CSIRO PUBLISHING

Functional Plant Biology, 2009, 36, 990–997

www.publish.csiro.au/journals/fpb

An infrared-based coefﬁcient to screen plant environmental
stress: concept, test and applications
Guo Yu Qiu A,D, Kenji Omasa B and Sadanori Sase C
A

School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen 518055, China.
Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.
C
National Institute for Rural Engineering, Tsukuba, Ibaraki 305-8609, Japan.
D
Corresponding author. Email: qiugy@szpku.edu.cn
BThis paper originates from a presentation at the 1st International Plant Phenomics Symposium,
Canberra, Australia, April 2009.

Abstract. By introducing a reference dry leaf (a leaf without transpiration), a formerly proposed plant transpiration transfer
coefﬁcient (hat) was applied to detect environmental stress caused by water shortage and high temperature on melon, tomato
and lettuce plants under various conditions. Results showed that there were obvious differences between leaf temperature,
dry reference leaf temperature and air temperature. The proposed coefﬁcient hat could integrate the three temperatures andquantitatively evaluate the environmental stress of plants. Experimental results showed that the water stress of melon plants
under two irrigation treatments was clearly distinguished by using the coefﬁcient. The water stress of a tomato plant as the soil
dried under a controlled environmental condition was sensitively detected by using hat. A linear relationship between hat
and conventional crop water stress index was revealed with a regression determination coefﬁcient R2 = 0.97. Further, hat wasused to detect the heat stress of lettuce plants under high air temperature conditions (28.7C) with three root temperature
treatments (21.5, 25.9 and 29.5C). The canopy temperature under these treatments was respectively 26.44, 27.15 and27.46C and the corresponding hat value was –1.11, –0.74 and –0.59. Heat stress was also sensitively detected using hat.
The main advantage of hat is its simplicity for use in infrared applications.
Additional keywords: heat stress, IR, lettuce, melon, plant transpiration transfer coefﬁcient, remote sensing, tomato,transpiration, water stress.

Introduction
The surface temperature of plants varies with evapotranspiration(ET), photosynthesis and environmental factors. Because ofthis characteristic, plant surface temperature has been used as
an indicator of water and environmental stress, and extensive
research has been conducted to explore the relationship between
plant surface temperature and other factors. Monteith and Szeicz(1962) presented a theoretical discussion of the relationshipbetween surface temperature and stomatal resistance. Carlson
et al. (1972) found that plant leaf temperature increased as therelative leaf water content and vapour pressure deﬁcit decreased.
Ehrler (1973) demonstrated the linear relationship between
the leaf–air temperature difference and the vapour pressuredeﬁcit. Later, a quantitative expression relating the canopy–air
temperature difference to ET, net radiation, soil heat ﬂux andaerodynamic resistance was developed (Monteith 1981; Hatﬁeld1985). Plant temperatures in these early works were mainly
measured by thermocouples.
Beginning in the 1980s, the use of surface temperature as anindicator of water and environmental stress increased due to thedevelopment of an infrared (IR) thermometer. For example, it was CSIRO 2009

applied to estimate ET (Garder et al. 1981; Hatﬁeld 1983; Jackson
et al. 1983; Ben-Asher et al. 1992; Qiu et al. 1996a; Qiu and
Ben-Asher 2009), photosynthesis (Weyers and Lawson 1997)
and crop water stress index (Jackson et al. 1981, 1988; Idso 1982;
Qiu et al. 1996b).
From the early 1980s to the early 1990s, the application of
surface temperature in plant science dramatically increased due tothe development of digital IR imaging techniques. IR imaging
was initially applied only under controlled conditions. The
approach developed by Omasa et al. (1980, 1981a, 1981b)
and Hashimoto et al. (1984) were the earliest works to use
digital IR imaging in plant science. Later, this technique was
gradually improved and applied widely in the detection of
stomatal movement, stomatal conductance and photosynthesis(e.g. Hashimoto et al. 1990; Omasa 1990; Omasa and Croxdale
1992; Omasa 2002; Omasa and Takayama 2003). Recently, thistechnique was further applied to screen plant genotypes fordrought tolerance (Jones 2009), salinity tolerance (James et al.
2008; Sirault et al. 2009) and stomatal mutants (Genty 2009). IR
imaging has also been applied under ﬁeld conditions on a plant
canopy scale and beyond (Jones 2009) for quantitatively

10.1071/FP09132

1445-4408/09/110990

IR-based coefﬁcient to screen environment stressdetecting environmental stress and guide irrigation or monitoring
plant phenotypes (Jones 1999, 2009).
Because plant surface temperature can be measured or
estimated by remote sensing in combination with other plantand environmental factors, there has been increased use insatellite based remote sensing (Karnieli et al. 2001). Moranet al. (1994) proposed a surface–air temperature andvegetation index to estimate crop water deﬁcit and Moranet al. (1996) combined the Penman-Monteith equation withmeasurements of surface temperature and reﬂectance toestimate the ET of semiarid grasslands. Moran et al. (1997)
also suggested that measurements of soil and crop properties
combined with multispectral imagery could produce accurate,
real time maps for soil and crops.
On the basis of the above research, remote sensing of
surface temperature with IR has become an establishedtechnique for the diagnosis of bioenvironmental informationand has been widely applied in the ﬁelds of plant physiology,
ecophysiology, environmental monitoring and agriculture(Jones 1999). Monitored bioenvironmental processes include
transpiration, stomatal conductance, metabolic processes,
disease and infection (Jones 2004). Since the late 1990s, IR
technique has been receiving more attention in applications
ranging from micro to macro scales (Suleiman and Crago
2004; Omasa and Aiga 2006). The use of thermal remotesensing, especially when combined with spectral reﬂectance oreven ﬂuorescence measurement, is becoming a powerful andincreasingly-used tool to diagnose and monitor the effects ofenvironmental stress on plants (Jones 2009).
However, plant surface temperature can vary both spatiallyand temporally. For example, leaf surface temperature can varywith transpiration rate, stomatal opening, air temperature, soil
water content, wind velocity and albedo (Leigh et al. 2006). Thus,
temperature variability is a limitation for the real application of
IR technique, especially when ‘scaling up’ to the ﬁeld level.
As summarised by Jones (2009), calibration or normalisation
can make it more quantitative. So far, there have been several
approaches to normalisation: normalising against air temperature(such as stress degree day, Jackson et al. 1977), normalisingagainst calculated wet or dry references (crop water stress index(CWSI), Idso 1982) or actual wet or dry surface (Qiu et al. 1996b,
2000; Jones 1999) and calculation using meteorological data
(air temperature, net radiation, humidity, wind velocity, Leinonen
and Jones 2004).
Among these normalising methods, using real dry references
has several advantages. Because the dry surface is installed in thesame environmental conditions as the actual surface, it responds
to environmental variability in a way similar to the real surface.
Indeed, in many cases using the actual dry surface is easier for
application and maintenance.
Due to these characteristics, the dry reference approach
was applied here and further improved by normalising the leaf
temperature simultaneously against a dry reference temperature
and air temperature (Qiu 1996). Because there were three kinds oftemperature included in his approach, Qiu’s model was referred as‘three temperatures model (3T model)’. Brieﬂy, the 3T model was
proposed by Qiu (1996) and included two components: soil
evaporation and plant transpiration. Later, the soil evaporation
part was developed to estimate soil evaporation rate (Qiu et al.

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991

1998, 1999), soil evaporation stage (Qiu and Ben-Asher 2009)
and remote sensing application (Qiu et al. 2006). However,progress of plant transpiration part was less developed. In
1996, the transpiration submodel in the 3T model wasdeveloped for estimation of plant transpiration rate (Qiu et al.
1996a) and then extended for estimation of the crop water stress(Qiu et al. 1996b) under ﬁeld conditions. Afterward, it was further
improved for greenhouse conditions (Qiu et al. 2000). Later,comparisons of the 3T model with Penman-Monteith and Bowen
ratio methods were conducted (Qiu et al. 2002). In 2003,
a plant transpiration transfer coefﬁcient (hat) was proposed(Qiu et al. 2003).
According to Qiu (1996), a reference leaf canopy (dry leaf
canopy without transpiration, hereafter referred to as thereference leaf) in the plant canopy, with a relatively small
volume, would experience temperature, humidity, wind speed
and other environmental parameters of the plant canopy were notsigniﬁcantly modiﬁed by the reference leaf. It was assumed thatthe radiation absorbance and albedo property of the reference
leaf was similar to the other plant leaves. The temperatures of theplant canopy and reference leaf were assumed to be represented
by the sunlit temperatures of leaves and reference leaves,respectively. Then, by neglecting the soil heat ﬂux under plant
canopy, the energy balance of the plant canopy and reference leaf
could be given as:
Rn ¼ H þ LE

ð1ÞRnf ¼ H fð2Þ

where Rn and Rnf are the net radiation of the plant canopy
and reference leaf, respectively, H and Hf are the sensible heatﬂux of the plant canopy and reference leaf, respectively, and LE
is latent heat (transpiration rate) of the plant canopy, all measured
in J m–2 s–1.
Usually, sensible heat ﬂux is expressed as:
H ¼ rC p

Tc  Tarað3Þ

where r is the density of air (kg m–3), Cp the heat capacity of air(J kg–1), Tc and Ta are the temperatures of the canopy and air (C),
respectively, and ra is the aerodynamic resistance (s m–1).
Because the reference leaf is in the same canopy as the plantleaf, the same ra value could be used for the reference leaf
(Qiu 1996). Combining the energy balance equation for plant
canopy and reference leaf, we obtained the following equation toestimate plant transpiration (LE):LE ¼ Rn  Rnf

Tc  TaTf  Ta

ð4Þ

where Tf is the temperatures of the reference leaf (C). Equation (4)shows that the parameters included in the 3T model were net
radiation and temperature. Generally, net radiation is estimatedby the net short wave and long wave radiation, which could, inturn, be estimated by solar radiation, albedo, surface temperatureand other parameters (Qiu et al. 1996a).
In the 3T model, canopy temperature, reference dryleaf temperature and air temperature were the key components

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G. Y. Qiu et al.

used to calculate transpiration. Therefore, a plant’s transpirationtransfer coefﬁcient (hat) was deﬁned as (Qiu et al. 2003):
hat ¼

Tc  TaTf  Ta(a)ð5Þ

Theoretically, hat  1, if Tc = Tf, hat assumes its maximum
value (hat = 1) and transpiration assumes its minimum value(LE = 0). This limit was determined by lack of water fortranspiration or by serious environmental stress. However,when hat was at its minimum value, transpiration could reachits maximum value (potential transpiration rate). This limit wasdetermined by the available energy for transpiration under noenvironmental stress. Therefore, hat could determine thetranspiration rate from zero to potential transpiration rate.
A lower value of hat corresponded to a higher transpiration
rate and low environmental stress. A plant suffering
environmental stress would have a higher hat value than that ofa non-suffering one.
By checking Eqn (5), we found that it could quantitatively
determine plant environmental stress and was easier for
application. This kind of technique could promote theapplication of IR technique in plant function monitoring if we
can make full use of it. The objective of this study was to test andapply hat for the monitoring of plant water and heat stress undervarious conditions.

(b)Materials and methods
50
45

(c)

Tf

Tc

Ta

40

Temperature (°C)

Three experiments were conducted to test and apply the proposed
coefﬁcient at the National Institute for Rural Engineeringin Tsukuba, Japan, one in a greenhouse and two in growthchambers. In this study, the reference leaf was made fromgreen paper. The procedures to prepare the reference leaf
were: (i) choosing the green paper, which should be as similar
in colour to the plant leaf as possible; (ii) cutting the paper into theshape of the plant leaf; and (iii) installing the paper leaf into theupper part of the plant canopy. The reference paper was not beshaded by nearby leaves. Before and during each experiment,
equipment was carefully calibrated.

35
30
25
20
15

Experiment 1: Controlled soil water in a greenhousewith melon cropThis experiment was conducted from April to July (1998) ina glasshouse (Fig. 1a). The dimensions of the glasshousewere 60.4 m in length, 14.4 m in width and 3.9 m in height at
the ridge. Two irrigation treatments were arranged. One was
fully irrigated (area A, volumetric water content was varied in
the range of 0.3–0.4 m3 m–3). Another was not fully irrigated(area B, volumetric water content was varied in the range of
0.2–0.3 m3 m–3). The melon crop (Cucumis melo L.) was planted
in rows 1.5 m apart and the distance between individual plants
was 0.8 m. Water was supplied by drip irrigation under theplastic ﬁlm. The soil surface was covered with a plastic ﬁlm
to prevent evaporation. The temperature of the reference leaf
was continuously measured with Cu-Co thermocouples and airtemperature was continuously measured with shielded-ventilated
Cu-Co thermocouples. Canopy temperatures of the plants ineach treatment were continuously measured with an infrared10
143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169

Day of year
Fig. 1. Glasshouse experiment with melon plants. (a) The experimentarrangement and (b) the corresponding thermal image on 8 July 1998.
(c) Variation of the three temperatures in day of year (DOY) 143–169,
where Tc is the temperature of the melon leaf, Tf is the temperature of thedry reference leaf and Ta is the temperature of the air.

thermometer (THI-500, Tasco Co. Ltd, Japan).Temperature
imaging was measured with a thermal camera (TH3100, NEC
San-ei Co. Ltd, Japan) and soil moisture in each treatment area
was measured with a TDR soil moisture measurement system(Campbell Scientiﬁc Inc., USA). All data were sampled at 5-s
intervals and recorded every 10 min. Radiation and air humidity
data were recorded in a nearby meteorological station.

IR-based coefﬁcient to screen environment stress

Experiment 2: Well-controlled experiment in a growthchamber with tomato cropThis experiment was conducted in May 1997 in a growthchamber. The growth chamber had a ﬂoor area of 7.3 m2 andwas equipped with lighting and air conditioning. Air temperature
was set at 31C and relative humidity was set at 60%. Lighting
hours were 0500–1700 hours and light intensity was 157 W m–2.
One tomato plant (Lycopersicon esculentum Mill.) was planted
in a pot ﬁlled with soil, 0.30 m in height and 0.26 m in diameter.
The pot was sealed with an aluminium ﬁlm to prevent soil
evaporation. In this experiment, soil water content gradually
decreased from a well watered condition to dry condition.
Other environmental conditions were kept constant. The
temperatures of the canopy and the reference leaf were
measured with Cu-Co thermocouples and air temperature wasmeasured with shielded Cu-Co thermocouples (sampled at 5-s
intervals and recorded every 10 min). Canopy temperatureand reference leaf temperature were also measured with athermograph (JTG-3210, JEOL Co. Ltd, Tokyo, Japan). Plant
transpiration was measured by weighing the pot with an SG32000
balance (Mettler Toledo Inc. Greifensee, Switzerland) and data
were recorded every 10 min.
Experiment 3: Hydroponic lettuce in a growth chamberwith heat stressThis experiment was conducted in September–October 1997.
An environmental chamber with a ﬂoor area of 7.3 m2 was usedin this experiment. The chamber was equipped with lighting,air conditioning and a nutrient solution circulating system. Three
growing containers, each measuring 0.75  2.0 m, were installedon movable benches. Styrofoam boards with holes for supporting
plants were placed on the containers. Nutrient solution was
circulated via a separate solution reservoir ﬁtted ineach container, which allowed for the control of the solution’s
temperature. Seedlings of butterhead lettuce (Luctuca sativa L.
cv. ‘Okayama Sarada’) were transplanted into the growing
containers 10 days after germination. Throughout theexperimental period air temperature was maintained at 28.7C
during light periods (12 h) and 25C during dark periods (12 h).
Relative humidity was 70% throughout the experimental period.
Twelve 400-W BOC lamps were used, producing a light intensityof 400 mmol m–2 s–1. The only difference between the operating
systems for each container was the temperature of the nutrient
solution (root temperature). Temperatures in the three reservoirs
were 21.5, 25.9 and 29.5C, respectively. Temperatures of the
canopy (three replications for each treatment), reference leaf, airand nutrient solution were measured with Cu-Co thermocouples
at 5-s intervals and recorded every 10 min. Canopy temperature
was also measured with a thermograph (JTG-3210, JEOL Co.
Ltd) and an infrared thermometer (IR-0506C, Minolta Camera
Co. Ltd, Japan).
Results
Variation patterns of the three temperatures
Figure 1 shows the experimental arrangement with melon crop(Fig. 1a), the corresponding thermal imaging (Fig. 1b) andvariations of the three temperatures of the greenhouse melon
during the main observation period (Fig. 1c). Canopy temperature

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993

was the average of area A and area B. Tf was higher than Tc and Ta
during the daytime. On clear days (e.g. day of year (DOY) 151,
152, 155 and 169), the temperature difference between Tf and Tc
could be as much as 20C. Ta was generally higher than Tc.
This was because the soil surface was not fully covered by the
canopy, so solar radiation could be directly absorbed by the soil.
Moreover, the plastic ﬁlm covering the soil prevented evaporationfrom the soil and the soil surface temperature could be as
high as 50C. Therefore, the absorbed solar energy directly
affected the air temperature through sensible heat transfer andincreased the air temperature. However, as reported previously,
Tc could sometimes be higher or lower than Ta, depending onﬁeld condition (Qiu 1996). These results showed that there
were obvious differences among leaf temperature, reference
leaf temperature and air temperature. It is possible tosimultaneously use the dry reference temperature and airtemperature to normalise the observed leaf temperature.
Detecting water stress
There were two conventional ways to express CWSI. One was byusing leaf temperature, such as CWSI = (Tc – Tcl)/(Tcu – Tcl),
where Tcu and Tcl were the upper limiting and lower limiting
canopy temperatures, respectively (Jackson et al. 1981). The
other was by using transpiration rate, such as CWSI = 1 – LE/LEp,
where LEp was the potential transpiration rate (Qiu et al. 1996b).
Although water stress could be evaluated using the conventionaltemperature-based CWSI, the necessity of solar radiation andhumidity in estimating the upper or lower limiting canopy
temperatures (Idso 1982; Jackson et al. 1988) is a limitation inremote sensing application. In the proposed hat, only temperature
is included, since it is relatively easier for use remote sensing
applications. The reliability of hat for monitoring plant water
stress is discussed below.
To monitor plant water stress, the data in Experiment 2 wereanalysed. Irrigation was conducted on the night of 23 May andthen the data measured during the following 3-day-period wereused. Figure 2 shows the comparisons between hat and LE/LEp(Fig. 2a) and between hat and CWSI = 1 – LE/LEp (Fig. 2b) of
tomato plant. During the 3-day drying period, radiation, airtemperature and humidity were kept constant and the only
variable environmental factor was the decrease in soil watercontent due to plant transpiration.
In this experiment, the reference leaf temperature was around
44C and the air temperature was around 35C. As a result ofwater stress, the transpiration rate decreased from 120–140 g h–1
on 24 May to 80–120 g h–1 on 25 May and 30–70 g h–1 on 26 May.
The corresponding plant surface temperature increased from 33,
34–39 and 39–43C, respectively. The ratio of LE/LEp was 1.0
from 24 May to the early morning of 25 May, indicating that there
was no water stress for tomato plant. The corresponding values of
hat were –0.2– 0. Water stress began to show in the early morningof 24 May and then gradually increased. During the same period
the ratio of LE/LEp gradually decreased from 1.0 to 0.2 and thevalues of hat gradually increased from 0 to 0.75
Figure 2a shows that hat sensitively reﬂected the changes inthe LE/LEp ratio. It may also well related to CWSI = 1 – LE/LEp.
Therefore, a comparison of hat and CWSI = 1 – LE/LEp is madeand the results are shown in Fig. 2b. As hat gradually increased

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1.2

G. Y. Qiu et al.

(a)

1.0

0.8

0.6

0.4

0.2

0.0

hat

–0.2
–0.4

7

9

11 13

15

May 24

7

9

LE/LEp

11 14

16

8

May 25
Date and Time (h)10 12 14

16

May 26

0.8

(b)
0.7

y = 1.54x – 0.15
R2 = 0.97

0.6
0.5

approached 0.4 at 1700 hours. The corresponding CWSI was~0.35–0.40, indicating slight to medium water stress. Our otherobservations showed that a hat value ranging from 0.4–0.5,
usually indicated medium water stress (data not shown). At theend of the third day (26 May) hat and CWSI had increased to 0.8
and 0.65, respectively, indicating severe water stress.
These results show that hat could reasonably indicate plantwater stress in a well-controlled environment. It was then further
applied to the greenhouse melon, which was not as well controlled
as the tomato plant used in Experiment 2. Results showed that,during the 18-days of observation, for areas A and B, the averagevolumetric water contents were 0.36 and 0.27 m3 m–3, the averagetranspiration rate were 4.18 and 3.65 mm day–1 and the average hat
values were –2.56 and –2.08, respectively. The differences in soil
water content were clearly reﬂected by the difference in hat value.
To show this difference more clearly, cumulative values of soil
water content, transpiration rate and hat were plotted in Fig. 3.
This shows that the soil water content and the transpiration rate
in area A were higher than in area B (Fig. 3a, b) and that thecorresponding hat value in area B was higher than that in area A(Fig. 3c). The difference in soil water content was again clearlyreﬂected in the difference in hat.
In this experiment, despite the decrease in soil water content
due to transpiration, the soil water content remained relatively
high over the experimental period (0.25 m3 m–3). Therefore,
the melon plants experienced little or no water stress. Thisobservation was also conﬁrmed by the low hat values because
all of them were less than –1.0. These results again suggested that,
under little or no water stress conditions, hat had a lower value
and ﬂuctuated with changes in weather conditions.

hat

0.4

Detecting heat stress
0.3
0.2
0.1
0.0
–0.1
–0.2

0.0

0.1

0.2

0.3

0.4

0.5

CWSI = 1 – LE/LEp

0.6

0.7

Fig. 2. A comparison of hat with (a) the ratio of LE/LEp and(b) CWSI = 1 – LE/LEp of tomato plant during a 3-day drying process.
Data were measured in Experiment 2.

from –0.1 to 0.75, the corresponding CWSI increased from 0 to
0.7. A linear relationship between them was revealed with aregression determination coefﬁcient R2 = 0.97
These results show that hat values could give a quantitativeevaluation of plant water stress. During the ﬁrst day after
irrigation (May 24) hat was low (–0.1 to –0.2), while thetranspiration rate was high and CWSI was zero. Lower valuesof hat indicate no water stress. Starting at 1300 hours on thesecond day (25 May), hat began to increase gradually andIncreasing global warming may cause heat stress for many plant
species. This will be especially true if water stress and heat stressoccur simultaneously. In this study, we used hat to detect heatstress on a lettuce crop. Lettuce is traditionally grown in coolclimates and the optimal day time temperature for lettuce is 24C
(Thompson et al. 1998). Under high temperatures conditions,
growth is stunted, the leaves may be bitter and the seed stalk forms
and elongates rapidly.
In this study, we designed an experiment (Experiment 3)
to detect the heat stress by using hat. The lettuce crop was
continuously exposed to high air temperature (28.7C, ~4.5Chigher than lettuce’s optimal temperature) and three different root
temperature conditions (21.5, 25.9 and 29.5C, respectively).
Figure 4a shows the reference dry temperature, air temperatureand canopy temperature for the three root temperature
treatments. Although lettuce plants were exposed to the same
air temperatures, the differences in canopy temperature weredetected by thermal imaging by the differences in root
temperature. Over the experimental period, the average canopy
temperatures were 26.44, 27.15 and 27.46C for root temperature
treatment of 21.5, 25.9 and 29.5C, respectively. The differencein average root temperature between them was 4C and thedifference in canopy temperature was ~0.5C. In the low root
temperature (21.5C) treatment, the canopy of the lettuce suffered
heat stress but the roots did not suffer heat stress. In the medium
root temperature (25.9C) and the high root temperature (29.5C)IR-based coefﬁcient to screen environment stress

Functional Plant Biology

80

8

(a)
7

70

6

60

0

(b)

995

(c)

4

3

2

50

Cumulative hat

5

Cumulative transpiration (mm)Cumulative soil water

–10

40

30

–20

–30

20
–40

1

10

0
173 176 179 182 185 1880–50
173 176 179 182 185 188

Area A173 176 179 182 185 188

Area B

Fig. 3. Comparison of (a) cumulative volumetric soil water content, (b) transpiration rate and (c) hat of the melon
crop grown in a greenhouse in June–July 1998 (Experiment 1). Area A received more water than area B. The
transpiration rate was calculated using Eqn (1). The numbers of the horizontal axis were the days of the year.
32

(a)

31
30

Temperature

treatments, the lettuce plants suffered heat stress in both the roots
and canopy. However, the stress level was different due todifferent root temperature and this difference was detected byusing hat (Fig. 4b). In the low root temperature (21.5C) treatment,
the lettuce suffered less heat stress and had an average hat value of–1.11, which was about –0.3 lower than the medium temperature
treatment. In the medium root temperature (25.9C) treatment,
average hat value was –0.74, which was between those of the low
and high root temperature treatments. The high root temperature(29.5C) treatment had the highest hat values (averaged value was–0.59), which indicates that the lettuce crops in this treatment
suffered more heat stress.

29
28
27
26
25
3-Oct

6-Oct

7-Oct

8-Oct

9-Oct

13-Oct

Tf

Ta

Tc1

Tc2

Tc3

14-OctDiscussion
–0.3

(b)
–0.6
–0.9

hat

Root-zone temperature changes which cause stress to plantcommunities is very important to global warming researchers.
Global warming could reduce soil evaporation rate by decreasingwater content of the surface soil. Conversely, it could increase
plant transpiration rate due to more vigorous development of theroot system (Weng and Luo 2008). A suitable way to detect
transpiration rate change under root warming condition was
highly desired (Y. Luo, pers. comm.). The proposed hat could
provide a solution to this challenge. Results of this study showthat hat could effectively detect the changes caused by root
temperature differences. To date, we have not been able todetermine the relative contribution of water stress and heatstress when both of them occurred simultaneously, although
we could determine the heat stress under controlled waterconditions. More research into this topic will be necessary fora better understanding that global warming may cause throughecosystem changes.
In this study, we examined an alternative index to the morecommonly used ‘crop water stress index’. This index replaced the

–1.2
–1.5
–1.8
3-Oct

6-Oct
Root T = 21.5

7-Oct

8-Oct

9-Oct

Root T = 25.9

13-Oct14-OctRoot T = 29.5

Fig. 4. Variations in (a) temperatures and (b) hat values of hydroponic
lettuce under high air temperature conditions (Ta = 28.7C) for three rootzone temperature (Root T) treatments. Tc1, Tc2 and Tc3 are canopy
temperatures for different root temperature treatments, corresponding toroot temperature of 21.5, 25.9 and 29.5C, respectively. The experiment
was conducted in 1997 in a growth chamber (Experiment 3).

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use of a wet reference surface with air temperature measurement.
The most important advantage of this index was that it is easy
to measure, especially for remote sensing applications. The
application of this index by using thermal imaging showedthat it could be used to screening large numbers of plants.
Because air temperature was included, this index was moreclosely related with transpiration than stomatal conductance. For
this reason, although it was valuable for detecting thephysiological results of water deﬁcits and heat stress, as
indicated by Jones (2007), this kind of index may not be very
useful in mechanistic studies aiming to understand the process.
This point was clearly shown in the heat stress experiment inwhich we observed signiﬁcant differences in canopy temperaturefor different root temperature treatments. The corresponding hat
values also showed obvious differences. These results showed theheat stress levels, but we could not explain its mechanism by using
hat. Additional measurements are necessary to fully understandthe included mechanism.
Although we did not provide a direct comparison of hat withstomatal conductance, surface temperature and crop water stressindex could be closely related with stomatal conductance undercertain conditions, as shown by Grant et al. (2007). In general, hat
is a valuable index for various applications if we pay attention to
its limitations.
Conclusions
Three different temperature measurements were included in the
proposed hat: leaf temperature, reference dry leaf temperature
and air temperature. Generally, there were obvious differencesamong them. The difference between the dry reference andleaf could be as much as 20C. The proposed index could
integrate these differences and quantitatively evaluate theenvironmental stress to the plant. From semi-controlled
glasshouse to well-controlled chamber conditions, our results
showed that water stress and heat stress of plants could be
effectively detected by using hat. Despite the fact that it wasclosely related to transpiration rate rather than stomatal
conductance, the proposed index was valuable for plant stressdetection, especially for remote sensing application, because it
was easier to measure than other indices.
Acknowledgement
This study was jointly supported by the National Basic Research Programof China (2009CB421308), National Natural Science Foundation ofChina (40771037), Ministry of Education, Cultural, Sports, Science andTechnology-Japan and the University of Tokyo.

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Manuscript received 3 June 2009, accepted 5 September 2009http://www.publish.csiro.au/journals/fpb