Identification of Weed Species in Commercial Soybean Areas by High-Resolution Drone Images

Multispectral sensors onboard remotely piloted aircraft systems (RPAs) can be used for mapping and identifying weed species and preventing crop yield losses. The objective of this study was to identify and quantify weed species in soybean using high-resolution images obtained by an RPA. Soybean fields were photographed 33 times every 100 ha. Weed flora in 384 sampling areas was surveyed by aerial imaging in approximately 60.000 ha. Results on analysis of the community structure of the observed a total of 16 plant families and 52 species. Species from Asteraceae and Poaceae were the most numerous. Results of principal component analysis showed that the percentage of infestation and the number of species were positively correlated to the first component. The areas with the highest percentage of infestation had the highest diversity of species. However, the percentage of infestation and the number of species observed were not correlated with the area size. The survey of weeds by aerial imagery was efficient for identifying, quantifying, and mapping weeds in commercial agricultural areas and can be used in other studies and for the purposes of management in commercial areas.