Development of a Disease Prediction Model for Brown Spot Disease severity of Rice based on Weather Variable Parameters

Aweather base forecasting system is an important aspect that can reduce by optimising the timing and frequency by reducing chemicals usage. The aim of forecasting system is to reduce fungicides use and accurate prediction is important to synchronize the use of disease control measures to avoid crop losses (Taylor et al. 2003). A prediction model based on the relationship between environmental conditions at the time of management and late season disease severity could be used to guide management decisions. Thus, if a sound forewarning system is developed, the explosive nature of the disease could be prevented by timely application of control measures. In this regard Multiple Regression Analysis (MRA) approaches are being used to help, synthesize and develop understanding of the complex plant-pathogen-environment relations. The resultant models enable exploration of the factors that govern disease epidemics and the design of control systems that minimize yield losses. The same models have potential to guide breeding programs and work to develop strategies that will prolong the usefulness of disease resistance gene. Thus in the present studies on brown spot disease of Rice prediction models based on weather parameters was developed. Brown spot disease of rice caused by Heminthosporium oryzae (Breda de Haan) is a major fungal disease which has been reported to occur in all rice growing countries including Japan, China, Burma, Sri Lanka, Bangladesh, Iran, Africa, South America, Russia, North America, Philipines, Saudi Arabia, Australia, Malaysia and Thailand (Ou, 1985; Khalili, et al. 2012). In India the disease was known to occur in all rice growing states but more severe in dry and direct seeded rice in the state of Bihar, Chhatisgarh, Madhya Pradesh, Orissa, Assam, Jharkhand and West Bengal (Gangopadhyay, 1983; Ou, 1985; Ghose et al., 1960). This particular disease has been reported to cause enormous losses ingrain yield upto 90% particularly when leaf spotting phase assumes epiphytotic proportions as observed in great Bengal famine in 1942 (Ghose et al. 1960), in general it can cause yield loss upto 45% when no protection was given. The weather influences all stages of host and brown spot pathogen life cycles as well as the development of disease (Chakrabarty et al. 2000). A warning system is previously developed and is being used to schedule fungicide applications for controlling Lettuce downy mildew caused by Bremia letucae Regal in coastal California (Scherm et al. 1995). The problem, nature and epidemiologist specific questions determine the mathematical tool to be used for modelling plant disease epidemics (Kranz and Royle, 1978; Sutherst, 1993; Xu, 2006).