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Fruits are rich in phenolic compounds with health-promoting activities. However, phenolic profiles vary between fruits. Hence, specific extraction methods are required for accurate profiling of the functional compounds. This study aims to develop an optimised method by response surface methodology to extract phenolics from apricots (Prunus armeniaca) and correctly characterise apricots’ phenolic profile. For this, the effects of the solid-to-liquid ratio, temperature, extraction solvent, extraction time and sequential extraction steps on the extraction of major phenolic families were investigated. Methanol- and ethanol-based extractions were suitable, although methanol was the optimal solvent. The optimised extraction conditions were 20 g mL⁻¹, 38 °C and 72% methanol (1% formic acid). When this method was used in apricots, the characterisation of their phenolic profile by HPLC-ESI-MS/MS showed a higher extraction of phenolic compounds than other studies in the literature that use non-specific extraction methods. The developed method is fast and economically feasible for accurate characterisation of the phenolic profile of apricot fruits and thus can be routinely used to extract apricot phenolic compounds for their characterisation.
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Food &
Function
PAPER
Cite this: DOI: 10.1039/c9fo00353c
Received 20th February 2019,
Accepted 2nd July 2019
DOI: 10.1039/c9fo00353c
rsc.li/food-function
Optimization of extraction methods for
characterization of phenolic compounds in apricot
fruit (Prunus armeniaca)
Lisard Iglesias-Carres, Anna Mas-Capdevila, Francisca Isabel Bravo,
Cinta Bladé,Anna Arola-Arnal * and Begoña Muguerza
Fruits are rich in phenolic compounds with health-promoting activities. However, phenolic proles vary
between fruits. Hence, specic extraction methods are required for accurate proling of the functional
compounds. This study aims to develop an optimised method by response surface methodology to
extract phenolics from apricots (Prunus armeniaca) and correctly characterise apricotsphenolic prole.
For this, the eects of the solid-to-liquid ratio, temperature, extraction solvent, extraction time and
sequential extraction steps on the extraction of major phenolic families were investigated. Methanol- and
ethanol-based extractions were suitable, although methanol was the optimal solvent. The optimised
extraction conditions were 20 g mL
1
, 38 °C and 72% methanol (1% formic acid). When this method was
used in apricots, the characterisation of their phenolic prole by HPLC-ESI-MS/MS showed a higher
extraction of phenolic compounds than other studies in the literature that use non-specic extraction
methods. The developed method is fast and economically feasible for accurate characterisation of the
phenolic prole of apricot fruits and thus can be routinely used to extract apricot phenolic compounds
for their characterisation.
1. Introduction
Diets rich in fruits and vegetables are associated with a ben-
eficial role in several human diseases, and these benefits are
attributed to the phenolic content of plants.
1
Indeed, in recent
years, phenolic compounds have attracted interest due to their
beneficial health eects. Dierent phenolic compounds have
been reported to exhibit dierent health-promoting activities.
2
In addition, dierent fruits have dierent phenolic profiles.
37
Therefore, their potential roles in human health dier.
In this sense, it is important to note that when characteris-
ing the phenolic profile of a food matrix, only compounds
that are extracted can be quantified. Given the diversity of
food matrixes and phenolic profiles of foods, specific
methods that fully extract fruit phenolics should be devel-
oped. This is essential to correlate the consumption of a
mixture of phenolics with a beneficial health eect. Factors
such as the liquid-to-solid ratio (LSR), type of solvent, temp-
erature and extraction time can greatly influence phenolic
extraction from food matrixes.
812
In systems where several
factors can aect the output, response surface methodology
(RSM)isausefultooltooptimiseextractionprocesses.The
primary advantage of this approach is the evaluation of the
eect of multiple variables and their interactions on the
output variables with a reduced number of trials.
1315
Indeed,
RSM has been widely used to optimise the extraction of
phenolic compounds from various plant materials and
fruits.
35,7,1121
Apricots are one of the dietary sources with the highest
polyphenol content
22
and can be considered as natural func-
tional food. Indeed, apricot consumption is associated with
several health eects, including hepatoprotective, anti-inflam-
matory and anti-hypertensive eects, among others.
23
The phe-
nolic content in apricots can vary between varieties
2427
and
depends on maturity
28
and the region and system of
cultivation.
27,29
Nevertheless, apricots have been widely
reported to be rich in flavonoids, specifically flavanols and fla-
vonols, and non-flavonoid phenolics, specifically hydroxycin-
namic derivatives.
26,28
In apricots, flavonols occur largely as
quercetin and kaempferol glucosides, quercetin-3-O-rutinoside
(rutin) being their main component.
23,28
Flavanols occur
mainly as (+)-catechin and ()-epicatechin, one or the other
being the predominant form depending on the apricot
Electronic supplementary information (ESI) available. See DOI: 10.1039/
c9fo00353c
Deceased.
Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia,
Nutrigenomics Research Group, Tarragona, 43007, Spain.
E-mail: anna.arola@urv.cat
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variety.
26
In addition, several dimeric flavanol forms can
accumulate up to significant levels.
25,28
Among the hydroxycin-
namic derivatives, chlorogenic acid is widely reported as the
main compound.
28
Neochlorogenic acid, p-coumaric acid,
caeic acid and gallic acid can also be present in dierent
apricot cultivars.
26,28
In addition, other phenolics from
dierent families, such as resveratrol, can also occur in small
quantities.
25,29
The phenolic composition of apricots has been widely
determined by using dierent extraction methods,
24,25,30
non-
specific for apricots. For instance, many of the studies that
evaluate phenolic compounds in apricots use adaptations of
the method described by Bengoechea et al.,
2629,31,32
which
was developed for the extraction of phenolic compounds from
peach and apple purees and concentrates.
6
Importantly, the
selection of one extraction method over another has crucial
eects on the extraction of phenolic compounds and thus the
characterisation of the food matrix.
10,33
However, so far,
specific methods that aim to focus on the full extraction of all
relevant phenolic families from apricots are lacking. In this
sense, Zitka et al.
10
evaluated the eect of some extraction
factors (i.e. solvent and temperature) on polyphenol extraction
from apricots, but this study was centred on the extraction of
particular apricot phenolic compounds. Similarly, other
authors have developed optimized methods to extract apricot
polyphenols, not from the fresh apricot matrix, but from pro-
cessed apricots,
25
sun dried apricots,
5
and apricot waste.
34
For
example, Erdoan et al. evaluated the eect of some extraction
variables (i.e. solvent, pressure, time and temperature) by the
one-variable-at-a-time approach in an accelerated solvent
extraction system for the total polyphenols in processed apri-
cots.
25
In the same line, Cheaib et al. studied the eect of
certain extraction variables (i.e. temperature and solvent) on
the extraction of the total phenolic, flavonoid and tannin con-
tents from apricot pomace (pressed skins and pulp resi-
dues).
34
As for sun-dried apricots, Wani et al. optimised
several parameters (i.e. temperature and solvent) to extract the
highest polyphenol content with the highest anti-oxidant
activity by an RSM approach.
5
However, none of the men-
tioned studies developed a specific method to extract the
maximum content of the most representative families in apri-
cots by an RSM approach. Importantly, beneficial health
eects of apricots are mainly associated with the consumption
of fresh fruit, and thus full characterization of the phenolic
composition of apricot fruits is required to identify the
involved bioactive compounds. Hence, the primary aim of this
study is to develop an apricot-specific phenolic compound
extraction methodology that allows accurate characterisation
of the apricot fruit phenolic profile. To do so, an RSM was
applied, and extracts were analysed by HPLC-ESI-MS/M. The
development of this methodology is novel as it is the first
approach to develop a specific phenolic compound extraction
methodology that aims to extract all the phenolic families
from apricots, and this will be useful to completely character-
ise the phenolic profile in detail for bioactivity, comparison or
any other studies.
2. Experimental
2.1. Plant material
Apricots (Prunus armeniaca, Charisma variety) were purchased
from Mercabarna (Barcelona, Spain). Apricot stones were
manually removed and discarded. Apricots (peel and flesh)
were first frozen in liquid nitrogen and ground. Next, homo-
genates were lyophilised for a week in a Telstar LyoQuest lyo-
philizer (Thermo Fisher Scientific, Madrid, Spain) at 85 °C
and further ground to obtain a fine powder. The apricot
powder was kept dry and protected from humidity and light
exposure until extraction.
2.2. Chemicals and reagents
Acetonitrile, methanol, ethanol (HPLC analytical grade) and
glacial acetic acid were purchased from Panreac (Barcelona,
Spain). Ultrapure water was obtained from a Milli-Q Advantage
A10 system (Madrid, Spain). Formic acid was purchased
from Scharlab (Barcelona, Spain). The FolinCiocalteu and
p-dimethylaminocinnamaldehyde (DMACA) reagents were
purchased from Fluka/Sigma-Aldrich (Madrid, Spain).
Chlorogenic acid, eriodictyol, eriodyctiol-7-O-glucoside, hypero-
side (quercetin-3-O-galactoside), isorhamnetin-3-O-glucoside,
kaempferol, kaempferol-3-O-glucoside, and kaempferol-3-O-ruti-
noside were purchased from Extrasynthese (Lyon, France), and
benzoic acid, caeic acid, (+)-catechin, epigallocatechin gallate
(EGCG), p-coumaric acid, ()-epicatechin, ferulic acid, gallic
acid, procyanidin dimer B2, protocatechuic acid and quercetin
were purchased from Fluka/Sigma-Aldrich (Madrid, Spain).
Resveratrol was purchased from Quimivita (Barcelona, Spain)
and rutin was kindly provided by Nutrafur (Murcia, Spain).
All standard compounds were individually dissolved in
methanol at 2000 mg L
1
, with the exception of isorhamnetin-
3-O-glucoside, dissolved at 1000 mg L
1
, and hyperoside, dis-
solved at 500 mg L
1
. All standard stock solutions were newly
prepared every 3 months and stored in amber-glass flasks at
20 °C. Mixed standard stock solutions were prepared with
Milli-Q water to obtain the concentration needed to construct
the calibration curves.
2.3. Extraction procedure
Apricot powder was weighed to obtain the desired LSR and
mixed with 1 mL of pre-heated extraction solvent (methanol :
water, v : v). Dierent methanol proportions, temperatures,
times and extraction steps were used throughout the experi-
ment. In addition, methanol was prepared in all cases includ-
ing 1% formic acid. Extractions were performed at 500 rpm
agitation under protection from light exposure. Samples were
centrifuged at 9500gfor 10 min at 4 °C, and supernatants were
stored at 20 °C until further analysis.
2.4. Single factor studies
Prior to RSM, a first set of tests were performed to select
experimental ranges for independent variables. Individual
eects of the LSR, methanol concentration and temperature
were evaluated based on the total phenolic content (TPC), total
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flavonol content (TFoC), tartaric ester content (TEC) and total
flavanol content (TFaC) as the major phenolic families present
in apricots.
26,28,29
To select the RSM ranges of the extraction
variables dierent sets of extractions were performed: as for
the LSR, this extraction variable was tested at 10, 20, 40, 60
and 80 mL g
1
; as for temperature, this variable was tested at
25, 40, 55, 70, and 85°; and as for methanol percentage, this
variable was tested at 30, 50, 60, 70 and 90%. The LSR, tem-
perature and methanol percentage were kept constant at
20 mL g
1
, 55 °C, and 50% when not under study. All extrac-
tions lasted for 30 min as this extraction time is considered to
be neither too long to promote phenolic degradation nor too
short to impede phenolic solubilisation into the solvent as
reported in other studies.
4,5,1113,15
2.5. Surface response design
The extraction was optimised by using an experimental design
by RSM. A face-centered central composite design with two
factors and three levels, consisting of 11 randomised runs with
3 centre points, was selected. Independent variables used in
the RSM were temperature (2555 °C, X
i
) and methanol pro-
portion (60100%, X
j
). The LSR (20 mL g
1
) and extraction
time (30 min) were fixed as constant variables during the RSM
experiment. Experimental data were fitted to a second poly-
nomial response surface, which follows the equation
Y¼β0þX
k
i¼1
βiχiþX
k
i¼1
βiiχii 2þX
i¼1
X
j¼iþ1
βijχii χji ð1Þ
where Yis a dependent variable, β
0
is the constant coecient,
and β
i
,β
ii
and β
ij
are the linear, quadratic and interaction
regression coecients, respectively. X
i
,X
ii
and X
ji
represent
independent variables.
Individual phenolic compounds were quantified by the
HPLC-DAD method and used in the RSM optimisation study.
The results of the RSM design were analysed with
Design-Expert 9.0.6 software (Trial version, Stat-Ease Inc.,
Minneapolis, MN, USA). Single parameters that were not influ-
enced by the extraction factors were omitted in the model.
2.6. Kinetic study
A kinetic study was performed to evaluate the eect of time on
the polyphenol extraction yield. Seven extraction times,
ranging from 0 to 120 min, were selected. The LSR was fixed at
20 mL g
1
, methanol percentage at 72% and temperature at
38 °C. TPC, TFoC, TEC and TFaC were determined to evaluate
the eect of time on the polyphenol extraction.
2.7. Sequential extractions
Three consecutive extractions were performed to evaluate the
influence of multiple extractions on the polyphenol extraction
yield. The LSR was fixed at 20 mL g
1
, methanol percentage at
72% and temperature at 38 °C. Samples were mixed with the
solvent, vortexed and centrifuged (9500g, 10 min, 4 °C). TPC,
TFoC, TEC and TFaC were determined to evaluate the eect of
sequential extractions on the polyphenol extraction yield.
2.8. Methanolethanol comparison
To evaluate the eciency of ethanol in polyphenol extraction,
apricot powder was extracted twice under the following con-
ditions: LSR of 20 mL g
1
, methanol or ethanol (EtOH) pro-
portion of 72% (1% formic acid), temperature of 38 °C.
Samples were mixed with the solvent, vortexed and centrifuged
(9500g, 10 min, 4 °C). The TPC, TFaC, TEC and TFoC were
determined to evaluate the eciency of ethanol in polyphenol
extraction.
2.9. Analysis of response variables
2.9.1. Total phenolic content. The TPC of extracts was
determined by the FolinCiocalteu method adapted from
Iglesias-Carres et al.
11
Briefly, 50 µL of the extract and 50 µL of
the FolinCiocalteu reagent were successively added to an
Eppendorf tube containing 500 µl of Milli-Q water and mixed.
After standing for 3 minutes in the dark, the samples received
100 µL of Na
2
CO
3
(25%) and were brought to a final volume of
1 mL with Milli-Q water. Absorbance was read at 725 nm using
an Eon BioTek spectrophotometer (Izasa, Barcelona, Spain)
against a water sample (blank) that underwent equal treatment
after 1 hour of incubation in the dark. Gallic acid was used
to construct the calibration curve between 40 mg L
1
and
400 mg L
1
. The results were expressed as milligrams of gallic
acid equivalents per gram of dry weight (mg GAE per g dw).
2.9.2. Total flavonol and tartaric ester content. The TFoC
and TEC were determined with the method described by
Cacace et al.
3
Briefly, 250 µL of extracts were mixed with
250 µL of 0.1% HCl in ethanol 95% and 4.55 mL of 2% HCl
and were allowed to react for 15 minutes. Absorbance was then
read at 360 and 320 nm for flavanol and tartaric ester quantifi-
cation, respectively, using an Eon BioTek spectrophotometer
(Izasa, Barcelona, Spain). Quercetin and caeic acid were used
to construct calibration curves, and the results were expressed
as milligrams of quercetin or caeic acid equivalents per
gram of dry weight (mg quercetin per g dw; mg caeic acid
per g dw).
2.9.3. Total flavanol content. The TFaC of extracts was esti-
mated by the DMACA method.
35
Briefly, 100 µL of extract
samples were mixed with 500 µL of DMACA solution (0.1% 1 N
HCl in methanol) and allowed to react at room temperature
for 10 min while protected from light exposure. Next, absor-
bance was read at 640 nm using an Eon BioTek spectrophoto-
meter (Izasa, Barcelona, Spain). Catechin concentrations
between 5 mg L
1
and 100 mg L
1
were used to construct a
calibration curve. The TFaC was expressed as milligrams of
catechin equivalents per gram of dry weight (mg catechin
per g dw).
2.9.4. HPLC-DAD method. Polyphenol separation was
achieved using a ZORBAX Eclipse XDB-C18 (150 mm × 2.1 mm
i.d., 5 µm particle size) as the chromatographic column
(Agilent Technologies, Palo Alto, CA, USA) equipped with a
Narrow-Bore guard column (2.1 mm × 12.5 mm, 5 µm particle
size). The mobile phase was water : acetic acid (99.8 : 0.2, v : v)
(A) and acetonitrile (B) in a gradient mode as follows: initial
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conditions 0% B; 030% B, 018 min; 30100% B, 1819 min;
100% B isocratic, 1920 min; 1000% B, 2021 min. A post-run
of 6 min was required for column re-equilibration. The flow
rate was set at 0.5 mL min
1
, and the injection volume was
10 µL for all runs.
Identification and quantification of phenolic compounds of
interest was achieved with a UV/ViS photodiode array detector
(1260 Infinity, Agilent Technologies, Palo Alto, CA, USA).
Chromatograms were recorded from 200 to 600 nm. Catechin
was detected at 280 nm, chlorogenic acid at 320 nm, and rutin
at 340 nm. The results were expressed as micrograms of
equivalents per gram of dry weight (mg per g dw).
Calibration curves, linearity, intraday variability (precision),
interday variability (reproducibility), detection and quantifi-
cation limits were calculated in mobile phase A spiked with
polyphenol standards (ESI Table 1). The peak areas of various
concentrations of standards were used to construct calibration
curves. The method precision was calculated as the relative
standard deviation (% RSD) of the concentration in a triplicate
analysis of three dierent spiked samples (100, 50 and
gmL
1
). Method reproducibility was calculated as the rela-
tive standard deviations (% RSD) of three dierent standard
compound concentrations (100, 50 and 1 µg mL
1
) analysed in
triplicate over three consecutive days. Sensitivity was evaluated
by determining the limits of detection (LOD) and quantifi-
cation (LOQ), which were respectively defined as the concen-
tration corresponding to 3-fold and 10-fold of the signal-to-
noise ratio.
2.9.5. HPLC-ESI-MS/MS method. The extracts were directly
analysed using a 1200 LC Series coupled to a 6410 MS/MS
(Agilent Technologies, Palo Alto, CA, USA). The column and
mobile phases used were the same as in the HPLC-DAD
method (see section 2.9.4). The gradient mode was as follows:
initial conditions 0% B; 00.5 min, 0% B; 0.52 min, 010% B;
212 min, 1030% B; 1216 min, 3060% B; 1617 min,
60100% B, 1720 min, 100% B; 2021 min, 1000% B. A post-
run of 6 min was required for column re-equilibration. The
flow rate was set at 0.4 mL min
1
, and the injection volume
was 2.5 µL for all runs. Electrospray ionization (ESI) was con-
ducted at 200 °C and 14 l min
1
with 20 psi nebulizer gas
pressure and 3000 V capillary voltage. The mass spectrometer
was operated in the negative mode, and MS/MS data were
acquired in dynamic mode. The optimized conditions for the
analysis of the phenolic compounds studied using
HPLC-ESI-MS/MS are summarized in ESI Table 2.Data acqui-
sition was carried out using MassHunter Software (Agilent
Technologies, Palo Alto, CA, USA). The calibration curves,
coecient of determination, linearity and detection and
quantification limits of the HPLC-ESI-MS/MS method can be
found in ESI Table 3and were evaluated following the same
principles as in the HPLC-DAD method (see section 2.9.4).
2.10. Statistics
The results of the RSM design were analysed using Design-
Expert 9.0.6 software (Trial version, Stat-Ease Inc.,
Minneapolis, MN, USA). SPSS 19 software (SPSS Inc., Chicago,
IL, USA) was used for any other statistical analyses. All experi-
ments were performed in triplicate; the statisticssignificance
was evaluated using One-way ANOVA or Studentst-test; and
p-values less than 0.05 were considered to be statistically
significant.
3. Results and discussion
The phenolic content of apricots
2629,31,32
as well as the ben-
eficial health eects
23
has been largely studied. However,
when apricot phenolics are analysed in the literature unspeci-
fic extraction methodologies are usually used. Importantly,
extraction conditions can greatly aect the extraction yields of
phenolic compounds
5,8,1113
and thus the characterization of a
given matrix. For correct characterization of apricot phenolic
composition, which is essential to link a specific polyphenol
or a group of polyphenols with a particular health eect, an
optimised method specific to extract apricot phenolics should
be used. To develop a methodology as such, the extraction
parameters aecting the extraction of phenolic compounds
from apricots were evaluated and optimised.
3.1. Single factor studies
The eects of the LSR, temperature and methanol proportion
on phenolic extraction were first evaluated individually (Fig. 1)
to select a relevant variable range for the RSM study. This one-
variable-at-a-time approach is useful to identify whether an
extraction parameter aects the extraction of phenolic com-
pounds from a given fruit matrix and its relevance.
13
To evalu-
ate the eect of these extraction parameters on the extraction
of apricot phenolics, the TPC, TFoC, TEC and TFaC were
chosen as dependent variables to give a global view of the
extraction of the most representative phenolic families present
in apricots.
26,28,29
Extraction time is a relevant parameter in
the extraction of phenolic compounds. The exposure to the
optimal extraction solvent and temperature during a certain
period of time results in a higher extraction rate.
16,17
However,
too long extraction times are not economically feasible and
might also promote the degradation of extracted phenolic
compounds.
36
Thus, the extraction time was fixed at 30 min as
this time is not too long or too short and has provided good
results in the extraction of phenolic compounds from other
food matrixes.
4,5,1113,15
Choosing an optimal LSR is key to the
extraction of phenolics, since working at a low LSR may lead to
solvent saturation
7
and working at a high LSR is economically
counterproductive. The TPC did not increase significantly at
values above 20 mL g
1
, whereas the TFoC, TEC and TFaC did
not show any changes due to the LSR (Fig. 1a). Therefore, the
LSR was fixed at 20 mL g
1
throughout the rest of the experi-
ment. This LSR is very similar to the optimum in other plant
matrixes,
13,16,21
including sun-dried apricots.
5
Temperature is a well-known factor that aects the extrac-
tion of phenolic compounds.
4,11,13,37
In this sense, extraction
temperature modulates several extraction parameters (i.e. sol-
vents viscosity and compound diusion coecient) which, in
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turn, modulate the extraction process.
8,38
Moreover, tempera-
ture can also modulate phenolic extraction by promoting their
chemical and enzymatic degradation.
15
Indeed the degra-
dation of phenolic compounds during extraction has been
reported for several phenolic families at high extraction
temperatures.
3,8
Nevertheless, in this study, the TPC was
poorly influenced by an increase of temperature whilst no
eect was reported for TFaC extraction (Fig. 1b). Consistent
with these findings, Gan et al. and Cacace et al. did not report
a significant eect of temperature on the TPC extractability in
Parkia speciosa pods and black currants, respectively.
3,21
In our
study, the TFoC and TEC decreased as temperature increased,
and these decreases were higher above 55 °C. This contradicts
the findings of the study of Van Der Sluis et al. on apple juice
that demonstrated epicatechin to be more sensitive to temp-
erature than chlorogenic acid.
39
However, factors such as phe-
nolic localisation in fruit tissues and interaction with the plant
matrix play an important role in extraction,
37
which could
explain the eect observed for this specific fruit and phenolic
families. Given our results, a range of temperatures between
25 and 55 °C was selected for the RSM study.
Throughout all experiments, methanol was always prepared
at a formic acid concentration of 1%. Low concentrations of
organic acids, such as formic acid, promote the degradation of
the plant matrix, which enhances the extraction rate of pheno-
lic compounds.
40
The eect of methanol proportion on the
TPC was not clear, which could be due to the wide variety of
phenolic families present in apricots.
28
However, the TFoC
and TEC were found to be higher at 90%. Consistent with this
finding, extractions with high proportions (80 and 100%) of
acidified methanol are reported to be capable of extracting tar-
taric esters and flavonols from apricot fruits, jams and
nectars.
26,28,29
The TFaC was found to achieve the greatest
extraction yield at 50% methanol, which is in line with the
results obtained for flavonoids in Morinda citrifolia fruit.
41
Given the few quantitative dierences reported between 50
and 60% MeOH in the extraction of flavanols and the impor-
tant dierences in the extraction of flavonols and tartaric
esters at higher proportions of methanol, a range of methanol
proportions between 60 and 100% was selected for the RSM
study.
3.2. Analysis of response surfaces
The extraction of apricot phenolics was optimised using an
RSM approach. RSM approaches, unlike single factor studies,
allow the evaluation of interaction eects between extraction
parameters and can also predict an optimal extraction point
that has to be verified experimentally.
42
In this specific study,
Fig. 1 Individual eects of the liquid-to-solid ratio (LSR) (a), temperature (T) (b) and methanol (MeOH) percentage (c) on the extraction of apricot
total phenolic content (TPC); total avonol content (TFoC); tartaric ester content (TEC) and total avanol content (TFaC). The results are expressed
as mg of phenolic component per gram of dry weight (mg per g dw) ± SD (n= 3).
a, b, c, d
Mean values with dierent letters were signicantly
dierent between extraction conditions (one-way ANOVA with Tukeyspost hoc test, p< 0.05). Abbreviations: caeic acid (Ca), catechin (Cat),
gallic acid equivalents (GAE), and quercetin (Quer). The gure was created with Graph-Pad PriSM 6.01 software (GraphPad, Sand Diego, CA, USA).
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a face-centered central composite design with two factors and
three levels was selected, consisting of 11 randomised runs
with 3 centre points. The previously optimised LSR (20 mL
g
1
) and extraction time (30 min) were fixed as constant vari-
ables during the RSM experiment. The independent variables
used in the RSM were methanol proportion (60100%, X
j
) and
temperature (2555 °C, X
i
). The compounds catechin, chloro-
genic acid and rutin were analysed individually by the
HPLC-DAD method and were included in the RSM as
relevant representatives of the phenolic families present in
apricots.
26,28,29
The obtained experimental extraction of cate-
chin, chlorogenic acid and rutin for all runs is reported in
Table 1.
3.2.1. Multiple linear regressions and the models ade-
quacy. The experimental data (Table 1) were used to determine
the regression coecients of eqn (1). All compounds analysed
generated a significant model, implying that at least one of the
extraction variables could explain the variation in the response
variables (Table 2). Indeed, the coecients of determination
(R
2
) were above 0.9, which means that the model represented
the data accurately. In addition, the lack of fit values was not
significant (p> 0.05), thus further validating the model.
Indeed, these results confirm that methanol percentage and
extraction temperature were identified as relevant extraction
parameters in the single factor study analyses.
3.2.2. Analysis of regression coecients and response
surface plots. The regression coecients of the model for cate-
chin, chlorogenic acid and rutin obtained from the multiple
linear regressions are reported in Table 2. Dependent variables
(i.e., catechin, chlorogenic acid and rutin) allowed direct
interpretation of the eect of the independent variables (i.e.,
methanol proportion and extraction temperature). The visual-
isation of the statistical significance of the independent vari-
ables on the dependent variables was facilitated by the gener-
ated surface contour plots (Fig. 2). Precisely, these figures
facilitate a more visual eect of the extraction variables on the
extraction of the studied phenolic compounds.
Regarding the eect of temperature, chlorogenic acid was
not influenced by this factor. However, a significant positive
linear eect and a negative quadratic eect were observed for
rutin, indicating that rutin extraction increases with tempera-
ture to a point after which it begins to decrease (Table 2). This
behaviour was previously described for flavanols
13
and total
phenolics
4,8
in other plant matrixes. For catechin, a linear
negative eect was found to be statistically significant, possibly
due to the thermosensitivity of flavanols.
13
Indeed, the
optimal extraction temperature for catechin according to our
optimised results was 32 °C (Fig. 2a), in agreement with the
optimal extraction temperature of 30 °C reported by Wani et al.
for sun-dried apricots.
5
The optimal extraction temperatures
reported for chlorogenic acid and rutin were 53 and 46 °C,
respectively (Fig. 2b and c), which are very similar to those
reported for several phenolics in other plant materials.
8,16
Table 1 Face-centred settings of independent variables and experi-
mental results of (+)-catechin, chlorogenic acid and rutin
Run T(°C) MeOH (%) Cat Chl Rut
1 25 60 1.21 1.51 0.54
2 55 60 1.08 1.61 0.58
3 25 100 1.14 1.23 0.31
4 55 100 1.10 1.16 0.34
5 25 80 1.27 1.47 0.50
6 55 80 1.24 1.51 0.56
7 40 60 1.18 1.55 0.61
8 40 100 1.17 1.29 0.36
9 40 80 1.29 1.52 0.56
10 40 80 1.24 1.48 0.54
11 40 80 1.33 1.52 0.53
Abbreviations: Temperature (T); methanol (MeOH); (+)-catechin (Cat);
chlorogenic acid (Chl); and rutin (Rut). The results are expressed as
mg of phenolic component per gram of dry weight (mg per g dw) ± SD
(n= 3).
Table 2 Analysis of variance and regression coecients of the predicted model for response variables in apricots
Model parameters Regression coecient Cat Chl Rut
Intercept β0 1.29 1.51 5.49 × 10
1
Linear
T×Tβ13.33 × 10
2
* 1.17 × 10
2
2.17 × 10
2
*
MeOH β21.00 × 10
2
1.65 × 10
1
*1.18 × 10
1
*
Interaction
T× MeOH β12 2.25 × 10
2
4.25 × 10
2
*2.50 × 10
3
Quadratic
T×Tβ11 3.73 × 10
2
3.03 × 10
2
2.87 × 10
2
*
MeOH × MeOH β22 1.17 × 10
1
*1.00 × 10
1
*7.37 × 10
2
*
R
2
0.9161 0.9746 0.9884
Adjusted R
2
0.8322 0.9491 0.9767
p-Value 0.0101 0.0005 0.0001
F-Value 10.92 38.30 84.96
Lack of fit
a
0.8957 0.2826 0.4910
Abbreviations: Temperature (T); methanol (MeOH); determination coecient (R
2
); (+)-catechin (Cat); Chlorogenic acid (Chl); rutin (Rut).
Dierences between groups determined by ANOVA. *p< 0.05.
a
p-Value of lack of the fit test.
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Cellular localisation and interaction with cell structural com-
ponents could explain the dierence in the optimal extraction
temperatures between the studied compounds.
37
When studying methanol percentage, a negative linear
eect of chlorogenic acid and rutin and a negative quadratic
eect for catechin, chlorogenic acid and rutin were observed
and were statistically significant. This implies that an increase
in methanol proportion will result in a reduction of the extrac-
tion of rutin and chlorogenic acid, as evidenced in Fig. 2. In
this sense, Yang et al. also reported a negative linear and quad-
ratic eect of the extraction solvent for total phenolics in
Phyllanthus emblica L
17
and Liyana-Pathirana et al. in the anti-
oxidant activity of soft wheat bran.
14
In addition, in this study,
catechin was reported to have an optimal methanol proportion
of 78% (Fig. 2a), which is highly similar to the optimal EtOH
proportion (84%) reported by Liu et al. for epicatechin in haw-
thorn fruit.
43
Indeed, a methanol proportion of 80% has been
shown to be ecient in extracting several phenolics, including
epicatechin and procyanidin B3.
44
In agreement with the
optimal reported methanol proportion of 63% for rutin
(Fig. 2b), Wijngaard et al. found an ethanol concentration of
64% to be optimal for the extraction of total flavonols.
18
In
this sense, solvents of approximately 50 and 60% have been
reported to be optimal in the extraction of total phenolics.
3,4
The optimal methanol proportion obtained in this study for
chlorogenic acid extraction was 60% (Fig. 2c), in agreement
with Yilmaz et al., who reported an optimal ethanol concen-
tration for neochlorogenic acid at 56% (ref. 4) and Wijngaard
et al. at 58% for chlorogenic acid.
18
Notably, aqueous mixtures
of organic solvents usually yield better extraction rates.
41,45
In
fact, the addition of water in extraction solvents promotes fruit
particle swelling. This increases the contact area between fruit
particles and the extraction solvent, which allows the solvent
to penetrate more easily into the food matrix, leading to
increased phenolic extraction yields.
45
A negative interaction (crossover eect) between tempera-
ture and methanol proportion was found to be statistically sig-
nificant for chlorogenic acid. Silva et al. reported a significant
interaction between ethanol concentration and temperature
for the total flavonols in Inga edulis leaves.
13
Similarly,
Pompeu et al. reported this type of interaction for antioxidant
activity in Euterpe oleracea fruit,
8
and Karacabey et al. reported
a significant negative interaction between ethanol concen-
tration and temperature in the antioxidant capacity of grape
crane extracts.
20
3.2.3. Validation of the model. The optimised combination
of extraction variables at the highest desirability (0.861) was a
temperature of 38 °C and methanol at 72%. To validate the
veracity of the model, 3 extractions were performed under the
optimised conditions. No significant dierences were reported
between the experimental and predicted extraction rates for
catechin, chlorogenic acid and rutin (Table 3). Therefore, the
model can accurately predict the behaviour of the response
variables within the range of extraction variables studied.
Fig. 2 Response surface plots for catechin (a), rutin (b) and chlorogenic acid (c) as a function of extraction temperature and methanol proportion.
Extractions were performed at a liquid-to-solid ratio of 20 mL g
1
under 500 rpm agitation for 30 minutes. Abbreviations: methanol (MeOH), cate-
chin (Cat), rutin (Rut) and chlorogenic acid (Chl). The gure was created with Design-expert 9.0.6 software (Trial version, Stat-Ease Inc., Minneapolis,
MN, USA).
Table 3 Overall optimal extraction parameters for phenolics in apricots
Extraction variables
Response variable Predicted ExperimentalT(°C) MeOH (%) Desirability
38 72 0.861 Cat 1.28 1.32 ± 0.03
Chl 1.56 1.56 ± 0.14
Rut 0.59 0.61 ± 0.01
Abbreviations: Temperature (T); methanol (MeOH); (+)-catechin (Cat); chlorogenic acid (Chl); rutin (Rut). The results are expressed as mg of
phenolic components per gram of dry weight (mg per g dw) ± SD (n= 3).
Food & Function Paper
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Thus, the extraction temperature and methanol proportion
were fixed at 38 °C and 72% throughout the rest of the study.
Similar to our results, Wani et al. reported a temperature of
30 °C to be optimal in the extraction of total phenolics from
sun-dried apricots,
5
and Tabaraki et al. reported an optimal
ethanol concentration between 60 and 70% for rice brans.
16
3.3. Eect of time on phenolic extraction
There are many literature examples in which time exerts a
significant influence on the extraction of several
phenolics.
4,9,11,17,25
It has been postulated that time can
promote the solubilisation of polyphenols in a solvent due to
the cell-wall weakening eects of optimised methanol and
temperature conditions.
16,17
Therefore, we further evaluate the
eect of time on the phenolic extraction of apricots under the
optimised conditions of 20 mL g
1
, 72% of methanol (1%
formic acid), 38 °C within a range of 0 to 120 minutes (500
rpm) (Fig. 3). Variables that encompass multiple representa-
tives of the same phenolic family provide a general view of the
eect of a particular extraction parameter. The TPC, TFoC,
TEC and TFaC represent the major phenolic families found in
apricots
26,28,29
and were used to study the eect of extraction
time in apricots. However, no significant changes were
reported due to time in any of the studied parameters.
Therefore, from practical and economic aspects, centrifugation
immediately after vortexing was set as the optimal procedure
(i.e., 0 min as the extraction time). Consistent with this
finding, Thoo et al. found no eect of time on the extraction of
flavonoids in Morinda citrifolia.
41
In addition, Yang et al.
reported a time of 23.16 min and Wani et al. a time of 30 min
as optimal in Phyllanthus emblica L. bark and sun-dried apri-
cots, respectively,
5,17
which are relatively short extraction
times.
3.4. Multi-step extractions
To evaluate whether better extraction could be attained with
this optimised method, three consecutive extractions were per-
formed under the optimised conditions of 20 mL g
1
, 38 °C,
72% of methanol (1% formic acid). Samples were vortexed
with pre-heated extraction solvents and immediately centri-
fuged. Values above 70% were observed for the TPC, TFoC and
TEC in the first extraction step (Fig. 4). Remarkably, few
studies evaluate the eect of consecutive extractions in the
literature,
7,9,17,46
and by applying this approach the extraction
of phenolic compounds from food matrixes can increase
considerably.
17,46
Values between 89% and 94% were reached
in the second extraction step. Similarly, Mané et al. reported
that flavanols, phenolic acids and anthocyanins in grape
skins, seeds and pulp were primarily extracted in the first
extraction step.
7
Chirinos et al. also reported a yield of 60% in
a single step for Tropaeolum tuberosum phenolic extraction.
9
However, since our aim was to extract a maximum content of
phenolics for accurate quantification, we set two extraction
steps as the optimal number of extraction steps in the rest of
the experiment. Remarkably, for all the parameters studied, no
significant dierences were reported between the second and
Fig. 3 Eect of time on the extraction of total phenolic (a), total avonol (b), tartaric ester (c), and total avanol (d) contents. Extractions were per-
formed at 20 mL g
1
, 38 °C, 72% methanol (1% formic acid), and agitation at 500 rpm. The results are expressed as mg of phenolic component per
gram of dry weight (mg per g dw) ± SD (n= 3). The gure was created with Graph-Pad PriSM 6.01 software (GraphPad, Sand Diego, CA, USA).
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third extraction steps, while the first and second steps were
significantly dierent.
3.5. Characterisation of apricot phenolics and the eect of
the extraction solvent
Considering that apricot characterisation has been mainly
realised using unspecific phenolic extraction
methodologies,
2629,31,32
we used our specific optimised
method to precisely and fully characterize the phenolic profile
of Charisma apricots. Moreover, methanolic and ethanolic
extractions were performed under the optimised conditions to
evaluate the eect of these solvents on the phenolic extraction
and characterisation. Our results demonstrate that the metha-
nol and the ethanol-base extractions reported dierent extrac-
tion yields for the TFoC (Table 4) and for individual com-
pounds determined by HPLC-ESI-MS/MS (Table 5). In most
individual phenolics, methanol achieved higher extractions
than ethanol, which is consistent with the literature,
9,25
but, in
most cases, the total extracted values in the methanolic and
ethanolic extraction were of a similar range. Paradoxically, the
TFoC was significantly higher in the ethanol-based extraction.
However, in the specific cases of protocatechuic acid and dihy-
droxybenzoic acid, the methanolic extraction clearly achieved
higher extraction rates than the ethanolic one. Ethanol showed
some higher extraction rates in individual compounds than
methanol. For instance, the ethanol-based extraction achieved
Fig. 4 Eect of multi-step extraction on total phenolic (a), total
avonol (b), tartaric ester (c), and total avanol (d) contents. Extractions
were performed at 20 mL g
1
, 38 °C and 72% methanol (1% formic acid).
The total quantity of phenolic component extracted after the third step
is expressed as mg of phenolic component per gram of dry weight (mg
per g dw) ± SD (n= 3). The gure was created with Graph-Pad PriSM
6.01 software (GraphPad, Sand Diego, CA, USA).
Table 4 Quantication of apricot (Prunus armeniaca) phenolics by
HPLC-DAD using methanol or ethanol as the extraction solvent
MeOH EtOH p-Value
TPC 5.33 ± 0.16 5.24 ± 0.14 0.232
TFoC 1.21 ± 0.10 1.47 ± 0.09 0.002
TEC 1.51 ± 0.10 1.55 ± 0.07 0.451
TFaC 0.252 ± 0.02 0.257 ± 0.01 0.556
Abbreviations: Total phenolic content (TPC); total flavonol content
(TFoC); tartaric ester content (TEC); and total flavanol content (TFaC).
Extractions were performed twice under optimised conditions: organic
solvent 72% and formic acid 1%, at 20 mL g
1
and 38 °C. The results
are expressed as mg of phenolic component per gram of dry weight
(mg per g dw) ± SD (n= 3). Statistics by Studentst-test.
Table 5 Quantication of apricot (Prunus armeniaca) phenolics by
HPLC-ESI-MS/MS
Compound MeOH EtOH p-Value
Benzoic acid 5.88 ± 0.30 6.21 ± 0.16 0.16
Hydroxybenzoic acid
a
2.34 ± 0.05 2.45 ± 0.10 0.17
Protocatechuic acid 185.11 ± 5.10 6.63 ± 0.21 <0.01
Dihydroxybenzoic acid
b
56.52 ± 1.30 n.q.
p-Coumaric acid n.q. n.q.
Gallic acid n.q. n.q.
Ferulic acid n.q. n.q.
Resveratrol 0.16 ± 0.00 0.15 ± 0.00 <0.01
Kaempferol 0.05 ± 0.03 0.03 ± 0.00 0.31
Catechin 20.00 ± 0.93 18.45 ± 0.83 0.10
Epicatechin 16.44 ± 0.90 15.31 ± 0.34 0.11
Quercetin n.q. n.q.
Protocatechuic acid glucoside
b
1.54 ± 0.05 1.59 ± 0.03 0.19
Gallic acid O-glucoside d1
c
0.01 ± 0.00 0.02 ± 0.00 0.03
Gallic acid O-glucoside d2
c
0.18 ± 0.01 0.20 ± 0.01 0.01
Caeic acid O-glucoside d1
d
2.79 ± 0.04 3.25 ± 0.26 0.04
Caeic acid O-glucoside d2
d
4.77 ± 0.21 5.16 ± 0.25 0.11
Caeic acid O-glucoside d3
d
20.43 ± 0.60 21.69 ± 0.68 0.07
Neochlorogenic acid
e
565.79 ± 16.82 586.19 ± 13.60 0.18
Chlorogenic acid 178.60 ± 13.11 216.36 ± 4.81 0.01
Cryptogenic acid
e
41.55 ± 3.50 36.60 ± 2.61 0.12
Feruloylquinic acid
f
3.32 ± 0.04 3.45 ± 0.05 0.02
Resveratrol O-glucoside d1
g
0.16 ± 0.00 0.15 ± 0.00 0.01
Resveratrol O-glucoside d2
g
0.13 ± 0.01 0.15 ± 0.01 0.06
Catechin gallate
h
0.70 ± 0.01 0.71 ± 0.02 0.24
Kaempferol-3-O-glucoside 0.47 ± 0.04 0.46 ± 0.01 0.75
Eriodictyol-7-O-glucoside 0.32 ± 0.01 0.32 ± 0.00 0.32
Catechin O-glucoside
h
0.51 ± 0.04 0.46 ± 0.01 0.10
Hyperoside 13.20 ± 0.84 12.87 ± 0.40 0.57
Isorhamnetin-3-O-glucoside 0.03 ± 0.00 0.03 ± 0.00 0.72
Procyanidin dimer d1
i
14.39 ± 0.73 11.44 ± 0.24 <0.01
Procyanidin dimer d2
i
6.63 ± 0.22 5.99 ± 0.34 0.05
Procyanidin dimer B2 6.69 ± 0.21 5.80 ± 0.26 0.01
Procyanidin dimer d3
i
1.00 ± 0.08 0.85 ± 0.04 0.04
Procyanidin dimer d4
i
2.80 ± 0.20 2.50 ± 0.06 0.07
Procyanidin dimer d5
i
0.68 ± 0.01 0.62 ± 0.01 <0.01
Kaempferol-3-O-rutinoside 14.51 ± 1.05 14.27 ± 0.21 0.72
Rutin 278.94 ± 9.71 238.33 ± 7.81 <0.01
Procyanidin trimer
i
0.38 ± 0.01 0.30 ± 0.03 0.01
Extractions were performed twice under optimised conditions: organic
solvent 72% and formic acid 1%, at 20 mL g
1
and 38 °C. The results
are expressed in mg per kg dw ± SD (n= 3) (statistics by Students
t-test). d1, d2, d3, d4 and d5 indicate dierent isomeric compounds.
a
Quantified using the calibration curve of benzoic acid.
b
Quantified
using the calibration curve of protocatechuic acid.
c
Quantified using
the calibration curve of gallic acid.
d
Quantified using the calibration
curve of caeic acid.
e
Quantified using the calibration curve of chloro-
genic acid.
f
Quantified using the calibration curve of ferulic acid.
g
Quantified using the calibration curve of resveratrol.
h
Quantified
using the calibration curve of catechin.
i
Quantified using the cali-
bration curve of procyanidin dimer B2. Abbreviations: n.d., not
detected; n.q., not quantified.
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significantly higher extractions of chlorogenic acid.
Remarkably, chlorogenic acid and related compounds such as
caeic acid have shown important health promoting activi-
ties.
2
Moreover, there are no dierences in the TPC, TEC and
TFaC of both extraction solvents. Therefore, considering that
ethanol is used in the food industry due to methanols tox-
icity,
47
our results suggest that the adaptation of this method-
ology on a larger scale could be used to produce phenolic rich
extracts with potential bioactive functions.
Methanol, which generally achieves better extraction rates,
was demonstrated to be the optimal solvent to accurately
profile the phenolic content of apricots. It is worth considering
that, since apricot phenolics vary due to their variety, maturity
stage and region of cultivation,
2629
comparing the extraction
rate of dierent methods is controversial. Our optimised
method achieved 5.33 ± 0.16 mg GAE per g dw, within the
range of the TPC (8.184.23 mg GAE per g dw) reported for
several apricot varieties.
24
However, our method extracted
higher TPC than apricots from dierent varieties in dierent
studies.
30
In agreement with the phenolic profile of apricots,
we found rutin and hydroxycinnamic acids (Table 5) to be the
most abundant compounds in apricots.
25,27,30
In the case of
the most representative phenolic compounds in apricots,
higher quantities were extracted with this optimized method
than the values reported in the literature. For example, rutin,
which was reported to range between 15.50 and 69.52 mg per
kg dw in several apricot varieties, was found at 278.94 ±
9.71 mg per kg dw in our study.
27
Similar concentrations of
chlorogenic acid were found in the study of Karabulut et al.
compared to the one we found.
30
However, our method
extracted 178.60 ± 13.11 mg chlorogenic acid per kg dw, which
is greater than the concentrations found in Ordubat (42.41 ±
0.01 mg per kg dw), Stark early orange (93.86 ± 0.01 mg per
kg dw) and Wilson delicious (147.31 ± 0.00 mg per kg dw),
among other varieties.
26
Similarly, lower concentrations of
chlorogenic acid were found in the study of Kan et al.
27
Karabulut et al. reported neochlorogenic acid at concen-
trations between 103.72 and 285.29 mg per kg dw,
30
and, in
this study, the observed neochlorogenic acids concentration
was 565.79 ± 16.82 mg per kg dw.
All in all, better extraction rates than reported in the litera-
ture using unspecific methods for apricots were achieved for
most of the representative phenolic compounds. In addition to
the good extraction rates achieved, this method is faster than
the one developed for sun-dried apricots
5
and other plant
matrixes.
4,13
Moreover, the required temperatures
4,11,13,15
and
LSR
11,15,19
are lower than those of other methods for dierent
plant matrixes, making our method more economically
feasible.
4. Conclusions
In this study, we developed a fast and economically feasible
method for the specific extraction of apricot phenolics. The
optimised conditions were as follows: 20 g mL
1
, 38 °C and
72% methanol (1% formic acid). The phenolic extraction using
this method allowed accurate characterisation of the phenolic
profile of apricots, which is essential in the study of their
bioactivity. Additionally, the ethanol-based extraction has
potential to be adapted to the food industry for the production
of phenolic-rich extracts with potential bioactive eects.
Abbreviations
Dw Dry weight
GAE Gallic acid equivalents
LSR Liquid-to-solid ratio
RSM Response surface methodology
TEC Tartaric ester content
TFaC Total flavanol content
TFoC Total flavonol content
TPC Total phenolic content
Conicts of interest
There are no conflicts to declare.
Acknowledgements
This work was supported by the Spanish Ministry of Economy
and Competitiveness (grant numbers AGL2013-49500-EXP and
AGL2016-77105-R) and by European Regional Development
Funds of the European Union within the Operative Program
FEDER of Catalunya 2014-2020 (PECT-NUTRISALT). L. I.-C. is
a recipient of a predoctoral fellowship from Universitat
Rovira i Virgili Martí i Franquès. Grant number:
2015PMF-PIPF-50. A. M.-C. is a recipient of a predoctoral fel-
lowship from Universitat Rovira i Virgili Martí i Franquès.
Grant number: 2015PMF-PIPF-51. A. A.-A. is a Serra Húnter
fellow. We express deep thanks to Dr Pol Herrero, Dr Antoni
Del Pino, Niurka Llópiz and Rosa M. Pastor for their technical
help and advice.
References
1 L. Hooper, P. A. Kroon, E. B. Rimm, J. S. Cohn, I. Harvey,
K. A. Le Cornu, J. J. Ryder, W. L. Hall and A. Cassidy,
Am. J. Clin. Nutr., 2008, 88,3850.
2 M. N. Cliord, I. B. Jaganath, I. A. Ludwig and A. Crozier,
Nat. Prod. Rep., 2017, 34, 13911421.
3 J. E. Cacace and G. Mazza, J. Food Sci., 2003, 68, 240248.
4F.M.Yılmaz, M. Karaaslan and H. Vardin, J. Food Sci.
Technol., 2015, 52, 28512859.
5 S. M. Wani, N. Jan, T. A. Wani, M. Ahmad, F. A. Masoodi
and A. Gani, J. Saudi Soc. Agric. Sci., 2017, 16, 119126.
6 M. L. Bengoechea, A. I. Sancho, B. Bartolomé, I. Estrella,
C. Gómez-Cordovés and M. T. Hernández, J. Agric. Food
Chem., 1997, 45, 40714075.
Paper Food & Function
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7 C. Mané, J. M. Souquet, D. Ollé, C. Verriés, F. Véran,
G. Mazerolles, V. Cheynier and H. Fulcrand, J. Agric. Food
Chem., 2007, 55, 72247233.
8 D. R. Pompeu, E. M. Silva and H. Rogez, Bioresour.
Technol., 2009, 100, 60766082.
9 R. Chirinos, H. Rogez, D. Campos, R. Pedreschi and
Y. Larondelle, Sep. Purif. Technol., 2007, 55, 217225.
10 O. Zitka, J. Sochor, O. Rop, S. Skalickova, P. Sobrova,
J. Zehnalek, M. Beklova, B. Krska, V. Adam and R. Kizek,
Molecules, 2011, 16, 29142936.
11 L. Iglesias-Carres, A. Mas-Capdevila, L. Sancho-Pardo,
F. I. Bravo, M. Mulero, B. Muguerza and A. Arola-Arnal,
Nutrients, 2018, 10, 1931.
12 L. Iglesias-Carres, A. Mas-Capdevila, F. I. Bravo,
G. Aragonès, B. Muguerza and A. Arola-Arnal, PLoS One,
2019, 14, e0211267.
13 E. M. Silva, H. Rogez and Y. Larondelle, Sep. Purif. Technol.,
2007, 55, 381387.
14 C. Liyana-Pathirana and F. Shahidi, Food Chem., 2005, 93,
4756.
15 K. N. Prasad, F. A. Hassan, B. Yang, K. W. Kong,
R. N. Ramanan, A. Azlan and A. Ismail, Food Chem., 2011,
128, 11211127.
16 R. Tabaraki and A. Nateghi, Ultrason. Sonochem., 2011, 18,
12791286.
17 L. Yang, J. G. Jiang, W. F. Li, J. Chen, D. Y. Wang and
L. Zhu, J. Sep. Sci., 2009, 32, 14371444.
18 H. H. Wijngaard and N. Brunton, J. Food Eng., 2010, 96,
134140.
19 Y. Liu, S. Wei and M. Liao, Ind. Crops Prod., 2013, 49, 837
843.
20 E. Karacabey and G. Mazza, Food Chem., 2010, 119, 343
348.
21 C. Y. Gan and A. A. Lati,Food Chem., 2011, 124, 1277
1283.
22 J. Pérez-Jiménez, V. Neveu, F. Vos and A. Scalbert,
Eur. J. Clin. Nutr., 2010, 64(Suppl 3), S112S120.
23 F. Fratianni, M. N. Ombra, A. DAcierno, L. Cipriano and
F. Nazzaro, Curr. Opin. Food Sci., 2018, 19,2329.
24 E. B. Akin, I. Karabulut and A. Topcu, Food Chem., 2008,
107, 939948.
25 S. Erdoan and S. Erdemoğlu, Int. J. Food Sci. Nutr., 2011,
62, 729739.
26 M. Gundogdu, S. Ercisli, S. Berk, T. Kan, I. Canan and
M. K. Gecer, J. Food Meas. Charact., 2017, 11, 20872093.
27 T. Kan, M. Gundogdu, S. Ercisli, F. Muradoglu, F. Celik,
M. K. Gecer, O. Kodad and M. Zia-Ul-Haq, Biol. Res., 2014,
47,16.
28 V. Dragovic-Uzelac, B. Levaj, V. Mrkic, D. Bursac and
M. Boras, Food Chem., 2007, 102, 966975.
29 T. Kan and S. Z. Bostan, J. Food Process. Preserv., 2013, 37,
163170.
30 I. Karabulut, T. Bilenler, K. Sislioglu, I. Gokbulut,
F. Seyhan, I. S. Ozdemir and B. Ozturk, J. Food Biochem.,
2018, 42, e12458e12470.
31 V. Dragovic-Uzelac, K. Delonga, B. Levaj, S. Djakovic and
J. Pospisil, J. Agric. Food Chem., 2005, 53, 48364842.
32 S. M. Wani, P. R. Hussain, F. A. Masoodi, M. Ahmad,
T. A. Wani, A. Gani, S. A. Rather and P. Suradkar, J. Agric.
Sci., 2017, 9,6682.
33 V. M. Burin, N. E. Ferreira-Lima, C. P. Panceri and
M. T. Bordignon-Luiz, Microchem. J., 2014, 114, 155
163.
34 Di. Cheaib, N. El Darra, H. N. Rajha, R. G. Maroun and
N. Louka, Sci. World J.
35 A. Arnous, D. P. Makris and P. Kefalas, J. Food Compos.
Anal., 2002, 15, 655665.
36 Y. Sun, W. Xu, W. Zhang, Q. Hu and X. Zeng, Sep. Purif.
Technol., 2011, 78, 311320.
37 M. Pinelo, A. Arnous and A. S. Meyer, Trends Food Sci.
Technol., 2006, 17, 579590.
38 J. E. Cacace and G. Mazza, J. Food Eng., 2003, 59, 379389.
39 A. A. Van Der Sluis, M. Dekker and M. A. J. S. Van Boekel,
J. Agric. Food Chem., 2005, 53, 10731080.
40 G. D. S. C. Borges, F. G. K. Vieira, C. Copetti, L. V. Gonzaga
and R. Fett, Food Res. Int., 2011, 44, 708715.
41 Y. Y. Thoo, S. K. Ho, J. Y. Liang, C. W. Ho and C. P. Tan,
Food Chem., 2010, 120, 290295.
42 D. Başand İ. H. Boyaci, J. Food Eng., 2007, 78, 846854.
43 J. L. Liu, J. F. Yuan and Z. Q. Zhang, Int. J. Food Sci.
Technol., 2010, 45, 24002406.
44 J. Oszmianski and C. Y. Lee, Am. J. Enol. Vitic., 1990, 41,
204206.
45 W. Li, Z. Wang, Y. P. Wang, C. Jiang, Q. Liu, Y. S. Sun and
Y. N. Zheng, Food Chem., 2012, 130, 10441049.
46 N. E. Durling, O. J. Catchpole, J. B. Grey, R. F. Webby,
K. A. Mitchell, L. Y. Foo and N. B. Perry, Food Chem., 2007,
101, 14171424.
47 R. Kushwaha and S. Karanjekar, Int. J. ChemTech Res., 2011,
3, 10331036.
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... Thus, this model was fit for the further analysis of the influence of process parameters. The model equation was significant at 95% confidence level with non-significant lack of fit [25,27,35]. The goodness of fit of this model was verified by the coefficient of R 2 (0.9456) and the adjusted R 2 (0.8756). ...
... This might be due to the lignans in the treated sesame oil samples [41]. The model equation was significant at 95% confidence level with non-significant lack of fit [25,27,35]. The goodness of fit of this model was verified by the coefficient of R 2 (0.9456) and the adjusted R 2 (0.8756). ...
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The ultrasound-assisted extraction of phenolic compounds from Euryale ferox seed shells was modeled using response surface methodology. A three-level-three-factor Box-Behnken design was employed to optimize three extraction variables, including extraction time (X-1), ethanol concentration (X-2), and ratio of aqueous ethanol to raw material (X-3), for the achievement of high extraction yield of the phenolic compounds. The statistical analyses show that the independent variables (X-1, X-2), the quadratic terms (X-1(2), X-2(2) and X-3(2)), and the interactions of X-1 with X-2 and X-3 have significant effect on the yield (p<0.01). The optimized conditions are X-1 of 21 min, X-2 of 52%, and X-3 of 31 mL/g. Under these conditions, the experimental yield is 15.69 +/- 0.082% (n=3), which is well matched with the predicted yield of 15.70%. The evaluation of antioxidant activity by DPPH assay indicates that the phenolic compounds from E. ferox seed shells possess significant antioxidant activity. HPLC analysis reveals that pyrogallol, gallic acid, chlorogenic acid and rutin are the major composition in the extracts.