Integration of An Active Sensor Algorithm with Soil-Based Management Zones for Nitrogen Management in Corn.

Active crop canopy sensors have been studied as a possible proximal sensing tool to assess in-season plant N status and direct spatially-variable N applications, and thereby increase NUE compared to uniform N application. A sensor-based N application algorithm was previously developed on small plots for use in corn. Some have also suggested the integration of crop-based sensing with soil-based management zones (MZ) as a more robust decision tool to guide variable-rate N application. The objectives of this study were to (1) evaluate the active sensor algorithm proposed by Solari et al. (2010) against uniform N application in a variety of soil and climatic conditions, and (2) explore the usefulness of an integrated MZ and active sensor approach for improving N management. Research was conducted on 6 irrigated producer cornfields in central Nebraska during the 2007 and 2008 growing seasons. Five N application strategies were applied to field-length strips in a RCBD with 3 replications per field. In-season sensing and yield measurements were collected, and partial factor productivity (PFP) was calculated for each treatment. Additionally, 8 different soil data layers were collected for MZ delineation. Compared to uniform N application, integrating MZ and sensor-based N application resulted in substantial N savings for fine-textured soils with eroded slopes (~40-120 kg ha^-1). Sensor-based treatments in these soil types increased PFP ~13-75 kg grain (kg N applied)^-1. In other soil conditions, however, the current sensor-based N application algorithm may require further calibration, or may not provide substantial benefits compared to conventional uniform N management.