Journal of Experimental Botany, Vol. 58, No. 4, pp. 765–772, 2007
Imaging Stress Responses in Plants Special Issue
doi:10.1093/jxb/erl210 Advance Access publication 16 November, 2006

SPECIAL ISSUE PAPER

3-D cell-level chlorophyll ﬂuorescence imaging ofozone-injured sunﬂower leaves using a new passive
light microscope system
Ryosuke Endo1,* and Kenji Omasa2
1

Advanced Research Institute for the Sciences and Humanities, Nihon University, 6F Ichigaya Tokyu Building,
4-2-1 Kudan-kita, Chiyoda, Tokyo 102-0073, Japan2

Department of Biological and Environmental Engineering, Graduate School of Agricultural and Life Sciences,
The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo 113-8657, Japan

Received 8 May 2006; Accepted 13 September 2006

Abstract
A passive light microscope system has been developed, capable of reconstructing an extended-focus 3-D
cell-level image of chlorophyll ﬂuorescence and FPSII
of intact attached leaves using a limited number of
focal plane images of chlorophyll ﬂuorescence. Using
this system, the relationships between the depth ofthe mesophyll cells in spongy tissue and the intensityof the chlorophyll ﬂuorescence and the FPSII were
investigated in sunﬂower leaves exposed to 300 ppb
ozone for 12 h at a PPFD of 300 mmol m22 s21 actinic
light. After ozone exposure, ﬂuorescence intensity (F)largely decreased in the cells just under the epidermal
cells (within ~20 mm of the epidermal cells), but thesites where ﬂuorescence intensity decreased had no
relationship to the position of the stomata. By contrast,
the distribution of FPSII showed no change after theozone exposure. These ﬁndings suggest that ozoneinduced inhibition occurs in the cells just under the
epidermal cells by reducing the light absorption of thechloroplasts, while the operating quantum efﬁciency
of PSII photochemistry is maintained.
Key words: Chlorophyll
microscope, ozone.

ﬂuorescence,

3-D

imaging,

Introduction
Tropospheric ozone is one of the worst global air pollutants, causing serious vegetative damage and forest

decline (Yunus and Iqbal, 1996; Sandermann et al., 1997).
Half of forests in the world are predicted to be exposed tophytotoxic ozone levels by 2100 (Fowler et al., 1999).
Stratospheric ozone is decreasing due to ozone destruction
by human-made chlorofluorocarbons and NOx, whereas theconcentration of ozone at ground level appears to be stable
or increasing in many industrialized countries (Oltmans
et al., 1998; Akimoto, 2003). Increases in the surface
ozone concentration are largely caused by photochemical
oxidant pollution produced in the atmosphere by complex
photochemical reactions involving NOx and hydrocarbons(Lelieveld and Crutzen, 1990; Oltmans et al., 1998).
Ozone damage in plants has been investigated with regard to its oxidizing potential and the consequential formation of radicals and reactive oxygen species, such as
the superoxide radical, hydrogen peroxide, and hydroxyl
radical (Heath, 1980, 1987). These radicals and reactive
oxygen species attack the plasma membrane, causing an
increase in oxidative stress within the cells (Heath, 1994;
Schraudner et al., 1997; Omasa et al., 2002) and, consequently, decreasing the plants’ physiological and biochemical activities. Because intercellular ozone concentrations
have been reported to be approximately zero under highozone exposure (Laisk et al., 1989; Omasa et al., 2000,
2002), ozone itself is unlikely to enter plant cells.
Plant productivity decreases due to ozone inhibition ofphotosynthesis. This inhibition can be the result ofchanges in stomatal conductance or photosynthetic enzymatic activities (Pell et al., 1992). Changes in stomatal
conductance may be associated with changes in theplasmalemmae of guard cells (Castillo and Heath, 1990;* To whom correspondence should be addressed. E-mail: ryosuke-endo@arish.nihon-u.ac.jpª The Author [2006]. Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved.
For Permissions, please e-mail: journals.permissions@oxfordjournals.org

766 Endo and Omasa

Torsethaugen et al., 1999), and changes in photosynthetic
enzymatic activities may be due to the effect of oxygen
radicals generated by ozone. However, it is unclear
whether these are the main factors involved in the declineof photosynthesis after ozone exposure.
The distribution of ozone-injured sites varies all overthe leaf, and the degree of injury is seldom uniform(Omasa et al., 1981). Therefore, specifying the effects ofozone on photosynthetic activity requires a spatial measuring method. Chlorophyll fluorescence imaging is oneof the most effective methods for analysing photosynthetic
activity in in situ plant leaves (Omasa et al., 1987; Daleyet al., 1989; Lichtenthaler and Miehé, 1997). Recently,
microscopic fluorescence imaging systems have beendeveloped for cellular- and chloroplast-level analyses(Oxborough and Baker, 1997; Küpper et al., 2000;
Leipner et al., 2001; Lawson et al., 2002; Endo andOmasa, 2004). Using a chlorophyll fluorescence imaging
system, Leipner et al. (2001) identified the primary sitesof ozone-induced perturbation in Phaseolus vulgaris. By
using a 680 nm bandpass filter and a 695 nm longpass
filter, chlorophyll fluorescence from the upper mesophyllcell layer in a leaf was differentiated from fluorescence
below the leaf surface. Ozone-injured sites were notrelated to the location of stomata, and a greater number of
injured sites was identified over the 695 nm images thanin the 680 nm images (Leipner et al., 2001). This method
showed a difference of inhibition in depth, based on thefact that fluorescence at 680 nm is strongly absorbed bychlorophylls within the overlying cells compared with
695 nm, although it does not allow direct measurement of
the depth of the cells in the leaves.
High-resolution imaging with a microscope causes theinevitable problem of the limited depth of the observable
field. Because a leaf surface tends to be uneven, not muchof a captured image is in focus, and inaccurate photosynthetic parameters can be generated from fluorescence
images that include areas that are out of focus. This
problem can be solved by reconstructing an extended-focus
image from a series of images captured at different focal
planes (shape from focus). This method provides not only
an extended-focus image but also a 3-D image; therefore,
the direct relationship between the photosynthetic parameter and depth of the cells in the leaves can be analysed.
Many methods have been developed to extract focal
points from each pixel in multifocal plane images (Nayar
and Nakagawa, 1994; Russ, 1998; Omasa, 2000). To
apply this technique to fluorescence imaging, a methodthat does not alter the intensity of each pixel before andafter processing is required, because fluorescence intensities of pixels in the images will be used to calculate thephotosynthetic parameters. The shape-from-focus method
is the most effective for extracting the focal point fromfocal plane images. Using this method, Rolfe and Scholes(2002) captured an extended-focus image of chlorophyll

fluorescence from intact leaves from a total of 39 images
at 5.5 lm intervals using a 310 objective lens. Using thissystem, however, it took a long time to acquire a series ofimages at different focal depths. This problem can cause inaccurate 3-D reconstruction because of sample movement,
especially at high magnification. Therefore, an alternative
reconstruction method capable of extracting an accurate
focal point from fewer focal plane images is required.
Omasa (2000) has developed a modified shape-fromfocus algorithm that was based on a linear regression (LR)
operator. This method is characterized by making an
extended-focus image from fewer focal plane images byinterpolating the distance between the captured images. In
addition, it was found that this method was effective forreconstructing range images from monocular light microscope images of plant cells (Omasa, 2000). However, thismethod was applied only to a reflected light image, andwas not applied to a chlorophyll fluorescence image.
Therefore, 3-D analysis of photosynthetic activity in in situ
plant leaves by this method, has not been investigated.
In this study, the method based on the LR operator wasapplied to produce microscopic extended-focus images of
the chlorophyll fluorescence of ozone-injured leaves, andthey were used to clarify the relationship between the depth
from the leaf surface and the injured site in an in situ sunflower leaf. This system was also designed to reconstruct
3-D chlorophyll fluorescence and UPSII images.

Materials and methods
Growth conditions
Sunflower (Helianthus annuus L. cv. ‘Sun Hope’) seeds were sownin a growth chamber in pots filled with artificial soil (mixture ofvermiculite, perlite, 1:1 v/v). The plants were illuminated for 12 heach day with fluorescent lights (PPFD 300 lmol m2 s1 at plantheight). The air temperature was 26.5 C during the day and 20 C
at night. The relative humidity was 45% during the day and 60% atnight. Plants were watered daily with a nutrient solution (1:1000
dilution of HYPONeX 5-10-5, HYPONeX Japan, Osaka, Japan).
The plants were grown for 4 weeks, and fully expanded mature
leaves were used in situ for the experiments.
Ozone treatment
At 4 weeks, the plants were transferred to another environmentallycontrolled chamber (illuminated with fluorescent lights at PPFD
300 lmol m2 s1) and exposed to air containing a 300 ppb ozone
concentration for 12 h. Ozone was generated using an ozone
generator (OES-10A, Dylec Inc., Osaka, Japan) and mixed with theinlet air entering the chamber. The ozone concentration inside thechamber was continuously monitored using an ozone monitor(Model 1200, Dylec Inc.). After ozone exposure, the treated plants
were transferred immediately to the 3-D chlorophyll fluorescenceimaging system.
Chlorophyll ﬂuorescence imaging system
Chlorophyll fluorescence images were captured with a computerized
light microscope system, which was described in Endo and Omasa

3-D chlorophyll ﬂuorescence imaging of ozone-injured leaves 767(2004). The system comprised a modified light microscope witha 320 objective lens (BD Plan Apo 20, N.A.¼0.42; Mitutoyo),a stepping-motor control system for controlling each axis of the
microscope stage and lens barrel, a cooled charge-coupled device(CCD) camera (Cascade, Photometrix), and a personal computer fordeconvoluting the series of focal plane images and analysing theresulting 3-D images and fluorescence parameter images. The
stepping motor system is connected to the computer and is able tomove the lens barrel precisely to acquire each focal plane image at
a constant 2-axis interval. The images, captured at 653 horizontal3492 vertical pixels per frame with 16-bit resolution, wererecorded on a hard disk and analysed using software developed with
Visual Basic (Version 6.0, Microsoft, Seattle, WA, USA) andcommercial software (Erdas Imagine Version 8.4, Erdas).
During the experiment, continuous actinic light at a PPFD of 300
lmol m2 s1 for photosynthesis and a saturation light pulse ata PPFD of 3800 lmol m2 s1 to cause transient saturation ofphotochemistry were provided by 180 W metal halide lamps (LSM180, Sumita Optical Glass Inc.) equipped with short-pass filters(model 4-96, k <620 nm; Corning, USA); the light was passed
through heat-absorbing filters via an optical fibre system and wascontrolled by electric shutters (Shutter Controller, EMS). Chlorophyll fluorescence excited by these lights was imaged by the CCD
camera through an optical filter (model 2-64, wavelength k >640
nm; Corning) in the lens barrel of the microscope.
After ozone exposure for 12 h, the plants were moved to themicroscopic imaging system stage. After a 20 min adaptation period
under continuous actinic light for photosynthesis (PPFD 300 lmolm2 s1), the fluorescence intensity image (F) from the abaxial sideof the sunflower leaf was captured. Just after this measurement,a fluorescence intensity image (F#)
m was measured during a 1.2 slight pulse (PPFD of 3800 lmol m2 s1) to cause saturation ofphotochemistry. To reconstruct a 3-D extended-focus image, a seriesof unprocessed F and F#m images was captured at different focal
planes for every additional 4 lm from a reference z point. Because
irradiation of a saturation pulse at short intervals can alter thephotochemistry of leaves, there was a 30 s period before capturing
the next set of F and F#m images after the focal plane was moved.
In total, 15 sets of F and F#m images we captured.
Image deconvolution
A linear regression (LR) operator was used to reconstruct extendedfocus 3-D images from a series of limited focal plane images, whichwere captured by z-axis traversal of the lens barrel (Omasa, 2000).
Figure 1 shows the procedure for producing an image deconvolution. For all pixels in all unprocessed images, the focus measurevalues were calculated automatically using software we developedwith Visual Basic (Version 6.0, Microsoft).
The LR operator, which is effective for determining the focus
measure, was used to obtain extended-focus images from a series of
unprocessed images at different focal planes. The data on each axisof the four square-line masks were calculated: Mk(i, j), where k¼1,
2, 3, 4, and (i, j) indicates the centre of the Ms3Ms line mask (Fig.
1). Focus measure f(i, j) can subsequently be determined using theLR operator, in which the sum of the absolute error between intensity I(i, j) and the regression line of I(i, j) is calculated using theleast-squares method on the axes (pk, k¼1, 2, 3, 4) of each mask:
XX
f ði; jÞ ¼jIðx; yÞ  ½ak ði; jÞ þ bði; jÞpk ði; jÞj ð1Þ
k¼1;2;3;4 x;y2Mkði;jÞ

where ak(i, j) and bk(i, j) represent the regression coefficients online mask Mk(i, j) in which x; y 2 Mk ði; jÞ indicates that (x, y) exists
in Mk(i, j).
The number of focal plane images was limited to 15 to shorten
the measuring time. Despite having used a discrete range of depth,

Fig. 1. The sequence of modified shape-from-focus images used in thealgorithm for 3-D reconstruction of the chlorophyll fluorescence
images.

the application of Gaussian interpolation provided smoother, moreaccurate range estimates (Fig. 1). The focus measure data at eachpixel (i, j) in the images of continuous focal planes have a Gaussian
distribution, where the optimum focus point, the focal range zp (i, j),is the peak of the Gaussian distribution. This assumption allows zp(i, j) to be determined from three focus measures ( fn–1, fn, fn+1) andthe distance between neighbouring focal planes (Dz):zp ¼

ðln fn  ln fnþ1 Þðz2n  z2n1 Þ  ðln fn  ln fn1 Þðz2n  z2nþ1 Þ
2Dz ðln fn  ln fn1 Þ þ ðln fn  ln fnþ1 Þ

ð2Þ

where fn is the largest value in a series of focus measures at the
pixel level estimated using equation (1) and coordinates (i, j) areomitted for simplicity. The 3-D image estimated by equation (2)included some spike-like noise, which was removed using a medianfilter.
An extended-focus image was generated by interpolating theoriginal chlorophyll fluorescence intensities using the informationon the focus range at each pixel. Intensity Ip(i, j) focused at (i, j)
was estimated byzn  zp
zp  zn1
Ip ¼ In1
þ In
ð3Þ
Dz
Dz
where In and In–1 are the fluorescence intensities at pixel (i, j) in theimage captured at zn and zn–1, respectively, and coordinates (i, j)
are omitted for simplicity.
Calculation of UPSII
To convert an intensity image into a yield image, each intensity
image (F and F#)
m was divided by the average value of fluorescenceemitted from a fluorescent standard card induced by the corresponding light intensity. Because the fluorescent card has a constantfluorescent yield regardless of light intensity, this process enabled
us to convert intensity images to yield images. The UPSII was
calculated using the following equation (Genty et al., 1989):
 0   
FmF
RSL  RAL 0 
UPSII ¼
ð4Þ
Fm
RSL

where RSL and RAL are the values of the fluorescence emitted fromthe fluorescent standard card induced by the saturation light pulse
and the actinic light, respectively. The UPSII image represents theyield of linear electron transport through PSII, with pixel values768 Endo and Omasa
ranging from 0 to 1 (Genty et al., 1989; Maxwell and Johnson,
2000).

Results
Figure 2 shows a series of unprocessed F images captured
at different focal planes before ozone exposure. The planeof focus in the first image was located close to the abaxial
leaf surface. At a 30 s interval after each 4 lm movementof the focal plane in the direction of the adaxial surface,
the following image was captured, and this process was
repeated 14 times. As can be seen in Fig. 2, each image
has an area in focus and an area out of focus, and eachshows the meshed structure indicative of the cells of
spongy tissue. Each image clearly showed that the sample
had non-uniform fluorescent intensity.
From these images, the fluorescence intensity of eachfocal point in the field of view was calculated using
equations (1) to (3), and extended-focus images of F andF#m were produced. Extended-focus 3-D images of F and

Fig. 2. A series of unprocessed chlorophyll fluorescence (F) images captured from the abaxial side of a sunflower leaf at steady-state under an
actinic light of 300 lmol m2 s1. Images were captured across 15 focal
planes at 4 lm intervals using a 320 objective lens. Scale bar¼40 lm.

F#m were reconstructed by overlaying the 3-D range image
with the extended-focus image. The resulting 3-D range
image was the smoothest and the most exact when themask size for the LR operation was Ms¼11 and that forthe median filter was Ms¼5. The UPSII image wascalculated from extended-focus images of F and F#m byequations (4), and 3-D UPSII was reconstructed in thesame way.
An extended-focus 3-D image of chlorophyll fluorescence (F) at steady-state at a PPFD of 300 lmol m2 s1actinic light before ozone exposure is shown in Fig. 3.
The relationship between the distance from the first focal
plane depth (Fig. 2A) and fluorescence intensity at the
pixels on the X–X# line (Fig. 3B) is shown in Fig. 3C.
Before ozone exposure, the fluorescence intensity was
non-uniformly distributed in the mesophyll areas and had
no relationship to the depth in the leaf (Fig. 3C).
An extended-focus 3-D image of UPSII at a PPFD of
300 lmol m2 s1 actinic light before ozone exposure
was constructed from the images of F and F#m (Fig. 4A). In
contrast to the chlorophyll fluorescence, the UPSII values
were uniformly distributed across the leaf area. The relationship between the distance from first focal plane andthe UPSII values at the pixels on the X–X# line (Fig. 3B)
are shown in Fig. 4B. The UPSII values on the X–X# line
(range, 0.43–0.51) had no relationship to the depth in theleaf.
An extended-focus 3-D image of fluorescence intensity(F) at steady-state after exposure to 300 ppb ozone for
12 h are shown in Fig. 5. After ozone exposure, areas ofhigh-intensity and low-intensity chlorophyll fluorescencewere recognized. The relationship between the distancefrom the first focal plane and the fluorescence intensity
along the X–X# line (Fig. 5B) is shown in Fig. 5C.
Fluorescence intensity was low near the abaxial leaf
surface and showed higher values deeper within the leaf.
Fluorescence intensities from cells approximately 40 lm
below the abaxial leaf surface were almost the same as
the mean fluorescence intensity of the leaf before ozone
exposure.
An extended-focus 3-D image of UPSII after exposure to
300 ppb ozone was constructed from the images of F andF#m (Fig. 6A). In contrast to the chlorophyll fluorescencevalues, the UPSII values were uniformly distributed acrossthe leaf area, despite the UPSII values having greater
variability than before ozone exposure. The relationshipbetween the distance from the first focal plane and the
UPSII values at the pixels on the X–X# line (Fig. 5B) are
shown in Fig. 6B. The UPSII values on X–X# line (range,
0.39–0.52) had no significant relationship to the depthof the cells in the leaf, although only a slight tendency
for the UPSII values to decrease closer to the abaxial leaf
surface was found.
Figure 7A shows the reflection image in the same areaof the ozone-exposed leaf as shown in Fig. 5B. The

3-D chlorophyll ﬂuorescence imaging of ozone-injured leaves 769

Fig. 4. 3-D extended-focus UPSII images of the mesophyll cells shownin Fig. 3. (A) The 3-D extended-focus UPSII image. (B) The relationshipbetween distance from the first focal plane and UPSII. The UPSII images
were calculated from two kinds of fluorescence intensity images: F was
taken at a PPFD of 300 lmol m2 s1 actinic light and F#m was taken
during a saturating light pulse of 3800 lmol m2 s1. The 623 points
plotted were taken along the centre line in (B). Scale bar¼40 lm.

Discussion
Fig. 3. 3-D extended-focus chlorophyll fluorescence (F) images ofmesophyll cells in the spongy tissue of a sunflower leaf before ozone
exposure, calculated using the linear regression (LR) operator describedin the text and Gaussian interpolation. (A) Image of the abaxial leaf
surface viewed at 45 from the horizontal. (B) Image of the leaf surface
viewed from directly above. (C) The relationship between distance fromthe first focal plane (Fig. 2A) and fluorescence intensity (n¼623 points).
The X–X# line in (B) is the profile analysis line used for the plot in (C).
Scale bar¼40 lm.

dashed white circle indicates a stoma. As can be seen in
Fig. 7B, there was no relationship between the site where
fluorescence intensity decreased strongly (dashed blackline) and the position of the stoma.

A new passive light microscope system was developedthat is capable of reconstructing 3-D cell-level images ofF, F#m, and UPSII of intact attached leaves from a limited
number of unprocessed images of chlorophyll fluorescence at different focal planes. The relationships between
the depth of mesophyll cells in spongy tissue and chlorophyll fluorescence parameters (F and UPSII) were investigated in sunflower leaves exposed to 300 ppb ozone for
12 h at a PPFD of 300 lmol m2 s1 actinic light.
In chlorophyll fluorescence imaging, 680 nm band-passand 695 nm long-pass filters have been used to estimate
the distance of cells from the leaf surface (Leipner et al.,2001). Fluorescence at 680 nm is strongly absorbed bychlorophylls compared with that over 695 nm. Therefore,

770 Endo and Omasa

Fig. 6. (A) 3-D extended-focus UPSII image of mesophyll cells shownin Fig. 5. (B) The relationship between distance from the first focal
plane and UPSII. UPSII images were calculated from two kinds offluorescence intensity images: F was taken at a PPFD of 300 lmol m2s1 actinic light and Fm# was taken during a saturating light pulse of3800 lmol m2 s1. The 623 points plotted were taken along the centre
line in (B). Scale bar¼40 lm.

Fig. 5. 3-D extended-focus chlorophyll fluorescence (F) images ofmesophyll cells in the same sunflower leaf after 300 ppb ozone
exposure for 12 h. (A) The leaf surface viewed at 45 from thehorizontal. (B) The surface viewed from directly above. (C) The relationship between distance from the first focal plane and fluorescenceintensity (n¼623 points). The X–X# line in (B) is the profile analysis
line used for the plot in panel (C). Scale bar¼40 lm.

the fluorescence at 680 nm is attributed to reflection of thefluorescence from chloroplasts in cell layers near to thethe leaf surface. By contrast, the fluorescence over 695 nm
reflects that from deeper cell layers, because the fluorescence over 695 nm is not absorbed as much as that at
680 nm. However, cells without overlying cells are notalways located near the abaxial leaf surface. In cancellous
structures such as spongy tissue, for example, the fluorescence from internal cells may be not absorbed as expected. The 3-D images reconstructed from a series of
focal plane images permit the position of internal cells tobe estimated more directly.
Before ozone exposure, the chlorophyll fluorescencevalues were non-uniformly distributed over the field ofview. If this result is attributed to the cells being found at
depths where chlorophyll fluorescence was not detected,
the UPSII value would be zero. However, as the UPSII
value of the extended-focus 3-D images were uniform at
0.43–0.51 (Fig. 4B), the non-uniform distribution of chlorophyll fluorescence was due to variability in chlorophyll
fluorescence intensity of the chloroplasts into the cells.
The uniform distribution of the UPSII values indicates3-D chlorophyll ﬂuorescence imaging of ozone-injured leaves 771

the function of the chloroplasts in the injured cell is
reduced. This would be consistent with the dysfunctionof guard-cell plasmalemmae caused by ozone invasion(Castillo and Heath, 1990; Torsethaugen et al., 1999).
No relationship was found between UPSII value and thedepth of cells below the leaf surface. This result indicatesthat ozone invasion of the leaf caused a decrease influorescence intensity in the perturbed cells, but it did notcause a decrease in the quantum efficiency of electron
flux through PSII at steady-state.
In summary, the passive light microscope systemdeveloped for this study allowed us to quantify the depthof cells in spongy tissue based on reconstructed 3-Dimages. Our findings indicate the importance of distancefrom the leaf surface with regard to ozone-injury. This 3D imaging system can thus be a very effective tool for
analysing the photosynthetic activity of uneven leaf cells,
especially when focus depth is restricted by the use of ahigh-magnification lens.

Acknowledgements
We thank K Takayama (Ehime University) and A Konishi (The
University of Tokyo) for helpful discussions and comments on
the manuscript. This study was funded by the Japan Society for the
Promotion of Science (no. 03J11319).

Fig. 7. (A) Reflection image and (B) fluorescence intensity (F) imageof the mesophyll cells shown in Fig. 5. The dashed white circles lines in(A) and (B) represent the position of a stomate confirmed from thereflection image. The black dotted line in (B) encloses an area in which
fluorescence intensity decreased strongly. Scale bar¼40 lm.

that, within the field of view, each chloroplast has the same
quantum efficiency of electron flux through PSII photochemistry.
The change in the distribution of chlorophyll fluorescence after exposure to 300 ppb ozone indicated theinhibition of photosynthesis that had been caused. Furthermore, the sites where the fluorescence intensity decreased were located close to the abaxial leaf surface andwere not related to the positions of the stoma, a finding
also reported by Leipner et al. (2001). Such a phenomenon
may occur as a result of ozone diffusion through gaps inthe cuticle, or ozone may diffuse rapidly once entering the
spongy tissue via open stomata through the air spaces.
Ozone exposure appears to increase the vulnerability ofthe mesophyll cells within sunflower leaves, and thefunction of the chloroplasts subsequently decreases due
to light irradiation. Based on the fluorescence images, decreases in chlorophyll fluorescence were not seen inchloroplast units but were observed at the single cell level,
indicating that ozone first attacks mesophyll cells and thenReferences
Akimoto H. 2003. Global air quality and pollution. Science 302,
1716–1719.
Castillo FJ, Heath RL. 1990. Ca2+ transport in membrane vesicles
from pinto bean leaves and its alteration after ozone exposure.
Plant Physiology 94, 788–795.
Daley PF, Raschke K, Ball JT, Berry JA. 1989. Topography ofphotosynthetic activity of leaves obtained from video images ofchlorophyll fluorescence. Plant Physiology 90, 1233–1238.
Endo R, Omasa K. 2004. Chlorophyll fluorescence imaging ofindividual algal cells: effects of herbicide on Spirogyra distenta at
different growth stages. Environmental Science and Technology 38, 4165–4168.
Fowler D, Cape JN, Coyle M, Flechard C, Kuylenstierna J,
Hicks K, Derwent D, Johnson C, Stevenson D. 1999. The
global exposure of forest ecosystems to air pollutants. Water, Air,and Soil Pollution 116, 5–32.
Genty B, Briantais JM, Baker NR. 1989. The relationshipbetween the quantum yield of photosynthetic electron-transportand quenching of chlorophyll fluorescence. Biochimica et Biophysica Acta 990, 87–92.
Heath RL. 1980. Initial events in injury to plants by air pollutants.
Annual Review of Plant Physiology 31, 395–431.
Heath RL. 1987. The biochemistry of ozone attack on plasma
membrane of plant cells. Recent Advances in Phytochemistry 21,
29–54.
Heath RL. 1994. Possible mechanisms for inhibition of photosynthesis by ozone. Photosynthesis Research 39, 439–451.
Küpper H, Šetlı́k I, Trtı́lek M, Nedbal L. 2000. A microscope fortwo-dimensional measurements of in vivo chlorophyll fluorescence772 Endo and Omasa
kinetics using pulsed measuring radiation, continuous actinic
radiation, and saturating flashes. Photosynthetica 38, 553–570.
Laisk A, Kull O, Moldau H. 1989. Ozone concentration in leafintercellular air space is close to zero. Plant Physiology 90,
1163–1167.
Lawson T, Oxborough K, Morison JIL, Baker NR. 2002.
Responses of photosynthetic electron transport in stomatal guard
cells and mesophyll cells in intact leaves to light, CO2, andhumidity. Plant Physiology 128, 52–62.
Lelieveld J, Crutzen PJ. 1990. Influences of cloud photochemical
processes on tropospheric ozone. Nature 343, 227–232.
Leipner J, Oxborough K, Baker NR. 2001. Primary sites ofozone-induced perturbations of photosynthesis in leaves: identification and characterization in Phaseolus vulgaris using highresolution chlorophyll fluorescence imaging. Journal of Experimental Botany 52, 1689–1696.
Lichtenthaler HK, Miehé JA. 1997. Fluorescence imaging as adiagnostic tool for plant stress. Trends in Plant Science 2,
316–320.
Maxwell K, Johnson GN. 2000. Chlorophyll fluorescence:a practical guide. Journal of Experimental Botany 51, 659–668.
Nayar SK, Nakagawa Y. 1994. Shape from focus. IEEE Transactions on Pattern Analysis and Machine Intelligence 16,
824–831.
Oltmans SJ, Lefohn AS, Scheel HE, et al. 1998. Trends of ozone
in the troposphere. Geophysical Research Letters 25, 139–142.
Omasa K. 2000. 3-D color video microscopy of intact plants. In:
Häder DP, ed. Image analysis: methods and applications, 2ndedn. Boca Raton, FL: CRC Press, 257–273.
Omasa K, Hashimoto Y, Aiga I. 1981. A quantitative analysis of
the relationships between O3 sorption and its acute effects onplant leaves using image instrumentation. Environmental Control
in Biology 19, 85–92.
Omasa K, Shimazaki K, Aiga I, Larcher W, Onoe M. 1987.
Image analysis of chlorophyll fluorescence transients for di-agnosing the photosynthetic system of attached leaves. Plant
Physiology 84, 748–752.
Omasa K, Tobe K, Hosomi M, Kobayashi M. 2000. Absorptionof ozone and seven organic pollutants by Populus nigra andCamellia sasanqua. Environmental Science and Technology 34,
2498–2500.
Omasa K, Tobe K, Kondo T. 2002. Absorption of organic andinorganic air pollutants by plants In: Omasa K. In: Saji H,
Youssefian S, Kondo N, eds. Air pollution and plant biotechnology: prospects for phytomonitoring and phytoremediation. Tokyo: Springer-Verlag, 155–178.
Oxborough K, Baker NR. 1997. An instrument capable ofimaging chlorophyll a fluorescence from intact leaves at very
low irradiance and at cellular and subcellular levels of organization. Plant, Cell and Environment 20, 1473–1483.
Pell EJ, Eckhard N, Eniyedi AJ. 1992. Timing of ozone stressand resulting status of ribulose biphosphate carboxylase-oxygenase
and associated net photosynthesis. New Phytologist 120,
397–408.
Rolfe SA, Scholes JD. 2002. Extended depth-of-focus imagingof chlorophyll fluorescence from intact leaves. Photosynthesis
Research 72, 107–115.
Russ JC. 1998. The image processing handbook, 3rd edn. London:
CRC Press.
Sandermann H, Wellburn AR, Heath RL. 1997. Forest decline
and ozone. Berlin: Springer-Verlag.
Schraudner M, Langerbartels C, Sanderman H. 1997. Changes
in the biochemical status of plant cells induced by the environmental pollutant ozone. Physiologica Plantarum 100,274–280.
Torsethaugen G, Pell EJ, Assmann SM. 1999. Ozone inhibits
guard cell K+ channels implicated in stomatal opening. Proceedings of the National Academy of Sciences, USA 96, 13577–13582.
Yunus M, Iqbal M. 1996. Plant response to air pollution. New
York: John Wiley & Sons.