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Abstract and Figures

Subsurface drip irrigation (SDI), because it can precisely deliver nutrients close to plant roots, could lead to carefully determined applications of fertilizer to meet crop needs and less risk of nitrate (NO3) leaching to groundwater. Appropriate fertilizer applications, however, depend on an accurate assessment of the spatial distribution of the main plant macronutrients (N, P and K) in the soil profile before planting. To develop nutrient sampling guidelines, we determined the spatial distributions of preplant nitrate (NO3), bicarbonate extractable phosphorus (Olsen-P) and exchangeable potassium (K) in the top 20 inches (50 centimeters) of subsurface drip irrigated processing tomato fields in three of the main growing regions in the Central Valley of California. Nutrient distribution varied with depth (P and K), distance from the center of the bed (NO3) and growing region (NO3 and K). No depletion of NO3, Olsen-P, or K in the root feeding areas close to the drip tape was detected. Preplant NO3 ranged considerably, from 45 to 438 pounds N per acre (50 to 491 kilograms/hectare), the higher levels in fields with consecutive crops of tomatoes. A sampling protocol that growers could use, developed from analysis of the distribution results, provided reliable estimates of preplant NO3 as well as P and K in all surveyed fields.
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222 CALIFORNIA AGRICULTURE • VOLUME 69, NUMBER 4
Soil sampling protocol reliably estimates preplant NO
3
in SDI tomatoes
by Cristina Lazcano, Jordon Wade, William R. Horwath and Martin Burger
Subsurface drip irrigation (SDI), because it can precisely deliver nutrients close to plant
roots, could lead to carefully determined applications of fertilizer to meet crop needs
and less risk of nitrate (NO
3
) leaching to groundwater. Appropriate fertilizer applica-
tions, however, depend on an accurate assessment of the spatial distribution of the
main plant macronutrients (N, P and K) in the soil prole before planting. To develop
nutrient sampling guidelines, we determined the spatial distributions of preplant
nitrate (NO
3
), bicarbonate extractable phosphorus (Olsen-P) and exchangeable potas-
sium (K) in the top 20 inches (50 centimeters) of subsurface drip irrigated processing
tomato elds in three of the main growing regions in the Central Valley of California.
Nutrient distribution varied with depth (P and K), distance from the center of the bed
(NO
3
) and growing region (NO
3
and K). No depletion of NO
3
, Olsen-P or K in the root
feeding areas close to the drip tape was detected. Preplant NO
3
ranged considerably,
from 45 to 438 pounds N per acre (50 to 491 kilograms/hectare), the higher levels in
elds with consecutive crops of tomatoes. A sampling protocol that growers could use,
developed from analysis of the distribution results, provided reliable estimates of pre-
plant NO
3
as well as P and K in all surveyed elds.
S
ubsurface drip irrigation (SDI) al-
lows for a precise delivery of water
and nutrients close to plant roots,
making it possible for growers to increase
water and nutrient use efciency and crop
yields.
Efcient use of nitrogen (N) is gaining
importance in terms of lowering the risk
of nitrate (NO
3
) leaching into ground-
water during the rainy and irrigation
seasons. Avoiding a buildup of large sur-
pluses of residual N is feasible under SDI
if the available N at preplant can be reli-
ably quantied. Our primary goal in this
study was to develop guidelines on how
to reliably, efciently and economically
sample for preplant NO
3
in processing
tomato elds under SDI.
A recent survey among tomato grow-
ers showed that soil NO
3
is determined
in only a limited number of elds every
year at preplant (Geisseler et al. 2015).
Online: http://californiaagriculture.ucanr.edu/
landingpage.cfm?article=ca.v069n04p222&fulltext=yes
doi: 10.3733/ca.v069n04p222
Martin Burger
Although subsurface drip irrigation is widely used
in California to produce processing tomatoes,
knowledge of nutrient distribution at preplant is
limited. To address this, UC researchers developed
a sampling protocol that can be used to estimate
preplant levels of nitrate, phosphorus and potassium.
Research Article
http://californiaagriculture.ucanr.edu OCTOBER–DECEMBER 2015 223
Currently, N fertilizer rates for processing
tomatoes of about 178 pounds per acre
(lb/ac) (200 kilograms per hectare [kg/ha])
are recommended under SDI (Hartz and
Bottoms 2009; Tei et al. 2002). Tomato
plants take up an average of 263 lb/ac
(296 kg/ha), with 71% of the N allocated
to the fruit by harvest (Hartz and Bottoms
2009). N concentration in fruit at optimum
fertilization rates has been reported as
4.47 pounds per U.S. ton (lb/US tn) (2.24
kilograms per megagram [kg/Mg]) mar-
ketable fruit (Tei et al. 2002).
Mineral fertilizer is considered the
main source of N in conventionally man-
aged tomato systems, but other sources
such as soil residual, or carryover, NO
3
,
mineralization of soil organic matter, and
NO
3
in irrigation water contribute to
the supply of crop-available N. The latter
sources are often not considered in fertil-
izer rate calculations, and as a result, N
inputs can be in excess of crop need.
There are several difculties in esti-
mating preplant NO
3
levels, a concern
mentioned in Dzurella et al. (2012): (1)
NO
3
is one of the plant nutrients with the
highest mobility, and therefore highest
spatial variability, in soils, which makes
it difcult to estimate total available N.
(2) Under SDI, NO
3
may accumulate at
the periphery of the wetted soil volume
and be depleted where roots prolifer-
ate at high density, such as near the drip
tape emitter (Lecompte et al. 2008). As a
consequence, NO
3
concentration in fur-
rows can be up to 16 times higher than
in the center of the bed (Lecompte et al.
2008). (3) NO
3
concentration and
spatial
distribution might be affected by ratios of
atmospheric precipitation to evapotrans-
piration (ET).
The extent and distribution of pre-
cipitation determines NO
3
leaching po-
tential, especially under Mediterranean
climate conditions (Poch-Massegú et al.
2014), with greater downward movement
of NO
3
occurring seasonally; whereas at-
mospheric variables, such as temperature,
affect NO
3
movement through their in-
uence on evapotranspiration rates. Both
irrigation management and weather con-
ditions affect NO
3
levels and spatial dis-
tribution. Therefore, measurements under
varied climatic conditions are necessary
to assess the extent such factors have on
NO
3
distribution in drip-irrigated pro-
cessing tomato elds.
Unlike NO
3
, phosphorous (P) and
potassium (K) are less mobile in the soil
prole. While less mobility reduces the
loss of these nutrients through leaching,
it also limits diffusion from enriched soil
patches outside of the root growth zone.
As a result, elds with several years of
SDI cultivation might present a character-
istic depletion within the root zone, where
nutrient uptake is most intense (Hartz
and Hanson 2009).
In spite of the widespread use of SDI
in processing tomatoes, there is a lack of
knowledge of the spatial distribution of
the main plant macronutrients (N, P and
K) at preplant. Complicating this further,
management practices (i.e., rotations,
continuous SDI cultivation) and climatic
factors (i.e., precipitation and evapotrans-
piration) inuence the spatial distribution
of these nutrients.
We carried out a survey to address
the lack of knowledge in this area: we as-
sessed preplant distribution of NO
3
, ex-
tractable P and exchangeable K in relation
to the SDI line in commercial processing
tomato elds. Crop N uptake and nitro-
gen use efciency were evaluated in rela-
tion to preplant inorganic N levels and
Preplant soil samples were collected at 5-inch intervals from the center of the bed towards the center of
the furrow.
Weighing of the vine biomass,
left, and fruit biomass, right,
collected at each location
within a eld. Vine biomass,
which is incorporated into the
soil after harvest, contributed
an average N input of 109 lb/ac.
Cristina Lazcano
Cristina Lazcano
Cristina Lazcano
224 CALIFORNIA AGRICULTURE • VOLUME 69, NUMBER 4
fertilizer N inputs in order to evaluate the
performance of current practices of SDI
processing tomato production. The main
goal, as mentioned above, was to develop
guidelines on the simplest way to reliably
assess preplant NO
3
.
Sampling sites, procedures
A total of 16 commercial processing
tomato production elds were selected
for the study. Fields were located along a
transect of a decreasing ratio of precipita-
tion to potential evapotranspiration (ET
o
),
with six elds in Yolo County (ET
o
= 1.01),
four in San Joaquin County (ET
o
= 0.54)
and six in Fresno County (ET
o
= 0.31),
three of the growing regions with the
largest production of processing tomatoes
in the state.
The selected elds had been cultivated
under SDI for a minimum of 2 and a
maximum of 9 years. Fields comprised a
range of different management conditions
typical of processing tomato production
in California, including different bed
sizes (60 versus 80 inches [in], or 1.5 ver-
sus 2 meters [m]), the number of consecu-
tive years in tomato production and the
planting of fall/winter crops in the elds
(table 1).
Preplant soil sampling was carried
out in all 16 elds from late February
to mid-May, depending on the planting
schedule and before the application of
any fertilizers. In each eld, ve random
locations were selected and a systematic
sampling was carried out using a soil
probe at regular (5 in, or 13 centimeter
[cm]) intervals from the center of the
bed to the center of the furrow. At each
sampling point, two sets of soil from 0
to 10, and 10 to 20 inches (0 to 25, and
25 and 50 cm) in depth were taken and
composited per depth. The exact position
of the ve sampling locations (± 9.8 feet,
or 3 m) was recorded using GPS latitude-
longitude coordinates in order to collect
plant and soil samples from the same
locations at harvest. Harvest NO
3
con-
centrations were measured before the
incorporation of vine residue by taking
one core 10 inches from the center of the
bed to a depth of 20 inches at each of the
ve locations per eld.
Analysis of soil samples
The soil samples were stored in plastic
bags, transported to the laboratory and
stored at 4°C. Gravimetric soil moisture
content was determined immediately
after collection by drying a subsample
at 221°F (105°C). In addition, a 10-gram
subsample was immediately extracted
with 2M potassium chloride (KCl) so-
lution for the colorimetric analysis of
NO
3
concentration (Doane and Horwath
TABLE 1. Main characteristics and management practices of the 16 elds sampled
County
Field ID Soil series
Soil texture*
Drips/
bed
Years
under
drip
Consecutive
years with
tomatoes†
Bed size
(in)
Drip
depth
(in)
Cover/
winter
crop
Fertilizer inputs
% Sand % Clay Preplant In-season
Fall/
winter
Yolo Y1 Yolo silt loam 11.3 21.0 1 2 1 80 na No 8-24-5-0.5
(Zn)
UN-32 None
Y2 Sycamore silt
loam
11.3 21.0 1 60 na No 8-24-5-0.5
(Zn)
UN-32 None
Y3 Marvin silty
clay loam
34.0 23.0 1 2 1 60 12 Triticale 8-24-5-0.5
(Zn)
28-0-0-5 (S) Gypsum
Y4 Tehama loam 34.0 23.0 1 4 2 60 12 Triticale 8-24-5-0.5
(Zn)
28-0-0-5 (S) Gypsum
Y5 Capay silty
clay
5.5 47.5 1 9 0 60 10 Triticale 8-24-6 UN-32, 0-0-
14, HPhos32
Manure
Y6 Brentwood
silty clay
5.5 47.5 1 2 0 60 10 Triticale 8-24-6 UN-32, 0-0-
14, HPhos32
Manure
San
Joaquin
SJ1 Stockton clay 13.7 50.0 2 5 0 80 12 No 10-34-0 UN-32,
CAN17, KCl
None
SJ2 Jacktone clay 22.1 50.0 2 5 1 80 12 No 10-34-0 CAN17, KCl None
SJ3 Capay clay 29.5 39.2 1 4 4 60 na Triticale 8-24-6-3
(Zn)
UN-32 None
SJ4 Stomar clay
loam
22.1 50.0 1 3 4 60 na Triticale 8-24-6-3
(Zn)
1-3-10 None
Fresno F1 Westhaven
loam
33.0 29.5 1 4 2 60 12 Grain crop Transplant
supreme
15-15-0,
CAN17
None
F2 Calax clay
loam
27.5 35.0 1 4 4 60 12 Grain crop Transplant
supreme
15-15-0,
CAN17
None
F3 Fresno ne
sandy loam
52.0 21.2 1 5 5 60 12 No 4-10-10 UN-32 None
F4 Fresno ne
sandy loam
52.0 21.2 1 4 4 60 12 No 4-10-10 UN-32 None
F5 Westhaven
loam
34.0 21.0 1 3 2 80 15 No 6-21-0 UN-32, 22-
5.9-0.6 (S)
None
F6 Westhaven
loam
34.0 21.0 1 3 2 80 15 No 6-21-0 UN-32, 22-
5.9-0.6 (S)
None
* At 0–20 inches.
† Before the study.
http://californiaagriculture.ucanr.edu OCTOBER–DECEMBER 2015 225
2003). Available Olsen-P was analyzed
colorimetrically after extraction with so-
dium bicarbonate (NaHCO
3
) (Kuo 1996).
Exchangeable K was determined by in-
ductively coupled plasma atomic emission
spectrometry (ICP-AES) on an air-dried
and ground preplant soil subsample af-
ter extraction with ammonium acetate
(Thomas 1982).
N uptake and use eciency
Crop N uptake was determined by
hand-harvest at the preplant sampling
locations. Briey, we sampled a length
of 1 meter along the bed and all plants
within this meter were counted and cut at
soil level. Fruit and vines were separated,
weighed and a subsample of both com-
ponents selected for further determina-
tion of dry mass and percentage N (% N)
through dry combustion on a C and N an-
alyzer (Costech Analytical Technologies
Inc., Valencia, CA) (Dumas 1848).
Vine and fruit biomass and % N per
plant were calculated and then extrapo-
lated to the rest of the eld using plant
density of the area harvested. Apparent
nitrogen use efciency of the tomato
crop (NUE
C
) was calculated as the ratio
between N uptake by the tomato crop,
including fruit and vine sampled at each
eld, and the available N, taking into
account both the preplant soil NO
3
and
the fertilizer inputs reported by the
growers.
Nitrogen outputs were calculated
based on the marketable yields reported
by the growers and the average N content
of the fruit sampled from the hand-har-
vest plots. Apparent nitrogen use ef-
ciency of the harvested fruit (NUE
F
)
was
calculated as the ratio between N outputs
in the harvested fruit and the available N,
including preplant soil NO
3
and fertil-
izer inputs.
P levels and distribution
Twelve of the 16 elds showed signi-
cantly higher Olsen-P concentration in
the upper layer of soil than the deeper
layer (g. 1). Concentrations were homo-
geneous across the beds, with only two
elds showing signicant differences be-
tween sampling points (data not shown).
Signicant differences in extractable P
between sampling distances from the cen-
ter of the bed were observed in the Yolo
growing region, with higher concentra-
tions closer to the center of the bed (g. 1).
No signicant differences between
growing regions were detected (p = 0.77),
although average concentrations in the 0
to 20 inches soil layer tended to be highest
in the Fresno (13.7 ± 3.1 parts per million,
ppm) area, followed by the Yolo and San
Joaquin areas (12 ± 1.7 and 10.6 ± 2.9 ppm,
respectively).
Our study showed that Olsen-P was
not lower within the root growth area
than outside of it. This nding was in
contrast to the earlier suggestion that the
amount of available P can substantially
decline close to the drip tape because of
concentrated root feeding (Hartz and
Hanson 2009). In fact, in this study, within
the Yolo County area, Olsen-P concen-
trations were higher closer to the center
of the bed and decreased toward the
furrows.
The majority of the elds in this
study showed average P concentrations
lower than 15 ppm in both layers (table
2), within the threshold value of 12 to 20
ppm, where there is potential for a yield
response to a P application. Generally,
elds with < 15 ppm of available P would
TABLE 2. Preplant concentration of Olsen-P and exchangeable K in the 16 elds sampled
County
Field ID
Preplant PO
4
-P (ppm) Preplant K (meq/100 grams)
Average
0–10 inch
depth
10–20 inch
depth Average
0–10 inch
depth
10–20 inch
depth
Yolo Y1 7.6 11.4 3.8 0.6 0.7 0.5
Y2 13.5 17.2 9.7 0.6 0.7 0.6
Y3 18.1 21.1 15.1 0.8 0.8 0.8
Y4 7.2 9.8 4.7 0.6 0.6 0.6
Y5 14.6 12.0 17.2 1.2 1.0 1.3
Y6 11.2 11.9 10.6 0.7 0.7 0.7
San Joaquin SJ1 4.5 4.6 4.4 1.2 1.2 1.2
SJ2 8.4 8.3 8.5 0.6 0.6 0.6
SJ3 18.6 25.6 11.7 1.1 1.3 0.9
SJ4 10.9 12.5 9.4 0.9 0.9 0.8
Fresno F1 13.9 16.8 10.9 1.1 1.2 1.0
F2 9.5 11.9 7.1 1.4 1.6 1.2
F3 28.0 35.5 20.5 1.5 1.7 1.2
F4 15.3 21.6 9.1 0.7 0.7 0.5
F5 6.7 7.9 5.6 1.2 1.1 1.2
F6 8.7 10.2 7.2 1.42 1.68 1.15
0–10 in 10–20 in
0–10 in 10–20 in
0–10 in 10–20 in
0
5 10 15 20 25 30 35 40
5
10
15
20
25
0
5 10 15 20 25 30 35 40
5
10
15
20
25
0
5
10
15
20
25
PO
4
(ppm)
Yolo County
San Joaquin County
Fresno County
Distance
PO
4
(ppm)PO
4
(ppm)
5 10 15 20 25 30 35 40
Depth: p < 0.001
Distance: p < 0.001
Depth*distance: p = 0.70
Depth: p < 0.001
Distance: p = 0.32
Depth*distance: p = 0.15
Depth: p < 0.001
Distance: p = 0.93
Depth*distance: p = 0.18
Fig. 1. Change in PO
4
content of the soil at
dierent distances from the center of the bed
and at two depth intervals (0 to 10, and 10 to 20
inches) in Yolo, San Joaquin and Fresno counties.
Statistical signicance of the depth, distance and
the interaction between them (depth*distance) is
shown at each of the three growing regions.
226 CALIFORNIA AGRICULTURE • VOLUME 69, NUMBER 4
0–10 in 10–20 in
0–10 in 10–20 in
0–10 in 10–20 in
5 10 15 20 25 30 35 40
5 10 15 20 25 30 35 40
0.0
0.4
0.8
1.2
1.6
2.0
0.2
0.6
1.0
1.4
1.8
0.0
0.4
0.8
1.2
1.6
2.0
0.2
0.6
1.0
1.4
1.8
0.0
0.4
0.8
1.2
1.6
2.0
0.2
0.6
1.0
1.4
1.8
K
+
(meq/100 g)
Yolo County
San Joaquin County
Fresno County
Distance
K
+
(meq/100 g)K
+
(meq/100 g)
5 10 15 20 25 30 35 40
Depth: p < 0.01
Distance: p = 0.41
Depth*distance: p = 0.26
Depth: p < 0.01
Distance: p < 0.01
Depth*distance: p = 0.23
Depth: p < 0.01
Distance: p = 0.01
Depth*distance: p = 0.03
respond to a P application, whereas elds
with more than 25 ppm would be unlikely
to do so (Hartz 2008). In this study, only
one of the elds had extractable P higher
than 25 ppm. These results show that
some of the elds could benet from addi-
tional P fertilization, yet current fertiliza-
tion practices are effective in avoiding P
depletion in the root-feeding zone.
K levels and distribution
Soil exchangeable K content was
mostly homogeneous within the beds,
and no depletion was observed close to
the drip tape in any of the three growing
areas (g. 2). The lack of K depletion in
the root zone may be because potassium
can easily be supplied through fertigation,
with the advantage of little potential for
xation before the plants take it up since
K xation in interlayer sites of soil min-
erals mainly takes place during drying
following water additions (Cassman et al.
1990). As shown in table 2, average eld
exchangeable K concentrations were gen-
erally high and well above 130 to 150 ppm
(0.33 to 0.38 meq/100 g [grams]), which
has been dened as the threshold for
yield responses in furrow-irrigated pro-
cessing tomato in California (Hartz 2002;
Hartz and Hanson 2009; Miyao 2002).
For drip irrigation, yield thresholds
have been estimated to be higher at 200
to 300 ppm (0.51 to 0.77 meq/100 g),
although there is still limited informa-
tion available in this respect (Hartz and
Hanson 2009). All elds were above 200
ppm (0.51 meq/100 g), meaning that yield
increases resulting from K additions
could not be expected; however, K appli-
cations benet fruit quality even at levels
that are not yield limiting (Hartz et al.
2005).
High exchangeable K is not rare in
processing tomato soils; concentrations
ranging from 187 to 331 ppm (0.48 to 0.85
meq/100 g) have been previously reported
for the Yolo growing region (Hartz et al.
2005). Concentrations reported in our
survey are, however, well over these val-
ues, particularly in Fresno County (1.20 ±
0.12 meq/100 g) followed by San Joaquin
(0.95 ± 0.14 meq/100 g) and Yolo counties
(0.75 ± 0.12 meq/100 g), with signicant
differences between the three growing ar-
eas (p < 0.01). Exchangeable K was similar
at the two depths in Yolo County (g. 2),
whereas K concentrations were higher
in the upper soil layer in Fresno and San
Joaquin counties (p < 0.01 and p < 0.05,
respectively). In the elds in San Joaquin
County, K concentration tended to de-
crease from the center of the bed toward
the furrow.
NO
3
levels and NUE
Preplant NO
3
-N in the depth interval
of 0 to 20 inches (0 to 50 cm) ranged from
45 to 438 lb/ac (50 to 491 kg/ha) among
all the elds. The average NO
3
-N
content
in this layer was signicantly higher in
San Joaquin and Fresno counties (232 ± 31
and 216 ± 54 lb/ac, or 261 ± 34 and 243 ± 61
tn/ha, respectively) than in Yolo County
(70 ± 8 lb/ac, or 79 ± 9 tn/ha) (p < 0.001).
The growers reported seasonal fertil-
izer N inputs ranging from 115 to 320
lb/ac (129 to 360 kg/ha), bringing total
available N (preplant NO
3
and fertilizer
N) to range from 209 to 758 lb/ac (235
to 852 kg/ha)
(table 3). According to the
hand-harvest data, average whole plant
N uptake was 274 lb/ac (308 kg/ha), with
a range of 150 to 401 lb/ac (167 to 451
kg/ha) among all the elds. The results
of our survey suggest that N fertilization
could be decreased without yield penalty
in some of the elds, especially those in
Fresno and San Joaquin counties.
Preplant NO
3
concentrations were
positively correlated with the number
of consecutive years that the elds were
cropped with processing tomatoes
(R
2
= 0.67; p < 0.01). In Yolo County, the
number of years of consecutive tomato
was between 0 and 2, whereas in San
Joaquin and Fresno counties it was
between 0 and 5 (table 1). These differ-
ences in years of consecutive tomato
production may, in part, explain the
differences in preplant NO
3
levels
observed among the processing tomato
growing areas. Another likely reason
for the higher preplant NO
3
levels in
Fresno County may be the lower rain-
fall in this area. Lower precipitation and
higher evaporation rates in Fresno may
lower leaching and promote buildup of
NO
3
closer to the soil surface, whereas
in Yolo County, which receives more
rainfall, some of the residual NO
3
may
have been leached below 20 inches
(50 cm) during the rainy season.
Crop marketable yield reported
by the growers in the different elds
ranged from 39.9 to 63.1 tn/ac (90.7 to
143.3 Mg/ha) (table
3), being higher in
the Fresno (57.1 ± 2.9 tn/ac, or 130 ± 6.5
Mg/ha) than the San Joaquin and Yolo
growing regions (51.9 ± 4 tn/ac
, and 49.9
± 2.6 tn/ac or 116.7 ± 9 Mg/ha and 112.3
± 5.85 Mg/ha, respectively). Similar crop
yields have been reported by Hartz and
Bottoms (2009) for Yolo County.
Tomato plants took up between 150
and 401 lb/ac of N (table 3), of which they
allocated between 82 and 251 lb/ac to fruit
Fig. 2. Exchangeable K content of the soil at
dierent distances from the center of the bed
and at two depth intervals (0 to 10, and 10 to 20
inches) in Yolo, San Joaquin and Fresno counties.
Statistical signicance of the depth, distance and
the interaction between them (depth*distance) is
shown at each of the three growing regions.
Preplant NO
3
-N in the depth interval of 0 to 20 inches
(0 to 50 cm) ranged from 45 to 438 lb/ac (50 to 491 kg/ha).
http://californiaagriculture.ucanr.edu OCTOBER–DECEMBER 2015 227
production, representing between 55%
and 63% of total plant N. Fruit N alloca-
tion was, in most cases, lower than that
reported by Hartz and Bottoms (2009) for
processing tomatoes with adequate N fer-
tilization. Across the 16 elds studied, the
apparent NUE
C
was highly variable, rang-
ing between 1.25 and 0.52 (table 3), and
being higher for Yolo County (0.92 ± 0.11)
than for Fresno and San Joaquin counties
(0.80 ± 0.08 and 0.78 ± 0.10, respectively).
Nitrogen outputs in the harvested crop
ranged from 93 to 174 lb/ac (105 to 196
kg/ha; table 3), and the apparent N use ef-
ciency of the harvested fruit (NUE
F
) was
between 0.15 and 0.64 (table 3).
NUE
C
values close to or above 1 show
that soil sources other than fertilizer or
preplant N contributed to plant uptake.
In-season soil mineralized N and NO
3
in
irrigation water can be substantial sources
of N for the tomato plants in addition
to fertilizer or preplant N. To estimate
potential mineralizable N, subsamples of
10 grams of air-dried soil from the surface
layer, 0 to 10 inches (0 to 25 cm), of the 16
elds were incubated in the laboratory
under aerobic conditions at 55% water
holding capacity. After 105 days, miner-
alization of organic N sources provided
an average of 53 lb/ac (60 kg/ha) as NH
4
+
and NO
3
, with some elds producing
as much as 82 lb/ac (91 kg/ha) (table 3).
Earlier, Krusekopf et al. (2002), following
a similar procedure, arrived at the same
average estimate of mineralized N of 53.4
lb/ac (60 kg/ha) in a study involving 10
tomato elds in the Sacramento and San
Joaquin valleys.
Vine biomass, which is incorporated
into the soil after harvest, contributed
an average input of 109 lb/ac (122 kg/ha)
(table 3) and could represent a large part
of this potentially mineralizable N pool.
In addition to the N that becomes avail-
able during crop growth, NO
3
in the
irrigation water can also be a substantial
source of N. No data was collected in this
study regarding the NO
3
content of ir-
rigation water at the different elds. One
of the growers reported that an average
of 21 lb/ac (24 kg/ha) was supplied to
the crop in the irrigation water. If these
two N inputs (i.e., mineralization and
irrigation water) are taken into account,
then the actual crop NUE is lower than
reported here.
In the present study, postharvest, or
residual, NO
3
concentrations measured
to a depth of 20 inches ranged from 43
to 392 lb/ac NO
3
-N (48 to 441 kg/ha),
with an average of 141 lb/ac NO
3
-N
(159 kg/ha) (table 3). This survey showed
high residual levels of NO
3
in some to-
mato elds. Fields exhibiting low NUE
and high levels of residual NO
3
have a
greater leaching potential during the ir-
rigation season and/or during winter.
These elds would benet from fertilizer
applications that are adjusted according to
preplant soil NO
3
concentrations.
Nutrient distribution
No general pattern in NO
3
-N distribu-
tion around the drip tape was observed
across the 16 elds, although signicant
differences in NO
3
-N concentration be-
tween sampling distances from the center
of the bed were observed for the majority
of the 16 elds (data not shown). When the
data was averaged across each growing
region, elds from Fresno County showed
a higher NO
3
-N concentration at 15 and
20 inches (38 and 51 cm) than 5 inches (13
cm) from the center of the bed, particu-
larly in the upper layer, 0 to 10 inches (0
to 25 cm), of soil; whereas in Yolo County,
NO
3
-N concentrations decreased with
increasing distance from the drip tape
(g. 3).
TABLE 3. Preplant N levels, N inputs, N uptake in the crop and residual soil N in the 16 elds of the study
County
Field ID
Preplant NO
3
-N (lb/ac )
Fertilizer N
(lb/ac)
Total
available N
(lb/ac)
Marketable
yield
(tn/ac)
N output†
(lb/ac)
Crop N (lb/ac )*
NUEC* NUEF†
Min N
(lb/ac)
Residual
soil N
(lb/ac)
0–20’
depth
0–10’
depth
10–20’
depth Vine Fruit
Whole
plant
Yolo Y1 78.2 38.5 39.8 175 253 58.2 148 145 172 317 1.25 0.58 46.0 53
Y2 106.1 71.2 52.6 177 283 58.3 n.d.‡ n.d. n.d. n.d. n.d. n.d. 55.3 n.d.
Y3 62.0 29.7 25.4 147 209 48.9 134 65 112 177 0.85 0.64 60.9 83
Y4 62.6 21.0 21.9 146 209 49.9 120 66 157 223 1.07 0.57 58.7 107
Y5 45.0 20.6 24.4 213 258 40.7 93 68 82 150 0.58 0.36 50.2 70
Y6 64.7 30.1 34.5 187 252 51.9 123 84 133 217 0.86 0.49 n.d. 125
San
Joaquin
SJ1 199.4 87.1 109.6 115 314 57.0 111 99 180 279 0.89 0.38 38.9 152
SJ2 159.2 73.6 88.3 135 294 55.0 118 110 179 289 0.98 0.38 61.3 123
SJ3 293.0 159.6 133.5 220 513 55.7 156 168 198 366 0.71 0.30 55.2 392
SJ4 275.1 142.7 132.4 220 495 39.9 124 121 136 257 0.52 0.25 58.8 339
Fresno F1 115.7 82.6 70.1 205 321 60.8 172 107 183 290 0.90 0.54 49.8 132
F2 171.7 75.1 104.1 205 377 61.7 174 116 216 332 0.88 0.46 44.8 111
F3 437.7 244.1 193.6 320 758 45.5 110 150 251 401 0.53 0.15 70.8 43
F4 318.0 200.9 117.0 320 638 53.3 n.d. n.d. n.d. n.d. n.d. n.d. 81.7 n.d.
F5 113.4 55.1 58.3 187 300 57.9 150 139 143 282 0.94 0.50 31.8 89
F6 142.6 76.3 66.3 208 351 63.1 147 82 180 262 0.75 0.42 28.0 151
* Based on hand-harvest at ve locations in each eld.
† Based on marketable yields reported by growers.
‡ n.d. = Not determined.
228 CALIFORNIA AGRICULTURE • VOLUME 69, NUMBER 4
Concentrations of NO
3
-N at the two
sampling depth intervals (0 to 10 and 10 to
20 in) were generally similar. Signicant
differences were only observed in Fresno
County (p < 0.01, g. 3), supporting the
hypothesis that in areas with lower pre-
cipitation, more NO
3
may accumulate in
the upper layer, whereas NO
3
in the soil
surface layer is leached to lower layers in
areas receiving more precipitation, ho-
mogenizing NO
3
-N concentration in the
soil prole.
NO
3
sampling protocol
With the information on preplant
spatial distribution of nutrient concentra-
tions, we elaborated a sampling protocol
that accurately estimates the amount of
NO
3
-N in the top 20 inches (50 cm) of
SDI processing tomato elds. The protocol
was based on a Minimax analysis by se-
lecting the minimum number of samples
within the eld and locations within the
bed (i.e., distances from the drip tape)
that best estimated soil NO
3
-N based
on the criterion of the minimum rela-
tive error from the eld average. Briey,
for all the elds, the amounts of NO
3
-N
in the two soil layers were summed for
each sampling distance from the center.
Subsequently, the averages of all possible
combinations of sample locations within
the bed or within the eld were compared
to the eld average of all the measure-
ments in a given eld, and the relative
errors were obtained according to the fol-
lowing formula:
Relative error = (|X
D
– X
F
|/X
F
)
¯
¯
¯
¯
where
X
D
¯
¯
is the average NO
3
-N concen-
tration for the given combination of 1, 2, 3,
4 or 5 sampling distances within the bed,
and
X
F
¯
is the average NO
3
-N concentra-
tion of the eld.
The combination of samples with
the lowest relative error across all elds
(< 5% from the eld mean) and the lowest
number of samples taken was selected as
the best sampling procedure to estimate
average soil NO
3
-N. Calculations were
made separately for elds with 80-inch
and 60-inch beds, with SAS version 9.1
statistical software.
We found that in elds with 80-inch
(2 m) beds taking two cores at 15 and
30 inches (38 and 76 cm) or at 20 and 25
inches (51 and 64 cm) from the bed center
reduced the sampling error to 4% and 3%,
respectively (table 4). For 60-inch (1.5 m)
beds, taking three cores at 5, 10 and 20
inches (13, 25 and 51 cm) or at 5, 20 and
25 inches (13, 51 and 64 cm) reduced the
sampling error to 4% of the eld average
(table 5). In addition, the Minimax analy-
sis showed that these samples should be
taken in at least four different locations
within the eld in 80-inch (2 m) beds, and
in at least three locations in elds with
60-inch (1.5 m) beds.
This sampling method also guarantees
the collection of representative samples
for Olsen-P and exchangeable K. In the
case of P, in the elds with 80-inch (2 m)
beds, collecting two soil samples at 15 and
30 inches or at 20 and 25 inches from the
bed center would result in a sampling er-
ror of 11% and 12%, respectively. In elds
with 60-inch (1.5 m) beds, collecting three
soil samples at 5, 10 and 20 inches or 5,
20 and 25 inches would yield a sampling
error of 10% and 5%, respectively. In the
case of exchangeable K, the sampling er-
ror would be signicantly lower because
of the higher homogeneity of this nutri-
ent’s distribution across the beds. In elds
with 80-inch (2 m) beds, we observed a
sampling error of 3% in either of the com-
bination of sampling distances (15 and 30
inches or 20 and 25 inches) and in 60-inch
(1.5 m) beds of 2% and 1%.
TABLE 4. Average NO
3
-N content of the whole eld and of samples taken at dierent distances from the center of the bed across 80-inch beds
Field ID
Whole eld
Average NO₃
-N content
lb/ac
5’’ 10’ 15’ 20’ 25’ 30’ 35’ 40’ 15’ + 30’ 20’ + 25’
(12.7 cm) (25.4 cm) (38.1 cm) (50.8 cm) (63.5 cm) (76.2 cm) (88.9 cm) (101.6 cm) (38.1 + 76.2 cm) (50.8 + 63.5 cm)
Y1 78.2 106.9 92.1 93.4 72.3 78.7 72.0 52.0 58.4 82.7 75.5
SJ1 159.2 167.0 162.7 138.3 136.8 186.2 180.0 167.1 135.1 159.1 161.5
SJ2 199.4 206.5 182.0 169.4 237.9 187.8 196.6 210.6 204.0 183.0 212.9
F5 113.4 111.7 175.1 123.7 125.8 102.1 96.3 88.5 84.1 110.0 113.9
F6 148.8 187.9 198.9 150.0 152.5 151.8 132.5 123.4 65.6 141.2 152.2
Relative error (%)* 14.6 23.4 11.5 10.9 7.1 9.7 16.7 24.9 4.4 2.9
* Relative error from the eld average of the dierent sampling distances and best combination of sampling distances is according to the Minimax analysis.
0–10 in 10–20 in
0–10 in 10–20 in
0–10 in 10–20 in
0
5 10 15 20 25 30 35 40
40
10
30
20
60
50
0
5 10 15 20 25 30 35 40
40
20
80
60
120
100
160
140
200
180
0
5
10
15
20
25
NO
3
−N(lb ac)
Yolo County
San Joaquin County
Fresno County
Distance
NO
3
−N(lb ac)NO
3
−N(lb ac)
5 10 15 20 25 30 35 40
Depth: p = 0.14
Distance: p = 0.01
Depth*distance: p = 0.84
Depth: p = 0.72
Distance: p = 0.04
Depth*distance: p = 0.93
Depth: p = 0.006
Distance: p < 0.001
Depth*distance: p = 0.18
Fig. 3. NO
3
content of the soil at dierent
distances from the center of the bed and at two
depth intervals (0 to 10, and 10 to 20 inches).
Average NO
3
content and standard errors by
county for each layer and 5-inch lateral distance
are shown. Statistical signicance of the depth,
distance and the interaction between them
(depth*distance) is shown at each of the three
growing regions.
http://californiaagriculture.ucanr.edu OCTOBER–DECEMBER 2015 229
The data collected in this study pro-
vides a snapshot of current management
practices and soil nutrient status for SDI
processing tomatoes in California. It
shows considerable buildup of residual
NO
3
in soils, particularly after several
years of consecutive processing tomato
cultivation. Regular preplant soil sam-
pling using the protocol developed in
this study would enable growers to adjust
fertilizer rates, reduce the occurrence of
excessive NO
3
levels and detect subopti-
mal nutrient levels in their elds. Yet, how
much of the pre-plant NO
3
available can
be accessed by the roots is contingent on
the SDI wetting pattern, which may vary
among elds depending on soil hydraulic
properties. c
C. Lazcano is Adjunct Assistant Professor in the
Department of Geography at the University of Calgary
and was previously Postdoctoral Researcher in the
Department of Land, Air and Water Resources at UC
Davis; J. Wade is Graduate Student Researcher; W.R.
Horwath is Professor of Soil Biogeochemistry; and M.
Burger is Associate Project Scientist in the Department of
Land, Air and Water Resources at UC Davis.
We would like to thank the farm advisors Brenna J.
Aegerter and Thomas Turini from UC ANR Cooperative
Extension, who greatly contributed to the organization
of the project and the search for collaborating growers.
Authors are also grateful to the California Tomato
Research Institute for financial support, as well as
the processing tomato growers who participated in
this study.
TABLE 5. Average NO
3
-N content of the whole eld and of samples taken at dierent distances from the center of the bed across 60-inch beds
Average NO
3
-N content
lb/ac
Field ID Whole eld
5’’ 10’ 15’ 20’ 25’ 30’ 5’ + 10’ + 20’ 5’ + 20’ + 25’
(12.7 cm) (25.4 cm) (38.1 cm) (50.8 cm) (63.5 cm) (76.2 cm) (12.7 + 25.4 + 50.8 cm) (12.7 + 50.8 + 63.5 cm)
Y2 123.8 157.7 159.2 142.8 115.7 90.9 76.4 126.1 121.4
Y3 63.6 66.2 43.4 52.3 70.8 65.3 83.5 59.7 67.5
Y4 64.2 40.6 42.6 55.5 56.0 89.1 101.6 66.6 61.9
Y5 45.0 56.3 47.2 59.0 40.6 34.1 33.1 46.4 43.7
Y6 64.7 68.0 60.5 60.1 71.1 62.4 66.1 62.2 67.2
SJ3 293.0 277.5 361.0 298.3 349.4 247.0 225.2 294.8 291.3
SJ4 275.1 258.2 244.6 256.2 367.5 267.5 256.7 252.5 297.7
F1 115.7 161.7 103.7 137.2 110.3 88.1 93.3 111.4 120.0
F2 318.0 153.7 257.2 327.8 445.6 427.8 295.9 293.6 342.4
F3 171.7 142.8 150.8 191.5 191.9 205.7 147.4 163.2 180.2
F4 437.7 226.2 408.2 647.3 619.0 401.6 323.7 459.7 415.6
Relative error (%) 24.2 17.1 15.9 18.3 18.3 23.0 4.4 4.4
* Relative error from the eld average of the dierent sampling distances and best combination of sampling distances is according to the Minimax analysis.
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... The very great variability in available P is surprising, particularly in the CONV system. This contrasts with Hurisso et al. (2018), who observed great analytical precision and spatial correlation on another available P measure, Mehlich P. Subsurface drip-irrigated systems may have greater spatial variability than rainfed systems, as the targeted delivery of small quantities of water and nutrients to a limited area may result in zones of depletion in the wetting zone and high concentrations near the bed edges (Lazcano et al., 2015). The fact that the variability was particularly great in the CONV system suggests that the variability observed may also partly be due to the fact that P is applied in a starter band. ...
... The fact that the variability was particularly great in the CONV system suggests that the variability observed may also partly be due to the fact that P is applied in a starter band. As P is relatively immobile in the soil, banding may lead to zones of high and low concentrations (Beegle, 2005), and increased sampling density and specialized sampling schemes are recommended in fields that receive banded (or fertigated) fertilizers (Geisseler & Miyao, 2016;Lazcano et al., 2015). ...
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Low fertiliser-use efficiency and high N losses from leaching are still reported in drip-irrigated tomatoes. One reason for this is the lack of reference data for soil N status, to allow proper N nutrition under conditions of high nitrate gradients in the soil profile. In this study, root colonisation, nitrate concentration, and plant N uptake were monitored dynamically on a tomato crop at two levels of N nutrition: sufficient (445 kg N ha-1; HN), or limiting (256 kg ha-1; LN). N stress in the LN treatment resulted in a 180% increase in root length and a 200% increase in the total soil volume occupied by the roots, along with reduced aerial growth. Root spatial development tended to decrease at the end of the season in the HN treatment, while root expansion was continuous in the LN conditions. Differences in soil N concentrations between treatments were found only in wetted soil zones with low or no root growth, while soil N in well-rooted zones was uniformly low in both treatments. As a result, the best linear relationship between soil nitrate concentration and plant N status (assessed by the nitrogen nutrition index; NNI) was found when the mean soil nitrate concentration was calculated for a large soil volume; in this case, a hemisphere approx. 65 cm in radius. In this volume, the critical nitrate concentration required to obtain a NNI of 1.0 was 102 mg l-1. Nitrate accumulation at the periphery of the wetted soil volume should be checked regularly to improve fertiliser-use efficiency.
Article
As growers of processing tomato (Lycopersicon esculentum Mill.) adopt drip irrigation, plant vigor and fruit yield typically increase, suggesting a need for re-evaluation of established nitrogen (N) fertilization practices. Trials were conducted in California in 2007-2008 to evaluate growth and N uptake dynamics of drip-irrigated processing tomatoes across N fertigation regimes ranging from deficient to excessive. Whole plants were collected at 2-week intervals for determination of biomass and N content, recently matured whole leaves for total N and petioles for NO3-N. Additionally, six commercial fields were sampled at 3- to 4-week intervals to document N uptake and crop N status under conditions representative of the industry. A seasonal N rate of'200 kg ha-1 appeared adequate to maximize fruit yield across the range of field conditions encountered. The four highest-yielding fields (143 Mg ha-1 mean fresh fruit mass) averaged 14 Mg ha-1 of above-ground biomass with fruit representing 62%; these fields averaged 296 kg ha-1 biomass N, of which 71% was in fruit. The rate of biomass development and N uptake peaked during the period between early fruit setting and early red fruit development (a period of ≅ 6 weeks) during which N uptake averaged 4 to 5 kg ha-1 d-1. Leaf N concentration was highly correlated with whole plant N (r2 = 0.83) and provided a reliable indicator of plant N sufficiency throughout the season. Petiole NO3-N did not reliably discriminate between crops with adequate or deficient N availability; current petiole NO3-N sufficiency guidelines are unrealistically high.
Article
Agriculture constitutes a major source of non-point pollution (e.g., nitrates) where overall water resources are affected, in particular, aquifers. Intensive agricultural practices take place in regions with appropriate weather conditions that are usually deficient in water resources. The preservation of water resources in these types of regions depends on the evaluation of the efficiency of agricultural practices for specific crops and conditions. Although water scarcity is a characteristic feature in the Western Mediterranean, it is one of the most appropriate regions in the world for intensive agriculture development for climatic reasons. In the current work, percolation and N leaching from different crops (corn, potato, and rotation of lettuce and melon) under different irrigation methods (surface, sprinkler and drip) were evaluated through experimental plots. Water (irrigation + precipitation) and fertilizer inputs were accurately controlled. Soil water content and nitrate concentration were monitored from time domain reflectometry measurements, and cup lysimeters and destructive sampling, respectively. Percolation and nitrate leaching was simulated from different numerical codes (STICS and GLEAMS, tipping bucket method; HYDRUS-1D, Richards’ equation), which were chosen based on the available information and the specific purposes of each experiment. For the studied periods, the obtained results showed high percolation values: 34, 58 and 37% of total applied water for corn, potato, and rotation of lettuce and melon, respectively. Also, high N leaching values across all experiences were observed, even higher than the applied doses in some periods as consequence of remobilizing mineralized N, despite following the recommended agricultural management practices. Percolation and N leaching were mostly controlled by the precipitation regime, namely, unevenly distributed intensive rainfall events, mainly in autumn and spring, which have a great impact in irrigated agriculture due to the permanent high soil water content. In detail, irrigation water applied for frost prevention on potato crops and plastic cover for melon crops, played a very important role for both percolation and N leaching. Whilst for the corn crop, N leaching mainly took place in the fallow period (autumn and winter), where the rain leached N present in soil from previous crops.
Article
Growth, N uptake and light interception were studied in processing tomato grown in the field in Central Italy (Tiber Valley, 43°N, elev. 165 m) at different levels of fertiliser-N in 1996–97–99. Plant N concentration declined during the entire crop cycle. The relationship between the total above-ground dry biomass (DW, Mgha−1) and critical N concentration (%Nc, the minimum N concentration required for maximum plant growth, calculated according to Justes et al., Ann. Bot., 1994, 74, 397–407) was %Nc=4.53 DW−0.327 for total-N, and %Nc=3.90 DW−0.270 for reduced-N. The critical dilution curves were applied when the above-ground dry biomass varied between 1.2 and 12.4 Mgha−1 and for stages of development ranging from the onset of fruit growth (∼40 days after transplanting) to maturity. Increasing N availability increased dry matter accumulation. Relationships between crop total-N uptake (Nupt, kgNha−1) and accumulated dry matter in the aerial biomass (DW, Mgha−1) fit very well to the model Nupt=10 a DW 1−b (Lemaire and Salette, Agronomie, 1984, 7, 381–389) for each fertiliser-N level in all three experiments. In all years the ‘critical uptake’ curve (Nupt=45.3 DW 0.673) was between the uptake curves obtained with the fertiliser-N rates of 100 and 200 kgha−1. Increasing N supply increased the amount of absorbed PAR accumulated throughout the growth cycle and slightly affected the Radiation Use Efficiency. Results are discussed also taking into account the effect of N availability on source-sink relationships.