Proceedings
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| Filter results4 paper(s) found. |
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1. 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 |
2. 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 |
3. Grid Soil Sample Interpolation Using Geographicaly Weighted Regression and Random ForestSoil sampling is useful in agriculture for setting fertilizer application rates. High density soil samples can also be used for variable rate seeding and other precision agriculture applications. Half-acre grid soil samples were collected from 6 soybean fields, and phosphorous (P), potassium (K), and organic matter (OM) were measured. Each soil parameter was interpolated for each field, with terrain attributes as covariates, using two different methods: geographically weighted regression (GWR)... E. Matcham, S. Subburayalu, J. Fulton, E. Hawkins, P. Paul, L. Lindsey |
4. Relationship of in-season soil nitrogen concentration with corn yield and potential nitrogen lossesModeled or measured soil mineral N (SMN) levels during the corn growing season have been used to set sidedress N rates, but there has been little research linking SMN levels at different growth stages to yield to help guide this process. The degree to which SMN level influences the risk of N losses is also not known. Data from 32 site-years of field experiments in Illinois (2015–2018) that included 12 combinations of N fertilizer rate, timing, and source, were used to evaluate... G. Preza-fontes, E. Nafziger, L. Christianson, C. Pittelkow |