A Forecast Model for Bacterial Grain Rot of Rice and Its Implementation in the National Crop Pest Management System

Abstract

Bacterial grain rot (BGR) of rice, which is caused by Burkholderia glumae, occurs worldwide and is a constraint on rice production by infecting spikelets of panicles. Seedling symptoms of B. glumae infection include brown, water-soaked soft rot of the leaf sheaths. Infected grains are shrunken and pale-green, later becoming dirty yellow to brow and very dry. Severe infections could result in substantial yield loss. Previous studies on population dynamics on rice plants showed that colonization of leaf sheaths by the pathogen plays an important role in primary infection. Disease incidence of BGR varies every year depending on weather conditions in Korea. Currently, no resistant cultivars have been reported yet. The major strategy to control the disease is one or two chemical sprays around the heading stage of rice plants. However, chemical sprays are often made by rice growers even if weather conditions are not favorable enough for epidemic development of the disease. The present study was conducted (1) to determine a quantitative measure of environmental conduciveness to epidemic development of BGR

(2) to develop a forecast model based on the conduciveness of weather conditions to decide whether to spray chemicals during the heading stage of rice plants

and (3) to implement the BGR forecast model in the National Crop Pest Management System (NCPMS) of the Rural Development Administration. The disease forecast model, which was named BGRcast, determined daily conduciveness of weather conditions to epidemic development of BGR and forecasts 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 by the bacteria in the field. The BGRcast calculated daily environmental conduciveness, ???? , 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., survival, inoculum build-up and infection phases. Daily average of ???? were calculated for the inoculum build-up phase (????????) and the infection phase (????????). The ???????? and ???????? were considered environmental conduciveness for the periods of inoculum build-up in association with rice plants and panicle infection during the heading stage. The disease forecast model was able to forecast correctly actual occurrence of BGR at the probability of 71.4% and its false alarm ratio was 47.6%. With the thresholds of ???????? = 0.3 and ???????? = 0.5, the model was able to provide advisories that could be used to make decisions on whether to spray bactericide at the pre- and post-heading stage. It was concluded that BGRcast could be used in practice by rice growers to improve effectiveness of conventional spray programs to control BGR. The NCPMS is the nation-wide disease and insect pest management system for agricultural crops. NCPMS is composed of three main systems

monitoring, forecasting and diagnosis of diseases and insect pests. Currently, BGRcast is being used in NCPMS to support rice growers who are keen to spray chemicals only when infection risk of B. glumae is high enough to cause significant yield loss. The forecast information is delivered to registered users via short message service (SMS) automatically at 7 AM every day. The number of registered users has increased from 1,136 users in 2011 to 4,013 in 2014.