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Paccioretti, P
Westfall, D.G
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Authors
Khosla, R
Westfall, D.G
Longchamps, L
Longchamps, L
Panneton, B
Westfall, D.G
Khosla, R
Cesario Pinto, J
Thompson, L
Mueller, N
Mieno, T
Puntel, L
Paccioretti, P
Balboa, G
Balboa, G
Puntel, L
Thompson, L
Paccioretti, P
Topics
Precision Nutrient Management
Guidance, Robotics, Automation, and GPS Systems
On Farm Experimentation with Site-Specific Technologies
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Type
Poster
Oral
Year
2012
2024
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1. Early Detection of Corn N-Deficiency by Active Fluorescence Sensing in Maize

Globally, the agricultural nitrogen use efficiency (NUE) is no more than 40 %. This low efficiency comes with an agronomic, economic and environmental cost. By better management of spatial and temporal variability of crop nitrogen need, NUE can be improved. Currently available crop canopy sensors based on reflectance are capable... R. Khosla, D.G. Westfall, L. Longchamps

2. Testing The Author Sequence - Finalize

This is just a test to verify the bug with the authors sequence. ... L. Longchamps, B. Panneton, D.G. Westfall, R. Khosla

3. Site-specific Evaluation of Sensor-based Winter Wheat Nitrogen Tools Via On-farm Research

Crop producers face the challenge of optimizing high yields and nitrogen use efficiency (NUE) in their agricultural practices. Enhancing NUE has been demonstrated by adopting digital agricultural technologies for site-specific nitrogen (N) management, such as remote-sensing based N recommendations for winter wheat. However, winter wheat fields are often uniformly fertilized, disregarding the inherent variability within the fields. Thus, an on-farm evaluation of sensor-based N tools is needed to... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa

4. Barriers and Adoption of Precision Ag Tehcnologies for Nitrogen Management Nebraska

A statewide survey of Nebraska farmers shows that they determine the N rate based on soil lab recommendations (82%),  intuition, traditional rate, and own experience (67%). The adoption of dynamic site-specific models (23%), and sensor-based algorithms (11%) remains low. The survey identified the main barriers to the adoption of these N management technologies.  ... G. Balboa, L. Puntel, L. Thompson, P. Paccioretti