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Functional Plant Biology, 2009, 36, 970–977

www.publish.csiro.au/journals/fpb

A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography Xavier R. R. Sirault A,B,C, Richard A. James A and Robert T. Furbank A,B A

CSIRO Plant Industry, Black Mountain, Corner Clunies Ross Street and Barry Drive, Canberra, ACT 2601, Australia. B Australian Plant Phenomics Facility – The High Resolution Plant Phenomics Centre, Corner Clunies Ross Street and Barry Drive, Canberra, ACT 2601, Australia. C Corresponding author. Email: [email protected] This paper originates from a presentation at the 1st International Plant Phenomics Symposium, Canberra, Australia, April 2009.

Abstract. A high-throughput, automated image analysis protocol for the capture, identification and analysis of thermal images acquired with a long-wave infrared (IR) camera was developed to quantify the osmotic stress response of wheat and barley to salinity. There was a strong curvilinear relationship between direct measurements of stomatal conductance and leaf temperature of barley grown in a range of salt concentrations. This indicated that thermography accurately reflected the physiological status of salt-stressed barley seedlings. Leaf temperature differences between barley grown at 200 mM NaCl and 0 mM NaCl reached 1.6C – the sensitivity of the IR signal increasing at higher salt concentrations. Seventeen durum wheat genotypes and one barley genotype, known to vary for osmotic stress tolerance, were grown in control (no salt) and 150 mM NaCl treatments to validate the newly-developed automated thermal imaging protocol. The ranking of the 18 genotypes based on both a growth study and the IR measurements was consistent with previous reports in the literature for these genotypes. This study shows the potential of IR thermal imaging for the screening of large numbers of genotypes varying for stomatal traits, specifically those related to salt tolerance. Additional keywords: Hordeum vulgare, IR, transpiration, Triticum turgidum.

Introduction Salinity is a significant limiting factor for cereal production in Australia and in many parts of the world (Flowers et al. 1997; Singh and Chatrath 2001). Research on salt-induced damage and physiological effects on crops has been extensively reviewed over the last 50 years (e.g. Bernstein and Hayward 1958; Flowers et al. 1977; Munns and Tester 2008). Munns et al. (2006) described three main mechanisms for salt tolerance in crop plants: (1) controlling salt uptake, (2) reducing damage from accumulated sodium ions, and (3) tolerance to osmotic stress. Most research into salt tolerance has targeted the first two components, i.e. how to keep salt out of the plant or how to minimise its impact once in the plant (e.g. James et al. 2006). However, the growth of salt-stressed crop plants is mostly limited by the osmotic effect of salinity, irrespective of the crop’s ability to exclude salt. The osmotic effect can be described as a water-stress effect as a result of the presence of salts in the soil (Epstein 1980), as high concentrations of salts in the soil make it harder for the roots to extract water. This results in reduced growth rates and stomatal conductance (Fricke et al. 2004; James et al. 2008). Genotypic variation for tolerance to osmotic stress has been investigated and assessed by measuring the stomatal conductance CSIRO 2009

response of plants grown in high salt (150 mM NaCl) relative to non-salt (control) conditions (James et al. 2008). The precision of this screening technique depended on accurately measuring stomatal conductance on leaves that were fully expanded before the commencement of the salt treatment and shortly after the desired salt concentration is achieved. These precautions were necessary to avoid variation in stomatal conductance associated with salt-induced changes to leaf morphology and the accumulation of salt in the leaves to potentially toxic concentrations. Although, James et al. (2008) identified genotypic variation in stomatal response using steady-state porometry, there were limitations in their study in terms of precision, repeatability and efficiency (speed). As stated by Jones (1999), small differences in stomatal conductance are difficult to detect with a porometer with any confidence. For reliable results, more than one reading of stomatal conductance should be taken per plant/ genotype (Rebetzke et al. 2001). However, the main drawbacks limiting steady-state porometry as a screening tool are its low signal-to-noise ratio at low salt concentrations and significant interference with natural leaf behaviour (Jones 1999). A potential non-contact alternative to porometry for measuring leaf stomatal conductance could utilise infrared

10.1071/FP09182

1445-4408/09/110970

Screening for salinity tolerance with infrared imaging

(IR) thermography. IR thermography ‘visualises’ surface temperature distribution of an object by focusing the longwave radiation emitted by the object onto a temperaturesensitive detector – the object’s temperature determines how much radiation is emitted at what wavelength following Planck’s law. Leaf temperature varies with transpiration rate (Tanner 1963; Fuchs 1990), which is largely a function of stomatal conductance. Jones (1999) showed that IR measurements of stomatal conductance were correlated with estimates obtained using a diffusion porometer and, therefore, areas of high temperature reflect stomatal closure, and areas of low temperature reflect stomatal opening. Thermal imaging has been particularly valuable for screening for stomatal behaviour (Liang et al. 2005), crop water stress (Alchanatis et al. 2006) and water use (Kummerlen et al. 1999; Merlot et al. 2002; Horie et al. 2006). In particular, Raskin and Ladyman (1988) and Riera et al. (2005) were successful at isolating Arabidopsis and barley mutants with the inability to close stomata. As leaf temperature differences due to variation in transpiration rates can be ‘visualised’ by IR thermal imaging, it is likely that this technology could be used to assess osmotic stress tolerance in cereal crops. To our knowledge, there are no reports in the literature on the application of IR thermal imaging for screening of salt tolerance. Jones (1999) indicated that variation in stomatal conductance of the order of 5% could be detected using a high resolution imager. It is, therefore, likely that IR thermography could identify genotypic variation in stomatal response such as that detailed by James et al. (2008). Moreover, being image based, IR thermography should be amenable to a high-throughput (automated) protocol removing the laborious and subjective task of manually processing thermal images. This is essential for screening of large numbers of genotypes and populations in breeding programs. The specific objectives of this present study were 2-fold: (1) to develop an accurate, rapid, high through-put screening protocol for osmotic stress tolerance in cereals using IR thermography, and (2) to validate the new screening protocol on a collection of durum wheats previously characterised for osmotic stress tolerance by James et al. (2008).

Materials and methods Quantifying temperature response to salinity using thermal imaging Germplasm and growing conditions Seeds of barley (Hordeum vulgare L.) cultivar Himalaya were surface sterilised with 1% hypochlorite and germinated in Petri dishes for 2 days. Germinated seeds were planted 1.5 cm deep, one per pot into square pots (6.5 cm width, 16 cm depth) containing a 50 : 50 mix of coarse river sand : perlite. Seedlings were watered with half-strength modified Hoagland solution (P reduced from 1 mM to 100 mM) according to Munns and James (2003). At 8 days after emergence, 25 mM NaCl was added to the irrigation solution twice daily to obtain required salinity levels of 0, 50, 100, 150 and 200 mM. Seedlings were randomly allocated to the different salinity levels, four seedlings for each salinity level.

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Seedlings were grown in a controlled environment chamber with 10 h photoperiod, a photosynthetic photon-flux density of 650 mmol m–2 s–1 from a mix of incandescent metal halide and fluorescent light bulbs and temperatures of 24C during the day and 18C during the night. Relative humidity in the chamber was maintained at ~50%. Image acquisition system Thermal images of seedlings were acquired between 1100 and 1400 hours, 3 days after imposing the salt treatment, in the controlled environment chamber using a ThermaCAM SC660 IR camera (FLIR Systems Inc., Boston, MA, USA). Additionally, a time-series analysis over two hours was also acquired to study variation in leaf temperature across time (see Accessory Publication to this paper). Thermal data from the seedlings were acquired at 20-s intervals. The SC660 IR camera uses a focal plane array, uncooled microbolometer with 640 480-detector elements, a spectral range of 7.5–13 mm, a thermal resolution of 0.045C and an accuracy of 1%. A 24 lens was mounted on the camera and emissivity in this study was deemed to be 0.95 (Tanner 1963). The IR camera was placed in the controlled environment chamber 2 hours before the measurement series to allow the optics to reach thermal equilibrium with air temperature. The IR camera was positioned at a distance of 0.8 m, perpendicular to the seedlings. In each image, two salt-treated seedlings were juxtaposed with a (non-salt) control seedling to assess the difference in leaf temperature due to salinity, rather than determining absolute leaf temperature (Fig. 1). Stomatal conductance To determine environmental conditions that would maximise transpiration rate under controlled environment chamber

Salt 150 mM

Control

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Fig. 1. Infrared thermograph of the set-up for assessing leaf temperature differences simultaneously of salt-treated durum wheat seedlings relative to a non-salt (control) durum wheat seedling. Thermographs were acquired 3 days after the salt stress was imposed. Air temperature was 24C and RH was ~50%.

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conditions, a LI-6400 gas-exchange system (Li-Cor, Lincoln, NE, USA) was used to examine the influence of vapourpressure deficit of the air (VPD) on both conductance and transpiration rate. As a result, the relative humidity in the controlled environment chamber was set at 50% to give a VPD of 1.5 kPa. Abaxial stomatal conductance measurements were obtained using an AP4 cycling porometer (Delta-T Devices Ltd, Burwell, UK), three days after the final salt concentrations were reached. Abaxial stomatal conductance had previously been shown to be more sensitive to salinity than adaxial stomatal conductance of wheat grown in controlled environment chambers (James et al. 2008). Stomatal conductance measurements were made from the mid-portion of the most recently expanded leaf (leaf 2) immediately following IR measurements.

Development of IR measurement protocol Images and data acquisition Images were stored directly onto a hard-drive as 14-bit resolution files using ThermaCAM Researcher Pro 2.9 (FLIR Systems Inc.). IR images were converted into matrices of raw temperature data in C (T480,640(R)) using ThermaCAM Researcher Pro for the development of the segmentation algorithm.

28.2°C

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Segmentation algorithm Temperature matrices T480,640(R) were transformed into 8-bit resolution, grey-level images for viewing in MATLAB release 2009a (The MathWorks, Natick, MA, USA), using a custom-built function ‘tmp2img.m’ (Fig. 2a). The function scales and normalises the temperature data using the following transformation: ðir;c Þ ¼

with

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where (tr,c) is the temperature value at position (r,c), tmax and tmin are the maximum and minimum temperatures in the temperature matrix T480,640(R), and (ir,c) is the grey level intensity at position (r,c). Seedlings were automatically identified in the grey image by using Otsu’s thresholding method (Otsu 1979), which assumes only two populations of pixels in an image, i.e. background and foreground – the foreground corresponding to the seedling. To obtain a homogeneous background, the thermographs of the seedlings were acquired against a bronze-coloured acrylic (PlastiX, Sydney, NSW, Australia). Acrylic does not transmit IR radiation and its different emissivity results in an apparent temperature two degrees hotter than the air temperature. This provided a clear threshold value, ithreshold, for separating

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Fig. 2. Segmentation algorithm for analysing infrared thermographic images; (a) infrared thermograph of Himalaya barley in 150 mM NaCl (left) v. non-salt ‘control’ (right) visualised as an 8-bit grey image (iron bow palette), (b) histogram of grey-level values with ithreshold computed according to Otsu’s method; (c) binary image of (a); and (d) result of array multiplication to apportion temperature data to seedlings, 3 days after the salt stress was imposed. Air temperature was 24C and RH was ~50%.


background and foreground pixels in the IR images (Fig. 2b). A binary matrix, B480,640(R), was, thus, computed as: 0 if ðir;c Þ ithreshold 1 r 480 with ðBr;c Þ ¼ ; ð2Þ 1 if ðir;c Þ < ithreshold 1 c 640 where (Br,c) is the binary value in matrix B at position (r,c) (Fig. 2c). Each plant in the binary matrix was then labelled with an integer value using the ‘bwlabel’ function of the image processing toolbox (The MathWorks). Visual observations of the resulting images demonstrated that the thresholding approach was accurate and effective (Fig. 2d). Seedling temperature The binary matrix B was then used as a mask to derive the temperature of the two seedlings in the thermograph only. By multiplying arrays T480,640(R) and B480,640(R) according to array arithmetic rules – element by element multiplication, temperature values for the seedlings were derived. A structure identifying the location and the number of pixels for each labelled seedling was defined in Matlab, allowing automatic calculation of the average temperature for each labelled seedling (Fig. 2d). The difference between the control and salt-treated seedling was then computed. Each seedling was represented by a minimum of 3000 independent, thermally calibrated data points. IR thermography screen validation: evaluation of durum wheat genotypes at 150 mM NaCl Germplasm Seventeen durum wheat (Triticum turgidum L. ssp. durum Desf.) genotypes and one barley cultivar Franklin, varying for osmotic stress tolerance were chosen based on the published work by James et al. (2008). The durum wheats included cultivars and landraces from a range of international locations, and three Australian durum cultivars, Tamaroi, Wollaroi and Bellaroi. Growth conditions and experimental design Sterilised and germinated seeds, six per genotype, were planted into pots containing a 50 : 50 mix of coarse riversand : perlite in square pots as described previously. At 8 days after emergence, two seedlings per genotype were randomly chosen and deemed ‘control’ seedlings and were watered with modified Hoagland solution. The remaining four seedlings were watered with NaCl solutions incrementing by 25 mM twice daily over 3 days to the required salinity level of 150 mM NaCl. Supplemental Ca2+ (CaCl2) was added to maintain a Na+ : Ca2+ ratio of 15 : 1. Seedlings were randomised according to a split-plot design with four replicates. Plants were grown in a glasshouse under natural light conditions (~1200–1500 mmol m–2 s–1) and transferred into a controlled environment chamber 1 day before the first series of IR measurements to acclimatise. Conditions in the controlled environment chamber were as described above.


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IR screening and biomass measurements Thermal images of seedlings were acquired between 1100 and 1300 hours in a controlled environment chamber using the acquisition system described above. In each thermograph, two salt-treated seedlings were contrasted simultaneously to a control plant (Fig. 1). The temperature differential was calculated using the algorithm described in Fig. 2. Shoots of all genotypes were harvested at 25 days after emergence and dried at 70C for 3 days and weighed. Statistical analysis Data were analysed according to a mixed linear model using the REML procedure in GENSTAT 10 (VSN International, Hemel Hempstead, England, UK). ‘Replicate’ was fitted as a random term in the model while genotype was assumed fixed. All data reported are best linear unbiased estimators (BLUEs) and standard errors derived from the analysis. Results Relationship between stomatal conductance and a change in leaf temperature due to different salinity levels The relationship between stomatal conductance and a change in leaf temperature of Himalaya barley grown in a range of NaCl concentrations increasing from 0 to 200 mM NaCl, is shown in Fig. 3. The relationship between conductance and leaf temperature was curvilinear and mathematically described by a fourth-order polynomial function: y ¼ 3:53:106 x4 þ 1:23:103 x3 0:14x2 þ 5:57; R2 ¼ 0:9932:

ð3Þ

Significant variation (P < 0.05) in stomatal response and leaf temperature were found across salinity treatments. Stomatal conductance decreased by ~60% at 200 mM NaCl, which corresponded to an increase in leaf temperature of ~1.6C (Fig. 3b). Similarly, a 40% decrease in stomatal conductance equated to an increase in leaf temperature of 0.5C at 100 mM NaCl. Preliminary experiments showed oscillatory patterns of leaf temperature induced by the cycling of the controlled growth chamber condenser (see Accessory Publication to this paper). These temperature oscillations were synchronised across the leaf surface with periods of 8 min, which gave confidence that relative differences between treated and control seedlings were maintained at any time during a full 8-min cycle. A seedling acclimatised to higher salinity levels within 2 days: homogeneous false-colour images of transpiration were obtained 2 days after the imposition of the salt treatment. Validation of IR thermography of durum wheat genotypes at 150 mM NaCl Genetic variation in seedling leaf temperature response due to osmotic stress (150 mM NaCl or 0.76 MPa) was assessed in 18 genotypes using IR thermography. Temperature responses were calculated as the difference in leaf temperature of saltstressed seedlings from non-stressed ‘control’ seedlings (T150 – TC) (Fig. 4). Significant variation (P < 0.05) in seedling leaf temperature response was found between genotypes, of

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Stomatal conductance (normalised against control) Fig. 3. Relationship between increasing salt concentrations, stomatal conductance and the change in leaf temperature on the second leaf of Himalaya barley seedlings grown in a range of salt treatments; (a) false-colour (iron bow palette), thermal infrared image of Himalaya barley at five levels of NaCl (0 to 200 mM); (b) relationship between abaxial stomatal conductance and change in leaf temperature for the second leaf of Himalaya barley, 3 days after the salt stress was imposed. Air temperature was 24C and RH was ~50%. Bars indicate s.e. (n = 4).

about 1C. Seedling leaf temperature increased by a minimum of 0.77C for Edmore and a maximum of 1.82C for Brkulja. The temperature responses of Australian durum cultivars Tamaroi and Wollaroi were large, above 1.5C, and Bellaroi and Franklin (barley) displayed a relatively small increase of 0.85C. Salt tolerance is usually assessed in growth studies as the percentage difference of biomass in salt, relative to non-salt control conditions. The relationship between shoot dry weight as a percentage of control and an increase in seedling leaf temperature was linear and negative (P < 0.05) as depicted in

Fig. 5. Genotypes that maintained lower leaf temperatures at 150 mM NaCl had a higher degree of salt tolerance. These genotypes also developed a greater leaf area (data not shown). Conversely, seedlings with high leaf temperatures due to salt had a lower degree of salt tolerance. Discussion This study was undertaken to develop and test a new automated approach for the screening of osmotic stress tolerance in cereals. The main assumption in this study was that changes in stomatal


2.5 (1.82)

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Ed mo r Be e llar Fra oi nk He lin rcu le BL 97 s 00 23 Co ult er BL 95 00 90 Du Az ul de rex L. 29 Em 1 ble m Kh ab Wo ur llar oi Ko e Lin lz e1 41 Lin e1 38 Ta ma roi Lin e1 39 Brk ulja

o

Increase in leaf temperature due to salt (T150 – TC ) ( C)


Genotypes

Salt tolerance (shoot DW in salt, % control)

Fig. 4. Increase in leaf temperature (T150 TC) of 17 durum wheat genotypes and Franklin barley due at 150 mM NaCl, 3 days after the salt stress was imposed. Air temperature was 24C and RH was ~50%. Bars indicate s.e. (n = 4).

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Fig. 5. Relationship between an increase in leaf temperature due to 150 mM NaCl (T150 TC) and salt tolerance of 17 durum wheat genotypes and Franklin barley, 3 days after the salt stress was imposed. Air temperature was 24C and RH was ~50%. Shoots of all genotypes were harvested at 13 days after the slat treatment.

conductance due to salinity could be detected and the level of the stress response precisely quantified by IR thermography. Previously, Leinonen and Jones (2004) stressed that ‘the effective use of thermal imaging requires consistent, preferably automated methods for analysing the images’. In this study, we optimised experimental and environmental conditions under which genotypes with altered stomatal response to salt can be identified by IR imaging. One of the critical steps for automating the analyses of IR images was to separate the desired region of interest, i.e. the seedling, from the background. Previously, methods for the

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identification of areas of interest in images relied on the accurate co-registration of signals acquired by different sensors, e.g. visible and IR (Mather 1999; Leinonen and Jones 2004). In this study, the collection of a single signal, which was then transformed into an 8-bit grey image to obtain an equivalent visible image of the scene, negates the need for co-registration, hence providing a simple and flexible system. The separation of foreground from background was achieved by the use of an acrylic stand as a background. Acrylic does not transmit IR radiation but reflects it. As the emissivity of acrylic is different from that of a wheat or barley seedling, its temperature was perceived to be at least 2C hotter than the leaf temperature of the control seedling with the environmental conditions described herein. The use of a background for thresholding has been used previously (Pearce and Fuller 2001) but deemed impractical (Leinonen and Jones 2004). Nonetheless, it proved to be very efficient for our screening protocol as demonstrated by the homogeneity of the background in Fig. 2a, b – the histogram of pixel value. However, at high salinity levels, one major problem could arise as illustrated in Fig. 3a: seedlings in 200 mM NaCl tend to fade in the background due to their higher temperatures (1.6C hotter than the control seedling). This makes the identification of the seedling difficult and the complexity of the image analysis process is significantly increased as the seedling is now composed of multiple objects. To address the problem, environmental conditions and in particular the impact of VPD, on both transpiration and conductance, can be altered to favour a more distinct temperature signal from the plant in contrast to the background. Jones (1999) indicated that ‘the effective sensitivity in terms of changes in stomatal conductance that would be detectable with a thermal imaging system having a temperature resolution of 0.1C’ is greatest at low conductances. By acquiring thermographs of seedlings in an atmosphere with a VPD ranging from 1.5 to 2.0 kPa, one can maximise transpiration rate while maintaining lower conductance (data not shown), thus, keeping the seedling slightly cooler than the background while maintaining higher effective sensitivity even at high salinity levels. As the osmotic stress increases, transpiration rates and the resulting leaf latent-heat flux decreases, leading to an increased surface temperature that consequently increases the difference in temperature between salt treated and control seedlings (Fig. 3). Based on the theoretical results published by Jones (1999), reducing total conductance from 200 mmol m2 s1 to 75 mmol m2 s1 (i.e. 62.5% reduction) at a VPD of 1.6 kPa and an irradiance of 100 W m2 with no wind speed, should result in a leaf temperature 2C higher than the air temperature. In the present study, ‘control’ seedlings had an abaxial stomatal conductance of ~200 mmol m2 s1 (data not shown) when grown under a light intensity of 650 mmol m2 s1 (~135 W m2). Under these conditions, seedlings in 200 mM NaCl, i.e. with a 60% reduction in conductance, were ~1.5C hotter (Fig. 2). This is well within theoretical boundaries. The main benefits of the thermal imaging screening protocol are its precision, non-invasiveness and speed, compared with other methods used to measure stomatal conductance, such as porometry. Only a few seconds are required to acquire a thermograph comprising more than 3000 individual

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measurements for each object, thus taking into account spatial heterogeneity. To be as useful, porometry would require repeated point measurements (Jones 1999; Rebetzke et al. 2001), but the obvious drawbacks of porometry are its interference with the natural behaviour of the leaf (through handling) and the inherent low signal-to-noise ratio. As a result, IR thermography could significantly improve the efficiency of selection in a conventional breeding program by measuring many seedlings over a short period of time. As IR thermography is sensitive to very small changes in leaf temperature, it may also be suitable for screening at lower salt concentrations, i.e. 50 or 100 mM NaCl compared with 150 mM NaCl or higher, which may be important logistically when screening large populations. Several factors such as surface emittance, changes in ambient temperature and humidity and background thermal radiation could introduce errors in the measurement of absolute leaf temperature. This issue was overcome by measuring relative temperature differences between saltstressed and control seedlings simultaneously. Jones (1999) showed that when used on a relative mode, IR thermography had comparable, and in many circumstances, better resolution than that shown for other methods currently available (Weyers and Lawson 1997). Additionally, to minimise fluctuations in environmental factors our experiments were completed in controlled environment chambers and care was also taken to account for variability of leaf angles as stressed by Kaukoranta et al. (2005). By screening seedlings rather than more advanced plants, leaf angles were no longer randomly distributed, providing a comparable surface to the IR camera. These conditions were also used when performing a validation screen of the IR thermography screening protocol, using genotypes known to vary for osmotic stress tolerance (Figs 3, 4). James et al. (2008) previously screened these lines (under similar growing conditions) for osmotic stress tolerance by using porometry to measure the stomatal response due to high salinity. These authors identified two putative groups, namely a ‘small response lines’ group, i.e. with an average 30% reduction in stomatal conductance, and a ‘large response lines’ group, i.e. with an average 54% reduction in stomatal conductance. Many genotypes previously described as having a small (stomatal) response also showed a small increase in leaf temperature (e.g. Edmore, Hercules, Coulter, BL950090). Conversely, genotypes such as Brkulja, Koelz and Line 138 previously classified as ‘large (stomatal) response’ and also figured in this study as the genotypes with the highest increase in leaf temperature. The ranking of the check cultivars, Bellaroi, Franklin, Wollaroi and Tamaroi was also similar to the study by James et al. (2008). In Fig. 5, there was a negative correlation between increased leaf temperature and salt tolerance, demonstrating that it is possible to assess genotypic variation for tolerance to osmotic stress using IR thermography. In conclusion, a segmentation method for accurately analysing IR thermographic images was developed and evaluated. This new screening method is precise, automated and quick and, our results indicate that it is possible to use IR thermography for the screening of tolerance to osmotic stress in cereals.


Acknowledgements The authors wish to thank Dr Rana Munns for helpful comments on the manuscript and the High Resolution Plant Phenomics Centre (Canberra node of the Australian Plant Phenomics Facility) where the research was conducted.

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Manuscript received 20 July 2009, accepted 15 September 2009

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