• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.257-257
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• 2022

Late blight, caused by the hemibiotrophic oomycete pathogen Phytophthora infestans, has been the most important disease limiting potato production worldwide. P. infestans undergo major population shifts in agricultural systems via the successive emergence and migration of asexual lineages. The phenotypic and genotypic bases of these selective sweeps are largely unknown but management strategies need to adapt to reflect the changing pathogen population. Here, we used molecular markers to divide the 86 South Korea isolates into six clonal lineages: KR_1_A1, KR_2_A2, SIB-1, US-11, SIB-1 like, and KR-2 like. We documented the emergence of a new lineage, termed SIB-1 like, and KR-2 like, and their rapid replacement of other lineages to exceed 35% of the pathogen population across South Korea. Genome analyses of the Korean P. infestans populations revealed extensive genetic polymorphism, particularly in effector genes. Importantly, SIB-1 like isolates carry an intact Avr8 effector gene that triggers resistance in potato carrying the corresponding R immune receptor gene R8 cloned from Solarium demissum. These findings point toward a strategy for deploying genetic resistance to mitigate the impact of the SIB-1 like lineage and illustrate how pathogen population monitoring, combined with genome analysis, informs the management of devastating disease epidemics. Further study is being done on pathogenicity of the SIB-1 like isolates on cultivated potatoes and changes in expression patterns of disease effector genes within the SIB-1 like isolates

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.195-197
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• 2003

Soil moisture is a crucial variable in research works of hydrology, meteorology and plant sciences. Adequate soil moisture is essential for plant growth; excesses and deficits of soil moisture must be considered in agricultural practices. There are already several remote sensing methods used for monitoring soil moisture, such as thermal inertia, vegetation water-supplying index, crop water stress index and multi-factor regression. In this paper, an improved method has been discussed which is based on the thermal inertia. We analyzed the problems of monitoring soil moisture using satellites at first, and then put forward an simplified method which directly uses land surface temperature differences to measure soil moisture. Also we have taken the influence of vegetation into account, and import NDVI into the model. The method was used in the study of soil moisture in Heilongjiang Province, China, and we draw the conclusion by the experiments that the model can evidently increase the precision of monitoring soil moisture.

• Journal of Ecology and Environment
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• 제38권3호
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• pp.353-360
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• 2015

A survey of weed occurrence was conducted to identify problematic weed species in a horticultural crop field to get basic information for effective weed control. Surveys of weed species occurring in horticultural crop fields (garlic, onion, red pepper and Chinese cabbage) were conducted in Chungnam province of Korea from April to October in 2014. A total of 516 sites of the 17 regions were identified as having 114 weed species belonging to 32 families. The most dominant weed species in the horticultural crop fields were Chenopodium album var. centrorubrum (8.83%), followed by Digitaria ciliaris (5.71%), Conyza canadensis (5.46%) and Capsella bursa-pastoris (4.67%). Specifically, as a result of this study, the occurrence of 35 species of exotic weeds, such as Chenopodium album and Taraxacum officinale, were confirmed. Almost 68% of the investigation sites was determined under dominance value 1 (range of cover < 10; numerous individuals) by Braun-Branquet cover-abundance scale, indicating a proper weed control in horticultural crop field. As a result of scientific and technological advances, an improved cultivation method is changing the weed occurrence in agricultural land. Additional research needs to be undertaken for the development of weed control methods through such periodic monitoring of occurrence of weeds.

• 한국토양비료학회지
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• 제47권2호
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• pp.85-91
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• 2014

Ground-based polarimetric scatterometers have been effective tools to monitor the growth of crop with multi-polarization and frequencies and various incident angles. An important advantage of these systems that can be exploited is temporal observation of a specific crop target. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. We analyzed the relationships between L-, C- and X-band signatures, biophysical measurements over the whole corn growth period. The Vertical transmit and Vertical receive polarization (VV) backscattering coefficients for all bands were greater than those of the Horizontal transmit and Horizontal receive polarization (HH) until early-July, and then thereafter HH-polarization was greater than VV-polarization or Horizontal transmit and Vertical receive polarization (HV) until the harvesting stage (Day Of Year, DOY 240). The results of correlation analysis between the backscattering coefficients for all bands and corn growth data showed that L-band HH-polarization (L-HH) was the most suited for monitoring the fresh weight ($r=0.95^{***}$), dry weight ($r=0.95^{***}$), leaf area index ($r=0.86^{**}$), and vegetation water content ($r=0.93^{***}$). Retrieval equations were developed for estimating corn growth parameters using L-HH. The results indicated that L-HH could be used for estimating the vegetation biophysical parameters considered here with high accuracy. Those results can be useful in determining frequency and polarization of satellite Synthetic Aperture Radar stem and in designing a future ground-based microwave system for a long-term monitoring of corn.

• 한국토양비료학회지
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• 제47권5호
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• pp.313-318
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• 2014

The remote monitoring system of water salinity was assessed in Wando reclaimed land lake during a farming season in 2009. Increasing of water salinity in this lake used to bring about salt damage on rice plant occasionally. At the early stage of the rice growing period, rice growth was not damaged due to enough rainfall with more than 120 mm from the mid-May to the first ten days of June. Data collection using on-site water salinity measuring sensors every 2 hours and real-time transmission in system were carried out for the experiment. We compared the transmitted values from the sensor system with water sample values collected and analyzed by a local technical office. Salt concentrations measured by sensor in real-time monitoring system were available data. The regression equation between rainfall and water salinity was presented as (water salinity after rainfall) = $0.621{\times}$(water salinity before rainfall)${\times}exp(-0.0139{\times}rainfall)$, ($r^2=0.579$, p<0.01). It is suggested that the system is useful for stable farming in the area where farmer use water in reclaimed lakes as an irrigation source.

• 한국콘텐츠학회논문지
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• 제10권2호
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• pp.63-71
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• 2010

본 논문에서는 다양한 환경 센서를 이용하여 농작물 재배 환경에 필요한 정보를 수집하고 실시간으로 모니터링 할 수 있는 센서 네트워크 기반의 농업 환경 모니터링 시스템을 제안한다. 기존의 센서 네트워크 기반의 무선 센서 노드들은 대부분 각 센서들의 특성에 따라 별도의 변환/제어 모듈이 필요했다. 이러한 문제점을 해결하기 위해 본 시스템에서는 농작물 재배지에서 필요로 하는 정보를 얻기 위해 사용되는 여러가지 센서들을 단일 노드에 통합할 수 있는 통합 센서 모듈을 개발한다. 또한 통합 센서 모듈에 맞는 센서 네트워크 모니터링 시스템을 개발한다. 개발된 시스템의 동작 상태를 검증하기 위해 테스트 환경에 통합 센서 노드를 설치하여 설치 환경 정보를 센싱할 수 있도록 하여 실시간으로 모니터링할 수 있게 하였다.

• 산업경영시스템학회지
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• 제45권4호
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• pp.180-186
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• 2022

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

• Weed & Turfgrass Science
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• 제6권4호
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• pp.350-354
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• 2017

Conyza canadensis is the weed species which most frequently develops resistance to glyphosate in many agricultural crop fields. The continuous use of glyphosate has resulted in the spontaneous occurrences of resistant biotypes. This research was conducted to investigate the response of suspected C. canadensis biotypes to glyphosate. Seeds of C. canadensis were collected from 18 sites in tangerine orchards in Jeju province of Korea. In the preliminary screening, 6 resistant and 12 susceptible biotypes were found at the recommended glyphosate rate ($3.28kga.i.ha^{-1}$). The susceptible biotypes were completely killed at the field application rate whereas the resistant biotypes were initially injured but recovered 14 days after glyphosate application. This is the first case of glyphosate resistance found in Korea despite the national ban on genetically modified glyphosate tolerant crops cultivation. Extended monitoring should be conducted to understand how widely spread the glyphosate resistant C. canadensis is and to estimate the severity of this weed problem in the tangerine orchards of Korea.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2005년도 국제학술회의
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• 한국농림기상학회지
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• 제3권1호
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.