• 한국환경과학회지
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• 제24권4호
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• pp.515-524
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• 2015

The estimation of groundwater usage in Jeju island is important to understand hydrologic cycle system and to plan management of water resource because large amounts of groundwater have been used for agricultural and domestic purpose. The model has been developed to estimate agricultural groundwater usage for garlic at uplands and citrus at orchards raising outdoors using the soil water balance model from FAO 56, respectively. The total amount of water supplied for the crop evapotranspiration and the multipurpose function such as sprout promotion can be simulated by the model. However, due to the discrepancy of water use in initial stage between calculated and observed, the model was calibrated and verified using actual groundwater usage monitoring data for 3.5 years (2011.6 to 2014.12) at three uplands for garlic and three orchards for citrus. Consequently, it would be concluded that the model simulated efficiently actual water usage in that root mean square (RMS) and normalized RMS of the validation stage were less than 8.99 mm and 2.43%, respectively, in two different conditions.

• 한국토양비료학회지
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• 제50권5호
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• pp.409-421
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• 2017

Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to select optimal vegetation indices and regression model for estimating of rice growth using UAV images. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110 and Cannon IXUS camera during farming season in 2016 on the experiment field of National Institute of Crop Science. Before heading stage of rice, there were strong relationships between rice growth parameters (plant height, dry weight and LAI (Leaf Area Index)) and NDVI (Normalized Difference Vegetation Index) using natural exponential function ($R{\geq}0.97$). After heading stage, there were strong relationships between rice dry weight and NDVI, gNDVI (green NDVI), RVI (Ratio Vegetation Index), CI-G (Chlorophyll Index-Green) using quadratic function ($R{\leq}-0.98$). There were no apparent relationships between rice growth parameters and vegetation indices using only Red-Green-Blue band images.

• 한국농공학회논문집
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• 제46권1호
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• pp.75-86
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• 2004

The objective of the research is to develop agricultural resue technologies of reclaiming the effluents from a municipal wastewater treatment plant and reusing for irrigated rice paddies. The Suwon wastewater treatment plant was selected for wastewater reuse tests. The control was the plots with groundwater irrigation (TR＃1), the treatment (TR＃2) using polluted stream water as it was, and three others using wastewater after treatment. Three levels of wastewater treatments were employed： the effluent from the wastewater treatment plant (TR＃3), sand filtering after treatment plant(TR＃4), and ultra-violet treatment after sand filtering (TR＃5). The randomized block method was applied to wastewater application to paddy rice with five treatments and six replica. The effects of various wastewater treatment levels on water quality, paddy soil, crop growth, yields, and the health hazards were investigated. The primary results indicate that cultivating rice with reclaimed wastewater irrigation did not cause a problem to adverse effects on crop growth and yields. Overall, wastewater could be used as a practical alternative measure for reclaimed wastewater irrigation. However, long-term monitoring is recommended on the effects on soil chemical characteristics and its related health concerns.

• 한국토양비료학회지
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• 제48권6호
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• pp.571-581
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• 2015

Soil moisture content is generally accepted as an important factor to understand the process of crop growth and is the basis of earth system models for analysis and prediction of the crop condition. To continuously monitor soil moisture changes at kilometer scale, it is demanded to create high resolution data from the current, several tens of kilometers. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) from 10 km to 30 m resolution using a soil texture and field measurements that have a high correlation with the SMC. As a result, the soil moisture variations of both data (before and after downscaling) were identical, and the Root Mean Square Error (RMSE) of SMC exhibited the low values. Also, time series analyses showed that three kinds of SMC data (field measurement, original AMSR2, and downscaled AMSR2) had very similar temporal variations. Our method can be applied to downscaling of other soil variables and can contribute to monitoring small-scale changes of soil moisture by providing high resolution data.

• The Plant Pathology Journal
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• 제38권2호
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• pp.159-166
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• 2022

Barley yellow dwarf virus (BYDV) has been a major viral pathogen causing significant losses of cereal crops including oats worldwide. It spreads naturally through aphids, and a rapid, specific, and reliable diagnostic method is imperative for disease monitoring and management. Here, we established a rapid and reliable method for isothermal reverse transcription recombinase polymerase amplification (RT-RPA) combined with a lateral flow strips (LFS) assay for the detection of BYDV-infected oat samples based on the conserved sequences of the BYDV coat protein gene. Specific primers and a probe for RT-RPA reacted and optimally incubated at 42℃ for 10 min, and the end-labeled amplification products were visualized on LFS within 10 min. The RT-RPA-LFS assay showed no cross-reactivity with other major cereal viruses, including barley mild mosaic virus, barley yellow mosaic virus, and rice black streaked dwarf virus, indicating high specificity of the assay. The sensitivity of the RT-RPA-LFS assay was similar to that of reverse transcription polymerase chain reaction, and it was successfully validated to detect BYDV in oat samples from six different regions and in individual aphids. These results confirm the outstanding potential of the RT-RPA-LFS assay for rapid detection of BYDV.

• 한국환경농학회지
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• 제36권4호
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• pp.293-298
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• 2017

BACKGROUND: Pyrethroids (PYRs) are a widely used insecticide in agriculture and household area. In mammals, PYRs such as deltamethrin is metabolized to 3-phenoxybenzoic acid (3-PBA) in liver that is mainly excreted in urine. This study is designed to single exposure of deltamethrin to rats in a dose-dependent manner and identify the correlation between deltamethrin exposure and its metabolite (3-PBA) in urine. METHODS AND RESULTS: Exposure levels of deltamethrin were control (0 mg/kg bw), low (0.0705 mg/kg bw), medium (0.705 mg/kg bw) and high (7.05 mg/kg bw) dose. Low concentration was derived by ussing Korea predictive operator exposure model (KoPOEM). Dermal exposure persisted for 6 h, and urine specimens were collected for 24 h. The urine matrix was removed after a series of procedures and 3-PBA was analyzed by gas chromatography/mass spectrometry. CONCLUSION: There was a strong correlation ($R^2=0.83$) between the amount of oral exposure to delta me thrin and urinary levelof3-PBAexcreted. In dermal exposure groups of deltamethrin except high-dose, also there was a good correlation between urinary 3-PBA and deltamethrin exposure, but not stronger than in oral deltamethrin exposure groups. Based on these results, therefore, the amount of 3-PBA in urine can be used as a good monitoring indicator that reflexing the exposure level of deltamethrin to human body.

• Journal of Biosystems Engineering
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• 제41권2호
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• pp.126-137
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• 2016

Purpose: The overall objective of this study was to evaluate the vegetation fraction of soybeans, grown under different cropping conditions using an unmanned aerial vehicle (UAV) equipped with a red, green, and blue (RGB) camera. Methods: Test plots were prepared based on different cropping treatments, i.e., soybean single-cropping, with and without herbicide application and soybean and barley-cover cropping, with and without herbicide application. The UAV flights were manually controlled using a remote flight controller on the ground, with 2.4 GHz radio frequency communication. For image pre-processing, the acquired images were pre-treated and georeferenced using a fisheye distortion removal function, and ground control points were collected using Google Maps. Tarpaulin panels of different colors were used to calibrate the multi-temporal images by converting the RGB digital number values into the RGB reflectance spectrum, utilizing a linear regression method. Excess Green (ExG) vegetation indices for each of the test plots were compared with the M-statistic method in order to quantitatively evaluate the greenness of soybean fields under different cropping systems. Results: The reflectance calibration methods used in the study showed high coefficients of determination, ranging from 0.8 to 0.9, indicating the feasibility of a linear regression fitting method for monitoring multi-temporal RGB images of soybean fields. As expected, the ExG vegetation indices changed according to different soybean growth stages, showing clear differences among the test plots with different cropping treatments in the early season of < 60 days after sowing (DAS). With the M-statistic method, the test plots under different treatments could be discriminated in the early seasons of <41 DAS, showing a value of M > 1. Conclusion: Therefore, multi-temporal images obtained with an UAV and a RGB camera could be applied for quantifying overall vegetation fractions and crop growth status, and this information could contribute to determine proper treatments for the vegetation fraction.

• 한국측량학회지
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• 제38권6호
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• pp.671-679
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• 2020

경지면적의 작물 상황에 대한 모니터링 및 분석은 식량자급율을 높이기 위한 가장 중요한 요소이지만, 기존의 모니터링 방법은 노동 집약적이며 시간이 많이 들어 식량자급율을 높이기 위한 방안으로 그 활용성이 떨어진다. 이와같은 단점을 극복하기 위하여 국내에 다수 존재하고 있는 소규모 농지에서의 복합 작물 정보를 모니터링 하기위한 효율적인 방법을 개발할 필요가 있다. 본 연구에서는 복합작물의 분류 정확도를 높이기 위하여 무인항공기에서 취득된 RGB영상과 이를 이용한 식생지수를 딥러닝 입력데이터로 적용하고 복합 밭작물을 분류하였다. 각각의 입력데이터 분류 결과 RGB 영상을 이용한 분류는 전체정확도 80.23%, Kappa 계수 0.65가 나타났고, RGB영상과 식생지수를 이용한 방법의 경우 식생지수 3개(ExG,ExR,VDVI) 추가 데이터는 전체정확도 89.51%, Kappa 계수 0.80이며, 식생지수 6개(ExG,ExR,VDVI,RGRI,NGRDI,ExGR)는 90.35%, Kappa 계수 0.82로 분석되었다. 분류결과 RGB영상만을 이용한 방법에 비하여 식생지수를 추가한 결과 값이 비교적 높게 분석되었으며, 복합작물을 분류하는데 있어 식생지수를 추가한 데이터가 더 좋은 결과를 나타내었다.

• 한국응용곤충학회지
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• 제59권4호
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• pp.411-416
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• 2020

2015년부터 2018년까지 시설하우스에서 토마토 재배기간인 11월부터 이듬해 5월까지 충남 논산, 부여, 전북 익산에서 가루이의 종류와 발생 현황을 조사하였다. 반면 5월부터 10월까지는 억제재배를 하는 전북 장수지역에서 조사를 수행하였다. 시기별로 가루이를 채집하여 동정한 결과 온실가루이(Trialeurodes vaporariorum)와 담배가루이(Bemisia tabaci)의 발생이 확인되었다. 주로 온실가루이와 담배가루이가 혼재되어 있는 경우가 많았으며 두 종 중 담배가루이의 발생이 높게 나타났다. 가루이의 발생은 3월 하순부터 증가하기 시작하여 5월에는 밀도가 급격하게 증가하였고 수확기가 끝나는 시점에서는 밀도가 가장 높았다. 따라서, 시설하우스에서 가루이의 효율적 방제를 위해서는 촉성재배는 3월 상순부터, 억제작형은 6월 상순부터 예찰하고 밀도가 증가하기 전에 초기 방제하여야 할 것이다.

• 대한원격탐사학회지
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• 제38권6_1호
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• pp.1219-1230
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• 2022

농업관측에서의 다중분광 드론은 식생구분 및 식생활력도 분석에 있어 복사량이나 반사도와 같은 물리량을 기반으로 한 정량적이고 신뢰성 있는 데이터가 필요하다. 작황분석 모니터링을 위한 원격탐사 자료의 경우 동일지역에 대해 여러 시기에 걸쳐 촬영된 영상이 요구되며, 특히 엽면적 지수 또는 엽록소와 같은 생물리자료의 경우 동일한 기준에서의 시계열 자료를 통해 분석되므로 직접적으로 비교 가능한 반사도 자료가 필요하다. 드론영상을 기반 정사영상(정합영상)은 전체 영상 화소값이 왜곡되거나 접합 경계면 화소값의 차이가 발생하여 정확한 물리량 산출에 한계를 가진다. 본 연구는 시계열 작황 모니터링을 위한 드론영상의 보정방법에 따른 지상 반사도와 드론영상 기반 식생지수를 산정하고 그 결과를 지상관측자료와 비교하여 전처리 방법에 따른 드론영상의 분광학적 특성을 구명하고자 수행하였다.