HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (11) Citing Articles via Google Scholar Google Scholar Articles by Inman, D. Articles by Reich, R. Search for Related Content PubMed Articles by Inman, D. Articles by Reich, R. Agricola Articles by Inman, D. Articles by Reich, R. Related Collections Maize Nutrient Management Nitrogen

Nutrient Uptake

Nitrogen Uptake across Site Specific Management Zones in Irrigated Corn Production Systems

^a Dep. of Soil and Crop Sciences, Colorado State Univ., Fort Collins, CO 80523-1170
^b Dep. of Forestry, Colorado State Univ., Fort Collins, CO 80523-1170

^* Corresponding author (rkhosla{at}colostate.edu)

Received for publication March 25, 2004.

	ABSTRACT

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Development of improved fertilizer management practices has the potential to increase fertilizer use efficiency and improve environmental quality. The objectives of this study were (i) to characterize the within field spatial variability of N uptake across irrigated corn production fields, (ii) to quantify and compare N uptake and grain yield across three site specific management zones (SSMZs), and (iii) to compare grain yield response to applied N between management zones. This study was conducted on continuous corn (Zea mays L.) in irrigated fields in northeastern Colorado. Fields were classified into high, medium, and low site specific management zones. Treatments consisted of a control and two uniform N application rates over 2 site-years (one field over 2 consecutive yr and another field over 1 yr). Nitrogen fertilizer rates varied with site-year and ranged from 56 to 268 kg N ha^–1. Aboveground biomass samples were collected at physiological maturity and analyzed for total N. Between management zones, N uptake, grain yield, and grain yield response to applied N were found to be statistically different (p < 0.05). Management zones were found to be less spatially variable than the whole field. The SSMZs accurately characterized variability in N uptake as well as grain yield response to applied N. Thus, variation in N uptake and grain yield can potentially be managed using SSMZs.

Abbreviations: DGPS, differentially corrected global positioning system • GIS, geographic information system • GPS, global positioning system • NUE, nitrogen use efficiency • SSMZ, site specific management zone • VRA, variable-rate application

	INTRODUCTION

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
PLANT NUTRIENTS such as N, P, and K are often applied to plants to ensure economically viable grain yields in large-scale cropping systems (Swanson, 1982; Mengel, 1990). Development of improved nutrient management strategies has been a primary focus of agricultural research for over 10 yr (Gauer et al., 1992; Spellman et al., 1996; Mulla and Bhatti, 1997; Khosla and Alley, 1999; Khosla et al., 2002). Crop management strategies that improve nutrient use efficiency may increase farm profits and greatly reduce the deleterious environmental effects associated with fertilizer loss.

Nitrogen is often the most limiting nutrient in agro-ecosystems and is therefore applied in the highest quantities (Havlin et al., 1999; FAO, 2001). According to the Food and Agriculture Organization of the United Nations, about 82 million Mg of nitrogenous fertilizers were applied globally in 2001 (FAO, 2001). Of that, 60% was used for cereal production (Alexandratos, 1995). Raun and Johnson (1999) estimate worldwide nitrogen use efficiency (NUE) for cereal production to be 33%, meaning that in the year 2001 alone, approximately 33 million Mg of N fertilizer was lost. Although there are many causes and pathways for N loss, application of N in amounts that exceed crop requirements elevates postharvest NO₃–N levels in the soil and increases the potential for leaching of NO₃–N into groundwater supplies (Schepers et al., 1991).

In-field spatial variability of soil and crop parameters has long been recognized as affecting overall crop yield (Johnson et al., 2003). Studies indicate that within-field yield variation can be attributed to several factors including, but not limited to, variability in soil types, changes in landscape position, cropping history, soil physical and chemical properties, as well as nutrient availability across fields (Wibawa et al., 1993; Sawyer, 1994; Penney et al., 1996). Variable rate application (VRA) of N fertilizers to manage inherent soil spatial variability has been shown to increase NUE in some crops. In eastern Washington, Mulla and Bhatti (1997) showed that N application could be reduced by as much as 42 kg ha^–1 using VRA. Khosla and Alley (1999) found that using VRA on a 14.4-ha field in Virginia reduced total N applied by 22 kg N ha^–1 without a reduction in grain yield when compared with a uniform N treatment. Moreover, the results of Mulla and Bhatti (1997), Khosla and Alley (1999), Khosla et al. (2002), and Hornung et al. (2003) all demonstrated that N input optimization via high N application rates in more productive areas and low N rates in less productive areas has potential to increase NUE.

	Site Specific Management Zones

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
The use of site specific management zones (SSMZ) for VRA has been shown to be a simple and effective way to increase NUE (Khosla et al., 2002; Hornung et al., 2003). Site specific management zones are defined as homogeneous subregions of a field that have similar yield limiting factors (Doerge, 1999; Khosla and Shaver, 2001). Numerous methods and combinations of methods have been used to delineate management zones including remotely sensed imagery (Bhatti et al., 1991), yield data (Mulla and Bhatti, 1997), farmer's experience combined with bare soil imagery and topography (Fleming et al., 1999), soil electrical conductivity (Sudduth et al., 1998), grid-soil sampling, and soil survey information (Franzen et al., 2000). Conceptually, using a management zone delineation technique, a production field could be classified into management zones that reflect the zone's productivity potential. For example, a field may be classified into three zones—high, medium, and low productivity potential management zones. Using the management zones approach, agricultural inputs are envisaged to be applied variably across the field in accordance with the productivity potential of the management zone. However, within a management zone, agricultural inputs are applied uniformly at a constant rate.

	Nitrogen Uptake and Variability

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Nitrogen management strategies that create a balance between N input and the crop N uptake could help alleviate problems associated with N loss (Grant et al., 2002). Accumulated soil N is highly susceptible to leaching and can potentially threaten groundwater supplies. Sustainable nutrient management practices should ideally replenish soil nutrients, which are depleted through crop uptake and harvest to soil fertility levels that can support economic crop growth and yield (Grant et al., 2002; Heckman et al., 2003). One means of maintaining soil N fertility levels without exceeding crop N requirements is to tailor N inputs to meet the specific crop N requirements. Published crop nutrient removal values are available from federal and state agencies (USDA, 2003) and have been used to help guide producers in making more informed application decisions. However, the usefulness of values reported in such publications is questionable. Heckman et al. (2003) made the point that "[nutrient removal] values that were established in the past may not be correct for current agronomic technologies such as hybrid, higher plant populations, yield potential, fertilizer practice, and soil conditions." In their study, Heckman et al. (2003) found that mean nutrient (N, P, and K) concentrations in corn (Zea mays L.) grain across 23 site-years were similar to published reference values. However, their results also revealed that nutrient concentration variability within a single corn hybrid grown across six site-years was as high as that of 10 different hybrids grown across 23 site-years (Heckman et al., 2003). Therefore, using average nutrient removal values as a means to estimate nutrient removal across varying conditions is questionable. For this reason most university soil analysis labs make N fertilizer recommendations based on a N requirement (amount of N required to produce one unit of grain yield) in conjunction with an estimated yield goal and residual soil NO₃–N test results.

Review of the current literature indicates that N uptake has not been thoroughly studied from a SSMZ perspective. We hypothesize that SSMZs can be used to effectively characterize N uptake spatial variability and could establish the usefulness for variable nutrient (N) application using SSMZs across the field.

The objectives of this study were (i) to characterize the within-field variability of N uptake across irrigated corn production fields, (ii) to quantify and compare N uptake and grain yield across three site specific management zones, and (iii) to compare grain yield response to applied N between site specific management zones.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Study Sites
This study was conducted over 3 site-years (one field over 2 consecutive yr and another field over 1 yr). Sites were located in northeastern Colorado under a continuous corn cropping system, with center-pivot sprinkler irrigation for all site-years. Study sites ranged from 51 to 89 ha in size.

Site-years 1 and 2 were on a field mapped as having Bijou (coarse-loamy, mixed, superactive, mesic, Ustic Haplargids), Truckton (coarse-loamy, mixed, superactive, mesic, Aridic Argiustolls), and Valentine (mixed, mesic, Typic Ustipsamments) soil series (Soil Survey Staff, 1968). These soils are characterized as being very deep. The Truckton soil is well drained, Bijou is somewhat excessively drained, and Valentine is excessively drained. Both Truckton and Bijou soils are derived from arkose parent material and occur on terraces, fans, and uplands. Valentine soils are eolian derived and occur on uplands.

Site-year 3 was located on a field that was mapped as having Albinas (fine-loamy, mixed, superactive, mesic Pachic Argiustolls), Ascalon (fine-loamy, mixed, superactive, mesic, Aridic Argiustolls), and Haxton (fine-loamy, mixed, superactive, mesic Pachic Argiustolls) soil series (Soil Survey Staff, 1981). These soils are characterized as being very deep, well drained, and have accumulated carbonates in the soil solum. The Ascalon series occurs on upland positions and is formed from calcareous parent material. The Haxtun series consists of eolian deposits that overlay buried soil, occurring in drainages and depressions. The Albinas series is alluvial and occurs on fans and terraces.

Experimental Procedure
Before planting, soil samples were collected at depths of 0 to 30 and 30 to 60 cm. A systematic unaligned sampling grid was used with a sampling density of 2.5 samples per hectare on the entire field (independent of management zones). Each geo-referenced soil sample consisted of four to six cores that were composited into one sample. Soil samples were air-dried and ground to pass a 2-mm sieve (Soil Survey Staff, 1996). Soil pH was analyzed using a 1:1 soil/water mixture (Thomas, 1996). Particle size analysis was conducted using the hydrometer method (Bouyoucos, 1962). A summary of soil texture, pH, and organic matter for each site-year is presented in Table 1. Total NO₃–N was determined using the method of Mulvaney (1996). An interpolation technique, inverse-distance weighting, was used in ArcView (Version 3.2) to generate surfaces for soil texture, and soil organic matter.

Site-specific management zones were delineated on all fields using the commercially available AgriTrak Professional software (Fleming et al., 1999). This program relies on three Geographic Information System (GIS) data layers: (i) bare soil aerial imagery on conventionally tilled land; (ii) farmer's perception of field topography; and (iii) farmer's past crop and soil management experience. These data layers were incorporated into a MapInfo (GIS) database to run mathematical interpolation surfaces to develop three management zones (Khosla et al., 2002). Traits such as dark color, low-lying topography, and historic high yields were designated as a zone of potentially high productivity or high zone. Details of this technique are provided in Fleming et al. (1999), Khosla et al. (2002), and Koch et al. (2004).

Nitrogen applications were made at the six-leaf crop growth stage (V6) using undiluted urea ammonium nitrate 32% solution applied with an eight-row cultivator. Nitrogen treatments were based on the N rate algorithm given by Mortvedt et al. (1996) for each site-year. The three N treatments were (i) the recommended N rate (as determined from the N rate algorithm), (ii) approximately half the recommended rate, and (iii) a control treatment (0 kg N ha^–1) (Table 2). Experimental strips were randomly allocated and consisted of 24 rows of corn that spanned the length of the field (>700 m). Treatments were replicated once and were nested within management zones. At the crop's physiological maturity (R6 growth stage) aboveground biomass samples were collected for grain yield and N content analysis. Four samples were randomly located and collected from each experimental unit (treatment in each management zone). Each sample consisted of two 1-m long sections of a corn row. Samples were separated into grain, husk and cob, and leaf and stalk portions; air-dried to a constant weight; analyzed for grain yield; and ground. Samples were then analyzed for total N concentration. Nitrogen uptake was found by the percentage of total N contained in the aboveground portion of the samples multiplied by the biomass weight and then converted to kg of N ha^–1. Grain yield was determined by converting the total grain weight per sample at 15.5% moisture to Mg ha^–1.

Data Analysis
Statistical analysis was performed using SPLUS 6.1 and SAS 8.0. Grain yield and N uptake differences between management zones were analyzed using a fixed-effect, two factor nested design analysis of variance (ANOVA) in which treatments were nested within management zones. In the ANOVA model, observational errors (i.e., subsamples within treatments) were nested within experimental errors. When ANOVA was found significant at P < 0.05, mean separation was performed using least squares difference (LSD) at P < 0.05. The spatial structure of the data was analyzed using semi-variogram plots. Moran's I was used to assess the spatial auto-correlation of N uptake and grain yield for each site-year and for each management zone within each site-year. A spatial auto-regressive model was used to analyze the spatial relationship between N uptake and grain yield within each site-year. Inverse distance weighting was used to create the spatial weight matrices used in Moran's I and spatial auto-regressive model. Since site-years 1 and 2 were located on the same field, an F test of unequal variance was used to test if grain yield and N uptake were equal across growing seasons at p < 0.05. Least squares regression analysis was used to model grain yield response to applied N and to examine the relationship between soil properties and N uptake. Best-fit models for grain yield response to N were determined using the All-Possible Regressions Procedure (SAS Inst., 2001). Indicator variables were introduced in the grain yield response model to test for differences among management zones (high, medium, and low). A complete review of the use and interpretation of indicator variables is provided by Neter et al. (1996).

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Within-Field Spatial Variability
Results from the semi-variograms indicate that both site-year 1 and 2 have significant spatial dependence for both N uptake and grain yield, with the former having stronger spatial structure (Fig. 1). Results from Moran's I and spatial auto-regressive model are presented in Table 3. Coefficients from Moran's I further support significant spatial dependence for both N uptake and grain yield. Mean N uptake, grain yield, and coefficient of variation (CV) for each site-year are shown in Table 4. Taylor et al. (1998) and Washmon (2002) used the CV as a measure of spatial variability for crop parameters. When the population of interest is spatially distributed, higher CVs indicate greater spatial variability. In our study, CV values for N uptake ranged from 22 to 35%; this coupled with the results of Moran's I indicates that N uptake had a high degree of spatial variability across the field. However, average N uptake values for all site-years were in agreement with published reference N uptake values (PPI, 2004). Average N uptake in this study ranged from 161 to 261 kg N ha^–1 across all site-years. Our results, like those of Heckman et al. (2003), raise questions about the usefulness of mean nutrient uptake values. Considering that the N uptake spatial variability was relatively high, using mean N uptake values to target N application rates potentially could have resulted in some portions of the fields being under- or over-fertilized.

View larger version (15K): [in this window] [in a new window]   Fig. 1. Semi-variogram for N uptake and grain yield for site-year 1.

Grain yield for all site-years was typical of this region (Table 4), with yields ranging from 9.9 to 11.6 Mg ha^–1. Grain yield variability was lower (CV = 18–21%) than that observed for N uptake (CV = 22–35%). Grain yield also exhibited less spatial variability than N uptake (Fig. 1, Table 3). A negative association was found between CV and grain yield. These results agree with those of Taylor et al. (1998) and Washmon (2002) in which an inverse relationship between CV and grain yield was reported. Higher overall yields are associated with yield uniformity and therefore low CVs (Taylor et al., 1998).

As with the N uptake results, CVs for grain yield between site-years 1 and 2 were similar, 20 and 21%, respectively (Table 4). Using an F test of unequal variances, it was found that grain yield variances were statistically equal between the two growing seasons (p < 0.05). Nitrogen uptake measurements taken at physiological maturity (R6 growth stage) were well correlated to grain yield in all site-years (r = 0.64–0.80, p < 0.05). These results were similar to those reported by Muchow (1988) and Katsvairo et al. (2003). The relationships were much stronger using spatial auto-regressive models (r² = 0.97–0.98, p < 0.05), indicating that these two parameters are spatially dependant (Table 3). The outcome from the above statistical analyses (CVs, F test of unequal variances, and spatial autoregressive models) suggest that the patterns of spatial variability in soil properties correspond to patterns of spatial variability in grain yield. Our results indicate that the effectiveness of N management practices are limited by soil properties, for example, low yielding areas (low zone) may continue to be low yielding until the soil properties of such areas are improved. Therefore, the fields used in this study would be good candidates for site specific N management using a management zone approach. Fields that have highly variable crop parameters, due to variability in soil properties, would conceptually be better managed using the SSMZ approach.

Variability between Management Zones
Mean N uptake across SSMZs and N application treatments are presented in Fig. 2. The N uptake was found to be significantly different for the N application treatments in this study (P < 0.05). Mean N uptake increased with increasing SSMZ productivity potential. Nitrogen uptake differed significantly between SSMZs for all N application rates for site-years 1 and 2. This supports our hypothesis that SSMZs have the potential to characterize spatial variability in N uptake. Using the SSMZ approach, the low and high productivity zones were consistently separable for site-years 1 and 2 based on N uptake (p < 0.05).

View larger version (43K): [in this window] [in a new window]   Fig. 2. Mean N uptake across low, medium, and high management zones for site-year 1, 2, and 3. Error bars represent standard deviation of the mean. Different letters are significantly different (p < 0.05).

Although not significantly different, site-year 3 mean N uptake values followed a similar trend as was observed for site-years 1 and 2. We believe N uptake values for site-year 3 were impacted by hail damage that occurred during the midvegetative crop growth stage (V-8 to V-10 crop growth stage). The damage was moderate, reducing the overall biomass and the crop's photosynthetic ability, and thus reducing overall crop N uptake across the field.

Mean grain yield across SSMZs and N application treatments are presented in Fig. 3. The grain yields were significantly different for the N application treatments in this study (P < 0.05). Overall, mean grain yield increased with increasing SSMZ productivity potential. In sites years 1 and 2, the medium zone was found to be statistically equal to the low zone for the control treatment and high zone for the 192 kg N ha^–1 treatment. Most likely, inclusions of isolated and small areas of low and high zones within the medium zone prevented an unambiguous classification of grain yield. For site-year 3, we observed a lack of response between management zones (p < 0.05) for the third N treatment (114 kg N ha^–1). However, the overall trend was similar to the trends seen in site-years 1 and 2.

View larger version (51K): [in this window] [in a new window]   Fig. 3. Mean grain yield across low, medium, and high management zones for site-year 1, 2, and 3. Error bars represent one standard deviation of the mean. Different letters are significantly different (p < 0.05).

View this table: [in this window] [in a new window]   Table 5. Mean N uptake, average grain yield, CV, and Moran's I for site-specific management zones (SSMZs) for all site-years.

View larger version (16K): [in this window] [in a new window]   Fig. 4. Grain yield response to applied N across site-specific management zones in irrigated corn production systems for site-years 1, 2, and 3.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

	ACKNOWLEDGMENTS

 
The authors acknowledge and thank the USDA-IFAFS and Agricultural Experiment Station for funding this research project. Our gratitude also goes out to Brad Koch, Andy Hornung, Chris Woodward, Tim Shaver, Bill Gangloff, and Kim Fleming for their support of this study.

	REFERENCES

TOP ABSTRACT INTRODUCTION Site Specific Management Zones Nitrogen Uptake and Variability MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 

• Alexandratos, N. (ed.). 1995. World agriculture: Towards 2010: An FAO study. FAO, Rome, and John Wiley & Sons, New York.
• Bhatti, A.U., D.J. Mulla, and B.E. Frazier. 1991. Estimation of soil properties and wheat yields on complex eroded hills using geostatistics and Thematic Mapper images. Remote Sens. Environ. 37:181–191.
• Bouyoucos, G.J. 1962. Hydrometer method improved for making particle size analysis of soils. Agron. J. 54:464–465.[Abstract/Free Full Text]
• Doerge, T. 1999. Defining management zones for precision farming. Crop Insights 8(21):1–5.
• Fleming, K.L., D.G. Westfall, D.W. Wiens, L.E. Rothe, J.E. Cipra, and D.F. Heermann. 1999. Evaluating farmer developed management zone maps for precision farming. p. 335–343. In P.C. Robert et al. (ed.) Precision agriculture. ASA, CSSA, and SSSA, Madison, WI.
• Food and Agriculture Organization of the United Nations. 2001. FAOSTAT: Statistical database. [Online] [Subset Fertilizer within Agriculture database] Available at http://apps.fao.org. (accessed 6 Aug 2003; verified 21 Sept. 2004). FAO, Rome, Italy.
• Franzen, D.W., A.D. Halvorson, and V.L. Hofman. 2000. Management zones for soil N and P levels in the Northern Great Plains. In P.C. Robert et al. (ed.) Precision agriculture. ASA, CSSA, and SSSA, Madison, WI.
• Gauer, L.E., C.A. Grant, D.T. Gehl, and L.D. Bailey. 1992. Effects of nitrogen fertilization on grain protein content, nitrogen uptake, and nitrogen use efficiency of six spring wheat (Triticum aestivum L.) cultivars, in relation to estimate moisture supply. Can. J. Plant Sci. 72:235–241.
• Grant, C.A., G.A. Peterson, and C.A. Campbell. 2002. Nutrient considerations for diversified cropping systems in the Northern Great Plains. Agron. J. 94:186–198.[Abstract/Free Full Text]
• Havlin, J.L., J.D. Beaton, S.L. Tinsdale, and W.L. Nelson. 1999. Soil fertility and fertilizers. Pearson Education, Upper Saddle River, NJ.
• Heckman, J.R., J.T. Sims, D.B. Beegle, F.J. Coale, S.J. Herbert, T.W. Bruulsema, and W.J. Bamka. 2003. Nutrient removal by corn grain harvest. Agron. J. 95:587–591.[Abstract/Free Full Text]
• Hornung, A., R. Khosla, R. Reich, and D.G. Westfall. 2003. Evaluation of site specific management zones: Grain yield and nitrogen use efficiency. In J. Stafford and A. Werner (ed.) Precision agriculture. Proc. of the 4th European Conf., Berlin, Germany. 15–19 June 2003. Waginengen Academic Publ., Waginengen, the Netherlands.
• Johnson, C.K., D.A. Mortensen, B.J. Weinhold, J.F. Shanahan, and J.W. Doran. 2003. Site specific management zones based on soil electrical conductivity in a semiarid cropping system. Agron. J. 95:303–315.[Abstract/Free Full Text]
• Katsvairo, T.W., W.J. Cox, H.M. Van Es, and M. Glos. 2003. Spatial yield response of two corn hybrids at two nitrogen levels. Agron. J. 95:1012–1022.[Abstract/Free Full Text]
• Khosla, R., and M.M. Alley. 1999. Soil-specific nitrogen management on Mid-Atlantic Coastal Plain soils. Better Crops 83(3):6–7.
• Khosla, R., K. Fleming, J.A. Delgado, T. Shaver, and D.G. Westfall. 2002. Use of site specific management zones to improve nitrogen management for precision agriculture. J. Soil Water Conserv. 57:515–518.
• Khosla, R., and T. Shaver. 2001. Zoning in on nitrogen needs. Colorado State Univ. Agronomy Newsletter 21(1):24–26.
• Koch, B., R. Khosla, M. Frasier, D.G. Westfall, and D. Inman. 2004. Economic feasibility of variable rate nitrogen application utilizing site-specific management zones. Agron. J. 96:1572–1580.[Abstract/Free Full Text]
• Mengel, K. 1990. Impacts of intensive palnt nutrient management on crop production and environment. In p. 42–52. Trans. of the 14th Int. Congress of Soil Sci., Plenary Papers, Kyoto, Japan. Int. Soc. Soil Sci., Kyoto, Japan.
• Mortvedt, J.J., D.G. Westfall, and R.L. Croissant. 1996. Fertilizing corn. Fact Sheet 0.538. Colorado State Univ. Coop. Ext., Fort Collins, CO.
• Muchow, R.C. 1988. Effect of nitrogen supply on the comparative productivity of maize and sorghum in a semi-arid tropical environment: III. Grain yield and nitrogen accumulation. Field Crops Res. 18:31–43.
• Mulla, D.J., and A.U. Bhatti. 1997. An evaluation of indicator properties affecting spatial patterns in N and P requirements for winter wheat yield. p. 145–153. In J.V. Stafford (ed.) Precision agriculture '97, 1st European Conf. Prec. Agric., Warwick Univ., UK. 7–10 Sept. 1997. Bios Scientific Publ., Oxford, Herndon, VA.
• Mulvaney, R.L. 1996. Nitrogen—inorganic forms. p. 1146–1162. In D.L. Sparks et al. (ed.) Methods of soil analysis. Part 3. SSSA Book Ser. 5. SSSA and ASA, Madison, WI.
• Neter, J., M.H. Kunter, C.J. Nachtscheim, and W. Wasserman. 1996. Applied linear regression models. 3rd ed. McGraw-Hill/Irwin Publ., Chicago, IL.
• Penney, D.C., S.C. Nolan, R.C. McKenzie, T.W. Goddard, and L. Kryzanowski. 1996. Yield and nutrient mapping for site specific fertilizer management. Commun. Soil Sci. Plant Anal. 27:1265–1279.
• Potash and Phosphate Institute. 2004. Nutrient uptake and removal by field crops [Online]. Available at http://www.ppi-ppic.org (accessed 2 Feb. 2004; verified 21 Sept. 2004). PPI, Norcross, GA.
• Raun, W.R., and G.V. Johnson. 1999. Improving nitrogen use efficiency for cereal production. Agron. J. 91:357–363.[Abstract/Free Full Text]
• SAS Institute. 2001. Statistical analysis software. Version 8. SAS Inst., Cary, NC.
• Sawyer, J.E. 1994. Concepts of variable rate technology with considerations for fertilizer application. J. Prod. Agric. 7:195–201.
• Schepers, J.S., M.G. Moravek, E.E. Alberts, and K.D. Frank. 1991. Maize production impacts on groundwater quality. J. Environ. Qual. 20:12–16.[Abstract/Free Full Text]
• Soil Survey Staff. 1968. Soil survey of Morgan County, Colorado. USDA Coop. Soil Survey. U.S. Gov. Print. Office, Washington, DC.
• Soil Survey Staff. 1981. Soil survey of Yuma County, Colorado. USDA Coop. Soil Survey. U.S. Gov. Print. Office, Washington, DC.
• Soil Survey Staff. 1996. Soil survey laboratory methods manual. Soil Survey Invest. Rep. 42. Version 3.0. National Soil Survey Center, Lincoln, NE.
• Spellman, D.E., A. Rongni, D.G. Westfall, R.M. Waskom, and P.N. Soltanpour. 1996. Pre-sidedress nitrate soil testing to manage nitrogen fertility in irrigated corn in a semi-arid environment. Commun. Soil Sci. Plant Anal. 27:561–574.
• Sudduth, K.A., N.R. Kitchen, and S.T. Drummond. 1998. Soil conductivity sensing on clay-pan soil: Comparison of electromagnetic induction and direct methods. p. 979–990. In P.C. Robert et al. (ed.) Precision agriculture. ASA, CSSA, and SSSA, Madison, WI.
• Swanson, E.R. 1982. Economic implications of controls on nitrogen fertilizer use. p. 773–790. In F.J. Stephenson (ed.) Nitrogen in agricultural soils. Agron. Monogr. 22. ASA and SSSA, Madison, WI.
• Taylor, R.K., G.J. Kluitenburg, M.D. Schrock, N. Zhang, J.P. Schmidt, and J.L. Halvin. 1998. Using yield monitor data to determine spatial crop production potential. ASAE Pap. 981048. Presented at 1998 Int. Meeting, Orlando, FL. ASAE, St. Joseph, MI.
• Thomas, G.W. 1996. Soil pH and soil acidity. p. 475–490. In D.L. Sparks et al. (ed.) Methods of soil analysis. Part 3. SSSA Book Ser. 5. SSSA and ASA, Madison, WI.
• U.S. Department of Agriculture. 2003. Natural Resources Conservation Service Crop Nutrient Tool [Online]. Available at http://npk.nrcs.usda.gov/nutrient_body.html (accessed 20 Oct. 2003; verified 21 Sept. 2004). USDA, Washington, DC.
• Washmon, C.N. 2002. Within field variability in wheat grain yields over nine years in Oklahoma. J. Plant Nutr. 25:2655–2662.
• Westfall, D.G., W.J. Gangloff, R. Khosla, R.M. Reich, A. Hornung, D.F. Heermann, H.J. Farahani, and K. Fleming. 2003. Development of production level management zones for nitrogen fertilization. p. 141–142. In A. Werner and A. Jarfe (ed.) Program book of the joint conference of ECPA-ECPLF. Wageningen Academic Publ., the Netherlands.
• Wibawa, W.D., D.L. Dludlu, L.J. Swenson, D.G. Hopkins, and W.C. Danke. 1993. Variable fertilizer application based on yield goal, soil fertility, and soil map unit. J. Prod. Agric. 6:255–261.

This article has been cited by other articles:

				D. Inman, R. Khosla, R. Reich, and D. G. Westfall Normalized Difference Vegetation Index and Soil Color-Based Management Zones in Irrigated Maize Agron. J., January 11, 2008; 100(1): 60 - 66. [Abstract] [Full Text] [PDF]

				Y. Miao, D. J. Mulla, W. D. Batchelor, J. O. Paz, P. C. Robert, and M. Wiebers Evaluating Management Zone Optimal Nitrogen Rates with a Crop Growth Model Agron. J., April 11, 2006; 98(3): 545 - 553. [Abstract] [Full Text] [PDF]

				A. Hornung, R. Khosla, R. Reich, D. Inman, and D. G. Westfall Comparison of Site-Specific Management Zones: Soil-Color-Based and Yield-Based Agron. J., March 2, 2006; 98(2): 407 - 415. [Abstract] [Full Text] [PDF]

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (11) Citing Articles via Google Scholar Google Scholar Articles by Inman, D. Articles by Reich, R. Search for Related Content PubMed Articles by Inman, D. Articles by Reich, R. Agricola Articles by Inman, D. Articles by Reich, R. Related Collections Maize Nutrient Management Nitrogen