• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.200-200
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• 2020

본 연구에서는 SWAT 모형과 APEX-Paddy 모형의 연계 모델링을 통한 대표 BMP(Best management practice) 적용, 정식시기 및 벼 생육기간을 고려한 시나리오 적용을 통해 농업용수의 관리 및 수질환경 개선 등에 활용할 수 있는 저영향 영농활동을 분석하고자 하였다. 만경강 유역을 대상으로 SWAT 모형을 구축하고 유역 내에 위치한 논 시험포장을 대상으로 강우-유출 및 비점오염원 모니터링 자료를 활용하여 APEX-Paddy 모형을 구축하였다. SWAT 모형과 APEX 모형을 연계하여 유역의 수문, 수질에 대한 정밀한 모델링을 수행하였으며, 이는 저영향 영농활동을 분석하기 위한 필드단위의 정확한 결과를 유역차원에 반영하기 위함이다. 특히, 본 연구에 사용된 APEX-Paddy 모형은 농촌진흥청과 Texas A&M의 공동연구를 통해 개발된 새로운 모형으로서 한국의 논 영농활동 및 담수환경을 반영하여 논에서의 유출 및 비점오염원을 모의할 수 있다. 연계 모형의 적합성 평가를 위해 R² (Determine of Coefficient), RMSE (Root mean square error), NSE (Nash-sutcliffe efficiency)를 사용하였다. 적합성 평가 지표를 분석한 결과, 유출량은 R² 평균 0.91, RMSE 평균 2.87 mm/day, NSE 평균 0.78로 나타났다. T-N 부하량은 R² 평균 0.74, RMSE 평균 59.3 kg/ha/day, NSE 평균 0.50으로 나타났다. 저영향 영농활동 관리방안을 위한 시나리오로 1) 논의 물꼬높이(BMP) 관리 적용, 2) 벼 생육기간 조절을 고려하여 기온변화에 따른 정식시기, 벼 생육기간 등을 조정하여 적용하였다. 기후변화 시나리오는 10개 GCM 모델의 RCP 8.5 시나리오를 통해 분석하였으며, 유역차원의 미래 영향을 분석한 결과, 물꼬관리 BMP에 따라 담수심이 증가되며, 관개량이 감소하고 유출량 10.7%, T-N 11.2% 저감되는 것을 나타냈으며, 벼 생육기간 조절은 BMP보다 상대적으로 효과가 높진 않았지만, 유출량 1.4%, T-N 3.1%의 저감효과를 나타냈다. 따라서 두 가지의 저영향 영농활동 관리방안은 미래기간의 기후변화에 대응하여 농업용수 및 물관리에 도움이 될 것으로 사료된다. 하지만 본 연구결과는 모델링 결과에 의존한 것이며, 추후 지속적인 연구와 보완이 필요하다.

• Journal of The Korean Society of Grassland and Forage Science
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• v.12 no.3
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• pp.64-129
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• 1992

최근 초지중심 사양형태의 증가와 초지면적의 확대에 따라 단순한 사료로서가 아니라 영양가치가 높고 기호성이 높은 목초생산이 요구되고 있다. 그러나, 고위생산을 위해 다량으로 사용된 질소질비료에 의하여 질산태 중독 등의 문제가 야기되고 있어 목초의 생리 및 영양에 관한 연구가 필요하게 되었다. 사료성분 혹은 영양가치에 대한 연구는 이미 일찍부터 다루어져 왔으나, 주로 야초류, 청예작물 및 농가부산물 등의 일반성분 특히, 조단백질과 조섬유함량의 연구가 주가 되었고 다년생 목초류에 대한 연구는 1975년경부터 본격화 되기 시작하였다. 그동안 한국초지학회지와 축산학회지($1972\sim1991$)에 게재된 총 151편의 생리 및 영양에 관한 연구 중에서 다년생 목초류를 취급한 것은 불과 63편에 머물고 있다. 이 분야의 연구는 각종 목초 사료작물에 대한 재배조건과 생육단계에 따른 생리생태학적 연구와 사료성분, 소화율 및 가소화양분 함량의 일반적인 변화, 경향을 검토하여 사료 가치 평가를 위한 기준으로 삼았다. 그러나 다년생 목초류는 물론 사료 작물에 있어서 육종 생리분야의 연구는 매우 미흡한 상태로써 단지 발아, 생육, 저장탄수화물 및 유독성분 등 단편적인 연구만이 행해지고 있을 뿐이다. 또한 사료 성분이 가축의 기호성에 미치는 영향을 구명하기 위한 연구는 거의 이루어지고 있지 않으므로 금후 탄수화물과 미량 요소에 대한 자세한 연구 검토가 필요하다고 생각된다. 특히 목초와 사료작물의 화학적인 조성과 가축의 생리에 관련한 여러가지 문제들도 앞으로 보다 깊이 연구되어야 할 과제라고 생각된다.권을 잡기 위해 10년지기였던 IBM과 MS사는 각각 OS/2와 윈도즈를 내세우고 양보할 수 없는 힘겨루기에 들어갔다. 또 이들 양사는 펜컴퓨터,멀티미디어등 차세대제품의 운영체제 시장을 둘러싸고 일찍부터 격전에 들어갔으며 IBM과 MS사의 혼전을 틈타 썬마이크로시스템을 필두로한 워크스테이션 업체 및 유닉스진영까지 고성능 PC시장을 겨냥한 OS를 속속 개발, 90년대의 OS 전쟁은 한치 앞을 내다볼 수 없는 안개국면으로 접어들고 있다. DOS에서 32비트시대,펜컴퓨터, 멀티미디어에 이르는 차세대제품을 둘러싼 업계의 OS 쟁탈전을 통해 OS의 발전동향과 미래를 전망해 본다. results in the large change of the objective function, the sum of squares of deviations of the observed and computed groundwater levels. 본 논문에서는 가파른 산사면에서 산사태의 발생을 예측하기 위한 수문학적 인 지하수 흐름 모델을 개발하였다. 이 모델은 물리적인 개념에 기본하였으며, Lumped-parameter를 이용하였다. 개발된 지하수 흐름 모델은 두 모델을 조합하여 구성되어 있으며, 비포화대 흐름을 위해서는 수정된 abcd 모델을, 포화대 흐름에 대해서는 시간 지체 효과를 고려할 수 있는 선형 저수지 모델을 이용하였다. 지하수 흐름 모델은 토층의 두께, 산사면의 경사각, 포화투수계수, 잠재 증발산 량과 같은 불확실한 상수들과 a, b, c, 그리고 K와 같은 자유모델변수들을 가진다. 자유모델변수들은 유입-유출 자료들로부터 평가할 수

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.72-80
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• 2023

Melons, a rich source of vitamins and fibers, are commonly grown in the soil. Hydroponic cultivation could improve yield and quality of melon and selection of substrate volume and the kind of substrates is important for hydroponic cultivation of melons. This study investigated the effect on melon growth according to volume of granular rockwool and substrates of coir and rockwool slab. 'Geumsegye' melon (Cucumis melo L. cv. Geumsegye) was cultivated hydroponically according to volume of granular rockwool to 1.0, 1.5, 2.0, 3.0, and 4.0 L, and was also cultivated using coir and rockwool slabs. Logistic model was applied to estimate the growth characteristics of melons such as plant height, leaf length, leaf width, and the characteristics of fruit. The growth characteristics of melons were significantly increased at 4.0 L compared to those grown of 1.0 L volume of on granular rockwool, and the results were the highest in coir and rockwool slabs. Melons grown in rockwool slabs showed the largest fruit fresh weight, fruit length, and fruit width. During hydroponic cultivation, growth characteristics of melon appropriate at the 4.0 L volume of granular rockwool, and the highest at coir and rockwool slabs. This study provides a basis for understanding the effect of root zone environment to the growth characteristics and fruit quality of non-netted melon.

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.48-56
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• 2023

High-pressure sodium (HPS) lamps have been widely used as a useful supplemental light source to emit sufficient photosynthetically active radiation and provide a radiant heat, which contribute the heat requirement in greenhouses. The objective of this study to analyze the thermal characteristics of HPS lamp and thermal behavior in supplemented greenhouse, and evaluate the performance of a horizontal leaf temperature of sweet pepper plants using computational fluid dynamics (CFD) simulation. We simulated horizontal leaf temperature on upper canopy according to three growth stage scenarios, which represented 1.0, 1.6, and 2.2 plant height, respectively. We also measured vertical leaf and air temperature accompanied by heat generation of HPS lamps. There was large leaf to air temperature differential due to non-uniformity in temperature. In our numerical calculation, thermal energy of HPS lamps contributed of 50.1% the total heat requirement on Dec. 2022. The CFD model was validated by comparing measured and simulated data at the same operating condition. Mean absolute error and root mean square error were below 0.5, which means the CFD simulation values were highly accurate. Our result about vertical leaf and air temperature can be used in decision making for efficient thermal energy management and crop growth.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.563-566
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• 2017

In order to prevent livestock diseases and produce the high quality livestock products in the livestock industry, it is necessary to manage the conditions of the livestock farms in the optimal condition. Therefore, these days the research on livestock growth models that analyze the factors of the air environment, the breeding environment, and the numerical rules of livestock in vivo is being carried out to improve and manage the environment in which livestock are kept. However, conventional models of growth are not sufficient to support the decision-making to control complex environment in pen by analyzing and interpreting air environment and breeding environment in a complex way. In this paper, we propose a method to control the complex environment in pen by using artificial neural network model based on biological information, air environment, breeding environment and production information.

• Journal of Bio-Environment Control
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• v.22 no.2
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• pp.182-187
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• 2013

In closed plant production system like plant factory, changes in environmental factors should be identified for conducting efficient environmental control as well as predicting energy consumption. Since high relative humidity (RH) is essential for crop production in the plant factory, transpiration is closely related with RH and should be quantified. In this study, four varieties of lettuces (Lactuca sativa L.) were grown in a plant factory, and the leaf areas and transpiration rates of the plants according to DAT (day after transplanting) were measured. The coefficients of the simplified Penman-Monteith equation were calibrated in order to calculate the transpiration rate in the plant factory and the total amount of transpiration during cultivation period was predicted by simulation. The following model was used: $E_d=a*(1-e^{-k*LAI})*RAD_{in}+b*LAI*VPD_d$ (at daytime) and $E_n=b*LAI*VPD_n$ (at nighttime) for estimating transpiration of the lettuce in the plant factory. Leaf area and transpiration rate increased with DAT as exponential growth. Proportional relationship was obtained between leaf area and transpiration rate. Total amounts of transpiration of lettuces grown in plant factory could be obtained by the models with high $r^2$ values. The results indicated the simplified Penman-Monteith equation could be used to predict water requirements as well as heating and cooling loads required in plant factory system.

• Journal of Mushroom
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• v.17 no.4
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• pp.211-217
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• 2019

Currently, cultivation of mushrooms using the Information and Communication Technology (ICT)-based smart farming technique is increasing rapidly. The main environmental factors for growth of mushrooms are temperature, humidity, carbon dioxide (CO₂), and light. Among all the mentioned factors, currently, only temperature has been maintained under automatic control. However, humidity and ventilation are controlled using a timer, based on technical experience.Therefore, in this study, a Pleurotus eryngii first-generation smart farm model was set up that can automatically control temperature, humidity, and ventilation. After installing the environmental control system and the monitoring device, the environmental condition of the mushroom cultivation room and the growth of the fruiting bodies were studied. The data thus obtained was compared to that obtained using the conventional cultivation method.In farm A, the temperature during the primordia formation stage was about 17℃, and was maintained at approximately 16℃ during the fruiting stage. The humidity was initially maintained at 95%, and the farm was not humidified after the primordia formation stage. There was no sensor for CO₂ management, and the system was ventilated as required by observing the shape of the pileus and the stipe. It was observed that, the concentration of CO₂ was between 700 and 2,500 ppm during the growth period. The average weight of the mushrooms produced in farm A was 125 g, and the quality was between that of the premium and the first grade.In farm B. The CO₂ sensor was in use for measurement purposes only; the system was ventilated as required by observing the shape of the pileus and the stipe. During the growth period, the CO₂ concentration was observed to be between 640 and 4,500 ppm. The average weight of the mushrooms produced in farm B was 102 g.These results indicate that the quality of the king oyster mushroom is determined by the environmental conditions, especially by the concentration of CO₂. Thus, the data obtained in this study can be used as an optimal smart farm model, where, by improving the environmental control method of farm A, better quality mushrooms were obtained.

• Journal of the Korean Institute of Landscape Architecture
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• v.31 no.4
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• pp.90-100
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• 2003

본 연구는 기존 건축물 옥상녹화에 이용 가능한 저토심 옥상녹화 시스템 을 연구하고 개발하고자 수행되었다. 연구목적을 달성하기위해서 시스템의 개념적 모델이 선행 연구로부터 유추되었고 개념적 모델로부터 실험을 위한 시스템들이 제안되었다. 건축물 옥상 위에 설치된 이 시스템들에서 기린초의 생육에 대하여 인공배지 종류, 토심, 그리고 배수 형태의 효과들이 2002년 4월 3일부터 10월 18일까지 연구되었다. 인공배지 종류는 단용과 혼용이고, 토심은 5cm, l0cm,그리고 15cm이며, 배수 형태는 저수$.$배수형과 배수형으로 하였다. 여기서, 인공배지 단용은 폐유리 미분 100에 발포제를 1∼2정도 첨가하고, 착색제를 1정도 첨가한 후, 6∼8$^{\circ}C$/min로 승온하여 750∼85$0^{\circ}C$의 온도에서 발포시킨 다공질 유리를 수냉식으로 급랭하고, 분쇄기로 이송하여 l0mm이하로 분쇄하고 입도를 조절하여 얻어진 다공질 유리 파쇄물과 수피를 부피 비 6:4로 혼합하여 조성된 것이며 인공배지 혼용은 인공배 지 단용에 양토(모래 46%, 미사 40%, 점토 14%)를 부피비 5:5로 혼합하여 조성된 것이다. 피복면적, 지상부와 지하부의 생체중과 건물중, 그리고 시각적 질을 조사하였다. 각 변수들은 던칸의 다중범위 검정으로 통계처리 하였으며 처리들간의 유의수준은 5%였다. 그리고 기존 건축물 옥상에 대한 과부하의 위험을 피하기 위해서 각 시스템의 중량이 평가되었다. 그 결과를 요약하면 다음과 같다. 실험기간 중에 피복면적에 대한 배수 형태의 효과는 유의성 있는 차이를 나타내지 않았다. 인공배지 혼용의 피복면적은 인공배지 단용의 것보다 통계적으로 유의성 있게 높았다. 토심 5cm처리의 피복면적은 나머지 처리들의 피복면적보다 통계적으로 유의성 있게 낮았다. 토심 l0cm처리와 토심 15cm처리는 통계적으로 유의성이 없는 것으로 나타났다. 지상부와 뿌리의 생체중 및 건물중과 시각적 질에 대한 처리들의 효과는 피복면적에 대한 것과 유사하거나 동일하였다. 결과적으로, 기린초의 생육은 인공배지 단용보다 인공배지 혼용에서 더 높았고, 토심 10∼15cm에서 더 높았으며, 배수 형태에서는 뚜렷한 차이를 나타내지 않았다. 이 결과를 토대로, 기존 건축물 옥상에 적용 가능한 시스템의 허용하중과 기린초의 생육을 동시에 고려해볼 때, 저토심 옥상녹화 시스템 은 인공배지 종류에서는 혼용이, 토심은 10cm, 그리고 배수형태는 배수형이 적합하다고 보았다. 제안된 조건으로 조성된 시스템은 인공배지가 포장용수량상태일 때 그 중량이 약 115kg/$m^2$정도로 나타났다.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.699-708
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• 2017

The present study was to develop an approach for predicting soybean yield using a crop growth simulation model at the regional level where the detailed and site-specific information on cultivation management practices is not easily accessible for model input. CROPGRO-Soybean model included in Decision Support System for Agrotechnology Transfer (DSSAT) was employed for this study, and Illinois which is a major soybean production region of USA was selected as a study region. As a first step to predict soybean yield of Illinois using CROPGRO-Soybean model, genetic coefficients representative for each soybean maturity group (MG I~VI) were estimated through sowing date experiments using domestic and foreign cultivars with diverse maturity in Seoul National University Farm ($37.27^{\circ}N$, $126.99^{\circ}E$) for two years. The model using the representative genetic coefficients simulated the developmental stages of cultivars within each maturity group fairly well. Soybean yields for the grids of $10km{\times}10km$ in Illinois state were simulated from 2,000 to 2,011 with weather data under 18 simulation conditions including the combinations of three maturity groups, three seeding dates and two irrigation regimes. Planting dates and maturity groups were assigned differently to the three sub-regions divided longitudinally. The yearly state yields that were estimated by averaging all the grid yields simulated under non-irrigated and fully-Irrigated conditions showed a big difference from the statistical yields and did not explain the annual trend of yield increase due to the improved cultivation technologies. Using the grain yield data of 9 agricultural districts in Illinois observed and estimated from the simulated grid yield under 18 simulation conditions, a multiple regression model was constructed to estimate soybean yield at agricultural district level. In this model a year variable was also added to reflect the yearly yield trend. This model explained the yearly and district yield variation fairly well with a determination coefficients of $R^2=0.61$ (n = 108). Yearly state yields which were calculated by weighting the model-estimated yearly average agricultural district yield by the cultivation area of each agricultural district showed very close correspondence ($R^2=0.80$) to the yearly statistical state yields. Furthermore, the model predicted state yield fairly well in 2012 in which data were not used for the model construction and severe yield reduction was recorded due to drought.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.246-251
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• 2017

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.