Proceedings
Authors
| Filter results8 paper(s) found. |
|---|
1. The Influence of Field Geometry on the Operational Stability of Uav-based SprayingThe use of spraying drones has expanded rapidly in precision agriculture; however, operational factors such as field geometry may compromise application stability. This study aimed to evaluate the influence of field shape on operational variability and operational capacity during spraying performed with a DJI Agras T100 drone. The experiment was conducted in two fields with distinct geometries: a regular (rectangular) field and an irregularly shaped field, located at the Technology Development... A. Felipe dos santos, R.Q. alvez, T.O. Barboza, M.C. Arnosti, G.F. Valdez , G.L. Silveira |
2. Automated Initial Plant Stand Assessment in Bean Crops Using Uav-based Yolov8 DetectionThe use of RGB images acquired by unmanned aerial vehicles (UAVs), combined with artificial intelligence techniques, has increased significantly in recent years for object identification and crop monitoring in agriculture. These technologies enable rapid plant stand count, facilitating decision-making processes. However, limited information is available regarding the optimal flight height for identifying bean plants at early growth stages. Therefore, the objective of this study was to evaluate... G. Valdes fernandez , G. Lacerda da silveira, R. Fernandes queiroz alves , T. Costa barboza, M.C. Arnosti, A. Felipe dos santos, W.B. Da silva, O. Pereira da costa |
3. Comparative Analysis of YOLOv3–YOLOv12 Architectures for Automatic Oil Palm Detection in Agricultural MonitoringOil palm (Elaeis guineensis) is considered the most productive oilseed crop worldwide, and Brazil holds one of the greatest global potentials for palm oil production. Efficient monitoring of cultivated areas is therefore essential for proper crop management, enabling the detection of planting gaps, yield estimation, and decision-making support. In this context, computer vision techniques based on deep learning models, particularly those from the YOLO (You Only Look Once) family, have... M.C. Arnosti, A. Felipe dos santos, T. Costa barboza, L.S. Souza pinto, E. Amaral, G. Lacerda da silveira, G. Valdes fernandez |
4. Geometric Assessment of Software-Based Path Planning for Mechanized Seeding OperationsThis study evaluated the impact of different software-based planning routines on the geometry of guidance lines for mechanized seeding operations. A controlled comparative case-study approach was implemented using two agricultural fields in Minas Gerais, Brazil. One irregular field of 33.6 ha and one predominantly rectilinear field of 107.6 ha. Two anonymized tools, Software A and Software B, were applied to identical boundary polygons, with one headland pass and 9 m line spacing. The exported... A. Felipe dos santos, R.D. Borges, M.C. Arnosti, C. Marcassa lonzi de oliveira |
5. Multi-Band UAV-Borne SAR Sensitivity (C, L, and P Bands) for Detecting Leaf-Cutting Ant Nests in Eucalyptus PlantationsPlanted forests in Brazil cover approximately 10.5 million hectares and are recognized worldwide for sustainable management and the supply of bioproducts derived from renewable raw materials. In addition, the country stands out in pulp production and exports, ranking second only to the United States. However, the planted forest sector has faced phytosanitary challenges, particularly related to leaf-cutting ants, which cause biomass losses and reduce leaf area, compromising photosynthetic capacity... W. Batista da silva , A. Santos, T. Costa barboza, O.P. Costa, G. Valdes fernandez , M. Ciscato, G. . Silveira, R. . Filho |
6. Evaluation of the Performance of Computer Vision Models in the Detection and Counting of Tomato Plants Infected by Tomato Spotted Wilt Virus (TSWV)Tomato is one of the most economically important vegetable crops worldwide. However, this crop is severely affected by Tomato Spotted Wilt Virus (TSWV), whose transmission occurs mainly through thrips. Thus, identifying infected plants is an important step to reduce the dissemination and infection of healthy plants, reducing economic losses. Computer vision-based models have been widely used in the automated detection of plant diseases. In this context, this work aimed to evaluate the performance... L.S. Souza pinto, S. . azevedo, M. . Medeiros, A. Felipe dos santos, T. Costa barboza, M.C. Arnosti, G. Valdes fernandez , G. Lacerda da silveira |
7. Automated Detection of European Canker (Neonectria ditissima) in Apple Trees via Multispectral Sensors and Computer VisionEuropean canker, caused by the fungus Neonectria ditissima, represents one of the major economic challenges for Brazilian pomiculture, severely affecting ‘Gala’ and ‘Fuji’ cultivars. The disease manifests primarily in woody tissues, such as trunks and branches, although it can also cause fruit rot during the pre-harvest stage. Infection occurs obligatorily through wounds, whether natural (leaf scars) or resulting from management practices (pruning and harvesting).... S. Alves, E.C. Da silva, L.D. Marchioretto, L. Gebler |
8. Assessment of Spatiotemporal Variability in Desiccation Efficiency Using a Spray Drone Through Vegetation IndicesThe increasing adoption of spray drones in precision agriculture has raised important questions regarding operational parameters and their influence on herbicide performance under field conditions. Although unmanned aerial spraying systems offer advantages such as reduced soil compaction, greater operational flexibility, and rapid field coverage, the interaction between flight parameters and droplet deposition dynamics remains insufficiently understood. This study aimed to evaluate the spatial... G. Lacerda da silveira, M.C. Arnosti, G. Valdes fernandez , T. Costa barboza, A. Felipe dos santos, E. Amaral |