Coffee rust is a major disease problem for coffee plantations around the world. This disease is also of great importance in Brazil, which is the main coffee producer and exporter in the world, with an expected production of about 36.1 million bags for 2016. Among the main threats for coffee plantations, diseases, like coffee rust, are the most important. For coffee rust management, use of fungicide sprays for control is the most efficient method; however, it is usually applied based on calendar-timed criteria, which does not consider environmental favorability for disease occurrence. An early-season coffee rust warning system based on weather-determined risk of disease outbreaks would be of great interest for producers, allowing them to be prepared before the growing season and rationalizing the use of chemicals in their fields, avoiding epidemics. Using weather and disease incidence data from three locations in the state of Minas Gerais, Brazil, collected since 1998, a coffee rust forecast system was developed based on weather conditions and was evaluated with independent data, besides it is currently under field evaluation in order to evaluate its suitability for coffee rust management. In this project, the system will be applied to different production coffee areas in Brazil (Paraná, São Paulo and Minas Gerais states), using historical weather series from 1961 to the present. The main motivation for that is to evaluate how the disease developed under different phases of ENSO in these areas in order to develop and evaluate the feasibility of an early-season coffee rust warning system for preparing producers and coffee chain to control the disease appropriately.
News published in Agência FAPESP Newsletter about the scholarship: