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Ohmic processing: Electrical conductivities of pork cuts
MEAT SCIENCE Meat Science 67 (2004) 507–514 www.elsevier.com/locate/meatsci
Ohmic processing: Electrical conductivities of pork cuts N. Shirsat, J.G. Lyng *, N.P. Brunton, B. McKenna Department of Food Science, Faculty of Agriculture, University College Dublin, Belfield, Dublin 4, Ireland Received 6 May 2003; received in revised form 20 August 2003; accepted 5 December 2003
Abstract Efficacy of ohmic processing can be influenced by the conductivities of individual components within the food and their behaviour and interactions during the heating process. This study relates to the determination of electrical conductivities of a selection of pork meat cuts used in meat processing. Conductivity measurements of pork cuts indicated that lean is highly conductive compared to fat and addition of fat to lean reduced the overall conductivity but the addition of fat over the range (i.e. 0–100%) was non-linear. Light microscopy suggested that differences in the conductivities of leg and shoulder lean (entire) (0.76 vs. 0.64 S m1 , respectively) could be due to the denser muscle fibre structure and/or higher intra-muscular fat in shoulder vs. leg. This could be of significance for ohmic processing of full muscle products. Ó 2004 Elsevier Ltd. All rights reserved. Keywords: Ohmic processing; Pork meat cuts; Electrical conductivity
1. Introduction There is a renewed interest in ohmic heating with increasing consumer demands for a minimally processed range of safer, wholesome and nutritious convenience food products (Manvell, 1997). In addition, electrotechnologies for food processing are cleaner, more environmentally friendly and energy efficient than conventional methods currently in use. In a review of the application of electro-technologies Jamieson and Williamson (1999), postulated that ohmic, microwave (MW) and radio frequency (RF) are the most promising technologies for electro-heating on an industrial scale. Ohmic processing, sometimes described as resistive heating, consists of passing mains alternating current directly through a conductive food, which in turn leads to heat generation. Because heating accompanies the current, heat distribution throughout the product is far more rapid and even, which in turn can result in better flavour retention and particulate integrity compared to conventional processes (Skudder, 1993). Efficiency of
ohmic heating is dependent on the conductive nature of the food to be processed (Zoltai & Swearingen, 1996) and hence a knowledge of the conductivity of the food as a whole and its components is essential in designing a successful heating process. Methods for determining electric conductivity of substances by measuring the resistance to the flow of current have been described in various textbooks (Cummings & Torrance, 1992; Levitt, 1954; Ma, Davis, Obaldo, & Barbosa-Canovas, 1998). Mizrahi, Kopelman, and Perlman (1975) designed a cell to measure the conductivity of solid objects of varying geometry mostly for whole foods such as potato, corn on the cob and baby carrots. The conductivity was determined by repeatedly immersing the product in a salt solution until no change in the conductivity of the solution was detected and therefore the conductivity of the product was assumed to be the same as that of the solution. Mitchell and de Alwis (1989) designed a conductivity measurement cell based on the following equation: k¼S
l ; A
ð1Þ
*
Corresponding author. Tel.: +353-1-716-7710; fax: +353-1-7161149. E-mail address: [email protected] (J.G. Lyng). 0309-1740/$ - see front matter Ó 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.meatsci.2003.12.003
where k is the electrical conductivity (S m1 ), S the electrical conductance (S) and l and A are the length and
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cross-sectional area (m and m2 , respectively) of the sample. The authors postulated that determination of the cell constant by calibration was unnecessary for food solids and instead they used l=A as the resistive cell constant. According to Levitt (1954), a conductivity cell needs to be calibrated before it is possible to measure electrical conductance from measurements of cell resistance. By passing an electric current through a given cell, filled with a solution of known k, a resistance R ðXÞ, of the solution can be determined. Then the cell constant K is defined using the equation K ¼ k R:
ð2Þ
The conductivity of meat is a key factor for understanding how meat behaves during ohmic heating. Most processed meats can be broadly categorised into products manufactured from entire non-comminuted muscle (e.g. ham, gammon/bacon steak, picnic ham, etc.) or products manufactured from comminuted muscle (e.g. sausages, frankfurter, luncheon meat, etc.). A typical meat batter generally contains 70% minced meat with the balance generally made up of water, filler (such as flour, rusk, starch, etc.) and seasoning. However, different batters will have different percentages of nonmeat ingredients and lean to fat ratios of minced meat will also vary. There is very little information available on the influence of lean to fat ratio on the conductivity of meat. A variety of meat cuts such as lean trimmings from pork leg and shoulder, back fat, belly, etc. are used in the production of meat batters. The ratio of lean to fat depends on the level of trimming. Lean being the major constituent would be expected to have a greater overall influence on the conductive nature of the batter. Conductivities of beef (Kim, Kim, Park, Cho, & Han, 1996; Palaniappan & Sastry, 1991) and chicken (Mitchell & de Alwis, 1989) have been published but no reference is made to the type of meat cut, particle size or lean to fat ratio. Similar deficiencies were found in the published data on ohmic heating of beef and chicken (Palaniappan & Sastry, 1991) and also pork (Halden, de Alwis, & Fryer, 1990). The objective of the present work was to design a cell to measure the conductivities of minced and entire lean and fat components of meat individually and in combination. In addition, light microscopy (Drury & Wallington, 1967) examination of leg and shoulder lean was conducted in an attempt to explain differences in the conductivities of these components.
2. Materials and methods 2.1. Meat preparation Fresh pork cuts of leg (topside), shoulder (picnic), back fat and belly from three pigs were procured (within 72 h of slaughter) from a local meat processing
factory (Glanbia Fresh Pork Ltd., Edenderry, County Offaly, Ireland). The pork cuts were trimmed to separate lean from fat and sinews so as to ensure the conductivities of 100% visual lean and 100% visual fat from each cut could be determined. Cuts from each animal were kept separately and each animal was assigned as a batch. 2.2. Proximate analysis Samples of lean and fat for chemical analysis were prepared by mincing meat cuts through a 5 mm plate (Tritacarne, Model TS8E, Omas Food Machinery, 21040 Oggiona S. Stelano, Italy), followed by hand mixing and a final second mincing again through a 5 mm plate. Samples for analysis were stored in sealed plastic cups and refrigerated at 2 °C until required for analysis. Proximate analysis on all samples was carried out using Soderberg (1995) methods. Meat samples were also analysed for salt content (Fox, 1963). Analysis of variance (ANOVA) was used to determine significant composition differences between samples. 2.3. Measurement of conductivity in pork cuts Lean and fat meat cuts prepared in Section 2.1 were used for conductivity measurements. Entire pieces of lean and fat cuts (5 cm long and 2.7 cm diameter) were prepared using a specially designed tool (similar to a large cork borer). The entire specimen of lean cuts were prepared by sectioning, as far possible, in the direction of the muscle fibres to avoid any possible variation in the conductivity due to the orientation of fibres. In sectioning fat no such precautions were taken. Minced samples (5 mm) for conductivity measurements were prepared as described in Section 2.2. A range of samples, from 100% minced lean up to 100% minced fat were prepared by hand mixing thoroughly and then vacuum packing prior to their use for conductivity measurements. A conductivity cell (Fig. 1) was constructed from a polyvinyl chloride (PVC) pipe, 5 cm long and 2.65 cm (i.d.) diameter. Specially designed screw caps, fitted with high grade (316) stainless steel electrodes, were used to seal the ends of the tube. An opening was provided in the centre of the tube for the insertion of a thermocouple (Type T, TM Electronics, Worthing, UK). Temperature was recorded with a Digitron meter (Model No. 2751-K, Digitron Instrumentation Ltd., Mead Road, SG13 7AW Hertfordshire, UK). Voltage and current were monitored with a digital multimeter (Model No. UNI-T M3900, ALTAI, Manchester, UK). Variable power supply was derived from a 25 V transformer connected to Variac Duratrak (Model No. V6HPT, The Claude Lyons Group, Brook Road, Waltham Cross, Hertfordshire EN8 7LR, UK).
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Fig. 1. Circuit diagram for electrical conductivity measurement cell.
The conductivity cell constant was determined by LevittÕs method (1954) using 0.01, 0.05, 0.1, 0.2, 0.3 and 0.5 M KCl (Analar, BDH Chemicals Ltd., Poole, UK) solutions as the reference standards. The conductivity of each concentration of reference electrolyte was checked using a conductivity meter (Model No. WTW-LF 92, TetraCon 96, Wissenschftl, Techn.Werestatten 8120 Weilheim, Germany) to ensure that the measured conductivity values corresponded with published values (CRC, 1996). The calibration was validated using 0.02, 0.05 and 0.17 M solutions of NaCl (Merck KGaA, 64271 Darmstadt, Germany). For each sample three readings were taken. In the case of the meat pieces (entire) cylindrical pieces (50 g) were placed between the electrodes in the conductivity cell. Every effort was made to ensure that the pieces were positioned in such a way that the muscle fibres ran parallel to the electric field (i.e. longitudinally). This was done to avoid possible variation in the conductivity due to the orientation of muscle fibres as seen in liquid particulate systems, where particle orientation with respect to electrical field has been shown to have a significant effect on the conductivities of solids (De Alwis & Fryer, 1990; Sastry & Palaniappan, 1992). In contrast fat pieces, were randomly packed in the conductivity cell with no regard for fat cell orientation. When the conductivity cell was sealed with screw caps, the sample was compressed between the electrodes to expel any air within the cell through the opening provided for the temperature probe. Samples of minced portions of lean and fat were packed into the conductivity cell, tapping intermittently with a metal plunger to ensure no air pockets were formed. As before when the conductivity cell was sealed, any air along with excess sample was expelled through the opening provided for the temperature probe. All conductivity and ohmic heating experiments were carried out at 3.6 V cm1 and a frequency of 50 Hz with the product at 20 °C.
2.4. Light microscopy Samples of lean leg (topside) and shoulder (picnic) from four different pig carcases were taken within an hour of slaughter and immediately fixed in 10% buffered formalin solution (Disbrey & Rack, 1970) for 24 h. The tissues were routinely processed in a Shandon 2LE Tissue Processor (Shandon Southern Products Ltd., Astmoor, Runcorn Cheshire, UK). Blocks of tissue measuring approximately 15 mm 15 mm 5 mm were selected in such a way as to allow transverse and longitudinal sectioning of muscle fibres. The blocks were placed in labelled ‘‘Tissue-Tek’’ (Ames Division Miles laboratories Inc., P.O. Box 70, Elkhart, IN 46515, USA) processing cassette and then into a tissue processor (Drury & Wallington, 1967; Disbrey & Rack, 1970). At the end of the process, tissues were removed from the tissue processor and ‘‘blocked out’’ in fresh wax (BDH Poole, Dorset UK) in Tissue-Tek moulds with the labelled cassette bases attached to them. The wax blocks were allowed to solidify on a cold plate (Shandon Southern Products Ltd., Astmoor, Runcorn Cheshire, UK) prior to sectioning. The tissue blocks were mounted on a Leitz rotary microtome (Ernest Leitz, Wetzlar GMBH, Austria) and 5 lm thick sections were cut. These were floated onto the surface of a Paraffin Section Mounting Bath at 54 °C (Shandon Southern Products Ltd., Astmoor, Runcorn Cheshire, UK) to remove the compression effects of sectioning and mounted onto labelled glass slides. Sections were dried in an oven (MEDITE, Medizintachnik, 31303 Burgdorf, Wollenweberstre 12, Germany) overnight at 56 °C before staining. Sections were stained with haematoxylin and eosin (Drury & Wallington, 1967). Light microscopy (Model No. Labophot-2, Nikon, Japan) was used to examine transverse sections of leg and shoulder muscles for the transverse diameter of the muscle fibres and longitudinal sections for
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Table 1 Proximate analysis results for lean and fat pork cuts Meat type
Moisture (%)
Protein (%)
Fat (%)
Salt (%)
Ash (%)
Leg lean Shoulder lean Belly lean Back fat Belly fat
77.0a 76.5a 74.8b
22.0a 21.7c 21.5b
0.4c 0.9b 2.3a
0.2 0.2 0.2
0.4c 0.7b 1.2a
a;b
13.2b 32.3a
4.0b 6.6a
82.7a 60.7b
0.1b 0.4a
– –
Mean in the same column with unlike letters are different (P < 0:05).
and shoulder were significantly different (P < 0:01) but no significant difference (P P 0:05) was found in the moisture and salt contents. Lean belly had significantly lower moisture and higher fat and ash contents than the other lean components and was intermediate in protein content (P < 0:05). Back fat had significantly lower (P < 0:05) moisture, protein fat and ash contents than belly fat. The conductivity cell constructed for this work was calibrated using LevittÕs method (1954). The conductivities values for standard NaCl solutions measured by a conductivity meter and conductivity cell are presented in Table 2. Conductivity values, together with relative standard deviation (RSD) (%) for lean and fat cuts are presented in Table 3. RSD values for lean meat varied from 1.1% to 3.5% but for fat the variation was larger (i.e. 16–43%). The conductivity of the lean meats was considerably higher than fat. Conductivity of lean leg (entire) was significantly (P < 0:01) higher than shoulder but the conductivity values for the minced leg and shoulder were not significantly different from each other (P P 0:05). Conductivity of entire lean pieces of pork were lower than those of minced pork (Table 3) particularly in the case of shoulder and belly. The non-conductive nature of fat and its effect on the conductivity of lean minced muscle is illustrated in Fig. 2. RSD for electrical conductivity measurements at different lean to fat ratios varied from 2% to 13% being higher at the higher percentage of fat. Increasing fat content decreased the overall conductivity of the mixture. However, the relationship between fat content and conductivity appears to asymptotic rather than linear. As the percentage of fat in lean was reduced, the
intra-muscular fat and images were recorded using a digital video camera (Model No. 3-JCDKY-F55B, Victor company Ltd., Japan). Sites (10 in each specimen) were selected at random and measured for the area (lm2 ) of inter-muscular fat. ANOVA was used to assess whether significant differences existed between intermuscular fat content of leg and shoulder lean.
3. Results Overall average proximate analysis results for leg lean, shoulder lean, belly fat and back fat are presented in Table 1. Within each of the meats above ANOVA revealed no significant differences (P P 0:05) between the composition of the individual batches. ANOVA and subsequent Tukey pairwise comparison of the means did indicate that the protein, fat and ash values for pork leg Table 2 Conductivities of aqueous NaCl solutions measured at 20 °C using a conductivity meter and cell NaCl (mol l1 )
0.02 0.05 0.17
Conductivity (S m1 ) Publisheda
Measured TetraCon meterb
Measured manufactured cell
0.20 0.57 1.79
0.24 0.56 1.79
0.24 0.57 1.84
RSD (%)c
1.39 1.40 2.89
a
Data source: Palaniappan and Sastry (1991). Model No. WTW-LF 92, TetraCon 96, Wissenschftl, -Techn. Werestatten 8120 Weilheim, Germany. c RSD, relative standard deviation. b
Table 3 Conductivities of pork measured at 20 °C, 3.6 V cm1 and 50 Hz Pork cuts
Entire
Minced 1
Conductivity (S m ) Leg lean Shoulder lean Belly lean Back fat Belly fat a;b c
a
0.76 0.64b 0.68b 0.04 0.09
RSD (%)
Conductivity (S m1 )
RSD (%)
2.55 2.19 1.73
0.86 0.82 0.86
2.16 1.17 3.48
c
25.0 16.4
Mean in the same column with unlike letters are different (P < 0:05). RSD, relative standard deviation.
0.01 0.05
43.3 20.0
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511
0.9 0.8
Conductivity (S m-1)
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0
10
20 30 40 50 60 70 80 % Added Lean (Note: balance made up of added fat)
90
100
Fig. 2. Effect of added fat (0–100%) on the conductivity of a lean-fat blend.
conductivity of lean increased until the level of fat (<10%) had a limited effect on the conductivity of the mixture. The muscle structures of lean leg and shoulder in entire form were examined by light microscopy. Several transverse sections of leg and shoulder were stained with haematoxylin and eosin in order to evaluate the transverse diameter of muscle fibres (Fig. 3). The results appeared to suggest that the average diameters of myofibril bundles in the shoulder were almost half of that in the leg. Transverse tissue sections of leg and shoulder were also microscopically examined for intra-muscular fat (Fig. 4). ANOVA indicated that with respect to intra-
muscular fat content, there was no significant difference within a given leg or shoulder muscle but a significant difference was recorded (P < 0:05) between the shoulder and leg (Table 4).
4. Discussion Levitt (1954) maintained that the most accurate way of measuring the conductivity cell constant is by calibrating with standard KCl solution and not by dimensions (l=A). Calibration, of the conductivity cell manufactured in this work using LevittÕs method (1954), based on effective dimensions, gave a closer correlation between the con-
Fig. 3. Transverse sections of pork leg and shoulder showing muscle fibril bundles (a) leg (b) shoulder.
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Fig. 4. Transverse sections of pork leg and shoulder showing inter-muscular fat (a) leg (b) shoulder.
Table 4 Fat contents of lean pork leg and shoulder measured using light microscopy Meat cut
Fat content (lm2 )
Pork leg Pork shoulder
36.44a 64.61b
a;b Mean in the same column with unlike letters are different (P < 0:05).
ductivities values for standard NaCl solutions measured by conductivity meter and conductivity cell (Table 2). An electric current is carried either by electrons, as in metals and most semi-conductors (electronic) or by movement of ions (electrolytic) as in liquids (Levitt, 1954). All fresh foods, such as meat, fish, fruits and vegetables have sizeable amounts of water in them and any dissolved salts will make them electrically conductive. Higher conductivity values for lean meats relative to fat (Table 3) appeared to be due to the presence of higher level of moisture and salt compared to fat (Table 1). The conductivity differences observed between entire pieces of lean leg and lean shoulder (Table 3) are difficult to explain. Moisture and salt, the most important constituents with respect to conductivity are of similar magnitude in all three lean meat cuts and yet the conductivity values of leg (entire) are higher than shoulder (entire) (Table 3). In addition, whilst differences in protein, fat and ash are statistically significant (P < 0:01) between leg and shoulder cuts, in real terms (<0.5%) these differences are probably not large enough to influence the conductivity of the meat cuts (Table 1 and Fig. 2) as is also evident from the similar conductivity values for the two cuts in the minced form (Table 3). This suggests that the differences in conductivities of two cuts in entire form may be related to structural differences.
Whilst considerable work has been carried out on the effects of particle size, shape and orientation on the conductivity of solids in liquid–particulate mixture (De Alwis, Halden, & Fryer, 1989), the effect of structural differences within the meat itself remained unexplored. The present results indicate that, apart from proximate composition, the type of meat cut, i.e. pork leg or shoulder could have an additional effect on the conductivity of solids when processing meat pieces. Mincing disrupts the connective tissue and cellular structure in whole meat. The connective tissue network may act as an electrochemical pathway for the conduction of electrical current and its disruption may serve to reduce electrical conductivity. A possible explanation for the higher conductivity values in minced lean meat cuts compared to their entire form is that mincing also ruptures the myofibrillar cell tissue releasing moisture and inorganic constituents (e.g. Na, K, P, etc.) as shown in Table 3. In contrast, conductivities of minced fat were lower than those of whole fat. The reduction was probably not caused by air incorporation during mincing as every effort was made to eliminate air from the minced fat. Pork fat would be expected to have much lower levels of moisture and aside from Ca has lower levels of inorganic constituents than lean pork (Chan, Brown, Lee, & Buss, 1995). A possible explanation for the lower conductivity in minced fat could be that the small amount of electric current conducted through the connective tissue network (which may serve to conduct a small amount of current through the fat) in the fat is disrupted on mincing whilst relative to lean meat a much lower release of moisture and inorganic constituents occurs. The net result may lead to an overall reduction in the conductivity of minced fat relative to entire. However, further work would be required to verify these hypotheses.
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The poorly conductive nature of fat is known but its effects on the conductivity of lean have not been quantified. Addition of fat to lean (Fig. 2) could possibly affect the conductivity of the mixture in two ways. First, the reduction caused by the fat itself due to its poor conductivity and second, when fat is mixed with lean, it tends to coat the lean meat particles, thus creating a barrier for the passage of electric current. In either event the reduction in the conductivity of lean was not proportional to its fat content, particularly at the extreme end of composition ratios (i.e. lean:fat ¼ 90:10 and 10:90), Fig. 2. The conductivity differences between the leg and shoulder muscles could be due to differences in their structural density or connective tissue content and/or intra-muscular fat. Compared to leg, shoulder meat has been shown to have a higher content of connective tissue (Casey, Crossland, & Patterson, 1985) as well as intramuscular fat (Lawrie, 1991). The light microscopy results of transverse sections suggested a greater number of myofibrillar bundles per unit area in shoulder vs. leg (Fig. 3). Greater numbers of myofibrillar bundles per unit area suggest greater amounts of endomysial and perimysial connective tissue in shoulder than leg, which in turn could explain the findings of Casey et al. (1985). The light microscopy results of longitudinal sections of the two cuts also indicated a significantly higher (P < 0:05) intra-muscular fat content in shoulder compared to leg meat. This indicates that in the case of intact (entire) tissue the presence of a significantly higher quantity of fat (Table 2), even if the magnitude of the difference was of the order of 0.4%, could adversely affect the conductivity possibly due to its location. Similar results were obtained for the transverse tissue sections. Conductivity measurements of minced lean containing varying percentages of fat shows an adverse effect of fat content on the conductivity of minced lean (Fig. 2). Halden et al. (1990) have shown that when pork meat and fat were ohmically treated together the two solid materials heated at different rates as fat is less conductive than lean. However, these authors did not specify the fat content of the meat nor its anatomical location. Published conductivities values for chicken vary from 0.8 S m1 (Mitchell & de Alwis, 1989) to 0.37 S m1 (Palaniappan & Sastry, 1991). A possible explanation for this broad range of conductivities for chicken could be due to differences in their composition and/or the meat cut used. In addition, it is also evident from the present work that differences in electrical conductivity of meats can be related not only to proximate composition but can also be influenced by internal structure which in turn is determined by anatomical location. Reports of other structural influences such as particulate orientation have been well documented for liquid-particulate systems (De Alwis & Fryer, 1990; Sastry & Palaniappan, 1992). For smaller particles, (e.g. emulsions, colloids
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and other dispersions) such as those in the present study (which were less than 5 mm), the effect of orientation on the conductivity can be ignored but for larger particles (15–25 mm), orientation relative to the electrical field has a significant influence on electrical properties as well as the relative heating rates of the phases.
5. Conclusion Whilst the present study confirms the overall reducing nature of fat on the conductivity of lean muscle, it also appears that structural differences may influence the conductivity of muscle. Therefore in designing processes for ohmic heating of meat cuts the anatomical location of the cut may influence the efficacy of heating though further work is needed to verify this. In addition, whilst disruption of cellular structure by mincing lean whole meat increases its conductivity, the opposite effect was observed for entire and minced pork fat. A possible explanation for this is the release of greater amounts of moisture and ions in minced lean as compared to fat where the reduction may be due to disruption of its limited connective tissue network which may be the primary route for electrical conduction. However, further investigations are required to confirm this hypothesis.
Acknowledgements The authors are grateful to Eamon Fitzpatrick, (Veterinary Anatomy Department, University College Dublin, Belfield, Dublin 4, Ireland) for the assistance given with the histological part of this research.
References Casey, J. C., Crossland, A. R., & Patterson, R. L. S. (1985). Collagen content of meat carcasses of known history. Meat Science, 12, 189– 203. Chan, W., Brown, J., Lee, S. M., & Buss, D. H. (1995). Meat poultry and game supplement to McCance and WiddowsonÕs The Composition of Foods. Cambridge: Royal Society of Chemistry and Minister of Agriculture, Fisheries and Food. CRC (1996). In D. R. Lide (Ed.), Handbook of chemistry and physics (76th ed.). Cleveland, OH: The Chemical Rubber Company. Cummings, W. G., & Torrance, K. (1992). Chemical analysis – electrochemical techniques. In B. E. Noltingk (Ed.), JonesÕ instrument technology (part 2) (pp. 106–117). London: Butterworths. De Alwis, A. A. P., & Fryer, P. J. (1990). Mathematical modelling of the ohmic heating process. In R. W. Field & J. A. Howell (Eds.), Process engineering in the food industry (part 2: convenience foods and quality assurance) (pp. 45–58). Andover: Chapman & Hall. De Alwis, A. A. P., Halden, K., & Fryer, P. J. (1989). Shape and conductivity effects in the ohmic heating of foods. Chemical Engineering Research and Design, 67, 159–168.
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Disbrey, B. D., & Rack, J. H. (1970). Histological laboratory methods. Edinburgh: E & S Livingstone. Drury, R. A. B., & Wallington, E. A. (1967). CarletonÕs histological technique (4th ed.). Oxford: Oxford University Press. Fox, P. F. (1963). Potentiometric determination of salt in cheese. Journal of Dairy Science, 46, 744–745. Halden, A. A., de Alwis, A. A. P., & Fryer, P. J. (1990). Changes in the electrical conductivity of foods during ohmic heating. Journal Food Science and Technology, 25, 9–25. Jamieson, L., & Williamson, P. (1999). The potential of electrotechnologies for the processing of foods. Food Science and Technology Today, 13(2), 97–101. Kim, S. H., Kim, G. T., Park, J. Y., Cho, M. G., Han, B. H. (1996). A study on the ohmic heating of viscous food. Foods and Biotechnology, 5(4), 274–279. Lawrie, R. A. (1991). Chemical and biochemical constitution of muscles. In Meat science (5th ed., pp. 69–77). Oxford: Pergamon. Levitt, B. P. (1954). Conductivity of electrolytes. In FindlayÕs practical physical chemistry (pp. 238–241). Harlow: Longman. Ma, L., Davis, D. C., Obaldo, L. G., & Barbosa-Canovas, G. V. (1998). Electrical properties of biological products. In Engineering
properties of foods and other biological materials. A laboratory manual (pp. 163–179). St. Joseph, MI, USA: ASAE Publication. Manvell, C. (1997). Minimal processing of food. Food Science and Technology Today, 11(2), 107–111. Mitchell, F. R. G., & de Alwis, A. A. P. (1989). Electrical conductivity meter for food samples. Journal of Physics E, 554–556. Mizrahi, S., Kopelman, J., & Perlman, J. (1975). Blanching by electroconductive heating. Journal of Food Technology, 10, 281–288. Palaniappan, S., & Sastry, S. K. (1991). Electrical conductivities of selected foods during ohmic heating. Journal of Food Processing and Engineering, 14, 221–236. Sastry, S. K., & Palaniappan, S. (1992). Ohmic heating of liquid– particle mixtures. Food Technology, 46(12), 64–67. Skudder, P. J. (1993). New system for sterilization of particulate food products by ohmic heating. In H. Reuter (Ed.), Aseptic processing of foods (pp. 95–106). Soderberg, D. L. (1995). Meat and meat products. In P. Cunniff (Ed.), Official methods of analysis (16th ed.). Arlington, VA: Association of Official Analytical Chemists. Zoltai, P., & Swearingen, P. (1996). Product development considerations for ohmic processing. Food Technology, 50(5), 263–266.
Ohmic processing: Electrical conductivities of pork cuts N. Shirsat, J.G. Lyng *, N.P. Brunton, B. McKenna Department of Food Science, Faculty of Agriculture, University College Dublin, Belfield, Dublin 4, Ireland Received 6 May 2003; received in revised form 20 August 2003; accepted 5 December 2003
Abstract Efficacy of ohmic processing can be influenced by the conductivities of individual components within the food and their behaviour and interactions during the heating process. This study relates to the determination of electrical conductivities of a selection of pork meat cuts used in meat processing. Conductivity measurements of pork cuts indicated that lean is highly conductive compared to fat and addition of fat to lean reduced the overall conductivity but the addition of fat over the range (i.e. 0–100%) was non-linear. Light microscopy suggested that differences in the conductivities of leg and shoulder lean (entire) (0.76 vs. 0.64 S m1 , respectively) could be due to the denser muscle fibre structure and/or higher intra-muscular fat in shoulder vs. leg. This could be of significance for ohmic processing of full muscle products. Ó 2004 Elsevier Ltd. All rights reserved. Keywords: Ohmic processing; Pork meat cuts; Electrical conductivity
1. Introduction There is a renewed interest in ohmic heating with increasing consumer demands for a minimally processed range of safer, wholesome and nutritious convenience food products (Manvell, 1997). In addition, electrotechnologies for food processing are cleaner, more environmentally friendly and energy efficient than conventional methods currently in use. In a review of the application of electro-technologies Jamieson and Williamson (1999), postulated that ohmic, microwave (MW) and radio frequency (RF) are the most promising technologies for electro-heating on an industrial scale. Ohmic processing, sometimes described as resistive heating, consists of passing mains alternating current directly through a conductive food, which in turn leads to heat generation. Because heating accompanies the current, heat distribution throughout the product is far more rapid and even, which in turn can result in better flavour retention and particulate integrity compared to conventional processes (Skudder, 1993). Efficiency of
ohmic heating is dependent on the conductive nature of the food to be processed (Zoltai & Swearingen, 1996) and hence a knowledge of the conductivity of the food as a whole and its components is essential in designing a successful heating process. Methods for determining electric conductivity of substances by measuring the resistance to the flow of current have been described in various textbooks (Cummings & Torrance, 1992; Levitt, 1954; Ma, Davis, Obaldo, & Barbosa-Canovas, 1998). Mizrahi, Kopelman, and Perlman (1975) designed a cell to measure the conductivity of solid objects of varying geometry mostly for whole foods such as potato, corn on the cob and baby carrots. The conductivity was determined by repeatedly immersing the product in a salt solution until no change in the conductivity of the solution was detected and therefore the conductivity of the product was assumed to be the same as that of the solution. Mitchell and de Alwis (1989) designed a conductivity measurement cell based on the following equation: k¼S
l ; A
ð1Þ
*
Corresponding author. Tel.: +353-1-716-7710; fax: +353-1-7161149. E-mail address: [email protected] (J.G. Lyng). 0309-1740/$ - see front matter Ó 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.meatsci.2003.12.003
where k is the electrical conductivity (S m1 ), S the electrical conductance (S) and l and A are the length and
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cross-sectional area (m and m2 , respectively) of the sample. The authors postulated that determination of the cell constant by calibration was unnecessary for food solids and instead they used l=A as the resistive cell constant. According to Levitt (1954), a conductivity cell needs to be calibrated before it is possible to measure electrical conductance from measurements of cell resistance. By passing an electric current through a given cell, filled with a solution of known k, a resistance R ðXÞ, of the solution can be determined. Then the cell constant K is defined using the equation K ¼ k R:
ð2Þ
The conductivity of meat is a key factor for understanding how meat behaves during ohmic heating. Most processed meats can be broadly categorised into products manufactured from entire non-comminuted muscle (e.g. ham, gammon/bacon steak, picnic ham, etc.) or products manufactured from comminuted muscle (e.g. sausages, frankfurter, luncheon meat, etc.). A typical meat batter generally contains 70% minced meat with the balance generally made up of water, filler (such as flour, rusk, starch, etc.) and seasoning. However, different batters will have different percentages of nonmeat ingredients and lean to fat ratios of minced meat will also vary. There is very little information available on the influence of lean to fat ratio on the conductivity of meat. A variety of meat cuts such as lean trimmings from pork leg and shoulder, back fat, belly, etc. are used in the production of meat batters. The ratio of lean to fat depends on the level of trimming. Lean being the major constituent would be expected to have a greater overall influence on the conductive nature of the batter. Conductivities of beef (Kim, Kim, Park, Cho, & Han, 1996; Palaniappan & Sastry, 1991) and chicken (Mitchell & de Alwis, 1989) have been published but no reference is made to the type of meat cut, particle size or lean to fat ratio. Similar deficiencies were found in the published data on ohmic heating of beef and chicken (Palaniappan & Sastry, 1991) and also pork (Halden, de Alwis, & Fryer, 1990). The objective of the present work was to design a cell to measure the conductivities of minced and entire lean and fat components of meat individually and in combination. In addition, light microscopy (Drury & Wallington, 1967) examination of leg and shoulder lean was conducted in an attempt to explain differences in the conductivities of these components.
2. Materials and methods 2.1. Meat preparation Fresh pork cuts of leg (topside), shoulder (picnic), back fat and belly from three pigs were procured (within 72 h of slaughter) from a local meat processing
factory (Glanbia Fresh Pork Ltd., Edenderry, County Offaly, Ireland). The pork cuts were trimmed to separate lean from fat and sinews so as to ensure the conductivities of 100% visual lean and 100% visual fat from each cut could be determined. Cuts from each animal were kept separately and each animal was assigned as a batch. 2.2. Proximate analysis Samples of lean and fat for chemical analysis were prepared by mincing meat cuts through a 5 mm plate (Tritacarne, Model TS8E, Omas Food Machinery, 21040 Oggiona S. Stelano, Italy), followed by hand mixing and a final second mincing again through a 5 mm plate. Samples for analysis were stored in sealed plastic cups and refrigerated at 2 °C until required for analysis. Proximate analysis on all samples was carried out using Soderberg (1995) methods. Meat samples were also analysed for salt content (Fox, 1963). Analysis of variance (ANOVA) was used to determine significant composition differences between samples. 2.3. Measurement of conductivity in pork cuts Lean and fat meat cuts prepared in Section 2.1 were used for conductivity measurements. Entire pieces of lean and fat cuts (5 cm long and 2.7 cm diameter) were prepared using a specially designed tool (similar to a large cork borer). The entire specimen of lean cuts were prepared by sectioning, as far possible, in the direction of the muscle fibres to avoid any possible variation in the conductivity due to the orientation of fibres. In sectioning fat no such precautions were taken. Minced samples (5 mm) for conductivity measurements were prepared as described in Section 2.2. A range of samples, from 100% minced lean up to 100% minced fat were prepared by hand mixing thoroughly and then vacuum packing prior to their use for conductivity measurements. A conductivity cell (Fig. 1) was constructed from a polyvinyl chloride (PVC) pipe, 5 cm long and 2.65 cm (i.d.) diameter. Specially designed screw caps, fitted with high grade (316) stainless steel electrodes, were used to seal the ends of the tube. An opening was provided in the centre of the tube for the insertion of a thermocouple (Type T, TM Electronics, Worthing, UK). Temperature was recorded with a Digitron meter (Model No. 2751-K, Digitron Instrumentation Ltd., Mead Road, SG13 7AW Hertfordshire, UK). Voltage and current were monitored with a digital multimeter (Model No. UNI-T M3900, ALTAI, Manchester, UK). Variable power supply was derived from a 25 V transformer connected to Variac Duratrak (Model No. V6HPT, The Claude Lyons Group, Brook Road, Waltham Cross, Hertfordshire EN8 7LR, UK).
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Fig. 1. Circuit diagram for electrical conductivity measurement cell.
The conductivity cell constant was determined by LevittÕs method (1954) using 0.01, 0.05, 0.1, 0.2, 0.3 and 0.5 M KCl (Analar, BDH Chemicals Ltd., Poole, UK) solutions as the reference standards. The conductivity of each concentration of reference electrolyte was checked using a conductivity meter (Model No. WTW-LF 92, TetraCon 96, Wissenschftl, Techn.Werestatten 8120 Weilheim, Germany) to ensure that the measured conductivity values corresponded with published values (CRC, 1996). The calibration was validated using 0.02, 0.05 and 0.17 M solutions of NaCl (Merck KGaA, 64271 Darmstadt, Germany). For each sample three readings were taken. In the case of the meat pieces (entire) cylindrical pieces (50 g) were placed between the electrodes in the conductivity cell. Every effort was made to ensure that the pieces were positioned in such a way that the muscle fibres ran parallel to the electric field (i.e. longitudinally). This was done to avoid possible variation in the conductivity due to the orientation of muscle fibres as seen in liquid particulate systems, where particle orientation with respect to electrical field has been shown to have a significant effect on the conductivities of solids (De Alwis & Fryer, 1990; Sastry & Palaniappan, 1992). In contrast fat pieces, were randomly packed in the conductivity cell with no regard for fat cell orientation. When the conductivity cell was sealed with screw caps, the sample was compressed between the electrodes to expel any air within the cell through the opening provided for the temperature probe. Samples of minced portions of lean and fat were packed into the conductivity cell, tapping intermittently with a metal plunger to ensure no air pockets were formed. As before when the conductivity cell was sealed, any air along with excess sample was expelled through the opening provided for the temperature probe. All conductivity and ohmic heating experiments were carried out at 3.6 V cm1 and a frequency of 50 Hz with the product at 20 °C.
2.4. Light microscopy Samples of lean leg (topside) and shoulder (picnic) from four different pig carcases were taken within an hour of slaughter and immediately fixed in 10% buffered formalin solution (Disbrey & Rack, 1970) for 24 h. The tissues were routinely processed in a Shandon 2LE Tissue Processor (Shandon Southern Products Ltd., Astmoor, Runcorn Cheshire, UK). Blocks of tissue measuring approximately 15 mm 15 mm 5 mm were selected in such a way as to allow transverse and longitudinal sectioning of muscle fibres. The blocks were placed in labelled ‘‘Tissue-Tek’’ (Ames Division Miles laboratories Inc., P.O. Box 70, Elkhart, IN 46515, USA) processing cassette and then into a tissue processor (Drury & Wallington, 1967; Disbrey & Rack, 1970). At the end of the process, tissues were removed from the tissue processor and ‘‘blocked out’’ in fresh wax (BDH Poole, Dorset UK) in Tissue-Tek moulds with the labelled cassette bases attached to them. The wax blocks were allowed to solidify on a cold plate (Shandon Southern Products Ltd., Astmoor, Runcorn Cheshire, UK) prior to sectioning. The tissue blocks were mounted on a Leitz rotary microtome (Ernest Leitz, Wetzlar GMBH, Austria) and 5 lm thick sections were cut. These were floated onto the surface of a Paraffin Section Mounting Bath at 54 °C (Shandon Southern Products Ltd., Astmoor, Runcorn Cheshire, UK) to remove the compression effects of sectioning and mounted onto labelled glass slides. Sections were dried in an oven (MEDITE, Medizintachnik, 31303 Burgdorf, Wollenweberstre 12, Germany) overnight at 56 °C before staining. Sections were stained with haematoxylin and eosin (Drury & Wallington, 1967). Light microscopy (Model No. Labophot-2, Nikon, Japan) was used to examine transverse sections of leg and shoulder muscles for the transverse diameter of the muscle fibres and longitudinal sections for
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Table 1 Proximate analysis results for lean and fat pork cuts Meat type
Moisture (%)
Protein (%)
Fat (%)
Salt (%)
Ash (%)
Leg lean Shoulder lean Belly lean Back fat Belly fat
77.0a 76.5a 74.8b
22.0a 21.7c 21.5b
0.4c 0.9b 2.3a
0.2 0.2 0.2
0.4c 0.7b 1.2a
a;b
13.2b 32.3a
4.0b 6.6a
82.7a 60.7b
0.1b 0.4a
– –
Mean in the same column with unlike letters are different (P < 0:05).
and shoulder were significantly different (P < 0:01) but no significant difference (P P 0:05) was found in the moisture and salt contents. Lean belly had significantly lower moisture and higher fat and ash contents than the other lean components and was intermediate in protein content (P < 0:05). Back fat had significantly lower (P < 0:05) moisture, protein fat and ash contents than belly fat. The conductivity cell constructed for this work was calibrated using LevittÕs method (1954). The conductivities values for standard NaCl solutions measured by a conductivity meter and conductivity cell are presented in Table 2. Conductivity values, together with relative standard deviation (RSD) (%) for lean and fat cuts are presented in Table 3. RSD values for lean meat varied from 1.1% to 3.5% but for fat the variation was larger (i.e. 16–43%). The conductivity of the lean meats was considerably higher than fat. Conductivity of lean leg (entire) was significantly (P < 0:01) higher than shoulder but the conductivity values for the minced leg and shoulder were not significantly different from each other (P P 0:05). Conductivity of entire lean pieces of pork were lower than those of minced pork (Table 3) particularly in the case of shoulder and belly. The non-conductive nature of fat and its effect on the conductivity of lean minced muscle is illustrated in Fig. 2. RSD for electrical conductivity measurements at different lean to fat ratios varied from 2% to 13% being higher at the higher percentage of fat. Increasing fat content decreased the overall conductivity of the mixture. However, the relationship between fat content and conductivity appears to asymptotic rather than linear. As the percentage of fat in lean was reduced, the
intra-muscular fat and images were recorded using a digital video camera (Model No. 3-JCDKY-F55B, Victor company Ltd., Japan). Sites (10 in each specimen) were selected at random and measured for the area (lm2 ) of inter-muscular fat. ANOVA was used to assess whether significant differences existed between intermuscular fat content of leg and shoulder lean.
3. Results Overall average proximate analysis results for leg lean, shoulder lean, belly fat and back fat are presented in Table 1. Within each of the meats above ANOVA revealed no significant differences (P P 0:05) between the composition of the individual batches. ANOVA and subsequent Tukey pairwise comparison of the means did indicate that the protein, fat and ash values for pork leg Table 2 Conductivities of aqueous NaCl solutions measured at 20 °C using a conductivity meter and cell NaCl (mol l1 )
0.02 0.05 0.17
Conductivity (S m1 ) Publisheda
Measured TetraCon meterb
Measured manufactured cell
0.20 0.57 1.79
0.24 0.56 1.79
0.24 0.57 1.84
RSD (%)c
1.39 1.40 2.89
a
Data source: Palaniappan and Sastry (1991). Model No. WTW-LF 92, TetraCon 96, Wissenschftl, -Techn. Werestatten 8120 Weilheim, Germany. c RSD, relative standard deviation. b
Table 3 Conductivities of pork measured at 20 °C, 3.6 V cm1 and 50 Hz Pork cuts
Entire
Minced 1
Conductivity (S m ) Leg lean Shoulder lean Belly lean Back fat Belly fat a;b c
a
0.76 0.64b 0.68b 0.04 0.09
RSD (%)
Conductivity (S m1 )
RSD (%)
2.55 2.19 1.73
0.86 0.82 0.86
2.16 1.17 3.48
c
25.0 16.4
Mean in the same column with unlike letters are different (P < 0:05). RSD, relative standard deviation.
0.01 0.05
43.3 20.0
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0.9 0.8
Conductivity (S m-1)
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0
10
20 30 40 50 60 70 80 % Added Lean (Note: balance made up of added fat)
90
100
Fig. 2. Effect of added fat (0–100%) on the conductivity of a lean-fat blend.
conductivity of lean increased until the level of fat (<10%) had a limited effect on the conductivity of the mixture. The muscle structures of lean leg and shoulder in entire form were examined by light microscopy. Several transverse sections of leg and shoulder were stained with haematoxylin and eosin in order to evaluate the transverse diameter of muscle fibres (Fig. 3). The results appeared to suggest that the average diameters of myofibril bundles in the shoulder were almost half of that in the leg. Transverse tissue sections of leg and shoulder were also microscopically examined for intra-muscular fat (Fig. 4). ANOVA indicated that with respect to intra-
muscular fat content, there was no significant difference within a given leg or shoulder muscle but a significant difference was recorded (P < 0:05) between the shoulder and leg (Table 4).
4. Discussion Levitt (1954) maintained that the most accurate way of measuring the conductivity cell constant is by calibrating with standard KCl solution and not by dimensions (l=A). Calibration, of the conductivity cell manufactured in this work using LevittÕs method (1954), based on effective dimensions, gave a closer correlation between the con-
Fig. 3. Transverse sections of pork leg and shoulder showing muscle fibril bundles (a) leg (b) shoulder.
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Fig. 4. Transverse sections of pork leg and shoulder showing inter-muscular fat (a) leg (b) shoulder.
Table 4 Fat contents of lean pork leg and shoulder measured using light microscopy Meat cut
Fat content (lm2 )
Pork leg Pork shoulder
36.44a 64.61b
a;b Mean in the same column with unlike letters are different (P < 0:05).
ductivities values for standard NaCl solutions measured by conductivity meter and conductivity cell (Table 2). An electric current is carried either by electrons, as in metals and most semi-conductors (electronic) or by movement of ions (electrolytic) as in liquids (Levitt, 1954). All fresh foods, such as meat, fish, fruits and vegetables have sizeable amounts of water in them and any dissolved salts will make them electrically conductive. Higher conductivity values for lean meats relative to fat (Table 3) appeared to be due to the presence of higher level of moisture and salt compared to fat (Table 1). The conductivity differences observed between entire pieces of lean leg and lean shoulder (Table 3) are difficult to explain. Moisture and salt, the most important constituents with respect to conductivity are of similar magnitude in all three lean meat cuts and yet the conductivity values of leg (entire) are higher than shoulder (entire) (Table 3). In addition, whilst differences in protein, fat and ash are statistically significant (P < 0:01) between leg and shoulder cuts, in real terms (<0.5%) these differences are probably not large enough to influence the conductivity of the meat cuts (Table 1 and Fig. 2) as is also evident from the similar conductivity values for the two cuts in the minced form (Table 3). This suggests that the differences in conductivities of two cuts in entire form may be related to structural differences.
Whilst considerable work has been carried out on the effects of particle size, shape and orientation on the conductivity of solids in liquid–particulate mixture (De Alwis, Halden, & Fryer, 1989), the effect of structural differences within the meat itself remained unexplored. The present results indicate that, apart from proximate composition, the type of meat cut, i.e. pork leg or shoulder could have an additional effect on the conductivity of solids when processing meat pieces. Mincing disrupts the connective tissue and cellular structure in whole meat. The connective tissue network may act as an electrochemical pathway for the conduction of electrical current and its disruption may serve to reduce electrical conductivity. A possible explanation for the higher conductivity values in minced lean meat cuts compared to their entire form is that mincing also ruptures the myofibrillar cell tissue releasing moisture and inorganic constituents (e.g. Na, K, P, etc.) as shown in Table 3. In contrast, conductivities of minced fat were lower than those of whole fat. The reduction was probably not caused by air incorporation during mincing as every effort was made to eliminate air from the minced fat. Pork fat would be expected to have much lower levels of moisture and aside from Ca has lower levels of inorganic constituents than lean pork (Chan, Brown, Lee, & Buss, 1995). A possible explanation for the lower conductivity in minced fat could be that the small amount of electric current conducted through the connective tissue network (which may serve to conduct a small amount of current through the fat) in the fat is disrupted on mincing whilst relative to lean meat a much lower release of moisture and inorganic constituents occurs. The net result may lead to an overall reduction in the conductivity of minced fat relative to entire. However, further work would be required to verify these hypotheses.
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The poorly conductive nature of fat is known but its effects on the conductivity of lean have not been quantified. Addition of fat to lean (Fig. 2) could possibly affect the conductivity of the mixture in two ways. First, the reduction caused by the fat itself due to its poor conductivity and second, when fat is mixed with lean, it tends to coat the lean meat particles, thus creating a barrier for the passage of electric current. In either event the reduction in the conductivity of lean was not proportional to its fat content, particularly at the extreme end of composition ratios (i.e. lean:fat ¼ 90:10 and 10:90), Fig. 2. The conductivity differences between the leg and shoulder muscles could be due to differences in their structural density or connective tissue content and/or intra-muscular fat. Compared to leg, shoulder meat has been shown to have a higher content of connective tissue (Casey, Crossland, & Patterson, 1985) as well as intramuscular fat (Lawrie, 1991). The light microscopy results of transverse sections suggested a greater number of myofibrillar bundles per unit area in shoulder vs. leg (Fig. 3). Greater numbers of myofibrillar bundles per unit area suggest greater amounts of endomysial and perimysial connective tissue in shoulder than leg, which in turn could explain the findings of Casey et al. (1985). The light microscopy results of longitudinal sections of the two cuts also indicated a significantly higher (P < 0:05) intra-muscular fat content in shoulder compared to leg meat. This indicates that in the case of intact (entire) tissue the presence of a significantly higher quantity of fat (Table 2), even if the magnitude of the difference was of the order of 0.4%, could adversely affect the conductivity possibly due to its location. Similar results were obtained for the transverse tissue sections. Conductivity measurements of minced lean containing varying percentages of fat shows an adverse effect of fat content on the conductivity of minced lean (Fig. 2). Halden et al. (1990) have shown that when pork meat and fat were ohmically treated together the two solid materials heated at different rates as fat is less conductive than lean. However, these authors did not specify the fat content of the meat nor its anatomical location. Published conductivities values for chicken vary from 0.8 S m1 (Mitchell & de Alwis, 1989) to 0.37 S m1 (Palaniappan & Sastry, 1991). A possible explanation for this broad range of conductivities for chicken could be due to differences in their composition and/or the meat cut used. In addition, it is also evident from the present work that differences in electrical conductivity of meats can be related not only to proximate composition but can also be influenced by internal structure which in turn is determined by anatomical location. Reports of other structural influences such as particulate orientation have been well documented for liquid-particulate systems (De Alwis & Fryer, 1990; Sastry & Palaniappan, 1992). For smaller particles, (e.g. emulsions, colloids
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and other dispersions) such as those in the present study (which were less than 5 mm), the effect of orientation on the conductivity can be ignored but for larger particles (15–25 mm), orientation relative to the electrical field has a significant influence on electrical properties as well as the relative heating rates of the phases.
5. Conclusion Whilst the present study confirms the overall reducing nature of fat on the conductivity of lean muscle, it also appears that structural differences may influence the conductivity of muscle. Therefore in designing processes for ohmic heating of meat cuts the anatomical location of the cut may influence the efficacy of heating though further work is needed to verify this. In addition, whilst disruption of cellular structure by mincing lean whole meat increases its conductivity, the opposite effect was observed for entire and minced pork fat. A possible explanation for this is the release of greater amounts of moisture and ions in minced lean as compared to fat where the reduction may be due to disruption of its limited connective tissue network which may be the primary route for electrical conduction. However, further investigations are required to confirm this hypothesis.
Acknowledgements The authors are grateful to Eamon Fitzpatrick, (Veterinary Anatomy Department, University College Dublin, Belfield, Dublin 4, Ireland) for the assistance given with the histological part of this research.
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