use of soil nitrogen parameters and texture for spatially

Use of soil nitrogen parameters and texturefor spatially-variable nitrogen fertilization

H. Shahandeh • A. L. Wright • F. M. Hons

Published online: 4 March 2010� Springer Science+Business Media, LLC 2010

Abstract Recent studies have demonstrated the potential importance of using soil texture

to modify fertilizer N recommendations. The objective of this study was to determine (i) if

surface clay content can be used as an auxiliary variable for estimating spatial variability of

soil NO3–N, and (ii) if this information is useful for variable rate N fertilization of non-

irrigated corn [Zea mays (L.)] in south central Texas, USA across years. A 64 ha corn field

with variable soil type and N fertility level was used for this study during 2004–2007. Plant

and surface and sub-surface soil samples were collected at different grid points and ana-

lyzed for yield, soil N parameters and texture. A uniform rate (UR) of 120 kg N ha-1 in

2004 and variable rates (VAR) of 0, 60, 120, and 180 kg N ha-1 in 2005 through 2007

were applied to different sites in the field. Distinct yield variation was observed over this

time period. Yield and soil surface clay content and soil N parameters were strongly

spatially structured. Corn grain yield was positively related to residual NO3–N with depth

and either negatively or positively related to clay content depending on precipitation.

Residual NO3–N to 0.60 and 0.90 m depths was more related to corn yield than from

shallower depths. The relationship of clay content with soil NO3–N was weak and not

temporally stable. Yield response to N rate also varied temporally. Supply of available N

with depth, soil texture and growing season precipitation determined proper N manage-

ment for this field.

Keywords Spatial soil N variability � Residual NO3–N � Soil texture �Variable and uniform N rates � Corn grain yield

H. Shahandeh (&) � F. M. HonsDepartment of Soil and Crop Science, Texas A&M University, College Station, TX 77843-2474, USAe-mail: [email protected]

A. L. WrightEverglades Research and Education Center, University of Florida, 32 00E. Pal Beach Road,Belle Glade, FL 33430-4702, USA

123

Precision Agric (2011) 12:146–163DOI 10.1007/s11119-010-9163-8

Introduction

To improve N management in cropping systems, similar N fertilization rates should be

applied to homogeneous sub-regions of a field that have similar yield limiting factors

(Khosla et al. 2002; Koch et al. 2004). This practice is likely to achieve the greatest benefit

when information about soil N reserves in surface and subsurface soil is also available

(Eghball et al. 1997; Schmidt et al. 2002). Information about soil N reserve is usually

obtained through a single criterion like soil NO3–N in surface and/or subsurface samples.

The current recommended method for determining N fertilization for crop production in

Texas involves soil testing for residual NO3–N in surface soil (0–0.15 m) and integrating

with the anticipated yield goal for uniform application to the soil (McFarland et al. 1990).

It has recently been suggested that to better determine the efficacy of variable-rate N

fertilization and its contribution to yield, the spatial variation in NO3–N accumulated

below 0.15 m depth should also be assessed (Katsvario et al. 2003; Shahandeh et al. 2005).

However, some experiments show that residual soil NO3–N with depth is not enough and

information on other soil N parameters, like mineralizable soil N, is also needed for

variable rate N management (Schmidt et al. 2002; Eghball et al. 2003).

For practical importance, knowledge about relationships between yield, soil properties,

and soil N parameters is highly desirable. Evaluating N supply parameters for N fertil-

ization in the field is time consuming and expensive, but if information on N supply is

related to other soil physical and chemical properties within the field, these relationships

can have significant importance for variable rate N fertilization with respect to cost and

ease of measurements (Mamo et al. 2003; Baxter et al. 2003).

Within-field yield variation has been attributed to changes in landscape position,

nutrient availability, soil chemical and physical properties, cropping history and soil type

(Inman et al. 2005; Baxter et al. 2003; Delin and Linden 2002; Pierce and Nowak 1999;

Sawyer 1994; Wibawa et al. 1993). These attributes are known to be prime factors for

variable rate nutrient technology (Machado et al. 2002). For, example, if soil surface clay

content is related to soil N supply, then estimating clay content would be a more eco-

nomical alternative for describing soil N supply and spatial distribution since it is less

variable in time and could be determined accurately and for relatively low cost (Han et al.

2003; Chen et al. 2004). Clay content measured with only limited sampling for NO3–N has

been suggested as a way to infer and estimate N availability for future N fertilization (Cox

et al. 2003).

The objectives of this study were to evaluate relationships between corn yield, soil N

parameters and soil texture in a spatially variable field. Relationships between soil N

supply with texture were used to assess the potential of variable rate N fertilization for non-

irrigated corn production in Central Texas over time.

Materials and methods

Experimental site

Research was conducted in a 64 ha field adjacent to the Brazos River at the Texas AgriLife

Research Farm in Burleson County near College Station, TX (30�3205300N, 96�2502800W)

from 2004 to 2007 (Fig. 1a). The site had been managed under minimum tillage since 1996

and was planted to corn prior to this study. The alluvial soil used for the study is an

intergrade of Weswood silt loam (fine-silty, mixed superactive, thermic Udifluventic

Precision Agric (2011) 12:146–163 147

123

Haplustepts) and Ships clay (very fine, mixed, active, thermic Chromic Hapluderts) with

pH of 7.9–8.1 (Fig. 1a). A point grid was laid out across this field in 2004 with 50 m

between grid points in north and east directions using a Trimble GPS Pathfinder Pro XRS

(Trimble, Sunnyvale, CA, USA) (Fig. 1b). The 64 ha field was planted in 0.91 m rows

with corn variety Dekalb 687 (Monsanto, St. Louis, MO) on 12 March in 2004, 21 March

Exp. Site in: N Applied, kg ha-1

2004

2005-2007

UR, 120

VAR, 0-180

B

050 m 250 m

ShA Ships clay, 0 to 1% slopeWwB Weswood silty clay loam, 1 to 3% slope

WwA Weswood silty clay loam, 0 to 1% slopeWeA Weswood silt loam, 0 to 1% slope

Legend

ShA

WeA

WwB

WwA

A

A

A

B

Fig. 1 Texas A&M research farm (a) and experimental site (b) in Burleson County near College Station,TX from 2004 to 2007

148 Precision Agric (2011) 12:146–163

123

in 2005, 2 March in 2006 and 7 March in 2007 with a Case/IH Early Riser planter (Racine,

WI, USA) at a rate of *65 000 seed ha-1. BicepTM herbicide (metolachlor/atrazine) was

used for weed control, along with in-season cultivation.

The corn received a uniform N rate of 120 kg N ha-1 in 2004. The N source was urea

ammonium nitrate solution (32-0-0) that was knifed into the furrow midway between plant

rows at the six-leaf growth stage (V6) (Iowa State University 1993) using an eight-row

cultivator. One hundred grids (plots) were superimposed on top of the 64 ha experimental

field with each grid being 8 rows wide and 0.50 m long (Fig. 1b).

Based on results from the 2004 study on the spatial structure of corn grain yield

(Fig. 2a), field elevation (Fig. 2b), soil texture (Fig. 3), and NO3–N concentration with

depth (Fig. 4), locations at the upper and lower elevation portions of a field section that

comprised *20 ha were selected for variable rate N fertilization in 2005–2007 (Fig. 1b).

The upper segment was located at higher elevation with lower clay content and higher

residual soil NO3–N with depth and the bottom segment was located at lower elevation

with higher clay and lower residual soil NO3–N content. Variable-rate N strips (0, 60, 120,

and 180 kg ha-1) in three replications were applied to these sites in 2005–2007. Strips

were 8 rows wide 9 150 m long.

Soil and plant measurements

Soil samples were collected to 0.90 m depth using a tractor-mounted hydraulic soil

sampler near the center of each grid point before corn fertilization or after harvest in

April or September of each year. Two cores were taken at 1-m radii from each grid

point center and were sectioned into depths of 0–0.15, 0.15–0.30, 0.30–0.60, and 0.60–

0.90 m and composited with depth. Samples were dried in a forced-draft oven at 50�C,

then ground with a flail-type soil grinder (Custom Lab, Orange City, FL, USA) to pass

a 2-mm sieve.

Soil N mineralization (Nmin), C mineralization, soil organic C (SOC), soil total N, and

soil texture were determined on 0–0.15 m soil samples. Residual NO3–N and other plant

essential nutrients were determined on soil samples from all depths. Soil C and N min-

eralization were determined according to Franzluebbers et al. (1994a, b). Approximately

20 g of oven-dried soil were placed in 50-ml beakers, wetted to -0.03 MPa, and incubated

at 25�C in air-tight containers along with a vial containing 10 ml of 1.0 M KOH and

another vial containing water to maintain humidity. Vials of KOH were replaced at 1, 10,

and 24 d. Mineralized C as CO2 was determined at each sampling date by titrating the

KOH with 1.0 M HCl to the phenolphthalein endpoint (Anderson 1982). Soil NH4– and

NO3–N at 0 and 24 d were extracted with 2 M KCl and determined using autoanalyzer

techniques (Technicon Industrial Systems 1977a, b). Initial inorganic N was subtracted

from that measured at 24 d to determine net soil Nmin.

Soil organic C was determined using the modified Mebius method (Nelson and

Sommers 1982), while soil total N was determined by autoanalyzer techniques (Technicon

Industrial Systems 1977a) following Kjeldahl digestion (Nelson and Sommers 1980). Soil

particle size distribution was determined on all samples using the procedure of Day (1965),

which utilizes hydrometer analysis following dispersion of soil by both chemical and

physical means.

A 3 m length of each of the middle two rows of each grid were hand-harvested for grain

yield in August at maturity and shelled using a stationary plot sheller, before using a

combine equipped with a calibrated Ag Leader PF3000 yield monitor with elevator

mounted sensor (Ag Leader Technol., Ames, IA, USA) and a differential global

Precision Agric (2011) 12:146–163 149

123

positioning system receiver to harvest the remainder of the field. Grain moisture was

determined by electrical resistance and yields were calculated at a moisture content of

140 g kg-1.

Yield

11.8

Ela69.4-70.069-0-69.468.7-69.068.3-68.768.0-68.367.6-68.067.2-67.666.8-67.266.5-66.866.2-66.5

-1

11.8-13.110.5-11.89.2-10.57.8-9.26.5-7.85.2-6.53.9-5.22.6-3.91.3-2.60-1.3

Elevation, m

A

B

50 m 250 m0

Yield, t ha

Fig. 2 Yield (a) and elevation contour maps (b) of the 64 ha in 2004

150 Precision Agric (2011) 12:146–163

123

Statistical and spatial variability analyses

Correlation and spatial statistics were used to relate surface and profile residual soil NO3–

N, soil Nmin, and other soil characteristics with corn grain yield. Geostatistical methods,

variography and kriging (Isaaks and Srivastava 1989) were used to map variability of soil

and plant parameters. Geostatistical software (GS? v5.0, Gamma Design Software,

0 50 100 150 200 250 300 350 400 4500

50

100

150

200

250

300

350

2500300035004000450050005500600065007000750080008500900095001000010500110001150012000125001300013500

0 50 100 150 200 250 300 350 400 4500

50

100

150

200

250

300

350

20222426283032343638404244464850525456586062646668

Easting, m

No

rth

ing

, mN

ort

hin

g, m

Clay, %

Corn Yield, kg ha-1, 2004

%

kg ha-1

Fig. 3 Kriged contour maps of yield and clay content in the 20 ha field in 2004

Precision Agric (2011) 12:146–163 151

123

St. Plainwell, MI, USA) was used to analyze the spatial structure of the data and to define

semi-variogram parameters. Contour maps of corn yield distribution and clay content were

produced in Surfer (version 8, Golden Software, Golden, CO, USA) based on grid files

created from the kriged values from GS?. A detailed description of analysis is presented in

Shahandeh et al. (2005).

Results and discussion

Spatial variability of corn grain yield in 64 ha field with uniform rate of N fertilization

The yield map from data generated by the combine equipped with a yield monitor showed

distinct spatial variability of corn yield within the 64 ha corn field in 2004 (Fig. 2a). The

yield map is presented as a contour map with 1.2 t ha-1 contour intervals and with colored

legends representing green for high and red for low values. Yield varied from about 13 to

\2 t ha-1 and closely followed the elevation distribution map of the field generated by the

mounted elevation sensor (Fig. 2b). High yields were obtained at higher elevation and low

yields at lower elevation. However, to find the true spatial variation of yield in the field,

information on soil-landscape features like elevation may not be enough and determination

of plant and soil N properties at a finer scale may be required (Dobermann and Ping 2004;

Scharf et al. 2006).

0 50 100 150 200 250 300 350 400 4500

50

100

150

200

250

300

350

101112131415161718192021222324252627282930313233343536

0 50 100 150 200 250 300 350 400 4500

50

100

150

200

250

300

350

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

0 50 100 150 200 250 300 350 400 4500

50

100

150

200

250

300

350

5101520253035404550556065707580859095100

0 50 100 150 200 250 300 350 400 4500

50

100

150

200

250

300

350

800

900

1000

1100

1200

1300

1400

1500

1600

1700

1800

1900

2000

2100

2200

Easting, m Easting, m

No

rth

ing

, mN

ort

hin

g, m

kg ha-1 kg ha-1

mg kg-1mg kg-1

NO3-N-15 cm, 2004 NO3-N-90 cm, 2004

Total N, 2004 Mineralized N-24d, 2004

Fig. 4 Kriged contour maps of soil N properties, residual soil NO3–N to 0.15 and 0.90 m depths, total Nand Nmin in the 20 ha field in 2004

152 Precision Agric (2011) 12:146–163

123

Spatial variability of corn grain yield, soil nitrogen parameters and texture in 20 ha

field

A sub-field of about 20 ha in the upper section of the 64 ha field was selected to determine

detailed spatial variability (Fig. 1b). Descriptive statistics and spatial variability of

parameters measured for this sub-field are shown in Table 1. Yield and soil properties were

highly variable in this 20 ha sub-field. For example, surface clay content varied from 18 to

67% and residual NO3–N concentration to 0.15 m depth varied from 7 to 59 kg ha-1. The

coefficient of variation (CV) used for measuring spatial variability of plant and soil

properties ranged between 26 to 52% (Table 1). The lowest variation was observed for soil

total N, organic N and NO3–N concentration to 0.90 m depth, and the highest variation was

noted for N mineralized at 24 d.

The CV values reported for soil N parameters were similar to CV values reported in

other spatially variable fields (Cambardella et al. 1994; Mahmoudjafari et al. 1997;

Shahandeh et al. 2005). For example, Nmin had a CV of 52% with a mean concentration of

31 mg kg-1 and a range of 9–96 mg kg-1. The high CV for Nmin may have resulted from

non-homogeneous incorporation of variable corn residues produced and/or incorporation

of residue into a non-homogeneous soil (Fig. 1 and Table 1) (Rover et al. 1999). Variable

yield and the associated variable residue produced support these possibilities. Mean corn

grain yield was 8 350 kg ha-1, but varied from 1 783 on the west side to 12 548 kg ha-1

on the east side of field (Fig. 2 and Table 1).

To characterize the structure of spatial variability in the field, variograms and spatial

distribution maps of yield, soil clay content, and soil N parameters (NO3–N to 0.15 and

0.90 m depths, total N and Nmin) were constructed (Figs. 3 and 4). In each figure, light

shading represents higher values while darker shading is associated with lower values.

Grain yields and soil N characteristics were generally higher in the eastern portion of the

field and lower in the western portion. In contrast, surface clay content (0 to 0.15 m)

Table 1 Descriptive statistics of parameters measured in the 20-ha plot within the 64 ha corn field in 2004

Parameter Mean Maximum Minimum CV

Grain yield (kg ha-1) 8 350 12 548 1 783 34

Total N (mg kg-1) 1 151 2 160 550 26

Organic N (mg kg-1) 1 147 2 156 548 26

NH4–N at 24dincubationa (mg kg-1) 6 17 5 27

NO3–N at 24dincubation (mg kg-1) 37 92 18 36

N mineralized at 24dincubationb (mg kg-1) 31 96 9 52

NO3–N to 0.15 m depth (kg ha-1) 24 59 7 39




SOC (mg C g-1)c 11 27 8 28

Clay (%) 45 67 18 30

a 24dincubation = NH4–N, NO3–N, produced after 24 days of incubationb N Mineralized at 24d = incubated inorganic N at 24 d for 0.15 m depth minus initial inorganic N for0.15 m depthc SOC, soil organic C

Precision Agric (2011) 12:146–163 153

123

tended to be higher in the western direction and followed a trend opposite to yield and N

parameter distribution. In general, yield and soil N parameters were positively related with

elevation, but were negatively related with clay content.

Relationship between corn grain yield, soil nitrogen parameters and soil texture

To better illustrate relationships in 2004 between corn grain yield, surface clay content and

soil N parameters, yields[10 000 kg ha-1 and clay contents of\40% were separated and

the contour lines for 40% and 10 000 kg ha-1 made bold in Fig. 3. This graphical sepa-

ration tended to divide soil and plant properties in the 20 ha sub-field into higher (top) and

lower (bottom) landscape positions.

Table 2 shows the correlation coefficients for relationships between yield, soil N

parameters and surface clay content in the 20 ha field and in the smaller top and bottom

segments in 2004. Correlation coefficients for the 20 ha field indicated that grain yield was

positively related to NO3–N concentration and Nmin, and negatively related to surface clay

content. Nitrate N concentrations with depth were generally highly correlated and the

highest correlation coefficients were at deeper depths. However, NO3–N concentration was

not related to clay content at any depth. Clay content was positively related to SOC and

Nmin. Clay protection of adsorbed organic compounds may partially explain this result.

Similar results were reported by Shahandeh et al. (2005) and Johnson et al. (2003).

Relationships between grain yield, N parameters and clay content were somewhat

different, however, when analyzed separately for top or bottom field segments. For

example, stronger relationships between clay content, yield, and mineralized N were

observed in the bottom field segment, while clay content only was related to soil NO3–N to

a depth of 0.90 m in the top segment (Table 2). In general, stronger relationships between

N parameters and yield were observed in the top field segment compared to the whole field

or bottom segment.

The different relationships between clay content and N parameters in this field support

Pierce and Nowak’s (1999) argument that N in soil will vary spatially with clay, soil N

supply and organic matter content. Higher soil N supply (residual NO3–N with depth,

Nmin, and total N) was generally associated with lower clay content in the top field

segment, and lower N supply with higher clay content in the bottom segment (Tables 1 and

2). Kriged maps (Figs. 3 and 4) also supported a close spatial relationship between corn

grain yield and soil texture and N supply parameters in the top and bottom field segments.

When similar spatial structure exists, there is a possibility that results from one variable

can be inferred from other properties (Baxter et al. 2003; Han et al. 2003).

One approach to evaluate whether similar spatial structure exists is to apply variable N

rates in more homogeneous sub-regions of the field. It has been suggested that it is

preferable to evaluate variable N rates in areas that possess homogeneous attributes in

landscape and soil conditions (Schepers et al. 2004; Franzen et al. 2002; Khosla et al. 2002;

Diker et al. 2004).

Variable rate N fertilization in homogeneous sub-regions and its relation to N supply

over time

Continued uniform application of N would probably have resulted in over application of N

in the eastern areas of the field and under-fertilization in other parts of the field (Figs. 3 and

4). Variable rate N fertilization might help optimize grain yield in this field, but the success

of variable N rate fertilization will also depend on the ability to predict and define the

154 Precision Agric (2011) 12:146–163

123

Tab

le2

Pea

rso

nco

rrel

atio

nco

effi

cien

tsfo

rco

rng

rain

yie

ldan

dso

ilN

par

amet

ers

for

the

wh

ole

20

ha

corn

fiel

dan

dsm

alle

rh

igh

eran

dlo

wer

elev

atio

nse

gm

ents

in2

00

4

Par

amet

ers

NO

3–

N0

.15

mN

O3–

N0

.30

mN

O3–

N0

.60

mN

O3–

N0

.90

mT

ota

lN

SO

Ca

Nm

inat

24

dC

lay

Wh

ole

fiel

d

Gra

iny

ield

0.2

3*

–0

.25*

0.4

1*

––

0.3

7*

*-

0.4

7*

**

NO

3–

Nto

0.1

5m

0.8

4*

**

0.5

9*

**

0.3

9*

*–

–0

.28

*–

NO

3–

Nto

0.3

0m

0.8

1*

**

0.5

1*

**

––

––

NO

3–

Nto

0.6

0m

0.6

3*

**

––

––

NO

3–

Nto

0.9

0m

––

––

To

tal

N0

.54*

**

0.6

0*

**

–

SO

C0

.38

**

0.3

7*

*

Nm

iner

aliz

ed0

.28

*

To

pfi

eld

Gra

iny

ield

0.3

6*

*–

0.3

2*

0.5

0*

**

0.3

9*

*0

.45*

*0

.52

**

*–

NO

3–

Nto

0.1

5m

0.8

4*

**

0.6

1*

**

0.5

4*

**

0.6

0*

**

–0

.34

*–

NO

3–

Nto

0.3

0m

0.8

9*

**

0.7

1*

**

––

––

NO

3–

Nto

0.6

0m

0.9

4*

**

0.3

0*

–0

.32

*–

NO

3–

Nto

0.9

0m

0.7

1*

**

–0

.54

**

*0

.29

*

To

tal

N0

.89*

**

0.7

3*

**

–

SO

C0

.66

**

*–

Nm

iner

aliz

ed–

Bo

tto

mfi

eld

Gra

iny

ield

––

0.3

0*

––

––

-0

.66*

**

NO

3–

Nto

0.1

5m

0.6

3*

**

0.4

0*

*0

.40*

*–

–0

.22

*–

NO

3–

Nto

0.3

0m

0.6

1*

**

0.4

1*

*–

––

–

NO

3–

Nto

0.6

0m

0.6

3*

**

––

––

NO

3–

Nto

0.9

0m

––

––

To

tal

N0

.49*

**

0.4

3*

*–

Precision Agric (2011) 12:146–163 155

123

Tab

le2

con

tin

ued

Par

amet

ers

NO

3–

N0

.15

mN

O3–

N0

.30

mN

O3–

N0

.60

mN

O3–

N0

.90

mT

ota

lN

SO

Ca

Nm

inat

24

dC

lay

SO

C–

–

Nm

iner

aliz

ed-

0.4

1*

*

‘‘–

’’in

dic

ates

no

nsi

gn

ifica

nt

*S

ign

ifica

nt

atth

e0

.05

lev

el;

**

Sig

nifi

can

tat

the

0.0

1le

vel

;*

**

Sig

nifi

cant

atth

e0

.00

1le

vel

aS

OC

,so

ilo

rgan

icC

156 Precision Agric (2011) 12:146–163

123

magnitude of the dynamics of soil N supply with depth over time (Mamo et al. 2003;

Khosla et al. 2006).

To determine corn response to variable N rate over time, studies were conducted in

more homogeneous soil textural locations in the higher and lower elevation field segments

in 2005–2007 (Fig. 2b). The top segment was located at higher elevation with greater

yield, higher residual NO3–N with depth, and lower clay content (22–31% clay,

CV = 9.7%) (Tables 1, 2, 3, 4; Figs. 2, 3, 4). The bottom segment was located at lower

elevation with lower yield, lower residual NO3–N with depth, and higher clay content

(54–68% clay, CV = 5.8%).

Descriptive statistics for corn yield and residual NO3–N to 0.90 m depth for higher and

lower elevation field segments are given in Tables 3 and 4, respectively. Similar to 2004

results, corn grain yield was greater in the higher than the lower elevation segment of the

field during 2005 to 2007. Corn grown in higher and lower elevation segments also

responded differently to variable N rate fertilization in each year. For example, there was

no response to N fertilization in the higher elevation portion of the field in 2005. To

achieve maximum yield in the higher elevation field segment, no N fertilization was

needed in 2005, while 120 kg N ha-1 was required in 2006 and 2007. In the higher

elevation field segment, the yield increase from the highest rate of applied N

(180 kg N ha-1) was only 274 kg ha-1 (from 6 978 to 7 252 kg ha-1) in 2005, but was

5 307 kg ha-1 in 2007 with greater precipitation (Fig. 5) and lower residual NO3–N.

Table 3 Descriptive statistics of parameters measured for N rate transects in the upper elevation segment ofthe 20 ha corn field experiment in 2005, 2006, and 2007

Parameter N transect Mean(kg ha-1)

Maximum(kg ha-1)

Minimum(kg ha-1)

CV (%)

2005

Grain yield 0 kg N ha-1 6978 a 7283 6250 6.7

60 kg N ha-1 6993 a 7362 6394 5.9

120 kg N ha-1 7190 a 7489 6433 5.5

180 kg N ha-1 7252 a 7817 6893 5.3

NO3–N to 0.90 m 120 kg N ha-1 65 107 24 6.6

2006


60 kg N ha-1 10307 ab 10714 9161 12.3

120 kg N ha-1 10669 b 11136 10677 5.3

180 kg N ha-1 10926 b 11696 11111 6.1

NO3–N to 0.90 m 120 kg N ha-1 45 88 19 9.7

2007


60 kg N ha-1 9393 b 11600 7102 17.0

120 kg N ha-1 11058 c 12055 10710 5.8

180 kg N ha-1 11886 c 12987 11038 4.3

NO3–N to 0.90 m 120 kg N ha-1 33 71 15 5.6

Clay (%) All 27.0 31.0 22.0 9.7

Means within a column and characteristic followed by the same letter are not significantly different(LSD0.05)

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Corn yield response to N in the lower elevation segment was very different than that

observed for the higher elevation segment, especially in 2005 (Table 4). In fact, a sig-

nificant grain yield response to the first increment of N fertilizer was observed in all years

Table 4 Descriptive statistics of parameters measured for N rate transects in the lower elevation segment ofthe 20 ha corn field experiment in 2005, 2006, and 2007

Parameter N transect Mean(kg ha-1)

Maximum(kg ha-1)

Minimum(kg ha-1)

CV (%)

2005


60 kg N ha-1 2518 b 3158 1533 33.3

120 kg N ha-1 3715 c 4014 2741 24.1

180 kg N ha-1 4531 d 4689 2900 21.0

NO3–N to 0.90 m 120 kg N ha-1 32 75 16 30.0

2006


60 kg N ha-1 8091 b 9668 7124 9.6

120 kg N ha-1 8404 b 9286 7815 9.5

180 kg N ha-1 9107 bc 10028 8250 7.5

NO3–N to 0.90 m 120 kg N ha-1 28 65 15 9.5

2007


60 kg N ha-1 6020 b 6909 4310 13.2

120 kg N ha-1 8384 c 8874 7805 6.5

180 kg N ha-1 9227 d 9983 9034 3.9

NO3–N to 0.90 m 120 kg N ha-1 21 40 12 11.4

Clay (%) All 61.0 68.0 54.0 5.8

Means within a column and characteristic followed by the same letter are not significantly different(LSD0.05)

Date

Mar

-04

May

-04

Jun-

04

Mar

-05

Apr

-05

May

-05

Jun-

05

Jul-0

5

Mar

-06

May

-06

Jun-

06

Jul-0

6

Mar

-07

May

-07

Jun-

07

Pre

cip

itat

ion

, m

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Jul-0

4

Apr

-06

50 yr. Ave.

Corn Growing Season Rainfall

Apr-May-Jun

Mar-Jul

Fig. 5 Growing season precipitation (March–July) during 2004 to 2007 near College Station, TX

158 Precision Agric (2011) 12:146–163

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in the lower elevation segment. Yield responded positively to the greatest added N rate in

both 2005 and 2007. Corn in the lower elevation segment may have been more responsive

to N fertilization due to lower residual soil NO3–N in this section.

The temporal response to N supply in higher and lower elevation field segments might

have been caused by different weather conditions (Fig. 5). The 50-year average seasonal

rainfall was 0.415 m and growing season rainfall was 0.627, 0.375, 0.413, and 0.606 m for

2004, 2005, 2006, and 2007, respectively. Based on the fifty-year rainfall average, corn

growing season rainfall was divided into wetter (2004 and 2007), drier (2005) and average

(2006) rainfall seasons.

Researchers have demonstrated that a significant interaction can exist between crop N

response and moisture availability (Mamo et al. 2003; Machado et al. 2002). Available soil

moisture was likely influenced by both clay content and elevation. Average clay content

was 27% in the higher elevation segment and 61% in the lower elevation segment. The

higher clay content in the lower elevation segment could have influenced the amount of

plant available water for grain production later in the season, especially in a drier year. In

the drier season (2005), N application had no significant effect on yield in the higher

elevation field segment. Nitrogen applied to the lower elevation segment, however, had a

positive effect on yield. Schepers et al. (2004) and Kravchenko and Bullock (2000)

reported a similar positive relationship between yield and moisture at lower elevation in

bottom lands during dry years.

However, in the wetter year (2007), the dominant factor influencing corn grain yield

was probably soil N supply with depth. For example, corn grain yield with 180 kg N ha-1

was about doubled (from 6 579 to 11 886 kg ha-1) in the higher elevation field segment,

and almost tripled (from 3 308 to 9 227 kg ha-1) in the lower elevation segment in 2007

(Tables 3 and 4). Yield increases in the average rainfall year (2006) were also influenced

by N fertilization. Corn grain yield that year was relatively high in part due to the large

amount of rainfall in June, which was about 0.05 m above the 50 year average (Fig. 5).

In general, corn produced the highest grain yield in both higher and lower elevation field

segments when 120 or 180 kg N ha-1 were applied in a wetter year. Reasons for the

significant response to higher N rates in the wetter year were the decrease in residual soil

NO3–N with time (Tables 3 and 4) and greater water available for growth. Mean residual

NO3–N to 0.90 m depth was 33 and 21 kg ha-1 in 2007 versus 65 and 32 kg ha-1 in 2005

for higher and lower elevation field segments, respectively. Machado et al. (2002) similarly

found that in wet years the most limiting factor for corn production was NO3–N supply

with depth. Nitrogen may also be lost in the bottom segment in wetter years because of

higher clay content. Schepers et al. (2004) and Kravchenko and Bullock (2000) reported

crop N stress in lower areas during wet seasons partly because of N loss through leaching

and/or denitrification associated with excess water.

The CV of yield within the N transect is an indicator of the interaction of corn grain

yield response to variable N rate and growing season precipitation. Kravchenko et al.

(2005) found that variability of corn yield response to added N can increase in high rainfall

years. However, in our experiment, the greatest yield variation was observed in transects

with 0 kg N ha-1 in the drier year (CV 44.0%) in the lower elevation field segment and

potentially may be related to its clay content (Cox et al. 2003). The least variation in yield

was observed in transects receiving 180 kg N ha-1 in either higher (CV 4.3%) or lower

(CV 3.9%) elevation field segment in the wetter year. In general, less yield variation was

observed as N rates increased in the wetter year in this experiment.

Correlation coefficients between corn grain yield and NO3–N with depth and clay

content in transects receiving 120 kg N ha-1 in higher and lower elevation field segments

Precision Agric (2011) 12:146–163 159

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were calculated for 2005, 2006 and 2007 (Table 5). Corn grain yield was significantly and

positively related to residual NO3–N in all years regardless of field segment or landform

conditions. The highest correlations for corn grain yield and NO3–N were obtained at

deeper depths of either 0.60 or 0.90 m in the higher elevation field segment in 2007. The

high correlation of corn grain yield and residual NO3–N in this experiment supported

Kravchenko’s et al. (2005) findings that yield response to N could increase in higher

rainfall years. The lowest correlations between corn grain yield and NO3–N with depth

were observed in both higher and lower elevation segments in the drier year.

The relationship between corn grain yield and soil clay content was not consistent in

either higher or lower elevation field segments across years (Table 5). For example, corn

grain yield in the higher elevation field segment containing less clay had no relation with

clay content in 2005, 2006, or 2007. In the lower elevation segment, however, corn yield

had a positive, no, or a negative relationship with clay content in 2005, 2006, and 2007,

respectively. Corn yield in the lower elevation segment was negatively related to clay

content in the wetter year and positively related in the drier year.

Clay content was not related to residual soil NO3–N at any depth in the lower elevation

segment in any year (Table 5). Clay content in the higher elevation field segment was

positively related with residual NO3–N to 0.30 m depth in 2005, to 0.15 m in 2006, and

showed no relationship in 2007. Clay content was related to residual soil NO3–N to 0.90 m

depth, Nmin and SOC in the 20 ha field in 2004 (Table 2). It was anticipated that these

relationships might be stable and would continue over time. Stable relationships may have

allowed us to describe soil N supply using clay content as an auxiliary variable for

estimating soil NO3–N for variable rate fertilization (Baxter et al. 2003; Chen et al. 2004;

Han et al. 2003).

Table 5 Pearson correlation coefficients for corn grain yield, surface soil clay content and residual NO3–Nwith depth in 120 kg N ha-1 transects in top and bottom segments of the 20 ha field in 2005, 2006, and2007

Parameter Landformsegment

Correlation (r)

NO3–N0.15 m

NO3–N0.30 m

NO3–N0.60 m

NO3–N0.90 m

Clay

2005

Grain yield Higher 0.340** 0.365** 0.348** 0.312** –

Clay Higher 0.362* 0.269* – – –

Grain yield Lower 0.362** 0.269* – – 0.301*

Clay Lower – – – – –

2006

Grain yield Higher 0.289* 0.451** 0.460** 0.512*** –

Clay Higher 0.355* – – – –

Grain yield Lower 0.509*** 0.557*** 0.476** 0.468** –


2007

Grain yield Higher 0.678*** 0.746*** 0.776*** 0.772*** –

Clay Higher – – – – –

Grain yield Lower 0.518*** 0.580*** 0.559*** 0.584*** -0.521***


*, **, *** Significant at the 0.05, 0.01, or 0.001 level

160 Precision Agric (2011) 12:146–163

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At least two factors influence variable rate N fertilization for a spatially variable field.

The first is the degree of N spatial variability within the field, and the second is yield

response variability within management zones to achieve yield goals with recommended N

rates. Both these factors in our study were affected by soil N reserve with depth and

growing season precipitation. In addition, seasonal rainfall and N reserve with depth

affected corn yield differently depending on position in the field. More homogeneous sub-

regions were delineated based on clay content and elevation. Clay content interacted with

precipitation to influence soil N supply. Schepers et al. (2004) found management zones

within a field for variable rate N fertilization for corn would only have been beneficial 3

out of 5 seasons even under irrigation. In general, a major difficulty in implementing

variable rate technology in our field study was the inability to relate and accurately depict

the variation in residual N supply and its interaction with seasonal precipitation over time

(Schepers et al. 2004; Miao et al. 2006; Derby et al. 2007).

Conclusions

Strong relationships between the spatial distribution of corn grain yield, soil clay content,

and several soil N parameters were observed in a 64 ha field experiment in 2004. Corn

grain yield was negatively related to clay content and positively related to residual soil

NO3–N to depths of 0.60 and 0.90 m. These relationships were tested along with variable

rate N fertilization in more homogeneous sub-regions from 2005 to 2007. Corn yield

responded differently to variable rate N fertilization within these sub-regions across years.

Our results indicated the difficulty in consistently associating yields with soil conditions

and to clearly establish the benefit of variable rate N addition over conventional uniform

application in this field across years. Nitrogen is both spatially and temporally dynamic and

its availability to plants at any one location and time depends on many factors. Predictions

of growing season precipitation must become more accurate if residual soil NO3–N, clay

content, and other factors are to be effectively used as bases for variable rate N application.

However, site-specific management zones for corn production in this field may be war-

ranted if information about residual NO3–N with depth, clay content, and elevation are

known.

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