Comparison of Soil Nitrogen Tests for Corn Fertilizer Recommendations in the Humid Southeastern USA

Abstract

C urrently recommended N management in North Carolina and elsewhere in the humid southeastern USA is based on realistic yield expectations (RYE). In North Carolina, N recommendations based on RYE are made from a database of RYE by soil map unit or based on a grower's documented historic yields (the average of the best three yields during a 5-yr period; North Carolina Nutrient Management Workgroup, 2003). The recommended N rate is calculated using the RYE and a soil-and crop-dependent N application factor (18-22.5 kg N Mg −1 corn grain yield). These N fertilizer recommendations are based on decades of fi eld response trials (Kamprath et al., 1973; Kamprath, 1986), but can result in under-or overapplication, in part because they do not consider soil N (Mulvaney et al., 2001). Soils under certain management practices (e.g., manure applications or legume cover crops) or soils with high organic matter content may have suffi cient residual and potentially mineralizable N for optimum corn growth and need little or no N fertilizer. Overapplication of N fertilizer has been linked to high levels of NO 3 in shallow groundwater underneath agricultural fi elds in North Carolina and elsewhere (Gambrell et al., 1974; Jacobs and Gilliam, 1985). The Neuse River Basin in North Carolina has experienced fi sh kills linked to nonpoint sources of NO 3 pollution (North Carolina Division of Water Quality, 1996, p. 44). Agricultural N pollution could be reduced by more effectively determining accurate fertilizer rates, so less N is susceptible to leaching and runoff (Khan et al., 2001). A soil N test to predict corn N need or corn responsiveness to N fertilizer could be used to more accurately predict fertilizer recommendations. The challenge is to develop a soil N test that is accurate, timely, and cost effective for predicting corn yield response to N fertilizer or corn fertilizer N requirement. The climate in the southeastern USA complicates soil N test development because of warm temperatures and rainfall that exceeds evapotranspiration, resulting in rapid mineralization, immobilization, leaching, and denitrifi cation. The preplant and presidedress NO 3 tests have had limited success in estimating corn N need in the humid southern USA (Bundy et al., 1992; Grove, 1992). Soil N tests that measure mineralizable N under aerobic conditions are not practical for predicting yield response to fertilizer because they require a long incubation period (30-60 d; Bundy and Meisinger, 1994). Potential soil tests for predicting fertilizer response in corn would be an anaerobic IRNT (Bundy

Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

“…Since its development, the Illinois soil N test has been evaluated by many researchers who have reported both successes in using the Illinois soil N test to differentiate N responsive from nonresponsive sites Mulvaney et al, 2006;Sharifi et al, 2007;Williams et al, 2007aWilliams et al, , 2007b and failures (Barker et al, 2006;Laboski et al, 2008;Osterhaus et al, 2008).…”

Predicting Nitrogen Fertilizer Needs for Rice in Arkansas Using Alkaline Hydrolyzable-Nitrogen

“…Substantial research eff orts have focused on the utilization of the ISNT as a method to predict corn response and N fertilizer needs, but results have been mixed with limited success. Williams et al (2007aWilliams et al ( , 2007b successfully correlated and calibrated the ISNT for corn economic optimum N rates (EONR) in North Carolina and showed that the ISNT's predictive ability was enhanced when soils were categorized based on drainage classifi cation. A study by Ruff o et al (2006) identifi ed ISNT as the single most important parameter evaluated in conjunction with site-specifi c yield-response functions.…”

Calculation of theoretical nitrogen rate for simple nitrogen recommendations in intensive cropping systems: A case study on the North China Plain

“…Methods based on yield response curves cannot explain the spatial and temporal variation found in practice (i.e. curves often obtained from former field trials and other sites) (Williams et al, 2007). Methods based on soil testing involve the problem of searching for a reliable testing index.…”