Progress of beet Cercospora leaf spot under different spraying regimes

Abstract

Cercospora leaf spot (CLS) caused by Cercospora beticola Sacc. is controlled by foliar spraying with fungicides following a fixed schedule, without considering the disease progress. A forecasting system can predict the progress of the disease and direct the spraying regime, reducing the number of applications and optimizing the disease management. To evaluate the progress of CLS under the different spraying regimes, the statistical modeling technique known as mixed models was applied. These models include not only fixed effects but also random effects for each individual in the studied population. In the harvest seasons of 2018 and 2019, the spraying regimes used were based on systems with accumulated estimated severity (SE) values of 0.15; 0.25, and 0.35, in addition to standard controls with spraying intervals of five and seven days. The accumulated severity of CLS as a function of time in the five spraying regimes was calibrated with a Gompertz model adjusted by the mixed model and the random effect adjusted to the upper asymptote. As a result of the model calibration, the spraying regime treatment with SE=0.35 did not differ from the standard controls regarding the area under the disease progress curve (AACPD), final severity, and productivity. The data presented in this study demonstrate the efficiency of a forecasting system in CLS management, with the advantage of reducing the number of fungicide sprayings and environmental impact.