Determination of height in corn (Zea mays L.) crops through the use of images produced by UAVs

Abstract

Behind only soybean production, corn is the second most produced grain in Brazil. Remote sensing is generally considered one of the most important technologies for precision agriculture and smart agriculture, enabling producers to monitor various parameters in agricultural crops. This work aimed to determine the height of plants in corn crops through the photogrammetry technique using unmanned aerial vehicles (UAVs). The experiment was conducted in the municipality of Montividiu, State of Goiás, Brazil, in the 2023 harvest. The mapped crop was corn, the georeferenced images were captured via drone, with 249 photos generated during approximately 14 min of flight. The geoprocessing of the orthomosaic and digital surface model was ArcGIS, in which the sketch was plotted on the orthophoto (georeferenced image) to later extract the height data for each treatment. The original data were subjected to the normality test with 5% significance and homogeneity test with 5% significance, then the data were subjected to analysis of variance using the F test with p < 0.05 and, when significant, it was used if the Tukey test with p < 0.05. Block A had the best performance for average plant height with values above 0.8 m. The use of UAVs proved to be an important and efficient tool in determining the height of corn plants for future work on phytopathology, nutrient deficits, areas with leaching or even distinguishing different cultivars.