-
pe
Lu
, Avdlbace
e gof
ncr
of the bioactive compounds gallic acid, (+)-catechin,
()-epicatechin, and (E)-resveratrol. Anthocyaninscontent also
increased at an average of 50 mg/l. The volatile prole of wines
analysed by SBSEGCMS
nd marive in
play a fundamental role in dening the polyphenol and
volatileproles of wines. Moreover, biochemical and chemical
reactionstaking place during winemaking and ageing, such as
oxidation,polymerization and complexation reactions, have a
signicant ef-fect on the wine prole (Bayonove, Baumes, Crouzet,
& Gnata,2003; Cheynier, Moutounet, & Sarni-Manchado,
2003).
Young red wines have a characteristic bright red colour
associ-ated to a higher content of anthocyanins in an equilibrium
state
and norisoprenoids play a fundamental role (Ebeler &
Thorngate,2009; Francis & Newton, 2005; Zalacain, Marn, Alonso,
& Salinas,2007). These compounds have been associated with the
fruity, o-ral and citrus aroma of wine and some authors have
related themwith the expression of terroir or typicity from
particular viticulturalregions (Bayonove et al., 2003). Given its
importance and consider-ing that most regular quality wines have a
limited concentration ofsuch compounds, strategies for increasing
their concentration inregular quality wines are important.
The use of additives is becoming a common practice in the
wineindustry for improving the sensory prole of wines in order
to
Corresponding author. Tel.: +34 967599310; fax: +34 96
599338.
Food Chemistry 136 (2013) 224236
Contents lists available at
he
lseE-mail address: [email protected] (A. Zalacain).quality
parameters. However, many wine cellars deal with limitedbudgets,
where little is left for approaching constantly changingconsumer
demands. Sometimes this translates into accumulationof out-of-trend
wines before bottling, generating a low revenueperspective.
Therefore, considering strategies to overcome thisproblem should be
taken into account by regulating authorities.
Many sensory and quality parameters of wines are related tothe
composition and concentration of avonoids, phenolic acids,and
volatile compounds extracted from grapes during
winemaking(Ribreau-Gayon, Dubourdieu, Donche, & Lonvaud, 2004).
Har-vesting and oenological techniques used for producing wine
also
shorter time in standard wines than correct, high quality, and
pre-mium wines (Zamora, 2003). The decline of their overall
attributesis partly related to a low concentration of polyphenols,
as well as tooxidative degradation and polymerization-condensation
phenom-ena (Cheynier et al., 2003; Li, Guo, & Wang, 2008).
Moreover, sincemost standard and low quality wines are made from
grapes withmoderate or decient contents of polyphenols, they are
doomedto the use of widely recognized additives like SO2 and
ascorbic acidto reduce oxidative reactions (Oliveira et al.,
2011).
The volatile prole of wines is also considered one of the
mainquality attributes, where varietal compounds like
monoterpenesKeywords:Waste grape skinsWineColourPhenolic
compoundsVolatilesPre-bottling
1. Introduction
Dynamic consumer preferences aproducers to be constantly
innovat0308-8146/$ - see front matter 2012 Elsevier Ltd.
Ahttp://dx.doi.org/10.1016/j.foodchem.2012.07.110was only
moderately inuenced by the treatments. Mixtures of dehydrated waste
grape skins were usefulto improve the colour and polyphenol prole
of red wines, considering them a useful tool for correctingcolour
loss before bottling.
2012 Elsevier Ltd. All rights reserved.
ket trends require wineterms of sensory and
called copigmentation (Boulton, 2001), as well as to a lower
expo-sure to oxygen and derived colour degradation reactions than
agedwines (Oliveira, Ferreira, De Freitas, & Silva, 2011). The
optimal sen-sorial attributes, where colour has a major role, is
known to last forAccepted 25 July 2012Available online 4 August
2012
component. Total polyphenols mean increase was 10% with a
maximum value of 20%. Analysis of lowmolecular weight phenolic
compounds by HPLCDAD showed a signicant (p < 0.05) content
increasePre-bottling use of dehydrated waste graand aroma
composition of red wines
Miguel Angel Pedroza a, Manuel Carmona b, GonzaloAmaya Zalacain
a,a Escuela Tcnica Superior de Ingenieros Agrnomos, Universidad de
Castilla-La ManchabAlbacete Science & Technology Park
Foundation, Universidad de Castilla La Mancha, A
a r t i c l e i n f o
Article history:Received 16 April 2012Received in revised form
21 June 2012
a b s t r a c t
Different dehydrated wastwines as an innovative waycolour
intensity of wines i
Food C
journal homepage: www.ell rights reserved.skins to improve
colour, phenolic
is Alonso a, Maria Rosario Salinas a,
a. de Espaa, s/n, Albacete E-02071, Spainte E-02071, Spain
rape skins from the juice industry were added into aged and
young redcompensating for colour loss before bottling. After
addition of grape skins,eased a mean 11% and a maximum of 31% with
predominance of the red
SciVerse ScienceDirect
mistry
vier .com/locate / foodchem
-
hemmake them more competitive and to reduce defects. Wood
chips,enzymes, enological tannin, are some examples of
internationallyapproved enological practices (OIV, 2012) which
modify the com-position and sensory characteristics of wines. On
the other hand,other products obtained from grape skins like
additive E-163, alsoknown as Anthocyanins or Enocyanin, are
currently commercializedglobally for use in the food industry.
Recently, consumer demandfor labeling wine ingredients and
additives has brought to debatewhether wine cellars should indicate
their use. In this direction,the use of natural and vegetal based
additives, such as enologicaltannin from grape seeds and grape
skins, is commonly better per-ceived by consumers (Cheng, Bekhit,
Sedcole, & Hamid, 2010).
Process sustainability is progressively becoming a
mandatorystandard in developed countries making relevant the
proposalsfor reusing or exploiting current industrial wastes. In
the case ofthe wine industry, one of the major wastes is grape marc
(mixtureof grape skins, seeds and stalks). This waste and its
componentshave been recently studied for their potential use as raw
materials,ingredients and antioxidants (Arvanitoyannis, Ladas,
& Mavroma-tis, 2006; Bekhit et al., 2011; Casazza, Aliakbarian,
De Faveri, Fiori,& Perego, 2011; Fiori, 2010; Pinelo, Arnous,
& Meyer, 2006; Ping,Brosse, Chrusciel, Navarrete, & Pizzi,
2011; Spigno & De Faveri,2007). Waste grape skins from the
juice industry are commonlyobtained after shorter processing time
(4 days of maceration) thanthose from red winemaking. This fact
implies that juice industrygrape marc is not as exhausted as that
from winemaking and thusa richer source of several compounds.
Recently Pedroza, Carmona, Salinas, and Zalacain (2011),
evalu-ated the production of ros wines by macerating dehydrated
wastegrape skins into white wines, resulting in a stable product
with tai-lor made characteristics according to those obtained in
model winesolutions. Furthermore, this approach made it possible to
reuse anagroindustrial byproduct offering an alternative for
commerciali-zation of both; the white wine (converted into ros) and
the wastegrape skins. The aim of this work was to use dehydrated
wastegrape skins as a new oenological tool for compensating
colour,phenolic and aroma degradation in red wines before bottling.
Mix-tures of waste grape skins were assayed for producing
differentcompositional proles, evaluating their immediate impact
andstorage behaviour.
2. Materials and methods
2.1. Dehydrated waste grape skins (DWGS)
Waste grapemarcs of Vitis vinifera Bobal (red variety) and
amix-ture of 70% Airn (white variety) with an unknown red
variety,namely AMIX, were obtained from a juice concentrate factory
inCastilla-La Mancha (Julian Soler, Cuenca, Spain). Samples
obtainedimmediately after pressing the macerated must were
collected inplastic bags (60 kg) and frozen at 20 C. In the
laboratory, wastegrapemarcswere thawed at 25 C and ovendried at 60
C, accordingto Pedroza, Carmona, Pardo, Salinas, and Zalacain
(2012) until a con-stant weight was achieved (35% moisture
content). Dried sampleswere sieved through 3 mm mesh to remove seed
and stalks. Dehy-dratedwaste grape skins (DWGS)were then ground in
a cuttingmillMS 100 (Retsch, GmbH & Co. KG, Denmark) and sieved
to 1.0 mmparticles. Four types of DWGS were then prepared: 100%
Bobal (Bo-bal), 100% AMIX (AMIX), 75% AMIX + 25% Bobal (GM75), and
50%AMIX + 50% Bobal (GM50). The later mixtures were selected to
ob-tain intermediate values between plain AMIX and Bobal DWGS.
2.2. Wines
M.A. Pedroza et al. / Food CTwo aged (A05 and A07) and two young
(Y08 and Y09) redwines were provided by a local winery. Young wines
correspondedto table wines commercialized as bulk product with a
shelf life nolonger than three years after bottling. These wines
were resultfrom traditional winemaking (510 days of maceration;
fermenta-tion temperature 25 C in stainless steel tanks) of several
red grapevarieties cultivated regionally (Tempranillo, Cabernet
Sauvignon,Merlot, etc.). Aged wines were produced similarly as
young wines,but with longer maceration times (1020 days) and
subjected to atleast 6 months of storage in American oak barrels
(250 L). All wineshad pH range = 3.53.9 and alcohol content =
13.514% vol. In or-der to obtain representative samples of wines
before bottling, sam-pling was performed at the bottling line in
750 ml amber glassbottles (four bottles of each wine with synthetic
cork closures).Wines were then taken to the laboratory and prepared
for itstreatment.
2.3. Maceration conditions
DWGS were macerated according to conditions established
byPedroza et al. (2011). Briey, a dosage of 5 g DWGS/L was
macer-ated into each wine during 3 days at 18 C. Amber crystal
asksof 125 ml with screwcap plastic closures and 5 0.5 ml
headspacewere used during the experiment. After maceration, DWGS
wereremoved with a strainer and the wines stored in the same typeof
crystal bottles at 18 C. Wine evolution analysis started
immedi-ately after maceration, and then after 3 and 6 months (T0,
T3, andT6 respectively).
2.4. Chemicals and standards
FolinCiocalteu reagent from Merck (Darmstadt, Germany). So-dium
Carbonate from Panreac (Barcelona, Spain). Caffeic acid,
(+)-catechin, p-coumaric acid, ()-epicatechin, gallic acid, and
(E)-res-veratrol, from SigmaAldrich (Steinheim, Germany) were used
asstandards for low molecular weight phenolic compound
analysis.Malvidin-3-glucoside (Mv-3-G) standard from Extrasynthse
(Gen-eay, France) was used for anthocyanins quantication.
HPLC-gradeacetonitrile was from Panreac (Barcelona, Spain).
Eugenol, farnesol,1-hexanol, b-ionone, isoamyl acetate, D-limonene,
nerolidol, (E)-whiskylactone, (Z)-whiskylactone, supplied by
SigmaAldrich(Steinheim, Germany), and b-damascenone supplied by
Firmenich(Geneva, Switzerland) were used as calibration standards
in winemodel solution (12% v/v ethanol, pH = 3.6, 5 g/l tartaric
acid) forvolatile analysis.
2.5. Sample characterization
2.5.1. UVvis spectrophotometryStandard colour parameters and
total phenolic compoundswere
measured in a Lambda 25 UVVis spectrophotometer (Perkin El-mer,
Norwalk, CT) with quartz cells. All samples were rst lteredthrough
a PVDF Durapore lter of 0.45 lm (Millipore, Bedford,MA). Colour was
determined following Glories method (Glories,1984), measuring
absorbance at 420, 520, and 620 nm. Total poly-phenols (TP) were
determined at 750 nm according to Singletonand Rossi (Singleton
& Rossi, 1965) and expressed as mg/l of gallicacid equivalents
(GAE) according to a calibration curve with theequation TP =
(0.2735 Absorbancy 0.036) 1000), R2 = 0.994and with a mean relative
standard deviation below 5%.
2.5.2. Phenolic compounds determination by HPLCDADPhenolic
compound analysis was carried out according to Coz-
zolino et al. (2004). The samples were ltered through a
PVDFDurapore lter of 0.45 lm (Millipore, Bedford, MA) and
injected
istry 136 (2013) 224236 225into an Agilent 1100 HPLC
chromatograph (Palo Alto, CA) equippedwith a Phenomenex (Torrance,
CA) Synergi 4 l Hydro-RP column(4 lm particle size, 80 pore size,
150 2.0 mm) at 25 C.
-
In red wines, Shade represents a measure of colour
degradation
A07, where evolution was mostly stable. All second order
interac-
hemSolvents were: (A) 1% v/v acetonitrile, 1.5% v/v phosphoric
acid inwater and (B) 20% v/v solvent A, 80% v/v acetonitrile.
Gradient elu-tion at a constant ow rate of 0.4 ml/min was: 0 min
(14.5% solventB), 18 min (27.5% solvent B), 20 min (27.5% solvent
B), 21 min(50.5% solvent B), 22 min (50.5% solvent B), 26 min (100%
solventB), and 28 min (100% solvent B). The injection volume used
was20 ll. Compound detection was carried out with a diode
arraydetector by comparison with the corresponding UVvis spectraand
retention time of pure standards in the chromatogram. Gallicacid,
(+)-catechin, vanillic acid, syringic acid and ()-epicatechinwere
identied at 280 nm; ferulic acid and caffeic acid were iden-tied at
324 nm, (trans)-resveratrol and p-coumaric acid wereidentied at 308
nm; malvidin-3-G, was identied at 520 nmwhiledelphinidin-3-G,
cyanidin-3-G, petunidin-3-G, peonidin-3-G wereidentied according to
the literature (Alcalde-Eon, Escribano-Bai-lon, Santos-Buelga,
& Rivas-Gonzalo, 2006) and quantied as mal-vidin-3-G
equivalents. Quantication was based on 5-pointcalibration curves of
respective standards (R2 > 0.95, tted to ori-gin) in wine model
solution previously described. Relative stan-dard deviation of all
calibration points was below 1%. Datareported represent the mean of
two replicates.
2.5.3. Volatile compound determination by SBSEGCMSTen
millilitres of wines were used in duplicate to determine the
free volatile fraction (Pedroza, Zalacain, Lara, & Salinas,
2010) byimmersion of a polydimethylsiloxane coated stir bar
[Twister,0.5 mm lm thickness, 10 mm length from Gerstel, (Mlheim
ander Ruhr, Germany)] and stirring at 500 rpm during 1 h at 25
C.After this time, the stir bar was removed from samples, rinsed
withdistilled water, dried with cellulose tissue and nally
transferredinto thermal desorption tubes for the GC/MS
analysis.
Volatile compounds were desorbed from the stir bar in an ATD400
(Perkin Elmer, Norwalk, CT) under the following conditions:oven
temperature at 290 C; desorption time, 4 min; cold trap
tem-perature, 30 C; helium inlet ow, 45 ml min1. After this,
thecompounds were transferred into the HewlettPackard 6890
(PaloAlto, CA) gas chromatograph coupled to an HewlettPackard
3Dmass detector (Palo Alto, CA) with a fused silica capillary
columnSGE BP21 (stationary phase 30 m length, 0.25 mm i.d., and0.25
lm lm thickness) (Ringwood, Australia). The chromato-graphic
program was set at 40 C (held for 2 min), raised to230 C at 10 C
min1 and held for 15 min. Electron impact modeat 70 eV was used for
mass spectrometry analysis. The mass rangevaried from 35 to 500 u
(Scan Monitoring) and the detector tem-perature was 150 C.
Identication was carried out using the NISTlibrary and standard
spectra. Quantication was based on 5-pointcalibration curves of
respective standards (R2 > 0.95, tted to ori-gin) in synthetic
wine solution previously described. Mean relativestandard deviation
of calibration curves was in all cases below 6%except for 1-hexanol
(45%) and farnesol (15%). Data reported rep-resent the mean of two
replicates. To avoid matrix interferencesbetween the volatile
compounds, the MS quantication was car-ried out in the single ion
monitoring (SIM) mode using their char-acteristic m/z values
reported in the NIST library and those fromZalacain et al.
(2007).
2.6. Statistical analysis
An experimental design considering wine (A05, A07, Y08,
Y09),DWGS type (control, AMIX, Bobal, GM75, GM50), and storage
time(0, 3, 6 months) as categorical factors. Main effect of each
factorand second order interactions between factors on the
dependentvariables (composition of samples) were evaluated by means
of
226 M.A. Pedroza et al. / Food Cmultifactor analysis of Variance
(ANOVA) with Statgraphics Centu-rion 16.1. SPSS Statistics 19.0
Software (Chicago, IL) was used foridentifying homogeneous subsets
according to ANOVA post hoctions for CI and shade were
statistically signicant, however, inter-action plots comparing wine
and grape skins revealed that thesince it is the balance between
the yellow and red colour (Zamora,2003) where the higher the value,
the higher the inuence of yel-low component and thus lower quality.
All DWGS produced a dim-inution of Shade, where Bobal had smaller
values than the rest oftreatments, although slight differences were
found with the othergrape skins (Table 1). Shade changes were
slightly more positive inA07, Y08 and Y09 than in A05, where GM50
and GM75 had theclosest values compared to those of control. It is
important to notethat A05 control wine had the highest shade value,
with a predom-inant yellow component and thus with higher colour
degradation.
Evaluation of CI and Shade at T3 and T6 revealed that DWGShad
different evolution trends in each type of wine. CI predomi-nantly
increased with time in all samples, where Bobal had thehighest
average increase (16% at T3 and 20% at T6). The most inu-enced wine
was Y09 at T6, where GM75 reached a maximum in-crease of 45% with
respect to control wine (Table 1). DWGS alsocaused a signicant
increase in A05 wines after 6 months (2125%). In contrast, the use
of DWGS had a low increase of CI inTukeys test. ANOVA was performed
using two sided p 6 0.05 andLevenes test for assessing equality of
variance.
3. Results and discussions
Colour loss is a natural process experienced by all types
ofwines due to chemical and biochemical transformations relatedwith
the polyphenols content and the presence of oxygen. Suchchanges are
particularly important for red wines because colouris an important
quality parameter that may inuence consumerpreferences (Parpinello,
Versari, Chinnici, & Galassi, 2009). Previ-ous work on
dehydration and characterization of waste grape skinsfrom the juice
industry (Pedroza et al., 2012) and extraction condi-tions in wine
model solution and white wines (Pedroza et al., 2011)pointed out
favourable parameters for releasing colour, polyphe-nols and aroma
compounds. These works also suggested that theuse of DWGS mixtures
could be studied in order to t the needsof certain types of wines
like those having colour loss before bot-tling. The following
ndings evaluated the effect of DWGS in differ-ent types of red wine
that experienced colour loss before bottling.
3.1. Colour
The addition of DWGS into wines caused a signicant impact inthe
Colour Intensity (CI) and Shade of all wines (Table 1). BobalDWGS
produced the highest CI increase with respect to control,having an
overall average increase of 15% followed by GM50(13%), GM75 (10%),
and nally AMIX (5%). The maximum CI in-crease was observed in
Bobal-Y09 (31%). The improvement of CIwas mainly ascribed to the
increase of absorbance at 520 nm (datanot shown), which is commonly
related with the amount of antho-cyanins of wines and in this case
with those released by each typeof DWGS. Grape skins had the least
inuence on CI of A07 wine, asno signicant increase with respect to
control was observed. Onthe other hand, all types of DWGS produced
a signicant increaseof CI in Y09 and A05 wines. According to these
results, it seems thatthe type of wine regulates the impact of
DWGS, where the initial CIis not a restrictive variable for colour
release. Moreover, this re-marks that the treatment may improve the
colour of both agedand young wines.
istry 136 (2013) 224236highest impact of grape skins was
achieved in Y09 wine, where Bo-bal and GM75 were the DWGS producing
the highest values duringthe whole experiment.
-
Table 1UVvis determinations of Colour and Total polyphenols from
young (Y08, Y09) and aged (A05, A07) red wines exhibiting colour
loss and added with Dehydrated Waste Grape Skins (GM75: mixture of
75% AMIX + 25% Bobal; GM50:mixture of 50% AMIX and 50% Bobal).
M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
227
-
Table 2Monomeric Antocyanin glycosides composition (mg/l) from
young red wines (Y08, Y09) added with Dehydrated Waste Grape Skins
(GM75: mixture of 75% AMIX + 25% Bobal; GM50: mixture of 50% AMIX
and 50% Bobal).
228M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
-
Table 3Monomeric Antocyanin glycosides composition (mg/l) from
aged red wines (A05, A07) added with Dehydrated Waste Grape Skins
(GM75: mixture of 75% AMIX + 25% Bobal; GM50: mixture of 50% AMIX
and 50% Bobal).
M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
229
-
Table 4Low molecular weight phenolic compounds composition
(mg/l) of young red wines (Y08, Y09) added with Dehydrated Waste
Grape Skins (GM75: mixture of 75% AMIX + 25% Bobal; GM50: mixture
of 50% AMIX and 50% Bobal).
230M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
-
Table 5Low molecular weight phenolic compounds composition
(mg/l) of aged red wines (A05, A07) added with Dehydrated Waste
Grapeskins (GM75: mixture of 75% AMIX + 25% Bobal; GM50: mixture of
50% AMIX and 50% Bobal) (Seeabove-mentioned references for further
information).
M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
231
-
Table 6Volatile compounds (lg/l) of young red wines (Y08, Y09)
added with Dehydrated Waste Grape Skins (GM75: mixture of 75% AMIX
+ 25% Bobal; GM50: mixture of 50% AMIX and 50% Bobal).
232M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
-
Table 7Volatile compounds (lg/l) of aged red wines (A05, A07)
added with Dehydrated Waste Grape Skins (GM75: mixture of 75% AMIX
+ 25% Bobal; GM50: mixture of 50% AMIX and 50% Bobal). (See
above-mentioned references for furtherinformation.).
M.A.Pedroza
etal./Food
Chemistry
136(2013)
224236
233
-
and nally Bobal (Table 4). It was noted that AMIX, GM50, andGM75
produced always higher yields than Bobal, regardless of
hemOn the other hand, Shade values of wines with DWGS had a
ten-dency to increase with time while control wines were more
stable.This result was mainly attributed to the increase of the
yellowcomponent which may be ascribed to oxidative browning of
poly-phenols (Li et al., 2008). Such browning may be directly
relatedwith the decrease of total polyphenols subject of the
followingdiscussion.
3.2. Total polyphenols
After maceration (T0), Total polyphenols (TP) were
signicantlyincreased (520%) by all treatments, where Bobal had the
higherimpact, closely followed by the mixtures GM75 and GM50
(Ta-ble 1). It was appreciated that DWGS released the highest
amountof TP in A05 wines (98 6 mg GAE/L) in contrast with Y09
wines(31 3 mg GAE/L). A previous work macerating Bobal and AMIXin
wine model solution and using the same extraction
parameters(Pedroza et al., 2011), showed that both DWGS were able
to releaseup to 180 mg GAE/L. This fact suggests that the maximum
releaseof TP may be primarily controlled by the matrix, leaving a
residualrole to the grape skin type. Moreover, when evaluating
whitewines, it was observed that DWGS released up to 391 mg
GAE/L,indicating that white wine matrix (with lower content of
polyphe-nols) have more favourable equilibrium conditions thus
acceptinga higher amount of polyphenols in solution. It appears
that afterDWGS addition, TP reached an equilibrium concentration
similarwithin all types of wines regardless of treatment, where an
averagevalue of 618 11 mg GAE/L could be characteristic of our
samples.However, these results remark the potential of DWGS for
improv-ing the phenolic content of wines to the extent of matching
theconcentration of aged wines to that of treated young wines.
Regarding evolution of TP, DWGS-wines had a similar behaviouras
control ones in all treatments (Table 1). This was in agreementwith
previous observations on the evolution of TP in ros wineselaborated
with DWGS (Pedroza et al., 2011). A higher decreaseof TP was
observed in Y09 after 6 months where AMIX treatmenthad the higher
loss. Such a decrease could be related to the in-crease of the
shade values previously discussed. It can also benoted from the
evolution data (Table 1) that TP may increase atT3 with a following
decrease after T6, remarking the continuouslychanging dynamic
equilibrium occurring during wine storage. Re-sults suggest that
using DWGS do not cause particular alteration inthe evolution of
total polyphenols, and that their positive effect isstable for up
to 6 months. All second order interactions were statis-tically
signicant, showing that all wines treated with grape skinshad
superior mean TP values than control wines during the
wholeexperiment. In addition, the concentration of TP was similar
be-tween all wines-grape skin combinations, where bobal had not
sig-nicant superior values.
3.3. Anthocyanins
After maceration, DWGS released into all wines an average of50
mg/l of total monoglucoside anthocyanins. Bobal was the
DWGSproducing the highest release (63 mg/l) in A05 wine, while
AMIXhad the lowest (37%) in A07 wine (Table 2). However, when
eval-uating the average release of each DWGS in all wines, it was
foundthat Bobal and GM50 had similar yields (52 mg/l) followed
byAMIX (47 mg/l) and GM75 (46 mg/l). It was remarkable that
thesevalues were similar in all wines since the release of
anthocyaninsdepends on the equilibrium concentration of each wine,
and itwould be expected that young wines, with higher endogenous
con-centration of anthocyanins before treatment, had a less
efcient
234 M.A. Pedroza et al. / Food Cextraction than aged wines (with
signicantly lower anthocyaninsand therefore a less saturated
solution). This average anthocyaninsyield was similar to that
obtained in model wine solutions withthe type of wine. This was in
agreement with previous ndingson model wine solutions where AMIX
released a higher amountof LMWPC, (Pedroza et al., 2011; Pedroza et
al., 2012) thereforemixtures of DWGS are a good strategy for
balancing the decien-cies of composition. Since LMWPC relate to
sensory attributes likethe acid taste of wines and bitterness, the
use of DWGS may allowwinemakers to design particular taste proles
by adjusting theproportion of different grape skins. Regarding the
copigmentationphenomena, Boulton (2001) suggests that an increase
in the con-centration of co-factor molecules, such as gallic acid,
catechin, caf-feic acid, epicatechin, etc., during maceration of
wines may play acentral role for increasing the solubility of
anthocyanins in thewine solution and therefore achieving higher
extraction yield ofanthocyanins and improved colour. Moreover, the
increase of co-factor concentration has been considered to prevent
colour degra-dation in grape juice (Brenes, Del Pozo-Insfran, &
Talcott, 2005).
Main LMWPC released by DWGS in wines were gallic acid,
(+)-catechin, ()-epicatechin, and (E)-resveratrol (Tables 4 and 5).
Gal-lic acid had the highest increase in Y09 wine (7074%).
Catechinand ()-epicatechin were better released in A05 (74353%
and168263% respectively). The former three compounds have
beenreported to have antioxidant activity with suitable use as
dietarysupplements (Yilmaz & Toledo, 2004). Caffeic and
coumaric acidshad signicantly higher yields in both young wines.
(E)-resveratrolhad a signicant increase in Y08 (115136%). The later
molecule isof signicant relevance since it is being attributed with
health pro-Bobal (50 mg/l) and lower to that obtained when
macerating AMIXwith white wines (68 mg/l) (Pedroza et al., 2011)
Such facts sug-gest that the white wine matrix has other variables
participatingin the solubility of anthocyanins.
Anthocyanins experienced a signicant decrease during
storage,accounting for a 5070% loss after 3 months and a
complementary640% loss after 6 months (Tables 2 and 3). Evolution
patterns ofthe different anthocyanins were similar within all
wines. AMIXand GM75 had the lowest decrease of anthocyanins (77 2%)
inA05, A07, and Y08. Apparently, DWGS with higher amount of
whitegrape skins were able to keep a higher concentration of free
antho-cyanins in solution for a longer time. However, this
behaviour notobserved in Y09 wine, as it had the highest decrease
(8589%) ofanthocyanins regardless of DWGS type. Observed changes
maybe ascribed either to polymerization-stabilization reactions
(Boul-ton, 2001; Cheynier et al., 2003) and/or degradation due to
chem-ical oxidation phenomena (Li et al., 2008). Since the colour
ofsamples does not change as abruptly as the anthocyanins
concen-tration, we considered that the rst hypothesis may
predominantlyoccur, supporting the concept of the partial role of
monoglucosideanthocyanins in colour (Zamora, 2003). In spite of the
degradation,samples with DWGS had signicantly higher concentration
of totalanthocyanins at the end of the experiment. All factor
interactionswere statistically signicant, however, the most
important differ-ences were noted in the concentration of
anthocyanins betweentreated and control wines, regardless of the
grape skin type.
3.4. Low molecular weight phenolic compounds
After maceration treatment (T0), DWGS were able to signi-cantly
increase the concentration of total low molecular weightphenolic
compounds (LMWPC) in young and aged wines (Tables4 and 5). This was
particularly important for A05 wine, whereGM50 produced the highest
increase, followed by AMIX, GM75
istry 136 (2013) 224236moting properties such as prevention of
cardiovascular diseasesand antioxidant activity (Fernndez-Mar,
Mateos, Garca-Parrilla,Puertas, & Cantos-Villar, 2012;
Frombaum, Le Clanche,
-
ero, Pardo, Alonso, & Salinas, 2002; Garde-Cerdn &
Ancn-Azpilic-
the best results were observed during the rst 3 months when
vol-
because of its novelty, probably, the most important challenges
forits aproval as wine additive will come from political and
cultural
hemBonnefont-Rousselot, & Borderie, 2012). Coumaric acid
concentra-tion decreased after DWGS addition in A07 (Table 4).
In general, after 6 months of storage all wines with DWGS
hadsuperior content of total LMWPC than control wines. DWGS
withhigher proportion of white grape skins continued having the
higheramount of LMWPC. This was also conrmed by interaction
plotscomparing average values of total LMWPC during the whole
exper-iment. It was observed that the composition of aged wines
wasmore unstable than that of young wines; the evolution of
Y08wines showed that gallic acid, (+)-catechin and caffeic acid
re-mained stable during the trial, while ()-epicatechin, and
(E)-res-veratrol reached a maximum concentration at T6. On the
otherhand, Y09 wines with DWGS had higher concentration of
caffeicacid (T6), ()-epicatechin (T3), and (E)-resveratrol (T6).
Increasingwith time of the later compound is of particular interest
since theymight be released by hydrolysis from their glycosilated
precursors(Gmez-Gallego, Garca-Carpintero, Snchez-Palomo,
Hermosn-Gutirrez, & Gonzlez Vias, 2012). Interaction plots
revealed thatA05 was the most affected wine during storage,
although it wasalso the wine most favoured by the DWGS
treatment.
3.5. Volatile composition
The volatile composition of wines was modied after additionof
DWGS by the increase of b-ionone (oral descriptor). This com-pound
is an important impact odourant because of its low
olfactorythreshold and appreciated descriptor. The increase of
b-ionone wasof the most importance in the case of aged wines (Table
7), wherethis compound was absent or below its olfactory threshold
(OT)(0.09 lg/l (Francis & Newton, 2005)) in control wine and
afteraddition of DWGS, it increased to a concentration 26 times
overthe OT. Bobal was the DWGS releasing the highest amount of
b-io-none (0.54 lg/l in A05 wine). Wine-time was the only
statisticallysignicant interaction of this compound, describing a
decreasewith time, particularly important in the case of young
wines.
On the other hand, nerolidol and b-damascenone
concentrationdecreased after treatment regardless of the DWGS type.
This phe-nomena was also observed when adding DWGS to white
wines(Pedroza et al., 2011) However, in the case of
b-damascenone,the concentration (0.772.33 lg/l) remained over the
OT(0.05 lg/l (Francis & Newton, 2005)), thus its characteristic
oral-fruity note (Bayonove et al., 2003) may persist in the
wine.Although statistically signicant interactions (wine-DWGS
andwine-time) were observed for this compound, the most
importantdifferences were always associated to control wines having
highermean concentration than those with DWGS.
The herbaceous compounds represented by 1-hexanol re-mained
mostly without signicant differences or in some casesin a lower
concentration than control wines. Also this compoundwas not over
its OT. Nerolidol and Farnesol were not detected inY09 after
addition of DWGS, indicating that in this particular winethese
compounds could be transformed during treatments as a re-sult of
hydrolysis and cyclation reactions taking place at wine con-ditions
(Marco, 2006). This was not observed in the rest of wines,thus this
behaviour was not clear. When evaluating the evolutionof wines in
terms of chemical families (Tables 6 and 7), an increasewith time
of isoamyl acetate (banana note) was observed in alltreated wines,
but no particular DWGS seems to induce suchbehaviour. Since this
compound is produced by yeast (Styger, Prior,& Bauer, 2011),
this could be related with refermentation of wines,although no
visual sign of this was observed. Terpenes in A05, A07and Y08
increased after 6 months of storage. Increasing of thesecompounds
with storage may be due to their existence in glycosi-
M.A. Pedroza et al. / Food Clated forms and subsequent chemical
hydrolysis. It may as well berelated to their susceptibility to
different reactions and transfor-mations (isomerization, cyclation,
oxidation, etc.) (Gnata, 2003).concerns related with the usage
conditions.
Acknowledgements
M.A.P. has received a CONACYT grant from the Mexican
Govern-ment. This Study has been funded by Junta de Comunidades
deCastilla-La Mancha (Project PAI08-0148-9842). Thanks to Ana
Solerfrom Julian Soler S.A. Juice Concentrate Factory for supplying
wastegrape skins. Thanks to Kathy Walsh for proofreading
themanuscript.
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Pre-bottling use of dehydrated waste grape skins to improve
colour, phenolic and aroma composition of red wines1 Introduction2
Materials and methods2.1 Dehydrated waste grape skins (DWGS)2.2
Wines2.3 Maceration conditions2.4 Chemicals and standards2.5 Sample
characterization2.5.1 UVvis spectrophotometry2.5.2 Phenolic
compounds determination by HPLCDAD2.5.3 Volatile compound
determination by SBSEGCMS
2.6 Statistical analysis
3 Results and discussions3.1 Colour3.2 Total polyphenols3.3
Anthocyanins3.4 Low molecular weight phenolic compounds3.5 Volatile
composition
4 ConclusionsAcknowledgementsReferences