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Recovery of brines from cheesemaking using High-Pressure Homogenization treatments
Accepted Manuscript Recovery Of Brines From Cheesemaking Using High-Pressure Homogenization Treatments
Nadia Innocente, Marilena Marino, Sonia Calligaris PII:
S0260-8774(18)30531-4
DOI:
10.1016/j.jfoodeng.2018.12.012
Reference:
JFOE 9492
To appear in:
Journal of Food Engineering
Received Date:
26 August 2018
Accepted Date:
17 December 2018
Please cite this article as: Nadia Innocente, Marilena Marino, Sonia Calligaris, Recovery Of Brines From Cheesemaking Using High-Pressure Homogenization Treatments, Journal of Food Engineering (2018), doi: 10.1016/j.jfoodeng.2018.12.012
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RECOVERY OF BRINES FROM CHEESEMAKING USING HIGH-
2
PRESSURE HOMOGENIZATION TREATMENTS
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Nadia Innocente, Marilena Marino*, Sonia Calligaris
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Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università degli Studi di Udine, via
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Sondrio 2/A, 33100 Udine
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* Corresponding author:
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Marilena Marino, PhD
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Tel. +39 432 558150
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E-mail address: [email protected]
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1
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Abstract
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The effect of High-Pressure Homogenization treatments at 150 MPa on the viability of microbial
15
flora in natural and spiked brines for cheesemaking was assessed. The microbial reductions
16
increased with the number of passes through the homogenization valve (with or without
17
temperature control) and this behavior was well described by a linear equation. Higher microbial
18
reduction rates were observed when temperature was not controlled during processing. In this case,
19
temperature progressively increased because of HPH process up to 75 °C after 11 passes. The
20
killing effect of HPH treatments was caused by the synergic action of physical and mechanical
21
stresses suffered by the product during the passage through the homogenization valve. These effects
22
were further enlarged when temperature increased as number of passes also increased. The HPH
23
treatments allowed an almost total inactivation of most of the native contaminants just after 5
24
passages, and the same treatment was effective against potentially pathogenic and spoilage
25
microorganisms in the spiked brines, causing the total inactivation of L. monocytogenes.
26 27
Keywords
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High-Pressure Homogenization
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Cheese brine
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Native microflora
31
Listeria monocytogenes
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Pseudomonas
33 34
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1.
Introduction
36 37
Cheese salting is one of the most important operations in cheese making that could affect the overall
38
quality of the product (Guinee, 2004; Innocente et al., 2013). The most widely used salting method
39
is brining that consists of soaking curds in a concentrated salt solution for a time period ranging
40
from few minutes to several hours or days (Innocente et al., 2009). During soaking the curd takes up
41
salt, which decreases the brine salt concentration, and releases water and other compounds,
42
including soluble proteins, fats, minerals, lactose and lactate, making the brine a nutrient-rich
43
medium for microorganisms. Due to these changes, the use of brines over long periods of time
44
causes a significant increase of the microbial flora that is mainly composed of halotolerant
45
microorganisms, such as corynebacteria, micro-staphylococci, yeasts and moulds. Moreover, cheese
46
brines in dairy plants could host microbial spoilers and foodborne pathogens, either coming from
47
environmental sources or from contaminated cheeses. Salmonella enterica, Listeria monocytogenes,
48
Staphylococcus aureus, Escherichia coli and Pseudomonas spp. have been shown to survive for
49
long periods in model and commercial brines (Brown et al., 2018; Larson et al., 1999; Marino et al.,
50
2017). For this reason, the control of brine microbiological quality is of primary importance to
51
ensure consistent daily production. The total replacement of brine is a cost-consuming process not
52
only for the continuous need for water and salt but also for the disposal of used brine. Nowadays,
53
brines are transported and treated externally with costs of about 50-150 euro/ton (Eykens et al.,
54
2018). Thus, strategies for brine recovery and reuse are highly demanded to reduce operating costs
55
and minimize water and environmental footprint. The most common brine recovery method used
56
today in the dairy industry is heat treatment at temperatures higher than 80 °C for 20-50 min
57
(Bintsis, 2007). During the intense heating, besides the desired microbial inactivation, brine
58
compositional changes could occur, mainly associated with protein and salt precipitation
59
accompanied with a decrease in acidity. The main issue related to this event is the lowering of
60
calcium content due to precipitation of calcium phosphate, which negatively affects the further re-
61
use of brines and the quality of the cheese. Moreover, the high temperatures applied may cause the
62
stainless steel exchangers to corrode due to the high salt concentration and the low pH of the brines
63
(Bintsis, 2007). Numerous studies have focused on the possible application of various
64
unconventional treatments for the microbiological regeneration of brines, such as microfiltration,
65
UV-treatment, and ozonization (Bintsis et al., 2000a; Eykens et al., 2018; Guinee, 2007; Marino et
66
al., 2015).
67
High-pressure homogenization (HPH) is a novel technology, which was proven to be efficient in
68
microbial inactivation of fluid foods (Martínez-Monteagudo et al., 2017; Patrignani and Lanciotti, 3
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2016). This technology is based on the same principle as the conventional homogenization, but it is
70
capable of working at higher pressures from 100 to 400 MPa. The killing of vegetative
71
microorganisms is attributed to a combination of physical and mechanical stresses that the fluid
72
undergoes when passing through the high-pressure valve gap, such as spatial pressure and speed
73
gradients, cavitation, pressure drop, shear stress, turbulence and impingement (Donsì et al., 2009;
74
Engler and Robinson, 1981; Shirgaonkar et al., 1998). In such conditions, microbial death is
75
considered to be due to permeabilization of the cell membrane, followed by the deformation of cell
76
structure and cytoplasmatic organelles and leaking out of intracellular material (Ortega-Rivas,
77
2012). Moreover, the temperature increase suffered by the fluid during the process (about 2.5 °C
78
per 10 MPa) as well as the product inlet temperature could affect the microbial inactivation
79
efficiency of the processing (Patrignani and Lanciotti, 2016).
80
HPH technology has shown a great impulse both at industrial level and at research during the last
81
decades demonstrating good antimicrobial effectiveness, while reducing the detrimental effects
82
associated with heat treatments. The aim of the present work was to evaluate the potential of HPH
83
for improving the microbiological quality of used brines for cheesemaking as an alternative to the
84
conventional regeneration treatments. To this purpose, used brines with different salt contents were
85
subjected to HPH treatments at 150 MPa for an increasing number of passes with and without
86
temperature control and the viabilities of native microbial flora were evaluated. Moreover, the
87
resistance to the HPH treatments of specific foodborne pathogens and spoilers (Listeria
88
monocytogenes, Staphylococcus aureus, Pseudomonas fluorescens and Escherichia coli) in spiked
89
brine samples was estimated.
90 91
2.
Materials and methods
92 93
2.1. Brine samples
94
Five used brines were obtained from dairies located in North-Eastern Italy. All brines were used to
95
salt semi-hard cheeses from raw or pasteurized cows' milk and were kept at an average temperature
96
of 11-13 °C. Each brine sample was collected aseptically, cooled, and transported to the laboratory
97
at +4 ° C. Brines were analyzed for titratable acidity, protein and sodium chloride content as
98
previously described (Marino et al., 2015). pH was determined directly using a pH meter at
99
controlled temperature (Hanna Instruments, mod. pH 301, Villafranca Padovana, Italy).
100
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2.2. HPH treatments
102
Before the HPH treatments, at the arrival at the laboratory, each brine sample was divided into two
103
aliquots: (i) the first containing native microflora, i.e. naturally contaminated brines, and the second
104
(ii) spiked aliquot, i.e. brines artificially contaminated with specific foodborne pathogens and
105
spoilers (see paragraph 2.4).
106
For HPH treatments a continuous lab-scale high-pressure homogenizer (Panda Plus 2000, GEA
107
Niro Soavi S.p.a., Parma, Italy) supplied with two Re + type tungsten carbide homogenization
108
valves, with a flow rate of 2.5 cm3/s, was used. The first valve, which is the actual homogenization
109
stage, was set at 150 MPa and the second one at 5 MPa. Aliquots of 200 mL of brine were
110
homogenised via 11 multiple consecutive passes at 10.8 L/h flow rate. Two different sets of
111
experiments were carried out: (i) without temperature control, and (ii) with temperature control, in
112
which the homogenizer inlet and outlet were connected to a heat exchanger (Julabo F70, Julabo
113
GmbH, Seelbach, Germany) set at + 4 °C, to avoid the heating of the brines during processing
114
(Calligaris et al., 2018; Comuzzo et al., 2017; Innocente et al., 2014). The brine inlet temperature
115
was 13 °C, and the brine temperature at the HPH valve outlet as well as the temperature at the heat
116
exchanger outlet was measured by a thermocouple (Ellab, Hillerød, Denmark) connected to a
117
portable data logger (mod. 502A1, Tersid, Milan, Italy). All the experiments were carried out in two
118
replicates on five different brines. After homogenization, 10 mL of each treated suspension were
119
collected in sterile Falcon
120
tubes and subjected to microbiological analysis as reported below.
121 122
2.3. Thermal treatment
123
The total temperature-time combination received by the samples treated at 150 MPa via different
124
numbers of passes through the HPH valve was calculated considering the temperature registered at
125
HPH valve outlet and the residence time of brine in the pipe section located between the HPH valve
126
outlet and the heat exchanger (0.5 s). The same temperature-time combinations were then applied to
127
the brine samples (both naturally contaminated and spiked) in the absence of the HPH treatment
128
(Georget et al., 2014; Thiebaud et al., 2003). To this purpose, brines were treated in a One Gradient
129
Thermocycler (Euroclone, Pero, MI, Italy) by mimicking the same temperature/time profile
130
produced during HPH treatments without temperature control. Following the treatments, the
131
samples were immediately cooled in an ice bath and submitted to microbiological analyses.
132
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2.4.
Microbiological analyses
134
Naturally contaminated brine samples were decimally diluted in Maximum Recovery Diluent
135
(MRD) and examined for the following microbial indexes: total mesophilic count on Gelatin Sugar-
136
Free Agar (incubation at 30 °C for 48 h), Pseudomonas spp. on Pseudomonas Agar Base added
137
with CFC Selective Supplement (30 °C for 48 h), microstaphylococci on Mannitol Salt Agar (30 °C
138
for 48 h), Staphylococcus aureus on Baird Parker Agar RPF (37 °C for 48 h), lactic acid bacteria
139
(LAB) on MRS agar pH=5.4 with 0.025% Delvocid (DSM, Heerlen, the Netherlands) (30 °C for 48
140
h under anaerobic conditions), and yeasts and molds on oxytetracycline Glucose Yeast Extract Agar
141
(25°C for 72 h). To assess the presence of L. monocytogenes, the ISO method 11290 (Anonymous,
142
2017) was used.
143
All the brine samples were spiked with four target bacterial species (S. aureus, L. monocytogenes,
144
E. coli and P. fluorescens). To account for variation in growth and survival, three strains for each
145
species were used as follows: S. aureus (i) DSMZ 20231, (ii) DIAL317, cheese brine isolate, and
146
(iii) DIAL 411, milk isolate; L. monocytogenes (i) DSM 20600, (ii) DSA198, dairy plant isolate,
147
and (iii) DSA1195 cheese isolate; E. coli (i) DSMZ 1116, (ii) DIAL4315 cheese isolate, (iii)
148
DIAL1411 milk isolate; P. fluorescens (i) CECT 378, (ii) DIAL22, dairy plant isolate, and (iii)
149
DIAL049 milk isolate. For each strain, the species assignment was confirmed by partial 16SrRNA
150
gene amplification (Martino et al., 2013). All strains were maintained at −80 °C in Brain Heart
151
Infusion (BHI) with 30% glycerol added. The strains were separately cultured in 2 mL of BHI at 30
152
°C (P. fluorescens) or 37 °C (S. aureus, L. monocytogenes, and E. coli) for 18 h. Then the cultures
153
belonging to the same species were combined, the cells collected by centrifugation at 13,000 rpm
154
(Beckman, Avanti J-25, Palo Alto, CA) at +4 °C for 2 min and washed three times with MRD. Final
155
pellets were resuspended in MRD and added to brines at a final concentration of about 107 CFU/mL
156
per species. Spiked brines were submitted to HPH treatments and immediately analyzed for viable
157
counts using Baird Parker Agar Base with Egg Yolk Tellurite Emulsion for S. aureus (incubation at
158
37 °C for 48 h), Palcam Agar Base with Palcam Selective Supplement for L. monocytogenes (37 °C
159
for 48 h), Violet Red Bile Glucose Agar for E. coli (37 °C for 24 h), and Pseudomonas Agar Base
160
with Pseudomonas CFC Supplement for P. fluorescens (30 °C for 48 h). All culture media were
161
obtained from Oxoid (Milan, Italy).
162 163
2.5. Data fitting
164
Microbial inactivation (log N/N0) as a function of the number of passes was fitted by a linear
165
regression as previously described (Maresca et al., 2011):
166 6
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Log (N/N0) = - k m
(Eq. 1)
168 169
where k is the model parameter and m is the number of passes. The parameter k is the theoretical
170
log-cycle inactivation corresponding to a single pass, then it indicates the sensitivity of the
171
microorganism species to the number of passes at 150 MPa.
172
Microbial inactivation (log N/N0) as a function of the temperature was modelled according to the
173
Weibull distribution (Mafart et al., 2001):
174 175
Log (N/N0)= - (T/)β
(Eq. 2)
176 177
where (N/N0) is the fractional count at the temperature T, is the temperature that allowed to
178
obtain the first logarithmic reduction of the microbial count and β the shape parameter.
179 180
2.6. Statistical analysis
181
The results are the average of at least three measurements carried out on two replicated experiments
182
on each brine. Data are reported as the mean value ± standard deviation. One-way analysis of
183
variance, preceded by the Levene test to verify the homogeneity of variance, were carried out on the
184
means using Statistics 8.0 (Statsoft, Tulsa, Oklahoma, USA). Differences between the means were
185
assessed using the Tukey’s HSD post-hoc test (p<0.05). Linear regression analysis was performed
186
using Microsoft Excel 2013. Modelling according to the Weibull distribution was carried out
187
through GInaFiT tool (Geeraerd et al., 2005). The goodness of fitting was evaluated based on visual
188
inspection of residual plot and by calculation of the coefficient of determination (R2) and the root
189
mean squared error (RMSE).
190 191
3.
Results and discussion
192 193
The brines were first analyzed for their physicochemical and microbiological characteristics (Table
194
1). Large variations were observed in the NaCl concentrations, which ranged from 10.5 to 20.2
195
g/100 mL. These differences can be attributed to inter-factory cheesemaking procedures, variations
196
in curd dimensions and salting time, as well as in milk and curd composition at salting. Low salt
197
content, as observed in brines 1 and 4, can be also related to a long time of reuse or a high daily
198
workload as well as to an inadequate restoration of salt. In fact, during brine salting, NaCl
199
molecules move from brine to the curd as a consequence of the gradient in osmotic pressure
200
between the cheese moisture and the brine, with a consequent reduction of the salt content of the 7
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brine (Walstra et al., 2005). To keep the salinity in an adequate range, additional salt has to be
202
added to the brine. The brines 1 and 4 are also characterized by a higher protein content, which is
203
expelled from the cheeses in exchange for sodium chloride during soaking. On the other hand, no
204
significant differences were found in the values of pH and acidity among different brines.
205
The total mesophilic counts ranged from 5.34 to 6.14 Log CFU/mL among brines and were quite
206
high despite the unfavourable environment. This microflora comes primarily from the surfaces of
207
the cheese curd, and its growth is sustained by the nutrient substances migrating from the cheese to
208
the brine during salting. Brines represent a good growth medium for this specific microflora that is
209
able to withstand the environmental stresses (e.g., acidic pH, high salt concentrations, and low
210
temperature) that characterize cheese brines. The limited literature data indicate that the core
211
microflora is composed by salt-tolerant and psychrotrophic genera such as Acinetobacter,
212
Halomonas, Idiomarina, Staphylococcus, Tetragenococcus, and Pseudomonas, but also of lactic
213
acid bacteria, mainly Lactobacillus, Lactococcus, and Streptococcus (Marino et al., 2017, 2015).
214
Indeed, in this study lactic acid bacteria ranged 4.73-6.89 Log CFU/mL.
215
Microstaphylococci and yeasts and moulds counts ranged 3.13-5.32 Log CFU/mL and 3.03-4.83
216
Log CFU/mL, respectively. In spite of their possible role in the development of the sensory features
217
of cheeses, their ability to metabolize lactic acid, free amino acids and other products derived from
218
the proteolytic activity may cause a pH increase, thus improving the chance of survival and/or
219
growth for pathogenic and spoilage bacteria. In any case, S. aureus and L. monocytogenes were not
220
found in the tested samples (i.e., <1 CFU/mL for S. aureus and absent 25/mL for L.
221
monocytogenes). Enterobacteria and coliforms were below the detection limit (i.e., <1 CFU/mL),
222
too. Instead, Pseudomonas spp. ranged from 3.14 to 5.02 Log CFU/mL. This microbial genus
223
strictly connected to food spoilage is usually present at high levels in raw milk used for
224
cheesemaking. Therefore they contaminate brines being present at high concentration in unripened
225
curds (Carraro et al., 2011). Another possible source of these bacteria is the dairy environment since
226
they are frequently found as resident microbiota on surfaces (Maifreni et al., 2015). Whatever the
227
source, they can survive in brines, which are usually stored at low temperatures, due to their
228
psychrotrophic nature. Considering these results as a whole, brines’ microbial populations appeared
229
quite similar among the five samples, despite the differences in salt content and acidity.
230 231
3.1. HPH inactivation of native flora in brines
232
Figure 1 shows the brine temperature as a function of the number of passes through the
233
homogenization valve at 150 MPa under controlled and uncontrolled temperature conditions. As the
234
number of passes increased, brine temperature increased, reaching 75 °C after 11 passes under 8
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uncontrolled temperature regime. The temperature increase was expected and attributable to the
236
adiabatic heating generated in the homogenizer as a consequence of the physical phenomena that
237
fluid experimented during the process (Patrignani and Lanciotti, 2016). On the other hand, the
238
temperature remained below 36 °C after 11 passes when brines were cooled after each pass of the
239
homogenization process (controlled temperature conditions).
240
The microbial survival as a function of homogenization passes for both uncontrolled and controlled
241
temperature regime in naturally contaminated brines was then evaluated (Figure 2). It should be
242
highlighted that the data reported are the mean ± standard deviation of all the experimental trials
243
obtained after HPH treatments of the five brines considered (10 single trials, coming from two
244
independent replicates for each brine). In fact, no significant different behaviour was observed
245
depending on brine physicochemical characteristics, as confirmed by the low values of the resulting
246
standard deviations. This result indicates that in the range of the considered compositional
247
parameters, the HPH effect was not affected by the brine composition.
248
The native microbial populations decreased as the number of passes increased in both controlled
249
and uncontrolled temperature conditions (Figure 2). When the temperature remained below 36 °C
250
during the controlled temperature regime, the microbial reductions ranged 1-2 Log CFU/mL after
251
11 passes through the HPH valve. By contrast, a more intense and progressive reduction was
252
evident as a consequence of the uncontrolled temperature treatments. Indeed, a reduction of about 6
253
Log CFU/mL in total mesophilic counts was observed after 11 passes (final temperature 75 °C),
254
while lactic acid bacteria were almost completely inactivated (<1 CFU/mL) after eight passes
255
(71°C). Microstaphylococci, Pseudomonas spp., and yeasts and moulds were totally inactivated
256
(<10 CFU/mL) after only five passes (63 °C). In all cases, the microbial inactivation resulted well
257
described by a linear behavior as a function of the number of passes (R2≥ 0.91). Table 2 reports the
258
regression parameters of microbial inactivation estimated by fitting the data with the linear
259
regression model (Eq. 1). In particular, k values were estimated, which are a measure of the
260
inactivation rate of the treatment.
261
Considering the brines HPH-treated under controlled temperature conditions, the k values for
262
microstaphylococci and lactic acid bacteria resulted lower than that of Pseudomonas spp. These
263
results are in agreement with previous studies showing that Gram-positive bacteria (as
264
microstaphylococci and lactic acid bacteria are) are more resistant to HPH than Gram-negative
265
bacteria (Pseudomonas spp.). This resistance to mechanical stress has been attributed to the
266
composition of the cell wall, more precisely, to peptidoglycan structure. Indeed, it is well known
267
that Gram-positive bacteria have a thicker peptidoglycan (about 40 layers) than Gram-negative (1
268
up to 5 layers) (Reith and Mayer, 2011). According to this consideration, it is conceivable that, in 9
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the case of samples treated with temperature control, the HPH treatments killed bacteria mainly
270
through a mechanical stress on cells, caused by the spatial pressure and velocity gradients,
271
turbulence, impingement and/or cavitation, that occur in a liquid during an HPH process
272
(Shirgaonkar et al., 1998). Other authors also postulated that the cell shape can be an additional
273
factor determining bacterial resistance to HPH, and cocci are expected to be more easily disrupted
274
than rods. Indeed, it is well known that shear stresses and the resulting cell damages may more
275
strongly affect rod bacteria, which have wider cell surface areas than the more compact coccoid
276
cells (Senz et al., 2015). This observation may explain, at least in part, the higher resistance of
277
microstaphylococci (k=-0.091) compared whit that of lactic acid bacteria (k= -0.141), which are
278
presumably a mixture of cocci and rods. However, these differences may also be related to a greater
279
ability of microstaphylococci to adapt to brine environment and therefore to overcome mechanical
280
stresses more easily (Marino et al., 2017).
281
Yeasts and moulds showed k values comparable to that of Gram-positive bacteria. This can be due
282
from one side to the cell wall structure of the eukaryotic cell that is strengthened by β-glucan and
283
mannoprotein layers, from the other side to their higher sensitiveness to HPH because of the larger
284
size of yeast and moulds in comparison to bacteria (Donsì et al., 2013). Moreover, eukaryotic
285
organisms such as yeasts and moulds have a lower cell surface area:volume ratio, and a higher
286
complexity due to the compartmentation of the cellular functions, thus becoming more sensitive to
287
mechanical stresses as compared to prokaryotic cells (Alamprese and Foschino, 2011).
288
For all microorganisms considered, the k values were higher in the samples treated under
289
uncontrolled temperature conditions than under controlled ones. As expected and consistent with
290
literature data on other matrices, the temperature suffered by the samples during the HPH process
291
contributed to bacteria inactivation (Codina-Torrella et al., 2018). Microstaphylococci showed the
292
highest resistance, which could be attributed to the thermoduric nature of this group of bacteria
293
(Sepulveda et al., 2005).
294
To better decipher the relative contribution of the mechanical and thermal stresses on the microbial
295
killing, the temperature increase suffered by samples HPH-treated under uncontrolled temperature
296
conditions (Figure 1) was simulated without passages through the HPH valve. In Figure 3 the
297
microbial survival was plotted as a function of the temperature for samples HPH-treated in
298
uncontrolled temperature conditions and for unhomogenized samples. For each experimental
299
condition and for each microbial group considered, the microbial reduction vs. temperature was
300
modelled according to the Weibull distribution (Eq. 2), and model parameters were reported in
301
Table 3. The Weibull model exhibited a strong fit, as indicated by the high coefficients (R2>0.95)
302
and relatively low RSME obtained for all microbial groups considered. The shape parameters (β) 10
ACCEPTED MANUSCRIPT 303
were always higher than 1, indicating the existence of a shoulder in the inactivation kinetics. The
304
shoulder suggests an initial resistance to stress, after which the remaining cells became increasingly
305
susceptible to the treatment as the process stresses increase. In other words, this indicates that there
306
is cumulative damage occurring making it increasingly difficult for the cells to survive.
307
By using the Weibull model, it was possible to calculate the temperature that allowed to obtain the
308
first log-reduction of the microbial count (, °C). For all microbial groups considered, the values
309
in samples HPH-treated under uncontrolled temperature conditions were lower than those of the
310
samples thermally treated without homogenization. In other terms, the inactivation power of
311
thermal treatments at 150 MPa was higher than those at atmospheric pressure. In particular, the
312
greatest differences were found for microstaphylococci, Pseudomonas spp., yeasts and moulds. In
313
these cases, the temperature that allowed achieving the 90% inactivation of the viable count was
314
even 20 °C lower at 150 MPa than at atmospheric pressure. It can, therefore, be concluded that at
315
the working pressure considered in this study, the microbial reductions were achieved by the
316
synergic action of physical and mechanical stresses, due to forcing through the homogenization
317
valve, and temperature.
318 319
3.2. HPH treatments of spiked brines
320
Various types of microorganisms, which include potential pathogens and spoilers, are reported in
321
the literature as possible contaminants of cheese brines (Bintsis et al., 2000b; Marino et al., 2017).
322
In this study, P. fluorescens, L. monocytogenes, S. aureus and E. coli were selected as target species
323
of HPH treatments, in consideration of their involvement in spoilage of dairy foods or their ability
324
to cause dairy-associated foodborne diseases (Segat et al., 2014). To this aim, brines were spiked
325
with a cocktail culture of selected strains and submitted to HPH-treatments under controlled and
326
uncontrolled temperature conditions. Figure 4 shows the inactivation curves of these species as a
327
function of the number of passes through the HPH valve.
328
The number of passes through the homogenization valve strongly affected the viability of all
329
bacterial species in both controlled and uncontrolled temperature conditions. Table 4 reports model
330
parameters of bacterial inactivation estimated by fitting the linear regression model. The application
331
of this kinetic model returned high coefficient of determination values (R2>0.96).
332
As previously highlighted for microorganisms naturally present in brines, the k values in HPH-
333
treated samples under uncontrolled temperature conditions were higher than those treated under
334
controlled temperature conditions. Moreover, in agreement with previously reported data, Gram-
335
positive bacteria were significantly more resistant than Gram-negative bacteria. Anyway, for both
336
L. monocytogenes and S. aureus, an inactivation of about 7 Log CFU/mL was observed after 5 and 11
ACCEPTED MANUSCRIPT 337
4 passes, respectively. These results are relevant in consideration of the role of these bacteria as
338
pathogens and their relative resistance to environmental stresses, above all high salt concentrations
339
(Brown et al., 2018). Among the Gram-negative bacteria, E. coli was more sensitive to HPH
340
treatments than P. fluorescens. This result is apparently in disagreement with previous data,
341
reporting a higher sensitivity of P. fluorescens respect to E. coli (Wuytack et al., 2002). This
342
inconsistency could be due to the fact that in the two studies different strains were used.
343
Also in this part of the study, in order to better understand the respective contributions to
344
inactivation of the thermal and mechanical stresses during HPH-treatments, the temperature
345
increase measured during HPH-treatments was simulated at atmospheric pressure. Figure 5 shows
346
the microbial reductions in spiked brines as a function of the temperature for samples HPH-treated
347
under uncontrolled temperature conditions and for unhomogenized samples.
348
For each experimental condition and for each microbial group considered, the microbial reduction
349
vs. temperature was modelled according to the Weibull distribution, which exhibited a strong fit as
350
indicated by the high coefficients of determination (R2>0.95) and relatively low RSME (Table 5).
351
For all microbial species, the temperature that allowed to obtain the first logarithmic reduction of
352
the microbial count was lower in samples HPH treated in uncontrolled temperature conditions than
353
in samples thermally treated without homogenization. For example, in the case of S. aureus, the
354
temperature that allowed to achieve the 90% inactivation of the viable count was 71.50 °C at the
355
atmospheric pressure and 45.48 °C at 150 MPa, respectively. Similar observations were made for
356
the other bacterial species. It can, therefore, be confirmed that both the mechanical phenomena and
357
the temperature increase taking place in the HPH valve contributed to microbial inactivation of
358
microorganisms inoculated in brine.
359 360
4.
Conclusions
361 362
The data obtained have shown that the HPH treatments carried out on cheese brines are effective in
363
reducing the microbial counts of native flora. By comparing the results obtained in the HPH
364
treatments performed under controlled temperature conditions and the thermal treatments without
365
homogenization, it was possible to evidence that both the mechanical and the thermal damage
366
contribute to the total antimicrobial effect. Therefore, considering the same temperatures reached by
367
the brine, an HPH treatment allows a stronger reduction of the microbial counts compared to a
368
conventional thermal regeneration treatment. Regarding the reduction of the native microbial flora,
369
the HPH treatments allow an almost total inactivation of most of the contaminants
370
(microstaphylococci, Pseudomonas, yeasts and molds) just after 5 passages through the 12
ACCEPTED MANUSCRIPT 371
homogenization valve at 150 MPa without thermal control. Greater resistance has been observed
372
only for total mesophilic bacteria and lactic acid bacteria. In any case, considering that the purpose
373
of brine regeneration is to keep microbial flora under control and not to carry out a sterilization, it is
374
believed that the treatment might be successfully applied in the dairy field. The same treatment was
375
also effective against potentially pathogenic and spoilage microorganisms in the spiked brines,
376
allowing the total inactivation of L. monocytogenes, one of the biggest microbial threats in the food
377
context.
378
Based on results acquired in this study, HPH can be considered a feasible novel technology to the
379
implemented in dairy industry instead of conventional heat treatment to recovery brines, allowing
380
brine management in a more sustainable way. Starting from this point and in the attempt to develop
381
a process that can be industrially exploitable, further research has to be carried out to define the best
382
combination in terms of inlet and processing temperature, homogenization pressure and number of
383
passes to obtain the desired brine microbial inactivation. Due to emerging nature of the technology,
384
experiments conducted at lab scale should be then validated at industrial scale.
385 386
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food matrices and characterisation of the penocin operon. Antonie van Leeuwenhoek, Int. J.
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Shirgaonkar, I.Z., Lothe, R.R., Pandit, A.B., 1998. Comments on the mechanism of microbial cell disruption in high-pressure and high-speed devices. Biotechnol. Prog. 14, 657–660. Thiebaud, M., Dumay, E., Picart, L., Guiraud, J.P., Cheftel, J.C., 2003. High-pressure
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homogenisation of raw bovine milk. Effects on fat globule size distribution and microbial
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inactivation. Int. Dairy J. 13, 427–439.
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Walstra, P., Wouters, J.T.M., Geurts, T.J., 2005. Cheese manufacture, in: Walstra, P., Wouters,
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J.T.M., Geurts, T.J. (Eds.), Dairy Science and Technology. CRC Press, Boca Raton, FL, pp.
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583–640.
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Wuytack, E.Y., Diels, A.M.J., Michiels, C.W., 2002. Bacterial inactivation by high-pressure
490
homogenisation and high hydrostatic pressure. Int. J. Food Microbiol. 77, 205–212.
491
16
ACCEPTED MANUSCRIPT Figure captions Figure 1. Brine temperature at the HPH valve outlet as a function of the number of passes at 150 MPa for samples treated under controlled (■) and uncontrolled (▲) temperature conditions. Brine inlet temperature was 13°C. Figure 2. Microbial inactivation in naturally contaminated brines as a function of the number of passes through HPH valve. (a) Total mesophilic count; b) Lactic acid bacteria; (c) Microstaphylococci; (d) Pseudomonas spp.; (e) Yeasts and moulds. ■ HPH treatment under controlled temperature conditions; ▲ HPH treatment under uncontrolled temperature conditions. Regular lines represent data fitted by the linear regression model. Figure 3. Microbial inactivation in naturally contaminated brines as a function of temperature for HPH treated (▲) and unhomogenized samples (●). (a) Total mesophilic count; (b) Lactic acid bacteria; (c) Microstaphylococci; (d) Pseudomonas spp.; (e) Yeasts and moulds. Regular lines represent data fitted by the Weibull model.
Figure 4. Microbial inactivation in spiked brines as a function of the number of passes through homogenization valve at 150 MPa pressure. (a) L. monocytogenes; b) S. aureus; (c) P. fluorescens; (d) E. coli. ■ HPH treatment under controlled temperature conditions; ▲ HPH treatment in uncontrolled temperature conditions. Regular lines represent data fitted by the linear regression model.
Figure 5. Microbial inactivation in spiked brines as a function of temperature for HPH treated (▲) and unpressured samples (●). (a) L. monocytogenes; b) S. aureus; (c) P. fluorescens; (d) E. coli. Regular lines represent data fitted by the Weibull model.
ACCEPTED MANUSCRIPT Highlights
HPH treatments are effective in killing microflora in used brines for cheesemaking
The microbial inactivation follows a linear kinetic as a function of the number of passes
Inactivation rates are higher for HPH treatments under uncontrolled temperature conditions
Microbial killing originates by the synergic action of high pressure and temperature
5 passages through the HPH valve reduce of 5 Log CFU/mL the viability of L. monocytogenes
ACCEPTED MANUSCRIPT Table 1. Physicochemical characteristics and microbial viable counts (Log CFU/mL) of cheese brines Brine sample 1
2
3
4
5
NaCl (g/100 mL)
13.8
16.6
20.2
10.5
18.5
pH
5.32
5.25
5.28
5.21
5.29
Acidity (°SH/50 mL)
8.4
11.3
10.6
10.6
10.1
Proteins (g/100 g)
0.31
0.10
0.16
0.27
0.13
Total mesophilic count
5.78
6.14
6.04
5.34
5.88
Lactic acid bacteria
5.41
6.89
4.73
5.04
5.67
Microstaphylococci
4.03
3.93
5.32
4.05
3.13
Pseudomonas spp.
5.02
4.92
3.14
4.83
3.87
Yeasts and moulds
4.83
4.51
3.03
4.52
3.58
ACCEPTED MANUSCRIPT Table 2. Model parameter k and regression coefficient R2 obtained from the fitting of inactivation data of native flora in brines as a function of number of homogenization passes Controlled T
Uncontrolled T
k ± SE
R2
k ± SE
R2
Total count
-0.196 ± 0.023
0.94
-0.529 ± 0.016
0.99
Lactic acid bacteria
-0.141 ± 0.022
0.91
-0.551 ± 0.022
0.99
Microstaphylococci
-0.091 ± 0.012
0.95
-0.423 ± 0.056
0.97
Pseudomonas spp.
-0.185 ± 0.019
0.95
-0.589 ± 0.081
0.95
Yeasts and molds
-0.151 ± 0.020
0.92
-0.652 ± 0.055
0.98
ACCEPTED MANUSCRIPT Table 3. Model parameters and regression coefficient estimated by fitting Weibull model on reduction of brine native flora counts as a function of temperature for HPH treatments at 150 MPa under uncontrolled temperature conditions and for thermal treatments without homogenization. = temperature that allowed to obtain the first logarithmic reduction of the microbial count (°C); β= shape parameter; R2= coefficient of determination; RMSE= root mean squared error Thermal treatment
Thermal treatment
at atmospheric pressure
at 150 MPa
(°C)
β
R2
RMSE
(°C)
β
R2
RMSE
Total count
45.03
2.55
0.99
0.1158
40.35
2.95
0.98
0.4303
Lactic acid bacteria
64.89
9.38
0.95
0.4075
53.89
4.86
0.98
0.3084
Microstaphylococci
65.22
5.28
0.95
0.1858
44.69
1.79
0.98
0.1341
Pseudomonas spp.
54.48
3.72
0.95
0.3350
31.42
2.30
0.99
0.2722
Yeasts and molds
62.64
5.45
1.00
0.0713
37.79
2.08
0.99
0.1540
ACCEPTED MANUSCRIPT Table 4. Model parameter k and regression coefficient R2 obtained from the fitting of inactivation data of spiked brines as a function of number of homogenization passes. Controlled T
Uncontrolled T
k ± SE
R2
k ± SE
R2
L. monocytogenes
-0.201 ± 0.007
0.99
-1.063 ± 0.088
0.97
S. aureus
-0.226 ± 0.011
0.98
-0.925 ± 0.099
0.97
P. fluorescens
-0.519 ± 0.024
0.98
-1.503 ± 0.213
0.96
E. coli
-0.981 ± 0.045
0.97
-2.128 ± 0.080
0.97
ACCEPTED MANUSCRIPT Table 5. Model parameters and regression coefficient estimated by fitting Weibull model on reduction of spiked brines counts as a function of temperature for HPH treatments at 150 MPa under uncontrolled temperature conditions and for thermal treatments without homogenization. =temperature that allowed to obtain the first logarithmic reduction of the microbial count (°C); β=shape parameter; R2= coefficient of determination; RMSE= root mean squared error Thermal treatment
Thermal treatment
at atmospheric pressure
at 150 MPa
(°C)
β
R2
RMSE
(°C)
β
R2
RMSE
L. monocytogenes
61.44
2.28
0.99
0.0707
46.15
4.32
1.00
0.0857
S. aureus
71.50
7.95
0.98
0.0921
45.48
3.98
1.00
0.1196
P. fluorescens
34.66
1.91
1.00
0.1149
26.58
2.07
0.98
0.4610
E. coli
40.41
2.51
0.97
0.3208
28.74
1.91
0.98
0.3740
Nadia Innocente, Marilena Marino, Sonia Calligaris PII:
S0260-8774(18)30531-4
DOI:
10.1016/j.jfoodeng.2018.12.012
Reference:
JFOE 9492
To appear in:
Journal of Food Engineering
Received Date:
26 August 2018
Accepted Date:
17 December 2018
Please cite this article as: Nadia Innocente, Marilena Marino, Sonia Calligaris, Recovery Of Brines From Cheesemaking Using High-Pressure Homogenization Treatments, Journal of Food Engineering (2018), doi: 10.1016/j.jfoodeng.2018.12.012
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ACCEPTED MANUSCRIPT 1
RECOVERY OF BRINES FROM CHEESEMAKING USING HIGH-
2
PRESSURE HOMOGENIZATION TREATMENTS
3
Nadia Innocente, Marilena Marino*, Sonia Calligaris
4 5
Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università degli Studi di Udine, via
6
Sondrio 2/A, 33100 Udine
7 8
* Corresponding author:
9
Marilena Marino, PhD
10
Tel. +39 432 558150
11
E-mail address: [email protected]
12
1
ACCEPTED MANUSCRIPT 13
Abstract
14
The effect of High-Pressure Homogenization treatments at 150 MPa on the viability of microbial
15
flora in natural and spiked brines for cheesemaking was assessed. The microbial reductions
16
increased with the number of passes through the homogenization valve (with or without
17
temperature control) and this behavior was well described by a linear equation. Higher microbial
18
reduction rates were observed when temperature was not controlled during processing. In this case,
19
temperature progressively increased because of HPH process up to 75 °C after 11 passes. The
20
killing effect of HPH treatments was caused by the synergic action of physical and mechanical
21
stresses suffered by the product during the passage through the homogenization valve. These effects
22
were further enlarged when temperature increased as number of passes also increased. The HPH
23
treatments allowed an almost total inactivation of most of the native contaminants just after 5
24
passages, and the same treatment was effective against potentially pathogenic and spoilage
25
microorganisms in the spiked brines, causing the total inactivation of L. monocytogenes.
26 27
Keywords
28
High-Pressure Homogenization
29
Cheese brine
30
Native microflora
31
Listeria monocytogenes
32
Pseudomonas
33 34
2
ACCEPTED MANUSCRIPT 35
1.
Introduction
36 37
Cheese salting is one of the most important operations in cheese making that could affect the overall
38
quality of the product (Guinee, 2004; Innocente et al., 2013). The most widely used salting method
39
is brining that consists of soaking curds in a concentrated salt solution for a time period ranging
40
from few minutes to several hours or days (Innocente et al., 2009). During soaking the curd takes up
41
salt, which decreases the brine salt concentration, and releases water and other compounds,
42
including soluble proteins, fats, minerals, lactose and lactate, making the brine a nutrient-rich
43
medium for microorganisms. Due to these changes, the use of brines over long periods of time
44
causes a significant increase of the microbial flora that is mainly composed of halotolerant
45
microorganisms, such as corynebacteria, micro-staphylococci, yeasts and moulds. Moreover, cheese
46
brines in dairy plants could host microbial spoilers and foodborne pathogens, either coming from
47
environmental sources or from contaminated cheeses. Salmonella enterica, Listeria monocytogenes,
48
Staphylococcus aureus, Escherichia coli and Pseudomonas spp. have been shown to survive for
49
long periods in model and commercial brines (Brown et al., 2018; Larson et al., 1999; Marino et al.,
50
2017). For this reason, the control of brine microbiological quality is of primary importance to
51
ensure consistent daily production. The total replacement of brine is a cost-consuming process not
52
only for the continuous need for water and salt but also for the disposal of used brine. Nowadays,
53
brines are transported and treated externally with costs of about 50-150 euro/ton (Eykens et al.,
54
2018). Thus, strategies for brine recovery and reuse are highly demanded to reduce operating costs
55
and minimize water and environmental footprint. The most common brine recovery method used
56
today in the dairy industry is heat treatment at temperatures higher than 80 °C for 20-50 min
57
(Bintsis, 2007). During the intense heating, besides the desired microbial inactivation, brine
58
compositional changes could occur, mainly associated with protein and salt precipitation
59
accompanied with a decrease in acidity. The main issue related to this event is the lowering of
60
calcium content due to precipitation of calcium phosphate, which negatively affects the further re-
61
use of brines and the quality of the cheese. Moreover, the high temperatures applied may cause the
62
stainless steel exchangers to corrode due to the high salt concentration and the low pH of the brines
63
(Bintsis, 2007). Numerous studies have focused on the possible application of various
64
unconventional treatments for the microbiological regeneration of brines, such as microfiltration,
65
UV-treatment, and ozonization (Bintsis et al., 2000a; Eykens et al., 2018; Guinee, 2007; Marino et
66
al., 2015).
67
High-pressure homogenization (HPH) is a novel technology, which was proven to be efficient in
68
microbial inactivation of fluid foods (Martínez-Monteagudo et al., 2017; Patrignani and Lanciotti, 3
ACCEPTED MANUSCRIPT 69
2016). This technology is based on the same principle as the conventional homogenization, but it is
70
capable of working at higher pressures from 100 to 400 MPa. The killing of vegetative
71
microorganisms is attributed to a combination of physical and mechanical stresses that the fluid
72
undergoes when passing through the high-pressure valve gap, such as spatial pressure and speed
73
gradients, cavitation, pressure drop, shear stress, turbulence and impingement (Donsì et al., 2009;
74
Engler and Robinson, 1981; Shirgaonkar et al., 1998). In such conditions, microbial death is
75
considered to be due to permeabilization of the cell membrane, followed by the deformation of cell
76
structure and cytoplasmatic organelles and leaking out of intracellular material (Ortega-Rivas,
77
2012). Moreover, the temperature increase suffered by the fluid during the process (about 2.5 °C
78
per 10 MPa) as well as the product inlet temperature could affect the microbial inactivation
79
efficiency of the processing (Patrignani and Lanciotti, 2016).
80
HPH technology has shown a great impulse both at industrial level and at research during the last
81
decades demonstrating good antimicrobial effectiveness, while reducing the detrimental effects
82
associated with heat treatments. The aim of the present work was to evaluate the potential of HPH
83
for improving the microbiological quality of used brines for cheesemaking as an alternative to the
84
conventional regeneration treatments. To this purpose, used brines with different salt contents were
85
subjected to HPH treatments at 150 MPa for an increasing number of passes with and without
86
temperature control and the viabilities of native microbial flora were evaluated. Moreover, the
87
resistance to the HPH treatments of specific foodborne pathogens and spoilers (Listeria
88
monocytogenes, Staphylococcus aureus, Pseudomonas fluorescens and Escherichia coli) in spiked
89
brine samples was estimated.
90 91
2.
Materials and methods
92 93
2.1. Brine samples
94
Five used brines were obtained from dairies located in North-Eastern Italy. All brines were used to
95
salt semi-hard cheeses from raw or pasteurized cows' milk and were kept at an average temperature
96
of 11-13 °C. Each brine sample was collected aseptically, cooled, and transported to the laboratory
97
at +4 ° C. Brines were analyzed for titratable acidity, protein and sodium chloride content as
98
previously described (Marino et al., 2015). pH was determined directly using a pH meter at
99
controlled temperature (Hanna Instruments, mod. pH 301, Villafranca Padovana, Italy).
100
4
ACCEPTED MANUSCRIPT 101
2.2. HPH treatments
102
Before the HPH treatments, at the arrival at the laboratory, each brine sample was divided into two
103
aliquots: (i) the first containing native microflora, i.e. naturally contaminated brines, and the second
104
(ii) spiked aliquot, i.e. brines artificially contaminated with specific foodborne pathogens and
105
spoilers (see paragraph 2.4).
106
For HPH treatments a continuous lab-scale high-pressure homogenizer (Panda Plus 2000, GEA
107
Niro Soavi S.p.a., Parma, Italy) supplied with two Re + type tungsten carbide homogenization
108
valves, with a flow rate of 2.5 cm3/s, was used. The first valve, which is the actual homogenization
109
stage, was set at 150 MPa and the second one at 5 MPa. Aliquots of 200 mL of brine were
110
homogenised via 11 multiple consecutive passes at 10.8 L/h flow rate. Two different sets of
111
experiments were carried out: (i) without temperature control, and (ii) with temperature control, in
112
which the homogenizer inlet and outlet were connected to a heat exchanger (Julabo F70, Julabo
113
GmbH, Seelbach, Germany) set at + 4 °C, to avoid the heating of the brines during processing
114
(Calligaris et al., 2018; Comuzzo et al., 2017; Innocente et al., 2014). The brine inlet temperature
115
was 13 °C, and the brine temperature at the HPH valve outlet as well as the temperature at the heat
116
exchanger outlet was measured by a thermocouple (Ellab, Hillerød, Denmark) connected to a
117
portable data logger (mod. 502A1, Tersid, Milan, Italy). All the experiments were carried out in two
118
replicates on five different brines. After homogenization, 10 mL of each treated suspension were
119
collected in sterile Falcon
120
tubes and subjected to microbiological analysis as reported below.
121 122
2.3. Thermal treatment
123
The total temperature-time combination received by the samples treated at 150 MPa via different
124
numbers of passes through the HPH valve was calculated considering the temperature registered at
125
HPH valve outlet and the residence time of brine in the pipe section located between the HPH valve
126
outlet and the heat exchanger (0.5 s). The same temperature-time combinations were then applied to
127
the brine samples (both naturally contaminated and spiked) in the absence of the HPH treatment
128
(Georget et al., 2014; Thiebaud et al., 2003). To this purpose, brines were treated in a One Gradient
129
Thermocycler (Euroclone, Pero, MI, Italy) by mimicking the same temperature/time profile
130
produced during HPH treatments without temperature control. Following the treatments, the
131
samples were immediately cooled in an ice bath and submitted to microbiological analyses.
132
5
ACCEPTED MANUSCRIPT 133
2.4.
Microbiological analyses
134
Naturally contaminated brine samples were decimally diluted in Maximum Recovery Diluent
135
(MRD) and examined for the following microbial indexes: total mesophilic count on Gelatin Sugar-
136
Free Agar (incubation at 30 °C for 48 h), Pseudomonas spp. on Pseudomonas Agar Base added
137
with CFC Selective Supplement (30 °C for 48 h), microstaphylococci on Mannitol Salt Agar (30 °C
138
for 48 h), Staphylococcus aureus on Baird Parker Agar RPF (37 °C for 48 h), lactic acid bacteria
139
(LAB) on MRS agar pH=5.4 with 0.025% Delvocid (DSM, Heerlen, the Netherlands) (30 °C for 48
140
h under anaerobic conditions), and yeasts and molds on oxytetracycline Glucose Yeast Extract Agar
141
(25°C for 72 h). To assess the presence of L. monocytogenes, the ISO method 11290 (Anonymous,
142
2017) was used.
143
All the brine samples were spiked with four target bacterial species (S. aureus, L. monocytogenes,
144
E. coli and P. fluorescens). To account for variation in growth and survival, three strains for each
145
species were used as follows: S. aureus (i) DSMZ 20231, (ii) DIAL317, cheese brine isolate, and
146
(iii) DIAL 411, milk isolate; L. monocytogenes (i) DSM 20600, (ii) DSA198, dairy plant isolate,
147
and (iii) DSA1195 cheese isolate; E. coli (i) DSMZ 1116, (ii) DIAL4315 cheese isolate, (iii)
148
DIAL1411 milk isolate; P. fluorescens (i) CECT 378, (ii) DIAL22, dairy plant isolate, and (iii)
149
DIAL049 milk isolate. For each strain, the species assignment was confirmed by partial 16SrRNA
150
gene amplification (Martino et al., 2013). All strains were maintained at −80 °C in Brain Heart
151
Infusion (BHI) with 30% glycerol added. The strains were separately cultured in 2 mL of BHI at 30
152
°C (P. fluorescens) or 37 °C (S. aureus, L. monocytogenes, and E. coli) for 18 h. Then the cultures
153
belonging to the same species were combined, the cells collected by centrifugation at 13,000 rpm
154
(Beckman, Avanti J-25, Palo Alto, CA) at +4 °C for 2 min and washed three times with MRD. Final
155
pellets were resuspended in MRD and added to brines at a final concentration of about 107 CFU/mL
156
per species. Spiked brines were submitted to HPH treatments and immediately analyzed for viable
157
counts using Baird Parker Agar Base with Egg Yolk Tellurite Emulsion for S. aureus (incubation at
158
37 °C for 48 h), Palcam Agar Base with Palcam Selective Supplement for L. monocytogenes (37 °C
159
for 48 h), Violet Red Bile Glucose Agar for E. coli (37 °C for 24 h), and Pseudomonas Agar Base
160
with Pseudomonas CFC Supplement for P. fluorescens (30 °C for 48 h). All culture media were
161
obtained from Oxoid (Milan, Italy).
162 163
2.5. Data fitting
164
Microbial inactivation (log N/N0) as a function of the number of passes was fitted by a linear
165
regression as previously described (Maresca et al., 2011):
166 6
ACCEPTED MANUSCRIPT 167
Log (N/N0) = - k m
(Eq. 1)
168 169
where k is the model parameter and m is the number of passes. The parameter k is the theoretical
170
log-cycle inactivation corresponding to a single pass, then it indicates the sensitivity of the
171
microorganism species to the number of passes at 150 MPa.
172
Microbial inactivation (log N/N0) as a function of the temperature was modelled according to the
173
Weibull distribution (Mafart et al., 2001):
174 175
Log (N/N0)= - (T/)β
(Eq. 2)
176 177
where (N/N0) is the fractional count at the temperature T, is the temperature that allowed to
178
obtain the first logarithmic reduction of the microbial count and β the shape parameter.
179 180
2.6. Statistical analysis
181
The results are the average of at least three measurements carried out on two replicated experiments
182
on each brine. Data are reported as the mean value ± standard deviation. One-way analysis of
183
variance, preceded by the Levene test to verify the homogeneity of variance, were carried out on the
184
means using Statistics 8.0 (Statsoft, Tulsa, Oklahoma, USA). Differences between the means were
185
assessed using the Tukey’s HSD post-hoc test (p<0.05). Linear regression analysis was performed
186
using Microsoft Excel 2013. Modelling according to the Weibull distribution was carried out
187
through GInaFiT tool (Geeraerd et al., 2005). The goodness of fitting was evaluated based on visual
188
inspection of residual plot and by calculation of the coefficient of determination (R2) and the root
189
mean squared error (RMSE).
190 191
3.
Results and discussion
192 193
The brines were first analyzed for their physicochemical and microbiological characteristics (Table
194
1). Large variations were observed in the NaCl concentrations, which ranged from 10.5 to 20.2
195
g/100 mL. These differences can be attributed to inter-factory cheesemaking procedures, variations
196
in curd dimensions and salting time, as well as in milk and curd composition at salting. Low salt
197
content, as observed in brines 1 and 4, can be also related to a long time of reuse or a high daily
198
workload as well as to an inadequate restoration of salt. In fact, during brine salting, NaCl
199
molecules move from brine to the curd as a consequence of the gradient in osmotic pressure
200
between the cheese moisture and the brine, with a consequent reduction of the salt content of the 7
ACCEPTED MANUSCRIPT 201
brine (Walstra et al., 2005). To keep the salinity in an adequate range, additional salt has to be
202
added to the brine. The brines 1 and 4 are also characterized by a higher protein content, which is
203
expelled from the cheeses in exchange for sodium chloride during soaking. On the other hand, no
204
significant differences were found in the values of pH and acidity among different brines.
205
The total mesophilic counts ranged from 5.34 to 6.14 Log CFU/mL among brines and were quite
206
high despite the unfavourable environment. This microflora comes primarily from the surfaces of
207
the cheese curd, and its growth is sustained by the nutrient substances migrating from the cheese to
208
the brine during salting. Brines represent a good growth medium for this specific microflora that is
209
able to withstand the environmental stresses (e.g., acidic pH, high salt concentrations, and low
210
temperature) that characterize cheese brines. The limited literature data indicate that the core
211
microflora is composed by salt-tolerant and psychrotrophic genera such as Acinetobacter,
212
Halomonas, Idiomarina, Staphylococcus, Tetragenococcus, and Pseudomonas, but also of lactic
213
acid bacteria, mainly Lactobacillus, Lactococcus, and Streptococcus (Marino et al., 2017, 2015).
214
Indeed, in this study lactic acid bacteria ranged 4.73-6.89 Log CFU/mL.
215
Microstaphylococci and yeasts and moulds counts ranged 3.13-5.32 Log CFU/mL and 3.03-4.83
216
Log CFU/mL, respectively. In spite of their possible role in the development of the sensory features
217
of cheeses, their ability to metabolize lactic acid, free amino acids and other products derived from
218
the proteolytic activity may cause a pH increase, thus improving the chance of survival and/or
219
growth for pathogenic and spoilage bacteria. In any case, S. aureus and L. monocytogenes were not
220
found in the tested samples (i.e., <1 CFU/mL for S. aureus and absent 25/mL for L.
221
monocytogenes). Enterobacteria and coliforms were below the detection limit (i.e., <1 CFU/mL),
222
too. Instead, Pseudomonas spp. ranged from 3.14 to 5.02 Log CFU/mL. This microbial genus
223
strictly connected to food spoilage is usually present at high levels in raw milk used for
224
cheesemaking. Therefore they contaminate brines being present at high concentration in unripened
225
curds (Carraro et al., 2011). Another possible source of these bacteria is the dairy environment since
226
they are frequently found as resident microbiota on surfaces (Maifreni et al., 2015). Whatever the
227
source, they can survive in brines, which are usually stored at low temperatures, due to their
228
psychrotrophic nature. Considering these results as a whole, brines’ microbial populations appeared
229
quite similar among the five samples, despite the differences in salt content and acidity.
230 231
3.1. HPH inactivation of native flora in brines
232
Figure 1 shows the brine temperature as a function of the number of passes through the
233
homogenization valve at 150 MPa under controlled and uncontrolled temperature conditions. As the
234
number of passes increased, brine temperature increased, reaching 75 °C after 11 passes under 8
ACCEPTED MANUSCRIPT 235
uncontrolled temperature regime. The temperature increase was expected and attributable to the
236
adiabatic heating generated in the homogenizer as a consequence of the physical phenomena that
237
fluid experimented during the process (Patrignani and Lanciotti, 2016). On the other hand, the
238
temperature remained below 36 °C after 11 passes when brines were cooled after each pass of the
239
homogenization process (controlled temperature conditions).
240
The microbial survival as a function of homogenization passes for both uncontrolled and controlled
241
temperature regime in naturally contaminated brines was then evaluated (Figure 2). It should be
242
highlighted that the data reported are the mean ± standard deviation of all the experimental trials
243
obtained after HPH treatments of the five brines considered (10 single trials, coming from two
244
independent replicates for each brine). In fact, no significant different behaviour was observed
245
depending on brine physicochemical characteristics, as confirmed by the low values of the resulting
246
standard deviations. This result indicates that in the range of the considered compositional
247
parameters, the HPH effect was not affected by the brine composition.
248
The native microbial populations decreased as the number of passes increased in both controlled
249
and uncontrolled temperature conditions (Figure 2). When the temperature remained below 36 °C
250
during the controlled temperature regime, the microbial reductions ranged 1-2 Log CFU/mL after
251
11 passes through the HPH valve. By contrast, a more intense and progressive reduction was
252
evident as a consequence of the uncontrolled temperature treatments. Indeed, a reduction of about 6
253
Log CFU/mL in total mesophilic counts was observed after 11 passes (final temperature 75 °C),
254
while lactic acid bacteria were almost completely inactivated (<1 CFU/mL) after eight passes
255
(71°C). Microstaphylococci, Pseudomonas spp., and yeasts and moulds were totally inactivated
256
(<10 CFU/mL) after only five passes (63 °C). In all cases, the microbial inactivation resulted well
257
described by a linear behavior as a function of the number of passes (R2≥ 0.91). Table 2 reports the
258
regression parameters of microbial inactivation estimated by fitting the data with the linear
259
regression model (Eq. 1). In particular, k values were estimated, which are a measure of the
260
inactivation rate of the treatment.
261
Considering the brines HPH-treated under controlled temperature conditions, the k values for
262
microstaphylococci and lactic acid bacteria resulted lower than that of Pseudomonas spp. These
263
results are in agreement with previous studies showing that Gram-positive bacteria (as
264
microstaphylococci and lactic acid bacteria are) are more resistant to HPH than Gram-negative
265
bacteria (Pseudomonas spp.). This resistance to mechanical stress has been attributed to the
266
composition of the cell wall, more precisely, to peptidoglycan structure. Indeed, it is well known
267
that Gram-positive bacteria have a thicker peptidoglycan (about 40 layers) than Gram-negative (1
268
up to 5 layers) (Reith and Mayer, 2011). According to this consideration, it is conceivable that, in 9
ACCEPTED MANUSCRIPT 269
the case of samples treated with temperature control, the HPH treatments killed bacteria mainly
270
through a mechanical stress on cells, caused by the spatial pressure and velocity gradients,
271
turbulence, impingement and/or cavitation, that occur in a liquid during an HPH process
272
(Shirgaonkar et al., 1998). Other authors also postulated that the cell shape can be an additional
273
factor determining bacterial resistance to HPH, and cocci are expected to be more easily disrupted
274
than rods. Indeed, it is well known that shear stresses and the resulting cell damages may more
275
strongly affect rod bacteria, which have wider cell surface areas than the more compact coccoid
276
cells (Senz et al., 2015). This observation may explain, at least in part, the higher resistance of
277
microstaphylococci (k=-0.091) compared whit that of lactic acid bacteria (k= -0.141), which are
278
presumably a mixture of cocci and rods. However, these differences may also be related to a greater
279
ability of microstaphylococci to adapt to brine environment and therefore to overcome mechanical
280
stresses more easily (Marino et al., 2017).
281
Yeasts and moulds showed k values comparable to that of Gram-positive bacteria. This can be due
282
from one side to the cell wall structure of the eukaryotic cell that is strengthened by β-glucan and
283
mannoprotein layers, from the other side to their higher sensitiveness to HPH because of the larger
284
size of yeast and moulds in comparison to bacteria (Donsì et al., 2013). Moreover, eukaryotic
285
organisms such as yeasts and moulds have a lower cell surface area:volume ratio, and a higher
286
complexity due to the compartmentation of the cellular functions, thus becoming more sensitive to
287
mechanical stresses as compared to prokaryotic cells (Alamprese and Foschino, 2011).
288
For all microorganisms considered, the k values were higher in the samples treated under
289
uncontrolled temperature conditions than under controlled ones. As expected and consistent with
290
literature data on other matrices, the temperature suffered by the samples during the HPH process
291
contributed to bacteria inactivation (Codina-Torrella et al., 2018). Microstaphylococci showed the
292
highest resistance, which could be attributed to the thermoduric nature of this group of bacteria
293
(Sepulveda et al., 2005).
294
To better decipher the relative contribution of the mechanical and thermal stresses on the microbial
295
killing, the temperature increase suffered by samples HPH-treated under uncontrolled temperature
296
conditions (Figure 1) was simulated without passages through the HPH valve. In Figure 3 the
297
microbial survival was plotted as a function of the temperature for samples HPH-treated in
298
uncontrolled temperature conditions and for unhomogenized samples. For each experimental
299
condition and for each microbial group considered, the microbial reduction vs. temperature was
300
modelled according to the Weibull distribution (Eq. 2), and model parameters were reported in
301
Table 3. The Weibull model exhibited a strong fit, as indicated by the high coefficients (R2>0.95)
302
and relatively low RSME obtained for all microbial groups considered. The shape parameters (β) 10
ACCEPTED MANUSCRIPT 303
were always higher than 1, indicating the existence of a shoulder in the inactivation kinetics. The
304
shoulder suggests an initial resistance to stress, after which the remaining cells became increasingly
305
susceptible to the treatment as the process stresses increase. In other words, this indicates that there
306
is cumulative damage occurring making it increasingly difficult for the cells to survive.
307
By using the Weibull model, it was possible to calculate the temperature that allowed to obtain the
308
first log-reduction of the microbial count (, °C). For all microbial groups considered, the values
309
in samples HPH-treated under uncontrolled temperature conditions were lower than those of the
310
samples thermally treated without homogenization. In other terms, the inactivation power of
311
thermal treatments at 150 MPa was higher than those at atmospheric pressure. In particular, the
312
greatest differences were found for microstaphylococci, Pseudomonas spp., yeasts and moulds. In
313
these cases, the temperature that allowed achieving the 90% inactivation of the viable count was
314
even 20 °C lower at 150 MPa than at atmospheric pressure. It can, therefore, be concluded that at
315
the working pressure considered in this study, the microbial reductions were achieved by the
316
synergic action of physical and mechanical stresses, due to forcing through the homogenization
317
valve, and temperature.
318 319
3.2. HPH treatments of spiked brines
320
Various types of microorganisms, which include potential pathogens and spoilers, are reported in
321
the literature as possible contaminants of cheese brines (Bintsis et al., 2000b; Marino et al., 2017).
322
In this study, P. fluorescens, L. monocytogenes, S. aureus and E. coli were selected as target species
323
of HPH treatments, in consideration of their involvement in spoilage of dairy foods or their ability
324
to cause dairy-associated foodborne diseases (Segat et al., 2014). To this aim, brines were spiked
325
with a cocktail culture of selected strains and submitted to HPH-treatments under controlled and
326
uncontrolled temperature conditions. Figure 4 shows the inactivation curves of these species as a
327
function of the number of passes through the HPH valve.
328
The number of passes through the homogenization valve strongly affected the viability of all
329
bacterial species in both controlled and uncontrolled temperature conditions. Table 4 reports model
330
parameters of bacterial inactivation estimated by fitting the linear regression model. The application
331
of this kinetic model returned high coefficient of determination values (R2>0.96).
332
As previously highlighted for microorganisms naturally present in brines, the k values in HPH-
333
treated samples under uncontrolled temperature conditions were higher than those treated under
334
controlled temperature conditions. Moreover, in agreement with previously reported data, Gram-
335
positive bacteria were significantly more resistant than Gram-negative bacteria. Anyway, for both
336
L. monocytogenes and S. aureus, an inactivation of about 7 Log CFU/mL was observed after 5 and 11
ACCEPTED MANUSCRIPT 337
4 passes, respectively. These results are relevant in consideration of the role of these bacteria as
338
pathogens and their relative resistance to environmental stresses, above all high salt concentrations
339
(Brown et al., 2018). Among the Gram-negative bacteria, E. coli was more sensitive to HPH
340
treatments than P. fluorescens. This result is apparently in disagreement with previous data,
341
reporting a higher sensitivity of P. fluorescens respect to E. coli (Wuytack et al., 2002). This
342
inconsistency could be due to the fact that in the two studies different strains were used.
343
Also in this part of the study, in order to better understand the respective contributions to
344
inactivation of the thermal and mechanical stresses during HPH-treatments, the temperature
345
increase measured during HPH-treatments was simulated at atmospheric pressure. Figure 5 shows
346
the microbial reductions in spiked brines as a function of the temperature for samples HPH-treated
347
under uncontrolled temperature conditions and for unhomogenized samples.
348
For each experimental condition and for each microbial group considered, the microbial reduction
349
vs. temperature was modelled according to the Weibull distribution, which exhibited a strong fit as
350
indicated by the high coefficients of determination (R2>0.95) and relatively low RSME (Table 5).
351
For all microbial species, the temperature that allowed to obtain the first logarithmic reduction of
352
the microbial count was lower in samples HPH treated in uncontrolled temperature conditions than
353
in samples thermally treated without homogenization. For example, in the case of S. aureus, the
354
temperature that allowed to achieve the 90% inactivation of the viable count was 71.50 °C at the
355
atmospheric pressure and 45.48 °C at 150 MPa, respectively. Similar observations were made for
356
the other bacterial species. It can, therefore, be confirmed that both the mechanical phenomena and
357
the temperature increase taking place in the HPH valve contributed to microbial inactivation of
358
microorganisms inoculated in brine.
359 360
4.
Conclusions
361 362
The data obtained have shown that the HPH treatments carried out on cheese brines are effective in
363
reducing the microbial counts of native flora. By comparing the results obtained in the HPH
364
treatments performed under controlled temperature conditions and the thermal treatments without
365
homogenization, it was possible to evidence that both the mechanical and the thermal damage
366
contribute to the total antimicrobial effect. Therefore, considering the same temperatures reached by
367
the brine, an HPH treatment allows a stronger reduction of the microbial counts compared to a
368
conventional thermal regeneration treatment. Regarding the reduction of the native microbial flora,
369
the HPH treatments allow an almost total inactivation of most of the contaminants
370
(microstaphylococci, Pseudomonas, yeasts and molds) just after 5 passages through the 12
ACCEPTED MANUSCRIPT 371
homogenization valve at 150 MPa without thermal control. Greater resistance has been observed
372
only for total mesophilic bacteria and lactic acid bacteria. In any case, considering that the purpose
373
of brine regeneration is to keep microbial flora under control and not to carry out a sterilization, it is
374
believed that the treatment might be successfully applied in the dairy field. The same treatment was
375
also effective against potentially pathogenic and spoilage microorganisms in the spiked brines,
376
allowing the total inactivation of L. monocytogenes, one of the biggest microbial threats in the food
377
context.
378
Based on results acquired in this study, HPH can be considered a feasible novel technology to the
379
implemented in dairy industry instead of conventional heat treatment to recovery brines, allowing
380
brine management in a more sustainable way. Starting from this point and in the attempt to develop
381
a process that can be industrially exploitable, further research has to be carried out to define the best
382
combination in terms of inlet and processing temperature, homogenization pressure and number of
383
passes to obtain the desired brine microbial inactivation. Due to emerging nature of the technology,
384
experiments conducted at lab scale should be then validated at industrial scale.
385 386
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ACCEPTED MANUSCRIPT Figure captions Figure 1. Brine temperature at the HPH valve outlet as a function of the number of passes at 150 MPa for samples treated under controlled (■) and uncontrolled (▲) temperature conditions. Brine inlet temperature was 13°C. Figure 2. Microbial inactivation in naturally contaminated brines as a function of the number of passes through HPH valve. (a) Total mesophilic count; b) Lactic acid bacteria; (c) Microstaphylococci; (d) Pseudomonas spp.; (e) Yeasts and moulds. ■ HPH treatment under controlled temperature conditions; ▲ HPH treatment under uncontrolled temperature conditions. Regular lines represent data fitted by the linear regression model. Figure 3. Microbial inactivation in naturally contaminated brines as a function of temperature for HPH treated (▲) and unhomogenized samples (●). (a) Total mesophilic count; (b) Lactic acid bacteria; (c) Microstaphylococci; (d) Pseudomonas spp.; (e) Yeasts and moulds. Regular lines represent data fitted by the Weibull model.
Figure 4. Microbial inactivation in spiked brines as a function of the number of passes through homogenization valve at 150 MPa pressure. (a) L. monocytogenes; b) S. aureus; (c) P. fluorescens; (d) E. coli. ■ HPH treatment under controlled temperature conditions; ▲ HPH treatment in uncontrolled temperature conditions. Regular lines represent data fitted by the linear regression model.
Figure 5. Microbial inactivation in spiked brines as a function of temperature for HPH treated (▲) and unpressured samples (●). (a) L. monocytogenes; b) S. aureus; (c) P. fluorescens; (d) E. coli. Regular lines represent data fitted by the Weibull model.
ACCEPTED MANUSCRIPT Highlights
HPH treatments are effective in killing microflora in used brines for cheesemaking
The microbial inactivation follows a linear kinetic as a function of the number of passes
Inactivation rates are higher for HPH treatments under uncontrolled temperature conditions
Microbial killing originates by the synergic action of high pressure and temperature
5 passages through the HPH valve reduce of 5 Log CFU/mL the viability of L. monocytogenes
ACCEPTED MANUSCRIPT Table 1. Physicochemical characteristics and microbial viable counts (Log CFU/mL) of cheese brines Brine sample 1
2
3
4
5
NaCl (g/100 mL)
13.8
16.6
20.2
10.5
18.5
pH
5.32
5.25
5.28
5.21
5.29
Acidity (°SH/50 mL)
8.4
11.3
10.6
10.6
10.1
Proteins (g/100 g)
0.31
0.10
0.16
0.27
0.13
Total mesophilic count
5.78
6.14
6.04
5.34
5.88
Lactic acid bacteria
5.41
6.89
4.73
5.04
5.67
Microstaphylococci
4.03
3.93
5.32
4.05
3.13
Pseudomonas spp.
5.02
4.92
3.14
4.83
3.87
Yeasts and moulds
4.83
4.51
3.03
4.52
3.58
ACCEPTED MANUSCRIPT Table 2. Model parameter k and regression coefficient R2 obtained from the fitting of inactivation data of native flora in brines as a function of number of homogenization passes Controlled T
Uncontrolled T
k ± SE
R2
k ± SE
R2
Total count
-0.196 ± 0.023
0.94
-0.529 ± 0.016
0.99
Lactic acid bacteria
-0.141 ± 0.022
0.91
-0.551 ± 0.022
0.99
Microstaphylococci
-0.091 ± 0.012
0.95
-0.423 ± 0.056
0.97
Pseudomonas spp.
-0.185 ± 0.019
0.95
-0.589 ± 0.081
0.95
Yeasts and molds
-0.151 ± 0.020
0.92
-0.652 ± 0.055
0.98
ACCEPTED MANUSCRIPT Table 3. Model parameters and regression coefficient estimated by fitting Weibull model on reduction of brine native flora counts as a function of temperature for HPH treatments at 150 MPa under uncontrolled temperature conditions and for thermal treatments without homogenization. = temperature that allowed to obtain the first logarithmic reduction of the microbial count (°C); β= shape parameter; R2= coefficient of determination; RMSE= root mean squared error Thermal treatment
Thermal treatment
at atmospheric pressure
at 150 MPa
(°C)
β
R2
RMSE
(°C)
β
R2
RMSE
Total count
45.03
2.55
0.99
0.1158
40.35
2.95
0.98
0.4303
Lactic acid bacteria
64.89
9.38
0.95
0.4075
53.89
4.86
0.98
0.3084
Microstaphylococci
65.22
5.28
0.95
0.1858
44.69
1.79
0.98
0.1341
Pseudomonas spp.
54.48
3.72
0.95
0.3350
31.42
2.30
0.99
0.2722
Yeasts and molds
62.64
5.45
1.00
0.0713
37.79
2.08
0.99
0.1540
ACCEPTED MANUSCRIPT Table 4. Model parameter k and regression coefficient R2 obtained from the fitting of inactivation data of spiked brines as a function of number of homogenization passes. Controlled T
Uncontrolled T
k ± SE
R2
k ± SE
R2
L. monocytogenes
-0.201 ± 0.007
0.99
-1.063 ± 0.088
0.97
S. aureus
-0.226 ± 0.011
0.98
-0.925 ± 0.099
0.97
P. fluorescens
-0.519 ± 0.024
0.98
-1.503 ± 0.213
0.96
E. coli
-0.981 ± 0.045
0.97
-2.128 ± 0.080
0.97
ACCEPTED MANUSCRIPT Table 5. Model parameters and regression coefficient estimated by fitting Weibull model on reduction of spiked brines counts as a function of temperature for HPH treatments at 150 MPa under uncontrolled temperature conditions and for thermal treatments without homogenization. =temperature that allowed to obtain the first logarithmic reduction of the microbial count (°C); β=shape parameter; R2= coefficient of determination; RMSE= root mean squared error Thermal treatment
Thermal treatment
at atmospheric pressure
at 150 MPa
(°C)
β
R2
RMSE
(°C)
β
R2
RMSE
L. monocytogenes
61.44
2.28
0.99
0.0707
46.15
4.32
1.00
0.0857
S. aureus
71.50
7.95
0.98
0.0921
45.48
3.98
1.00
0.1196
P. fluorescens
34.66
1.91
1.00
0.1149
26.58
2.07
0.98
0.4610
E. coli
40.41
2.51
0.97
0.3208
28.74
1.91
0.98
0.3740