Proposal of a weather-based prediction system for Yellow Sigatoka in Santa Catarina State, Brazil

Abstract

Banana (Musa spp.) is one of the main fruits produced in Brazil, and its production is among the largest in the world. The Sigatoka disease complex is widely distributed across banana producing regions mainly comprising the fungi Pseudocercospora fijiensis and P. musae, causal agents of Black and Yellow Sigatoka, respectively. This study observed the epidemiological factors affecting the development of Yellow Sigatoka disease in a banana plantation not sprayed with fungicides in the subtropical climate of Santa Catarina, Brazil, to propose a prediction system for the disease. Yellow Sigatoka severity was assessed using Infection Index, Gross Sum and Youngest Leaf Spot. Air temperature (°C), relative air humidity (%) and leaf wetness (h) were monitored by an automatic meteorological station with data collected each 30s. Leaf wetness and average temperature are the main meteorological variables that explain Yellow Sigatoka increase. A prediction system model was developed to predict disease severity.

Keywords

• Temperature
• Leaf Wetness
• Disease Progress Curve
• Musa spp.