Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Kolln, O.T

Saraswat, D

Slaeem, S

» Add more authors

Add filter to result:

Authors

Slaeem, S

Zaman, Q.U

Madani, A

Schumann, A

Percival, D

Ahmad, H.N

Farooque, A.A

Khan, F

Graziano Magalhães, P.S

Sanches, G.M

Kolln, O.T

Franco, H.C

Braunbeck, O.A

Driemeier, C

Jha, S

Saraswat, D

Ward, M.D

Ahmad, A

Aggarwal, V

Saraswat, D

El Gamal, A

Johal, G

Topics

Spatial Variability in Crop, Soil and Natural Resources

Big Data, Data Mining and Deep Learning

Applications of Unmanned Aerial Systems

Type

Poster

Oral

Year

2012

2014

2018

2022

Home » Authors » Results

Authors

Filter results4 paper(s) found.
1. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry Fields Wild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve crop... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan Download paper
2. Precision Agriculture In Sugarcane Production. A Key Tool To Understand Its Variability. Precision agriculture (PA) for sugarcane represents an important tool to manage local application of fertilizers, mainly because sugarcane is third in fertilizer consumption among Brazilian crops, after soybean and corn. Among the limiting factors detected for PA adoption in the sugarcane industry, one could mention the cropping system complexity, data handling costs, and lack of appropriate decision support systems. The objective of our research group has... P.S. Graziano magalhães, G.M. Sanches, O.T. Kolln, H.C. Franco, O.A. Braunbeck, C. Driemeier Download paper
3. Analyzing Trends for Agricultural Decision Support System Using Twitter Data The trends and reactions of the general public towards global events can be analyzed using data from social platforms, including Twitter. The number of tweets has been reported to help detect variations in communication traffic within subsets like countries, age groups and industries. Similarly, publicly accessible data and (in particular) data from social media about agricultural issues provide a great opportunity for obtaining instantaneous snapshots of farmers’ opinions and a method to... S. Jha, D. Saraswat, M.D. Ward Download paper
4. 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

Filter results4 paper(s) found.

1. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry Fields

Wild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve crop... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan

Download paper

2. Precision Agriculture In Sugarcane Production. A Key Tool To Understand Its Variability.

Precision agriculture (PA) for sugarcane represents an important tool to manage local application of fertilizers, mainly because sugarcane is third in fertilizer consumption among Brazilian crops, after soybean and corn. Among the limiting factors detected for PA adoption in the sugarcane industry, one could mention the cropping system complexity, data handling costs, and lack of appropriate decision support systems. The objective of our research group has... P.S. Graziano magalhães, G.M. Sanches, O.T. Kolln, H.C. Franco, O.A. Braunbeck, C. Driemeier

Download paper

3. Analyzing Trends for Agricultural Decision Support System Using Twitter Data

The trends and reactions of the general public towards global events can be analyzed using data from social platforms, including Twitter. The number of tweets has been reported to help detect variations in communication traffic within subsets like countries, age groups and industries. Similarly, publicly accessible data and (in particular) data from social media about agricultural issues provide a great opportunity for obtaining instantaneous snapshots of farmers’ opinions and a method to... S. Jha, D. Saraswat, M.D. Ward

Download paper

4. 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