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Roel, A
Skerikova, M
Li, H
Archontoulis, S
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Authors
Lee, W
Wang, K
Li, H
Ehsani, R
Yang, C
Kroulik, M
Brant, V
Zabransky, P
Chyba, J
Krcek, V
Skerikova, M
Puntel, L
Pagani, A
Archontoulis, S
Balboa, G
Puntel, L
Melchiori, R
Ortega, R
Tiscornia, G
Bolfe, E
Roel, A
Scaramuzza, F
Best, S
Berger, A
Hansel, D
Palacios, D
Thompson, L
Puntel, L
Archontoulis, S
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
ISPA Community: Latin America
Decision Support Systems
Type
Poster
Oral
Year
2012
2018
2022
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Filter results5 paper(s) found.

1. Spectral Angle Mapper (SAM) Based Citrus Greening Disease Detection Using Airborne Hyperspectral Imaging

Over the past two decades, hyperspectral (HS) imaging has provided remarkable performance in ground objects classification and disease identification, due to its high spectral resolution. In this paper, a novel method named ‘extended spectral angle mapping (ESAM)’ is proposed to detect citrus greening disease (Huanglongbing or HLB), which is a destructive disease of citrus. Firstly, Savitzky-Golay smoothing filter was applied to the raw image to remove spectral noise within the data,... W. Lee, K. Wang, H. Li, R. Ehsani, C. Yang

2. Machine Monitoring As a Smartfarming Concept Tool

Current development trends are associated with the digitization of production processes and the interconnection of individual information layers from multiple sources into common databases, contexts and functionalities. In order to automatic data collection  of machine operating data, the farm tractors were equipped with monitoring units ITineris for continuous collection and transmission of information from tractors CAN Bus. All data sets are completed with GPS location data. Acreage... M. Kroulik, V. Brant, P. Zabransky, J. Chyba, V. Krcek, M. Skerikova

3. 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

4. How Digital is Agriculture in South America? Adoption and Limitations

A rapidly growing population in a context of land and water scarcity, and climate change has driven an increase in healthy, nutritious, and affordable food demand while maintaining the current cropping area. Digital agriculture (DA) can contribute solutions to meet the demands in an efficient and sustainable way. South America (SA) is one of the main grain and protein producers in the world but the status of DA in the region is unknown. This article presents the results from a systematic review... G. Balboa, L. Puntel, R. Melchiori, R. Ortega, G. Tiscornia, E. Bolfe, A. Roel, F. Scaramuzza, S. Best, A. Berger, D. Hansel, D. Palacios

5. 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