Modelling black Sigatoka epidemics with seasonal dispersal of Mycosphaerella fijiensis ascospores over a banana plantation in the Ribeira Valley, São Paulo, Brazil

Abstract

Knowing the patterns of Black Sigatoka development is essential to propose adequate disease management practices and evaluate their effects, which can be achieved through temporal analysis by integrating the evolving interactions of the pathosystem components, expressed by data on cumulative incidence and severity, and summarizing these data in a disease progress curve. Airborne spores are essential components for the progression of an epidemic in the context of a specific pathosystem. In this perspective, the spore count is an essential approach to assess and model an epidemic. This study evaluated the temporal dynamics of Black Sigatoka in a banana plantation in the Ribeira Valley, state of São Paulo, Brazil, while simultaneously performing a year-long evaluation of fungal spore aerobiology. The disease was intense during the rainy season, but the leaf emergence rate was high enough for quickly inverting the severity peak (between 169 and 197 days of evaluation). After that, the disease severity raised until reach the higher rates (around the score 7 out of 8). The disease progress curve of Black Sigatoka showed peaks of extreme severity, one in the rainy and another in the dry season, with high levels of ascospores in the air. The ascospore concentration and the severity of the disease correlated significantly on the same day of sampling and 15 days after ascospore sampling, corresponding to the average latency period of the disease in the region. The patterns of the disease progress curve in both peaks fitted the monomolecular model, with higher rates of disease increase in the rainy season.