• The Plant Pathology Journal
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• v.36 no.1
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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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• v.31 no.4
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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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• v.34 no.5
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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.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 1999.04a
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• pp.45.2-45
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• 1999

• 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.

• The Korean Journal of Pesticide Science
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• v.5 no.1
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• pp.1-11
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• 2001

Climate in the year of 2000 was characterized as a long severe drought in tile spring, unusually high and low temperature in summer, two times of typoons, and floods by heavy rains in fall. Rice leaf and panicle blast and bacterial grain rot occurred severely comparing with 1999 and Bipolaris leaf spot spread over tile country. Phytophthora blight and anthracnose in red-pepper became epidemic especially in the late season causing severe yield losses. Tomato fusaruim wilt, CGMMV, powdery mildew, and sudden wilt syndrom of cucurbits and strawberry powdery mildew were also severe in 2000. In garlic, sclerotium rot occurred severely mainly due to the frequent rainfalls in planting time and much snowfalls in 1999's winter. Spring potato had severe infection of viruses due to a long spring drought, and fall potato had high incidence of bacterial soft rot and bacterial wilt due to fall floods by heavy rains. In sweet potato fusarium wilt was the most severe as in other year. Disease incidence of apple and pear trees was rotatively mild compared with previous years. In wheat and barley, Gibberella petch rarely occurred because of spring drought.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2002.11a
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• pp.42.1-42
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• 2002

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2002.11a
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• pp.46.3-47
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• 2002

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2005.04a
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• pp.66.2-67
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• 2005

• The Plant Pathology Journal
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• v.32 no.6
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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.