Tese
Modelagem da severidade de Phakopsora pachrhizi em soja e relações de seus pontos críticos de desenvolvimento com variáveis meteorológicas
Fecha
2022-09-23Autor
Escobar, Otávio dos Santos
Institución
Resumen
Asian soybean rust is a disease with a high impact on soybean yield levels, especially in
Latin America. As it is a fungal disease, climatic conditions are directly linked to its level
of progress and degree of severity in soybean plants. This fungal disease is responsible
for the early defoliation of plants, thus affecting the formation and development of grains,
causing significant productivity losses. The objective of this work was to model the
growth curve of this disease over five seasons, determining critical growth points of the
disease and, through multivariate analyses, verify the interaction between these critical
points and the climatic variables. The database came from an experimental station in the
municipality of Santa Maria, Rio Grande do Sul, in a randomized block design with four
replications in five seasons. Nonlinear regression models were fitted for the progress of
disease severity growth in the crop cycle. The logistic model is the most suitable, as it
represents in a real way the estimates of the parameters and the critical points of the
model, being an important way to evaluate this growth rate. To identify the linear
relationships between the variables, Pearson's correlation and principal component
analysis (PCA) were performed. There are linear relationships between climatic
conditions and the emergence of critical points in the progress of disease severity. Where,
water regimes and temperature levels prior to hotspots, are important parameters to
describe and explain the emergence of hotspots in the progress of disease severity and
serve as indices to predict disease behavior.