• 한국농림기상학회지
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• 제23권4호
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• pp.374-390
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• 2021

농산물 중에서도 노지채소는 생육특성상 기상요건의 변화에 민감하게 반응한다. 온난화로 인한 노지 채소류의 급격한 재배적지 및 생산성 변동의 대응 방안으로 작물모형을 활용한 연구가 활발히 진행되어 왔으며 신뢰도 높은 생산성 예측을 위해 관련된 다양한 요인에 대한 분석이 필요한 상황이다. 본 연구에서는 정밀한 작물 생육 모형의 개발에 앞서 대표적인 노지 채소 작물인 마늘과 양파를 대상으로 문헌 조사를 수행하여 생육 및 생산성과 관련된 모형 개발 연구 동향을 분석하였다. 또한, 작물의 생육 또는 생산성을 예측하는 모형에 관한 문헌들을 분류하여 모형 개발을 위한 시사점을 파악하고자 하였다. 이를 위해 문헌이 수록된 데이터베이스를 이용하여 키워드 조합으로 검색하여 얻어진 관련 문헌들을 수집하였으며, 텍스트마이닝 기법 중 워드클라우드와 의미연결망을 활용하여 수집된 논문들에서 나타난 연구 동향을 분석하였다. 또한 각각의 문헌들을 분석하여 양파와 마늘의 생육 및 수량에 영향을 미치는 요소를 탐색하였다. 그 결과 국내외 모두 식량작물인 벼에 비해 노지채소는 문헌 건수가 월등히 적었다. 또한 텍스트마이닝을 통한 분석결과 연구동향의 경우 기후변화와 원격탐사 등이 주로 검색되었으며, 작물생육 관련인자로는 기온, 관수 등이 많은 것으로 조사되었다. 문헌 분석을 통해 확인된 마늘과 양파의 생산성에 영향을 미치는 조건들은 환경 및 재배요인에 따라 다양하게 나타났는데, 토양 조건의 경우 토양 무기 성분, pH 농도 및 토양 수분 등이, 생산성과 관련된 재배관리 조건으로는 파종 시기, 품종, 종자처리 방식, 관수간격, 시비량 및 비료 성분 등이 주요 인자로 분류되었다. 기상 조건의 경우, 기온, 강수량, 일사량 및 습도 등이 다수의 문헌에서 주요 인자로 사용되었다. 본 연구의 결과들은 차후 추가적인 작물모형 개발에 활용할 수 있는 핵심적인 입력 요소를 파악하기 위해 사용될 수 있을 것으로 기대된다.

• Agribusiness and Information Management
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• 제7권1호
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• pp.1-9
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• 2015

The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.

• 원예과학기술지
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• 제31권1호
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• pp.103-109
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• 2013

Estimating the high tuber solids needs a simulation system on potato growth, and its development should be obtained by using agricultural elements which analyze the relationship between crop growth and agricultural factors. An accurate simulation to predict solids level against climatic change employs a calculation of in vivo energy consumption and bias for growth and induction shape in a slight environmental adaptation. So, to calculate in vivo energy consumption, this study took a concept of estimate of the amount of basal metabolism in each tuber. In the validation experiments, the results of measuring solid accumulation of potatoes harvested at dates suggested by simulation agreed with the actual measured values in each regional field during the growth period of years from 2006 till 2010. The mean values of tuber solids level and inter-annual level variation in validation experiments were predicted well by the simulation model. And also, the results of validation experiments represent that concentration of tuber solids were due mainly to the duration of sunshine, above 190 hours per a month, and the cumulative amount of radiation, above 2,200 $MJ{\cdot}m^{-2}$, of the effective growth period.

• 한국농림기상학회지
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• 제22권4호
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• pp.233-238
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• 2020

식물의 생리적 과정과 환경 요인 간 상호작용에 바탕을 둔 프로세스 모형은 작물 생육 및 생산성 예측을 위한 좋은 도구이다. 탄소 획득과 바이오매스 증가는 프로세스 모형 개발의 주요 구성요소로서, 작물모형 내에서 광합성 과정의 이해 및 통합에 중요한 역할을 한다. 본 연구는 1980년 Farquhar 등에 의해 제안된 C3 식물 잎의 광합성 모델인 FvCB 모형의 양파에 대한 적용 가능성 평가 및 적합한 모수 추정을 목표로 수행되었다. 이를 위해 온도구배하우스에서 재배된 조생종 양파 품종인 '싱싱볼'과 '썬더볼'의 광합성 측정 결과를 바탕으로 Vcmax, Jmax, TPU 및 Rd 값을 추정하였다. 본 연구에서 개발된 양파의 기체교환 모형은 다양한 환경 조건에서 양파의 광합성 반응 예측 및 설명에 유용하게 활용될 것으로 기대된다.

• 한국산업융합학회 논문집
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• 제20권5호
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• pp.395-404
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• 2017

Cultivating soybeans in rice paddy field reduces labor costs and increases the yield. Soybeans, however, are highly susceptible to excessive soil water in paddy field. Controlled drainage system can adjust groundwater level (GWL) and control soil moisture content, resulting in improvement soil environments for optimum crop growth. The objective of this study was to fit the soybean growth data (canopy height and stem diameter) using Gompertz model and Logistic model at different GWL and validate those models. The soybean, Daewon cultivar, was grown on the lysimeters controlled GWL (20cm and 40cm). The soil textures were silt loam and sandy loam. The canopy height and stem diameter were measured from the 20th days after seeding until harvest. The Gompertz and Logistic models were fitted with the growth data and each growth rate and maximum growth value was estimated. At the canopy height, the $R_2$ and RMSE were 0.99 and 1.58 in Gompertz model and 0.99 and 1.33 in Logistic model, respectively. The large discrepancy was shown in full maturity stage (R8), where plants have shed substantial amount of leaves. Regardless of soil texture, the maximum growth values at 40cm GWL were greater than the value at 20cm GWL. The growth rates were larger at silt loam. At the stem diameter, the $R_2$ and RMSE were 0.96 and 0.27 in Gompertz model and 0.96 and 0.26 in Logistic model, respectively. Unlike the canopy height, the stem diameter in R8 stage didn't decrease significantly. At both GWLs, the maximum growth values and the growth rates at silt loam were all larger than the values at sandy loam. In conclusion, Gompertz model and Logistic model both well fit the canopy heights and stem diameters of soybeans. These growth models can provide invaluable information for the development of precision water management system.

• 한국작물학회지
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• 제44권1호
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• pp.55-58
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• 1999

Plant water status during growth is directly and indirectly associated with seed yield. The objective of the present study was to determine the genotypic differences in leaf water characteristics at an early growth stage of soybean [Glycine max (L.) Merrill] plants through the pressure-bomb technique. Measurements of water potential as well as relative water content (RWC) were made at the third leaf from the fully-expanded top leaf of eight different soybean genotypes grown for 31 to 35 days after field emergence. On the basis of the modified exponential model, pressure-volume (PV) curves were fitted well ($R^2$=0.92＊＊ to 0.99＊＊ for the curvi-linear region and R=0.67＊＊ to 0.96＊＊ for the linear region), indicating that a segmented model using PROC NLIN of SAS could be used effectively to estimate the leaf water characteristics. The regression analysis for the pressure-volume (PV) curve revealed genotypic variation in the solute potential at saturation (Ψ$_{s,sat}$ :-10.7 to -14.8 bar), solute potential at incipient plasmolysis (Ψ$_{s,ip}$ : -14.3 to -18.3 bar), RWC at incipient plasmolysis (RW $C_{ip}$ : 83.3 to 91.7%), high integrated turgor pressure from saturation to plasmolysis ( $_1$$^{b}$ : 0.39 to 0.81), and maximum volumetric modulus of elasticity ($\varepsilon$$_{max}$ : 150 to 445 bar).).

• 한국농공학회논문집
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• 제64권2호
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• pp.1-13
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• 2022

Agrivoltaic facility is the composite system that the solar panel is installed above the farmland, and it enables crop and electricity production simultaneously. Solar panels of the agrivoltaic facilities can block and reduce the amount of solar irradiance arriving at the farmland, but it can help the crop growth by preventing excessive solar irradiance. Therefore, to clarify how the agrivoltaic facilities affect the crop growth, precise solar irradiance distribution under the solar panel should be modeled. In this study, PAR (photosynthetically active radiation), radiation from 400 to 700 nm, which crops usually use to grow, was extracted from the total irradiance and its distribution model under various conditions was developed. Monthly irradiance distributions varied because the elevation of the sun was changed over time, which made the position changed that the local maximum and minimum irradiance appear. The higher panel height did not cause any significant difference in the amount of irradiance reaching below the solar panel, but its distribution became more uniform. Furthermore, the panel angles with the most irradiance arriving below the solar panel were different by month, but its difference was up to 2%p between the irradiance with 30° angle which is usually recommended in Korea. Finally, the interval between panels was adjusted; when the ratio of the length of the panel to the empty space was 1:2, the irradiance of 0.719 times was reached compared to when there was no panel, 0.579 times for 1:1 and 0.442 times for 2:1.

• 한국농림기상학회지
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• 제21권3호
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• pp.187-195
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• 2019

기후변화에 따른 환경 스트레스 대응 기술과 영농의사결정 플랫폼 개발을 위해서는 환경 조건에 따른 작물의 반응을 이해하기 위한 시스템 개발이 매우 중요하다. 본 연구는 한국형 SPAR 시스템이 다양한 환경 조건에서 작물 생육 반응을 어떻게 정량화하고, 향후 작물 생육 모형 개발에 어떻게 연계될 수 있는지에 대해 방향을 제시하고자 수행되었다. 한국형 SPAR 시스템은 온도, $CO_2$ 농도 등의 기상요소와 양 수분 관리 등 재배요소를 동시에 정밀 조절할 수 있을 뿐 만 아니라 군락수준에서 광합성 및 호흡 등 작물의 생육 반응을 실시간으로 정량화하기에 최적화되어 있다. 본 시스템을 통해 수집된 군락 광합성 정보는 실제 작물의 환경조건에 따른 생육량 변동을 매우 유의하게 반영하여 향후 작물 생육 모형에 실질적으로 적용 가능한 환경-유전 요인간 특이적 반응 함수 개발에 크게 활용될 것으로 기대된다.

• 한국토양비료학회지
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• 제50권4호
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• pp.306-317
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• 2017

Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.

• 한국농공학회논문집
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• 제57권3호
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• pp.65-76
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• 2015

Estimating water requirements for upland crops are characterized by standing soil moisture condition during the entire crop growth period. However, scarce rainfall and intermittent dry spells often cause soil moisture depletion resulting in unsaturated condition in the fields. Changes in rainfall patterns due to climate change have significant influence on the increasing the occurrence of extreme soil moisture depletion. Therefore, it is necessary to evaluate agricultural drought for upland crop water planning and management in the context of climate change. The objective of this study is to predict the impacts of climate change on agricultural drought for upland crops and changes in the temporal trends of drought characteristics. First, the changes in crop evapotranspiration and soil moisture in the six upland crops, such as Soybeans, Maize, Potatoes, Red Peppers, Chinese Cabbage (spring and fall) were analyzed by applying the soil moisture model from commonly available crop and soil characteristics and climate data, and were analyzed for the past 30 years (1981-2010), and Representative Concentration Pathways (RCP) climate change scenarios (2011-2100). Second, the changes on the temporal trends of drought characteristics were performed using run theory, which was used to compare drought duration, severity, and magnitude to allow for quantitative evaluations under past and future climate conditions.