Sugarbeet leaf diseases – Forecasting approaches for the optimization of fungicide application

Epidemics of leaf diseases in farm crops largely depend on the weather. This suggests the idea of determining functional connections between weather parameters and epidemiological magnitudes for use in forecasting models.

Based on Italian results, two empirical forecasting models, resting on regression analytical functions, were developed for Cercospora beticola, which use temperature, relative humidity and easily ascertainable crop parameters as inputs. CERCBET 1 forecasts the regional course of the initial appearance in a region. The model has been tested and is ready for practical application. By means of CERCBET 1, guidance for the monitoring conducted by advisory services and instructions for field inspections by the sugar beet growers can be provided. CERCBET 3, which uses the same inputs, recommends field-specific dates for fungicide application. The model can be adapted flexibly for control thresholds based on C. beticola disease incidents. The forecast can be fine-tuned by including field-specific cultural factors. Two models were also developed for Erysiphe betae: ERYBET 1 for forecasting the regional initial appearance, and ERYBET 2 for calculating the prevalence of infection. ERYBET 1 uses as predictors parameters which describe the weather in winter and spring. These models are still to be tested comprehensively. Epidemiological studies of beet rust, Uromyces betae, were started. Two model approaches for the simulation of the course of attack (UROBET 2) and calculation of the prevalence of infection (UROBET 3) have been derived from experiments in climate chambers.

All disease-specific models will to be made available for counselling and application in a complex but easily manageable decision model accessible through the internet.