Adjusting corn nitrogen management by including a mineralizable-nitrogen test with the preplant and presidedress nitrate tests

Jason D. Clark, Fabián G. Fernández, Kristen S. Veum, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Daniel E. Kaiser, Newell R. Kitchen, Carrie A.M. Laboski, Emerson D. Nafziger, Carl J. Rosen, John E. Sawyer, John F. Shanahan

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The anaerobic potentially mineralizable N (PMN) test combined with the preplant (PPNT) and presidedress (PSNT) nitrate tests may improve corn (Zea mays L.) N fertilization predictions. Forty-nine corn N response experiments (mostly corn following soybean [Glycine max (L.) Merr.]) were conducted in the U.S. Midwest from 2014–2016 to evaluate the ability of the PPNT and PSNT to predict corn relative yield (RY) and N fertilizer over- and under-application rates when adjusted by PMN. Before planting and N fertilization, PPNT (0–30, 30–60, and 60–90 cm) and PMN (0–30 cm) samples were obtained. In-season soil samples were obtained at the V5 development stage for PSNT (0–30, 30–60 cm) in all N rate treatments and PMN (0–30 cm) in only the 0 and 180 kg N ha−1 preplant N treatments. Increasing NO3–N sampling depths beyond 30 cm with or without PMN improved RY predictability marginally (R2 increase up to 0.20) and reduced over- and under-application frequencies up to 14%. Including PMN (preplant only) with PPNT or PSNT improved RY predictability minimally (R2 increase up to 0.10) only for coarse- and medium-textured soils, but N fertilizer over- and under-application frequencies were not substantially reduced (≤12%). These marginal improvements in RY predictability and N fertilizer over- and under-application frequencies, regardless of the variables used (e.g., fertilization, sampling depth, soil texture, and growing degree-day categories), demonstrate that including PMN with soil NO3–N alone does not improve corn N fertilization need predictions enough to recommend their use.

Original languageEnglish (US)
Pages (from-to)3050-3064
Number of pages15
JournalAgronomy Journal
Volume112
Issue number4
DOIs
StatePublished - Jul 1 2020

Bibliographical note

Funding Information:
We would like to thank DuPont Pioneer for funding this research. The authors thank the supporting scientists [Matt Yost; Dan Barker (IA); Lakesh Sharma, Amitava Chatterjee, and Norm Cattanach (ND); Todd Andraski (WI); and Tim Hart (DuPont Pioneer)], graduate students [Curtis Ransom and Gregory Bean (MO), Christopher Bandura (WI), and Matt Shafer (IN)], field technicians [Matt Volkmann (MO); Jason Niekamp and Joshua Vonk (IL); Glen Slater (NE); Andrew Scobbie, Thor Sellie, Nicholas Severson, Darby Martin, and Erik Joerres (MN)], and cooperating farmers and research farm personnel for their help in completing this project. Mention of trade names or commercial products in this publication is solely for the purpose of providing information and does not imply recommendation or endorsement by the affiliated Universities or the U.S. Department of Agriculture.

Publisher Copyright:
© 2020 The Authors. Agronomy Journal © 2020 American Society of Agronomy

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