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An Integrated Modeling Approach for Predicting Potential Epidemics of Bacterial Blossom Blight in Kiwifruit under Climate Change
Kwang-Hyung Kim, Young Jin Koh 한국식물병리학회 The Plant Pathology Journal 14 Pages
한국식물병리학회 The Plant Pathology Journal 2019, 35권 5호 7 459-472 (14 pages)
increasing variation in climatic conditions under climate change directly influences plant-microbe interactions. To account for as many variables as possible that may play critical roles in such interactions, the use of an integrated modeling approach is necessary. Here, we report for the first time a local impact assessment and adaptation study of future epidemics of kiwifruit bacterial blossom blight (KBB) in Jeonnam province, Korea, using an integrated modeling approach. This study included a... -
ASSESSMENT OF WIND CHARACTERISTICS AND ATMOSPHERIC DISPERSION MODELING OF 137Cs ON THE BARAKAH NPP AREA IN THE UAE
Lee. Jong Kuk, Kim. Jea Chul, Lee. Kun Jai, Belorid. Miloslav, Beeley. Philip A., Yun. Jong-Il 한국원자력학회 Nuclear engineering and technology : an international journal of the Korean Nuclear Society 12 Pages
한국원자력학회 Nuclear engineering and technology : an international journal of the Korean Nuclear Society 2014, Vol.46 No.4 557-568 (12 pages)
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Uncertainty of Hydro-meteorological Predictions Due to Climate Change in the Republic of Korea
은코모제피 템바, 정상옥, Nkomozepi. Temba, Chung. Sang-Ok 한국수자원학회 韓國水資源學會論文集 11 Pages
한국수자원학회 韓國水資源學會論文集 2014, Vol.47 No.3 257-267 (11 pages)
수문기상학 연구에서 매우 중요하다. 본 연구에서는 기후변화가 우리나라 5대강 유역의 유출량에 미치는 영향을 분석하기 위하여 Catchment Modeling Toolkit의 네가지 수문기상 모형을 사용하였다. 세 가지 RCP 시나리오에 대하여 12개 GCM 모형으로부터 미래 2021에서 2040까지(2030s), 2051에서 2070까지 (2060s) 및 2081에서 2099까지(2090s) 기간에 대한 기후자료를 추출하였다. 이들 자료는 LARS-WG 방법으로 상세화 하였으며, 수문기상 모형들은 1999부터 2009까지의 관측 자료를 이용하여 보정 및 검정하였다. 본 연구에서 미래의... -
Development of a Daily Epidemiological Model of Rice Blast Tailored for Seasonal Disease Early Warning in South Korea
Kwang-Hyung Kim, Imgook Jung 한국식물병리학회 The Plant Pathology Journal 12 Pages
한국식물병리학회 The Plant Pathology Journal 2020, 36권 5호 3 406-417 (12 pages)
Early warning services for crop diseases are valuable when they provide timely forecasts that farmers can utilize to inform their disease management decisions. In South Korea, collaborative disease controls that utilize unmanned aerial vehicles are commonly performed for most rice paddies. However, such controls could benefit from seasonal disease early warnings with a lead time of a few months. As a first step to establish a seasonal disease early warning service using seasonal climate... -
Application of Numerical Weather Prediction Data to Estimate Infection Risk of Bacterial Grain Rot of Rice in Korea
Hyo-suk Kim, Ki Seok Do, Joo Hyeon Park, Wee Soo Kang, Yong Hwan Lee, Eun Woo Park 한국식물병리학회 The Plant Pathology Journal 13 Pages
한국식물병리학회 The Plant Pathology Journal 2020, 36권 1호 5 54-66 (13 pages)
by the Korea Meteorological Administration (KMA), disease forecast on bacterial grain rot (BGR) of rice was examined as compared with the model output based on the automated weather stations (AWS)-observed weather data. We analyzed performance of BGRcast based on the UM-predicted and the AWS-observed daily minimum temperature and average relative humidity in 2014 and 2015 from 29 locations representing major rice growing areas in Korea using regression analysis and two-way contingency table... -
MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
Hyo-suk Kim, Jung-hee Jo, Wee Soo Kang, Yun Su Do, Dong Hyuk Lee, Mun-Il Ahn, Joo Hyeon Park, Eun Woo Park 한국식물병리학회 The Plant Pathology Journal 13 Pages
한국식물병리학회 The Plant Pathology Journal 2019, 35권 6호 5 585-597 (13 pages)
A disease forecast model for Marssonina blotch of apple was developed based on field observations on airborne spore catches, weather conditions, and disease incidence in 2013 and 2015. The model consisted of the airborne spore model (ASM) and the daily infection rate model (IRM). It was found that more than 80% of airborne spore catches for the experiment period was made during the spore liberation period (SLP), which is the period of days of a rain event plus the following 2 days. Of 13... -
Effects of Interrupted Wetness Periods on Conidial Germination, Germ Tube Elongation and Infection Periods of Botryosphaeria dothidea Causing Apple White Rot
한국식물병리학회 The Plant Pathology Journal 7 Pages
한국식물병리학회 The Plant Pathology Journal 2016, 32권 1호 1 1-7 (7 pages)
Responses of Botryosphaeria dothidea to interrupted wetness periods were investigated under in vivo and in vitro conditions. Conidia of B. dothidea were allowed to germinate on apple fruits under wetting condition at 25ºC for 5 hr. They were air-dried for 0, 1, 2 or 4 hr, and then rewetted at 25ºC for 5 hr. Following an initial wetness period of 5 hr, 83% of the conidia germinated. The percent conidial germination increased to 96% when wetting was extended... -
Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper
한국식물병리학회 The Plant Pathology Journal 11 Pages
한국식물병리학회 The Plant Pathology Journal 2014, 30권 2호 3 125-135 (11 pages)
A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on... -
A Forecast Model for the First Occurrence of Phytophthora Blight on Chili Pepper after Overwintering
한국식물병리학회 The Plant Pathology Journal 13 Pages
한국식물병리학회 The Plant Pathology Journal 2012, 28권 2호 6 172-184 (13 pages)
An infection risk model for Phytophthora blight on chili pepper was developed to estimate the first date of disease occurrence in the field. The model consisted of three parts including estimation of zoosporangium formation, soil water content, and amount of active inoculum in soil. Daily weather data on air temperature, relative humidity and rainfall, and the soil texture data of local areas were used to estimate infection risk level that was quantified as the accumulated amount of active...
