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Journal of Agricultural and Food Chemistry
Olfactometry Profiles and Quantitation of Volatile Sulfur Compounds of Swiss Tilsit cheeses
Authors: Pascal Fuchsmann, Mireille Tena Stern, Yves-Alain Brügger, and Katharina Breme
Agroscope, Institute for Food Sciences IFS, Schwarzenburgstrasse 161, CH-3003 Berne, Switzerland
Corresponding author: Phone +41 (0) 58 463 82 60, Fax +41 (0) 58 463 82 27, Email
[email protected] ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
1
Abstract
2
In order to establish the odor profiles of three differently fabricated commercial Swiss
3
Tilsit cheeses, analyses were conducted using headspace solid-phase microextraction
4
gas chromatography–mass spectrometry/pulsed flame-photometric detection, and gas
5
chromatography–olfactometry to identify and quantitate volatile compounds. In
6
addition, odor quality and the impact of target sulfur compounds on the overall odor of
7
the cheeses were investigated. The odor profile was found to be mainly influenced by
8
buttery-cheesy and sulfury odor notes in all cheeses. Buttery-cheesy odor notes were
9
attributed to three main molecules: butanoic acid, 3-methylbutanoic acid, and butane-
10
2,3-dione. Over a dozen volatile sulfur compounds were detected at ppb (parts per
11
billion) levels, but only a few influenced the odor profile of the cheeses: methanethiol,
12
dimethyl disulfide, bis(methylthio)methane, dimethyl trisulfide, 3-(methylthio)propanal,
13
and 2-methyltetrahydrothiophen-3-one (tentative). In conclusion, the conducted
14
analyses allowed to differentiate the cheeses, and gas chromatography-olfactometry
15
results confirmed that partially thermized milk cheese has a more intense and more
16
multifaceted overall flavor.
17 18
KEYWORDS: GC-Olfactometry, 2W-GC-O, PFPD, Swiss Tilsit cheese, headspace
19
SPME, volatile sulfur compounds, VIDEO-Sniff, average Odor Activity Values
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INTRODUCTION
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Swiss Tilsit is a very popular semi-hard cheese manufactured only in the Eastern part
22
of Switzerland. There are five main varieties of Swiss Tilsit, but only three types are
23
generally found on the commercial market: the so-called “green” Swiss Tilsit (made
24
from pasteurized milk with at least 45 % fat in dry matter (FDM), corresponding to an
25
approximate fat content of 28 g/100 g and a ripening time of 30–60 days, sold with a
26
green label), red Tilsit (thermized milk and raw milk, at least 45 % FDM and an
27
approximate fat content of 29.5 g/100 g, 70–110 days of ripening, sold with a red
28
label), and yellow Tilsit (pasteurized milk with a higher fat content, at least 55 % FDM
29
and an approximate fat content of 33 g/100 g, 30–70 days of ripening, sold with a
30
yellow label) (www.Tilsiter.ch, 2014). Precise fabrication parameters are individual to
31
each cheese plant, but it is known that differences in raw materials lead to sensory
32
differences, especially for cheeses made from raw milk, which are said to show a more
33
intense and complex flavor than cheeses made from pasteurized milk,1, 2 possibly due
34
to the diversity of the microflora present.
35
Volatile sulfur compounds (VSCs), such as methanethiol (MeSH), hydrogen sulfide
36
(H2S), methyl thioacetate (MTA), 3-(methylthio)propanal, and methylsulfides, including
37
dimethyl sulfide (DMS), dimethyl disulfide (DMDS), and dimethyl trisulfide (DMTS), are
38
reported as key flavor compounds in a variety of cheeses.3-5 These VSCs are mainly
39
derived from the decomposition of the sulfur-containing amino acids cysteine and
40
methionine. Due to low odor thresholds, they have very pronounced sensory
41
properties, even at low concentrations. For that reason, a variation in the concentration
42
of VSCs can have a significant influence on cheese flavor. Several publications report
43
on the analysis of VSCs in semi-hard cheeses,6-8 stating that the studied cheeses are
44
characterized by important sensory differences due to variations in fat content,
45
microflora diversity, and ripening time.
46
As they are often present in low quantities only (but have a high impact on flavor), and
47
because they are highly volatile and reactive, analyzing VSCs remains a challenge.9-11 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
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Cheese and dairy products in general, just like other food products, contain many
49
aromatic molecules. However, not all these have an impact on the foodstuff, and only
50
a few of these molecules contribute to the aroma.12 Gas chromatography coupled with
51
olfactometry (GC-O) is used to identify odor-active compounds by using the human
52
nose as an analytical detector of volatile odorant compounds and helps to rapidly
53
identify so-called “odorant zones” in an aromagram. Different methodologies are
54
available, and the technique including these methods has been extensively described
55
in the literature.13, 14 The use of multiway GC-O-systems, where at least two panelists
56
work simultaneously on the same sample, represents an important gain of time,
57
especially when dealing with sensitive and perishable food samples, and also assures
58
the reliability of results.
59
The combination of headspace solid-phase microextraction gas chromatography–
60
mass spectrometry, and olfactometry (HS-SPME-GC-MS-O) with sulfur-specific pulsed
61
flame-photometric detection (PFPD) in order to specifically identify and quantitate
62
odorant sulfur compounds, even at trace levels,15 is an efficient way to determine both
63
overall odor profiles and the specific odor impact of trace VSCs.
64
Here, we report a comparative study of the odorant profiles of Swiss Tilsit cheeses,
65
with a focus on odor-impact VSCs determined by HS-GC-MS-O with a two-way-GC-O
66
system using the VIDEO-Sniff method (vocabulary-intensity-duration of elementary
67
odors by sniffing),13 a hybrid olfactometry method combining detection frequency,
68
intensity, and descriptive vocabulary of the judges, and their quantitation by HS-
69
SPME-GC-MS/PFPD.
70
To date, and to the authors’ knowledge, there is no publication reporting on the
71
comparative study of differently manufactured Swiss Tilsit cheeses using olfactometry
72
and with a focus on VSC odor impact and quantitation.
73
MATERIALS AND METHODS
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Chemicals. Chemical compounds were purchased from Sigma-Aldrich Chemie GmbH
75
(Buchs, Switzerland) and Alfa Aesar GmbH & Co KG (Karlsruhe, Germany). Acetic ACS Paragon Plus Environment
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acid (Aldrich 320099), 2-acetyl-2-thiazoline (Aldrich W381718), allyl sulfide (Aldrich
77
A35801), benzaldehyde (Aldrich W212709), benzyl alcohol (Aldrich 305197),
78
bis(methylthio)methane (Aldrich W387800), butane-2,3-dione (Aldrich B85307), butan-
79
2-one (Aldrich 360473), butanoic acid (Aldrich W222119), carbon disulfide (Aldrich
80
335266),
81
W313505), dimethyl disulfide (Aldrich W353604), 2,5-dimethylpyrazine (Aldrich
82
W327204), dimethyl sulfide (Aldrich W274623), dimethyl sulfone (Aldrich M81705),
83
dimethyl sulfoxide (Aldrich D8418), dimethyl trisulfide (Aldrich W327506), ethanol
84
(Aldrich 02860), ethyl butanoate (Aldrich W242705), ethyl hexanoate (Aldrich
85
W243906), 4-ethylguaiacol (Aldrich W243604), ethyl isobutyrate (Aldrich W242802),
86
ethyl methyl sulfide (Aldrich 238317), ethyl octanoate (Aldrich W244902), hexanal
87
(Aldrich 115606), hexanoic acid (Aldrich W255904), 3-methylbutyl acetate (Aldrich
88
W205532), methanethiol (Aldrich 742805), 3-methylbutanal (Aldrich W269204), 3-
89
methylbutanoic acid (Aldrich W310204), 3-methylbutan-2-ol (Aldrich 110949), 3-
90
methylindole (Aldrich W301912), methyl
91
methylpropanoic acid (Aldrich W222216), 5-methylnonan-5-ol (Aldrich S505021), 4-
92
methylpentanoic acid (Aldrich 277827), S-methyl thioacetate (Aldrich CDS001513), 2-
93
methyltetrahydrothiophen-3-one (Aldrich W351202), methyl thiocyanate (Aldrich
94
722197), 3-(methylthio)propanal (Aldrich W274704), nonanal (Aldrich W278203), δ-
95
octalactone (Aldrich w321405), octanal (Aldrich W279706), octanoic acid (Aldrich
96
W279900), oct-1-en-3-ol (Aldrich W280518), oct-1-en-3-one (Aldrich W351504), oct-3-
97
en-2-one (Aldrich W341606), pentanoic acid (Aldrich W310107), phenol (Aldrich
98
P1037), potassium thiocyanate (Aldrich 207799), polyethylene glycol 200 (P3015), 2-
99
phenylethanol (Aldrich 77861), pentane-2,3-dione (Aldrich W284106), α-pinene
100
(Aldrich 147524), sodium sulfide nonahydrate (Aldrich 208043), sulfuric acid 98%
101
(Aldrich
102
W309311), m-xylene (Aldrich 95670).
decan-2-one
320501),
(Aldrich
tridecan-2-one
W510637),
(Aldrich
(2E,4E)-deca-2,4-dienal
(Aldrich
isothiocyanate (Aldrich 112771),
W338818),
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undecan-2-one
2-
(Aldrich
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Carbonyl sulfide was prepared according to Paris D. N. Svoronos et al.16 The solution
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was stored at – 80 °C during maximum 1 week.
105
Hydrogen sulfide was prepared according to Vazquez-Landaverde et al.17 The solution
106
was stored at 4 °C during maximum 1 week.
107
A stock solution of 1 % methanethiol was prepared by bubbling gas in cold (4 °C)
108
polyethylene glycol 200. The solution was stored at – 20 °C during maximum 1 week.
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Cheese samples. Ten pieces of Swiss Tilsit cheese of each type and of similar
110
commercial size and weight (approximately 200 g) were obtained from a supermarket
111
located in Bern, Switzerland (Table 1). The cheeses were kept at 4 °C in vacuum-
112
sealed plastic bags for a maximum of 1 month until analysis.
113
Sample preparation. The samples for all analyses were obtained on the basis of a
114
procedure described by Burbank and Qian.7 In the present study, 2 cm of rind and
115
cheese were removed from all sides of the cheese to provide a sample as
116
homogeneous as possible. The sample was then finely cut with a ceramic knife to
117
avoid contact with metal, thus limiting the oxidation of sulfur compounds. Cut cheese
118
(2.00 ± 0.10 g) was placed in 20 ml HS vials (Interchim, Montluçon, France). For
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calibration curves, cut cheese was homogenized together with 10 µl of an internal
120
standard solution containing ethyl methyl sulfide (2 mg kg-1) dissolved in polyethylene
121
glycol 200. The mixture was homogenized using a glass pestle. The vials were placed
122
in an ice bath at 0 °C to cool the exothermic reaction when 4.00 ± 0.10 g of CaCl2 was
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added to each mixture. Three replicates per sample were prepared. To prevent
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oxidation, the vials were flushed with argon for 5 s with two needles to create an
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“argon stream” in the vial after it being hermetically sealed with a blue silicone/Teflon®
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septum (Interchim, Montluçon, France).
127
Solid-phase micro-extraction (SPME) and chromatography
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Identification and quantitation of VSCs by GC-MS/PFPD. Samples were extracted
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using a 1 cm carboxen/polydimethylsiloxane (CAR/PDMS) 85 µm StableFlexTM fiber
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(Supelco, Bellefonte, PA, USA) as the manufacturer’s recommendation and the ACS Paragon Plus Environment
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literature9, 18-22 revealed that this coating is the best solution for the extraction of highly
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volatile sulfur compounds, such as carbonyl sulfide, hydrogen sulfide, or methanethiol
133
from foodstuffs.
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The fiber was conditioned according to the supplier’s recommendations (300 °C for
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60 min). The analyses were realized using an MPS2 autosampler equipped with
136
Maestro1 software, V.1.4.8.14/3.5 (Gerstel, Sursee, Switzerland), a Trace GC Ultra
137
GC coupled with a DSQ II mass selective detector (MSD) (Thermo Finnigan, Milan,
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Italy), and a PFPD (OI Analytical, College Station, USA).
139
The headspace was extracted for 120 min at 60 °C with an agitation rate of 250 rpm
140
without preheating. Bound volatiles were desorbed for 1 min at 250 °C in the injector,
141
which was in the splitless mode for 30 s, and then the split valve was opened (split
142
flow: 80 mL min-1). Volatile compounds were separated on a TRB-FFAP fused silica
143
capillary column (100 % polyethylenglycol PEG with nitroterephthalic acid, bonded and
144
crosslinked, 30 m × 0.32 mm, 1.0 µm film; Teknokroma, Barcelona, Spain) with helium
145
as the carrier gas at a constant flow of 2.1 mL min-1 (37 cm sec-1).
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The oven temperature was programmed as follows: 5 min at 35 °C, then heated to
147
150 °C at a rate of 10 °C min-1, held for 1 min, and then heated to 220 °C at a rate of
148
20 °C min-1, with a final hold time of 5 min. The settings of the PFPD were as follows:
149
250 °C, voltage at 540 V, ignitor current at 2.6 A, trigger level at 300, range at 10, and
150
attenuation at 32 with the following flow rates: air1 at 17 mL min-1, H2 at 14 mL min-1,
151
and air2 at 10 mL min-1. The MS settings were as follows: transfer line at 230 °C,
152
source temperature at 230 °C, and the analytes were monitored in SCAN mode
153
between 30 amu and 150 amu without solvent delay.
154
Calibration curves were established by the method of standard additions in the cheese
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matrix. 100 µl of calibration solution prepared in polyethylene glycol 200 were added to
156
the matrix as given in Table 3, together with 10 µl of the internal standard solution
157
containing ethyl methyl sulfide (2 mg kg-1) to correct variations during the extraction.
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The detector response signals were integrated using the Xcalibur 2.0.7 software
159
(Thermo Fisher Scientific AG, Reinach, Switzerland). The NIST/EPA/NIH mass
160
spectral library (NIST11) version 2.0g (NIST, Gaithersburg, MD, USA) was used for
161
peak identification. The PFPD signal was used to trace the VSCs in the
162
chromatogram.
163
Gas chromatography-olfactometry
164
Odor-active compounds were analyzed using a two-way odor detection port (ODP2;
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Gerstel, Sursee, Switzerland) connected to a 6890N Agilent gas chromatograph (2W-
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GC-O) coupled with a 5973N MSD (Agilent Technology, Santa Clara, CA, USA), and a
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PFPD (OI Analytical, Texas, USA) and equipped with an MPS2 autosampler and the
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Maestro1 software, V.1.4.8.14/3.5 (Gerstel, Sursee, Switzerland).
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For GC-O analyses, volatile organic compounds were extracted using a 2 cm
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50/30 µm
171
StableFlexTM fiber (Supelco, Bellefonte, PA, USA). In order to obtain a representative
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evaluation of the odor of the samples in olfactometry, a DVB/CAR/PDMS fiber is
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suitable for the extraction of volatile and semi-volatile compounds and was reported to
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give good odor representativeness for dairy products.23 The fiber was conditioned
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according to the supplier’s recommendations (270 °C for 60 min).
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The cheese headspace was extracted for 16 h at 45 °C with an agitation rate of
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250 rpm without preheating. The SPME extraction time was optimized for an optimal
178
olfactory analysis in order to obtain clearly perceivable odorant signals.9 Absence of
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artifact formation was checked using 16 h as the incubation time and only 45 min for
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the extraction, and the results were compared with short incubation and extraction
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conditions (5 min incubation, 45 min extraction). Bound volatiles were desorbed for
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1 min at 250 °C in the injector, which was in the splitless mode for 30 s; then the split
183
valve was opened (split flow: 80 mL min-1). Volatile compounds were separated on a
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TRB-FFAP fused silica capillary column (60 m × 0.32 mm, 0.5 µm film; Teknokroma,
divinylbenzene/carboxen/polydimethylsiloxane
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(DVB/CAR/PDMS)
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Barcelona, Spain) with helium as the carrier gas at a constant flow of 2.3 mL min-1
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(39 cm sec-1).
187
The oven temperature was programmed as follows: 5 min at 35 °C, then heated to
188
150 °C at a rate of 10 °C min-1, held for 1 min, then heated to 220 °C at a rate of
189
20 °C min-1 with a final hold time of 5 min.
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The olfactometric ports were provided by Gerstel (Sursee, Switzerland) and are
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designed for two panelists to detect volatile compounds simultaneously. The
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dimensions and capillaries after the GC separation were adapted to obtain an optimal
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and timely synchronized signal between the physical detectors and the two sniffers.24
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The sample is split through deactivated silica capillaries into the following proportions:
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MSD: PFPD: ODP: ODP 1: 1: 1.5: 1.5, corresponding to a flow rate of 0.46 ml min-1:
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0.46 ml min-1: 0.69 ml min-1, and 0.69 ml min-1. The transfer line for each ODP is
197
heated at 220 °C to prevent the condensation of volatiles in the capillaries.
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Olfactory analyses were performed by a trained panel of eight sniffers. A single
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individual response is by definition not reproducible, and a minimum of eight sniffers is
200
required to obtain a reliable aromagram.25,
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microphone and must simultaneously press a button and comment on the odor they
202
perceive while indicating its intensity on a scale from one to five, one being barely
203
perceptible and five being a very strong odor. Comments are registered and
204
processed at the end of each session with AcquiSniff® version: 6.5.9 (INRA, Clermont-
205
Ferrand, France).
206
The aromagrams were computed using the VIDEO-Sniff method and the AcquiSniff®
207
software. All vocabulary employed by the judges was sorted into the 11 olfactory
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classes (Table 2).27
209
The settings of the PFPD were as follows: 250 °C, voltage at 540 V, ignitor current at
210
2.6 A, trigger level at 300, range at 10, and attenuation at 32 with the following flow
211
rates: air1 at 17 mL min-1, H2 at 14 mL min-1, and air2 at 10 mL min-1. The MSD
212
settings were as follows: transfer line at 230 °C, source temperature at 230 °C, and the
26
Panelists are equipped with a
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analytes were monitored in SCAN mode between 30 amu and 150 amu without
214
solvent delay.
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The detectors’ response signals were integrated using the Chemstation Data Analysis
216
software version E.02.00.493 (Agilent Technologies, Santa Clara, CA, United States).
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Aromagrams were recorded and processed using the VIDEO-Sniff method and
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AcquiSniff Software®, as described in the literature.13 The NIST/EPA/NIH mass
219
spectral library (NIST11) version 2.0g (NIST, Gaithersburg, MD) was used for peak
220
identification.
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GC–Olfactometry panel training
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GC-O is used to identify odor-active compounds with the aid of the human nose.13 It is
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not necessary to be specially trained to participate as an olfactometry panelist.
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However, it is very convenient for data processing to work with panelists who are
225
familiar with odors and use the same language. For this, all panelists were trained
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statically for four months to memorize 17 odorant molecules (ethyl isobutyrate, 3-
227
methylbutyl
228
phenylethanol, 3-methylindole, α-pinene, allyl sulfide, dimethyl trisulfide, butanoic acid,
229
4-ethylguaiacol, 3-(methylthio)propanal, 2-acetyl-2-thiazoline, nonanal, (2E,4E)-deca-
230
2,4-dienal, and 3-methylbutanal) of ten different odor families commonly present in
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cheese and dairy products (buttery-cheesy, empyreumatic, floral-fruity, green-fatty,
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malty-chemical, meaty, spicy, nutty, sulfur, and earthy-undergrowth). After successful
233
completion, they were familiarized with the GC-O-setup and trained three times using
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a standard solution containing the 17 molecules. Panel performance was monitored
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through regular training, and information was recorded in a database.
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Determination of “average odor activity values by sniffing (aOAVsniff)” using gas
237
chromatography–olfactometric detection limits of the compounds (GCOt) and
238
“average absolute quantified amounts (aAQA)”
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Gas chromatography–olfactometric detection limits of target VSCs (GCOt)28 were
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determined by the injection of several standard solutions of pure compounds at known
acetate,
oct-1-en-3-ol,
oct-1-en-3-one,
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pentane-2,3-dione,
2-
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concentrations, using dilution factor of 2, until the molecule was no longer identifiable
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by the panelists with the same GC-O method as described above and used in all
243
applications. The procedure was repeated with two trained panelists, and the average
244
values for each compound were used. The method was successfully verified using two
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different GC-O units to confirm the feasibility of the technique.
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During sniffing analyses of the cheeses, “average absolute quantified amounts
247
(aAQA)” were determined by MS quantitation as described in order to ensure that
248
these data correspond to the run during which olfactometric perception was recorded.
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Finally and according to the classical concept of OAV,29 aOAVsniff are calculated by
250
dividing the aAQA by the GCOt (Table 3).
251
Statistical analysis
252
Olfactory charts and statistics were realized using AcquiSniff® version: 6.5.9 (INRA,
253
Clermont-Ferrand, France).
254 255
RESULTS AND DISCUSSION
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Olfactometry evaluation
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A total of 36 odorant zones were perceived during the sniffing of the three kinds of
258
Tilsit cheese by the eight panelists. Red Tilsit showed the most odorant zones in the
259
aromagram with 31 odorant zones, followed by yellow Tilsit with 29 odorant zones and
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green Tilsit with 25 odorant zones. Altogether, 41 odorant compounds were found to
261
be responsible for the 36 odorant zones and could be identified by combining odor,
262
LRI (Linear Retention Indices), PFPD, and qMS (quadrupole Mass Spectrometer)
263
information. The results are presented in Table 4. A minimum of 50 % of the panelists
264
detected 17 odorant zones in the red Tilsit, 15 odorant zones in the yellow Tilsit, and
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13 odorant zones in the green Tilsit. Detection frequency less than 50 % is generally
266
considered as noise,30 but molecules detected by less than 50 % of the panel might
267
also contribute to the overall odor of a sample. The aromagrams of the three cheeses
268
are given in Figure 1. ACS Paragon Plus Environment
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A common core of odorant compounds of the three Tilsit cheeses with a detection
270
frequency of at least 50 % consists of hexanal (peak 6 in Figure 1; odor descriptors:
271
green, grass, floral; GC-O-VIDEO-Sniff characteristics in all three cheeses such as the
272
mean intensity*detection frequency value and detection frequency in percentage are
273
given in Table 4), octanal (peak 12; fruity), butane-2,3-dione (peak 4; buttery, creamy,
274
cheesy), non-8-en-2-onet(Std) (peak 10; cooked potatoes, earthy, roasted, meaty, salty
275
meat; t= tentatively identified, e.g. reference compound not injected (t(Std)) or odor
276
descriptor (t(Odor)) or reference compound not exactly matching and/or no detection by
277
MS (t(MS))) , 3-methylbutan-2-olt(Odor) (peak 8; plastic, fatty, chemical, solvent, gum),
278
butanoic acid (peak 31; cheesy, rancid), 3-methylbutanoic acid (peak 32; cheesy,
279
rancid raclette cheese), MeSH (peak 1; cheesy, old socks, cabbage, cellar, rancid,
280
putrid), DMDS (peak 7; pungent, sulfur), bis(methylthio)methane (peak 13; animalic,
281
cheesy, sulfury, garlic, onion, rancid), DMTS (peak 17; garlic, sulfury, gas, metallic),
282
and 3-(methylthio)propanal (peak 23; boiled potatoes, sulfury).
283
Two odor-active compounds, oct-1-en-3-one (peak 14; earthy, mushrooms, green) and
284
2-methylpropanoic acid (peak 26; green, fatty, fruity, rancid), were perceived in both
285
red and yellow Tilsit with a detection frequency of at least 50 %. Acetic acid (peak 21;
286
chemical, green, fresh, acid, pungent, spicy) was perceived in both yellow and green
287
Tilsit.
288
Some compounds were found exclusively in one of the cheeses with a detection
289
frequency of at least 50 % and lower than 50 % in the other ones. Red Tilsit contains a
290
wider variety of such compounds, with five specific odor-active compounds that were
291
only found in red Tilsit: 3-methylbutanal (peak 3; burned, cooked, roasted, spicy), octa-
292
3,5-dien-2-onet(Std) (peak 28; floral, earthy), ethyl butanoate (peak 5; fruity, floral), 2-
293
methyltetrahydrothiophen-3-onet(odor threshold) (peak 27; cheesy, sulfur, pungent), and m-
294
xylenet(Odor) (peak 9; roasted, fatty, old oil, bread). Two specific odor-active compounds
295
were detected exclusively in yellow Tilsit: undecan-2-one (peak 30; floral, fresh, fruity,
296
mint) and 2,3-dimethyl-5-(1-propenyl)pyrazinet(Std) (peak 29; green, cut grass, plant), ACS Paragon Plus Environment
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and one specific odor-active compound was detected exclusively in green Tilsit: 2,5-
298
dimethylpyrazine (peak 15; mushroom, green).
299
In addition, 18 compounds were perceived with a detection frequency of panelists
300
lower that 50 % but could be easily identified by LRI, qMS, or odor. Again, red Tilsit
301
shows a greater number of these odorant compounds with 14 such molecules, of
302
which three were exclusively perceived in red Tilsit. Yellow Tilsit contains 12
303
molecules, including two specific compounds, and green Tilsit contains the least with
304
only nine molecules without specific compounds. The following compounds were
305
identified with a detection frequency of less than 50 %: nonanalt(Odor) (peak 16; fruity,
306
cooked, roasted, vanilla, honey), benzaldehyde (peak 25; sesame-spicy, fatty, green,
307
oily, animalic), butan-2-one (peak 2; burned plastic, plastic), decan-2-one (peak 24;
308
cooked, roasted, boiled potatoes), oct-3-en-2-one (peak 18; mushrooms), tridecan-2-
309
onet(Odor) (peak 34; wax, fatty), δ-octalactone (peak 38; fatty, green, floral, fruity,
310
creamy, buttery), 5-methylnonan-5-ol (peak 20, green, chemical, earthy), benzyl
311
alcohol (peak 37; urine, wax, fruity, ball pen), phenol (peak 39; plastic), ethyl
312
hexanoate (peak 11; fruity, sweet), ethyl octanoatet(Odor) (peak 19; wine, cork,
313
chemical), hexanoic acid (peak 36; cheesy, sweaty), pentanoic acid (peak 33; cheesy,
314
rancid), octanoic acid (peak 40; cheesy, rancid, fatty, ham), 4-methylpentanoic acid
315
(peak 35; cheesy, rancid), and 2,6-diethylpyrazinet(LRI,
316
sulfury, plastic).
317
The co-elution of odor-active compounds complicates the identification of an odorant
318
zone. A co-elution example with hexanal (green, grass) and DMDS (pungent, sulfur)
319
described using both green and pungent descriptors illustrates the difficulty of
320
identifying the compound only using the odor perception descriptors given by the
321
panelists.
322
Distribution according to the number of citations of the odor families shows that the
323
dominant odor family contributing to the odor of the different cheeses is “cheesy-
324
buttery”, as expected (citation percentages: green Tilsit, 42 %; red Tilsit, 41 %; and
Std)
ACS Paragon Plus Environment
(peak 22; chemical, green,
Journal of Agricultural and Food Chemistry
325
yellow Tilsit, 33 %). It is followed by the “sulfur” family (green Tilsit, 24 %; yellow Tilsit,
326
20 %; and red Tilsit, 14 %), the “malty-chemical” family (red Tilsit, 13 %; yellow Tilsit,
327
12 %; and green Tilsit, 5 %), and the “fatty-green” family, especially in red and yellow
328
Tilsit (yellow Tilsit, 12 %; red Tilsit, 10 %; and green Tilsit, 8 %). Other odor families
329
also contribute to the overall flavor but to a lesser extent, especially in green Tilsit. The
330
“cheesy-buttery” and “sulfur” families together account for over 50 % of all odor
331
citations in all three cheeses (green Tilsit, 66 %; red Tilsit, 55 %; and yellow Tilsit,
332
53 %).
333
The citation percentages of the dominant class “buttery-cheesy” depicted in yellow in
334
the aromagram (Figure 1) are very similar for the green and red Tilsit (41–42 %) and
335
are a little less predominant in the yellow Tilsit (33 %). The “buttery-cheesy” odor
336
zones are mainly evoked by three compounds: butanoic acid (cheesy, rancid), 3-
337
methylbutanoic acid (cheesy, rancid, raclette cheese), and butane-2,3-dione (buttery,
338
creamy, cheesy). These odorant compounds were detected by at least 50 % of the
339
panelists (Table 4).
340
The odor class “sulfur” depicted in blue represents 24 % of total detected odor zones
341
in green Tilsit, despite a lower overall sulfur compound concentration (Table 3). This
342
might be explained by the nature of the matrix as well as the distribution and release of
343
the compounds.
344
The “fatty-green” class depicted in green represents 10–12 % in red and yellow Tilsit,
345
and is less frequently evoked in green Tilsit (8 %). However, a single strong “fatty-
346
green” odor zone evoked due to hexanal (green, grass, and floral) was more intense in
347
the green Tilsit (Table 4, peak number 6).
348
The class “malty-chemical” shown in brown is less represented in green Tilsit and is
349
mainly due to three compounds (3-methylbutanal, benzaldehyde, and 5-methylnonan-
350
5-ol), which seem to be mainly present in red and yellow Tilsit.
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The “fruity-floral” class shown in pink is slightly more frequent in red Tilsit and comes
352
from the presence of esters, such as ethyl butanoate (fruity, floral) or ethyl hexanoate
353
(fruity, sweet).
354
“Spicy” notes depicted in violet are present in the form of acetic acid (chemical, green,
355
fresh, acid, pungent, spicy) in all cheeses, and benzaldehyde (spicy, fatty, green, oily,
356
animalic) is only present in red and yellow Tilsit.
357
The “earthy-undergrowth” notes shown in dark green come from the perception of
358
mushroom notes. The compounds responsible were partially identified (Table 4: non-
359
8-en-2-onet(Std), oct-1-en-3-one, oct-3-en-2-one, and octa-3,5-dien-2-onet(Std)). Two
360
additional specific aroma-active zones with a strong “earthy-undergrowth” note are
361
present only in green Tilsit between peaks 21 and 23 and between peaks 37 and 38
362
(Figure 1). Due to the very low amount in the sample, these molecules could not be
363
identified.
364
The class “nutty” shown in orange contributes to 1 % of all detected items in cheeses.
365
This odor class was described by the panelists as cooked nut, chestnut, and nutty.
366
The very low concentrations in the cheeses did not allow for identification by
367
conventional detectors in the present study.
368
Calculation of “average odor activity values by sniffing (aOAVsniff)”
369
The olfactory impact of a compound depends on both its concentration in a sample
370
and its odor threshold. In general, to account for these two parameters, the literature
371
refers to the odor activity value (OAV), which is the ratio of the concentration of a
372
compound to its odor threshold, to describe how strongly an odorant compound is
373
perceived by the human nose.29 The odor threshold values are usually taken from the
374
literature and are determined in a simple matrix, such as water, oil, or air, using a
375
static method. It is therefore difficult to apply such OAVs, especially to a complex
376
matrix such as cheese.
377
However, the odor perception threshold is the lowest concentration of a compound
378
that can be perceived in a matrix. It is different from the odor recognition threshold at ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
379
which an odorant is both perceived and its odor recognized/identified/described. In
380
general, perception thresholds are two to five time lower than identification
381
thresholds.31 Sniffing analysis is a dynamic method, and the panelists are trained to
382
detect and describe odorant zones. However, for both perception and identification,
383
the compound concentration has to be higher than the respective thresholds, and the
384
time during which the thresholds are high enough might be too short for the panelists
385
to react, or the panelists might be exhaling and thus miss the stimulus. This is why it is
386
preferable to work with identification thresholds, which ensure that the determined
387
OAV is truly the one of the target compound, and not with perception thresholds.
388
Therefore, we decided not to employ the classic concept used in the literature, but to
389
determine such gas chromatography–olfactometric detection limits GCOt for target
390
odorant VSCs28 and use them for aOAVsniff calculations: aOAVsniff of target odorant
391
VSCs were calculated by dividing the average absolute quantified amount (aAQA) of a
392
VSC found during sniffing analyses in the sample by the GCOt and are given in
393
Table 3.
394
The aOAVsniff can help to estimate the potential odor impact a compound might have
395
on the overall odor profile. As it is based on the theory of the classical OAV, an
396
aOAVsniff with a high value is a strong indication that the compound contributes greatly
397
to the cheese aroma.29
398
Sulfur profiles of the three Swiss Tilsit cheeses
399
A total of 21 VSCs were detected by GC/PFPD in the studied cheeses. Twenty-one in
400
yellow Tilsit, 18 in red, and 18 in green. Of these 21 compounds only six were found to
401
be odorant by 2W-GC-O: six in green Tilsit, six in red Tilsit, and five in yellow Tilsit.
402
Fifteen selected sulfur compounds were quantified at ppb levels (Table 3).
403
MeSH, DMDS, bis(methylthio)methane, DMTS, and 3-(methylthio)propanal, all known
404
for their low odor thresholds, were found at ppb levels in all three cheeses and were
405
also detected by 2W-GC-O.
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Page 17 of 35
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406
2-methyltetrahydrothiophen-3-onet(odor
threshold)
407
was confirmed by LRI, qMS, PFPD, and odor specifications. Using its absolute
408
quantified amount found during sniffing analyses in the samples and its GCOt (100 ng)
409
determined with the pure reference compound, an aOAVsniff < 1 was calculated for 2-
410
methyltetrahydrothiophen-3-onet(odor
411
detectable by the panelists. Numerous reasons could explain the fact that the
412
compound was nevertheless smelled and confirmed by odor descriptor comparison,
413
two hypotheses being:
threshold)
was also detected in all cheeses and
. Hence, it should in theory not be
414
a) the molecule has an asymmetric carbon and hence two enantiomers exist.
415
There are no stereochemistry specifications for the commercially available
416
mixture used to determine the molecule properties (LRI, qMS, and odor
417
specifications) and it might differ from the compound or enantiomer ratio found
418
in the cheeses.
419 420
b) a synergistic effect or coelution, as octa-3,5-diene-2-onet(Std) elutes at the same time. Further investigations will be needed to elucidate this question.
421
When adding the amount in µg kg-1 of all the quantified VSCs, the total amount of
422
quantified VSCs is 4377 µg kg-1 in yellow Tilsit, 2800 µg kg-1 in green Tilsit, and
423
2761 µg kg-1 in red Tilsit. When only focusing on odorant VSCs detected during 2W-
424
GC-O, the overall amounts add up to 664.5 µg kg-1 corresponding to 15.2 % of the
425
total quantified VSCs in yellow Tilsit, 327.0 µg kg-1 corresponding to 11.8 % in red
426
Tilsit, and 54.4 µg kg-1 corresponding to 1.9 % in green Tilsit. COS, H2S, CS2, DMS,
427
MeSAc, MTC, MITC, DMSO, and Me2SO2 were also quantified, but due to their high
428
odor thresholds or odorless aspect, they were not considered.
429
Calibration curves on five points show correlation coefficients R2 higher than 0.97 for
430
all quantified compounds. Of 15 compounds, ten were above the quantitation limits
431
(LOQ). DMS in green Tilsit was below LOQ. MITC was below LOQ in all Tilsits, and 3-
432
(methylthio)propanal was below LOQ in the green and yellow Tilsit.
ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
433
The contribution of MeSH (odor description, Table 4: cheesy, old socks, cabbage,
434
cellar, rancid, putrid) as the sulfur compound with an aOAVsniff of 400 is the most
435
important in the studied cheeses. It was perceived with almost the same intensity in
436
each of the cheeses. However, the quantified concentration of MeSH is higher in
437
yellow Tilsit (15 times higher than in green Tilsit and three times higher than in red
438
Tilsit). Its olfactory impact is so important that the signal covers DMS, which has a
439
close retention time. The next most important VSC is DMTS (garlic, sulfury, gas,
440
metallic), with an aOAVsniff of 150. Although its concentration is 11 times lower in green
441
Tilsit than in yellow Tilsit, it was found to be more intense in the latter than in the other
442
cheeses. The nature of the matrix can explain this phenomenon, as can the variability
443
of the panelists. The samples were not measured on the same day, and the
444
environment and the physical state of the panelists may influence the results. 3-
445
(methylthio)propanal (boiled potatoes, sulfury) with an aOAVsniff of 25 also contributes
446
equally to the overall odor of all cheeses. It is difficult to evaluate the impact of DMDS
447
(pungent, sulfur) in this experiment as it co-eluted with hexanal (green, grass, floral)
448
and its aOAVsniff is only 3.5. Bis(methylthio)methane (animalic, cheesy, sulfury, garlic,
449
onion, rancid) with an aOAVsniff of 3 has a strong impact in yellow Tilsit despite being
450
present at the same concentration in the red Tilsit. The variability of the panelists can
451
explain this difference.
452
The other quantified VSCs are odorless, such as COS, DMSO, and Me2SO2, or the
453
aOAVsniff is less than 1 (H2S, CS2, MTC, MITC, and 2-methyltetrahydrothiophen-3-
454
onet(odor threshold)). Therefore, they do not directly affect the overall odor because their
455
concentrations are below the odor threshold. However, they might still contribute due
456
to synergistic effects, which were not evaluated in the present study.
457
Origin of sulfur compounds in a cheese matrix
458
Several VSCs were found to have an impact on the odor of the studied Swiss Tilsit
459
cheeses. Their origin in a cheese matrix is of great interest, especially as variations in
460
their concentrations may strongly influence the cheese’s odor profile. VSCs in cheese ACS Paragon Plus Environment
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Page 19 of 35
Journal of Agricultural and Food Chemistry
461
originate from the enzymatic or non-enzymatic degradation of the amino acids
462
cysteine and methionine by the action of microorganisms. Methionine, present in
463
larger amounts in the cheese than cysteine, is the most important source of VSCs.32, 33
464
The vast majority of complex sulfur compounds derives from two major and highly
465
reactive compounds, MeSH and H2S. H2S is formed by Strecker degradation of
466
cysteine with diketones such as butane-2,3-dione and pentane-2,3-dione or it can also
467
be formed by thermal degradation of thiamine, during which the rearrangement of a
468
thiazole group liberates H2S.34 Another metabolic pathway through the degradation of
469
cysteine by the activity of cystathionine lyases of L. casei can also explain the
470
formation of H2S in cheese.35 MeSH is formed by Strecker degradation of
471
methionine,36 and a study carried out by Bogicevic et al.35 shows the major role of
472
deamination and dethiolation by lyases in cheese. Strains of L. casei whose genes ctl1
473
and ctl2 were present exhibited cystathionine lyase activity and broke down
474
methionine. The presence and the formation of CS2 is not well defined. A high
475
concentration is correlated with the heat treatment of milk, and the concentration of
476
CS2 decreases with storage time.37 CS2 may also be an extraction artifact due to the
477
reaction of COS with the matrix.16 This hypothesis was confirmed by internal
478
laboratory tests. A large part of DMS can come from animal feed due to the non-
479
enzymatic degradation at a pH of 7.5 of the S-methylmethionine sulphonium salt
480
present in cattle feed.34 MeSAc can be formed by Brevibacterium linens, but in
481
general, the biosynthetic pathway involved in thioester production is not yet
482
elucidated.38 However, the combination of Micrococcus strains with B. linens shows a
483
vastly higher concentration in MeSAc compared to when the strains are present
484
separately in the cheese matrix. These microorganisms appear on the surface of the
485
cheese after a ripening period of two and three weeks,39, 40 and their metabolites have
486
been found to contribute to cheese flavor.41 MeSH can react with free fatty acids to
487
form S-methyl thioesters, such as MeSAc, and contribute to a cooked cauliflower
488
aroma.7 DMDS is the result of the Strecker degradation of methionine and the reaction ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
Page 20 of 35
489
of methionine with riboflavin. It also originates from the oxidation of MeSH during heat
490
treatment of milk.34 DMTS is mainly due to the oxidation of DMDS, the latter being a
491
product of the oxidation of MeSH.42 Oxidative reactions are accelerated by the
492
presence of transition metals such as Cu (II) or Fe (III).4 These metals are commonly
493
present in low concentrations in cheese produced traditionally or industrially in
494
production
495
(methylthio)propanal requires the decarboxylation of 4-methylthio-2-ketobutyrate, and
496
this reaction can be carried out by Lc. lactis strains.36 DMSO is an intermediate
497
oxidation step of DMS, the final oxidation product being Me2SO2.34 MTC and MITC can
498
be produced by a few Pseudomonas strains, which are naturally present in milk before
499
heat treatment.43 Bis(methylthio)methane can be formed through condensation or the
500
aldol reaction of the MeSH with the formaldehyde. This compound has already been
501
found in Gouda and Camembert cheeses.44,
502
threshold)
503
cheese. This molecule is formed by chemical reactions or is produced by
504
microorganisms. The microbial mechanism is still unknown.46-48
facilities,
for
example
in
cheese
45
kettles.
The
formation
of
3-
2-methyltetrahydrothiophen-3-onet(odor
has been found in many foodstuffs, such as coffee, whisky, yogurt, and
505 506
To conclude, quantitation of VSCs shows a clear difference in concentration between
507
the cheeses. Red Tilsit made from partially thermized milk and yellow Tilsit made with
508
pasteurized milk and a higher fat content contain the highest amounts for most of the
509
target VSCs. This can, however, not be explained by a unique reason, but can be
510
caused by several factors such as treatment of the raw milk, a longer ripening time, fat
511
content and also by a wide variety of indigenous microflora in raw milk.
512
According to the literature, a higher fat content can affect the growth of microflora,
513
enzymatic activity, partitioning, and matrix effects, thus influencing the concentration of
514
VSCs.49 The literature showed that flavor compound retention by lipids can be
515
significant for sulfur compounds. A lipid concentration above 10 % in the matrix can
516
decrease the release of sulfur compounds into the headspace by up to 20 %.50 In the ACS Paragon Plus Environment
Page 21 of 35
Journal of Agricultural and Food Chemistry
517
present case, all cheeses contain more than 10 % fat (between 28 g and 33 g fat per
518
100 g of cheese), and despite this, no negative influence of fat content on VSC release
519
was observed with the employed analytical protocol. The protein content, on the other
520
hand, has not been found to influence flavor release in a cheese matrix50 and was not
521
evaluated in the present study.
522
GC-olfactometry analyses in the employed analytical conditions suggest that the
523
overall odor of the studied Tilsit cheeses is mainly determined by cheesy-buttery odor
524
notes, followed by sulfur, malty-chemical, and fatty-green odor zones. When summing
525
up all perceived odor zones in the cheeses (mean intensity*detection frequency
526
values, Table 4), green Tilsit had an overall value of 40.2, red Tilsit had an overall
527
value of 48.0, and yellow Tilsit had an overall value of 45.8. These values illustrate that
528
red Tilsit is the most flavorful cheese of the three samples, followed by yellow Tilsit.
529
Green Tilsit, as expected, shows the least intense overall odor. Numerous odorant
530
compounds were identified in all three cheeses, but the number of compounds that
531
were only found in one of the cheeses and not in the others was higher for red Tilsit,
532
which alone of the three cheeses had m-xylenet(Odor), ethyl hexanoate, oct-3-en-2-one,
533
and unknown peak 41.
534
Concerning VSCs, 2W-GC-O showed that MeSH, DMDS (co-elution with hexanal),
535
bis(methylthio)methane,
536
methyltetrahydrothiophen-3-onet(odor
537
were the only identified VSCs to have a strong impact on the odorant profile of the
538
tested cheese samples. In total, the “sulfury” odor family represents up to 14 % of the
539
total odor profile. The aromagrams of the cheeses show differences, but the
540
differences in VSCs were not as pronounced as one might expect based on the
541
quantitation results. This might either be due to the use of optimal analytical conditions
542
for each technique or to a limitation of the methodology: when the concentration of a
543
given compound greatly exceeds the odor threshold, the panelist cannot rate the
544
intensity of the perceived odor stronger than the maximum of the employed scale (1–
DMTS, threshold)
3-(methylthio)propanal,
and
2-
(co-elution with octa-3,5-dien-2-onet(Std))
ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
545
5), and detection frequency cannot exceed 100 %. This is particularly the case for the
546
most intense peaks and might explain why, despite clear differences in quantified VSC
547
amounts, these are not directly translated in the aromagrams. However, when
548
counting the number of times a certain odor family is perceived, differences become
549
more evident but are not congruent with the quantitation results.
550 551
Our work allowed for the clear differentiation of the three commercial Tilsit cheeses in
552
terms of VSCs, odorant VSCs, and GC-O profiles. GC-O results confirm the general
553
opinion that Tilsit cheese made from raw milk has a more intense and more diverse
554
overall flavor than cheese manufactured with pasteurized milk. VSC quantitation could
555
not be directly linked to this statement, as optimal analytical conditions were employed
556
for each technique and other factors, such as limitation of GC-O methodology, but also
557
fabrication process, fat content and ripening time, are likely to have an impact. Further
558
research, including practice trials, is necessary to determine the precise causes of the
559
differences found in this study and future results should be combined with sensory
560
profiling information.
561
Acknowledgements
562
The authors gratefully acknowledge all panelists for their participation and René
563
Badertscher, Cornelia Bär, and René Imhof for revision of the manuscript.
564
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FIGURE CAPTIONS തതതതത Figure 1. Mean olfactory signal by classes (OSC
Int x Det)
of green (A), red (B), and
yellow (C) Tilsit over eight judges. The signals are classified in 10 distinct odor families out of the 11 families represented in Table 2. The family “undefined” is not represented in the aromagram. Labels corresponding to the peak numbers are given in Table 4. The compounds were separated on a TRB-FFAP capillary column.
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Table 1 – Description of cheeses (www.Tilsiter.ch, 2014)
Thermal treatment
Fat in dry matter (FDM) Approx. fat content in 100 g Ripening time Taste perception
Green Tilsit Pasteurized milk
Red Tilsit Partially thermized milk
at least 45 % FDM
at least 45 % FDM
Yellow Tilsit Pasteurized milk with higher fat content at least 55 % FDM
28 g
29.5 g
33 g
30–60 days Mild aroma, slightly sour
70–110 days Rich, spicy, and pungent
30–75 days Creamy, slightly sour, mild aroma
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Table 2 – Distribution of vocabulary items by eight GC-O sniffers in 11 classes Odor classes Buttery-cheesy
Earthy-undergrowth Empyreumatic Floral-fruity
Green-fatty
Malty-chemical
Meaty Nutty Spicy Sulfur Undefined
Odor descriptors Acid, animalic, buttery, caramel, creamy, butyric acid, cheese, cheesy, rancid, raclette cheese, sweaty, vomit, propionic acid, cooked milk, Tilsit, ripe, pungent, cheesy surface, diacetyl, old socks, cellar Earthy, mushrooms, forest, musty, old wardrobe, pine green, champignons Bread, burned, roasted, cooked, smoked Floral, fresh gum, fruity, strawberry, sweet, mint, pineapple, rose, vanilla, artificial fruit, rubbery, citrus, honey, terpene, cooked apple, cherry, fresh fruit, wine Fatty, green, fresh vegetable, grass, plant, oil, persil, old fat, wax, colored pencil, basilica, fresh cut grass, cut grass, bee wax, vitamin supplier Chemical, malty, cleaning product, plastic, gum, solvent, urine, acetic acid, medical like a hospital, glass cleaner, alcoholic, cork Bouillon, cooked meat, ham Cooked nut, chestnut, nutty Sesame-spicy, spicy Garlic, gas, potatoes, putrid, methanethiol, onion, sulfury, pungent, rotten, decomposed, compost, moldy ?, nd, warm, unpleasant, unknown
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Table 3 – Concentration of VSCs in Swiss Tilsit cheese sample Tilsit cheese sample1
Ions 3
LOD
4
Calibration concentrations
Regression
Compounds2
(µg kg-1)
equation
COS
0.1, 1, 10, 100, and 1000
Y=4905.3x
0.9990
0.180
0.610
32, 44, 60*
119.1±21.3
191.0±80.4
H2S
0.1, 1, 10, 100, and 1000
Y=4398.9x
0.9988
2.500
8.400
33, 34*, 35
163.0±58.0
147.0±19.6
R2
LOQ
(µg kg-1)
monitored
Green
Red
aAQA
GCOt
aOAVsniff
(ng)
(ng)
(-)
311.0±29.6
NA
odorless
NA
89.0±10.6
0.7
12