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Kempenaar, C
Krogmeier, J
Kruger, G
Kleinhenz, B
Karam, A
Kabaliuk, N
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Authors
Kruger, G
van Donk, S
Shaver, T.M
Kleinhenz, B
Röhrig, M
Scheiber, M
Feldhaus, J
Hartmann, B
Golla, B
Federle , C
Martini, D
Post, S
Jermy, M
Gaynor, P
Kabaliuk, N
Werner, A
van Evert, F.K
Been, T
Booij, J.A
Kempenaar, C
Kessel, G.J
Molendijk, L.P
Wang, Y
Balmos, A
Krogmeier, J
Buckmaster, D
Krogmeier, J
Buckmaster, D
Ault, A
Wang, Y
Zhang, Y
Layton, A
Noel, S
Balmos, A
Nze Memiaghe, J
Cambouris, A.N
Ziadi, N
Duchemin, M
Karam, A
Javed, B
Cambouris, A
Duchemin, M
Longchamps, L
Basran, P.S
Arnold, S
Fenech, A
Karam, A
Nze Memiaghe, J
Cambouris, A
Duchemin, M
Ziadi, N
Karam, A
Basir, M.S
Krogmeier, J
Zhang, Y
Buckmaster, D
Jha, S
Krogmeier, J
Buckmaster, D
Love, D.J
Grant, R.H
Crawford, M
Brinton, C
Wang, C
Cappelleri, D
Balmos, A
Zhang, Y
Bailey, J
Balmos, A
Castiblanco Rubio, F.A
Krogmeier, J
Buckmaster, D
Love, D
Zhang, J
Allen, M
Topics
Proximal Sensing in Precision Agriculture
Precision Crop Protection
Precision Crop Protection
Profitability and Success Stories in Precision Agriculture
Big Data, Data Mining and Deep Learning
Decision Support Systems
Precision Agriculture and Global Food Security
Land Improvement and Conservation Practices
Data Analytics for Production Ag
Big Data, Data Mining and Deep Learning
Edge Computing and Cloud Solutions
Type
Poster
Oral
Year
2014
2018
2022
2024
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Filter results12 paper(s) found.

1. Suitability Of Crop Canopy Sensors For Determining Irrigation Differences In Maize

Water is the most limiting factor for agricultural production in the semiarid environment of the western Great Plains of the United States.  Dry climate conditions combined with a large availability of ground water has led to crop systems that are dependent on irrigation for maximum yields.  An increased emphasis on water is forcing users to find new ways to increase the efficiency of water used for agriculture.  Crop canopy sensors may have the potential to determine... G. Kruger, S. Van donk, T.M. Shaver

2. Pesticide Application Manager (PAM) - Decision Support In Crop Protection Based On Terrain-, Machine-, Business- And Public Data

Introduction   Pesticide Application Manager (PAM) is a project, co-financed by the German Federal Office for Agriculture and Food (BLE) that aims to develop solutions for automating important processes in crop protection.   Due to a series of rules and legal requirements for planning, implementation and documentation, crop protection is one of the most... B. Kleinhenz, M. Röhrig, M. Scheiber, J. Feldhaus, B. Hartmann, B. Golla, C. Federle , D. Martini

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. Akkerweb: A Platform for Precision Farming Data, Science, and Practice

The concept of precision farming (PF) was formulated about 40 years ago and the scientific knowledge for some applications of PF in The Netherlands has been available for almost 20 years. Also, in many cases equipment is available to implement PF in practice. In spite of all this PF uptake is still limited. An important reason for the limited uptake of PF is in the challenges that must be overcome to let data flow from sensors to data storage, to combine data sources and process them into recommendations,... F.K. Van evert, T. Been, J.A. Booij, C. Kempenaar, G.J. Kessel, L.P. Molendijk

5. Data-Driven Agricultural Machinery Activity Anomaly Detection and Classification

In modern agriculture, machinery has become the one of the necessities in providing safe, effective and economical farming operations and logistics. In a typical farming operation, different machines perform different tasks, and sometimes are used together for collaborative work. In such cases, different machines are associated with representative activity patterns, for example, in a harvest scenario, combines move through a field following regular swaths while grain carts follow irregular paths... Y. Wang, A. Balmos, J. Krogmeier, D. Buckmaster

6. Use Cases for Real Time Data in Agriculture

Agricultural data of many types (yield, weather, soil moisture, field operations, topography, etc.) comes in varied geospatial aggregation levels and time increments. For much of this data, consumption and utilization is not time sensitive. For other data elements, time is of the essence. We hypothesize that better quality data (for those later analyses) will also follow from real-time presentation and application of data for it is during the time that data is being collected that errors can be... J. Krogmeier, D. Buckmaster, A. Ault, Y. Wang, Y. Zhang, A. Layton, S. Noel, A. Balmos

7. Impacts of Interpolating Methods on Soil Agri-environmental Phosphorus Maps Under Corn Production

Phosphorus (P) is an essential nutrient for crops production including corn. However, the excessive P application, tends to P accumulation at the soil surface under crops systems. This may contribute to increase water and groundwater pollution by surface runoff. To prevent this, an agri-environmental P index, (P/Al)M3, was developed in Eastern Canada and USA. This index aims to estimate soil P saturation for accurate P fertilizer recommendations, while integrating agronomical aspects... J. Nze memiaghe, A.N. Cambouris, N. Ziadi, M. Duchemin, A. Karam

8. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato Production

In modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam

9. Delineating Management Zones for Optimizing Soil Phosphorus Recommendations Under a No Till Field in Eastern Canada

Corn (Zea mays L.) and soybean (Glycine max L.) represent the most common crop rotation in Eastern Canada. These crops are cultivated using no-tillage (NT) practice to enhance agroecosystem sustainability. However, NT practice can cause several agri-environmental issues related to phosphorus (P) stratification, movement and runoff leading to P eutrophication in waters. Another major challenge is the expensive costs of extensive soil sampling and laboratory tests needed for accurate... J. Nze memiaghe, A. Cambouris, M. Duchemin, N. Ziadi, A. Karam

10. Private Simple Databases for Digital Records of Contextual Events and Activities

Farmers’ commitment and ability to keep good records varies tremendously. Records and notes are often cryptic, misplaced, or damaged and for many, remain unused. If such information were recorded digitally and stored in the cloud, we immediately solve some access and consistency issues and make this data FAIR (findable, accessible, interoperable, reusable). More importantly, interoperable digital formats can also enable mining for insights and analysis... M.S. Basir, J. Krogmeier, Y. Zhang, D. Buckmaster

11. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial Intelligence

The Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power infrastructure,... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos

12. Enabling Field-level Connectivity in Rural Digital Agriculture with Cloud-based LoRaWAN

The widespread adoption of next-generation digital agriculture technologies in rural areas faces a critical challenge in the form of inadequate field-level connectivity. Traditional approaches to connecting people fall short in providing cost-effective solutions for many remote agricultural locations, exacerbating the digital divide. Current cellular networks, including 5G with millimeter wave technology, are urban-centric and struggle to meet the evolving digital agricultural needs, presenting... Y. Zhang, J. Bailey, A. Balmos, F.A. Castiblanco rubio, J. Krogmeier, D. Buckmaster, D. Love, J. Zhang, M. Allen