Food Sci. Biotechnol. 21(2): 497-502 (2012)

DOI 10.1007/s10068-012-0063-8

Development of a Time-Temperature Integrator System Using

Burkholderia cepacia Lipase

Won Kim, Euna Park, and KwangWon Hong

Received: 24 October 2011 / Revised: 24 November 2011 / Accepted: 28 November 2011 / Published Online: 30 April 2012

© KoSFoST and Springer 2012

Abstract A time-temperature integrator (TTI) is a device

used to show a time-temperature dependent change that

reflects the temperature history and quality status of the

food to which it is attached. An enzymatic TTI system

based on the reaction between Burkholderia cepacia lipase

and tricaprylin, which causes a pH change, was developed.

The temperature dependence of the response rate of this

new lipase-type TTI was modeled using the Arrhenius

equation, and the estimated activation energy was calculated

as 70.61±11.10 kJ/mol (±95% confidence interval). The

TTI response was validated under dynamic storage conditions

with independent variable temperature experiments, and a

good agreement was obtained between the predicted and

measured values.

Keywords: time-temperature integrator (TTI), Burkholderia

cepacia lipase, Arrhenius equation, activation energy

Introduction

Temperature is a decisive factor influencing the quality and

safety of a food product during storage and distribution.

Therefore, monitoring and recording the temperature history

for the entire life cycle of food products is very important

for predicting quality and shelf-life of food products (1). A

time-temperature integrator/indicator (TTI) is a simple

device that monitors and records the time-temperature

history of food products to which it is attached as a label

(2). A TTI indicates irreversible visual responses such as

color changes or a moving color front through biological,

chemical, and physical reactions (3). The visual response

of the TTI helps consumers predict the quality and

expiration date of products more easily (4). Many cases of

applying a TTI to food products have been being reported,

as inexpensive and effective TTIs are being developed and

various studies on the quality index of food products have

been conducted. A TTI has been applied to various

refrigerated and frozen food products such as meat, poultry,

dairy products, seafood, and vegetables as well as during

the milk sterilization process (5-10). Generally, the response

of a TTI and decreased food quality must correspond to

successfully apply a TTI to food products. In other words,

the activation energy (Ea), indicating the temperature

sensitivity of the TTI response, should be similar to the Ea

of the quality change in the food product (11,12).

Therefore, systematic kinetic research on food product

deterioration and the response of a TTI is required to use

a TTI as a quality indicator.

TTIs currently being used for commercial purposes can

be classified into diffusion-based TTI, enzymatic TTI,

polymeric TTI, and microbial TTI (4,13). Among these,

the only enzymatic TTI, VITSAB TTI (Vitsab A.B.,

Malmö, Sweden), is based on an irreversible color change

induced by a pH decline resulting from the controlled

enzymatic hydrolysis of a lipid substrate (3,4). The indicator

consists of 2 separate compartments containing an aqueous

solution of a lipolytic enzyme such as pancreatic lipase and

another containing the liquid substrate suspended in an

aqueous medium and a pH indicator mix (4). As substrates

of lipase, various triacylglycerols such as tricaproin,

tripelargonin, and tributyrin can be used (3). When using

these substrates, it is typically difficult to obtain stable

substrates emulsion in low temperature, and thus selection

of proper emulsifier is critical in the process (14).

Nevertheless, as lipase-based TTI can be used with

different combinations of enzymes and substrates, it has a

Won Kim, Euna Park, KwangWon Hong ( )Department of Food Science and Biotechnology, Dongguk University,Seoul 100-715, KoreaTel: +82-2-2260-3369, Fax: +82-2-2260-3369E-mail: hkwon@dongguk.edu

RESEARCH ARTICLE

498 Kim et al.

merit that distinct TTI with different activation energy can

be developed and applied to a variety of food quality

change (3,4).

Burkholderia cepacia lipase displays high stability at

different temperatures and pHs and can tolerate various

organic solvents (15). Additionally, developing a TTI using

this lipase would be economical and could be considered a

great commercial utilization value, because this lipase is

secreted outside of the cell and is able to create various

catalytic reactions in liquefied or non-liquefied states.

In this study, a lipase-type TTI system was developed

based on the reaction in which the B. cepacia lipase

hydrolyzes tricaprylin. The kinetic parameters of this TTI

were calculated through a color change at various constant

temperatures. Additionally, a dynamic model was developed

based on the calculated kinetic parameters to investigate

the accuracy of the TTI and its applicability to food

products.

Materials and Methods

Preparation of a B. cepacia lipase (BCL)-based TTI

The lipase used in this study was commercially available as

Amano Lipase PS (Sigma-Aldrich, St. Louis, MO, USA),

which is the lipase from B. cepacia. The TTI reaction

mixture was formed with 4 mM tricaprylin (C8:0), 0.1%

Triton X-100, 2.5% Mcilvaine’s buffer (0.2 M Na2HPO4,

0.1 M citric acid, pH 7.5) and an 8.5% pH indicator

solution (mixture of 0.1% of bromothymol blue, methyl

red, and neutral red at 12:4:1 ratio). The pH indicator led

to an irreversible color change from green to orange and

finally to red (the endpoint), indicating a progressive

decline from pH 8.0 to 6.0. The TTI reaction mixture was

emulsified by a homogenizer (Diax-900; Heidolph, Kelheim,

Germany) for 3 min at 26,000 rpm.

Determining BCL-TTI kinetic parameters The reaction

was started in 50 mL of BCL-TTI reaction mixture by

adding 1 unit of BCL to each mixture that had reached

constant temperature after pre-storing the incubator at 5

different temperatures (5, 10, 15, 20, and 26oC) for 3 h.

The ∆E value of the BCL-TTI reaction mixture was

measured under the conditions of D65 illumination and a

2o observation angle using a colorimeter (Minolta CM-

2500d; Minolta Co., Ltd., Osaka, Japan). All experiments

were repeated 3 times and reported as the mean and

standard deviation (SD).

The chromaticity change (∆E value) was measured using

CIE Lab color space coordinates to objectively describe the

irreversible BCL-TTI color change. The BCL-TTI reaction

rate was determined using the ∆E value change per unit

time at different constant temperatures, and the ∆E value

was expressed by the following equation.

(1)

where, L* is the difference in brightness (white-black)

change between t=0 and measured unit time. a* is the

difference in redness-greenness, and b* is the difference in

yellowness-blueness (16).

The TTI response function according to the ∆E value

can be expressed as follows (1).

(2)

where, F(X) is total TTI color difference, in other words

the ∆E value. The response rate constant under each storage

temperature was determined through linear regression

analysis of the ∆E value against time t (h). The temperature

dependence of the TTI response was described with the

Arrhenius equation and expressed as follows.

(3)

where, k0 is the Arrhenius pre-exponential factor (1/h)

value, Ea is activation energy (kJ/mol), R is the ideal gas

constant (8.314×10−3 kJ/kmol), and T is absolute

temperature (K).

Measurement of the BCL-TTI color change under

dynamic storage conditions For the dynamic storage

experiments, 4 non-isothermal temperature storage profiles

were used. Temperature profile 1 (TP.1) involved storage

for 18 h at 8oC, 2 h at 13oC, 2 h at 18oC, 2 h at 23oC, and

finally 24 h at 12oC. Temperature profile 2 (TP.2) included

a step wise changing profile of 3 h at 25oC and 3 h at 18oC.

Temperature profile 3 (TP.3) and profile 4 (TP.4) included

a periodically alternating 6 h cycles of (2 h at 20oC, 2 h at

15oC and 2 h at 10o) and (2 h at 20oC, 2 h at 12oC, 2 h at

5oC), respectively. BCL was added to 50 mL of the BCL-

TTI reaction mixture at a concentration of 0.02 units/mL to

measure the change in ∆E per unit time during storage in

a programmable incubator. All samples were measured 6

times. The response rate k for each temperature profile was

calculated using a linear regression analysis based on the

measured ∆E value. This was compared and analyzed with

the predicted value to check for significance and correlation.

The relative error between the predicted and measured

reaction rates were calculated using the following equation.

Applicability was examined by setting the relative error

limit of the predicted and measured values as <20%

(17,18).

(4)

Statistical analysis All linear regression analyses were

conducted using PASW statistics 18.0 (SPSS Inc., Chicago,

∆E ∆L∗( )2

∆a∗( )2

∆b∗( )2

+ +[ ]=

F X( ) ktti t⋅=

k k0exp

Ea

R T⋅---------–⎝ ⎠

⎛ ⎞⋅=

%RE kmeasured kpredicted–( ) kmeasured⁄ 100×=

A TTI System Using Burkholderia cepacia Lipase 499

IL, USA). Additionally, the 95% confidence interval of the

BCL-TTI Ea value was calculated. All data points are

indicated as mean values and SD indicated by error bars.

Results and Discussion

BCL-TTI color changes The changes in pH and color

after starting the TTI reaction were measured. Figure 1

shows a good correlation between pH and the TTI

chromaticity change (∆E value) at 25oC. The pH of the TTI

decreased proportionally from 8.0 to 5.88±0.05, whereas

the ∆E value increased proportionally from 0 to 27.13±

0.31. The TTI-specific color change is indicated in Fig. 2.

The distinct color change to the red was obtained when the

∆E response reached a value of 25, and that time was

selected as the end point of the BCL-TTI system.

Arrhenius analysis of the BCL-TTI The TTI was

stored at different constant temperatures (5, 10, 15, 20, and

26oC) to determine the reaction order and the reaction rate

k by measuring the ∆E value changes according to time.

The times to reach the endpoint (∆E=25) were 10.73 h at

26oC, 15.93 h at 20oC, 27.71 h at 15°C, 49.34 h at 10oC,

and 90.38 h at 5oC (Fig. 3). As a result of the linear

regression analysis, the response rate k was 2.32 (R2=

0.995) at 26oC, 1.56 (R2=0.997) at 20°C, 0.90 (R2=0.996)

at 15oC, 0.48 (R2=0.990) at 10oC, and 0.24 (R2=0.961) at

5oC, and all coefficient of determinations (R2) were ≥0.96

(Table 1). The TTI activation energy (Ea) can be calculated

by plotting a curve between 1/T and lnk (Fig. 4). The BCL-

TTI Ea was 70.61±11.10 kJ/mol at the 95% confidence

interval. Among the commercially available TTIs, the Ea

values of the VITSAB Type M, Fresh Check Indicator

Type A6, and Fresh Check Indicator TJ2 were 68.70±9.03,

83.60±10.71, and 92.67±9.76 kJ/mol, respectively (12,19),

so the BCL-TTI had similar Ea values as these TTIs.

Fig. 2. Color response of the Burkholderia cepacia lipase (BCL)-based time temperature integrator (TTI) from activation to endpoint at 25oC.

Fig. 3. Response of the Burkholderia cepacia lipase (BCL)-based time temperature integrator (TTI) stored under isothermalconditions.

Fig. 1. pH and ∆E values changes in the Burkholderia cepacia

lipase (BCL)-based time temperature integrator (TTI) at 25oC.

500 Kim et al.

Generally, the difference in Ea between a food product and

TTI must be <±20 kJ/mol to apply TTI to food products

(3).

The quality loss in various food products was measured

using an Arrhenius analysis, and the Ea values are reported.

The growth Ea values for Pseudomonas spp. and

psychrotrophic microorganisms in refrigerated beef were

74.29 and 85.50 kJ/mol, respectively (20). The growth Ea

values of Pseudomonas spp. and total aerobic bacteria of

poultry products were 78.7±18.8 and 91.2±6.7 kJ/mol

(±95%, confidence interval, CI), respectively, so applying a

TTI with an Ea of 79.9±7.5 kJ/mol (±95% CI) represented

poultry spoilage (21). Additionally the growth Ea values of

Pseudomonas spp. in fish such as turbot and bouqe were

86.10 and 81.6±11.6 kJ/mol (±95% CI), respectively

(12,22). The quality change in these fish can be represented

by TTIs such as the Fresh Check Indicator type A6

(83.60±10.71 kJ/mol), the VITSAB type M (68.70±9.03

kJ/mol) or the VITSAB type S (102.1±6.2 kJ/mol) with

similar Ea values (12,22). Thus, the BCL-TTI can also be

applied as an indicator to show temperature variations in

these food products.

Dynamic modeling of the BCL-TTI The kinetic

parameters of BCL-TTI were verified under non-isothermal

conditions, simulating temperature fluctuations which may

occur in the chill chain. BCL-TTIs were stored under

dynamic temperature profiles. The comparison of the

actual ∆E values and the predicted ∆E values by dynamic

modeling of each temperature profile are shown in Fig. 5.

The time it took to reach the endpoint (∆E=25) for each

profile was 46.12 h in TP.1, 14.60 h in TP.2, 30.15 h in

TP.3, and 36.08 h in TP.4. The ∆E values actually measured

from these times (tend) were 24.71±0.85, 23.1±0.45,

22.66±0.78, and 24.42±0.64 (±SD), respectively. These

∆E values were very close to the endpoint value of 25, so

we determined that the predicted value and the actually

measured value closely matched.

Table 2 shows the response rate k (1/h) predicted and

measured for the 4 temperature profiles along with their

relative errors (% RE). Each response rate k (1/h) was

calculated using linear regression analysis after predicting

and measuring the ∆E value according to tend. All

correlation coefficients (R2) were 0.970. Additionally, the

relative errors between the predicted and measured values

for each temperature profile were 4.05, 6.95, 10.92, and

3.75%, respectively, indicating a very high correlation. The

results showed that dynamic modeling through kinetic

parameter and numerical analysis worked well.

In conclusion, various kinetic parameters were calculated

through the steady state and 4 types of temperature profiles

were used to verify these variables to determine the

usability of the BCL-TTI developed in this study. As a

result of comparing the measured and predicted values

using a dynamic modeling numerical analysis, we verified

that all 4 types of models were very highly correlated.

Therefore, it seems that a BCL-based TTI [70.61±11.10

kJ/mol (±95% CI)] will become an effective tool to

evaluate food quality in products with similar Ea values.

Acknowledgments This research was supported by the

Agriculture Research Center (ARC, 710003-03-1-SB110)

program of the Ministry for Food, Agriculture, Forestry

and Fisheries, Korea.

Fig. 4. Arrhenius plot of the Burkholderia cepacia lipase(BCL)-based time temperature integrator (TTI) response rate.

Table 1. Arrhenius kinetic parameters of the Burkholderia

cepacia lipase (BCL)-based time temperature integrator (TTI)

Temperature(oC)

k (1/h) R2 Ea±95% CI1)

(kJ/mol)R2

26 2.32 0.995

70.61±11.10 0.993

20 1.57 0.997

15 0.90 0.996

10 0.51 0.982

5 0.28 0.910

1)Ea, activation energy; CI, confidence intervals

Table 2. Correlation between the dynamic modeling and theBurkholderia cepacia lipase (BCL)-based time temperatureintegrator (TTI) response by regression analysis at differenttemperature profiles

Predicted Measured% RE1)

k (1/h) R2 k (1/h) R2

TP1 0.59 0.983 0.57 0.977 4.05

TP2 1.62 0.995 1.51 0.994 6.95

TP3 0.83 0.999 0.74 0.990 10.92

TP4 0.69 0.998 0.67 0.993 3.75

1)RE, relative error

A TTI System Using Burkholderia cepacia Lipase 501

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