Proceedings

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Fornale, M
Charvat Jr., K
Archontoulis, S
Alves, M.R
Yilma, W
Pavuluri, K
Osann, A
Cousins, A
Yeh, M
CAMPOS, J
Ferrandis Vallterra, S
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Authors
Vancutsem, F
Leemans, V
Ferrandis Vallterra, S
Bodson, B
Destain, J
Destain, M
Dumont, B
Chou, T
Yeh, M
Chen, J
Basso, B
Pavuluri, K
Wade, T
Sankaran, S
Wang, M
Ellsworth, P
Cousins, A
Charvat, K
Reznik, T
Lukas, V
Charvat Jr., K
Horakova, S
Splichal, M
Kepka, M
Tekin, A
Fornale, M
Puntel, L
Pagani, A
Archontoulis, S
Osann, A
Campos, I
Calera, M
Plaza, C
Bodas, V
Calera, A
Villodre, J
Campoy, J
Sanchez, S
Jimenez, N
Lopez, H
Charvat, K
Berzins, R
Bergheim, R
Zadrazil, F
Macura, J
Langovskis, D
Snevajs, H
Kubickova, H
Horakova, S
Charvat Jr., K
Siegfried, J
Khosla, R
Mandal, D
Yilma, W
Thompson, L
Puntel, L
Archontoulis, S
Gil, E
Garcia-Ruíz, F
BISCAMPS, J
SALCEDO, R
CAMPOS, J
Amaral, L.R
Oldoni, H
Melo, D.D
Rosin, N.A
Alves, M.R
Demattê, J.M
Topics
Modeling and Geo-statistics
Precision Aerial Application
Proximal Sensing in Precision Agriculture
Precision Agriculture and Climate Change
Unmanned Aerial Systems
Decision Support Systems
In-Season Nitrogen Management
Geospatial Data
Applications of Unmanned Aerial Systems
Decision Support Systems
Precision Crop Protection
Geospatial Data
Type
Poster
Oral
Year
2012
2014
2016
2018
2022
2024
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Filter results13 paper(s) found.

1. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat Yield

In crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to predict... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont

2. I-SALUS: New Web Based Spatial Systems for Simulating Crop Yield and Environmental Impact

  SALUS (System Approach to Land Use Sustainability) model is designed to simulate the impact of agronomic management on yield and environmental impact. SALUS model has new approaches and algorithms for simulating soil carbon, nitrogen, phosphorous, tillage, soil water balance and yield components. In the past, the use of the crop model was not easy for general... T. Chou, M. Yeh, J. Chen, B. Basso

3. Sampling Size Study for Canopy Spectral Reflectance Measurements

Reliable... K. Pavuluri, T. Wade

4. Rapid Sensing For Water Stress Detection In Foxtail Millet (Setaria Italica)

In recent years, the drought conditions due to changing climate patterns have adversely affected the U.S. agriculture. The 2012 drought that damaged major crops in Midwest was one of the most severe in last 25 years. It has resulted in losses of production, revenue, livestock and jobs, and has increased food prices. Under these circumstances, farmers are focused to use the water resources carefully. The researchers are working together to develop new crop varieties resistant to water... S. Sankaran, M. Wang, P. Ellsworth, A. Cousins

5. Quo Vadis Precision Farming

The agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka

6. 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

7. Prediction of Corn Economic Optimum Nitrogen Rate in Argentina

Static (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aires,... L. Puntel, A. Pagani, S. Archontoulis

8. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential

This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez

9. Enhancing Spatial Resolution of Maize Grain Yield Data

Grain yield data is frequently used for precision agriculture management purposes and as a parameter for evaluating agronomy experiments, but unexpected challenges sometimes interfere with harvest plans or cause total losses. The spatial detail of modern grain yield monitoring data is also limited by combine header width, which could be nearly 14 m in some crops.  Remote sensing data, such as multispectral imagery collected via satellite and unmanned aerial systems (UAS), could be used to... J. Siegfried, R. Khosla, D. Mandal, W. Yilma

10. Evaluating APSIM Model for Site-Specific N Management in Nebraska

Many approaches have been developed to estimate the optimal N application rates and increase nitrogen use efficiency (NUE). In particular, in-season and variable-rate fertilizer applications have the potential to apply N during the time of rapid plant N uptake and at the rate needed, thereby reducing the potential for nitrogen fertilizer losses. However, there remains great challenges in determining the optimal N rate to apply in site-specific locations within a field in a given year. Additionally,... L. Thompson, L. Puntel, S. Archontoulis

11. Map Whiteboard As Collaboration Tool for Smart Farming Advisory Services

Precision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook.  The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides  individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr.

12. Variable Rate Application to Improve Cro Protection in Orchards and Vineyards. Prescription Maps and Satellites to Accomplish EU Farm to Fork Strategy

Accurate canopy characterization is crucial for a targeted application of plant protection products following variable rate application (VRA) concept. Remote sensing offers a robust and rapid monitoring tool that allows determining the characteristics of the vegetation from aerial platforms at different spatial resolutions. Previous work have demonstrated that drone-based imagery can be used to estimate canopy height, width, and canopy volume accurately enough to allow a full automation of VRA... E. Gil, F. Garcia-ruíz, J. Biscamps, R. Salcedo, J. Campos

13. Yield Potential Zones and Their Relationship with Soil Taxonomic Classes and Management Zones

The use of management zones (MZ) to subdivide agricultural areas based on the variability of yield potential and production factors is increasingly being explored by scientific research and demanded by farmers. However, there is still much uncertainty about which layers of information and procedures should be adopted for this purpose. Thus, our goal was to demonstrate whether simplistic approaches to creating MZ can satisfactorily address the variability of yield potential and soil classes. For... L.R. Amaral, H. Oldoni, D.D. Melo, N.A. Rosin, M.R. Alves, J.M. Demattê