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Anyang, South Korea

Kim J.-H.,Sun Moon University | Kang W.-S.,EPINET Co. | Yun S.-C.,Sun Moon University
Plant Pathology Journal

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 the model is initiated when the pathogen population exceeds 1015 cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required. © The Korean Society of Plant Pathology. Source

Seo I.-H.,Seoul National University | Seo I.-H.,Seoul National University of Science and Technology | Lee I.-B.,Seoul National University | Hong S.-W.,Seoul National University | And 3 more authors.
Biosystems Engineering

Livestock infectious diseases, such as foot-and-mouth disease (FMD), cause substantial economic damage to livestock farms and their related industries. Among various causes of disease spread, airborne dispersion has previously been considered to be an important factor that could not be controlled by preventive measures to stop the spread of disease that focus on direct and indirect contact. Forecasting and predicting airborne virus spread are important to make time for developing strategies and to minimise the damage of the disease. To predict the airborne spread of the disease a modelling approach is important since field experiments using sensors are ineffective because of the rarefied concentrations of virus in the air. The simulation of airborne spread during past outbreaks required improvement both for farmers and for policy decision makers. In this study a free license computational fluid dynamics (CFD) code was used to simulate airborne virus spread. Forecasting data from the Korea Meteorological Administration (KMA) was directly connected in the developed model for real-time forecasting for 48h in three-hourly intervals. To reduce computation time, scalar transport for airborne virus spread was simulated based on a database for the CFD computed airflow in the investigated area using representative wind conditions. The simulation results, and the weather data were then used to make a database for a web-based forecasting system that could be accessible to users. © 2014 IAgrE. Source

Lee H.,Seoul National University | Kang W.S.,EPINET Co. | Ahn M.I.,EPINET Co. | Cho K.,Korea University | Lee J.-H.,Seoul National University
International Journal of Biometeorology

Climate change could shift the phenology of insects and plants and alter their linkage in space and time. We examined the synchrony of rice and its insect pest, Scotinophara lurida (Burmeister), under the representative concentration pathways (RCP) 8.5 climate change scenario by comparing the mean spring immigration time of overwintered S. lurida with the mean rice transplanting times in Korea. The immigration time of S. lurida was estimated using an overwintered adult flight model. The rice transplanting time of three cultivars (early, medium, and medium-late maturing) was estimated by forecasting the optimal cultivation period using leaf appearance and final leaf number models. A temperature increase significantly advanced the 99 % immigration time of S. lurida from Julian day 192.1 in the 2000s to 178.4 in the 2050s and 163.1 in the 2090s. In contrast, rice transplanting time was significantly delayed in the early-maturing cultivar from day 141.2 in the 2000s to 166.7 in the 2050s and 190.6 in the 2090s, in the medium-maturing cultivar from day 130.6 in the 2000s to 156.6 in the 2050s and 184.7 in the 2090s, and in the medium-late maturing cultivar from day 128.5 in 2000s to 152.9 in the 2050s and 182.3 in the 2090s. These simulation results predict a significant future phenological asynchrony between S. lurida and rice in Korea. © 2015 ISB Source

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