Proceedings :: International Society of Precision Agriculture

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Arias, A

Aggarwal, V

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Authors

Baumbauer, C

Goodrich, P

Arias, A

Ahmad, A

Aggarwal, V

Saraswat, D

El Gamal, A

Johal, G

Topics

Proximal and Remote Sensing of Soil and Crop (including Phenotyping)

Applications of Unmanned Aerial Systems

Type

Oral

Year

2022

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Filter results2 paper(s) found.
1. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS Imagery Deep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal Download paper
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 Download paper

Filter results2 paper(s) found.

1. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS Imagery

Deep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal

Download paper

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

Download paper