Proceedings
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| Filter results9 paper(s) found. |
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1. Sensing-Based Correlation Analysis of Surface Elevation and Topsoil Depth in Japanese Rice Paddy FieldProper management of soil physical properties is fundamental for stabilizing crop yields and optimizing resource efficiency in large-scale rice paddy production. Among these properties, field surface elevation and topsoil depth (TD) are critical determinants of water management effectiveness and root zone environments. This study conducted a high-resolution grid-based correlation analysis between surface elevation and TD in a 1.4-ha paddy field in Tottori Prefecture, Japan. To overcome the limitations... E. Morimoto, J. Lee, K. Nishida, H. Itoh |
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. Influence of Meteorological Variables on Bean Yield in the Semi-Arid Region: A Data-Driven Approach for Agricultural Decision SupportCommon bean is a strategic crop for the Brazilian semi-arid region, predominantly cultivated under rainfed systems that are highly dependent on climate variability. In regions characterized by irregular rainfall patterns, high temperatures, and extreme weather events, incorporating temporal analyses based on meteorological data becomes essential for evidence-based agricultural planning. Within the context of precision agriculture, the integration of historical climate series and productivity indicators... A. Fonseca, J.F. Dos Anjos, E.F. Da Silva, G.B. Moura, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.C. Bezerra |
4. Development of an IoT Platform for Soil and Climate Monitoring in Irrigated Fruit Production in the Semi-Arid Region of PernambucoIrrigated fruit production in the São Francisco hinterland, led by the Petrolina production hub, reached US$ 294 million in exports in 2023, consolidating mango and grape crops as strategic pillars of Pernambuco’s economy and of the Brazilian semi-arid region. This production system is dependent on irrigation due to irregular rainfall distribution, high evaporative demand, and recurrent drought conditions. Despite its international competitiveness and technological advances in irrigation... A. Fonseca, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, A.D. Ribeiro |
5. Nonlinear Modeling of Vegetation Response to Rainfall Variability in the Brazilian Semi-Arid Region Using Sentinel-2 and CHIRPS DataHigh climate variability in the Brazilian semi-arid region poses significant challenges to agriculture and the sustainable management of Caatinga ecosystems, requiring monitoring tools capable of anticipating vegetation responses to rainfall fluctuations. However, the spectral response of vegetation to precipitation does not always follow linear patterns and may reflect ecohydrological thresholds and water saturation effects. Sentinel-2 data were used to derive the Soil Adjusted Vegetation Index... A. Fonseca, E.F. Da Silva, A.C. Bezerra, G.B. Moura, J.F. Dos Anjos, E.D. Figueirôa , G.P. Coelho, J.P. De Andrade, E. Lopes, J.I. Silva |
6. 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 |
7. Mobile Edge AI for Detection of Grape Clusters and Disease Symptoms in VineyardsPrecision viticulture demands accessible technological solutions that enable rapid disease diagnosis and production monitoring directly in the field. In real-world production contexts, dependence on cloud connectivity, external servers, or specialized hardware limits the adoption of computer vision tools by small and medium-sized farmers. In this context, this work presents a solution based on artificial intelligence embedded in a mobile application for the detection of grape bunches and leaves... E.M. Da Silveira, F.I. Nogueira, S.D. Camargo, A. Freire Campos, J. Valiati, E.F. Leite |
8. 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 |
9. Digital Agriculture in Decision-Making for Sustainable Disease Management in Soybean CropsSoybean (Glycine max L.) stands out as one of the main crops of agronomic interest, widely used in human and animal nutrition due to its high protein content and diversity of derivatives. Soybean crop productivity is strongly influenced by meteorological conditions, adopted management practices, and the incidence of pathogens, which can significantly reduce the plant’s photosynthetically active area, directly impacting final yield. In this context, the present study aimed to evaluate... E. Rolim Farias Da Silva, L. Lüdtke, G. Ductra Bortolotti, I. Maldaner, L. , J. Sgarbossa, L. Silveira Pavão, A. Müllich |