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Shaw, J
Squires, T
Landivar, J
Serra, S
Sun, C
Li, H
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Authors
Lee, W
Wang, K
Li, H
Ehsani, R
Yang, C
Khot, L
Sankaran, S
Johnson, D
Carter, A
Serra, S
Musacchi, S
Cummings, T
Poncet, A.M
Fulton, J.P
McDonald, T.P
Knappenberger, T
Bridges, R.W
Shaw, J
Balkcom, K
Oliveira, L.P
Ortiz, B.V
Morata, G.T
Squires, T
Jones, J
Lee, J
song, S
Oh, S
Krishnaswamy, K
Sun, C
Adu-Gyamfi, Y
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Fernandez, O
Bhandari, M
Landivar-Scoot, J.L
Eldefrawy, M
Zhao, L
Landivar, J
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Spatial Variability in Crop, Soil and Natural Resources
On Farm Experimentation with Site-Specific Technologies
Precision Agriculture and Global Food Security
Artificial Intelligence (AI) in Agriculture
Data Analytics for Production Ag
Type
Poster
Oral
Year
2012
2014
2016
2022
2024
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Authors

Filter results7 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. Unmanned Aerial System Applications In Washington State Agriculture

Three applications of unmanned aerial systems (UAS) based imaging were explored in row, field, and horticultural crops at Washington State University (WSU). The applications were: to evaluate the necrosis rate in potato field crop rotation trials, to quantify the emergence rates of three winter wheat advanced yield trials, and detecting canker disease-infection in pear. The UAS equipped with green-NDVI imaging was used to acquire field aerial images. In the first application,... L. Khot, S. Sankaran, D. Johnson, A. Carter, S. Serra, S. Musacchi, T. Cummings

3. Measurement of In-field Variability for Active Seeding Depth Applications in Southeastern US

Proper seeding depth control is essential to optimize row-crop planter performance, and adjustment of planter settings to within field spatial variability is required to maximize crop yield potential. The objectives of this study were to characterize planting depth response to varying soil conditions within fields, and to discuss implementation of active seeding depth technologies in Southeastern US. This study was conducted in 2014 and 2015 in central Alabama for non-irrigated maize (Zea mays... A.M. Poncet, J.P. Fulton, T.P. Mcdonald, T. Knappenberger, R.W. Bridges, J. Shaw, K. Balkcom

4. Is Row-unit Vibration Affected by Planter Speeds and Downforce?

Row-unit vibration is an issue created mainly by planter`s opening disks and gauge-wheels contact with the ground. Variability on row-unit vibration could interfere on seed metering and delivery process, affecting crop emergence and final stand. With the amount of embedded technology present on planters, producers are being encouraged to increase planting speeds, which is also one of the main factors for row-unit vibration increasement. In this way, knowing the proper speeds, and using other instruments... L.P. Oliveira, B.V. Ortiz, G.T. Morata, T. Squires, J. Jones

5. Smart Food Oases: Development of a Distributed Point-to-point Urban Food Ecosystem in Food Desert Areas

Urban agriculture has been getting much attention in the past decade as a solution to overcome food insecurity and accessibility of food for urban residents and to have better green environments in cities. Urban agriculture is expected to provide better nutrients to residents, reduce transportation and environmental costs, and help urban dwellers access food efficiently. The present study is to build a collaborative ecosystem among urban growers/producers and create bridges from these farmers... J. Lee, S. Song, S. Oh, K. Krishnaswamy, C. Sun, Y. Adu-gyamfi

6. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySat

Satellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari

7. Ground-based Imagery Data Collection of Cotton Using a Robotic Platform

In modern agriculture, technological advancements are pivotal in optimizing crop production and resource management. Integrating robotics and image processing techniques allows the efficient collection, analysis, and storage of high-resolution images crucial for monitoring crop health, identifying pest infestations, assessing growth stages, making precise management decisions and predicting yield potential. The objective of this project is to utilize the Farm-NG Amiga robot to develop an image... O. Fernandez, M. Bhandari, J.L. Landivar-scoot, M. Eldefrawy, L. Zhao, J. Landivar

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