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Splichal, M
Salem, M.A
Sawyer, J
Stone, H
Schneider, D.A
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Authors
Ortiz, B.V
Vellidis, G
Balkcom, K
Stone, H
Fulton, J.P
vanSanten, E
Stanley, J.N
Schneider, D.A
Lamb, D.W
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Charvat, K
Reznik, T
Lukas, V
Charvat Jr., K
Horakova, S
Splichal, M
Kepka, M
Rabia, A.H
Salem, M.A
Salem, M.A
Rabia, A.H
Topics
Guidance, Robotics, Automation, and GPS Systems
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Precision Agriculture and Climate Change
Big Data, Data Mining and Deep Learning
Precision Crop Protection
Type
Poster
Oral
Year
2012
2016
2024
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Authors

Filter results6 paper(s) found.

1. Evaluation of The Advantages of Using GPS-Based Auto-Guidance on Rolling Terrain Peanut Fields

  ... B.V. Ortiz, G. Vellidis, K. Balkcom, H. Stone, J. Fulton, E. Vansanten

2. Spatial Apparent Electrical Conductivity (ECa), Soil Moisture and Water Use Efficiency in Vertosol Soils

Producing high resolution maps of water use efficiency (crop yield per unit of water consumption; WUE) for precision crop management is limited by our ability to readily produce maps of soil moisture... J.N. Stanley, D.A. Schneider, D.W. Lamb

3. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

4. Quo Vadis Precision Farming

The agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka

5. Potato Disease Detection Using Laser Speckle Imaging and Deep Learning

Early detection of potato diseases is essential for minimizing crop loss. Implementing advanced imaging techniques can significantly improve the accuracy and efficiency of disease detection in potato crops. Leveraging machine learning algorithms can further enhance the speed and precision of disease identification, enabling timely intervention measures. This work presents a novel potato disease detection technique using whole-potato speckle imaging and deep learning. Laser Speckle Imaging (LSI),... A.H. Rabia, M.A. Salem

6. Development of a High-throughput UAV System for Precision Weed Detection and Control Using Laser Speckle Imaging and UV-C Irradiation

Traditional weed control methods, predominantly reliant on herbicides or labor-intensive ground robots, present notable environmental and efficiency challenges within agricultural practices. To address these concerns, this study introduces an innovative approach utilizing unmanned aerial vehicles (UAVs) for autonomous weed detection and control in agricultural fields. Our proposed system depends on the agility of UAV platforms, integrating two primary technologies. Firstly, Laser Speckle Imaging... M.A. Salem, A.H. Rabia