• The Plant Pathology Journal
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• 제36권1호
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• pp.54-66
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• 2020

This study was conducted to evaluate usefulness of numerical weather prediction data generated by the Unified Model (UM) for plant disease forecast. Using the UM06- and UM18-predicted weather data, which were released at 0600 and 1800 Universal Time Coordinated (UTC), respectively, 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 analysis. Temporal changes in weather conduciveness at two locations in 2014 were also analyzed with regard to daily weather conduciveness (C_i) and the 20-day and 7-day moving averages of C_i for the inoculum build-up phase (C_inc) prior to the panicle emergence of rice plants and the infection phase (C_inf) during the heading stage of rice plants, respectively. Based on C_inc and C_inf, we were able to obtain the same disease warnings at all locations regardless of the sources of weather data. In conclusion, the numerical weather prediction data from KMA could be reliable to apply as input data for plant disease forecast models. Weather prediction data would facilitate applications of weather-driven disease models for better disease management. Crop growers would have better options for disease control including both protective and curative measures when weather prediction data are used for disease warning.

• 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.

• The Plant Pathology Journal
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• 제34권5호
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• pp.393-402
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• 2018

Rice world production is affected due to the growing impact of diseases such as bacterial panicle blight, produced by Burkholderia glumae. The pathogen-induced symptoms include seedling rot, grain rot and leafsheath browning in rice plants. It is currently recognized the entrance of this pathogen to the plant, from infected seeds and from environmental sources of the microorganism. However, it is still not fully elucidated the dynamics and permanence of the pathogen in the plant, from its entry until the development of disease symptoms in seedlings or panicles. In this work it was evaluated the infection of B. glumae rice plants, starting from inoculated seeds and substrates, and its subsequent monitoring after infection. Various organs of the plant during the vegetative stage and until the beginning of the reproductive stage, were evaluated. In both inoculation models, the bacteria was maintained in the plant as an endophyte between $1{\times}10^1$ and $1{\times}10^5cfu$ of B. $glumae.g^{-1}$ of plant throughout the vegetative stage. An increase of bacterial population towards initiation of the panicle was observed, and in the maturity of the grain, an endophyte population was identified in the flag leaf at $1{\times}10^6cfu$ of B. $glumae.g^{-1}$ fresh weight of rice plant, conducting towards the symptoms of bacterial panicle blight. The results found, suggest that B. glumae in rice plants developed from infected seeds or from the substrate, can colonize seedlings, establishing and maintaining a bacterial population over time, using rice plants as habitat to survive endophyticly until formation of bacterial panicle blight symptoms.

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 1999년도 정기총회 및 춘계 학술발표회
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• pp.45.2-45
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• 1999

• 식물병연구
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• 제10권3호
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• pp.167-174
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• 2004

세균성벼알마름병(RGBR)의 발생예찰 모델을 만들기 위하여 출수기가 다른 오대벼 등 21개 품종을 1998년 5월 30일과 6월 15일에 이앙하여 벼 출수기와 이병수율을 조사하고 출수기 전후의 미기상과 병 발생과의 관계를 SAS 프로그램을 이용하여 분석하였다. 세균성벼알름병은 출수기가 7월 29일부터 8월 19일 사이의 품종에서 대부분 발생하였고 8월 22일 이후에 출수한 품종에서는 전혀 발생하지 않았다. 벼 출수기를 기준으로 출수기 3일 전부터 7일(r=-0.871**), 10일(r=-0.863**)의 일교차와 15일(r=0.8709**)과 출수기부터 7일(r=0.862**), 10일(r=0.860**), 15일(r =0.844**) 동안의 상대습도와 높은 상관관계를 보였다. 결정계수($R^2$)와 수정된 결정계수($R^2$$_{adj}$), 잔차평균제곱(MSE)를 이용하여 예찰모델을 구한 결과, 출수 전 3일부터 7일 동안의 평균기온, 최저기온, 평균상대습도(RHavr), 최저상대습도(RHmin), 강우일수, 풍속의 6개 변수를 이용한 RGBR =92.83 - 2.437avr + 1.887min - 1.04RHavr + 0.37RHmin + 0.43RD - 3.68WS($R^2$=0.824)의 회귀식을 구할 수 있었다.다.

• 농약과학회지
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• 제5권1호
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• pp.1-11
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• 2001

2000년 기상의 특징은 봄철의 극심한 가뭄과 여름철의 이상고온 및 저온현상, 장마기 두차례의 태풍 및 가을철 집중호우에 의한 침수로 요약된다. 벼는 전년에 비해 잎 이삭도열병이 심하게 발생하였으며, 세균성벼알마름병, 깨씨무늬병이 전국적으로 발생하여 문제시되었다. 고추는 역병과 탄저병이 생육후기에 심하게 발생하여 큰 피해를 가져왔으며 토마토는 일부지역에서 시들음병이, 오이, 수박은 CGMMV, 흰가루병, 급성위조증상, 딸기는 흰가루병이 심하게 발생하였다. 마늘은 파종기의 잦은 강우와 겨울철의 많은 강설로 흑색썩음균핵병이 대발생하였고, 봄감자는 가뭄에 의하여 바이러스병이, 가을감자는 집중호우에 의한 침수로 무름병, 풋마름병이 심하게 발생하였으며 고구마는 여느해와 마찬가지로 덩굴쪼김병의 발생이 심하였다. 사과 배의 병해는 예년에 비해 발생이 경미하였고 맥류의 붉은곰팡이병은 봄철의 가뭄으로 발생이 거의 없었다.

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2002년도 총회 및 추계학술발표회
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• pp.42.1-42
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• 2002

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2002년도 총회 및 추계학술발표회
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• pp.46.3-47
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• 2002

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2005년도 한국식물병리학회 임시총회 및 춘계학술발표회
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• pp.66.2-67
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• 2005

• The Plant Pathology Journal
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• 제32권6호
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• pp.575-579
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• 2016

Burkholderia glumae (bacterial grain rot), Xanthomonas oryzae pv. oryzae (bacterial leaf blight), and Acidovorax avenae subsp. avenae (bacterial brown stripe) are major seedborne pathogens of rice. Based on the 16S and 23S rDNA sequences for A. avenae subsp. avenae and B. glumae, and transposase A gene sequence for X. oryzae pv. oryzae, three sets of primers had been designed to produce 402 bp for B. glumae, 490 bp for X. oryzae, and 290 bp for A. avenae subsp. avenae with the $63^{\circ}C$ as an optimum annealing temperature. Samples collected from naturally infected fields were detected with two bacteria, B. glumae and A. avenae subsp. avenae but X. oryzae pv. oryzae was not detected. This assay can be used to identify pathogens directly from infected seeds, and will be an effective tool for the identification of the three pathogens in rice plants.