• 한국작물학회:학술대회논문집
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• 한국작물학회 2019년도 추계학술대회
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• pp.19-19
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• 2019

It is necessary to maintain stable crop productions under the unsuitable environments, because the drought and flood may be frequently caused by the global warming. Therefore, it is agent to improve the crop growth model corresponded to soil moisture status. Chili pepper (Capsicum annuum) is one of the useful crop in Asia, and then it is affected by change of precipitation in consequence drought and flood occur however crop model to evaluate water stresses on chili pepper is not enough yet. In this study, development of crop model under different soil moisture status was attempted. The experiment was conducted on the slope fields in the greenhouse. The water level was kept at 20cm above the bottom of the container. Habanero (C. chinense) was used as material for crop model. Sap bleeding rate, SPAD value, chlorophyll content, stomatal conductance, leaf water potential, plant height, leaf area and shoot dry weight were measured at 10 days after treatment (DAT) and 13 DAT. Moreover, temperature and RH in the greenhouse, soil volume water contents (VWC) and soil water potential were measured. As a result, VWC showed 4.0% at the driest plot and 31.4% at the wettest plot at 13 DAT. The growth model was calculated using WVC and the growth analysis parameters. It was considered available, because its coefficient of determination showed 0.84 and there are significant relationship based on plants physiology among the parameters and the changes over time. Furthermore, we analyzed the important factors for higher accuracy prediction using multiple regression analysis.

• 농업과학연구
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• 제43권4호
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• pp.537-546
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• 2016

The development of models for agriculture systems, especially for crop production, has supported the prediction of crop yields under various environmental change scenarios and the selection of better crop species or cultivar. Crop models could be used as tools for supporting reasonable nutrient management approaches for agricultural land. This paper outlines the simplified structure of main crop models (crop growth model, crop-soil model, and crop-soil-environment model) frequently used in agricultural systems and shows diverse application of their simulated results. Crop growth models such as LINTUL, SUCROS, could provide simulated data for daily growth, potential production, and photosynthesis assimilate partitioning to various organs with different physiological stages, and for evaluating crop nutrient demand. Crop-Soil models (DSSAT, APSIM, WOFOST, QUEFTS) simulate growth, development, and yields of crops; soil processes describing nutrient uptake from root zone; and soil nutrient supply capability, e.g., mineralization/decomposition of soil organic matter. The crop model built for the DSSAT family software has limitations in spatial variability due to its simulation mechanism based on a single homogeneous field unit. To introduce well-performing crop models, the potential applications for crop-soil-environment models such as DSSAT, APSIM, or even a newly designed model, should first be compared. The parameterization of various crops under different cultivation conditions like those of intensive farming systems common in Korea, shortened crop growth period, should be considered as well as various resource inputs.

• 한국작물학회지
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• 제52권4호
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• pp.393-402
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• 2007

Remote sensing data can be integrated into crop models, making simulation improved. A crop model that uses remote sensing data was evaluated for its capability, which was performed through comparing three different methods of canopy measurement for cotton(Gossypium hirsutum L.). The measurement methods used were leaf area index(LAI), hand-held remotely sensed perpendicular vegetation index(PVI), and satellite remotely sensed PVI. Simulated values of cotton growth and lint yield showed reasonable agreement with the corresponding measurements when canopy measurements of LAI and hand-held remotely sensed PVI were used for model calibration. Meanwhile, simulated lint yields involving the satellite remotely sensed PVI were in rough agreement with the measured lint yields. We believe this matter could be improved by using remote sensing data obtained from finer resolution sensors. The model not only has simple input requirements but also is easy to use. It promises to expand its applicability to other regions for crop production, and to be applicable to regional crop growth monitoring and yield mapping projects.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2000년도 추계 학술대회지
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• pp.12-27
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• 2000

During the recent decades, he problem of climate variability and change has been in the forefront of scientific problems. The objective of this study was to assess the impact of climate variability on crop growth and yield. The growth duration was the main impact of climate variability on crop yield. Phyllochronterval was shortened in the global worming situations. A simple model to describe developmental traits was provided from heading data of directly seeded rice cultivars and temperature data. Daily mean development rate could be explained by the average temperature during the growth stage. Simple regression equation between daily mean development rate(x) and the average temperature(y) during the growth period as y = ax + b. It can be simply modified as x = 1/a $\ast$ (y-b). The parameters of the model could depict the thermo sensitivity of the cultivars. On the base of this model, the three doubled CO2 GCM scenarios were assessed. The average of these would suggest a decline in rice production of about 11% if we maintained the current cultivars. Future cultivar's developmental traits could be suggested by the two model parameters.

• Journal of Biosystems Engineering
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• 제24권5호
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• pp.445-452
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• 1999

This study was conducted to develop a searching algorithm for optimal daily temperature setpoint greenhouse. An algorithm using crop growth and energy models was developed to determine optimum crop growth environment. The results of this study were as follows: 1. Mathematical models for crop growth and energy consumption were derived to define optimal daily temperature setpoint. 2. Optimum temperature setpoint, which could maximize performance criterion, was determined by using Pontryagin maximum principle. 3. Dynamic control of daily temperature using the developed algorithm showed higher performance criterion than static control with fixed temperature setpoint. Performance criteria for dynamic control models were with simulated periodic weather data and with real weather data, increased by 48% and 60%, respectively.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2004년도 춘계 학술대회지
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• pp.104-105
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• 2004

[ $\bigcirc$ ] In the phenology model of ORYZA2000, the effect of photoperiod on the developmental rate was a little ignored because most crop parameters were measured with IRRI varieties which are insensitive to photoperiod, therefore it is very difficult to apply this phenology model directly to Korean varieties which are usually sensitive to photoperiod. $\bigcirc$ After introducing PPFAC and PPSE to improve the phenology model, the precision of heading date prediction was improved but not satisfied. $\bigcirc$ In the growth simulation using data from several regions, yield tended to be overestimated under high nitrogen applicated condition. $\bigcirc$ The precision of yield was much improved by introducing nitrogen use efficiency, but still different between regions because of different soil fertility or property of irrigation water between regions

• Journal of Biosystems Engineering
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• 제24권1호
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• pp.25-30
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• 1999

The effectiveness of many greenhouse environment control methodologies depends on the growth information of crops. Acquisition of the growth information of crops requires a non-invasive and continuous monitoring method. Crop growth monitoring system using digital imaging technique was developed to conduct non-destructive and intact plant growth analyses. The monitoring system automatically measures crop growth information sends an appropriate control signal to the nutrient solution supplying system. To develop the monitoring system, a linear model that explains the relationship between the fresh weight and the top projected leaf area of a lettuce plant was developed from an experiment. The monitoring system was evaluated buy successive lettuce growing experiments. Results of the experiments showed that the developed system could estimate the fresh weight of lettuce from a lettuce image by using the linear model and generate an EC control signal according to the lettuce growth stage.

• 한국농림기상학회지
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• 제21권3호
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• pp.167-174
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• 2019

작물 생육모형은 기존의 경험적 작물모형과는 달리 벼의 생장과정을 모의 할 수 있는 장점이 있다. 이러한 작물생육 모형들은 80년대 후반부터 적극적으로 국내도입이 이루어 졌다. 유럽에서 개발된 MACROS로 부터 시작하여 이후 Oryza1 및 Oryza2000 모형과 북미에서 개발된 DSSAT 계열의 모형인 CERES-RICE 모형을 도입하게 되었다. 각각의 모형들은 최초에는 단순히 품종수 적합 후 특정지역에의 수량을 모의하는데 활용되었으나 2000년대에 이르러서는 국내에 적합한 작물모형으로 발전시킬 수 있는 단계에 이르게 되었다. 그러나, 작물생육모형을 기후변화 영향평가를 위한 용도로 주로 사용하였고 실용적인 수준에서의 활용은 미미하였다. 일부 농가 적용을 위한 시도가 있었으나 널리 활용되지는 못하였다. 이러한 활용상의 문제점은 기상자료의 공간해상도가 문제가 가장 크며, 그 다음으로는 각 지역별이 품종에 대한 품종모수 자료가 부족하기 때문이다. 이러한 활용상의 문제점을 극복하기 위해서는 기상관측의 공간해상력을 높이기 위한 관측소의 확대 또는 공간 내삽법이 필요할 것으로 생각된다. 또한 신품종이 일정 재배면적 이상 확대될 경우 이에 대해 품종모수를 적합할 제도적 기술적 방법이 필요하다. 작물모형의 활용 확대를 위해서는 기상 또는 토양 분야와도 연결이 필요하다. 이를 위해서는 군락의 증산 속도와 토양모형에 정보가 필요하며 이는 군락 광합성 관련 부분과 토양 특성에 대해서 새로운 접근이 필요함을 의미한다.

• 한국농림기상학회지
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• 제15권4호
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• pp.282-290
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• 2013

대기와 지표면을 구성하고 있는 토양 및 식생은 생물리학적/생지화학적인 과정을 통해 서로 상호작용을 한다. 이러한 과정을 모의하기 위해 지표모델과 작물 생육모델이 사용되고 있다. 지표모델인 Noah MP 모델과 작물생육모델인 CERES-Rice 모델을 비교하기 위해 해남 플럭스 관측소 인근 지역에서 작물의 생육과 증발산량을 모의하였다. 플럭스 관측자료가 수집된 2003년부터 2012년까지 해남 플럭스 관측소의 주요 식생인 벼를 대상으로 생육과 증발산량을 모의되었다. Noah MP 모델은 단순한 식생 모의 과정으로 인해 개화기를 전후로 하는 벼의 LAI 변화양상을 정확하게 반영하지 못하였다. 벼의 생체중 예측에 있어서도 실제 관측될 수 있는 생체중보다 대략 10분의 1 수준에 해당하는 생체중이 모의되었다. 증발산량 모의의 경우에도, CERES-Rice 모델의 모의값보다 약 21%에 해당하는 증발산량을 모의하였다. 반면, CERES-Rice 모델의 경우 LAI의 변화와 생체중 모의 값은 실제의 벼 생육 양상과 유사할 것으로 추정되었다. 또한, 증발산량의 경우에도 해남 플럭스 관측소에서 측정된 값과 비교하였을 때 Noah-MP모델의 모의값이 CERES-Rice 모델의 모의값에 비해 RMSE 값이 1.8배 높았다. Noah MP 모델이 보이는 높은 오차값들은 Noah MP모델이 논의 지표상태를 적절히 반영하지 못하였기 때문으로 사료되었고, 특히 과소추정된 생체중을 보정하여 증발산량을 예측할 경우 오차를 30%까지 줄일 수 있을 것으로 보인다. 따라서, Noah MP 모델에 논에서의 지표 특성을 반영할 수 있다면 보다 정확한 물질순환과 에너지 교환을 예측할 수 있을 것으로 사료된다.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2011년도 학술발표회
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• pp.12-14
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• 2011

Crop growth simulation models have been developed as research and management tools. When these models are needed to incorporate new knowledge on phenology and physiology of crops, programming languages have been used for development and documentation of these models. However, researchers may have limited skill in programming languages. Furthermore, software developer may find it challenging to improve the crop models because documentation of the models are rarely available. The Unified Modeling Language (UML) can provide a simple approach for development and documentation of model. A template for implementation of the model can be obtained using the UML, which would facilitate code re-use and model improvement.