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Analytica Chimica Acta 533 (2005) 185–191
Standardization of antioxidant properties of honey by a combination
of spectrophotometric/fluorimetric assays and chemometrics
Giangiacomo Berettaa, Paola Granataa, Maria Ferrerob,
Marica Oriolia, Roberto Maffei Facinoa,∗
aIstituto Chimico Farmaceutico Tossicologico, Facolt`a di Farmacia, Universit`a di Milano, Viale Abruzzi 42, 20131 Milano, Italia
bScuola di Specializzazione in Scienza e Tecnologia Cosmetiche, Facolt`a di Farmacia, Universit`a di Milano, Viale Abruzzi 42, 20131 Milano, Italia
Received 5 October 2004; received in revised form 3 November 2004; accepted 3 November 2004
Available online 30 January 2005
Abstract
Theaimofthisworkwastoestablishasolidplatformofanalyticalinformationforthedefinition/standardizationoftheantioxidantproperties
of honey. We investigated first the antioxidant/radical scavenging capacity of 14 commercial honeys of different floral and geographic origin,
using a battery of spectrophotometric tests: Folin-Ciocalteu assay for phenol content (PC), ferric reducing antioxidant power (FRAP assay)
for total antioxidant activity, 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay for antiradical activity, absorbance:450 (ABS450) for color intensity
and one fluorimetric method: ORAC, oxygen reactive antioxidant capacity for the antilipoperoxidant activity. Then the data from different
procedures were compared and analysed by multivariate techniques (correlation matrix calculation, principal component analysis (PCA)).
Significant correlations were obtained for all the antioxidant markers (rranging from 0.933 to 0.716), with antioxidant properties strictly
correlated to the phenolic content and honey color intensity. PCA found different clusters of honey based on the antioxidant power and
very likely also on chemical composition. The results of this study demonstrated that only through a combination of antioxidant testings,
comparative analyses, and chemometric evaluation we can achieve a strictly rigorous guideline for the characterization of the antioxidant
activity of honey, an invaluable tool for the understanding/demonstration of its antioxidants linked therapeutic efficacy.
© 2004 Elsevier B.V. All rights reserved.
Keywords: Standardization; Honey; Antioxidants; Optical methods; Multivariate analysis
1. Introduction
Honey has been an ingredient of traditional medicine
on account of its dietary and curative properties since
ancient times. Starting in the early 1970s researchers from
different scientific fields have investigated the chemical
and biological properties of honey, these latter including
antibacterial, bacteriostatic, anti-inflammatory, wound and
sunburn healing activities that have only been assessed
in more rigorous and scientific studies in the last few
years [1–5]. Recent views propose honey not only as a
health-promoting dietary supplement, but shed light on its
∗Corresponding author. Tel.: +39 0250317534/64; fax: +39 0250317565.
E-mail address: roberto.maffeifacino@unimi.it (R. Maffei Facino).
antioxidant, non-peroxide-dependent properties [6]. This
makes honey more than just a nourishment of high value,
but a valuable dietary source of antioxidants.
Beside caffeic, coumaric acid and their esters honey
contains phenolic acids and their derivatives flavonoid
aglycones (pinobanksin, chrisin, galangin, luteolin, and
kaempferol) carotenoids, ascorbic acid, an antioxidant
pool that by acting synergistically can explain many of the
biological/therapeutic properties of honey [7,8].
Surprisingly, the majority of analytical efforts on honey
until now have focused on the search for and characterization
of features such as amino acids, proteins, trace elements,
volatiles, sugar composition, and pollens, as markers of the
geographical, botanical, and seasonal origin but few have
analysed its antioxidant biologically active constituents
0003-2670/$ – see front matter © 2004 Elsevier B.V. All rights reserved.
doi:10.1016/j.aca.2004.11.010
186 G. Beretta et al. / Analytica Chimica Acta 533 (2005) 185–191
[9–12]. Studies of the enhanced antioxidant power of human
serum after honey intake in vivo have only appeared recently.
They indicate that consumption of honey alone or with other
antioxidant beverages significantly increases the antioxidant
capacity of human serum [13,14]. Similarly, fructose had
less pro-oxidant effect when taken as dietary honey in vivo
than in fructose-treated subjects [15]. Hamzaoglu reported
that tumor implantation in rats was markedly reduced by the
application of honey pre- and post-operatively, suggesting
that the physico-chemical and chemical properties of honey
antioxidants can protect wounds against tumor implantation
[16]. Swellam subsequently demonstrated the antitumor
effect of bee honey against bladder cancer in vitro and
in vivo [17].
What casts doubt on the beneficial properties of honey
antioxidants is the fact that the most significant therapeutic
findings have been obtained with honeys not standardized as
regards their antioxidant properties. This is presumably be-
causethe literature doesnot endorse anysystematic approach
takingaccountofdifferentmarkersofantioxidantactivity and
making the proper correlations, so as to furnish a comprehen-
sive view of the antioxidant capacity of a honey sample.
The lack of standardization lies also on the fact that honey
is a highly complex mixture of at least to 200 phytochem-
icals whose composition is strictly dependent on floral and
geographical origin.
The aim of this work was therefore to set up a reliable
andsimple procedure for the definition/standardization of the
antioxidant activity of various honeys (of different floral and
geographical origin). This through a combination of different
antioxidantassaysand a chemometric approach. Themarkers
used were: color intensity (ABS450), Folin-Ciocalteu assay
forthe total phenoliccontent (PC), theferric reducing antiox-
idant power (FRAP) assay for total antioxidant activity, the
DPPH assay to analyse antiradical capacity, and the oxygen
radicals absorbance capacity (ORAC) assay for antilipoper-
oxidant activity. The underlying interrelations between the
parameterswere studied using chemometric methodsfor data
elaboration. To our knowledge this is the first approach to ra-
tional standardization of the antioxidant properties of honey
and provides a trace for further analytical investigations on
the profile of antioxidant phytochemicals so that more rigor-
ous biological studies can be planned.
2. Experimental
2.1. Apparatus
Spectrophotometric measurements were done with a
computer-aided Perkin-Elmer UV-VIS spectrophotometer
Lambda 16 (Perkin-Elmer, Monza, Italy).
Fluorimetric determinations were carried out with a Wal-
lac Victor2Multiwell instrument (Perkin-Elmer, Monza,
Italy) with fluorescent filters (λec =485 nm; λem =535nm).
2.2. Chemicals
The organic solvents were all analytical grade (Sigma–
Aldrich, Milan, Italy). 2,2-Azobis(2-amidinopropane)
dihydrochloride (AAPH) was from Wako Chemicals (Rich-
mond, VA, USA), -phycoerythrin (-PE) from Porphydium
cruentum and 6-hydroxy-2,5,7,8-tetramethyl-2-carboxylic
acid (Trolox) were purchased from Sigma–Aldrich (Milan).
1,1-Diphenyl-2-picrylhydrazyl (DPPH), 2,4,6-trypiridyl-
s-triazine (TPTZ), Folin-Ciocalteu reagent, and hydrogen
peroxide 30% were from Fluka (Buchs, Switzerland).
FeCl3·6H2O and FeSO4·7H2O were from Carlo Erba
(Milan, Italy).
2.3. Honey samples
Commercial honeys from the following floral sources
were purchased in different markets and stores during 2003:
strawberry tree (Arbutus unedo), buckwheat (Fagopyrum
esculetum), chestnut (Castanea sativa), sulla (Hedysarum
coronarium), clover (Trifolium incarnatum), dandelion
(Taraxacum officinalis, two different samples), chicory
(Chicorium intybus), acacia (Robinia pseudoacacia), moun-
tain multi-flora, honeydew. Three “pure tropical” honeys
were from Burkina Faso, Africa, and labeled Africa 1, 2, 3.
Samplesof honey were stored at 4 ◦C in the dark until pro-
cessing. All honey samples were tested by the usual available
physico-chemical tests (pH, electrical conductivity, titrable
acidity, ash content) and by qualitative tests (Lugol test and
diastases index for authenticity, hydroxymethylfurfural test
(HMF) for quality) and by quantitative test (reducing and
non-reducing sugar) [18]. A sugar analogue consisting of
40% fructose, 30% glucose, 10% maltose and 20% water
was made to check whether the main sugar components of
honey can interfere in all the proposed assays.
3. Methods
3.1. Phenol content (PC)
The total phenol content was determined by a mod-
ification of the Folin-Ciocalteu method and the results
expressed as mggallicacid/kg honey (mggallic acid/kg) [19].
Samples of different honeys were treated with warm distilled
water (500mg/5mL water), and sonicated for 5min, until
a clear solution was obtained. Then 100L of the solution,
corresponding to 10mg of fresh honey, were added to
1mL of Folin-Ciocalteu reagent previously diluted 1:10
with distilled water. The mixture was vortexed for 2min,
and the content transferred into a 1.5mL cuvette (1cm
path); absorbance was determined after 20min at 750nm
against the sugar analogue. Determinations were done in
quadruplicate. As we were working under acidic conditions
there was no interference from the sugar analogue [19], and
no precipitate formed during the analysis. The linearity of the
G. Beretta et al. / Analytica Chimica Acta 533 (2005) 185–191 187
method was checked from 10 to 250g/mL (R2=0.99) of
gallic acid (dissolved in methanol/water 1:1). The linearity
of the optical response honey–Folin-Ciocalteu reaction was
checked for each sample in the range of 1–20% added honey
solution.
3.2. Total antioxidant activity: FRAP assay
Total antioxidant activity was assayed with the original
method of Benzie and Strain [20] highly suited to measure
the Fe3+/Fe2+ couple reducing ability of a complex matrix.
Honey samples were treated as described above and the ab-
sorbance of the complex TPTZ-Fe(II) formed in the presence
of 50 L of honey solution (1g/10mL) was determined until
fulldevelopmentofthereaction.Theabsorbanceofthehoney
was measured at 593nm against the sugar analogue. Precip-
itation or flocculation was never observed. Determinations
were done in quadruplicate.
Aqueous solutions of FeSO4·7H2O (200–1000 M) were
usedfor the calibration and the results are expressed as FRAP
value (M Fe(II)) of the honey solution (10%).
3.3. Antiradical activity: DPPH assay
Thescavengingactivity(H/e−transferringability)against
DPPH radical was evaluated according to the method of
Brand-Williams [21], with minor modifications. The assay
mixture contained 1.9mL of 130 M DPPH (final concen-
tration 83.3M) dissolved in absolute ethanol, 1mL of ac-
etate buffer solution (100mM, pH 5.5) and 0.1mL of the
honey sample solution (see above) containing from 30 to
600mg/mL native honey; the final volume was 3mL. The
mixture was shaken vigorously on a Vortex mixer then incu-
bated 90 min at 25◦C in a water bath in the dark, after which
the absorbance of the remaining DPPH was determined at
517nm against a blank.
Blank was honey at the same concentration above
described containing all reagents except DPPH. This to
eliminate honey color interference. The scavenging activity
was expressed as IC50 (mg/mL). All analyses were done in
quadruplicate. The sugar analogue by itself (see above) did
not reduce the original DPPH absorbance.
3.4. Antilipoperoxidant activity: ORAC assay
The ORAC assay was based on the procedure described
by Cao et al. [22]. Free radicals are produced by AAPH
and the fluorescent marker -PE is oxidized, losing its
fluorescence. All reagents were prepared in phosphate buffer
(pH 7.0) and Trolox (5g/ml, 20M, final concentration)
was used as standard. Each well of the plate reader contained
in the final volume of 500L assay solution constituted
by: -PE (16.7nM), 1–8mg/mL of honey, and AAPH
2.2mg/mL (final concentration). After addition of the
AAPH, the plate was shaken automatically for 3s, then the
fluorescence was measured every 2min for 60min with
emission and excitation wavelengths of λ=535 and 485nm.
All fluorescence measurements were made at 37◦C and the
ORAC values were calculated as area under the curve (AUC)
and expressed as molTroloxequivalent(TE)/g. A sugar
analogue was prepared as described for the Folin-Ciocalteu
assay. Blank was: phosphate buffer (pH 7), -PE, AAPH.
3.5. Color intensity: ABS450
Since the color of honey partly reflects the content
of pigments with antioxidant properties (carotenoids,
flavonoids, etc.), honey was diluted to 50% (w/v) with
Table 1
Phenol content (mggallicacid/kg), FRAP values, honey color (ABS450), antiradical power (DPPH), and oxygen radical absorbance capacity (ORAC) of tested
honeys
Type of honey Phenol content (PC)
(mggallicacid/kg) FRAP value
(MFe(II)) Antiradical power
(DPPH, IC50)ORAC (TEa/g) ABS450
(mAU, 50w/v)
Strawberry tree 789.6 ±13.8 a 1501.4±60.2 a 1.63 ±0.17 a 21.07 ±0.34 a 3413
Africa 1 567.3 ±1.2 b 808.1±18.3 b 3.61 ±0.13 b 11.07 ±0.43 b 2363
Buckwheat 482.2 ±2.4 c 800.7±23.8 b 4.00 ±0.44 b 11.60 ±0.027 b 2245
Honeydew 255.6 ±7.5 d 772.0±21.5 b 8.48 ±0.24 c 6.30 ±0.22 c 466
Africa 2 595.2 ±13.1 e 448.1±4.7 c 5.13 ±0.13 d 18.23 ±0.33 d 1139
Chestnut 211.2 ±5.5 f 388.6±8.2 d 7.93 ±0.04 e 8.90 ±0.45 e 610
Africa 3 287.4 ±2.3 g 381.0±19.2 e 3.47 ±0.04 b 18.00 ±0.26 d 590
Multi-flora 170.4 ±1.7 h 361.9±10.8 e 5.32 ±0.03 d 8.22 ±0.42 e 415
Dandelion 2 102.1 ±10.0 i 224.4±6.0 f 24.39 ±0.07 f 7.59 ±0.60 e 225
Chicory 158.5 ±3.8 l 209.5±2.8 g 5.81 ±0.04 g 6.72 ±0.33 c 244
Dandelion 1 52.5 ±1.5 m 212.2±2.2 g 47.62 ±0.39 h 2.00 ±0.02 f 39
Sulla 106.6 ±4.6 i 155.2±6.6 h 16.90 ±0.11 i 5.66 ±0.13 g 222
Acacia 55.2 ±2.8 m 79.5±3.7 i 45.45 ±0.04 l 2.12 ±0.01 h 25
Clover 67.1 ±5.6 o 72.8±3.0 i 25.00 ±0.01 m 2.15 ±0.02 h 107
Sugar analogue 0.0 0.0 0.0 1.40 ±0.01 i –
Data are means±S.D. of four independent determinations. Means within a column sharing the same letter are not significantly different by Student’s t-test
(P<0.05).
aTrolox equivalent (M).
188 G. Beretta et al. / Analytica Chimica Acta 533 (2005) 185–191
warm water (45–50◦C), sonicated for 5min and filtered
(0.45m pore size, Agilent Technologies, Milan, Italy) to
eliminate large particles, and the net absorbance was defined
as the difference between spectrophotometric absorbance at
450 and 720nm.
3.6. Data analysis
Analysis of variance according to Student’s t-test (two-
tailed) was done to compare the PC, FRAP, DPPH, ORAC
and ABS450 values of the different honeys. In Table 1, within
each column, averages denoted with the same letter were not
significantly different by this test (P<0.05).
The antioxidant test results were investigated with
multivariate analysis. The correlation matrix was calculated,
giving the correlation coefficients between each pair of
variables, i.e. the analytical parameters tested. Each term of
thematrix is a number ranging from −1 to +1: the + or −sign
indicates a positive or negative interdependence between
variables (direction), and the absolute value indicates the
strength of the interdependence. To identify new meaningful
underlying variables and to reduce the dimensions of the
data set we performed a principal component analysis.
Briefly, PCA uses linear combinations of the variables of the
original data set to generate a smaller number of uncorrelated
variables called principal components. The results of the
analysis are presented in terms of scree, loading and score
plots. All calculations and graphic representations were
done using the Xlstat 5.0 software (Addinsoft, USA).
4. Results
4.1. Phenol content (PC)
In the first part of the study, the total phenol content
(mggallicacid/kg) of the different honeys was investigated
using the modified Folin-Ciocalteu assay which is sensi-
tive to phenol and polyphenol entities and other electron-
donatingantioxidants (ascorbic acid, VitaminE). As reported
in Table 1, the phenol content was low in pale honeys of
monofloral origin: clover, acacia, dandelion 1, higher in sulla
anddandelion2,risingfurther in chicory and mountain multi-
flora. Total phenol content was much higher in all the other
honeys. Strawberry tree honey had the highest content, ap-
proaching 0.1% (789.57±13.79 mggallic acid/kg). The aver-
age content of total phenols was in good agreement with that
reported in literature for the same kinds of honey. In partic-
ular, the value for Mexican buckwheat honey matched that
reported in literature for the Californian one (482.17±2.40
versus 456±55mggallic acid/kg) [23].
4.2. Total antioxidant activity: FRAP
To determine the total antioxidant content we used the
FRAP assay which is the only one that directly estimates
antioxidants or reductants in a sample, and is based on the
ability of the analyte to reduce the Fe3+/Fe2+ couple. The
disadvantage is that it does not measure thiols because their
reductionpotentials are generally below that of the Fe3+/Fe2+
half reaction. However, since only a small amount of these
compounds is expected in honey, their contribution to the
total antioxidant capacity can be considered negligible. The
FRAP values, expressed as Fe(II) (M) of the 10% (w/v)
honey solution, ranged from 72.8 ±3.7M for clover honey
to 1501.4±60.2 M for strawberry tree honey (Table 1).
The FRAP assay showed large difference in antioxidant
profile of various honeys, the least active being those of
monofloral origin (Clover, Acacia, Sulla, Dandelion).
4.3. Antiradical activity (DPPH)
The DPPH radical scavenging test is one of the short-
est available to investigate the overall hydrogen/electron-
donatingactivityof single antioxidants and health-promoting
dietary antioxidant supplements. The scavenging ability
of the honeys rose dose-dependently in the range of
1–20mghoney/mL of the final assay solution (data not
shown). Table 1 shows the scavenging ability expressed
as IC50 on the DPPH radical. There were marked dif-
ferences between honeys. Again the least active were
those of monofloral origin: clover, acacia, sulla, dandelion;
the most active strawberry tree (IC50 =1.63±0.17mg/mL)
whose antiradical potency was 30 times that of dandelion 1
(IC50 =47.62 ±0.39 mg/mL).
4.4. Antilipoperoxidant activity (ORAC)
Fig. 1 reports as an example the typical quenching curve
of -PE fluorescence in the ORAC assay in the presence of
one selected honey (strawberry tree), Trolox, and the sugar
analogue. The ORAC values of honeys calculated as AUC
ranged from 2.0 to 21.0molTE/g (Table 1). The ORAC
value for strawberry tree honey was exceptionally high and,
to our knowledge, the highest observed for any honey to
Fig. 1. Representative quenching curves of -PE in the ORAC assay in the
presence of strawberry tree honey (1mg/mL), sugar analogue (1mg/mL),
and Trolox (20M) as standard.
G. Beretta et al. / Analytica Chimica Acta 533 (2005) 185–191 189
date. Except for clover, acacia, and dandelion 1 whose AUC
values were fairly close to, though still significantly different
(P<0.05) from that of the sugar analogue, all the others
had much higher AUC values (Table 1). Similar ORAC
values have been reported by Gheldof et al. for American
buckwheat, acacia, and clover honeys [23].
4.5. Color intensity (ABS450)
The absorbance of a 50% (w/v) honey solution var-
ied from 25mAU for the pale-white honey (acacia) to
3413mAU for the dark-brown strawberry tree honey. This
marked difference might be a reliable index of the presence
of pigments with antioxidant activity (carotenoids, Maillard
reaction products) [24]. Alternatively it could be due to
a specific contaminating pigments arising from handling,
processing, and storage, and/or from biochemical reactions
during honey maturation which could lead to components
with no antioxidant activity.
4.6. Data analysis
The different parameters were analysed by a multivariate
approach. The original data set was re-normalized by an
autoscaling transformation since the values for the various
parameters are expressed in different units (Fig. 2). In
order to include in the data set the reference sample (sugar
analogue), which is inactive in the DPPH assay, IC50 values
were transformed into their reciprocal (IC−1
50 =1/IC50)so
the reference sample scores zero.
The correlation matrix (Table 2) showed a significant
correlation between all the variables. However, even small
differences between correlation coefficients must be care-
fully examined since they can provide useful information
on the antioxidant activity of honey. The scree plot (data
not shown) indicates that the first two principal components
account for 95% of the total variance. The other principal
components most likely absorb numerical noise and/or
Fig. 2. Autoscaling transformation of data for antioxidant markers (phe-
nol content, PC, FRAP, DPPH, ORAC values, and ABS450) for 14 honey
samples.
Table 2
Correlation matrix
Phenol
content FRAP ABS450 DPPH:
1/IC50
ORAC
Phenol content 1 0.885 0.933 0.918 0.868
FRAP 0.885 10.918 0.889 0.716
ABS450 0.933 0.918 10.884 0.731
DPPH: 1/IC50 0.918 0.889 0.884 10.861
ORAC 0.868 0.716 0.731 0.861 1
In bold (except in the diagonal) are reported the values at the level of signif-
icance, α= 0.050 (two-tailed t-test).
experimental error. The loadings plot (Fig. 3A) indicates
the direction of each original variable, and the scores plot
(Fig. 3B) the position of each honey sample in the new
experimental space of the two independent coordinates.
Fig. 3. Graph of loading plot (A) of antioxidant markers and scores plot (B)
of various honeys of different floral and geographical origin.
190 G. Beretta et al. / Analytica Chimica Acta 533 (2005) 185–191
5. Discussion
From this study (Table 1) and from the data reported in
literature [6,23] it seems that the same kind of honey, even
from different parts of the world, has similar antioxidant
power. Industrial or artisanal processing, handling, and
storage seem to be minor factors in affecting the antioxidant
capacity [6]. This leads us to conclude that the floral origin
is the major determinant in the antioxidant potency so we
established a tentative scheme of rationalization to compare
the results from the tests we made.
On the basis of the correlation matrix (Table 2), each co-
efficient was considered in order to establish the correlations
between different couples of assays. The highly significant
correlationbetween total phenol content andtotal antioxidant
activity (rPC/FRAP =0.885) indicates that the reducing power
of honey is due to phenolic/polyphenolic entities that can
reduce the Fe3+ to Fe2+ couple. Similarly, the high correla-
tion between phenols and DPPH activity (rPC/DPPH =0.918)
showsthatphenolicchemicalsgoverntheantiradicalpotency.
The same indication comes from ORAC values where the
antilipoperoxidantcapacity is correlated with thephenol con-
tent (rPC/ORAC =0.868). The close interdependence between
PC, FRAP, DPPH, and ORAC indicates that the antioxidant
capacity of the honeys is due to their phenolic constituents,
whichareabletointeractwithMo(VI)andFe(III)withaH/e−
transferring mechanism, and less to other chemical entities.
The lower correlation coefficient between FRAP and
ORAC arises from the anomalous ORAC behaviour of two
honeys (Africa 2 and 3, Table 2 and Fig. 2). Very likely, these
contain chemicals that can quench peroxy-radicals also by
additionreactions [25]. These substances might, for instance,
be nucleophilic thiols, strong nitrogen bases highly conju-
gated phenols (curcuminoids), able to entrap peroxy radicals
and form stable compounds [26]. The close correlations be-
tween honey color and phenol content (rABS450/PC =0.933),
total antioxidant activity (rABS450/FRAP =0.918), and ORAC
values (rABS450/ORAC =0.731), support the seminal ob-
servation by Frankel who noted, working only with one
test, DPPH, that color can at least partly reflect a honey’s
antioxidant capacity [27].
The correlations described can be interpreted in the
light of PCA. As reported in the loadings plot (Fig. 3A),
the PC1 direction coincides with that of the PC. Therefore
it is reasonable to assume that PC1 includes most of the
information (up to 89% of the total variance) due to the
phenolic chemicals detected by the different analytical
methods. The high loading values of FRAP, DPPH and
honey color variables confirm, according to multivariate
analysis, the major role of phenolic species in the antioxidant
capacity of honey. PC2 explains 7% of the total variance,
with the major contribution of ORAC (60%).
The score plot reported in Fig. 3B shows the antioxidant
behaviour of honey in the space of the two new variables
PC1 and PC2. Moving along PC1 from left to right in
the graph, we find different patterns of grouping with
low-antioxidant honeys (acacia, dandelion 1, and clover)
close to the sugar analogue while samples with intermediate
antioxidant activity (sulla, chestnut, chicory, dandelion 1,
and mountain multi-flora) separated and grouped in the
first quadrant. Strawberry tree honey, which had the highest
antioxidant activity, is quite far from the others. Buckwheat
and Africa 1 lie in an intermediate position. Africa 2 and
Africa 3 honeys are sharply separated from the others along
the PC2 axis, on account of their unusually high ORAC
values. Similarly, honeydew honey, the only one not from a
floral source, holds its own individual position between the
low- and high-antioxidant honeys. Honeydew is a sugar-rich
biological material produced from the exudates of trees and
plants with the aid of insects (family Aphididae), which
bees collect for honey production. Chemometric analysis
suggests that the chemical composition in antioxidants of
this honey sample may be different from floral honeys.
6. Conclusions
The aim of the work was to set up a practical analytical
approach for the standardization of antioxidant proprieties of
honey.
The indication that clearly emerges from this work is that
only from a combination of antioxidant tests, comparative
analyses, and chemometric evaluation can we obtain a solid
platform of information to characterize the antioxidant prop-
ertiesofhoneywithout losing some important oxidant events.
Among the chemometric tools, the score plot of PCA analy-
sis, which shows different patterns of grouping of the honey
samples, seems to be the one that gives an immediate and
comprehensive view of the antioxidant power linked to dif-
ferences in chemical composition.
The present study can provide the scientific community
with a reliable analytical support/confirmation of the bene-
ficial antioxidant-linked effects of honey. The findings can
also provide the phytochemist with basic information before
theexpensiveandtime-consumingeffortofidentificationand
characterization of the antioxidant components of honey.
Acknowledgements
The financial support for one of us, G.B., from Bottega
Verde (Biella, Italy) is gratefully acknowledged.
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