% higher than the control variety, ‘Vernal.’ ‘Alfaking’ exhibited 2.1% higher crude protein content than ‘Vernal’ in forage nutritive value. The development of this new alfalfa variety, which exhibits excellent adaptability to challenging environmental conditions, is expected to enhance forage cultivation and productivity in Korea.

장내 미생물 군집은 소화 과정, 면역 시스템, 질병 발생 등 숙주의 다양한 면에 광범위한 영향을 주는 것으로 알려져 있으며, 주요 장내 미생물 종은 숙주의 생리 기능에 핵심적인 역할을 수행한다고 발표된 바 있다. 곤충의 장내 미생물 군집에 관한 연구가 최근 활발히 이루어지고 있으며, 이들 연구는 주로 장내 미생물 군집과 기생충, 병원체 간의 상호작용, 종간의 신호 전달 네트워크, 먹이의 소화 과정 등을 중심으로 이루어지고 있다. 이러한 연구들은 대부분 Illumina MiSeq을 활용하여 16S rRNA 유전자의 V1부터 V9 영역 중 선택된 특정 부분을 대상으로 짧은 서열 정보를 대상으로 진행되었다. 그러나, 최근에는 PacBio HiFi 기술이 상용화되면서 16S rRNA의 전장 분석이 가능할 수 있게 되었다. 이번 연구는 장수말벌(Vespa mandarinia)의 해부를 통해 gut과 carcass 부분을 분리한 뒤, 각 샘플을 Illumina MiSeq과 PacBio HiFi 기술을 활용하여 미생물 군집 간의 차이점을 확인하기 위하여 수행되었다.

Haemaphysalis longicornis는 사람과 동물에게 여러 심각한 병원체를 전달하는 주요 매개체로, 한반도에 널리 분포하고 있다. H. longicornis는 Rickettsia spp., Borrelia spp., Francisella spp., Coxiella spp., 그리고 중증열성혈소판 감소증후군 바이러스 (SFTS virus) 등을 매개하는 것으로 알려져 있다. 국내에 서식하는 H. longicornis의 미생물 군집과 관련된 연구는 많이 진행되지 않은 것으로 확인되었다. 이 연구는 한반도 내 다양한 지역에서 채집된 H. longicornis의 미생물군집 다양성을 지역별, 성장 단계 및 성별에 따라 분석하였다. 2019년 6월부터 7월까지 질병관리청 권역별기후변화매개체감시거점센터 16개 지역에서 채집한 H. longicornis의 16S rRNA 유전자 V3-V4 영역을 PCR로 증폭 후 Illumina MiSeq 플랫폼으로 시퀀싱하였다. Qiime2를 활용한 미생물 다양성 분석을 통해 총 46개의 샘플에서 1,754,418개의 non-chimeric reads를 얻었으며, 평균 126개 의 operating taxonmic unit (OTU) 을 식별하여 총 1,398개의 OTU를 확인하였다. 대부분의 지역에서 Coxiella spp.가 우점종으로 나타났으며, 특히 Coxiella endosymbiont는 가장 높은 우점도를 보이며, Coxiella burnetii와 계통 발생 학적으로 유사한 것으로 확인되었다. 이 연구를 통해 분석된 결과는 각 지역의 H. longicornis 미생물군집 데이터 베이스 구축에 활용되었으며, 이를 통해 지역별 미생물군집의 특이성을 식별할 수 있게 하였다. 이는 한반도의 H. longicornis에 의한 질병 전파 연구와 이를 통한 공중보건 개선에 기여할 것으로 기대된다.