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Impact of crema on the aroma release and the in-mouth sensory perception of espresso coffee


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A set of six espresso coffees with different foam characteristics and similar above cup and in-mouth flavour sensory profiles was produced by combination of two varying parameters, the extraction pressure and the filtration of the coffee beverage. The coffees were subsequently evaluated in a comparative manner by a set of analytical (headspace, nose-space) and sensory (Temporal Dominance of Sensations) techniques. The presence of espresso crema in its standard quantity was demonstrated to be associated with the optimum release of pleasant high volatiles, both in the above cup headspace and in-mouth. On the other hand, the TDS study demonstrated that increasing amount of crema was associated with increasing roasted dominance along coffee consumption. Furthermore, a parallel was established between the roasted sensory dominance and the dominant release of 2-methylfuran in the nose-space. This was, however, an indirect link as 2-methylfuran was indeed a chemical marker of roasting but does not contribute to the roasted aroma. Lowering the standard amount of crema by filtration clearly decreased the release of pleasant high volatiles and the in-mouth roasted sensory dominance. On the other hand, increasing the usual crema volume by increasing the extraction pressure did not bring any added value concerning the above cup and in-mouth release of pleasant high volatiles.
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rXXXX American Chemical Society |J. Agric. Food Chem. XXXX, XXX, 000000
Influence of Foam Structure on the Release Kinetics of Volatiles from
Espresso Coffee Prior to Consumption
Susanne Dold,
Christian Lindinger,
Eric Kolodziejczyk,
Philippe Pollien,
Santo Ali,
Juan Carlos Germain,
Sonia Garcia Perin,
Nicolas Pineau,
Britta Folmer,
Karl-Heinz Engel,
Denis Barron,
and Christoph Hartmann*
Nestle Research Center, P.O. Box 44, 1000 Lausanne 26, Switzerland
Chair General Food Technology, Technische Universitat Munchen, Maximus-von-Imhof-Forum 2, 85350 Freising-Weihenstephan,
Rue du Village 5, 1052 Le Mont sur Lausanne, Switzerland
Nestle Nespresso S.A., Avenue de Rhodanie 40, 1007 Lausanne, Switzerland
ABSTRACT: The relationship between the physical structure of espresso coee foam, called crema, and the above-the-cup aroma
release was studied. Espresso coee samples were produced using the Nespresso extraction system. The samples were extracted with
water with dierent levels of mineral content, which resulted in liquid phases with similar volatile proles but foams with dierent
structure properties. The structure parameters foam volume, foam drainage, and lamella lm thickness at the foam surface were
quantied using computer-assisted microscopic image analysis and a digital caliper. The above-the-cup volatile concentration was
measured online by using PTR-MS and headspace sampling. A correlation study was done between crema structure parameters and
above-the-cup volatile concentration. In the rst 2.5 min after the start of the coee extraction, the presence of foam induced an
increase of concentration of selected volatile markers, independently if the crema was of high or low stability. At times longer than
2.5 min, the aroma marker concentration depends on both the stability of the crema and the volatility of the specic aroma
compounds. Mechanisms of above-the-cup volatile release involved gas bubble stability, evaporation, and diusion. It was concluded
that after the initial aroma burst (during the rst 23 min after the beginning of extraction), for the present sample space a crema of
high stability provides a stronger aroma barrier over several minutes.
KEYWORDS: espresso coee, crema, above-the-cup volatile release, foam structure
The term aroma refers to perceptions of volatiles in the atmo-
sphere through the olfactory system. It is related to volatile organic
compounds (VOCs) that reach the olfactory epithelium in the
upper part of the nose. During food consumption, the VOCs
released to the headspace can enter the consumers nose, leading
to an aroma impression even before the start of eating or drinking.
Whereas in total more than 800 VOCs have been identied in
coee aroma, several studies
have shown that only fewer than
50 of them can be considered as impact aroma compounds.
Espresso coee is the beverage prepared by short percolation
(30 (5 s) of hot water (90 (5C) at high pressure (above
7 bar) through a layer of roasted and ground coee (6.5 (1.5 g).
The extraction results in a polyphasic colloidal system. A foam
layer of small bubbles is formed on top of the aqueous solution
with dispersed ne coee particles and microscopic oil droplets.
On the physicochemical point of view, the espresso coee foam,
called crema, is a dynamic biphasic colloidal system. It is com-
posed of gas bubbles framed by liquid lms called lamella. The
gas phase of the crema consists of air, water vapor from the
percolation process, carbon dioxide formed in the Maillard reaction
during coee roasting and present in the roasted and ground
coee grain asperities, and volatile aroma compounds that are
released from the liquid into the gas phase. Several factors aect
the formation of the crema. The carbon dioxide formed during
the Maillard reaction and the pressure applied during the extrac-
tion are the two main factors.
In the Nespresso system used in
current study the pressure during the extraction is determined
not only through the particle size and the packing of the coee
but also through the membrane of the Nespresso capsule that
provides a back-pressure before rupture. The somewhat elastic
aluminum membrane ruptures upon swelling when the pressure
inside the capsule becomes high enough.
When gas is dispersed in water, the increase in interfacial area
increases the free energy of the system. According to the thermo-
dynamic dictum, all systems strive to reach a state of global energy
minimum. Liquid foams are not stable, but collapse by separating
into two phases to minimize the interfacial area and the systems
free energy. This instability makes foams very dicult to study.
Most foams owe their existence to the presence of surface active
molecular compounds, which decelerate foam destabilization by
reducing the surface energy and by stabilizing the lamella lms
against rupture.
The destabilization of espresso coee foam
has been ascribed to the mechanism of drainage,
meaning that
the liquid between the bubbles drains to the bulk. The lamella
lms become thin and eventually rupture. This leads to bubble
coalescence and, in the case of exposed lms, to foam collapse,
Received: May 5, 2011
Revised: September 7, 2011
Accepted: September 10, 2011 |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
including the release of entrapped gas and a loss of foam struc-
ture. Thus, the lamella lms are of crucial importance for foam
stability. Their thickness is reduced not only by drainage but also
by evaporation, considering the temperature of espresso coee.
Besides the roasted and ground coee, the second most im-
portant ingredient of espresso coee is water. It constitutes >95% of
the beverage.
Calcium and magnesium ions in the water have been
found to decrease foam stability as already claimed by Navarini and
content, respectively by the interaction between the cations and
protein/polysaccharide complexes, leading to a destabilization of
the foaming mechanism.
The crema of espresso coee is highly appreciated by con-
sumers for its sensory properties, notably its appearance prior to
consumption. Once in the mouth it contributes to the creaminess
and smoothness of the drinking experience. Crema is tradition-
ally believed to act as an aroma-sealing lid that traps the volatilized
compounds and doses their emission into the atmosphere.
In the current contribution, we propose that the crema structure
aects and supports volatile release.
Given the importance of aroma in coee consumption and the
consumersappreciation of crema, the objective of this work was
to investigate the inuence of the physical structure of espresso
coee foam on headspace volatile release. Several parameters of
crema structure were analyzed with regard to their impact on
volatile release above the cup.
Materials. Two different blends of commercial Nespresso capsules
were used: blend A (A) (lot 92333786PD 17:49 B) and blend B (B)
(lot MOUON-13 07:39 A). Both types of capsules contained pure
Arabica coffee. The main sensory attributes for blend A are roasted and
cocoa notes; blend B has roasted and fruity notes. For coffee extraction
commercial bottled waters of different mineral contents were used:
Acqua Panna (Pan) (lot L9245087701) for its mediumlow miner-
alization (calcium, 32.9 mg/L; magnesium, 6.5 mg/L) and Contrex
(Con) (lot 92473019N6) for its high mineralization (calcium, 468.0 mg/L;
magnesium, 74.5 mg/L). For all extractions a commercial Nespresso
machine C190 Plus was used.
Foam Structure Analysis Methods. The elapsed time before the
start of foam structure analysis and the elapsed time before the start of
the volatile release analysis methods was synchronized. The starting
point of all measurements, t= 0 min, was set as being 1 min after the start
of coffee extraction.
Foam Volume. Foam volume was determined using a digital caliper
(Garant IP65-CI50, Hoffmann Group, Munich, Germany). Measure-
ments were carried out in a commercial Nespresso glass cup (Essenza
espresso cup ref 3301/2/B). The distance from the top of the cup to a
certain fill level was linked to the respective fill volume by doing a
calibration with distilled water of 20 C. Volumes were plotted against
filling heights, and a third-order polynomial was fitted as calibration
curve. For foam volume analysis, 40 g of coffee beverage was extracted
into the cup. The distance from the top of the cup to the foam surface
and from the top of the cup to the liquid surface was measured with
the digital caliper. Corresponding filling volumes were calculated using
the third-order polynomial fit. The foam volume was calculated as the
difference of the two volumes. The measurement was done at t= 0 min
and at t= 5 min (equaling 1 and 6 min after the start of coffee extraction).
Ten repetitions were done for each sample. Averages and standard
deviations were calculated.
Foam Drainage. Foam drainage was determined using computer-
assisted microscopic image analysis. An amount of 25 g of coffee beverage
was extractedinto a plastic vessel. The plastic vessel had a transparent and
plane side wall, which allows a cross-sectional view of the crema and the
liquid volume beneath the crema. The plastic vessel was placed into a dark
chamber facing a digital microscopy camera (Infinity Y2-1C, Lumenera
Corp., Ottawa, Canada). Microscopic images were taken every 15 s,
starting at t= 0 min (1 min after the start of coffee extraction). In total
40 images were taken. The microscopic images were analyzed using the
image processing software Colibri developed in-house. For each picture,
the area (level) of the liquid underneath the foam was calculated. Data
were normalized by equating the area at t= 0 min to 100%. This allowed a
relative comparison between the drainage kinetics of thedifferent samples.
Triplicates were done for each sample. Averages and standard deviations
were calculated for each data point.
Foam Surface Area Fraction. The quality of the foam surface
was analyzed using computer-assisted microscopic image analysis. An
amount of 40 g of coffee beverage was extracted into a commercial
Nespresso porcelain cup and placed into a dark chamber under a digital
microscopy camera (Infinity Y2-1C, Lumenera Corp.) and a luminous
ring (Schott S40-55, Schott AG, Mainz, Germany). Five samples were
extracted and analyzed for each of the four investigated coffee beverages.
For each of the five samples, a series of 20 microscopic images of the
complete illuminated foam surface was taken at intervals of 30 s starting
at t= 0 min (1 min after the start of coffee extraction). Positioning of the
camera and coffee sample remained the same throughout the measure-
ments. The microscopic images were analyzed using the image proces-
sing software Colibri (noncommercialized in-house development). Each
color image was transformed into a black/white image. For each black/
white image the area fraction was calculated as the ratio between the area of
white parts of the crema surface in the transformed image and the total area
of the crema surface. Averages and standard deviations have been calculated
from the five repetitions for each time point and for each coffee beverage.
Volatile Release Analysis Methods. The above-the-cup aroma
intensity of the samples was measured online by proton transfer reaction
mass spectrometry (PTR-MS). The setup consisted of a headspace
sampling oven linked to a proton transfer reaction mass spectrometer.
Identification of the chemical compounds contributing to the ion trace
markers monitored by PTR-MS was done. The VOCs were identified by
using Tenax trapping and gas chromatography (GC) with simultaneous
and parallel detection by PTR-MS and time-of-flight mass spectrometry
(TOF-MS). The volatile release analysis methods used for this work
were described in detail by Lindinger et al.
Online Headspace Volatile Release. A double-jacketed, water-
heated sample cell (glass vial) was placed inside an oven at a temperature
of 100 C with active air circulation. A water bath at a temperature of
50 C was connected to the sample cell to keep the sample at constant
temperature. The sample cell was connected to the fix-installed top of
the cell by a clamp and sealed by a silicone O-ring. Three tubes were
installed in the cover of the cell. The first tube was supplied by the
preheated purge gas, the second provided a thermocouple to measure
the sample temperature, and through the third one the sample gas was
pushed out of the vial. Before analysis by PTR-MS, the sample gas was
diluted with dry air. Two flow controllers provided the dilution gas and
the purge gas, keeping the dilution ratio constant. Only a small fraction
of sample gas (40 standard cubic centimeters per minute (sccm)) was
used for analysis by PTR-MS (high-sensitivity PTR-MS, Ionicon Analytik
GmbH, Innsbruck, Austria). The major part was removed through an
exhaust line. Dry synthetic air was used as purge gas and dilution gas. The
flow rate of the purge gas was maintained at 300 sccm, the one of the
dilution gas at 3000 sccm.
To analyze the impact of crema, volatile release was measured for each
of the four beverages with crema (wc) and without crema (woc). For the
preparation of a sample without crema, a glass funnel covered with two
paper lters (KIMTECH Science precision wipes, Kimberly-Clark
Corp., Dallas, TX) was put on the sample cell and 40 g of coee brew |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
was extracted and ltered. On average, a residue of 3 g of crema mixed
with coee was held back, and 37 g of coee brew was collected into the
sample cell. The elapsed time from the start of the extraction to the end
of ltration (45 s) and then to connection of the sample cell to the
headspace sampling oven (15 s) was maintained constant at 60 s. To
prepare a sample with crema, the coee was directly extracted into the
sample cell. On average, 40 g coee brew was collected. As for the coee
preparation without crema, the sample cell was connected to the oven
setup 60 s after the start of the coee extraction. Therefore the time delay
(45 s) caused by ltering in the case of extraction without crema did not
inuence the comparability of the measurements.
The concentration (parts per billion) in the gas phase of 58 selected
ion traces was obtained during 10 consecutive minutes after connection
of the sample cell. The 58 ion traces chosen showed to be the most
discriminating over the mass range m/z20160 for coee headspace
analysis. For each analysis three individual headspace release measure-
ments were done. Between consecutive measurements, the sample cell
was equilibrated in the oven setup for 30 min. Ion trace release proles
were obtained by calculating average concentrations and standard
deviations for each data point (each 12.4 s).
Identification of Volatile Organic Compounds. To analyze
the chemical compounds contributing to the ion traces monitored by
PTR-MS, entrapment on Tenax traps was used. Tenax traps were
desorbed with an automatic thermodesorption unit (ATD), which was
connected to a GC column. Tenax traps were desorbed at 300 C for
10 min on the ATD unit (ATD Turbo Matrix 350, PerkinElmer Inc.,
Boston, MA) and purged with a helium flow of 20 sccm to the ATD trap.
The volatile compounds were cryofocused at 30 C for 10 min,
desorbed at 320 C for 3 min, and injected into the GC (Agilent 6890N
series GC, Agilent Technologies Inc., Santa Clara, CA) at 200 C.
A 60 m DB-Wax column (J&W scientific Inc., Folsom, CA) with an
internal diameter of 0.32 mm and a film thickness of 0.5 μm was used.
The temperature was kept at 20 C for 5 min, increased at a rate of
4C/min to 240 C, and maintained for 10 min. Helium at 3 sccm was
used as flow carrier gas. After thermodesorption and GC separation,
the eluent was split (1:1) to two detectors that were supplied parallel
and simultaneously: TOF-MS (Pegasus III TOF-MS, LECO Corp., St.
Joseph, MI) for identification based on the fragmentation patterns and
PTR-MS (high-sensitivity PTR-MS, Ionicon Analytik GmbH) to iden-
tify the ion trace found online and to semiquantify contribution
compounds by their GC peaks for a selected ion corresponding to the
same ion trace in the online mode. To allow a proper coupling of GC
with PTR-MS, the effluent gas of the GC column had to be mixed with
moist air prior to splitting. As the mobility of ions depends on the buffer
gas and its humidity, these parameters had to be kept constant to obtain
the same PTR-MS fragmentation pattern. In the online mode dry
synthetic air was used as buffer gas for the humid headspace sample.
The gas from the GC column in the offline mode was dry helium. To
compensate for this, the PTR-MS reaction chamber was fed by two inlets
in the offline mode. One came from the GC column carrying the dry
helium. The other one came from the PTR-MS headspace oven setup,
where the sample cell was filled with 100 mL of purified water to mimic
the humidity of the headspace sample gas in the online mode.
The identication of the chemical compounds contributing to the ion
traces monitored by PTR-MS was done by comparing GC relative
retention times (RI) and fragmentation patterns detected by TOF-MS
to commercial and internal databases (Wiley Registry of Mass Spectral
Data, 9th edition, Wiley, European Distribution Centre, PO22 9NQ
UK; FMD, internal Flavor Molecules Database).
Physical Foam Structure. Foam Volume. Foam volumes of
the four espresso coffee samples were determined with a digital
caliper. Results are shown in Figure 1. A ttest (two-sided, unpaired,
= 0.01) was applied to check for significant differences. The
risk level α
= 0.01 was the threshold level we fixed to confirm the
significance of a difference. The pvalues produced from the ttests
were compared to α
. If the observed pvalue was below α
concluded that the difference was significant.
The initial foam volumes (t= 0 min) are not signicantly
dierent between the beverages prepared with Acqua Panna and
those prepared with Contrex. At t= 5 min, the foam volumes of
espresso coees prepared using dierent waters show signicant
dierences. Higher foam volumes were measured for the espres-
so coees prepared with Acqua Panna than for those prepared
with Contrex. For both types of coee capsules, the foam of
espresso coees prepared with mediumlow mineralized Acqua
Panna shows higher stability in volume than the foam of the
corresponding espresso coees prepared with the highly miner-
alized Contrex.
Foam Drainage. The amount of liquid draining from the
espresso coffee foam was obtained by measuring the increase of
the area-projected volume of liquid phase underneath the foam.
Data were normalized by equating the area ofliquid phase present
at t= 0 min (equals 1 min after the start of coffee extraction) to
100%. Figure 2 shows averages and standard deviations obtained
of triplicates for the four espresso coffee samples. The espresso
coffees prepared with Contrex show a higher increase of the area of
liquid underneath the foam than the corresponding beverages
prepared with Acqua Panna. This observation applies to each data
point within the study period of 10 min. For both types of coffee
capsules, blends A and B, more liquid drains out of the foams of
espresso coffees prepared with Contrex than of the foams of
espresso coffees prepared with Acqua Panna.
Foam Surface Area Fraction. Figure 3 shows average area
fractions and standard deviations obtained of five measurement
repetitions for each of the four different espresso coffee beverages.
All four espresso coffee samples show the same area fraction of
Figure 1. Foam volumes of espresso coees prepared from blends
A and B, both using Acqua Panna (Pan) and Contrex (Con) at t= 0 min
and at t= 5 min (equaling 1 and 6 min after the start of coee extraction)
(averages and standard deviations of 10 repetitions shown). |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
approximately 0.6 at t= 0 min. The temporal evolution of the
area fraction shows clear differences between the beverages
prepared with Acqua Panna and those prepared with Contrex.
At elapsed times >6 min after the start of the coffee extraction,
the area fractions of both espresso coffees prepared with Acqua
Panna remain at higher values compared to those of the espresso
coffees prepared with Contrex. Consequently, the kinetics of the
area fraction depends on water ion content. The area fraction
indicates the intensity of light reflected by the crema surface. The
visual perception whitein the black/white images results from
reflected light. According to basic electromagnetic theory, the
capacity to reflect light depends on the thickness of the lamella
films located at the foam surface.
Thus, the results of the area
fraction can be interpreted as follows: All four espresso coffees
show approximately the same value for the area fraction at t=0
min, meaning that the initial film thickness of the lamella films
located at the top of the crema does not differ considerably
between samples. The faster decrease of the area fraction for
espressos prepared with water of higher mineral level compared
to espressos prepared with water of lower mineral level indicates
a more pronounced thinning of the lamella films located at the
foam surface.
Generally, a decrease in foam volume can be assigned to phase
segregation, implying the loss of gas into the surrounding air and
the loss of uid into the liquid bulk due to drainage. The latter
implicates thinning of the lamella lms, which in turn leads to
lm rupture and foam collapse, including a loss of entrapped gas
and a loss in foam volume.
Thus, the observations on foam
volume, foam drainage, and foam surface quality support each
other and demonstrate that the foams of espresso coees prepared
with water of high mineralization show a lower stability than the
foams of the corresponding espresso coees prepared with water
of low to medium mineralization.
A possible explanation for the lower stability measured for
espresso coees prepared with water of high mineral content is
the potential disturbing eect of the ions on the interactions
between the foaming fractions. Surfactant molecules can bind to
proteins and polysaccharides, forming surfactantbiopolymer
complexes, which may have functional characteristics dierent
from those of the individual components. The interaction can be
based on dierent mechanisms, whereby the most important are
electrostatic and hydrophobic interactions. These have a strong
inuence on physicochemical properties of the system, which, in
the case of espresso coee, are directly linked to the physical crema
structure. It is possible that the ions of the high mineralized water
disturb these electrostatic interactions of surfactantbiopolymer
complexes and change the stability of the surface physical
Volatile Release above the Cup. The headspace volatile
release was measured online using PTR-MS. Each of the 58
monitored ion traces shows its own release pattern. Within the
framework of this study, some markers were selected for further
investigation and discussion. Three selection criteria were applied:
First, the signal-to-noise ratio of the ion trace release profile
should be >10.
Second, the selected markers should represent
potential coffee aroma compounds. This selection criterion was
applied by using an internal database (FMD, internal Flavor
Molecules Database). However, compounds such as 2-furfurylthiol,
Figure 3. Area fraction (calculated by dividing the area of white parts of
the crema surface in the black/white images by the total area of the
crema surface) starting at t= 0 min (equals 1 min after the start of coee
extraction) for blends A and B, both prepared with Acqua Panna (Pan)
and Contrex (Con) (averages and standard deviations of ve repetitions
Figure 2. Increase of area projected volume of liquid phase underneath
espresso coee foam starting at t= 0 min (equals 1 min after the start of
coee extraction) for blends A and B, both prepared with Acqua Panna
(Pan) and Contrex (Con) (averages and standard deviations of tripli-
cates shown). |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
3-mercapto-3-methylbutylformate, methional, β-damascenone,
and Furaneol known to have a high aroma impact are not
covered by the markers, because they are present in coffee
headspace at concentrations too low to be detectable by online
Third, ion traces associated with acetic acid were excluded, as
this molecule showed disturbing eects due to interaction of the
molecule with the tubing system of the headspace sampling
setup. By applying these three selection criteria, 8 of 58 ion traces
were chosen for further analysis for blend A (m/z45, 59, 69, 73,
75, 81, 87, and 95), and 7 of 58 ion traces (m/z45, 59, 69, 73, 75,
81, and 87) were chosen for blend B.
Figures 4 and 5 exemplarily show the release proles of m/z
45, 59, and 81 for blends A and B, prepared with Contrex and
Acqua Panna, both with crema (wc) and without crema (woc).
Table 1 shows the chemical components contributing to m/z
45, 59, and 81. Each marker represents several chemical com-
pounds. Thus, the release proles need to be considered as the
superposition of release proles of all contributing compounds.
The three markers m/z45, 59, and 81 represent volatiles with
both very high and very low volatilities. The other investigated
markers are similar to or between the extremes represented by
these three marker characteristics.
Within the rst 2.5 min after the start of the coee extraction,
the presence of crema generally resulted in an above-the-cup
volatile concentration signicantly higher than that of the liquid
coee phase without crema. This was shown for both coee
blends and for all investigated release patterns. After this initial
burst, the impact of crema is more dierentiated. Depending on
the investigated group of chemical compounds and on the type
of water used, the crema on top of the liquid coee phase can
either act as long-term enhancer of the volatile release above cup
or have no eect or act as a long-term barrier of volatile release.
These ndings demonstrate that the concept of crema being an
aroma-sealing lid
cannot be generalized. When the impacts of
foams with dierent stability patterns starting at t= 2.5 min are
compared, it can be observed within the given sample space that
the volatile concentration above the cup is higher for espresso
coees prepared with water with high mineral content (here:
Contrex). For the corresponding liquid coee phases without
crema, no considerable inuence of the type of water used for coee
preparation could be evidenced. With regard to this nding, it is
suggested that espresso coees with a crema of lower stability
provide higher above-the-cup volatile concentrations at longer
times after the extraction (>2.5 min). To conrm this prelimin-
ary conclusion, the data of physical foam structure and volatile
release were used for a statistical correlation study.
Correlation of Physical Foam Structure and Above the
Cup Volatile Release. For espresso coffee samples prepared
with crema (A Pan wc, A Con wc, B Pan wc, and B Con wc), a
normalized principal component analysis (PCA) was done
considering the markers m/z45, 59, 69, 73, 75, 81, and 87.
Variables (i.e., markers) are represented as lines. The smaller the
angle between two variables, the better is the correlation. Indivi-
duals (i.e., coffee samples) are represented as dots. When a coffee
sample is positioned at large distance from the center (reference)
and close (orthogonal projection) to the vector of a marker, the
coffee sample has a high value for this marker. In addition, the
data obtained for the structure parameters foam volume
(FoamVol), foam drainage (FoamDrain), and foam surface area
fraction (FoamSAF) are added as supplementary variables (i.e.,
these variables are added a posteriori on the PCA map).
Three dierent PCAs were done. The rst one using data
obtained at tburst, the time corresponding to the highest aroma
release intensity, which occurs around 45 s after the start of the
headspace release measurements (Figure 6). The second PCA was
Figure 4. Volatile release proles of PTR-MS ion traces m/z45, 59, and
81 for samples prepared from blend A with Contrex (Con) and Acqua
Panna (Pan), both with crema (wc) and without crema (woc) (t= 0 min
equals 1 min after starting coee extraction) (averages and standard
deviations of triplicates). |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
done on data obtained at t= 5 min, equaling 6 min after the start of
the coee extraction (Figure 7). The third PCA was done on the
calculated dierences between the data obtained at tburst and the
data obtained at t=5min(tburst t= 5 min) (Figure 8).
The PCA at tburst (Figure 6) shows that the essential infor-
mation is reected by the rst principal component (93%,
horizontal axis). It is almost one-dimensional. The volatile
release of all seven markers is highly negatively correlated with
the foam surface area fraction. From the results of the PCA for
this time point it can be concluded that the thinner the lamella
lms located at the foam surface, the higher is this initial aroma
burst. There is no correlation with the foam drainage or the foam
volume at this short time after extraction. It cannot be observed
either that foams of dierent stabilities cause dierent initial
above-the-cup aroma intensities. Therefore, we suggest that the
rupture of the thin exposed lamella lms leads to bubble collapse
and release of entrapped gas.
Thus, the initial burst could
be explained as follows: The VOCs entrapped in the gas phase of
the foam bubbles are released into the headspace as the bubbles
at the crema surface explode due to rupture of thin exposed lamella
lms. Thinning of lms at the top of foams is caused either by
evaporation of the liquid phase or through gravity-driven drainage.
As no correlation with foam drainage was shown and considering
the temperature of freshly brewed coee, we concluded that
evaporation is a major inuencing phenomenon here. At the high
exchange surface area of the crema, volatiles will evaporate from
the liquid phase to the gas phase above the cup and will thus be
available for perception. Rate-limiting eects are unlikely for the
liquid phase, because the liquid is exposed to natural convection.
Consequently, in the presence of crema the mechanisms of
volatile release are lamella rupture and evaporation. The high
exchange surface area of crema allows a burst of both high and
low volatile aroma compounds. In the absence of crema the
mechanism of volatile release is purely driven by evaporation at
the liquid-gas interface.
The PCA of data obtained 6 min after the start of the coee
extraction (t= 5 min) (Figure 7) is almost one-dimensional, too,
but shows correlations other than the PCA at tburst. The volatile
release is strongly negatively correlated with the foam volume
and negatively correlated with the foam surface area fraction. It
can be concluded that the thinner the lamella lms at the foam
surface and the lower the foam volume, the higher is the volatile
concentration above the cup. Large foam drainage can also be
considered as contributor to a high above-the-cup aroma in-
tensity because the corresponding vector in the PCA has a small
angle with most marker vectors. A low foam volume, thin lamella
lms at the foam surface, and drainage of the liquid out of the
foam into the bulk are all indicators for foam destabilization.
Accordingly, for all coee samples, the PCA for t= 5 min reveals
that the volatile release of espresso prepared with the highly
mineralized water (Contrex) is globally higher than the volatile
release of espresso prepared with low mineralized water (Acqua
Panna). Thus, this PCA conrms the assumption that was
already made on the basis of the results of the foam structure
analysis and the volatile release analysis. After the initial aroma
burst, a crema of low stability gives higher above-the-cup volatile
concentrations than a crema of high stability in the present
sample space. This can be explained to a large extent by the fact
that foam bubbles rupture due to thin lamella lms and release
the trapped volatiles into the surrounding air. For a more stable
crema the VOCs remain trapped in the gas bubbles for a longer
time. For the initial aroma burst it was suggested that evaporation
leads to thinning of lamella lms. From the correlation observed
between above-the-cup volatile concentration and foam destabi-
lization for the situation after the initial aroma burst, the thinning
of lamella lms can be attributed to drainage.
Figure 5. Volatile release proles of PTR-MS ion traces m/z45, 59, and
81 for samples prepared from blend B with Contrex (Con) and Acqua
Panna (Pan), both with crema (wc) and without crema (woc) (t= 0 min
equals 1 min after the start of coee extraction) (averages and standard
deviations of triplicates). |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
In a third PCA, dierences in the volatile release proles
between tburst and t= 5 min were correlated to dierences in the
foam structure between tburst and t= 5 min. The PCA for the
dierence Di(Figure 8) illustrates that the decrease of volatile
concentration of markers m/z73, 87, 45, and 59 is positively
correlated with the decrease of foam drainage and negatively
correlated with the decrease of foam surface area fraction.
For these markers, the decrease in volatile release is stronger
for the espresso coees prepared with Acqua Panna than for the
espresso coees prepared with Contrex. Correspondingly, for a
more stable crema with less drainage and thicker lamella lms, we
observed a stronger decrease in volatile release with respect to its
maximum level of intensity. However, for three other groups of
chemical compounds (markers m/z81, 69, and 75), the PCA
indicates a much weaker correlation between foam stability and
volatile release as compared to the four markers mentioned
above. The decrease of the volatile release for the markers m/z81
and 69 tends to correlate strongly with the decrease in foam
volume, whereby it has to be considered that m/z75 is only
weakly represented in this PCA. It is suggested that the dierent
correlations of the markers are related to the volatility of the
dierent compounds (Table 1). The low-volatile compounds are
less present in the gaseous phase of the crema, and thus their
concentration above the cup is less correlated to the destabiliza-
tion process of the crema.
Four eects are proposed to take place depending on the
volatility of the aromas and the stability of the crema: For high-
volatile compounds (K=10
) and a crema of low
stability, the crema acts as an enhancer for aroma release. High
volatiles are abundant in the gas phase of the foam bubbles and
released upon their rupture. Examples for this eect are the
release patterns of Contrex m/z45 and Contrex m/z59. For low-
volatile compounds (K=10
) and a crema of low
stability, the creation of new interface upon bubble rupture
increases the diusion of low-volatile aromas. The release pattern
of Contrex m/z81 shows this behavior. For high-volatile
compounds and a crema of high stability, the crema acts as a
barrier that entraps volatiles. Acqua Panna m/z45 and Acqua
Panna m/z59 are examples for this eect. For low-volatile
aromas and a crema of high stability, the aromas will be released
from the interface through a diusion process, as, for example,
shown by the release pattern of Panna m/z81.
Table 1. Chemical Compositions of the PTR-MS Ion Traces
m/z45, 59, and 81 Obtained by GC-MS Coupling
for Blends A and
B, Both Prepared with Acqua Panna and Contrex
m/z45 (fruity, green, malty notes) m/z59 (buttery, green notes) m/z81 (roasted notes)
compound K
compound K
compound K
acetaldehyde 1.63 10
acetone n/a 2-furanmethanol 1.19 10
2-methylbutanal 8.36 10
2,3-butanedione 5.98 10
2-furfuryl formate n/a
3-methylbutanal 7.91 10
propanal 1.80 10
2-furfuryl acetate 6.12 10
2-methyltetrahydrofuran-3-one n/a pyridine n/a
pyrazine n/a
Tentatively identied using commercial and internal databases.
Sensory descriptors (internal data bases) of odorant compounds identied in the
chemical composition of PTR-MS ion traces were assigned directly to the corresponding masses. Air/liquid partition coecients K
(without unit)
were measured by stripping with pure air an aqueous solution containing individually the dissolved chemical compounds at mg/L levels. Depletion of
VOCs relative concentration in the gas phase measured at 60 C by PTR-MS allowed determination of partition coecients.
Figure 6. PCA of foam structure parameters and volatile release of
selected markers (vectors) for tburst (105 s after the start of coee
extraction) for the four dierent espresso coee samples with crema
Figure 7. PCA of foam structure parameters and volatile release of
selected markers (vectors) for t= 5 min (6 min after the start of coee
extraction) for the four dierent espresso coee samples with crema
(points). |J. Agric. Food Chem. XXXX, XXX, 000–000
Journal of Agricultural and Food Chemistry ARTICLE
Conclusion. These results show for the first time the influence
of crema stability properties on the volatile release profiles above
the cup. In summary, during the first 2.5 min after the start of the
espresso coffee extraction, the presence of crema provides a
volatile burst above the cup, no matter if the crema is of high or
low stability. Six minutes after the start of the extraction, a crema
of low stability gives higher above-the-cup volatile concentrations
than a crema of high stability. After the initial aroma burst, a
crema of low stability provides a more long-lasting high above-
the-cup aroma intensity.
It is still an open question whether these release kinetics and
their dierences can be perceived by a consumer or not, and
beyond, which kinetics would then be the most liked. It should be
kept in mind that in an average consumption behavior the rst sip
would occur during the burst of the aromas above the cup
(during the rst 2.5 min), and most probably the cup is fully
consumed after 5 min. To provide a sensory validation, time-
resolved sensory studies and consumer preference studies are
Corresponding Author
*Phone: +41 21 785 8102. E-mail: Christoph.Hartmann@rdls.
VOCs, volatile organic compounds; A, blend A;B, blend B; Pan,
Acqua Panna; Con, Contrex; PTR-MS, proton transfer reaction
mass spectrometry; GC, gas chromatography; TOF-MS, time-of-
ight mass spectrometry; sccm, standard cubic centimeters
per minute; ppb, parts per billion; ATD, automatic thermode-
sorption; wc, with crema; woc, without crema; PCA, principal
component analysis; RI, retention index (time); FoamVol, foam
volume; FoamDrain, foam drainage; FoamSAF, foam surface area
fraction; α
, risk level of signicance used in the ttest.
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selected markers (vectors) for the dierence Di(values for tburst
values for t= 5 min) for the four dierent espresso coee samples with
crema (points).
... Additionally, the coffee matrix has been known to affect volatile partitioning during sample preparation, with several studies documenting the impact of coffee preparation methods (e.g. brewing methods, crema, serving temperature) and macromolecule matrix constituents (e.g. proteins, lipids) on aroma release (Barron et al., 2012;Itobe et al., 2015). This exerts significant and complicated influences on analyte recoveries, which may introduce sampling biases (Sgorbini et al., 2019;Zanin et al., 2020). ...
... These attributes make PTR-MS particularly amenable to on-line analysis of real-time events such as roasting or aroma release, thus adding dimensionality to the analysis of coffee (as further reviewed by Yeretzian et al. (2019)). However, like other DI-MS methods, PTR-MS faces challenges in compound identification due to the lack of chromatographic separation, although coupling this with GC (GC-PTR-MS) may aid in annotating some compounds in the PTR-MS spectra (Barron et al., 2012;Mateus et al., 2007). Other CI methods such as atmospheric pressure CI (APCI) (Hatakeyama & Taylor, 2019) and selected ion flow tube-MS (SIFT-MS) (Dryahina et al., 2018) have been used with DI-MS (Table 1), although the comparative advantage of these detection methods to more well-established PTR-MS has yet to be determined (Dryahina et al., 2018;Gerbig et al., 2017;Hatakeyama & Taylor, 2019;Heide et al., 2020). ...
Coffee has attracted significant research interest owing to its complex volatile composition and aroma, which imparts a pleasant sensorial experience that remains challenging to analyse and interpret. This review summarises analytical challenges associated with coffee’s volatile and matrix complexity, and recent developments in instrumental techniques to resolve them. The benefits of state-of-the-art analytical techniques applied to coffee volatile analysis from experimental design to sample preparation, separation, detection, and data analysis are evaluated. Complementary method selection coupled with progressive experimental design and data analysis are vital to unravel the increasing comprehensiveness of coffee volatile datasets. Considering this, analytical workflows for conventional, targeted, and untargeted coffee volatile analyses are thus proposed considering the trends towards sorptive extraction, multidimensional gas chromatography, and high-resolution mass spectrometry. In conclusion, no single analytical method addresses coffee’s complexity in its entirely, and volatile analysis must be tailored to the key objectives and concerns of the analyst.
... Proton-transferreaction mass spectrometry (PTR-MS) was first used to monitor coffee aroma release with in-mouth and nosespace measurements [3,7] with a focus on inter-and intra-individual differences among consumers and release mechanisms. PTR-MS was later applied to the investigation of the effect of coffee foam on VOC release in espresso coffees [8], the study of inter-individual differences in coffee aroma release [9], and the correlation between time-resolved aroma release and retronasal perception [10]. ...
Full-text available
This work presents in vitro and in vivo aroma release analysis of three espresso coffees carried out by PTR-ToF-MS headspace and nosespace analysis, respectively. The products were C. arabica coffees prepared using an espresso coffee machine: a low-caffeine C. arabica var. laurina light roast, a low-caffeine C. arabica var. laurina dark roast, and a single-origin coffee from Ethiopia which were roasted to a medium roast degree. Headspace analysis allowed for discrimination between coffees with a prediction accuracy of 92% or higher. Relevant discriminating compounds were related to the roasting degree and varietal compounds. Coffee nosespace consisted of 35 mass peaks overall. Despite this relatively low number of detected peaks, coffee discrimination was still possible with ≥93% accuracy. The compounds most relevant to the discrimination were those related to the roasting degree. Major differences—both qualitative and quantitative—were found between headspace and nosespace profiles.
... Beverages 2022, 8,28 ...
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The coffee extraction methods modify the structure of the foam (when it is present) and the sensory profile of the beverage. In this research, three ways of extracting and two varieties of 100% Arabica were compared. Nineteen bars and fifteen bars were applied to the coffee thanks to the use of compatible capsules and machines. The method with the moka was considered, which acts at low pressures and does not allow the formation of foam (crema). In addition, the Brazil and Guatemala Arabica varieties were considered to understand the extent to which Arabica coffee can respond in structural and sensorial terms to the extraction techniques applied. The results show that 19-bar espresso coffees have a very stable crema with very small bubbles, which give a uniform and fine structure to the coffee crema. On the contrary, the pressure at 15 bars generates more unstable foams and bubbles that tend to be disproportionate, with more marked effects in the Brazil variety. The sensory profiles of the coffees respond to the extraction techniques applied. While the coffee extracted with the moka has sensory descriptors with rather low values, those obtained at 19 and 15 bars have much wider profiles. In conclusion, different pressure intensities to the coffee extraction affect the quality of crema and the solubilization of organoleptically active compounds.
... Volatile compounds instrumental analysis corroborated the sensory results as they revealed that swallowing induced a higher and earlier release of larger amounts of aroma. Barron et al. (2012) [16] have applied these two temporal methods to espresso coffee to measure the impact of foam/"crema" on the aroma release and in-mouth sensory perception. ...
This thesis involves developing fast, rapid, and non-invasive headspace and nosespace analysis techniques based on PTR-ToF-MS coupled with an autosampler and tailored data analysis tools. The investigated case studies are related to coffee flavour also in connection with different technological and fundamental aspects as roasting and origin. In a first study, an automated headspace sampling method was developed by combining a GC autosampler to PTR-ToF-MS to analyse the aroma profiles of three monoorigin (Brazil, Ethiopia and Guatemala) roasted and ground Coffea arabica samples from different batches. Unsupervised and supervised multivariate data analysis techniques were applied for data exploration and to classify coffees according to origin. Coffee samples were successfully separated according to origin by unsupervised methods (Principal Component Analysis, PCA). This separation was confirmed with Partial Least Square Regression-Discriminant Analysis (PLS-DA). The samples of one batch could be used as training set to predict geographic origin of the samples of the other batch, suggesting the possibility to predict further batches in coffee production by means of the same approach. As a follow-up study, the developed headspace sampling method was applied to analyse six roasted Coffea arabica coffees, both brew and powder, of different geographical origins (Brazil, Ethiopia, Guatemala, Costa Rica, Colombia, and India). For the first time, the volatile compounds released from coffee were analysed with PTR-ToF-MS in Switching Reagent Ion (SRI) mode by using different ionization agents: H3O + , NO + and O2 +. Significant differences were found among volatile concentrations for the different origins both for powders and brews, in particular high concentrations of terpenes for Ethiopia, sulphur compounds for Colombia and thiazoles for Brazil and India. Effective classification models have been set for the different ionization modes and data fusion of the data obtained by different reagent ions further reduced the classification errors. The next project was the development and application of an experimental protocol to monitor the volatile compounds released from single coffee beans at different stages of roasting. A laboratory scale oven was used to roast the green coffee beans (Coffeea arabica) from different geographical origins (Brazil, Guatemala and Ethiopia) by sampling every one min up to 25 min. Two batches of one coffee origin were selected and at each time point, 3 coffee beans were roasted. This resulted in volatile profiling of a large sample-set: 468 coffee beans (3 origins x 2 batches x 3 replicates x 26 time points). The weight losses due to roasting process were Abstract ii
... In the TDS task, the temporal change of each sensory attribute is obtained by recoding the most dominant attribute (i.e., the most impressive attribute, but not necessarily the strongest attribute) that changes over the course of time. Several studies employed the TDS task using beverages such as coffee [18][19][20], blackcurrant squashes [21], red wine [22,23], white wine [24,25], and vodka [26]. ...
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In most cases, a meal cannot be finished with a single bite and sip. During eating and drinking, consumers receive dynamic food perceptions from sensory attributes in foods. Thus, we performed multi-sip time–intensity (TI) evaluation of sensory attribute. In each of ten trials, the participant evaluated continuously the intensity of retronasal aroma for 60 s after swallowing oolong tea. We compared the TI parameters (Imax: maximum intensity, Tmax: time point at which intensity reached the maximum value, AUC: area under the TI curve, Dplateau: duration between the first and last time points with values exceeding 90% of the maximum intensity, Rinc: rate of intensity increase between the first time points with values exceeding 5% and 90% of the maximum intensity, and Rdec: rate of intensity decrease between the last time points with values exceeding 5% and 90% of the maximum intensity) and TI curves among the ten trials, and approximated each TI curve with an exponential model. Some TI parameters (Imax, Tmax, AUC, and Rinc) differed significantly between the first and subsequent trials. The TI curve was significantly lower in the first trial than in the subsequent trials, and TI curve during the time from starting the evaluation to reaching maximum intensity was significantly lower in the second trial than in the subsequent trials. The time constant of the fitted exponential function revealed that the decay of retronasal aroma intensity was slightly faster in the second through fourth trials than in the first and the fifth through tenth trials. These results indicate that olfaction might be more perceptive while consumers sip a cup of the beverage.
... Actually, a survey analyzed the saccharides in 42 sweet snacks and beverages in Japan and reported that three sweet teas contained an average of 0.05 M to 0.18 M sucrose [7]. Although the sex of study participants considerably affects various sensory functions [8], no previous studies have considered the participants' sex when examining temporal aspects of these flavor enhancements [5] [9] [10] [11]. In this study, we examined the effect of participants' sex on temporal sequence of flavor sensations elicited by fruit-flavored teas with an average level of sugar (0.05 M) preliminarily. ...
Proton Transfer Reaction‐Time‐of‐Flight‐ Mass Spectrometry (PTR‐ToF‐MS) is an analytical chemistry technique that can be used for measuring the concentration of volatile organic compounds directly in the subjects’ noses (nosespace, in vivo analysis) during a tasting and over time. It can be combined with temporal sensory methods such as Temporal Dominance of Sensations (TDS) or Temporal Check All That Apply (TCATA) in order to obtain simultaneous sensory and physico‐chemical signals. This paper aims to provide a methodology to analyze in vivo PTR‐MS and temporal sensory data and illustrate it on a real dataset. First, relevant pretreatments of PTR‐MS data were established, including breathing correction, blank periods removal and standardization. Then, a statistical multiblock analysis was presented: the Regularized Generalized Canonical Correlation Analysis (RGCCA). The versality of the approach was demonstrated, as it can be used to answer most of problematics (exploratory or supervised). Finally, this methodology is illustrated on a dataset of PTR‐MS and TDS or TCATA data collected simultaneously. In this study, 16 semi‐trained subjects evaluated 3 chocolates in TDS and TCATA on six flavor attributes (Spicy, Cocoa, Woody, Fruity, Roasty and Dry Fruits) with 2 replicates for each sensory method. Results showed that TCATA and TDS gave similar results, but TDS was shown to slightly better preserve the PTR‐MS observed product configuration than TCATA. All computing tools developed in this work are freely available.
Flavor molecules belong to different chemical classes, and possess various sensory properties. They are present in the foods, but in order to reach the sensory receptors they have to be released in the saliva during the eating process and for aroma compounds in the air phase from the oral to the nasal cavity. This chapter will present an overview of the different aroma and taste compounds, their dynamic release from the food matrix into the saliva and the oronasal cavity, taking into account the in-mouth physiological process, and the influence on flavor perception. In-mouth flavor compound release and flavor perception are very complex phenomena which are not well understood yet. The properties of the food matrix and oral physiological characteristics and their interactions are the main drivers for interindividual variability. The development of mechanistic models allowed a better understanding of the release of aroma and taste compounds during the eating process. However, the release behavior does not always explain sensory perception, due to other physiological mechanisms at the central and peripheral levels.
Volatile compounds carry valuable information regarding the properties of foodstuffs. Volatiles emitted from food can be used as, for example, indicators of quality, shelf-life, or authenticity. A better understanding of the multitude of transformations which occur during food processing could facilitate the optimisation of production, increase the desirability of food products, and also their wholesomeness. However, as some of these transformations are fast-paced, it is necessary to monitor them using techniques which enable real-time determination of volatiles, such as proton transfer reaction–mass spectrometry (PTR–MS). Recent years have seen a marked increase in its use in food analysis, since it can be used to obtain insight into the dynamics of the monitored processes and can be the basis for precise quality control methods for food processing. This review highlights recent works in which PTR–MS was used in monitoring during foodstuffs production, preparation and storage.
Coffee foam is the frothy layer that forms above the liquid phase of espresso and instant coffee beverages. While the carbon dioxide formed during roasting is responsible for crema formation in espresso, gasification is the established foaming approach in instant coffee. The protein-like fractions and polysaccharides extracted from roasted coffee promote foamability and foam stability, respectively. Crema of consolidated texture retains the volatile aromatic substances and prevents the espresso from cooling too rapidly. Further, an inverse relationship has been observed between foam persistence and volatility of aroma molecules above the cup. Gasified spray-dried instant coffee exhibited an accelerated delivery rate of hydrophobic aroma compounds. Thus, foam is the signature of a high-quality cup of coffee. Despite its various functionalities, coffee foam is scarcely investigated owing to its metastable nature. Only recently, the chemical, structural, and interfacial rheology properties of the coffee foam have been looked at. The current study intends to review the scientific knowledge acquired on coffee foam, thus far. The initial sections describe the general attributes and functions of espresso and instant coffee foam. Further, the mechanisms of formation and stabilization of coffee foam are detailed, followed by the factors influencing the same. The following discussions focus on the role of coffee foam in determining the sensory and aroma release characteristics of the beverages. The scope for future research in this field of study is highlighted in the concluding section.
Espresso coffee world-wide success, besides being a phenomenon of fashion, seems to be based on the greater sensory satisfaction it gives to the consumer when compared with coffees prepared with other brewing methods. Conditions normally used in the espresso brewing technique enhance several surface tension-related phenomena such as foam and emulsion formation and stabilisation which strongly affects the organoleptic beverage properties. In spite of the relevant role played by surface tension in several quality characteristics of espresso coffee, little attention has been paid in its determination and its time-dependency has not yet been investigated.In the present work, experimental techniques such as maximum bubble pressure and pendant drop have been used to characterise in a wide time window the dynamic surface tension of air–espresso coffee beverage interface at two different temperatures. The experimental data show a remarkable decrease of the surface tension with time for beverages prepared by using pure arabica as well as pure robusta roasted coffee, with a profile dependent upon the coffee variety. This behaviour is definitely related to the presence of surface active components and is consistent with a system having good wetting properties for oral cavity surfaces. A possible role of some natural surface active chemical components, like lipids, on tensiometric behaviour is discussed.
Recently we introduced a dynamic approach to determine Henry’s law constants (HLCs) of volatile organic compounds (VOCs) in water, and applied it to a series organic compounds dissolved in pure water. Here, we first discuss a further development of the original approach such that it can be applied to complex liquid food systems (coffee). Second, we examine the impact of non-volatile constituents on the HLC. More specifically, we evaluate the impact of non-volatile coffee constituents on the HLC of 2-methylpropanal, 3- and 2-methylbutanal, dimethylsulfide, dimethyldisulfide and ethyl-2-methylbutyrate. Finally, we demonstrate that the concentration on the VOC in solution does not affect the HLC, over the investigated concentration range of 10−4 to 10ppm.
Protein-protein and protein-surfactant interactions have been investigated in bulk aqueous solution and in oil-in-water emulsion systems by electrophoretic mobility measurements. The interaction between oppositely charged β-lactoglobulin and gelatin has been studied under neutral pH conditions. The addition of cationic gelatin to a β-lactoglobulin-stabilized emulsion induces flocculation and charge neutralization of the emulsion droplets. The procedure of mixing the gelatin solution with the β-lactoglobulin-stabilized emulsion has no significant effect on the observed mobility behaviour of the emulsion droplets. Binding of the anionic surfactant sodium lauryl ether sulphate (SLES 2EO) to β-lactoglobulin and gelatin was observed under neutral pH conditions. The charge neutralization line for gelatin + SLES 2EO complexes in distilled water appears consistent with its maximum precipitation line. However, the charge neutralization line of gelatin + SLES 2EO at pH 7.0 occurs at slightly lower surfactant concentrations compared to the maximum precipitation line. The addition of SLES 2EO to a gelatin-stabilized emulsion causes a change in calculated zeta potential of the emulsion droplets and a partial charge neutralization for the flocculated emulsion droplets. Electrophoretic mobility measured in solutions of β-lactoglobulin + gelatin + SLES 2EO shows that the three-component complexes (or precipitates) are negatively charged. Various possible interaction mechanisms are discussed taking account also of results obtained on the same systems by other complementary techniques.
Temporal dominance of sensations (TDS) and time intensity (TI) were used to characterize specific organoleptic properties of six beverage products. Results from these two sensory techniques were compared by using three different statistical approaches. Firstly, both TI and TDS results were analysed by parametric modelling, to determine key parameters of each individual curve. Average parameters over judges and repetitions were used to build ‘time intensity’ curves. Similarities in the results were highlighted; however TI was shown to be more precise in the determination of the perception kinetic. Secondly, a multiple factorial analysis (MFA) was carried out, aiming at getting product perception pattern over the time, as determined by TDS and TI. MFA results confirmed that the two sensory techniques lead to similar conclusions, as attested by the calculated multivariate correlation coefficient RV = 0.854. This was true for product perception pattern over the time, as well as for product description, given that attributes used in both sensorial techniques appeared strongly correlated. Thirdly, for each product and attribute pair, ‘score over time’ curves were extrapolated from raw data by averaging scores for each time measurement over panellists and repetitions. To do so, attribute scores were set to ‘0’ when a panellist had finished evaluating a given attribute. As a result, for each sensory technique, one curve by product and attribute could be obtained, allowing products and techniques comparison. Overall, conclusions of all three statistical approaches were that TI and TDS brought similar information in terms of differences between products, attributes, and evolution over the time. TDS could be used to illustrate product perception as a function of time, whereas TI would be better suited if the determination of the kinetic of one specific attribute is required.
IntroductionExtraction Methods Beverage CharacterizationModified Coffee BeveragesReferences
We investigated the role of both candy texture and eating technique (melting or chewing) on the dynamics of aroma release. One novelty of this type of analysis was the simultaneous application of instrumental and sensory analysis. Four candy textures were established based on their storage modulus at 1 Hz by varying the gelatine content between 0 and 15% w/w. The invivo release of three aroma compounds was monitored using Proton Transfer Reaction Mass Spectrometry and with a trained panel of testers. The gelatine content had no significant effect on the headspace/product partition and diffusion properties of the aroma compounds. The highest invivo release for all aroma compounds was obtained with the 2% gelatine sample. Our findings indicated that aroma release was determined by interaction between the product properties and oral behaviour. Relations between the dynamics of release and perception (method of Temporal Dominance of Sensations) have been established on temporal parameters.Research highlights► This study focus on the effect of candy structure on aroma release and perception. ► The highest in vivo release was obtained with the 2% gelatine sample. ► Release results from interactions between product properties and oral behaviour. ► Relations were established between sensory and release temporal parameters.
Proteins play an important role as macromolecular surfactants in foam and emulsion-type food products. The functioning of proteins in these applications is determined by their structure and properties in the adsorbed layers at air-water and oil-water interfaces. In addition, because typical food proteins are mixtures of several protein components, interaction between these components in the adsorbed layer also impacts their ability as surfactants to stabilize dispersed systems. In this paper, recent progress in our understanding of the molecular mechanisms involved in the formation and stability of protein-stabilized foams and emulsions has been reviewed.