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Yilmaz, H
Yenibehit, N
Yan, J
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Authors
Jotautienė, E
Karayel, D
Yilmaz, H
Grigas, A
Yenibehit, N
Pedersen, S.M
Tamirat, T.W
Françani, A.O
Zhao, L
Ferreira , J
Yan, J
Ferreira, E.J
Jorge, L.A
Topics
Agricultural Robotics, Automation, and Mechanization
Site-Specific Nutrient, Lime and Seed Management
Precision Crop Protection, Pest, and Plant Health
Type
Oral
Poster
Year
2026
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1. Development and Evaluation of a Novel Seeding Metering System for Mechanic Seeder Toward Precision Agriculture

Recent 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. Do Precision and Climate Concerns Shape Fertilizer Usage Proportions? Evidence from Denmark

Farmers are constantly facing pressure to enhance crop productivity while minimizing environmental and climate impacts through efficient input management. In Denmark, because of concerns over nitrogen leaching, greenhouse gas emissions, and water quality degradation, there are tight regulations to fertilizer use. This makes precision farming technologies a key to the efficient management of nutrients through site-specific input application based on crop and soil variability. However, adoption... N. Yenibehit, S.M. Pedersen, T.W. Tamirat

3. Characterizing Cross-Crop Stink Bug Spectral Signatures from Hyperspectral Data

Effective crop protection in agricultural production systems requires the ability to detect pest-induced stress in a timely and reliable manner. In large-scale farming systems, stink bugs attack multiple crop species, making cross-crop pest detection a critical capability for scalable monitoring solutions. Rather than developing crop-specific models that require retraining for each species, identifying crop-independent spectral signatures of stink bug infestation enables transferable detection... A.O. Françani, L. Zhao, J. Ferreira , J. Yan, E.J. Ferreira, L.A. Jorge