Proceedings
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| Filter results11 paper(s) found. |
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1. Development and Evaluation of a Novel Seeding Metering System for Mechanic Seeder Toward Precision AgricultureRecent progress in precision and digital agriculture has increasingly relied on the integration of computational modeling, sensor-based analysis, and data-driven design to improve agricultural machinery performance. Seed metering systems are central to this progress, as they regulate seed delivery for both uniform crop establishment and variable-rate seeding applications. In conventional agricultural systems, where field conditions are assumed to be relatively homogeneous, uniform seed spacing... E. Jotautienė, D. Karayel, H. Yilmaz, A. Grigas |
2. Autonomous Robotic Spraying System for Weed Management in Woody Perennial CropsWeed management in woody crops remains a major agronomic, economic, and environmental challenge. In orchard environments, tree trunks, low canopies, and narrow intra-row spacing severely restrict conventional machinery access to the under-canopy zone. As a result, weed control near tree trunks remains predominantly manual. This limitation coincides with an increasing scarcity of agricultural labor, leading to higher production costs and delays in weed... M. Pérez-ruiz, L. Sánchez-fernández, A. Nizzoli, E. Apolo-apolo, J. Martínez-guanter |
3. Spatial Prediction of Soil Classes and Nutrients Using Random Forest in the Context of Precision ViticulturePrecision viticulture is based on modeling the spatial variability of soil, plant, and topographic attributes to support optimized management decisions. In this context, machine learning based spatial prediction algorithms have been increasingly applied for spatial interpolation. Their application in vineyards has shown strong potential to improve the representation of spatial variability and to support site-specific management strategies in viticulture. The objective of this study was to evaluate... F. Lasch, B. Trevizan Paese, J.M. Moura-bueno, G. Brunetto , A.A. Kokkonen, F. De Araújo Pedron, R.S. Dalmolin, L. De Paula Amaral |
4. Remote Sensing for Identifying Soybean Cultivars and Estimating Crop YieldsTraditional methods for cultivar identification and agricultural productivity estimation have been increasingly complemented or replaced by innovative approaches using geotechnologies and Artificial Intelligence (AI). These modern techniques offer greater efficiency, speed, and sustainability in agricultural production systems. Among these advances, Remote Sensing (RS) has stood out as an effective tool for agricultural monitoring. It allows the collection of spectral and biophysical information... B. Matwijou, J.R. Oliveira, M. Da Silva, G.G. Scheidt, A. Lopes De Brito Filho, M.G. Da Silva Brochado, F. Morlin Carneiro |
5. Evaluation of Diffuse Reflectance Spectroscopy and Machine Learning Methods for Soil Available Phosphorus and Potassium PredictionPhosphorus (P) and potassium (K) are essential elements for plants. Accurate evaluation of soil available P and K contents is fundamental for precision agriculture and site-specific nutrient management. However, traditional chemical analyses are time-consuming, labor-intensive, and costly. In this context, diffuse reflectance spectroscopy (DRS) has been introduced as a cheaper and rapid alternative; however, its accuracy in estimating soil P and K contents has not been fully proven, particularly... C. Guerra Martins, D.L. Grando, J. Moura Bueno, G. Brunetto, A.A. Kokkonen, L. Peranzoni Deponti, L. Bastos |
6. Embrapii: What Can We Learn About Precision Agriculture and Environmental Sustainability After Investments of US$100 Million+ in Agricultural Industrial Innovation in Brazil?Innovation policies have increasingly targeted digital and sustainable transformation, yet systematic assessments of large-scale public-private investments in precision agriculture innovation remain scarce, particularly in tropical contexts. This article analyzes the experience of Embrapii (Brazilian Agency for Research and Industrial Innovation) after fostering more than US$100 million in investments in over 600 research, development, and innovation (RD&I) projects applied to agriculture... J. Videira Menezes, E.M. Dias, M.L. Rebello Pinho Dias Scoton, D.H. Oliveira, I. Mendes Gaya Lopes Dos Santos, F. Stallivieri, L. Cunha De Sousa |
7. Standardisation Challenges in Precision Agriculture: Mapping the Landscape and Advancing Semantic InteroperabilityBackground: Precision agriculture increasingly depends on digital technologies and the exchange of data between equipment, sensors, platforms and decision support tools. A wide range of standards is available, including machine data formats such as ISOXML and semantic resources such as AGROVOC and rmAgro. Despite this variety, the overall standardisation landscape remains fragmented. Even within single countries, differences in code lists, vocabularies and data publishing... J. Tummers, F. Sijbrandij, T. Ten Den, A. Gupta, T. Bresilla, B. Veldhuisen |
8. Towards Trusted Satellite Data for Precision Farming: Mitigating Spoofing and Improving Data Integrity Using Galileo OSNMA and HAS and Copernicus Traceability ServiceBackground: Precision agriculture increasingly relies on GNSS positioning not only to execute field operations with high spatial accuracy, but also to provide trustworthy data for documentation, certification, and regulatory compliance. However, GNSS signals remain vulnerable to degradation, jamming, and especially spoofing—an intentional manipulation of satellite signals causing machinery to believe it is in a different position. Such incidents have already been observed... B. Veldhuisen, T. Bresilla, J. Tummers, F. Sijbrandij, T. Ten Den, A. Gupta, T. Van Der Wal |
9. 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 |
10. 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 |
11. Spatial Variability of Foliar Nutrient Contents in a Vineyard of the Campanha Gaúcha RegionLeaf analysis is an essential tool for understanding nutrient availability, absorption, and redistribution processes in plants, providing technical support for decision-making in precision viticulture systems. The spatial variability of nutrient contents in leaf tissue is associated with soil heterogeneity, topographic conditions, and vineyard management practices. The objective of this study was to evaluate the spatial variability of macronutrients in grapevine leaf tissue, identifying distribution... R. Balsamo Brondani, B.T. Paese, J.M. Moura-bueno, A.A. Kokkonen, G. Brunetto |