Ho et al., 2006

Postharvest Biology and Technology 41 (2006) 113–120

Gas diffusion properties at different positions in the pear

Q. Tri Ho ∗, Bert E. Verlinden, Pieter Verboven, Bart M. NicolaıBIOSYST-MeBioS, Faculty of Bioscience Engineering, Katholieke Universiteit Leuven, Willem de Croylaan 42, B-3001 Leuven, Belgium

Received 31 August 2005; accepted 2 April 2006

Abstract

Gas transport properties of fruit are important for understanding the internal atmosphere during controlled atmosphere storage. The gasdiffusivities at different positions in the pear were determined using a measurement set-up with optical sensors. In addition, the effect oftemperature, picking date and browning-inducing conditions on the diffusion properties of pear fruit tissue were studied. The diffusivities ofO2 and CO2 were low at the skin with values of (1.86 ± 0.78) × 10−10 and (5.06 ± 3.15) × 10−10 m2/s. Along the equatorial radial directionof the pear, gas diffusivities in the cortex tissue were almost constant with an average of (2.22 ± 0.28) × 10−10 and (2.32 ± 0.21) × 10−9 m2/sfor O2 and CO2 diffusivities, respectively, while diffusivities were much higher in the core of the pear. Results showed that the diffusivitiesof gas in the tissue along the vertical axis of the pear were (11.1 ± 7.2) × 10−10 and (6.97 ± 3.79) × 10−9 m2/s for O2 and CO2 diffusivities,rivi©

K

1

sffOeo(tmfibaam

0d

espectively. Gas diffusion properties in the vertical axis were higher than along the equatorial radius axis direction. The O2 diffusivity was notnfluenced by temperature while temperature had a statistically significant effect on CO2 diffusivity although small compared to its biologicalariable. Picking date had no effect on the gas diffusivities. Diffusivities in brown tissue of disordered pears were smaller than in sound tissuerrespective of whether the sound tissue came from a healthy or a disordered pear.

2006 Elsevier B.V. All rights reserved.

eywords: Diffusivity; Measurement; Respiration; Pyrus communis; Modeling; Optical gas sensors

. Introduction

Gas transport properties of tissues are important to under-tand the tissue aeration process and respiration physiology ofruit. The gas-filled intercellular space is thought to be the dif-usion pathway through plant organs for supplying adequate

2 for respiration and CO2 for photosynthesis (Terashimat al., 2001). Transport of gases in fruit and vegetablesccurs through the wax layer on the epidermis, gas porese.g., stomata and lenticels) in the skin and mainly throughhe intercellular space in the fruit tissue. The diffusion ofetabolic gases through tissue is usually described by Fick’srst law which states that the flux of a gas diffusing through aarrier of tissue is proportional to the concentration gradientcross this barrier with the diffusion coefficient acting asn apparent proportionality coefficient. The most advancedodel of gas transport in fruit to date has been developed by

∗ Corresponding author. Tel.: +32 16 322384; fax: +32 16 322955.E-mail address: [email protected] (Q.T. Ho).

Lammertyn et al. (2003a) and consists of a system of coupledrespiration-diffusion equations. The authors used this modelto investigate the effect of storage atmosphere conditions onthe development of controlled atmosphere-related disorderssuch as core breakdown in ‘Conference’ pears (2003b). Themodel was validated and a reasonably good correspondencebetween measured and predicted internal gas concentrationswas found. One of the reasons for the remaining modelprediction error is probably the incomplete knowledgeabout the tissue diffusivity which appears in the model as aparameter.

Since pears are composed of skin, cortex and core, dif-ferences in tissue structure are found at different positions inthe pear. Therefore, it is expected that the diffusion propertiesof the fruit are different at different positions and in differentdirections (anisotrope) in the fruit. Also harvest maturity mayhave an effect on the diffusion properties of the fruit. When‘Conference’ pears are picked late, the chance of developinginternal browning during long term controlled atmospherestorage is much higher (Lammertyn et al., 2000; Verlinden et

925-5214/$ – see front matter © 2006 Elsevier B.V. All rights reserved.oi:10.1016/j.postharvbio.2006.04.002

mailto:[email protected]

dx.doi.org/10.1016/j.postharvbio.2006.04.002

114 Q.T. Ho et al. / Postharvest Biology and Technology 41 (2006) 113–120

al., 2002). This disorder is due to membrane damage, result-ing in cell death and as a consequence the leaking of cellliquid into the intercellular space, possibly affecting the dif-fusion coefficients. Therefore, it would be interesting to knowthe gas diffusivity of brown tissue of a disordered pear. Also,reducing the temperature has been known to be the main fac-tor in retarding the metabolism of fruit and extending the shelflife of the produce. The effect of temperature on the respi-ration has been described using Arrhenius’ Law (Cameronet al., 1994; Lammertyn et al., 2001b). However, the effectof temperature on gas diffusion should be known as wellto understand the internal atmosphere corresponding to theexternal atmosphere conditions at a certain temperature.

Several methods have been developed to measure thegas transport properties of various horticultural commodi-ties (Cameron and Yang, 1982; Banks, 1985) for which itwas assumed that the skin was the only barrier to gas dif-fusion and the fruit internal gas concentration was constant.Fick’s first law of diffusion has some limitations to estimatediffusion properties of fruit in this way since the concentra-tion gradient in the skin or tissue is often transient. Further,the assumptions of constant internal gas concentration withinthe fruit and considering the skin as the only barrier to gasdiffusion do not hold for all types of commodities, espe-cially not for fruit with a high tissue density. Recently, someauthors (Lammertyn et al., 2001a; Schotsmans et al., 2003,2eStmtcceomfiifpscOtmwdh

mdssnb

2. Materials and methods

2.1. Fruit material

Pears (Pyrus communis cv. Conference) were harvestedin September at the Fruitteeltcentrum (Rillaar, Belgium). Toinvestigate maturity effects on diffusivity properties of pearduring storage, pears were harvested at the commercial har-vest time (8 September 2004) and a late harvest time (22September 2004). Then, pears were cooled and stored accord-ing to commercial protocols for a period of 21 days at −0.5 ◦Cpreceding CA storage (2.5 kPa O2, 0.7 kPa CO2 at −0.5 ◦C)until they were used for the experiments.

An investigation of the O2 and CO2 diffusivities at differ-ent positions in the pear was carried out. A schematic view ofsampling is given in Fig. 1. In order to assess the distributionof diffusivities along the radial direction, in total 44 tissuesamples from 14 different pears were taken along the radialdirection at the equatorial region of the fruit from the cortexto the core of the pear. Additionally, the diffusivities of sevenskin samples from seven pears were measured. The samplingprocedure is described in detail in Ho et al. (2006). Becauseof the shape of the pear we did not expect large gradientsin the two tangential directions perpendicular to the radialdirection. It is, therefore, not important to know the diffusivi-ties in these directions accurately. The sample position on therfdtrtd

tfa(ipM

004; Ho et al., 2006) have been studying gas exchange prop-rties at the tissue level. Lammertyn et al. (2001a,b) andchotsmans et al. (2003) determined the diffusion proper-

ies of the tissue taking into account tissue respiration. Theireasurement set-up consisted of two chambers separated by a

issue sample. The changes in the gas concentration in the twohambers were measured after applying an initial gas con-entration difference between the two chambers. Lammertynt al. (2001a) determined on this way diffusion propertiesf pear tissue taking into account respiration. However, theeasurement of gas diffusion properties of fruit tissue is dif-cult due to the available gas measurement techniques, the

nherent biological variability of biological material as well asast deterioration and respiration activity of cut tissue sam-les. Recently, Ho et al. (2006) developed a measurementet-up for gas diffusivities in tissue using fluorescent opti-al probes. The optical sensors produced good informative2 and CO2 partial pressure versus time profiles. Diffusivi-

ies of O2 and CO2 were estimated based on a finite elementodel describing simultaneous O2 and CO2 gas transport asell as respiration in the tissue. The authors found that theiffusivity of CO2 in the tissue was one order of magnitudeigher than O2 diffusivity.

The specific objectives of this study were (1) to deter-ine the O2 and CO2 diffusivities at different positions and

irections in the pear and (2) to study whether the diffu-ion properties of pear tissue were affected by maturity stage,torage browning-inducing conditions and temperature. Theovel measurement setup described by Ho et al. (2006) wille used for this purpose.

adial direction was expressed as the relative distance (x/R)rom the center of the pear. In addition, sampling was alsoone in the vertical axis of the pear from top to bottom. Inhe vertical axis, the sample position was expressed as theelative distance (y/L) from the stem end of the pear. Four-een samples of 14 different pears were used to measure theiffusivity in the vertical axis.

To study storage condition effects on diffusivity proper-ies, pears were stored according to commercial protocolsor a period of 21 days at −0.5 ◦C preceding CA stor-ge (described above) and browning-inducing conditions0.5 kPa O2, 5 kPa CO2 at −0.5 ◦C). Pears in browning-nducing conditions were stored at least 6 months until theresence of the storage disorder (browning) was observed.ore than eight samples of sound tissue and brown tissue of

Fig. 1. Schematic view of sampling.

Q.T. Ho et al. / Postharvest Biology and Technology 41 (2006) 113–120 115

Fig. 2. Schematic view of cross-section of the experimental setup.

disordered pears for each combination of picking time andstorage condition were taken to measure diffusion properties.The samples were taken in the cortex tissue along the radialdirection at relative positions from the center ranging from0.4 to 0.8.

2.2. Diffusion measurement

The set-up developed by Ho et al. (2006) was used. Theset-up consisted of two chambers separated by a disked shapetissue sample (Fig. 2). Due to different gas concentrations inthe measurement and flushing chambers, diffusion took placethrough the tissue sample in between. The method involvedmeasuring O2 and CO2 partial pressure profiles as a func-tion of time in a small measurement chamber closed fromthe environment with the tissue disk. At the initial time, themeasurement chamber contained 30 kPa O2, 3 kPa CO2 and67 kPa N2. In the flushing chamber the gas concentration wasmaintained constant by gas flushing with N2 containing 5 kPaO2, 8 kPa CO2, at 10 L/h. O2 concentrations were chosen highenough to avoid fermentation activity. Additionally the O2and CO2 gradients were chosen in a way that the resultingO2 and CO2 fluxes through the sample would compensateeach other avoiding a total pressure difference between thetwo chambers. Total pressure difference is to be avoided as itwtfBcflO4i

Es

temperatures of 5, 10 and 20 ◦C. The temperature of thesystem was kept constant by submerging the set-up in atemperature-controlled water bath (F10-HC, Julabo LaborTechnik GmbH, Seelbach, Germany). To take into accountthe temperature dependency of the optical sensor signals, thesensors were recalibrated for each measurement at a differenttemperature. Eight cortex tissue samples were taken from thefruit to measure the O2 and CO2 diffusivities at each tempera-ture condition. Samples of cortex tissue were taken along theradial direction at a relative position x/R between 0.4 and 0.8(Fig. 1). Sampling and experimental procedures have beendescribed in more details by Ho et al. (2006).

2.3. Respiration measurement

A non-competitive inhibition model (Peppelenbos andvan’t Leven, 1996) was used to describe the respiration ofthe tissue as follows:

RO2 = Vm,O2PO2

(Km,O2 + PO2 )(1 + (PCO2/Kmn,CO2 ))(1)

RCO2 = rqoxRO2 (2)

with Vm,O2 (mol/m3s) the maximum O2 consumption rate,Km,O2 (kPa) the Michaelis–Menten constant for O2 con-sCctapf3b

wuhtraeaao

TR

P

V

E

K

K

r

D

ould result in hydraulic gas transport rather than diffusionransport (Ho et al., 2006). The gas mixtures were preparedrom pure gases by means of mass flow controllers (5850 S,rooks Instruments, The Netherlands). The O2 and CO2 con-entrations were measured in the measurement chamber withuorescent optical probes (Foxy-Resp and FCO2-R, Oceanptics, Duiven, The Netherlands). Pressure sensors (PMP070, GE Druck, Germany) monitored the pressure changesn each chamber during the measurements.

Most of the measurements were carried out at 20 ± 0.3 ◦C.xcept when investigating temperature effects on diffu-ivity properties of pear, experiments were carried out at

umption, PO2 (kPa) the O2 partial pressure, PCO2 (kPa) theO2 partial pressure, Kmn,CO2 (kPa) the Michaelis–Mentenonstant for non-competitive CO2 inhibition, rqox the respira-ion quotient at high O2 partial pressure, and RO2 (mol/m3s)nd RCO2 (mol/m3s) is the O2 consumption rate and CO2roduction rate of the sample, respectively. Since gas dif-usion was studied at a high O2 partial pressure (from 5 to5 kPa O2), no fermentative CO2 production term needed toe included in Eq. (2).

The respiration parameters of Eqs. (1) and (2) at 20 ◦Cere measured by Ho et al. (2006) on similar samples assed in the current study but on other pears from the samearvest batch and are listed in Table 1. To study the effect ofemperature on the maximal O2 consumption rate (Vm,O2 ),espiration measurements were carried out at 5, 10 and 20 ◦Ct 30 kPa O2 combined with 0 kPa of CO2 as described by Hot al. (2006). The samples were prepared in the same manners the samples for the diffusion set-up to approach the samemount of wounding and respiration. The temperature effectn Vm,O2 was described by Arrhenius’s law.

able 1espiration parameters of the cortex tissue of ‘Conference’ pear

arameter Estimated value

m,O2 (× 104 mol/m3s) 2.47 ± 0.12

a,Vm,O2(kJ/mol) 80.2 ± 5.6

m,O2 (kPa) 1.16 ± 0.44

mn,CO2 (kPa) 135 ± 40

qox 0.95 ± 0.04

ata area accompanied by ±S.E.


2.4. Respiration diffusion model and parameterestimation

The model construction and parameter estimation pro-cedure was described by Lammertyn et al. (2001a). Theequations for the respiration diffusion model are given by

∂C

∂t= D∇2C + R (3)

D∂C

∂n= h(C∞ − C) at Γ (4)

where ∂/∂n denotes partial derivative in the outward normaldirection, C the O2 or CO2 concentration (mol/m3), D thediffusion coefficient (m2/s), R the O2 consumption or CO2production (mol/m3s), �2 the Laplace operator (1/m2), h theconvective mass transfer coefficient (m/s), t the time (s) andΓ is the surface of the tissue exposed to the flushing chamber.Index ∞ refers to the gas atmosphere in the flushing chamber.

The concentration change in the measurement chamberwas due to the diffusion of the gas through the tissue and therespiration taking place in the tissue. The tissue respirationas a function of the O2 and CO2 partial pressure describedabove was incorporated in Eq. (3).

Eqs. (3) and (4) were solved using the finite elementmethod in one dimension using the FemLab finite elementcmaniTtfec(t

Mdmc

cf

D

wtDwDbd

To investigate the variability of diffusivity within a pearand between pears, an analysis of variance was carried outon the gas diffusivities of the four samples per pear of ninepears that were measured along the radial axis in the cortextissue at the relative position from the center ranging from0.35 to 0.9.

Estimation of the activation energy described by Arrhe-nius’s Law, and statistical analyses were performed usingthe SAS/STAT software 8.2 (SAS Institute Inc., Cary NC.USA).

3. Results

3.1. Position-dependent diffusivity in a fruit

To study the effect of position in the fruit on gas diffusion,tissue samples were taken along the radial direction at theequatorial region of the fruit from the skin to the core of thepear as well as in the vertical axis from the top to the bottomof the pear. The skin had the lowest diffusivity values whichwere (1.86 ± 0.78) × 10−10 and (5.06 ± 3.15) × 10−10 m2/sfor O2 and CO2, respectively. Along the radial direction, O2and CO2 diffusivities seemed uniform throughout the cortextissue while diffusivities were high in the core of the pear(Fig. 3). CO diffusivities were much higher compared toOaTTffas

Fapt(m(

ode (Femlab 3.1, Comsol AB, Stockholm). The gases in theeasurement chamber and the sample tissue were considered

s two materials consisting of 20 elements each resulting in 41odes in total. The diffusion coefficient of the gas moleculesn air at 20 ◦C was set equal to 6 × 10−5 m2/s (Lide, 1999).he sample was modeled as the second material, for which

he diffusion coefficient was to be estimated. The gas trans-er from the flushing chamber to the tissue or the skin wasxpressed by Eq. (4) as a convection boundary condition. Theonvective mass transfer coefficient was taken as very high1 × 106 m/s). This means it was assumed that no resistanceo gas transport occurred at this interface.

An iterative least squares estimation procedure written inATLAB (The Mathworks, Inc., Natick, USA) was used to

etermine gas diffusivities of the pear tissues by fitting theodel solutions to the measured O2 and CO2 concentration

hange profiles.The position dependent O2 and CO2 diffusivities of the

ortex tissue along the radial direction were described by theollowing expression:

= (Dc − D0) exp(− x

aR

)+ D0 (5)

ith Dc (m2/s) is the diffusivity in the center of the pear, x/Rhe relative position along the radial direction of the fruit,

0 (m2/s) the asymptotic diffusivity and a is the coefficienthich determines how fast diffusivity D decreases towards0 along the radial direction. Eq. (5) was fitted to the datay non-linear regression. A logarithmic transformation of theata was applied to stabilize the variance.

2

2 diffusivity. The model parameters of Eq. (5) for the O2nd CO2 diffusivity along the radial direction are given inable 2. A high variation among the samples was also found.he analysis of variance carried out on the O2 and CO2 dif-

usivities from the samples coming from the relative positionrom the center ranging from 0.35 to 0.9 showed that the vari-bility of the O2 and CO2 diffusivity within a pear was theame as the variability between pears.

ig. 3. O2 and CO2 diffusivity of tissue along the radial direction of the peart the equatorial region. x/R is the relative distance from the center of theear along the radial direction. Values of O2 and CO2 diffusivities of cortexissue are indicated as (*) and (×), respectively. Solid line (—) and dash line- -) represent the model for O2 and CO2 diffusivities of cortex tissue. Theean values of O2 and CO2 diffusivities of the skin are indicated as (�) and�), respectively. Bars indicate standard deviations surrounding the mean.


Table 2Model parameters describing O2 and CO2 diffusivities distribution along theradial direction at the equatorial region

Dc (× 10−10 m2/s) D0 (× 10−10 m2/s) a

O2 diffusivity 37.25 ± 7.32 2.22 ± 0.28 0.10 ± 0.02CO2 diffusivity 85.85 ± 14.26 23.18 ± 2.12 0.10 ± 0.04

Data area accompanied by ±S.E.

Since the coefficient a was 0.1 for both O2 and CO2 diffu-sivity along the radial direction, the diffusivity almost reachedthe value of D0 at positions near the skin (Fig. 3). Therefore,D0 can be considered as diffusivity near the skin.

Gas diffusion along the vertical axis of the pear was moreor less constant (Fig. 4). Results showed that the gas dif-fusivities in the tissue along the vertical axis of the pearwere (11.1 ± 7.2) × 10−10 and (6.97 ± 3.79) × 10−9 m2/s forO2 and CO2, respectively. Gas diffusion properties in thevertical axis were higher than along the equatorial radialdirection.

3.2. Maturity effect and storage condition on gasdiffusivities

To study the effect of fruit maturity and storage con-ditions on the gas diffusion properties, the optimal pickedpears and late picked pears were stored at normal storage andbrowning-inducing conditions. During 6 months of storagein browning-inducing conditions, brown heart disorder wasfound in the late picked pears only. The tissue of disorderedpears was classified into two classes. Non-browning tissue ofdisordered pears was classified as sound tissue and browningtissue of disordered pears was categorized as brown tissue.Diffusion properties of tissue of healthy pears, sound tissueoF

Fyyar

Fig. 5. O2 and CO2 diffusivity along the radial direction at the equatorialregion of different picked pears and storage conditions. Legend: (1) indi-cates sound tissue of optimal picked pear under normal storage conditions;(2) indicates sound tissue of late picked pear in normal storage conditions;(3) indicates brown tissue of late picked pear in browning-inducing condi-tions; (4) indicates sound tissue of late picked pear in browning-inducingconditions. Vertical bars indicate 95% confidence intervals of the mean.

In healthy pears, the average O2 diffusivity in the tis-sue of the optimal picked pears and late picked pearswas (2.87 ± 0.45) × 10−10 and (2.45 ± 0.35) × 10−10 m2/s,respectively, while the average CO2 diffusivity in the tis-sue of the optimally picked pears and late picked pearswas (2.6 ± 0.36) × 10−9 and (2.22 ± 0.72) × 10−9 m2/s. TheCO2 diffusivity of optimally picked pears and late pickedpears was higher than the O2 diffusivity. Large variabilitywas found among the experimental values so that there wereno significant differences between the optimally picked pearsand late picked pears.

The average O2 diffusivity of the sound tissue and browntissue of late picked pears in browning-inducing conditionswas (2.46 ± 0.65) × 10−10 and (1.85 ± 0.64) × 10−10 m2/s,respectively, while the average CO2 diffusivity of thesound tissue and brown tissue of late picked pears were(1.58 ± 0.76) × 10−9 and (1.42 ± 0.35) × 10−9 m2/s. The O2and CO2 diffusivities of brown tissue in late picked pearswere less than those of healthy tissue of optimal picked pears(Fig. 5).

Due to the large variability, the diffusivities of sound tissueof brown pear were not different from the diffusivities ofhealthy tissue of late pears.

3.3. Temperature affected on respiration and gasd

ppws

f brown pears and brown tissue of brown pears are shown inig. 5.

ig. 4. O2 and CO2 diffusivity of tissue along the vertical axis of the pear./L is the relative position of the sample along the vertical axis of the distancefrom the top and the length L of pear. Values of O2 and CO2 diffusivities

re indicated as (*) and (×), respectively. Solid line (—) and dash line (- -)epresent the mean O2 and CO2 diffusivities of cortex tissue.

iffusivity of tissue

Arrhenius’ law was applied to study the effect of the tem-erature on the respiration as well as diffusion properties ofear tissue. Three temperature conditions (5, 10 and 20 ◦C)ere compared for their effect on the respiration and diffu-

ivity in cortex tissue.


Fig. 6. Arrhenius plot of the maximal O2 consumption rate (Vm,O2 ) of cortextissue. The line indicates the Arrhenius equation while the symbols indicatethe measured values.

In Fig. 6, the Arrhenius plot of the maximal O2 con-sumption rate (Vm,O2 ) is shown. The Arrhenius equa-tion described the experiment well as was confirmed bythe high R2 value (R2 = 0.98). The results showed thattissue respiration was strongly affected by the tempera-ture since the activation energy for tissue respiration was80.2 ± 5.6 kJ/mol.

Samples of cortex tissue were taken along the radial direc-tion to study the effect of temperature on O2 and CO2 dif-fusivities. Large variability of O2 and CO2 diffusivity wasobserved. The CO2 diffusivity was much higher than the O2diffusivity. Arrhenius plots of O2 and CO2 diffusivities areshown in Fig. 7. Since the activation energy for O2 diffusivityEa,DO2 with a 95% confidence interval was (−9 ± 13) kJ/mol,there was no significant temperature effect on the O2 dif-fusivity. The activation energy for CO2 diffusivity Ea,DCO2

was 17 ± 13 kJ/mol. A statistically significant effect of tem-perature on the CO2 diffusivity was found but it was smallcompared to the biological variability which was concludedfrom the low R2 value (R2 = 0.15).

4. Discussion

4.1. Position-dependent diffusivities in a fruit

The gas diffusivity experiment along the radial directionshowed that O2 and CO2 diffusivities were small in the skin,uniform throughout the cortex tissue and were high in the coreof the pear. Similar results were also found by Schotsmans etal. (2003). The diffusivity appeared to be the smallest in theskin, larger in the cortex region and the largest in the core.However, due to the very high variability this trend was notstatistically significant.

A report by Schotsmans (2003) showed that diffusivitydistribution along the radial direction in ‘Jonica’ apples wasdifferent. The diffusivity was small in the skin, significantlylarger in the cortex tissue and again significantly smaller nearthe core. The apple tissue showed the core had a low intercel-lular air space volume (11%) which might have resulted ina significant reduction of gas transport while the intercellu-lar air space volume of apple cortex tissue was substantiallyhigher (19%) (Schotsmans, 2003).

Specific features found in cortex tissue are sclereids. Thesclereids seem to be concentrated in the outer cortex tis-sue and their amount decreases toward the core. Locally,these sclereid groups can pose local barriers for gas trans-port. This would result in local adverse gas conditionsa(sbbvssot2

r

ssue at d
Fig. 7. Arrhenius plot of O2 and CO2 diffusivities in the cortex ti
nd thus trigger the local development of storage disordersSchotsmans, 2003). Different amounts and distribution ofclereids between and in pears might partly explain the highlyiological variability of the pear samples. Postharvest productehavior is inherently affected by the omnipresent biologicalariation (Hertog et al., 2002). Biological variation in diffu-ivities of the pear could be due to for instance difference inhape and size of the pears during development, the amountf lignified cells, irregular cell distribution, growing condi-ions which may depend on the position in the tree (Ho et al.,006).

A higher diffusivity along the vertical axis than along theadial direction was observed. It could be that the vascular

ifferent temperatures. Vertical bars indicate standard deviations.


bundles arranged in the direction from top to bottom of thepear facilitated the gas transport. Therefore, continuity of gastransport channels in this direction could be better than alongthe radial direction and explain the high diffusivity in thevertical axis compared to the values along the radial direction.

From our experiments, it appeared that the O2 diffusivitywas smaller than the CO2 diffusivity. CO2 has a higher solu-bility in water than O2. For instance, the concentration of CO2in equilibrium with 8 kPa (3.28 mol/m3) CO2 in the gas phaseis 3.1 mol CO2 /m3 at 20 ◦C in water while for O2 the con-centration in water in equilibrium with 30 kPa (12.31 mol/m3)for O2 in the gas phase at 20 ◦C is 0.41 mol/m3. The diffu-sivity of CO2 in air and water at 20 ◦C are 1.6 × 10−5 and1.67 × 10−9 m2/s, respectively (Lide, 1999). Therefore, a sig-nificant portion of CO2 can be transported in the liquid phaseas well while O2 is mainly transported in the gas phase of theintercellular space of pear fruit tissue. This can explain thehigh diffusion coefficient of CO2 compared to O2 diffusioncoefficient.

4.2. Maturity effect and storage condition on gasdiffusivities

Reports about gas exchange properties, more specificallyskin resistance of fruit, are not very consistent. While someauthors (Park et al., 1993) found changes during the harvest-isinfdfpcSOaedEoii

daalcmoctlm

4.3. Temperature effect on respiration and gas diffusivityof tissue

Temperature is the most important factor to control fruitmetabolism during storage. The influence of the temperatureon the maximal O2 consumption rate is given by the activationenergy. The activation energy of the maximal O2 consump-tion rate of pear tissue in this experiment (80.2 ± 5.6 kJ/mol)was close to the value of intact pear (64.6 ± 4.8 kJ/mol)described by Lammertyn et al. (2001b).

Temperature effects on respiration rate are well known,however, attempts to characterize temperature influence ontissue diffusion have not revealed substantial temperatureeffects (Schotsmans, 2003). Moreover, a report by Dadzieet al. (1993) showed that there was no temperature effect onskin permeation. Calculating the activation energy of CO2diffusivity in air and water from literature data (Lide, 1999)shows values of 6.5 and 19.5 kJ/mol, respectively. The activa-tion energy of the CO2 diffusion in tissue found in the currentstudy was in between that in the gas and water phase and canbe considered in agreement with the literature data. The sol-ubility of O2 in water is low compared to CO2 and thereforemost of the O2 transport occurs in the gas phase. Further-more, it is likely that O2 and CO2 have the same behavior inthe gas phase. Hence, the low activation energy for diffusivityof CO found in the literature can be considered in agreementwtotTttdddbs

5

pwtwptwswhbif

ng period, others did not. Elgar et al. (1999) found that thekin resistance to gas diffusion of ‘Braeburn’ apples was notnfluenced by harvest date. Schotsmans et al. (2002) reportedo influence of harvest date on skin resistance to gas dif-usion for ‘Jonica’ and ‘Braeburn’ apples nor for ‘Doyenneu Comice’ and ‘Conference’ pears. Also no change of dif-usivity of O2 and CO2 in cortex tissue of ‘Conference’ear during 3 weeks before and 3 weeks after the commer-ial harvesting date was found by Schotsmans et al. (2003).chotsmans et al. (2003) reported an average diffusivity of2 and CO2 in fruit cortex tissue of (3.8 ± 0.4) × 10−10

nd (3.8 ± 0.5) × 10−9 m2/s, respectively. The results of thisxperiment also revealed no differences between O2 and CO2iffusivity of the optimally picked pears and late picked pears.ven though significant structural and composition changesccur during the maturation period, this does not necessarilymply that the diffusivity of the respiratory gases (O2, CO2)s influenced by these changes (Schotsmans et al., 2003).

Browning of pear tissue is related to membrane damageue to low O2 and high CO2 concentrations under controlledtmosphere storage. This phenomenon is probably caused byslow gas transport rate with small diffusion in the tissue

eading to a shortage of O2 and accumulation of CO2 in theenter of the fruit. The lower diffusivity values of brown tissueight be due to the fact that the intercellular space system

f brown pear might have low cross-section dimension of airhannels, restricted length and reduced continuity as most ofhe intercellular space is flooded by leaking cells. This couldead to a low efficiency of the intercellular space system as a

eans of aerating the tissue.

2ith the value Ea,DO2 of (−9 ± 13) kJ/mol found for O2 in

he current experiments. Temperature has a small influencen diffusion while it has a large effect on respiration, sincehe activation energy for the latter was 80.2 ± 5.6 kJ/mol.herefore, the gas diffusivity will not increase much due

o an increase of temperature while the respiration rate onhe other hand will rapidly increase. This could result in O2epletion and CO2 excess in the pear at high temperature andevelopment of large gas gradients that can lead to storageisorders (Schotsmans, 2003). Storage temperatures shoulde low enough to have low respiration activity resulting inmall gas gradients.

. Conclusion

The diffusivity of O2 and CO2 at different positions in theear was investigated. Both the diffusivity of O2 and CO2ere low at the skin. Along the equatorial radial direction of

he pear, the diffusivity of both O2 and CO2 in the cortex tissueas almost constant while they were high in the core of theear. Gas diffusion coefficients in the vertical axis were higherhan along the equatorial radial direction. The O2 diffusivityas not influenced by temperature while temperature had a

tatistically significant effect on CO2 diffusivity although itas small compared to its biological variability. Picking datead no effect on the gas diffusivity of tissue. Diffusivities inrown tissue of disordered pears were lower than diffusivitiesn sound tissue irrespective whether the sound tissue camerom a healthy or a disordered pear.


Acknowledgements

Financial support by the Flanders Fund for ScientificResearch (FWO-Vlaanderen) (project G.0200.02) and theK.U. Leuven (project IDO/00/008 and OT 04/31, IRO PhDscholarship for Q.T. Ho) are gratefully acknowledged. PieterVerboven is postdoctoral researcher of the Flemish Fund forScientific Research (FWO-Vlaanderen).

References

Banks, N.H., 1985. Estimating skin resistance to gas diffusion in applesand potatoes. J. Exp. Bot. 36, 1842–1850.

Cameron, A.C., Yang, S., 1982. A simple method for the determination ofresistance to gas diffusion in plant organs. Plant Physiol. 70, 21–23.

Cameron, A.C., Beaudry, R.M., Banks, N.H., Yelanich, M.V., 1994.Modified-atmosphere packaging of blueberry fruit: modeling respi-ration and package oxygen partial pressures as a function of temper-ature. J. Am. Soc. Hortic. Sci. 119, 534–539.

Dadzie, B.K., Banks, N.H., Cleland, D.J., Hewett, E.W., 1993. Role ofskin resistance to gas diffusion in the response of fruits to modifiedatmospheres. Acta Hortic. 343, 129–134.

Elgar, H.J., Watkins, C.B., Lallu, N., 1999. Harvest date and crop loadeffects on a carbon dioxide-related storage injury of ‘Braeburn’ apple.HortScience 34, 305–309.

Hertog, M.L.A.T.M., Lammertyn, J., Desmet, M., Scheerlinck, N.,Nicolaı, B.M., 2002. The impact of biological variation on postharvest

H

L

L

Lammertyn, J., Franck, C., Verlinden, B.E., Nicolaı, B.M., 2001b. Com-parative study of the O2, CO2 and temperature effect on respirationbetween ‘Conference’ pear cell protoplasts in suspension and intactpears. J. Exp. Bot. 362, 1769–1777.

Lammertyn, J., Scheerlinck, N., Jancsok, P., Verlinden, B.E., Nicolaı,B.M., 2003a. A respiration–diffusion model for ‘Conference’ pears.I. Model development and validation. Postharvest Biol. Technol. 30,29–42.

Lammertyn, J., Scheerlinck, N., Jancsok, P., Verlinden, B.E., Nicolaı,B.M., 2003b. A respiration–diffusion model for ‘Conference’ pears. II.Simulation and relation to core breakdown. Postharvest Biol. Technol.30, 43–55.

Lide, D.R., 1999. Handbook of Chemistry and Physics. CRC Press, NewYork.

Park, Y.M., Blanpied, G.D., Jozwiak, Z., Liu, F.W., 1993. Postharveststudies of resistance to gas diffusion in McIntosh apples. PostharvestBiol. Technol. 2, 329–339.

Peppelenbos, H.W., van’t Leven, J., 1996. Evaluation of four types ofinhibition for modeling the influence of carbon dioxide on oxygenconsumption of fruits and vegetables. Postharvest Biol. Technol. 7,27–40.

Schotsmans, W., 2003. Gas diffusion properties of pome fruit in relation tostorage potential. Ph.D. Dissertation. Katholieke Universiteit Leuven,Leuven.

Schotsmans, W., Verlinden, B.E., Lammertyn, J., Peirs, A., Jancsok, P.,Scheerlinck, N., Nicolaı, B.M., 2002. Factors affecting resistanceto gas diffusion of pip fruit. Postharvest Biol. Technol. 25, 169–179.

Schotsmans, W., Verlinden, B.E., Lammertyn, J., Nicolaı, B.M., 2003.Simultaneous measurement of oxygen and carbon dioxide diffu-sivity in pear fruit tissue. Postharvest Biol. Technol. 29, 155–

S

T

V

population dynamics. Postharvest Biol. Technol. 26, 253–263.o, Q.T., Verlinden, B.E., Verboven, P., Vandewalle, S., Nicolaı, B.M.,

2006. Simultaneous measurement of oxygen and carbon dioxide dif-fusivities in pear fruit tissue using optical sensors. J. Sci. Food Agric.,in press.

ammertyn, J., Aerts, M., Verlinden, B.E., Schotsmans, W., Nicolaı, B.M.,2000. Logistic regression analysis of factors influencing core break-down in ‘Conference’ pear. Postharvest Biol. Technol. 20, 25–37.

ammertyn, J., Scheerlinck, N., Verlinden, B.E., Schotsmans, W., Nicolaı,B.M., 2001a. Simultaneous determination of oxygen diffusivity andrespiration in pear skin and tissue. Postharvest Biol. Technol. 23,93–104.

166.chotsmans, W., Verlinden, B.E., Lammertyn, J., Nicolaı, B.M., 2004.

The relationship between gas transport properties and histology ofapple. J. Sci. Food Agric. 84, 1131–1140.

erashima, I., Miyazawa, S., Hanba, T.Y., 2001. Why are sun leavesthicker than shade leaves? Consideration based on analyses of CO2

diffusion in the leaf. J. Plant Res. 114, 93–105.erlinden, B.E., de Jager, A., Lammertyn, J., Nicolaı, B.M., 2002. Effect

of harvest and delaying controlled atmosphere storage conditions oncore breakdown incidence in ‘Conference’ pears. Biosyst. Eng. 83,339–347.