The rice leaf blast simulation model EPIBLAST

Abstract

Rice blast, caused by Pyricularia oryzae, is one of the biggest constraints to stable rice production in most of the temperate regions and so me tropieal and subtropical countries. To minimize yield loss by blast disease, large efforts have been made to solve the blast problem. However, it is very difficult to eliminate blast from fields due to the complexity of the life cycle of P. oryzae. In Korea, we experimented and collected field data of the blast fungus to study in epidemiology and developed a leaf blast simulation model EPIBLAST. It is devised for quantitative forecasting of the incidence of the leaf blast disease. In EPIBLAST, temperature, relative humidity, rainfall, dew period, and wind velocity are the meteorologieal input variables. Healthy, diseased and dead leaf area are plant physiologieal state variables. Inoculum potential, sporulation, conidia release and dispersal, penetration, and incubation period are by epidemiologieal processes. The accuracy of EPIBLAST predictions was field tested during the 1991 cropping season. EPIBLAST predicts peak of the leaf blast epidemie as early as middle of July. It can also prediet similar disease progress patterns with direct observation, but so me fluctuations were observed due to sensitivity of EPIBLAST to minute weather changes. It needs further revision.