Soil Tests for Corn Nitrogen Recommendations and Their Relationships with Soil and Landscape Properties.

Abstract

An accurate soil nitrogen (N) test is needed to improve corn production, profitability, and reduce environmental concerns of increasing nitrate (NO₃) levels in groundwater. The objectives of this study were to (i) compare soil N tests: amino sugar N (ASN), gas pressure (GP), pre-plant NO₃ (PPNT), and incubation and residual N (IRN) for precision and ability to predict corn response parameters e.g., economic optimum N rates (EONR); and (ii) examine the spatial relationships of ASN with soil and landscape properties to develop a more efficient sampling strategy. Small-plot N-response trials (NRT) were conducted in 2001 to 2004 at 31 sites. Field scale (FS) ASN variability was measured in 2003 and 2004 at four sites located in the North Carolina Piedmont and Coastal Plain. The ASN test had lower coefficients of variation than the GP, PPNT, and IRN tests (10 versus 15, 30, 52%, respectively). Each tests was correlated with economic optimum N rates from NRT sites, but coefficients of determination were low for the PPNT, IRN, and GP tests. The ASN test had the strongest correlation with EONR, but only when sites were classified as well (r² = 0.85) or poorly (r² = 0.78) drained. A comparison of ASN and EONR regression models across years and cost ratios (different corn price and fertilizer cost) were not statistically different. Amino sugar N was positively correlated with humic matter (HM; r² = 0.25 to 0.71) at each FS sites. Elevation was negatively correlated with ASN at the Lower and Middle Coastal Plain (r² = 0.44 and 0.11, respectively). In the Piedmont, ASN was negatively correlated with slope (r² = 0.10 and 0.04). Amino sugar N was positively correlated with soil texture (percent clay) for the Middle Coastal Plain (r² = 0.56) but negatively correlated for a site in the Piedmont (r² = 0.04). Amino sugar N is spatially sensitive to changes in soil and landscape properties, and soil sampling zones may be created using HM, soil texture, and soil type to reduce sampling costs and time. These results show that the ASN test was the best test for predicting economical optimum N rates and could be used to develop a site specific soil test based fertilizer recommendation.