• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.24-24
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• 2023

현대화된 재배법은 작물의 생육을 위해 시설내부의 환경을 제어하고 실시간 센싱 정보를 저장하는 시스템을 구축하고 이를 활용하고 있으나, 작물의 생육·생장에 미치는 직접적인 영향에 대한 생육데이터 취득은 아직까지도 전문 재배사·농민이 수작업을 통해 조사되고 있다. 본 연구는 작물의 생육데이터 자동 취득을 위한 장치를 개발하고 이를 실용화하기 위한 정확도 측정 시험을 진행하였다. 실험을 위한 장치구성은 3D Depth 카메라(Intel D415)와 운용 PC이며 딥러닝 모델을 이용하여 작물의 세부기관을 자동으로 인식하는 모델을 포함한다. 장치는 다양한 재배환경의 작물 생육데이터 취득을 위하여 휴대용, 고정형, 로봇형 3가지 유형으로 개발하였고 측정 정확도 검증은 휴대용 생육측정장치를 활용하여 조사하였다. 이러한 연구를 통해 수작업이 아닌 영상에 의한 생육 데이터수집으로 작물의 생육정보(측정값+이미지)를 확보함으로써 환경데이터와 함께 객관적인 정보에 의한 작물의 생산량, 수확시기 등을 예측하는데 활용될 수 있을것으로 예상된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.468-468
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• 2011

작물생육모형은 다양한 환경조건 하에서 주요 작물에 대한 생육 및 생산량의 종합적인 모의가 가능하며, DSSAT(Decision Support System for Agrotechnology Transfer)의 경우 지난 20여 년간 많은 연구자들에 의해서 작물생육을 모의하는데 사용되어왔다. 또한, 하수재이용은 물 부족을 겪는 많은 국가에서 주요한 대체수자원으로 간주되고 있으며, 생활용수, 공업용수, 농업용수 등의 다양한 형태로 이용되고 있다. 본 연구에서는 DSSAT을 이용하여 하수 처리수의 농업용수 재이용에 따른 논벼의 수확량을 모의하고 분석하였다. 하수처리수의 농업용수 재이용에 따른 논벼 수확량 분석을 위하여 기상, 토양, 관개량 및 관개수 수질 등의 입력자료를 구축하였다. DSSAT을 이용한 논벼 수확량의 모의치와 수원시 하수처리장 인근에 조성된 시험포장에서 실측한 4년간(2006년~2009년)의 수확량 자료와의 비교를 통해 작물생육모형의 적용성을 평가하였다. DSSAT을 이용한 논벼 수확량의 모의치는 실제 수확량과 높은 상관관계를 보여줌으로서 하수재이용에 따른 논벼 수확량 분석에서 작물생육모형이 적용 가능한 것으로 나타났다.

• Korean Journal of Organic Agriculture
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• v.11 no.2
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• pp.103-113
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• 2003

The chemical properties of oak tree wood vinegar and the effect of wood vinegar on the tomato seedling were investigated to apply wood vinegar efficiently to the organic - and natural farming system. On the basis of the results from chemical properties of the oak tree wood vinegar, mineral nutrient contents of wood vinegar was low. Therefore, wood vinegar could not be a suitable nutrient source for the plant growth at 500∼1000 times dilution level. which commonly used in the farming, if only wood vinegar is supplied for the nutrient source for the plant growth. The application of wood vinegar increased root growth up the 500 times dilution level while decreased shoot growth. Furthermore. the anion concentrations such as nitrate and phosphate of the plant were decreased by the application of wood vinegar while cation concentrations such as K. Ca. and Mg were increased. Phenolic compounds of wood vinegar such as chlorogenic acid and ferulic acid enhanced the root growth. Interestingly the application of ferulic acid increased both root and shoot growth at the level of 10$^{-4}$ M concentration. It indicated that the effect of wood vinegar on the production of healthy plant seedling may be due to the beneficial root growth by phenolic compounds such as chlorogenic acid and/or ferulic acid of the wood vinegar. However. the effect of the wood vinegar on the plant growth could be influenced by synergism or antagonism of different phenolic compounds in wood vinegar used. In addition. drench in the soil of wood vinegar may be more beneficial compared to foliar application for the improvement of root activity and plant growth.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1199-1206
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• 2021

Accordingly, attention is also being paid to the agricultural use of remote sensing technique that non-destructively and continuously detects the growth and physiological status of crops. However, when remote sensing techniques are used for crop monitoring, it is possible to continuously monitor the abnormality of crops in real time. For this, standard growth information of crops is required and relative growth considering the cultivation environment must be identified. With the relationship between GDD (Growing Degree Days), which is the cumulative temperature related to crop growth obtained from ideal cultivation management, and the vegetation index as standard growth information, compared with the vegetation index observed with the spectralreflectance sensor(SRS_NDVI & SRS_PRI) in each rice paddy treated with standard cultivation management and non-fertilized, it was quantitatively identified as a time series. In the future, it is necessary to accumulate a database targeting various climatic conditions and varieties in the standard cultivation management area to establish a more reliable standard growth information.

• Proceedings of the KGS Conference
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• 2003.11a
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• pp.54-58
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• 2003

작물은 각 지역의 기후 특성을 잘 반영하는 기후 경관 중의 하나이다. 작물의 분포는 농업기술의 발달정도, 작물의 수익성 등의 영향을 받지만 기후의 영향이 가장 크다. 그 지역의 기후 특성에 알맞은 작물을 심어야 생육이 활발하며 생산량도 증가한다. 반면에 기후 조건에 맞지 않은 작물을 재배할 경우 생육이 불량하며 수량성도 떨어진다. 그러므로 기후 환경은 지역마다 다양한 작물의 분포를 야기 시킨다. (중략)

• Smart Media Journal
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• v.11 no.2
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• pp.53-62
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• 2022

Due to the accelerated global warming phenomenon after industrialization, the frequency of changes in the existing environment and abnormal climate is increasing. Agriculture is an industry that is very sensitive to climate change, and global warming causes problems such as reducing crop yields and changing growing regions. In addition, environmental changes make the growth period of crops irregular, making it difficult for even experienced farmers to easily estimate the growth stage of crops, thereby causing various problems. Therefore, in this paper, we propose a CNN model for estimating the growth stage of crops. The proposed model was a model that modified the pooling layer of ResNet, and confirmed the accuracy of higher performance than the growth stage estimation of the ResNet and DenseNet models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.68-78
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• 2020

Crop models have been used to predict vegetable crop yield, which would have a considerable economic impact on consumers as well as producers. A small number of models have been developed to estimate growth and yield of vegetables due to limited availability of growth observation data in high-quality. In this study, we aimed to analyze the protocols designed for collection of the observation data for major vegetable crops including cabbage, radish, garlic, onion and pepper. We also designed the protocols suitable for development and verification of a vegetable crop growth model. In particular, different measures were proposed to improve the existing protocol used by Statistics Korea (KOSTAT) and Rural Development Administration (RDA), which would enhance reliability of parameter estimation for the crop model. It would be advantageous to select sampling sites in areas where reliable weather observation data can be obtained because crop models quantify the response of crop growth to given weather conditions. It is recommended to choose multiple sampling sites where climate conditions would differ. It is crucial to collect time series data for comparison between observed and simulated crop growth and yield. A crop model can be developed to predict actual yield rather than attainable yield using data for crop damage caused by diseases and pests as well as weather anomalies. A bigdata platform where the observation data are to be shared would facilitate the development of crop models for vegetable crops.

• Proceedings of the Korean Society of Crop Science Conference
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• 2021.04a
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• pp.58-58
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• 2021

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.129-129
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• 2019

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.120-120
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• 2019