• Plant Resources
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• v.7 no.1
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• pp.36-38
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• 2004

Bacterial grain rot of rice caused by Burkholderia glumae was examined between weather condition and disease incidence. From 1998 to 2000, average disease incidence was 3.0 ％ without difference in survey regions. However, it was related closely to amount of rainfall that disease incidence higher in 1998 and 2000 to 3.0 ％ and 3.6 ％ respectively than 2.3 in 1999 relatively small volum of rainfall season.

• The Plant Pathology Journal
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• v.26 no.1
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• pp.37-48
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• 2010

This paper describes a web-based information system for plant disease forecast that was developed for crop growers in Gyeonggi-do, Korea. The system generates hourly or daily warnings at the spatial resolution of $240\;m{\times}240\;m$ based on weather data. The system consists of four components including weather data acquisition system, job process system, data storage system, and web service system. The spatial resolution of disease forecast is high enough to estimate daily or hourly infection risks of individual farms, so that farmers can use the forecast information practically in determining if and when fungicides are to be sprayed to control diseases. Currently, forecasting models for blast, sheath blight, and grain rot of rice, and scab and rust of pear are available for the system. As for the spatial interpolation of weather data, the interpolated temperature and relative humidity showed high accuracy as compared with the observed data at the same locations. However, the spatial interpolation of rainfall and leaf wetness events needs to be improved. For rice blast forecasting, 44.5% of infection warnings based on the observed weather data were correctly estimated when the disease forecast was made based on the interpolated weather data. The low accuracy in disease forecast based on the interpolated weather data was mainly due to the failure in estimating leaf wetness events.

• Korean Journal of Environmental Agriculture
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• v.41 no.1
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• pp.16-23
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• 2022

BACKGROUND: Rice production by the current standard cultivation method is predicted to decrease due to global warming. It seems that there has been a strong warming trend in Hwaseong-si, Gyeonggi-do. This study attempted to understand the climate change in Hwaseongsi, Gyeonggi-do and to analyze the effect of climate change on rice production. METHODS AND RESULTS: The statistical and physicochemical analyses were performed using the rice cultivar 'Chucheongbyeo' yields grown at the rice paddy field plot in the Gyeonggi-do Agricultural Research and Extension Services and the weather data measured in near the rice paddy plot. CONCLUSION(S): There was no significant difference between the average rice yields per area in 2000s (2001~2010) and 2010s (2011~2020), but the rice yield variability was greater in 2010s than in 2000s. The mean, minimum, maximum temperature, and the sunshine hours were evaluated for the correlation with the rice yield. The understanding of climate change in Hwaseong-si, Gyeonggi-do and the major weather factors affecting changes in rice yield, presented in this study, would enhance scientific understanding of regional climate change, and improve rice cultivation management.

• Journal of Biosystems Engineering
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• v.23 no.3
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• pp.229-244
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• 1998

This study was performed to determine proper fan and heater management schemes for natural air drying of rough rice in round steel bin with stirring device under Korean weather conditions. A computer simulation model was developed to predict moisture content changes, energy requirements, and drymatter losses during drying of rough rice by natural air. Drying test was conducted to validate the simulation model using round steel bin of holding capacity of 300ton at Rice Processing Complex in Jincheon. The bin was filled with rough rice every day and mixing by stirring device. Moisture contents, ambient air temperatures, relative humidities, static pressures in plenum chamber in the bin, airflow rates, and electrical and fuel energy were measured. Relative errors of moisture content changes predicted by the simulation model were below 5ft, and relative errors of final moisture content, final grain weight, required energy ranged from 0.9% to 6%. These not levels indicated that the simulation model can satisfactorily predict the performance factors of natural air drying system such as drying rates and energr consumptions comparing error level of 10% to 15% in other drying simulation models generally used in dryer desists. Twelve different fan and heater management schemes were evaluated using the computer simulation model based on three hourly weather data from Suweon for the period of 1952-1994. The best management schemes were selected comparing the drymatter losses, required drying times, required energy consumptions. Operating fan without heating only when ambient relative humidity was below 85% or 90% appeared to be the most effective method of In operation in favorable drying weather. Under adverse drying climates or to reduce required drying time, operating fan continuously, and heating air with $1.5^{\circ}C$ temperature rise only when ambient relative humidity was over 85% appeared to be the most suitable method.

• Research in Plant Disease
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• v.7 no.3
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• pp.150-154
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• 2001

The relationships between the weather conditions and the occurrence of rice bacterial grain rot caused by Burkholderia glumae during the rice heading period, were examined by analying the data accumulated from 1992 through 2000 and by conducting greenhouse and field experiment to develop a model far forecasting the disease. The disease severely occurred in 1994, 1995, 1998, and 2000, when it was high in temperature and rainfall during the heading period of middle-late rice varieties. While it occurred weakly in 1993 was high in rainfall and low temperature and it was reversely in 1997. When treated under wetting condition (above the 24-hour)after inoculation at heading period, the infection rate increased as the inculum concentration increased, it was 86.1% at 10$^{8}$ cfu/ml. When under drying condition, the disease of 12.5% occurred only at $^{8}$ cfu/ml. On the other hand, 1,000 grain weight and the percentage of ripened grains remarkably decreased as the infection rate increased.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 1987.06a
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• pp.28-29
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• 1987

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.246-251
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• 2017

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.44-55
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• 1994

This paper describes the development of real-time irrigation reservoir operation models that adequately allocate available water resources for paddy rice irrigation. Water requirement deficiency index(WRDI) was proposed as a guide to evaluate the operational performance of release schemes by comparing accumulated differences between daily release requirements for irrigated areas and actual release amounts. Seven reservoir release rules were developed, which are constant release rate method (CRR), mean storage curve method(MSC), frequency analysis method of reservoir storage rate(FAS), storage requirement curve method(SRC), constant optimal storage rate method (COS), ten-day optimal storage rate method(TOS), and release optimization method(ROM). Long-term forecasting reservoir operation model(LFROM) was formulated to find an optimal release scheme which minimizes WRDIs with long-term weather generation. Rainfall sequences, rainfall amount, and evaporation amount throughout the growing season were to be forecasted and the results used as an input for the model. And short-term forecasting reservoir operation model(SFROM) was developed to find an optimal release scheme which minimizes WRDIs with short-term weather forecasts. The model uses rainfall sequences forecasted by the weather service, and uses rainfall and evaporation amounts generated according to rainfall sequences.

• 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