Relação espaço-temporal e espectral da ferrugem do café arábica com índices de vegetação do Sentinel-2

Abstract

Coffee rust (Hemileia vastatrix Berkeley & Broome) is the main coffee disease in Brazil. The control of coffee rust is carried out with chemicals according to the calendar to prevent the disease epidemic. The objective of this work was to identify coffee rust using MSI / Sentinel-2 by means of analyzes involving vegetation indeces and coffee rust incidence, defoliation and yeld data obtained in situ. The sample area located in the EPAMIG experimental field in Três Pontas-MG contained two plots in 42 years old coffee crop, in a cultivar susceptible to rust. Conventional chemical control of rust was carried out in only one of the plots. Coffee rust incidence in areas with and without chemical control were assessed monthly for five months, from December 2018 to April 2019, a period with ideal environmental conditions for the occurrence of the disease. After Pearson's correlation performed between 10 different vegetation indexes with data on coffee rust incidence, defoliation and yeld, relationships between the variables under study were verified. Correlations occurred mainly between coffee rust levels in February 2019 and the vegetation indices generated with the Sentinel-2 image from August 2018, September 2018 and February 2019 (IRECIAug r = 0.566; IRECISep r = 0.493; NDMIFeb r = -0.518; NDVI(RE1)Feb r = -0.562; CI(RE1)Feb r = -0.573; MSR(RE1)Feb r = -0.569), for areas where there was no coffee rust control. The indeces obtained through relationships that use only the Red-Edge 1 and Near Infra-Red bands (NDVI (RE1), CI (RE1) and MSR (RE1)) were more sensitive to capture the spectral changes of vegetation due to the occurrence of coffee rust over the months. The IRECI index, on the other hand, demonstrated sensitivity to predict areas with a higher potential for coffee rust incidence.