Nitrogen fertilization rates in cereal production systems are generally determined by subtracting soil test N from a specified N requirement based on the grain yield goal, which represents the best achievable grain yield in the last 4 to 5 yr. If grain yield could be predicted in season, topdress N rates could be adjusted based on projected N removal. Our study was conducted to determine if the potential grain yield of winter wheat (Triticum aestivum L.) could be predicted using in‐season spectral measurements collected between January and March. The normalized difference vegetation index (NDVI) was determined from reflectance measurements under daytime lighting in the red and near‐infrared (NIR) regions of the spectra. In‐season estimated yield (EY) was computed using the sum of two postdormancy NDVI measurements (Jan. and Mar.) divided by the cumulative growing degree days (GDD) from the first to second reading. A significant relationship between grain yield and EY was observed true(R2=0.50,P>0.0001true) when combining all nine locations across a 2‐yr period. Our estimates of potential grain yield (made in early Mar.) differed from measured grain yield (mid‐July) at three sites where yield‐altering factors (e.g., late summer rains delayed harvest and increased grain yield loss due to lodging and shattering) were encountered after the final sensing. Evaluating data from six of the nine locations across a 2‐yr period, EY values explained 83% of the variability in measured grain yield. Use of EY may assist in refining in‐season application of fertilizer N based on predicted potential grain yield.

ABSTRACTand Ͼ10% in corn (Hilton et al., 1994). Fertilizer N losses due to surface runoff range between 1 and 13%In 2001, N fertilizer prices nearly doubled as a result of increased (Blevins et al., 1996; Chichester and Richardson, 1992 23% of the total N applied (Drury et al., 1996). In

Nitrogen (N) fertilization for cereal crop production does not follow any kind of generalized methodology that guarantees maximum nitrogen use efficiency (NUE). The objective of this work was to amalgamate some of the current concepts for N management in cereal production into an applied algorithm. This work at Oklahoma State University from 1992 to present has focused primarily on the use of optical sensors in red and near infrared bands for predicting yield, and using that information in an algorithm to estimate fertilizer requirements. The current algorithm, "WheatN.1.0," may be separated into several discreet components: 1) mid-season prediction of grain yield, determined by dividing the normalized difference vegetative index (NDVI) by the number of days from planting to sensing (estimate of biomass produced per day on the specific date when sensor readings are collected); 2) estimating temporally dependent responsiveness to applied N by placing non-N-limiting strips in production fields each year, and comparing these to the farmer practice (response index); and 3) determining the spatial variability within each 0.4 m 2 area using the coefficient of variation (CV) from NDVI readings. These components are then integrated into a functional algorithm to estimate application rate whereby N removal is estimated based on the predicted yield potential for each 0.4 m 2 area and adjusted for the seasonally dependent responsiveness to applied N. This work shows that yield potential prediction equations for winter wheat can be reliably established with only 2 years of field data. Furthermore, basing mid-season N fertilizer rates 2759 on predicted yield potential and a response index can increase NUE by over 15% in winter wheat when compared to conventional methods. Using our optical sensorbased algorithm that employs yield prediction and N responsiveness by location (0.4 m 2 resolution) can increase yields and decrease environmental contamination due to excessive N fertilization.

ABSTRACTand Ͼ10% in corn (Hilton et al., 1994). Fertilizer N losses due to surface runoff range between 1 and 13%In 2001, N fertilizer prices nearly doubled as a result of increased (Blevins et al., 1996; Chichester and Richardson, 1992 23% of the total N applied (Drury et al., 1996). In

season, while potentially costly, could significantly increase NUE. Current nitrogen use efficiency (NUE) of cereal crop productionRecently, methods for estimating winter wheat N reis estimated to be near 33%, indicating that much of the applied quirements based on early season estimates of N uptake fertilizer N is not utilized by the plant and is susceptible to loss from and potential yield were developed (Lukina et al., 2001; the soil-plant system. Supplying fertilizer N only when a crop response is expected may improve use efficiency and profitability. A response Raun et al., 2002). Remote sensing collected by a modiindex using harvest data was recently proposed that indicates the fied daytime-lighting reflectance-sensor was used to esactual crop response to additional N within a given year. This response timate early season plant N uptake. The estimate was index, RI Harvest , is calculated by dividing the average grain yield of the based on a relationship between NDVI and plant N uphighest yielding treatment receiving N by the average yield of a check take between Feekes physiological stage 4 (leaf sheaths treatment (0 N). Although theoretically useful, RI Harvest does not allow lengthen) and 6 (first node of stem visible) (Large, 1954; for in-season adjustment of N application. The objective of this work Stone et al., 1996; Solie et al., 1996). The NDVI was was to determine the relationship between RI Harvest and the response calculated using the following equation:index measured in-season (RI NDVI ) using the normalized difference vegetative index (NDVI). Research was conducted in 23 existing field NDVI ϭ [(NIR ref /NIR inc ) experiments in Oklahoma. Each field experiment evaluated crop re-Ϫ (Red ref /Red inc )]/[(NIR ref /NIR inc )sponse to varying levels of preplant N. At Feekes growth stages 5, 9, and 10.5, RI Harvest was accurately predicted using RI NDVI (r 2 Ͼ 0.56).

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Crop yield level and nitrogen (N) responsiveness influence the demand for fertilizer. If they were found to be unrelated, this would justify using a combination of both for determining fertilizer N requirements. Failure to understand the independence of crop response to N and yield level has led to confusion as to what theory is appropriate for making N fertilizer rate recommendations. The sufficiency approach applies a fixed rate of N at a computed sufficiency level, regardless of yield potential. Alternatively, mid-season optical sensor estimates of yield potential and crop response to additional N provide a physiological basis to estimate N removal and a biologically based N application rate. This study investigated the relationship between grain yield and response to N in long-term wheat and corn experiments. No relationship between response to N and grain yield was found. There was also no relationship between yield and year at two of three sites. Finally, there was no relationship between response to N and year at any site. Because yield and response to N were consistently independent of one another, and as both affect the demand for fertilizer N, estimates of both should be combined to calculate realistic in-season N rates.

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