use of soil nitrogen parameters and texture for spatially
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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: h-shahandeh@tamu.edu
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
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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
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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
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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
NO3–N to 0.30 m depth (kg ha-1) 45 89 17 30
NO3–N to 0.60 m depth (kg ha-1) 68 117 29 27
NO3–N to 0.90 m depth (kg ha-1) 82 143 40 26
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
Grain yield 0 kg N ha-1 9940 a 10407 9092 15.8
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
Grain yield 0 kg N ha-1 6579 a 6704 4213 14.3
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)
Precision Agric (2011) 12:146–163 157
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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
Grain yield 0 kg N ha-1 1806 a 2300 892 44.0
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
Grain yield 0 kg N ha-1 6469 a 7548 5156 11.4
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
Grain yield 0 kg N ha-1 3308 a 4519 2136 22.6
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
123
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** –
Clay Lower – – – – –
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***
Clay Lower – – – – –
*, **, *** 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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