Proceedings
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| Filter results6 paper(s) found. |
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1. Large-Scale Sugarcane Yield Prediction Across Regions by Integrating Multi-Source Remote Sensing and Machine LearningSugarcane (Saccharum officinarum L.) is one of the most important agro-industrial crops worldwide, playing a key role in sugar, bioethanol, and renewable energy production. Early and accurate yield estimation during the growing season is essential to support agricultural planning, resource management, and decision-making in the sugar-energy industry under increasing climate variability. However, most yield models are calibrated to single locations and struggle to transfer across regions. The primary... R. Fortes Gallego, F. Serra Burriel, M. Cabrera Dengra, C. Ferraz, A. Do Vale Dondo |
2. Detection of Maize Foliar Diseases Using AI Optimized for Deployment on Edge DevicesMaize is a strategic crop for both regional and global food security. Its productivity is significantly affected by several foliar diseases, among which—common rust, gray leaf spot, and blight—are some of the most prevalent and damaging. These pathologies can cause substantial yield losses if not detected and treated in a timely manner, making early diagnosis a fundamental factor to ensure healthy and sustainable crop development. However, traditional diagnostic methods based on manual... O.J. González Zarate, L. Macea Zabaleta, N. Castillo Ojeda, A.F. Flórez Olivera, T.A. Rodolfo, C. Gonzalez Aguilera |
3. Influence of Terrain Attributes on the Spatial Variability of Soil Macronutrients in Vineyards of Southern BrazilNutrient variability in vineyards directly affects grapevine development and grape yield, highlighting the importance of appropriate nutritional management, since optimizing soil nutrient levels contributes to improved grape, and, consequently, wine quality. The objective of this study was to evaluate the spatial variability of soil macronutrient distribution in a vineyard and to correlate it with terrain attributes. The study was conducted in a 10-ha commercial Pinot Noir vineyard located in... A. Costa Tolfo, B. Trevizan Paese, J.M. Moura Bueno, A.A. Kokkonen, G. Brunetto, S. Schemmer |
4. Relationship Between Soil Classes and Grape Yield in a Vineyard of the Campanha Gaúcha RegionBrazilian viticulture has shown significant expansion in recent decades. However, this productive growth has brought new challenges for vineyard management, particularly regarding the understanding of soil spatial variability and its relationship with grape yield and quality. The objective of this study was to correlate the spatial variability of soil classes with grape yield. The study was conducted in a commercial vineyard located in Santana do Livramento, in the Campanha Gaúcha region,... B. Baumgardt, B. Trevizan Paese, J.M. Moura Bueno, G. Brunetto, A.A. Kokkonen, A. Benetti |
5. Evaluation of the Similarity between Management Zones Based on Spectral Indices and Soil Electrical ConductivityThe delineation of management zones is one of the main strategies in precision agriculture, as it enables site-specific interventions and improves input-use efficiency. Soil electrical conductivity (EC) is widely used to represent the spatial variability of soil physical and chemical attributes and is often considered a reliable indicator. However, acquiring EC data requires specific equipment and field operations, which may increase operational costs. In contrast, spectral indices derived from... |
6. PTx TRIMBLE - Far Beyond the Map: The Power of Split-Second Decision-Making in the Cockpit... G. Coscelli Rocco |