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Yılmaz, H
Gebler, H.F
Guimarães, C
García Seleme, F
Xavier, J.D
Wojciechowski, T
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Authors
Karayel, D
Jotautiene, E
Yılmaz, H
Wojciechowski, T
Niedbała, G
Bobran, K
Xavier, J.D
Schenatto, K
Miranda, G.V
Bazzi, C.L
Sobjak, R
Suarez, F
Gómez Montenegro, B
Dottori, C
Alemandri, V
de Breuil, S
Bruno, C
García Seleme, F
Gebler, H.F
Silva Costa, B.R
Molin, J.P
Gebler, H.F
Grego, C.R
Rodrigues, G.C
Pereira, A
Fagundes, F
Fonteca, V
Guimarães, C
Monteiro, M
Azevedo, I
da Rosa, A
Wagner, N.K
Teixeira, C
Topics
Agricultural Robotics, Automation, and Mechanization
Decision Support Systems, Cloud Platforms, and Open Data Solutions
UAV-Based Scouting, Imaging, and Targeted Applications
Predictive Modeling, Phenotyping, and Digital Tools for Decision Support
Precision Horticulture and Specialty Crop Management
Remote and Proximal Sensing of Soils and Crops
Type
Poster
Year
2026
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Filter results7 paper(s) found.

1. A Seeder for Sustainable Agriculture Enabling Intercropping and Multi-Variety Sowing and Adaptable to Precision Agriculture through Variable-Rate Seeding

Davut Karayel*1,2 Egle Jotautiene2 Hasan Yılmaz1,2 1Akdeniz University, Faculty of Agriculture, Department of Agricultural Machinery and Technologies Engineering, Antalya, Turkey 2Vytautas Magnus University, Agriculture Academy, Faculty of Engineering, Department of Agricultural Engineering and Safety, Kaunas, Lithuania. * Corresponding author and presenter   Abstract Adapting... D. Karayel, E. Jotautiene, H. Yılmaz

2. PRAGMATIC - Innovative IT Platform for Yield and Cost Prediction of Agricultural Production

The  aim  of  the  R&D  was  to  develop  a  prototype  of  an  innovative  IT  platform  containing algorithms  for  predicting  yields  and  production  costs  of  agricultural  commodities  for  three reference crops, i.e.: blueberries, apples and potatoes in the supply chain from the field to the production  line.  The  system  are ... T. Wojciechowski, G. Niedbała, K. Bobran

3. A Machine Learning Framework for Crop Productivity Classification and Risk Assessment

The integration of Artificial Intelligence and Remote Sensing is essential for the early identification of agricultural fields with suboptimal growing conditions. Such capabilities are vital for targeted interventions, supply chain logistics, and agricultural risk management. This study developed and validated a machine learning framework designed to classify the productivity conditions of corn, soybean, and wheat into ‘Low’, ‘Medium’, and ‘High’ tiers, utilizing... J.D. Xavier, K. Schenatto, G.V. Miranda, C.L. Bazzi, R. Sobjak

4. A Methodological Framework for Modeling Plant Virus Occurrence Using Biometeorological Data: Insights from Multi-crop Case Studies in Argentina

Viral diseases represent a major threat to the productive stability of agricultural systems. Their spatial and temporal occurrence is influenced by environmental conditions that regulate interactions among viruses, vectors, and hosts, making disease anticipation difficult using statistical traditional approaches. This situation highlights the need to understand the dynamics of the different biological components capable of affecting agricultural systems, and design and apply tools that facilitate... F. Suarez, B. Gómez Montenegro, C. Dottori, V. Alemandri, S. De Breuil, C. Bruno, F. García Seleme

5. Applying Precision Agriculture Principles to Assess Spatial Variability of Soil Fertility Profiles in Coffee Farms at a Regional Scale.

In the last two decades, the development and increasing efficiency of Precision and Digital Agriculture technologies has been observed in a broad range of farming systems. One of the consequences of this was the popularization of digital data collection, resulting in the current scenario where agricultural companies usually have large georeferenced databases concerning climate, soil and plant traits. These datasets are also produced by agricultural cooperatives such as the Cooxupé (Regional... H.F. Gebler, B.R. Silva Costa, J.P. Molin

6. Producing Ordinary Kriging Interpolated Maps for Biomass Observation Through Values Captured with NDVI and NDRE Imagery.

Geostatistics is a well-established method in the scientific community for aiding decision-making in situations with spatial dependence. Generally, the methodology adopted for interpolating fertility maps is the use of data from soil sampling on the property, generating representative thematic maps. However, the number of samples required for this methodology can be problematic when the analysis site is a small farm or one divided into multiple plots, common scenarios in Brazilian coffee farming. Considering... H.F. Gebler, C.R. Grego, G.C. Rodrigues, A. Pereira, F. Fagundes

7. A Architecture for GNSS-Based Autonomous Navigation in Agricultural Robots

Global Navigation Satellite Systems (GNSS), especially when used with real-time correction techniques such as Real-Time Kinematic (RTK), are widely employed in precision agriculture due to their ability to provide accurate absolute positioning. This capability enables georeferenced operations such as planting, selective spraying, and autonomous navigation across large agricultural areas, even in environments with few structural references. In contrast, modern robotic navigation frameworks, such... V. Fonteca, C. Guimarães, M. Monteiro, I. Azevedo, A. Da Rosa, N.K. Wagner, C. Teixeira