Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Reeg, P

Johal, G

Neelakantan, S

Jiménez Castaño, V

» Add more authors

Add filter to result:

Authors

Mueller, T

Neelakantan, S

Helmers, M

Dosskey, M

Reeg, P

Kyveryga, P.M

Mueller, T.A

Ahmad, A

Aggarwal, V

Saraswat, D

El Gamal, A

Johal, G

Sánchez Virosta, �

Gómez-Candón, D

Montoya Sevilla, F

Pérez García, Y

Jiménez Castaño, V

González Piqueras, J

López-Urrea, R

Sánchez Tomás, J

Topics

Precision Conservation Management

Profitability, Sustainability and Adoption

Applications of Unmanned Aerial Systems

Proximal and Remote Sensing of Soils and Crops (including Phenotyping)

Type

Oral

Year

2014

2022

2024

Home » Authors » Results

Authors

Filter results4 paper(s) found.
1. Precision Design Of Vegetative Buffers Precision agriculture techniques can be applied at field margins to improve performance of water quality protection practices. Effectiveness of vegetative buffers, conventionally designed to have uniform width along field margins, is limited by spatially non-uniform runoff from fields. Effectiveness can be improved by placing relatively wider buffer at locations where loads are greater. A GIS tool was developed that accounts for non-uniform flow and produces more-effective, variable-width,... T. Mueller, S. Neelakantan, M. Helmers, M. Dosskey Download paper
2. Evaluating Decision Systems For Using Variable Rates In Planting Soybean Increased interest in managing seeding rates within soybean fields is being driven by the advances in technologies and the need to increase productivity and economic returns. A wealth of previous research was focused on studying how different seeding rates affect soybean yields at small-plot scales. However, little is known how different site-specific factors influence the responsiveness of soybean to higher or lower plant population densities at field levels, especially across geographic... P. Reeg, P.M. Kyveryga, T.A. Mueller Download paper
3. 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
4. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming Context The increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an... Download paper

Filter results4 paper(s) found.

1. Precision Design Of Vegetative Buffers

Precision agriculture techniques can be applied at field margins to improve performance of water quality protection practices. Effectiveness of vegetative buffers, conventionally designed to have uniform width along field margins, is limited by spatially non-uniform runoff from fields. Effectiveness can be improved by placing relatively wider buffer at locations where loads are greater. A GIS tool was developed that accounts for non-uniform flow and produces more-effective, variable-width,... T. Mueller, S. Neelakantan, M. Helmers, M. Dosskey

Download paper

2. Evaluating Decision Systems For Using Variable Rates In Planting Soybean

Increased interest in managing seeding rates within soybean fields is being driven by the advances in technologies and the need to increase productivity and economic returns. A wealth of previous research was focused on studying how different seeding rates affect soybean yields at small-plot scales. However, little is known how different site-specific factors influence the responsiveness of soybean to higher or lower plant population densities at field levels, especially across geographic... P. Reeg, P.M. Kyveryga, T.A. Mueller

Download paper

3. 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

4. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming Context

The increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an...

Download paper