Decisions concerning optimum rates of fertilization directly or indirectly involve fitting some type of model to yield data collected when several rates of fertilizer are applied. Although several different models are commonly used to describe crop yield response to fertilizers, it is seldom explained why one model is selected over others. The objective of the work reported here was to compare and evaluate several models (linear‐plus‐plateau, quadratic‐plus‐plateau, quadratic, exponential, and square root) commonly used for describing the response of corn (Zea mays L.) to N fertilizer. The evaluation involved 12 site‐years of data, each having 10 rates of N appied preplanting. All models fit the data equally well when evaluated by using the R2 statistic. All models indicated similar maximum yields, but there were marked discrepancies among models when predicting economic optimum rates of fertilization. Mean (across all site‐years) economic optimum rates of fertilization as indicated by the various models ranged from 128 to 379 kg N ha−1 at a common fertilizer‐to‐corn price ratio. Statistical analyses indicated that the most commonly used model, the quadratic model, did not give a valid description of the yield responses and tended to indicate optimal rates of fertilization that were too high. The quadratic‐plus‐plateau model best described the yield responses observed in this study. The results clearly show that, especially amid increasing concerns about the economic and environmental effects of overfertilization, the renson for selecting one model over others deserves more attention than it has received in the past.

A soil test for improving N management is greatly needed in much of the Corn Belt. Relationships between yields of corn (Zea mays L.) grain and concentrations of nitrate in the surface l‐ft layer of soils when corn plants were 6 to 12 in. tall were studied across a total of 756 plots at several locations during 1985 and 1986 to evaluate the late‐spring soil test for nitrate. The time of sampling for this soil test represents a compromise between the need to sample late enough to reflect the effects of spring weather conditions on N availability but early enough so that supplemental N can be applied as a sidedressing if needed. A linear‐response‐and‐plateau (LRP) model showed that nitrate concentrations could explain 82% of the variability in relative yields (yields expressed as percentages of the highest yields observed within rotation‐site‐years) across all data collected. Although this model indicates that 21 ppm nitrate‐N in the surface l‐ft layer of soil is adequate to attain maximum yields, we suggest that a range of 20 to 25 ppm should be considered optimal. These findings indicate that this soil test offers great potential for improving N management in the Corn Belt. Amid mounting concerns that many farmers are applying more fertilizer than is desirable for environmental and (or) economic reasons, the most important use of the soil test may be to reduce excessive applications of fertilizer by showing when additional N is not needed.

Recent studies have shown good correlations between corn (Zea mays L.) yields and concentrations of NO3 in the surface 30‐cm layer of soil in late spring. Here we report additional correlations and evaluate the benefits of sampling to 60 cm instead of to 30 cm only. The study involved 45 site‐years (1346 plot‐years) of data collected in 1987, 1988, and 1989 in Iowa. Weather conditions were dryer than normal, with a severe drought occurring in 1988. Each site‐year included seven to 10 rates of N applied before planting. Samples representing the surface 0‐ to 30‐cm and the 30‐ to 60‐cm layers of soils were collected when corn plants were 15 to 30 cm tall. Nitrate concentrations in these soil layers were correlated with grain yields. The deeper sampling slightly improved the correlations between grain yields and soil NO3 concentrations, but the advantage was probably not great enough to justify the costs of the deeper sampling. The critical concentration of NO3 was 23 to 26 mg N kg−1 in the surface 30‐cm layer of soil and 16 to 19 mg N kg−1 in the surface 60‐cm layer of soil. Overall, the results support the idea that a soil test based on concentrations of NO3 in the surface 30‐cm layer of soil when corn plants are 15 to 30 cm tall has great promise for improving N management during corn production.

The N status of corn (Zea mays L.) often is evaluated by analyzing the leaf opposite and below the primary ear at silking. The objective of this study was to assess the reliability of leaf N concentration as an indicator of the N status of corn. The study involved 12 site‐years of data, each having 10 rates of N applied preplant. Leaf N concentrations tended to increase with increases in rates of N application and with increases in grain yields. Because optimal and above‐optimal rates of N application resulted in similar leaf N concentrations, however, there was little basis for defining a critical concentration of N (i.e., a concentration of N indicative of adequate but not excessive N availability). The relationships between leaf N concentrations and adjusted rates of N fertilization (i.e., rates of fertilization adjusted relative to economic optimum) were statistically significant, but they had low predictability. For example, only 16% of the variability in leaf N concentrations could be explained by a model that considered only data between ± 100 lb N/acre from economic optimum. Overall, the results indicate that leaf N concentrations are not a sensitive indicator of the N status of corn.

Grain analysis is frequently used to determine the N status of corn (Zea mays L.). The objective of this study was to assess the reliability of N concentration in grain as an indicator of the N status of corn. The study involved 12 site‐years of data, each having 10 rates of N applied preplanting. Nitrogen concentrations in grain tended to increase with increases in rates of N application. Nitrogen concentrations also tended to increase with increases in relative yields, but the relationships often were C‐shaped, and there was no basis for establishing critical N concentrations. The relationships between N concentrations in grain and adjusted rates of N fertilization (i.e., rates of fertilization expressed relative to economic optimum) were statistically significant, but they had low predictability. For example, only 19% of the variability in N concentrations could be explained by a model that considered only data between ± 100 kg N ha−1 from economic optimum rates of fertilization. Only 1% of the variability could be explained by a model that considered only data between ±50 kg N ha−1 from economic optimum. These observations indicate that, especially where the availability of N is near or above optimal, N concentration in grain does not provide a reliable indicator of the N status of corn.