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Tekin, A
Jorgensen, R.N
Ji, W
Klingner, S
Dalla Nora, D
Drover, D
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Authors
Friedrich, J
Becker, M
Schneider, M.F
Klingner, S
Tekin, A
Fornale, M
Corassa, G.M
Amado, T.J
Schwalbert, R.A
Reimche, G.B
Dalla Nora, D
Horbe, T.
Tabaldi, F.M
Biswas, A
Ji, W
Perron, I
Cambouris, A
Zebarth, B
Adamchuk, V
Rydahl, P
Jorgensen, R.N
Dyrmann, M
Jensen, N
Sorensen, M.D
Bojer, O.M
Andersen, P
Nederend, J
Drover, D
Reiche, B
Deen, B
Lee, L
Taylor, G.W
Saifuzzaman, M
Adamchuk, V.I
Huang, H
Ji, W
Rabe, N
Biswas, A
Leksono, E
Adamchuk, V
Ji, W
Leclerc, M
Huang, H
Adamchuk, V
Biswas, A
Ji, W
Lauzon, S
Topics
Engineering Technologies and Advances
Unmanned Aerial Systems
Spatial Variability in Crop, Soil and Natural Resources
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Crop Protection
Applications of Unmanned Aerial Systems
Big Data, Data Mining and Deep Learning
Geospatial Data
Type
Oral
Poster
Year
2014
2016
2018
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Authors

Filter results9 paper(s) found.

1. New Innovation Approaches In Precision Farming – The Example Of The Base Fertilization Process

Nowadays, innovations in Precision Farming are mostly bound to further developments and new solution approaches on the technical level. However, for efficient service provision it is important to work on strategies for application of these technologies. To satisfy customers’ demands for highly specialized methods and detailed results collaboration between various companies in service consortiums is often required. In doing so, every company can provide its proven and evidentially effective... J. Friedrich, M. Becker, M.F. Schneider, S. Klingner

2. Developing UAV Image Acquisition System and Processing Steps for Quantitative Use of the Data in Precision Agriculture

Mapping natural variability of crops and land is first step of the management cycle in terms of crop production. Several methods have been developed and engaged for data recording and analyzing that generate prescription maps such as yield monitoring, soil mapping, remote sensing etc. Although conventional remote sensing by capturing images via satellites has been very popular tool to monitor the earth surface, it has several drawbacks such as orbital period, unattended capture, investment cost.... A. Tekin, M. Fornale

3. High-resolution Mapping with On-the-go Soil Sensor and Its Relation with Corn Yield and Soil Acidity in a Dystrophic Red Oxisol

Spatial representations of soil attributes with low resolution can lead to gross errors of recommendation and compromise the efficiency of soil corrections and consequently the grain yield. However, obtaining the spatial variability of soil attributes with high resolution by soil sampling is not recommended because of its large time spent and high cost of laboratory analysis what makes difficult their large-scale application. This way, the on-the-go soil sensing has been used in precision agriculture... G.M. Corassa, T.J. Amado, R.A. Schwalbert, G.B. reimche, D. Dalla nora, T. . horbe, F.M. tabaldi

4. Proximal Soil Sensing-Led Management Zone Delineation for Potato Fields

A fundamental aspect of precision agriculture or site-specific crop management is the ability to recognize and address local changes in the crop production environment (e.g. soil) within the boundaries of a traditional management unit. However, the status quo approach to define local fertilizer need relies on systematic soil sampling followed by time and labour-intensive laboratory analysis. Proximal soil sensing offers numerous advantages over conventional soil characterization and has shown... A. Biswas, W. Ji, I. Perron, A. Cambouris, B. Zebarth, V. Adamchuk

5. Spatial Variability of Optimized Herbicide Mixtures and Dosages

Driven by 25 years of Danish, political 'pesticide action plans', aiming at reducing the use of pesticides, a Danish Decision Support System (DSS) for Integrated Weed Management (IWM) has been constructed. This online tool, called ‘IPMwise’ is now in its 4th generation. It integrates the 8 general IPM-principles as defined by the EU. In Denmark, this DSS includes 30 crops, 105 weeds and full assortments of herbicides. Due to generic qualities in both the integrated... P. Rydahl, R.N. Jorgensen, M. Dyrmann, N. Jensen, M.D. Sorensen, O.M. Bojer, P. Andersen

6. The Guelph Plot Analyzer: Semi-Automatic Extraction of Small-Plot Research Data from Aerial Imagery

Small-plot trials are the foundation of open-field agricultural research because they strike a balance between the control of an artificial environment and the realism of field-scale production. However, the size and scope of this research field is often limited by the ability to collect data, which is limited by access to labour. Remote sensing has long been investigated to allocate labour more efficiently, therefore enabling the rapid collection of data. Imagery collected by unmanned aerial... J. Nederend, D. Drover, B. Reiche, B. Deen, L. Lee, G.W. Taylor

7. Data Clustering Tools for Understanding Spatial Heterogeneity in Crop Production by Integrating Proximal Soil Sensing and Remote Sensing Data

Remote sensing (RS) and proximal soil sensing (PSS) technologies offer an advanced array of methods for obtaining soil property information and determining soil variability for precision agriculture. A large amount of data collected using these sensors may provide essential information for precision or site-specific management in a production field. In this paper, we introduced a new clustering technique was introduced and compared with existing clustering tools for determining relatively homogeneous... M. Saifuzzaman, V.I. Adamchuk, H. Huang, W. Ji, N. Rabe, A. Biswas

8. Development of a Soil ECa Inversion Algorithm for Topsoil Depth Characterization

Electromagnetic induction (EMI) proximal soil sensor systems can deliver rapid information about soil. One such example is the DUALEM-21S (Dualem, Inc. Milton, Ontario, Canada). EMI sensors measure soil apparent electrical conductivity (ECa) corresponding to different depth of investigation depending on the instrument configuration. The interpretation of the ECa measurements is not straightforward and it is often site-specific. Inversion is required to explore specific depths. This inversion process... E. Leksono, V. Adamchuk, W. Ji, M. Leclerc

9. Analysis of Soil Properties Predictability Using Different On-the-Go Soil Mapping Systems

Understanding the spatial variability of soil chemical and physical attributes allows for the optimization of the profitability of nutrient and water management for crop development. Considering the advantages and accessibility of various types of multi-sensor platforms capable of acquiring large sensing data pertaining to soil information across a landscape, this study compares data obtained using four common soil mapping systems: 1) topography obtained using a real-time kinematic (RTK) global... H. Huang, V. Adamchuk, A. Biswas, W. Ji, S. Lauzon

Showing 1 to 9 of 9 entries