• Research in Plant Disease
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• v.22 no.3
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• pp.168-177
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• 2016

A forecast model for estimating the infection risk of bacterial canker caused by Pseudomonas syringae pv. actinidiae on kiwifruit leaves in Korea was developed using the generic infection model of Magarey et al. (2005). Two-way contingency table analysis was carried out to evaluate accuracy of forecast models including the model developed in this study for estimating the infection of bacterial canker on kiwifruit using the weather and disease data collected from three kiwifruit orchards at Seogwipo in 2015. All the tested models had more than 80% of probability of detection indicating that all the tested models could be effective to manage the disease. The model developed in this study showed the highest values in proportion of correct (51.1%), probability of detection (90.9%), and critical success index (47.6%). It indicated that the model developed in this study would be the best model for estimating the infection of bacterial wilt on kiwifruit leaves in Korea. The model developed in this study could be used for a part of decision support system for managing bacterial wilt on kiwifruit leaves and help growers to reduce the loss caused by the disease in Korea.

• Research in Plant Disease
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• v.26 no.4
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• pp.229-238
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• 2020

Field validation of PBcast, an infection risk model for Phytophthora blight of pepper, was conducted through a designed field experiment in 2012 and 2013. Conduciveness of weather conditions at 26 locations in Korea in 2014-2017 was also evaluated using PBcast. The PBcast estimated daily infection risk (IR) of Phytophthora capsici based on weather and soil texture data. In the designed filed experiment, four treatments including routine sprays at 7-day intervals (RTN7), forecast-based sprays when IR reached 200 (IR200) and 224 (IR224), and no spray (CTRL) were compared in terms of disease incidence and number of sprays recommended for disease control. In 2012, IR had reached over 200 twice, but never reached 224. In 2013, IR had reached over 200 three times and once higher than 224. The RTN7 plots were sprayed 17 and 18 times in 2012 and 2013, respectively. Weather conditions throughout the country were generally conducive for Phytophthora blight and 3-4 times of fungicide sprays would have been reduced if the PBcast forecast information was adopted in the decision-making for fungicide sprays. In conclusion, the PBcast forecast would be useful to reduce fungicide applications without losing the disease control efficacy to protect pepper crop from Phytophthora blight.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.24-24
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• 2003

Since Rice bacterial grain rot (RGBR) was reported at 1986 in Korea, it has been severely occurred in 1994, 1995, 1998, and especially around 16,609 ha in 2000, and became a major disease in rice cultivation field. This study was focused on investigation of ecology of RGBR, weather conditions that affect development of epidemics, and development of an effective RGBR forecast system based on weather conditions during the rice heading period.(중략)

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.108.2-109
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• 2003

The Gyeonggi-do Agricultural Research and Extension Services has developed a web-site (www.epilove.com) in collaboration with EPINET to provide information on agricultural weather and rice disease and insect pest management in Gyeonggi-do. Weather information includes near real-time weather data monitored by automated weather stations (AWS) installed at rice paddy fields of 11 Agricultural Technology Centers (ATC) in Gyeonggi-do, and weekly weather forecast by Korea Meteorological Administration (KMA). Map images of hourly air temperature and rainfall are also generated at 309m x 309m resolution using hourly data obtained from AWS installed at 191 locations by KMA. Based on near real-time weather data from 11 ATC, hourly infection risks of rice blast, sheath blight, and bacterial grain rot for individual districts are estimated by disease forecasting models, BLAST, SHBLIGHT, and GRAINROT. Users can diagnose various diseases and insects of rice and find their information in detail by browsing thumbnail images of them. A database on agrochemicals is linked to the system for disease and insect diagnosis to help users search for appropriate agrochemicals to control diseases and insect pests.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.115-116
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• 2018

• Research in Plant Disease
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• v.21 no.2
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• pp.67-73
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• 2015

Bacterial blossom blight of kiwifruit (Actinidia deliciosa) caused by Pseudomonas syringae pv. syringae is known to be largely affected by weather conditions during the blooming period. While there have been many studies that investigated scientific relations between weather conditions and the epidemics of bacterial blossom blight of kiwifruit, no forecasting models have been developed thus far. In this study, we collected all the relevant information on the epidemiology of the blossom blight in relation to weather variables, and developed the Pss-KBB Risk Model that is based on the Maryblyt model for the fire blight of apple and pear. Subsequent model validation was conducted using 10 years of ground truth data from kiwifruit orchards in Haenam, Korea. As a result, it was shown that the Pss-KBB Risk Model resulted in better performance in estimating the disease severity compared with other two simple models using either temperature or precipitation information only. Overall, we concluded that by utilizing the Pss-KBB Risk Model and weather forecast information, potential infection risk of the bacterial blossom blight of kiwifruit can be accurately predicted, which will eventually lead kiwifruit growers to utilize the best practices related to spraying chemicals at the most effective time.

• The Plant Pathology Journal
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• v.40 no.3
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• pp.290-298
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• 2024

K-Maryblyt has been developed for the effective control of secondary fire blight infections on blossoms and the elimination of primary inoculum sources from cankers and newly emerged shoots early in the season for both apple and pear trees. This model facilitates the precise determination of the blossom infection timing and identification of primary inoculum sources, akin to Maryblyt, predicting flower infections and the appearance of symptoms on various plant parts, including cankers, blossoms, and shoots. Nevertheless, K-Maryblyt has undergone significant improvements: Integration of Phenology Models for both apple and pear trees, Adoption of observed or predicted hourly temperatures for Epiphytic Infection Potential (EIP) calculation, incorporation of adjusted equations resulting in reduced mean error with 10.08 degree-hours (DH) for apple and 9.28 DH for pear, introduction of a relative humidity variable for pear EIP calculation, and adaptation of modified degree-day calculation methods for expected symptoms. Since the transition to a model-based control policy in 2022, the system has disseminated 158,440 messages related to blossom control and symptom prediction to farmers and professional managers in its inaugural year. Furthermore, the system has been refined to include control messages that account for the mechanism of action of pesticides distributed to farmers in specific counties, considering flower opening conditions and weather suitability for spraying. Operating as a pivotal module within the Fire Blight Forecasting Information System (FBcastS), K-Maryblyt plays a crucial role in providing essential fire blight information to farmers, professional managers, and policymakers.

• 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.

• Research in Plant Disease
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• v.25 no.4
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• pp.196-204
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• 2019

Rice panicle blast occurred severely in southern provinces of Korea in 2014. The proportion of panicle blast incidence area to cultivated area of rice were 11.0% and 14.6% in Jeollanam-do and Gyeongsangnam-do, respectively. To identify the causal factors of the outbreak, we investigated weather conditions in August, amount of cultivated area of mainly grown cultivars, and nitrogen contents in plants with different disease incidences in 2014. 'Saenuri,' 'Ilmibyeo,' 'Unkwang,' 'Dongjin 1 ho,' 'Nampyeongbyeo,' and 'Hwangkeumnuri' were mainly grown cultivars. Monthly average of daily air temperature in August 2014 was 3.2℃ and 3.1℃ less than 2018 in Haenam and Miryang, respectively. Rainfall in August 2014 was 70.0% and 42.0% greater than 2018 in Haenam and Miryang, respectively. The numbers of blast warning days in August calculated nationwide using a forecast model for blast infection were higher in 2014 than in 2018, and they were in high level throughout the country in 2014. Nitrogen contents in plant samples from high-incidence plots were significantly higher than those from low-incidence plots. Consequently, excessive use of nitrogen fertilizers was the main factor for the disease outbreak at the level of specific farms, in addition to the collective cultivation of susceptible cultivar, low temperatures and frequent rainfalls in August.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.137-147
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• 2013

Most of livestock houses are concentrated in certain area with mass rearing system resulting in rapid spread of infectious diseases such as HPAI (highly pathogenic avian influenza). The livestock-related vehicles which frequently travel between farms could be a major factor for disease spread by means of transmission of airborne aerosol including pathogens. This study was focused on the quantitative measurement of aerosol concentration by field experiment while vehicles were passing through the road. The TSP (total suspended particle) and PM10 (particle matter) were measured using air sampler with teflon filter installed downward the road with consideration of weather forecast and the direction of road. And aerosol spectrometer and video recorders were also used to measure the real-time distribution of aerosol concentration by its size. The results showed that PM2.5 was not considerable for transmission of airborne aerosol from the livestock-related vehicle. The mass generated from the road during the vehicle movement was measured and calculated to 241.4 ${\mu}g/m^3$ by means of the difference between TSP and PM2.5. The dispersion distance was predicted by 79.6 m from the trend curve.