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| Filter results8 paper(s) found. |
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1. Management Zone Delineation Techniques to Aid In-Season Sensor Based Nitrogen ApplicationThe increased efficiency of nitr ogen fertilizer (N) use has been a long-term goal in reduction of nitrate contamination in the stat e of Nebraska. Preliminary rese arch has shown sensor based in- season application of nitrogen has the ability to be economic and environmentally viable. Although benefits have been published there is an opportunity for increased accuracy of N application through the integration of preprocesse d georeferenced management zones. In-season sensor based N application relies... |
2. 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 |
3. 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 |
4. Improving Nitrogen Management in Dryland Winter Wheat Production in NebraskaWheat producers in Nebraska endured a significant loss in profit due to reduced grain protein in years that had wet springs such as in 2016 and 2017. Among many potential factors, soil nitrogen (N) is the most central factor that affects protein levels in wheat. To investigate the effect of N on wheat grain yield and protein content, field trials across the State were initiated in 2018. The specific objectives of the field study were to evaluate the effects of different N rates and application... |
5. Site-Specific Yield and Protein Response to Nitrogen Rate and Timing in Winter WheatNitrogen (N) fertilizer management is crucial in cereal crop production. Improved prediction of optimal N fertilizer rates for winter wheat can decrease N losses and enhance profits. We tested seven N fertilizer rates (0, 25, 50, 75, 100, 125, and 150 kg N ha-1) applied at three timings (Fall, Spring, and Split Fall/Spring) in seven small plot trials located in commercial fields... J. Cesario pereira pinto, L. Puntel, L. Thompson, N. Mueller |
6. Benchmarking Nitrogen Recommendation Tools for Nebraska Winter WheatAttaining high yield and high nitrogen (N) use efficiency (NUE) remains a current research challenge in crop production. Digital ag technologies for site-specific N management have been demonstrated to improve NUE. This is due to the ability of digital technologies to account for the spatial and temporal distribution of crop N demand and available soil N in the field, which varies greatly according to soil properties, climate, and management. In addition, winter wheat protein content is highly... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, G. Balboa |
7. Improving Digital Soil Maps for Site-specific Soil Fertility Management Using Feature SelectionDigital soil mapping (DSM) has become an attractive option to manage site-specific soil fertility management thanks to its capabilities of creating highly accurate, fine-resolution (e.g., 3 m) soil maps with uncertainty measures associated with soil property predictions. One approach to making soil maps with geospatial technologies is to build statistical models using machine learning (ML) based on the relationships between environmental covariates (e.g., digital terrain attributes, satellite,... C. Ferhatoglu, B.A. Miller |
8. Evaluation of Instinct II and Radiate on Soft Red Winter Wheat in Northwest OhioProducers in Northwest Ohio are encouraged to purchase various additives for urea-ammonium nitrate (UAN) with the expectation to increase grain yields; however, they have limited information on the benefits of these products except what was provided by the selling company. Two products that were commonly promoted were Instinct II, a nitrification inhibitor, and Radiate, a growth regulator. A three-year study was completed at the OARDC Northwest Agricultural Research Station near Custar, Ohio to... E.M. Lentz |