Abstract
Cercospora leaf spot (CLS), caused by the fungal pathogen Cercospora beticola, is the most economically important disease of sugar beet. If left unmanaged, CLS can significantly reduce crop yields and sugar content. Timely fungicide applications are critical management tools used by growers to combat CLS with the timing of applications informed by disease forecasting models. Currently deployed CLS forecasting models rely heavily on relative humidity and temperature as indicators of symptom onset but neglect indicators of infection initiation. Recently, field studies involving spore trapping and CLS infection progression monitoring have revealed high spore abundance early in the growing season leading to the initiation of asymptomatic infection prior to symptom onset. As fungicide applications are not curative, synchronizing fungicide applications with asymptomatic infection onset may present an opportunity to better manage CLS and indicators of infection onset need to be incorporated into CLS risk models. Lab and greenhouse studies have shown that C. beticola spores can germinate at temperatures as low as 10℃ if moisture conditions are favorable. Here we used weather sensors and correlated environmental conditions that correspond to favorable spore germination conditions and propose these parameters be incorporated into existing CLS risk models. This two-part model system has potential to increase the utility of CLS risk models to better target fungicide applications to be maximally protectant against CLS disease onset.