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Gnyp, M.L
Carter, P
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Authors
Gnyp, M.L
Panitzki, M
Reusch, S
Jasper, J
Bolten, A
Bareth, G
Huang, S
Miao, Y
Yuan, F
Gnyp, M.L
Yao, Y
Cao, Q
Lenz-Wiedemann, V
Bareth, G
Ransom, C.J
Bean, M
Kitchen, N
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Kitchen, N.R
Yost, M.A
Ransom, C.J
Bean, G
Camberato, J
Carter, P
Ferguson, R
Fernandez, F
Franzen, D
Laboski, C
Nafziger, E
Sawyer, J
Topics
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
In-Season Nitrogen Management
Type
Oral
Year
2016
2018
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1. Comparison Between Tractor-based and UAV-based Spectrometer Measurements in Winter Wheat

In-season variable rate nitrogen fertilizer application needs a fast and efficient determination of nitrogen status in crops. Common sensor-based monitoring of nitrogen status mainly relies on tractor mounted active or passive sensors. Over the last few years, researchers tested different sensors and indicated the potential of in-season monitoring of nitrogen status by unmanned aerial vehicles (UAVs) in various crops. However, the UAV-platforms and the available sensors are not yet accepted to... M. Gnyp, M. Panitzki, S. Reusch, J. Jasper, A. Bolten, G. Bareth

2. Potential Improvement in Rice Nitrogen Status Monitoring Using Rapideye and Worldview-2 Satellite Remote Sensing

For in-season site-specific nitrogen (N) management of rice to be successful, it is crucially important to diagnose rice N status efficiently across large area in a timely fashion. Satellite remote sensing provides a promising technology for crop growth monitoring and precision management over large areas. The FORMOSAT-2 satellite remote sensing imageries with 4 wavebands have been used to estimate rice N status. The objective of this study was to evaluate the potential of using high spatial resolution... S. Huang, Y. Miao, F. Yuan, M.L. Gnyp, Y. Yao, Q. Cao, V. Lenz-wiedemann, G. Bareth

3. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor Algorithm

Nitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

4. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer Response

Improving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer