• 한국작물학회:학술대회논문집
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• 한국작물학회 2006년도 한국약용작물학회 공동춘계학술발표회
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• pp.288-289
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• 2006

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.114-119
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• 2000

To estimate Agricultural water demand, many factors such as weather, type of crop, soil, cultivation method, crop coefficient and cultivation area, etc. must be considered. But it is not easy to estimate water demand in consideration of these many factors, which are variable according to a period and regional environment. So, this study provides estimation system for agricultural water demand(ESAD) in order to estimate water demand easily and accurately, calculates the present and future agricultural water demand and arranges all factors needed for water demand estimation. This study calibrates the application of estimation system for agricultural water demand with the data observed in the other Studies and analyzes agricultural water demand nationwide.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2019년도 하계 학술발표초록집
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• pp.186-186
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• 2019

• 한국농림기상학회지
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• 제22권1호
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• pp.1-12
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• 2020

토양수분은 농업에서 필수적인 자원으로 이의 변화와 부족을 예측함으로써 관리되어왔다. 최근 현장에서의 적용 용이성과 다양한 지역에 대한 일반화 가능성이 뛰어난 통계 및 기계학습 알고리즘을 활용한 토양수분 예측 연구가 활발히 진행되고 있다. 하지만 국내에서 생성되는 데이터를 이용한 연구들은 부족한 실정이다. 이에 본 연구는 1) 국내 공공기상 데이터만으로 충분한 성능을 내는 토양수분 예측 모델을 만들 수 있는지, 2) 어떠한 기계학습 모델이 국내에서 생산되는 데이터와 토양환경에서 가장 높은 예측 성능을 보이는지, 3) 단일 기계학습 모델을 이용해 다양한 지역에 적용 가능한지를 확인해보려 한다. 본 연구에서 Support Vector Machines (SVM), Random Forest (RF), Extremely Randomized Trees (ET), Gradient Boosting Machines (GBM), and Deep Feedforward Network (DFN) 알고리즘과 종관기상관측 자료, 농업기상관측자료를 활용하여 안동, 보성, 철원, 순천 지역의 토양 수분을 예측하는 모델을 만들었다. 그 결과, GBM을 이용한 모델이 R² : 0.96, Root Mean Squared Error(RMSE) : 1.8로 가장 낮은 예측 오차를 보였다. 또한 GBM을 사용한 모델이 가장 낮은 지역간 예측 오차 분산을 보여 가장 일반화하기에 적절한 모델로 확인되었다.

• 한국농림기상학회지
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• 제20권4호
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• pp.305-312
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• 2018

기후변화에 대한 논의가 지속되면서 다양한 영역에서 이와 관련된 연구가 진행되고 있다. 농업은 기후와 가장 밀접하게 관련된 산업으로, 기후변화와 그에 따른 이상기후에 의해 생산성이 크게 달라질 수 있다. 본 연구에서는 기후변화 및 이상기후에 따른 작목별 농산물의 생산성 변화를 살펴보고, 이상기후 종류별 발효횟수가 증가함에 따라 비효율성이 증가하는 작목을 분류하였다. 이상기후를 대리할 수 있는 자료로 기상청에서 발표하는 기상특보의 발효횟수를 활용하였고, 분석에 고려된 기상특보의 종류에는 강풍특보, 호우특보, 대설특보, 건조특보, 한파특보, 태풍특보, 폭염특보가 있다. 8개 과수 작목의 생산 효율성 대해 각 기상특보의 발효횟수가 미치는 영향을 확률적 프런티어 분석을 통해 살펴본 결과 한파특보와 대설특보가 많은 수의 과수작목에 부정적인 영향을 미치는 것으로 나타났다. 농촌진흥청의 농산물 소득조사 자료를 활용한 상기 분석결과는 기후변화와 다양한 이상기후에 대한 국내 농업의 대응전략을 효율적으로 수립하는 데 기초자료로써 활용될 수 있다고 판단된다.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2000년도 추계 학술대회지
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• pp.28-45
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• 2000

It was unusual crop weather for 1998 and 1999 compared with normal in Korea. The consecutive days of the optimum ripening period for rice plant that had daily mean temperature 21-23C for 40 days after heading, increased with long anomalies in 1998-99. The air temperature during ripening period was much higher than the optimum temperature and lower sunshine hour than normal in the local adaptability tests of newly developed rice lines during those years. In response of rice cultivation to warming and cloudy weather during crop season, the yield shall be decreased. Most scientists agree that the rate of heating is accelerating and temperature change could become increasingly disruptive. Weather patterns should also become more erratic. Agrometeorologists could be analyzed yearly variations of temperature, sunshine hour and rainfall pattern focused on transient agroclimate change for last a decade. Rice agronomists could be established taking advantage of real time agricultural meteorology information system for fertilization, irrigation, pest control and harvest. Also they could be analyzed the characteristics of flowering response of the recommended and newly bred rice cultivars for suitable cropping plan such as cultural patterns and sowing or transplanting date. Rice breeders should be deeply considered introducing the characteristics of basic vegetative type of flowering response like Tonsil rices as prospective rice cultivars corresponding to global warming because of the rices needed higher temperature at ripening stage than Japonica rices, photoperiod sensitive and thermo-sensitive ecotypes

• 한국농공학회논문집
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• 제60권3호
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• pp.15-25
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• 2018

Estimating the reference evapotranspiration is an important factor to consider in irrigation system design and agricultural water use. However, there is a limitation in using the FAO Penman-Monteith (FAO P-M) equation, which requires various meteorological data. The purpose of this study is to compare three reference evapotranspiration (ETo) equations in the case of meteorological data missing for 11 study weather stations. Firstly, the FAO P-M equation is used for reference potential evapotranspiration estimation with the actual solar radiation data $R_n$ and the actual vapor pressure $e_a$. Then, in the case of $R_n$, and $e_a$ are missed, the reference evapotranspirations applying FAO P-M, Priestley-Taylor (P-T), Hargreaves (HG) equation were calculated using other meteorological factors. Secondly, MAE, RMSE, $R^2$ were calculated to compare ETo relationship from the ETo equations. From the results, ETo with Hargreaves equation in coastal areas and the Priestley-Taylor equation in the inland areas showed relatively high correlation with FAO P-M when $e_a$ data is missed. In the case of $R_n$ data is missed or two weather data, $e_a$, and $R_n$ data are all missed, $R^2$ value in Priestley-Taylor equation was highest in coastal areas, and $R^2$ values in Hargreaves equation were the high values for 7 inland areas. The results of sensitivity analysis showed that net radiation was the most sensitive for P-T and HG equation, and for FAO P-M, the most sensitive factor was net radiation and relative humidity, air temperature and wind speed were follows. Therefore, in considering of the accessibility to the coast, the types of the missing wether data, and the correlation and the magnitude of error, the reference evapotranspiration equations would be selected in sense of different conditions.

• 한국농림기상학회지
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• 제3권3호
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• pp.156-162
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• 2001

In order to monitor local climatic information, twelve automated weather stations (AWS) were installed in alpine area by the Alpine Agricultural Experiment Station, Rural Development Administration (RDA), at the field of major crop located in around highland area, and collected data from 1993 to 2000. Hourly measurements of air and soil temperature (underground 10 cm,20 cm), relative humidity, wind speed and direction, precipitation, solar radiation and leaf wetness were automatically performed and the data could be collected through a public phone line. Datalogger was selected as CR10X (Campbell scientific, LTD, USA) out of consideration for sensers' compatibility, economics, endurance and conveniences. All AWS in alpine area were combined for net work and daily climatic data were analyzed in text and graphic file by program (Chumsungdae, LTD) on 1 km $\times$ 1 km grid tell basis. In this analysis system, important multi-functionalities, monitoring and analysis of local climatic information in alpine area was emphasized. The first objective was to obtain the output of a real time data from AWS. Secondly, daily climatic normals for each grid tell were calculated from geo-statistical relationships based on the climatic records of existing weather stations as well as their topographical informations. On 1 km $\times$ 1 km grid cell basis, real time climatic data from the automated weather stations and daily climatic normals were analyzed and graphed. In the future, if several simulation models were developed and connected with this system it would be possible to precisely forecast crop growth and yield or plant disease and pest by using climatic information in alpine area.

• The Plant Pathology Journal
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• 제31권4호
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• pp.350-362
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• 2015

A disease forecast model for bacterial grain rot (BGR) of rice, which is caused by Burkholderia glumae, was developed in this study. The model, which was named 'BGRcast', determined daily conduciveness of weather conditions to epidemic development of BGR and forecasted risk of BGR development. All data that were used to develop and validate the BGRcast model were collected from field observations on disease incidence at Naju, Korea during 1998-2004 and 2010. In this study, we have proposed the environmental conduciveness as a measure of conduciveness of weather conditions for population growth of B. glumae and panicle infection in the field. The BGRcast calculated daily environmental conduciveness, $C_i$, based on daily minimum temperature and daily average relative humidity. With regard to the developmental stages of rice plants, the epidemic development of BGR was divided into three phases, i.e., lag, inoculum build-up and infection phases. Daily average of $C_i$ was calculated for the inoculum build-up phase ($C_{inf}$) and the infection phase ($C_{inc}$). The $C_{inc}$ and $C_{inf}$ were considered environmental conduciveness for the periods of inoculum build-up in association with rice plants and panicle infection during the heading stage, respectively. The BGRcast model was able to forecast actual occurrence of BGR at the probability of 71.4% and its false alarm ratio was 47.6%. With the thresholds of $C_{inc}=0.3$ and $C_{inf}=0.5$, the model was able to provide advisories that could be used to make decisions on whether to spray bactericide at the preand post-heading stage.

• 한국농공학회논문집
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• 제50권3호
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• pp.71-79
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• 2008

Generally the price of agricultural products has much different characteristics from that of manufacturing products. If products have the limitation of long-term storage and the short period of cultivation, the price of products can be more unstable. Moreover, the price forecasting is very difficult because it doesn't follow any cycle or trend. However price can be regarded as risk instead of uncertainty if we can calculate the probability of price. Reliability analysis techniques are used for forecasting the price change of Chinese cabbage. This study aims to show the usability of reliability analysis for price forecasting. A price-forecasting model was developed based on weather data of the first 10 days of the full cultivating cycle (80 days) 70 days and the average price and standard deviation of wholesale market prices from 1996 to 2001 and applied to forecast the boom price, or the orice which is over the tolerance of market prices, of upland Chinese cabbage in 2002 and 2003. Applied results showed the possibility of boom price forecasting using reliability analysis techniques.