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Published online 17 August 2005
Published in Agron J 97:1342-1351 (2005)
DOI: 10.2134/agronj2005.0051
© 2005 American Society of Agronomy
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Nitrogen Management

Interactions of Nitrogen, Weather, Soil, and Irrigation on Corn Yield

Nathan E. Derbya,*, Dean D. Steelea, Jeff Terpstraa, Raymond E. Knightonb and Francis X. M. Caseya

a Dep. of Stat., North Dakota State Univ., Fargo, ND 58105
b USDA-CSREES, Washington, DC 20250

* Corresponding author (Nathan.Derby{at}ndsu.edu)

Received for publication February 14, 2005.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Numerous factors that affect corn yield in the Northern Great Plains are not considered in current N fertilizer recommendations. A linear model to describe the interactions of N fertility, weather, soil, and irrigation on corn (Zea mays L.) yield was developed for a 6-yr field study in southeastern North Dakota. Varying rates of postemergence fertilizer N were applied to plots in four quadrants of a sprinkler-irrigated field. Four irrigation-scheduling methods varied by year (Y) and quadrant (Q). Grain yield, stover yield, and N uptake response to a covariate (soil N plus starter fertilizer N), N treatment (Nt), Q, Y, irrigation treatment (I), previous irrigation treatment (P), and the two-way interactions that included Nt, were investigated using standard regression techniques. Yield increased significantly with Nt up to a rate of 135 kg N ha–1 for most Y, Q, and I. Average yearly yield was adversely affected by cool climatic conditions in 2 yr. Soil conditions in two quadrants resulted in a 1.25 Mg ha–1 average annual yield reduction compared with the other quadrants. An irrigation scheduling method utilizing a water balance algorithm resulted in higher yields compared with the other scheduling methods. The interactions of Nt with Q, Y, and I were significant. Optimized total N rates (the sum of soil nitrate N, starter N, and postemergence Nt) derived from quadratic-linear plateau analysis varied (232–374 kg N ha–1) with Y, Q, and I and averaged 295 kg N ha–1. Soil properties, soil moisture availability, and yearly climatic factors should be considered when making fertilizer recommendations.

Abbreviations: CGDD, cumulative growing degree days • ET, evapotranspiration • I, irrigation treatment • NE, northeast • Nt, nitrogen treatment • Ntot, total nitrogen • NW, northwest • P, previous irrigation treatment • Q, quadrant • SE, southeast • SW, southwest • Y, year


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
MAXIMUM CORN GRAIN YIELDS are influenced by a number of factors, including N fertility, growing season conditions, water availability, and soil conditions. Studies investigating N fertility rates have shown that corn yields increase in a quadratic fashion with increased applied N to a plateau level (Cerrato and Blackmer, 1990). Maximum yields have been observed at N rates less than the maximum rates applied in various studies (Onken et al., 1985; Schlegel and Havlin, 1995). Albus and Moraghan (1995) found marked yield responses to N fertilizer in a number of short-season corn hybrids.

In the Northern Great Plains, favorable growing conditions are important due to the short growing season. Derby et al. (2004) found that yield was adversely affected by cool growing season conditions. Similarly, Swan et al. (1987) reported decreased corn yields with insufficient cumulative growing degree days (CGDD). Wienhold et al. (1995) found 60% greater yields with increasing N fertility when the growing season was warm but no difference in yields with increased N when the season was cool.

Soil moisture status is also important in maintaining maximum corn yields, and maintaining optimal soil moisture is facilitated by irrigation in areas of coarse-textured soils. Stegman (1982) found that yields decreased with increased water stress, but if the water stress is limited to one portion of the growing season and irrigation replenishes the profile moisture, high yields can still be achieved. Some research has indicated that crop N requirements are lower for irrigated versus rainfed soils (Oberle and Keeney, 1990), unless rainfed condition results in water stress.

Current recommendations for corn fertilization in North Dakota indicate that 21.4 to 26.8 kg of N is needed per Mg of corn grain yield, which is equivalent to 1.2 to 1.5 lb of N per standard (56 lb) bushel of corn in conventional units (Dahnke et al., 1992; Berglund and McWilliams, 1999). Typically, the N recommendations are adjusted for soil test N, date of sampling, and previous crop. Current nutrient recommendations, which are based on many site-years of yield response curves, make no adjustments for variation in weather conditions, soil type, and management factors on a site-specific or year-specific basis (Dahnke and Olson, 1990).

The objective of this study was to determine the yield response of corn in the Northern Great Plains to the combined effects of increased applied N fertilizer, irrigation scheduling method, soil type, and yearly climatic variation.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Field Experiments
For the 1990 through 1995 growing seasons, a field-scale study of irrigation and fertilizer N management effects on groundwater quality was conducted near Oakes, ND, USA. Meteorological data were measured at an automated weather station approximately 2.4 km from the site. The weather station was located at 46°04' N, 98°06' W, and 401 m elevation and is part of the North Dakota Agricultural Weather Network (NDAWN) (Enz et al., 1997). Growing degree units were calculated from NDAWN data based on a lower limit of 10°C and an upper limit of 30°C (Gilmore and Rogers, 1958). Rainfall and irrigation amounts were measured directly at the field site. This site was 64 ha, of which 53.4 ha was irrigated by a sprinkler (center pivot) irrigation system. The soil at the site (Fig. 1) was primarily Hecla loamy fine sand (sandy, mixed, frigid Oxyaquic Hapludoll) on the south portion of the field and Wyndmere fine sandy loam (coarse-loamy, mixed, superactive, frigid Aeric Calciaquoll) and Stirum fine sandy loam (coarse-loamy, mixed, superactive, frigid Typic Natraquolls) on the north portion of the field.



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  		Fig. 1. Order 1 soil survey, plot locations, and quadrant boundaries on research quarter section. Soil electrical conductivity (dS m–1) is indicated by dashed contour lines.

 
The field was divided into four quadrants (denoted NW = northwest, NE = northeast, SW = southwest, and SE = southeast) to accommodate differences in soil types and for four different irrigation scheduling method purposes. Irrigation treatments were assigned to quadrants every year based on a statistical design (Cochran and Cox, 1957) in which years and quadrants were the dimensions of a modified Latin square. Steele et al. (2000) described the irrigation aspects of the experiment in detail, including complete descriptions of the treatments, irrigation scheduling criteria, application depths targeted for each irrigation event (32 mm per event for Method A, B, and D and 25 mm per event for Method C), and seasonal (1991–1995) irrigation totals (averaged 136, 125, 106, and 122 mm for Methods A, B, C, and D, respectively). The irrigation scheduling methods were (A) irrigation when tensiometer readings at 0.30-m depth reached 40 ± 10 kPa and/or crop water stress index (CWSI) values reached 0.25 ± 0.05; (B) irrigation based on a water balance algorithm (Stegman and Coe, 1984) that allowed 60 to 70% estimated depletion of plant-extractable water before the first irrigation, full evapotranspiration (ET) replacement from the first irrigation through the blister kernel (R2) stage, followed by irrigation whenever soil moisture depletion reached 60 to 70% for the period R2 through maturity; (C) irrigation based on a water balance algorithm that replaced 80% of estimated crop ET, i.e., the same criteria as Method B, but each irrigation was 20% smaller; and (D) irrigation based on CERES–Maize crop growth model (Jones and Kiniry, 1986) predictions of plant-extractible soil water (PESW), i.e., irrigations occurred when the estimated PESW was at 60 to 70% depletion. Steele et al. (1994) described the CWSI method used in this study. Analysis of irrigation efficiency values showed no significant differences due to irrigation methods (Steele et al., 2000). Irrigation events were applied by on-site research personnel.

Tillage, planting, cultivation, pesticide application, and starter fertilization were done by the farmer cooperator. Spring seedbed preparation tillage was done with a combination disk/chisel plow implement, usually two times before planting. The corn was planted in rows spaced 76.2 cm apart at a seed density of approximately 74000 seeds ha–1. Starter fertilizer was applied with the seed during the planting operation. Weed control was a combination of between-row cultivation at about V6 and spraying of selective herbicides at appropriate times. Pesticide applications were done on an as-needed basis to control insect infestations.

The research team scheduled the irrigations and managed the postemergence fertilization of 72 small plots. These plots were established along two transects within the irrigated portion of the field (Fig. 1). Each plot was 9.1 m (12 rows) wide by 18.3 m long, and the plots were arranged in groups of six plots with three six-plot groups per field quadrant. The location of each plot area was referenced by angle and distance from fixed points for identification in subsequent years. The fertilizer treatments within each block of six plots ranged from a reference regime of zero applied N to what was considered a nonlimiting regime, with four intermediate regimes. Treatments were designated as Nt1 = 0 kg N ha–1, Nt2 = 45 kg N ha–1, Nt3 = 90 kg N ha–1, Nt4 = 135 kg N ha–1, Nt5 = 180 kg N ha–1, and Nt6 = 225 kg N ha–1, not including the starter N. These N application treatments were randomly arranged within each block at the outset of the study. Each Nt was applied to the same plot for each year of the study to facilitate a "mining down" of residual soil N at the lower, yield-limiting rates, i.e., plots were not annually re-randomized.

Postemergence fertilizer Nt was applied in three splits, starting when the corn reached the six-leaf stage (V6) (Hanway, 1966, p. 3–18). Dates of planting, spring soil test N, fertilizer application, and starter fertilizer rates are shown in Table 1. The amount of starter fertilizer varied in 1994 and 1995 because the farmer cooperator planted the field. The fertilizer N amounts, forms, and application methods for each Nt are summarized in Table 2. The last two applications of N were applied by hand as urea because of lack of equipment and the practicality of injecting urea ammonium nitrate (UAN) at an advanced stage of corn growth. Soil samples for N were taken from each plot area at the four-leaf stage to a depth of 91 cm.


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  		Table 1. Planting, harvest, and fertilizer split dates; average spring soil N; and starter fertilizer rates for plots.

 

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  		Table 2. Amounts, forms, and application methods for fertilizer N split applications.

 
After the corn reached physiological maturity (R6), two adjacent 4.6-m rows were hand-harvested from each plot. All ears were harvested, and the whole plants were weighed to calculate stover yield. The ears were dried at 60°C and then shelled. The dry grain was weighed, and yields were calculated on a 15.5% moisture content, wet basis. Grain and stover subsamples were ground and analyzed for Ntot by the Kjeldahl method (Bremner and Mulvaney, 1982).

Data Analysis
Linear model techniques were used to analyze the data. The model for the main effects with two-way interactions involving Nt is

[1]
where the response G was determined for corn grain yield, stover yield, grain N content, grain N uptake, stover N content, stover N uptake, or total plant N uptake; µ is the overall effect; X is the covariate spring soil N plus starter fertilizer N; Nt1, Nt2,..., Nt6 represent the effects of the six N treatments 0, 45, 90, 135, 180, and 225 kg N ha–1, respectively; I1, I2, I3, and I4 represent the effects of the four irrigation scheduling methods A, B, C, and D, respectively; P1, P2, P3, and P4 represent the effects of the previous year's four irrigation scheduling methods A, B, C, and D, respectively; Y1, Y2,..., Y6 represent the effect of years 1990–1995, respectively; Q1, Q2, Q3, and Q4 represent the effect of the four quadrants SW, SE, NW, and NE, respectively; (NtI) is the interaction effect of the six N treatments and four irrigation treatments; (NtP) is the interaction effect of the six N treatments and the four previous-year irrigation treatments; (NtY) is the interaction effect of the six N treatments and the 6 yr; (NtQ) is the interaction effect of the six N treatments and the four quadrants; and {epsilon}ijklm represents random error. This model contains all of the possible two-way interaction terms involving N treatment. We note that some unforeseen linear dependencies in our design prevented us from fitting a model with other two-way (and higher order) interactions. However, since N was the main focus, two-way interactions are fairly easy to interpret, the model R2 is high, and no violations of statistical assumptions were identified (via a residual analysis), we feel that this is the most appropriate model for this data set. Analyses were performed using S-Plus statistical software (MathSoft, 1999).

The yield response to Ntot (the sum of soil nitrate N, starter N, and Nt) was modeled with the SAS NLIN procedure (Ihnen and Goodnight, 1985) and is described by the following quadratic-plus-plateau model:

[2]

[3]
where Y is grain yield (Mg ha–1); X is the sum of applied and soil N (kg ha–1); a, b, and c are coefficients obtained by fitting this model to the LSMEAN yield values; C is the critical or optimized rate of fertilization (kg ha–1); and YP is the plateau yield (Mg ha–1). The values of C and YP are obtained from the fitted model. The model (Eq. [2] and [3]) was used to determine the optimized N rate (the N at which maximum yield was achieved) for years, quadrants, and irrigation scheduling method. Since the plateau yield was considered to be the maximum yield, the value of C for maximum yield was calculated by equating the first derivative of the response equations (Eq. [2]) to zero and solving for X (Eq. [4])

[4]
This is the point C at which the quadratic and plateau portions of the curve meet and represents the optimized N rate for maximum yield but not necessarily maximum economic return, as will be discussed later.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
While corn grain yield is the focus of the discussion, the effects on the response variables grain N content and N uptake, stover yield, stover N content and N uptake, and total plant N uptake are also presented in the tables to illustrate the robustness of the statistical model used. However, the discussion regarding those parameters will be limited. Discussion of Nt rate pertains to postemergence N application and does not include the N applied as starter or soil test N. We note that although the different Nts varied in timing, form of fertilizer, and application method (Table 2), we feel that this type of split application resulted in the best crop utilization of the applied N by reducing the risk of leaching losses compared with if all of the N had been applied at once.

Analysis-of-covariance summary information is listed in Table 3. The residual standard error for corn grain yield was 1.06 Mg ha–1 on 340 degrees of freedom. The R2 value for the model was 0.91, i.e., 91% of the yield response is explained by Eq. [1]. The F statistic for the model was 36.66 on 90 and 340 df, resulting in p < 0.001. Upon further examination, all factors in Eq. [1] for corn grain yield were found to be significant at {alpha} = 0.05 or lower except the NtP interaction and the covariate soil test N plus starter fertilizer N. High R2 values and similar significance of terms was observed for the other response variables grain N content, grain N uptake, stover yield, stover N content, stover N uptake, and total plant N uptake. This indicates that the model was appropriate for this study.


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  		Table 3. Analysis-of-covariance summary for irrigated corn grain yields, grain N percentage, grain N uptake, stover yield, stover N percentage, stover N uptake, and total plant N uptake.

 
Main Effects
Corn grain yields, grain N content and N uptake, stover yield, stover N content and N uptake, and total plant N uptake in this study were influenced significantly by N treatment (Nt), soil properties or quadrant (Q), yearly climatic variations (Y), irrigation scheduling method (I), and the previous year's irrigation scheduling method (P). Corn grain yield, stover yield, plant N content, and N uptake as affected by each main effect are shown in Table 4. Significant differences of yield means within response parameters Nt, I, P, Y, and Q were indicated in the instances where the two-way interactions of I, P, Y, and Q with Nt were not significant (Table 3). If there was a significant interaction, response parameter means could not be compared for that main effect. Further discussion about significant differences within interactions will follow.


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  		Table 4. Corn grain yield (and other response variables) means and statistical groupings for main effects.

 
With regard to corn grain yield, previous irrigation treatment (P) was the only main effect of which treatment means could be compared since the NtP interaction was not significant (Table 3). Corn grain yield varied significantly by P with a previous year's irrigation treatment of C resulting in the highest yield. The effect of P resulted in an average yield range of 1.08 Mg ha–1.

Comparison of response variable means (other than grain yield due to significant interaction) for I treatments indicated that Irrigation Treatments B and C were not significantly different for all variables except grain N content and resulted in the highest values for grain N content and uptake and stover yield, N content, and N uptake. Response variable means within previous irrigation treatment (P) showed that Treatment C resulted in significantly higher values for all variables (Table 4). Treatments B and C were based on the same water balance algorithm with water applications being 20% smaller for C.

Comparison of means for grain N content and uptake and stover yield, N content, and N uptake for main effect Q showed a clear separation between the two north quadrants, NE and NW, and the two south quadrants, SE and SW (Table 4). Quadrants SE and SW had higher values for all variables. The quadrant effect was basically a soil effect, with less productive salt-affected soils on the northern portion of the field. Lower productivity was a result of low water permeability and sodium effects on the Stirum soil and the higher salinity in the northern portion of the field [electrical conductivity (EC) = 3.0–3.5 dS m–1] compared with the south (EC = 2.0–2.5 dS m–1) (Fig. 1). Although it would appear that the soil type is not the same for all plots within some quadrants (Fig. 1), we maintain that it is very difficult to delineate exactly where a change in soil type actually occurs in the field. Experience has shown us that the productivity of the soil on the NE and NW quadrants was much lower than the SE and SW. This was confirmed by the statistically significant lower mean values in the north versus the south Q treatments for all variables, a result of reduced plant vigor. Lower plant N uptake may result in excess nitrate leaching and groundwater contamination, not to mention the reduced economic return due to overapplication of fertilizer. Yield potential of different areas of a field needs to be considered when making N fertilizer recommendations and may warrant variable-rate applications.

Two-Way Interactions
The interactions of Nt with the other main effects were also investigated. The two-way interactions of Nt with Y, Q, and I are shown in Tables 5, 6, and 7, respectively. The interaction of Nt with P is not shown because NtP was not significant for any of the response variables except stover N content.


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  		Table 5. Treatment means and statistical groupings for the N x year interaction.

 

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  		Table 6. Treatment means and statistical groupings for the N x quadrant (NtQ) interaction.

 

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  		Table 7. Treatment means and statistical groupings for the N x irrigation treatment (NtI) interaction.

 
There was a significant interaction between the Nt and Y treatments. For the NtY interaction (Table 5), the grain and stover yield increased significantly with increased Nt up to 135 kg ha–1 in most years, with grain yield increases observed only to Nt of 45 and 90 kg ha–1 in 1990 and 1993, respectively. There were only slight increases in yield when the Nt was increased to 180 kg ha–1. However, N accumulation in the plant did show some increases at higher N rates. There was no significant difference between the yields at 135 and 180 or 225 kg N ha–1 for any year except 1995.

In 1990, the first year of the study, grain and stover yield had the least response to additional applied Nt, and grain yield did not vary significantly for Nt higher than 45 kg ha–1. This was caused by increased availability of soil N resulting from mineralization from the initiation of irrigation in 1989 (Casey et al., 2002). A similar lack of response to fertilizer N was observed by Onken et al. (1985) during a year when the soil had high residual N. The greatest responses to Nt were observed in 1991, 1994, and 1995, which were normal growing seasons (CGDD = 1245, 1255, and 1198°C, respectively). Yield response to Nt was less in 1992 and 1993, which were cool, wet years and had the lowest CGDD (1092 and 982°C, respectively). Yield was highly correlated with CGDD from emergence to harvest (r = 0.94) and was dramatically lower in 1992 and 1993. Yields in 1992 were depressed as a result of cooler-than-normal temperatures while 1993 yields were low because of cool weather and a frost in September before the crop matured (Derby et al., 2004). Interestingly, stover N content and stover N uptake were highest across all Nt in 1993. Although early-season temperature was a very important component of the yearly weather effect, Y was likely a combination of many factors. Derby et al. (2004) considered both temperature and solar radiation when calculating CGDD and ET values for midseason N fertility management. Variable precipitation patterns would have also affected crop growth because, even though the site was irrigated, the irrigation regimes were designed to allow soil moisture deficits, so precipitation variation was still an important factor in determining corn yield. This analysis indicated that interannual variability caused by adverse weather conditions can result in substantial yield reductions by shortening the growing season and preventing maturity. Hence, the use of a static yield response curve for N recommendations that averages over interannual variability could result in overfertilization because of unrealized yield goals in unseasonably cool years. If weather conditions warrant, reduced early-season fertilization with a midseason adjustment may be an alternative to current fertilizer management schemes, and Derby et al. (2004) provide a model to adjust in-season rates based on CGDD or ET for the Northern Great Plains.

Although there was definite separation in yields between the north and south portions of the field (NtQ interaction), maximum yield was also obtained at the 135 to 180 kg N ha–1 treatment range with no significant difference in yields between those rates within each quadrant (Table 6). Although response of yield to Nt was basically identical for the quadrants, it was the magnitude of the response that differed between the south and north quadrants. As discussed above, the SW quadrant had the highest yields overall, and the interaction shows that the yield increased significantly until an Nt rate of 135 kg N ha–1. In comparison, the significant yield increases for the NW quadrant were also observed until an Nt rate of 135 kg ha–1, but the yield was 1.83 Mg ha–1 less than on the SW quadrant.

Mean yields for the N treatment–irrigation treatment interaction (NtI) are shown in Table 7. Yield was again near maximum at 135 kg ha–1 with no significant difference between the 135 and 180 kg ha–1 Nt rates except for Irrigation Treatment D. The NtI interaction showed that no significant increases in grain yields were measured above Nt rates of 135 kg N ha–1, except for D where the maximum yield was obtained at 180 kg N ha–1. Irrigation Treatment B had the highest yields across all Nt rates. This indicated that Irrigation B may have been better suited to providing sufficient amounts of water during critical periods of corn growth when the rate of nutrient uptake was also increasing. The NtP interaction was not significant for any of the response variables; hence, pair-wise comparisons within previous irrigation scheduling methods are not presented.

Optimized Nitrogen Rates and Recommendations
The discussion in this section focuses on Ntot rate at maximum corn grain yields for Y, Q, and I. The Ntot rate for these calculations and yield response curves is the sum of soil nitrate N, starter N, and the postemergence Nt. In general, yield response to Ntot followed a quadratic-plus-plateau relationship (Eq. [2] and [3]). This typical yield response to applied N, often referred to as the Law of Diminishing Returns (Willcox, 1949), has been reported extensively (Cerrato and Blackmer, 1990; Dahnke and Olson, 1990; Vanotti and Bundy, 1994; Schlegel and Havlin, 1995). The quadratic-plus-plateau nonlinear models for each year, quadrant, and irrigation treatment indicated that there were wide ranges of Ntot rates that optimized yield (Fig. 2) . The average optimized Ntot rate for all observations for the study period was 295 kg N ha–1. The range of optimized Ntot rates between years (Fig. 2a) was from 232 kg ha–1 in 1993 to 296 kg ha–1 in 1994. Note that the low-yielding years, 1992 and 1993, did not vary much from the other years in terms of optimized Ntot rate.



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  		Fig. 2. Quadratic-plus-plateau response curves for (a) years, (b) quadrants, and (c) irrigation treatments. Optimized total N rates at 98% of maximum yield are indicated by vertical dashed lines. Maximum yields are indicated by large circles. Heavy solid and dashed lines are for all yield observations over the course of the study. The current North Dakota State University recommendation (dashed-dotted line) is based on 21.4 kg of N per Mg of corn grain yield, which is equivalent to 1.2 lb of N per standard (56 lb) bushel of corn.

 
The highest-yielding quadrants (SE and SW) had the lowest average optimized Ntot rates of 291 kg ha–1 while the lowest-yielding quadrants (NE and NW) had the highest average optimized Ntot rate of 334 kg ha–1 (Fig. 2b). Although the maximum yields varied little between irrigation treatments, Irrigation Treatment D had a higher optimized Ntot rate than the other treatments even though all irrigation treatments had similar maximum yields (Fig. 2c).

To reduce fertilizer N inputs while maintaining near maximum yields, we can consider N application for 98% of maximum yield (Dahnke and Olson, 1990). For example, the optimized Ntot rate considering all observations for the study was 295 kg N ha–1 at the maximum yield of 9.93 Mg ha–1 (Table 8). Compare that to a yield of 9.73 Mg ha–1 (98% of 9.93 Mg ha–1) where the corresponding Ntot rate for all observations in Fig. 2 is 251 kg ha–1. That is a 15% reduction in applied N for a 2% reduction in yield. Economically, a producer would have a net increase of approximately $8.80 ha–1 assuming a corn price of $78.57 Mg–1 ($2.00 bu–1) and fertilizer N cost of $0.55 kg–1 ($0.25 lb–1). An even higher return could be calculated if application costs are considered. Environmentally, the difference of 44 kg N ha–1 would not be available for surface or groundwater contamination.


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  		Table 8. Comparison of optimized N rates at maximum yields to N rates at 98% of maximum yield and corresponding change in per-hectare income when fertilizing for 98% of maximum yield.

 
Current N recommendations are adequate some years because they were developed over many site-years. This is confirmed by the agreement of the current recommendation to the yield response curve for 1994 in Fig. 2a. The current recommendation line [0.0214 kg of N per kg of corn grain yield, which is equivalent to 1.2 lb N per standard (56 lb) bushel of corn] does come close to the point of 98% of maximum yield for 1994. However, the current recommendation fails by over-recommending N in cool, wet years (1992 and 1993) when there is a need to optimize management to avoid environmental degradation. The comparisons are similar for quadrants (Fig. 2b) and irrigation treatments (Fig. 2c) where the current recommendation fits the response curves adequately at lower yields but would result in overfertilization at higher yield goals. Given the current environmental issues, we should not continue to recommend the highest N rates every year assuming the growing conditions will allow for maximum yield potential.

It is clear that there was not simply one optimized Ntot rate for maximum corn yield but a range, depending on weather conditions for a given year, timely water applications, and soil properties. Research of this nature provides information that can be used to develop a more robust fertilizer N recommendation scheme that takes into account yearly weather (Derby et al., 2004), soil properties, and soil moisture availability. It may not be environmentally wise to continue N recommendations based on a static yield response curve and assuming that maximum yield will be achieved every year. Based on readily available information such as early- to midseason CGDD and soil properties, producers can modify their practices to maximize profits in good years and minimize environmental degradation in poor years.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Nitrogen fertility has a major role in maintaining maximum corn grain yields; however, a number of other factors limit yields even when N fertility is optimal. In this study of corn yield in the Northern Great Plains, USA, postemergence N rates greater than 135 kg N ha–1 did not significantly increase yield. Based on quadratic response curves, 98% of maximum yield was realized at a Ntot rate of 251 kg N ha–1 over the entire study period but ranged between 190 and 318 kg N ha–1 depending on year, quadrant, and irrigation scheduling method. Areas of the field with sodium- and salt-affected soils had significantly lower productivity. Similarly, cool, wet years had lower productivity than years with warm growing seasons. Timely water applications scheduled using a water balance algorithm and in-season soil moisture corrections also maintained high yields compared with other irrigation scheduling methods. Research of this nature should be used to modify existing fertilizer recommendation methods to include adjustments for low-productivity soil, proper irrigation management, and midseason adjustments based on current growing season conditions to minimize costs and water quality impacts.


   ACKNOWLEDGMENTS
 
The research was supported by North Dakota Agricultural Experiment Station Project 5041 and by the U.S. Department of Interior, Bureau of Reclamation. Use of equipment and trade names does not constitute endorsement by North Dakota State University or the U.S. Bureau of Reclamation; names are provided for information only. The authors gratefully acknowledge the assistance of Dale Coe, Walter Albus, James Moos, Wade Kuehl, and Dale Esser for field operations.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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K. Girma, S. L. Holtz, D. B. Arnall, L. M. Fultz, T. L. Hanks, K. D. Lawles, C. J. Mack, K. W. Owen, S. D. Reed, J. Santillano, et al.
Weather, Fertilizer, Previous Year Yield, and Fertilizer Levels Affect Ensuing Year Fertilizer Response of Wheat
Agron. J., November 6, 2007; 99(6): 1607 - 1614.
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N. E. Derby, F. X. M. Casey, and D. W. Franzen
Comparison of Nitrogen Management Zone Delineation Methods for Corn Grain Yield
Agron. J., February 6, 2007; 99(2): 405 - 414.
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A. R. Kemanian, C. O. Stockle, and D. R. Huggins
Estimating Grain and Straw Nitrogen Concentration in Grain Crops Based on Aboveground Nitrogen Concentration and Harvest Index
Agron. J., January 1, 2007; 99(1): 158 - 165.
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J. P. Schmidt, N. Hong, A. Dellinger, D. B. Beegle, and H. Lin
Hillslope Variability in Corn Response to Nitrogen Linked to In-Season Soil Moisture Redistribution
Agron. J., January 1, 2007; 99(1): 229 - 237.
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