• Title/Summary/Keyword: 작물 생육 모형

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Analysis of Reclaimed Wastewater Irrigation on Paddy Rice Yield Using DSSAT (작물생육모형을 이용한 하수처리수의 농업용수 재이용에 따른 논벼 수확량 분석)

  • Jeong, Han-Seok;Seong, Chung-Hyun;Jung, Ki-Woong;Kim, Kwang-Min;Park, Seung-Woo
    • 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.

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Analysis of Crop Survey Protocols to Support Parameter Calibration and Verification for Crop Models of Major Vegetables (주요 채소 작물 대상 작물 모형 모수 추정 및 검증을 지원하기 위한 생육 조사 프로토콜 분석)

  • Kim, Kwang Soo;Kim, Junhwan;Hyun, Shinwoo
    • 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.

Using spatial data and crop growth modeling to predict performance of South Korean rice varieties grown in western coastal plains in North Korea II. Genetic coefficients of South Korean cultivars for CERES-Rice (공간정보와 생육모의에 의한 남한 벼 품종의 북한 서부지대 적응성 예측 II. 남한 벼 품종의 모수 추정)

  • 김재영;한상욱;김희동;김영호
    • Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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    • 2002.11a
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    • pp.69-72
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    • 2002
  • 작물생육모형은 작물의 광합성과정 등 주요 생리과정을 정량적으로 연구하기 위해 30여 년 전부터 소개되기 시작하였다. 다양한 환경조건 하에서 생장 및 발육의 종합적인 모의가 가능한 정도로 발전한 최근에는 주요 식량작물에 대해 실용수준의 모형들이 개발되어 다양한 용도로 쓰이고 있다.(중략)

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Improving and Validating a Greenhouse Tomato Model "GreenTom" for Simulating Artificial Defoliation (적엽작업을 반영하기 위한 시설토마토 생육모형(GreenTom) 개선 및 검증)

  • Kim, Yean-Uk;Kim, Jin Hyun;Lee, Byun-Woo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.4
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    • pp.373-379
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    • 2019
  • Smart-farm has been spreading across Korea to improve the labor efficiency and productivity of greenhouse crops. Although notable improvements have been made in the monitoring technologies and environmental-controlling systems in greenhouses, only a few simple decision-support systems are available for predicting the optimum environmental conditions for crop growth. In this study, a tomato growth model (GreenTom), which was developed by Seoul National University in 1997, was calibrated and validated to examine if the model can be used as a decision-supporting system. The original GreenTom model was not able to simulate artificial defoliation, which resulted in overestimation of the leaf area index in the late growth. Thus, an algorithm for simulating the artificial defoliation was developed and added to the original model. The node development, leaf growth, stem growth, fruit growth, and leaf area index were generally well simulated by the modified model indicating that the model could be used effectively in the decision-making of smart greenhouse.

Assessing the Climate Change Impacts on Future Upland Drought using the Soil Moisture Model and CMIP5 GCMs (CMIP5 GCMs와 토양수분모형을 이용한 기후변화에 따른 미래 밭가뭄 평가)

  • Jeon, Min-Gi;Nam, Won-Ho;Hong, Eun-Mi;Hwang, Seon-Ah
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.66-66
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    • 2020
  • 최근 기후변화로 인한 전 세계적인 기온상승이 야기되고 있으며, 농업에 직접적인 영향을 주는 기상학적 및 수문학적 변화가 급격하게 진행되고 있다. 우리나라의 경우 최근 7년 동안 지역별로 극심한 가뭄이 매년 발생하고 있고, 가뭄의 발생 빈도와 강도가 증가하는 추세이다. 특히 밭의 경우 농업용 저수지 등 수리시설물로부터 관개용수를 공급받는 논 작물과 달리 자연 강우를 통해 필요한 용수량을 공급받는 천수답이 대부분이고 관개시설이 부족하기 때문에, 기후변화에 의한 가뭄의 취약성이 높다. 밭작물은 작물의 생육 시기와 기후 환경, 수자원 환경에 민감하고 토양수분을 흡수함으로써 생육하기 때문에 이러한 밭작물의 소비수량 및 관개용수량은 증발산량 뿐만 아니라 토양내 수분의 이동을 고려하여 수분 부족량을 산정해야 한다. 본 연구에서는 미래 기후변화에 의한 밭가뭄 평가를 위하여 밭 작물별 소비수량 및 관개용수량을 추정하기 위한 밭 토양수분 물수지 모형 (Soil Moisture Model)을 구성하였다. 또한 대표농도경로 (Representative Concentration Pathway, RCP) 시나리오 기반의 제5차 결합기후모델상호비교사업 (Coupled Model Intercomparison Project Phase 5, CMIP5)에서 제공하는 RCP 시나리오를 기반으로 한 전지구 기후모델 (General Circulation Model, GCM)의 기후예측결과를 적용함으로써 미래 밭 가뭄 평가를 수행하였다. 과거 기상자료 및 미래 대표농도경로 시나리오와 작물 기초자료를 수집하여 과거 및 미래 작물증발산량을 산정하였으며, 토양수분 물수지 모형에 적용하여 밭작물의 토양수분 변화를 모의하고 기후변화에 따른 작물별/생육시기별 소비수량 및 관개용수량을 추정하였다.

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Development of fertilizer-distributed algorithms based on crop growth models (작물생육모형 기반 비료시비량 분배 알고리즘 개발)

  • Doyun Kim;Yejin Lee;Tae-Young Heo
    • The Korean Journal of Applied Statistics
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    • v.36 no.6
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    • pp.619-629
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    • 2023
  • Fertilizers are crucial for increasing crop yield, but using too much of them without taking into account the nutrients that the crops need can increase costs for farm management and have a negative impact on the environment. Through smart agriculture, fertilizers can be applied as needed at the right time to reflect the growth characteristics of crops, reducing the burden of fertilizer losses and providing economical nutrient management. In this study, we use the total dry weight of field-cultivated red pepper and green onion grown in various growing environments to fit a nonlinear model-based crop growth model using different growth curves (logistic, Gompertz, Richards, and double logistic curve), and we propose a fertilizer distributed algorithm based on crop growth rate.

Production of Farm-level Agro-information for Adaptation to Climate Change (기후변화 대응을 위한 농장수준 농업정보 생산)

  • Moon, Kyung Hwan;Seo, Hyeong Ho;Shin, Min Ji;Song, Eung Young;Oh, Soonja
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.3
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    • pp.158-166
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    • 2019
  • Implementing proper land management techniques, such as selecting the best crops and applying the best cultivation techniques at the farm level, is an effective way for farmers to adapt to climate change. Also it will be helpful if the farmer can get the information of agro-weather and the growth status of cultivating crops in real time and the simulated results of applying optional technologies. To test this, a system (web site) was developed to produce agro-weather data and crop growth information of farms by combining agricultural climate maps and crop growth modeling techniques to highland area for summer-season Chinese cabbage production. The system has been shown to be a viable tool for producing farm-level information and providing it directly to farmers. Further improvements will be required in the speed of information access, the microclimate models for some meteorological factors, and the crop growth models to test different options.

History and Future Direction for the Development of Rice Growth Models in Korea (벼 작물생육모형 국내 도입 활용과 앞으로의 연구 방향)

  • Kim, Junhwan;Sang, Wangyu;Shin, Pyeong;Baek, Jaekyeong;Cho, Chongil;Seo, Myungchul
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.3
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    • pp.167-174
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    • 2019
  • A process-oriented crop growth model can simulate the biophysical process of rice under diverse environmental and management conditions, which would make it more versatile than an empirical crop model. In the present study, we examined chronology and background of the development of the rice growth models in Korea, which would provide insights on the needs for improvement of the models. The rice crop growth models were introduced in Korea in the late 80s. Until 2000s, these crop models have been used to simulate the yield in a specific area in Korea. Since then, improvement of crop growth models has been made to take into account biological characteristics of rice growth and development in more detail. Still, the use of the crop growth models has been limited to the assessment of climate change impact on crop production. Efforts have been made to apply the crop growth model, e.g., the CERES-Rice model, to develop decision support system for crop management at a farm level. However, the decision support system based on a crop growth model was attractive to a small number of stakeholders most likely due to scarcity of on-site weather data and reliable parameter sets for cultivars grown in Korea. The wide use of the crop growth models would be facilitated by approaches to extend spatial availability of reliable weather data, which could be either measured on-site or estimates using spatial interpolation. New approaches for calibration of cultivar parameters for new cultivars would also help lower hurdles to crop growth models.