- Email: [email protected]
Simultaneous measurement of oxygen and carbon dioxide diffusivity in pear fruit tissue
Postharvest Biology and Technology 29 (2003) 155 /166 www.elsevier.com/locate/postharvbio
Simultaneous measurement of oxygen and carbon dioxide diffusivity in pear fruit tissue W. Schotsmans *, B.E. Verlinden, J. Lammertyn, B.M. Nicolaı¨ Flanders Centre/Laboratory of Postharvest Technology, Katholieke Universiteit Leuven, Willem de Croylaan 42, B-3001 Leuven, Belgium Received 10 July 2002; accepted 10 December 2002
Abstract Diffusion and respiration characteristics of pear tissue are needed to estimate the composition of the internal atmosphere of a pear fruit. In this contribution, a methodology is described to measure diffusion characteristics of tissue. The experimental set-up consists of two thermostatted chambers separated with a slice of fruit tissue. A gradient was established over the sample by applying different gas concentrations to both chambers. Due to this gradient, gas diffused from one chamber into the other through the tissue sample. A mathematical model consisting of six differential equations (two for each atmospheric gas) was used to describe this gas transport process through the tissue taking into account diffusion, loss of gas due to sampling, pressure-driven bulk transport, and gas consumption and production due to respiration and oxidation. The diffusion parameters of different respiratory gases in pear fruit tissue could be accurately estimated. The CO2-diffusivity in the fruit flesh (19.2 /10 9 m2 s 1) was found to be larger than in the skin (1.15 /10 9 m2 s 1) and larger than the O2-diffusivity (2.10/10 9 m2 s 1 in the fruit flesh and 1.03 /10 9 m2 s 1 in the skin). The gradient in CO2-diffusivity in the fruit was significant, with the smallest CO2-diffusivity in the skin and the highest near the core of the pear fruit. There was no change in diffusivity in the weeks prior to and after the optimal harvest date for long-term storage. # 2003 Elsevier B.V. All rights reserved. Keywords: Pear; Diffusivity; Respiratory gases; O2; CO2
1. Introduction Controlled atmosphere storage is based on retarding physiological processes in the fruit by decreasing the temperature and oxygen availability and increasing the carbon dioxide concentration in
* Corresponding author. Tel.: /32-16-32-26-68; fax: /3216-32-29-55. E-mail address: [email protected] (W. Schotsmans).
the external atmosphere. Knowledge of the relation between the established external atmosphere and the resulting internal atmosphere of the fruit is important for understanding and developing controlled atmosphere treatments and modified atmosphere packaging for extended product life. It can aid in explaining the large variability in responses of fruit to their storage atmospheres, as well as improve the understanding of the development of storage-related disorders such as core breakdown in ‘Conference’ pears (Pyrus communis cv. Con-
0925-5214/03/$ - see front matter # 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0925-5214(02)00251-X
156
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Nomenclature A C D J K l m M P r R s t T V x Subscripts i j tot
exchange surface (m2) gas concentration (mol m 3) diffusivity of gas (m2 s 1) flux (mol s 1 m 2) permeability for gas (m2 s 1) sample thickness (m) mass (g) molar mass (g) pressure (Pa) respiration (mol kg1 s 1) universal gas constant (8.3144 Pa m3 mol 1 K 1) pressure change due to sampling (Pa s 1) time (s) temperature (K) volume of chamber (m3) spatial coordinate (m) O2, CO2 or N2 L (left chamber), R (right chamber) total
ference), since these are believed to be caused by an unfavourable composition of the internal atmosphere (Lammertyn, 2001). The gas concentration inside the fruit is affected by both local respiration behaviour and gas diffusion properties of the flesh and skin resulting in a different oxygen and carbon dioxide tension than that of the applied external atmosphere. Gas exchange between a plant organ and its environment follows a specific path (Kader, 1988), and the rate of gas movement depends on the properties of the gas molecule, the concentration gradient and the physical properties of the intervening barriers. Several methods have been developed to assess the diffusion properties of various horticultural commodities (Burg and Burg, 1965; Burton, 1965). In early work (Burg and Burg, 1965), diffusion through flesh samples was found to be much more rapid than through isolated pieces of skin. For most horticultural produce, the skin represents the major barrier to gas exchange (Solomos, 1987). Measurement of resistance to gas transport on whole fruit (Solomos, 1987; Banks, 1985; Emond et al., 1991; Knee, 1991; Schotsmans et al., 2002) is
non-destructive but based on the assumption that the skin represents the main barrier to gas exchange. However, although the diffusivity of gases in the fruit flesh is 10 /20 times higher than the diffusivity in the skin, it does not exclude the fruit flesh as a possible barrier, especially for fruit with low internal free space volumes (Solomos, 1987; Banks and Nicholson, 2000). When fruit flesh functions as a barrier, the diffusivity of gases in the fruit flesh is also needed to describe gas transport in fruit properly. Techniques to measure diffusivity have been developed, and are based on several assumptions. Streif (1999) developed a method based on the diffusion of an inert gas through a tissue sample. The diffusivity of oxygen and carbon dioxide was then recalculated using Graham’s law stating a constant relation between the diffusivity of two gases. A similar method (Zhang and Bunn, 2000) is based on a tissue sample separating two flowing gases. However, this does not resemble the actual conditions during storage. In both methods, respiration effects were not taken into account, although they do affect the measurements, as shown by Lammertyn et al.
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
(2001) where the respiration of the tissue and the diffusivity of the respiratory gases (O2, CO2) were measured separately. During the period surrounding harvest maturity several changes occur in the fruit. Fruit maturation and fruit ripening involve changes in texture, firmness, skin color, volatiles and chemical composition (sugar content, acidity, esters, alcohols) as well as changes in respiration and ethylene production. Reports about gas exchange properties, more specifically skin resistance of fruit, are not very consistent. While some authors (Park et al., 1993) found changes during the harvesting period, others did not. Elgar et al. (1999) found that the skin resistance to gas diffusion of ‘Braeburn’ apples was not influenced by harvest date. Schotsmans et al. (2002) reported no influence of harvest date on skin resistance to gas diffusion for ‘Jonica’ and ‘Braeburn’ apples nor for ‘Doyenne´ du Comice’ and ‘Conference’ pears. It is possible that changes in skin resistance during maturation occur since the fruit is going through so many changes, but it is also possible that there are no changes in skin resistance or that they cannot be measured with the available techniques since in the value of the skin resistance, information about the entire fruit is captured. Therefore, it would be interesting to measure diffusivity of specific tissue during harvest and see if the diffusivity changes. To our knowledge, it is not known whether diffusion properties are affected by tissue type, maturity of the fruit or storage. The objectives of this research were: (1) to develop a method for the simultaneous measurement of transport properties of O2, CO2 and N2 in fruit tissue, (2) to evaluate whether the gas transport properties vary inside the fruit and (3) to investigate whether they are affected by the maturity stage.
2. Materials and methods 2.1. Fruit material Three experiments were carried out on tissue and skin samples of pears. In the first experiment, the ‘Conference’ pears were harvested in Septem-
157
ber 2000 at a pre-climacteric stage at the research station PCF-PPS (Proeftuin voor Pit- en Steenfruit, Velm) and cooled for a period of 21 days at /0.5 8C preceding controlled atmosphere storage (/0.5 8C, 2% O2/0.7% CO2) according to commercial protocols. After 7 months of storage, a total of 24 skin samples and 21 fruit flesh samples (5 mm under the skin) was measured. In the second experiment, samples were taken from three different tissue groups along the radial axis, more specifically the skin, the mesocarp (13 / 17 mm under the skin depending on the size of the fruit) and the core tissue (24 /30 mm under the skin), to test the spatial distribution of diffusivity of O2 and CO2 within the fruit. The samples were obtained after 3 months of storage from ‘Conference’ pears harvested in 2001 at a pre-climacteric stage (12 September) at the Fruitteeltcentrum (Rillaar, Belgium), and cooled for a period of 21 days at /0.5 8C preceding controlled atmosphere storage (/0.5 8C, 2% O2/0.7% CO2). The third experiment was designed to investigate maturity effects and was performed from August (21 days before the optimal harvest date) to October 2001 (21 days after the optimal harvest date). In the period surrounding the optimal harvest date for long-term storage, ‘Conference’ pears were picked every Monday, Wednesday and Friday at the Fruitteeltcentrum (Rillaar, Belgium) and the diffusivity of the pear cortex tissue was measured in order to assess changes in diffusivity in the fruit flesh in this period. 2.2. Experimental set-up and procedures The diffusion set-up consisted of two doublesided glass chambers (left and right chambers, each 650 ml) separated by the tissue sample in a sample holder (Fig. 1). The sample holder was a metal cylinder consisting of two halves screwed together holding a PVC ring containing the tissue sample glued with cyano-acrylate glue. The connections between different materials were made airtight with rubber airtight seals to prevent leakage to the outside and to ensure that all gas transport took place through the tissue sample. A temperature-controlled waterbath (F10-HC, Julabo Labor Technik GmbH, Seelbach, Germany)
158
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Fig. 1. Experimental set-up for gas diffusion measurements consisting of two glass chambers separating the tissue that is to be measured.
circulating water through the water jacket of the chambers, kept the set-up at a constant temperature of 12.09/0.1 8C. Pear flesh samples were first cut with a professional slice cutter (EH 158-L, Graef, Germany), subsequently small cylinders with a diameter of 24 mm were cut with a cork borer. The thickness of the sample was measured with a digital calliper (Mitutoyo Ltd., UK) and ranged from 1 to 2 mm. The tissue sample was glued onto a polyvinylchloride ring (inner diameter of 22 mm) with cyanoacrylate glue. The glue was applied thinly to avoid a toxic effect on the cells. The same procedure was used for the skin samples. A razor blade was used to remove the flesh from the skin sample until a thickness of less than 1 mm was obtained. The samples were inserted in the set-up without delay after which one chamber was flushed (20 min at a volume flow rate of 20 l h1) with N2 containing 20 kPa O2/5 kPa CO2, while the other one was flushed with N2 containing 5 kPa O2/20 kPa CO2 to establish a large gas concentration gradient over the fruit tissue. Measurements were performed at constant temperature (12 8C). The gas mixtures were prepared from pure O2, CO2 and N2 by
means of mass flow controllers (Lammertyn et al., 2001) and subsequently directed through a heat exchanger and humidifier in order to deliver the gas to the experimental set-up at 12 8C and humidify the gas in order to minimise dehydration of the sample. After flushing, the chambers were sealed and four samples were taken within the next day with intervals of 3 h. Sampling consisted of measuring the gas composition with a micro-GC (CP2003-P, Chrompack, The Netherlands) with an automatic pump sampling system (40 s of sampling at a volume flow rate ranging from 5 to 20 ml min1) and monitoring the total pressure for each chamber with a pressure sensor (PTX 520-0, Druck, The Netherlands). The gas partial pressures obtained by multiplying the mole fractions and the total pressure were converted to moles using the universal gas law. As part of these diffusion measurements, respiration and oxidation effects due to the wounding of the tissue were measured separately using tissue samples with the same dimensions as the samples used for the diffusion experiment. The samples were prepared in the same manner as the samples for the diffusion set-up thus ensuring the
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
same amount of wounding. Samples (20 /30) were placed in two separate 1.2 l glass containers, one for each gas mixture, and flushed with each gas mixture during 20 min at a volume flow rate of 20 l h1. Subsequently, the containers were closed and a sample of the headspace was taken simultaneously with the diffusion measurements using a micro-GC with an automatic pump sampling system. The output was expressed in percentages or mole fractions and the total pressure was monitored with a pressure sensor. Partial pressures were obtained by multiplying the mole fractions and the total pressure, and were converted to mol m 3 using the universal gas law. 2.3. Model construction and calculations The model consisted of six differential equations; every differential equation consisted of three well-defined parts describing the change in moles of gas during time. The first part described diffusion based on Fick’s first law of diffusion. The second part deals with the consequences linked to the sampling procedure and the final part brings filtration of gas due to a pressure gradient over the tissue into the model. Preliminary tests with fruit tissue showed that, as expected, gas consumption and production due to respiration and oxidation interfere with the gas transport. Therefore, the model was expanded with a fourth part representing respiration and oxidation. The six differential equations of the model have the same form as shown in the following equation: dni;j (t) dni;j (t) dni;j (t) dt dt dt diff sampling dni;j (t) dni;j (t) ; (1) dt dt p resp where n is the number of moles of gas, t the time (s), i is O2, CO2 or N2, and j is L (left chamber) or R (right chamber). Different parts of the model will be discussed separately. 2.3.1. Diffusion The diffusion process was described using Fick’s first law of diffusion (Geankoplis, 1993):
Jd D
@C : @x
159
(2)
This law states that the flux of a gas, Jd (mol s 1 m2), diffusing through a barrier, is determined by the diffusivity of the gas, D (m2 s 1), and the concentration gradient over this barrier, @C /@x (mol m 3 m 1). For one dimension in steady-state conditions, the concentration gradient is linear (Cameron and Yang, 1982; Banks, 1985) and Eq. (2) can be rewritten. The concentration gradient is the difference in gas concentration between the two chambers with the barrier being the tissue sample with thickness l: @C DC CR CL 1 nR nL : (3) @x Dx Dx VR VL Dx A simple model for the change in absolute amount of gas due to diffusion, valid at constant temperature conditions, can be developed for each gas in the system: dni;L (t) D A ni;R (t) ni;L (t) i ; dt l VR VL diff (4) dni;R (t) Di A ni;R (t) ni;L (t) ; dt l VR VL diff where VL and VR (m3) are the volumes of the left and the right chambers, respectively, A (m2) is the surface area of the barrier, and l (m) the thickness of the tissue sample or barrier. 2.3.2. Sampling losses The second part of the model covers the removal of gas by sampling. The amount of gas that is subtracted from the system is not constant since it is subtracted by an automatic pump sampling system with varying velocities; therefore, it has to be calculated. This is possible since the pressure drop during sampling (DP ) is measured. The pressure drop during sampling can be recalculated to moles using the universal gas law. The amount subtracted from either chamber can then be calculated as Dn
DP(t)V RT
(5)
160
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
with DP the pressure drop during sampling (Pa), T (K) the absolute temperature and R the universal gas constant (m3 Pa mol 1 K 1). The amount of each gas as a function of time that is taken out is assumed to be proportional to the mole fraction of different gases at sampling (ni/ntot) and the sampling time (ts):
dni;L (t) KA P (t) (PR (t)PL (t)) i;j ; dt RTl Pj (t) p dni;R (t) KA P (t) (PR (t)PL (t)) i;j ; dt RTl Pj (t) p X Pi;L (t); PL (t) i
dni;L (t)
ni;L (t) DPL VL
PR (t)
;
dt ntot;L RTts sampling dni;R (t) n (t) DPR VR i;R : dt ntot;R RTts sampling
(6)
2.3.3. Gas transport due to overall pressure differences At the start of the experiment, the total pressure at both sides is equal. Due to the unbalanced gas transport between the chambers, pressure can build up in one chamber. The film or tissue will then act as a filter and with total pressure as the driving force; gases will be transferred in bulk, the composition proportional to the molar composition of the environment where the force is applied (thus, the composition of the chamber with the highest pressure). This filtration transport can be described with Darcy’s law (Geankoplis, 1993). The flux of a gas through a filter, Jp (mol s 1 m 2), due to a pressure difference can be described using the permeability of the filter, K (m2 s 1) and the total pressure gradient, @P /@x :
Jp
K @P : RT @x
(7)
Translated to the used set-up, the following equations were obtained. The factor Pi,j(t)/Pj(t) denotes the mole fraction of gas i in the gas flow coming from side j where the overall pressure is highest:
L; j R;
X
Pi;R (t);
i
if PL (t)PR (t); if PL (t)BPR (t):
(8)
If the pressure is higher at the left side, transport will proceed from the left to the right and so the mole fraction of gas in the gas mixture on the left is required. If the pressure is higher at the right side, transport will proceed from the right to the left and the mole fraction of gas in the gas mixture on the right is required.
2.3.4. Respiration and oxidation When working with fruit tissue, the total amount of oxygen decreases and the total amount of carbon dioxide increases due to respiration and oxidation effects. Respiration and oxidation were included in the model as a consumption term in the case of oxygen (rO2 in mol kg1 s 1) and a production term (rCO2 in mol kg1 s 1) in the case of carbon dioxide. The consumption of oxygen and the production of carbon dioxide were measured separately using tissue samples with the same dimensions as the samples used for the diffusion experiment and at the same temperature and atmospheric conditions as the diffusion experiment in order to decrease the number of parameters to be estimated simultaneously. In order to obtain the amount of produced or consumed gas in moles, the measured respiration rate was multiplied by half the mass of the fruit tissue sample (msample in kg) in the diffusion set-up since we assumed that half the tissue is under the respiring conditions from the left side and the other half under respiring conditions on the right side:
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
dnO2 ;j (t) dt resp dnCO2 ;j (t) dt
rO2 ;j rCO2 ;j
msample ; 2 msample
resp
2
:
(9)
The differential equations were integrated numerically with a FORTRAN program using NAG library Mark XIV routine DO2EBF (Numerical Algorithms Group Ltd., Oxford, UK, 1986). Parameter values were obtained by manual alteration of the values followed by an automatic parameter estimation procedure (NAG-routine E04FDF). In order to check the correctness of the estimated parameters, the experimental data were plotted together with the model predictions and visually assessed. Data analyses were performed using the statistical analysis system (SAS Institute, Inc., Cary, NC, 1992). Treatment effects were analysed by the GLM procedure and treatment mean separation was determined by Fisher’s LSD (P B/0.05) or Duncan’s multiple range tests. 2.4. Validation The film used for validation was a CoexBlasfolie VIP-3728 packaging film with a thickness of 0.040 mm (VINORA AG, Switzerland). Diffusivities for O2, CO2 and N2 at 23 8C were provided by the manufacturer and are shown in Table 3. Experiments on film were performed at 23 8C.
3. Results and discussion
in total pressure, which would otherwise contribute too much to the gas transport in the set-up. Respiration was measured at both 20 kPa O2/5 kPa CO2 and 5 kPa O2/20 kPa CO2, the conditions used for the diffusion experiments. Both skin and flesh respiration rates were significantly higher at 20 kPa O2 compared with 5 kPa O2 (Table 1). The O2 consumption rate and CO2 production rates of skin were significantly higher than for flesh. For skin, the more extensive wounding would cause an increase in wound respiration and non-respiratory O2-consuming reactions induced by scraping the remaining tissue from the skin (Lammertyn, 2001), and this could provide an explanation for the higher O2 consumption. In Fig. 2, O2 and CO2 partial pressure profiles for skin and flesh in both chambers for one representative sample each are shown. In the left chamber, the higher O2 partial pressure caused O2 transport to occur from the left to the right chamber while CO2 diffused in the opposite direction from the right chamber with higher CO2 partial pressure to the left chamber with lower CO2 partial pressure. In the skin, the pattern was similar for both respiratory gases, suggesting transport at the same rate, thus pointing to equal diffusion constants. When diffusivity values are compared (Table 1), this prediction stands; the average values for skin of 1.03 /109 m2 s 1 for O2 and 1.15 /109 m2 s 1 for CO2 diffusivity were not significantly different. From Fig. 2, it seems that transport through skin is faster than that through flesh but one must consider that the Table 1 Diffusivity and respiration rates for cortex tissue and skin tissue of ‘Conference’ pears after 7 months of storage
3.1. Diffusivity in pear skin and flesh The gradient was chosen such that transport of O2 and CO2 took place in opposite directions, whereas in reality CO2 normally moves outwards and O2 inwards. If both gradients would have the same direction, gas would accumulate in the chamber with the lower partial pressure causing a large difference in total pressure. With opposite gradients, this difference in total pressure is small, thus minimising transport caused by a difference
161
Cortex tissue DO2 (10 9 m2 s 1) DCO2 (10 9 m2 s 1) DCO2/DO2 rO2 at 20 kPa O2 (10 8 mol kg1 s 1) rO2 at 5 kPa O2 (10 8 mol kg1 s 1) rCO2 at 20 kPa O2 (10 8 mol kg 1 s 1) rCO2 at 5 kPa O2 (10 8 mol kg 1 s 1)
Skin
2.19/0.6 1.09/0.3 199/4 1.29/0.3 9.1 1.1 10.79/1.4 999/36 7.49/1.9 699/59 7.99/1.4 799/20 2.49/1.6 319/8
Values are presented with a 95% confidence interval of the mean.
162
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Fig. 2. Oxygen (upper) and carbon dioxide (lower) partial pressure profiles for skin (left) and cortex tissue (right) of ‘Conference’ pears after 7 months of storage for both the right (measured value ( /); model profile (- -)) and the left (measured value (k); model profile ( */)) chamber at 12 8C.
skin samples are considerably thinner than the flesh samples. In flesh, CO2 moved significantly faster than O2 (Fig. 2) resulting in a CO2-diffusivity of 19.2 /109 m2 s 1 and a nine times lower O2-diffusivity (2.1 /10 9 m2 s 1). Literature data about the coupled effect of gas diffusivity and respiration in pears are scarce although diffusivity in other horticultural commodities has been studied numerous times. It is interesting to compare the obtained results with literature data, even though these are not very consistent either. The results obtained in this research for the diffusivity of O2 and CO2 in flesh (2.1 /109 and 19.2 / 109 m2 s 1) are in agreement with the O2diffusivity in flesh of 1.71 /109 m2 s 1 and the CO2-diffusivity of 19.5 /109 m2 s1 reported by Lammertyn (2001). However, although the CO2diffusivity of 1.2 /10 9 m2 s 1 for pear skin was similar to that reported by Lammertyn (2001) (9.1 /1010 m2 s 1), the O2-diffusivity of 1.0 /
109 m2 s 1 for skin was four times higher than that reported by Lammertyn et al. (2001) (2.8 / 1010 m2 s 1). Large differences like this have also been reported by other authors; Solomos (1987) measured a CO2 diffusivity for potato skin and flesh of 2.2 /108 and 2.5 /107 m2 s1, respectively, while Abdul-Baki and Solomos (1994) obtained values of 6.24 /1011 m2 s 1 for skin and 2.5 /10 8 m2 s 1 for flesh. The ratio of CO2 to O2 diffusivity would be 0.8 for all tissue types when Graham’s effusion law would be used, assuming free diffusion in air. On the contrary, the ratio between CO2 and O2 diffusivity depended on the type of tissue in the present experiments. For flesh the ratio was 9.1 (11.4 found by Lammertyn et al., 2001), CO2 diffusivity was considerably larger than O2 diffusivity. The different transport paths followed by the gases in the flesh might explain this, since transport occurs mainly through the intercellular
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
free spaces, filled with air or liquid. Transport of both gases through air-filled free spaces is almost equal as well as the diffusivity of both gases in water (Lide, 1999), but the O2 and CO2 diffusivity in liquid water is approximately 104-fold less than in air (Amarante et al., 2001). Consequently, the main pathway for gas transport in fruit flesh tissue is through the intercellular free spaces, filled with air. On the other hand, CO2 is much more soluble in liquid than O2 (solubility of CO2 in water is 25 times higher than that of O2; Geankoplis, 1993). Because CO2 is more soluble in water, it can dissolve in the moisture present in the intercellular spaces and it can be transported along with the moisture. For skin, however, this is not the case and the ratio between CO2 and O2 diffusivity was 1.1 (3.2 found by Lammertyn et al., 2001), CO2 diffusivity was similar to O2 diffusivity. This could be due to the substantially smaller contribution of moisture transport in the overall transport of O2 and CO2 in the skin, because moisture transport in the cuticle is significantly slower than in the fruit flesh. Veraverbeke (2001) found diffusivities of moisture in cuticle to be 100/3000 times smaller compared with tissue in ‘Elstar’ and ‘Jonagold’ apples, respectively. These results indicate that Graham’s law cannot be used to calculate the diffusivity or skin resistance for one gas from the diffusivity or skin resistance for another gas. 3.2. Diffusivity during harvest The average O2 consumption rate at 20 kPa O2 was 22 /108 mol kg1 s 1 and slightly higher than at 5 kPa O2 (13 /10 8 mol kg1 s1), the average CO2 production rate at 20 kPa O2 was 16 /10 8 mol kg1 s 1 and was significantly higher than at 5 kPa O2 (10 /108 mol kg1 s 1). These consumption and production rates were constant during the whole period. For the diffusivity of O2 and CO2 in the fruit cortex tissue average values were obtained of 3.8 /10109/ 0.4 /1010 and 3.8 /10 99/0.5 /109 m2 s 1, respectively. No change in diffusivity of O2 or CO2 was detected during the 7 weeks in which measurements were performed (Fig. 3), confirming the results of skin resistance measurements (Schotsmans et al., 2002) where a similar conclusion was
163
drawn. Even though significant structural and compositional changes occur in this maturation period, this does not necessarily imply that the diffusivity of the respiratory gases (O2, CO2) is influenced by these changes.
3.3. Diffusivity at different positions in a fruit In order to assess the presence of a diffusivity gradient in a fruit, three samples were taken from each ‘Conference’ pear, one near the core, one at half radial distance in the cortex and one of the skin. The measured diffusivities were considerably different from those measured in the previous year. This may be due to several factors such as the different growing conditions and orchard, and the different storage duration. The values represented in Table 2 are averages over 10 fruit for each position measured in a period of 2 weeks with a 95% confidence interval surrounding the mean. A first and important observation is the magnitude of these confidence intervals, a direct consequence of working with biological material and a limited number of repetitions. Consequently, significant differences are scarce and mostly trends can be observed, as was the case for the influence of the radial position of the sample on the measured diffusivity. The O2-diffusivity seems uniform throughout the fruit (Fig. 4), concurring with findings for ‘Braeburn’, where the flesh exerted a significant resistance to O2 diffusion resulting in a significant O2 gradient between tissue immediately beneath the peel and the center of fruit (Rajapakse et al., 1990). On the other hand, the CO2-diffusivity gradient was very pronounced. The CO2-diffusivity (Table 2) was 9.8 /109 m2 s 1 at the core, half (5.2 /10 9 m2 s 1) at half radial distance and minimal in the skin (3.8 /10 10 m2 s 1). Calbo (1985), Solomos (1987) and Argenta et al. (2002) also reported the existence of significant CO2 gradients within apple fruit. In avocado flesh, a decrease in diffusivity was related to the clogging of air spaces by cell exudates, while an increased O2 gradient in nectarines could be linked to the decreased intercellular space volume (Rajapakse et al., 1990).
164
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Fig. 3. Oxygen (A) and carbon dioxide (B) diffusivities in cortex tissue of ‘Conference’ pears at 12 8C during the period surrounding the optimal harvest date for long-term storage. Vertical bars indicate 95% confidence intervals surrounding the mean. Table 2 Oxygen and carbon dioxide diffusivity (10 9 m2 s 1) at different radial distances in ‘Conference’ pear measured after 3 months of storage Skin
At half radius
Near core
DO2 (10 10 m2 s 1) 0.339/0.24a* 0.439/0.17a 0.879/0.69a DCO2 (1010 m2 s 1) 0.439/0.65a 1.739/1.15a 7.649/6.96a DCO2/DO2 1.3 4.0 8.7 Values are presented with a 95% confidence interval of the mean. * Means with the same letter are not significantly different (Fisher’s LSD; P/0.05).
The ratio CO2/O2 diffusivity (4.0) was lower after 3 months compared with that at the time of harvest (9). Although the O2-diffusivity did not change during the 3 months of storage, the CO2diffusivity decreased during this time, from 3.8 / 109 m2 s 1 at harvest to 1.7 /109 m2 s 1 after 3 months of storage.
3.4. Validation Validation measurements were performed with film at 23 8C, which is the temperature at which the permeability of the film was determined by the manufacturer. The results are presented in Table 3. There was an acceptable agreement between the estimated diffusivity for O2 and CO2 and with the values provided by the manufacturer. The overestimated N2-diffusivity was probably the result of the fact that no partial pressure gradient was applied for N2. If no significant gradient is present, it is impossible to obtain an accurate estimate for that parameter in the model.
4. Conclusions A diffusion chamber set-up was constructed to determine the diffusivity of O2 and CO2 in pear fruit tissue. The diffusion parameters of the different respiratory gases could be estimated
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
165
Fig. 4. Oxygen (A) and carbon dioxide (B) diffusivities at different positions in ‘Conference’ pears measured at 12 8C after 3 months of storage. Vertical bars indicate 95% confidence limits of the mean.
Table 3 Diffusivity (10 13 m2 s 1) of the packaging film provided by the manufacturer and result of the validation experiment Gas
O2
CO2
Diffusivity Estimated diffusivity
15.6 20.89/1.4
58.9 55.69/5.4
N2 3.84 6.39/6.1
with satisfying accuracy. In flesh, the CO2-diffusivity was mostly larger than the O2-diffusivity. This can be explained when the different transport paths followed by the gases in the flesh are taken into account. Transport of O2 and CO2 through air-filled free spaces is similar but CO2 is much more soluble in liquid, and can thus be transported along with moisture through the free spaces filled with liquid. For skin, however, this is not the case and the ratio between CO2 and O2 diffusivity was very small since both gases diffuse mainly through
pores. As expected from former skin resistance measurements, no change in diffusivity was found in the weeks prior to and after the optimal harvest date for long-term storage. This means that even though significant structural and compositional changes occur in this period, these changes do not necessarily influence the diffusivity of the respiratory gases. After 3 months of storage, a significant rise in CO2-diffusivity in the fruit flesh was found, CO2-diffusivity was smallest at the skin and increased significantly from the skin to the core of the pear fruit, while no difference in O2diffusivity was observed. The results imply that it is not possible to determine the diffusivity or resistance of one gas and recalculate to another using Graham’s law since this law states a constant relationship between diffusivities and this is not the case for fruit tissue where the ratio between CO2 and O2 diffusivity depends on tissue type and age of the fruit.
166
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Acknowledgements The financial support of the Flemish Minister for Science and Technology, the Ministry of SME and Agriculture (Project D12-5771A), the EU (Fair project CT96-1803) are gratefully acknowledged and the Catholic University Leuven (IDOproject 00/008). Author Wendy Schotsmans is a doctoral fellow of IWT. The financial support of this institute is acknowledged with gratitude. Jeroen Lammertyn is postdoctoral fellow with the Flemisch Fund for Scientific Research (FWO-Vlaanderen).
References Abdul-Baki, A.A., Solomos, T., 1994. Diffusivity of carbon dioxide through the skin and flesh of ‘Russet Burbank’ potato tubers. J. Am. Soc. Hort. Sci. 119, 742 /746. Amarante, C., Banks, N.H., Ganesh, S., 2001. Relationship between character of skin cover of coated pears and permeance to water vapour and gases. Postharvest Biol. Technol. 21, 291 /301. Argenta, L., Fan, X., Mattheis, J., 2002. Impact of watercore on gas permeance and incidence of internal disorders in ‘Fuji’ apple. Postharvest Biol. Technol. 24, 113 /122. Banks, N.H., 1985. Estimating skin resistance to gas diffusion in apples and potatoes. J. Exp. Bot. 36, 1842 /1850. Banks, N.H., Nicholson, S.E., 2000. Internal atmosphere composition and skin permeance to gases of pepper fruit. Postharvest Biol. Technol. 18, 33 /41. Burg, S.P., Burg, E.A., 1965. Gas exchange in fruits. Physiol. Plant. 18, 870 /874. Burton, W.G., 1965. The permeability to oxygen of the periderm of the potato tuber. J. Exp. Bot. 16, 16 /23. Calbo, A.G., 1985. Gas exchange in fruits and vegetables and the use of oscillating pressure storage. Ph.D. Thesis. University of California, Davis, CA. Cameron, A.C., Yang, S.F., 1982. A simple method for the determination of resistance to gas diffusion in plant organs. Plant. Physiol. 70, 21 /23.
Elgar, H.J., Watkins, C.B., Lallu, N., 1999. Harvest date and crop load effects on a carbon dioxide-related storage injury of ‘Braeburn’ apple. HortScience 34, 305 /309. Emond, J.P., Castaigne, F., Toupin, C.J., Desilets, D., 1991. Mathematical modelling of gas exchange in modified atmosphere packaging. Trans. ASAE 34, 239 /245. Geankoplis, C.J., 1993. Transport Processes and Unit Operations. Prentice-Hall, Englewood Cliffs, NJ. Kader, A.A., 1988. Respiration and gas exchange of vegetables. In: Weichmann, J. (Ed.), Postharvest Physiology of Vegetables: Food Science and Technology. Marcel Dekker, New York, pp. 25 /43. Knee, M., 1991. Rapid measurement of diffusion of gas through the skin of apple fruits. HortScience 26, 885 /887. Lammertyn, J., 2001. A respiration /diffusion model to study core breakdown in Conference pears. Ph.D. Dissertation. Katholieke Universiteit Leuven, Leuven. Lammertyn, J., Scheerlinck, N., Verlinden, B.E., Schotsmans, W., Nicolaı¨, B.M., 2001. Simultaneous determination of oxygen diffusivity and respiration in pear skin and tissue. Postharvest Biol. Technol. 23, 93 /104. Lide, D.R., 1999. Handbook of Chemistry and Physics. CRC Press, New York. Park, Y.M., Blanpied, G.D., Jozwiak, Z., Liu, F.W., 1993. Postharvest studies of resistance to gas diffusion in McIntosh apples. Postharvest Biol. Technol. 2, 329 /339. Rajapakse, N.C., Banks, N.H., Hewett, E.W., Cleland, D.J., 1990. Development of oxygen concentration gradients in flesh tissues of bulky plant organs. J. Am. Soc. Hort. Sci. 115, 793 /797. Schotsmans, W., Verlinden, B.E., Lammertyn, J., Peirs, A., Jancso´k, P., Scheerlinck, N., Nicolaı¨, B.M., 2002. Factors affecting resistance to gas diffusion of pip fruit. Postharvest Biol. Technol. 25, 169 /179. Solomos, T., 1987. Principles of gas exchange in bulky plant tissues. HortScience 22, 766 /771. Streif, J., 1999. Vortragstagung der DGQ. Deutsche Gesellschaft fu¨r Qualita¨tsforschun, Freising-Weihenstephan, XXXIV. Veraverbeke, E., 2001. Changes in epicuticular wax structure and composition in relation to moisture loss of apple during postharvest storage. Ph.D. Dissertation. Katholieke Universiteit Leuven, Leuven. Zhang, J., Bunn, J.M., 2000. Oxygen diffusivity of apple flesh and skin. Trans. ASAE 43, 359 /363.
Simultaneous measurement of oxygen and carbon dioxide diffusivity in pear fruit tissue W. Schotsmans *, B.E. Verlinden, J. Lammertyn, B.M. Nicolaı¨ Flanders Centre/Laboratory of Postharvest Technology, Katholieke Universiteit Leuven, Willem de Croylaan 42, B-3001 Leuven, Belgium Received 10 July 2002; accepted 10 December 2002
Abstract Diffusion and respiration characteristics of pear tissue are needed to estimate the composition of the internal atmosphere of a pear fruit. In this contribution, a methodology is described to measure diffusion characteristics of tissue. The experimental set-up consists of two thermostatted chambers separated with a slice of fruit tissue. A gradient was established over the sample by applying different gas concentrations to both chambers. Due to this gradient, gas diffused from one chamber into the other through the tissue sample. A mathematical model consisting of six differential equations (two for each atmospheric gas) was used to describe this gas transport process through the tissue taking into account diffusion, loss of gas due to sampling, pressure-driven bulk transport, and gas consumption and production due to respiration and oxidation. The diffusion parameters of different respiratory gases in pear fruit tissue could be accurately estimated. The CO2-diffusivity in the fruit flesh (19.2 /10 9 m2 s 1) was found to be larger than in the skin (1.15 /10 9 m2 s 1) and larger than the O2-diffusivity (2.10/10 9 m2 s 1 in the fruit flesh and 1.03 /10 9 m2 s 1 in the skin). The gradient in CO2-diffusivity in the fruit was significant, with the smallest CO2-diffusivity in the skin and the highest near the core of the pear fruit. There was no change in diffusivity in the weeks prior to and after the optimal harvest date for long-term storage. # 2003 Elsevier B.V. All rights reserved. Keywords: Pear; Diffusivity; Respiratory gases; O2; CO2
1. Introduction Controlled atmosphere storage is based on retarding physiological processes in the fruit by decreasing the temperature and oxygen availability and increasing the carbon dioxide concentration in
* Corresponding author. Tel.: /32-16-32-26-68; fax: /3216-32-29-55. E-mail address: [email protected] (W. Schotsmans).
the external atmosphere. Knowledge of the relation between the established external atmosphere and the resulting internal atmosphere of the fruit is important for understanding and developing controlled atmosphere treatments and modified atmosphere packaging for extended product life. It can aid in explaining the large variability in responses of fruit to their storage atmospheres, as well as improve the understanding of the development of storage-related disorders such as core breakdown in ‘Conference’ pears (Pyrus communis cv. Con-
0925-5214/03/$ - see front matter # 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0925-5214(02)00251-X
156
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Nomenclature A C D J K l m M P r R s t T V x Subscripts i j tot
exchange surface (m2) gas concentration (mol m 3) diffusivity of gas (m2 s 1) flux (mol s 1 m 2) permeability for gas (m2 s 1) sample thickness (m) mass (g) molar mass (g) pressure (Pa) respiration (mol kg1 s 1) universal gas constant (8.3144 Pa m3 mol 1 K 1) pressure change due to sampling (Pa s 1) time (s) temperature (K) volume of chamber (m3) spatial coordinate (m) O2, CO2 or N2 L (left chamber), R (right chamber) total
ference), since these are believed to be caused by an unfavourable composition of the internal atmosphere (Lammertyn, 2001). The gas concentration inside the fruit is affected by both local respiration behaviour and gas diffusion properties of the flesh and skin resulting in a different oxygen and carbon dioxide tension than that of the applied external atmosphere. Gas exchange between a plant organ and its environment follows a specific path (Kader, 1988), and the rate of gas movement depends on the properties of the gas molecule, the concentration gradient and the physical properties of the intervening barriers. Several methods have been developed to assess the diffusion properties of various horticultural commodities (Burg and Burg, 1965; Burton, 1965). In early work (Burg and Burg, 1965), diffusion through flesh samples was found to be much more rapid than through isolated pieces of skin. For most horticultural produce, the skin represents the major barrier to gas exchange (Solomos, 1987). Measurement of resistance to gas transport on whole fruit (Solomos, 1987; Banks, 1985; Emond et al., 1991; Knee, 1991; Schotsmans et al., 2002) is
non-destructive but based on the assumption that the skin represents the main barrier to gas exchange. However, although the diffusivity of gases in the fruit flesh is 10 /20 times higher than the diffusivity in the skin, it does not exclude the fruit flesh as a possible barrier, especially for fruit with low internal free space volumes (Solomos, 1987; Banks and Nicholson, 2000). When fruit flesh functions as a barrier, the diffusivity of gases in the fruit flesh is also needed to describe gas transport in fruit properly. Techniques to measure diffusivity have been developed, and are based on several assumptions. Streif (1999) developed a method based on the diffusion of an inert gas through a tissue sample. The diffusivity of oxygen and carbon dioxide was then recalculated using Graham’s law stating a constant relation between the diffusivity of two gases. A similar method (Zhang and Bunn, 2000) is based on a tissue sample separating two flowing gases. However, this does not resemble the actual conditions during storage. In both methods, respiration effects were not taken into account, although they do affect the measurements, as shown by Lammertyn et al.
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
(2001) where the respiration of the tissue and the diffusivity of the respiratory gases (O2, CO2) were measured separately. During the period surrounding harvest maturity several changes occur in the fruit. Fruit maturation and fruit ripening involve changes in texture, firmness, skin color, volatiles and chemical composition (sugar content, acidity, esters, alcohols) as well as changes in respiration and ethylene production. Reports about gas exchange properties, more specifically skin resistance of fruit, are not very consistent. While some authors (Park et al., 1993) found changes during the harvesting period, others did not. Elgar et al. (1999) found that the skin resistance to gas diffusion of ‘Braeburn’ apples was not influenced by harvest date. Schotsmans et al. (2002) reported no influence of harvest date on skin resistance to gas diffusion for ‘Jonica’ and ‘Braeburn’ apples nor for ‘Doyenne´ du Comice’ and ‘Conference’ pears. It is possible that changes in skin resistance during maturation occur since the fruit is going through so many changes, but it is also possible that there are no changes in skin resistance or that they cannot be measured with the available techniques since in the value of the skin resistance, information about the entire fruit is captured. Therefore, it would be interesting to measure diffusivity of specific tissue during harvest and see if the diffusivity changes. To our knowledge, it is not known whether diffusion properties are affected by tissue type, maturity of the fruit or storage. The objectives of this research were: (1) to develop a method for the simultaneous measurement of transport properties of O2, CO2 and N2 in fruit tissue, (2) to evaluate whether the gas transport properties vary inside the fruit and (3) to investigate whether they are affected by the maturity stage.
2. Materials and methods 2.1. Fruit material Three experiments were carried out on tissue and skin samples of pears. In the first experiment, the ‘Conference’ pears were harvested in Septem-
157
ber 2000 at a pre-climacteric stage at the research station PCF-PPS (Proeftuin voor Pit- en Steenfruit, Velm) and cooled for a period of 21 days at /0.5 8C preceding controlled atmosphere storage (/0.5 8C, 2% O2/0.7% CO2) according to commercial protocols. After 7 months of storage, a total of 24 skin samples and 21 fruit flesh samples (5 mm under the skin) was measured. In the second experiment, samples were taken from three different tissue groups along the radial axis, more specifically the skin, the mesocarp (13 / 17 mm under the skin depending on the size of the fruit) and the core tissue (24 /30 mm under the skin), to test the spatial distribution of diffusivity of O2 and CO2 within the fruit. The samples were obtained after 3 months of storage from ‘Conference’ pears harvested in 2001 at a pre-climacteric stage (12 September) at the Fruitteeltcentrum (Rillaar, Belgium), and cooled for a period of 21 days at /0.5 8C preceding controlled atmosphere storage (/0.5 8C, 2% O2/0.7% CO2). The third experiment was designed to investigate maturity effects and was performed from August (21 days before the optimal harvest date) to October 2001 (21 days after the optimal harvest date). In the period surrounding the optimal harvest date for long-term storage, ‘Conference’ pears were picked every Monday, Wednesday and Friday at the Fruitteeltcentrum (Rillaar, Belgium) and the diffusivity of the pear cortex tissue was measured in order to assess changes in diffusivity in the fruit flesh in this period. 2.2. Experimental set-up and procedures The diffusion set-up consisted of two doublesided glass chambers (left and right chambers, each 650 ml) separated by the tissue sample in a sample holder (Fig. 1). The sample holder was a metal cylinder consisting of two halves screwed together holding a PVC ring containing the tissue sample glued with cyano-acrylate glue. The connections between different materials were made airtight with rubber airtight seals to prevent leakage to the outside and to ensure that all gas transport took place through the tissue sample. A temperature-controlled waterbath (F10-HC, Julabo Labor Technik GmbH, Seelbach, Germany)
158
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Fig. 1. Experimental set-up for gas diffusion measurements consisting of two glass chambers separating the tissue that is to be measured.
circulating water through the water jacket of the chambers, kept the set-up at a constant temperature of 12.09/0.1 8C. Pear flesh samples were first cut with a professional slice cutter (EH 158-L, Graef, Germany), subsequently small cylinders with a diameter of 24 mm were cut with a cork borer. The thickness of the sample was measured with a digital calliper (Mitutoyo Ltd., UK) and ranged from 1 to 2 mm. The tissue sample was glued onto a polyvinylchloride ring (inner diameter of 22 mm) with cyanoacrylate glue. The glue was applied thinly to avoid a toxic effect on the cells. The same procedure was used for the skin samples. A razor blade was used to remove the flesh from the skin sample until a thickness of less than 1 mm was obtained. The samples were inserted in the set-up without delay after which one chamber was flushed (20 min at a volume flow rate of 20 l h1) with N2 containing 20 kPa O2/5 kPa CO2, while the other one was flushed with N2 containing 5 kPa O2/20 kPa CO2 to establish a large gas concentration gradient over the fruit tissue. Measurements were performed at constant temperature (12 8C). The gas mixtures were prepared from pure O2, CO2 and N2 by
means of mass flow controllers (Lammertyn et al., 2001) and subsequently directed through a heat exchanger and humidifier in order to deliver the gas to the experimental set-up at 12 8C and humidify the gas in order to minimise dehydration of the sample. After flushing, the chambers were sealed and four samples were taken within the next day with intervals of 3 h. Sampling consisted of measuring the gas composition with a micro-GC (CP2003-P, Chrompack, The Netherlands) with an automatic pump sampling system (40 s of sampling at a volume flow rate ranging from 5 to 20 ml min1) and monitoring the total pressure for each chamber with a pressure sensor (PTX 520-0, Druck, The Netherlands). The gas partial pressures obtained by multiplying the mole fractions and the total pressure were converted to moles using the universal gas law. As part of these diffusion measurements, respiration and oxidation effects due to the wounding of the tissue were measured separately using tissue samples with the same dimensions as the samples used for the diffusion experiment. The samples were prepared in the same manner as the samples for the diffusion set-up thus ensuring the
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
same amount of wounding. Samples (20 /30) were placed in two separate 1.2 l glass containers, one for each gas mixture, and flushed with each gas mixture during 20 min at a volume flow rate of 20 l h1. Subsequently, the containers were closed and a sample of the headspace was taken simultaneously with the diffusion measurements using a micro-GC with an automatic pump sampling system. The output was expressed in percentages or mole fractions and the total pressure was monitored with a pressure sensor. Partial pressures were obtained by multiplying the mole fractions and the total pressure, and were converted to mol m 3 using the universal gas law. 2.3. Model construction and calculations The model consisted of six differential equations; every differential equation consisted of three well-defined parts describing the change in moles of gas during time. The first part described diffusion based on Fick’s first law of diffusion. The second part deals with the consequences linked to the sampling procedure and the final part brings filtration of gas due to a pressure gradient over the tissue into the model. Preliminary tests with fruit tissue showed that, as expected, gas consumption and production due to respiration and oxidation interfere with the gas transport. Therefore, the model was expanded with a fourth part representing respiration and oxidation. The six differential equations of the model have the same form as shown in the following equation: dni;j (t) dni;j (t) dni;j (t) dt dt dt diff sampling dni;j (t) dni;j (t) ; (1) dt dt p resp where n is the number of moles of gas, t the time (s), i is O2, CO2 or N2, and j is L (left chamber) or R (right chamber). Different parts of the model will be discussed separately. 2.3.1. Diffusion The diffusion process was described using Fick’s first law of diffusion (Geankoplis, 1993):
Jd D
@C : @x
159
(2)
This law states that the flux of a gas, Jd (mol s 1 m2), diffusing through a barrier, is determined by the diffusivity of the gas, D (m2 s 1), and the concentration gradient over this barrier, @C /@x (mol m 3 m 1). For one dimension in steady-state conditions, the concentration gradient is linear (Cameron and Yang, 1982; Banks, 1985) and Eq. (2) can be rewritten. The concentration gradient is the difference in gas concentration between the two chambers with the barrier being the tissue sample with thickness l: @C DC CR CL 1 nR nL : (3) @x Dx Dx VR VL Dx A simple model for the change in absolute amount of gas due to diffusion, valid at constant temperature conditions, can be developed for each gas in the system: dni;L (t) D A ni;R (t) ni;L (t) i ; dt l VR VL diff (4) dni;R (t) Di A ni;R (t) ni;L (t) ; dt l VR VL diff where VL and VR (m3) are the volumes of the left and the right chambers, respectively, A (m2) is the surface area of the barrier, and l (m) the thickness of the tissue sample or barrier. 2.3.2. Sampling losses The second part of the model covers the removal of gas by sampling. The amount of gas that is subtracted from the system is not constant since it is subtracted by an automatic pump sampling system with varying velocities; therefore, it has to be calculated. This is possible since the pressure drop during sampling (DP ) is measured. The pressure drop during sampling can be recalculated to moles using the universal gas law. The amount subtracted from either chamber can then be calculated as Dn
DP(t)V RT
(5)
160
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
with DP the pressure drop during sampling (Pa), T (K) the absolute temperature and R the universal gas constant (m3 Pa mol 1 K 1). The amount of each gas as a function of time that is taken out is assumed to be proportional to the mole fraction of different gases at sampling (ni/ntot) and the sampling time (ts):
dni;L (t) KA P (t) (PR (t)PL (t)) i;j ; dt RTl Pj (t) p dni;R (t) KA P (t) (PR (t)PL (t)) i;j ; dt RTl Pj (t) p X Pi;L (t); PL (t) i
dni;L (t)
ni;L (t) DPL VL
PR (t)
;
dt ntot;L RTts sampling dni;R (t) n (t) DPR VR i;R : dt ntot;R RTts sampling
(6)
2.3.3. Gas transport due to overall pressure differences At the start of the experiment, the total pressure at both sides is equal. Due to the unbalanced gas transport between the chambers, pressure can build up in one chamber. The film or tissue will then act as a filter and with total pressure as the driving force; gases will be transferred in bulk, the composition proportional to the molar composition of the environment where the force is applied (thus, the composition of the chamber with the highest pressure). This filtration transport can be described with Darcy’s law (Geankoplis, 1993). The flux of a gas through a filter, Jp (mol s 1 m 2), due to a pressure difference can be described using the permeability of the filter, K (m2 s 1) and the total pressure gradient, @P /@x :
Jp
K @P : RT @x
(7)
Translated to the used set-up, the following equations were obtained. The factor Pi,j(t)/Pj(t) denotes the mole fraction of gas i in the gas flow coming from side j where the overall pressure is highest:
L; j R;
X
Pi;R (t);
i
if PL (t)PR (t); if PL (t)BPR (t):
(8)
If the pressure is higher at the left side, transport will proceed from the left to the right and so the mole fraction of gas in the gas mixture on the left is required. If the pressure is higher at the right side, transport will proceed from the right to the left and the mole fraction of gas in the gas mixture on the right is required.
2.3.4. Respiration and oxidation When working with fruit tissue, the total amount of oxygen decreases and the total amount of carbon dioxide increases due to respiration and oxidation effects. Respiration and oxidation were included in the model as a consumption term in the case of oxygen (rO2 in mol kg1 s 1) and a production term (rCO2 in mol kg1 s 1) in the case of carbon dioxide. The consumption of oxygen and the production of carbon dioxide were measured separately using tissue samples with the same dimensions as the samples used for the diffusion experiment and at the same temperature and atmospheric conditions as the diffusion experiment in order to decrease the number of parameters to be estimated simultaneously. In order to obtain the amount of produced or consumed gas in moles, the measured respiration rate was multiplied by half the mass of the fruit tissue sample (msample in kg) in the diffusion set-up since we assumed that half the tissue is under the respiring conditions from the left side and the other half under respiring conditions on the right side:
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
dnO2 ;j (t) dt resp dnCO2 ;j (t) dt
rO2 ;j rCO2 ;j
msample ; 2 msample
resp
2
:
(9)
The differential equations were integrated numerically with a FORTRAN program using NAG library Mark XIV routine DO2EBF (Numerical Algorithms Group Ltd., Oxford, UK, 1986). Parameter values were obtained by manual alteration of the values followed by an automatic parameter estimation procedure (NAG-routine E04FDF). In order to check the correctness of the estimated parameters, the experimental data were plotted together with the model predictions and visually assessed. Data analyses were performed using the statistical analysis system (SAS Institute, Inc., Cary, NC, 1992). Treatment effects were analysed by the GLM procedure and treatment mean separation was determined by Fisher’s LSD (P B/0.05) or Duncan’s multiple range tests. 2.4. Validation The film used for validation was a CoexBlasfolie VIP-3728 packaging film with a thickness of 0.040 mm (VINORA AG, Switzerland). Diffusivities for O2, CO2 and N2 at 23 8C were provided by the manufacturer and are shown in Table 3. Experiments on film were performed at 23 8C.
3. Results and discussion
in total pressure, which would otherwise contribute too much to the gas transport in the set-up. Respiration was measured at both 20 kPa O2/5 kPa CO2 and 5 kPa O2/20 kPa CO2, the conditions used for the diffusion experiments. Both skin and flesh respiration rates were significantly higher at 20 kPa O2 compared with 5 kPa O2 (Table 1). The O2 consumption rate and CO2 production rates of skin were significantly higher than for flesh. For skin, the more extensive wounding would cause an increase in wound respiration and non-respiratory O2-consuming reactions induced by scraping the remaining tissue from the skin (Lammertyn, 2001), and this could provide an explanation for the higher O2 consumption. In Fig. 2, O2 and CO2 partial pressure profiles for skin and flesh in both chambers for one representative sample each are shown. In the left chamber, the higher O2 partial pressure caused O2 transport to occur from the left to the right chamber while CO2 diffused in the opposite direction from the right chamber with higher CO2 partial pressure to the left chamber with lower CO2 partial pressure. In the skin, the pattern was similar for both respiratory gases, suggesting transport at the same rate, thus pointing to equal diffusion constants. When diffusivity values are compared (Table 1), this prediction stands; the average values for skin of 1.03 /109 m2 s 1 for O2 and 1.15 /109 m2 s 1 for CO2 diffusivity were not significantly different. From Fig. 2, it seems that transport through skin is faster than that through flesh but one must consider that the Table 1 Diffusivity and respiration rates for cortex tissue and skin tissue of ‘Conference’ pears after 7 months of storage
3.1. Diffusivity in pear skin and flesh The gradient was chosen such that transport of O2 and CO2 took place in opposite directions, whereas in reality CO2 normally moves outwards and O2 inwards. If both gradients would have the same direction, gas would accumulate in the chamber with the lower partial pressure causing a large difference in total pressure. With opposite gradients, this difference in total pressure is small, thus minimising transport caused by a difference
161
Cortex tissue DO2 (10 9 m2 s 1) DCO2 (10 9 m2 s 1) DCO2/DO2 rO2 at 20 kPa O2 (10 8 mol kg1 s 1) rO2 at 5 kPa O2 (10 8 mol kg1 s 1) rCO2 at 20 kPa O2 (10 8 mol kg 1 s 1) rCO2 at 5 kPa O2 (10 8 mol kg 1 s 1)
Skin
2.19/0.6 1.09/0.3 199/4 1.29/0.3 9.1 1.1 10.79/1.4 999/36 7.49/1.9 699/59 7.99/1.4 799/20 2.49/1.6 319/8
Values are presented with a 95% confidence interval of the mean.
162
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Fig. 2. Oxygen (upper) and carbon dioxide (lower) partial pressure profiles for skin (left) and cortex tissue (right) of ‘Conference’ pears after 7 months of storage for both the right (measured value ( /); model profile (- -)) and the left (measured value (k); model profile ( */)) chamber at 12 8C.
skin samples are considerably thinner than the flesh samples. In flesh, CO2 moved significantly faster than O2 (Fig. 2) resulting in a CO2-diffusivity of 19.2 /109 m2 s 1 and a nine times lower O2-diffusivity (2.1 /10 9 m2 s 1). Literature data about the coupled effect of gas diffusivity and respiration in pears are scarce although diffusivity in other horticultural commodities has been studied numerous times. It is interesting to compare the obtained results with literature data, even though these are not very consistent either. The results obtained in this research for the diffusivity of O2 and CO2 in flesh (2.1 /109 and 19.2 / 109 m2 s 1) are in agreement with the O2diffusivity in flesh of 1.71 /109 m2 s 1 and the CO2-diffusivity of 19.5 /109 m2 s1 reported by Lammertyn (2001). However, although the CO2diffusivity of 1.2 /10 9 m2 s 1 for pear skin was similar to that reported by Lammertyn (2001) (9.1 /1010 m2 s 1), the O2-diffusivity of 1.0 /
109 m2 s 1 for skin was four times higher than that reported by Lammertyn et al. (2001) (2.8 / 1010 m2 s 1). Large differences like this have also been reported by other authors; Solomos (1987) measured a CO2 diffusivity for potato skin and flesh of 2.2 /108 and 2.5 /107 m2 s1, respectively, while Abdul-Baki and Solomos (1994) obtained values of 6.24 /1011 m2 s 1 for skin and 2.5 /10 8 m2 s 1 for flesh. The ratio of CO2 to O2 diffusivity would be 0.8 for all tissue types when Graham’s effusion law would be used, assuming free diffusion in air. On the contrary, the ratio between CO2 and O2 diffusivity depended on the type of tissue in the present experiments. For flesh the ratio was 9.1 (11.4 found by Lammertyn et al., 2001), CO2 diffusivity was considerably larger than O2 diffusivity. The different transport paths followed by the gases in the flesh might explain this, since transport occurs mainly through the intercellular
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
free spaces, filled with air or liquid. Transport of both gases through air-filled free spaces is almost equal as well as the diffusivity of both gases in water (Lide, 1999), but the O2 and CO2 diffusivity in liquid water is approximately 104-fold less than in air (Amarante et al., 2001). Consequently, the main pathway for gas transport in fruit flesh tissue is through the intercellular free spaces, filled with air. On the other hand, CO2 is much more soluble in liquid than O2 (solubility of CO2 in water is 25 times higher than that of O2; Geankoplis, 1993). Because CO2 is more soluble in water, it can dissolve in the moisture present in the intercellular spaces and it can be transported along with the moisture. For skin, however, this is not the case and the ratio between CO2 and O2 diffusivity was 1.1 (3.2 found by Lammertyn et al., 2001), CO2 diffusivity was similar to O2 diffusivity. This could be due to the substantially smaller contribution of moisture transport in the overall transport of O2 and CO2 in the skin, because moisture transport in the cuticle is significantly slower than in the fruit flesh. Veraverbeke (2001) found diffusivities of moisture in cuticle to be 100/3000 times smaller compared with tissue in ‘Elstar’ and ‘Jonagold’ apples, respectively. These results indicate that Graham’s law cannot be used to calculate the diffusivity or skin resistance for one gas from the diffusivity or skin resistance for another gas. 3.2. Diffusivity during harvest The average O2 consumption rate at 20 kPa O2 was 22 /108 mol kg1 s 1 and slightly higher than at 5 kPa O2 (13 /10 8 mol kg1 s1), the average CO2 production rate at 20 kPa O2 was 16 /10 8 mol kg1 s 1 and was significantly higher than at 5 kPa O2 (10 /108 mol kg1 s 1). These consumption and production rates were constant during the whole period. For the diffusivity of O2 and CO2 in the fruit cortex tissue average values were obtained of 3.8 /10109/ 0.4 /1010 and 3.8 /10 99/0.5 /109 m2 s 1, respectively. No change in diffusivity of O2 or CO2 was detected during the 7 weeks in which measurements were performed (Fig. 3), confirming the results of skin resistance measurements (Schotsmans et al., 2002) where a similar conclusion was
163
drawn. Even though significant structural and compositional changes occur in this maturation period, this does not necessarily imply that the diffusivity of the respiratory gases (O2, CO2) is influenced by these changes.
3.3. Diffusivity at different positions in a fruit In order to assess the presence of a diffusivity gradient in a fruit, three samples were taken from each ‘Conference’ pear, one near the core, one at half radial distance in the cortex and one of the skin. The measured diffusivities were considerably different from those measured in the previous year. This may be due to several factors such as the different growing conditions and orchard, and the different storage duration. The values represented in Table 2 are averages over 10 fruit for each position measured in a period of 2 weeks with a 95% confidence interval surrounding the mean. A first and important observation is the magnitude of these confidence intervals, a direct consequence of working with biological material and a limited number of repetitions. Consequently, significant differences are scarce and mostly trends can be observed, as was the case for the influence of the radial position of the sample on the measured diffusivity. The O2-diffusivity seems uniform throughout the fruit (Fig. 4), concurring with findings for ‘Braeburn’, where the flesh exerted a significant resistance to O2 diffusion resulting in a significant O2 gradient between tissue immediately beneath the peel and the center of fruit (Rajapakse et al., 1990). On the other hand, the CO2-diffusivity gradient was very pronounced. The CO2-diffusivity (Table 2) was 9.8 /109 m2 s 1 at the core, half (5.2 /10 9 m2 s 1) at half radial distance and minimal in the skin (3.8 /10 10 m2 s 1). Calbo (1985), Solomos (1987) and Argenta et al. (2002) also reported the existence of significant CO2 gradients within apple fruit. In avocado flesh, a decrease in diffusivity was related to the clogging of air spaces by cell exudates, while an increased O2 gradient in nectarines could be linked to the decreased intercellular space volume (Rajapakse et al., 1990).
164
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Fig. 3. Oxygen (A) and carbon dioxide (B) diffusivities in cortex tissue of ‘Conference’ pears at 12 8C during the period surrounding the optimal harvest date for long-term storage. Vertical bars indicate 95% confidence intervals surrounding the mean. Table 2 Oxygen and carbon dioxide diffusivity (10 9 m2 s 1) at different radial distances in ‘Conference’ pear measured after 3 months of storage Skin
At half radius
Near core
DO2 (10 10 m2 s 1) 0.339/0.24a* 0.439/0.17a 0.879/0.69a DCO2 (1010 m2 s 1) 0.439/0.65a 1.739/1.15a 7.649/6.96a DCO2/DO2 1.3 4.0 8.7 Values are presented with a 95% confidence interval of the mean. * Means with the same letter are not significantly different (Fisher’s LSD; P/0.05).
The ratio CO2/O2 diffusivity (4.0) was lower after 3 months compared with that at the time of harvest (9). Although the O2-diffusivity did not change during the 3 months of storage, the CO2diffusivity decreased during this time, from 3.8 / 109 m2 s 1 at harvest to 1.7 /109 m2 s 1 after 3 months of storage.
3.4. Validation Validation measurements were performed with film at 23 8C, which is the temperature at which the permeability of the film was determined by the manufacturer. The results are presented in Table 3. There was an acceptable agreement between the estimated diffusivity for O2 and CO2 and with the values provided by the manufacturer. The overestimated N2-diffusivity was probably the result of the fact that no partial pressure gradient was applied for N2. If no significant gradient is present, it is impossible to obtain an accurate estimate for that parameter in the model.
4. Conclusions A diffusion chamber set-up was constructed to determine the diffusivity of O2 and CO2 in pear fruit tissue. The diffusion parameters of the different respiratory gases could be estimated
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
165
Fig. 4. Oxygen (A) and carbon dioxide (B) diffusivities at different positions in ‘Conference’ pears measured at 12 8C after 3 months of storage. Vertical bars indicate 95% confidence limits of the mean.
Table 3 Diffusivity (10 13 m2 s 1) of the packaging film provided by the manufacturer and result of the validation experiment Gas
O2
CO2
Diffusivity Estimated diffusivity
15.6 20.89/1.4
58.9 55.69/5.4
N2 3.84 6.39/6.1
with satisfying accuracy. In flesh, the CO2-diffusivity was mostly larger than the O2-diffusivity. This can be explained when the different transport paths followed by the gases in the flesh are taken into account. Transport of O2 and CO2 through air-filled free spaces is similar but CO2 is much more soluble in liquid, and can thus be transported along with moisture through the free spaces filled with liquid. For skin, however, this is not the case and the ratio between CO2 and O2 diffusivity was very small since both gases diffuse mainly through
pores. As expected from former skin resistance measurements, no change in diffusivity was found in the weeks prior to and after the optimal harvest date for long-term storage. This means that even though significant structural and compositional changes occur in this period, these changes do not necessarily influence the diffusivity of the respiratory gases. After 3 months of storage, a significant rise in CO2-diffusivity in the fruit flesh was found, CO2-diffusivity was smallest at the skin and increased significantly from the skin to the core of the pear fruit, while no difference in O2diffusivity was observed. The results imply that it is not possible to determine the diffusivity or resistance of one gas and recalculate to another using Graham’s law since this law states a constant relationship between diffusivities and this is not the case for fruit tissue where the ratio between CO2 and O2 diffusivity depends on tissue type and age of the fruit.
166
W. Schotsmans et al. / Postharvest Biology and Technology 29 (2003) 155 /166
Acknowledgements The financial support of the Flemish Minister for Science and Technology, the Ministry of SME and Agriculture (Project D12-5771A), the EU (Fair project CT96-1803) are gratefully acknowledged and the Catholic University Leuven (IDOproject 00/008). Author Wendy Schotsmans is a doctoral fellow of IWT. The financial support of this institute is acknowledged with gratitude. Jeroen Lammertyn is postdoctoral fellow with the Flemisch Fund for Scientific Research (FWO-Vlaanderen).
References Abdul-Baki, A.A., Solomos, T., 1994. Diffusivity of carbon dioxide through the skin and flesh of ‘Russet Burbank’ potato tubers. J. Am. Soc. Hort. Sci. 119, 742 /746. Amarante, C., Banks, N.H., Ganesh, S., 2001. Relationship between character of skin cover of coated pears and permeance to water vapour and gases. Postharvest Biol. Technol. 21, 291 /301. Argenta, L., Fan, X., Mattheis, J., 2002. Impact of watercore on gas permeance and incidence of internal disorders in ‘Fuji’ apple. Postharvest Biol. Technol. 24, 113 /122. Banks, N.H., 1985. Estimating skin resistance to gas diffusion in apples and potatoes. J. Exp. Bot. 36, 1842 /1850. Banks, N.H., Nicholson, S.E., 2000. Internal atmosphere composition and skin permeance to gases of pepper fruit. Postharvest Biol. Technol. 18, 33 /41. Burg, S.P., Burg, E.A., 1965. Gas exchange in fruits. Physiol. Plant. 18, 870 /874. Burton, W.G., 1965. The permeability to oxygen of the periderm of the potato tuber. J. Exp. Bot. 16, 16 /23. Calbo, A.G., 1985. Gas exchange in fruits and vegetables and the use of oscillating pressure storage. Ph.D. Thesis. University of California, Davis, CA. Cameron, A.C., Yang, S.F., 1982. A simple method for the determination of resistance to gas diffusion in plant organs. Plant. Physiol. 70, 21 /23.
Elgar, H.J., Watkins, C.B., Lallu, N., 1999. Harvest date and crop load effects on a carbon dioxide-related storage injury of ‘Braeburn’ apple. HortScience 34, 305 /309. Emond, J.P., Castaigne, F., Toupin, C.J., Desilets, D., 1991. Mathematical modelling of gas exchange in modified atmosphere packaging. Trans. ASAE 34, 239 /245. Geankoplis, C.J., 1993. Transport Processes and Unit Operations. Prentice-Hall, Englewood Cliffs, NJ. Kader, A.A., 1988. Respiration and gas exchange of vegetables. In: Weichmann, J. (Ed.), Postharvest Physiology of Vegetables: Food Science and Technology. Marcel Dekker, New York, pp. 25 /43. Knee, M., 1991. Rapid measurement of diffusion of gas through the skin of apple fruits. HortScience 26, 885 /887. Lammertyn, J., 2001. A respiration /diffusion model to study core breakdown in Conference pears. Ph.D. Dissertation. Katholieke Universiteit Leuven, Leuven. Lammertyn, J., Scheerlinck, N., Verlinden, B.E., Schotsmans, W., Nicolaı¨, B.M., 2001. Simultaneous determination of oxygen diffusivity and respiration in pear skin and tissue. Postharvest Biol. Technol. 23, 93 /104. Lide, D.R., 1999. Handbook of Chemistry and Physics. CRC Press, New York. Park, Y.M., Blanpied, G.D., Jozwiak, Z., Liu, F.W., 1993. Postharvest studies of resistance to gas diffusion in McIntosh apples. Postharvest Biol. Technol. 2, 329 /339. Rajapakse, N.C., Banks, N.H., Hewett, E.W., Cleland, D.J., 1990. Development of oxygen concentration gradients in flesh tissues of bulky plant organs. J. Am. Soc. Hort. Sci. 115, 793 /797. Schotsmans, W., Verlinden, B.E., Lammertyn, J., Peirs, A., Jancso´k, P., Scheerlinck, N., Nicolaı¨, B.M., 2002. Factors affecting resistance to gas diffusion of pip fruit. Postharvest Biol. Technol. 25, 169 /179. Solomos, T., 1987. Principles of gas exchange in bulky plant tissues. HortScience 22, 766 /771. Streif, J., 1999. Vortragstagung der DGQ. Deutsche Gesellschaft fu¨r Qualita¨tsforschun, Freising-Weihenstephan, XXXIV. Veraverbeke, E., 2001. Changes in epicuticular wax structure and composition in relation to moisture loss of apple during postharvest storage. Ph.D. Dissertation. Katholieke Universiteit Leuven, Leuven. Zhang, J., Bunn, J.M., 2000. Oxygen diffusivity of apple flesh and skin. Trans. ASAE 43, 359 /363.