BGRcast: A Disease Forecast Model to Support Decision-making for Chemical Sprays to Control Bacterial Grain Rot of Rice

Abstract

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, Ci, 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 Ci was calculated for the inoculum build-up phase (Cinf) and the infection phase (Cinc). The Cinc and Cinf 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 Cinc = 0.3 and Cinf = 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.

Warming increases Bacterial Panicle Blight (Burkholderia glumae) occurrences and impacts on USA rice production

“…Existing literature suggests that BPB occurrences are triggered by conditions of high daily minimum temperatures in combination with simultaneously high relative humidity during the flowering stage. Specifically, this study uses 22 °C minimum daily temperature and 80% relative humidity based on previous findings [11,20,21,26]. BPB was commonly found when relative humidity was over 95% for 24 hours during flowering [11].…”

“…A study in Japan found that BPB developed when minimum daily temperature was ≥ 23° C and moderate rainfall (< 30 mm/day) occurred during the rice-heading stage. In their comprehensive in-field study, [20] found that BPB was not present when the minimum daily temperature was below 22°C and daily mean relative humidity was lower than 80% for the period of seven days from the first panicle emergence through the heading stage. The range of relative humidity needed for BPB to develop is more nebulous, [15] found that BPB occurred when relative humidity was between 75% and 95%.…”

“…AMTemp lt corresponds to the average minimum daily temperature seven days surrounding panicle emergence in year t in county/parish l . TRH is the threshold of relative humidity which can vary between 75% and 80% based on the minimum RH percentage required for a BPB occurrence, respectively [15,20]. In this study, occurrences are modeled where TRH is equal to or greater than 77%.…”

Sustainable Strategies for Managing Bacterial Panicle Blight in Rice

“…Tsushima et al [57] found BPB commonly occurred when relative humidity was more than 95% for 24 hours during flowering. Lee et al [58] reported that the disease did not develop when the minimum daily temperature was less than 22°C and when relative humidity was below 80% during the heading stage. Nandakumar et al [1] found that the optimum temperature for the growth of B. glumae and B. gladioli ranged from 35 to 40°C.…”

Effects of Interrupted Wetness Periods on Conidial Germination, Germ Tube Elongation and Infection Periods of Botryosphaeria dothidea Causing Apple White Rot

“…The presence of free water, especially on the host surface, triggers a number of biological activities of fungal pathogens, including spore discharge, spore germination and host infection in many host-parasite interactions. Either wetness period or relative humidity are therefore commonly employed in disease warning systems as a critical determinant of infection risk ( Arauz et al, 2010 ; Grove, 2002 ; Huber and Gillespie, 1992 ; Kim and Yun, 2013 ; Lee et al, 2015 ; Xu et al, 2007 ).…”