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Zhao, L
Arias, A
Khalid, M.B
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Authors
Zainal Abidin, M.B
Shibusawa, S
Ohaba, M
Li, Q
Kodaira, M
Khalid, M.B
Baumbauer, C
Goodrich, P
Arias, A
Fernandez, O
Bhandari, M
Landivar-Scoot, J.L
Eldefrawy, M
Zhao, L
Landivar, J
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Topics
Modeling and Geo-statistics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Data Analytics for Production Ag
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2022
2024
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Filter results4 paper(s) found.

1. Transient Water Flow Model in a Soil-Plant System for Subsurface Precision Irrigation

The spatial variability of plant-water characteristic in the soil is still unclear. This limits the attempt to model the soil-plant-atmosphere system with this factor. Understanding the non-steady water flow along the soil-plant component is essential to understand their spatial variability.... M.B. Zainal abidin, S. Shibusawa, M. Ohaba, Q. Li, M. Kodaira, M.B. Khalid

2. Printed Nitrate Sensors for In-soil Measurements

Managing nitrate is a central concert for precision agriculture, from delineating management zones, to optimizing nitrogen use efficiency through in-season applications, to minimizing leaching and greenhouse gas emissions. However, measurement methods for in-soil nitrate are limiting. State-of-the-art soil nitrate analysis requires taking soil or liquid samples to laboratories for chemical or spectrographic analysis. These methods are accurate, but costly, labor intensive, and cover limited geographic... C. Baumbauer, P. Goodrich, A. Arias

3. 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

4. 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