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This article in CM

  1. Vol. 5 No. 1
     
    Accepted: Feb 27, 2006


    * Corresponding author(s): Ravi_Sripada@ncsu.edu
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doi:10.1094/CM-2006-0405-01-RS

Attempt to Validate a Remote Sensing-Based Late-Season Corn Nitrogen Requirement Prediction System

  1. Ravi P. Sripada *a,
  2. Ronnie W. Heinigerb,
  3. Jeffrey G. Whitec,
  4. Carl R. Crozier and
  5. Alan D. Meijerd
  1. a Department of Crop Science, North Carolina State University, Box 7620, Raleigh 27695-7620
    b Department of Crop Science, Vernon James Research and Extension Center, North Carolina State University, 207 Research Road, Plymouth 27962
    c Department of Soil Science, North Carolina State University, Box 7619, Raleigh 27695-7619
    d Department of Soil Science, Vernon James Research and Extension Center, North Carolina State University, 207 Research Road, Plymouth 27962

Abstract

Recent research showed that corn (Zea mays L.) may respond profitably to N applied at tasseling (VT), and that aerial color-infrared (CIR) photography could be used to predict economic optimum N rates at VT using the green difference vegetation index (GDVI, near-infrared brightness minus green brightness) calculated relative to a high N reference strip (relative GDVI, RGDVI). This technique could be used by farmers to identify N stress and quantify N requirements. To validate this technique for practical application, experiments were conducted with different rates of N applied at planting and at VT on irrigated and non-irrigated sites in North Carolina during 2003. In both irrigated and non-irrigated systems, maximum yield potential was achieved with 200 lb of N per acre at planting. The difference between predicted and observed optimum N rate at VT ranged from -27 to 80 lb/acre. Greater differences between predicted and observed optimum N rate at VT occurred when N requirement was high, which was attributed to lower yield potential in 2003 compared to the years when the model was developed. Although the model tended to over-predict N rates, it did capture differences in N requirements across the range of conditions tested, indicating that this technique can be an effective tool to determine late-season corn N need. Differences between the estimated and actual N rates might be reduced by incorporating a method for determining yield potential.

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