Algorithms for Translating Active Sensor Readings into In-season N Applications.
John Shanahan, USDA-ARS, Lincoln, NE 68583-0934, United States of America, Fernando Solari, Univ of Nebraska, Lincoln, NE 68503-0915, James Schepers, 113 Keim Hall, Univ of Nebraska, Lincoln, NE 68583-0915, and Gary Varvel, USDA-ARS, Univ of Nebraska, PO Box 830934, Lincoln, NE 68583-0934.
Traditional nitrogen (N) management schemes for corn production in the USA have resulted in low N use efficiency (NUE), environmental contamination, and considerable public debate regarding use of N fertilizers in crop production. Hence, development of alternative schemes that improve NUE and minimize environmental impact will be crucial to sustaining corn-based farming in the USA. The recent availability of active crop canopy sensors has provided an opportunity for making real time assessments of canopy vigor and/or N status. This paper will highlight research under way to develop algorithms for converting sensor reading into in-season variable rate N applications that improve NUE under site-specific soil and ever-changing climatic conditions.