O uso de drone na avaliação da distribuição longitudinal de plantas de milho (zea mays l) semeadas com uma semeadora tração humana

Abstract

Precision agriculture has expanded with the use of technologies such as drones, enabling efficient crop monitoring. This study aimed to evaluate the performance of a human-powered seeder in the longitudinal distribution of maize (Zea mays L.) seeds using aerial images captured by a drone. The experiment was conducted under no-tillage conditions in Bom Lugar – Maranhão, Brazil. DJI Mini 3 drone flights were carried out at different phenological stages of the crop, generating orthomosaics and Digital Elevation Models (DEM) using Agisoft Metashape software. Planting failures were estimated through supervised classification in the SPRING software, allowing the identification of plantability gaps, stand uniformity issues, and operational deficiencies in the seeder. The results demonstrated that drone technology is effective for diagnostics and agronomic decision-making in small-scale farming systems, contributing to resource optimization and increased productivity