Optimizing thermal imaging as a technique for detecting stomatal closure induced by drought stress under greenhouse conditions

Optimizing thermal imaging as a technique fordetecting stomatal closure induced by drought stressunder greenhouse conditionsOlga M. Granta*, M. Manuela Chavesa,b and Hamlyn G. Jonesc

aLaboratorio de Ecofisiologia Molecular, Instituto de Tecnologia Quımica e Biologica, Apartado 127, 2781-901 Oeiras, PortugalbDepartamento Botanica e Engenharia Biologica, Instituto Superior de Agronomia, Universidade Tecnica de Lisboa, Tapada da Ajuda, 1349-017

Lisboa, PortugalcPlant Research Unit, Division of Environmental and Applied Biology, School of Life Sciences, University of Dundee at SCRI, Invergowrie, Dundee DD2

5DA, Scotland, UK

Correspondence

*Corresponding author,

e-mail: [email protected]

Received 23 June 2005; revised 2 December

2005

doi: 10.1111/j.1399-3054.2006.00686.x

Temperature of leaves or canopies can be used as an indicator of stomatalaperture, which is considered a sensitive response to soil water deficit. In thispaper we analyse the robustness and sensitivity of thermal imaging fordetecting changes in stomatal conductance and leaf water status in a rangeof plant species. Thermal imaging successfully distinguished between irri-gated and non-irrigated plants of a variety of species under greenhouse orcontrolled chamber conditions, with strong correlations between thermalindices and stomatal conductance measured by porometry. Our results alsohighlighted issues that need to be addressed in order to be confident ofalways detecting drought stress using this technique. These include variabil-ity in leaf angles and the limited reliability of ‘wet’ and ‘dry’ leaves torepresent leaves with stomata fully open or stomata fully closed. Theseresults should assist the design of protocols for application in crop produc-tion or ecosystem monitoring.

Introduction

The early diagnosis of stress in plants has been hampered inthe past by the need for destructive sampling or intensive insitu measurements. Imaging approaches using reflectance,fluorescence, or thermal sensors have been appliedsince the early 1980s (e.g. Omasa et al. 1983, Nilsson1991, Chaerle and Van Der Straeten 2000, Chaerle et al.2004, Riera et al. 2005) for non-destructive and non-invasive monitoring of the physiological condition of plants.Use of these imaging technologies in the field (e.g. Joneset al. 2002) can help increase efficiency in crop manage-ment and crop breeding (Chaves et al. 2003) or assist themonitoring and management of natural ecosystems.However, these new imaging techniques must be validated

and calibrated against classical physiological analysis of gasexchange and water relations (Chaves et al. 2003).

Under limited water availability, reductions in stoma-tal conductance can occur even before any change inplant water status (Davies et al. 2000), meaning thatmonitoring stomatal conductance can be a better indi-cator of plant responses to drying soil than monitoringwater potential (Jones 2004b). However, cuvette methodsfor measuring stomatal conductance are time-consuming,labour-intensive and only give point measurements.Thermography, based on the principle that as water is lostthrough the stomata, leaves cool, and hence as stomataclose, leaf temperatures rise, is a promising alternative.

The objective of research in this area must now be todefine the limitations and refine the technique so that its

Abbreviations – ANOVA, analysis of variance; CWSI, crop water stress index; gs, stomatal conductance to water; T, temperature.

Physiol. Plant. 127, 2006 507

Physiologia Plantarum 127: 507–518. 2006 Copyright � Physiologia Plantarum 2006, ISSN 0031-9317

use can be optimized and results can be trusted undereach set of conditions. In this paper, we report studiesaimed at comparing the precision of thermography andconventional porometry and water relations measure-ments for distinguishing between water-stressed andwell-watered control plants in greenhouse conditions.In particular, we compared absolute leaf temperaturesand thermal indices of plant stress with porometricmeasurements of stomatal conductances and pressurechamber measurements of water potential. A variety ofspecies with leaves of different sizes and different sto-matal responses to water deficits (Quick et al. 1992),together with a variety of controlled experimental con-ditions were used, in order to provide an empiricalassessment of the range of conditions for which thermalimaging may be useful.

Materials and methods

Plant material

All plants were grown in soil/sand (1:1 v/v) in a green-house at Instituto de Tecnologia Quımica e Biologica,Oeiras, Portugal. Grapevines (Vitis vinifera L), cv.‘Moscatel,’ were acquired in January 2001 and oneplant grown per pot (30 cm diameter · 30 cm height).At the start of May 2003 all plants were cut back to1.5 m. Thirty plants were arranged in groups of threeplants of similar size. In January 2004, grapevines ofcv. ‘Castelao’ were grown in similar pots and arrangedin a row parallel to the main window of the green-house, with growing stems supported along a wirefence. All grapevines were grafted on 1103 Paulsenrootstock. Seeds of Phaseolus vulgaris (L.) (Frenchbeans) were germinated in October 2003 and twoseedlings transferred to each of 12 pots (20 cm dia-meter · 20 cm height). Seeds of Lupinus albus (L.)(lupins) were hydrated in deionized water and germi-nated on damp filter paper in January 2004 and thenone plant grown per pot (18 cm diameter · 35 cmheight).

Experimental environments

All experimental work was carried out either in thegreenhouse or in a controlled chamber (Fitoclima700EDTU, Aralab Lda., S. Domingos de Rana,Portugal). In the greenhouse, air temperature was set at20�C, controlled by a thermostat. Relative humidity andradiation were not controlled, and no additional lightingwas used. In the controlled chamber, air temperaturewas set at 25�C, relative humidity at 50%, and radiationat 47.5 W m�2 (PAR of 1300 mmol m�2 s�1).

Thermal imaging

All thermal images were obtained with a thermal imager(IR Snapshot 525, Infrared Solutions, MN) that operatesin the wavebands 8–12 mm, has a thermal resolution of0.1�C, and produces pictures with spatial resolution of120 · 120 pixels. Images were analysed in SnapViewPro software (Infrared Solutions); all images were cor-rected for spatial calibration drift by subtracting corre-sponding reference images of an isothermal surface(Jones et al. 2002). For each series of measurements,the background temperature was determined as out-lined in the imager manual as the temperature of acrumpled sheet of aluminium foil in a similar positionto the leaves of interest. Emissivity for leaf measure-ments was set at 0.95 throughout (see review by Jones2004a). Temperatures measured with the infrared ima-ger were found to increase over the first images after thecamera was turned on, and therefore, we ensured thattemperatures were stable before commencing measure-ments (this required up to 10 min).

Reference surfaces

The wet and dry reference surfaces (Jones 1999a) usedwere leaves of the plants being studied, either stillattached to the plant or cut off and placed close to theleaves of interest. Wet references were sprayed withwater on both sides. Dry reference leaves were coveredin petroleum jelly (vaseline) on both sides. Green blot-ting paper (Papertrace, Preston, UK) was used in someof the experiments instead of natural leaves. In this casethe dry reference was a strip of blotting paper, un-altered, and the wet reference was a wet strip of blottingpaper. Wet references were regularly sprayed to main-tain their moisture. The temperatures of these references(Tdry and Twet) were used in conjunction with thetemperatures of the samples of interest (Tleaf) to obtainthermal indices.

Thermal indices

The index IG was calculated from leaf temperatures:IG 5 (Tdry – Tleaf)/(Tleaf – Twet). Under any given environ-mental conditions, this index is theoretically propor-tional to gs (Jones 1999b). A crop water-stress index(CWSI) analogous to that of Idso (1982) was also calcu-lated, where CWSI 5 (Tdry – Tleaf)/(Tdry – Twet).

Physiological measurements

Stomatal conductance (gs) was measured with a steadystate porometer (LiCor 1600, LiCor, NE). Stomatal

508 Physiol. Plant. 127, 2006

conductance and leaf temperature were measured onthe same leaves, with porometer measurements imme-diately following thermal imaging. Pre-dawn and mid-day leaf water potentials (C) were measured with apressure chamber (Model 600 Pressure ChamberInstrument, PMS, Albany, OR).

Water deficit experiments

Grapevines

From early May 2003, grapevine plants were wateredevery second day with 1.5 l to field capacity. Treatmentswere imposed in mid-May. The treatments were fullwatering (i.e. to field capacity; control), half watering(plants received half the quantity of water given to con-trol plants), and one-third watering (plants received one-third the quantity of water given to control plants).Watering was applied every second day to 10 replicatesof each treatment. Stomatal conductance and leaf tem-perature were measured at 10:00 h on one marked leafper plant, before treatments were imposed, and regu-larly thereafter. The imager was held approximately50 cm from the leaves. The same attached leaves wereused throughout, and the left part of each leaf wascovered in vaseline to act as the dry reference, whilethe lower part was sprayed with water to act as a wetreference.

In 2004 only two treatments were used – water stressin which the quantity of water given to plants wasprogressively reduced over time from early July untillate August, and a control in which plants were wateredevery day to field capacity. Eleven replicates weremeasured per treatment. Temperatures of leaves on theplants and some dry reference leaves (cut leavesattached to the wiring of the vine support trellis, ata similar height and orientation to the leaves beingmeasured on the vines) were recorded between 8:00and 9:00 h and stomatal conductance was measuredthereafter.

Beans

Bean plants were arranged in three groups of four pots,each containing two seeds, and were watered daily,until the first trifoliate leaves reached maturity, afterwhich half the pots (two in each group, chosen ran-domly) were droughted (no further watering; ‘waterstressed, WS’) while the other half were still watereddaily (‘well watered, WW’).

Stomatal conductance, leaf temperature, and waterpotential were measured at intervals after the start ofthe drought treatment. For infrared measurements, the

infrared imager was mounted on a tripod, 1 m above theleaves. Two nylon grids were placed over the plants andthe leaves were maintained in a flat position by insertionbetween the layers of nylon. Images were taken with theleaves thus maintained horizontal, and immediatelyafterwards with the grid removed so that the leaveswere at their natural angles. Wet and dry referenceleaves (cut) were included on the grid. After 23 days ofthe drought treatment, all leaves but one per plant wereremoved, so that the remaining leaves would be moreeasily identifiable in images and to ensure that porom-eter and infrared measurements referred to the sameleaves. Plants were re-grouped into two groups of sixpots and measurements with and without the grid tokeep the leaves horizontal were repeated.

Leaf temperature as measured both by thermal ima-ging and with thermocouples, and indices and stomatalconductance were recorded at different times of days onthese bean plants, to determine the optimum time fordistinguishing between water-stressed and controltreatments.

Lupins

Lupin plants were divided between two treatments:well-watered plants (WW) were watered every dayand water-stressed (WS) were not watered for 2 weeks.There were four replicates in either treatment. After 2weeks the plants were transferred from the greenhouseto the controlled chamber. Stomatal conductance wasmeasured and infrared images were taken of a leaf fromeach plant (i), then of pairs of leaves – one from a WSplant and one from a WW plant – placed side by side(ii), and finally of each whole plant (iii), to determinewhether variation between treatments in thermal vari-ables can be more easily detected at the leaf or wholeplant level, and when comparing within images ratherthan between images. Cut leaves were included asreferences.

Declining stomatal conductance in cut leaves

Trifoliate leaves of French bean plants were cut fromtheir plants and attached with a paper clip to a piece ofwire between two retort stands. Adjacent to the leaveswere placed two strips of green blotting paper – the wetand dry references. The stomatal conductance of eachleaf was measured immediately after attachment to thewire and frequently thereafter until it was no longerpossible to detect any conductance. Thermal imageswere taken between porometer measurements. Thusseries of up to 30 measurements could be obtained foreach leaf as it became increasingly stressed.


Data analyses and statistics

Data were analysed in STATISTICA (1995). Data weretested for normality and homogeneity of variances usingKolmogorov-Smirnov and Levene’s tests, respectively.The significance of relationships between IG and gs weretested by Pearson-Product correlations. Differencesbetween treatments were tested with t-tests when therewere only two treatments. Where variances were nothomogenous, t-tests with separate variance estimatesand approximate degrees of freedom were computed.Where there were three treatments, treatment dif-ferences were analysed with Analysis of Variance.Where plants were replicated in blocks, treatment wasanalysed as a fixed factor and block as a randomfactor. Coefficients of variation (5 100 * SD/mean)were calculated for leaf temperatures IG and gs. Outlierswere removed prior to analyses.

Results

Water deficits in grapevine

Results for all types of measurements (thermal imaging,porometry, water potential) varied according to the dateof measurement. Although there were no detectabledifferences in mid-day water potentials on day 14, bydays 28 and 33, pre-dawn water potentials were signifi-cantly higher in fully watered (control) plants than inplants receiving one-third the amount of water(Table 1). As expected, no significant treatment differ-ences in gs were detectable at the start of the experi-ment, but differences emerged by day 11 (Fig. 1A) witha trend of increasing treatment differences thereafter,though no differences were detectable on day 18 (aday with generally high conductances, low PAR, andhigh humidity; Fig. 1C). On day 28 conductances wererelatively low in all treatments. In general, the responseof IG as calculated from thermal images mirrored thechanges in stomatal conductance (gs) (Fig. 1B), exceptfor the lack of a significant treatment response on day 14and some other small differences (on day 11 plants

receiving the half-watering treatment showed signifi-cantly lower IG than control plants, but gs on that dateonly significantly differed between plants receiving con-trol and one-third watering; on day 28, plants receivingthe one-third treatment showed significantly lower gs

than plants receiving full watering, but, surprisingly, itwas plants receiving the half-treatment that showedlower IG). Treatments did not show significant differ-ences in Tleaf on any day, showing the importance ofindices, rather than absolute temperatures, where thereis environmental variation.

Although IG is theoretically proportional to gs, in thisexperiment IG and gs for individual leaves were onlysignificantly correlated (P � 0.05) on dates when theoverall range of conductances was greater than350 mmol m�2 s�1 (days 11, 14, and 33; this is therange over all individual leaves, data not shown;r2 5 0.50, 0.50 and 0.45, respectively). However,there was a highly significant correlation of the averagegs for each treatment on each date with the average IGfor the same treatments on the same dates (P < 0.0001,Fig. 2A). Wet leaves were not included in the secondgrapevine experiment, but Tdry – Tleaf (the numerator ofIG) for either treatment on different dates correlatedsignificantly (P 5 0.002) with gs for the same treatmentsand dates (Fig. 2B). In the case of the first experiment,however, the correlation was much poorer for Tdry –Tleaf with gs than IG with gs.

Water deficits in beans

For beans there was no significant difference betweentreatments in gs, pre-dawn water potential, leaf tempera-ture or IG in the first 20 days from imposition of treat-ments. By day 22, there was a significant differencebetween treatments in gs (Fig. 3A). Pre-dawn waterpotential on day 23 showed significant differencesbetween treatments, as did leaf temperature, IG, andCWSI measured by thermography (Fig. 3B-D). Wefound good agreement between leaf temperatures mea-sured by thermocouples and thermal imaging. Providedthe thermal imager is allowed to come to thermal

Table 1. Water potential (MPa) of Moscatel grapevines in three treatments on various dates at mid-day (MD) and pre-dawn (PD). n 5 10, NS denotes

non-significant

Treatment

Day Time Full Half One-Third Significance

14 MD �0.95 � 0.08 �1.04 � 0.09 �1.13 � 0.06 NS

28 PD �0.49 � 0.05 �0.63 � 0.08 �0.84 � 0.09 P 5 0.016

33 PD �0.57 � 0.09 �0.97 � 0.08 �0.98 � 0.09 P 5 0.011


equilibrium after turning on (the first readings oftenshow a rapid increase in temperature), the coefficientof variation in leaf temperature over a short period oftime (limited environmental change) was lower whenmeasured with the thermal imager than with a thermo-couple (data not shown).

By day 35 the difference between treatments in gs washighly significant (P < 0.0001). Treatment differences

were also significant for the infrared variables(P 5 0.017 for Tleaf, P 5 0.039 for IG, and P 5 0.010for CWSI). IG showed a highly significant Pearson cor-relation (P < 0.001) with gs. Two days later, the r2 valuefor the relationship between IG and gs was reduced from0.77 to 0.40 when the grid was removed. Additionally,when the leaves were kept flat with the grid there weresignificant differences between treatments in Tleaf, IG,

1 5 11 14 18 28 33 36

g s (m

mol

m–2

s–1

)

0

100

200

300

400A

B

C

Day of treatment

1 5 11 14 18 28 33 36

1 5 11 14 18 28 33 36

I G

0.0

0.4

0.8

1.2

1.6

b

b

a

a

b

b

a

ab

ab

b

a

b

a

bb

a

b

b

RH

(%

)

20

40

60

80

PA

R (

μmol

m–2

s–1

)

200

400

600

800

1000

aab

b

a ba

a

b

b

aa

a

aa a a a

a

a

a

a

a

aa a

a

a

a aa

Fig. 1. gs (A) and IG (B) on

various days after three water-

ing treatments were imposed

on Moscatel grapevines in a

greenhouse, with correspond-

ing relative humidity (open

circles) and PAR (closed circles)

during the measurements

(C). Plants were watered to

field capacity (open bars), or

with one-half (striped bars), or

one-third (closed bars) the

quantity given to the control.

n 5 10 plants per treatment

per day. Bars represent

means � SE. Significant differ-

ences between treatments

within a day are indicated by

different letters (LSD following

ANOVA). Negative error bars at

the top of (A) and (B) refer to

the overall standard error for

each date 5 square root (Mean

square error/n).


and CWSI (all P 5 0.01), but no significant differenceswere found in infrared variables between treatmentswhen the grid was removed. Thus with the leaves attheir natural angles, thermal measurements were not assensitive at detecting the difference between treatmentsas was gs (P < 0.001).

Water deficits in lupins

After two weeks of ‘stressed’ plants not having beenwatered, gs showed significant differences between treat-ments with well-watered (WW) plants exhibiting gs 2.5times that in stressed (WS) plants (Fig. 4A). The followingday infrared images were taken of (i) a leaf on each plant;(ii) pairs of leaves – one from a WS plant and one from aWW plant – placed side by side; and (iii) finally of each

whole plant. Significant differences in leaf temperaturewere found between WS and WW plants whether weused the temperature of individual leaves imaged sepa-rately, individual leaves from pairs of plants together, orthe average of several (five) leaves on each plant(Fig. 4C). In (i) and (ii) every WS leaf was hotter thanevery WW leaf. In (iii) every average for the five leavesper plant was hotter in WS than in WW, but someindividual leaves of WW plants had higher temperaturesthan the leaves of the corresponding WS plants.

A modified index was calculated using the sameformula as IG but with maximum and minimumtemperatures rather than average temperaturesfor the dry and wet references, respectively, i.e.IG (max/min) 5 (max Tdry – Tleaf)/(Tleaf – min Twet). Itwas considered that the average value of the dryreference may be excessively influenced by somelow temperatures, for example near the edges ofthe leaves, which can result in lower temperaturesfor the dry references than the leaves of interest.Using the extreme values of the references, ratherthan the averages, should remove this problem.There were significant correlations of gs with leaftemperature, IG and IG (max/min) (Figs 4E,F),despite thermal images having been taken a dayafter porometer measurements. While the correlationis poorer for IG (max/min) than for IG, the wetminimum temperatures [used in IG (max/min)] didnot show a significant difference between treatmentswhereas the wet average (as used in IG) temperaturewas significantly cooler in WW than WS plants(Fig. 4B). The use of IG (max/min) also removesthe one value of IG that was lower than 0, as a resultof an apparently hotter leaf than the reference dryleaf. The significance of the difference between treat-ments is very similar whether IG or IG (max/min) isused (P 5 0.021 and P 5 0.023, respectively), butin IG the average WW value is 3.6 times higherthan the average WS value, whereas with IG (max/min) the average WW value is only 2.8 times higherthan the average WS value (Fig. 4D).

Declining stomatal conductance in cut leaves

Bean leaves drying over time showed highly significantrelationships between IG and gs (Fig. 5A). R2 values weretypically around 0.7, which still leaves some unexplainedvariability in the relationship. This seems to relate tovariability in IG rather than gs, as the pattern of decreasinggs over time was smoother than that for IG (Fig. 5B).Variability in IG related to variability in the wet and dryreferences as well as to variability in leaf temperatures.

IG

0.0 0.2 0.4 0.6 0.8 1.0

g s (m

mol

m–2

s–1

)g s

(mm

ol m

–2 s

–1)

0

50

100

150

200

250

300

350

Tdry–Tleaf

0 2 84 6 100

50

100

150

200B

A

r 2

= 0.91, P = 0.002

r 2

= 0.59, P = 0.0001

Fig. 2. The relationship for grapevine leaves between (A) gs and IG in an

experiment with three irrigations and between (B) gs and Tdry � Tleaf in

an experiment with two irrigation treatments. Each point represents the

mean � SE for one treatment on one date. The dates of measurements

were 12, 21, and 25 July, and 3 August Correlations are for all points,

n 5 24 in (A) and n 5 8 in (B).


Discussion

Detection of stress

In the experiments with beans and lupins, differencesbetween water-deficit and well-watered (control) plantsin water potential, gs, leaf temperature and IG were detect-able at about the same time, indicating that thermalimaging can be as useful as more traditional methods fordetecting the initiation of stress. For grapevine, differencesin IG and stomatal conductance (gs) emerged at the sametime but significant differences in Tleaf were not detected(see summary in Table 2). This probably reflects the greaterenvironmental variation inevitable in an experiment withrelatively large plants across a greenhouse than thatoccurred in the smaller scale studies with beans and lupins.Treatment differences were also clearly dependent on con-temporary conditions, a fact that needs to be considered inany stress monitoring or in irrigation scheduling applica-tions. Additionally, the significance of differences betweentreatments for different infrared variables (Tleaf, IG, CWSI)varied with date, making it difficult to state which variableis the most sensitive for detecting plant stress. However, asan indication of gs, only IG is theoretically expected to belinearly related to gs (Jones 1999b). Additionally, whenmonitoring plants over time, if environmental conditionsare changing, then leaf temperature will change, and itmay become difficult to distinguish a change in leaf

temperature due to the onset of, or increase in, stress,from a change due to increasing air temperature or otherenvironmental changes. For some applications therefore itwill be more appropriate to use indices derived from leaftemperature rather than leaf temperature itself. For others,such as comparing cultivars, leaf temperature alone shouldbe sufficient. Jones (1999b) pointed out that the sensitivityof different measures using leaf and reference tempera-tures, e.g. (Tleaf – Tdry) vs (Tleaf – Twet), to changes in theenvironment can be very different depending on stomatalconductance and environmental conditions.

The highest temperatures and greatest differences intemperature between Tdry and Twet were recorded nearsolar noon. This might indicate that this would be thebest time to detect temperature differences betweentreatments, and is in accordance to the theoreticalstudy of Fuchs (1990). Under field measurements, how-ever, even well-watered healthy plants may shut theirstomata before solar noon, particularly in hot, sunnyconditions (Correia et al. 1990). Additionally, as dis-cussed by Jones et al. (2002) in relation to the relativeadvantages of measuring sunlit and shaded canopies,measurements to obtain the greatest difference betweenmeans are not always the most suitable: variation intemperature within canopies can be greater undergreater exposure. Timing of measurements thereforeneeds to be determined for specific conditions.

WW WS

g s (m

mol

m–2

s–1

)

0

100

200

300

400

500

600

WW WS

ΨP

D (

MP

a)

–0.5

–0.4

–0.3

–0.2

–0.1

0.0

WW WS

Tle

af (

°C)

20

22

24

26

28

30C

A

D

B

WW WS

I G o

r C

WS

I

0.0

0.5

1.0

1.5

2.0

BP = 0.032

P < 0.001

P = 0.03

IG P = 0.045CWSI P = 0.032

Fig. 3. Values of gs (A), CPD

(B), Tleaf (C), and IG (open

columns) and CWSI (striped

columns) (D) for well-watered

(WW) and water-stressed (WS)

French beans on days 22 (gs)

and 23 (all other measure-

ments) of treatments.

Differences between treat-

ments are indicated on the

graphs (ANOVA). n 5 12 plants

per treatment. Bars represent

means � SE.


Reference temperatures

The large temporal variation in temperature for wet anddry references may lead to serious errors in the calcula-tion of IG. Wet reference variation can arise from differ-ing times between spraying the ‘wet’ leaves and imageacquisition, with incipient drying occurring on occa-sions. As in other studies (e.g. Jones 1999b, Jones et al.2002) there were occasions when Tleaf fell outside therange defined by Tdry and Twet. It is likely that theseanomalies arose from differences in leaf orientationrather than any cooling or other effect (such as alterationof emissivity) of petroleum jelly. The use of real leaves,rather than, e.g. filter paper models, ensures that thereferences have similar radiative properties to the leavesof interest. Nonetheless, different exposure to the sun ofthe references and the plant canopy remains proble-matic (Jones et al. 2002). The use of maximum dryreference temperatures and minimum wet referencetemperatures rather than averages, could remove someof the variability between images as a result of slightvariation in exposure.

In the lupin experiment, the wet reference tempera-ture was significantly cooler in WW than WS plants,which may indicate that evaporative cooling in WW

plants has an effect on the temperature of the reference.A similar observation has been reported for grapevinein the field (Jones et al. 2002) where the treatmentappeared to influence reference temperatures. This sug-gests that plant water status has a detectable effect onthe surrounding microclimate. Jones et al. (2002) sug-gested an alternative possibility – that irrigation treat-ment affected canopy structure to the extent that theradiative environment was altered. Such an effectwould not occur in the pot experiments reported here,where all plants had similar numbers and sizes ofleaves.

Leaf angle

As pointed out above, leaf angle affects radiationinterception, and hence the leaf energy balanceand temperature. Variation in leaf angle was hereshown to affect the relationship between IG and gs.This is to be expected if the leaves of interestand the reference leaves used in the calculation ofIG are not similarly exposed. Additionally, fromenergy budget considerations, leaves at differentangles with similar gs could have very different

Tleaf (°C)

–1 0 1 2 3 4 5

I G o

r I G

(m

ax/m

in)

IG or IG (max/min)

10

20

30

40

50

WW WS

WW WS

g s (m

mol

m–2

s–1

)

0

10

20

30

40A B

C D

E F

20

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WW WS

WW WST

wet

(°C

)

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24

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4

20 22 24 26 28 30

Tle

af (

°C)

10

20

30

40

50

r 2

= 0.77, P = 0.04

r 2

= 0.84, P = 0.001

r 2

= 0.62, P = 0.021

P = 0.009 P =0.032

P ≤ 0.002

g s (m

mol

m–2

s–1

)

g s (m

mol

m–2

s–1

)

P ≤ 0.023

Fig. 4. Stomatal conductance

(gs) (A), temperature of the wet

reference (B), leaf temperature

when individual lupin leaves

were imaged separately (open

columns), when pairs of lupin

leaves were imaged (striped

columns), and when several

leaves per plant were imaged

(closed columns) (C), and IG(open columns) and IG (max

min�1) (striped columns) (D) of

well-watered (WW) and water-

stressed (WS) lupin plants after

2 weeks of treatments, and the

relationship between gs and

Tleaf (E) and IG (closed circles)

and IG (max min�1) (open

circles) (F) with corresponding

linear correlations. Differences

between treatments are

indicated on the graphs (ANOVA).

n 5 4 plants per treatment

(A-D) and 8 plants for correla-

tions (E-F). Bars represent

means � SE.


temperatures, and conversely leaves at differentangles with similar temperatures could have verydifferent stomatal conductances. If leaf angles aremeasured in greenhouse or field monitoring, theeffects of deviation from horizontal could be mod-elled. Such work would, however, be time consum-ing. With lupins, some individual leaves of WW

plants had higher temperatures than the leaves ofthe corresponding WS plants. Averaging data for alarge population of leaves may be needed to mini-mize the resulting errors.

Additionally, the effect of leaf wilting, folding or roll-ing in stressed canopies on the measured temperature ofthe canopy or leaves needs to determined. The archi-tectural arrangement of a plant canopy will influenceleaf temperature not only due to determining the angleof leaves towards the light source (as in the bean experi-ment), but also due to determining the degree of self-shading in the canopy (Pearcy et al. 2004). Variation inthe degree of self-shading within different canopiescould contribute additional variation to Tleaf (Boissardet al. 1990) and IG, further adding to the difficulty ofusing IG to consistently detect stress. Estimations ofcanopy structure should perhaps be incorporated intomodels of evaporation and stomatal conductance frominfrared temperatures (Taconet et al. 1995). The influ-ence of self-shading, can, however, be minimized if themost suitable view angle is used. Some researchersconsider that a view angle similar to the solar azimuthis the most suitable, since leaves orientated towards thesun show a greater sensitivity of temperature to stomatalconductance than leaves that are less directly exposed(Fuchs 1990); others have chosen to take measurementsfrom more than one orientation (see review by Jones2004a).

Fuchs (1990) considered that variation in orientationof leaves within canopies increasingly affects the leafenergy budget as stomata close, and thus as stomataclose variation in temperature within the canopyincreases. The degree of variation in temperature couldtherefore be used as an indicator of stress. In the experi-ments reported here, the coefficient of variation oftemperature was not greater for stressed compared tocontrol plants, but the theory requires randomly distrib-uted leaves which may not have been the case for thepresent experiments.

IG

I G

0.0

0.0

0.2

0.2

0.4

0.4

A

B

0.6

0.6

0.8

0.8

1.0

1.0

g s (m

mol

m–2

s–1

)g s

(mm

ol m

–2 s

–1)

0

200

400

600

800

Time

14:00 14:20 14:40 15:00 15:20 15:40 16:000

200

400

600

800

r 2

= 0.77

Fig. 5. Relationship between IG and gs of a French bean leaf following

cutting until very low conductance (A) and trends over time in gs (closed

circles) and IG (open circles) (B).

Table 2. Summary of thermal measurements that significantly correlated with stomatal conductance (gs), or detected significant differences between

treatments. n.a., not applicable

Plant Environment Treatments Correlated with gs Difference between treatments

Grapevine cv. Greenhouse Field capacity, half-field capacity, IG IG

Moscatel one-third field capacity

Grapevine cv. Greenhouse Well-watered, water-stressed Tdry – Tleaf None

Castelao

Bean plants Greenhouse Well-watered, water-stressed IG Tleaf, IG, CWSI – when leaves flat

Cut bean leaves Greenhouse Cut IG NA

Lupin Controlled chamber Well-watered, water-stressed IG, IG (max/min) Tleaf, IG, IG (max/min)


Thermometry/thermography vs porometry

For grapevine, although the pattern of IG and gs for thedifferent treatments over the different dates was gener-ally very similar, the lack of correlation on some occa-sions could be attributed to limited treatment variationand large environmental and even short-term temporalvariation. After cutting bean leaves from their respectiveplants, the time course of leaf and reference tempera-tures included some variability apparently unrelated toincreasing stomatal closure or meteorological condi-tions. As a result, poorer correlations between IG andgs of cut bean leaves were found than those reported byJones (1999a). This is perhaps to be expected as thelatter were obtained under more controlled laboratoryconditions, and where the range of stomatal conduc-tances was greater.

Problems relating to the use of infrared-sensed leaftemperature as an indicator of stomatal conductancehave already been noted (see Ludlow and Muchow1990). Although Blum et al. (1982) found significantrelationships between leaf water potential and leaftemperature, they did not always find significantrelationships between stomatal conductance and leaftemperature. However, other attempts to relate leaf tem-perature and stomatal conductance or water stress havebeen successful (Nilsson 1995, Jones 1999b).

Our evaluation of thermal imaging for detection ofstomatal closure depends both on the accuracy of thereference porometry measurements and on the innatebiological variability. Over a range from 16 to over1000 mmol m�2 s�1, the leaf conductance obtainedfrom six replicates was shown to have a mean error ofabout 10% with an AP4 porometer (Delta-T Devices Ltd2004). For the LI-COR LI-1600, over the operating rangeof 20–80% humidity, an error in measured relativehumidity of � 3% has been calculated to produce an

error in the measured leaf conductance of over 18%(Mcdermitt 1990). Nonetheless, porometry or infraredgas analysis are currently the methods of choice formeasuring stomatal conductance in the field or green-house. An accuracy equal to these methods wouldseem a desirable preliminary goal in the developmentof thermal imaging as a technique for investigators ofstress in plants. Already, the ability of thermal ima-ging to integrate information over whole leaves, andseveral leaves, can allow a more realistic assessmentof plant or canopy stress than does porometry.According to Jones (1999a), a thermal imager of thetype we used, with a temperature resolution of 0.1�C,should be able to resolve differences in conductanceof significantly better than 10% of the larger valueand often better than 5% over a wide range of con-ductances. The accuracy of the imager we used isstated at � 2�C, or an error of 2%, whichever islarger. However, this accuracy is only relevantwhere Tleaf is of interest, and not where indicesusing reference temperatures are calculated. Othererrors including in the estimation of backgroundreflectance or emissivity (see Jones 2004a) canincrease the error in measured leaf temperatures.

All methods for monitoring plant water status in prac-tical agriculture/horticulture have their drawbacks (seereview by Jones 2004b). Various measurements (waterpotential, porometry, sap flow) are very much depen-dent on environmental conditions at the time of mea-surement. Other disadvantages include the need fordestructive sampling (water potential) or calibration ofsensors to individual plants (sap flow). Thermographyhas several advantages over other plant-based methodsfor determining plant water status, and current efforts inmodelling should soon diminish various limitations toits application.

Table 3. Limitations currently associated with thermal imaging in relation to drought stress, and potential solutions

Association Limitation Solution

Thermal imager Accuracy Collaboration with manufacturers of imagers

Temperature drift Collaboration with manufacturers of imagers

Cost of thermal imager Declining; collaborate with manufacturers

Image analysis slow Development of automatic systems (see Leinonen and Jones 2004)

Thermal indices Unreliable references Alternative wet and dry reference surfaces, or replace references with

environmental measurements to allow calculation of conductance

from energy balance model

Influence of canopy structure on temperature

distributions

Include canopy architecture in model of canopy temperature responses

to environmental variability

Estimation of gs Need for estimate of boundary layer conductance Calculate from meteorological data or heated model leaves

Precision irrigation Need to define thresholds for irrigation Integrate models of the relationship between productivity

and stomatal conductance for different crops and environments


Conclusions

In conclusion, under a variety of conditions a goodcorrelation was found between the index IG, as obtainedfrom thermography, and stomatal conductance, as mea-sured with a porometer. However, to be an effectivemethod for monitoring plants in the field or greenhouse,confidence is required that the technique will effectivelydetect any stress during all measurements. The follow-ing guidelines can be used to optimize the technique –the time between spraying the wet reference leaf andtaking the image must be standardized, all plants andreferences must be subjected to a similar radiationenvironment, and the imager must be allowed to equili-brate before measurements. In addition averagingvalues for populations of leaves may help reduce errorsarising from variation in leaf angle. The estimation ofstomatal conductance requires additional information,relating to the boundary layer conductance (Jones2004a). For application to irrigation scheduling andsome other areas, it is necessary to calibrate the mea-sure in terms of threshold values above or below whichirrigation should be applied. The main limitationsof thermal imaging are summarized in Table 3.Improvements of the approach will need to address allthe issues here indicated and will require cooperationbetween plant physiologists and technologists.

Acknowledgements – This work was largely funded by the

European Union project STRESSIMAGING, contract HPRN-

CT-2002–00254 ‘Diagnosis and analysis of plant stress using

thermal and other imaging techniques’. OMG benefited from

an EU Training Network fellowship under this programme

and a fellowship from Fundacao para a Ciencia e a

Tecnologia (SFRH/BPD/17909/2004).

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Edited by D. Van Der Straeten


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Optimizing thermal imaging as a technique for detecting stomatal closure induced by drought stress under greenhouse conditions