Combination of biological and chemical soil tests best predict maize nitrogen response

Authors

M. D. McDaniel, Iowa State UniversityFollow
Daniel T. Walters, University of Nebraska - LincolnFollow
L. G. Bundy, University of Wisconsin-Madison
Xiaofei Li, Mississippi State UniversityFollow
Rhae A. Drijber, University of Nebraska - LincolnFollow
John E. Sawyer, Iowa State UniversityFollow
Michael J. Castellano, Iowa State UniversityFollow
C. A.M. Laboski, University of Wisconsin-MadisonFollow
Peter C. Scharf, University of Missouri - ColumbiaFollow

ORCID IDs

M. D. McDaniel https://orcid.org/0000-0001-6267-7293

X. Li https://orcid.org/0000-0001-5781-4687

J. E. Sawyer https://orcid.org/0000-0003-4080-9616

M. J. Castellano https://orcid.org/0000-0003-1411-7931

Document Type

Article

Date of this Version

2-2020

Citation

McDaniel M, Walters D, Bundy L, et al. Combination of biological and chemical soil tests best predict maize nitrogen response. Agronomy Journal. 2020;112:1263–1278. https://doi.org/10.1002/agj2.20129

Comments

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License. © 2020 The Authors.

Abstract

Soil tests can help optimize nitrogen (N) fertilizer rates, thereby improving farmer profitability and environmental performance. In US Midwest maize (Zea mays) production, however, most soil N tests have limited accuracy to predict N fertilizer requirements. Here we tested the individual and combined ability of 30 soil tests (12 rapid N extractions, seven biological carbon or N tests, six long-term incubation kinetic parameters, and five other routine soil tests), as well as environmental and management data, to predict maize response to N fertilizer across 56 site-years in the US Midwest. Out of 30 soil tests, and across all site-years, a 14-d aerobic incubation best predicted whether maize responded to N fertilizer, and a 5-min tetraphenyl borate extraction best predicted agronomic optimum N rate. We combined these two tests to evaluate their ability to predict N fertilizer response against the most commonly used soil N test in the US Midwest, the pre-sidedress or late-spring nitrate test (PSNT or LSNT). The combination of soil tests nearly doubled the ability to predict nonresponsive sites compared to PSNT, and on average resulted in a 40% reduction in over-application and 37% reduction in under-application of N fertilizer. Weather and management variables marginally improved the prediction of maize N response. Our results indicate that a simple combination of biological N mineralization (14-d aerobic incubation) and chemical extraction (5-min tetraphenyl borate) assays could improve current N fertilizer recommendations.