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1. Soil Fertility for Functional FoodsIn the agri-food industry today, two trends cannot be ignored. First, the health conscious "baby boom" generation is demanding and will continue to demand foods that enhance their wellness. Crop producers must increasingly focus on the goal of producing crops that meet their needs. Second, the tools of molecular biology give agricultural scientists the opportunity to attain that goal. Biotechnology involves not only genetic engineering, but also includes tools that enhance the traditional selection... |
2. Recommendation Development Under 4R Nutrient StewardshipThe 4R Nutrient Stewardship concept defines the right source, rate, timing and placement of plant nutrients as those leadi ng to the economic, social and e nvironmental benefits desired by stakeholders. This implies roles for both science and stakeholder engagement . Scientific data on the linkages to outcomes needs to be communicat ed to stakeholders to ensure their valid participation and to build public confidence. Th e 4R Nutrient Stewardship concept helps to link science to practice and communicate... |
3. Phosphorus Placement For Corn, Soybeans, and WheatRoot-Soil Interface Transport Pathways Three mechanisms are commonly cited for how nutrients reach plant roots: 1) root interception, 2) mass flow, and 3) diffusion. Root interception occurs when a plant root, as it grows, comes into direct contact with a nutrient. Quantities of nutrients reaching plant roots in this manner are estimated to be proportional to the volume of soil occupied by roots (Barber et al., 1963). For instance, if roots occupy one percent of the soil volume, then the quantity... |
4. 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 |
5. 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 |