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Ganascini, D
Gaynor, P
Green, O
Mandel, R
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Authors
Fountas, S
Bochtis, D
Sorensen, C
Green, O
J, R
Bartzanas, T
Mandel, R
Post, S
Jermy, M
Gaynor, P
Kabaliuk, N
Werner, A
Larsen, D
Skovsen, S
Steen, K.A
Grooters, K
Green, O
Jørgensen, R.N
Eriksen, J
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
Jørgensen, R.N
Skovsen, S
Green, O
Sørensen, C.G
Topics
Spatial Variability in Crop, Soil and Natural Resources
Education and Training in Precision Agriculture
Precision Crop Protection
Applications of Unmanned Aerial Systems
Decision Support Systems
Robotics and Automation with Row and Horticultural Crops
Type
Oral
Poster
Year
2010
2018
2022
2024
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Filter results6 paper(s) found.

1. Spatial-temporal Management Zones For Biomass Moisture

 Biomass handling operations (harvesting, raking, collection, and transportation) are critical operations within the agricultural production system since they constitute the first link in the biomass supply chain, a fact of substantial importance considering the increasingly involvement of biomass in bio-refinery and bio-energy procedures. Nevertheless, the inherent uncertainty, imposed by the interaction between environmental, biological, and machinery factors, makes the available scheduling... S. Fountas, D. Bochtis, C. Sorensen, O. Green, R. J, T. Bartzanas

2. Farmer Perspectives Of Precision Agriculture In Western Australia

Many farmers in the Western Australian wheatbelt have successfully adopted guidance and yield mapping technologies. However they have so far avoided adopting variable rate technology (VRT).  While agronomists and farmers can determine the limiting factors to production, whether it is soil fertility, pH, plant available water capacity (PAWC) or others, they have less confidence in managing spatial variability. Although WA farmers understand the need to adopt these techniques they have... R. Mandel

3. Real-Time Control of Spray Drop Application

Electrostatic application of spray drops provides unique opportunities to precisely control the application of pesticides due to the additional electrostatic force on the spray drops, in addition to the normally seen forces of aerodynamic drag, gravity, and inertia. In this work, we develop a computational model to predict the spray drop trajectories. The model is validated through experiments with high speed photography of spray drop trajectories, and quantification of which trajectories lead... S. Post, M. Jermy, P. Gaynor, N. Kabaliuk, A. Werner

4. Autonomous Mapping of Grass-Clover Ratio Based on Unmanned Aerial Vehicles and Convolutional Neural Networks

This paper presents a method which can provide support in determining the grass-clover ratio, in grass-clover fields, based on images from an unmanned aerial vehicle. Automated estimation of the grass-clover ratio can serve as a tool for optimizing fertilization of grass-clover fields. A higher clover content gives a higher performance of the cows, when the harvested material is used for fodder, and thereby this has a direct impact on the dairy industry. An android application... D. Larsen, S. Skovsen, K.A. Steen, K. Grooters, O. Green, R.N. Jørgensen, J. Eriksen

5. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

6. Enhancing Precision Agriculture Through Dual Weed Mapping: Delineating Inter and Intra-row Weed Populations for Optimized Crop Protection

In the field of precision agriculture, effective management of weed populations is essential for optimizing crop yield and health. This paper presents an innovative approach to weed management by employing dual weed mapping techniques that differentiate between inter-row and intra-row weed populations. Utilizing advanced imaging and data analysis of CropEye images collected by the Robotti robot from AgroIntelli (AgroIntelli A/S, Aarhus, Denmark), we have developed methods to generate distinct... R.N. Jørgensen, S. Skovsen, O. Green, C.G. Sørensen