• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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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

• Proceedings of the KSRS Conference
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• 2003.11a
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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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• v.38 no.3
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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.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.2
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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.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.5
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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.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.63-71
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• 2010

In this paper, we propose the Agricultural Environment Monitoring System based on Sensor Network which can collect information of crop cultivation environment and monitor it in real-time by using various environment sensors. Existing wireless sensor nodes, based on the sensor network, require extra conversion/control module depending on the characteristics. To solve this problem, we developed an integrated sensor module which can integrate various kinds of sensors used to obtain the necessary information for the area under crop cultivation. In addition, we developed sensor networks monitoring system which is suitable for an integrated sensor module. To verify the operating status of the proposed system, an integrated sensor node is installed in the test environment so that it can sense information of the environment and monitor it in real-time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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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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• v.6 no.4
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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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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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.