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Predictions of some product parameters based on the processing conditions of ultra-high-temperature milk plants
International Dairy Journal 18 (2008) 939–944
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Predictions of some product parameters based on the processing conditions of ultra-high-temperature milk plants H. Tran a, N. Datta a, M.J. Lewis b, H.C. Deeth a, * a b
Dairy Industry Centre for UHT Processing, School of Land, Crop and Food Sciences, University of Queensland, St Lucia, Qld 4072, Australia School of Food Biosciences, The University of Reading, Whiteknights, Reading, UK
a r t i c l e i n f o
a b s t r a c t
Article history: Received 30 April 2007 Received in revised form 17 August 2007 Accepted 16 January 2008
The temperature–time profiles of 22 Australian industrial ultra-high-temperature (UHT) plants and 3 pilot plants, using both indirect and direct heating, were surveyed. From these data, the operating parameters of each plant, the chemical index C*, the bacteriological index B* and the predicted changes in the levels of b-lactoglobulin, a-lactalbumin, lactulose, furosine and browning were determined using a simulation program based on published formulae and reaction kinetics data. There was a wide spread of heating conditions used, some of which resulted in a large margin of bacteriological safety and high chemical indices. However, no conditions were severe enough to cause browning during processing. The data showed a clear distinction between the indirect and direct heating plants. They also indicated that degree of denaturation of a-lactalbumin varied over a wide range and may be a useful discriminatory index of heat treatment. Application of the program to pilot plants illustrated its value in determining processing conditions in these plants to simulate the conditions in industrial UHT plants. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction UHT (ultra-high-temperature) treatment of milk produces a commercially sterile product which normally has a shelf-life at room temperature of at least 6 months. However, UHT treatment causes chemical changes to the milk components that affect milk flavour, nutrients and physical stability. The high temperature reached in UHT processing is primarily responsible for the effect of the process on bacteria, including spores, while the length of time that the product is subjected to elevated temperatures determines the extent of chemical change (Lewis & Heppell, 2000). The temperatures and times used to describe a UHT process, e.g., 140 C for 4 s, relate to the temperature and time the product spends in the holding tube. They take no account of the conditions in the heating and cooling sections or the heating method employed, e.g., whether direct or indirect heating. These can have a major effect on the overall heat treatment and the heat-induced changes and quality of the product (Datta, Elliott, Perkins, & Deeth, 2002; Lewis & Heppell, 2000; Swartzel, 1982). In order to determine the total effect of the heat treatment on the processing parameters and product properties, Browning, Lewis, and MacDougall (2001) used a computer simulation program (Excel) based on kinetic data for a range of parameters and
* Corresponding author. Tel.: þ61 7 33469191; fax: þ61 7 33651177. E-mail address: [email protected] (H.C. Deeth). 0958-6946/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.idairyj.2008.01.006
chemical changes relating to UHT processing. Using the temperature–time profile of a UHT plant, the program enables the processing parameters for the plant to be computed and various properties of the processed product to be predicted. This paper discusses the application of this program to industrial UHT processing plants in Australia. 2. Materials and methods 2.1. Collection of data on ultra-high-temperature plants The following data were collected for 22 UHT plants (17 indirect and 5 direct) and 3 pilot plants (2 indirect and 1 direct) at 12 locations across Australia which were processing milk (whole, reduced-fat, skim and flavoured), custard and cream: flow rate of the plant; plant dimensions of the heating and cooling sections (number, length, type and diameter of shells/tubes for tubular systems, and number of plates, hold-up volume of plates, and plate surface details for plate systems) and holding stages (length and internal diameter of holding tube); temperatures (inlet and outlet temperatures at each tube or stage); and, for direct heating plants, details of the injector or infusion chamber and vacuum chamber. Lengths of tubes, where accessible, were physically measured using a measuring tape. Lengths of obscured tubes, internal diameters of tubes and other dimensions that could not be physically measured were obtained from plant manufacturer specification data.
H. Tran et al. / International Dairy Journal 18 (2008) 939–944
Temperatures were taken from plant instrumentation where available. Other temperatures were measured on the outside surface of the tubes using a T-type thermocouple clamped to the tube by a specially fabricated wraparound heat-resistant sleeve. In order to estimate the temperature of the product within the tube from these external surface measurements, surface temperatures were taken as close as possible to several points where the product temperature was available through the installed instrumentation. The surface temperatures were then adjusted to provide estimates of the internal temperature. The difference between the surface and internal temperatures was typically 3.5 C.
160
Temperature (Deg. C)
940
140 120 100 80 60 40 20 0
0
50
100
150
2.2. Inputs into calculations
2.2.2. Equations for processing parameters B*, representing the bacteriological effect relative to a reference temperature of 135 C, was calculated from the equation B* ¼ !10((T135)/10.5) dt/10.1. A process with a B* ¼ 1 would produce a 9-log cycle reduction of thermophilic spores assuming a z-value of 10.5 C and would be equivalent to 10.1 s at 135 C (Kessler, 1981). B*(adjusted) is the B* relative to the fastest particle (e.g., bacterial spore) transiting a section or the whole process. The calculated B* was adjusted for the effect of Reynolds number, which indicates the nature of the flow or the mean residence time distribution. If the flow is turbulent (i.e., Reynolds number > 4100) the velocity of the fastest particle is considered to be 1.2 mean particle velocity (Kessler, 1981; Lewis & Heppell, 2000) so that the B*(adjusted) is B*/1.2. The dynamic viscosities used to calculate Reynolds numbers were based on reported equations for milks and creams between 70 and 135 C (Bertsch & Cerf, 1983). C*, representing the chemical effect relevant to a reference temperature of
Temperature (Deg. C)
160 140 120 100 80 60 40 20 0
50
100
250
300
350
400
450
Time (s)
2.2.1. Temperature–time profiles From the data collected from each UHT plant, residence times, velocities and total volumes of tubes in each section, as well as the total residence time and total volume of tubes for the entire plant, were calculated. From these, the temperature–time profiles for the indirect and direct UHT plants were plotted as illustrated in Figs. 1 and 2, respectively. All data points shown represent measured or calculated data. The profile between adjacent points was assumed to be linear. For the direct plants, the time taken for the temperature to be raised from that of the product at the start of the heating section to the beginning of the holding tube was assumed to be 0.5 s (Burton, 1988). Similarly, the time taken to cool the product in the vacuum chamber was assumed to be 0.5 s. The average time a product spends in the vacuum chamber is shown as a holding time at the outlet temperature.
0
200
150
200
250
300
350
Time (s) Fig. 1. Selected temperature–time profiles of industrial indirect UHT plants surveyed Different symbols represent different UHT plants.
Fig. 2. Selected temperature–time profiles of industrial direct UHT plants surveyed Different symbols represent different UHT plants.
135 C, was calculated from the equation C* ¼ !10((T135)/31.4) dt/ 30.5. A process with a C* ¼ 1 would reduce the concentration of thiamine by 3% assuming a z-value of 31.4 C and would be equivalent to 30.5 s at 135 C (Kessler, 1981). 2.2.3. Kinetic data of heat-induced changes The predicted changes in milk components during heat treatment were kinetically modeled using reported values of reaction rate (k), activation energy (Ea) and reaction order (n) of the reactions, and, in cases where n > 1, the initial concentration of the milk component. Kinetic data used for browning were those reported by Lewis and Heppell (2000), thiamine and lysine loss by Kessler and Fink (1986), denaturation of b-lactoglobulin by Dannenberg and Kessler (1988) and Lyster (1970), denaturation of alactalbumin by Lyster (1970), furosine by Claeys, Ludikhuyze, and Hendrickx (2001), and lactulose formation by Rombaut, Dewettinck, De Mangelaere, and Huyghebaert (2002). 2.3. Calculation of results for ultra-high-temperature plants The data and equations given above were used to calculate the process parameters and chemical changes occurring in each section of the UHT plants using an Excel program based on the one published by Browning et al. (2001). The results were integrated using the trapezoidal rule (Bloch, 2000). 3. Results and discussion An example of the data calculated for an indirect plant is shown in Table 1. Similar data were obtained for direct plants except the times of heating to and cooling from the highest temperature were very short. Table 1 shows the contribution of the different sections of the plants to the various parameters. In particular, the contributions of the holding tube to the overall results varied considerably between the different plants, although the difference was greatest between the indirect and direct plants. However, it should be noted that the figures for b-lactoglobulin (b-lg) and a-lactalbumin (a-la) are cumulative, whereas the others are for individual sections and are additive for the total system. The calculated data for all industrial plants surveyed are summarized in Table 2 while the temperature–time profiles for some of the indirect and direct plants are shown in Figs. 1 and 2, respectively. These profiles show that a wide range of temperatures and times are used commercially and clearly demonstrate the value of a program such as the one used in this work to transform these different profiles into easily comparable total process parameters and estimates of effects on product components.
H. Tran et al. / International Dairy Journal 18 (2008) 939–944
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Table 1 Example of data calculated by the model program for an industrial UHT plant (indirect) Stage in process
Pre-heating Intermediate heating 1 Intermediate holding Intermediate heating 2 Final heating High-temperature holding First cooling Homo Final cooling
Temp ( C) In
Out
4 65 95 95 127 140 140 90 94
65 95 95 127 140 140 90 94 20
Time (s) 51.5 20.6 62.5 26.3 20.6 4.3 41.2 9.0 51.5
Totald
227
B*
B* (adjusted)
C*
0 0 0 0.06 2.02 1.26 1.12 0 0
0 0 0 0.05 1.68 1.05 0.93 0 0
4.46
3.71
b-lg Denaturationa (%)
b-lg Denaturationb (%)
0 0.01 0.11 0.19 0.63 0.20 0.52 0.06 0.02
0 43 95 98 99 99 100 100 100
0 20 78 87 93 93 95 96 96
1.74
100
96
a-la
Total browning (s)c
Lactulose (mg 100 g1)
Furosine (mg 100 g protein1)
14 28 52 58 72 74 74
0.1 0.8 6.4 15.2 66.0 22.9 50.3 3.3 0.8
0 o 0.5 2.1 11.6 4.2 7.9 0.2 0
0 0.7 5.0 14.4 43.2 49.0 74 77 77
74
165.8
26.5
77
Denaturationb (%) 0
a
According to Dannenberg and Kessler (1988). b According to Lyster (1970). c Expressed as an equivalent time (s) at 121 C. d Whey protein denaturation data are cumulative whereas other data are additive. B* ¼ the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. B* (adjusted) ¼ B* adjusted for the fastest particle based on Reynolds number. C* ¼ the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine.
3.1. Bacteriological (B*) and chemical (C*) indices The adjusted B* values of the industrial plants, i.e., adjusted for flow characteristics based on Reynolds number, ranged from 1.6 to 16.5 for indirect plants and 1.7 to 11.8 for direct plants. All plants had Reynolds numbers > 4100 indicating turbulent flow; therefore, the adjustment factor used was 1.2, i.e., B* ¼ 1.2 B*(adjusted). According to the rule of thumb for UHT processing that B* should be greater than 1 (to ensure a 9-log reduction in thermophilic spores) (Kessler, 1981), all the UHT plants surveyed met this criterion, with some operating at excessively high B*. Operating at a B* value much higher than 1 provides a safety margin and may be useful for
destroying highly heat-resistant spores but in most cases is unlikely to have a significant effect on the microbiological quality. Because of the different kinetics for bacterial inactivation and chemical changes, a very high B* value does not necessarily indicate excessive chemical changes (e.g., cooked flavour production) in the product; this is accounted for by the C* value. This point is particularly relevant to direct heating, where B* is high and C* is relatively low. The C* values ranged from 0.9 to 3.0 for indirect plants and 0.4 to 1.5 for direct plants. Plants should operate at a C* < 1 (where C* ¼ 1 is equivalent to a 3% loss of thiamine) because a C* value much higher than 1 is indicative of excessive chemical change which may result in off-flavour production, excessive nutrient loss and, in
Table 2 Whole process data calculated by the model program for 22 industrial UHT plants Plant no.
Highest temperature ( C)
Holding time (s)
Overall process B (adj)
C
Indirect UHT plants 1 144 2 144 3 144 4 138 5 140 6 142 7 139 8 139 9 137 10 144 11 142 12 142 13 137 14 137 15 138 16 138 17 145
5 8 19 2 4 4 6 5 16 6 5 8 9 12.5 10 25 2.5
8.7 10.1 16.5 1.6 3.7 4.8 2. 6 2.9 4.4 6. 7 8.2 8.2 1.6 2.1 3.1 4.8 4.6
Direct UHT plants 18 146 19 143 20 143 21 143 22 145
6 2 10 4 13
4.1 1.7 5.6 2.7 11.8
a
*
*
Holding tube *
*
b-lg
a-la
Denaturationa,b (%)
Denaturationb (%)
Total browning (s)c
Lactulose (mg 100 g1)
Furosine (mg 100 g protein1)
B (adj)
C
1.9 2.1 2.8 1.0 1.7 1.5 1.3 1.5 2.8 1.6 3.0 3.0 0.9 1.1 1.8 1.6 0.9
3.0 4.4 10.8 0.3 1.1 1. 7 1.2 1. 2 2.0 3.3 1.9 2.3 1.1 1.5 1.4 4.0 1.9
0.3 0.5 1.2 0.1 0.2 0.2 0.3 0.2 0.6 0.4 0.3 0.4 0.3 0.5 0.4 1.0 0.2
100/94 100/95 100/96 99/92 100/96 100/96 99/94 100/95 100/97 100/95 100/97 100/97 99/91 99/92 100/95 99/94 99/96
72 74 82 51 74 75 59 69 90 67 89 89 35 56 75 68 25
206 225 308 90 166 192 121 146 288 169 299 305 85 105 168 170 100
36 39 55 14 26 32 20 23 46 29 50 51 14 17 27 29 17
82 86 104 43 77 83 54 67 120 64 104 107 32 40 63 51 40
0.5 0.4 0.8 0.5 1.5
4.1 1.2 4.8 1.9 9.7
0.4 1.0 0.6 0.2 0.9
89/74 92/78 97/87 95/81 99/92
27 22 40 27 58
51 39 95 53 170
9 6 17 9 30
14 15 28 18 50
According to Dannenberg and Kessler (1988). According to Lyster (1970). c Expressed as an equivalent time (s) at 121 C. B* ¼ the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. C* ¼ the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine. B* (adj) ¼ B* adjusted for the fastest particle based on Reynolds number. b
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H. Tran et al. / International Dairy Journal 18 (2008) 939–944
extreme cases, colour change (browning). The above data suggest that the heat intensity in some plants, especially some indirect plants, may be too high. This could be reduced by a slight reduction in the UHT processing temperature, which would decrease both the B* and C* values; microbial quality should not be compromised, provided B* was still well above 1.0, and chemical quality should be improved. However, age gelation is delayed in milk with a high C* value, as indigenous plasmin and bacterial proteases are inactivated to a greater extent (Datta & Deeth, 2001). In indirect plants, the effect of the cooling stage on C* is generally not as important as the effect of the heating stage because, in the cooling stage, the product temperature generally falls rapidly, while the rise in temperature in the heating stage is usually slower (Fig. 1). The contribution of the holding tube in the industrial plants to the overall B* and C* values is also shown in Table 3. These show the very high contribution of the holding tube in the direct plants and a lower contribution in the indirect plants, with the difference being greatest for the B* values. This illustrates how misleading it is to quote nominal temperature–time combinations as indicators of the bacteriological and chemical effects of a UHT plant. 3.2. Chemical heat indices The chemical heat index data are summarized in Table 2. The data for b-lg demonstrate the higher degree of denaturation in indirect than in direct plants (Table 4), which has been reported by many authors and accords with the experimental data on milks for Australian plants (Elliott, Datta, Amenu, & Deeth, 2005). Denaturation of b-lactoglobulin was very high for indirect plants and is not a good indicator to discriminate between plants. However, it does discriminate between direct and indirect plants. Two values were calculated for denaturation of b-lg: one using the kinetic parameters of Dannenberg and Kessler (1988) and the other the parameters reported by Lyster (1970). The calculated values are somewhat different and reflect the different methods used to by the authors – immunodiffusion (Lyster, 1970) and acid precipitation (Dannenberg & Kessler, 1988). The data for a-la denaturation show higher levels of denaturation for indirect plants than direct plants (Table 4) and agree well with the experimental data of Elliott et al. (2005). These data show a much greater spread than the b-lg data, suggesting that a-la may be a good universal chemical heat index. The conditions used in the indirect plants result in almost complete denaturation of b-lg but cause a range of levels of denaturation of a-la, from 25 to 90%. The commonly accepted chemical index for UHT milk, C*, relates to
Table 3 Percentage contribution of the holding tube to B* and C* in industrial indirect and direct UHT plantsa % Contribution B* C* of the holding tube No. of indirect No. of direct No. of indirect No. of direct plants (n ¼ 17) plants (n ¼ 5) plants (n ¼ 17) plants (n ¼ 5) 0–<10 10–<20 20–<30 30–<40 40–<50 50–<60 60–<70 70–<80 80–<90 90–100
0 0 3 3 5 2 2 1 1 0
0 0 0 0 0 0 1 0 3 1
2 6 5 1 2 0 1 0 0 0
0 0 0 1 1 0 1 1 1 0
a B* is the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. C* is the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine.
Table 4 Predicted percentage denaturation of b-lactoglobulin and a-lactalbumin, and levels of lactulose and furosine, in milk from commercial UHT plants No. of indirect plantse
No. of direct plantse
% Denaturation of b-lactoglobulina 74–76 77–79 80–82 83–85 86–88 89–91 92–94 95–97 98–100
0 0 0 0 0 0 0 0 17
1 1 0 1 1 1 0 0 0
% Denaturation of a-lactalbuminb <20 20–<30 30–<40 40–<50 50–<60 60–<70 70–<80 80–<90 90–100
0 1 1 1 3 2 5 3 1
0 3 0 1 1 1 0 0 0
Lactulose (mg 100 g1)c 0–<10 10–<20 20–<30 30–<40 40–<50 50–<60
0 4 6 3 1 3
3 1 0 1 0 0
Furosine (mg 100 g protein1)d 0–<30 30–<60 60–<90 90–<120
0 6 7 4
4 1 0 0
a b c d e
Based on the reaction kinetics parameters of Dannenberg and Kessler (1988). Lyster (1970). Rombaut et al. (2002). Claeys et al. (2001). Total number of indirect plants ¼ 17 and direct plants ¼ 5.
destruction of thiamine; however, thiamine is seldom measured. By contrast, (undenatured) a-la is measured in many laboratories and could be used as a convenient index of UHT heat treatment. Lactulose and furosine are other commonly used chemical indices of heat-induced changes in milk. The calculated data for these compounds are shown in Table 2 and summarized in Table 4. Lactulose levels in Australian UHT milk have been reported to range from 12.1 to 24.4 mg 100 g1 (direct UHT process) and from 45.4 to 53.1 mg 100 g1 (indirect UHT process) (Elliott et al., 2005). The results calculated from the model program on the industrial plants are in agreement with this range. They are all lower than the limit of 60 mg 100 g1 for UHT milk in European regulations. A browning value above w400 (corresponding to milk heated at 121 C for 400 s) has been given as the threshold for colour detection in unmodified milks (Browning et al., 2001; Fink & Kessler, 1988). From the values in Table 2, none of the conditions being used in the plants surveyed is likely to produce milk with a noticeably brown colour. Given that some plants were operating at quite high heat intensity, it is apparent that extreme conditions are required to cause discoloration. However, there is evidence that the higher the browning index, the more susceptible milk is to further browning during storage, especially at >30 C (Wirjantoro, Lewis, Grandison, Williams, & Delves-Broughton, 2001).
H. Tran et al. / International Dairy Journal 18 (2008) 939–944
3.3. Pilot plant data and relevance to industrial plants In principle, this procedure for determining process and product parameters from temperature–time profiles is applicable to pilot plants as well as commercial plants. Data are shown in Table 5 for a 100 L h1 APV pilot plant, in both direct and indirect modes, and a 10 L h1 bench-top plant, similar to that reported by Wadsworth and Bassette (1985), when operating under various heating conditions. These data demonstrate how the type of analysis discussed in this paper can be used to tailor pilot plants to operate at specified B* and/or C* values corresponding to those for given configurations of full-scale plants. In this way, trial products can be given very similar heat treatment in the small-scale plants to those in the fullscale plants. This is not possible by using the same nominal (holding tube) temperature–time combinations. This approach also highlights the different flow characteristics of pilot-scale equipment relative to commercial plants. The calculated Reynolds numbers, particularly in the holding tube, which usually has a greater diameter than the heating and cooling tubes in commercial plants, are much lower in the small-scale plants, indicating largely laminar flow. In this work, the flow in the holding tubes of the 100 L h1 pilot plant was turbulent (Re ¼ 5360) but in the pre-heat and cooling tubes was laminar (Re ¼ 630). In the miniUHT plant operating at 10 L h1, the corresponding Reynolds numbers were 1270 and 150, indicating laminar flow in both sections. Hence, the residence time distributions are greater in the small plants than in the large commercial plants. This is more significant for microbiological parameters than chemical parameters, which supports the use of the adjusted B* values calculated in this work. For the laminar flow sections of the pilot plants, the B* values were adjusted by a factor of 2, i.e., B* ¼ 2 B*(adjusted). 3.4. Limitations of the calculated data While every effort was made to ensure the accuracy of the data, the following factors placed limitations on the results obtained. The data obtained for some plants were incomplete because of either limited access to the heating sections or lack of information
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about hold-up volumes (e.g., in plate heat exchangers and vacuum flash vessels). Also time of heating and cooling in direct plants is largely unknown although it is generally considered to be 0.5 s both to heat from 75 to 140 C and to flash cool from 140 to 75 C (Burton, 1988). In some indirect tubular plants, temperature data could be obtained at several points along the heat exchanger. This enabled convex heating curves to be plotted rather than straight lines between the lowest and highest temperatures, giving more accurate information. By contrast, limited temperature measurements were possible in some plants and straight lines only could be drawn between consecutive data points. The calculated chemical changes are based on published kinetic data for whole milk and hence the data calculated for reduced-fat milk, flavoured milk, cream and custard may not be accurate. For example, Reynolds numbers were based on milk and hence are not accurate for other products, particularly viscous products such as cream and custard, as Reynolds number is inversely proportional to viscosity. Furthermore, full account has not been taken of the variation in viscosity with temperature. Values for B* were adjusted for the flow characteristics of the plants, as shown by the Reynolds numbers, so they apply to the fastest particle. The adjusted values provide the most accurate indication of the minimum bactericidal treatment by the plant; however, they underestimate the bactericidal effect on most bacterial cells in the product. The published reaction kinetic data also vary because of the different methodology and analytical methods used to obtain the data. An example of this is the different kinetic data reported for denaturation of b-lactoglobulin by Dannenberg and Kessler (1988) and Lyster (1970). Furthermore, the whey protein denaturation calculations (which are based on reaction orders >1 and hence require the initial concentration to be known to produce accurate data) assume the same initial level of these proteins in the different products from the different factories, which is unlikely to be true; however, further refinement of these data was not possible. In addition, some changes such as the Maillard browning reaction and lactulose formation are pH-dependent and the kinetic models used do not take this into account. Thus if the pH of milk is
Table 5 Whole process data calculated by the model program for three pilot plants
a-la Denaturationb (%)
Total browning (s)c
Lactulose (mg 100 g1)
Furosine (mg 100 g protein1)
UHT tubular pilot plant (100 L h1) with pre-heat holding at 90 C for 31 s 135 4.2 1.2 1.1 0.4 0.1 99/94 139 4.2 2.6 1.3 0.8 0.2 100/94 140 4.2 3.2 1.4 1.1 0.2 100/95 142 4.2 4.9 1.6 1.6 0.2 100/95 144 4.2 7.4 1.8 2.5 0.3 100/95
60 65 67 69 72
97 128 138 159 184
15 20 22 26 31
37 45 47 52 57
UHT infusion pilot plant (100 L h1) without pre-heat holding 135 4.2 0.5 0.3 0.5 139 4.2 1.2 0.4 1.1 140 4.2 1.5 0.4 1.4 142 4.2 2.4 0.5 2.2 144 4.2 3.7 0.5 3.4
0.2 0.3 0.3 0.3 0.4
91/76 93/78 93/78 93/79 94/80
19 22 23 24 26
28 38 41 48 56
4 6 7 8 10
12 15 16 18 20
Mini-UHT plant (10 L h1) pre-heat to 75 C with 135 5.42 1.0 0.7 139 5.42 2.4 0.9 140 5.42 2.9 0.9 142 5.42 4.5 1.0 144 5.42 6.8 1.2
0.2 0.2 0.3 0.30 0.3
98/90 99/91 99/91 99/91 99/92
42 47 48 51 53
63 84 91 105 122
10 14 15 18 21
23 28 29 32 35
Highest temperature ( C)
a
Holding time(s)
Overall process
Holding tube
B* (adj)
B* (adj)
C*
8 s holding 0.5 1.3 1.6 2.5 3.9
C*
b-lg Denaturationa,b (%)
According to Dannenberg and Kessler (1988). According to Lyster (1970). c Expressed as an equivalent time (s) at 121 C. B* ¼ the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. C* ¼ the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine. B* (adj) ¼ B* adjusted for the fastest particle based on Reynolds number. b
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increased, lactulose and browning levels may be higher than predicted. This is relevant because there are natural variations in milk pH and in levels of milk minerals (Tsioulpas, Lewis, & Grandison, 2007a; Tsioulpas, Lewis, & Grandison, 2007b), which influence the extent of these reactions. It is also important to consider cases in which stabilizers such as trisodium citrate or disodium hydrogen phosphate are added to milk, as these increase milk pH. Kinetics for browning will also differ when other sugars are added to milk dessert products such as custard. Overall, the approach used in this work has the potential to provide processors with guidance for changing the processing conditions for particular circumstances. However, its usefulness could be enhanced by addressing some of the above limitations and also extending its scope to include prediction of, for example, fouling potential, reduction in nutritive value, flavour changes and inactivation of milk plasmin and heat-resistant bacterial enzymes which cause defects during storage of UHT milk. 4. Conclusions Knowledge of the processing parameters of UHT plants (plant dimensions and configurations, flow rates, temperatures), combined with the use of a kinetics-based computer program, enabled the plants to be characterised in terms of their chemical and bacteriological indices as well as predictions to be made of the changes to milk components. Industrial plants showed a wide range of temperature–time profiles and the program transformed these different profiles into easily comparable total process parameters and estimates of the effects on quality aspects such as colour and nutritive value. It was concluded that this approach is superior to the use of nominal temperature–time combinations (of the holding tube) to indicate the bacteriological and chemical effects of a UHT plant, since the heat input in all sections of the plant is taken into account. A major benefit of the program used in this work is its ability to predict the changes in several milk components. While several chemical indicators of heating severity have been proposed, this work showed that the levels of wide spread a-lactalbumin predicted by the computer program show a widespread between the commercial plants under the heating conditions used and may be a convenient index of heat treatment. The usefulness of the predictive aspect of this approach was illustrated by its application to pilot plants to enable their operation to be tailored to closely reflect that of commercial plants. However, small tubular plants largely operate under laminar flow conditions and this must be taken into account when comparing their operation
with that of large commercial plants which invariably operate under turbulent flow conditions. Acknowledgements The authors wish to acknowledge the companies whose plants were surveyed for their cooperation and assistance, John and Mark Pain, Hipex Pty Ltd for assistance in temperature measurements, and Dairy Australia for financial support. References Bertsch, A. J., & Cerf, O. (1983). Dynamic viscosities of milk and cream from 70 to 135 C. Journal of Dairy Research, 50, 193–200. Bloch, S. C. (2000). Excel for engineers and scientists. New York, USA: Wiley. Browning, E., Lewis, M., & MacDougall, D. (2001). Predicting safety and quality parameters for UHT-processed milks. International Journal of Dairy Technology, 54, 111–120. Burton, H. (1988). Ultra-high-temperature processing of milk and milk products. London, UK/New York, USA: Elsevier Applied Science. Claeys, W. L., Ludikhuyze, L. R., & Hendrickx, M. E. (2001). Formation kinetics of hydroxymethylfurfural, lactulose and furosine in milk heated under isothermal and non-isothermal conditions. Journal of Dairy Research, 68, 287–301. Dannenberg, F., & Kessler, H. G. (1988). Reaction kinetics of the denaturation of whey proteins in milk. Journal of Food Science, 53, 258–263. Datta, N., & Deeth, H. C. (2001). Age gelation of UHT milk – a review. Institution of Chemical Engineers, 79(Part C), 197–209. Datta, N., Elliott, A. J., Perkins, M. L., & Deeth, H. C. (2002). Ultra-high-temperature (UHT) treatment of milk: comparison of direct and indirect modes of heating. Australian Journal of Dairy Technology, 57, 211–227. Elliott, A. J., Datta, N., Amenu, B., & Deeth, H. C. (2005). Heat-induced and other chemical changes in commercial UHT milks. Journal of Dairy Research, 72, 442–446. Fink, R., & Kessler, H. G. (1988). Comparison of methods for distinguishing UHT treatment and sterilization of milk. Milchwissenschaft, 43, 275–280. Kessler, H. G. (1981). Food engineering and dairy technology. Freising, Federal Republic of Germany: Verlag A. Kessler. Kessler, H. G., & Fink, R. (1986). Changes in heated and storage milk with an interpretation by reaction kinetics. Journal of Food Science, 51, 1105–1111. Lewis, M., & Heppell, N. (2000). Continuous thermal processing of foods – Pasteurization and UHT sterilization. Gaithersburg, MD, USA: Aspen Publishers. Lyster, R. L. J. (1970). The denaturation of a-lactalbumin and ß-lactoglobulin in heated milk. Journal of Dairy Research, 37, 233–243. Rombaut, R., Dewettinck, K., De Mangelaere, G., & Huyghebaert, A. (2002). Inactivation of heat resistant spores in bovine milk and lactulose formation. Milchwissenschaft, 57, 432–436. Swartzel, K. R. (1982). Arrhenius kinetics as applied to product constituent losses in ultra high temperature processing. Journal of Food Science, 47, 1886–1891. Tsioulpas, A., Lewis, M. J., & Grandison, A. S. (2007a). A study of the pH of individual milk samples. International Journal of Dairy Technology, 60, 96–97. Tsioulpas, A., Lewis, M. J., & Grandison, A. S. (2007b). Effect of minerals on casein micelle stability. Journal of Dairy Research, 74, 167–173. Wadsworth, K. D., & Bassette, R. (1985). Laboratory-scale system to process ultra high temperature milk. Journal of Food Protection, 48, 530–531. Wirjantoro, T. I., Lewis, M. J., Grandison, A. S., Williams, G. C., & Delves-Broughton, J. (2001). The effect of nisin on the keeping quality of reduced heat treated (RHT) milks. Journal of Food Protection, 64, 213–219.
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International Dairy Journal journal homepage: www.elsevier.com/locate/idairyj
Predictions of some product parameters based on the processing conditions of ultra-high-temperature milk plants H. Tran a, N. Datta a, M.J. Lewis b, H.C. Deeth a, * a b
Dairy Industry Centre for UHT Processing, School of Land, Crop and Food Sciences, University of Queensland, St Lucia, Qld 4072, Australia School of Food Biosciences, The University of Reading, Whiteknights, Reading, UK
a r t i c l e i n f o
a b s t r a c t
Article history: Received 30 April 2007 Received in revised form 17 August 2007 Accepted 16 January 2008
The temperature–time profiles of 22 Australian industrial ultra-high-temperature (UHT) plants and 3 pilot plants, using both indirect and direct heating, were surveyed. From these data, the operating parameters of each plant, the chemical index C*, the bacteriological index B* and the predicted changes in the levels of b-lactoglobulin, a-lactalbumin, lactulose, furosine and browning were determined using a simulation program based on published formulae and reaction kinetics data. There was a wide spread of heating conditions used, some of which resulted in a large margin of bacteriological safety and high chemical indices. However, no conditions were severe enough to cause browning during processing. The data showed a clear distinction between the indirect and direct heating plants. They also indicated that degree of denaturation of a-lactalbumin varied over a wide range and may be a useful discriminatory index of heat treatment. Application of the program to pilot plants illustrated its value in determining processing conditions in these plants to simulate the conditions in industrial UHT plants. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction UHT (ultra-high-temperature) treatment of milk produces a commercially sterile product which normally has a shelf-life at room temperature of at least 6 months. However, UHT treatment causes chemical changes to the milk components that affect milk flavour, nutrients and physical stability. The high temperature reached in UHT processing is primarily responsible for the effect of the process on bacteria, including spores, while the length of time that the product is subjected to elevated temperatures determines the extent of chemical change (Lewis & Heppell, 2000). The temperatures and times used to describe a UHT process, e.g., 140 C for 4 s, relate to the temperature and time the product spends in the holding tube. They take no account of the conditions in the heating and cooling sections or the heating method employed, e.g., whether direct or indirect heating. These can have a major effect on the overall heat treatment and the heat-induced changes and quality of the product (Datta, Elliott, Perkins, & Deeth, 2002; Lewis & Heppell, 2000; Swartzel, 1982). In order to determine the total effect of the heat treatment on the processing parameters and product properties, Browning, Lewis, and MacDougall (2001) used a computer simulation program (Excel) based on kinetic data for a range of parameters and
* Corresponding author. Tel.: þ61 7 33469191; fax: þ61 7 33651177. E-mail address: [email protected] (H.C. Deeth). 0958-6946/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.idairyj.2008.01.006
chemical changes relating to UHT processing. Using the temperature–time profile of a UHT plant, the program enables the processing parameters for the plant to be computed and various properties of the processed product to be predicted. This paper discusses the application of this program to industrial UHT processing plants in Australia. 2. Materials and methods 2.1. Collection of data on ultra-high-temperature plants The following data were collected for 22 UHT plants (17 indirect and 5 direct) and 3 pilot plants (2 indirect and 1 direct) at 12 locations across Australia which were processing milk (whole, reduced-fat, skim and flavoured), custard and cream: flow rate of the plant; plant dimensions of the heating and cooling sections (number, length, type and diameter of shells/tubes for tubular systems, and number of plates, hold-up volume of plates, and plate surface details for plate systems) and holding stages (length and internal diameter of holding tube); temperatures (inlet and outlet temperatures at each tube or stage); and, for direct heating plants, details of the injector or infusion chamber and vacuum chamber. Lengths of tubes, where accessible, were physically measured using a measuring tape. Lengths of obscured tubes, internal diameters of tubes and other dimensions that could not be physically measured were obtained from plant manufacturer specification data.
H. Tran et al. / International Dairy Journal 18 (2008) 939–944
Temperatures were taken from plant instrumentation where available. Other temperatures were measured on the outside surface of the tubes using a T-type thermocouple clamped to the tube by a specially fabricated wraparound heat-resistant sleeve. In order to estimate the temperature of the product within the tube from these external surface measurements, surface temperatures were taken as close as possible to several points where the product temperature was available through the installed instrumentation. The surface temperatures were then adjusted to provide estimates of the internal temperature. The difference between the surface and internal temperatures was typically 3.5 C.
160
Temperature (Deg. C)
940
140 120 100 80 60 40 20 0
0
50
100
150
2.2. Inputs into calculations
2.2.2. Equations for processing parameters B*, representing the bacteriological effect relative to a reference temperature of 135 C, was calculated from the equation B* ¼ !10((T135)/10.5) dt/10.1. A process with a B* ¼ 1 would produce a 9-log cycle reduction of thermophilic spores assuming a z-value of 10.5 C and would be equivalent to 10.1 s at 135 C (Kessler, 1981). B*(adjusted) is the B* relative to the fastest particle (e.g., bacterial spore) transiting a section or the whole process. The calculated B* was adjusted for the effect of Reynolds number, which indicates the nature of the flow or the mean residence time distribution. If the flow is turbulent (i.e., Reynolds number > 4100) the velocity of the fastest particle is considered to be 1.2 mean particle velocity (Kessler, 1981; Lewis & Heppell, 2000) so that the B*(adjusted) is B*/1.2. The dynamic viscosities used to calculate Reynolds numbers were based on reported equations for milks and creams between 70 and 135 C (Bertsch & Cerf, 1983). C*, representing the chemical effect relevant to a reference temperature of
Temperature (Deg. C)
160 140 120 100 80 60 40 20 0
50
100
250
300
350
400
450
Time (s)
2.2.1. Temperature–time profiles From the data collected from each UHT plant, residence times, velocities and total volumes of tubes in each section, as well as the total residence time and total volume of tubes for the entire plant, were calculated. From these, the temperature–time profiles for the indirect and direct UHT plants were plotted as illustrated in Figs. 1 and 2, respectively. All data points shown represent measured or calculated data. The profile between adjacent points was assumed to be linear. For the direct plants, the time taken for the temperature to be raised from that of the product at the start of the heating section to the beginning of the holding tube was assumed to be 0.5 s (Burton, 1988). Similarly, the time taken to cool the product in the vacuum chamber was assumed to be 0.5 s. The average time a product spends in the vacuum chamber is shown as a holding time at the outlet temperature.
0
200
150
200
250
300
350
Time (s) Fig. 1. Selected temperature–time profiles of industrial indirect UHT plants surveyed Different symbols represent different UHT plants.
Fig. 2. Selected temperature–time profiles of industrial direct UHT plants surveyed Different symbols represent different UHT plants.
135 C, was calculated from the equation C* ¼ !10((T135)/31.4) dt/ 30.5. A process with a C* ¼ 1 would reduce the concentration of thiamine by 3% assuming a z-value of 31.4 C and would be equivalent to 30.5 s at 135 C (Kessler, 1981). 2.2.3. Kinetic data of heat-induced changes The predicted changes in milk components during heat treatment were kinetically modeled using reported values of reaction rate (k), activation energy (Ea) and reaction order (n) of the reactions, and, in cases where n > 1, the initial concentration of the milk component. Kinetic data used for browning were those reported by Lewis and Heppell (2000), thiamine and lysine loss by Kessler and Fink (1986), denaturation of b-lactoglobulin by Dannenberg and Kessler (1988) and Lyster (1970), denaturation of alactalbumin by Lyster (1970), furosine by Claeys, Ludikhuyze, and Hendrickx (2001), and lactulose formation by Rombaut, Dewettinck, De Mangelaere, and Huyghebaert (2002). 2.3. Calculation of results for ultra-high-temperature plants The data and equations given above were used to calculate the process parameters and chemical changes occurring in each section of the UHT plants using an Excel program based on the one published by Browning et al. (2001). The results were integrated using the trapezoidal rule (Bloch, 2000). 3. Results and discussion An example of the data calculated for an indirect plant is shown in Table 1. Similar data were obtained for direct plants except the times of heating to and cooling from the highest temperature were very short. Table 1 shows the contribution of the different sections of the plants to the various parameters. In particular, the contributions of the holding tube to the overall results varied considerably between the different plants, although the difference was greatest between the indirect and direct plants. However, it should be noted that the figures for b-lactoglobulin (b-lg) and a-lactalbumin (a-la) are cumulative, whereas the others are for individual sections and are additive for the total system. The calculated data for all industrial plants surveyed are summarized in Table 2 while the temperature–time profiles for some of the indirect and direct plants are shown in Figs. 1 and 2, respectively. These profiles show that a wide range of temperatures and times are used commercially and clearly demonstrate the value of a program such as the one used in this work to transform these different profiles into easily comparable total process parameters and estimates of effects on product components.
H. Tran et al. / International Dairy Journal 18 (2008) 939–944
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Table 1 Example of data calculated by the model program for an industrial UHT plant (indirect) Stage in process
Pre-heating Intermediate heating 1 Intermediate holding Intermediate heating 2 Final heating High-temperature holding First cooling Homo Final cooling
Temp ( C) In
Out
4 65 95 95 127 140 140 90 94
65 95 95 127 140 140 90 94 20
Time (s) 51.5 20.6 62.5 26.3 20.6 4.3 41.2 9.0 51.5
Totald
227
B*
B* (adjusted)
C*
0 0 0 0.06 2.02 1.26 1.12 0 0
0 0 0 0.05 1.68 1.05 0.93 0 0
4.46
3.71
b-lg Denaturationa (%)
b-lg Denaturationb (%)
0 0.01 0.11 0.19 0.63 0.20 0.52 0.06 0.02
0 43 95 98 99 99 100 100 100
0 20 78 87 93 93 95 96 96
1.74
100
96
a-la
Total browning (s)c
Lactulose (mg 100 g1)
Furosine (mg 100 g protein1)
14 28 52 58 72 74 74
0.1 0.8 6.4 15.2 66.0 22.9 50.3 3.3 0.8
0 o 0.5 2.1 11.6 4.2 7.9 0.2 0
0 0.7 5.0 14.4 43.2 49.0 74 77 77
74
165.8
26.5
77
Denaturationb (%) 0
a
According to Dannenberg and Kessler (1988). b According to Lyster (1970). c Expressed as an equivalent time (s) at 121 C. d Whey protein denaturation data are cumulative whereas other data are additive. B* ¼ the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. B* (adjusted) ¼ B* adjusted for the fastest particle based on Reynolds number. C* ¼ the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine.
3.1. Bacteriological (B*) and chemical (C*) indices The adjusted B* values of the industrial plants, i.e., adjusted for flow characteristics based on Reynolds number, ranged from 1.6 to 16.5 for indirect plants and 1.7 to 11.8 for direct plants. All plants had Reynolds numbers > 4100 indicating turbulent flow; therefore, the adjustment factor used was 1.2, i.e., B* ¼ 1.2 B*(adjusted). According to the rule of thumb for UHT processing that B* should be greater than 1 (to ensure a 9-log reduction in thermophilic spores) (Kessler, 1981), all the UHT plants surveyed met this criterion, with some operating at excessively high B*. Operating at a B* value much higher than 1 provides a safety margin and may be useful for
destroying highly heat-resistant spores but in most cases is unlikely to have a significant effect on the microbiological quality. Because of the different kinetics for bacterial inactivation and chemical changes, a very high B* value does not necessarily indicate excessive chemical changes (e.g., cooked flavour production) in the product; this is accounted for by the C* value. This point is particularly relevant to direct heating, where B* is high and C* is relatively low. The C* values ranged from 0.9 to 3.0 for indirect plants and 0.4 to 1.5 for direct plants. Plants should operate at a C* < 1 (where C* ¼ 1 is equivalent to a 3% loss of thiamine) because a C* value much higher than 1 is indicative of excessive chemical change which may result in off-flavour production, excessive nutrient loss and, in
Table 2 Whole process data calculated by the model program for 22 industrial UHT plants Plant no.
Highest temperature ( C)
Holding time (s)
Overall process B (adj)
C
Indirect UHT plants 1 144 2 144 3 144 4 138 5 140 6 142 7 139 8 139 9 137 10 144 11 142 12 142 13 137 14 137 15 138 16 138 17 145
5 8 19 2 4 4 6 5 16 6 5 8 9 12.5 10 25 2.5
8.7 10.1 16.5 1.6 3.7 4.8 2. 6 2.9 4.4 6. 7 8.2 8.2 1.6 2.1 3.1 4.8 4.6
Direct UHT plants 18 146 19 143 20 143 21 143 22 145
6 2 10 4 13
4.1 1.7 5.6 2.7 11.8
a
*
*
Holding tube *
*
b-lg
a-la
Denaturationa,b (%)
Denaturationb (%)
Total browning (s)c
Lactulose (mg 100 g1)
Furosine (mg 100 g protein1)
B (adj)
C
1.9 2.1 2.8 1.0 1.7 1.5 1.3 1.5 2.8 1.6 3.0 3.0 0.9 1.1 1.8 1.6 0.9
3.0 4.4 10.8 0.3 1.1 1. 7 1.2 1. 2 2.0 3.3 1.9 2.3 1.1 1.5 1.4 4.0 1.9
0.3 0.5 1.2 0.1 0.2 0.2 0.3 0.2 0.6 0.4 0.3 0.4 0.3 0.5 0.4 1.0 0.2
100/94 100/95 100/96 99/92 100/96 100/96 99/94 100/95 100/97 100/95 100/97 100/97 99/91 99/92 100/95 99/94 99/96
72 74 82 51 74 75 59 69 90 67 89 89 35 56 75 68 25
206 225 308 90 166 192 121 146 288 169 299 305 85 105 168 170 100
36 39 55 14 26 32 20 23 46 29 50 51 14 17 27 29 17
82 86 104 43 77 83 54 67 120 64 104 107 32 40 63 51 40
0.5 0.4 0.8 0.5 1.5
4.1 1.2 4.8 1.9 9.7
0.4 1.0 0.6 0.2 0.9
89/74 92/78 97/87 95/81 99/92
27 22 40 27 58
51 39 95 53 170
9 6 17 9 30
14 15 28 18 50
According to Dannenberg and Kessler (1988). According to Lyster (1970). c Expressed as an equivalent time (s) at 121 C. B* ¼ the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. C* ¼ the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine. B* (adj) ¼ B* adjusted for the fastest particle based on Reynolds number. b
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H. Tran et al. / International Dairy Journal 18 (2008) 939–944
extreme cases, colour change (browning). The above data suggest that the heat intensity in some plants, especially some indirect plants, may be too high. This could be reduced by a slight reduction in the UHT processing temperature, which would decrease both the B* and C* values; microbial quality should not be compromised, provided B* was still well above 1.0, and chemical quality should be improved. However, age gelation is delayed in milk with a high C* value, as indigenous plasmin and bacterial proteases are inactivated to a greater extent (Datta & Deeth, 2001). In indirect plants, the effect of the cooling stage on C* is generally not as important as the effect of the heating stage because, in the cooling stage, the product temperature generally falls rapidly, while the rise in temperature in the heating stage is usually slower (Fig. 1). The contribution of the holding tube in the industrial plants to the overall B* and C* values is also shown in Table 3. These show the very high contribution of the holding tube in the direct plants and a lower contribution in the indirect plants, with the difference being greatest for the B* values. This illustrates how misleading it is to quote nominal temperature–time combinations as indicators of the bacteriological and chemical effects of a UHT plant. 3.2. Chemical heat indices The chemical heat index data are summarized in Table 2. The data for b-lg demonstrate the higher degree of denaturation in indirect than in direct plants (Table 4), which has been reported by many authors and accords with the experimental data on milks for Australian plants (Elliott, Datta, Amenu, & Deeth, 2005). Denaturation of b-lactoglobulin was very high for indirect plants and is not a good indicator to discriminate between plants. However, it does discriminate between direct and indirect plants. Two values were calculated for denaturation of b-lg: one using the kinetic parameters of Dannenberg and Kessler (1988) and the other the parameters reported by Lyster (1970). The calculated values are somewhat different and reflect the different methods used to by the authors – immunodiffusion (Lyster, 1970) and acid precipitation (Dannenberg & Kessler, 1988). The data for a-la denaturation show higher levels of denaturation for indirect plants than direct plants (Table 4) and agree well with the experimental data of Elliott et al. (2005). These data show a much greater spread than the b-lg data, suggesting that a-la may be a good universal chemical heat index. The conditions used in the indirect plants result in almost complete denaturation of b-lg but cause a range of levels of denaturation of a-la, from 25 to 90%. The commonly accepted chemical index for UHT milk, C*, relates to
Table 3 Percentage contribution of the holding tube to B* and C* in industrial indirect and direct UHT plantsa % Contribution B* C* of the holding tube No. of indirect No. of direct No. of indirect No. of direct plants (n ¼ 17) plants (n ¼ 5) plants (n ¼ 17) plants (n ¼ 5) 0–<10 10–<20 20–<30 30–<40 40–<50 50–<60 60–<70 70–<80 80–<90 90–100
0 0 3 3 5 2 2 1 1 0
0 0 0 0 0 0 1 0 3 1
2 6 5 1 2 0 1 0 0 0
0 0 0 1 1 0 1 1 1 0
a B* is the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. C* is the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine.
Table 4 Predicted percentage denaturation of b-lactoglobulin and a-lactalbumin, and levels of lactulose and furosine, in milk from commercial UHT plants No. of indirect plantse
No. of direct plantse
% Denaturation of b-lactoglobulina 74–76 77–79 80–82 83–85 86–88 89–91 92–94 95–97 98–100
0 0 0 0 0 0 0 0 17
1 1 0 1 1 1 0 0 0
% Denaturation of a-lactalbuminb <20 20–<30 30–<40 40–<50 50–<60 60–<70 70–<80 80–<90 90–100
0 1 1 1 3 2 5 3 1
0 3 0 1 1 1 0 0 0
Lactulose (mg 100 g1)c 0–<10 10–<20 20–<30 30–<40 40–<50 50–<60
0 4 6 3 1 3
3 1 0 1 0 0
Furosine (mg 100 g protein1)d 0–<30 30–<60 60–<90 90–<120
0 6 7 4
4 1 0 0
a b c d e
Based on the reaction kinetics parameters of Dannenberg and Kessler (1988). Lyster (1970). Rombaut et al. (2002). Claeys et al. (2001). Total number of indirect plants ¼ 17 and direct plants ¼ 5.
destruction of thiamine; however, thiamine is seldom measured. By contrast, (undenatured) a-la is measured in many laboratories and could be used as a convenient index of UHT heat treatment. Lactulose and furosine are other commonly used chemical indices of heat-induced changes in milk. The calculated data for these compounds are shown in Table 2 and summarized in Table 4. Lactulose levels in Australian UHT milk have been reported to range from 12.1 to 24.4 mg 100 g1 (direct UHT process) and from 45.4 to 53.1 mg 100 g1 (indirect UHT process) (Elliott et al., 2005). The results calculated from the model program on the industrial plants are in agreement with this range. They are all lower than the limit of 60 mg 100 g1 for UHT milk in European regulations. A browning value above w400 (corresponding to milk heated at 121 C for 400 s) has been given as the threshold for colour detection in unmodified milks (Browning et al., 2001; Fink & Kessler, 1988). From the values in Table 2, none of the conditions being used in the plants surveyed is likely to produce milk with a noticeably brown colour. Given that some plants were operating at quite high heat intensity, it is apparent that extreme conditions are required to cause discoloration. However, there is evidence that the higher the browning index, the more susceptible milk is to further browning during storage, especially at >30 C (Wirjantoro, Lewis, Grandison, Williams, & Delves-Broughton, 2001).
H. Tran et al. / International Dairy Journal 18 (2008) 939–944
3.3. Pilot plant data and relevance to industrial plants In principle, this procedure for determining process and product parameters from temperature–time profiles is applicable to pilot plants as well as commercial plants. Data are shown in Table 5 for a 100 L h1 APV pilot plant, in both direct and indirect modes, and a 10 L h1 bench-top plant, similar to that reported by Wadsworth and Bassette (1985), when operating under various heating conditions. These data demonstrate how the type of analysis discussed in this paper can be used to tailor pilot plants to operate at specified B* and/or C* values corresponding to those for given configurations of full-scale plants. In this way, trial products can be given very similar heat treatment in the small-scale plants to those in the fullscale plants. This is not possible by using the same nominal (holding tube) temperature–time combinations. This approach also highlights the different flow characteristics of pilot-scale equipment relative to commercial plants. The calculated Reynolds numbers, particularly in the holding tube, which usually has a greater diameter than the heating and cooling tubes in commercial plants, are much lower in the small-scale plants, indicating largely laminar flow. In this work, the flow in the holding tubes of the 100 L h1 pilot plant was turbulent (Re ¼ 5360) but in the pre-heat and cooling tubes was laminar (Re ¼ 630). In the miniUHT plant operating at 10 L h1, the corresponding Reynolds numbers were 1270 and 150, indicating laminar flow in both sections. Hence, the residence time distributions are greater in the small plants than in the large commercial plants. This is more significant for microbiological parameters than chemical parameters, which supports the use of the adjusted B* values calculated in this work. For the laminar flow sections of the pilot plants, the B* values were adjusted by a factor of 2, i.e., B* ¼ 2 B*(adjusted). 3.4. Limitations of the calculated data While every effort was made to ensure the accuracy of the data, the following factors placed limitations on the results obtained. The data obtained for some plants were incomplete because of either limited access to the heating sections or lack of information
943
about hold-up volumes (e.g., in plate heat exchangers and vacuum flash vessels). Also time of heating and cooling in direct plants is largely unknown although it is generally considered to be 0.5 s both to heat from 75 to 140 C and to flash cool from 140 to 75 C (Burton, 1988). In some indirect tubular plants, temperature data could be obtained at several points along the heat exchanger. This enabled convex heating curves to be plotted rather than straight lines between the lowest and highest temperatures, giving more accurate information. By contrast, limited temperature measurements were possible in some plants and straight lines only could be drawn between consecutive data points. The calculated chemical changes are based on published kinetic data for whole milk and hence the data calculated for reduced-fat milk, flavoured milk, cream and custard may not be accurate. For example, Reynolds numbers were based on milk and hence are not accurate for other products, particularly viscous products such as cream and custard, as Reynolds number is inversely proportional to viscosity. Furthermore, full account has not been taken of the variation in viscosity with temperature. Values for B* were adjusted for the flow characteristics of the plants, as shown by the Reynolds numbers, so they apply to the fastest particle. The adjusted values provide the most accurate indication of the minimum bactericidal treatment by the plant; however, they underestimate the bactericidal effect on most bacterial cells in the product. The published reaction kinetic data also vary because of the different methodology and analytical methods used to obtain the data. An example of this is the different kinetic data reported for denaturation of b-lactoglobulin by Dannenberg and Kessler (1988) and Lyster (1970). Furthermore, the whey protein denaturation calculations (which are based on reaction orders >1 and hence require the initial concentration to be known to produce accurate data) assume the same initial level of these proteins in the different products from the different factories, which is unlikely to be true; however, further refinement of these data was not possible. In addition, some changes such as the Maillard browning reaction and lactulose formation are pH-dependent and the kinetic models used do not take this into account. Thus if the pH of milk is
Table 5 Whole process data calculated by the model program for three pilot plants
a-la Denaturationb (%)
Total browning (s)c
Lactulose (mg 100 g1)
Furosine (mg 100 g protein1)
UHT tubular pilot plant (100 L h1) with pre-heat holding at 90 C for 31 s 135 4.2 1.2 1.1 0.4 0.1 99/94 139 4.2 2.6 1.3 0.8 0.2 100/94 140 4.2 3.2 1.4 1.1 0.2 100/95 142 4.2 4.9 1.6 1.6 0.2 100/95 144 4.2 7.4 1.8 2.5 0.3 100/95
60 65 67 69 72
97 128 138 159 184
15 20 22 26 31
37 45 47 52 57
UHT infusion pilot plant (100 L h1) without pre-heat holding 135 4.2 0.5 0.3 0.5 139 4.2 1.2 0.4 1.1 140 4.2 1.5 0.4 1.4 142 4.2 2.4 0.5 2.2 144 4.2 3.7 0.5 3.4
0.2 0.3 0.3 0.3 0.4
91/76 93/78 93/78 93/79 94/80
19 22 23 24 26
28 38 41 48 56
4 6 7 8 10
12 15 16 18 20
Mini-UHT plant (10 L h1) pre-heat to 75 C with 135 5.42 1.0 0.7 139 5.42 2.4 0.9 140 5.42 2.9 0.9 142 5.42 4.5 1.0 144 5.42 6.8 1.2
0.2 0.2 0.3 0.30 0.3
98/90 99/91 99/91 99/91 99/92
42 47 48 51 53
63 84 91 105 122
10 14 15 18 21
23 28 29 32 35
Highest temperature ( C)
a
Holding time(s)
Overall process
Holding tube
B* (adj)
B* (adj)
C*
8 s holding 0.5 1.3 1.6 2.5 3.9
C*
b-lg Denaturationa,b (%)
According to Dannenberg and Kessler (1988). According to Lyster (1970). c Expressed as an equivalent time (s) at 121 C. B* ¼ the bacteriological effect relevant to a reference temperature of 135 C; B* ¼ 1 is equivalent to a 9-decimal reduction of thermophilic spores. C* ¼ the chemical effect relevant to a reference temperature of 135 C; C* ¼ 1 is equivalent to a 3% reduction in thiamine. B* (adj) ¼ B* adjusted for the fastest particle based on Reynolds number. b
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increased, lactulose and browning levels may be higher than predicted. This is relevant because there are natural variations in milk pH and in levels of milk minerals (Tsioulpas, Lewis, & Grandison, 2007a; Tsioulpas, Lewis, & Grandison, 2007b), which influence the extent of these reactions. It is also important to consider cases in which stabilizers such as trisodium citrate or disodium hydrogen phosphate are added to milk, as these increase milk pH. Kinetics for browning will also differ when other sugars are added to milk dessert products such as custard. Overall, the approach used in this work has the potential to provide processors with guidance for changing the processing conditions for particular circumstances. However, its usefulness could be enhanced by addressing some of the above limitations and also extending its scope to include prediction of, for example, fouling potential, reduction in nutritive value, flavour changes and inactivation of milk plasmin and heat-resistant bacterial enzymes which cause defects during storage of UHT milk. 4. Conclusions Knowledge of the processing parameters of UHT plants (plant dimensions and configurations, flow rates, temperatures), combined with the use of a kinetics-based computer program, enabled the plants to be characterised in terms of their chemical and bacteriological indices as well as predictions to be made of the changes to milk components. Industrial plants showed a wide range of temperature–time profiles and the program transformed these different profiles into easily comparable total process parameters and estimates of the effects on quality aspects such as colour and nutritive value. It was concluded that this approach is superior to the use of nominal temperature–time combinations (of the holding tube) to indicate the bacteriological and chemical effects of a UHT plant, since the heat input in all sections of the plant is taken into account. A major benefit of the program used in this work is its ability to predict the changes in several milk components. While several chemical indicators of heating severity have been proposed, this work showed that the levels of wide spread a-lactalbumin predicted by the computer program show a widespread between the commercial plants under the heating conditions used and may be a convenient index of heat treatment. The usefulness of the predictive aspect of this approach was illustrated by its application to pilot plants to enable their operation to be tailored to closely reflect that of commercial plants. However, small tubular plants largely operate under laminar flow conditions and this must be taken into account when comparing their operation
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