Proceedings
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| Filter results6 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. 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 |
4. 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 |
5. 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 |
6. 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 |