Food testing Analysis May 2000 issue

The Search for Shelf Life

An update on continued efforts in understanding practical strategies for

determining and testing the shelf life of food products.

By Theodore P. Labuza, Ph.D.

Introduction

The drive by the food and beverage industry to achieve higher quality and

extended shelf life food products accelerated in the 1990s. Some of the contributing

factors in the search for improved shelf life include increased consumer demand for

fresh, convenient, safe and superior quality foods available year-round, and the

continued globalization of food distribution systems, which has placed pressure on the

food industry to ensure shelf stability and storage times as products travel further and

further from their place of origin.

But even as innovative packaging, new technologies and testing method

developments have spurred achievements for some food manufacturers in successfully

extending the shelf life of some products, most notably, fresh-cut salads, other

emerging pressures indicate that the need for improved shelf life testing and

assessment procedures is significant. One such trend is worth noting: the continued

introduction of legal drivers for shelf life testing. Although there is no federally

mandated, uniform open dating system, many U.S. government organizations have

ruled that certain foods must have some type of open date.[1,2] The European Union

also has such legislation in place for all food products.

For the food industry, meeting these ostensibly contrary objectives of consumer

demand for longer shelf life but minimally processed foods requires the implementation

of enhanced preservation parameters, improvement in testing and analytical

procedures, a better understanding of food quality factors as related to their

organoleptic characteristics, and continued education of scientists in food quality

modeling and accelerated shelf life testing (ASLT) procedures. This article will briefly

review the current state of shelf life determination testing methods, tools and

technologies employed to ensure that consumers receive high quality food products

with the added convenience of extended shelf life.

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Essential Factors of Shelf Life

The study of food preservation is not likely to produce clear-cut results for

across-the-board application, primarily because foods are very complex, active

systems. To attain knowledge of a foods expected shelf life, one must understand the

microbiological, enzymatic and physicochemical reactions that simultaneously take

place in any given food, identify the mechanisms responsible for spoilage or loss of

desirable characteristics such as flavor, odor or nutrients, and implement scientific

models for estimating the period it will retain an acceptable level of eating quality from a

safety and organoleptic perspective.

The four critical factors in this endeavor are formulation, processing, packaging

and storage conditions, and their relative impact depends on the perishability of the

food. In general, most perishable foods that are properly stored have under 14 days of

shelf life, which is limited in most cases by biochemical (enzymatic/senescence) or

microbial decay. With new aseptic technology, irradiation or high pressure processing,

as well as controlled atmosphere/modified atmosphere packaging (CAP/MAP), such

foods may last up to 90 days. Properly stored semi-perishable foods, such as some

cheeses and frozen desserts, have a shelf life of up to 6 months, while shelf-stable

foods, such as most canned goods, last more than six months and as long as three

years under proper storage conditions.

An understanding of the interplay between these factors is key to shelf life

estimation and testing. For example, a change in a single processing parameter may

lead to undesirable chemical or physical changes in a product, or it may require

reformulation or a change in packaging in order to attain the required shelf life. Similarly,

the very act of processing may subject the formulated materials and ingredients to

conditions that are unfavorable or inhibitory to undesirable deteriorative reactions and

promotive to desirable physical and chemical changes thus giving the food product its

final form and characteristics. And, once the food leaves the processing stage, its

keeping properties and the extent to which it will retain its intended attributes is a

function of its microenvironment. The important parameters are gas composition

(oxygen, carbon dioxide, inert gases, ethylene, and so on), the relative humidity (RH),

pressure or mechanical stresses, light and temperature. These parameters are

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dependent on two of the other critical factors: packaging and storage conditions.

Appropriate shelf life testing is normally required to take into account the different

scenarios brought about by this interplay.

Of course, the real-world pressure on the product development scientist is to

provide a good guesstimate on product shelf life in the face of very real time

constraints placed on him by marketing and research and development (R&D)

managers. These food scientists gather information on the specific processing method

to be employed, the types of raw materials and functional ingredients used, prior

experience with similar formulations, packaging, and so on, and perform confined

experiments under abuse conditions to extrapolate limited data to the projected shelf life

in order to answer the basic questions, "What is the shelf life of the food?" and "Will it

reach the consumer in acceptable quality?"

There are several established approaches to gathering this information, including

estimating shelf life based on published data, utilizing known distribution times for

similar products on the market, or using consumer complaints as the basis for

determining if a problem is occurring. These methods have their downsides, however,

including the fact that most shelf life data on specific engineered foods is proprietary,

similar products to benchmark against do not exist, or there is no information on actual

consumer home storage times. If one is confident in a product's shelf life or it is already

in the marketplace, one can use a distribution test method. Product is collected at

supermarket sites and stored in the lab under home-use conditions. Only one such

study has been reported in the literature, although this method has been used by

others, especially in cases when states or countries instituted new open dating

legislation.[3,4] This method results in the product shelf life based on both distribution

and home storage conditions. The most frequently used methodology is accelerated

shelf life testing (ASLT), where the objective is to store the finished product/package

combination under some abuse condition, examine the product periodically until end of

shelf life occurs, and then use this data to project shelf life under true distribution

conditions.[5] Of course, ASLT has garnered much attention in the last 20 years or

more, since it offers a way to estimate shelf life without having to wait from one to two

years for the answer.

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Modeling for Shelf-Life Estimation and ASLT

Selecting an appropriate, reliable approach to modeling quality loss of a food

product is an important first step in estimating shelf life, and allows for the efficient

design of appropriate shelf life tests. Shelf life predictions are based on fundamental

principles of food quality loss modeling, primarily kinetic modeling of different

deterioration mechanisms that occur in food systems, which have been detailed

extensively in the literature.[6-19] A general equation describing quality loss in a food

system may be expressed as: rQ = [phi](Ci, Ej), which states that the rate of quality

degradation (rQ) is a function of a number of composition factors (Ci), such as

concentration of reactive species, microorganism levels, catalysts, reaction inhibitors,

pH and water activity, as well as environmental factors (Ej) such as temperature,

relative humidity, light, mechanical stress and total pressure. Following modeling,

desirable and undesirable quality factors then can be measured using chemical,

physical, microbiological or sensory parameters.

Environmental factors can significantly affect the rates of the reactions and need

to be defined and closely monitored during kinetic experiments. A kinetic model for

quality loss is not only particular to the studied food system, but also to the set of

environmental conditions of the experiment, including the permeability of the packaging

material. It would be desirable to generalize the models so that they include, as

parameters, the environmental factors that more strongly affect the quality loss rates

and which are susceptible to variation during the life of the food. Some of these

important factors in food preservation and quality are detailed.

Temperature. The important effect of temperature on reaction rates has long

been recognized. Generally, reaction rates increase with increasing temperatures. The

most prevalent and widely used model is the Arrhenius relation, derived from

thermodynamic laws as well as statistical mechanics principles. The Arrhenius relation,

developed theoretically for reversible molecular chemical reactions, has been

experimentally shown to hold empirically for a number of more complex chemical and

physical phenomena (e.g., viscosity, diffusion, sorption). Food quality loss reactions

described by the kinetic models have also been shown to follow an Arrhenius behaviour

with temperature.

An alternative way of expressing temperature dependence which has been

extensively used by the food industry is the Q10 approach. Q10 is defined as the ratio of

the reaction rate constants at temperatures differing by 10C. This model can be used

to describe how much faster a reaction will go if the product is held at some other

temperature, including high abuse temperatures. If the temperature-accelerating factor

is given, then extrapolation to lower temperatures, such as those found during

distribution, may be used to predicted expected product shelf life. This is the principle

behind accelerated shelf life testing.

ASLT, as described previously, involves the use of higher testing temperatures in

food quality loss and shelf life experiments and extrapolation of the results to regular

storage conditions through the use of the Arrhenius equation, which cuts downtesting

time substantially. A reaction of an average E[[A]] of 20 kcal/mol may be accelerated by

nine to 13 times with a 20C increase in the testing temperature, depending on the

temperature zone.[15] This principle and the methodology in conducting effective

ASLTs are described in the literature.[6,20]. However, caution should be exercised

when interpreting results and extrapolating data to other conditions. For example, when

the product/package system is tested, the package also controls shelf life so that the

true shelf life of the food itself is unknown; thus, if a new package with different

permeabilities to oxygen, water, or carbon dioxide is chosen, the prior results may not

be applicable. If the ASLT conditions are chosen properly, however, and the appropriate

algorithms for extrapolation are used, then shelf life under any "known" distribution

should be predictable.

A few other practical problems that may arise in the use of ASLT conditions

include, but are not limited to:

Error may occur in analytical or sensory evaluation. Generally, any analytical

measurement should have a variability of less than 10% to minimize prediction errors.

Generally, as temperature rises, phase changes may occur which can

accelerate certain reactions, such as fat changing from a solid to liquid. Thus, the actual

shelf life at the lower temperature may be shorter than predicted. However, it has been

known since 1990 that for dry foods with a given moisture content put at a higher

temperature (above the glass transition temperature), the projection of shelf life using a

shelf life plot to room temperature storage could be wrong, resulting in either a

prediction of greater or shorter time than actual shelf life. This has opened the door for a

whole set of new laboratory testing procedures such as measuring the glass transition

using differential scanning calorimetry (DSC), or by some thermal rheological method

like dynamic mechanical analysis (DMA) or dynamic mechanical thermal analysis

(DMTA). Some instrument companies have developed measurement technologies in

these areas, notably in DSC (Perkin-Elmer, TA Instruments), DMTA (Rheometrix) , and

DMA (Perkin-Elmer).

Upon freezing, such as used for storage of control samples, reactants are

concentrated in the unfrozen liquid, creating a higher rate of quality loss at certain

temperatures, which is unaccounted for by the Q[[10]] value, and will cause prediction

errors.

If high enough temperatures are used, proteins may become denatured. This

can result in both increases and decreases in the reaction rate of certain amino acid

side-chains and thus cause either under- or overprediction of true shelf life.

The solubility of gases, expecially oxygen, in fat or water decreases by almost

25% for each 10C rise in temperature. An oxidative reaction (loss of Vitamin E, A, C or

linoleic acid) can increase in rate if oxygen availability is the limiting factor. Thus, at the

higher temperature, the rate will be lower than the theoretical rate, resulting in

underprediction of true shelf life at normal storage temperature.

Other Environmental Factors. The relative humidity of the immediate

environment which directly affects the moisture content and water activity (a[[w]]) of a

food is the second most important environmental factor that affects the rate of food

deterioration reactions.[21] Water activity describes a thermodynamic energy property

of water in the food, and in part, acts as a solvent and participates in chemical

reactions.[22] Although a higher a[[w]] does not necessarily mean a faster reaction rate,

critical levels of a[[w]] can be established above which undesirable factors that lead to

the deterioration of food occurs, such as microbial growth or textural changes.

Controlling the a[[w]] is the basis for preservation of dry and intermediate moisture

foods.[23] Besides the specific critical a[[w]] limits, water activity has a pronounced

effect on chemical reactions in these foods. Generally, the ability of water to act as a

solvent, reaction medium and as a reactant itself increases with increasing a[[w]] up to a

point, and then other factors decrease reaction rates. As a result, many deteriorative

reactions increase exponentially in rate with increasing a[[w]] above the value

corresponding to the monolayer moisture, the value at which most reactions have a

minimum rate. For example, if one has a wet food and tries to dehydrate it to different

water activities, from the wet state, in fact, the reaction rate will increase, reach a

maxima, and then decrease. Thus, as you remove water and lower the water activity,

the rates do not decrease, they can actually increase first. This is a key concept from

the standpoint of intermediate moisture foods, for example, especially with regard to

many food products in the nutraceutical field like semi-soft food bars, which are

generally in a water activity range where rates of deterioration are very high. For lipid

oxidation, the rate increases again as the a[[w]] decreases below the monolayer, and for

most aqueous phase reactions, one rate decreases again above a certain a[[w]] in the

0.6 to 0.8 range.

Mathematical models that incorporate the effect of a[[w]] as an additional

parameter can be used for shelf life predictions of moisture-sensitive foods. Also, ASLT

methods have been used to predict shelf life at normal conditions based on data

collected at high temperature and high humidity conditions.[24]

Understanding gas composition, which is also a factor that may play a significant

role in some quality loss reactions, is important but not clearly understood or

researched. Oxygen availability is very important for oxidative reactions and can affect

both the rate and reaction apparent order, depending upon whether it is limiting or in

excess.[13] It also affects the respiration rates and senescence of plant materials and

microbial growth depending on the redox potential. Vacuum packaging and nitrogen

flushing is based on slowing down undesirable reactions by limiting the availability of

O2. Further, the presence and relative amount of other gases, especially carbon dioxide,

strongly affects biological and microbial reactions in fresh meat and fruit and

vegetables. The mode of action of CO2 has not been completely elucidated, but is partly

connected to surface acidification.[25] Different commodities have different optimum O2-

CO2-N2 gas composition requirements for maximum shelf life. Excess CO2 in many

cases is detrimental. Other important gases are ethylene and CO. Controlled and

modified atmosphere packaging are based on these principles. Ideally by selecting a

packaging material with the desirable permeance properties, the concentration of gases

and the RH inside the package can be kept within predictable limits determined by the

conditions set at processing. Gas transport models that incorporate the oxygen uptake

and CO2 generation by the food allow the calculation of packaging requirements.

Unfortunately, very few, if any, polymer films satisfy the requirements for both O2 and

CO2 control.

One key problem in gas composition analysis is that analysts will flush with a

certain gas, but because films are permeable to gases and some gases may react with

a food (i.e., CO[[2]] may dissolve in the food or oxygen may be used up in oxidation

reactions), it is very possible for the gas composition to change over time. Therefore, it

is important to know what those changes are. What one would like to know is the steady

state composition, because eventually there is a balance between what is ingressing or

egressing out of the package and what is reacting with the package. Many scientists,

including the author, are currently working to develop a scientific method for this.

Currently, a major study is being conducted at the University of Minnesota (UM) on

carbon dioxide degassing from fresh roasted ground coffee. Many coffee manufacturers

are changing to incorporate flexible packages, and if one does not control the package

permeability, the amount of coffee, and so on, there is bursting of the package. What

the UM researchers are trying to do is determine the equlilibrium compoisiton of gas, so

that if one flushes it, there will be equilibrium with the dissolved gas and there would be

no emission from the food. This is unique to coffee, but provides a good example of why

the knowledge of the film permeability is key. Certainly, instrumentation that can

measure gas composition by probing into the package is an important tool in these

efforts (Mocon Instruments, Cole-Parmer).

Quality Indices Used in Shelf Life Testing

Obtaining a reliable approach to modeling quality loss of a food product is based

on defining an appropriate index that measures, or directly corresponds to, food quality.

Again, shelf life can be defined as the time until a product becomes unacceptable to

consumers under a given storage condition. These indices include sensory evaluation,

as well as chemical, microbiological and physical testing through instrumental or

classical methods. The quality indices used most commonly today in shelf life and

storage studies are detailed below.

Sensory Evaluation. Sensory evaluation by a trained panel usually gives a good

estimate of the overall quality state of a food. One approach in sensory testing is to try

to determine, at a certain level of probability, whether a product has changed (difference

tests). Hence, this approach gives "endpoint" information and does not allow for

modeling quality loss with time. Hedonic testing is a somewhat different approach that

to attempts to model the progressive loss of overall quality characteristics, using a

graded hedonic scale. If hedonic testing is properly conducted, the value of the

perception (y) can be used as a quality index and plotted against time (t). However, for

hedonic testing, the requirements on the sensory panel for uniformity, experience and

size are stricter than the difference tests and often these requirements are not met,

resulting in unreliable data. Another problem with this approach is the considerable

difficulty in establishing a meaningful scale for each food productan expert panel is

not necessarily representative of consumers, let alone different consumer

segments.[26] Even if that assumption can be made, a cut-off level of acceptability has

to be decided upon.

A usual approach to sensory testing is to assign the zero time value as 100%

and the end of shelf life value as 0% quality, and thus the times in between correspond

proportionally to different levels of quality. This is based on the assumption that the

sensory response is linear with time, which is often not true. Typically, however, industry

does not test to determine end of shelf life. Hedonic or difference sensory testing, for

example, are too variable, which makes getting a good endpoint difficult. To illustrate

this, one might place a box of cereal in the freezer and another on the counter a room

temperature. In the morning, the person takes the cereal out of the freezer, pours some

flakes into a bowl and tastes them. Next the person takes the cereal from the counter,

pours the flakes into a different bowl, and tastes them. Now, the person tries to

determine whether there is any flavor difference between them, and if there is a

detectable difference, then he knows that the room temperature cereal has reached the

end of its shelf life. But the consumer does not do this in the real world. With the

exception of rapid decay foodsrefrigerated products like milkthe consumer is not

going to be able to detect a sensory difference from day-to-day in shelf-stable items

such as cereal or canned soup. Hence, typical sensory testing using hedonics or

difference testing is not going to give you a consistently accurate view of shelf life for a

given product.

Weibull Hazard Method. While there are different statistical and graphical

approaches for using sensory data in shelf life testing, this maximum likelihood

graphical procedure has been increasingly used with good results in the food

industry.[3-4, 27] In fact, it was not that long ago that the Weibull Hazard Method was

almost exclusively used in the chemical and pharmaceutical industries as a good

systematic approach to sensory testing.[19] The Weibull method is simple in that it asks

only, "Is the product acceptable?" The intensity of testing is increased near the end of

shelf life, so that a true shelf life is determined. Data analysis involves plotting hazard

values versus time and using the Weibull distribution to determine shelf life equal to the

time at which 50% of consumers find product unacceptable. Essentially, then, if all of

the food product from a given days production was magically distributed, ended up on

the table in the home at the same time, and everyone in the home tasted the product,

the Weibull concept states that, at that time, 50% of the tasters would say that the

product is not of good quality. The value of the Weibull plot as a tool is that one can see

a truer picture of the logistics in distribution. [If one wants to get the product in the

home and consumed at only 1%, which is a shorter time, but at 1% I am not going

to displease many people and if I get 95% of my product through in that time Ive

got a pretty good deal, so now the rest of that product is going to be consumed

later and later so theres a logrithmic probability of failure as I go out for a longer

and longer time.]

No one yet in the food industry is combining this method with their logistics

management activities, however. Although the Weibull method is based on sound

statistical approaches and several groups have used the method with great

successnotably, luncheon meats,[3] cassava flour,[28] breakfast cereal,[29], ice

cream,[30] refrigerated meats,[31] frozen foods,[32] cottage cheese,[33] pasteurized

milk,[34] and sausages,[35] sensory scientists have not embraced it, nor is it taught

regularly as part of food science sensory curricula. However, with modifications to

Gaculas original method, the method does offer a good alternative that smaller food

companies can use very easily without maintaining a sophisticated sensory panel.

In two papers currently under review, the application of Weibull Hazard Analysis

to milk and coffee illustrates this procedures usefulness.[36,37] In the case of milk, a

study was conducted to determine whether or not a consumer determined end of

sensory shelf life could be described by some microbial index, regardless of the

temperature conditions at which the milk is stored. While the shelf life of pasteurized

milk is traditionally estimated by the counts of both total and psychrotrophic microbial

load, the values reported to date for both microbial populations at the end of the sensory

shelf life of milk are not consistent. Using the Weibull Hazard Method, the study

examined the relation between the total and psychrotophic microbial growth in milk and

its sensory shelf life. Milk was stored at five constant temperatures (2, 5, 7, 12, and

15 C) and both total and psychrotrophic microbial counts were enumerated using 3M

Petrifilm (3M Co., St. Paul, MN) to obtain the lag time and the growth rate values. A

TempTale (Sensitech, Beverly, MA) temperature recorder, placed in the coolers along

with the milk verified the temperature history. The lag time of the total and

psychrotrophic growth responded to temperature following the Arrhenius equation. The

loss of sensory quality of the milk followed a log shelf life versus temperature

dependency. It was shown that the sensory quality of milk is more sensitive to

temperature than the lag time of the microbial populations, and that the microbial count

at the sensory end of shelf life is poorly correlated with the sensory shelf life. It is

therefore suggested that sensory testing, not microbial plate counts, be used to

determine the sensory shelf life of milk. The Weibull method gave end of shelf life

values fairly similar to that of prior work using the ADSA sensory scoring method using

two to three expert panelists.

In the second study, shelf life results for roasted and ground coffee were

obtained with the Weibull Hazard method. In this case, the focus was to determine the

effect of oxygen, a[[w]] and temperature on shelf life. Roasted and ground coffee was

stored at constant O[[2]] (0.5-21%), a[[w]] (0.106-0.408) and temperature (4-35oC).

Samples of roasted ground coffee were removed at each sampling time, weighed on a

balance (Mettler-Toledo, Hightstown, NJ) and brewed with 1L of bottled drinking water

using standard coffee filter paper in a table top coffee maker. The brewed coffee was

kept in thermos jars, poured into pre-warmed ceramic cups and covered with aluminum

foil. Samples were then identified with random numbers and served to untrained tasters.

The results were transferred to a master spreadsheet for hazard calculation and then to

a Weibull Hazard plot. Product acceptability was monitored by use of a modified Weibull

Hazard sensory method in which end of shelf life was the time at which 50% of the

untrained tasters found the product unacceptable. The effect of O[[2]], a[[w]] and

temperature was studied from a kinetics standpoint. The shelf life was studied at

different oxygen levels between 0.5 to 21%, and it was found that the higher the oxygen

level, the faster the loss of shelf life, and therefore, the difference between the low

oxygen versus air was 20-fold shelf life. A water activity increase of 0.1 led to a 60%

increase in the rate of deterioration, suggesting that non-enzymatic browning activity is

also occurring, while a temperature increase of 10oC raised the rate of deterioration

about 15-23%. The activation energy for shelf life was @ 3 kcal/mole, indicating diffusion

within the glassy matrix is controlling deterioration.

These two studies, one on microbial/enzymatic decay and the other on

oxidation/Maillard browning, indicate that the Weibull method for sensory end of shelf

life can be applied to simplify shelf life determination of a complex food system.

While typical sensory evaluation data is widely used and accepted in shelf life

determination, some of the inherent problems belie total reliance for accurate

assessments. Some of the more apparent problems include the high cost of using large

testing panels, issues surrounding panelists tasting spoiled or potentially hazardous

samples, and the fact that sensory data are not "objective" enough for regulatory

compliance or legal actions. These are some of the reasons that make evident the need

for alternative techniques using chemical and other indices for evaluating quality.[38]

Instrumental Measurements. Chemical, microbiological and physical tests are

widely used in the study of food quality. Characteristics used by the consumer for

evaluation of a product, such as flavor, color and textural properties can be measured

instrumentally or chemically. Careful evaluation of the chemical and biological reactions

and physical changes that occur in the food during and after processing, based on the

accumulated knowledge in food science, allows the recognition of the ones that are

most important to its safety, integrity and overall quality.[6] Physicochemical or

microbiological parameters can be used to evaluate quality. The values of these

parameters can be correlated to sensory results for the same food and a limit that

corresponds to the lowest acceptable organoleptic quality can be set.

Chemical and Physical Property Tests. There are a variety of chemical and

physical property test methods and instrumentation that can provide shelf life scientists

with usable sensory data. In Europe, scientists commonly use pentane in headspace for

cereal products; in the U.S. hexanal is used. General Mills was a leader in developing

standards for both pentane and hexanal use as a shelf life determination method for

cereals. Another good chemical method, although not used to a great extent today, is

the determination of peroxide value. However, the key to this approach is to check

product often, because peroxides follow a lag phase with a rapid increase where they

reach a peak and then descend to zero. Thus, if the researcher checks peroxides at

zero time at three months and six months, she may not be able to measure any

discernable differences and conclude that it isnt oxidizing, when in fact, between three

and six months, the value rose to its peak and descended again. Peroxide value

requires more analysis, then, but its usefulness lies in the fact that end of shelf life

typically occurs somewhere around 25-50% of the peak.

Oxygen uptake is another method used in shelf life determination, although the

problem with its use is that the industry doesnt have a specified number stating that at

so many ccs of oxygen per gram of food is the point at which end of shelf life occurs for

different foods. This method has only been used for three foodspotato chips, freeze-

dried shrimp and coffee.

In terms of determining shelf life for legal/regulatory compliance, the analysis of

Vitamin C and Vitamin A for the nutritional label is another important area. Essentially,

there are two standards of analysis: one for natural foods (i.e., peas), where 80 % of the

samples you take must meet 80% or more of the label value; and one for products that

have been fortified with vitamins and minerals, which must meet the label value in 100%

of the samples. High-performance liquid chromatography (HPLC) is very useful in

determining Vitamins A and C. Also, in specific products, the loss of even one

compound can impact sensory characterisicsthe best example of this is

aspertameand again, HPLC has proved to be a good tool in these cases, as well.

In addition, some new or improved instrumental techniques have emerged that

also assist in the determination of organoleptic characteristic determination to aid in the

prediction of shelf life in foods. These include:

Electronic nose. Although it has yet to be clearly established as a viable

instrument, the electronic nose employs an interesting paradigm of sensors that

respond to compounds in the headspace while utilizing a neural network learning

process. This can be very useful in cases in which the a[[w]] in a food product is low, but

it should be noted that the a[[w]] can affect response significantly.

Texture analyzers. One of the valuable instruments that has come to the fore in

this area in the last five years is the availability of miniaturized texture analyzers (TA

Instruments, Instron Corp.).

Colorimeters. These instruments are useful because they operate on the LAB

scale, which measures three-dimensional space. There are two types available: those

that measure large samples (HunterLab, Brinkmann), and portable colorimeters that

enable measurements in a very small range (Minolta).

Rheology instruments. As noted earlier, rheometry is a useful technique for

accelerated shelf life testing. These can be used for characterizing foods, food

additives, ingredients and packaging materials. Many are of these are controlled stress

rheometers, which enables measurement of important viscoelastic characteristics and

provides data on texture perception, thermal processing effects and storage stability

(ATS Rheosystems, TA Instruments, Haake, Bohlin, Rheometrix).

Powder X-ray diffraction (XRD). Although this has not been applied to a great

extent in the food industry, powder XRD is very useful for determining the level of

caking in powders by measuring the degree of crystallinity.

Microbiological Tests. With regard to microbiological shelf life testing,

investigators are primarily interested in pathogenic and spoilage microorganisms and

toxins. As discussed, the consumer push for more minimally processed fresh and

refrigerated foods and convenient ready-to-eat meals, coupled with food scientists

better understanding in recent years that pathogenic bacteria can grow in refrigerated

temperatures, has resulted in an increase of concern in this area. According to a recent

Institute of Food Technologists (IFT) Status Summary on the microbiological concerns

of extended shelf life refrigerated foods such as ready-to-eat luncheon meats and

complete heat-and-eat meals, psychrotrophic and mesophilic pathogens are of primary

concern, since they are able to grow during temperature abuse or extended storage.[39]

In these cases, determining what the potential for psychrotropic microorganism growth

in a refrigerated storage peiod, as well as its impact on organoleptic quality or spoilage

in a food, for example, is important in estimating microbial shelf life of a food product.

Some of the microorganisms of current interest include Listeria spp., enteropathogenic

Escherichia coli, Yersinia enterocolitica, and some strains of Clostridium botulinium and

Bacillus cereus. In addition, some types of yeasts, molds and psychrotrophic

bacterialactic acid bacteria (LAB), Pseudomonas spp., and Microbacterium

spp.may grow to high enough levels to cause spoilage even in sufficiently refrigerated

temperatures for the proper amount of time.

Certainly, from a pathogen standpoint, there are several newer, highly sensitive,

rapid microbiological methods and automated systems available, many of which can be

applied in shelf life determination/prediction applications.[40,41] Impedance and

conductance systems can be used to detect poor quality or substandard samples in less

than eight hours, and are used widely in the food industry, especially in Europe

(BioMerieux Bactometer, Malthus IDG). Biochemical methods based on the presence of

the lipospolysaccaride of gram-negative limulus amoebocyte lysate (LAL), for example,

are rapid tests for screening gram-negative spoilage bacteria in milk, meats, fish and

food ingredients. Even adenosine triphosphate (ATP)-based assay tests can be used

for quick detection of contamination and shelf life prediction (Celsis Pasteurized Milk

Screen). Food microbiologists who want to predict the growth of microorganisms for

food spoilage also use the results of routine standard plate count or rapid automated

plate count methods to measure the state of decomposition or the degree of freshness

of a food.

It should be noted that, technically, if a pathogen is detected in the food, that food

is illegal under the Food Drug & Cosmetic Act (FDCA), which states that a food is

adulterated if it may cause injury to health. The FDCA does not establish numerical

tolerances. In the last few months, the U.S. Department of Agriculture (USDA) issued

Federal Register notices stating that if E. coli O157:H7 or Listeria monocytogenes is

detected, then the food product is illegal. However, with the advent of rapid methods

such as enzyme-linked immunosorbent assays (ELISAs), DNA probes, automated

polymerase chain reaction (PCR) and bacteriophage technologies that allow microbial

detection at lower and lower levels, food regulatory agencies will feel increased

pressure to establish these numbers. In addition, some rapid microbial system

manufacturers now claim that newer methods enable users to detect one pathogen in

350 grams of food. Currently, the standard in the FDA milk compliance policy guide, for

example, is one pathogen in 25 grams. Again, these better analytical capabilities raise a

real question in terms of regulatory control in the future.

Real-World Shelf Life Technologies

The work performed at the food company to determine, test and even extend the shelf life of

consumers must then take proper measures to ensure that the food is handled properly.

Part of a recent survey conducted by researchers under the auspices of The Retail

Food Industry Center at the University of Minnesota suggests that consumer confusion

about the shelf life of perishable foods centers on open dating practices. The two-part

survey, Perishable Refrigerated Products and Home Practices Survey, reported that

while open dating can be used as an indication of freshness on food products and that

many consumers use the dates when making purchasing decisions, many do not

understand their meanings.[42] Notably, although all of the respondents looked at the

open dates to some degree, the misconceptions regarding its meanings continued.

Today, for example, fewer people seem to understand the meaning of the open date on

milk containers than 20 years ago, despite the fact that it is the product which

consumers most often check for a date. Most consumers surveyed believed the date is

somewhat to extremely reliable, and 63% of respondents often or always sort

through open dated products to find foods with the longest number of days left

according to its given date. This is in spite of the fact that 36% of respondents had

purchased one of the listed food products within the past year which had spoiled before

the given date.

In addition to concluding that federally regulated, uniform open dating system is

necessary to make the practice more consistent and consumer-friendly, the survey also

emphasizes that while open dates can not guarantee a products safety, used in

conjunction with time-temperature integrators (TTIs), it can help the food industry

guarantee high quality products once the food leaves the place of manufacture. The

open date gives consumers an idea of the amount of shelf life left in their foods, while

the emerging TTI technology makes distributors, retailers and consumers more

accountable for maintaining proper temperature conditions through out the duration of

the products shelf life. TTIs are a fairly new device on the U.S. marketplace. While

participants in this study were optimistic about the potential benefits of TTIs, 76% were

not familiar with the device at all.[43]

Time-Temperature Integrators. Recently, a congressman in Alabama proposed

that products found beyond their shelf life, based on the package date, would constitute

a $10,000 fine for the supermarket. In this case, a TTI would be a very beneficial tool for

the retailer, since it acts as a tell the truth tag with regard to the temperature exposure

history of the product. A TTI is a simple, inexpensive device that can show an easily

measurable, time-temperature dependent change that reflects the full or partial

temperature history of a food product to which it is attached. TTI operation is based on

mechanical, chemical, enzymatic or microbiological systems that change irreversibly

from the time of their activation. The rate of change is temperature dependent,

increasing at higher temperatures in a manner similar to most physicochemical

reactions. The change is usually expressed as a visible response, in the form of a

mechanical deformation, color development or color movement. The visible reading

gives some information on the storage conditions that have preceded it.

The ability of TTIs to function as cumulative recorders of temperature history

from their activation time to the time each response measurement is taken makes them

useful for two types of applications. First, TTIs can be used to monitor the temperature

exposure of individual food packages, cartons or pallet loads during distribution up to

the time they are displayed at the supermarket. By being attached to individual cases or

pallets they can give a measure of the preceding temperature conditions at each

receiving point. The information gathered from all stations could be used for overall

monitoring of the distribution system, thus allowing for identification and possible

correction of the more problematic links.[44]

Second, TTIs can be used as quality monitors. Since quality loss is a function of

temperature history and since a TTI provides a measure of that history, the devices

response can presumably be correlated to the quality level of the food. If that can be

achieved, TTIs can be used either as an inventory management and stock rotation tool

at the retail level, or attached on individual packaged products, can serve as dynamic or

active shelf life labeling instead of (or in conjunction with) open date labeling.[45] The

TTI would assure consumers that the products were properly handled and would

indicate remaining shelf life.

A variety of TTIs based on different physicochemical principles have been

described in the literature.[46-52] Three types of TTIs are commercially available: One

based on a time-temperature dependent diffusion of a polymer moving along a matrix

(3M Monitor Mark); the second on a change of color due to a controlled enzymatic

reaction (COX Technologies Vitsab); and the third on development of color based on a

solid state polymerization (Lifelines Freshness Monitor). Time-temperature self-

adhesive labels can also be used to show via color change when a certain temperature

is reached or exceeded (DeltaTrak WarmMark).

Other Temperature Monitoring Technologies. Alternatives to monitoring

temperature during food distribution include the use of flexible, miniaturized electronic

temperature recording devices.[53] These small, battery-powered devices record time-

temperature information that can be displayed and processed at the receiving end by

interfacing with a microcomputer. Examples of such devices are the Temp Mentor and

Data Mentor (Ryan Instruments); the Datatrace Micropack Tracer (Ball); and the

TempTale temperature recorder (Sensitech).

The Search Continues

The approaches, methods and technologies used to determine shelf life are as

varied as the food and beverage products tested. Although the food industry is still in

search of a magic condition in which to place the product and a magic number that

can be multiplied to obtain its true, real-world shelf life, no magical formula exists to

date. But food quality, safety, regulatory and market drivers are coalescing, spurring

continued research, better analytical and testing methodologies, and new technological

innovations that will move the industry closer to realizing its goals of improved shelf life

determinations.

bio--Theodore P. Labuza, Ph.D., is a Morse Alumni Distinguished Teaching Professor

of Food Science in the Department of Food Science and Nutrition at the University of

Minnesota. He teaches courses in food physical chemistry, reaction kinetics, food safety

and risk assessment, food processing and food law. Labuzas extensive research is

related to the properties of water and influence of temperature on the processing,

packaging and storage stability of foods, drugs and biologics, especially as related to

texture and glass transition phenomena, the physical chemistry and kinetics involved in

processing and shelf life testing, and evaluation of time-temperature integrators. He is

an author of more than 200 scientific refereed research articles, 15 textbooks, 59 book

chapters, seven patents and 98 other semi-technical articles. Labuza is a member of

the American Chemical Society (ACS), Institute of Food Technologists (IFT),

Association of Food & Drug Officials (AFDO), American Institute Chemical Engineers

(AIChE), American Dairy Science Association (ADSA), Society for Food Distribution

Research, American Association of Cereal Chemists (AACC), American Institute of

Nutrition (AIN), U.S. Military R&D Association, and Institute of Packaging Professionals

(IOPP).

Among his many professional activities in IFT, Labuza has participated as an IFT

regional communicator from 1975 to 1981, an IFT Scientific Lecturer, chair of the IFT

Expert Panel on Food Safety and Nutrition (1981 to 1986), on the IFT Finance

Subcommittee (1988-1990), member of the Office of Scientific Public Affairs (OSPA)

Committee (1986-1990), chair of the IFT Foundation (1988-90) and President of IFT

during 1988-89. He was elected a IFT Fellow (1979). Labuza received the IFT Samuel

Cate Prescott Research Award (1972), the Cruess Excellence in Teaching Award

(1979) and the Babcock Hart Nutrition Award (1988) and IFT's highest award, the

Nicholas Appert Award (1998). In 1995, Labuza received the Dairy and Food

Industries/American Association of Agricultural Engineers Food Engineer's Award and

the Gamma Sigma Delta, National Agricultural Honorary Society Award of Merit. In

1998, he received the Marcel Loncin Research Prize ($50,000) from IFT.

Acknowledgments

Sections of this overview have been published as part of the contribution series of the

Minnesota Agricultural Experimental Station, based on research conducted under Project

18-78 and a Project supported by 3M Co. Other research cited in this article was supported,

in part, by the University of Minnesota Retail Food Industry Center (TRFIC), which is funded

by the Alfred P. Sloan Foundation; the Brazilian National Council of Research and

Technology (CNPq) and the Graduate School of the University of Minnesota; and the

Minnesota-South Dakota Dairy Foods Research Center.

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