NMR imaging of continuous and intermittent drying of pasta

Transcription

1 Journal of Food Engineering 78 (2007) NMR imaging of continuous and intermittent drying of pasta Huajing Xing a, Pawan Singh Takhar b, *,1, Greg Helms c, Brian He d a Department of Food Science and Toxicology, University of Idaho, Agricultural Biotechnology, Rm 203, Moscow, ID 83844, USA b Department of Animal and Food Sciences, Texas Tech University, Box 42141, Lubbock, TX , USA c Department of Chemistry, Washington State University, Pullman, WA 99164, USA d Department of Biological and Agricultural Engineering, University of Idaho, Moscow, ID 83844, USA Received 31 December 2004; accepted 14 September 2005 Available online 17 November 2005 Abstract An NMR imaging technique published in literature was adapted to investigate the role of glass transition on Fickian and non-fickian modes of moisture transport in pasta. The modified technique allowed measuring the moisture distribution in samples with initial moisture content from 10% to 50% or higher. A change in slope in the signal intensity versus moisture content curves indicated different state or distribution of water in pasta samples below 16.9% moisture content for both 22 C and 40 C data. Sharp shape of moisture content profiles during continuous drying experiments indicated non-fickian moisture transport near the glass transition regime. With progress of drying at 40 C, the moisture profiles became more round, as pasta approached towards the glassy state, which indicated Fickian transport. A sharp change in pastaõs moisture content during drying near glass transition caused a wide contrast in pastaõs mechanical properties across its cross-section, which may make it prone to stress-cracking. During intermittent drying, a wet layer near the surface of pasta samples was clearly observed, which caused greater amount of moisture loss than during continuous drying. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Glass transition; Non-Fickian; Pasta; Imaging; Drying; Intermittent 1. Introduction * Corresponding author. Fax: address: pawan.takhar@ttu.edu (P.S. Takhar). 1 Author has previously published as Pawan P. Singh. Many foods undergo glass transition in the temperature and moisture content range used for drying. Glass transition plays a critical role in moisture transport and stresscracking behavior of foods. Several studies in polymer science and food engineering have shown that fluid transport in biopolymers follows FickÕs law only when the biopolymers are in rubbery or glassy states sufficiently far from the glass transition region (Kim, Caruthers, & Peppas, 1996; Singh, Cushman, & Maier, 2003). In the vicinity of glass transition, the flow becomes non-fickian. To study the effect of glass transition during drying on stress-cracking and Fickian and non-fickian modes of moisture transport, it is important to determine the moisture profiles (water distribution across the cross-section) in a food. Moisture profiles in a food material can be measured using destructive and non-destructive methods. Slicing and freezing give inside values of moisture content. However, it is not an accurate method because it is difficult to cut a food with high precision, and some moisture is lost due to contact with the slicing equipment. Methods such as heating in a convection oven provide accurate measure of average moisture content in the materials, but do not provide the moisture distribution across the food cross-section. Recently, non-destructive and non-invasive experimental methods such as nuclear magnetic resonance (NMR) imaging have emerged as promising techniques for obtaining moisture profiles in foods (Ruan & Chen, 1998). Non-invasive and non-destructive features allow the experiments to be conducted without destroying the structure or modifying the physical properties of materials. McCarthy and Kauten (1990) and McCarthy et al. (1994) /$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi: /j.jfoodeng

2 62 H. Xing et al. / Journal of Food Engineering 78 (2007) showed the NMR imaging picture of the cross-section of an extruded food sample. They applied the field gradient in X, Y and Z directions for a while and then turned the gradients off. This gives the ability to choose a region in the sample for recording the NMR signal. NMR has been used to obtain the moisture profiles in numerous food materials during drying (Duce & Hall, 1995; Hills & Babonneau, 1994b; Ishida, Ogawa, Koizumi, & Kano, 1997; Song & Litchfield, 1994; Tomer, Mantle, Gladden, & Newton, 1999). Verstreken, Hecke, and Scheerlinck (1998) and Schrader and Litchfield (1992) compared moisture profiles obtained using NMR to the profiles obtained using finite difference solution of a Fickian diffusion equation in a cylindrical food gel. NMR showed significantly higher moisture content around the center of the material as compared to the outer edge. The moisture content values around the center were greater than the predictions of FickÕs law. Verstreken et al. (1998) estimated the parameter of moisture transport in apples using NMR imaging. A multi-echo sequence to correct for transverse relaxation time (T 2 ) influences was applied to obtain the water concentration. They obtained the diffusivity of water in skin and flesh of apples. Thybo et al. (2004) predicted the sensory texture quality attributes of cooked potatoes by NMR imaging of raw potatoes in combination with different image analysis methods. They showed that NMR imaging not only mapped the moisture distribution, but also gave the information about the anatomic structures in raw potatoes. The purpose of our study was to use NMR imaging to study moisture profiles in pasta during drying. Hills and Babonneau (1994a) and Hills et al. (1997) studied the moisture transport during drying of extruded pasta with radial NMR imaging. Hills, Godward, and Wright (1997) developed and implemented an NMR pulse sequence used in a 300 MHz NMR machine to continuously image the moisture profiles (moisture content values at different radial locations) in a cylindrical pasta sample with the progress of drying. The limitation of their method was its inability to measure moisture profiles when the initial moisture content of pasta is less than 68%. 2 However, industry dries pasta with initial moisture content of about 40%. As detailed under materials and methods section, we solved this problem by adapting (Hills & Babonneau, 1994a) technique to allow measuring the moisture content from 50% or higher to about 10%. Previous NMR based experiments with pasta were conducted using continuous drying only. In continuous drying, airflow at a certain temperature and humidity is applied for some time. We compared the effect of both continuous and intermittent drying on moisture profiles in pasta. Some advantages of intermittent drying are energy savings, shorter effective drying time, high moisture removal rates, and fewer stress cracks (Chou, 2 All moisture content values are reported on a mass dry basis (d.b.). Chua, Mujumdar, Hawlader, & Ho, 2000). There are several ways of performing intermittent drying such as changing the air temperature, periodically applying the airflow, changing direction of airflow, etc (Chou et al., 2000). We performed intermittent drying by changing the air temperature between high and low values. The specific objectives of our study were: (1) To develop an NMR pulse sequence for measuring the proton signal for a wide range of pasta moisture contents. (2) To investigate the role of glass transition on Fickian and non-fickian modes of moisture transport in pasta. (3) To compare the effect of continuous and intermittent drying on moisture profiles in pasta. 2. Materials and methods Cylindrical pasta samples (spaghetti) were provided by a pasta manufacturing company in the Northwest. To ensure sample-to-sample uniformity in properties, the samples were collected during a single batch in the manufacturing process. The length and radius of a sample were 248 ± 5 mm and 1.7 ± 0.1 mm, respectively. The initial moisture content of samples was about 9.0% on dry basis. The samples were stored in polyethylene bags at room temperature before their use in experiments Conditioning of samples Before running the NMR experiments, pasta samples were conditioned at different moisture levels. First, we attempted the boiling method to obtain pasta samples with moisture content from 10% to 50%. The pasta samples were placed in a single layer in a container and boiled in water at an approximately constant temperature of 50 C. To obtain different moisture levels, the samples were taken out of the boiling water at different times. With this method, it was difficult to ensure sample-to-sample uniformity in moisture content values in samples taken out of the boiling water at the same time. Therefore, we decided to condition the samples using a temperature humidity chamber (Tenney TH Jr., Environmental Equipment Co., Los Angeles, CA) to obtain different moisture levels. The chamber was programmed to run at 30 C and varying relative humidity. Varying relative humidity allowed adding moisture to the samples without forming cracks (Kulkarni, 2005). An example of the temperature humidity profile for conditioning samples is shown in Fig. 1. To obtain different levels of moisture content, sets of 19 samples were taken out of the chamber at different time intervals. The resulting moisture content levels were 9.0%, 12.5%, 13.4%, 14.2%, 16.9%, 17.5%, 18.2% and 19.9%. Among the 19 samples, 10 were capped with NMR tubes for use in NMR experiments and nine were used for average moisture content determination using the vacuum oven

3 H. Xing et al. / Journal of Food Engineering 78 (2007) Fig. 1. Relative humidity (dashed line) and temperature (solid line) profiles used to condition pasta samples at different moisture levels. Temperature varied slightly around 30 C. method. The conditioned pasta samples were stored in the double zip-lock bags in a cold room to prevent moisture loss and also let the moisture inside pasta samples become uniform. Right before the NMR experiments, vacuum oven was used to measure the moisture content values. The conditioned samples were ground to small particles and weighed using an analytical balance. The vacuum oven was preheated to 103 C and the samples were placed in the oven for 5 h for drying (AOAC Method No ) NMR experiments Imaging experiments were performed using Varian Inova 500 MHz NMR machine (Varian Incorporated, Palo Alto, CA) with the magnetic field strength of T, available at the center for NMR Spectroscopy at the Washington State University. The safe operating temperature range for the NMR machines field gradient probe was 0 50 C. Therefore, we could not perform experiments at temperatures greater than 50 C. In modern pasta processing, drying is performed in the temperature range of C (Kill & Turnbull, 2001). We performed drying experiments at 22 and 40 C. The data obtained at these temperatures could still be used to validate our fluid transport modelõs predictions, and this model could be used to generate data at higher temperatures in future studies. The radial pulse sequence published by Hills et al. (1997) was adapted for obtaining the NMR signal. The adapted pulse sequence is shown in Fig. 2. A hard 90 pulse was delivered on the X-axis, which caused the magnetic moment aligned along the Z-axis to tip along the Y-axis. The magnetization along the Y-axis was then allowed to precess for a period of 5 ms, after which a weak pulsed field gradient was applied along the Z-axis. At the same time a soft 180 pulse was delivered along the X-axis. These two elements were applied simultaneously and the combination gave the ability to select a certain region of the whole pasta sample along the Z-axis for recording the signal. Then another field gradient in the X-axis was used to select the signal region along the X direction. To obtain a linear relation between signal intensity and moisture content (proton density), we needed to ensure that T R /T 1 > 5 and T E /T 2! 0 (Song, Litchfield, & Morrist, 1992). Here, T R is the recycle time, T E is the echo time and T 2 is the transverse relaxation time. In our experiments, T 2 was hard to measure because multiple echoes were needed. Since the pasta samples were dry with a relaxation time of about 2 ms, which was very short, the multiple echoes could not be obtained. Although, there is a way to measure the longitudinal relaxation time (T 1 ), we were not able to develop the technique to measure it. As discussed subsequently, we directly measured moisture content values by using the gravimetric method and related them to the signal intensity to verify whether a linear relation existed between the two. In comparison to the pulse sequence of Hills et al. (1997), our echo time (T E ) was shorter and the slice selected along the Z-axis was larger. This resulted in higher signal intensity. Our X and Y slice selections were about the same as of Hills et al. (1997) and our pulse sequence was slightly shorter Mounting samples in the NMR machine Dried nitrogen (0% humidity) with a flow rate of 10 L/s was used for drying pasta in the NMR machine. One 2 mm hole was made in the center of the 5 mm NMR tube cap to hold pasta (Fig. 3). Eight small holes were made around the center hole to let the drying nitrogen pass through. The pasta sample with known amount of average moisture content was fitted in the cap and placed in the tube and put Fig. 2. Radial imaging pulse used for NMR experiments.

4 64 H. Xing et al. / Journal of Food Engineering 78 (2007) Free Induction Decay (FID) obtained from NMR experiments was converted to signal intensity values using Fast Fourier Transform using MestRe-C software (Magnetic Resonance Companion, Santiago de Compostela, Spain). RLOWESS method of MATLAB (Mathworks Inc., Natick, MA, USA) was used to smoothen the signal profiles (Fig. 5). RLOWESS method was selected because it is resistant to outliers, which were commonly observed in the NMR data. This smoothing process is similar to the moving average method. Each smoothed value is determined by neighboring data points defined within a span. A regression weight function is defined for the data points contained within a span. A span of 15 data points was used for most of the NMR runs. In some experimental runs, many points clustered together at the peak. A span of 15 points could not clearly identify the averaged peak in these cases. Therefore, a span of five points was selected for these experimental runs. 3. Results and discussion 3.1. Signal versus moisture content relation Fig. 3. NMR tube with mounted pasta sample. into the 500 MHz NMR machine. Dried nitrogen at two temperatures of 22 C and 40 C was passed through the tube for continuous drying. First, five pasta samples at each level of moisture content were mapped for the initial moisture content at 22 C and 40 C. This helped to establish the calibration relation between NMR signal intensity and moisture content. Next, the highest moisture content pasta samples were tested for a long time (approximately 2.5 h) until the change in moisture content became negligible. During intermittent drying experiments, the nitrogen temperature was kept at 40 C for a certain period of time (such as 30 min, 45 min, and 60 min), and then lowered to 22 C for 5 min (Fig. 4). Transitions from high to low temperature or vice versa were made in 4 min. Fig. 4. Temperature profiles used for intermittent drying. Calibration was performed at both 22 C and 40 C to obtain the relationship between NMR signal intensity and moisture content. To obtain signal intensity, NMR calibration runs at each moisture content level were replicated five times using five different samples. Moisture content values in the vacuum oven had three replications at each moisture content level. Outliers were neglected. The center of the pasta sample has the highest moisture content, which exhibits the peak signal intensity (Fig. 5). The moisture content decreases towards outside. Figs. 6 and 7 show the calibration results for 40 C and 22 C data, respectively. In samples with known initial moisture content values between 9% and 20%, we obtained the relationship between these values and the proton signal intensity at 40 C and 22 C. The average moisture content values between 9% and 20% were measured using the vacuum oven method. Therefore, when the pasta sample was put in the NMR tube, the moisture content was assumed to be uniform throughout the sample. During the first few NMR scans, the center was assumed to be at the average level of moisture content. For 40 C calibration, Fig. 6 shows that the points with moisture content below 16.9% and signal intensity below also went off the trend and followed a different slope. For the 22 C calibration, Fig. 7 shows that the points with moisture content below 16.9% and signal intensity below went off the trend and followed a different slope. A linear regression equation was fitted to four points on the right. A straight line was passed through the first two points. Kulkarni (2005) used a Dynamic Mechanical Analyzer to measure the glass transition temperature for pasta samples. The results showed that glass transition occurs at 40 C when the moisture content is around 15%. In

5 H. Xing et al. / Journal of Food Engineering 78 (2007) Fig. 5. Calibration profile smoothened by the RLOWESS method implemented using Matlab. of water molecules or from different states or distribution of water at different moisture contents. It may have also resulted from glass transition or hindered movement of water molecules caused by surface forces. To further understand the reason for slope change, further experiments are needed at different temperatures Continuous drying results Fig. 6. Moisture content versus signal intensity at 40 C. Figs. 8 and 9 show the moisture content versus radial position for continuous drying at 40 C and 22 C, respectively. Since the spaghetti samples started drying right after being taken out of the zip-lock bag, the label 0 min refers to the first NMR scan performed after some uncontrolled drying. Data points were sliced at different drying times to obtain the final moisture distribution profiles in ASCII Fig. 7. Moisture content versus signal intensity at 22 C. Fig. 6, slope change occurs at about 16.9% moisture content, which is close to the 15% moisture content value obtained by Kulkarni (2005). It is possible that the slope change observed in Fig. 6 was caused by lower mobility Fig. 8. Moisture distribution for continuous drying at 40 C.

6 66 H. Xing et al. / Journal of Food Engineering 78 (2007) drying profiles lie in the glassy state near glass transition. The theory of Singh et al. (2003) predicts Fickian behaviors in glassy state when sufficiently far from glass transition. The figure shows more roundness in the profiles compared to the 40 C data (Fig. 8). This indicates that moisture transport approaches Fickian behavior in the glassy state Intermittent drying results Fig. 9. Moisture distribution for continuous drying at 22 C. format. The radial distance scale was changed to be the same for each slice and the final signal intensity profiles were obtained. The signal intensity values at 40 C and 22 C were converted to the moisture content values using the equations shown in calibration Figs. 6 and 7, respectively. Rheological data of Kulkarni (2005) showed that in pasta at 40 C glass transition initiates (change from glassy to transition state) at 15% moisture content. To see the effect of glass transition on slope of moisture content, a horizontal line is drawn at 15% moisture content in Fig. 8. The region below this line is in the glassy state and the region above the line is in the glass transition state. Notice that the moisture profiles in the glass transition region show sharp shapes. With progress of drying, as we move towards the glassy state, the profiles become relatively round. This is consistent with the predictions of Singh et al. (2003) equation that moisture transport does not follow FickÕs Law in the glass transition state. To further establish round shape of profiles in the glassy state, experiments for a longer period of time were needed. However, these experiments could not be conducted because drying progressed at a very slow rate in the glassy state. A sudden change in moisture profiles at 40 C above glass transition moisture content (15%) causes a sudden change in pastaõs mechanical properties. Pasta near the surface exists in a brittle glassy state. The pasta interior is in a glass transition state, where it is softer and easier to deform. The whole pasta matrix shrinks due to moisture loss, which causes strains inside the pasta. These strains, coupled with sudden change in pastaõs mechanical properties, would cause a clear contrast in stresses between inside and surface of the pasta. This may make pasta more prone to stresscracking. Therefore, in pasta undergoing glass transition near industrial moisture content of about 40% and above, the drying process needs to be optimized carefully. Fig. 9 shows the drying profiles obtained at 22 C. At 22.5 C pasta undergoes glass transition at 24% moisture content (Liu, Qi, & Hayakawa, 1997). Therefore, all the To conduct intermittent drying experiments, the temperature of the dried nitrogen passing through NMR machine was varied between 40 C and 22 C. To convert signal intensity values to moisture content, the calibration Figs. 6 and 7 were utilized using the method similar to the one used for continuous drying. Since, the calibration figures were measured at only two temperatures (40 and 22 C), only the NMR signals at high (40 C) and low (22 C) parts of intermittent temperature profiles (Fig. 4) were converted to the corresponding moisture values. NMR signals for the changing part of the intermittent temperature profile were not converted to the moisture values. Figs. 10 and 11 show the moisture profiles for the two intermittent drying conditions (remaining data not shown). Fig. 10 shows that at the beginning of drying up to 16 min, the profiles appear sharper and wider. It indicates non-fickian transport, which appears to have resulted from pasta existing in glass transition state above 15% moisture content. As drying progresses, the profiles changed to rounder and narrower shapes, which indicates Fickian transport in pasta existing in the glassy state. This trend is similar to continuous drying. In comparison to the continuous drying, intermittent drying Figs. 10 and 11 show higher moisture content towards the edges and lower moisture content near the center. This indicates that a wet layer was formed near the surface during intermittent drying. This was expected because of the following hypothesis the moisture started migrating towards the surface at 40 C drying temperature. Fig. 10. Moisture distribution for intermittent drying at 40 C for 30 min and 22 C for 5 min.

7 H. Xing et al. / Journal of Food Engineering 78 (2007) average moisture change near the center is summarized in Table 1. The table shows that during intermittent drying, although a resting period was provided by lowering the temperature to 22 C, pasta lost more moisture content than during continuous drying. Although, the percent change in moisture content during intermittent drying condition shown in the last column is the same as the continuous drying at 40 C, still the intermittent drying appears to be more effective because its initial moisture content was lower (0.122). Intermittent drying for 60 min at 40 C caused greater moisture loss than intermittent drying for 30 min at 22 C. Thus, the time step size and drying air conditions need to be carefully controlled to optimize drying with intermittent method. 4. Conclusions and implications Fig. 11. Moisture distribution for intermittent drying at 40 C for 60 min and 22 C for 5 min. After the external temperature is changed, moisture gradients inside pasta will take some time to change. When the outside temperature was changed from 40 to 22 C, the rate of drying near the surface reduced due to lowered diffusivity near the surface (diffusivity decreases with temperature). However, some of the moisture, which was moving towards the surface at 40 C, kept moving due to moisture gradients and accumulated near the surface. The wet surface caused a greater moisture differential between the surface and the drying nitrogen. Thus, pasta was expected to loose moisture at a faster rate during intermittent drying than during continuous drying. To compare moisture loss between continuous and intermittent drying, the data were sliced at 0 min and 117 min. To obtain average moisture content at 0 and 117 min, the respective moisture profiles were integrated per unit length of a sample using the following equation: R R 0 Mr dr AvgMC ¼ ð1þ R 2 =2 where M is the moisture content value at a given radial location, AvgMC is the average moisture content, r is the radial location and R is the radial position near surface where the outermost moisture value was recorded. The The technique of Hills et al. (1997) was successfully adopted by using a longer slice along the Z-axis, which allowed measuring moisture distribution in samples with initial moisture content from 10% to 50% or higher. This moisture content range covers the range used in the pasta processing industry. The calibration relationship between NMR signal intensity and moisture content in pasta was successfully established. The relation helped converting the signal intensity values to moisture content values during continuous and intermittent drying. A change in slope in the signal intensity versus moisture content curves indicated different state or distribution of water in pasta samples below 16.9% moisture content for both 22 C and 40 C data. This may also have been caused by glass transition or water moleculesõ close proximity to the pasta biopolymers at low moisture contents. The moisture content profiles during continuous drying experiments showed sharp shapes in the glass transition regime. This indicated that moisture transport did not follow FickÕs law near glass transition. This prediction was in agreement with the fluid transport theory of Singh et al. (2003) for biopolymers. With progress of drying at 40 C, the moisture profiles became more round, as pasta approached towards the glassy state, which indicated that drying behavior approached Fickian type of transport. This shows that FickÕs law commonly used in food and chemical engineering applications may not be accurate for modeling fluid transport near glass transition, and more sophisticated transport models need to be used. A sharp change in Table 1 Comparison of average moisture change near the center of pasta during continuous and intermittent drying Moisture content during continuous drying at 22 C Moisture content during continuous drying at 40 C Moisture content during intermittent drying at 40 C for 30 min and 22 C for 5 min Initial (at 0 min) After 117 min of drying Moisture change Percent change Moisture content during intermittent drying at 40 C for 60 min and 22 C for 5 min

8 68 H. Xing et al. / Journal of Food Engineering 78 (2007) pastaõs moisture content during drying near glass transition, causes a wide contrast in pastaõs mechanical properties, with the surface existing in a brittle glassy state and the center existing in a soft near glass transition state. This may make pasta more prone to stress cracking. Thus, drying of food materials undergoing glass transition needs to be optimized carefully to prevent crack formation. During intermittent drying a wet layer near the surface of pasta was clearly observed. In comparison, the surface layer remained dry during continuous drying. The wet layer near the surface caused greater amount of moisture loss during intermittent drying than continuous drying. In addition, since intermittent drying consumes less amount of energy than the continuous method, it may be a more efficient method for drying food materials. Intermittent drying with a step size of 60 min at high temperature (40 C) and 5 min at low temperature (22 C) appeared to be more efficient than drying with a step size of 30 min at high temperature and 5 min at low temperature. Thus, the time step size and drying air conditions need to be carefully controlled to optimize intermittent drying. Acknowledgements Thanks to University of Idaho Research Council and NSF-EPSCoR for financial support of this project. References Chou, S. K., Chua, K. J., Mujumdar, A. S., Hawlader, M. N. A., & Ho, J. C. (2000). On the intermittent drying of an agricultural product. Food and Bioproducts Processing, 78(C4), Duce, S. L., & Hall, L. D. (1995). Visualisation of the hydration of food by nuclear magnetic resonance imaging. Journal of Food Engineering, 26, Hills, B. P., & Babonneau, F. (1994a). Quantitative radial imaging of porous particles beds with varying water contents. Magnetic Resonance Imaging, 12(7), Hills, B. P., & Babonneau, F. (1994b). A quantitative study of water proton relaxation in packed beds of porous particles with varying water content. Magnetic Resonance Imaging, 12(6), Hills, B. P., Godward, J., & Wright, K. M. (1997). Fast radial NMR microimaging studies of pasta drying. Journal of Food Engineering, 33, Ishida, N., Ogawa, H., Koizumi, M., & Kano, H. (1997). Ontogenetic changes of the water status and accumulated soluble compounds in growing cherry fruits studied by NMR imaging. Magnetic Resonance in Chemistry, 35, S22 S28. Kill, K., & Turnbull, K. (2001). Pasta and semolina technology. Oxford, London: Blackwell Science. Kim, D., Caruthers, J. M., & Peppas, N. A. (1996). Experimental verification of a predictive model of penetrant transport in glassy polymers. Chemical Engineering Science, 51(21), Kulkarni, M. (2005). Determination of viscoelastic properties, glass transition behavior and sorption profiles of pasta as a function of temperature and moisture content. Ph.D. thesis, University of Idaho, Moscow, ID, USA. Liu, H., Qi, J., & Hayakawa, K. (1997). Rheological properties including tensile fracture stress of semolina extrudates influenced by moisture content. Journal of Food Science, 62, , 820. McCarthy, M., & Kauten, R. J. (1990). Magnetic resonance imaging applications in food research. Trends in Food Science and Technology, 1, McCarthy, M. J., Lasseux, D., & Maneval, J. (1994). NMR imaging in the study of diffusion of water in foods. Journal of Food Engineering, 22, Ruan, R. R., & Chen, P. L. (1998). Water in foods and biological materials. Boca Raton, FL, USA: CRC Press. Schrader, G. W., & Litchfield, J. B. (1992). Moisture profiles in a model food gel during drying: measurement using magnetic resonance imaging and evaluation of the fickian model. Drying Technology, 10(2), Singh, P., Cushman, J., & Maier, D. (2003). Multiscale fluid transport theory for swelling biopolymers. Chemical Engineering Science, 58, Song, H. P., & Litchfield, J. B. (1994). Measurement of stress cracking in maize kernels by magnetic resonance imaging. Journal of Agricultural Engineering Research, 57, Song, H. P., Litchfield, J. B., & Morrist, H. D. (1992). Three-dimensional microscopic MRI of maize kernels during drying. Journal of Agricultural Engineering Research, 53, Thybo, A. K., Szczypinski, P. M., Karlsson, A. H., Donstrup, S., Stodkilde-Jorgensen, H. S., & Andersen, H. J. (2004). Prediction of sensory texture quality attributes of cooked potatoes by NMRimaging (MRI) of raw potatoes in combination with different image analysis methods. Journal of Food Engineering, 61, Tomer, G., Mantle, M. D., Gladden, L. F., & Newton, J. M. (1999). Measuring water distribution in extrudates using magnetic resonance imaging (MRI). International Journal of Pharmaceuties, 189, Verstreken, E., Hecke, P. V., & Scheerlinck, N. (1998). Parameter estimation for moisture transport in apples with the aid of NMR imaging. Magnetic Resonance in Chemistry, 36,