Journal of Experimental Botany, Vol. 47, No. 304, pp. 1699-1707, November 1996
Journal of
Experimental
Botany
Validating sap flow measurement in field-grown
sunflower and corn1
Y. Cohen 24 and Y. Li3
2
Department of Environmental Physics and Irrigation, Agricultural Research Organization, The Volcani Center,
PO Box 6, Bet Dagan 50250, Israel
3
Xinjiang Institute of Geography, Chinese Academy of Science, Urumqi, Xinjiang, People's Republic of China
Received 2 November 1995; Accepted 28 June 1996
Abstract
Introduction
Sap flow measurement has been widely used recently
in studying plant response to the environment, but
results have not always been satisfactory. The possibility that the non-uniform distribution of the conducting elements in the stem cross-sectional area
introduces error in the measurements was examined.
The heat pulse method, combined with anatomical
observations of the stem at the point of sap flow measurement, was applied in corn and sunflower, to study
the interaction between anatomical structure and sap
flow distribution. The probability of the temperature
sensor being in contact with conducting elements was
strongly affected by its insertion depth into the stem;
the measured heat pulse velocity for a given transpirational flux was correlated with the number of conducting elements in contact with the sensor.
Consequently, the calibration coefficient is affected
by the position of the thermocouple junction in relation
to the conducting elements. This dependence of
apparent heat pulse velocity on density of conducting
elements suggests that thermal equilibration in
species with large stems may not be achieved within
the limited time of heat dissipation. The relationship
between sap flow and leaf area of single plants was
used to test the consistency and the accuracy of the
sap flow measurements. The ratio of measured to
potential transpiration was used to validate the use
under field conditions, of the calibration coefficient
determined in potted plants.
When lysimeter systems are not available, measurement
of sap flow in the stem becomes an alternative method
for determining canopy transpiration under field conditions. The accuracy of water uptake estimates based on
sap flow measurement depends on two scales of integration: on a single plant level the integration is affected by
variability in the distribution of the conducting elements
in the stem cross-sectional area; and on a community
level integration should be made to account for the
variability among plants (Dugas, 1990; Cohen, 1994).
Both levels were examined in this study, the first under
greenhouse and laboratory conditions, and the second in
the field.
The single plant level of the integration was studied by
means of the heat pulse method. The correlation between
stem anatomical structure and heat pulse velocity was
examined in potted plants of two herbaceous species with
large stem diameter. The heat pulse method was selected
in this study because it is easily adapted to field conditions.
The technique has been applied previously to herbaceous
species with small stem diameter; it involves a calibration
coefficient that varies between species and is assumed to
be dependent on stem anatomical structure (Cohen,
1994). Use of the equations describing the heat dissipation
in wood with moving sap requires that the stationary
wood and the moving sap act together like a single
medium moving at a uniform speed (Marshall, 1958).
The effect of stem anatomical structure on the deviation
of computed sap flow from the theoretical value was
recognized in conifer trees by Marshall (1958). Later it
has been shown that variation in the cross-sectional
distribution of sap flow causes inconsistent results in some
Key words: Heat pulse, transpiration, LAI, potential
transpiration.
1
4
Contribution from the Agricultural Research Organization, the Volcani Center, Bet Dagan, Israel. No. 1694-E, 1995 series.
To whom correspondence should be addressed. Fax: +972 3 9604017.
C Oxford University Press 1996
1700 Cohen and Li
herbaceous species (Baker and Nieber, 1989; Ishida et al.,
1991). For instance, the vascular system in mature dicot
plants consists of a ring of bundles in the periphery of
the stem (Esau, 1960). In young dicot stems or at the
top of the stem, the bundles are distinct and form strands,
whereas at lower levels they merge to form a continuous
ring (Knowles, 1978). Monocot species, on the other
hand, have widely spaced vascular bundles, which are not
restricted to one circle in transection, but are scattered
throughout the section (Sass, 1977).
With such an uneven distribution of the vascular
system, it is likely that in a species with a large stem
diameter (corn, sunflower), the sensor, which occupies
only a small proportion of the stem cross-sectional area,
measures a heat pulse velocity which differs from the
average value for the entire stem area. An important
question related to this aspect is, what would be the effect
of the density of the vascular system on the time required
to equalize the temperatures of the stationary tissue and
the flowing sap, following a heat pulse? It is assumed that
the higher thermal conductivity of the stainless steel
needle, relative to that of the stem tissue, allows reasonable averaging of the temperature over the length of the
needle. The objective of the present study was to test this
assumption for corn and sunflower.
Integration of the community level depends on the
variability among plants in the field. The measurement
procedures and the calibration coefficients which had
been determined in potted plants were applied in the field,
to evaluate the effect of plant variability on the estimation
of canopy transpiration. In previous studies this variability had been addressed by selecting plants with a wide
range of stem diameter or plant leaf area, two parameters
which were usually considered to be related to plant
transpiration rate (Kanemasu et al., 1976; Tanner and
Jury, 1976; Al-Kaisi et al., 1989). The objective of the
present study was to validate the extrapolation of measured single plant sap flow to canopy transpiration, with
plant leaf area used as a parameter reflecting the variability between plants.
Materials and methods
where k (mm2 s ') is the thermal diffusivity of the stem and tm
is the time at which the temperature at the upper sensor reaches
a maximum. A more detailed explanation of an alternative use
of equations 1 and 2 has been presented previously (Cohen
et al., 1993). The sap flux in the stem, 7, is defined as
Ji = [(pc)/(j>lCi)]v
(3)
where />, and c, are the density and specific heat of the liquid,
and p and c are the density and specific heat of the wood,
respectively. The determination of p and c is destructive,
therefore, in contrast to the case of trees, their evaluation in
the measured plant is not possible during the heat pulse velocity
measurement. On the other hand, slight variations between
plants and changes in the volume fractions of water and woody
matrix in the course of the day are common in herbaceous
plants (Kitano and Eguchi, 1989). However, sap flow measurements by the heat balance methods assume a fixed value of
stem thermal conductivity, despite the variation induced by
stem water content fluctuations (Sakuratani, 1984, Ishida et al.,
1991). In this procedure the sap flow is computed from the
heat pulse velocity, stem area, and a calibration coefficient
which combines p and c values, the effect of the implantation
wound size, and the structure of the xylem conducting area.
The consistency of this coefficient for a given species, irrespective
of plant age, and time of day, as found in our previous studies
of cotton, soybean, corn (Cohen et al., 1988, 1993) and pepper
(unpublished data), suggests that the effect on sap flux of
diurnal changes in p and c is not significant.
The probe block used for the heat pulse velocity measurement
consists of a line heating element and two temperature sensors
mounted on a phenolic fibre plate, 40 x 20 x 8 mm. The heating
element and the sensors are made from hypodermic stainlesssteel needles of 0.5 mm o.d. and 0.25 mm i.d. and a detailed
description of the probe has been given by Cohen et al. (1988).
The insertion depth of the thermocouple needle was determined
by placing pertinax (polyphenol) spacers of 2.3 mm width
between the probe block and the stem. When 0, 1 or 2 spacers
were used, the insertion depths were 7.8, 5.5 or 3.2 mm,
respectively.
A previously described transpiration model (Fuchs et al,
1987) was used to compute the potential transpiration (Tp).
Inputs to this model were global radiation (Kipp and Zonen,
Delft, Netherlands), air temperature and humidity (Model 201,
Campbell Scientific, Logan, UT, USA) and wind speed (Model
014A, Met One, Sunnyvale, CA, USA), measured at 2.5 m
above the soil surface in an automated meteorological station.
Data were scanned every 10 min, averaged for 60 min intervals,
and recorded with a battery-powered datalogger (CR21,
Campbell Scientific). Potential transpiration Tp (m s" 1 ) was
calculated by using the Penman equation (Monteith, 1965):
(4)
Measurements
The heat pulse velocity (v) was measured as described previously
(Cohen et al., 1988). For low or moderate sap flow rates v was
estimated as
= (Xl-X2)/2t0
(1)
where Xx and X2 are the distances from the heater to the
thermocouple junctions above (9 mm) and below (4 mm) the
heater, respectively; t0 is the elapsed time from pulse emission
to the first recurrence of the initial temperature difference. For
high sap flow rates the accuracy of t0 estimation is unacceptable,
therefore, v was estimated as
(2)
Where s is the slope of the saturation vapour pressure curve
(kPa°C"'), y is the psychrometric constant (kPa°C~'), /?„ is
the net radiation observed by the foliage (J m~ 2 s~'), p is the
density of air (kg m~ 3 ), cis the specific heat of air(J k g " 1 0 C ~ ' ) ,
e,-e, is the air-water vapour pressure deficit (kPa).
The resistance for water flux from the canopy ru, was
computed as:
in which r, is the aerodynamic resistance (s m" 1 ), rb is the
boundary layer resistance (s m " 1 ) , and SLA1 is the sunlit leaf
area index.
Sap flow in sunflower and corn
The net radiation Rr, was computed after Fuchs et al. (1987):
RB = (0.55YfxKxSLA/-RLN
(6)
where n is an empirical factor between 0 and 1 that accounts
for radiation entrapment resulting from multiple scattering
between sunlit leaves, K is the direct component of global
radiation, and RLN is the net thermal radiation. A constant
value of 0.5 was assigned to n. The factor / equals 0.5 divided
by the cosine of sun angle from the zenith. Other inputs to the
model were the leaf area index, crop height, row width, and
leaf width.
Calibration
Calibration and field tests were conducted in corn (Zea mays
L. cv. Jubilee) and sunflower (Helianthus annuus L.). For
calibration, plants were grown in pots 250 mm in diameter and
300 mm in depth, filled with a mix of sand and peat and located
in a plastic-covered shelter measuring 20 x 6 x 2.5 m. The pots
were wetted daily, and nutrient solution was added as required.
Heat pulse velocity measurements were carried out in plants of
different ages and the computed flow rates were compared with
the rates of water loss, measured by automatically weighing the
pot to the nearest 0.1 g every 15 min.
At the end of the calibration period (2-3 d for each plant),
the plant was removed from the pot, the soil was carefully
washed from the root system and the plant was transferred for
24 h to a new pot containing a dilute safranin solution. Thin
cross-sections of the stem, about 0.2 mm thick, were taken near
the point of probe insertion and examined under a microscope.
The number of bundles in corn and sunflower stems was
determined in 25-30 microscopic fields of 2.3 mm diameter
each. For instance, in a corn stem of 18 mm diameter, 15
microscopic fields were examined in the first annulus at a depth
of 0-2.3 mm below the bark, seven fields in the second annulus,
2.3-4.6 mm below the bark, four fields in the third annulus,
4.6-6.9 mm below the bark, and four fields in the central part
of the stem.
1701
irrespective of their location relative to the dripper. The row
spacing was 1 m and the plant population density was close to
3.6 x 10" plants ha" 1 . The plot contained 18 rows, each 15 m
long. Two irrigation treatments were applied: 330 and 156 mm
of water applied at weekly intervals for the whole season. The
experimental design comprised randomized blocks, with four
replicates.
The probes for heat pulse velocity measurement were installed
on the second internode of the stem, to a depth of 5.5 mm,
using one pertinax spacer. One probe was installed in each of
20 plants (10 plants per treatment) and heat pulse velocity was
measured simultaneously in the 10 plants of one treatment
every 15 min, so that the sap flow of each treatment was
monitored at 30 min intervals. Stem diameter measurements
were taken on installation and removal of the probes. Before
installation of the probes, stem diameters of all plants in a 6 m
row length in each treatment were determined. The stem
diameter distribution of the sample was used to select 10 plants
with a diameter distribution matching that of the sample, for
heat pulse velocity measurements. The number of plants per
unit area and the average computed sap flow rate of the
individual plant (kg h" 1 ) were used to calculate the canopy
transpiration (T) per unit ground area (mm h " 1 ) .
A battery-powered data logger (CR7X, Campbell Scientific)
was used to monitor the sensors and control the relays operating
the heaters. The maximum distance between the data logger
and the measured plants was 5 m. At the end of the measurement
period, after removal of the probes, the plants were cut below
the lowest leaf, for determination of the leaf area in the
laboratory, with an optical area meter (Delta T Devices,
Burwell, Cambridge, England).
Two neutron probe access tubes were installed in each side
of the sprinkler line to a depth of 1.5 m, at distances of 2, 4, 7,
and 10 m from both sides of the sprinkler line. Probe readings
were taken at 0.3 m depth intervals 2, 4 and 6 d after each
irrigation event. Leaf water potentials were measured with a
pressure chamber (Arimad-2, Kibbutz Kfar Charuv, Israel)
between 10.00 and 12.00 h on four sunlit leaves from each row,
2, 4 and 6 d after each irrigation event.
Field experiments
Data were collected from experimental sites at the Volcani
Center in Bet Dagan (32°01' N, 34°50/ E, 25 masl) and at
Kibbutz Yefa'at in the Yizre'el Valley (32°40' N, 35° 13' E, 50
masl). The experiment in Bet Dagan was conducted during the
summers of 1990 and 1994 in a 0.4 ha corn plot. The soil is
classified as a sandy loam soil (Rhodoxeralf by USD A
designation) with 10% clay and 85% sand. The plot measured
30 x 140 m, with row spacing of 1 m and a plant density of
6-8 m" 1 . Two irrigation lines with sprinkler discharge of 8 mm
h " 1 at a pressure greater than about 150 kPa were placed along
the plot at a distance of 12 m from the sides to provide a
central overlap of 6 m. Irrigation was applied at weekly
intervals, and the amount of water applied to the plot averaged
0.7 of the weekly total pan evaporation. The water application
rate varied with distance from the line source, from zero on
rows near the plot border to 1.8 times the pan evaporation in
the central rows, where the supplies from the two irrigation
lines overlapped.
The experiment in the Yizre'el Valley was conducted during
the summer of 1994, with sunflowers in a 0.5 ha plot located
within a large commercial field. The soil, classified as vertic or
typic aquic chromoxerent, consists of 60% clay, 35% silt and
5% sand. Drip irrigation systems were used, with one line of
drippers per row, in-line spacing of 1 m between drippers and
a nominal water discharge of 2.3 1 h ~' from each dripper.
Plants were selected for heat pulse velocity measurement
Results
The results of measurements of transpiration (T) of the
plants in the plastic-covered shelter and apparent heat
pulse velocity measurements, taken simultaneously at
15 min intervals are shown in Fig. 1. Heat pulse velocity
was measured by two sensors installed in the same corn
plant at the second and fourth internodes, to 5.5 and
7.8 mm depth, respectively, on opposite sides of the stem.
The product of apparent heat pulse velocity and stem
cross-sectional area (av) at the point of measurement was
highly correlated with T determined by weight loss,
irrespective of the sensor depth in the stem. The slopes
of the regression lines in Fig. 1, for sensors inserted to
5.5 and 7.8 mm depths were 1.57 and 1.88, respectively.
As described previously (Cohen et al., 1993) the slope is
taken as a calibration coefficient for a given species.
Slope and correlation coefficient values of the linear
regressions between Tand av of six calibrated corn plants
of different stem diameters, with similar sensor installation
configurations as shown in Fig. 1, are given in Table 1.
1702
Cohen and Li
Table 2. Bundle density and number of bundles in contact with
2.3 mm sensor segments at various depths beneath the bark of
corn stem of 17.5 mm diameter
0.15i
-.
0.12
Depth beneath bark (mm)
sensor depth 5.5 mm
T = -0.001 + 1.57 av
R 2 » 0.93
sensor depth 7.8 mm
T = 0.0004 + 1.88 av
0-2.3
4.6-6 9
2.3-4.6
p
D
0.06
0.27
0.40
0.27
-
1.69
1 93
2.17
2.41
2.14*
B,
P
D
B.
P
D
B.
1 94
2.22
2.49
2.77
2.45*
0.14
0.71
0.15
_
-
0.72
0.96
1 20
_
0.96*
0.83
1 11
1.38
_
1.10*
0 75
0.25
_
_
-
0.48
0 72
0.54*
0.55
0 83
0.62*
R 2 = 0.95
0.03
0.06
0.09
0.12
0.15
* weighted average.
P probability of appearance of particular density
D (bundles mm" 2 ).
B, number of bundles in contact with the sensor
av (kg h plant )
Fig. 1. The relationship between transpiration (7*) determined by weight
loss and the product of heat pulse velocity and the stem area (av)
measured by two sensors installed at different depths in the corn stem.
Table 1. Slope and correlation coefficient (R 2 ) of the linear
regressions between the product of heat pulse velocity and stem
area (av) and transpiration (T) in corn plants of different stem
area: two sensors were inserted to 5.5 and 7.8 mm depths on
opposite sides of the stem
Stem area
113
154
177
201
227
283
Average
SD
Sensor at 5.5 mm depth
Sensor at 7.8 mm depth
Slope
R
2
Slope
R2
64
.62
.53
.61
.59
.56
.59
0.057
0.91
0.90
0.94
0.89
0.92
0.94
2.11
1.72
2.14
2.02
1.93
1.84
1.96
0.148
0.97
0.94
0.89
0.88
0.92
0 86
With the sensor inserted to a 5.5 mm depth, the slope of
the linear regression was smaller and less variable than
with insertion to a 7.8 mm depth. The relative position
of the sensors, i.e. whether the deeper insertion was at
the upper or lower position on the stem did not affect
the slope. In another group of six plants, with two probes
inserted in the same stem, both to a depth of 5.5 mm, an
average slope of 1.57 was obtained for both sensors with
standard deviation (SD) of 0.048. The linear regression
slopes obtained for plants into which probes were inserted
to a 3.2 mm depth were much lower than those shown in
Table 1, but the variability among plants or among different orientations of the stems was high. Therefore, the
measurements by insertion to a 3.2 mm depth were
excluded from the analysis.
The number of bundles in contact with the sensor (Bt)
in each of three measured sections of a 17.5 mm diameter
corn stem is given in Table 2. B, was taken as bundle
density (D) multiplied by the stem area occupied by the
sensor (2.3 x 0.5= 1.15 mm2). The probability (P) of
appearance of D expresses the proportion of the stem
area with a particular D to the total area of the stem
section. In the section nearest to the bark the bundle
density was higher than in deeper sections, therefore, the
weighted average number of bundles in contact with the
sensor was 2.7 as compared with 0.69 in the annulus at
a depth of 4.6-6.9 mm below the bark. Excluding slight
variations between plants, the bundle arrangement shown
in Table 2 were repeated in all other measured mature
corn plants. Variations in bundle density among different
stem orientations were not significant (not shown in
Table 2).
The sensor position within the cross-sectional area of
a 19 mm diameter corn stem, and the location of the
thermocouple in the needle are shown in Fig. 2, in which
the probability of a 2.3 mm-long sensor section being in
contact with various numbers of conducting bundles, as
calculated from all examined plants is also given. The
probability that a sensor section extending from 0-2.3 mm
Depth tmneath bark Imm)
A |
Thermocouple junction
| 0-2.3
0.8
0.6
0.2
0.0
0
1
2
3
4
NUMBER OF BUNDLES IN CONTACT WITH THE SENSOR
Fig. 2. Sensor position within the cross-sectional area of a 19 mm
diameter com stem and the probability of a sensor being in contact
with various numbers of conducting bundles.
Sap flow in sunflower and corn
depth below the bark will be in contact with one, two,
three or four bundles is 0.04, 0.57, 0.37 or 0.02, respectively. With increasing depth beneath the bark, the number
of bundles in contact with the sensor diminishes markedly.
In a sunflower stem, the conducting system forms a nonsymmetrical ring of bundles located adjacent to the bark
and not more than about 3 mm beneath it. In a stem of
16 mm diameter, the continuity of the ring of conducting
elements is often interrupted by non-conducting tissue,
but in a young stem of 10 mm diameter completely
separate coloured blocks of various diameters were
observed.
The slopes and correlation coefficients of the linear
regressions between T and av of six calibrated sunflower
plants of different stem diameters with sensors inserted
to a depth of 5.5 mm below the bark on opposite sides
of the stem are given in Table 3. The slope value was 0.73
(or 0.72) with a standard deviation of 0.054 (or 0.048).
The similarity between the two sides in the slope values
suggests that there is little orientational variability in the
sunflower stem. Insertion of the sensors to a depth of
7.8 mm in another group of six sunflower plants yielded
a poor relationship between T and av; the slopes of the
linear regressions were between 1.01 and 1.41, and they
varied widely among plants and between the two sides of
the stem (Table 4). Tables 1, 3 and 4 indicate that stem
diameter had no effect on the regression slopes (calibration coefficient), although it might be expected that the
density of the conducting tissue would change with age.
The findings also suggest that the tangential distribution
of bundles in the stems of both species may be considered
uniform. In contrast, the radial distribution of the bundles
is not uniform, therefore, the calibration coefficient
depended on insertion depth.
Field measurements of sap flow were made in 1990
with sensors at depths of 5.5 and 7.8 mm, but only the
data from 5.5 mm depth will be considered here. During
1994, heat pulse sensors were inserted into corn and
sunflower stems to a 5.5 mm depth. Figure 3 shows the
Table 3. Slopes and correlation coefficient (R 2 ) of the linear
regressions between the product of heat pulse velocity and stem
area (av) and transpiration in sunflower plants of various stem
areas: two sensors were inserted to a 5.5 mm depth on opposite
sides of the stem
Stem area
(mm 2 )
64
106
125
158
211
232
Average
SD
Side A
Opposite to side A
Slope
R1
Slope
R2
0.81
0.72
0.73
0.66
0.79
0.68
0.73
0.054
0.83
0 89
0.94
0.91
0.92
0.95
0.77
0.73
0.80
0.66
0.72
0.69
0.72
0.048
0.84
0.83
0.88
0.94
0.93
0.96
1703
Table 4. Slopes and correlation coefficient of the linear regressions
between the product of heat pulse velocity and stem area (av) and
transpiration (T) in sunflower plants of various stem areas: two
sensors were inserted to a 7.8 mm depth on opposite sides of
the stem
Stem area
(mm 2 )
76
117
137
149
167
206
Average
SD
Side A
Opposite to side A
Slope
R1
slope
R1
1.34
1.01
1.41
1.09
1.28
1.15
1.21
0.141
0.92
0.87
0.93
0.91
0.84
0.%
.12
.39
.21
.13
.41
.09
.23
0.149
0.83
0.88
0.94
0.91
0.95
0.89
0.8
distance from sprinkler line (m)
c
CD
1
0.6
73
0.4
Q_
<
0.
T80
182
184 186
188
DAY OF YEAR
190
19
Fig. 3. Daily sap flow of corn plants at various distances from the
sprinkler line.
daily sap flow of corn for various distances from the
sprinkler line, measured in 1994; since the water amount
decreased with distance from the sprinkler line, leaf area
and sap flow decreased accordingly. The figure indicates
the capability of the method to measure small day-to-day
differences in sap flow as well as differences between rows
and between dry and wet soils. The values in Fig. 3 are
averages over five plants for each distance from the
sprinkler line.
The relationship between sap flow of 10 plants, taken
at 1 m from the sprinkler line, and their leaf area is shown
in Fig. 4. The parameters of the linear regression for the
data points in the figure and of regressions for other
groups of 10 plants, taken at distances of 1, 4, 7, and
10 m from the line, are given in Table 5. There is a clear
linear link between sap flow rate and LAI for LAI values
of up to 3.9, which may be deduced from the closeness
of the regression slope values for the three longer distances
from the sprinkler line, and also from the high correlation
coefficients (R2). On the other hand, the slope of the
linear regression at 1 m distance, with an LAI of 4.9 was
lower than those of the plants at longer distances from
the sprinkler line. It indicates that the LAI of the plant
1704 Cohen and Li
Table 5. LAI and regression parameters of the linear relationship between sap flow of individual corn plants and leaf area of plants at
various distances from sprinkler line
Distance from line
(m)
LAI
(mean of 10 plants)
I
4
7
10
Regression parameters
4.9
3.9
2.8
I 2
0.4
0.6
0.8
2
LEAF AREA (m plant')
Fig. 4. The relationship between sap flow and leaf area for 10 corn
plants, taken at 1 m distance from the sprinkler line.
at 1 m distance was above the threshold level at which
the sap flow per unit area diminishes because of attenuation of radiation by the canopy. It may also be explained
by ageing of the leaves, with some older portions becoming non-functional in water vapour exchange. The low
correlation coefficient of the linear regression at 1 m from
the line also suggests wide variability in exposure to
radiation.
A high correlation between sap flow and leaf area in
individual plants was also found in sunflower (Fig. 5).
The maximum leaf area of water-stressed sunflower plants
(irrigation of 150 mm) was nearly 0.4 m2 per plant compared with 1 m 2 in well-irrigated plants (230 mm). For
this reason the maximum LAI was 3.1 and 2.2, respect-
1^
•
l/rigrton with 150 mm
SE of coefficient
0 21
0.07
0.11
0.03
0.753
0.841
0.863
0.859
0.74
0.87
0.93
0.91
0.15
0.11
0.09
011
ively, for the plots irrigated with 230 and 150 mm annually. These values of LAI are below the values obtained
in well-developed stands of sunflower (Jaafar et ai, 1993).
Figure 5 indicates no difference between the two irrigation
treatments in sap flow per leaf unit area.
To validate the use of the heat pulse method for
determination of canopy transpiration, the relationship
between measured transpiration and potential transpiration was studied. The comparison between the two was
made only for days when there were indications that
water supply to the plants was sufficient. Figure 6 shows
the distribution of soil water content for a mature corn
canopy, on the second day after the irrigation. The soil
water content at 1-5 m distance from the sprinkler line
was close to full water capacity at all depths, excluding
0.15 m. On the same day, the soil water content at greater
distances from the sprinkler line was below the maximum
capacity, therefore, plants could have been under differing
degrees of water stress. Midday leaf water potential
during the first and second days after an irrigation event
at 1 -5 m distance from sprinkler line was — 1.2 ± 0.1 MPa,
but at greater distances from the sprinkler line it was
—1.6 ±0.15 MPa. In view of the above results it is
assumed that for the first 2 d after an irrigation event,
water availability to the plant was not a limiting factor
for transpiration of plants located up to 5 m from the
sprinkler line. No measurement of leaf conductance was
carried out either in 1990 or in 1994, but in 1995 a set of
intensive leaf conductance measurements was made in
Z 0.20
m
R - 0.73
O 0.15
o
0
O
^0.6
a.
0
R2
SF - 0.05 + 1.83 LA
1.6
C/3
Slope
_ 0.30
'E
" E 0.25
-—2.6
A
Constant
£ o.io
<
Irrigation with 230 mm
SF - 0 1 B + 1.88 LA
0.05
R - 0.83
0.2
0.4
0.6
0.8
1.2
LEAF AREA (m 2 plant'1)
Fig. 5. The relationship between sap flow and leaf area for sunflower
plants irrigated by two different water amounts.
°
r*—••
distance from sprinkler line (m)
1 3 5 7 10
O
0.3
D
A
•
•
0 . 6 0 . 9
SOIL DEPTH (m)
1.2
1.5
Fig. 6. Soil water content as a function of soil depth for several
distances from the sprinkler line, under a mature corn canopy.
Sap flow in sunflower and corn
corn on the same plot. Sunlit leaf conductance of about
4.5 mm s" 1 was maintained, as long as the weighted
volumetric soil water content at 0.15-0.75 m depth was
above 0.22 m 3 m~3.
Canopy transpiration (T) was computed from sap flow
and plant number per unit area. The contribution of the
secondary shoots to canopy transpiration was taken into
account by calculating the ratio between their leaf area
and that of the whole plant. As described above, the
transpiration model takes account of several plant parameters, including leaf area. In computation of Tp, therefore,
values of Tp on a given day will depend on the LAI.
Figure 7 presents the diurnal course of T and Tp for two
groups of 10 corn plants grown in 1990, at 1 m and 5 m,
respectively, from the sprinkler line, with an average of 7.8
plants per 1 m row. The LAI (based on the leaf area of
the plants in which sap flow was measured) was 5.7 and
4.2 for plants at 1 m and 5 m distance, respectively. The
computed Tp for 1 m distance was 9.28 mm d" 1 while that
for 5 m distance was 7.15 mm d" 1 . Figure 7 shows that
canopy transpiration, as computed from sap flow measurements, was closely related to Tp at both distances but
lagged behind it. The T/Tp ratio on a daily basis was 0.85
or 0.82 for plants at 1 m or 5 m from the sprinkler line,
respectively. The results of measured transpiration taken
on other days were also closely related to Tp, with the
T/Tp ratio around 0.8, as long as soil water content was
close to field capacity. The close relationship between
potential and measured transpiration, with a consistent
ratio between the two, irrespective of plant size, indicates
the high reliability of extrapolating single plant heat pulse
measurement results to canopy transpiration.
Discussion
In both corn and sunflower, when the thermocouple
junction was positioned in the vicinity of densely packed
conducting elements, the measured heat pulse velocity for
a given transpirational flux was higher than in areas with
sparsely distributed elements. This was evident when the
thermocouple junction was inserted deep into the stems
of both species, where the number of conducting elements
was zero or close to zero. This influence of junction
position on measured heat pulse velocity explains the
different calibration coefficients found for the two species
and for different insertion depths into the stems. It also
indicates that the relatively high thermal conductivity of
the stainless steel was not sufficient to average the temperature over the length of the needle.
In corn and, more likely, in sunflower stems, a section
of thermocouple needle (nearest the bark) is always in
contact with sap-conducting elements, because of the high
density of bundles in corn and the continuous ring of
active conducting tissue near the bark in sunflower.
Hence, it might be expected that the thermocouple needle
section would immediately detect the wave of heat carried
by the sap. However, with increasing needle insertion
depth, the measured heat dissipation rate decreases
because of the low density of bundles in the deeper layers
of the stem. The change in bundle density with depth
may explain the difference in calibration coefficients
between corn and sunflower. Because of the continuous
ring of sap-conducting tissue in a mature sunflower stem,
the thermocouple needle section near the bark is always
in contact with conducting elements and is immediately
heated by the moving sap, so that the measured heat
pulse velocity per unit transpirational flux is high,
resulting in a low calibration coefficient for sunflower.
On the other hand, in corn the conducting bundles are
distributed unevenly in the stem, so that the probability
for the sensor to be in contact with conducting tissue is
smaller than in sunflower, even near the bark, and it
decreases with increasing penetration into the stem.
Therefore, the measured heat pulse velocity per unit
transpirational flux is low and the cahbration coefficient
for corn is high.
These findings imply that, following a heat pulse, a
local thermal equilibrium between the stationary tissue
1.2
5 m distance from the sprinkler line
___
1 m distance from the sprinkler line
1
£
£
0.8
a
I-
0.6
o
0.4
0.2
0
4
8
12
16
20
1705
0
4
8
12
16
2C
24
TIME OF DAY
Fig. 7. Diurnal course of transpiration (7*) and potential transpiration (Tp) for plants grown at 1 m or 5 m distance from the sprinkler line.
1706
Cohen and Li
and flowing liquid is established as the theory requires
(Marshall, 1958). However, a thermal equilibrium over
the entire area occupied by the sensor is not attainable
within the time limit of the heat pulse. This problem is
likely to be more critical in large stems than in small
ones, since the conducting system is more evenly distributed in the latter (Webber, 1938), and the metal needle
occupies a proportionately larger area of the stem.
Difficulties in the analysis of stem sap flow by means of
heat pulse velocity measurements were found in an earlier
study also, and were attributed to non-uniformity of heat
dissipation in the stem (Pickard, 1973). Non-uniform
radial heat dissipation in the stems of herbaceous species
has been discussed in other studies also (Kitano and
Eguchi, 1989; Ishida et ai, 1991). In large stems such as
tree trunks, the existence of a radial gradient in convective
heat pulse velocity has been recognized and been taken
into account by using a multisensor temperature probe.
Such a sensor facilitates independent measurements in
radially narrow regions within the stem (Dye et al., 1991;
Olbrich, 1991).
In view of the interaction between the stem anatomical
structure and the sensor configuration, the calibration
coefficient should be determined individually for each
species and for any given sensor configuration. While the
necessity for calibration of the method for each species
was stressed in our previous studies, the present results
emphasize the interaction between sensor location and
stem structure in determining the calibration coefficient.
For instance, the importance of inserting the sensor to an
exactly determined depth was not carefully considered in
our previous study with corn (Cohen et al., 1993) and,
consequently, the calibration coefficient varied widely
among plants and was slightly higher than in the present
study. The shape of the bundles in corn has been found
to be fairly constant in several lines and hybrids (Sass,
1977), which indicates that the same calibration coefficient
can be used for various corn varieties and environmental
conditions.
The findings of the present study may be used more
widely in the interpretation of other sap flow methods,
which use a steady-state heating of a stem section and in
which temperature changes are monitored mostly at the
stem surface (Sakuratani, 1984; Baker and Nieber, 1989).
When the conducting system structure is similar to that
in sunflower, the bark temperature variation most likely
represents thermal changes caused by diurnal variations
in the sap flow rate, but with a conducting system like
that in corn or sorghum, the effect of changes in the heat
balance of the stem section on the bark temperature
strongly depends on the radial heat conductivity of the
stem (Zhang and Kirkham, 1995). Since the findings in
the present study indicate low heat conductivity in the
tissue between the bundles, it may be expected that
changes in sap velocity in bundles located away from the
bark would not be detected instantaneously by means of
stem-surface temperature measurements.
In spite of the theoretical and technical problems
described above, the heat pulse method has been found
useful for monitoring canopy transpiration in field-grown
cotton (Cohen et al., 1995). The present data validate the
use of the method for plants with large stem diameter.
Because no absolute measurement was used in the field
to determine transpiration, the relationship between the
sap flow and leaf area of single plants was used to test
the consistency and the accuracy of sap flow measurements. The close correlation between leaf area index and
7 has been demonstrated by other researchers (Kanemasu
et al., 1976; Tanner and Jury, 1976; Ritchie and Johnson,
1990). The high correlation between sap flow and leaf
area found in the present study validates the use of this
measurement procedure and suggests that the results were
free of external environmental noise. The high correlation
between potential transpiration computed by the model
and transpiration measured by the heat pulse method,
under non-limiting water supply, validates the use of the
calibration coefficient determined for potted plants. A
consistent ratio between the potential and measured transpiration, irrespective of plant size, plant age and environmental conditions, validates the extrapolation of the
results of sap flow measurements in single plants to
canopy transpiration.
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