Micro-CT imaging and analysis of eggplants and carrots during air drying

G. van Dalen

1, J. Qiu

1,2, S. Khalloufi

1

1 Unilever Research & Development, Olivier van Noortlaan 120, 3133AT Vlaardingen, the

Netherlands 2 Agrotechnology & Food Sciences, Wageningen University, The Netherlands

Introduction

Drying is an efficient method used to preserve food products and can significantly lower the storage and transport costs. It not only significantly reduces the moisture content, microbiological activity and undesirable enzymatic modifications, but also reduces the product mass and volume and does not require refrigeration during storage. However, during the drying processes, food products undergo various macro and/or micro changes in physical and chemical structures which can be explained by porosity, density, volume reduction, etc. Simulations by using models to predict volume reduction, density and porosity are important tools for drying technologie[1]. These models can further be improved by including the initial porosity of fresh foodstuffs. The initial porosity can present a significant portion of the total volume of fresh foodstuffs. Therefore, ignoring this considerable volume fraction in modelling porosity will lead to poor predictions. Using both shrinkage and collapse mechanisms is necessary to describe the porosity profiles. Vegetables with different initial porosities will be studied. Carrots were chosen as prototype for low initial porosity vegetables and eggplants as a vegetable with high porosities. X-ray microtomography (micro-CT) is used for the non-invasive visualisation and analysis of the 3D microstructure of food products at a sub-micron level spatial resolution [2]. Micro-CT has proven to be a very useful technique for the characterisation of the internal microstructure of cellular food products, such as cereals[3,4], bread[5,6]], desserts[7,8], aerated chocolate[2], and dried vegetables[9,10,11]. In this study micro-CT is used to quantify the density, porosity and shrinkage during air drying of carrots and eggplants (aubergine).

Method Vegetables were obtained from a local supermarket. The obtained vegetables were cut into small cylinders of 2 cm length and 0.8 cm diameter and ready for the following drying process[2]. The prepared samples were dried in a food dehydrator (9-Tray W/Timer REFURB, Excalibur, USA), at a constant temperature of 60˚C. At different drying time points, the samples were taken out and their mass (mt) was weighed immediately, by an electronic analytical balance (±0.1mg, Cubis® AC120S, Sartorius, UK). Each sample was placed into a sample holder immediately after weighing, to prevent the further loss of moisture content in the environment, and ready for the subsequent testing by micro-CT. For each drying time, two different samples were tested by micro-CT in duplicate.

Measurements of moisture content of eggplants and carrots at different drying time were carried out after micro-CT imaging. The tested samples were dried by a vacuum oven dryer (Gallenkamp vacuum oven, Fistreem International Ltd., UK), at the drying condition of -1000 mbar and 80˚C. The selection of drying time was 24 hours in order to make sure that all the samples were totally dried. Next, the mass of the sample (mt-d) was measured and the moisture content was calculated using the following equation:

moisture content (X/X0) = (mt-mt-d)/(m0-m0-d) Where mt is the sample mass at different drying time and mt-d is the mass of the sample after totally drying. Samples were imaged using a Skyscan 1172 desktop micro-CT system (Belgium, http://www.skyscan.be) with a 100kV X-ray source (10 W, 20-100 kV, 0-250 μA, < 5 μm spot size) and a 10 Mp X-ray detector (4000 * 2096 pixels). Power settings of 59 kV and 167 μA were used. Images were acquired using a step size of 0.33º over 180 degrees and frame averaging of 3. Scans with pixel sizes ranging from 6.5 μm to 8.2 μm were made. The total scanning time (~600 images) was 50 - 90 min for a single scan. For the fresh sample 2 scans were made, which were stitched together (oversized scan). A stack of 2000-3000 horizontal cross sections with a pixel size of ~1400 * 1400 was obtained after tomographic reconstruction of the projection images. A beam hardening correction of 40%, ring artifact correction of 20 and smoothing of 4 were selected. Samples were imaged in plastic cylindrical sample holders with an inner diameter of 8mm. The sample was fixed in the sample holder using styrofoam (Figure 1).

Figure 1 Preparation of cylinders from an eggplant (left) with cylinders of samples of fresh

and dried eggplant in a plastic cylindrical sample holders with an inner diameter of 8 mm.

For image analysis and 3D visualisation the AvizoFire software version 8.0.1 from the FEI - Visualization Sciences Group was used. The sample holder was removed by using binary masking. The volume of the sample (V) was calculated from the number of pixels in 3D binary image of the sample (after binary filling of the pores). The bulk density of the sample was calculated from its mass and total volume (ρb = m / V).

The total sample volume (V) can be analysed from scans with a low resolution. Using a pixel size of 8.2 µm, a sample with a length of 17 mm can be imaged using a single scan. However to analyse the porosity (ε) from the images of dried vegetables using binary image processing a much higher resolution is needed. This is illustrated in Figure 2. The images of a fully dried eggplant show a very open structure with small and large pores separated by very thin walls. Thresholding was done using an automatic procedure (Otsu[12]). The method is based on statistical separation of the two classes “background pixels = air” and “foreground pixels = solid” and automatically identifies the optimal threshold. A lower resolution results in blurring of the solid material by which more solid material is detected and therefore less air and thus a lower porosity. To image a total sample of a length of 20 mm at a pixel size of 1.5 µm at least 7 scans are needed. In order to avoid high resolution scans with long measurement times, the

porosity was calculated from the particle density ρp and the bulk density (ρb). The particle

density ρp is defined as the ratio of the mass of sample to its volume including water and

excluding air:

𝜀 = 1 −𝜌𝑝

𝜌𝑏× 100%

The particle density was determined using the composition of food matrices:

1

𝜌𝑝= ∑

𝑋𝑖

𝜌𝑖

In which ρi is the density of the i

th component in the matrix and Xi is the mass fraction of the i

th

component. In this study, the density of different food components and the compositions of eggplants and carrots are obtained from open literatures[13,14]. For eggplants and carrots a density of 1489 kg/m

3 was used for the solid material and 1050 kg/m

3 for water.

The porosity (ε) of a fully dried eggplant sample determined from the particle density is 94% which is in good agreement with the porosity analysed from the image obtained at 1.5 µm (95 %, see Figure 2).

The volume reduction or shrinkage coefficient (Sv) is defined using the following equation:

Sv = V / V0 V and V0 = the sample volume during drying and the initial (fresh) volume, respectively. The volume includes also the pores.

Figure 2 Influence of the image resolution on the porosity analysed from a stack of micro-

CT images of a fully dried eggplant (left: grey level image, right: binary image). The porosity determined from the total volume of the dried eggplant sample and the densities of different food components is 94%.

Results Representative vertical cross section through 3D micro-CT images of cylinders of fresh carrots and eggplants are shown in Figure 3. The image of the carrot shows a very dense structure with small pores and low porosity whereas the image of the eggplant shows a very open structure with a high porosity. The air spaces are in general not homogeneously distributed within the tissues of fresh porous vegetables. This is illustrated in Figure 4 for eggplants. Only the central part of the eggplant cylinders taken from across the radial axes were used in the drying experiments.

Figure 3 Vertical cross sections of micro-CT images of fresh carrots (left) and eggplants

(right) (inner diameter tube = 8.2 mm) with enlarged views at the centre.

Figure 4 Photograph of a cylinder of a fresh eggplant sample (A) with micro-CT image of a

vertical cross section (B) and volume fraction of air across the radial axes (C) [1]. Selections of vertical cross sections and 3D visualisations of carrots and eggplants during air drying are shown in Figure 5 and Figure 6. The images show clearly an overall volume reduction in time. This volume reduction is larger for carrots than for eggplants. A large amount of the initial amount of air in the eggplant sample will still be present after drying.

Figure 5 Vertical cross sections through 3D micro-CT images of eggplant (top) and carrot

(bottom) during drying (inner diameter sample holder = 8.2 mm).

Figure 6 3D visualisation of micro-CT images of eggplant (top, box size = 8.9 mm * 8.5 mm

* 24.9 mm) and carrot (bottom, box size = 10.0 mm * 10.0 mm * 20.8 mm) during drying.

The mass and calculated moisture content of the eggplant and carrot cylinders during drying are presented in (Figure 7). The eggplant samples dry much faster than the carrot samples.

Figure 7 Mass (left) and calculated moisture content (right) of eggplant and carrot cylinders as a function of the drying time. The results of the analysis of the shrinkage coefficient of eggplants and carrots are plotted as a function of moisture content and shown in Figure 8. Eggplants are reported as a vegetable with high porosities. They show a sharp decrease of volume at the beginning of the drying while it became slower at lower moisture content. At the end of the drying, the volume of the eggplant decreased to 30% of its initial volume and then increased a little. This phenomenon might be attributed to the elasticity of the food matrix. Carrots are reported as a low-porosity vegetable. They show a linear decrease of volume with a decrease of moisture content. At the end of the drying, the volume of the carrot decreased to 9% of its initial volume.

Figure 8 Shrinkage coefficient (Sv) of eggplants and carrots as a function of moisture

content. The bulk density change of eggplants and carrots is plotted in Figure 9. At the beginning of drying, the bulk density of eggplants tends to slightly increase with a small slope. At around the moisture content of X/X0 = 0.5, an inversion point is observed and then the bulk density begins to decrease sharply with a large slope, down to about 100 kg/m

3. At the end of the

drying, the bulk density reduces to 16% of the initial bulk density. The bulk density of carrots behaves differently from eggplants and keeps increasing with the drying process. The final bulk density reaches up to 1300 kg/m

3.

The results of analysis of the porosity of eggplants and carrots are plotted as a function of moisture content and shown in Figure 10. The porosity of eggplants first decreases slightly. Around a moisture content of X/X0 = 0 .5, an inversion point is observed and then the porosity

0.0

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shri

nka

ge c

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fici

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t

moisture content [X/X0]

eggplant

carrot

begins to increase sharply with a large slope. At the end of the drying, the finial porosity reaches 94%. The porosity of carrots decreases at the beginning of drying and then increases. The slopes of both decrease and increase are very small. At the end of drying, the porosity is around 6%, which is still lower than its initial value.

Figure 9 Bulk density of eggplants and carrots as a function of moisture content.

Figure 10 Porosity (ε) of eggplants and carrots as a function of moisture content.

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1,200

1,400

0.0 0.2 0.4 0.6 0.8 1.0

bu

lk d

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/m3

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eggplant

carrot

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carrot

Conclusion This study demonstrates the capability of micro-CT to visualise and analyse the 3D microstructure of vegetables during air drying. The density, porosity and shrinkage could be analysed from the 3D micro-CT images and can be used to validate theoretical models to predict these drying parameters as function of the moisture content[15]. The presented method determines the porosity using the particle density and the total sample volume analysed by micro-CT. This method will be useful for the characterisation of porous products.

References:

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