|Sudduth, Kenneth - Ken|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/20/2004
Publication Date: 3/1/2005
Citation: Scharf, P.C., Kitchen, N.R., Sudduth, K.A., Davis, J.G., Hubbard, V.C., Lory, J.A. 2005. Field-scale variability in optimal nitrogen fertilizer rate for corn. Agronomy Journal. 97:452-461.
Interpretive Summary: Farmers are interested in knowing how much nitrogen (N) fertilizer to apply to crops, taking into account both annual climate differences as well as within-field soil differences. There are two compelling reasons generating this interest. First, N fertilizer prices have greatly increased in recent years. This causes many farmers to worry that they are applying too much N. Concurrently, they don't want to under-apply N fertilizer, because it is very important to yield. For example, most U.S. corn grain yield would be 40 to 70% less without N fertilizer. Secondly, possible loss of N in fertilizer or manure also causes environmental concern. Nitrogen from agricultural sources has been shown to affect streams, rivers, and the ocean. Therefore, both farmers and the public want N to be managed so that crop needs are met but losses to the environment are minimal. This study was done to see how variable corn N fertilizer need was among and within full-sized production corn fields. For eight different fields spanning three growing seasons, the amount of N that was needed to grow corn was found to be highly variable among fields. Some fields needed on average only 50 lbs of N per acre, while others needed on average about 200 lbs of N per acre. This showed a need to manage N fertilizer differently for different fields. However, even within each field the correct amount of N to apply greatly varied. Inside all eight fields, some places needed at least 100 lbs of N per acre more than other places. In a few fields, some areas needed almost no N while other areas needed more than 200 lbs of N per acre. Our results strongly support further research on N management systems that address spatially variable N needs. The results of this study will be used to evaluate both the economic and environmental benefits for different management approaches for applying N fertilizers. Farmers will benefit because they can reduce excess N applications, which with increasing N fertilizer cost, should save money. If fertilizer can be better matched with crop need, N loss to lakes and streams will be reduced and the environment will be improved, which benefits the general public.
Technical Abstract: Applying only as much N fertilizer as is needed by a crop has economic and environmental benefits. Small plot research has shown that fields can differ substantially in their need for N fertilizer. 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) N need in production corn fields. Eight experiments were conducted in three major soil areas (Mississippi delta alluvial, deep loess, claypan) over three years. Treatments were field-length strips of discrete N rates from 0 to 280 kg N/ha. 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 highly variable within fields. Median optimal N fertilizer rates for individual fields ranged from 63 to 208 kg N/ha, indicating a need to manage N fertilizer differently for different fields. In only one field was EONR for more than half of the field within 34 kg N/ha of the median EONR for the field. Coarse patterns of spatial variability in optimal N rate 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.