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1. Post-Harvest Soil Nitrate Following Corn Production in Eight Midwestern StatesApplying nitrogen (N) at economically optimal rates (EONR) and at times of rapid crop uptake are practices that are thought to minimize the amount of residual soil nitrate (RSN) in the profile that may be susceptible to loss. The objective of this study was to evaluate the effects of rate (0 to 280 lb N/a in 40 lb increments) and timing (pre-plant (PP) or PP plus V9 sidedress (PP+SD)) of N application on corn grain yield and RSN in the top 3 feet of soil relative to the calculated EONR. Thirty-two... C. Bandura, C. Laboski, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, N. Kitchen, E. Nafziger, J. Sawyer, J. Shanahan |
2. Variation in Internal N Efficiency of Corn and Impact on Yield-Goal Based N RecommendationsInternal N efficiency (IE) is defined as bushels per acre (GY) produced per pound of N per acre (PMN) in the plant at physiological maturity (R6). Internal N efficiency defines the required amount of plant N content at R6 in a yield-goal based N rate recommendations (currently used in 30 U.S. states) and several commercial N recommendation models. Commonly IE is assumed to be constant at an approximate value of 0.8 bu lb-N-1 in yield-goal based recommendations. Our research objective was... M. Shafer, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, N. Kitchen, C. Laboski, E. Nafziger, R. Nielsen, J. Sawyer, J. Shanahan |
3. Integrating Management Zones and Canopy Sensing for Improved Nitrogen Recommendation AlgorithmsActive 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 |
4. Comparison of Ground-Based Active Crop Canopy Sensor and Aerial Passive Crop Canopy Sensor for In-Season Nitrogen ManagementCrop 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 |