Special Issue – Regular Paper
Potential Errors in Electron Transport Rates Calculated
from Chlorophyll Fluorescence as Revealed by a
Multilayer Leaf Model
John R. Evans
Research School of Biological Sciences, The Australian National University, Canberra, Australian Capital Territory 2601, Australia
Increasingly, photosynthetic electron transport rate is
being calculated from chlorophyll fluorescence measurements. The fluorescence signal is a complex mixture of
contributions from different depths within the mesophyll.
One condition required for electron transport calculated
from fluorescence to represent the rate accurately is that
the ratio of photosynthetic capacity to light absorbed be
constant throughout the leaf. In order to explore the
fluorescence properties of leaves where this assumption is
not true, a new approximation for φPSII is used to generate
Fm′ and Fs values throughout the leaf. Fs is assumed to be
proportional to the amount of light absorbed from the
fluorescence measuring beam and constant, i.e. independent of the actinic irradiance or CO2 concentration.
This assumption is validated by measurements from
Eucalyptus maculata, Flaveria bidentis and Triticum
aestivum, with two different types of fluorometer, where
irradiance or CO2 response curves were measured with
normal or inverted leaf orientations. The new approach
enables fluorescence values to be generated at each layer in
a multilayer model. Two applications using this approach
are presented. First, the model is used to show that when
quantum yield varies through a leaf, then fluorescence will
lead to an incorrect estimate of electron transport rate.
Secondly, since chlorophyll fluorescence is also used to
calculate the CO2 concentration at the sites of carboxylation within chloroplasts, Cc , the model is also used to show
that Cc may vary with depth. Significant variation in Cc
through the mesophyll could lead to an apparent
dependence of internal conductance on irradiance or CO2.
Keywords: Chloroplast • Internal conductance • Leaf
anatomy • Light profiles • Mesophyll conductance •
Rubisco.
Introduction
Chlorophyll fluorescence is a powerful and versatile technique. The information gained from fluorescence depends
on how the light is applied and how the fluorescence is captured. One of the most common applications is to use fluorescence signals to calculate the photosynthetic electron
transport rate. This requires two fluorescence parameters to
be measured, the first under actinic light and the second
during a pulse of bright light that closes PSII. To calculate the
electron transport rate, values for the fraction of incident
light that is absorbed by the leaf, α, and the proportion of
that light absorbed by PSII, β, are needed. The two fluorescence parameters are used to calculate the photochemical
efficiency of PSII, φPSII, which has been shown to be linearly
related to quantum yields measured by gas exchange (Genty
et al. 1989). By imaging fluorescence, it is possible to resolve
photochemical efficiency spatially (Genty and Meyer 1995),
even to the level of individual chloroplasts (Lawson et al.
2002). However, resolving the profile of photochemical efficiency through leaves has yet to be achieved. Fluorescence
has also been used to measure the profile of light absorption
through leaves (Takahashi et al. 1994, Koizumi et al. 1998,
Vogelmann and Han, 2000, Vogelmann and Evans, 2002) and
the distribution of chlorophyll through leaves (Vogelmann
and Evans 2002, Evans and Vogelmann 2006).
At room temperature, chlorophyll fluorescence predominantly originates from PSII. In C4 leaves, the contribution
from PSI may be sufficiently great that it cannot be ignored
(Siebke et al. 1997, Pfundel 1998, Kramer et al. 2004). At
room temperature, chlorophyll fluorescence from a leaf has
emission peaks at 686 and 740 nm. Fluorescence > 715 nm is
usually measured, first to separate it from actinic light and,
secondly, because chlorophyll absorbs strongly at 680 nm,
Corresponding author: E-mail, [email protected]; Fax, +61-2-61254919.
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041, available online at www.pcp.oxfordjournals.org
© The Author 2009. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.
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698
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041 © The Author 2009.
Exploring fluorescence with a multilayer leaf model
fluorescence <700 nm will mainly consist of signal from
chloroplasts near the illuminated surface rather than properly representing the complete mesophyll. Leaf absorptance
declines rapidly from about 0.92 at 680 nm to 0.52 at 710 nm
and to 0.14 at 735 nm. Thus, at wavelengths > 715 nm, the
fluorescence emerging from a leaf originates not only from
near the surface but also from deep within the mesophyll.
The actual profile of fluorescence emission through a leaf
depends on the wavelength used to probe fluorescence. As
this may differ from the spectral quality of the actinic light,
there is potential for a mismatch to occur between the
absorption profile of the actinic and chlorophyll fluorescence measuring lights.
The fluorescence that emerges from a leaf is the cumulative sum of the contributions from chloroplasts scattered
throughout the mesophyll. It is known that the properties of
chloroplasts differ, depending on their light environment.
Chloroplasts near to the surface receiving light have greater
Chl a/b ratios, and greater cytochrome f and Rubisco contents per unit chlorophyll (Terashima and Inoue 1985b). The
diversity in chloroplast properties has the potential to result
in a complex fluorescence signal that does not simply relate
to whole-leaf photosynthesis. In fact, the strong linear relationships between photochemical efficiency and quantum
yield can only occur if the ratio of photosynthetic capacity
to light absorbed is the same for all chloroplasts in a leaf.
Another application of chlorophyll fluorescence is for
estimating the CO2 partial pressure at the sites of carboxylation within chloroplasts (Harley et al. 1992). This leads to the
estimation of internal conductance which is defined as
gi = A/(Ci – Cc), where A is the rate of CO2 assimilation, and Ci
and Cc are the CO2 concentrations in the intercellular airspaces and at the sites of carboxylation, respectively. Internal
conductance calculated from fluorescence was found to
decline for a range of species as Ci increased (Flexas et al.
2007) or as irradiance decreased (Flexas et al. 2007, Hassiotou
et al. 2008). Internal conductance calculated from a combination of carbon isotope discrimination and gas exchange
also declined with increasing Ci in Nicotiana tabacum (Flexas
et al. 2007). However, using the isotope discrimination
method, internal conductance was found to be independent
of both Ci and irradiance in Triticum aestivum (Tazoe et al.
2009). The difference between the true and observed internal conductance depends on the profiles of light absorption,
photosynthetic capacity and internal conductance (Lloyd
et al. 1992). Therefore, since the fluorescence and isotopic
methods weight the sampling through the mesophyll differently, this could possibly explain the difference between
these reports.
The objective of this study is to use a multilayer model of
photosynthesis to examine the fluorescence properties that
emerge for a whole leaf. This model developed from the
approach of Terashima and Saeki (1985) and has been
parameterized for spinach leaves (Evans and Vogelmann
2003) with profiles of light absorption and photosynthetic
capacity, Pmax. However, to calculate whole-leaf photochemical efficiency in the absence of data at the chloroplast level,
a new approximation is first introduced and validated. The
impact of the interaction between the profiles of light
absorption and Pmax is demonstrated by measuring normal
and inverted leaves.
Results
Despite the absence of data resolving fluorescence at the
intraleaf level, it is possible to simulate the emergent properties of a leaf by making some reasonable assumptions. The
first assumption is that as photochemical efficiency varies
due to changing irradiance or CO2 concentration, this is
mainly due to changes in Fm′. In contrast, Fs stays fairly constant (Fig. 1). This is evident for a range of species, both C3
and C4. It is also independent of leaf orientation, i.e. whether
light is applied to and fluorescence measured from the
adaxial surface or whether the leaf is inverted during the
measurement (Fig. 1A, C). When the CO2 concentration is
altered, the changes are also evident in Fm′ rather than Fs
(Fig. 1E), although the changes are smaller because CO2
varied the rate of electron transport less than irradiance.
Consequently, if one calculates photochemical efficiency as
φ′ = 1 – c/Fm′, where c is a constant for a given leaf and orientation, then φ′ is a good approximation to φPSII (Fig. 1B, D, F).
The conventional use of φPSII relies on the assumption
that the ratio of Pmax to light absorption is independent of
depth from the leaf surface. This assumption breaks down if
the color of light is changed or the leaf is inverted. Gas
exchange was measured concurrently with fluorescence for
two of the examples shown in Fig. 1. The rate of electron
transport calculated from φPSII ( Jf) or φ′ ( Jφ) is compared
with the rate of CO2 assimilation (A) (Fig. 2). For Flaveria
measured in the correct orientation, Jf was linearly related
to A. The slope of the regression was 6.3 mol e– (mol CO2)–1.
The rate of electron transport calculated assuming a constant Fs (Jφ) followed Jf closely except for the two highest
irradiances. In contrast, both Jf and Jφ were overestimated for
the inverted leaf. However, Jφ was remarkably similar to Jf
over the entire range of irradiance for the inverted leaf.
For Triticum measured under varying CO2 concentrations,
Jφ followed Jf, but the agreement was not as close as that
observed when irradiance varied. These examples demonstrate that, to a first approximation, it is reasonable to
assume a constant Fs that is independent of φPSII. Consequently, Equations 5 and 6 in the Materials and Methods can
be used to generate values for Fs,j and Fm,j′ for each layer in
the model leaf.
The multilayer model based on spinach was used to
explore the fluorescence properties of the leaf. The absorption
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041 © The Author 2009.
699
J. R. Evans
Eucalyptus maculata
0.8
A
B
adaxial Fm′
adaxial Fs
abaxial Fm′
abaxial Fs
100
0.6
0.4
φ′
Fluorescence
150
50
0
adaxial
abaxial
0.2
0
500
1000
1500
2000
2500
0.0
0.0
0.2
0.4
φPSII
Irradiance (µmol quanta m–2 s–1)
0.6
0.8
Flaveria bidentis
0.8
C
D
adaxial Fm′
adaxial Fs
abaxial Fm′
abaxial Fs
1000
0.6
φ′
Fluorescence
1500
500
0
0.4
adaxial
abaxial
0.2
0
500
1000
1500
0.0
0.0
2000
0.2
0.4
Irradiance (µmol quanta m–2 s–1)
0.6
0.8
φPSII
Triticum aestivum
1000
0.3
E
F
0.2
600
φ′
Fluorescence
800
400
Fm
Fs
200
0
0
100
200
300
400
500
600
0.1
0.0
0.0
Intercellular CO2 (µmol mol–1)
profiles for blue and green light incident on a leaf are shown
for both normal (adaxial) and inverted (abaxial) leaf orientations (Fig. 3). Due to the large extinction coefficient of the
pigments in a leaf at around 450 nm, blue light is strongly
absorbed near the surface. For a normally oriented leaf, 70%
of blue light is absorbed in the first third of the mesophyll.
Since green light is absorbed less strongly, it penetrates
deeper into the mesophyll and only 42% of the green light is
absorbed in the first third of the mesophyll. The observed
profile of Pmax is similar to that for green light absorption
700
0.1
0.2
φPSII
0.3
Fig. 1 Response of Fm′ and Fs to changes
in irradiance or intercellular CO 2
concentration. Eucalyptus maculata (A,
B), Flaveria bidentis (C, D), Triticum
aestivum (E, F). Raw data shown in A, C
and D with derived φ′ shown against
φPSII in B, D and F. φ′ = 1 – c/Fm′ , where
c was 38 or 29 for adaxial and abaxial
Eucalyptus, 600 or 450 for adaxial and
abaxial Flaveria and 640 for Triticum,
respectively.
except that it increases again slightly near the abaxial surface. For the simulations presented here, fluorescence
parameters at each layer were calculated using the same
wavelengths for both the actinic and fluorescence measuring
light. The fluorescence values summed from each layer were
used to calculate φPSIIL and then the electron transport
rate, Jφ. This rate was compared with the ‘true’ rate of electron transport, JM, for different wavelengths of light and leaf
orientations (Fig. 4). There was close agreement between JM
and Jφ when the leaf was measured under green light with
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041 © The Author 2009.
Exploring fluorescence with a multilayer leaf model
Electron transport rate (µmol m–2 s–1)
300
200
300
A
Flaveria
Jf abax
Jφ abax
Jf adax
Jφ adax
B
Triticum
Jf
Jφ
200
100
100
0
0
10
20
30
0
0
10
Rate of CO2 assimilation (µmol
20
30
40
m–2 s–1)
0.25
400
adaxial B
adaxial G
Pmax
abaxial B
abaxial G
0.20
abaxial B
adaxial B
abaxial G
adaxial G
300
Jφ (µmol m–2 s–1)
Fraction of light absorbed or Pmax in the layer
Fig. 2 Electron transport rates calculated from chlorophyll fluorescence in relation to the measured CO2 assimilation rates. Flaveria bidentis
leaves measured with varying irradiance applied to the adaxial (red) or abaxial (black) surface (A). Triticum aestivum leaves measured with
varying intercellular CO2 concentrations (B). The electron transport rate was calculated using either φPSII ( Jf) or φ′ ( Jφ) using the fluorescence
data shown in Fig. 1. For Flaveria, α and β were assumed to be 0.9 and 0.5, respectively and the linear regression between Jf and A with adaxial
light was: Jf = 4.2 (± 2.6) + 6.3 (± 0.2) A, r2 = 0.99.
0.15
200
0.10
100
0.05
0.00
0
100
200
300
400
Depth (µm)
500
600
700
0
0
50
100
150
Rate of electron transport, Jm (µmol
200
m–2 s–1)
Fig. 3 Profiles of light absorption and Pmax through the leaf used in the
multilayer leaf model. Profiles are based on the data collected from
spinach (Vogelmann and Evans 2002, Evans and Vogelmann 2003).
The light absorption profiles depend on leaf orientation because
chlorophyll is not uniformly distributed through the mesophyll and
because the optical properties of palisade and spongy tissues differ.
A value for Pmax of 200 µmol m–2 s–1 was assumed for the leaf.
Fig. 4 Modeled relationship between the electron transport rate
calculated from the sum of fluorescence emitted at each layer, Jφ , and
the ‘true’ electron transport rate, JM, with blue or green light applied to
the adaxial or abaxial surface.
the correct orientation. This was expected because this condition almost satisfies the assumption that the ratio of Pmax
to light absorbed is the same for each layer. However, for the
other simulations, the two rates deviate progressively from
each other as irradiance increases. When blue light applied
to the adaxial surface, or green light to the abaxial surface,
was modeled, the electron transport rate calculated from
chlorophyll fluorescence overestimated the ‘true’ rate JM by
60% at high irradiance. The modeled response clearly resembled that observed for an inverted leaf (Fig. 2A), which again
supports the assumption that Fs,j = cIj (Equation 5). The
discrepancy between Jφ and JM was even greater when blue
light was applied to the abaxial surface (Fig. 4).
Throughout this paper, it is assumed that the proportion
of light absorbed by PSII, β, is 0.5, regardless of the color of
the actinic or measuring light (which are the same in the
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041 © The Author 2009.
701
J. R. Evans
1.0
A
B
Relative drawdown (Ci – Cc)
0.5
Quantum yield
0.4
0.3
50
100
200
500
1000
1500
0.2
0.1
0.0
0
100
200
300
400
500
600
0.8
0.6
0.4
0.2
0.0
700
0
100
200
300
400
500
600
700
1.0
C
D
Relative drawdown (Ci – Cc)
0.5
Quantum yield
0.4
0.3
0.2
0.1
0.0
0
100
200
300
400
500
600
700
0.8
0.6
0.4
0.2
0.0
Depth (µm)
0
100
200
300
400
500
600
700
Depth (µm)
Fig. 5 Modeled profiles of quantum yield (A, C) or relative drawdown, Ci – Cc (B, D) through a leaf under blue (A, B) or green (C, D) light applied
to the adaxial surface, using the profiles of light absorption and Pmax given in Fig. 3.
simulations presented here) and regardless of the depth in
the leaf. It is conceivable that β could vary with depth,
although attempts to calculate this suggest that the difference between sun and shade chloroplasts is small (Evans
1988). The color of light, however, could be expected to alter
β as this has been put forward as one explanation of the
response of quantum yield to wavelength (Evans 1987). The
multilayer model could be used to investigate these assumptions, as any changes in β would apply to both electron
transport and fluorescence via Equation 1.
A sense of the underlying optical issue can be gained from
the profiles of quantum yield through the leaf. When blue
light applied to the adaxial surface is modeled, quantum
yield is reduced close to the adaxial surface, but is relatively
unchanged deep within the mesophyll (Fig. 5A). As irradiance
702
increases, quantum yields are progressively reduced deeper
into the mesophyll. However, even at high blue irradiance,
quantum yield varies almost linearly with depth. In contrast,
when green light applied to the adaxial surface is modeled,
there is an almost uniform reduction in quantum yield that
it is virtually independent of depth (Fig. 5C). Consequently,
the fluorescence signal, which is the sum of contributions
from a range of depths, depends strongly on the relationship
between the profiles of light absorption and Pmax through
the mesophyll. Although the profile of internal conductance
through a leaf is unknown, if one assumes that it scales with
Pmax, then the profile of the relative drawdown from Ci to Cc
can be calculated (Fig. 5B, D). The profiles resemble that for
quantum yield, but are not the same because they also
reflect the profile of Pmax. When blue light applied to the
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041 © The Author 2009.
Exploring fluorescence with a multilayer leaf model
adaxial surface is modeled, relative Ci – Cc is greatest near the
adaxial surface and decreases almost to zero at the abaxial
surface. However, when green light applied to the adaxial
surface is modeled, relative Ci – Cc is almost independent of
depth. At the leaf level, variation in Ci – Cc with depth would
result in an apparent increase in internal conductance with
increasing irradiance.
Discussion
It is remarkable that measurement of chlorophyll fluorescence from a leaf can give quantitatively accurate values of
photochemical efficiency without any need for calibration.
This occurs because φPSII is calculated from the ratio of two
fluorescence parameters, which makes it independent of the
absolute value for incident irradiance, leaf absorptance and
photon distribution between PSII and PSI. Of course, to validate this claim, it is necessary to compare φPSII with an independent estimate, usually obtained from gas exchange. The
comparison then needs accurate knowledge of the light
parameters and either the CO2 assimilation or oxygen evolution rates. At the time φPSII was proposed, a value for
φPSII/φCO2 of 15 was measured on maize leaves (Genty et al.
1989) which converts to 6.4 mol e– (mol CO2)–1, assuming
values for α and β of 0.85 and 0.5, respectively. Similar values
for J/A have been reported for Flaveria bidentis, 6.5 (Siebke
et al. 1997) and 6.7 (Dwyer et al. 2007), and the value obtained
here [6.3 ± 0.2 mol e– (mol CO2)–1, Fig. 2A] agrees with these
values.
Concealed within the fluorescence measurement is the
requirement that the ratio of Pmax to light absorbed is the
same for all chloroplasts within the leaf. Because this condition appears to be met under many conditions, it tends to
be forgotten. Alternatively, it is possible to correct for the
error by calibrating Jf against CO2 assimilation measured
under non-photorespiratory conditions. It is easy to demonstrate what happens when the ratio of Pmax to light absorbed
varies by comparing measurements from a normal and
inverted leaf (Fig. 2A), or when fluorescence is measured
with a blue light and white light is used for the actinic source.
Unraveling the basis for this from the deceptively simple
fluorescence parameters is not trivial. The major hurdle is
the scarcity of data on the profiles of light absorption and
Pmax through leaves, and the complete absence of profiles of
fluorescence parameters through a leaf. A new approach is
proposed that allows Fs and Fm′ to be calculated from Ij and
Pmax,j.
Profiles of light absorption
In principle, the profile of light absorption can be derived
from quantitative analysis of fluorescence images of transverse views of mesophyll tissue collected while light is applied
to the adaxial or abaxial surface. This method was first
demonstrated using a laser light source with a rice leaf (Takahashi et al. 1994) and was then applied to leaves of Rhizophora mucronata and Camellia japonica (Koizumi et al.
1998). Vogelmann and Han (2000) adapted the technique to
allow the whole leaf sample to be exposed to the light and
showed that the profile of light absorption through a spinach
leaf changed depending on the wavelength of the light. For
spinach leaves, analysis of the profiles of light absorption and
chlorophyll content inferred from multiple chlorophyll fluorescence images suggested that light absorption was influenced by both the extinction coefficient and path lengthening
(Vogelmann and Evans 2002). This had previously been
shown for C. japonica leaves that were paradermally sectioned (Terashima and Saeki 1983). However, some leaves
are optically complex due to the presence of oil glands, such
as in Eucalyptus pauciflora (Evans and Vogelmann 2006), or
the presence of Kranz anatomy (Evans et al. 2007) or bundle
sheath extensions (Karabourniotis et al. 2000). For these
leaves, obtaining the profile of light absorption is more
difficult.
The light absorption profiles used here were derived from
spinach leaves (Vogelmann and Evans 2002, Evans and
Vogelmann 2003). Blue and green light were analyzed as
these represent the two extremes. Red or white light would
be expected to be intermediate between them (Vogelmann
and Han 2000, Vogelmann and Evans 2002). To model a leaf
fully, the absorption profile of both the actinic and fluorescence measuring light need to be known. The wavelength of
modulated light used to measure chlorophyll fluorescence
differs between instruments.
Profile of Pmax
Biochemical analysis of paradermal sections from palisade or
spongy mesophyll demonstrated that chloroplasts acclimate
to their local light environment (Terashima and Inoue 1985a,
Terashima and Inoue 1985b). Coordinated changes to thylakoid components (cytochrome f, coupling factor), electron
transport capacities and Rubisco content were found. Subsequently, detailed profiles of Rubisco through spinach
leaves have been measured (Nishio et al. 1993) or inferred
from 14C labeling (Evans and Vogelmann 2003). Since the
profiles for electron transport capacity, Jmax, and Rubisco
activity, Vcmax, are likely to be similar, the term Pmax has been
used here rather than Jmax or Vcmax as used in the C3 photosynthesis model (Farquhar et al. 1980, von Caemmerer 2000).
A profile for Pmax was also derived for isobilateral E. pauciflora leaves (Evans and Vogelmann 2006). With only two
profiles of Pmax available, there is a clear need for more work
to be done. To some extent, the lack of data is a reflection of
the difficulty in making the measurements. An alternative
approach is to use chlorophyll fluorescence. Potentially this
offers a simpler method with excellent spatial resolution.
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J. R. Evans
At present we are limited by the ability to capture the weak
fluorescence using realistic irradiances and exposure times
of <1 s. However, improved sensitivity of CCD cameras
should enable these measurements in the future such that
Pmax could be derived from irradiance response curves of
φPSII. In this case, Fs,j would be used to measure Ij which
would enable Equation 2 to be fitted to φPSII collected at
different irradiances.
Implications for internal conductance
At the leaf level, internal conductance is closely related to
the surface area of chloroplasts exposed to intercellular airspace per unit leaf area (Evans et al. 1994). A rough assessment of how chloroplast surface area varied with depth was
made for N. tabacum and revealed a 2-fold variation that
peaked deep within the palisade layer and that was relatively
similar to the profile of Rubisco through a spinach leaf (Evans
1998). An alternative to analyzing transverse sections is to
use oblique paradermal sections. James et al. (1999) applied
this method to Eucalyptus globulus leaves to compare the
dorsiventral juvenile leaves with the isobilateral adult leaves.
However, at present, there is no species for which profiles of
both Rubisco and mesophyll surface area are known. Therefore, in order to model profiles of CO2 drawdown, it was necessary to make the assumption that the ratio of Rubisco to
exposed chloroplast surface area was constant and independent of depth. This assumption could be checked by measuring the profile of chloroplast thickness since chloroplast
volume is closely correlated with Rubisco content at the leaf
level. A constant ratio of Rubisco to chloroplast surface area
should mean that chloroplast thickness is independent of
depth, which could be assessed using confocal microscopy.
The assumption that exposed chloroplast surface area
and Rubisco co-vary through the leaf means that the internal conductance for a layer is directly proportional to Pmax
for that layer. Consequently, the drawdown Ci – Cc will scale
with Jj/Pmax,j. The drawdown profiles differed greatly in green
vs. blue light (Fig. 5B, D). When the profile of light absorption matched the profile of Pmax, as in green light, then Ci – Cc
was nearly independent of depth. Under blue light where
the two profiles differed considerably, the drawdown Ci – Cc
decreased dramatically through the leaf. The value for internal conductance in this case would depend on the weighting
placed on each layer. The calculation of internal conductance would be in error for the same reason that the
calculated rate of electron transport was overestimated
(Fig. 4). With the number of assumptions that have been
made, it is not yet feasible to quantify the effect. However,
the analysis indicates that internal conductance would
appear to increase as irradiance increased in the blue light
scenario. This is because as blue irradiance increases, it penetrates deeper into the mesophyll and additional chloroplasts are progressively engaged and contribute their internal
704
conductance. In contrast, in green light, the balance between
the contributions from various chloroplasts is independent
of irradiance.
The current model is driven by profiles in Pmax and
absorbed irradiance. However, as CO2 concentrations are
reduced, at some point the limitation changes from electron
transport to Rubisco. Since the drawdown Ci – Cc depends
on the rate of CO2 assimilation, an iterative solution would
need to be used to solve the model. It is evident that under
blue light, electron transport could be constrained by low
CO2 to a greater extent in the palisade compared with the
spongy tissue. In turn, this would impact on the Fm′ values
which would alter φPSIIL and hence the estimate of Cc. Therefore, it is conceivable that internal conductance calculated
from φPSII could depend on Ci. In this case, φPSIIL would be
influenced by the mismatch between the profiles of light
absorption and Pmax, and additionally by the further reduction in electron transport rate by low CO2 concentrations.
The finding that internal conductance calculated from φPSII
decreases as Ci increases (Flexas et al. 2007) is appealing
because of the growing evidence supporting the role of
cooporins in determining membrane permeability to CO2
(Terashima et al. 2006, Uehlein et al. 2008). However, there
is conflicting evidence on whether internal conductance
decreases with increasing Ci when internal conductance is
calculated from carbon isotope discrimination (Flexas et al.
2007, Tazoe et al. 2009). Considering that fluorescence signals correctly represent the complex sum of many sources
only when the ratio of Pmax to absorbed light is constant
throughout the leaf, it seems possible that the variation in
internal conductance calculated from φPSII as either irradiance or CO2 varies could be an artifact.
Materials and Methods
Chlorophyll fluorescence was measured with two PAM 101
fluorometers (H Walz, Effeltrich, Germany) positioned on
opposite sides of a bifacial Eucalyptus maculata leaf (Ögren
and Evans 1993). For the other species, combined fluorescence and gas exchange measurements were made with a
6400-40 LCF (LICOR, Lincoln, NE, USA). Both of these instruments use modulated red light to measure fluorescence. For
the LCF, Fm′ was calculated using the multiple intensity flash
routine, and the actinic light was 90% red and 10% blue.
With F. bidentis, an NADP malic enzyme C4 dicot, irradiance
response curves were measured in 400 µmol mol–1 ambient
CO2, with the leaf in the normal orientation and then
repeated with the leaf inverted, such that the actinic and
fluorescence measuring lights were applied to and fluorescence measured from the abaxial surface. For T. aestivum,
the responses of fluorescence and gas exchange to Ci were
measured by varying ambient CO2 concentration, with
an irradiance of 1,500 µmol PAR quanta m–2 s–1. In all cases,
Plant Cell Physiol. 50(4): 698–706 (2009) doi:10.1093/pcp/pcp041 © The Author 2009.
Exploring fluorescence with a multilayer leaf model
the air contained 21% oxygen and leaf temperature was
23 ± 1°C.
The multilayer model that has been parameterized for
spinach (Evans and Vogelmann 2003) was used to calculate
apparent photochemical efficiency. The model was also used
to explore the profile of quantum yield and drawdown
between Ci and Cc. The model consists of 17 paradermal
layers, each 40 µm thick, for which the fraction of light
absorbed, aj, and Pmax,j for each layer is defined. The light
absorbed by PSII in layer j, Ij is
(1)
where I is the incident irradiance, α is the leaf absorptance, β is the fraction of light absorbed by PSII and aj is the
fraction of light absorbed in layer j. The rate of electron
transport for layer j is calculated as
(2)
where θ is assumed to be 0.85. The modeled rate of electron transport for the leaf, JM, is the sum of Jj for all of the
layers. The photochemical efficiency of layer j, φPSIIj, is
therefore
(3)
The fluorescence intensity depends on the irradiance
absorbed by the chloroplast and the photochemical efficiency. At the leaf level, φPSII is calculated from the fluorescence under actinic light, Fs, and that under a saturating
pulse, Fm′ (Genty et al. 1989)
(4)
To construct fluorescence emission from a leaf, one therefore needs to know both Fs and Fm′ at each layer. As this
information is lacking, we need to calculate them. This is
possible from φPSII and the fraction of light absorbed at each
layer, if we assume as an approximation that
(5)
where c is a constant. Then Fm′ for layer j, Fm,j′ , can be calculated from Equations 1, 4 and 5 as
(6)
The apparent photochemical efficiency for the leaf, φPSIIL,
can then be calculated using the sum of the values for both
Fs,j and Fm,j′
(7)
The rate of electron transport for a leaf, Jf, is normally calculated as
(8)
so we define the apparent rate of electron transport, Jφ,
calculated from the apparent photochemical efficiency as
(9)
In this paper, it is assumed that fluorescence is not
absorbed within the leaf because fluorescence was measured
at wavelengths >715 nm.
To calculate the relative drawdown Ci – Cc for each layer,
it was assumed that the surface area of chloroplasts exposed
to intercellular airspace per unit leaf area for each layer was
proportional to Pmax for that layer which means that gi,j is
proportional to Pmax,j and
(10)
Acknowledgments
This work draws together strands that have involved the
work or discussions with Tom Vogelmann, Susanne von
Caemmerer, Marilyn Ball, Foteini Hassiotou and Stephanie
McCaffery.
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(Received December 18, 2008; Accepted March 5, 2009)