Amostragem de nematoides em lavoura de soja com base em NDVI gerados de imagens de satélite

Abstract

Each year, nematodes take up more space among the pests that cause the most damage to soybean crops. The aggressiveness of certain species reaches a point where it can completely eliminate crop productivity. Therefore, knowledge of their distribution in the planting area is essential for a successful pest control strategy. It is imperative to continuously update the methods that help combat these pests. The objective was to determine parameters for detecting nematodes using NDVI (Normalized Difference Vegetation Index) on images provided by the Sentinel-2 satellite group. The visualization, editing, and analysis were performed using the free software Qgis. The images were colored with false color in the RYG (Red-Yellow-Green) pattern, with 10 color classes, ranging from red (dead plants or exposed soil) to green (good health of the culture). The last three harvests of the Monique farm, located in the municipality of Nova Xavantina, were analyzed. The areas that presented results below the standard were georeferenced, and their coordinates were exported to a handheld GPS that assisted in the collection of samples from the possible nematode breeding sites. It was possible to identify areas with symptoms of nematode infestations, with the presence of Heterodera glycines, Pratylenchus brachyurus, and Meloidogyne incognita, the most important and aggressive species of the soybean culture. This allowed for the determination of areas of possible nematode foci before going to the field, facilitating the sampling of collection points.