The effect of dry aging on instrumental, chemical and microbiological parameters of organic beef loin muscle


Hulánková, R.; Kameník, J.; Saláková, A.; Závodský, D.; Borilova, G.

Lebensmittel-Wissenschaft und Technologie 89: 559-565

2018


LWT
-
Food
Science
and
Technology
89
(2018)
559-565
Contents
lists
available
at
ScienceDirect
LWT-
Food
Science
and
Technology
LWT
-
Food
Science
and
Technology
ELSEVT'
journal
homepage:
www.elsevier.com/locate/Iwt
The
effect
of
dry
aging
on
instrumental,
chemical
and
microbiological
parameters
of
organic
beef
loin
muscle
R.
Hulankova
,
J.
Kamenik
,
A.
Salakova
,
D.
Zavodskfr
,
G.
Borilova
a
University
of
Veterinary
and
Pharmaceutical
Sciences
Brno,
Faculty
of
Veterinary
Hygiene
and
Ecology,
Department
of
Meat
Hygiene
and
Technology,
Palackeho
tr.
1946/1,
612
42
Brno,
Czech
Republic
b
CEITEC
-
Central
European
Institute
of
Technology,
University
of
Veterinary
and
Pharmaceutical
Sciences
Brno,
Palackeho
tr.
1946/1,
612
42
Brno,
Czech
Republic
ARTICLE
INFO
ABSTRACT
Keywords:
Dry
aging
Beef
Organic
meat
Wamer-Bratzler
Meat
color
The
aim
of
this
study
was
to
assess
the
effect
of
aging
at
1
°C
for
12-36
d
on
instrumental,
chemical
and
microbiological
characteristics
of
beef
loin
muscles.
There
were
no
significant
changes
in
pH,
L*,
a*
and
b*
during
prolonged
aging.
The
aging
of
beef
had
a
positive
effect
on
its
tenderness
as
demonstrated
by
decreasing
of
shear
force.
The
water
losses
amounted
to
around
3.0%
up
to
21
d
of
aging,
with
further
increase
with
an
extended
period
of
aging.
Fresh
beef
had
a
good
microbiological
quality
with
Total
Viable
Count,
psychrotrophic
and
lactic
acid
bacteria
of
2.59
±
0.65,
2.47
±
0.61
and
1.04
±
0.25
log
CFU
per
cm
2
of
the
surface,
respectively.
The
mean
values
for
Total
Viable
Count
and
psychrotrophic
microorganisms
after
14
and
more
days
of
aging
were
approx.
5
log
CFU/cm
2
.
Prolonged
aging
for
more
than
14
d
increased
tenderness
but
did
not
promote
microbial
growth.
1.
Introduction
Tenderness
is
one
of
the
most
frequently
studied
characteristics
of
cooked
meat
(Baldwin,
2012).
The
tenderness
of
meat
is
influenced
primarily
by
the
composition
and
contractile
state
of
muscle
fibers,
the
amount
and
solubility
of
connective
tissue,
and
the
extent
of
proteolysis
post
mortem
(Joo,
Kim,
Hwang,
&
Ryu,
2013).
Proteolytic
changes
in
the
muscles
after
the
slaughter
of
the
animal
are
part
of
the
process
called
meat
aging.
Meat
aging
is
a
complex
process
to
which
groups
of
various
endogenic
proteases
contribute,
and
this
process
begins
im-
mediately
after
the
slaughter
of
the
animal
(Kemp
&
Parr,
2012).
The
structural
integrity
of
myofibrils
changes
as
a
consequence
of
the
de-
gradation
of
muscle
proteins
such
as
titin,
nebulin
and
desmin
(Starkey,
Geesink,
Collins,
Oddy,
&
Hopkins,
2016).
The
integrity
of
in-
tramuscular
connective
tissue
also
decreases,
evidently
as
a
result
of
the
action
of
collagenase
with
A-glucuronidase
or
hyaluronidase
(Nishimura,
2015).
The
action
of
enzymes
on
meat
proteins
requires
a
certain
amount
of
time
-
a
minimum
of
around
two
weeks
in
the
case
of
beef
(Perry,
2012).
In
addition
to
the
tenderness
of
the
meat,
aging
also
affects
the
juiciness
and
taste
of
the
meat
(Kim,
Kemp,
&
Samuelsson,
2016).
There
are,
in
principle,
two
methods
of
meat
aging.
Dry
aging
is
performed
by
placing
beef
carcasses
or
primal
cuts
in
cold
stores
with
a
managed
regime
of
air
temperature,
relative
humidity
and
air
flow
speed.
Wet
aging
means
the
vacuum-packing
of
cuts
of
meat
in
foil
with
barrier
properties
and
their
placement
in
cold
stores.
In
this
case,
the
air
temperature
is
the
important
parameter.
Neither
the
humidity
nor
the
speed
of
the
air
flow
play
any
role
in
wet
aging.
Dry
aging
of
meat
is,
however,
preferable
from
the
viewpoint
of
the
taste
of
the
meat
fol-
lowing
culinary
preparation.
Aromatic
substances
which
have
a
fa-
vourable
effect
on
taste
and
aroma
are
formed
during
dry
aging.
The
development
of
these
substances
is
proportional
to
the
length
of
meat
aging
(Perry,
2012).
Extending
the
storage
of
meat,
on
the
other
hand,
creates
conditions
for
the
growth
of
psychrotrophic
microflora
capable
of
multiplying
on
the
meat
at
refrigeration
temperatures.
Dry
aging,
in
which
meat
is
exposed
to
an
atmosphere
of
air,
may
provide
an
opportunity
for
aerobic
gram-negative
bacteria
of
the
genus
Pseudomonas
which
are
part
of
the
meat
spoilage
microbiota
(Blana
&
Nychas,
2014).
There-
fore,
in
addition
to
strictly
controlled
temperature
it
is
also
necessary
during
dry
aging
to
monitor
the
relative
humidity
in
the
cold
store
where
drying
of
the
meat
surface
inhibits
the
growth
of
bacteria
as
a
result
of
decreasing
water
activity.
However,
if
the
air
humidity
is
too
low,
there
is
a
risk
of
greater
weight
losses
resulting
from
the
eva-
poration
of
water
and
the
formation
of
a
surface
crust on
the
meat.
This
results
in
higher
economic
losses.
*
Corresponding
author.
University
of
Veterinary
and
Pharmaceutical
Sciences
Brno,
Faculty
of
Veterinary
Hygiene
and
Ecology,
Department
of
Meat
Hygiene
and
Technology,
Palackeho
tr.
1946/1,
612
42
Brno,
Czech
Republic.
E-mail
address:
hulankovar@vfu.cz
(R.
Hulankova).
https://doi.org/10.101641wt.2017.11.014
Received
2
May
2017;
Received
in
revised
form
27
October
2017;
Accepted
9
November
2017
Available
online
11
November
2017
0023-6438/
@
2017
Elsevier
Ltd.
All
rights
reserved.
R.
Huldnicovd
et
al.
LWT
-
Food
Science
and
Technology
89
(2018)
559-565
There
are
a
number
of
studies
that
consider
the
effect
of
aging
on
selected
properties
of
meat
(Colle
et
al.,
2015;
Kim
et
al.,
2016;
Laster
et
al.,
2008;
Lepper-Blilie,
Berg,
Buchanan,
&
Berg,
2016;
Starkey
et
al.,
2016).
However,
the
majority
of
them
have
monitored
changes
during
the
course
of
wet
aging
or
evaluated
quality
indicators
without
more
detailed
microbiological
analysis
of
the
meat.
In
recent
years,
dry
aging
of
beef
has
spread
from
the
USA
to
European
countries
such
as
Germany
(Bartholoma,
Schering,
&
Horn,
2013)
and
the
Czech
Republic.
There
are
only
rare
examples
of
publications
from
these
countries
assessing
the
effect
of
aging
on
the
properties
of
meat.
The
aim
of
this
study
was
to
perform
an
assessment
of
the
effect
of
dry
aging
performed
on
beef
hind
quarters
directly
at
the
slaughterhouse
on
the
instrumental,
che-
mical
and
microbiological
characteristics
of
loin
muscles.
2.
Materials
and
methods
2.1.
Samples
of
meat
The
samples
of
meat
were
taken
from
cattle
of
Aberdeen
Angus
breed
(bulls
old
26-43
months
and
heifers
old
18-32
months)
reared
under
organic
farming
conditions
on
several
farms
in
the
Czech
Republic.
The
animals
were
slaughtered
from
June
to
November
2016
at
one
slaughterhouse
intended
for
organic
meat
production.
After
slaughter,
the
cattle
carcasses
were
quartered
and
the
quarters
stored
in
a
cold
store
at
a
temperature
of
1
±
1
°C,
an
air
flow
0.5
±
0.2
m
5
-1
and
a
relative
air
humidity
of
85
±
2%.
Samples
of
loin
without
bone
weighing
around
300
g
were
taken
at
the
level
of
the
9th
thoracic
vertebra.
Sample
0
was
taken
24
h
after
slaughter
and
transported
at
4
°C
within
2
h
to
the
laboratory
at
the
University
of
Veterinary
and
Pharmaceutical
Sciences
Brno.
Another
sample
was
taken
at
the
end
of
aging
(12-36
d)
from
the
same
place
on
the
second
hind
quarter
and
transported
for
further
analyses
under
the
same
conditions.
A
total
of
54
samples
of
meat
from
27
carcasses
(bulls
n
=
14;
heifers
n
=
13)
were
analysed.
Each
group
of
samples
(bulls,
heifers)
was
further
di-
vided
into
two
groups
according
to
the
length
of
aging
-
a
period
of
aging
shorter
than
21
d
(the
average
length
amounted
to
14.6
d
in
heifers,
n
=
6,
and
13.9
d
in
bulls,
n
=
8)
and
a
period
of
aging
longer
than
21
d
(the
average
length
of
aging
amounted
to
26.7
d
in
heifers,
n
=
7,
and
26.8
d
in
bulls,
n
=
6).
Instrumental
and
chemical
para-
meters
were
analysed
specifically
in
m.
longissimus
thoracis.
2.2.
Instrumental
analysis
Meat
color
was
measured
using
a
Konica
Minolta
CM-2600d
spec-
trophotometer
(Konica
Minolta
Sensing
Inc.,
Osaka,
Japan)
calibrated
against
a
white
standard
plate
using
an
8-mm
diameter
measuring
aperture,
illuminant
D65
and
10°
standard
observer.
L*
(lightness),
a*
(redness),
b*
(yellowness)
were
measured,
the
value
of
chroma
C*
and
hue
angle
were
calculated
using
Equations
(1)
and
(2):
C*
=
Va*
2
+
b*
2
(1)
=
arctan—
b*
a*
(2)
At
the
beginning
(Day
0)
and
end
of
the
study,
color
measurements
of
the
loin
muscles
were
taken
from
five
locations
on
the
fresh
cut.
The
color
change
during
aging
was
determined
using
the
color
differences
coefficient
(AE)
between
the
initial
color
and
end
color
of
the
samples,
calculated
from
Equation
(3):
ziE*
=
V(L*
end
-
L*
0
)
2
+
(a*
en
d
-
a*
0
)
2
+
(b*
end
-
b*0)
2
(3)
pH
values
were
measured
with
a
Double
Pore
needle
probe
(Hamilton,
Switzerland)
on
a
340i
WTW
pH-meter
(WTW,
Germany).
The
pH
va-
lues
were
taken
from
three
locations
on
each
sample.
Warner-Bratzler
shear
force
(WBSF)
was
measured
using
the
method
described
by
Honikel
(1998)
after
heat
treatment.
For
each
heat
treated
sample,
six
strips
were
cut,
being
at
least
20
mm
long
and
with
a
100-mm
2
(10
x
10
mm)
cross-sectional
area.
The
strips
were
tested
on
an
Instron
5544
universal
testing
machine
(Instron
Cor.,
USA).
Heat
treatment
was
performed
on
a
contact
grill.
Samples
(2
cm
high)
were
grilled
in
aluminium
foil
for
5
min
and
40
s.
The
samples
were
rotated
after
half
this
period
had
elapsed.
2.3.
Chemical
analysis
A
drying
method
(ISO
1442,
1997)
at
103
±
2
T
for
a
period
of
24
h
was
used
for
the
determination
of
the
content
of
dry
matter.
The
fat
content
was
determined
using
a
SOXTEC
instrument
(TECATOR,
Sweden).
Diethyl
ether
(Penta
Inc.,
Czech
Republic)
was
used
as
the
extraction
agent.
Samples
were
left
in
the
drier
for
3
h
at
135
±
2
°C
and
extracted
by
the
agent
(diethyl
ether)
in
the
instrument.
The
col-
lagen
content
was
determined
spectrophotometrically
at
a
wavelength
of
550
nm
in
a
GENESYS
-
6
spectrophotometer
(Thermo
Electron
Corporation,
USA)
as
the
quantity
of
4-
hydroxyproline.
The
content
of
hydroxyproline
was
obtained
from
the
calibration
curve
and
converted
into
the
collagen
content.
Proteins
were
determined
by
subsequent
conversion
of
organic
nitrogen
to
inorganic
nitrogen
in
a
KJELTEC
in-
strument
(TECATOR,
Sweden)
by
the
Kjeldahl
method.
A
factor
of
6.25
was
used
for
the
conversion
of
the
nitrogen
content
into
the
protein
content.
2.4.
Microbiological
analysis
Sampling
was
performed
according
to
EN
ISO
6887-2
(2003).
Samples
were
analysed
for
the
total
viable
count
(TVC),
numbers
of
psychrotrophic
bacteria
(PSY),
lactic
acid
bacteria
(LAB),
En-
terobacteriaceae,
total
coliform
bacteria,
E.
coli,
Pseudomonas
spp.,
Bro-
chothrix
thermosphacta
and
the
presence
of
Listeria
monocytogenes.
TVC
and
PSY
were
determined
using
Standard
Plate
Count
Agar
(CM0463,
Oxoid,
UK)
after
incubation
for
72
h
at
30
°C
and
10
d
at
6.5
°C,
respectively,
according
to
EN
ISO
4833-1
(2013)
and
EN
ISO
17410
(2001).
The
quantification
of
LAB
was
performed
on
de
Man,
Rogosa
and
Sharpe
agar
(MRS
Agar,
CM0361,
Oxoid)
incubated
for
72
h
at
30
T,
in
accordance
with
ISO
15214
(2000).
The
family
En-
terobacteriaceae
and
the
colifonns
were
determined
using
Violet
Red
Bile
Glucose
agar
(CM0485,
Oxoid)
and
Violet
Red
Bile
Lactose
agar
(CM0107,
Oxoid),
respectively,
incubated
for
24
h
at
37
°C
according
to
ISO
21528-2
(2004)
and
ISO
4832
(2006).
E.coli
was
determined
ac-
cording
to
the
ISO
16649-2
(2001)
standard
method
using
Chromocult
TBX
agar
(116122,
Merck,
Germany)
after
incubation
for
24
h
at
44
T.
Brochothrix
thermosphacta
and
Pseudomonas
spp.
were
determined
using
STAA
agar
(CM0881,
Oxoid)
and
Pseudomonas
CFC
Selective
Agar
(CM0559,
Oxoid)
according
to
ISO
13722
(1996)
and
EN
ISO
13720
(2010),
with
incubation
at
22-25
°C
for
48
h.
The
number
of
colonies
formed
was
counted
and
reported
as
log
CFU/cm
2
or
log
CFU/g
for
each
sample.
Determination
of
the
presence
of
Listeria
monocytogenes
was
per-
formed
according
to
EN
ISO
11290-1
(1999)
using
pre-enrichment
in
half-strength
Fraser
broth,
followed
by
incubation
in
full-strength
Fraser
broth
(CM0895,
Oxoid)
and
plating
on
ALOA
(100427,
Merck,
Germany)
and
PALCAM
agar
(CM0877,
Oxoid).
Confirmation
was
performed
biochemically
using
a
VITEK2
analyser
(bioMerieux,
France).
2.5.
Statistical
analysis
In
total,
54
meat
samples
from
27
beef
carcasses
were
used
in
the
experiment.
Verification
of
the
difference
of
significance
of
the
in-
vestigated
instrumental
and
chemical
parameters
was
studied
using
Tuckey's
test
with
a
significance
level
of
0.05.
Correlation
between
parameters
at
the
beginning
(Day
0)
and
end
of
aging
was
determined
using
Pearson's
linear
correlation,
and
their
significances
were
set
at
560
R.
Huldnicovd
et
al.
LWT
-
Food
Science
and
Technology
89
(2018)
559-565
P
<
0.05,
P
<
0.01
and
P
<
0.001.
Finally,
a
multivariate
method
of
principal
component
analysis
(PCA)
based
on
a
correlation
matrix
was
employed
to
assess
relationships
among
variables
measured
during
aging.
The
figures
were
constructed
and
all
analyses
of
microbial
growth
performed
using
the
open
source
statistical
software
R
(R
Development
Core
Team.,
2009)
and
the
nlsMicrobio
(Baty
&
Delignette-Muller,
2015a)
and
nlstools
(Baty
&
Delignette-Muller,
2015b)
packages.
Smoothing
by
LOESS
(local
polynomial
regression
fitting
by
weighted
least
squares)
was
used
to
describe
the
trend
of
growth
(Cleveland,
Grosse,
&
Shyu,
1992)
and
the
experimental
data
were
also
fitted
by
the
Baranyi
model
without
lag
phase
(Baranyi
&
Roberts,
1994),
Equation
(4),
10(n
1
-..
-
No)
-
1)
egma.
'
(4)
where
N
t
is
the
bacterial
concentration
(log
CFU)
at
time
t
(days);
is
the
maximal
concentration
fitted
by
the
model
(log
CFU);
N
o
is
the
initial
concentration
fitted
by
the
model
(log
CFU);
µ„,
a
,
c
is
the
max-
imum
specific
growth
rate
(d
-1
).
The
goodness-of-fit
was
statistically
assessed
by
the
root-mean-
square
error
(RMSE),
Equation
(5),
RMSE
=
1
Y
I
(Nobs.
i
-
Npred,
n
i=i
1
(5)
where
N
pre
d
is
the
predicted
bacterial
concentration
(log
CFU);
N
o
b,
is
the
observed
bacterial
concentration
(log
CFU);
n
is
the
number
of
observations.
3.
Results
and
discussion
3.1.
Instrumental
and
chemical
analysis
Table
1
shows
the
results
of
the
evaluation
of
color
(L*,
a*,
b*,
AE,
C*,
h°),
pH
and
texture
(Warner-Bratzler
test)
before
aging
and
after
aging.
No
statistically
significant
differences
in
the
values
of
L*,
a*
and
b*
were
seen
in
the
CIEL*a*b*
system
during
the
course
of
aging.
The
measured
values
of
lightness
L*
and
the
parameters
a*
and
b*
were
lower
than
those
found
in
the
same
muscles
by
Kim
et
al.
(2016)
after
three
weeks
of
dry
aging.
The
overall
differences
in
color
AE
between
the
color
of
fresh
meat
(Day
0)
and
the
color
of
meat
at
the
end
of
aging
(Table
1)
were
above
2
which
indicates
differences
recognizable
by
the
inexperienced
observer
(according
to
the
CIE
criteria
of
classification
-
Commission
Internationale
de
l'Eclairage,
1976).
The
largest
differ-
ences
in
color
were
found
for
heifers
at
<
21
d.
The
values
of
pH
either
did
not
change
at
all
(heifers
<
21
d)
or
changed
only
negligibly
(other
groups)
during
the
course
of
aging,
and
the
differences
were
not
statistically
significant.
The
pH
values
found
in
this
study
corresponded
to
the
parameters
found
during
the
course
of
the
aging
of
beef
meat
by
Colle
et
al.
(2015),
with
pH
values
ranging
from
5.58
(2
d
after
slaughter)
to
5.63
(42
d
of
dry
aging),
with
values
of
5.60
after
both
14
and
21
d
of
aging,
in
the
in.
longissimus
thoracis.
Values
of
pH
of
5.5
(14
d
of
aging)
and
5.7
(21
d
of
aging)
were
also
found
in
beef
sirloin
by
Almstrom,
Seyfert,
Hunt,
and
Johnson
(2006).
The
aging
of
beef
has
a
positive
effect
on
its
tenderness
(Almstrom
et
al.,
2006).
Comparison
of
the
studied
groups
showed
a
fall
in
the
value
of
shear
force
in
the
loin
muscle
in
all
cases
(Table
1).
The
dif-
ference
was
statistically
significant
in
the
group
heifers
with
aging
>
21
d.
Almstrom
et
al.
(2006)
did
not
detect
any
differences
between
dry
aging
for
14
and
for
21
d
in
the
same
muscles.
Statistically
significant
differences
in
tenderness
scores
of
beef
longissimus
muscles
were
re-
ported
by
Kang
et
al.
(2017)
after
20
days
of
dry
ageing
at
2
°C.
Table
2
shows
the
results
of
chemical
analysis
of
the
composition
of
beef.
The
disadvantages
of
dry
aging
are
the
higher
evaporation
losses
and,
thereby,
the
lower
meat
yield
(DeGeer
et
al.,
2009).
Statistically
significant
differences
in
the
content
of
dry
matter
were
found
during
aging
in
all
four
tested
groups
(Table
2).
The
water
losses
amounted
to
around
3.0%
up
to
21
d
of
aging,
with
further
increases
with
an
ex-
tended
period
of
aging.
No
statistically
significant
differences
between
the
individual
groups
were
found
in
any
of
the
parameters
studied.
Statistically
significant
correlations
between
the
values
before
aging
and
after
aging
were
found
in
the
parameters
L*
(r
=
0.41,
P
<
0.05),
(r
=
0.66,
P
<
0.001),
pH
(r
=
0.56,
P
<
0.01),
content
of
dry
matter
(r
=
0.43,
P
<
0.05)
and
WBSF
(r
=
0.44,
P
<
0.05).
All
samples
(n
=
54)
characterized
by
color
parameters
(L*,
a*,
b*,
C*,
h°),
pH
value,
Warner-Bratzler
shear
force
test
and
chemical
com-
position
(4
parameters)
at
the
beginning
(Day
0)
and
end
of
aging
were
included
in
principal
component
analysis
(PCA)
to
explore
general
re-
lationships
between
meat,
aging
and
their
characteristics.
One
PCA
is
for
instrumental
data.
The
first
two
principal
compo-
nents
accounted
for
52.83%
of
total
variance
in
the
data.
The
projection
of
the
variables
on
the
factor
plane
confirms
our
previous
findings
of
strong
correlation
between
lightness
L*,
hue
value
h°,
pH
and
Warner-
Bratzler
shear
force
(Fig.
1).
Product
projection
on
the
factor
plane
is
determined
by
the
measured
characteristics
(Fig.
2).
It
is
apparent
from
PCA
analysis
that
there
are
some
samples
that
differ
from
others.
N
t
=
-
log„
(1
+
Table
1
Instrumental
analysis
of
beef
(m.
longissimus
thoracis)
during
dry
aging
at
+1
°
C
for
12-36
d
(mean
value
±
S.D.,
n
=
54).
Parameter
Heifers
<
21
d
of
aging
n
=
6
Heifers
>
21
d
of
aging
n
=
7
Bulls
<
21
d
of
aging
n
=
8
Bulls
>
21
d
of
aging
n
=
6
L*
BA
36.56
±
2.11
36.76
±
2.59
35.51
±
2.39
32.79
±
2.86
AA
33.59
±
2.67
36.22
±
1.53
37.21
±
3.69
32.61
±
5.29
a*
BA
12.03
±
1.00
11.11
±
1.88
12.97
±
2.02
12.71
±
0.95
AA
11.20
±
2.29
11.37
±
1.25
12.91
±
1.67
11.11
±
1.28
b*
BA
8.71
±
1.03
9.05
±
0.98
9.25
±
2.11
7.59
±
1.95
AA
7.87
±
1.13
8.99
±
1.19
9.71
±
2.11
7.59
±
1.95
AE
4.28
±
2.65
3.91
±
2.29
4.07
±
1.62
3.24
±
2.16
C*
BA
14.98
±
1.20
14.37
±
1.90
15.96
±
2.80
15.52
±
1.48
AA
13.72
±
2.45
14.54
±
1.52
16.22
±
2.43
13.54
±
1.91
BA
35.84
±
2.97
39.43
±
4.19
35.11
±
2.97
34.20
±
5.37
AA
35.47
±
2.90
38.21
±
3.49
36.64
±
4.05
33.82
±
5.67
pH
BA
5.68
±
0.23
5.53
±
0.08
5.60
±
0.05
5.67
±
0.12
AA
5.68
±
0.09
5.60
±
0.04
5.62
±
0.09
5.68
±
0.11
WBSF
BA
115.20
±
25.57
124.25
±
27.84'
106.24
±
28.21
123.02
±
24.77
[N]
AA
98.85
±
23.80
79.00
±
15.45
b
82.54
±
25.92
115.88
±
25.02
BA
-
samples
analysed
before
aging.
AA
-
samples
analysed
after
aging.
L*
-
lightness,
a*
-
redness,
b*
-
yellowness,
C*
-
Chroma,
h
°
-
hue,
AE
-
color
differences
coefficient,
WBSF
-
Wamer-Bratzler
shear
force.
an
statistical
significant
differences
between
value
before
and
after
aging.
561
CN
0
Pr
inc
ip
a
l
comp
onen
t
2
R.
HuIdnicoyd
et
al.
LWT
-
Food
Science
and
Technology
89
(2018)
559-565
Table
2
Chemical
analysis
of
beef
(m.
longissunus
thoracis)
during
dry
aging
at
+1
°
C
(mean
value
±
S.D.,
n
=
54).
Parameter
[%]
Heifers
<
21
d
of
aging
n
=
6
Heifers
>
21
d
of
aging
n
=
7
Bulls
<
21
d
of
aging
n
=
8
Bulls
>
21
d
of
aging
n
=
6
Dry
matter
BA
25.80
±
1.32'
25.86
±
1.54'
26.02
±
3.36'
26.87
±
1.66'
AA
28.73
±
1.59
6
32.62
±
3.93
6
28.99
±
3.08
6
30.39
±
1.59
6
Fat
BA
2.62
±
1.53
2.37
±
1.39
1.66
±
1.20
2.05
±
1.79
AA
2.40
±
1.52
3.26
±
1.89
1.22
±
0.93
2.05
±
1.79
Protein
BA
22.19
±
0.86
23.01
±
1.38
22.29
±
1.27'
22.64
±
0.53'
AA
24.20
±
2.18
25.39
±
3.77
24.79
±
1.54
6
22.64
±
0.53
1
'
Collagen
BA
0.57
±
0.17
0.70
±
0.49
1.05
±
0.67
0.83
±
0.39
AA
0.68
±
0.17
0.58
±
0.23
0.64
±
0.27
0.61
±
0.17
BA
-
samples
analysed
before
aging.
AA
-
samples
analysed
after
aging.
statistical
significant
differences
between
value
before
and
after
aging.
1
-1
L*
BA
C
B
b*
BA
a*
AA
a*
BA
pH
BA
H
AA
p
(..
AA
h*BA
b
A
L
AA
h
o
AA
'"
-.
.........
e
4
WBSF
BA
WBSF
AA
0
1
Principal
component
1
:
33.78%
Collagen
BA
Dry
matter
BA
Fat
BA
----------..„„
'N
Dry
Collagen
AA
m
ter
AA
Fat
AA
Protein
BA
0
1
Principal
component
1
:
27.17%
Pr
inc
ip
a
l
comp
onen
t 2
:
19.
05%
1
0
Fig.
1.
Position
of
instrumental
characteristics
of
dry-aged
beef
(m.
longissimus
thoracis)
at
Fig.
3.
Position
of
chemical
characteristics
of
dry-aged
beef
(m.
longissunus
thoracis)
at
first
two
principal
components
of
PCA
(BA
-
before
aging,
AA
-
after
aging),
n
=
54.
first
two
principal
components
of
PCA
(BA
-
before
aging,
AA
-
after
aging),
n
=
54.
2
o
E
,T)
-2
4
ri
:
0
o
0
o
0
o
a
O
o
o
0
o
Heifer
Bull
D
0
13
C
.
o
m
o
.
..3
,
o
0
Heifer
Bull
0
0
6
4
2
E
o
8
-2
fl
-6
-4
-2
0
2
4
6
8
-6
-4
-2
0
2
4
Principal
component
1:
33.78%
Principal
component
1:
27.17%
Fig.
2.
Position
of
bulls
and
heifers
at
first
two
principal
components
of
PCA
according
Fig.
4.
Position
of
bulls
and
heifers
at
first
two
principal
components
of
PCA
according
instrumental
parameters,
n
=
54.
The
second
PCA
is
for
chemical
data
(Fig.
3).
The
first
two
principal
components
accounted
for
52.20%
of
the
total
variance
in
the
data.
Product
projection
on
the
factor
plane
is
determined
by
the
measured
characteristics
(Fig.
4).
It
is
apparent
from
PCA
analysis
that
there
are
chemical
parameters,
n
=
54.
three
samples
that
differ
from
others.
562
7
-
1
b
6
-
5
-
o
0
:
0
S
o
0
0
0
0
0
0
0
0
0
0
0
R.
Huldnicovd
et
al.
LWT
-
Food
Science
and
Technology
89
(2018)
559-565
la
0
O
0
0
7
-
6
-
5
-
N
4
U.
3-
C)
0
2
-
0
o
o
0
So
O
0
8o
O
CS)
3-
o
2
-
0
-
0-
0
40
10
20
30
Days
of
aging
7
-
2a
6
-
5
-
N
4
-
u-
C)
3
-
C)
2
-
10
20
30
Days
of
aging
3.0
-
10
20
30
Days
of
aging
7
-
O
00
O
0
0
0
0
0
0 0
C)
4
-
U.
CS)
3-
o
2
-
0
-
10
20
30
Days
of
aging
3.0
-
40
0
0
/
§
O
0
0
8o
0
0
00
0
0
0
00
0
0
0
6
-
5
-
0
2b
0
0
0
0
O
0
0
0
0
0
40
0
40
3a
3b
2.5
-
2.5
-
o
0
0
0
00
0
0
0
N
2.0
-
E
u_
1.5-
U
C)
to
-
0
O
0
0
0
o
0
0,,
0
0
LL
U
1.5
-
0
0
0 0
0 0
C)
O
0
1.0
-
O
0
0
0
0
0
0
O
0
0
0
0
0
2.0
-
0.5
-
0.5
-
0.0
-
0.0
-
r
0
10
20
30
40
0
10
20
30
40
Days
of
aging
Days
of
aging
Fig.
5.
Numbers
of
Total
Viable
Count
(1),
psychrotrophic
bacteria
(2)
and
Lactic
Add
Bacteria
(3)
during
dry
aging
of
beef
at
+1
°C,
determined
on
the
surface
(a)
and
in
the
meat
(b).
Full
line
-
smoothing
by
LOESS,
dotted
line
-
Baranyi
model,
n
=
54.
563
R.
HuldnIcovd
et
al.
LWT
-
Food
Science
and
Technology
89
(2018)
559-565
Table
3
Growth
parameters
estimated
from
the
Baranyi
model
for
microbial
growth
during
dry
aging
of
beef
at
+1
°
C
for
12-36
d,
n
=
54.
Parameter
TVC
surface
PSY
surface
TVC
meat
PSY
meat
No
[log
CFU]
2.58
2.47
2.17
2.12
CI
(95%)
(2.24;
2.93)
(2.16;
2.78)
(1.91;
2.43)
(1.81;
2.43)
N
m
„,„
[log
CFU]
5.26
5.41
4.72 4.82
CI
(95%)
(4.81;
5.70)
(5.01;
5.80)
(4.38;
5.07)
(4.41;
5.23)
µ
m
„„
[d
0.520
0.596
0.464
0.495
CI
(95%)
(0.161; (0.176;
(0.263;
(0.244;
0.746)
0.878)
1.016)
0.665)
RMSE
0.868
0.782 0.652
0.778
CI:
confidence
interval.
RMSE:
root-mean-square
error.
TVC:
Total
Viable
Count,
PSY:
psychrotrophic
bacteria.
3.2.
Microbiological
analysis
There
were
no
Listeria
spp.
or
Brochothrix
thermosphacta
detected
in
the
samples.
Similarly,
for
most
of
the
samples,
the
counts
of
Pseudomonas
spp.,
the
family
Enterobacteriaceae
and
its
subgroups
(co-
liforms
and
E.
coli)
were
beneath
the
limit
of
detection
for
both
the
fresh
and
aged
meat
and
failed
to
show
any
trend
during
storage.
Fresh
beef
had
a
good microbiological
quality
with
TVC,
PSY
and
LAB
of
2.59
±
0.65,
2.47
±
0.61
and
1.04
±
0.25
log
CFU
per
cm
2
of
the
surface,
respectively,
and
2.17
±
0.47,
2.13
±
0.49
and
0.85
±
0.22
log
CFU
per
g
of
meat,
respectively.
For
comparison,
the
limits
in
EU
Regulation
No.
2073/2005
state
that
up
to
3.5
log
CFU/cm
2
is
con-
sidered
satisfactory
for
beef
carcasses
for
TVC
and
up
to
5
log
CFU/cm
2
is
still
acceptable.
The
initial
values
are
also
similar
to
those
in
other
studies
conducted
on
the
dry
aging
of
beef (Ahnstrom
et
al.,
2006;
Campbell,
Hunt,
Levis,
&
Chambers,
2001;
DeGeer
et
al.,
2009;
Li,
Babol,
Wallby,
&
Lundstron,
2013;
Li
et
al.,
2014).
The
numbers
of
bacteria
increased
notably
during
the
first
2
weeks
of
storage;
later
on
the
counts
did
not
change
greatly
(Fig.
5).
Although
in
some
cases
there
seemed
to
be
a
decreasing
trend
towards
the
end
of
storage
when
LOESS
smoothing
was
used,
we
are
fully
aware
that
this
may
result
from
the
lower
number
of
samples
taken
after
30
d
of
aging,
for
which
reason
the
Baranyi
model
of
growth
was
also
applied.
In
several
studies
on
dry
aging
of
beef,
an
increasing
trend
in
TVC
was
noted
during
21
d
of
storage
(Gudjonsclottir
et
al.,
2015;
Li
et
al.,
2014).
However,
in
the
studies
by
Campbell
et
al.
(2001)
and
Ahnstrom
et
al.
(2006),
the
numbers
after
21
d
were
moderately
lower
than
those
after
14
d.
The
decrease
after
approximately
two
weeks
of
storage
could
be
the
result
of
surface
drying during
aging,
as
the
water
content
decreased
significantly
(Table
3).
The
TVC
and
numbers
of
PSY
showed
similar
initial
values
(ap-
proximately
2.5
log
CFU)
and
maximal
values
(
<
7.0
log
CFU)
(Fig.
5).
The
parameters
of
the
Baranyi
model
showed
the
highest
specific
growth
rate
for
PSY
and
TVC
on
the
surface
and
the
lowest
for
bacteria
in
deep
tissue
to
where
microorganisms
infiltrate
from
the
surface.
The
mean
values
for
TVC
and
PSY
after
14
and
more
d
of
aging
(N
max
)
were
approximately
5
log
CFU
(Table
3).
Similar
results
were
reported
by
Ahnstrom
et
al.
(2006)
after
14
d
of
dry
aging
at
2.6
°C
(5.1
log
CFU/
cm
2
),
Gudjonsclottir
et
al.
(2015)
after
14
d
of
dry
aging
at
4
°C
(5.75
log
CFU/ml),
and
Li
et
al.
(2013)
after
14
d
of
dry
aging
at
2.9
°C
(5.2
log
CFU/cm
2
).
Other
authors
reported
higher
TVC
even
after
just
8
d
of
dry
aging
-
6.39
log
CFU/cm
2
after
storage
at
5.1
°C
(Li
et
al.,
2014)
and
7.49
log
CFU/g
after
storage
at
2
°C
(Yim
et
al.,
2015).
These
higher
values
can
be
explained
by
the
higher
storage
temperature
in
the
first
study
and
by
the
higher
level
of
initial
contamination
in
the
second
study.
The
numbers
of
LAB
in
our
study
were
generally
very
low,
initially
near
the
limit
of
detection,
and
the
highest
values
in
the
samples
of
aged
meat
did
not
exceed
3
log
CFU/g
or
cm
2
(Fig.
5).
Due
to
the
high
variability
of
the
data
and
low
numbers
throughout
the
experiment,
the
LAB
counts
could
not
be
fitted
by
the
model.
Similar
or
slightly
lower
values
during
dry
aging
of
beef
have
been
reported
by
several
other
studies
(Campbell
et
al.,
2001;
Li
et
al.,
2013),
whereas
Li
et
al.
(2014)
and
Gudjonsclottir
et
al.
(2015)
found
higher
numbers
of
LAB
(
>
3
log
CFU)
and
the
numbers
of
LAB
in
the
study
by
Ahnstrom
et
al.
(2006)
were
similar
to
the
TVC.
The
results
of
our
study
indicate
that
even
prolonged
dry
aging
can
result
in
meat
of
acceptable
microbiological
quality
with
counts
of
TVC
and
PSY
of
approximately
5
log
CFU/cm
2
or
g.
Generally,
an
off-fla-
vour,
which
is
a
result
of
spoilage
in
meat,
can
be
observed
from
a
bacteria
count
of
around
7
log
CFU
per
square
centimetre
or
gram,
although
some
negative
changes
can
be
observed
much
earlier
with
bacteria
counts
of
between
5
log
CFU
and
6
log
CFU
per
square
centi-
metre
or
gram
of
meat
or
meat
product
(Feiner,
2006).
4.
Conclusions
The
dry
aging
of
beef
increased
the
tenderness
of
loin
muscles
in
all
tested
groups,
with
the
difference
being
statistically
significant
in
the
group
of
heifers
with
aging
longer
than
21
d.
On
the
other
hand,
aging
increased
the
proportion
of
dry
matter
in
the
meat,
i.e.
water
losses
occurred
which
amounted
to
around
3%
during
aging
to
three
weeks
and
continued
to
increase.
Microbiological
tests
revealed
an
increase
in
the
total
number
of
bacteria
and
psychrotrophic
bacteria
during
the
course
of
aging
from
values
of
around
2.5
log
CFU/g
to
approximately
5
log
CFU/g
after
two
weeks
of
aging.
The
results
determined
in
the
study
show
the
positive
effect
of
dry
aging
on
the
tenderness
of
beef.
The
good
microbiological
quality
of
the
meat
can
be
maintained
over
several
weeks
if
the
hygiene
conditions
of
storage
are
good.
Conflicts
of
interest
The
authors
have
no
conflict
of
interest
to
declare.
Acknowledgement
The
work
was
supported
by
the
Security
Research
of
Ministry
of
Interior
of
the
Czech
Republic
VI20152020044.
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