Premium
Anaerobically Incubated Nitrogen Improved Nitrogen Diagnosis in Corn
Author(s) -
Orcellet Juan,
Reussi Calvo Nahuel Ignacio,
Sainz Rozas Hernán Rene,
Wyngaard Nicolás,
Echeverría Hernán E.
Publication year - 2017
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2016.02.0115
Subject(s) - nitrate , sowing , mineralization (soil science) , nitrogen , agronomy , chemistry , biology , organic chemistry
Core Ideas Traditional corn N diagnostic methods (pre‐plant nitrate N test and pre‐sidedress nitrate N test) only account for mineral N. Objective: to improve N diagnostic methods by considering N mineralization. Pre‐plant nitrate N test and pre‐sidedress nitrate N test were improved by anaerobic‐N (N an ) in areas with similar soil/climates. Models combining N an , texture and temperature improved pre‐plant nitrate N test and pre‐sidedress nitrate N test in all areas.Current N diagnostic methods for corn ( Zea mays L.) are often based on the nitrate nitrogen (NO 3 − –N) concentration before planting (pre‐plant nitrate test, PPNT) and nitrate nitrogen (NO 3 − –N) concentration at V6 stage (PSNT). These tests provide scant information on soil N mineralization during the growing season, which can supply a considerable proportion of corn N requirements. The objective of our study was to evaluate if in‐season N recommendations could be improved by inclusion of a N mineralization potential estimator. We conducted field experiments ( n = 35) in three different areas and in two planting dates. At each site we evaluated PPNT, PSNT, and NH 4 –N released during anaerobic incubation (N an ), which were then related to corn yield in unfertilized plots (0N) and corn response to nitrogen fertilization (N resp% ) using multiple regression analysis. The sole incorporation of N an to PPNT and PSNT models improved their capacity to predict corn yield in 0N plots and N resp% only in areas with similar edaphic‐climatic characteristics. Independently of the geographical region, when PPNT and PSNT were combined with N an , texture, and temperature, their capacity to predict yield in 0N plots was increased (PPNT: from R 2 0.02–0.47; PSNT: from R 2 0.09–0.53), as it was their capacity to estimate N resp% (PPNT: from R 2 0.06–0.23; PSNT: from R 2 0.19–0.42). The inclusion of N an can improve traditional N diagnostic models when it is combined with edaphic/climatic properties that account for the mineralization rate of this N pool.