• Korean journal of applied entomology
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• v.38 no.3
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• pp.231-240
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• 1999

The long-term tend an pattern changes of Chilo suppressalis(Walker) occurrence in Suwon were analyzed and the forecasting models for spring emergence of C. suppressalis in Suwon were developed. From 1965 to 196, the population dynamics of C. suppressalis in Suwon shows a cyclic fluctuation with one large peak an one small peak, and its periodicity was ca. 36 generations(18 years). C. suppressalis population dynamics in Suwon was characterized as controlled by the endogenous dynamics dictated by the 1st order negative feedback mechanism (fast density dependence). The dynaics mechanism of C. suppressalis populations was not changed although its population density decreased drastically over the years. Using th dta of C. suppressalis spring occurrence in Suwon, forecasting models for spring emergence of C.supressalis were developed based on temperature-dependent development model or degree days. In general, these models well described the C. suppressalis spring emergence pattern in Suwon. Also, forecasting problems in spring moth emergence related with C. suppressalis population dynamics were discussed.

• KAPE Magazine
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• s.146
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• pp.6-7
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• 2008

2005년 이전 OIE 위생규약상 BSE 예찰기준은 성우(24개월령 이상) 사육규모별로 BSE 유사 임상증상을 보이는 임상의심축을 일정 두수 검사하도록 권고하였으며, 우리나라는 당시 사육규모 당 99두의 임상의 심축만을 검사하면 동 기준을 충족했다. 그러나 OIE의 BSE 예찰기준은 2004년 EU 전염성해면상 뇌증(TSE) 연합 표준 실험실(Community Reference Laboratory, CRL)인 영국 수의연구청에 의해 개발된 BSurvE model과 동모델에 대한 회원국의 의견에 기초하여 2005년 이전의 두수제에서 점수제로 개정됐다. 우리나라는 점수제를 2007년부터 적용했다.

• Korean Journal Plant Pathology
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• v.3 no.3
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• pp.210-216
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• 1987

A computer program written to predict blast occurrence based on micro climatic events was developed and tested as an on-site microcomputer in field plots in 1984 and 1985. A microcomputer unit operating on alkaline batteries; continuously monitored air temperature, leaf wetness, and relative humidity; interpreted the microclimate information in relation to rice blast development and displayed daily values (0-8) of blast units of severity (BUS). Cumulative daily BUS values (CBUS) were highly correlated with blast development on the two susceptible cultivars, M-201 and Brazos grown in field plots. When CBUS values were used to predict the logit of disease proportions, the average coefficients of determination $(R^2)$ between these two factors were 71 to $91\%$, depending on cultivar and year. This was a significant improvement when compared to 61 to $79\%$ when days were used as a predictor of logit disease severity. The ability of CBUS to predict logit disease severity was slightly less with Brazos than M-201. This is significant inasmuch as Brazos showed field resistance at mid-sea­son. The results in this study indicate that the model has the potential for future use and that the model could be improved by incorporating other variables associated with host plants and pathogen races in addition to the key environmental variables.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2005.09a
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• pp.194-196
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• 2005

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1130-1135
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• 2009

Avian Influenza is an infectious desease of birds. The infection can cause a wide spectrum of symptoms in birds, ranging from mild illness to a rapidly fatal diseases which might bring a tremendous economic loss to poultry farms[1]. It can also give fatal diseases to human. Therefore it is important to surveil wildbirds that are primary transportation of avian influenza. This report showed a relationship between avian influenza and a habitat of wildbirds using system dynamics, and concluded with suggestion for surveilance.

• Smart Media Journal
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• v.8 no.3
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• pp.88-94
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• 2019

Livestock disease is a very important issue in the livestock industry because if livestock disease is not responded quickly enough, its damage can be devastating. To solve the issues involving the occurrence of livestock disease, it is necessary to diagnose in advance the status of livestock disease and develop systematic and scientific livestock feeding technologies. However, there is a lack of domestic studies on such technologies in Korea. This paper, therefore, proposes Livestock Disease Forecasting and Livestock Farm Integrated Control System using Cloud Computing to quickly manage livestock disease. The proposed system collects a variety of livestock data from wireless sensor networks and application. Moreover, it saves and manages the data with the use of the column-oriented database Hadoop HBase, a column-oriented database management system. This provides livestock disease forecasting and livestock farm integrated controlling service through MapReduce Model-based parallel data processing. Lastly, it also provides REST-based web service so that users can receive the service on various platforms, such as PCs or mobile devices.

• Research in Plant Disease
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• v.10 no.3
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• pp.167-174
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• 2004

To make the forecasting model of rice bacterial grain rot (RGBR) using the statistical procedures with SAS(Statistical Analysis System) based on micro-weather factors during heading period of rice, 21 rice varieties having the different heading time (40％ panicles headed) were planted at 30 May and 15 June in Naju. Heading time and diseased panicles were investigated from July to August in 1998. RGBR mainly occurred on varieties headed from 29 July to 19 August, but not on varieties headed after 22 August. RGBR was highly correlated with diurnal temperature during 7 days (r =-0.871 **) and 10 days (r =-0.867**) and minimum relative humidity during 15 days from 3 days before heading time. After examining the models with several ways ($R^2$, Adjusted $R^2$, MSE), one equations were selected： Y =92.83 - 2.43Tavr + 1.88Tmin - 1.04RHavr + 0.37RHmin + 0.43RD - 3.68WS ($R^2$=0.824) using six variables of average and minimum temperature (Tavr and Tmin), average and minimum relative humidity (RHavr and RHmin), rainy days (RD), and wind speed (WS) during 7 days from 3 days before to 3 days after heading time.

• Research in Plant Disease
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• v.18 no.4
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• pp.361-369
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• 2012

A population density model for bacterial wilt, which is caused by Ralstonia solanacearum, in hot pepper was developed to estimate the primary infection date after overwintering in the field. We developed the model mechansitically to predict reproduction of the pathogen and pathogensis on seedlings of the host. The model estimates the pathogen's populations both in the soil and in the host. In order to quantify environmental infection factors, various temperatures and initial population densities were determined for wilt symptoms on the seedlings of hot pepper in a chamber. Once, the pathogens living in soil multiply up to 400 cells/g of soil, they can infect successfully in the host. Primary infection in a host was supposed to be started when the population of the pathogen were over $10^9$ cells/g of root tissue. The estimated primary infection dates of bacterial wilt in 2011 in Korea were mostly mid-July or late-July which were 10-15 days earlier than those in 2010. Two kinds of meterological data, synoptic observation and field measurements from paddy field and orchard in Kyunggi, were operated the model for comparing the result dates. About 1-3 days were earlier from field data than from synoptic observation.

• Korean journal of applied entomology
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• v.25 no.4 s.69
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• pp.221-228
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• 1986

An empirical model to predict initial disease occurrence and subsequent progress of Alternaria leaf spot was constructed based on the modified degree day temperature and frequency of rainfall in three years field experiments. Climatic factors were analized 10-day bases, beginning April 20 to the end of August, and were used as variables for model construction. Cumulative degree portion (CDP) that is over $10^{\circ}C$ in the daily average temperature was used as a parameter to determine the relationship between temperature and initial disease occurrence. Around one hundred and sixty of CDP was needed to initiate disease incidence. This value was considered as temperature threshhold. After reaching 160 CDP, time of initial occurrence was determined by frequency of rainfall. At least four times of rainfall were necessary to be accumulated for initial occurrence of the disease after passing temperature threshhold. Disease progress after initial incidence generally followed the pattern of frequency of rainfall accumulated in those periods. Apparent infection rate (r) in the general differential equation dx/dt=xr(1-x) for individual epidemics when x is disease proportion and t is time, was a linear function of accumulation rate of rainfall frequency (Rc) and was able to be directly estimated based on the equation r=1.06Rc-0.11($R^2=0.993$). Disease severity (x) after t time could be predicted using exponential equation $[x/(1-x)]=[x_0/(1-x)]e^{(b_0+b_1R_c)t}$ derived from the differential equation, when $x_0$ is initial disease, $b_0\;and\;b_1$ are constants. There was a significant linear relationship between disease progress and cumulative number of air-borne conidia of Alternaria mali. When the cumulative number of air-borne conidia was used as an independent variable to predict disease severity, accuracy of prediction was poor with $R^2=0.3328$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.415-426
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• 2023

In this study, the horizontal and vertical structure of wind speed and wind direction were analyzed at the origin of migratory insect pests in China. Wind rose analysis was carried out using the Land-Atmosphere Modeling Package (LAMP) - WRF data, which has the spatiotemporal resolution of about 20 km and 1 hour intervals. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was employed for backward trajectory analysis between South Korea and Southeastern China with Global Data Assimilation System (GDAS). The research interest date is July 16, when rice planthopper and leafhopper were observed at the same time. In order to examine where a jet stream occurs in the vertical in source regions and South Korea during the period (July 8 to July 17 in 2021), three-dimensional wind information was extracted and analyzed using the east-west, north-south, and vertical component wind data of the LAM P. The vertical distribution of wind showed that the wind changed in favor of the inflow of migratory insect pests during the period. As a result of analyzing the wind rose, about 30% or more of the wind at a point close to South Korea was classified into the low-level jet stream. In addition, majority of the wind directions for the low-level jet streams (rather than high-level jet streams) at the five origin sites were heading toward South Korea and even Japan, and this was supported by the HYSPLIT-based backward trajectory analysis.