Food Control 18 (2007) 1086–1092
www.elsevier.com/locate/foodcont
Effective control of Listeria innocua by combination of nisin,
pH and low temperature in liquid cheese whey
L.I. Gallo a, A.M.R. Pilosof
a
b,c
, R.J. Jagus
a,*
Laboratorio de Microbiologı́a Industrial, Departamento de Ingenierı́a Quı́mica, Facultad de Ingenierı́a, Universidad de Buenos Aires,
Ciudad Universitaria (1428), Buenos Aires, Argentina
b
Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires,
Ciudad Universitaria (1428), Buenos Aires, Argentina
c
Member of Consejo Nacional de Investigaciones Cientı́ficas y Técnicas de la República, Argentina (CONICET)
Received 11 January 2006; received in revised form 26 June 2006; accepted 3 July 2006
Abstract
The effect and interactions of pH (5.5, 6.0 and 6.5), temperature (7 C and 20 C) and nisin (100 IU/ml; 300 IU/ml), on the growth
and survival of Listeria innocua in liquid cheese whey (LCW) were studied.
Growth data were analyzed by non-linear regression analysis to generate ‘‘best fit’’ Gompertz and logistic models. The growth kinetics
of L. innocua was dependent on the interaction of the three variables, particularly on the lag phase duration.
The effectiveness of nisin in controlling the growth of L. innocua in LCW was more pronounced at 7 C than at 20 C and as the pH
decreased from 6.5 to 5.5. As a consequence, this combined treatment may provide LCW with a degree of protection against this microorganism, particularly if employed in conjunction with low temperature.
2006 Elsevier Ltd. All rights reserved.
Keywords: Cheese whey; Listeria innocua; Nisin; Combined treatments
1. Introduction
Cheese whey is a by-product from the cheese industry,
well known for its nutritional and functional properties.
It is an important source of proteins, mainly b-lactoglobulin and a-lactalbumin, lactose and minerals, which makes
this product a functional food and a source of valuable
nutrients (González-Martı́nez et al., 2002).
Cheese whey is generally processed by ultrafiltration and
spray drying to produce whey protein concentrate (WPC).
However, the liquid from the membrane process could be
used directly as a liquid whey concentrate in the formulation of food products, if adequately stabilized.
Listeria monocytogenes is a foodborne pathogen capable
of growing at refrigeration temperature (Walker, Archer, &
*
Corresponding author. Tel.: +54 1 4576 3240; fax: +54 1 4576 3241.
E-mail address: [email protected] (R.J. Jagus).
0956-7135/$ - see front matter 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.foodcont.2006.07.009
Banks, 1990) and at relatively low pH (George, Lund, &
Brocklehurst, 1998). Its high incidence in raw milk (Lovett,
Francis, & Hunt, 1987) and foodborne outbreaks point L.
monocytogenes as a pathogen of concern to the dairy industry (Menéndez, Godinez, Rodrı́guez-Otero, & Centeno,
1997).
Listeria innocua, a non-pathogenic species, may be used
as a biological indicator for L. monocytogenes because of
their similar response to physico chemical or thermal treatments (Kamat & Nair, 1996).
The objective of the present work was to study the combined effect of nisin, pH and temperature on the growth
and survival of L. innocua in liquid whey. Hurdle technology, a multifactor procedure, can be employed to accomplish food preservation, where each factor contributes to
the stability and safety of the food product (Leistner,
1992; Leistner, 1994).
Temperature is a major factor on food deteriorative
reactions, especially, for microbial spoilage since specific
L.I. Gallo et al. / Food Control 18 (2007) 1086–1092
growth rate and lag phase duration are highly temperature
dependent (Giannuzzi, Pinotti, & Zaritzky, 1998). Besides,
although temperature plays a major role on microbial
stability, refrigeration temperatures are not always kept
constant during food handling. Thus, temperature effects
on microbial control have been widely studied by computer
supported models based on heat transfer and microbial
growth estimation (Li & Torres, 1993).
Nisin, a bacteriocin produced by strains of Lactococcus
lactis subsp. lactis, is widely used as a preservative in
pasteurized processed cheeses and cheese spreads (DelvesBroughton, 1990). It is the only bacteriocin which has been
approved by the World Health Organization (WHO) to be
used as a preservative in the food industry. Nisin displays
inhibitory activity towards a broad range of Gram-positive
organisms, including L. monocytogenes and Bacillus cereus
(Jaquette & Beuchat, 1998). The primary biological
target is the energy-transducing cytoplasmic membrane of
Gram-positive bacteria. Nisin binds electrostatically to
the negatively charged phospholipids and increases the
permeability of the membrane by pore formation, resulting
in rapid efflux of essential intracellular small molecules
(Abee, Rombouts, Hugenholtz, Guihard, & Letellier,
1994; Breukink et al., 1997; Montville, Chung, Chikindas,
& Chen, 1999). The efflux of cellular constituents results
in a complete collapse of the proton motive force and subsequently in cell death (Wincowski, Bruno, & Montville,
1994).
It has been reported that bacteriocins induce a transitory bactericidal effect against L. monocytogenes, often followed by a regrowth of cells in food models and in
laboratory media supplemented with nisin (Davies, Falahee, & Adams, 1996). This growth could be due to a
low concentration of bacteriocin to kill all cells, or to physico-chemical factors such as alkaline pH values (Liu &
Hansen, 1990), NaCl (Bell & De Lacy, 1985), or fat (Jung,
Bodyfelt, & Daeschel, 1992), which decrease bacteriocin
action, or due to the emergence of bacteriocin resistant cells
(Chi-Zhang, Yam, & Chikindas, 2004).
2. Materials and methods
2.1. Strain and growth conditions
L. innocua (CIP 8011, CCMA 29) was grown in 150 ml
Tryptic Soy broth enriched with 0.6% (w/v) yeast extract
(TSBYE), in a continuously agitated temperaturecontrolled shaker at 28 C overnight. Five milliliters were
inoculated in 150 ml fresh TSBYE, agitated for 1–2 h to
obtain the desired concentration of cells.
2.2. Nisin preparation
A stock solution (1 · 105 IU/ml) was prepared by
dissolving NisaplinTM (Danisco, Denmark) in sterile
distilled water. The pH was adjusted to 2.0 with 0.1 N
HCl to ensure high bacteriocin solubility and stored at
1087
20 C. When nisin was added to the sample from the
stock solution the pH of the medium was not altered.
2.3. Nisin, pH and temperature treatment
The liquid cheese whey (LCW) was prepared to 8 g/l
from solid whey protein concentrate 35% (w/w), provided
by Williner S.A., Arg.
Twenty milliliters of L. innocua culture in log or stationary phase (in agreement with a previously determined
growth curve) were centrifuged at 10,000 rpm for 30 min
and resuspended in 20 ml of LCW at different pH.
The different cell suspensions were exposed to the adequate concentration of nisin and incubated at 7 and
20 C for a maximum of 240 h.
The initial (N0) and the surviving (N) number of viable
cells at different storage times were determined. Dilution
drops (20 ll) were spotted in duplicated onto tryptic soy
agar enriched with 0.6% yeast extract (TSYE). The number
of CFU/ml was determined after incubation at 37 C for 48
hours. Determinations were made in triplicate.
2.4. Modelling of microbial growth
One of the recommended models for describing microbial growth is the modified-Gompertz equation (Zwietering, Jongenburger, Rombouts, & van’t Riet, 1990)
log N ¼ log N 0 þ a expð expðb ðt mÞÞÞ
ð1Þ
where log N is the decimal logarithm of microbial counts
[log (CFU/ml)] at time t; log N0 is the asymptotic log
counts as time decreases indefinitely, approximately equivalent to the log of the initial level of bacteria [log (CFU/
ml)]; a is the count increment as time increases indefinitely,
that is number of log cycles of growth [log (CFU/ml)]; m is
the time required to reach the maximum growth rate
(hours); and b is the specific growth rate at time m
(hours1).
From these parameters, the maximum specific growth
rate [l = b Æ a/e (log (CFU/ml)hour1), where e = 2.7182],
the lag phase duration [LPD = m (1/b) (hours)], and
the maximum population density [MPD = log N0 + a
(log CFU/ml)] were derived.
A logistic model (symmetrical curve) was also applied in
order to test its suitability
log N ¼ log N 0 þ a=ð1 þ expðd c tÞÞ
ð2Þ
where log N and log N0 have the same meaning as above; d
is a dimensionless parameter; and c is the specific growth
rate at the half-time value of the exponential phase
(hours1).
From these parameters, the exponential microbial
growth rate [l = a Æ c/4 (log (CFU/ml) hours1)], and
the lag phase duration [LPD = (d 2/c) (hours)], were
derived.
1088
L.I. Gallo et al. / Food Control 18 (2007) 1086–1092
pH 5.5
pH 6.0
pH 6.5
Log N (Log (CFU/ml))
12
10
8
6
4
2.5. Statistical analysis
2
100 IU/ml Nisin
0
0
24
48
72
96
Time (Hours)
pH 5.5
pH 6.0
pH 6.5
12
Log N (Log (CFU/ml))
The models were applied to every combination of pH,
nisin and temperature where microbial growth occurred.
In those cases where microorganisms did not show sigmoid
curves, an exponential equation was applied.
When the treatment showed a bacteriostatic effect,
straight lines were fitted to the data for log CFU/ml vs.
time. In this case exponential growth rate (l) was close to
zero (Gianuzzi, Pinotti, & Zaritzky, 1997).
10
8
6
4
2
300 IU/ml Nisin
0
0
24
48
72
96
Time (Hours)
Fig. 1. Fitting of Gompertz (curves) model to experimental data (data
point) of L. innocua growth in LCW at 20 C, pH = 5.5, 6.0 and 6.5,
untreated (- - -) and treated (—-) with (a) 100 IU/ml of nisin and (b)
300 IU/ml of nisin.
The equations were fitted to experimental data by nonlinear regression using Systat software (Systat, Table Curve
2D, Vs.1, Inc., 2001). The selected algorithm calculates the
set of parameters with the lowest residual sum of squares
and their 95% confidence interval for the different conditions tested. Average and standard deviation were calculated for the estimated parameters.
Analysis of variance (ANOVA) was applied to the
parameters to determine statistical differences between
different treatments and were compared using the Student
t-test for significant effects identified in the ANOVA
(p < 0.05).
To compare the performance of different models, the
correlation coefficient (R2) and the root mean square error
(RMSE) between experimental data and those predicted
using different models were calculated using Instat V3.03
(GraphPad Software Inc.) and Microsoft Excel. Additionally, the accuracy of models can be assessed graphically by
plotting the predicted values from both models versus the
observed values. A simple linear regression was fitted to
the points and the intercept, the slope and the R2 were
obtained. The closer the intercept is to 0, the slope to 1
Table 1
Gompertz and Logistic parameters for L. innocua growth at 20 C in LCW with different pH and treated with two concentrations of nisin
Parameters
100 IU/ml
pH 5.5
Gompertz model
log N0
a
b
m
R2
RMSE
Logistic model
log N0
a
c
d
R2
RMSE
2.4 ± 0.9a
4.78 ± 0.06
0.14 ± 0.02
36 ± 3
0.9600
0.1299
2.39 ± 0.09
4.81 ± 0.07
0.20 ± 0.02
8±1
0.9606
0.1284
300 IU/ml
pH 6.0
pH 6.5
pH 5.5
pH 6.0
pH 6.5
0.0007 ± 0.0007
8.7 ± 0.1
0.063 ± 0.001
2.4 ± 0.7
1.64 ± 0.04
5.16 ± 0.03
0.044 ± 0.003
43 ± 3
0.98 ± 0.05
5.9 ± 0.1
0.034 ± 0.002
22 ± 5
0.0003 ± 0.00002
8.6 ± 0.2
0.032 ± 0.003
5.3 ± 0.5
0.9602
0.1850
0.9575
0.1268
0.9965
0.0452
0.9644
0.0419
0.9391
0.1331
0.00022 ± 0.00003
8.7 ± 0.2
0.053 ± 0.001
1.02 ± 0.03
0.0006 ± 0.0006
8.7 ± 0.1
0.078 ± 0.007
0.70 ± 0.08
0.0008 ± 0.0004
8.96 ± 0.06
0.371 ± 0.006
8.9 ± 0.4
0.9557
0.2076
0.9518
0.1437
1.70 ± 0.04
4.93 ± 0.03
0.13 ± 0.05
6±1
0.9942
0.0503
0.08 ± 0.08
6.6 ± 0.3
0.044 ± 0.003
1.1 ± 0.1
0.002 ± 0.002
8.7 ± 0.5
0.038 ± 0.007
0.71 ± 0.09
0.9653
0.0385
0.9348
0.1192
R2, regression coefficient. RMSE, root mean square error. log N0, approximately equivalent to the log of the initial level of bacteria (log (CFU/ml));
a, number of log cycles of growth (log (CFU/ml); b, specific growth rate at time m (hours1); m, time required to reach the maximum growth rate (hours);
c, specific growth rate at the half-time value of the exponential phase (hours1); d, dimensionless parameter.
a
Average of two independent trials (±SD).
L.I. Gallo et al. / Food Control 18 (2007) 1086–1092
and the R2 is to 1, the better is the general predictive power
of the model (Zhao, Chen, & Schaffner, 2001).
1089
12
y = 0.9789x + 0.0816
2
R = 0.9761
10
8
6
4
2
Gompertz Model
0
0
2
4
6
8
10
12
Observed data
12
y = 0.9084x + 0.324
2
R = 0.9368
10
Estimated data
It has been previously reported that nisin addition
reduces L. monocytogenes and L. innocua populations in
milk (Harris, Fleming, & Klaenhammer, 1991). Zapico,
Máximo de Paz, & Núñez (1999) showed that it is possible
to achieve a reduction of 3.7–3.8 log cycles in whole milk
by the addition of 100 IU/ml of nisin.
When liquid cheese whey (LCW) was treated with 100
and 300 IU/ml of nisin (Fig. 1(a) and (b)), 5 and 6 log
reductions of L. innocua were achieved at all the pH values
(5.5, 6.0 and 6.5).
Various studies using laboratory media showed that
addition of nisin to a culture of L. monocytogenes resulted
in a rapid decrease of viable counts followed by regrowth
of surviving bacteria to levels similar to those of the
untreated cells (Schillinger, Chung, Keppler, & Holzapfel,
1998; Schillinger, Becker, Vignolo, & Holzapfel, 2001).
For this reason, it is important to evaluate the performance
of L. innocua in LCW during the storage at different
temperatures.
The Gompertz and logistic models were applied to every
culture in which microbial growth was detected and
allowed the prediction of the entire growth curve. Fig. 1
shows the fitting of Gompertz model to L. innocua growth
in LCW at 20 C, pH = 5.5, 6.0 and 6.5, treated with 100
and 300 IU/ml of nisin respectively. In all the experiments,
the initial inoculum size was 3 · 108 CFU/ml.
Table 1 shows the parameters of each model at 20 C in
the presence of nisin. The Gompertz model consistently
produced the best fit to all the growth curves as assessed
using the root mean square error (RMSE) and the correlation coefficient (R2) between the experimental and predicted values. Additionally, good agreement between
experimental data and predicted values were obtained, with
R2 = 0.937 and R2 = 0.976 for the logistic and Gompertz
models respectively (Fig. 2(a) and (b)). Thus, we concluded
that these equations allowed a good prediction of the combined effect of pH and nisin on the behavior of L. innocua
in LCW, preferring because of the closer fit, the Gompertz
model.
The Gompertz equation has become the most widely
used primary model for describing microbial growth
(Cayre, Vignolo, & Garro, 2003). In this investigation,
the Gompertz equation was regarded as sufficient to
describe the regrowth of L. innocua in LCW.
The derived parameters, as the maximum specific
growth rate (l), lag phase duration (LPD) and maximum
population density (MPD) are shown in Fig. 3.
In the absence of nisin (control LCW), at pH 6.0 and
6.5, L. innocua grew immediately, whereas the reduction
of pH to 5.5, produced a lag phase duration (LPD) of
almost 3.4 h (Fig. 3(a)). Robinson, Ocio, Kaloti, & Mackey
(1998), in accordance with our results, found that the lag
Estimated data
3. Results and discussion
8
6
4
2
Logistic Model
0
0
2
4
6
8
10
12
Observed data
Fig. 2. Correlation between observed and estimated data for the behaviour of L. innocua in LCW, calculated with (a) Gompertz model and (b)
Logistic model.
phase was little affected by pH, except close to the limit
of growth (pH = 4.5–5.5), whereas other authors (Johansen, Gram, & Meyer, 1994) found a progressive increase
in lag phase with decreasing pH. At all the pH values studied, the specific growth rates, SGR (l) in control LCW (no
nisin) were similar (Fig. 3(b)). Robinson et al. (1998) found
that the growth rate of L. monocytogenes in broth varied on
a biphasic manner.
The bacteriostatic activity of nisin was highly dependent
on the initial pH of the LCW. No growth was evident
before 28 and 38 h respectively, in cultures having 100 or
300 IU/ml and initial pH of 5.5 (Fig. 3(a) and (b)). Nevertheless, growth occurred at a higher specific rate after the
lag phase.
A maximum population density (MPD) of 3 · 109 CFU/
ml was reached during storage of control LCW at 20 C,
whereas in nisin treated LCW, the MPD reached was lower
(p < 0.05) (Fig. 3(c)). Depression of MPD’s in response to
an increase of nisin concentration or a reduction on pH
values was observed. An increment of nisin concentration
from 100 to 300 IU/ml in LCW, at pH = 6.0, reduced
the MPD from 7.9 · 108 CFU/ml to 7.9 · 106 CFU/ml
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L.I. Gallo et al. / Food Control 18 (2007) 1086–1092
6.5
0
0.15
0.1
0.05
0
5.5
300 l)
100
/m
(IU
in
Nis
6.0
pH
6.5
0
300
)
100
/ml
(IU
n
i
s
Ni
10
9
8
7
6.5
0
/m
300
100
(IU
6.0
pH
Ni
5.5
n
5
l)
6
si
MPD Log (CFU/ml)
6.0
pH
0.2
SGR (Log (CFU/ml)/hours)
5.5
0.25
LPD (Hours)
40
35
30
25
20
15
10
5
0
Fig. 3. Gompertz derived parameters for L. innocua growth in LCW at 20 C, pH = 5.5, 6.0 and 6.5, untreated and treated with 100 IU/ml and 300 IU/ml
of nisin: (a) lag phase duration (LPD), (b) specific growth rate (SGR) (l) and (c) maximum population density (MPD).
(p < 0.05). Whereas a change in the pH of the LCW from
5.5 to 6.5, in the presence of 300 IU/ml of nisin, produced
an increase of the MPD from 4.0 · 106 CFU/ml to
4.0 · 108 CFU/ml (p < 0.05).
Consequently, the combination of a reduced pH (5.5)
and nisin treatment (300 IU/ml) resulted in a final number
of microorganisms three orders lower than in the control
LCW after 192 h of storage at 20 C.
The transitory inhibitory effect of nisin has been
reported previously. Schillinger et al. (2001) found that
3000 IU/ml of nisin were required to cause a significant
reduction in Listeria viable counts in tofu, resulting in a
short-term inhibitory effect. The decrease in viable count
was followed by rapid regrowth of survivors to nisin, during storage of tofu at 10 C. After 24 h, Listeria had
already achieved a cell density which nearly compensated
the initial reduction caused by nisin, in opposite with our
results where the final count of the treated LCW was lower
than the control.
Survivors to nisin, however, are not necessarily resistant
to this bacteriocin. They may also have escaped the action
of nisin due to insufficient bacteriocin availability.
To distinguish whether the cells collected after treatment
with nisin had developed resistance to the bacteriocin or
were simply survivors, the inactivation of the cells was
studied with one or two additions of nisin at different
growth times. Cells recovered from the first addition of
nisin were exposed again to the same concentration of nisin
(50, 100 or 300 IU/ml) in a second phase.
As shown in Table 2, the reduction produced by nisin in
the second phase was lower than that obtained in the first
one, at all the levels of nisin. The results indicate that
recovered L. innocua cells from the first addition had developed tolerance to the bacteriocin over the time exposure.
Table 2
Inactivation of L. innocua in LCW at 20 C, after two-step treatment with 50, 100 and 300 IU/ml of nisin
Second phaseb
First phase
Nisin (IU/ml)
Time (Hour)
Reduction (log (N/N0))
Nisin (IU/ml)
Time (Hour)
Reduction (log (N/N0))c
50
100
300
0
0
0
4.1a
6.1
7.0
50
100
300
3
18
96
1.1
0.9
0.9
a
Average of two independent trials.
The cells were treated with the same concentration of nisin as in the First phase, after the Time indicated () of storage at 20 C. The viability of the
cells was evaluated as informed in Section 2.
c
The reduction achieved is indicated as the decimal logarithm of the rate between N and N0. ‘N0’ corresponds to the viable cells before the addition of
nisin, and ‘N’, to the viable cells obtained after the addition of nisin.
b
L.I. Gallo et al. / Food Control 18 (2007) 1086–1092
Log N (Log (CFU/ml))
12
10
14
12
10
Log (CFU/ml)
This shows close agreement with the observation of ChiZhang et al. (2004), with L. monocytogenes in broth system.
Nisin resistance in Listeria was attributed to changes in
cytoplasmatic membrane fatty acid and phospholipids
compositions in the cell wall (Bouttefroy, Mansour,
Linder, & Millière, 2000; Crandall & Montville, 1998;
Ming & Daeschel, 1995; Verheul, Russell, Van’t Hof,
Rombouts, & Abee, 1997).
Bouttefroy et al. (2000) found that L. monocytogenes
cells surviving nisin or curvacitin 13 were more resistant
to the bacteriocin than cells of the parental strain, and they
concluded that the transitory bactericidal effect of nisin was
due to the growth of spontaneous resistant variants.
A reduction in the storage temperature from 20 C to
7 C produced an important change in the behaviour of
control LCW. At 20 C, L. innocua grew immediately,
whereas at 7 C bacterial population decreased from
1.0 · 1010 to 3.2 · 108 CFU/ml in 240 h.
The treatment of LCW (pH = 5.5) with 100 and 300
IU/ml of nisin showed an immediate important reduction
of L. innocua population, reaching undetectable levels
(<1, 0 log10 CFU/ml) in 48 and 24 h respectively, during
the storage at 7 C (Fig. 4). In accordance with our results,
Robinson et al. (1998) demonstrated that L. monocytogenes
shows a sharp increase in the lag phase as temperature
decreased from 15 C to 5 C. Schillinger et al. (2001)
required 2000 IU/ml of nisin to effectively suppress Listeria
growth in homemade tofu stored at 10 C.
When the level of nisin was reduced to 25 and 50 IU/ml
(pH 5.5 and pH 6.0), the reductions were lower than those
observed with 100 and 300 IU/ml of nisin (p < 0.05)
(Fig. 5). Surprisingly, at pH 6.0, the storage at 7 C of
nisin-treated cells produced a rapid 1-log cycle regrowth
within the first four hours but the cell counts were stabilized in 4 · 108 and 5 · 107 CFU/ml for up to the 168 h
of storage in the presence of 25 and 50 IU/ml of nisin,
respectively.
At pH 5.5, no re-growth was observed after the immediate reduction by 25 IU/ml nisin addition. The regression
1091
8
6
4
2
0 IU/ml pH 6.0
25 IU/ml pH 6.0
50 IU/ml pH 6.0
0 IU/ml pH 5.5
25 IU/ml pH 5.5
50 IU/ml pH 5.5
0
0
24
48
72
96
120
Time (Hours)
144
168
192
Fig. 5. Behaviour of L. innocua in LCW at 7 C, showing the effect of
reducing pH and nisin addition.
analysis revealed that the slope of the regression line was
not significantly different from zero (p > 0.05). The MPD
reached was 2 · 105 CFU/ml. When the level of nisin was
50 IU/ml, a 1-cycle log regrowth of L. innocua was
observed during the 24 h of storage at 7 C and the MPD
reached was 5 · 105 CFU/ml.
In consequence, the MPD values achieved were dependent on the immediate bactericidal effect of nisin addition,
highly affected by initial pH. These data shows the importance of temperature as a controlling factor for L. innocua
regrowth in LCW.
4. Conclusion
It is possible to obtain an important reduction of L.
innocua in LCW with a combination of low pH and nisin
(pH = 5.5, 300 IU/ml of nisin) at 20 C for 38 h. However,
the initial bacterial reduction was followed by regrowth of
nisin-resistant cells. This behaviour indicates that additional barriers may be required to control the growth of
L. innocua. A drop in storage temperature to 7 C, showed
a dramatic reduction of Listeria population, reaching
undetectable levels in 48 h and allowed an increase of the
storage time to 10 days (pH 5.5 and 100 IU/ml of nisin)
without regrowth of the bacteria.
8
Acknowledgements
0 IU/ml
6
100 IU/ml
The authors gratefully acknowledge the financial support given by the Universidad de Buenos Aires, Facultad
de Ingenierı́a and Fundación Antorchas, Argentina. We
also thank Armando Aguirre (AMG S.R.L., Buenos Aires,
Argentina) for the donation of Nisaplin samples.
300 IU/ml
4
2
0
0
24
48
72
96
120
144
168
192
216
240
264
Time (Hours)
Fig. 4. Fitting of exponential model to experimental data of L. innocua
inactivation in LCW at 7 C, pH = 5.5, untreated and treated with
100 IU/ml and 300 IU/ml of nisin.
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