Journal of Experimental Botany, Vol. 61, No. 10, pp. 2745–2755, 2010
doi:10.1093/jxb/erq108 Advance Access publication 6 May, 2010
RESEARCH PAPER
Genotype effects on internal gas gradients in apple fruit
Q. Tri Ho1,*, Pieter Verboven1, Bert E. Verlinden1, Ann Schenk1, Mulugeta A. Delele1, Hardy Rolletschek2,
Jef Vercammen3 and Bart M. Nicolaı̈1
1
Flanders Centre of Postharvest Technology/BIOSYST-MeBioS, Faculty of Bioscience Engineering, Katholieke Universiteit Leuven,
Willem de Croylaan 42, B-3001 Leuven, Belgium
2
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Gatersleben, Germany
3
PCF Proeftuin Pit & Steenfruit, Fruittuinweg 1, B-3800 St Truiden, Belgium
* To whom correspondence should be addressed. E-mail: [email protected]
Received 22 February 2010; Revised 17 March 2010; Accepted 29 March 2010
Abstract
A permeation–diffusion–reaction model was applied to study gas exchange of apple fruit (Kanzi, Jonagold, and
Braeburn) as effected by morphology and respiratory metabolism. The gas exchange properties and respiration
parameters of the fruit organ tissues were measured. The actual internal tissue geometry of the fruit was
reconstructed from digital fruit images and the model was solved over this geometry using the finite element
method. The model was validated based on measurements of internal gas concentrations and the gas flux of the
fruit to its environment. Both measurements and an in silico study revealed that gradients of metabolic gases exist in
apple fruit, depending on diffusion properties and respiration of the different cultivars. Macroscale simulation
confirmed that Jonagold has large potential for controlled atmosphere (CA) storage while low diffusion properties of
cortex tissue in Braeburn indicated a risk of storage disorder development. Kanzi had less O2 anoxia at CA storage
compared with Braeburn.
Key words: Controlled atmosphere, diffusion, gas transport, modelling, storage.
Introduction
Metabolic processes such as photosynthesis and respiration
in biological plant materials are reflected in their rate of gas
exchange with the external environment. Gas exchange is
caused by differences in gas concentrations between the
external atmosphere and the internal atmosphere of plant
organs. In bulky organs, such as fruits and roots, these
gradients exist due to O2 consumption and CO2 production during respiration and fermentation (Kader, 1988;
Geigenberger et al., 2000; Ho et al., 2008). In developing
seeds, there is a combination of respiration and photosynthesis that causes large gradients in gas concentrations
(Rolletschek et al., 2002, 2003; Borisjuk and Rolletschek,
2009). In leaves, gradients are created by photosynthesis,
photorespiration, and respiration (Morison et al., 2005;
Warren et al., 2008).
Gas exchange is particularly relevant for bulky plant
organs such as apple and pear fruit that, after harvest, are
stored under a controlled atmosphere with reduced O2 and
increased CO2 levels to extend their commercial storage life.
Anoxia may occur under deviating storage conditions,
eventually leading to cell death and loss of the product
(Peppelenbos and Oosterhaven, 1998; Lammertyn et al.,
2000; Ma and Chen, 2003; Veltman et al., 2003; Franck
et al., 2007). The microstructure is believed to contribute
significantly to gas transport properties of tissue resulting in
internal gas concentration gradients (Verboven et al., 2008).
The fruit organ architecture and the tissue diffusion and
respiration properties need to be understood to verify this
hypothesis and to help explain internal gas gradients
(Lammertyn et al., 2001a; Schotsmans et al., 2003, 2004;
Ho et al., 2006a).
Because measurement of internal gas gradients has been
difficult, mathematical modelling approaches have been
applied to study gas exchange in plant organs. Denison
ª The Author [2010]. Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved.
For Permissions, please e-mail: [email protected]
2746 | Ho et al.
(1992) developed a reaction–diffusion model for oxygen
diffusion and respiration in legume root nodules and found
large effects of flooding of the intercellular space on O2
permeability. Aalto and Juurola (2002) constructed a threedimensional model of CO2 transport in leaves and implemented it into a computational fluid dynamics code. The
model accounted for the actual 3D microstructure of a leaf.
The authors used the model to investigate the effect of
stomatal opening, photosynthetic capacity, temperature,
and increased ambient CO2 levels on total CO2 flux.
Recently, a gas modelling approach was developed to study
gas exchange of pear fruit with their external environment
(Ho et al., 2008). The model incorporated the actual shape
of the fruit and tissue architecture and predicted respiratory
gas concentration internal gas concentrations including
permeation, diffusion, and respiration kinetics. The predicted internal gas profiles were not verified by measurements of internal gas concentrations. The applicability of
the approach to other species and cultivars was not verified.
Metabolic and morphological properties cause gas gradients in plant organs. In turn, such gas gradients may lead
to low oxygen that will cause metabolic and morphological
adaptation of the plant organs. In this article, the aim was
to validate the gas exchange model of Ho et al. (2008) to
understand better post-harvest physiology in low oxygen
caused by genotype differences in metabolic and morphological properties. Fruits from three commercial apple
genotypes (Kanzi, Jonagold, and Braeburn) are evaluated
by comparing predictions to measurements of internal gas
concentrations. Jonagold is a typical commercial genotype
for long-term storage at ultra-low oxygen (ULO) (Saquet
et al., 2000), while Braeburn has shown a large susceptibility
to physiological disorders in storage (Gong et al., 2001).
Kanzi is a new genotype apple.
Measured gas exchange properties of tissues (skin, cortex,
and core) are applied to the fruit model to study if the tissue
aeration process relates to storage conditions of the
different apple genotypes. The specific aim of the study is
then to determine optimal controlled atmosphere environments for different genotypes based on the methodology
presented.
Materials and methods
Materials
The experiments were performed on fruits of three apple genotypes
(Kanzi, Braeburn, and Jonagold). Fruit were harvested in the
autumn at the experimental garden of the Experimental Centre of
Fruit Growing (pcfruit, Velm, Belgium) in 2007. Jonagold and
Kanzi were cooled and stored under controlled atmosphere (CA)
of 1% O2, 2.5% CO2, and 3% O2, 0.7% CO2 at 1 C, respectively.
Braeburn was cooled and stored for a period of 21 d at 1 C
preceding CA storage (3% O2, 0.7% CO2 at 1 C) until they were
used for the experiments.
Model of gas exchange in intact fruit
A permeation–diffusion–reaction model was constructed to describe the diffusion and permeation processes in apple tissue for
the three major atmospheric gases O2, CO2, and N2. In this
continuum model, the transport on the microscale was volumeaveraged to a macroscopic equation containing apparent parameters for the macroscopic properties of the tissue. Equations for
transport of O2, CO2, and N2 were established by Ho et al. (2006b,
2008):
ai
dCi
þ =ðuCi Þ ¼ =Di =Ci þ Ri
dt
ð1Þ
and at the boundary
Ci ¼ Ci;00
ð2Þ
with ai the gas capacity of the component i (O2, CO2, and N2) of
the tissue (Ho et al., 2006b), Di (m2 s1) the apparent diffusion
coefficient, u (m s1) the apparent velocity vector, Ri (mol
m3 s1) the production term of the gas component i related to
O2 consumption or CO2 production, = (m1) the gradient
operator, and t (s) the time. The index N refers to the gas
concentration of the ambient atmosphere. The gas capacity ai is
defined as (Ho et al., 2006b):
ai ¼ e þ ð1 eÞRTH i ¼
Ci;tissue
Ci;g
ð3Þ
where e is the porosity of tissue, Ci,g (mol m3) and Ci,tissue (mol
m3) are the concentrations of the gas component i in the gas
phase and the tissue, respectively. The concentration of the
compound in the liquid phase of the fruit tissue normally follows
Henry’s law represented by constant Hi (mol m3 kPa1). R (8.314
J mol1 K1) is the universal gas constant and T (K) the
temperature.
The first term in equation (1) represents the accumulation of gas
i, the second term the permeation transport driven by an overall
pressure gradient, the third term the molecular diffusion due to
a partial pressure gradient, and the last term consumption or
production of gas i because of respiration or fermentation.
Permeation through the barrier of tissue by the pressure gradient
was described by Darcy’s law (Geankoplis, 1993):
j
K:R:T
u ¼ =P ¼ = +Ci
l
l
ð4Þ
with K (m2) the permeation coefficient, P (Pa) the pressure, and
l (Pa s) the viscosity of the gas. The relation between gas
concentration and pressure was assumed to follow the ideal gas
law (P¼CRT).
Note that the empty core was modelled and treated as air space
with a diffusivity equal to that of air (1.63105 m2 s1; Lide
(1999)), and a gas capacity a of 1. Since there would be no total
pressure gradient within the core, the convection term disappeared
in the core.
Gas transport properties and respiration measurement
Diffusivity measurement: The apparent diffusivity of apple tissue
samples was measured with the setup and procedures developed by
Ho et al. (2006a). The system used to measure gas transport
properties of fruit tissue consisted of two chambers (measurement
chamber and flushing chamber) separated by the disc-shaped tissue
sample. Due to the different applied gas concentrations between
the two chambers, gas diffusion took place. The O2 and CO2
concentrations were measured in the measurement chamber with
fluorescent optical probes (Foxy-Resp and FCO2-R; Ocean Optics,
Duiven, The Netherlands). The gas diffusion properties were then
estimated from the gas concentration profiles as described by Ho
et al. (2006a). The N2 diffusivity was determined indirectly from
the difference between the total pressure and the O2 partial gas
pressure of the binary O2–N2 gas mixture (Ho et al., 2006b).
Permeation properties of apple epidermis and cortex tissue were
determined by measuring the total pressure difference between two
chambers separated by a tissue sample (Ho et al., 2006b). Both
Genotype effects on internal gas gradients in apple fruit | 2747
chambers were flushed with humidified N2 gas at 10 l h1. The
pressure was adjusted so as to obtain a 6 kPa pressure difference
between the measurement and flushing chamber. The inlet and
outlet valves of one chamber were closed, and the decrease in
pressure of this chamber was monitored for at least 4 h. The
permeability was then estimated from this pressure drop using the
procedure described by Ho et al. (2006b).
To determine gas diffusivity of the different cortex tissues in
each genotype, 16 samples of cortex tissue were taken on the fruit
equator along the radial direction at a relative position x/R from
the fruit centre between 0.2 and 0.8; eight samples of cortex tissue
were measured in the vertical direction for each genotype. Details
of sample preparation are reported in the Supplementary data (S1)
at JXB online. To determine gas diffusivity of skin tissue, 6–8
samples of the skin were measured for each genotype. Samples
with an approximate thickness of 0.6 mm were obtained by means
of a razor blade.
Respiration kinetics
A non-competitive inhibition model (Hertog et al., 1998; Ho et al.,
2008) was used to describe the respiration rates R of the tissue.
Cortex tissue samples were prepared and tissue respiration rate
was measured in airtight glass jars at different initial gas
concentrations. Since the respiration rate was assumed to be
determined by one rate-limiting enzyme reaction, the Michaelis–
Menten constant which is a ratio of rate constants, would be
expected to be relatively independent of temperature (Hertog et al.,
1998). The Km value for O2 and CO2 was, therefore, assumed to be
constant. On the other hand, the maximal O2 consumption rate
Vm,O2 and maximal CO2 production rate, Vm,f,CO2 are functions of
the initially available enzyme concentration (Hertog et al., 1998).
Respiration model parameters were estimated by fitting the
respiration kinetics model equations to the experimental respiration rate data using the non-linear least square estimation procedure of Matlab (The Mathworks, Inc., Natick, USA). More
details of sample preparation and the respiration kinetics model
are described by Ho et al. (2008).
Apple tissue samples were placed in air-tight glass jars with three
repetitions for each gas condition. The respiration rate was
measured on apple tissue at 20 C at 0, 0.5, 3, 5, and 20 kPa O2
combined with 0 kPa of CO2. To study the inhibitory effect of
CO2, respiration measurements were carried out at 0, 5, and
20 kPa O2 in combination with 10 kPa CO2. For quantifying the
effect of temperature on the respiration rate, measurements were
carried out at 5, 10, and 20 C at 0 and 20 kPa O2 in combination
with 0 kPa CO2.
Geometrical apple model construction
The geometrical model of the apples was constructed based on
digital images of apple taken from apple cuts along the vertical
axis (Fig. 1). The images were then exported to the Matlab
software environment (Matlab 7.3.0, The Mathworks, Natick,
Massachusetts) for image processing (digitization). The apple
image was digitized to extract the contours of the apple (segmenting the apple from the background) and the core of the fruit. The
contour of half of the fruit was obtained; the central axis of the
apple coincided with the y-axis in a 2D axi-symmetric geometry
representation. In Fig. 1B different internal apple regions are
indicated based on the following definitions. The skin was defined
as the layer having the same thickness of the sample of skin tissue
(0.6 mm) that was used in the diffusivity measurement. The skin
layer was obtained by shrinking the contour of the apple shape
along the normal vector on each node of the contour. The inner
cortex and outer cortex were defined from measured differences in
diffusivity along the radial axis and obtained by determining the
contour where the relative position in the radial axis was 0.65.
Note that the inner cortex and outer cortex were not different in
terms of diffusivity in Jonagold, while a large difference in
Fig. 1. Half cut apple (A) and its geometry (B). Y and R indicate
vertical direction and radial axis, respectively.
diffusivity was found in Kanzi (See Supplementary Table S3 and
Supplementary Fig. S3 at JXB online). The geometrical description
based on contour information was transferred to the software
package Comsol 3.3 (Comsol AB, Stockholm), where a finite
element mesh was generated on the apple geometry. Equations 1–3
were discretized over this mesh and solved using the finite element
method in Comsol.
Gas exchange measurement
Steady gas concentration profiles in intact fruit: The O2 concentration in the centre of intact apple fruit was measured with
fluorescent optical probes (Foxy-18G probe with overcoat, Ocean
Optics, Duiven, The Netherlands). A rubber septum (thickness of
2 mm) was glued on the surface of the fruit with cyano-acrylate
glue (Super glue, Loctite-Henkel, Belgium) to avoid leaking of
atmospheric gas through the epidermis tissue to the measurement
position. The needle probe was inserted through the septum and
along the equatorial radial direction at 3 mm, 13 mm, and 24 mm
depth from the skin surface. Probes were calibrated in water with
dissolved O2 at different concentrations. Afterwards, a second
calibration was performed to correct for sensor drift (Ho et al.,
2006a). The sensor uses fluorescence quenching of a ruthenium
complex by O2, which diffuses in a dye covering the tip of the fibre
optic probe.
Unsteady gas exchange of intact fruit in jars: The intact fruits were
placed in 1.7 l glass jars. After an adaption of 24 h, during which
the jar head space was flushed with a known gas mixture, the jars
were closed. The O2 and CO2 gas partial pressures changes with
time were measured with a gas analyser (Checkmate II, PBI
Dansensor, Denmark) during the respiration period.
Results
Gas diffusion measurement
Measurements of the O2 and CO2 diffusivity along the
radial direction are shown in Fig. 2. A large variation of O2
and CO2 diffusivity was observed in Kanzi, Jonagold, and
Braeburn. The diffusivities of O2 and CO2 were the smallest
for the skin. Based on linear regression analysis it was
found that along the radial direction of the cortex tissue of
2748 | Ho et al.
Braeburn the O2 diffusivity slightly increased with distance
from the centre; in Kanzi both the O2 and the CO2
diffusivity increased significantly with distance from the
centre (see Supplementary Table S1 and Supplementary
Fig. S3 at JXB online). There was no clear trend of the O2
and CO2 diffusivities along the vertical axis since variation
was observed in the three apple genotypes (see Supplementary Fig. S1 at JXB online).
Table 1 summarizes the mean value and 95% confidence
intervals of the mean value of the O2 and CO2 diffusivity. The average O2 diffussivity of the skin of Kanzi,
Jonagold, and Braeburn ranged from 1.531010 m2 s1 to
3.131010 m2 s1 while the average CO2 diffussivity was
3.131010 m2 s1 to 9.831010 m2 s1. Diffusivity of the
cortex tissue was one magnitude larger than that of the skin.
A paired t test showed that both the skin diffusivity as well
as the radial and vertical cortex diffusivity of O2 was
significantly lower than that of CO2 for each genotype (see
Supplementary Table S2 at JXB online). Further, a t test
between genotypes showed that the radial diffusivity of
Jonagold inner cortex tissue (0.35<x/R<0.65) was significantly higher than that of Kanzi and Braeburn for both O2
and CO2. There were no significant differences between
Kanzi and Braeburn with respect to both the diffusivity of
O2 and CO2.
Significant differences were found between the O2 diffusivity of the inner cortex (x/R <0.65) and the outer cortex
(x/R >0.65) of Kanzi. By contrast, the average CO2
diffusivity of the outer cortex was not significantly different
from that of the inner cortex. The skin had the lowest
permeability with average values of 0.2731017 m2,
0.5931017 m2, and 0.5931017 m2 for Kanzi, Jonagold,
and Braeburn apple, respectively. The gas permeability in
cortex tissue along the radial direction was higher than
along the vertical axis and in the skin for Kanzi and
Jonagold. However, there was no significant difference,
possibly due to a large variation among the samples
(Table 2).
Tissue respiration kinetics
The respiration rates of the three apple genotypes as
a function of O2 partial pressure are shown in Fig. 3. The
respiration rate increases dramatically at concentrations of
Table 1. Mean gas diffusivity of Kanzi, Jonagold, and Braeburn
apple genotypes and 95% confidence interval of the mean
Radial: diffusivity along the radial direction at relative position x/R.
Vertical: diffusivity along the vertical axis. The number of samples
ranged from 5 to 8.
D o2 (3109 DC02(3109
m2 s1)
m2 s1)
Tissue Direction
Kanzi
Radial
Cortex
Vertical
Skin
Jonagold
Radial
Cortex
Vertical
Skin
Braeburn
Radial
Cortex
Vertical
Skin
0.35< x/R <0.65 2.7361.59
x/R >0.65
5.0561.14
1.1060.16
x/R ¼1
0.3160.11
0.35< x/R <0.65 10.165.2
x/R >0.65
10.166.32
2.0660.94
x/R ¼1
0.1960.13
0.35< x/R <0.65 1.7360.5
x/R >0.65
3.1461.21
2.1360.73
x/R ¼1
0.1560.05
18.167.8
25.069.11
7.5762.43
0.9860.44
35.1610.3
28.5614.2
5.7561.07
0.3160.22
10.664.0
14.163.9
8.6461.08
0.9560.52
Table 2. Gas permeability of three apple genotypes and 695%
confidence intervals of the mean
Radial: diffusivity along the radial direction at relative position x/R
from 0.35 to 0.65. Vertical: diffusivity along the vertical axis. () the
number of samples (ranged from 7 to 12).
Kanzi
Jonagold
Fig. 2. O2 diffusivity (*) and CO2 diffusivity (o) of apple tissue along
the radial direction for Kanzi, Jonagold, and Braeburn. x/R is the
relative distance from the centre to the skin along the radial
direction. Y scale is logarithmic.
Braeburn
Sample
Average
value
(31017 m2)
Minimum
value
(31017 m2)
Maximum
value
(31017 m2)
Radial
Vertical
Skin
Radial
Vertical
Skin
Radial
Vertical
Skin
6.9465.77 (12)
2.2962.76 (7)
0.2760.12 (8)
93.9680.1 (8)
1.7261.0 (7)
0.5960.35 (8)
2.2561.54 (12)
4.8261.17 (7)
0.5960.30 (8)
0.39
0.18
0.02
9.23
0.57
0.15
0.16
2.93
0.16
26.98
8.85
0.57
287.22
3.75
1.36
7.48
6.67
1.34
Genotype effects on internal gas gradients in apple fruit | 2749
O2 from 0 kPa to 5 kPa, and becomes stable at higher
concentrations of O2. The effect of CO2 on respiration rates
of the three apple genotypes was not very clear. An
increased CO2 partial pressure tends to decrease the
respiration rate. The non-competitive inhibition model
described well the measured values of O2 consumption and
CO2 production rates of cortex tissue for Kanzi, Jonagold,
and Braeburn apples. The R2adj values for O2 consumption
and CO2 production were 0.94, 0.94, and 0.91 in Kanzi,
Jonagold, and Braeburn cortex tissue, respectively. Km,O2,
the O2 concentration at which half of maximal value of O2
consumption can be reached, was small. The results showed
that the estimated value of Km,O2 was 0.6160.24 kPa
for Kanzi while the values for Jonagold and Braeburn
were 1.6460.32 kPa and 0.4660.22 kPa, respectively. High
values with a high variation were found for the Kmn,CO2
of Kanzi (1686212 kPa), Jonagold (1636149 kPa), and
Braeburn (80.2656.7 kPa). The high values and high
variation of Kmn,CO2 indicate that CO2 does not have
a relevant effect on apple respiration. Similar results were
also found by Peppelenbos and Van’t Leven (1996) for
Golden Delicious apple (Kmn,CO2¼64650 kPa) and Elstar
apple (Kmn,CO2¼916126 kPa). The values of rq,ox were
1.0360.1, 1.0260.08, and 1.0560.1 for Kanzi, Jonagold,
and Braeburn, respectively. Km,f,O2was small for Kanzi
(0.7860.37 kPa), Jonagold (0.8960.36 kPa), and Braeburn
(0.4760.27 kPa), indicating a rapid decrease of the fermentation metabolism with increasing oxygen. The kinetic
parameters and their 95% confidence interval are given in
Table 3.
Gas exchange in intact fruit
The permeation–diffusion–respiration model was solved to
describe the diffusion and permeation processes in apple
tissue for the three major atmospheric gases O2, CO2, and
N2. The used gas exchange properties are shown in Table 4.
Kinetic parameters were considered to vary from batch to
batch, depending on fruit maturity and season. In the
validation, parameters of Vm,O2 and Vm,f,CO2 were therefore
taken from the values of the intact fruit measured from the
batch used in the validation experiments.
Table 3. Respiration model parameter estimates of cortex respiration and their 95% confidence interval. (Vm,O2 and Vm,f,CO2 results
measured at 293 K)
Parameters
Kanzi
cortex
Vm,O2 (3104 mol m3 s1)
Ea,Vm,o2 (kJ mol1)
Km,O2 (kPa)
Kmn,CO2 (kPa)
Vm,f,CO2 (3104 mol m3 s1)
Ea,Vm,f,Co2 (kJ mol1)
Km,f,O2 (kPa)
Rq,ox
R2adj
Jonagold
cortex
1.760.12
77.8616
0.6160.24
1686212
2.160.16
68.4611.4
0.7860.37
1.0360.1
0.94
2.1460.12
62.5614.7
1.6460.32
1636149
2.4760.2
81.7615.5
0.8960.36
1.0260.08
0.94
Braeburn
cortex
1.4160.11
59614
0.4660.22
80.2656.7
1.7160.15
57.6611
0.4760.27
1.0560.1
0.91
Table 4. Gas transport properties and respiration kinetics parameters of model
Subcripts i and o indicating inner and outer cortex, respectively.
Fig. 3. Respiration of tissue. (A) O2 consumption and (B) CO2
production rate. Symbols (x) and (o) denote measurement at 0 and
10 kPa CO2 while solid (—) and dashed (- -) lines represent the
respiration model at 0 and 10 kPa CO2, respectively. (C) Arrhenius
plot of maximal O2 consumption (Vm,O2) and CO2 production
(Vm,f,CO2) rates of tissue at different temperatures. The symbols (x)
and (o) denote the Vm,O2 and Vm,f,CO2 measurements, respectively,
while the solid (—) and dashed (- -) lines represent the
corresponding models.
Parameters
Unit
Kanzi
Jonagold
Bareburn
D02,skin
DC02,skin
DN2,skin
Kskin
D02,i
DC02,i
DN2,i
Kr,i
D02,o
DC02,o
DN2,o
Kr,o
Vm,O2a
Ea,Vm,o2
Km,O2
Kmn,CO2
Vm,f,CO2a
Ea,Vm,f,Co2
Km,f,O2
rq,ox
3109 m2 s1
0.31
0.98
0.44
0.27
2.73
18.10
3.48
6.94
5.05
25.0
9.40
6.94
3.12
77.8
0.61
168
4.71
68.4
0.78
1.03
0.19
0.31
0.3
0.59
10.10
35.10
18.00
92.3
10.10
35.10
18.09
92.3
4.91
62.5
1.64
163
4.44
81.7
0.89
1.02
0.15
0.95
0.12
0.59
1.73
10.60
0.84
2.25
3.14
14.1
7.18
2.25
5.81
59
0.46
80.2
7.35
57.6
0.47
1.0
3109 m2 s1
3109 m2 s1
31017 m2
3109 m2 s1
3109 m2 s1
3109 m2 s1
31017 m2
3109 m2 s1
3109 m2 s1
3109 m2 s1
31017 m2
3105 mol m3 s1
(kJ mol1)
(kPa)
(kPa)
3105 mol m3 s1
(kJ mol1)
(kPa)
a
Value of intact fruit, expressed at 283 K 695% confidence interval.
The core was treated as an air space with diffusivity of the air
(1.63105 m2 s1; Lide, 1999).
2750 | Ho et al.
Simulations of the O2, CO2, and N2 distribution inside
the fruit are shown in Fig. 4. Due to the diffusion barrier,
a concentration gradient was found inside the apples. A
decrease of the O2 partial pressure and an increase of CO2
partial pressure towards the centre of the fruit were
observed. A steep gradient was predicted in the epidermis.
This was due to the low diffusion properties of the skin
compared to the cortex. The modelled cortex concentration
Fig. 4. Typical O2, CO2, and N2 distribution of the intact Kanzi, Jonagold, and Braeburn at 20 kPa O2, 0 kPa CO2, and 10 C. The
coloured bars indicate gas partial pressure (kPa).
Genotype effects on internal gas gradients in apple fruit | 2751
gradient was the least steep in Jonagold, then in Kanzi, and
the steepest gradient was observed in Braeburn. This was
expected since the gas diffusion properties of cortex tissue
increased from Braeburn over Kanzi to Jonagold.
O2 concentration inside the fruit: experiment
versus model
The measurements show that the O2 concentration in
the apple tissue was considerably lower than that of the
ambient atmosphere (Fig. 5). Steep O2 gradients just
beneath the skin were observed, indicating a high diffusion
barrier of the skin. The O2 concentration decreased further
towards the core of the fruit. This confirms the existence of
O2 concentration gradients from the surface to the core
of the fruit. The calculated O2 profiles from the surface to
the centre along the radial direction are shown with a solid
line in Fig. 5. The calculated O2 concentration decreases
parabolically towards the centre with slight differences in
slope between the inner and outer cortex.
No measurements could be taken directly under the skin.
To verify the goodness of fit, the O2 diffusion model was
therefore fitted to the measurements. The resulting values
of diffusivity were compared with the experimental ones.
The estimated values of O2 diffusivity of skin and cortex
(lumped value of inner and outer cortex) obtained from
fitting of the O2 diffusion model to the measured O2
concentration in the fruit were comparable and in the range
of measured diffusivity, except for larger values of estimated
diffusivity of the skin of Jonagold and Kanzi (see Supplementary Table S3 at JXB online). The Jonagold agreement
thus looks weak compared with others, due to the lower
diffusivity measured on the skin samples than those
obtained from the fit. In both cases, however, the standard
error was relatively large. Other approaches, such as
microscale simulations, need to be undertaken to investigate
such differences in more depth (Ho et al., 2009).
Unsteady gas exchange of intact fruit
The results of the dynamic gas exchange experiments with
intact fruit are shown in Fig. 6. The change of the O2 and
CO2 partial pressures in the jars was caused by the
respiration of the fruit. The O2 partial pressure in the jars
decreased during the measurements due to O2 consumption
of the fruit while the CO2 partial pressure increased due to
CO2 production by respiration. At 0 kPa O2, the CO2 was
produced by the fermentative respiration process and this
further increased the CO2 level in the closed jars. The model
predictions for both the O2 and CO2 partial pressure in
closed jars clearly compared well with the experimental data
for very different initial oxygen conditions.
Gas transport properties in relation to controlled
atmosphere (CA) storage of apples
Decreasing the temperature can be used to reduce the
concentration gradient inside the fruit (Fig. 7), as is widely
applied in fruit storage. Apple fruit can be commercially
Fig. 5. O2 concentration along the radial direction at the equatorial
region of the apple. Vertical bars indicate 95% confidence intervals
of the mean (five samples), solid line indicates model predictions.
The ambient condition was 21 kPa O2 and 0 kPa CO2 at 20 C.
stored at ultra-low oxygen (ULO) for a long period (Saquet
et al., 2000). An in silico simulation was applied at
a condition of 1 kPa O2, 2.5 kPa CO2 at 1 C (a typical
commercial CA storage condition of Jonagold) for the
different genotypes of apple. Computational analysis
showed that the O2 concentration near the core of the
Jonagold fruit decreased to a value of 0.5 kPa (50% of the
external O2 concentration) while Kanzi showed an O2
2752 | Ho et al.
Fig. 7. Steady-state O2 partial pressure distribution at 20 kPa O2
and 0 kPa CO2 at 20 C (A) and 1 C (B). The coloured bars
indicate gas partial pressure (kPa).
concentration near the core of 0.16 kPa at the same storage
condition. Braeburn has a high risk of anoxia near the core
at these ultra-low O2 storage condition since the O2
concentration reached to a level of 0.014 kPa.
Discussion
Fig. 6. O2 and CO2 concentration as a function of time in a closed
jar of Kanzi (A), Jonagold (B), and Braeburn (C). Dashed lines (- -)
and solid lines (—) indicate the O2 and CO2 partial pressure in jars
as predicted by the continuum gas exchange model. The symbols
(3) and (o) represent the measured O2 and CO2 gas partial
pressures. The initial condition was 20 kPa O2 and 0 kPa CO2 at
10 C. The dash dotted line (– –) and symbol (+) represent the
simulated and measured CO2 gas partial pressure in the jar when
initial condition was set to 0 kPa O2, 0 kPa CO2 and 10 C.
Low values of diffusivity of the skin were measured in the
different apple genotypes. Schotmans et al. (2003) and Ho
et al. (2006a) also observed a low diffusivity of the skin in
other fruit (3.331010 m2 s1 and 1.8631010 m2 s1 for O2
diffusivity; 4.331010 m2 s1 and 5.0631010 m2 s1 for
CO2 diffusivity, respectively). The values of diffusivity of
the cortex tissue were at least one order of magnitude larger
than that of the skin. Also Mannapperuma et al. (1991)
found values of 2.673109 m2 s1 and 3.283109 m2 s1 for
the O2 and CO2 diffusivity of ‘Golden Delicious’ apple
tissue while an O2 diffusivity of 1.713109 m2 s1 and CO2
diffusivity of 19.53109 m2 s1 was reported in pear cortex
tissue by Lammertyn et al. (2001a). The CO2 diffusivity was
much higher than the O2 diffusivity for each genotype. This
Genotype effects on internal gas gradients in apple fruit | 2753
is due to the high solubility of CO2 in the liquid phase,
which facilitates the CO2 gas exchange in the tissue
microstructure (Ho et al., 2009).
Figure 8A shows the O2 diffusion properties of the
different apple genotypes and Conference pear as a function
of porosity. The values of D02,tissue and Vm,O2 of Conference
pear were taken from Ho et al. (2006a) and Lammertyn
et al.(2001b), respectively. There is clearly a relationship
between porosity and diffusivity: a large porosity facilitates
gas exchange and leads to a large diffusivity.
A large variability of the measured permeation properties
was observed among the samples. While diffusion dominates the gas transport process in intact fruit, differences in
diffusion rates of the different gases leads to total pressure
gradients that caused convective exchange as described by
the permeation process. The high variation of measured
permeation properties did not affect the local respiratory
gas profiles to a large extent (see more detail in Supplementary Fig. S2 at JXB online).
Michaelis–Menten kinetics has been applied widely to
describe the respiration characteristics from intact fruits to
the cellular level (Peppelenbos and van’t Leven, 1996;
Hertog et al., 1998; Lammertyn et al., 2001b; Ho et al.,
2008). It was observed here that the values of the maximal
O2 consumption rate Vm,O2 and the maximal CO2 production rate Vm,f,CO2 of tissue were larger than those of the
intact fruit. This might be due to increased respiration due
to a stress response of the tissue when cut (Kato et al., 2002;
Hodges and Toivonen, 2008). Such effects are difficult
to quantify because there is currently no method available
to measure in vivo respiration kinetics. However, it may
explain some of the mismatches of Vm,O2 and Vm,f,CO2
between tissue and intact fruit. For the macroscale model,
the values of Vm,O2 and Vm,f,CO2 were taken from the values
of the intact fruit measured from the batch used in
validation. A good agreement was found between the model
and the experiment (Figs 5, 6). Note that Vm,O2 and Vm,f,CO2
depend on initially available enzyme concentration (Hertog
et al., 1998). Therefore, those values may change with fruit
maturity and season.
The measured O2 concentration inside the fruit in Fig. 5
confirmed the existence of concentration gradients in apple
fruit as predicted by the gas exchange model. Gradients
were also observed in seeds reported by Rolletschek et al.
(2003, 2004) and Borisjuk and Rolletschek (2009). Note
that, in seeds, embryo photosynthesis has been shown to
elevate the internal O2 concentration from anoxia up to
approximately 50% of atmospheric levels (Rolletschek et al.,
2003). Here, values were as low as 0.75% in Braeburn to
36.7% in Jonagold apple for ambient conditions of 20% and
20 C. In contrast to our findings, Schouten et al. (2004)
found no O2 gradient in pear fruit with a similar measurement methodology. When we inserted the needle into the
fruit without using a septum, as in their experiment, no O2
gradients were found either, most probably because of
leaking of atmospheric O2 along the length of the probe
because of the very high diffusivity or O2 in the air
(1.63105 m2 s1) compared to liquid (2.013109 m2 s1)
(Lide, 1999). When a rubber septum glued onto the surface
of the fruit to avoid leaking was used, large O2 gradients
were found. The absence of O2 gradients by Schouten et al.
(2004) might, therefore, be a measurement artefact.
The shape of the apple fruit is more similar to the sphere
than the cylinder. Therefore, the model was simplified with
variations of gas concentrations in the radial direction (r),
which was implemented by means of different diffusivity
values in the inner and outer cortex (Table 1). A simulation
taking into account a smaller vertical diffusion resulted in
lower O2 and larger CO2 concentrations in the centre of the
fruit. The extreme case of ambient air at storage temperature (20.8% O2, 0% CO2, 1 C) was considered. Small O2
concentration differences of –0.47, –0.39, and –0.15 kPa
and small CO2 concentration differences of 0.12, 0.2, and
0.19 kPa for Kanzi, Jonagold, and Braeburn, respectively,
were found, taking into account smaller vertical diffusivity
compared with simulation without smaller vertical diffusivity. These differences were insignificant for the overall
physiological processes in the fruit.
The model was applied to different genotypes of apple
fruit. Prediction of the internal gas concentration on those
Fig. 8. (A) Diffusivity of tissue (D02,tissue) versus porosity, and (B) maximal O2 consumption rate (Vm,O2 at 10 C) versus O2 diffusivity of
different apple genotypes and Conference pear. The values of D02,tissue and Vm,O2 of Conference pear were taken from Ho et al. (2006a)
and Lammertyn et al. (2001b), respectively. Bars indicate 95% confidence intervals of the mean.
2754 | Ho et al.
genotypes showed considerable differences. Internal gas
partial pressure affects its respiration, and, hence, energy
levels as well as the oxidation state of the antioxidant
system (Rolletschek et al., 2002; Franck et al., 2007). The
gas exchange model may, therefore, be useful for predicting
the internal gas concentration in order to control the plant’s
metabolism by changing the oxygen availability to the
correct level without causing anoxic conditions in the centre
of the fruit.
Anoxia due to the high diffusion barrier and metabolic
rate may lead to physiological disorders in the centre of the
fruit. Conference pear has been reported to be susceptible to
physiological disorders when the fruit was stored at low O2
condition (1% O2, 5% CO2 at –1 C; Franck et al., 2007).
Similar results were also found with Braeburn when the fruit
was stored at 1.5% O2, 1.25% CO2 at 0 C (Gong et al.,
2001). Susceptibility to physiological disorders may, therefore, be related to high respiration and low diffusion
properties of plant tissue (Fig. 7B). Conference pear has
been shown to have a high O2 consumption rate (Lammertyn
et al., 2001b) compared with other apple fruits.
From the results of the CA storage computation, it has
been demonstrated that Jonagold is indeed suitable for
long-term storage without a high risk of storage disorder
development (Saquet et al., 2000), while Braeburn has a high
sensitivity to browning at ULO storage conditions (1.5%
O2, 1.25% CO2 and 0 C, Gong et al., 2001). A simulation
of Braeburn at its conventional storage condition of 3 kPa
O2, 0.7 kPa CO2 at 1 C indicates that the O2 concentration
near the core attains a value of 0.178 kPa which was less
anoxia than storage at ULO conditions (O2 concentration
reached 0.014 kPa at 1% O2, 2.5% CO2 at 1 C). A
predicted O2 concentration near the core during a conventional storage of Kanzi at 2 kPa O2, 0.7 kPa CO2 and 1 C
was 0.6 kPa indicating that it is less susceptible to anoxia at
low oxygen levels than Braeburn.
Note that the macroscale model described here considered
the tissue as continuum. The diffusion properties, therefore
were considered as apparent parameters incorporating both
actual physical material constants and the micro-structure
of the tissue. However, plant tissue has a cellular structure
with air-filled pores and cells. This microscale topology will
contribute to a large extent to gas transport in the tissue
(Verboven et al., 2008). Even large intracellular concentration gradients were found leading to a lower intracellular
concentration compared with that calculated by the presented macroscale model (Ho et al., 2009).
Conclusions
The purpose of this article was to understand more fully the
relationship between gas gradients in plant organs in relation
to the metabolism and morphology that are dependent on
genotype. A macroscale gas exchange model demonstrated
the relationships and was used to investigate optimal postharvest conditions for apple fruit (cv. Kanzi, Jonagold, and
Braeburn). Morphological effects were evident from the
differences in diffusion properties of the different tissues
(cortex and skin) of the fruits, as well as from the
representative fruit shape and tissue composition. The
metabolic features were incorporated by a non-competitive
inhibition model of the respiration–fermentation metabolism,
that was identified experimentally and caused gradients of
oxygen and carbon dioxide in the fruits, even at ultralow oxygen concentrations in the storage environment. An
in silico study then revealed that the strength of these
gradients of metabolic gases depended on the respiration
and diffusion properties of apple genotypes. Jonagold
showed its potential for low oxygen storage while Braeburn
indicated a risk of storage disorder development at the same
condition compared to Jonagold and Kanzi due to the strong
diffusion barrier of the cortex tissue. The approach is also
valid for other plant organs, such as roots and leaves where
there are concerns with responses to impeded aeration.
Supplementary data
Supplementary data can be found at JXB online.
Supplementary information. S1. Diffusivity measurement.
S2. Respiration kinetics model. S3. Porosity measurement.
Supplementary Table S1. Parameters of linear fitting of
gaseous diffusivity of cortex tissue along the radial direction
and their 95% confidence interval.
Supplementary Table S2. t test between diffusivity groups
of different gasses, tissues and genotypes.
Supplementary Table S3. Estimated O2 diffusivities of
cortex and skin from the measured O2 concentration in the
fruit.
Supplementary Fig. S1. (a) O2 diffusivity (*) and CO2
diffusivity (o) of apple tissue along vertical direction for
Kanzi, Jonagold and Braeburn; (b) Position of sampling of
gas diffusion measurement in the vertical direction.
Supplementary Fig. S2. Effect of permeation on the
respiratory gas concentration from the center to the surface
of the fruit.
Supplementary Fig. S3. O2 diffusivity (*) and CO2
diffusivity (o) of apple tissue along the radial direction for
Kanzi, Jonagold and Braeburn
Acknowledgements
The authors wish to thank the Research Council of the KU
Leuven (OT 04/31, OT 08/023), the Flanders Fund for
Scientific Research (project G.0603.08), and the Institute for
the Promotion of Innovation by Science and Technology in
Flanders (project IWT-050633) for financial support. Quang
Tri Ho is post-doctoral fellow of the Research Council of
the KU Leuven.
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