• 한국응용곤충학회지
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• 제34권1호
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• pp.40-45
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• 1995

전국 8개 지역별 각 사과원에서 채집된 점박이응애(Tetranychus urticae Koch)에 대한 저항성 정도를 일본 감수성 계통과 비교한 결과 지역별 현저한 감수성 차이를 보였다. Azocyclotin, fenpropathrin, propargite 및 abamectin에 대해서는 낮거나 중간 정도의 저항성을, dicofol, fenpyroximate 및 pyridaben에 대해서는 높은 저항성을 나타내었다. 이들 계통은 한종 또는 두종 이상의 약제에 대해 감수성을 보여 특정 지역에 대해서는 적당한 살비제의 선택적 이용으로 점박이응애를 효과적으로 방제할 수 있을 것으로 사료된다.

• 한국농공학회논문집
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• 제64권1호
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• 한국축산식품학회지
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• 제43권6호
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• pp.1150-1169
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• 2023

Edible insects are gaining popularity as a potential future food source because of their high protein content and efficient use of space. Black soldier fly larvae (BSFL) are noteworthy because they can be used as feed for various animals including reptiles, dogs, fish, chickens, and pigs. However, if the edible insect industry is to advance, we should use automation to reduce labor and increase production. Consequently, there is a growing demand for sensing technologies that can automate the evaluation of insect quality. This study used short-wave infrared (SWIR) hyperspectral imaging to predict the proximate composition of dried BSFL, including moisture, crude protein, crude fat, crude fiber, and crude ash content. The larvae were dried at various temperatures and times, and images were captured using an SWIR camera. A partial least-squares regression (PLSR) model was developed to predict the proximate content. The SWIR-based hyperspectral camera accurately predicted the proximate composition of BSFL from the best preprocessing model; moisture, crude protein, crude fat, crude fiber, and crude ash content were predicted with high accuracy, with R² values of 0.89 or more, and root mean square error of prediction values were within 2%. Among preprocessing methods, mean normalization and max normalization methods were effective in proximate prediction models. Therefore, SWIR-based hyperspectral cameras can be used to create automated quality management systems for BSFL.

• 대한원격탐사학회지
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• 제40권3호
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• 한국농공학회논문집
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• 제60권6호
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• pp.121-131
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• 2018

Climate change has caused changes in environmental factors that have a direct impact on agriculture such as temperature and precipitation. The meteorological disaster that has the greatest impact on agriculture is drought, and its forecasts are closely related to agricultural production and water supply. In the case of terrestrial data, the accuracy of the spatial map obtained by interpolating the each point data is lowered because it is based on the point observation. Therefore, acquisition of various meteorological data through satellite imagery can complement this terrestrial based drought monitoring. In this study, Evaporative Stress Index (ESI) was used as satellite data for drought determination. The ESI was developed by NASA and USDA, and is calculated through thermal observations of GOES satellites, MODIS, Landsat 5, 7 and 8. We will identify the difference between ESI and other satellite-based drought assessment indices (Vegetation Health Index, VHI, Leaf Area Index, LAI, Enhanced Vegetation Index, EVI), and use it to analyze the drought in South Korea, and examines the applicability of ESI as a new indicator of agricultural drought monitoring.

• 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.

• 농약과학회지
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• 제20권1호
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• pp.23-29
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• 2016

국내산 유통 수삼 중 농약의 잔류특성을 구명하기 위하여 전국 15개 지역의 45개 재래시장 상점에서 45점의 시료를 채취한 후 GC-MS/MS와 LC-MS/MS를 이용한 다성분동시분석법을 이용하여 잔류농약을 분석하였으며, 검출된 농약은 GC-ECD/NPD를 이용한 개별분석으로 수삼 중 잔류농약을 정량하였다. 잔류농약 분석 결과 총 45점의 시료에서 cypermethrin, fenitrothion, fludioxonil, thifluzamide, tolclofos-methyl이 검출되었으며, 검출율은 35.6%이었다. Tolclofos-methyl이 가장 높은 검출빈도를 보였으며, 인삼에 대한 안전사용기준과 잔류허용기준이 설정되어 있지 않은 fenitrothion이 검출되었다. 수삼에서 검출된 농약은 모두 잔류허용기준 미만이었다. 수삼 중 검출된 농약의 일일섭취허용량 대비 일일섭취추정량은 0.03-16.67%이었다.

• 농약과학회지
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• 제14권1호
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• pp.1-9
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• 2010

청주지역에서 유통중인 농산물 중 농약의 잔류실태를 조사하고 안전성을 평가하기 위하여 도매시장과 재래시장에서 총 120점의 농산물을 채취하여 GLC와 HPLC 및 GC-MSD를 이용한 다성분동시분석법으로 분석하였다. Procymidone과 penconazole 및 tetraconazole과 같은 3종의 살균제가 양파, 부추, 토마토, 풋고추에서 검출되었다. 도매시장에서 채취한 양파에서 살균제 penconazole이 검출되었으며, 재래시장의 경우는 살균제 procymidone이 부추와 토마토에서, 살균제 tetraconazole이 풋고추에서 검출되어 3.3%의 검출율을 나타내었다. 검출된 농약의 일일섭취추정량(EDI)은 일일섭취허용량(ADI)의 0.1% 미만으로 안전한 것으로 판단되었다.

• 한국농공학회논문집
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• 제59권4호
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• pp.75-83
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• 2017

Many parts of problems in livestock industry today are associated with organic dust. Endotoxin and toxic gasses on the surface of dust and dust itself can cause aesthetic displeasure and respiratory disease. It also reduces livestock productivity by suppressing immunity of animals and carrying microbes causing animal disease. However, dust level of cattle farm was rarely reported in Korea, and regulation for cattle farm worker does not exist. In this paper, dust concentration and environmental condition were regularly monitored in a commercial Korean native cattle farm. The measurement was conducted according to location and working activities. From the measurement, distribution of dust concentration was affected by wind environment, as the result of natural ventilation. TMR mixer was a major source of dust in target cattle house. The maximum inhalable dust concentration was 637.8 times higher than exposure limit as feed dropped into the TMR mixer. It was expected that dust generation could be affected by particle size and drop height of feed. This study suggests potential risk of dust in cattle farm, and necessity for latter study. Effect of aerodynamic condition and TMR processing should be investigated for dust reduction study.

• 한국환경농학회지
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• 제30권3호
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• pp.323-329
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• 2011

BACKGROUND: The conazoles, difenoconazole, diniconazole, hexaconazole, penconazole and tetraconazole are a large class of synthetic fungicides used extensively for foliage and seed treatments in agricultural crops. The extensive use of conazoles has brought concerns on the potentiality of environmental contamination and toxicity. Thus studies on the development of methods for monitoring the conazoles are required. METHODS AND RESULTS: A modified quick, easy, effective, rugged and safe (QuEChERS) method was involved in sample preparation. Quadrapole time of flight mass spectrometer (Q-TOF MS) in electron spray ionization (ESI) mode was employed to determine conazoles in garlic samples. The limit of detection (LOD) and limit of quantification (LOQ) of conazoles by Q-TOF-MS ranged from 0.001 to 0.002 mg/L and 0.002 to 0.005 mg/L, respectively. Q-TOF-MS analysis exhibited less than 2.6 ppm error of accurate mass measurements for the detection of conazoles spiked at 0.05 mg/L in garlic matrix. Recovery values of conazoles fortified in garlic samples at 0.02, 0.05 and 0.1 mg/L were between 79.2 and 106.2% with a maximum 11.8% of standard deviation. No detectable conazoles were found in the domestic market samples by using the Q-TOF-MS method. CONCLUSION(s): High degree of confirmation for conazoles by accurate mass measurements demonstrated that Q-TOF-MS analysis combined with a QuEChERS method may be applicable to simultaneous determination of conazoles in garlic samples.