Soybean frogeye leaf spot (Cercospora sojina): first weather-based prediction models developed from weather station and satellite data

In Argentina, soybean frogeye leaf spot occurs sporadically. However, particularly in the Pampas Region, the incidence and severity of this fungal disease have significantly increased in the last years. In the present study, its epidemic progress was evaluated in six sites of the Pampas region during the 2009/2010 soybean season. Also, meteorological variables were calculated during the nine days previous to each field observation of disease occurrence for each site, using weather station and satellite data. Rain occurrence was obtained from the 3B42 TRMM product and temperature images were taken from NOAA-AVHRR. Then, logistic models were used to estimate probabilities of having severe or moderate to null disease. The stepwise procedure used to select the best model included the interaction (product) between wetness frequency (WF) and sum of days without precipitation (DwP) as a variable. Estimations from the resulting model agreed with the observed epidemiological curve for one of the sites studied (El Trébol, Santa Fe) during the 2010/2011 soybean season and coincided with the low disease presence recorded during the 2011/2012 soybean season. These new results could be useful as support for rational fungicide application.

Keywords:

Disease dynamics , Logistic models , Remote sensing , Epidemiological curveWeather predictor