Thermal Processing of Foods, A Retrospective, Part II: On-Line Methods for Ensuring Commercial Sterility

Thermal Processing of Foods, A Retrospective, Part II: On-Line Methods for Ensuring Commercial Sterility M. N. RAMESH Food Engineering Department Central Food Technological Research Institute Mysore 570 013, India

M. A. KUMAR Central Instrum en ts Facility Central Food Technological Research Institute Mysore 570 013, India S. G. PRAPULLA Fermentation Technology and Bioengineering Department Central Food Technological Research Institute Mysore 570 013, India

M. MAHADEVAIAH Food Packaging Technology Department Central Food Technological Research Institute Mysore 570 013, India

Introduction Fo Integrators On-Line Monitoring Systems Semiautomatic Retort Control Systems for Optimum Sterilization Computer-Aided Sterilization Process Indicators A. Bioindicators B. Color-Based Physical Indicators C. Chemical Markers D. Electronic Indicators VII. Suggestions for Future Work VIII. Conclusions References I. 11. 111. IV V VI.

315 ADVANCES IN APPLIED MICROBIOLOGY, VOLUME 44 Copyright 0 1997 by Academic Press, Inc. All rights of reproduction in any form reserved. on~,5-2164/97$25.00

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I. Introduction

The major cause for spoilage of thermally processed foods is the failure to follow a scientifically derived process schedule. The problem does not appear to lie in the process engineering area, where thermal process schedules are developed, but primarily in the manufacturing and production areas. The use of proper on-line methods involving trained personnel in canning plants is of utmost importance. The reason for the continuing spoilage and overprocessing of canned foods is that canning plants are often operated by untrained personnel who fail to administer the recommended sterilization processes. Though there is no way to remove the uncertainties in thermal processing, attempts have been made by food technologists and food engineers to critically evaluate the process, which have led to the development of control systems and instruments to ensure the commercial sterility of processed food products. These instruments indicate the sterility during processing, and the control system continuously monitors and controls the sterility value on-line and ensures commercial sterility without loss of nutrients. On-line methods are used to ensure minimum sterility, so as to avoid overprocessing and to facilitate nutrient retention. This indicates the actual time-temperature profile being experienced by the food. However, this method cannot eliminate the uncertainties involved in the development of time-temperature profiles. By this approach, a targeted sterility value can be accurately controlled and the effect of temperature abuse can be reduced to yield a better product, and one safe for immediate consumption. Sterilizing operations are used commercially in a number of industries, particularly in food and pharmaceuticals. The safety of the product being sterilized depends on correct operation of the sterilizing system, and thus a successful control procedure. The criterion for detection of adequate sterility is the sterilizing value Fo, which is determined by conducting heat-penetration tests by placing a temperature-measuring device at the point of slowest heating. During control operations, the temperature of the cold point is monitored so as to attain the prescribed Fo value. Simple thermocouples are used to determine the temperature distribution in commercial retorts. This chapter describes the on-line methods applied for within-container and aseptic processing. On-line methods for sterilization can be subclassified as:

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1. F,, integrators 2. On-line monitoring systems for determination of asepticity 3. Semiautomatic retort control systems 4. Computer-aided sterilization 5. Process indicators (time-temperature)

a. Bioindicators b. Color-based physical indicators c. Chemical markers d. Electronic indicators

II. Fo Integrators This is an instrument or a data acquisition system used to measure the accomplished lethality. It employs analog computing techniques to calculate process lethality or the F value of the process. The F value is defined as the duration of heat treatment at a suitable reference temperature that would be equivalent, with respect to destruction of a certain number of spoilage microorganisms, to the actual process. The instrument computes the F values continuously throughout a process from temperature signals derived from a sensor probe inserted at the cold point of the packed food. The instrument may be readily adapted for use with various types of temperature detection, including fine-wire thermocouples, or temperature telemetry used in case of agitating cookers. The temperature sensor generates an electrical signal proportional to the temperature at the sensing point. The electrical signal is converted to an equivalent Fvalue by suitable mathematical translation. As the F value is displayed rather than time-temperature profiles, it is easier to control the process when the targeted Fo value is reached. The principle of operation is depicted in Fig. 1. Skinner (1975) has developed an instrument that calculates the F value of a heat sterilization process using an analog technique. Holdsworth (1983) has listed a few of the commercially available F,, integrators indicated in Table I. Jairus and Shoemaker (1985) have developed a transducer to directly measure lethality rates during thermal processing. It consisted of a double-legged thermocouple, a thermocouple conditioner, and an antilog amplifier. The lethality rates measured in real time during thermal process experiments compared well with those calculated later from time-temperature profiles. A generalpurpose microcomputer data acquisition system was designed to evaluate this transducer. This system can also be used for data recording of similar routine and experimental processes.

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DispdY opening Menu

-

Initialize Lethality (L) = 0.00 Processing Time (t) 0.00 Time = 0.00 ScVlIntervd t = 0.00

-

I

Time

=

Time + t

-

Display / Print

FO E L

Processing Time(t)

FIG.1. Flowchart for the principle of operation of an Fo integrator.

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THERMAL PROCESSING OF FOODS, PART I1 TABLE I CflMMERCIALLYAVAILABLE DATAACQUISTI~N UNITS WITH THEIR SPECIFICATIONS Unit

Ball datatrace

Ultrakust Thermophil (PD30)

Redpost

No. of channels

Measuring range PC)

Resolution ("C)

Accuracy PC)

10 to 140

0.2 full range

10-40 : 0.5 40-120 : 0.25 120-140 : 0.5

1

Wessex Power Technology 189 Ashley Rd, Parkstone Poole, Dorset, BH14 9DL

-100 to 300

0.1

0.2%

3

Endamon Unit 6, Highfield Close Cove, Hampshire GUlW

f0.3

1 or 2

The Old Pumping Station Tolt Rd, Bourn Cambridge CB3 7TT

k0.5

8

full range

-5 to 100

0.1 (49-80)

Multitracker

190 to400

0.1

Address

Deanland House Cowley Rd, Cambridge CB4 4GU

Continuous data acquisition units (DAUs) for thermal process evaluation (May and Withers, 1993) are available that can withstand the extreme environment of the process while logging temperatures within the container. These DAU systems are battery-operated and employ platinum resistance thermometers, thermistors, or thermocouples for temperature measurement. May and Withers (1993) have also listed some of the commercially available data acquisition systems for thermal processing process evaluation. These DAUs and their features are given in Table 11. This is an open-loop system, and it only displays the accomplished lethality or Fo value. Since the actual Fo value or the accomplished lethality at the can center is displayed, it is convenient to control the process and the temperature of the retort. This leads to optimum sterilization without overcooking. The limitation of this approach is that it needs exba instrumentation and must be maintained properly for accurate readings. It also only displays the Fo value calculated based on an equation that is derived

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et

al.

TABLE I1 DATAACQUISITION UNITSAND Fo INTEGRATORS Use

Temperature

Accuracy

"C

"C

range

Sensor facilities

Automatic FO value computer Ellab A/S Denmark

Static & rotary batch retorts

4/6 in product 1in retort also rpm Cu-Constantan

10-150

f0.5

Lethality meter NCFT Reading University

Static retorts

1thermistor probe

90-135

-

Sterimeter (SRA 711) Telemetric Instrument, Sweden

Static retorts

Platinum resistance or Cu/Constantan thermocouple

85-135

f0.2

Ursamat Berlin Institute of Control Tech., Germany

Static retorts

Copper/ Constantan thermocouples

50-130

-

Cyclometer counter FO

Autodata Acurex California, USA

Static retorts

1 , 2 Or 4 Platinum resistance

20-127.5

f0.5

Digital and chart, Fo

Q-DOS minicomputer Q-DOS-Kings

Static

1OX Copper/ Constantan thermocouples

70-130

f 0.3

Computer screen and FO

Minicomputer software development CFPRA Glos., UK Lynn, UK

Static

12X Copper/ Constantan thermocouples

70-130

f0.4

Computer screen and floppy disk & heat frame data + FO

OBSLED Czechoslovakia

Static

Copper/ Constantan thermocouples

90-135

-

and Name

Display

Digital or chart Fo and rpm

Digital Fo Digital or chart alarm preset Fo

Digital and chart and Fo

using uncertainties and assumptions. However, this approach does assure minimum sterility as accomplished by the derived time-temperature profile.

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Ill. On-Line Monitoring Systems

Because of the important emphasis that must be placed on public safety when it comes to canned foods, processors must operate in strict compliance with the canned food regulations (Teixeira et al., 1982). Particular emphasis is placed on product batches that experience an unscheduled process deviation, such as a drop in retort temperature, during the course of the process. In such cases, the entire batch must be reprocessed or set aside for reevaluation by a competent authority. Such practices are costly, so that processors tend to operate with higher retort temperatures and longer process times than those specified in their established scheduled processes, so as to minimize the frequency at which process deviations occur. At the same time, processors also recognize that higher retort temperatures and longer durations tend to have an adverse effect on product quality, and they would like to minimize such overprocessing. With the advent of low-cost microcomputers, the measured Fo value can be improved to control the process. It is no surprise, then, that they are becoming common (Datta et a]., 1986). Such controls yield uniform product quality while minimizing energy waste due to overprocessing. This leads to optimum sterilization. The temperature sensed at the cold point of the packed food is used to calculate the F value of the process at the initial temperature of the can and the retort temperature of the system at any given time. A microprocessor, which forms the heart of the control system, monitors the steam inlet. Once the calculated Fo is equal to the targeted Fo value, the steam inlet is closed using suitable valves. Thus, the temperature of a particular system is measured on-line and any deviation is suitably taken care of during F value calculation. By this method, whatever the temperature of the system may be, once the cold point of the packed food reaches the Fo value, heating stops. An accuracy of +O.l% produces little additional savings in terms of either process time or overprocessing consequences. For the high-temperature process, the gains from reduced error arise more in terms of reduction in overprocessing than from significant savings of process time. This is a closed-loop control system, along with display of the accomplished lethality, at the same time controlling the process, when the targeted lethality is accomplished. It also corrects the deviation by suitably calculating the required Fo value based on the such process parameters as initial temperature and retort temperature. Thus, it is on-line monitoring of the Fo value. Teixeira et al. (1982) have used a numerical computer program model that was developed to simulate the thermal processing of

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conduction-heated canned foods. The discussed control logic applies to batch-operated retorts in which the process time can be easily adjusted to compensate for an uncontrolled change in retort temperature. Datta et al. (1986) have developed and demonstrated the performance of an on-line computer-based retort system for processing canned foods that can ensure the desired level of sterilization automatically in real time despite arbitrary deviations in the heating medium temperature. They also considered the cooling part of the F,, value for accomplished lethality to terminate the process. Navankasattusas and Lund (1978) have discussed the basics of the development of the time-temperature profile and systems for on-line measurement of lethality. This also includes a lethality rate generator and a lethality rate integrator. They also discussed monitoring and control of continuous thermal processing by on-line measurement of accomplished lethality with a miniaturized lethality meter, without a display unit, in an insulated container. The accomplished lethality is read after the detector has traveled through the entire path of the cooker. Teixeira (1995) reviewed some intelligent on-line control systems for retorts that have been developed in Europe and North America. Various approaches based on real-time accumulation of the accomplished sterilization value of lethality are described. The lethality value is calculated from data taken from test containers using on-line data acquisition systems. The on-line control systems have been classified as: 0

Intelligent control via real-time data acquisition.

0

Control by estimated correction factor. Intelligent control with heat transfer models.

Intelligent retort control systems have the ability to calculate the accomplished sterilized value of a process (Fo)in response to the integrated time-temperature history experienced by the product at its cold point. This accumulating sterilization is compared with the target value to be reached at the end of heating as a control decision criterion to determine the end of heating for the process. These intelligent on-line retort control systems can be very effective and reliable and have been put into commercial practice. However, they require instrumented test containers with probes and lead wires into each and every retort batch. This approach is quite practical where the product value is very high, process times are very long, and considerable downtime is available between batches. However, it is considered cost-prohibitive, so that much attention is being focused on development of indirect means for

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accomplishing intelligent on-line retort control, either by using estimated correction factors or mathematical heat transfer models. Control by the estimated correction factor approach assumes that the lowest temperature of the retort during a deviation will remain sustained for the duration of the process and sets a new extended process time calculated at the reduced temperature. This approach requires that process times for a range of specified retort temperatures be calculated and stored in the memory of the control system, for quick reference whenever needed. The principal disadvantage of this approach is that, when a low-temperature extended process schedule has been adopted, it usually leads to overprocessing, since most process deviations would quickly recover, allowing the retort to resume its normal operating temperature. A revised method for calculating the correction factor avoids this unnecessary overprocessing by extending the process time only to the desired extent to compensate for the deviation. The correction factor is calculated statistically. Although this approach minimizes overprocessing, it becomes unwieldy in situations where multiple deviations occur and when deviations will not fully recover or might be difficult to analyze. This necessitates an accurate knowledge of the product center temperature history in response to any dynamic retort temperature variation without measuring internal can temperature with probes of any kind. Heat transfer models fill the void in this area and provide accurate process schedules for specific processing equipment and products. A heat transfer model for simulating thermal sterilization of canned food is a mathematical equation capable of predicting the internal temperature over time in response to a change in temperature applied at the surface. The solution of the equation is obtained by a finite-difference model employing numerical techniques. The actual retort temperature is read directly from sensors and is continuously updated with each iteration of the numerical solution. The model predicts the correct internal temperature response for any unexpected deviation of retort temperature. By programming the control logic, heating is continued until target lethality is accomplished, facilitating attainment of the desired level of sterilization regardless of any unscheduled process deviations. This approach shows the greatest promise for use with truly intelligent on-line retort control systems. The advantage of this system is that it controls the process and ensures optimum sterilization even with deviations from the set parameters. The limitation of the approach is that it only accepts the set parameters. Actual time-temperature profiles to be set are to be derived by using any of the approaches discussed earlier.

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IV. Semiautomatic Retort Control Systems for Optimum Sterilization

Ramesh et al. (1994) have developed a semiautomatic retort control system for sterilization of foods using a microprocessor. The control system has two modes: direct retort temperature monitoring and container cold-point monitoring. The importance of this control system is that the actual container center temperature is used to control the retort temperature and the entire process. This facilitates optimum cooking, leading to greater nutrient retention and savings in energy by avoiding overcooking. The cooling part of the lethality is also accounted for by suitably modifying the targeted Fo value to be achieved during the heating period. This system can be easily retrofitted onto existing horizontal and vertical manually controlled batch retorts. The system is economical compared to the more sophisticated large computer-controlled systems. It is mainly aimed at small- and medium-scale food processing industries that have manually operated batch retorts and do not necessarily involve huge investments. A block diagram of this system developed is shown in Fig. 2. Gill et al. (1985) have retrofitted two retorts with computerized data acquisition and control systems. Process control was carried out on the basis of up to 10 test cans equipped with thermocouples. The system provided excellent on-line feed-forward control for conductively heated products, with anticipatory correction for cool-down lethality. A separate algorithm was used for convectively heated products. The on-line monitoring models that have been developed require prior knowledge of thermal difhsivity for the heating and cooling phases of the process (Teixeira et al., 1982; Datta et al., 1986). Variations in the proportions of ingredients of heterogeneous mixed food from one processing batch to another can cause significant deviations in the thermal properties of foods, which may lead to underor oversterilization. Ryniecki and Jayas (1993) have developed a method for automatic determination of model parameters for computer control of the sterilization of heterogeneous mixed food with an unknown thermal diffusivity value. This can be done prior to processing by sterilization of some of the test cans. This model was employed for prediction of the cumulative lethality contributed by the cooling portion of the sterilization process. This lethality was used in heating turnoff decisions. The model is fast and accurate for this purpose. It was validated in the laboratory using 5-9% bentonite suspensions. The final monitored cumulative lethality was within 18% of the desired cumulative lethality for these

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I

l

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l

l

l

P 9

SOLENOID VALVES

AM?LIFIBR

I’

1 I I

’ /

KEY

BOARD

DslluT

/

FIG.2. Block diagram of the retort control system.

I

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M. N. RAMESH et al.

suspensions. Lappo and Povey (1986) have developed a computer-based control system whose features include a modular design and the use of a high-level software language. The system is capable of following a prescribed time-temperature profile by altering its profile according to a computed Fo value. The Fo value is computed from any of 16 withincontainer temperature measurements or can be derived from retort temperatures. Control of pressure is also available during the cooling process in order to reduce stress on the container. Experimental data are presented to characterize the performance of the retort and instrumentation. The importance of instrumentation accuracy is discussed, and a computer calculation of heat penetration into a can is used to investigate the significance of errors in temperature screening with regard to process times. Completely automatic control of the retort heating profile is possible along with pressure control during cooling, so that on-line prediction and control of the Fo value is feasible. Also, a significant reduction in process time can be achieved by improving prediction of retort temperature measurement. Mihori et d.(19911 have developed an on-line control system that would achieve correct heat sterilization for conduction heating of food. The system collects a series of time-temperature data via a sensing probe during the early stages of the heating phase and analyzes the collected data for parameters of the conduction heating phase. During cooling, it integrates the lethality rate and determines the appropriate time to begin cooling to achieve a desired process lethality. This process has been validated by experiments. The advantage of this system is that it needs very little operator intervention and the process can be controlled independent of process deviations. Its limitations include the cost factor and maintenance requirements. The parameters to be controlled are to be predetermined. V. Computer-Aided Sterilization

M/s Steritech, a French company (Anon., 19951, in collaboration with the Agence Nationale de Valorisation de la Recherche, has developed a computer-controlled autoclave designed to conserve foods without much nutrient loss. Called Steritech, this system is equipped with a DOS software program that controls each phase of the sterilization process. The programming is flexible, and the process is interactive (to provide enhanced security). The computer and the autoclave maintain complete control over the sterilization process, which can be adapted to customer needs. As the temperature rises in the autoclave vessel, the quantity of steam injected is monitored and adjusted according to a

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number of criteria, including total product weight. The steam pressure inside the retort is also controlled. The computer continuously monitors and adjusts the opening of the proportional valve. At the start of the cooling phase, a powerful pump recycles the condensate at the bottom of the tank, resulting in savings in water usage. This patented system preheats the pressurized air to the temperature inside the autoclave before injecting it, which prevents thermal shock and ensures that the air will not expand. The calculated sterilization value (Fo)is integrated into the software, and sterilization automatically stops when the preset value is attained. Remote maintenance is performed by satellite by means of a modem equipped with software to access autoclaves anywhere in the world in real time. VI. Process Indicators

The determination of safe thermal process schedules is based on the time-temperature history at the cold point in packaged food. For still processing conditions, temperature monitoring can be easily established as it is static. However, for agitated forced convection-heated and particulate foods, identification of the cold point is rather difficult due to the practical difficulties involved in monitoring their temperature dynamic profiles. These difficulties have led investigators to assume still processing condition parameters with safety factors so as to compensate for uncertainty in particulate behavior (Pflug, 1987). Ronner (1990) has developed a bioindicator for monitoring and control of the sterilization process. Sastry et al. (1988) have developed bioindicators for verification and evaluation of thermal processing of particulate foods. Tobback et al. (1992) have described the application of immobilized enzymes as a time-temperature indicator system in thermal processing. Thus, the time-temperature indicator can be microbiological, enzyme-based, chemical, or physical systems and can be directly related to a change in any intrinsic food quality attribute. Much work has been targeted on the development of biological time-temperature indicators (TTIs) using immobilized enzymes. De Cordt et al. (1992) have developed one such TTI based on immobilized a-amylase on glass beads. This TTI can be employed in the range of 98-108°C and is only suitable for acid products below pH 4.6. The advantage of this device is that wireless measurements can be made. This is more vital for in-pack processing and for continuous aseptic processing of liquid foods. The feasibility of the use of TTIs with different carrier material has been discussed in detail by Maesmans et al. (1994a,b,c).

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M. N. W S H et a].

In addition, temperature measurement of moving particles is a serious problem, and aseptic processing of particulate foods relies on microbiological/biological validation (Dignen et a]., 1989). Problems associated with the use of microorganisms as bioindicators have been detailed in several studies (Weng et al., 1991a,b; Pflug and Odlaug, 1978; Berry et a]., 1989; Sastry eta]., 1988). The methodology, though, is subject to some inherent disadvantages: 1. Any TTIs used will have to be carefully calibrated with particular reference to the z and D values of the TTI with a known standard

for accurate measurement. 2. The TTIs have to be located in a carrier material. Such thermal and physical properties as conductivity, heat capacity, and density need to be precisely known. 3. These devices are not applicable to all temperature ranges. For example, biological TTIs will be more sensitive to more lethal temperatures than to low temperatures. A distinction can be made between two directions toward which evaluation of the impact of food preservation processes is moving (Hendrickx et al., 1995). 1. With the entry of food commodities prepared by combined processes

using different unit operations and various steps of food processing (like mixing, soaking, and drying) onto the market, evaluation procedures have to be developed to monitor food quality properties for which temperature is not the only rate-determining factor. A complete understanding and description of all the factors that influence the kinetics is necessary for development of “product history integrators” as suitable monitoring systems that give relevant information on the complete history, safety, and quality of the product. 2. For such “new” heating techniques as scraped surface heat exchangers and ohmic heating, the existing approaches are inadequate for particulate foods. Because of the technological difficulties involved in developing small-sized wireless data transmitters, rapid development of new and accurate TTIs is required to prevent modern heating techniques from eluding their marketplace. In general, process indicators quantify the integrated time-temperature impact on foods. Depending on the monitoring mechanism, process indicators can be subdivided into: 1) bioindicators, 2) color-based physical indicators, 3) chemical markers, and 4) electronic indicators.

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A. BIOINDICATORS

Food as such is nonhomogeneous, and the heating behavior of food is complex. It is practically impossible to determine the time-temperature curve and to identify the cold point in moving particulated foods, either due to agitation in the rotating retorts or in aseptic processing (Pflug and Odlaug, 1978). In such cases it is difficult to design, control, and verify the proper sterilization process. A bioindicator provides the required information and could be used as a tool to more accurately evaluate the impact of thermal processing on food (Weng et d.,1991a). Hendrickx et d. (1995) subdivided biological TTI systems into two categories: 1. Survivor-kill systems integrate the time-temperature history and indicate if a preset processing value is obtained or underprocessing has occurred depending on whether the microorganism systems are killed or have registered growth. By this method, if surviving organisms are present no conclusion can be drawn about the extent of heat treatment meted out to the product. 2. The count reduction approach, wherein the processing value can be

determined by the number of survivors.

An inoculated pack is a practical example of the use of a biological indicator unit. The initial concentration of the microorganism spores (lo8) contained in the food is raised to a detectable level of lo-" after heat treatment. In this way, an endpoint defined as a probable number can also be detected by or even of surviving units (PNSUs) of multiplying the initial spore load (No) of the food product (under normal conditions) by spore reduction (= NIN,) in the inoculated pack (Pflug, 1987). This is based on the assumption that increasing the concentration of spores will not alter their thermostability. An inoculated pack study is classified as a TTI approach and not as an in situ approach, because calibrated spores with known kinetic properties have to be used. They are not identical to the actual bioburden of the food: they are used to mimic inactivation of the bioburden. Whereas the inoculated pack was at first used to verify process calculations and heat-penetration measurements for still retorts, since the 1950s it has been applied to design and monitor heat sterilization processes in machines where it is almost impossible to determine the Fo value by physical-mathematical methods (Pflug, 1988). Different tools have been designed to control the location of microorganisms or their spores at a specified site in the food product instead of

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dispersing them over the entire contents of the can. Spore solutions have been enclosed in carrier units that largely simplify the recovery procedure after processing. A plastic rod filled with a calibrated B. stearothermophilus spore solution was suggested by Pflug (1976) that has been successfully used to validate sterilization processes for green beans and whole-kernel corn in a still retort and peas in brine in a Steritort. Sterilizing values determined from the physical-mathematical approach have been compared with their biological indicator units (BIUs) counterparts. These studies revealed that plastic rod BIUs can be used effectively to determine the sterilizing value given to cans processed in agitating retorts. According to Pflug et al. (1980), this method allows a routine determination of Fo with 15% accuracy. An aluminum biological indicator carrier has been proposed, as this material has the improved heat transfer characteristics and mechanical strength that is of particular importance in thermal processing of rapidly heating lowviscosity foods (Rodriguez and Teixeira, 1988; Smith et al., 1976, 1982). Paper strips inoculated with known amounts of spores are also employed for contamination-free test packaging. The problem with these biological thermocouples is that complete recovery of all heated organisms is not possible; in addition, the measurement is influenced by pH, the oxidation-reduction potential, the nutrient contents, etc. (Pflug et al., 1990). A bioindicator is encapsulated in a small vial and is placed at the cold point of the food package. This sensor is used to evaluate the lethality at that point during thermal processing. One of the bioindicators was commercially developed by the Swedish biotechnology company Diffchamb AB in Goteborg. This is an aqueous gel sphere in which specific microorganisms like the spores of B. stearothermophilus have been encapsulated. The sphere, which can be autoclaved, is surfacesterile and spore-tight. It possesses enough strength to allow passage through various types of process equipment. Mixed with food products, it can be treated during the sterilization or pasteurization process and later separated aseptically and cultivated in a nutrient solution. Should the heat treatment process prove to be insufficient, surviving microorganisms would bring about coloring of the gel sphere within 24 hours (Anon., 1990). Pflug et al. (1980) have carried out a series of experiments to evaluate the performance of plastic rod BIUs, which were used to measure the sterilization process to cans of food processed in a Steritort. The results indicated that BIUs can be used effectively to measure the Fo value

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delivered to containers of food heated in continuous agitating sterilization machines at an accuracy level that is essential on a par with that of time-temperature data. With the advent of aseptic processing, in the case of viscous liquid foods containing particulates, carrier systems for microbiological TTIs have been miniaturized to measure sterilization values under these conditions. Many small microbiological systems for determining the efficacy of in-pack sterilization have been studied. An overview of these systems is given in Table I11 (see Dignen et d., 1989). Various bioindicators used in different systems to evaluate thermal processing are indicated in Table IV. One advantage of using a microbiological TTI for monitoring the safety of a food product is that the temperature ranges in which the measuring device and target are sensitive to heat are equal, and in some cases the target and TTI may be identical. However, only calibrated microorganisms are to be used, and the heat inactivation kinetics of the microorganism have to be checked for the specific microorganism used in the TTIs. Also, using a microorganism to monitor the destruction of a quality attribute with specific kinetics (e.g., z = 10.C) is not sufficient, and not even tolerable. Without proper calibration in terms of D and z values in the actual heating, no conclusion can be drawn about the impact of heat treatment. Like any TTI, the biological TTI must have to comply with the basic requirement that z T T ~ = ztarget (Philipp and Sucker, 1990). Another advantage of the microbiological method is that heat penetration and thermal death time studies can be carried out simultaneously, thus eliminating some of the uncertainties involved in assembling the data obtained independently by these two types of studies. This method accounts for the effect of heat on the indicating microorganism at the scaled-up and as-applied states. This method is cost-effective and rapid. The results are easy to interpret and can be applied in both batch and continuous processes, that is, canning and aseptic processing (Anon., 1990). This can also serve as a complement to the instrument control system used for monitoring of sterilization of packaged containers. Only calibrated spores can be used to determine the killing power of the heat treatment. A biological indicator as such can never be a calibration standard from the methodology point of view. It will have to be validated first against a known physical standard (Pflug and Odlaug, 1986; Bruch, 1973, 1974).

332

M. N. W S H et al. TABLE 111 BIOINDICATORS EMPLOYING MICROSIZED MICROORGANISM-BASED TTIs ~

~

Carrier

Shape

Polymethylmethacrylate Alginate Glass Pea puree, meat puree Alginate Alginate + peach Polyacrylamide gel

Sphere Bead Bulb Cube Sphere Cube Sphere

Alginate + mushroom Alginate + potato puree Turkey Alginate + peach

Mushroom Cube Cube

~

~

Size (cm) 0.3 0.160.40

0.5 0.8-2.4

0.3 1.25

0.127

0.3-0.5

z value

Microorganism Bacillus anthracis B. stearothermophilus B. stearothermophilus B. stearothermophilus B. stearothermophilus B. stearothermophilus B. stearothermophilus B. subtilis E. polymyxa B. stearothennophilus Clostridium sporogenes C. sporogenes Z. bacilli

(“C) 60

8.5 10 11.4-1 1.8 9

N R ~ NR NR NR NR 12.5-12.7

8.5 NR

WR = not reported.

TABLE IV BIOINDICATORS USEDIN DIFFERENT SYSTEMS TO EVALUATE THERMAL PROCESSING OF FOODS Low-acids foods

B. stearothermophilus B. subtilis 5230 B. coagulans

Wet heat sterilization

C. sporogenes

Acid food pasteurization

Zygosaccharomyces bacilli

(60-65°C)

Pasteurization

Immobilized peroxidase (H,O,)

(95-100’C)

Continuous UHT processing

C. butyricum

B. COLOR-BASED PHYSICAL INDICATORS A color-based physical indicator is placed directly into the center of a can of food to determine heat penetration during processing. The indicator is held in a clear nylon pouch in a wire holder and placed in the test container before sealing. The nylon pouch permits penetration of the steam and yet provides protection for the indicator. The indicator

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is read after removal from the can. These indicators contain a chemically impregnated purple band that changes to green only if the process conditions are met. COOK-CHEX process indicators developed by Aseptic Thermo Co. are available for 14 different time-temperature conditions for all can sizes (Anon., 1972). It is a small and inexpensive device that indicates a time-temperature-dependent irreversible change that can be easily measured. This device mimics the change of a welldefined target quantity parameter of food undergoing the same variable temperature exposure (Taoukis and Labuza, 1989). Witonsky (1977) proposed a TTI that functions on a physical basis. A dry chemical in an embossed well of an aluminum plate is placed at the end of a paper wick. It is covered with a transparent film of known steam permeability. Steam permeating the film depresses the melting point of the colored chemical, and the molten chemical wicks up in the paper film, the distance of the color front from the base being a function of increasing temperature (Swartzel et al., 1991). The device could be calibrated in terms of Fo. The disadvantage of this device is that, as it is steam-activated, it cannot be used to monitor other types of heating media. Physical TTI systems are described as easy and accurate to prepare and calibrate, user-friendly in readout, and easy to recover. Further research should reveal physical phenomena with kinetic characteristics in the range of or equal to quality attribute inactivation in order to make such a system an interesting process evaluation tool. A retort temperature check card called TEMPILAQ has been developed by Williams (1969). It consists of a thick, colored bulb of known melting point. It is allowed to dry and is overlaid with thick porous paper (e.g.,Whatman no. 2 filter paper). As the temperature of the retort is raised, the color of the bulb is simultaneously developed. This only happens when the retort temperature reaches the set temperature. To prevent TEMPILAQ from soaking into the backing card, an aluminum foil interlayer can be used. TEMPILAQ lacquers with a wide range of melting points are available.

C. CHEMICAL MARKERS Selection of process parameters as well as the food particulate that will ensure commercial sterility at the cold point of the moving particulate is a challenging problem (Kim, 1994). The key processing parameters in a continuous thermal processing system are the temperature, flow rate, holding tube length, power setting, and conductivity of foods. A few alternatives like bioindicators and TTIs are available, as discussed earlier. However, instead of using external sources, it is better to use intrinsically formed compounds within the foods to demonstrate

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the sterility of thermally processed low-acid foods. Quantification of a microbiological TTI requires skills, and the analytical precision of the technique is rather low. The likelihood of contamination during microbiological sterility testing of foods has been recognized and documented (De Cordt et al., 1992). The inherent limitations of these methods for determining the efficacy of sterilization has prompted investigation of alternative approaches. These alternatives include chemical and physical TTIs and enzyme systems. For example, a covalently immobilized horseradish peroxidase together with an organic solvent was embedded in the food system and pasteurization efficiency aimed at destroying D-streptococci could be monitored in the temperature domain 65-90°C. These enzyme systems offer relatively easy readout and handling, which is a significant advantage over microbiological TTIs. The temperature domain wherein inactivation of enzyme occurs limits the monitoring of a sterilization process using these enzyme systems. Many methodologies have been attempted to assess the effect of heat treatment post facturn by monitoring the changing profile of innate biochemical markers. A commercial enzyme-monitoring system (Apizym, Analytlab Products) has been used to detect changes in the enzyme profile of meats before and after thermal processing (Townsend and Blankenship, 1987a,b; Brown, 1991). The enzyme fingerprint enables one to determine whether a specified temperature has been reached in the product. The result is dependent on the initial levels of enzyme, and the reproducibility of the results above 70°C is poor. Upper and lower limits of the temperature range are set by the biochemical markers, and conclusions on the degree of microbial destruction reached inside the product are hard to draw from these methodologies. Chemical TTIs detect a change in concentration of a chemical compound added to the food product to measure the efficacy of thermal processing. Thiamin mixed in beef puree and pea puree and added to peas-in-brine shows a reduction in its concentration after heat treatment. Even the thermal hydrolysis kinetics of disaccharides have been used for thermal evaluation. However, Wen Chin (1977), showed that the agreement was reasonable for processes with a negligible come-up time that were processed at a reference temperature of 121.l0C,whereas agreement was poor when the process had a considerable come-up time and thermal gradients throughout the system. A paper disk impregnated with reducing sugar and amino acid (Maillard's reaction) was employed by Favetto et al. (1988, 1989) to correlate the inactivation of foot-andmouth virus by monitoring the darkening of the disk. A disadvantage with such systems is the need to attach it to the packaging surface,

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which makes cold-point evaluation of the product impossible. There is an effort underway to predict impact on food safety by monitoring the response of the innate chemical constituents of food products (Kim and Taub, 1993). Thus, chemical TTIs offer high hopes as promising tools for evaluation of thermal process. The only, yet crucial, deficiency is that no reactions have been identified in the literature on heat treatments of foods that feature the temperature dependency (the z value or activation energy) required to monitor food safety in the sterilization temperature range, and only a few are available that can be used to follow the deterioration of other quality attributes. A conceptual ground for validating thermal processing using intrinsic chemical markers (ICMs) was defined, and three potentially useful markers have been selected (Kim et al., 1992; Kim and Taub, 1993).

The Methodology of Chemical Markers The food sample flows through the heat exchanger into the holding tube. Measurement of marker concentration (Ml, M2, or M3, based on the food constituent) can be made at the end of the holding tube. Since carbohydrates are commonly present in most foods, the change in carbohydrate profile is monitored using anion exclusion chromatography (AEC) separation and photodiode array (PDA) detection (which is sensitive in the UV region and has scanning capability). The UV absorption spectra of compounds eluted from the chromatographic column are obtained every 6 sec with the PDA detector, stored in the computer, and then manipulated for display as a three-dimensional (3D) representation, a contour map, a spectrum at a specific retention time, or a chromatogram at a specific wavelength. The AEC-PDA system consists of a Wescan (Derf 111) anion exclusion column (sulfonated polystyrene/divinylbenzene, 7.8 x 100 mm) and a Waters (Milford Man) 990 PDA detector. The heated food sample is homogenized for 1 min with a tenfold excess of water using polytron. The extract is centrifuged, filtered through a 0.45-pm membrane filter, and injected into the chromatography system through a-ZO/yl injection loop. The eluent used is a 0.01 Nsulfuric acid solution with a 1-ml/min flow rate (Kim and Taub, 1993).

The thermal reactions leading to formation of these markers are intrinsic to the food, that is, the new compounds are formed without adding any compounds prior to heating. The markers are easily detectable because their absorption maxima occur when the unheated foods show no absorption.

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Two of the markers, M1 and M3, were identified as 2,3-dihydro-3,5dihydroxy-6-methyl-4(H)-pyran-4-one (MW = 144) and 5-hydroxymethyl-furfural (MW = 126). It has also been shown that M2 has a similar molecular weight and is produced from a water-soluble component and protein. M1 is formed upon heating almost any food, including fruits and vegetables, meats, and starch-based foods. M2 is formed almost exclusively in meats, while M3 is formed in fruits and vegetables (Kim, 1994). Relating the marker yield to lethality is a nontrivial problem. The relationship is straightforward under isothermal conditions as long as the rate constants and the activation energies of microbial destruction and marker formation are accurately known. However, as the center temperature of a food particulate increases in the holding tube by heat conduction, a changing time-temperature condition has to be considered. A piece of meat is a typical particulate in an aseptically processed low-acid food. Formation of two markers (M1 and M2) has been verified in all the meats tested (Kim, 1994). Therefore, the two-marker approach appears promising for validating aseptically processed meat particulates. Kim (1994) has described a two-marker approach that uses the ratio of the yields of two markers and its potential application in ohmic heating, and microwave sterilization as well as conventional aseptic processing. Several chemical indices have been developed to optimize the heating process. Mulley et al. (1975) used thiamin hydrochloride. Textural change in meat was used as a heating index by Tennigen and Olstad (1979). Berry et al. (1989) studied the destruction kinetics of methyl methionine sulfonium (MMS) in buffer solutions and found it to be suitable for indexing microbial lethality. They recommended MMS as a substitute for microorganisms in thermal process evaluation. The activation energy associated with microorganisms is higher than that for nutrients and enzymes. Hence, for high-temperature short-time (HTST) processing it is better to use enzymes as indicators rather than microbial spores and nutrients. For vegetable processing, peroxidase inactivation is often used as an indicator because of its reported heat stability (Schwartz, 1992). Along similar lines, trypsin-a family of enzymes that preferentially catalyzes hydrolysis of ester and peptide bonds-has been used as a chemical marker. Awuah et al. (1993) have evaluated the possibility of using trypsin as a bioindicator for aseptic processing of high- and low-acid foods in the range of 90 to 130°C in tris-HC1 and citrate buffer. The decimal reduction equivalent heating times (EHTs) at 1 3 O O C of trypsin was 30.7 min at pH 6.0, 98.3 min at pH 5.1, and 135 min at pH 3.8, compared to 2.24 min for B. stearothermophilus. These EHT values

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are at the reference temperature of 121.l0C, which should be differentiated from decimal reduction at a particular condition. This gives a more realistic comparison of the inactivation behavior of various enzymes at different temperatures because the process times are based on Fo values calculated using a z value of 1O"C, whereas enzyme inactivation is characterized by its z and Do values. At lower temperatures, B. stearothermophilus has a higher thermal resistance of 11.4 min of EHT as compared to 0.4-2.4 min of EHT for trypsin. This trend reverses as processing temperature exceeds 12OoC, as is indicated in Fig. 3. Hence, at the high temperatures employed for aseptic processing, enzymes serve as better indicators for verification of the process (Awuah et al., 1993). The effect of temperature and pH on EHT value is shown in Table V. As the means of chemical detection have improved, considerable interest has arisen concerning chemical markers, that is, substances are formed naturally in foods at known rates during processing. It is hoped that measurement of such compounds can generate useful information about the time-temperature history of the food in a container during processing. Chemical markers function similarly to time-temperature indicators (Wells and Singh, 1988; Hendrickx et al., 1992) and are possibly of value in application to continuous retort systems or heat exchangers, holding tubes, and suspended particulate behavior in ultrahigh-temperature (UHT) processing (Sapru et al., 1992; David and Merson, 1990). There is a need to demonstrate the kind of information that can be obtained from chemical-marker measurements and to define the properties that such markers ought to have. For example, if the properties of a putative marker are known, it would be possible to decide whether measuring its yield would give adequate and reliable information about microbial destruction or inactivation. Ross (1993) worked on the relationship of bacterial destruction to chemical marker formation during thermal processing. Ramaswamy et al. (1995) used a chemical marker to measure holding tube lethality. Meat beads containing a glucose processor of a chemical marker and alginate beads containing the spores of B. stearothermophilus were prepared and subjected to steam heating at 110°C for selected time intervals. Marker yields were related to spore survival data and lethality values obtained from timetemperature data to generate calibration curves, as indicated in Table VI. Meatballs fabricated with meat (marker processor) and alginate (microbial spores) beads placed at the center were heated in continuously flowing CMC solutions (0.5% w/w) at 110 + 0.5"C in an aseptic

W W

co 1so

0

100

A

3

c

+

SO

x 0

0

2 n

L-

8

100

110

-m

1t o

1so

I40

(c)

FIG.3. Equivalent heating time (EHT) for a decimal reduction in activity of trypsin and selected bioindicators at various temperatures.

339

THERMAL PROCESSING OF FOODS, PART I1 TABLE V TIME-TEMPERATURE INACTIVATION OF ENZYME [TRYPSIN) IN DILUTE HCl AND CITRATE BUFFER Temperature (“Cl

D value (min)

3.8

90 100 110 120 130

279.7 144.0 68.9 31.5 18.4

2.45 2.16 1.84 1.50 1.26

5.1

90 100 110 120 130

132.0 72.8 50.8 22.8 11.7

2.12 1.86 1.71 1.36 1.07

6.0

90 100 110 120 130

33.3 27.9 11.8 8.5 3.4

1.52 1.45 1.07 0.93 0.53

PH

log D (min)

processing holding tube simulator. All treated samples were analyzed for marker yield as well as spore survival. As indicated in Table VI, the lethalities and spore count reductions in terms of Fvalues calculated from marker yield data showed excellent correlations with experimental values. These results indicate that the chemical markers have a potential to provide data on accumulated lethality and spore count reductions in aseptic processing systems where direct temperature determination at the center of a particle is difficult. Hence, with proper corrections, marker yield data could provide valuable input on produced process lethality and microbial spore count reduction. D. ELECTRONIC INDICATORS It is not practical to include thermocouples located in containers in a production system, and much research has gone into evaluating the alternatives for determination of temperature history during processing (Holdsworth, 1983). As a result, possible systems based on electronic memory or radiotelemetry have been extensively studied.

340

M. N. RAMESH et a]. TABLE VI CALIBRATION DATAFOR MARKER (Ml) AND MICROBIAL SPORE KILL

Heating

FOa

FOC (rnin)

time (rnin)

(min)

(aW

log N

2

0

0

5.76

0

0

10

0.45

0.004

5.58

0.18

0.14

20

1.23

0.19

4.96

0.80

0.63

M1

log(No/N)

30

2.0

0.042

3.98

1.78

1.40

40

2.78

0.068

2.32

3.44

2.71

50

3.56

0.10

1.0

4.76

3.76

‘Fo calculated using equation Fo = ji 10(T-nefl’zdt. h e a n of two measurements. “Fo calculated using DO(log(N0lN)).

A thermal memory cell (Swartzel et al., 1991) has been patented based on diffusion of ions in the insulator layer of a metal-insulator-semiconductor capacitor. The diffusion distance can be accurately read out by measuring the capacitance change of the cell before and after heat treatment. These authors claim that, by doping the insulator layer with at least two different mobile charge carriers of different activation energy and combining their readouts, conclusions can be drawn on the effect of the process on any food property, irrespective of their match with the kinetic characteristics (the E,, value) of ions used in the TTI. This is in contrast to the theoretical basis for proper TTI functioning. Advances in electrical circuit miniaturization have permitted the development of time-temperature memory devices for assessing thermal processing of packaged foods (Navankasattusas and Lund, 1978). Such a memory device consists of a temperature register module within an insulated container. This module is connected to a temperature transducer implanted inside a model food package. The module and model food package travel together through the continuous processing retorts, and the temperature history inside the model food package is registered at a constant preset time interval. As soon as the combined unit emerges from the retort, the module is connected to a temperature/accomplished lethality readout unit. Monitoring and control of a continuous processing unit by on-line measurement of accomplished lethality can also be made using a miniaturized lethality meter, without the display unit, in

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an insulated container. Wiring is eliminated by sending the lethality detector within an insulated container through the retort together with the model food package. The accomplished lethality is read out after the detector has traveled the entire path of the agitating retort, as with the system using the memory cell (Navankasattusas and Lund, 1978). The disadvantage of electronic memory is that it cannot be used for control, only for monitoring, whereas the radio telemetry-based system can be used for both. Sterility/lethality indicators that display the temperature in terms of lethality rates are available. They provide the advantage of direct display of lethality rates, thus eliminating transcription errors, but they have the disadvantage of not revealing the nature of heating or cooling. If the heating rate is uniform, this factor can be determined. However, for some types of products it is necessary to have more information because the slope of heating curve changes due to heating; that is, broken heating curves implying a change of heat transfer made from conduction to convection, or vice versa. A history of the time-temperature profile is very essential in calculating lethality rates. In addition, if time-temperature data are available, they can be used for calculation of process times for different-sized cans. Further, they provide the advantage of calculating process conditions at other temperatures (Holdsworth, 1983). VII. Suggestions for Future Work

Though on-line monitoring of sterility addresses the current needs of thermal processing to overcome process deviations, it does result in loss of products in the form of test cans. This poses a serious problem when highly valuable products are being processed, which can inhibit application of the approach. On-line control systems based on heat-transfer models provide solutions to overcome this limitation. However, these models require an accurate thermal diffusivity value for the food product. A better approach would be to combine nondestructive temperature sensing using heat-flux sensors mounted on the outside surface of the container with on-line determination of the thermal properties of the food during the initial stages of processing and application of the heat-transfer model. Though a few reports are available (e.g., Mihori et al., 1994; Watanabe et al., 1994), much needs to be done in this area. Although several researchers have pursued the legacy of the development of biological and chemical TTIs, a universal TTI has yet to have been developed. Calibrated microbiological TTIs have evoked much interest. With the advances in enzymatic and physical TTIs, renewed attention is being given to the possibilities and restrictions of these

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systems as TTIs in thermal processing of foods. There is need for better models to select a specific TTI for a food being processed, employing newer heating techniques like ohmic/microwave heating and scraped surface heat exchangers, and also for food with particulates, where existing approaches are inadequate. There is a need for the development of additional kinetic data and models, as determination of product temperature alone is not sufficient for ascertaining product quality. Such other factors as the physicalhhermal properties and the dynamic nature of the product should be considered in developing models for selecting TTIs. Though chemical markers offer an alternative for assessing the integrated time-temperature exposure of the food particulate, pertinent literary data are scarce and need to be developed. Since the intrinsic chemical-marker approach is safe, efforts should be made to commercialize the method in aseptic food processing. VIII. Conclusions

The production of sterilized foods requires that a product undergo a thermal process so as to render it microbiologically safe. Current practices in food industries for establishing process schedules require extensive heat-penetration experiments along with microbiological studies. Such a schedule is specific for each product-container-sterilizer combination. It is clear from the above discussions that on-line control systems facilitate optimum processing of foods and so ensure commercial sterility along with higher product quality and higher nutritional value as compared to conventional methods. On-line monitoring also allows processing times to be automatically adjusted to account for process deviations. On-line sterility monitoring ensures commercial sterility, which facilitates immediate release of processed products to consumers. On-line electronic control systems that employ thermocouples suffer the serious disadvantage of not being adaptable to aseptic processing due to the dynamic nature of the foods. Biological TTIs have the advantage of being able to be employed in HTST processing of foods. The applicability of TTIs for on-line monitoring of sterility in HTST processing indicates that the whole area of chemical indicators promises to be a fertile ground for researchers and patent hunters. The practical application of chemical TTIs is just the beginning. The use of a chemical index in sterilization processing has the potential of effecting a revolutionary change in the food and pharmaceutical industries (Mulley et al., 1975). A chemical marker-based TTI monitoring system can be encapsulated so that its kinetic charac-

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teristics can be determined independent of food composition, heating mode, or heating technology (Hendrickx et al., 1995). The concept of using intrinsic compounds developed during processing as internal time-temperature integrators is efficient and practical. These internally generated markers can be detected by spectrophotometry after their separation using anion-exclusion chromatography. Comparison of the relative marker concentration provides information on heat penetration within particulates. Also, the formation of these markers, which is associated with destruction of the bacterial population, facilitates computation of the sterility value of particulates subjected to thermal processing. Markers thus used could be applied to validate thermal processing of foods, particularly in aseptic food processing. Thus, these intrinsic markers are ideally suited to HTST profiles associated with conventional aseptic processing, ohmic-heated processing, and microwave-heated processing. When employed in food processing, intrinsic markers will assure the effectiveness of the process, so that the FDA should approve the process schedules developed using such TTIs. ACKNOWLEDGMENTS

The authors thank V. Prakash, Director of the Central Food Technological Research Institute, and A. Ramesh, N. G. Karanth, and R. Venkatakuppaiah, for their encouragement, and M. Asha, for her help in preparation of the manuscript. We also gratefully acknowledge the copyright permission granted by the different publishers for permitting us to utilize published material. REFERENCES Anon. (1972). Food Technol. 26, 18. Anon. (1990). Invention Intelligence 25, 155. Anon. (1995). Food Eng. Int. 20, 34. A m a h , G. B., Ramaswamy, H. S. Simpson, B. K., and Smith, J. P. (1993). 1.Food Processing Eng. 16,315. Berry, M. F., Singh, R. K., and Nelson, P. E. (1989). 1.Food Processing Preserv. 13,475. Brown, H. M. (1991). Tech. Memo No. 625, Campden Food and Drink Research Association, Chipping, UK. Bruch, C. W. (1973). Annu. 1.Pharm. Sci. NS2(1), 1. Bruch, C. W. (1974). Bull. Parenter. Drug Assoc. 28(3), 105. Datta, A. K., Teixeira, A. A., and Manson, J. E. (1986). J Food Sci. 51(2), 480. David, R. D., and Merson, R. L. (1990). 1.Food Sci. 55, 488. De Cordt, S. V., Van Hoof, K., Hu, J., Measmans, G., Hendrickx, M., and Tobback, P. (1992). Int. J. Food Sci. Technol. 27, 661.

344

M. N. RAMESH et 01.

Dignen, D. M., Berry, M. R., Pflug, I. J., and Gardine, T. D. (1989). Food Techno].43(3), 118.

Favetto, G. J., Chiriffe, J., Scorza, 0. C., and Hermida, C. A. (1988). J. Food Prot. 51(7), 542.

Favetto, G. J., Chiriffe, J., Scorza, 0. C., and Hermida, C. A. (1989). U.S. Pat. 4,834,017. Gill, T. A., Thompson, J. W., and Leblanc, B. (1985). Proc. Int. Congr. Eng. Food, 4th, Edmonton, Canada, p. 547. Hendrickx, M., Weng, Z., Maesmans, G., and Tobback, P. (1992). Int. J. Food Sci. Techno]. 27(1), 21.

Hendrickx, M., Maesmans, G., De Cordt, S., Noronaha, J., Vanloey, A., and Tobback, P. (1995). Crit. Rev. Food Sci. Nutr. 35(3), 231. Holdsworth, S. D. (1983). Process Biochem. 16(5), 24. Jairus, R. D., and Shoemaker, C. F. (1985). J. Food Sci. 50, 223. Kim, H. J. (1994). Activities of RbD Associates 46(1), 28. Kim, H. J., and Taub, I. A. (1993). Food Techno].47(1), 91. Kim, H. J., Taub, I. A., Richardson, M., Kustin, K., and Ross, E. (1992). Activities ofRbD Associates 44(1), 120. Lappo, B. P., and Povey, M. J. W. (1986). J. Food Eng. 5, 31. Maesmans, G. J., Hendrickx, M. E., De Cordt, S. V., and Tobback, P. (1994a). Food Res. Int. 27, 39. Maesmans, G. J., Hendrickx, M. E., De Cordt, S. V., Vanloey, A., Noronha, J., and Tobback, l? (1994b). Food Res. Int. 27, 413. Maesmans, G. J., Hendrickx, M. E., De Cordt, S. V., Vanloey, A., Noronha, J., and Tobback, P. ( 1 9 9 4 ~ )Food . Control 5(4), 249. May, N., and Withers, l? (1993). Food Techno].Int. Europe (1993 Annual), 97. Mihori, T., Watanbe, H., and Kaneko, S. (1991). J. Food Processing Preserv. 15, 135. Mihori, T., Xier, L., and Watanabe, H. (1994). Proc. ACoFOP Symp., 3rd, Paris. Mulley, A., Stumbo, C., and Hunting, W. (1975). J. Food Sci. 40, 993. Navankasattusas, S., and Lund, D. B. (1978). Food Techno].32(3), 79. Pflug, I. J. (1976). U.S. Pat. 3,960,670. Pflug, I. J. (1987). J. FoodProt. 50(4), 342. Pflug, I. J. (1988). Environmental Sterilization Laboratories, Minneapolis, MN. Pflug, I. J., and Odlaug, T. E. (1978). Food Techno].32(6), 63. Pflug, I. J., and Odlaug, T. E. (1986). J. Porenter. Sci. Technol. 40(5), 242. Pflug, I. J., Jones, A. T., and Blanchett, R. (1980). J. Food Sci. 45(4), 940. Pflug, I. J., Berry, M. R., and Dignen, B. (1990). J. Food Prot. 53(4), 312. Philipp, B., and Sucker, H. (1990). Phorm. Res. 7(12), 1273. Rarnaswamy, H. S., A m a h , G. B., Kim, H. J., and Choi, Y. M. (1995). Activities ofR@D Associates 47(3), 216. Ramesh, M. N., Kartik, V., Navneeth, L. V., and Bhanuprakash, K. N. (1994). Proc. Int. Con$ TEPEM 94,Madras, India. Rodriguez, A. C., and Teixeira, A. A. (1980). Trans. ASAE 31(4), 1233. Ronner, U. (1990). Food Techno].Int. Europe 90, 43. Ross, E. W. (1993). J. Food Processing Eng. 16, 247. Ryniecki, A., and Jayas, D. S. (1993). J. Food Eng. 19, 75. Sapru, V., Teixeira, A. A., Smerage, G. H., and Lindsay, J. A. (1992). J. Food Sci. 57, 1248. Sastry, S. K., Li, S. F., Patel, P., Konanayakam, M., Bafha, P., Doores, S., and Beelanan, R. B. (1988). J. Food Sci. 53(5), 1528. Schwartz, S. J. (1992). In “Advances in Aseptic Processing Technologies” (R. K. Singh and P. E. Nelson, eds.), p. 63. Elsevier Applied Science Publishers, New York.

THERMAL PROCESSING OF FOODS, PART I1

345

Skinner, R. (1975). Food Manuf. 50(10), 43. Smith, G., Pflug, I. J., and Chapman, P. (1976). Appl. Env. Microbiol. 32, 257. Smith, G., Kopelman, M., Jones, A., and Pflug, I. J. (1982). Appl. Env. Microbiol. 44, 12. Swartzel, K. R., Ganesan, S. G., Kuehn, R. T., Hamker, R. W., and Sadghi, F. (1991). U S . Pat. 5,021,981. Taoukis, P. S., and Labuza, T. P. (1989). J. Food Sci. 54(4), 783. Tennigen, A., and Olstad, S. (1979). In “Food Process Engineering,” Vol. 1: “Food Process Systems” (C. P. Linko, Y. Malkki, J. Olkku, and J. Larinkari, eds.), p. 146. Elsevier Applied Science Publications, London. Teixeira, A. A. (1995). Activities of R 6 D Associates 47(1), 205. Teixeira, A. A., and Manson, I. E. (1982). Food Technol. 36(4), 85. Tobback, P., Hendrickx, M. E., Weng, Z. M., Maesmans, G. J., and De Cordt, S. V. (1992). In “Advances in Food Engineering” (R. P. Singh and M. A. Wirakartakusumah, eds.), p. 561. CRC Press, Boca Raton, FL. Townsend, W. E., and Blankenship, L. C. (1987a). J. Food Sci. 52(2), 511. Townsend, W. E., and Blankenship, L. C. (1987b). 1.Food Sci. 52(62), 1445. Watanabe, H., Xier, L., and Mihori, T. (1994). Proc. ACoFOP Symp., 3rd, Paris, p. 375. Wells, J. H., and Singh, R. P. (1988). J. Food Sci. 53, 1866. Wen Chin, L. (1977). Ph.D. Dissertation, University of Massachusetts, Amherst. Weng, Z. M., Hendrickx, M., Measmans, G., and Tobback, P. (1991a). J. Food Sci.56, 567. Weng, Z. M., Hendrickx, M., Measmans, G., Gebruers, K., and Tobback, P. (1991b). 1.Food Sci. 56(2), 574. Witonsky, R. J. (1977). Bull. Parenter. Drug Assoc. 11(6), 274. Williams, M. L. B. (1969). Con. Inst. Food Technol. J. 2(4), 188.