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This article in SSSAJ

  1. Vol. 70 No. 1, p. 172-182
    Received: Jan 26, 2005

    * Corresponding author(s): mulvaney@uiuc.edu


Need for a Soil-Based Approach in Managing Nitrogen Fertilizers for Profitable Corn Production

  1. R. L. Mulvaney *,
  2. S. A. Khan and
  3. T. R. Ellsworth
  1. Dep. of Natural Resources and Environ. Sci., Univ. of Illinois, 1102 S. Goodwin Ave., Urbana, IL 61801


Nitrogen fertilization for corn (Zea mays L.) production has relied extensively on yield-based recommendations that were developed to represent regional averages, yet are routinely applied to individual fields, on the assumption that fertilizer N serves as the major supply for crop N uptake. Using data from 102 on-farm N-response studies, an evaluation was conducted of the Illinois proven-yield (PY) method for accuracy and economic profitability on a site-by-site basis. As additional objectives, the Illinois soil N test (ISNT) was evaluated for detecting whether N fertilization was economical, and for quantifying crop response to N fertilization relative to soil and management factors. For 18% of the site-years studied, N recommendations by the PY method were accurate to within 20 kg ha−1, whereas 13% were underfertilized by 25 to 129 kg ha−1 (60 kg ha−1 on average) at a current cost of $5 to $170 ha−1 ($75 ha−1 on average), and 69% were overfertilized by 21 to 235 kg ha−1 (103 kg ha−1 on average) at a cost of $12 to $130 ha−1 ($57 ha−1 on average). The latter group included 30 site-years that were completely nonresponsive to N fertilization, all but two of which were predicted by site-average ISNT values assuming a critical test level of 230 mg kg−1 This level was exceeded for 19 of 69 responsive site-years, mostly during 2001–2003 when corn followed soybean (Glycine max L. Merr.) with high plant populations. A higher critical test level would have been required under such conditions, owing to more extensive residue inputs that would promote microbial N immobilization, and increased crop uptake of mineralized soil N. The ISNT was significantly related to crop N requirement, and was the most powerful predictor of error in PY recommendations (P < 0.001).

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