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Daughtry, D
Helgason, C
Acconcia Dias, M
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Authors
Zhang, X
Helgason, C
Seielstad, G
Shi, L
Porter, W
Daughtry, D
Harris, G
Noland, R
Snider, J
Virk, S
Pereira de Souza, F
Shiratsuchi, L
tao, H
Acconcia Dias, M
Barbosa, M
Deri Setiyono, T
Campos, S
Pereira de Souza, F
Shiratsuchi, L
tao, H
Acconcia Dias, M
Barbosa, M
Deri Setiyono, T
Campos, S
Topics
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Applications of Unmanned Aerial Systems
Data Analytics for Production Ag
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2008
2018
2024
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Filter results4 paper(s) found.

1. Zone Mapping Application for Precision-farming: a Decision Support Tool for Variable Rate Application

We have developed a web-based decision support tool, Zone Mapping Application for Precision Farming (ZoneMAP, http://zonemap.umac.org), which can automatically determine the optimal number of management zones and delineate them using satellite imagery and field survey data provided by users. Application rates, say for fertilizer, can be prescribed for each zone and downloaded in a variety of formats to ensure compatibility with GPS-enabled farming applicators. ZoneMAP is linked to Digital Northern... X. Zhang, C. Helgason, G. Seielstad, L. Shi

2. Correlating Plant Nitrogen Status in Cotton with UAV Based Multispectral Imagery

Cotton is an indeterminate crop; therefore, fertility management has a major impact on the growth pattern and subsequent yield. Remote sensing has become a promising method of assessing in-season cotton N status in recent years with the adoption of reliable low-cost unmanned aerial vehicles (UAVs), high-resolution sensors and availability of advanced image processing software into the precision agriculture field. This study was conducted on a UGA Tifton campus farm located in Tifton, GA. The main... W. Porter, D. Daughtry, G. Harris, R. Noland, J. Snider, S. Virk

3. Computer Vision by UAVs for Estimate Soybean Population Across Different Physiological Growth Stages and Sowing Speeds

Soybean (Glycine max (Linnaeus) Merrill) production in the United States plays a crucial role in agriculture, occupying a considerable amount of cultivated land. However, the costs associated with soybean production have shown a notable increase in recent years, with seed-related expenses accounting for a significant proportion of the total. This increase in costs is attributed to a number of factors, including the introduction of patented and protected genetic traits, as well as inflationary... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. Deri setiyono, S. campos

4. Optimizing Soybean Management with UAV RGB and Multispectral Imagery: a Neural Network Method and Image Processing

Precision agriculture (PA) has emerged as a fundamental approach in contemporary agricultural management, aimed at maximizing efficiency in the use of resources and improving crop productivity. The transition to so-called "agriculture 4.0" represents a revolution in the way technology is applied in the field, with an emphasis on digital and automated solutions such as UAVs (Unmanned Aerial Vehicles). These devices offer new capabilities for capturing high-resolution images, enabling... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. deri setiyono, S. Campos