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Baroni, G
Beaudoin, N
Berger, A.W
Barlage, M
Borùvka, L
Benke, S
Beltarre, G
Brosnan, S
Brinton, C
Betzek, N.M
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Authors
Pattey, E
Jego, G
Tremblay, N
Drury, C
Ma, B
Sansoulet, J
Beaudoin, N
Borùvka, L
Saberioon, M
Vašát, R
Gholizadeh, A
Mahoney, W
Barlage, M
Gochis, D
Chen, F
Bishop-Hurley, G
Overs, L
Brosnan, S
Krumpholz, A
Henry, D
Betzek, N.M
Souza, E.G
Bazzi, C.L
Schenatto, K
Gavioli, A
Maggi, M.F
Gavioli, A
Souza, E.G
Bazzi, C.L
Betzek, N.M
Schenatto, K
Beneduzzi, H.M
Schenatto, K
de Souza, E.G
Bazzi, C.L
Gavioli, A
Betzek, N.M
Beneduzzi, H.M
Bazzi, C.L
Araujo, R
Souza, E.G
Schenatto, K
Gavioli, A
Betzek, N.M
Ferreyra, R
Applegate, D.B
Berger, A.W
Berne, D.T
Craker, B.E
Daggett, D.G
Gowler, A
Bullock, R.J
Haringx, S.C
Hillyer, C
Howatt, T
Nef, B.K
Rhea, S.T
Russo, J.M
Nieman, S.T
Sanders, P
Wilson, J.A
Wilson, J.W
Tevis, J.W
Stelford, M.W
Shearouse, T.W
Schultz, E.D
Reddy, L
Schenatto, K
Souza, E.G
Bazzi, C.L
Gavioli, A
Betzek, N.M
Magalhães, P.S
Cordero, E
Sacco, D
Moretti, B
Miniotti, E.F
Tenni, D
Beltarre, G
Romani, M
Grignani, C
Gavioli, A
Souza, E.G
Bazzi, C.L
Betzek, N.M
Schenatto, K
Betzek, N.M
Souza, E.G
Bazzi, C.L
Magalhães, P.G
Gavioli, A
Schenatto, K
Dall'Agnol, R.W
Kulmany, I.M
Benke, S
Bede, L
Pecze, R
Vona, V
Mazzoleni, R
Vinzio, F
Emamalizadeh, S
Allegro, G
Filippetti, I
Baroni, G
Jha, S
Krogmeier, J
Buckmaster, D
Love, D.J
Grant, R.H
Crawford, M
Brinton, C
Wang, C
Cappelleri, D
Balmos, A
Topics
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Dairy and Livestock Management
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Decision Support Systems in Precision Agriculture
Standards & Data Stewardship
On Farm Experimentation with Site-Specific Technologies
In-Season Nitrogen Management
Decision Support Systems
Geospatial Data
Land Improvement and Conservation Practices
Precision Agriculture for Sustainability and Environmental Protection
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2014
2016
2018
2022
2024
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Filter results16 paper(s) found.

1. Performance Evaluation of STICS Crop Model to Simulate Corn Growth Attributes in Response to N Rate and Climate Variations

Improving nitrogen use efficiency in crop plants contributes to increase the sustainability of agriculture. Crop models could be used as a tool to test the impact of climatic conditions on crop growth under several N management practices and to refine N application recommendation and strategy. STICS, a crop growth simulator developed by INRA (France), has the capability to assimilate leaf area index (LAI) from remote sensing to re-initialize input parameters, such as seeding date and seeding... E. Pattey, G. Jego, N. Tremblay, C. Drury, B. Ma, J. Sansoulet, N. Beaudoin

2. Visible And Near-Infrared Spectroscopy For Monitoring Potentially Toxic Elements In Reclaimed Dumpsite Soils Of The Czech Republic

Due to rapid economic development, high levels of potentially harmful elements and heavy metals are continuously being released into the brown coal mining dumpsites of the Czech Republic. Elevated metal contents in soils not only dramatically impact the soil quality, but also due to their persistent nature and long biological half-lives, contaminant elements can accumulate in the food chain and can eventually endanger human health. Conventional methods for investigating potentially... L. Borùvka, M. Saberioon, R. Vašát, A. Gholizadeh

3. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision Support

Technological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilation... W. Mahoney, M. Barlage, D. Gochis, F. Chen

4. Capturing, Demonstrating And Delivering Value From Integrating Real-Time On-Farm Sensing With External Information Flows

The requirement for significant productivity gains in the agricultural sector is undeniable. Sustainable, viable industries must be capable of consistently producing a margin above the base costs of production. This is particularly challenging for the extensive grazing enterprises in Australia as the operating environment has become increasingly complex, dynamic and challenging and there is a continual and increasing need to demonstrate improved efficiency to the wider community... G. Bishop-hurley, L. Overs, S. Brosnan, A. Krumpholz, D. Henry

5. Rectification of Management Zones Considering Moda and Median As a Criterion for Reclassification of Pixels

Management zones (MZ) make economically viable the application of precision agriculture techniques by dividing the production areas according to the homogeneity of its productive characteristics. The divisions are conducted through empirical techniques or cluster analysis, and, in some cases, the MZ are difficult to be delimited due to isolated cells or patches within sub-regions. The objective of this study was to apply computational techniques that provide smoothing of MZ, so as to become viable... N.M. Betzek, E.G. Souza, C.L. Bazzi, K. Schenatto, A. Gavioli, M.F. Maggi

6. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster Analysis

The delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi

7. Data Normalization Methods for Definition of Management Zones

The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evaluate... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi

8. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian Agriculture

With the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with better... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek

9. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPT

AgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy

10. Use of Farmer’s Experience for Management Zones Delineation

In the management of spatial variability of the fields, the management zone approach (MZs) divides the area into sub-regions of minimal soil and plant variability, which have maximum homogeneity of topography and soil conditions, so that these MZs must lead to the same potential yield. Farmers have experience of which areas of a field have high and low yields, and the use of this knowledge base can allow the identification of MZs in a field based on production history. The objective of this study... K. Schenatto, E.G. Souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, P.S. Magalhães

11. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments

Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani

12. Variable Selection and Data Clustering Methods for Agricultural Management Zones Delineation

Delineation of agricultural management zones (MZs) is the delimitation, within a field, of a number of sub-areas with high internal similarity in the topographic, soil and/or crop characteristics. This approach can contribute significantly to enable precision agriculture (PA) benefits for a larger number of producers, mainly due to the possibility of reducing costs related to the field management. Two fundamental tasks for the delineation of MZs are the variable selection and the cluster analysis.... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto

13. Application of Routines for Automation of Geostatistical Analysis Procedures and Interpolation of Data by Ordinary Kriging

Ordinary kriging (OK) is one of the most suitable interpolation methods for the construction of thematic maps used in precision agriculture. However, the use of OK is complex. Farmers/agronomists are generally not highly trained to use geostatistical methods to produce soil and plant attribute maps for precision agriculture and thus ensure that best management approaches are used. Therefore, the objective of this work was to develop and apply computational routines using procedures and geostatistical... N.M. Betzek, E.G. Souza, C.L. Bazzi, P.G. Magalhães, A. Gavioli, K. Schenatto, R.W. Dall'agnol

14. The Effect of Slope Gradient on the Modelling of Soil Carbon Dioxide Emissions in Different Tillage Systems at a Farm Using Precision Tillage Technology in Hungary

Understanding the role of natural drivers in greenhouse gas (GHG) emitted by agricultural soils is crucial because it contributes to selecting and adapting acceptable eco-friendly farming practices. Hence, Syngenta Ltd. collaborating with researchers, aimed to investigate the effect of two tillage treatments, conventional-tillage (CT) and minimum-tillage (MT) on soil carbon dioxide (CO2) emissions. The research field is in Hungary. Soil columns were derived from different tillage systems... I.M. Kulmany, S. Benke, L. Bede, R. Pecze, V. Vona

15. Enhancing Precision Agriculture with Cosmic-ray Neutron Sensing: Monitoring Soil Moisture Dynamics and Its Impact on Grapevine Physiology

Precision agriculture has emerged as a transformative approach in modern viticulture, seeking to optimize vineyard management. Vineyard operations rely heavily on effective water management, especially in regions where water availability can significantly affect grape quality and yield. The relationship between soil moisture and grapevine physiology is however complex. Therefore, understanding these relationships is crucial for optimizing vineyard operations. Cosmic-ray neutron sensing (CRNS)... R. Mazzoleni, F. Vinzio, S. Emamalizadeh, G. Allegro, I. Filippetti, G. Baroni

16. 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