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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #171380
Title: OPTIMAL N RATE FOR CORN: SPATIAL VARIABILITY, GEOSTATISTICS, AND PREDICTION

Author
item SCHARF, P - UNIV OF MO
item Kitchen, Newell
item Sudduth, Kenneth - Ken
item DAVIS, J - USDA-NRCS
item HUBBARD, V - UNIV OF MO
item LORY, J - UNIV OF MO

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 7/28/2004
Publication Date: 10/1/2004
Citation: Scharf, P.C., Kitchen, N.R., Sudduth, K.A., Davis, J.G., Hubbard, V.C., Lory, J.A. 2004. Optimal N rate for corn: Spatial variability, geostatistics, and prediction [abstract] [CD-ROM]. ASA-CSSA-SSSA Annual Meeting Abstracts.

Interpretive Summary:

Technical Abstract: Applying only as much N fertilizer as is needed by a crop has economic and environmental benefits. Research has shown that fields can differ substantially in their economically optimal N rate (EONR). Evidence is mounting that EONR can also vary substantially within fields. Our objective was to characterize spatial variability of EONR in production corn fields and evaluate methods for predicting EONR spatially. Eight experiments were conducted in three major soil areas over three years. Treatments were field length strips of discrete N rates from 0 to 280 kg N/ha. Yield response functions were fitted and used to calculate EONR for each 20 m section. 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. High within field variability in EONR was also observed. Semivariograms suggest that spatial dependence of EONR is different from one field to another. This implies that the scale of optimal N management may be different between fields. Neither yield patterns nor zone soil nitrate samples were able to serve as a basis for improved N management. At this writing, analyses are not final for soil electrical conductivity or crop color (measured in either aerial photographs or with a vehicle based spectral radiometer) as predictors of EONR. The variability in EONR that we observed justifies further attempts to predict EONR spatially within fields.