• Title/Summary/Keyword: 한국기술연구원

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Occurrence of Viral Diseases in the Early Growth Stage of Soybean in Korea (우리나라 콩 생육초기 바이러스병 발생 양상)

  • Sangmin Bak;Mina Kwon;Dong Hyun Kang;Hong-Kyu Lee;Young-Nam Yoon;In-Yeol Baek;Young Gyu Lee;Jae Sun Moon;Su-Heon Lee
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.67 no.4
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    • pp.253-264
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    • 2022
  • In this study, we investigated the occurrence of viral diseases in the early growth stage of soybean to establish management practices. We collected 83 soybean samples showing abnormal symptoms, approximately 3-4 weeks after seeding in the breeding field of the National Institute of Crop Science. Viruses were detected in the collected samples using reverse transcription polymerase chain reaction (RT-PCR) and metatranscriptome analysis of all those samples. The incidence of viral diseases in the field was less than 1% overall and up to 50% in certain cultivars and lines. RT-PCR and metatranscriptome analysis detected Soybean yellow mottle mosaic virus (SYMMV), Soybean mosaic virus (SMV), Soybean yellow common mosaic virus, Peanut stunt virus, and soybean geminivirus A (SGVA). Among these detected viruses, SYMMV and SMV were identified as major viruses causing infection in the early growth stage of soybean, with detection rates of 53.7% and 42.6%, respectively. Soybeans infected with SYMMV showed typical mosaic symptoms, whereas those infected with SMV showed a variety of symptoms such as mosaic, mottle, stunt, and chlorotic spots. Transmission characteristics of these viruses are variable, such that SMV is primarily transmitted by seeds, whereas SYMMV could be transmitted by insects, soil, and seeds. In this study, SGVA was detected in the early growth stage of soybean, and research on the current status and its effects on soybean after the early growth stage should be conducted.

Analysis of Plants Social Network for Vegetation Management on Taejongdae in Busan Metropolitan City (부산 태종대 식생관리를 위한 식물사회네트워크 분석)

  • Sang-Cheol Lee;Hyun-Mi Kang;Seok-Gon Park;Jae-Bong Baek;Chan-Yeol Yu;In-Chun Hwang;Song-Hyun Choi
    • Korean Journal of Environment and Ecology
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    • v.36 no.6
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    • pp.651-661
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    • 2022
  • Plants social network analysis, which combines plants society and social network analyses, is a new research method for understanding plants society. This study was conducted to investigate the relationship between species, using plant social network analysis targeting Taejongdae in Busan, and build basic data for management. Taejongdae, located in the warm temperate forest in Korea, is a representative coastal forest of Busan Metropolitan City, and the Pinus thunbergii-Eurya japonicacommunity is widely distributed. This study set up 100 quadrats (size of 100m2each) in Taejongdae to investigate the species that emerged and analyzed the interspecies association focusing on major species. Based on the results, a sociogram was created using the Gephi 0.9.2, and the network centrality and structure were analyzed. The results showed that the frequency of appearance was high in the order of P. thunbergii, E. japonica, Quercus serrata, Sorbus alnifolia, Ligustrum japonicum, and Styrax japonicusand that many evergreen broad-leaved trees appeared due to the environmental characteristics of the site. The plants social network of Taejongdae was composed of a small-scale network with 50 nodes and 172 links and was divided into 4 groups through modularization. The succession sere identified through a sociogram confirmed that the group that include P. thunbergiiand E. japonicawould progress to a deciduous broadleaf community dominated by Q. serrataand Carpinus tschonoskii, using hub nodes such as Prunus serrulataf. spontaneaand Toxicodendron trichocarpum. Another succession sere was highly likely to progress to an evergreen broad-leaved community dominated by Machilus thunbergiiand Neolitsea sericea, using M. thunbergiias a medium. In some areas, a transition to a deciduous broad-leaved community dominated by Celtis sinensis, Q. variabilisand Zelkova serratausing Lindera obtusilobaand C. sinensisas hub nodes was expected.

Chemical and Physical Influence Factors on Performance of Bentonite Grouts for Backfilling Ground Heat Exchanger (지중 열교환기용 멘토나이트 뒤채움재의 화학적, 물리적 영향 요소에 관한 연구)

  • Lee, Chul-Ho;Wi, Ji-Hae;Park, Moon-Seo;Choi, Hang-Seok;Shon, Byong-Hu
    • Journal of the Korean Geotechnical Society
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    • v.26 no.12
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    • pp.19-30
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    • 2010
  • Bentonite-based grout has been widely used to seal a borehole constructed for a closed-loop vertical ground heat exchanger in a geothermal heat pump system (GHP) because of its high swelling potential and low hydraulic conductivity. Three types of bentonites were compared one another in terms of viscosity and thermal conductivity in this paper. The viscosity and thermal conductivity of the grouts with bentonite contents of 5%, 10%, 15%, 20% and 25% by weight were examined to take into account a variable water content of bentonite grout depending on field conditions. To evaluate the effect of salinity (i.e., concentration of NaCl : 0.1M, 0.25M, and 0.5M) on swelling potential of the bentonite-based grouts, a series of volume reduction tests were performed. In addition, if the viscosity of bentonite-water mixture is relatively low, particle segregation can occur. To examine the segregation phenomenon, the degree of segregation has been evaluated for the bentonite grouts especially in case of relatively low viscosity. From the experimental results, it is found that (1) the viscosity of the bentonite mixture increased with time and/or with increasing the mixing ratio. However, the thermal conductivity of the bentonite mixture did not increase with time but increased with increasing the mixing ratio; (2) If bentonite grout has a relatively high swelling index, the volume reduction ratio in the saline condition will be low; (3) The additive, such as a silica sand, can settle down on the bottom of the borehole if the bentonite has a very low viscosity. Consequently, the thermal conductivity of the upper portion of the ground heat exchanger will be much smaller than that of the lower portion.

Development of disaster severity classification model using machine learning technique (머신러닝 기법을 이용한 재해강도 분류모형 개발)

  • Lee, Seungmin;Baek, Seonuk;Lee, Junhak;Kim, Kyungtak;Kim, Soojun;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.261-272
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    • 2023
  • In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

Comprehensive Review on the Implications of Extreme Weather Characteristics to Stormwater Nature-based Solutions (자연기반해법을 적용한 그린인프라 시설의 극한기후 영향 사례분석)

  • Miguel Enrico L. Robles;Franz Kevin F. Geronimo;Chiny C. Vispo;Haque Md Tashdedul;Minsu Jeon;Lee-Hyung Kim
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.353-365
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    • 2023
  • The effects of climate change on green infrastructure and environmental media remain uncertain and context-specific despite numerous climate projections globally. In this study, the extreme weather conditions in seven major cities in South Korea were characterized through statistical analysis of 20-year daily meteorological data extracted fro m the Korea Meteorological Administration (KMA). Additionally, the impacts of extreme weather on Nature-based Solutions (NbS) were determined through a comprehensive review. The results of the statistical analysis and comprehensive review revealed the studied cities are potentially vulnerable to varying extreme weather conditions, depending on geographic location, surface imperviousness, and local weather patterns. Temperature extremes were seen as potential threats to the resilience of NbS in Seoul, as both the highest maximum and lowest minimum temperatures were observed in the mentioned city. Moreover, extreme values for precipitation and maximum wind speed were observed in cities from the southern part of South Korea, particularly Busan, Ulsan, and Jeju. It was also found that extremely low temperatures induce the most impact on the resilience of NbS and environmental media. Extremely cold conditions were identified to reduce the pollutant removal efficiency of biochar, sand, gravel, and woodchip, as well as the nutrient uptake capabilities of constructed wetlands (CWs). In response to the negative impacts of extreme weather on the effectiveness of NbS, several adaptation strategies, such as the addition of shading and insulation systems, were also identified in this study. The results of this study are seen as beneficial to improving the resilience of NbS in South Korea and other locations with similar climate characteristics.

Investigation on the water quality challenges and benefits of buffer zone application to Yongdam reservoir, Republic of Korea (용담호의 홍수터 적용을 위한 문제점 및 이점 조사 연구)

  • Franz Kevin Geronimo;Hyeseon Choi;Minsu Jeon;Lee-Hyung Kim
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.274-283
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    • 2023
  • Buffer zones, an example of nature-based solutions, offer wide range of environmental, social and economic benefits due to their multifunctionality when applied to watershed areas promoting blue-green connectivity. This study evaluated the effects of buffer zone application to the water quality of Yongdam reservoir tributaries. Particularly, the challenges and improvement of the buffer zone design were identified and suggested, respectively. Water and soil samples were collected from a total of six sites in Yongdam reservoir from September 2021 to April 2022. Water quality analyses revealed that among the sites monitored, downstream of Sangjeonmyeon Galhyeonri (SG_W_D2) was found to have the highest concentration for water quality parameters turbidity, total suspended solids (TSS), chemical oxygen demand (COD), total phosphorus (TP) and total nitrogen (TN). This finding was attributed to the algal bloom observed during the sampling conducted in September and October 2021. It was found through the soil analyses that high TN and TP concentrations were also observed in all the agricultural land uses implying that nutrient accumulation in agricultural areas are high. Highest TN concentration was found in the agricultural area of Jeongcheonmyeon Wolpyeongri (JW_S_A) followed by Jucheonmyeon Sinyangri (JS_S_A) while the lowest TN concentration was found in the original soil of Sangjeonmyeon Galhyeonri (SG_S_O). Among the types of buffer zones identified in this study, Type II-A, Type II-B and Type III were found to have blue-green connectivity. However, initially, blue-green connectivity in these buffer zone types were not considered leading to poor design and poor performance. As such, improvement in the design considering blue-green network and renovation must be considered to optimize the performance of these buffer zones. The findings in this study is useful for designing buffer zones in the future.

A Comparative Study of Domestic Travel Patterns and Determinant Factors Affecting Satisfaction by Generations (대한민국 국민의 세대별 국내여행 방식 및 만족도 영향요인)

  • Mi-Sook Lee;Yoon-Joo Park
    • Information Systems Review
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    • v.22 no.2
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    • pp.137-166
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    • 2020
  • While South Koreans overseas travelling rate has been increased every year, domestic travelling rate has been at a standstill for several years. The purpose of this study is to analyze domestic traveling styles of Koreans according to their generations in order to provide generation-specific traveling services. For this purpose, we categorized the survey respondents into four different generations, which are Millennium (age 19~34), X generation (35~54), Baby Boomer (55~64) and senior by following the criterions of the Korea National Tourism Organization. After then, we analyze factors related to travel preparation process, the actual traveling activities and satisfaction after the travel. In this study, 16,713 data collected by the Ministry of Culture, Sports and Tourism are used. The results of this study show that Korean people tends to acquire domestic traveling information from their own or acquaintances past experiences. Also, they do not prefer the organized trip for domestic travels, thus do not buy package products a lot. In addition, natural scenery, rich in cultural heritage, and convenient accommodation are the most important determinant factors affecting the overall travel satisfaction of level for all generations. The traveling characteristics for each generation are as follows. Millennium get traveling information from the internet a lot, and more specifically, they refer portal sites and social network services (SNS) in many cases. Also, they tend to travel in summer peak season to popular destinations and pursues active traveling experiences. Generation X has similar traveling patterns with Millennium, however they major transportation method is using their own car. Also, transportation convenience and satisfactory leisure activity are important factors affecting the overall satisfaction level to Generation X. On the other hand, Baby boomer generation has a greater emphasis on appreciation of nature, visiting famous restaurants, and relaxation, rather than actively participating experiencing programs. They travel evenly in summer and spring/fall season to many different areas instead of focusing on popular tourist spots. In addition, shopping and eating delicious food are the important factors affecting the overall satisfaction level for them. Lastly, Senior generation has similar characteristics with Baby boomer in many ways, however, they travel a lot on the same day using public transportations or car rental service. They prefer spring and autumn trips rather than summer peak season, and tend to buy packaged travel products a lot compared with other generations. If these different traveling characteristics of each generation are considered for organizing and customizing tourism services, it is expected that domestic tourism satisfaction level will be ultimately increased.

Assessment of Methane Production Rate Based on Factors of Contaminated Sediments (오염퇴적물의 주요 영향인자에 따른 메탄발생 생성률 평가)

  • Dong Hyun Kim;Hyung Jun Park;Young Jun Bang;Seung Oh Lee
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.4
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    • pp.45-59
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    • 2023
  • The global focus on mitigating climate change has traditionally centered on carbon dioxide, but recent attention has shifted towards methane as a crucial factor in climate change adaptation. Natural settings, particularly aquatic environments such as wetlands, reservoirs, and lakes, play a significant role as sources of greenhouse gases. The accumulation of organic contaminants on the lake and reservoir beds can lead to the microbial decomposition of sedimentary material, generating greenhouse gases, notably methane, under anaerobic conditions. The escalation of methane emissions in freshwater is attributed to the growing impact of non-point sources, alterations in water bodies for diverse purposes, and the introduction of structures such as river crossings that disrupt natural flow patterns. Furthermore, the effects of climate change, including rising water temperatures and ensuing hydrological and water quality challenges, contribute to an acceleration in methane emissions into the atmosphere. Methane emissions occur through various pathways, with ebullition fluxes-where methane bubbles are formed and released from bed sediments-recognized as a major mechanism. This study employs Biochemical Methane Potential (BMP) tests to analyze and quantify the factors influencing methane gas emissions. Methane production rates are measured under diverse conditions, including temperature, substrate type (glucose), shear velocity, and sediment properties. Additionally, numerical simulations are conducted to analyze the relationship between fluid shear stress on the sand bed and methane ebullition rates. The findings reveal that biochemical factors significantly influence methane production, whereas shear velocity primarily affects methane ebullition. Sediment properties are identified as influential factors impacting both methane production and ebullition. Overall, this study establishes empirical relationships between bubble dynamics, the Weber number, and methane emissions, presenting a formula to estimate methane ebullition flux. Future research, incorporating specific conditions such as water depth, effective shear stress beneath the sediment's tensile strength, and organic matter, is expected to contribute to the development of biogeochemical and hydro-environmental impact assessment methods suitable for in-situ applications.

Analysis of the Impact of Satellite Remote Sensing Information on the Prediction Performance of Ungauged Basin Stream Flow Using Data-driven Models (인공위성 원격 탐사 정보가 자료 기반 모형의 미계측 유역 하천유출 예측성능에 미치는 영향 분석)

  • Seo, Jiyu;Jung, Haeun;Won, Jeongeun;Choi, Sijung;Kim, Sangdan
    • Journal of Wetlands Research
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    • v.26 no.2
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    • pp.147-159
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    • 2024
  • Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

Establishing Optimal Conditions for LED-Based Speed Breeding System in Soybean [Glycine max (L.) Merr.] (LED 기반 콩[Glycine max (L.) Merr.] 세대단축 시스템 구축을 위한 조건 설정)

  • Gyu Tae Park;Ji-Hyun Bae;Ju Seok Lee;Soo-Kwon Park;Dool-Yi Kim;Jung-Kyung Moon;Mi-Suk Seo
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.68 no.4
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    • pp.304-312
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    • 2023
  • Plant breeding is a time-consuming process, mainly due to the limited annual generational advancement. A speed breeding system, using LED light sources, has been applied to accelerate generational progression in various crops. However, detailed protocols applicable to soybeans are still insufficient. In this study, we report the optimized protocols for a speed breeding system comprising 12 soybean varieties with various maturity ecotypes. We investigated the effects of two light qualities (RGB ratio), three levels of light intensity (PPFD), and two soil conditions on the flowering time and development of soybeans. Our results showed that an increase in the red wavelength of the light spectrum led to a delay in flowering time. Furthermore, as light intensity increased, flowering time, average internode length, and plant height decreased, while the number of nodes, branches, and pods increased. When compared to agronomic soil, horticultural soil resulted in an increase of more than 50% in the number of nodes, branches, and pods. Consequently, the optimal conditions were determined as follows: a 10-hour short-day photoperiod, an equal RGB ratio (1:1:1), light intensity exceeding 1,300 PPFD, and the use of horticultural soil. Under these conditions, the average flowering time was found to be 27.3±2.48 days, with an average seed yield of 7.9±2.67. Thus, the speed breeding systems reduced the flowering time by more than 40 days, compared to the average flowering time of Korean soybean resources (approximately 70 days). By using a controlled growth chamber that is unaffected by external environmental conditions, up to 6 generations can be achieved per year. The use of LED illumination and streamlined facilities further contributes to cost savings. This study highlights the substantial potential of integrating modern crop breeding techniques, such as digital breeding and genetic editing, with generational shortening systems to accelerate crop improvement.