Jung Han. Innovations in Food Packaging

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Quality of packaged foods 27

100-

^ 90-

o 80-

i 70-

.-g'

60-

D- 50-

^ 40-

E 30-

20-

10-

\S.

\ \^

^ \

V >v

\ " -© ^

N. "^«,

\ " >^ ^ ^ ^ First order

Zero order \ ~^^"~~----^--

1 1 1 n 1 1

100

150 200

Time (days)

250 300

Figure 3.1 Change in quality versus time siiowing the effect of order of the reaction on the extent of

change.

where A^ is the initial value (time zero), A^ is the value at time t, and k is the rate

constant. A plot of first-order data as the concentration of A versus time gives a

curved line, as shown in Figure 3.1.

The time-dependence kinetic parameter can also be expressed as the D value (dec-

imal reduction

time).

The

D value and the

first-order

reaction rate constant are related

by the equation:

k = 2.303/Z)

(3.6)

In addition to describing the change in a property as a fiinction of time at a fixed

temperature it is important to describe the effect of temperature on the property,

because the rate of quality loss is temperature dependent. The Arrhenius relationship

is often used to describe the temperature dependence of deterioration rate as:

k = kQ

-EdJRT

(3.7)

where k

the rate constant for the deteriorative reaction,

is the rate constant, inde-

pendent of temperature,

is activation energy in kJ/mol, R is the gas constant (8.314

J/mol K) and T is an absolute temperature (K = 273 + °C). Essentially, the rate of

product deterioration as a function of temperature generally increases exponentially

with linear increase in temperature. From the Arrhenius equation, the activation

energy of a reaction or shelf life can be obtained. The Arrhenius equation is also used

to predict the shelf life at any unknown temperature. The shelf-life data and the acti-

vation energy are the key design parameters for time-temperature indicators (TTI).

TTIs are more suitable predictors of product's shelf

Hfe.

28 Innovations in Food Packaging

Shelf life

Shelf-life prediction

The shelf

Hfe

of novel foods that are not shelf stable may vary from batch to batch.

Accurate prediction of shelf life is, therefore, particularly important to ensure product

quality. Different approaches to shelf-life estimation have been

used.

Traditionally the

development of packaged foods has been largely an empirical procedure, involving

extensive laboratory evaluations of food formulations, packaging materials and vari-

ous package geometries. In an attempt to speed up the development process and opti-

mize food/package combinations, various mathematical models are able to predict the

shelf life of packed foods, and help in designing packaging systems to achieve the

desired results.

Mathematical modeling is the representation of real-life phenomena in terms of

a set of numerical expressions. The solutions of these mathematical systems are

supposed to stimulate the natural behavior of a food/package load. Whiting and

Buchanan (1994) proposed a three-level model classification scheme comprised of

primary, secondary, and tertiary

models.

Primary-level models describe the change in

microbial numbers over time, and secondary-level models indicate how the features

of primary models change with respect to one or more environmental factors - such

as pH, temperature and water activity. Tertiary-level models are personal computer

software packages that use the pertinent information from primary- and secondary-

level models to generate desired graphs, predictions and comparisons.

Predictive microbiology has been used to forecast the growth of spoilage micro-

organisms in order to determine the shelf life of a food

product.

Predictive models for

the growth of micro-organisms include temperature, pH and water activity as the main

growth-determining factors. However, other factors can significantly influence the

growth characteristics of the modeled micro-organisms, such as nitrite content,

organic acids and atmosphere (Devlieghere et

aL,

1999).

The effects of initial product

contamination, product characteristics, and storage conditions can be included in pre-

dictive models. However, specific spoilage organisms and spoilage reactions depend

upon intrinsic and extrinsic parameters. Recently, more attention has been paid to the

atmosphere as a fourth important growth-determining factor (Farber et aL, 1996;

Sutherland et

aL,

1996, 1997; Dalgaard et

aL,

1997; Fernandez et

aL,

1997). In these

studies the effect of storage temperature was described by the relative rate of spoilage

models, and the responses of numerous sensory, microbial, chemical, biochemical,

and physical measurements were correlated with remaining product shelf life.

Temperature models may predict the slope of the regression lines relating sensory or

microbial measurements and remaining shelf

life.

However, in general the regression

models are only applicable to products stored in given conditions (Olley and

Ratkowsky, 1973; Gibson, 1985; Bremner et aL, 1987). DevHeghere et al (1999)

compared two types of predictive models - an extended Ratkowsky model and a

response surface model - for the effect of temperature, concentration of dissolved

CO2,

and water activity

on the lag phase and the

maximum specific growth

rate

Lacto-

bacillus

sake for gas-packed cooked meat product. They reported that both developed

Quality of packaged foods 29

models proved to be useful in the prediction of the microbial shelf life of packed meat

products.

More recently, multivariate statistical methods have been used to relate the sensory

attributes of products (Girard and Nakai, 1994). Risbo (2003) observed that for a

packaged raisin-cereal mixture, shelf-life calculations based on the kinetic theory

show that the optimal product composition and product permeability for overall

product quality can be identified. In food packaging, measurements and predictions

of the shelf life of a product independent of the packaging structure are made first

and then integrated with the measurements and predictions made regarding the

effect of the package. Among the more relevant package properties are water

vapor transfer, gas transfer, odor transfer, flavor scalping, and other product/package

interactions.

To perform predictive modeling, the food model must be integrated with the pack-

age model. The package model must fit the food model - the package should be ana-

lyzed for its ability to function as a barrier against those variables that have been

identified as critical for the food's shelf life. Distribution parameters should be quan-

tified to determine their variability within the distribution environment. As a first

assumption, suppose that the main characteristics are the package barrier properties

(such as water vapor, oxygen or carbon-dioxide barrier) and that the package material

is unaffected by the packaging operations and distribution. In the predictive model,

assume that the internal package environment (water vapor, carbon dioxide, or oxy-

gen) changes as a permeant enters or leaves the package. Transmission of materials

will always occur from the high-concentration to the lower-concentration side of the

material. Standardize the transmission rate for the package area, gauge, time of

meas-

urement, and permeation properties for the package material/structure, the difference

of partial pressure of permeant across the package, and the environmental conditions -

in particular, temperature. Permeation is a function of dissolution into and diffusion

across the package material due to partial pressure P. The general models are based

on a standard differential equation which describes mass transfer across a permeable

membrane, with the effect on the product being the net gain or loss of the permeant by

the product (e.g. loss of carbon dioxide in a carbonated beverage, or loss of oxygen

attributable to reaction with a food component). The predictive model for the package

takes the general form:

dWIdt = (k/l)AdP (3.8)

where d^is the change in the weight of the critical food component, t is time, k is the

permeation coefficient of the package material, / is the package material thickness,

A is surface area of the package, and dP is the difference in partial pressures of the

permeant inside and outside of the package structure. Partial pressure requires knowl-

edge of the permeant: for oxygen external to the package it is 0.209; for carbon dioxide

outside the package it is 0.0003; for water vapor on the exterior it is six times the

relative of the distribution environment; for flavors and volatile components it is

essentially zero, etc. The elementary predictive model is for a monolayer material

structure of uniform thickness. When thickness changes, differential equations for the

thickness are incorporated into the model. When two or more materials are present, as

30 Innovations in Food Packaging

in a lamination, the net permeation is described by the sum of reciprocals of the indi-

vidual permeations:

IIP = l/Pj + I/P2 + ... + 1/^n (3-9)

plus the reciprocal of permeation across the boundary of different materials.

Shelf-life modeling and prediction have been limited by a serious paucity of key

variables, such as using only water vapor gain as a measure with no consumer accept-

ability input. The models do not replace the need for actual storage studies. Storage is

still necessary to verify product changes, find unusual effects, and, in some cases,

meet compliance criteria with government regulations. The use of these predictive

models in the food industry has been warranted by the need for rapid and cost-effective

provision of useful information for making decisions regarding product development,

prediction of safety and shelf life of

product, and identifying critical control points

in quality control

tests.

The use of models serves to reduce the time and effort neces-

sary to identify optimal packaging protection, and eliminate storage studies on mate-

rials with insufficient barrier properties to be reasonable candidates for the product.

The ability of the computer models to incorporate all of the known relevant variables

permits the food scientist, in concert with the packaging technologist, to predict accu-

rately and precisely the results of

package material and/or structural design change

on the shelf life of most product contents.

Storage conditions

The shelf life of a packaged food product is determined by numerous interactions

between parameters related to the product itself and/or associated with storage condi-

tions.

The quality changes in packaged products could be chemical, physical, enzy-

matic or microbiological, and are mainly due to mass transfer between foods and their

environment. Several studies have shown that barrier efficiency of packaging materi-

als depends not only on chemical composition of packaging material and penetrant,

but also on storage conditions (Giacin, 1995). Storage conditions (i.e. temperature,

humidity, atmospheric gas composition, and light) affect the appearance, aroma, flavor,

texture, and acceptability of packaged food

products.

Hence, appropriate packaging of

shelf-stable foods is essential, particularly during handling, transportation/distribution,

extended storage, and marketing.

Temperature

Storage temperature is probably the most important factor in maintaining the quality

and extending the shelf life of packaged foods. In most cases, an increase in storage

temperature degrades the quality and acceptability of packaged foods. To determine

the deleterious effects of temperature, it is often necessary to know how long a food

is exposed to that

temperature.

Biological reactions tend to increase by a factor of two

to three for each 10°C increase in temperature (Beaudry et al., 1992; Exama et al.,

1993).

Changes in environmental temperature create a specific problem in packaged

foods design because the respiration rate is more influenced by temperature changes

Quality of packaged foods 31

than by the O2 and CO2 permeabiHty of the permeable films used to obtain equilib-

rium modified atmosphere (EMAs). Owing to this fact, it is difficult to obtain an opti-

mum atmosphere inside a package when the surrounding temperature is not constant.

A film that produces a favorable atmosphere at the temperature for which the package

was designed may cause excessive accumulation of CO2 and/or depletion of O2 at

higher temperatures caused by an increased respiration rate. This anoxic situation

could lead to metabolic disorders such as fermentation, with production of off-flavors

(Kader et al., 1989; Silva et ai, 1999). In the case of a lower storage temperature,

decreased respiratory activity will lead to an accumulation of O2 above the optimal

3%,

resulting in a less effective EMA package. The influence of temperature on res-

piration rate was first quantified with the

QIQ

value, which is the respiration rate

increase for a 10°C rise in temperature:

Q,, = (Rr,/Rv^)mT2-n) ^^ ^^^

where

RY2

is the respiration rate at temperature T2, and

RYI

is the respiration rate at

temperature Ti. For various products,

QIQ

values may range from

to 4 depending on

the temperature range (Kader, 1987).

The Arrhenius equation is also used to quantify the effect of temperature on respi-

ration rate. The simultaneous use of this equation to describe the influence of temper-

ature on film permeability simplifies the mathematical modeling of MAP systems

(Exama et aL, 1993; Susana et al., 2002):

i?r = 8 X Qxp(-E/RT) (3.11)

The above equation may be rewritten with a reference temperature (Nelson, 1983;

Van Boekel, 1996):

Rv = 8^^f X Qxp[-E/R (l/T -

1/r^^f)]

(3.12)

Temperature variations during transportation and storage affect the produce respi-

ration rate (Exama et al, 1993). Kang et al. (2000) observed that temperature fluctua-

tions between 5°C and 15°C did not induce a harmfiil atmosphere inside the polyolefin

package, though high temperatures accelerated the weight loss, stipe elongation, and

darkening of the mushrooms. Temperature also has a significant effect on the sensory

quality of packaged food

products.

Enzymatic browning and shriveling, being the most

limiting sensory disorders of fresh cut produce, are inhibited by low-temperature storage

(Willocx, 1995; Garcia-Gimeno et al, 1998). The barrier efficiency of packages, too,

depends on temperature. Labuza and Contreas-Medellin (1981) observed that water

permeability decreases when temperature decreases, but may increase again at very

low temperatures. Morillon et al (2000) reported that corrected permeabilities of

cel-

lophane and polyethylene films decrease with temperature due to a preponderant

effect of temperature on water diffusion. Jacobsson et al. (2003) reported that change

of temperature during storage induced changes in smell, flavor, taste, and texture of

broccoli, depending on the packaging material used. However, the appearance of the

broccoli was found to be more dependent on the atmosphere than on the temperature

of storage.

32 Innovations in Food Packaging

Equilibrium relative humidity

Equilibrium relative humidity (ERH) is critical to the quality and safety of packaged

foods.

Moisture loss or gain from one region or food component

another region will

continuously occur in order to reach thermodynamic equilibrium with the surround-

ing food components and the environment.

The concept of water activity (a^) is an important property of food safety. Water

activity is widely used to predict the stability of food with respect to the potential for

growth of micro-organisms, and also some of the physical, chemical, and enzymic

changes that lead to deterioration. In packaged foods, the water-vapor permeability of

the packaging material is a decisive factor in controlling changes in moisture content

and thus the water activity (a^) of packaged foods. Water activity is defined as the

ratio of partial pressure of water vapor in the product {p) to that in presence of pure

water (/?o). A difference in the water activities of food components, food domains,

and the external environment outside the package introduces a driving force for water

transport (Labuza and

Hyman,

1998).

Water transport ceases when differences

water

activity have leveled out - i.e. water activities converge to a common equilibrium

value. For some systems, the equilibrium water activity is acceptable from the point of

view of textural (Katz,

1981;

Bourne, 1987), chemical (Leung, 1987), and microbio-

logical stability (Leneovich, 1987), and the shelf life is not limited by water transport.

For systems where this equilibrium water activity is undesirable to one or more of the

components, the product shelf life is determined by the dynamics of the water trans-

port process.

By measuring the water activity of foodstuffs, it is possible to predict which micro-

organisms will be potential sources of spoilage and infection. Non-enzymatic brown-

ing reactions and spontaneous autocatalytic lipid oxidation reactions are strongly

influenced by water activity. Troller and Christian (1978) observed that at very low

water activity levels, foods containing unsaturated fats and exposed to atmospheric

oxygen are highly susceptible to the development of oxidative rancidity. The high

oxidative rancidity occurs at a^ levels below the monolayer level, and as a^ increases,

both the rate and the extent of auto-oxidation increase until a^ in the range of

0.3-0.5

is reached. Above this point the rate of oxidation increases until a steady state is

reached, normally at a^ levels in excess of

0.75.

Water activity can also play a significant role in determining the activity of vitamins

in packaged foods. The rate of degradation of vitamins A, Bj, B2 and C increases as

a^ increases over the range 0.24-0.65. The rate of ascorbic acid and riboflavin degra-

dation increases with an increase in a^. Browning reactions generally increase with an

increasing a^ at low moisture content, reach a maximum at a^ of 0.4-0.8, and

decrease with a fiirther increase in water activity.

Gas atmosphere

The sensory properties of packaged foods depend on different physiological and bio-

chemical pathways that are induced by atmospheric conditions. Lipid oxidation and

non-enzymatic browning are the major chemical reactions that lead to deterioration in

the sensory quality of packaged foods. Responses to atmospheric modifications are

found to vary dramatically among packaged foods, and include both unwanted and

Quality of packaged foods 33

beneficial physiological

changes.

Desirable responses include

reduction

respiration,

oxidative tissue damage or discoloration, rate of chlorophyll degradation, and ethylene

sensitivity, with the concomitant reduction in the rate of ripening. Undesirable

responses include the induction of fermentation, development of disagreeable

flavors,

reduction in aroma biosynthesis, induction of tissue injury, and an alteration in the

makeup of microbial fauna.

Atmospheric oxygen generally has a detrimental effect on the nutritive quality of

foods,

and it is therefore desirable to maintain many types of foods at a low oxygen

concentration - or at least to prevent a continuous supply of oxygen into the package.

However, in the presence of sufficient oxygen, the sensory quality is less affected

(Watkins, 2000). Oxygen penetrating the packages affects the rate of carotenoid degra-

dation,

and thus

the color and ascorbic

acid

degradation

(Nagy,

1980;

Gvozdenovic et al,

2000).

The severity of off-flavor production will depend on the time of exposure to

conditions below the minimum required oxygen concentration and/or above the max-

imum tolerated carbon dioxide concentration (Beaudry, 1999, 2000; Watkins, 2000).

The diffusion of gases through

flexible

packaging material depends on the physico-

chemical structure of the barrier. The gas permeabilities of the common thermoplas-

tic packaging material are presented in Table 3.2.

Table 3.2 Permeability coeffid^^^ibr various |^^

Polymer

Low-density

polymer

High-density

polyethylene

Polypropylene

Unplasticized

poly(vinyl chloride)

Cellulase acetate

Polystyrene

Nylon 6

Poly( ethylene

terephthlate)

Poly(vinylidene

chloride)

PN2

(30°C)

2.7

0.4

2.8

2.9

0.1

0.05

0.0094

PO2

(30<»C)

10.6

1.2

7.8

0.38

0.22

0.053

PCO2

(30°C)

352

1.6

1.53

0.29

PSO2

(25°C)

200

1.16

220

22a

PH2O

(ZS^'C)

800

130

680

1560

75 000

000

7000

1000

PO2

PN2

2.9

3.9

3.0

2.8

3.8

4.4

5.6

PCO2

PO2

6.4

3.3

4.0

8.3

8.7

8.0

4.2

7.0

5.5

PCO2

PN2

18.5

13.0

25.0

24.3

30.3

16.0

30.6

30.9

Nature of

polymer

Some

crystal linity

Crystalline

Slightly

crystalline

Glassy,

amorphous

Glassy

Crystalline

Mean

3.8

6.2

Reprinted from Robertson (1993), p. 81, by courtesy of Marcel Dekker Inc.

*P X 10^^ml(STP)cmcm-2s-'' (cm Hg""").

^Nylon II.

23.6

34 Innovations in Food Packaging

Light

Exposure of packaged foods to both ultraviolet radiation and visible light causes

oxidative deterioration of

lipids,

vitamins, proteins, and colorants in foods, leading to

the formation of off-flavors, nutrient losses, and discoloration. Factors influencing the

deteriorative effect of light include the intensity of light, duration of light exposure,

and light transmittance of the packaging material. The interplay between product,

packaging, light, and oxygen in Figure 3.2 shows factors of importance for the light

absorption by the product, and the content of oxygen, respectively.

Availability of oxygen is

prerequisite for light-induced oxidation to occur. Hence,

vacuum packaging prevents light-induced oxidation by reducing the oxygen in the

headspace, thereby minimizing the rate of oxidation processes (Marsh et al., 1994;

Hong et

aL,

1995a). However, the critical concentration (in the package and dissolved

in the product) has not yet been determined, and is likely to vary between products

and to depend upon packaging and storage conditions. Reducing the oxygen content

of the headspace - for example, by vacuum packaging or packaging in modified

atmospheres with high carbon dioxide/nitrogen and low residual oxygen, and/or using

Factors influencing light absorbed

{Igbs^f)

Intensity of light

(/Q)

Spectrum of light source

Absorption

{labs,m)

^^^ reflection (/^^) of packaging material

Product reflection (/^p)

Product absorption

(labs,p)

Contents of specific endogenous absorbers

Factors influencing

Initial gas composition (O^^p+O^,/,)

Product to headspace volume ratio

Product respiration

O2 transpiration rate of packaging material

Figure 3.2 Schematic overview of product/packaging interactions of light with oxygen (reprinted from Mortensen

etal.,

2004,

with permission of Elsevier Ltd).

Quality of packaged foods 35

oxygen impermeable packaging - may actually reduce light-induced oxidation by

limiting the oxygen pool available for dissolution, and thereby the reaction in the

aqueous

phase.

Light protection offered

packaging materials depends on numerous

factors, including:

The inherent absorption characteristics of the material

The thickness of the material

The material processing conditions

The coloration of the material.

These may all

combined

optimize the photo-oxidative protection of specific foods.

Different packaging material categories offer varying degrees of protection against

light-induced changes due to differences in reflectance, transmittance, and oxygen

permeability determined by molecular composition of the material. Generally, metals

offer the best protection, followed by paper/paperboard, various plastics, and finally

glass,

through which up to approximately 90% of light is transmitted (Bosset et al,

1994;

Lennersten and Lingert, 1998). Unbleached paper provides

better light barrier

than bleached paper, especially at short wavelengths, due to the removal of and alter-

ations in the light-absorbing pigments (the lignins) during the bleaching process

(Mortensen et ai, 2003a). Hence, very different light transmission characteristics are

notable within different categories - a fact that should be utilized for optimization of

packaging with respect to photo-oxidation. For instance, a secondary packaging

consisting of cardboard may protect against photo-oxidation as well as providing

mechanical stability and ease of handling for the retailers.

Nelson and Cathcart (1984) examined

the

effect of the wall thickness of polyethylene

milk bottles on light transmission characteristics, and found that increasing the wall

thickness led to lower light transmission

rates.

Moreover, material processing (orienta-

tion of the polymer, crystallinity, and incorporation of additives) may have an impact

on the light transmission characteristics. Incorporation of titanium oxide into plastic

materials increases light scattering, thus reducing light transmittance - especially light

at wavelengths shorter

than

400 nm (Nelson and Cathcart,

1984;

Lennersten and Lingert,

1998).

Compounds such as carbon black, chalk and talc may also be applied to reduce

light transmittance. Cavitation, which may be used in, for example, the production of

polypropylene, is another approach to increase the light

barrier.

Lennersten and Lingert

(1998) concluded that cavitied films reflect more light than non-cavitied films, which

results in reduced light transmittance.

The catalytic effects of light

are

most pronounced for light in

lower

wavelengths of the

visible/ultraviolet spectrum (Bekbolet,

1990;

Lennersten and Lingert,

1998).

Increasing

light intensity, i.e. the photon flux, accelerates light-induced oxidation (Deger and

Ashoor, 1987; Hong et ah, 1995b; Alves et ai, 2002). Packaging materials absorb

most of the energy-rich ultraviolet light, which is generally not as harmful to the pack-

aged dairy product as is light in the blue-violet region (400-500

nm)

of the spectrum.

Hansen (1996) noted that monochromatic light at 405 and

448

nm was more detri-

mental to the examined dairy spread model than was monochromatic light at 460 nm.

Evidently, prolonged exposure time increases the light-induced damage (Kristensen

et ai,

2000;

Alves et al, 2002; Mortensen et ai, 2002a, 2002b, 2003a, 2003b, 2003c;

36 Innovations in Food Packaging

Wold et ai, 2002; Juric et

aL,

2003;

Kim et

aL,

2003).

These examples show that light

can play an important role in deterioration of nutrients. Depending on the light trans-

mission characteristics of the packaging materials, suitable packaging material can

offer protection of quality packaged foods by absorption or reflection of all or part of

the incident light. Lennersten and Lingnert (2000) observed that the effect on lipid

oxidation in low-fat mayonnaise was most pronounced with ultraviolet radiation,

although short-wavelength visible light also had a significant effect. Polymer materials

offered some protection against lipid oxidation by

filtering

out the ultraviolet radiation

to varying

degrees.

PEN and PET/PEN copolymer offered better protection than PET.

None of the materials offered sufficient protection against color changes.

The total amount of light absorbed by a packaged food can be calculated using the

following formula:

where

labs

= intensity of light absorbed by the food, 4 = intensity of incident light,

Ifp

= fractional transmission by the packaging material, 4^ =

firaction

reflected by the

packaging material, and

I^f

fi*action

reflected by the food.

The fraction of the incident light transmitted by any given material can be consid-

ered to follow the Beer-Lambert law:

/ = / e-^

(3.14)

where / = intensity of light transmitted by the packaging material, k =

characteris-

tic constant (absorbance) for the packaging material, andx = thickness of

the

pack-

aging material.

The absorbance k

varies

not only with the nature of the packaging material but also

with the wavelength. Thus the amount of light transmitted through a given package

will be dependent on the incident light and the properties of packaging material.

Aseptic packaging

Aseptic packaging is an alternative to conventional canning in

the

production of

shelf-

stable packaged food

products.

The word "aseptic", derived from the Greek word

septi-

cos,

means the absence or exclusion of putrefactive micro-organisms. Aseptic packaging

technology is

fimdamentally

different

fi-om

that of traditional food-processing systems.

Canning processes commercially sterilize

filled

and sealed containers, while in aseptic

packaging the presterilized product is filled into sterilized containers that are hermet-

ically sealed in a commercially sterile environment. This form of heat treatment enables

the commercial sterilization of the product,

and results in

minimal loss of product qual-

ity and nutrition. A typical flow diagram is shown in Figure 3.3.

In aseptic packaging, raw or unprocessed product is heated, sterilized by holding at

a high temperature for a predetermined amount of

time,

cooled, and then delivered to