Tree Physiology 23, 289–300
© 2003 Heron Publishing—Victoria, Canada
A biochemical model of photosynthesis for mango leaves: evidence for
the effect of fruit on photosynthetic capacity of nearby leaves
L. URBAN,1,2 X. LE ROUX,3,4 H. SINOQUET,3 S. JAFFUEL5 and M. JANNOYER1
1
INRA/CIRAD-Flhor, Station de Bassin-Martin, BP 180, 97455 Saint-Pierre, France
2
Author to whom correspondence should be addressed ([email protected])
3
U.M.R. PIAF (INRA-Université Blaise Pascal), Domaine de Crouelle, 63039 Clermont-Ferrand Cedex 02, France
4
Present address: U.M.R. 5557 Ecologie Microbienne (CNRS-Université Lyon 1), bat. 741, 43 boulevard du 11 novembre 1918, 69622 Villeurbanne,
France
5
CIRAD-Amis, Botanique et Bioinformatique de l’Architecture des Plantes, TA40/PSII, 2196 boulevard de la Lironde, 34398 Montpellier Cedex 5,
France
Received April 15, 2002; accepted August 25, 2002; published online March 3, 2003
Summary Variations in leaf nitrogen concentration per unit
mass (Nm ) and per unit area (Na ), mass-to-area ratio (Ma ), total
nonstructural carbohydrates (Ta ), and photosynthetic capacity
(maximum carboxylation rate, electron transport capacity, rate
of phosphate release in triose phosphate utilization and dark
respiration rate) were studied within the digitized crowns of
two 3-year-old mango trees (Mangifera indica L.) on La
Réunion Island. Additional measurements of Nm, Na, Ma, Ta and
photosynthetic capacities were performed on young, fully expanded leaves of 11-year-old mango trees. Leaves of similar
gap fractions were taken far from and close to developing
fruits. Unlike Nm, both Na and Ta were linearly correlated to gap
fraction. Similar relationships were found for all leaves whatever their age and origin, except for Ta, for which we found a
significant tree effect. Photosynthetic capacity was nonlinearly correlated to Na, and a unique relationship was obtained for all types of leaves. Photosynthetic acclimation to
light was mainly driven by changes in Ma, but allocation of total leaf N between the different photosynthetic functions also
played a substantial role in acclimation to the lowest irradiances. Leaves close to developing fruits exhibited a higher photosynthetic capacity than other leaves, but similar Ta. Our data
suggest that Ta does not control photosynthetic capacity in
mango leaves. We used the data to parameterize a biochemically based model of photosynthesis and an empirical stomatal
conductance model, allowing accurate predictions of net photosynthesis of leaves in field-grown mango trees.
Keywords: leaf age, leaf irradiance, leaf nitrogen, Mangifera
indica, nonstructural carbohydrates, radiation transfer model.
Introduction
Biochemically based models of leaf photosynthesis are used
increasingly to compare photosynthetic performance among
plant species (Wullschleger 1993) and to analyze photosynthetic acclimation to high CO2 concentrations (Harley et al.
1992, Peterson et al. 1999) and growth irradiance (Niinemets
and Tenhunen 1997, Le Roux et al. 1999a, 2001a). Such models may also be coupled to radiation transfer models to simulate photosynthesis at the canopy level (Harley et al. 1985,
Harley and Tenhunen 1991, Harley and Baldocchi 1995, De
Pury and Farquhar 1997) or at the individual plant level (Le
Roux et al. 2001b, Sinoquet et al. 2001).
Applying biochemically based photosynthesis models at the
individual plant level requires representation of the intra-canopy distribution of leaf photosynthetic capacity (i.e., the maximum rate of carboxylation (Vcmax), the light-saturated rate of
electron transport (Jmax), the rate of phosphate release in triose
phosphate utilization (TPU) and the mitochondrial respiration
rate due to phosphorylative oxidations (Rd)). Because proteins
of the Calvin cycle and thylakoids represent the majority of
leaf nitrogen, photosynthetic capacity is strongly related to
leaf nitrogen on an area (Na ) or mass (Nm ) basis (Field and
Mooney 1986, Evans 1989a, Kellomäki and Wang 1997, Walcroft et al. 1997). Furthermore, for leaves of a given age and
for a given nitrogen supply, Na appears to be strongly related to
light exposure (DeJong and Doyle 1985, Le Roux et al. 1999b,
2001a, Rosati et al. 1999, 2000). Therefore, the intra-canopy
distribution of leaf photosynthetic capacity has generally been
taken into account by documenting (1) the relationships between leaf photosynthetic capacity and Na, and (2) the relationships between Na and the mean leaf irradiance experienced
locally within the canopy. Such an approach is based on the assumption that plants allocate nitrogen resources within the
canopy to enhance photosynthetic capacity in locations experiencing high irradiances, thereby maximizing whole-plant
carbon gain (Field 1983, Hollinger 1996, Carswell et al.
2000).
Modeling the distribution of photosynthetic carbon gain
within individual fruit trees has been suggested as a promising
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URBAN, LE ROUX, SINOQUET, JAFFUEL AND JANNOYER
tool to predict the intra-crown heterogeneity of fruit growth
(Grossman and DeJong 1994, Lescourret et al. 1998, Le Roux
et al. 2001b), which is of importance for fruit production quality (Génard et al. 1998). However, several studies have emphasized that leaf characteristics can be influenced by the
presence or proximity of developing fruits in tree crowns.
Lower leaf nitrogen concentrations have been observed in
fruiting peach trees than in non-fruiting peach trees (Taylor
and May 1967, Taylor and Van den Ende 1969) and citrus
(Lenz 2000). In contrast, leaf N concentration was higher in
fruiting apple trees than in non-fruiting apple trees (ThiebusKaesberg and Lenz 1994), whereas leaf mass-to-area ratio
(Ma ) and chlorophyll concentrations were higher in the leaves
of fruit-bearing shoots of olive trees (Proietti 2000). Decreases
in leaf N concentration during the fruit growth period could be
attributed to N dilution in growing leaves or to remobilization
of N from leaves to fruits (Rufat and DeJong 2001). The influence of developing fruits on leaf characteristics could also be
explained by differences in carbohydrate accumulation in
leaves resulting from local source–sink imbalances, because
carbohydrates can exert a feedback inhibition on leaf photosynthesis and leaf photosynthetic capacity (Foyer 1988). Little
is known about the effects of local source–sink balance and associated changes in carbon export rate from leaves and leaf total nonstructural carbohydrate (Ta ) concentration on photosynthetic capacity within the crowns of field-grown trees. This
lack of knowledge may restrict our ability to accurately predict
the spatial distribution of local carbon gain and fruit growth
within the canopies of fruit trees.
The objectives of this study were: (1) to quantify spatial
variations in leaf photosynthetic capacity (Na, Vcmax, Jmax and
Rd) with changes in irradiance in the crowns of mango
(Mangifera indica L.) trees growing with non-limiting N supply; (2) to test whether photosynthetic capacities measured at a
given irradiance are affected by leaf age and the proximity of
developing fruits, and whether leaf Ta accumulation can be
used as an indicator of a local source–sink imbalance; and (3)
to propose a model of photosynthesis for mango leaves that
can be applied to non-fruiting 3-year-old trees and to fruiting
11-year-old trees. The effect of fruit development was studied
in 11-year-old trees by comparing leaves with similar light access, but located far from and close to developing fruits.
Materials and methods
Plant material
Measurements were performed on leaves from mango trees,
cv. Lirfa, grafted on ‘Maison rouge,’ at two locations on La
Réunion Island (20°52′48″ S, 55°31′48″ E). We studied fruiting 11-year-old trees grown in an experimental orchard near
Saint-Pierre, and non-fruiting 3-year-old trees grown at a
commercial farm near Saint-Paul. The 11-year-old trees were
spaced at 5 m (within rows) × 7 m (between rows) and were
around 3 m high, with a north-east–south-west row orientation. Access to tree tops was provided by scaffolding. The
3-year-old trees were spaced at 6 m (within rows) × 6 m (be-
tween rows) and were about 1.5 m high, with a north-west–
south-east row orientation.
Water was supplied every second day on a 100% actual
evapotranspiration basis. Variations in stem diameter at SaintPierre were monitored with eight linear variable displacement
transducers (LVDT, Solartron, Bognor, U.K.). Maximal daytime shrinkage was less than 20 µm for 3- to 4-cm thick stems,
indicating that no water stress occurred during our trial (data
not shown). The 11-year-old trees received 350 g N tree –1
(urea), 70 g P tree –1 (superphosphate) and 350 g K tree –1 (potassium sulfate) on March 1, 2000 (after harvest), and 700 g N
tree –1 (urea), 70 g P tree –1 (superphosphate) and 350 g K tree –1
(potassium sulphate) on October 31, 2000 (at the beginning of
the fruit growing phase). Each 3-year-old tree received 210 g
urea, 210 g potassium sulfate and 210 g superphosphate in
July, 210 g urea and 210 g potassium sulfate in October, and
420 g urea and 420 g potassium sulfate in March. Insects and
diseases were controlled according to recommendations commonly accepted for mango orchards.
Photosynthesis model
Net CO2 assimilation rate (Anet; µmol CO2 m –2 s –1) in C3 plants
is a function of the carboxylation rate (Vc), the oxygenation
rate (Vo) and the rate of CO2 evolution in light that results from
processes other than photorespiration (Rd):
A net = Vc – 0.5Vo – Rd
(1)
According to a modified version (Harley et al. 1992) of the
model proposed by Farquhar et al. (1980), Anet can be expressed as:
A net = (1 – 0.5O /( τC i ))min(Wc , Wj , Wp ) – Rd
(2)
where O represents partial pressure of O2 in the intercellular
air spaces (Pa), τ is the specificity factor of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), Ci is the partial
pressure of CO2 in the intercellular air spaces (Pa), Wc is the
carboxylation rate limited by the amount, activation state or
kinetic properties of Rubisco (µmol CO2 m –2 s –1), Wj is the
carboxylation rate limited by the rate of ribulose bisphosphate
regeneration (µmol CO2 m –2 s –1) and Wp is the carboxylation
rate limited by triose phosphate utilization in sucrose and
starch synthesis (µmol CO2 m –2 s –1). The limitations on Wc can
be expressed as:
Wc = Vcmax C i /(C i + K c (1 + O /K o ))
(3)
where Vcmax represents maximum rate of carboxylation (µmol
CO2 m –2 s –1), and Kc (Pa CO2) and Ko (Pa O2) are the Michaelis constants of Rubisco carboxylation and oxygenation, respectively.
Parameter Wj is controlled by the rate of electron flow J
(µmol electrons m –2 s –1):
Wj = JC i /( 4 (C i + O/ τ ))
TREE PHYSIOLOGY VOLUME 23, 2003
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A PHOTOSYNTHESIS MODEL FOR MANGO
with
J = αQ /(1 + α 2Q 2 / J max )0. 5
(5)
where Q is photosynthetically active photon flux density
(µmol m –2 s –1), α is apparent efficiency of light energy conversion (mol electrons per mol photons) and Jmax is light-saturated rate of electron transport (µmol m –2 s –1). The limitations
on Wp can be expressed as:
Wp = 3TPU + Vo /2 = 3TPU + Vc 0. 5 Ci /(Ci τ )
(6)
where TPU is the rate of phosphate release in triose phosphate
utilization (starch and sucrose production).
The temperature dependency of Vcmax, Jmax and TPU is described by:
Parameter (Vcmax , Jmax , TPU ) =
180.7 mol electrons (mol cyt. f ) –1 at a leaf temperature of
30 °C as proposed by Niinemets and Tenhunen (1997). The
factor 6.25 (g Rubisco per g N in Rubisco) converts N content
to protein content, and the factor 8.06 (mmol cyt. f per g N in
bioenergetic pools) assumes a constant 1:1:1.2 molar ratio for
cyt. f:ferredoxin NADP reductase:coupling factor.
Parameters Vcmax, Jmax, TPU and Rd were derived from A–Ci
curves taken in January–February 2001 in 11-year-old trees
and March–April 2001 in 3-year-old trees (see below). Other
parameters were derived from Harley et al. (1992), with the
exception of c(τ), c(Kc), c(Ko), ∆Ha(τ), ∆Ha(Kc) and ∆Ha(Ko),
for which we preferred the parameters determined from in vitro leaf gas exchange measurements performed on a Rubiscoantisense line of tobacco (Nicotinia tabacum L. cv. W38) by
Bernacchi et al. (2001) (Table 1).
Stomatal conductance model
The stomatal conductance model of Leuning (1995) was used:
(7)
exp(c – ∆H a /( RTl ))
1 + exp(( ∆STl – ∆H d ) / RTl )
where c is a scaling factor, ∆Ha (J mol –1) is the activation energy of the given parameter, R is the gas constant (8.3143 J K –1
mol –1), Tl (K) is leaf temperature, ∆S (J mol –1) is an entropy
term and ∆Hd (J mol –1) is the deactivation energy of the given
parameter. Similarly, the temperature dependency of Rd, τ, Kc
and Ko is described by:
Parameter ( Rd , τ , K c , K o ) = exp (c – ∆H a /( RTl ))
c = a Nln( N a ) + bN
g s = g 0 + a1 A net /((C s – Γ * )(1 + Ds /D0 ))
(12)
where gs represents actual stomatal conductance (mol H2O
m –2 s –1), g0 is the stomatal conductance when Anet = 0, a1 and
D0 are empirical coefficients, Cs and Ds are the partial pressure
of CO2 in the air (Pa) and the humidity deficit at the leaf surface (Pa), respectively, and Γ* is the CO2 compensation point
(Pa) (Γ* = 0.5O/τ). The supply function, which is given by:
C i = Ca – A net /g b – A net /g s
(8)
To account for the relationship commonly observed between the parameters defining photosynthetic capacity and Na
(Field 1983, Leuning et al. 1991, Harley et al. 1992), scaling
factors c may be linearly related to ln(Na):
(13)
where Ca is the partial pressure of CO2 (Pa) in ambient air and
gb is the leaf boundary layer conductance, was used in addition
to Equations 2 and 12 to find an analytical solution for the coupled leaf photosynthesis–stomatal conductance model (see
(9a)
Table 1. Values and units of the parameters used in the photosynthesis
model for mango (Equations 1 to 9). All parameter values are derived
from Harley et al. (1992) and Bernacchi et al. (2001).
We also tested the following relationship (see Results):
c = a N N a–1 + bN
291
(9b)
The model proposed by Niinemets and Tenhunen (1997)
was applied to determine the coefficients for leaf nitrogen partitioning into carboxylation, Pc, and bioenergetic pools, Pb.
The computation of Pc (g N in Rubisco per g total leaf N) and
Pb (g N in cytochrome f, ferredoxin, NADP reductase and coupling factors, per g total leaf N) is given by:
Pc = Vcmax /(6.25Vcr Na )
(10)
Pb = Jmax /(8.06Jmc Na )
(11)
where Vcr is the specific activity of Rubisco (µmol CO2 g –1
Rubisco) and Jmc is the potential rate of photosynthetic electron transport per unit of cytochrome f (mol electrons (mol cyt.
f ) –1 s –1). We used Vcr = 31.9 µmol CO2 g –1 Rubisco and Jmc =
Parameter
Value
Units
Source
α
0.24
35.747
17.997
–7.458
80470
14510
79500
53100
116300
–37830
84450
201000
201800
202900
650
650
mol mol –1
dimensionless
dimensionless
dimensionless
J mol –1
J mol –1
J mol –1
J mol –1
J mol –1
J mol –1
J mol –1
J mol –1
J mol –1
J mol –1
J K –1 mol –1
J K –1 mol –1
Harley et al. (1992)
Bernacchi et al. (2001)
Bernacchi et al. (2001)
Bernacchi et al. (2001)
Bernacchi et al. (2001)
Bernacchi et al. (2001)
Harley et al. (1992)
Harley et al. (1992)
Harley et al. (1992)
Bernacchi et al. (2001)
Harley et al. (1992)
Harley et al. (1992)
Harley et al. (1992)
Harley et al. (1992)
Harley et al. (1992)
Harley et al. (1992)
c(Kc)
c(Ko)
c(τ)
∆Ha (Kc)
∆Ha (Ko)
∆Ha (Jmax)
∆Ha (TPU)
∆Ha (Vcmax)
∆ Ha ( τ)
∆Ha (Rd)
∆Hd (Jmax)
∆Hd (TPU)
∆Hd (Vcmax)
∆S (Jmax)
∆S (Vcmax)
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URBAN, LE ROUX, SINOQUET, JAFFUEL AND JANNOYER
Baldocchi 1994).
Parameters g0, a1 and D0 were derived from concomitant Anet
and gs measurements performed on leaves from 3- and 11year-old trees, similar to those used for parameterization of the
photosynthesis model.
Gas exchange measurements
Gas exchange was measured with an infrared gas analyzer and
leaf chamber system with a red + blue light source (LI-6400,
Li-Cor, Lincoln, NE). Calculations were performed according
to von Caemmerer and Farquhar (1981).
At Saint-Paul, measurements were made to study the relationship between leaf photosynthetic capacity, total nitrogen
per unit leaf area and mean irradiance in two 3-year-old trees.
Forty-four leaves encompassing full light and shade conditions were selected within the canopies of the selected trees
and tagged. After completion of the tree digitizing procedure
(see below), A–Ci curves were established for 14 of these
leaves from March 19 to April 5, 2001. Leaves were exposed
to high irradiance and ambient CO2 concentration for at least
15 min before starting A–Ci curves. Thirteen measurements
were taken (Ca = 200, 180, 160, 140, 120, 100, 80, 60, 40, 30,
20, 10 and 5 Pa CO2) for each A–Ci curve. Conditions in the
leaf chamber were controlled (Tl = 30 °C, vapor pressure deficit at the leaf surface = 1.0 ± 0.2 kPa). The value of Q was set
to maintain the point of transition between the Rubisco-limited and RuBP regeneration-limited segments in the center of
the CO2 response curves. We set Q at 2000 µmol m–2 s –1 for
sun leaves and 500 µmol m –2 s –1 for shade leaves. The best fit
Vcmax, Jmax, TPU and Rd values were inferred by nonlinear least
square regressions (S-Plus 2000, MathSoft International, Bagshot, U.K.). Values of Rd were derived from A–Ci curves and
found to be in good agreement with values estimated from
measurements of CO2 evolution rates after 10 min in the dark.
The relationship between photosynthetic capacity and Na,
and the effect of developing fruits on the photosynthetic capacity of nearby leaves were assessed in January–February
2001 in four 11-year-old trees at Saint-Pierre. We compared
Vcmax, Jmax, TPU and Rd derived from A–Ci curves obtained on
seven young mature leaves from the same last flush without
fruits nearby (standard leaves), and on eight leaves, also from
the last flush, but close to developing fruits (similar to standard leaves in all other aspects). All leaves had the same orientation and were at similar heights (about 1.7 m). Fish-eye
pictures were taken to make sure that gap fractions did not differ between treatments (HemiView 3.1 SR1, Delta-T Devices,
Cambridge, U.K.). The procedure applied to establish A–Ci response curves was the same as that described for the
Saint-Paul study.
Measurements for gs modeling were performed in the
irradiance tracking mode to minimize light fluctuations (target
value coming from the external quantum sensor, potentially
changing every 3 s), on well-exposed young mature leaves
similar to those used for the A–Ci curves. The partial pressure
of CO2 in the air was set at 36 Pa. Leaf gas exchange rates of
the same six leaves were monitored (one measurement per leaf
during each 90-min period from 0730 to 1800 h). Two sets of
data were obtained: one set for standard leaves and leaves
close to developing fruits from 11-year-old trees at Saint-Pierre, and the other set for standard leaves from 3-year-old trees
at Saint-Paul.
Additional gas exchange measurements were performed to
test the model for standard leaves (Na = 2.15 + 0.03 g N m –2)
and leaves close to developing fruits (Na = 2.63 + 0.07 g N
m –2) on the 11-year-old trees at Saint-Pierre. Leaves used for
model testing were all well-lit, fully developed leaves from the
last vegetative flush, experiencing similar gap fractions. During the measurements, Q was in the 70 to 1870 µmol m–2 s –1
range. Temperature and humidity of the air were not controlled, but the leaf chamber was used in the irradiance tracking mode, and the partial pressure of CO2 in the air was set at
36 Pa to favor rapid stabilization. Measurements were performed on 12 different leaves every 2.5 h from 0730 to 1930 h
on one selected clear day.
Leaf nitrogen and nonstructural carbohydrates
Leaves used for A–Ci curves and all labeled leaves on the
3-year-old trees were collected and weighed. Leaf areas were
measured and the leaves were frozen in liquid nitrogen. Total
leaf nitrogen was determined with an elemental analyzer
(Carlo Erba Instruments, Milano, Italy). Glucose, fructose and
sucrose in the leaves were measured by an enzyme-based analyzer (YSI 2007, Yellow Springs Instruments, Yellow
Springs, OH). Starch was determined after enzymatic hydrolysis to glucose (Thievend et al. 1972).
Tree digitizing and leaf irradiance computation
The architecture of the two 3-year-old trees at Saint-Paul was
measured with a 3D digitizing technique (Sinoquet and Rivet
1997). Leaf location and orientation on individual shoots were
recorded with an electromagnetic 3D digitizer (Fastrak, Polhemus, Colchester, VT) and the 3A software package (Adam
et al. 1999). The spatial coordinates and the orientation of each
leaf were recorded at the junction point between petiole and
lamina, by setting the digitizer pointer parallel to the leaf
lamina (Sinoquet et al. 1998). Concurrently, leaf length was
measured and leaf age was recorded.
Leaf samples were used to establish allometric relationships
(1) between leaf length (L; cm) and width (W; cm), and (2) between L and leaf area (A; cm2), calculated from digitized images taken with a standard flat-bed scanner, using Mesurim
software (Madre 1998).
W = 0.2507L (r 2 = 0.71, n = 34 )
A = 0.7451L2 (r 2 = 0.98, n = 108)
Directional light interception was computed with VegeSTAR graphics software (Adam et al. 2000). VegeSTAR allows the visualization of 3D digitized plants and computation
of light interception from image processing of virtual plant
pictures (Sinoquet et al. 1998). The software computes the
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293
projected lit area by counting the colored pixels corresponding
to an organ or organ class in the picture. The computation thus
discards multiple scattering and treats leaves as black bodies.
VegeSTAR input files were obtained from the digitized data
(i.e., spatial location and orientation), and leaf width and area
were calculated from leaf length by means of the empirically
determined allometric relationships given above. Leaf shape
was idealized as a polygon obeying allometric relationships
(Sinoquet et al. 1998). Each leaf was given a false color in order to identify it on the plant images. Time-averaged irradiance of each leaf was estimated assuming diffuse light
conditions. The incident diffuse radiation was approximated
by a set of 46 light sources as proposed by Den Dulk (1989).
Each light direction was given a fraction of total incident radiation according to the standard overcast sky distribution
(SOC, Moon and Spencer 1942). For each light direction, the
silhouette-to-total-area ratio (STAR, Stenberg 1996) was calculated as the ratio of projected sunlit leaf area to total leaf
area. Mean leaf irradiance was then estimated as the mean of
the 46 directional STAR values weighted by the SOC distribution.
Leaf age was derived from direct observations made on the
studied trees in March and December 2000, and in March
2001, during the flushing periods.
Results
Effects of leaf irradiance and leaf age on leaf nitrogen and
total nonstructural carbohydrates
There was considerable variation in Nm among leaves (from
1.1 to 1.97%), but Nm was not correlated with the fraction of
intercepted light or with leaf age (Figure 1A). Both Na and Ta
were linearly related to the fraction of intercepted light (Figures 1B and 1C). A common relationship was observed between Na and irradiance for the two 3-year-old trees studied. In
contrast, the relationship between Ta and irradiance differed
significantly between the two 11-year-old trees. At a given
irradiance and over the whole range of irradiances, leaves of
Tree 1 exhibited higher Ta than leaves of Tree 2. The relationship between Na or Ta and irradiance was unaffected by leaf
age; Na was high in well-lit leaves older than 12 months.
Relationships between leaf photosynthetic capacity and leaf
nitrogen
Unlike Nm, Na was proportional to Ma, and a common relationship was observed for leaves of 3-year-old trees experiencing
different local light regimes, and well-lit leaves far from and
close to developing fruits of 11-year-old trees (Figures 2A and
2B).The lowest Na and Ma values were observed in shade
leaves sampled within the canopies of 3-year-old trees. Although Ta was proportional to Ma in leaves of both the
3-year-old trees at Saint-Paul and the 11-year-old trees at
Saint-Pierre (Figure 2C), Ta (slope of the relationship) was significantly higher (P < 0.01) in leaves of Tree 1 at Saint-Paul, as
was the starch to sucrose ratio. Sucrose was the major
Figure 1. Relationships between (A) leaf nitrogen concentration per
unit mass (Nm), (B) leaf nitrogen concentration per unit leaf area (Na ),
and (C) amount of total nonstructural carbohydrates per unit leaf area
(Ta) and the gap fraction for leaves in the crowns of two 3-year-old
trees. Measurements were performed on leaves less than 2 months old
(䊉), 8 months old (䊏), 12 to 14 months old (䉱) and 17 to 20 months
old (䉬).
nonstructural carbohydrate in mango leaves, and starch
concentrations were less than 10% of sucrose concentrations
(Table 2).
Nonlinear fits accounted slightly better for the relationship
between the four key parameters defining leaf photosynthetic
capacity (i.e., Vcmax, Jmax, TPU and Rd ) and Na than linear fits,
with the exception of Rd (Figure 3). Equation 9b was thus more
effective than Equation 9a for describing the relationship between Vcmax, Jmax or TPU and Na. At 30 °C, values of Vcmax, Jmax,
TPU and Rd ranged from 37.6 to 122.4 µmol CO2 m–2 s –1, 62.8
to 205.0 µmol electrons m –2 s –1, 3.9 to 14 µmol CO2 m–2 s –1
and 1.5 to 3.7 µmol CO2 m–2 s –1, respectively. The lowest values of Vcmax, Jmax, TPU and Rd were found in leaves sampled
deep in the crown of the 3-year-old trees. The ratios Jmax/Vcmax
and TPU/Vcmax remained constant (around 1.7 and 0.07, re-
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URBAN, LE ROUX, SINOQUET, JAFFUEL AND JANNOYER
Table 2. Characteristics of leaves far from (standard leaves) and close
to developing fruits: gap fraction, leaf nitrogen concentration (Nm ),
leaf mass/area ratio (Ma ), amount of nitrogen per unit leaf area ratio
(Na ), amounts of total nonstructural carbohydrates (Ta ), sucrose and
starch per unit leaf area, estimates of maximum rate of carboxylation
(Vcmax), light-saturated rate of electron transport (Jmax ), rate of phosphate release in triose phosphate utilization (TPU) and dark respiration rate (Rd ), and the ratios Jmax/Vcmax, TPU/Vcmax and Rd/Vcmax. All
measurements were performed on leaves of 11-year-old trees. Means
are presented ± SE (n = 7 for standard leaves and n = 8 for leaves close
to developing fruits). Within a row, values with different letters differ
significantly (P < 0.01).
Figure 2. Relationships between (A) leaf nitrogen concentration per
unit mass (Nm ), (B) leaf nitrogen concentration per unit leaf area (Na ),
and (C) amount of total nonstructural carbohydrates per unit leaf area,
(Ta ) and the leaf mass/area ratio (Ma ). Measurements were performed
on leaves of 3-year-old trees (Tree 1 (䊉) and Tree 2 (䊏)), leaves far
from (standard leaves) (䊊) and close to (䊐) developing fruits of
11-year-old trees. Linear regressions for Na versus Ma were not significantly different between treatments. The best fit line thus corresponds to all the leaves (middle panel). Best fit lines correspond to the
leaves of Tree 1 () and Tree 2 (---), and standard leaves and leaves
close to developing fruits of 11-year-old trees (⋅⋅⋅⋅) in the lower panel.
Characteristic
Standard leaves
Leaves close to
developing fruits
Gap fraction (no. units)
Nm (%)
Ma (g m –2)
Na (g m –2)
Ta (g m –2)
Sucrose (g m –2)
Starch (g m –2)
Vcmax
(µmol CO2 m –2 s –1)
Jmax
(µmol electrons m –2 s –1)
TPU
(µmol CO2 m –2 s –1)
Rd
(µmol CO2 m –2 s –1)
Jmax/Vcmax
TPU/Vcmax
Rd /Vcmax
0.53 ± 0.03 a
1.65 ± 0.08 a
148.7 ± 7.1 a
2.5 ± 0.1 a
6.7 ± 0.3 a
4.9 ± 0.4 a
0.4 ± 0.1 a
59.5 ± 1.9 a
0.52 ± 0.02 a
1.74 ± 0.06 a
168.9 ± 7.8 b
2.9 ± 0.1 b
7.4 ± 0.5 a
5.3 ± 0.3 a
0.5 ± 0.1 a
4.8 ± 2.9 b
132.5 ± 3.7 a
164.1 ± 4.8 b
10.6 ± 0.3 a
12.9 ± 0.3 b
–2.9 ± 0.1 a
–3.1 ± 0.1 a
2.27 ± 0.05 a
0.177 ± 0.003 a
–0.0485 ± 0.0003 a
2.20 ± 0.027 a
0.171 ± 0.004 a
–0.0404 ± 0.0017 b
Rubisco per g total leaf N, and 0.04 g N in cytochrome f,
ferredoxin, NADP reductase, and coupling factors, per g total
leaf N, respectively) when Na increased from 1.8 to 3.4 g m –2,
for all types of leaves.
In 11-year-old trees, several leaf characteristics differed significantly between standard leaves and leaves close to developing fruits (Table 2). For similar gap fractions, leaves close to
developing fruits exhibited higher values of Ma, Na, Vcmax, Jmax
and TPU, and lower values of Rd/Vcmax than standard leaves. In
contrast, Nm and Ta values did not differ between the two leaf
types.
Parameterization of the stomatal conductance model
spectively) over a large range of Na values (Figure 4). In contrast, Rd/Vcmax decreased from 0.04 to 0.02 when Na increased
from 1.5 to 3.4 g m –2.
The leaf N allocation coefficients Pc and Pb increased by
50% (from 0.1 to 0.19 g N in Rubisco per g total leaf N), and
by 40% (from 0.03 g to more than 0.04 g N in cytochrome f,
ferredoxin, NADP reductase and coupling factors per g total
leaf N), respectively, in leaves from 3-year-old trees when Na
increased from 1.4 to 1.8 g m –2 (Figure 5). But both coefficients remained relatively constant (around 0.19 g N in
The linear relationship between gs simulated with the Leuning
(1995) model and measured gs was unaffected by the presence
of fruit or tree age (Figure 6). This relationship also held for
gas exchange measurements made over a large range of growing conditions, with the notable exception of the pre-flowering
and flowering periods (data not shown).
Testing of the coupled model
The stomatal conductance–photosynthesis model parameterized from measurements made on standard leaves and leaves
TREE PHYSIOLOGY VOLUME 23, 2003
A PHOTOSYNTHESIS MODEL FOR MANGO
295
Figure 4. Relationships between (A) the ratio beween the light-saturated rate of electron transport (Jmax ) and the maximum rate of carboxylation (Vcmax ), (B) the ratio beween the rate of phosphate release
in triose phosphate utilization (TPU) and Vcmax, and (C) the ratio
beween the dark respiration rate (Rd ) and Vcmax and nitrogen concentration per unit leaf area (Na ). Measurements were performed on the
leaves of 3-year-old trees (䊉), standard leaves (䊊) and leaves close to
developing fruits (䊐) of 11-year-old trees.
Discussion
Figure 3. Relationships between the four key parameters of the photosynthesis model (maximum rate of carboxylation (Vcmax ), light-saturated rate of electron transport (Jmax ), rate of phosphate release in
triose phosphate utilization (TPU) and dark respiration rate (Rd)) and
nitrogen concentration per unit leaf area (Na ). Measurements were
performed on the leaves of 3-year-old trees (䊉), standard leaves (䊊)
and leaves close to developing fruits (䊐) of 11-year-old trees. Best fit
lines for pooled data correspond to the linear () and the y = ax –1 + b
(⋅⋅⋅⋅) models.
close to developing fruits, accurately predicts net photosynthesis of both standard leaves and leaves close to developing
fruits, experiencing similar gap fractions (Figure 7).
Photoacclimation in mango leaves
Leaf photosynthetic capacities of the 3-year-old mango trees
exhibited strong spatial variations (e.g., from 37.6 to
122.4 µmol CO2 m–2 s –1 for Vcmax). Parameters Vcmax, Jmax and
TPU were strongly related to Na and nonlinear fits accounted
slightly better for the relationships than linear fits. Linear relationships have been reported between photosynthetic capacities and Na in the chaparral shrub, Lepechinia calycina
(Benth.) Epl. (Field 1983), Eucalyptus grandis W. Hill.
(Leuning et al. 1991), cotton (Harley et al. 1992), Nothofagus
fusca (Hook. F.) Orst. (Hollinger 1996), Pinus radiata D. Don
(Walcroft et al. 1997), Pinus pinaster Ait. (Porté and Loustau
1998), Juglans regia L. (Le Roux et al. 1999a) and Prunus
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URBAN, LE ROUX, SINOQUET, JAFFUEL AND JANNOYER
Figure 5. Relationships between the coefficients for leaf nitrogen partitioning into carboxylation (Pc ) and bioenergetic pools (Pb) and nitrogen concentration per unit leaf area (Na ). Measurements were
performed on leaves of 3-year-old trees (䊉), and on standard leaves
(䊊) and leaves close to developing fruits (䊐) of 11-year-old trees.
persica (L.) Batsch. (Le Roux et al. 2001a). The nonlinearity
of the relationships observed for mango was weak, and should
be tested with additional data. The dependency of Rd on Na was
consistent with the relationships generally observed between
leaf photosynthetic capacity and Rd reported by Ceulemans
and Saugier (1991) and Reich et al. (1998). Our observations
thus support the idea that all parameters related to the major
biochemical limitations to photosynthesis vary in parallel, because leaf N has a major role in controlling each process involved, and because allocation of N is regulated in such a way
that these limitations remain balanced as total N varies (Chen
et al. 1993). However, a substantial increase in Rd/Vcmax with
increasing Na was observed (Figure 4), which contradicts the
assumption that leaf Rd is proportional to Vcmax (Farquhar et al.
1980, Niinemets and Tenhunen 1997). Further data are needed
to assess whether the observed increase in Rd/Vcmax with increasing Na was associated with measurement errors or indicates actual changes in the balance between Rd and photosynthetic capacity.
Photosynthetic light acclimation of leaves generally results
from changes in Nm, Ma and changes in partitioning of total
leaf nitrogen among the different pools of the photosynthetic
machinery (Evans 1989b). When mean leaf irradiance increased from 0.02 to 0.90 of incident irradiance, Ma increased
by about 90% (from 92 to 173 gDM m –2), and Nm increased by
20% (from 1.39 to 1.67%), resulting in a more than doubling
Figure 6. Comparison between gs simulated with the model of
Leuning (1995) and measured gs. Data were obtained from gas exchange measurements performed on leaves of 3-year-old trees (䊉),
and on standard leaves (䊊) and leaves close to developing fruits (䊐)
of 11-year-old trees, every 90 min from 0730 to 1800 h. Linear regressions were not significantly different between treatments. The best fit
line corresponds to all the leaves.
of Na (from 1.32 to 2.78 g m –2). Concurrently, the relative
amount of leaf N allocated to carboxylation (Pc) and electron
carriers (Pb) increased by 50 and 40%, respectively. However,
changes in total leaf N allocation seemed to play a more important role in light acclimation at low Na (Figure 5), because
Figure 7. Comparison of leaf net photosynthesis simulated by the
model, including the effect of the proximity effect of developing
fruits, and measured in situ on standard leaves (䊊) and leaves close to
developing fruits (䊐).
TREE PHYSIOLOGY VOLUME 23, 2003
A PHOTOSYNTHESIS MODEL FOR MANGO
increases in Na values above 1.8 g m –2 had no significant effect
on photosynthetic light acclimation. In mango, photosynthetic
light acclimation thus results mainly from changes in Ma and,
to a lesser extent, from changes in allocation of total leaf N at
low irradiance, whereas changes in Nm play only a minor role.
Changes in Ma are also of major importance for photoacclimation in other tree and shrub species (Gulmon and Chu
1981, Niinemets et al. 1998, Le Roux et al. 1999b, Rosati et al.
1999). In contrast, although adjustment of leaf N partitioning
among different pools of the photosynthetic machinery is expected from optimization theories (i.e., for optimizing daily
carbon gain of individual leaves in different light regimes:
Hikosaka and Terashima 1995), such an adjustment is of minor importance for species like Alocasia macrorrhiza (L.) G.
Don (Seemann et al. 1987) and Juglans regia (Le Roux et al.
1999a, 1999b), but significant for species like Phaseolus
vulgaris L., Cucumis sativus L. (Seemann et al. 1987) and
Prunus persica (Le Roux et al. 2001).
Factors affecting the relationship between photosynthetic
capacity and light regime
Effect of age Leaf characteristics such as photosynthetic capacity and Na generally exhibit strong patterns with leaf age,
with maximum values observed when leaves have just completed full expansion (Constable and Rawson 1980, Marshall
and Biscoe 1980, Dwyer and Stewart 1986, Field 1987, Wilson
et al. 2000, Frak et al. 2001). However, we observed that the relationship between Na and irradiance was unaffected by leaf
age in mango and that Na values remained high in old leaves experiencing high irradiance. This suggests that changes in Na
were influenced by irradiance rather than age during the first
year of growth in mango. Furthermore, the tight correlation observed between photosynthetic capacity and Na for leaves of
different age classes is consistent with previous studies reporting that changes in both variables are closely correlated during
leaf aging (Field and Mooney 1983, Vos and Oyarzun 1987).
Such observations suggest that aging represents a period of redistribution of N resources and not uncontrolled deterioration
of leaf biochemical characteristics (Field and Mooney 1983).
Effect of the local source–sink balance We observed that
photosynthetic capacity was substantially higher in leaves
close to developing fruits than in control leaves experiencing
the same light regime. Source–sink imbalances can exert feedback inhibition on leaf photosynthesis through carbohydrate
accumulation in leaves (Foyer, 1988). For instance, transient
accumulations of carbohydrates in leaves, which have been observed during the diurnal period, may impair the rate of electron transport (Pammenter et al. 1993). Changes in photosynthetic capacity, not just assimilation rates, are more likely
to be observed in association with lasting source–sink imbalances. One hypothesis is that high concentrations of carbohydrates repress the expression of genes coding for several
photosynthetic enzymes (Krapp and Stitt 1995, Koch 1996,
Drake et al. 1997). Alternatively, carbohydrates may interact
with hormonal signals to control gene expression (Thomas and
Rodriguez 1994). There is also some evidence that photo-
297
synthetic capacity is related to leaf carbohydrate status through
the effect of the latter on phosphate availability (Riesmeier et
al. 1993, Sun et al. 1999). However, we found increased photosynthetic capacity in leaves close to developing fruits compared with control leaves, whereas no significant difference in
Ta was observed, suggesting that Ta was probably not the signal
promoting photosynthetic capacity in leaves close to developing fruits. The common relationship observed between Na (i.e.,
photosynthetic capacity) and irradiance for the two trees studied, and the different relationships observed between Ta and
irradiance for these trees, provide further evidence that Ta was
not a major factor driving photosynthetic acclimation in
mango. This conclusion is inconsistent with the assumption of
recent models of photosynthetic acclimation (Dewar et al.
1998, Kull and Kruijt 1999).
Differences in photosynthetic capacity between standard
leaves and leaves close to developing fruits were mainly attributable to differences in Ma rather than in Nm. A fruit effect
on photosynthetic capacity was not expected because there
were no differences in mean leaf irradiance and leaf age (the
usual driving forces behind photosynthetic capacity) between
the two leaf types. We have no explanation for the observed
fruit effect.
Potential and limits of the stomatal conductance–photosynthesis model
The existence of an almost unique relationship between
photosynthetic capacity and Na, whatever the origin of leaves
(leaves selected from 3-year-old trees, standard leaves and
leaves close to developing fruits of 11-year-old trees) suggests
that this relationship is robust. Similarly, the linear relationship between gs and Anet also seems to be robust, at least in the
range of leaf temperatures of our gas exchange measurements
(from 25 to 35 °C) and in the absence of water stress. Because
changes in stomatal conductance may not parallel those of assimilation rate in response to temperature (Bunce 2000), the
relationship between gs and Anet needs to be reassessed at temperatures lower than 25 °C and higher than 35 °C, to extend
the predictive ability of our model. Although the effects of soil
drought on stomatal conductance have been demonstrated in
many field and laboratory experiments (Baldocchi 1997), the
two most common models of gs, the Ball-Berry model (Ball et
al. 1987) and the Leuning (1995) model, do not specifically incorporate a water stress function. This is a clear shortcoming
of our model of leaf photosynthesis because it relies on the
original Leuning model of gs. However, the robustness of the
relationships reported here augurs well for the ability of our
model to predict photosynthesis of mango leaves from well-irrigated trees of different ages and phenological stages.
Another shortcoming of our model is that most parameters
were estimated from measurements made at 30 °C. Previous
studies have shown the importance of the temperature response of leaf photosynthetic capacity, and the existence of
interspecific differences in responses obtained from different
species or under different environmental conditions (Dreyer et
al. 2001, Medlyn et al. 2002). The temperature dependency of
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URBAN, LE ROUX, SINOQUET, JAFFUEL AND JANNOYER
the parameters of photosynthetic capacity will thus have to be
studied for mango to improve the predictive ability of the
model.
Conclusion
Our data suggest that there is a fruit effect on photosynthetic
capacity of nearby leaves that does not seem to be driven by Ta.
Modeling the distribution of photosynthetic carbon gains
within fruit trees will have to take such an effect into account
in the future. Because the distribution of carbon sources has
potentially important consequences on the distribution of fruit
quality in the tree, the mango leaf model will also need to be
scaled up to the fruiting branch and tree canopy levels, for instance by using the RATP model (Sinoquet et al. 2001).
Scaling up the model could help assess effects on carbon acquisition at the fruiting unit level of: (1) plant and orchard geometry, namely the spatial distribution of fruiting units in the
canopy; (2) environmental variables; and (3) leaf physiological properties.
Acknowledgments
The authors thank Brigitte Saint-Joanis and Marc Vandame (INRA,
Clermont-Ferrand) for their technical assistance. This work was
partly funded by the Action Thématique Programmée CIRAD-INRA
“Modélisation de la croissance des fruits dans une architecture
ligneuse pour une meilleure maîtrise de la production et de sa
qualité.”
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