Forecasting of rice blast disease severity in West Bengal, India based on PDI values and Cumulative logit model

摘要

Blast disease of rice is generally considered the most important rice disease worldwide for its extensive distribution and also for its destructiveness under favourable environmental conditions. The disease incidence and development in time scale in relation to different parameters can be predicted through epidemiological study. Plant disease forecasting is a management system used to predict the occurrence or change in severity of plant diseases. A field experiment was conducted for three consecutive year in kharif season at two different sampling sites in North 24 Parganas, West Bengal to find out the effect of meteorological factors on severity of blast disease. The aim of the present study is to prepare models for predicting the severity, with the aim of helping to prevent or at least mitigate the spread of blast disease. For forecasting of disease severity, the comparative study of three years meteorological data was made. The congenial weather conditions for the infection of blast disease pathogen viz. Pyricularia oryzae was recorded. The crop phases during which rapid development of disease takes place were also recorded. Multiple regression analysis (MRA) of PDI values with the age of the plant, respective pathogenic spore concentration and with five meteorological parameters was performed. From step down equation, it was found that if the age of the plant and airborne spore concentration, RH and rain fall are increased, disease severity also increases significantly in both the seasons. From Cumulative logit model the covariates with their odds ratios were determined. From all the findings it can be concluded that among meteorological parameters high relative humidity, rain fall and comparatively low temperature are the common factor for disease incidence and severity.