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Dzinaj, T
Vigil, M
Seyhan, G.T
Shaver, T.M
Sulik, J
De Ketelaere, B
Dutilleul, P
Pereira, R.R
TISSEYRE, B
Pendke, M.S
Port, K
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Authors
Lopes, W.C
Domingues, G
Sousa, R.V
Porto, A.J
Inamasu, R.Y
Pereira, R.R
Poncet, A.M
McDonald, T.P
Pate, G
TISSEYRE, B
Fulton, J.P
Pawar, S.N
Gore, A.K
Shinde, G.U
Pendke, M.S
Ruckelshausen, A
Dzinaj, T
Kinder, T
Bosse, D
Klose, R
Kruger, G
van Donk, S
Shaver, T.M
Wouters, N
Van Beers, R
De Ketelaere, B
Deckers, T
De Baerdemaeker, J
Saeys, W
Seyhan, G.T
Yegul, U
Ayık, M
Adamchuk, V.I
Dhawale, N
Biswas, A
Lauzon‎, S
Dutilleul, P
Walthall, C
Hatfield, J
Schneider, S
Vigil, M
Colley III, R
Fulton, J
Douridas, N
Port, K
Lee, J
Fulton, J
Port, K
Colley III, R
Fulton, J.P
Hawkins, E
Colley III, R
Port, K
Shearer, S
Klopfenstein, A
Hoffmann Silva Karp, F
Adamchuk, V
Melnitchouck, A
Dutilleul, P
Hoffmann Silva Karp, F
Adamchuk, V
Dutilleul, P
Melnitchouck, A
Biswas, A
Asgedom, H
Hehar, G
Willness, C
Anderson, W
Duddu, H
Mooleki, P
Schoenau, J
Khakbazan, M
Lemke, R
Derdall, E
Shang, J
Liu, K
Sulik, J
Karppinen, E
Mbakwe, I
Topics
Guidance, Robotics, Automation, and GPS Systems
Education and Training in Precision Agriculture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Education and Training in Precision Agriculture
Proximal Sensing in Precision Agriculture
Sensor Application in Managing In-season CropVariability
Engineering Technologies and Advances
Big Data Mining & Statistical Issues in Precision Agriculture
Decision Support Systems in Precision Agriculture
Big Data, Data Mining and Deep Learning
Decision Support Systems
On Farm Experimentation with Site-Specific Technologies
Geospatial Data
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results15 paper(s) found.

1. Isobus Demonstrator And Working Environment For Agricultural Engineering Education

ISOBUS is the international standard for communication on agricultural equipment. In practice, however, a manufacturer independent tractor-implement communication is still a significant problem. This aspect has been identified as a major hindrance for the transfer of research results into products for precision farming.  As a consequence the ISOBUS standard should strongly be included in education and research, which is the focus of this work.   In... A. Ruckelshausen, T. Dzinaj, T. Kinder, D. Bosse, R. Klose

2. Compatible ISOBUS Applications Using a Computational Tool for Support the Phases of the Precision Agriculture Cycle

... W.C. Lopes, G. Domingues, R.V. Sousa, A.J. Porto, R.Y. Inamasu, R.R. Pereira

3. Maximizing Agriculture Equipment Capacity Using Precision Agriculture Technologies

Guidance systems are one of the primary Precision Agriculture technologies adopted by US farmers. While most practitioners establish their initial AB lines for fields based on previous management patterns, a potential exists in conducting analyses to establish AB lines or traffic patterns which maximize field capacity. The objective of this study was to... A.M. Poncet, T.P. Mcdonald, G. Pate, B. Tisseyre, J.P. Fulton

4. Climatological Diagnostic Analysis: A Case Study for Parbhani District in Marathwada Region of India

... S.N. Pawar, A.K. Gore, G.U. Shinde, M.S. Pendke

5. 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

6. Towards Automated Pneumatic Thinning Of Floral Buds On Pear Trees

Thinning of pome and stone fruit is an important horticultural practice that is used to enhance fruit set and quality by removing excess floral buds. As it is still mostly conducted through manual labor, thinning comprises a large part of a grower’s production costs. Various thinning machines developed in recent years have clearly demonstrated that mechanization of this technique is both feasible and cost effective. Generally, these machines still lack sufficient selectivity... N. Wouters, R. Van beers, B. De ketelaere, T. Deckers, J. De baerdemaeker, W. Saeys

7. Design of a Greenhouse Monitoring System Based on GSM Technologies

Nowadays, internet and mobile technologies are developing and being used in everyday life. Systems based on mobile technologies and IoT (Internet of Things) are being popular in every area of life and science. Innovative IoT applications are helping to increase the quality, quantity, sustainability and cost effectiveness of agricultural production. In this study; a system which monitors temperature, relative humidity and PAR (Photosynthetically Active Radiation) and warns the farmer... G.T. Seyhan, U. Yegul, M. Ayık

8. Integrated Analysis of Multilayer Proximal Soil Sensing Data

Data revealing spatial soil heterogeneity can be obtained in an economically feasible manner using on-the-go proximal soil sensing (PSS) platforms. Gathered georeferenced measurements demonstrate changes related to physical and chemical soil attributes across an agricultural field. However, since many PSS measurements are affected by multiple soil properties to different degrees, it is important to assess soil heterogeneity using a multilayer approach. Thus, analysis of multiple layers of geospatial... V.I. Adamchuk, N. Dhawale, A. Biswas, S. Lauzon‎, P. Dutilleul

9. Closing Yield Gaps with GxExM and Precision Agriculture

There are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate.  A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges.  The yield gap –defined as the difference between current farmer yields and potential... C. Walthall, J. Hatfield, S. Schneider, M. Vigil

10. On-Farm Digital Solutions and Their Associated Value to North American Farmers

Digital tools and data collection have become standard in a wide variety of present day agricultural operations. An array of digital tools, such as high resolution operational mapping, remote sensing, and farm management software offer solutions to many of the problems in modern agriculture. These technologies and services can, if implemented correctly, provide both immediate and long term agronomic value. A growing number of producers in Ohio and around North America question the proper method... R. Colley iii, J. Fulton, N. Douridas, K. Port

11. Overview and Value of Digital Technologies for North American Soybean Producers

In the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers.  Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies.  However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide.  The objective of this... J. Lee, J. Fulton, K. Port, R. Colley iii

12. eFields – An On-Farm Research Network to Inform Farm Recommendations

On-farm research has been traditionally used to provide local, field-scale information about agronomic practices. Farmers tend to have more confidence in on-farm research results because they are perceived to be more relevant to their farm operations compared to small plot research results. In recent years, more farmers have been conducting on-farm studies to help evaluate practices and input decisions.  Recent advances in precision agriculture technologies have stream-lined the on-farm... J.P. Fulton, E. Hawkins, R. Colley iii, K. Port, S. Shearer, A. Klopfenstein

13. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes

The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul

14. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study

Using proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas

15. Response of Canola and Wheat to Application of Enhanced Efficiency Nitrogen Fertilizers on Contrasting Management Zones

Investment on nitrogen (N) fertilizers is a major cost of growers, and variable rate (VR) application of N fertilizers could help optimize its usage. In the growing season of 2023, field experiments were conducted at four sites (i.e., Watrous – Saskatchewan SK and two fields in the vicinity of Strathmore, Alberta AB, Canada). The main objectives were to (i) determine performance of Enhanced Efficiency N Fertilizers - EENF (i.e., Coated urea, urea with double inhibitors - DI, urea mixed with... H. Asgedom, G. Hehar, C. Willness, W. Anderson, H. Duddu, P. Mooleki, J. Schoenau, M. Khakbazan, R. Lemke, E. derdall, J. Shang, K. Liu, J. Sulik, E. Karppinen, I. Mbakwe