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Available online at www.sciencedirect.com
Biosystems Engineering (2003) 86 (3), 257–266
doi:10.1016/S1537-5110(03)00138-7
AE}Automation and Emerging Technologies
Infrared Radiometry for Measuring Plant Leaf Temperature during
Thermal Weed Control Treatment
J. Rahkonen; H. Jokela
Department of Agricultural Engineering and Household Technology, University of Helsinki, P.O. Box 27, Helsinki FIN-00014, Finland;
e-mail of corresponding author: jukka.rahkonen@mmm.fi
(Received 1 July 2002; accepted in revised form 14 July 2003; published online 4 September 2003)
One side of a plant leaf was exposed to liquefied petroleum gas flames, while the temperature of the other side
was measured continuously with an imaging infrared radiometer. Temperature histories of leaves and the
performance of the measuring system were studied by flaming over 200 leaves and recording the measurements
for off-line analysis.
Flaming raised the temperature of the leaves very rapidly. The peak heating rate was typically around
1808C s1. The imaging speed of the radiometer, 50 fields s1, was sufficient to evaluate the temperature
histories. Flaming induced marked temperature differences in the flamed leaves, with veins heated to lower
temperatures than the thin areas between them. Thermograms with good spatial resolution were essential to
characterise the temperature distribution with gradients as steep as 508C over a 1 mm interval.
With a factory calibrated radiometer an accuracy of 218C in absolute temperature values for a
temperature range of 20–908C was achieved by determining the target emissivity with the radiometer. By
calibrating the radiometer for the actual conditions under measurements the error could be reduced to
108C. In conclusion, an imaging infrared radiometer is a superior instrument for measuring fast, spatially
distributed temperature changes in plant leaves during thermal weed control treatment.
# 2003 Silsoe Research Institute. All rights reserved
Published by Elsevier Ltd
1. Introduction
Thermal weed control is a collective name for various
physical methods to kill weeds by using exceptionally
high or low temperatures or electrical fields (Ascard,
1995). In practice, however, thermal weed control
usually refers to killing weeds by heat, and methods
involving the use of electrical fields or low temperatures
are rarely used. For high-temperature treatments, a
number of energy sources from focused sun rays to
microwave radiation (Diprose et al., 1984) have been
tested, but by far the most popular method is flaming
with liquefied petroleum gas (LPG) burners. Nonetheless, flaming is not the only method of practical
relevance. Infrared radiators (Reifschneider & Nunn,
1965), hot gas stream (Porterfield et al., 1967, Bertram &
Meyer, 1996) and hot water (Albrecht, 1985) are all used
to some extent for weed control or for an analogous
treatment, thermal defoliation.
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Irrespective of the energy source, all high-temperature
weed control methods kill plants by heating a critical
number of cells to a lethal temperature. Thus, valuable
information about the processes in thermal weed control
should be yielded by temperature measurements. However, few studies have been done on plant temperatures
in flaming, despite the first ones being performed in the
1960s and 1970s (Thomas, 1967; Porterfield et al., 1971).
Yet in other contexts, plant temperatures have been
measured intensively at least since 1875 by various
investigators, as reviewed by Gates (1980), and different
measurement methods and their advantages and disadvantages have been discussed widely.
Plant temperatures can be measured either by
contact sensors, usually small thermocouples or thermistors, or by infrared temperature meters. Accurate
measurements can be obtained with both methods,
assuming all possible error sources are understood and
eliminated.
257
# 2003 Silsoe Research Institute. All rights reserved
Published by Elsevier Ltd
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J. RAHKONEN; H. JOKELA
To ensure reliable temperature measurements with
contact sensors, a good thermal contact between the
sensor and object is necessary. With plants, this is best
achieved by inserting the sensor inside plant tissues.
Sensor insertion into thin parts, such as leaves, may be
difficult or may cause excessive damage. Leaf temperature is therefore usually obtained by attaching the sensor
onto the leaf surface, but great care is needed with this
method to assure an adequate thermal connection.
Another problem is heat conduction through connection
wires when a temperature difference exists between the
plant and its surroundings. Beadle et al. (1973) studied
the accuracy of leaf temperature measurements and
found that a poor thermal contact together with thermal
conduction along the thermocouple wires can lead to a
marked measurement error. With a relatively large
thermocouple junction, the error reached 358C, while
the temperature difference between the leaf and
surrounding air was no more than 798C. Errors of the
same magnitude are reported by Pieters and Schurer
(1973), who reported 5–78C measurement errors with a
238C temperature difference between the leaf and air.
With a careful positioning of thermocouples, the error
could be reduced to 18C. Tarnopolsky and Seginer
(1999) postulated, that to reduce conduction error to
1% of the temperature difference, at least 10 mm length
of thermocouple wires with insulation removed should
be glued to a leaf. Similar results have been given for
inserted sensors, which are also prone to conduction
error. Cook et al. (1964) got reliable measurements by
inserting the thermocouple junction and 10 mm length
of thermocouple wires under the leaf epidermal surface.
Plant temperature measurement by contact sensors is
laborious if measurement errors are to be eliminated. In
addition, the sensors themselves may affect the plant
temperature (Tanner, 1963). For these reasons, temperature measurement of vegetation by infrared thermometers
has become common since the 1960s, when the first
commercial models became available on the market.
Infrared thermometry is a non-invasive, non-destructive
method that has a negligible influence on the target
temperature. Infrared thermometers measure the surface
temperature, which can sometimes be a drawback.
Another drawback of non-imaging IR thermometers is
their spatial resolution, typically some millimetres at a
minimum, thus limiting their use with very small targets.
The accuracy of radiative temperature measurements of
plants have been discussed by Fuchs and Tanner (1966),
Sutherland and Bartholic (1979), Amiro et al. (1983),
Graham (1989), Hipps (1989), van de Griend et al. (1991),
and others. Errors in radiative temperature measurements
originate from incorrect estimates for emissivity values and
background radiation. The lower the emissivity, the
greater is the influence of erroneous estimates. Green
leaves have very high emissivity values, 095–100 (Gates,
1964; Idso & Jackson, 1968; Willey, 1985; Elwidge, 1988;
Hashimoto, 1990), rendering them a favourable target for
radiative temperature measurements. Fuchs and Tanner
(1966) have shown that the temperature of vegetation can
be measured with an infrared thermometer to an accuracy
of 01–038C when the emissivity is known.
A specialised branch of infrared thermometry is
imaging infrared radiometry, or infrared thermography.
In thermography, a large amount of point temperatures
(i.e. 256 256) are measured over an area and processed
to form a thermal map, or thermogram, of the target
surface. Thermography with a high spatial resolution is
a powerful tool for analysing and visualising targets
with thermal gradients. The imaging speed of the
instrument is high, e.g. 50–60 images per second, which
makes it especially suitable for exploring rapidly
changing thermal conditions.
Plant leaf temperature patterns have been studied by
thermocouple measurements (Cook et al., 1964) and by
thermography to determine the relationships between
temperature and water stress (Hashimoto et al., 1984)
and between temperature and stomatal conductance
(Jones, 1999). These investigations have shown that
under normal growing conditions, temperature differences of several degrees Celsius can be found within a
single leaf. Thus, it could be surmised that in thermal
weed control, with conditions far removed from the
natural, even wider temperature variations in leaves
would be present. With contact sensors, this thermal
variation would be very difficult to explore because the
high radiation and at least 12008C temperature difference between flames and leaf are likely to introduce
radiation and conduction error in measurements. Moreover, careful arranging of several thermocouples on
every leaf to be surveyed is both laborious and prone to
affect the temperature to be measured. The objective of
this paper is to present an experimental design enabling
the use of an imaging infrared radiometer for measuring
temporal and spatial variation of temperature in plant
leaves during thermal weed control and estimate the
accuracy of measurements obtained by this method. The
measurement data are used for describing the thermal
behaviour of true plant leaves treated with LPG flamer
and for evaluating the benefits and drawbacks of
alternative temperature measurement methods.
2. Materials and methods
2.1. Basic theory
Radiometric surface temperature measurements are
based on measuring the energy emitted by a target. The
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MEASUREMENT OF PLANT LEAF TEMPERATURE BY INFRARED RADIOMETRY
energy emitted by a blackbody (emissivity e ¼ 1) at any
given wavelength l is given by Planck’s distribution law
as follows:
EðlÞ ¼
8phcl5
expðhc=klTÞ 1
ð1Þ
where: c is the speed of light (3 108 m s1), h is Planck’s
constant (663 1034 Js), k is Boltzmann’s constant
(138 1023 J K1) and T is the object temperature in
K. Integration of Planck’s equation for all wavelengths
gives the total energy emitted by the blackbody. The
result of the integration is known as Stefan–Boltzmann’s
law,
R ¼ sT 4
ð2Þ
where: R is the flux emitted by unit area of a plane
surface into an imaginary hemisphere surrounding it
in W m2 and s is Stefan–Boltzmann’s constant
(567 108 W m2 K4).
With radiometers operating at a limited band width,
the Stefan–Boltzmann equation is not applicable,
instead Planck’s law must be used. Numerical integration of Planck’s law for a wavelength range of 8–12 mm
and a temperature range of 290–360 K is given by
R8212
mm
¼ s T 45
ð4Þ
Combining Eqns (3) and (4) gives the total amount of
thermal infrared radiation entering the radiometer set at
a wavelength of 8–12 mm and a temperature of 290–
360 K as follows:
RB ¼ es Tl45 þ ð1 eÞs Tb45
2.2. Imaging infrared radiometer
Thermal images were obtained by using an Inframetrics 760 E imaging infrared radiometer (Inframetrics, Inc., part of the FLIR Systems company since
1999). Model 760, manufactured in 1990–1998, is a
scanning long-wave (8–12 mm) device with a single
HgCdTe detector. The imaging speed of the scanner is
50 fields s1 with 240 infrared lines field1 and 194
resolution elements line1 [50% response on Slit Response Function (SRF)]. A spatial resolution of
18 mrad (50% SRF) is obtained by standard optics
with a 158 vertical field of view (FOV) and a 208
horizontal FOV.
The Inframetrics 760 system converts thermal measurements to an 8-bit (256 level) greyscale video signal
that can be recorded by a standard VHS videotape
recorder. For the recordings, a regular, new VHS
videotape was used. Analysis of the recorded measurements was performed by a model 760 compatible digital
thermal image processing system (Thermagram 50 by
Thermoteknix Systems Ltd.).
2.3. Experimental arrangement
ð3Þ
where s* is a constant analogous to Stefan–Boltzmann’s
constant.
Real objects invariably emit less energy than a
blackbody. The ratio of the actual radiation to the
hypothetical is indicated by emissivity e. For opaque
objects, such as green leaves at wavelengths beyond
8 mm (Gates & Tantraporn, 1952), Eqn (4) is valid for
emissivity and reflectivity l:
eþl¼1
259
ð5Þ
where: RB is the energy flux emitted at wavelength of
8–12 mm in W m2, Tt is the temperature of the target in
K and Tb is the background temperature in K that the
target is reflecting.
Equation (5) addresses the two sources of error in
radiative temperature measurements, viz. the estimates
of emissivity and background temperature. These errors
in connection with plant temperature measurements
have been discussed in more detail by Sutherland and
Bartholic (1979), Amiro et al. (1983), Hipps (1989) and
Svendsen et al. (1990).
To investigate the temperature of plants during
thermal treatment, the rate of heating and the spatial
temperature distribution, one leaf at a time was flamed
from one side with a LPG burner, while the temperature
of the other side of the leaf was recorded by an imaging
infrared radiometer. The experimental configuration is
shown in Fig. 1.
A vertical plate, made of painted metal, was inserted
in front of the infrared scanner at a distance of 70 cm. A
fresh leaf, just separated from a plant, was attached to a
plate with the underside towards the plate to completely
cover a round measuring window (diameter 244 mm) in
the middle of the plate. A metal spring was used to
smoothly press the margins of the leaf against the plate.
The upper surface of the leaf was flamed with a round,
horizontally moving LPG burner using gas phase
propane as a fuel. The burner was equipped with a
05 mm nozzle and was operated at a pressure of
100 kPa. By changing the burner speed, propane doses
5–180 kg ha1 were achieved. By comparison, under
field conditions, LPG consumption over the entire area
being flamed is usually 30–80 kg ha1.
The infrared scanner was focused to the middle of the
measuring window to continuously record the temperature of the underside of the leaf. The total length of the
optical path, including a 22 cm internal path inside the
scanner, was 92 cm. This, together with a 18 mrad
spatial resolution, resulted in a resolution unit size of
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J. RAHKONEN; H. JOKELA
Infrared radiometer
Leaf attached
on a metal sheet
Moving LPG burner
Control unit
Video tape recorder
Fig. 1. Experimental arrangement for measuring temperature of one side of a plant leaf by imaging infrared radiometer while the
other side is exposed to liquid petroleum gas (LPG) flames
17 mm by 17 mm on the leaf surface (50% SRF). The
total number of resolution units within the measuring
window was approximately 160.
2.4. Plant material
A primary requirement for a plant was that it be
relatively broad-leaved to offer sufficient surface area for
investigation of spatial temperature variation. The first
test plants were greenhouse-grown rape seeds (Brassica
rapa ssp. oleifera) and a benjamin tree (Ficus benjamina),
which had until the experiment been cared for as a
houseplant. Later, leaves from greenhouse grown field
sow-thistle (Sonchus arvensis) were also used. For each
plant species, about 100 leaves were flamed at various
flaming intensities, the extremes being 5 and 180 kg ha1
LPG. All the measurements were recorded on videotape
for later analysis.
& Davies, 1972; Pinkley et al., 1977; Zhang et al., 1986;
Salisbury & Milton, 1988). The background radiation
level was measured by using an aluminium foil inserted
near the water surface as a reflector. The radiation levels
of a reference surface and a leaf carefully lowered to
float on the water were measured. The emissivity of the
leaf was calculated using the equation:
ðRtarget Rbackground Þ
ereference
ð6Þ
etarget ¼
ðRreference Rbackground Þ
The emissivity value was determined to be 098 001
for both Brassica rapa and Sonchus arvensis leaves.
2.6. Thermal image analysis
2.5. Leaf emissivity measurement
Several different thermal analyses were performed by
using the Thermogram 5.0 digital infrared thermal
image processing system. Because of the large amount
of measurement data, all of the material was not
included in each analysis. The different analyses and
the material used in each are listed below.
Emissivities of three Brassica rapa and Sonchus
arvensis leaves were measured with a reference emittance
technique described in the Inframetrics model 760
operator’s manual. A well-stirred water bath at a
temperature of about 458C was used as a reference
material (Berliner et al., 1984). Temperature of the water
bath was controlled by a mercury thermometer accurate
to 018C. Emissivity of water (l ¼ 8–12 mm) was
assumed to be 098 (Buettner & Kern, 1965; Robinson
2.6.1. Repeatability of image analysis and total noise in
recorded signal
The manufacturer specifies the accuracy of model
760 radiometers to 28C or 2% of a blackbody target
source and the repeatability of measurements to 058C
or 05%. These values do not, however, represent the
accuracy and repeatability of temperature analysis
performed afterwards on the basis of recorded measurements. In the analysis system used in this study, the
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MEASUREMENT OF PLANT LEAF TEMPERATURE BY INFRARED RADIOMETRY
2.6.2. Spatial variation in temperature
Spatial variation in temperature was analysed by
capturing thermal images at the moment of peak
temperature for every flamed Brassica rapa leaf. These
thermal images represent well the temperature patterns
over a surface. Exact numbers were obtained by
computing histograms of the proportional distribution
of point temperatures within a measurement window.
Linear temperature gradients were studied by creating
line graphs describing temperatures along a line crossing
a leaf.
2.6.3. Temporal variation in temperature
Temporal variation in temperature was analysed by
plotting the average temperature of a selected area of
a leaf versus time at a maximum sample rate of 50 Hz.
Analysis was performed for all leaves of the three
species. The size of the area used for averaging was
limited by the computing speed to 1688 image pixels,
corresponding to a round surface area of 82 mm in
diameter. In addition, simultaneous temperature plots
from three circular areas, each with 392 image pixels in a
40 mm diameter, were generated for 50 Brassica rapa
leaves. The plot areas were situated on primary veins,
secondary veins and the thin areas between veins.
Calculations were performed based on actual conditions during measurements. The emissivity value of 098
was assumed to be correct to 001. The measured
background temperature in the laboratory was 178C,
and in extreme cases the actual radiative temperature
was estimated to vary between 12 and 278C. Errors were
calculated for the same temperature range as for the
numerical integration of Planck’s law, i.e. 17–878C
(290–360 K).
The influence of emissivity error was also calculated
for a case where emissivity is not measured but just
assumed to be 098. In this case, the upper limit for
actual emissivity is 100. Based on various references
for emissivity (l ¼ 8–12 mm) of green leaves, 095
was used as a lower limit (Tanner, 1963; Gates, 1964;
Fuchs & Tanner, 1966; Idso & Jackson, 1968;
Willey 1985; Salisbury, 1986; Elwidge, 1988; Hashimoto,
1990).
The temperature errors caused by the use of incorrect
estimates are shown in Fig. 2. When the emissivity value
of 098 is accurate to 001, the error in absolute
temperature is less than 068C up to 908C and less
than 048C below 608C. When temperature differences
are considered, the temperatures are read from the same
curve and the errors partly cancel each other out. Thus
the error at 708C true temperature difference between 20
and 908C is less than 058C. Considerably larger
errors can occur if the emissivity value is not determined
(the outmost curves), the maximum error ranging from
15 to +108C at 908C.
1.50
1.00
Temperature error, K
measurement signal goes through a long chain before
the initial radiative measurements are converted to the
final temperature values. This chain includes digital to
analogue (D/A) conversion to a recordable video signal,
videotape recording and playback, capturing of the
playback signal, and an A/D conversion before the
actual computerised image analysis can take place.
As neither the hardware nor the software manufacturer assessed the overall accuracy of the analysis, two
tests were performed. In a repeatability test series, at
least 10 temperature–time plots were generated from the
same measurements. The total noise included in the
temperature signal was investigated by creating histograms of single pixel temperatures from a recorded
measurement of a large target at a constant temperature.
0.50
0.00
− 0.50
− 1.00
− 1.50
3. Accuracy of measurements
3.1. Error induced by uncertain target emissivity and
background temperature values
The image processing system makes an automatic
background radiation correction and calculates the
target temperature by using the given emissivity and
background temperature values as parameters. Equation (5) can be used for calculating the temperature
errors arising from faulty parameters.
− 2.00
270
290
310
330
350
True target temperature, K
370
390
Fig. 2. Temperature errors in using values 098 and 290 K for
emissivity and background temperature, respectively, instead of
true values; true values: &}&, 100 and 300 K; } , 099
and 300 K; n}n, 097 and 285 K; +}+, 095 and 285 K; the
outermost curves represent maximum errors when true emissivity
varies between extreme values for green leaves, i.e. from 100 to
095, while the curves in between represent maximum errors
when emissivity value is measured to accuracy of 001, which
was the case in this study
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J. RAHKONEN; H. JOKELA
3.2. Other error sources
3.2.1. Accuracy of the instrument
The Inframetrics model 760 radiometer is factory
calibrated to an accuracy of 28C or 2%, which
is valid over an ambient temperature range of 15 to
508C. This is also the accuracy of the instrument used in
calculations. Lacking possibility for blackbody calibration and without knowing the actual calibration curves
no better accuracy could be assumed over the whole
measurement range of the instrument, even though
according to the manufacturer the typical accuracy at a
constant ambient temperature of 238C is 18C or 1%
(Inframetrics, Inc., 1991). At a limited target temperature range of 20–508C, the radiometer was calibrated
against a mercury thermometer while the plant leaf
emissivity was measured, and observed to be accurate
to 18C.
3.2.2. Total signal noise
The total signal noise of the image processing system
was measured by analysing thermal images obtained
from a painted metal plate at a uniform temperature.
Thermal images showed Gaussian distribution for single
pixel temperatures. The standard deviation was 0858C
at an average temperature of 2288C (sample size 19 008
pixels). At a 95% confidence level, the accuracy of a
single pixel measurement is 188C. To obtain 018C
accuracy, the result must be the average of at least 320
pixels. Pixel number 1688, used for time–temperature
plots, yields an accuracy of 0048C at a 95%
confidence level.
with 1688 image pixels were plotted over 20 s at a
maximum sample rate of 50 s. The average of the peak
temperatures was 6198C, with a minimum of 6158C
and a maximum of 6218C. Standard deviation was
0178C, therefore, at a 95% confidence level, the
accuracy was 048C.
The average temperatures on time–temperature plots
were compared with temperatures computed for the
same areas on sequential images captured from live
video. When the frame capture was successful, these two
temperatures were the same to 028C. This was,
however, not always the case. Occasionally, frame
capture failed totally or, in the worse case, the
temperature information on the captured image was
corrupted, leading to temperature error of several
degrees.
3.3. Total error
The total error for independent errors showing
normal distributions can be calculated as follows:
ffi
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Xn
2
Dm
ð7Þ
Dmtotal ¼ i
i¼1
where: Dmtotal is the total error and Dmi . . . Dmn are the
independent error terms. A summary of the errors
caused by individual error terms and the total error of
measurements is given in Table 1.
4. Results
4.1. Spatial temperature variation in leaves
3.2.3. Repeatability of live video temperature plotting
and video frame capturing
The reliability of live video temperature plotting was
tested by repeating the plotting 15 times for the same
video sequence. Average temperatures of a round area
Thermal images captured at the moment of peak
temperature demonstrated a marked spatial variability
in leaf surface temperature. A typical example is
presented in Fig. 3. A greyscale image is a thermograph
Table 1
Examples of independent error terms in temperature measurement by imaging infrared radiometer and the total error of
measurement
Source of the error
Magnitude of the error
Conditions
(a) Wrong estimates
(b) Wrong estimates
(c) Calibration error
(d) Calibration error
058C
15108C
28C or 2%
18C
(e) Sample error
(f) Plotting error
018C
048C
At 608C, emissivity measured
At 908C, emissivity estimated
At ambient temperature range of 15 to 508C
At ambient temperature range of 208C and target
temperature range of 20–508C
Averaged from 320 pixels
At 608C
Total error at 20–508C
Total error at 608C
Total error at 908C
128C
218C
25 to 238C
ða þ d þ e þ f Þ
ða þ c þ e þ f Þ
ðb þ c þ e þ f Þ
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MEASUREMENT OF PLANT LEAF TEMPERATURE BY INFRARED RADIOMETRY
with a whitish colour denoting higher temperatures.
Beneath the image, a line graph presents the temperatures along a horizontal line marked on the image. A
histogram gives the distribution of temperatures of the
19 984 image pixels within the measuring window.
The average temperature of the leaf at the moment of
image acquisition was 6408C. However, almost 40% of
the leaf area was either colder than 508C or hotter than
808C, the minimum and maximum temperatures being
246 and 9708C.
(a)
4.2. Temporal temperature variation in leaves
100
90
Temperature, °C
80
70
60
50
40
30
20
0
5
10
15
Distance, mm
(b)
20
25
400
350
Number of pixels
300
250
200
Different intensities in flaming treatments were
achieved by changing the burner velocity. This can be
seen in Fig. 4, which describes the average temperatures
of Sonchus arvensis leaves (seven replicates) flamed at
different intensities. Initially the temperature of the
leaves rises at a fairly equal speed in all treatments, but
with heavier flamings, the leaves are heated for longer
periods and reach higher temperatures. The maximum
rates of heating were 57, 160, 187 and 1808C s1 for
treatments 20, 30, 70 and 100 kg ha1 LPG, respectively
(calculated over a 01 s duration). The applicability of
the 50 Hz sample rate to characterise the temperature
changes was verified by visually checking the ascending
part of temperature curves. An example, given in Fig. 5,
presents temperature rise in a Brassica rapa leaf
receiving 70 kg ha1 LPG treatment.
Spatial temperature variation in leaves was also
changing with time as can be seen in Fig. 6. The figure
presents temperature histories of three distinct areas
within a single Brassica rapa leaf flamed at intensity of
70 kg ha1 LPG. The variation was as largest immediately after the thermal treatment and faded gradually,
but temperature differences of several degrees Celsius
150
100
100
90
50
21
30
40
48
57 64 72
Temperature, °C
80
87
94
Fig. 3. (a) Typical thermograph showing temperature variation
at the moment of peak temperature in a Brassica rapa leaf
flamed at 70 kg ha1; (b) curve presenting temperatures on the
line shown in the thermograph; (c) histogram presenting the
distribution of pixel temperatures within the circle shown in
the thermograph
Temperature, °C
0
(c)
100 kg/ha
80
70 kg/ha
70
30 kg/ha
60
50
20 kg/ha
40
30
20
10
0
1
2
3
4
5
Time, s
of a Brassica rapa leaf just flamed at 70 kg ha1 LPG.
Veins, which remain relatively cool, can be clearly
distinguished as dark lines from the thin middle areas
Fig. 4. Temperature histories of Sonchus arvensis leaves flamed
at intensities of 20, 30, 70 and 100 kg ha1 LPG; each curve is an
average of seven replicates
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J. RAHKONEN; H. JOKELA
70
Temperature, °C
60
50
40
30
20
10
1.4
1.5
1.6
1.7
1.8
1.9
Time, s
Fig 5. Temperature rise in a Brassica rapa leaf receiving
70 kg ha1 LPG flaming treatment; the points present momentary temperatures measured at 50 Hz sample rate
100
90
Temperature, °C
80
1
70
2
60
3
50
40
30
20
10
0
1
2
3
4
5
Time, s
Fig. 6. Simultaneous time–temperature plots from three circular
areas, each with 392 image pixels in a 40 mm diameter, situated
on: 1, the thin area between veins; 2, secondary vein; and 3,
primary vein of a Brassica rapa leaf flamed at intensity of
70 kg ha1 LPG
existed for many seconds. Figure 6 is also presenting an
extremely fast temperature rise: thin area of the leaf was
warmed up from 249 to 8698C within 01 s corresponding to heating rate of 6208C s1.
5. Discussion
Three distinct factors introduce error to temperature
measurement with imaging infrared radiometers: incorrect estimates of target emissivity and background
radiation, inaccuracy of the instrument itself, and
discrepancies over the signal processing chain between
native measurements and final results. For leaf temperature measurement during LPG flaming using one
particular measurement and analysis system, the magnitudes of these three errors were 058C, 208C and
048C, respectively, at 608C over an area of 320 image
pixels. Combining these independent errors yields an
overall measurement accuracy of 218C.
The first error, caused by the faulty estimates of
emissivity and background, is similar for all infrared
radiometers, with slight differences according to the
wavelength range utilised. To reduce this error, the
estimates should be determined with an accuracy better
than 001. However, radiative temperature measurement of green leaves is relatively insensitive to erroneous
parameters since the emissivity of leaves is very high
(e ¼ 095–100), and thus, more accurate estimates
would only yield a small improvement to the overall
accuracy. Furthermore, because of natural variation,
some uncertainty in the emissivity of leaves is likely to
remain.
The second error term, the accuracy of the radiometer
itself, is instrument-specific. The accuracy of the radiometer used in this study was specified by the manufacturer as 28C for an ambient temperature range of 15
to 508C. Further, according to the manufacturer, the
typical accuracy at an ambient temperature of 238C is
18C, but because calibration data was lacking, this
information was not deemed reliable. Had this data been
available, the accuracy under standardised ambient
conditions could be improved to 058C, the value
specified by the manufacturer for repeatability of
measurements. As calibration error is the biggest error
term, its reduction would greatly improve overall
accuracy. A 078C calibration error would yield an
overall accuracy of 108C if other conditions remain
unchanged.
The third error term, also system-specific, comprises
noise from various sources in the image analysis system
as well as the error caused by the step-wise response of
digital systems. The system used in this study, with an
eight-bit dynamic range and an analogue VHS videotape as a bulk data storage medium, gave an error of
048C. Some of this error might be eliminated by using
the new imaging infrared system with a 12-bit dynamic
range and all digital data storage, but again the potential
improvement to overall accuracy would be relatively
small. However, the benefit of using digital data storage
would be considerable if the problems occasionally
encountered in data retrieval with the analogue system
could be avoided.
Both the temporal and the spatial variations in
temperature of the leaves under flaming treatment were
great. The sample rate of 50 Hz obtained by the
radiometer was high enough to characterise the temporal variation, as can be seen in Fig. 5, where both the
rising part of the slope and the moment of peak
ARTICLE IN PRESS
MEASUREMENT OF PLANT LEAF TEMPERATURE BY INFRARED RADIOMETRY
temperature are well covered with several sample points.
In this measurement, a sample rate of 25 Hz can be
considered as a minimum to represent the shape of the
temperature curve correct.
In a thermogram, each point temperature is an
average temperature from a larger area called a
resolution unit. Temperatures from points with intervals
equal to or greater than the size of the resolution unit
are independent, otherwise they are averaged from areas
partly covering each others, thus leading to underestimated temperature differences. Therefore, the size of
the resolution unit should suit the minimum distance
over which accurate temperature differences are to be
measured.
In this study the size of the resolution unit was 17 mm
by 17 mm. Figure 3 shows temperature differences are as
high as 508C over 1 mm distance. This indicates that
reducing the size of the resolution unit would have been
advantageous. Standard optics of the radiometer make
used in this study allow a resolution unit size of 09 mm
by 09 mm, but with alternative optics even the size of
0004 mm by 0004 mm is achievable. Limiting factor in
practice is the distance between the leaf and the
radiometer needed to protect the valuable instrument
from flames possible penetrating through the measuring
window.
On the basis of our study, point temperatures with
at most 2 mm intervals should be measured at 25 Hz
sample rate at minimum in order to characterise
the spatial and temporal temperature variation in
plant leaves during thermal weed control properly.
In addition, the measuring device should have very
fast response time and it should be insensitive to
thermal disturbance caused by the thermal treatment.
In order to satisfy these demands a high-grade imaging
infrared radiometer with fast imaging speed and good
optics is a superior tool. Non-imaging infrared thermometers, based on the same principles of radiative
temperature measurements, can offer as good measurement accuracy as imaging radiometers, but because they
are limited to measure single-point temperatures no
information about spatial variation of temperature
can be gained. Infrared thermometers has also too
slow response times to properly record the very fast
temperature changes we found to occur during thermal
treatment.
By using contact sensors, because of the tough
conditions during a thermal treatment it would be very
hard to achieve measurement accuracy comparable with
radiative temperature measurement methods even in
single-point measurements. When not performed with
special care, measurement by thermocouples has been
reported to give a 5–78C temperature error with a
temperature difference of 238C between the leaf and
265
surroundings (Pieters & Schurer, 1973). Higher accuracy
can be obtained if good thermal contact exists between
the plant and the thermocouple, and conduction and
radiation errors are eliminated. In practice, this can be
achieved, for example, by gluing at least a 10 mm length
of thermocouple wires onto a leaf (Tarnopolsky &
Seginer, 1999). This will reduce the conduction error to
1% of the temperature difference. When it comes to
thermal weed control by flaming, where the temperature
difference between flames and air can be as high as
15008C, this 1% will result in a 158C error in measured
leaf temperature. One way to further reduce the
conduction error is to prevent flames from entering the
side of the leaves where the thermal sensors are located.
The experimental design would then be similar to that
used in this study, where flaming treatment was only
directed to one side of leaves to block out direct thermal
radiation from flames. However, gluing even a single
thermocouples on a leaf would change its thermal
properties, and to install thermocouples with 2 mm
intervals to measure the spatial variation in temperature
is not reasonable.
6. Conclusions
The temporal and spatial variations in temperature of
leaves during flaming are possible to measure with good
accuracy by using an imaging infrared radiometer and
an experimental setup described in this paper. In this
study, an accuracy of 218C in absolute temperature
values was achieved, and for temperature differences the
error can be reduced further to 108C for a temperature range of 20–908C.
The temperature of the leaves rose rapidly during
flaming, typically around 1808C s1. To record the
temperature changes successfully a sample rate of
25 Hz or higher was needed. The radiometer with an
imaging speed of 50 fields s1 had no problems in
recording the temporal variation in temperature.
The high spatial resolution of the imaging infrared
radiometer, 17 mm by 17 mm expressed as the size of
the resolution unit, was essential to reveal the large
spatial variation in temperature of leaves during
flaming. The steepest temperature gradients measured
reached 508C mm1.
In conclusion, plant leaf temperature during thermal
weed control treatment can be measured with success by
using an imaging infrared radiometer. The overall
accuracy of the infrared radiometer is at least as good
as obtainable with other temperature measurement
methods, and both the sample rate and spatial resolution of high-grade radiometers are good enough to
characterise the temperature patterns in leaves.
ARTICLE IN PRESS
266
J. RAHKONEN; H. JOKELA
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