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Krull, D
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Authors
Ferguson, R
Slater, G
Krull, D
Irmak, S
Crowther, J
Parrish, J
Ferguson, R
Luck, J
Glewen, K
Shaver, T
Krull, D
Thompson, L
Mueller, N
Krienke, B
Mieno, T
Ingram, T
Parrish, J
Ferguson, R
Luck, J
Glewen, K
Thompson, L
Krienke, B
Mueller, N
Ingram, T
Krull, D
Crowther, J
Shaver, T
Mieno, T
Topics
Type
Oral
Year
2009
2017
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1. Evaluation of Nitrate Leaching Potential from Slow and Controlled Release Nitrogen Fertilizer Application to Irrigated Corn

The use of slow and controlled release nitrogen (N) fertilizers as a practice to reduce nitrate leaching from irrigated corn was evaluated on coar se-textured soils in the Central Platte River Valley of Nebraska in 2007 & 2008. Slow-releas e methylene urea (MU) and polymer-coated urea (PCU) were compared to a standard fertil izer of urea ammonium nitrate (UAN) solution. Flooding in 2007 severely impacted the study site, and results are not reported here. Saturated soils were common at the site in...

2. Integrating Management Zones and Canopy Sensing for Improved Nitrogen Recommendation Algorithms

Active crop canopy sensors have been studied as a tool to direct spatially variable nitrogen (N) fertilizer applications in maize, with the goal of increasing the synchrony between N supply and crop demand and thus improving N use efficiency (NUE). However, N recommendation algorithms have often proven inaccurate in certain subfield regions due to local spatial variability. Modifying these algorithms by integrating soil-based management zones (MZ) may improve their accuracy... J. Crowther, J. Parrish, R. Ferguson, J. Luck, K. Glewen, T. Shaver, D. Krull, L. Thompson, N. Mueller, B. Krienke, T. Mieno, T. Ingram

3. Comparison of Ground-Based Active Crop Canopy Sensor and Aerial Passive Crop Canopy Sensor for In-Season Nitrogen Management

Crop canopy sensors represent one tool available to help calculate a reactive in-season nitrogen (N) application rate in corn. When utilizing such systems, corn growers must decide between using active versus passive crop canopy sensors. The objectives of this study was to 1) determine the correlation between N management by remote sensing using a passive sensor and N management using proximal sensing with an active sensors. Treatments were arranged as field length strips in a randomized complete... J. Parrish, R. Ferguson, J. Luck, K. Glewen, L. Thompson, B. Krienke, N. Mueller, T. Ingram, D. Krull, J. Crowther, T. Shaver, T. Mieno