z-logo
Premium
Field‐Scale Variability in Optimal Nitrogen Fertilizer Rate for Corn
Author(s) -
Scharf Peter C.,
Kitchen Newell R.,
Sudduth Kenneth A.,
Davis J. Glenn,
Hubbard Victoria C.,
Lory John A.
Publication year - 2005
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/agronj2005.0452
Subject(s) - fertilizer , agronomy , yield (engineering) , mathematics , grain yield , crop , agricultural engineering , environmental science , biology , physics , engineering , thermodynamics
Applying only as much N fertilizer as is needed by a crop has economic and environmental benefits. Understanding variability in need for N fertilizer within individual fields is necessary to guide approaches to meeting crop needs while minimizing N inputs and losses. Our objective was to characterize the spatial variability of corn ( Zea mays L.) N need in production corn fields. Eight experiments were conducted in three major soil areas (Mississippi Delta alluvial, deep loess, claypan) over 3 yr. Treatments were field‐length strips of discrete N rates from 0 to 280 kg N ha −1 . Yield data were partitioned into 20‐m increments, and a quadratic‐plateau function was used to describe yield response to N rate for each 20‐m section. Economically optimal N fertilizer rate (EONR) was very different between fields and was also highly variable within fields. Median EONR for individual fields ranged from 63 to 208 kg N ha −1 , indicating a need to manage N fertilizer differently for different fields. In seven of the eight fields, a uniform N application at the median EONR would cause more than half of the field to be over‐ or underfertilized by at least 34 kg N ha −1 . Coarse patterns of spatial variability in EONR were observed in some fields, but fine and complex patterns were also observed in most fields. This suggests that the use of a few appropriate management zones per field might produce some benefits but that N management systems using spatially dense information have potential for greater benefits. Our results suggest that further attempts to develop systems for predicting and addressing spatially variable N needs are justified in these production environments.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom