-
lysa
r
g De
ey
Received 10 February 2014Accepted 20 July 2014
ommon adulterationand other types of su-isbet, & Yavuz,
2007).honey is simulated bysuch as corn syrups,
Food Research International 64 (2014) 634646
Contents lists available at ScienceDirect
Food Research
l scontains maltose and sucrose at lower levels (Doner, 1977;
Doner &Hicks, 1982). It is accepted as a valuable product
because of its multiplebenets such as prebiotic (Sanz et al., 2005)
as well as nutritional and
high fructose corn syrups and invert syrups, which are
comparativelyinexpensive sweetening products (Swallow & Low,
1994). Addition offructose or industrial glucose results in a
change of the fructose/glucoselase, phosphatases) and vitamins
(ascorbic acid, niacin, pyridoxine,etc.) are among other minor
constituents present in natural honey(Alvarez-Suarez,
Gonzales-Paramas, Santos-Buelga, & Battino, 2010;Marghitas et
al., 2009). Although fructose and glucose, as the
predomi-nantmonosaccharides, exist in honeywith a percentage of
6085, it also
(Sivakeseva & Irudayaraj, 2002). The most cmethods are by
overfeeding of bees with sugarcrose or by adding saccharose (Guler,
Bakan, NIn addition, the natural carbohydrate prole ofusing some of
the simple and complex sugarsHoney, with its high nutritional and
benecial properties, is theoldest natural sweetening agent
(Ozdemir, Dagdemir, Ozdemir, &Sagdic, 2009). Honey is a
valuable source of rich nutritious compoundsfor the human body such
as sugars, macro and micro elements andbiologically active
substances (Smanalieva & Senge, 2009). Phenoliccompounds,
minerals, proteins, organic acids (gluconic acid, aceticacid,
etc.), free amino acids, enzymes (invertase, glucose oxidase,
cata-
(Zeina, Othman, & Al-Assad, 1996), anti-fungal (Molan,
1997), anti-bacterial and anti-inammatory activities (Doner, 1977;
Doner &Hicks, 1982). It is also used as an apitherapy agent due
to these charac-teristics (Ozdemir et al., 2009).
The cost of natural honeybee honey is much greater than that of
anyother sweeteners because of its high nutritional value and
unique avorcharacteristics; therefore producers tended to
adulterate honey withless expensive substances in order to decrease
the cost of honeyantioxidant characteristics (Tornuk et al.,
201
Corresponding author. Tel.: +90 212 383 4575; fax: +E-mail
address:[email protected] (M.T. Yilmaz).
http://dx.doi.org/10.1016/j.foodres.2014.07.0090963-9969/ 2014
Published by Elsevier Ltd.great attention due to its
anticarcinogenic (Al-Waili, 2004), antiviral1.
IntroductionAvailable online 27 July 2014
Keywords:HoneyAdulterationSaccharose and fructose
syrupsRheologyHPLC-RIDIn this study, natural honey was adulterated
with the addition of adulterants, namely saccharose and
fructosesyrups at a ratio of 0%, 10%, 20%, 30%, 40% and 50% by
weight. Steady, dynamic and creep tests were conducted,revealing
that the changes in the ow, viscoelastic and creep behavior of
natural honey were clear and remark-able. Syrup addition decreased
viscosity (), storage (G) and lossmodulus (G) values of the control
honey sam-ples. Deformation represented by the compliance (J(t))
values was more prominent in the adulterated honeysamples. In
addition, HPLC-RID analysis was conducted to determinemajor sugar
composition of the adulteratedsamples. Pearson's correlation test
indicated that there were signicant (P b 0.05; 0.01) correlations
betweensugar composition and rheology parameters, (viscosity), K, K
(intercepts for G and complex modulus (G),respectively) and 0
(viscosity of Maxwell dashpot), suggesting that K, K, K and 0 could
be prominent indica-tors for presence of saccharose or fructose
syrups added in natural honeywithin the studied concentration
levels.These results suggested that use of steady, dynamic and
creep analysis would be a novel and potential approachto detect
honey adulteration by fructose and saccharose syrups.
2014 Published by Elsevier Ltd.Article history:a b s t r a c ta
r t i c l e i n f oSteady, dynamic and creep rheological anadetect
honey adulteration by fructose andCorrelations with HPLC-RID
results
Mustafa Tahsin Yilmaz a,, Nevruz Berna Tatlisu a, OmeOsman
Sagdic a,d, Muhammet Arici a
a Yildiz Technical University, Chemical and Metallurgical
Engineering Faculty, Food Engineerinb Erciyes University,
Engineering Faculty, Food Engineering Department, 38039 Kayseri,
Turkeyc Bayburt University, Engineering Faculty, Food Engineering
Department, 69000, Bayburt, Turkd 'TBTAK MAM, Food Engineering
Institute, 41470, Gebze-Kocaeli, Turkey
j ourna l homepage: www.e3). Honey still attracts a
90 212 383 4571.sis as a novel approach toccharose syrups:
Said Toker a, Safa Karaman b, Enes Dertli c,
partment, 34210 Istanbul, Turkey
International
ev ie r .com/ locate / foodresratio, which has to be 11.2 in
natural honey (Puscas, Hosu, & Cimpoiu,2013). The ratio
differing from this value can mean that the honey isadulterated.
However, it is still difcult to understand and evaluatethe
adulterations in honey because of variations in honey
carbohydratesand their similarities with sugar syrup composition
(Kushnir, 1979),
-
635M.T. Yilmaz et al. / Food Research International 64 (2014)
634646which triggers the importance of method development for
quality con-trol of honey and detection of its adulteration.
Nomenclature
f frequency [Hz]G storage modulus [Pa]G loss modulus [Pa]G
complex modulus [Pa]G0 instantaneous shear modulus of the Maxwell
element
(Pa)G1 shear modulus of KelvinVoigt element (Pa)J creep
compliance (Pa1)JMAX compliance at the end of the creep test
(Pa1)JSM compliance pertaining to the Maxwell spring (Pa1)
viscosity [Pa s] angular frequency [rad s1]K intercept for complex
modulus [Pa]K intercept for storage modulus [Pa]K intercept for
loss modulus [Pa]R2 coefcient of determinationtan loss tangent
[dimensionless] shear rate [s1]50 viscosity at 50 s1 (Pa s)R (%)
percentage recovery shear rate (s1) shear stress (Pa)0 viscosity of
liquid lling the dashpot of the Maxwell el-
ement (Pa s)1 viscosity of liquid lling the dashpot of the
KelvinVoigt
element (Pa s)A great number of efforts have been exerted so far
to detect adul-teration in honey based on electrochemical analysis
(Gritzapis &Timotheou-Potamia, 1989), enzymatic methods (Le
Marec & Lesgards,1991), thin-layer chromatography (Pukl &
Prosek, 1990; Reiffov &Nemcov, 2006), carbon isotopy (White,
1992), ow injection analysis(Peris-Tortajada, Puchades, &
Maquieira, 1992), gas-chromatography(Carlsson, Karlsson, &
Sandberg, 1992), high-performance liquid chro-matography (Antoov,
Polakovi, & Ble, 1999; Bugner & Feinberg,1992),
anion-exchange liquid chromatography (Goodall, Dennis,Parker, &
Sharman, 1995; Swallow & Low, 1994), Fourier transform
in-frared spectroscopy (Sivakesava & Irudarayaj, 2001;
Sivakeseva &Irudayaraj, 2002), differential scanning
calorimetry (Cordella et al.,2002), mid-infrared near infrared
transectance spectroscopy (Kelly,Petisco, & Downey, 2006;
Sivakeseva & Irudayaraj, 2002), gas chroma-tographymass
spectroscopy (Ruiz-Matute, Soria, Martinez-Castro, &Sanz,
2007), high-performance anion exchange chromatography withpulsed
amperometric detection method (Cordella, Militao, Clement,
&Carbol-Bass, 2003; Morales, Corzo, & Sanz, 2008),
high-performancethin-layer chromatography (Puscas et al., 2013),
isotope ratio massspectrometry in combination with an elemental
analyzer (Tosun,2013) and low eld nuclear magnetic resonance
(Ribeiro et al., 2014).
Most of the aforementioned methods are based on
time-consumingchemical or enzymatic reactions requiring long
preparation steps andlaborious preliminary experiments as well as
expert operators.Therefore, alternative methods that would allow
faster and easierdetection of honey adulteration should be
continuously developedand tested. Accordingly, the EU Commission
has also tended to en-courage development of harmonized analytical
methods to permitthe verication for different honeys (Puscas et
al., 2013). In this re-spect, detection of adulteration based on
the changes in physicaland rheological properties of honey may be
an alternative and avery different approach considering the
aforementioned methods.Accordingly, the fructose/glucose ratio in
honey is a factor determin-ing the crystallization rate of honey,
thus directly affecting the rheo-logical, namely physical
properties of honey. Therefore, the use ofrheological methods can
be a novel and potential approach for detec-tion of honey
adulteration by fructose and saccharose syrups. Glu-cose tended to
crystallize more due to its lower solubility (Venir,Spaziani, &
Maltini, 2010). Glucose may crystallize as -D-glucosemonohydrate at
temperature ranges lower than 50 C (Venir et al.,2010). The other
two forms, namely, -D-glucose anhydrous and anhydrous forms, are
stable at the temperature range of 5080 Cand at temperatures above
80 C (Young, 1957). The transition tem-perature of glucose from its
monohydrate to anhydrous form isfound to be lower than 30 C when
saturated with fructose. In addi-tion, natural honeys exhibit
Newtonian behavior and their rheologi-cal properties are strongly
inuenced by temperature (Gmez-Diaz,Navaza, & Quintans-Riveiro,
2006; Kumar & Mandal, 2009; Yoo,2004). However, crystallized
honeys show non-Newtonian ow be-havior with yield stress and
thixotropy (Chen, Lin, Wu, & Chen,2009; Smanalieva & Senge,
2009). From these reports, it is clearthat the rheological
properties of honey are greatly inuenced bystorage temperature and
so resultant crystallization. Accordingly,storage temperature and
fructose/glucose (F/G) ratio are regardedto be determinants for
crystal size formed in the product (Lupano,1997). Honey samples
having F/G ratios more than 1.33 do not crys-tallize for a long
time (White, 1978), while those having less than1.11 ratio
crystallizes quickly (Smanalieva & Senge, 2009). These re-ports
also reveal a necessity to detect such adulterants in honeysstored
at different temperature levels. Therefore, temperaturesweep tests
should be also conducted to determine temperature de-pendency of
adulterated honey samples.
In the literature, no study has been conducted so far on
detectionof adulteration in honey based on its rheological changes.
This studywas undertaken to detect adulteration in natural honey by
saccha-rose and fructose syrups at different ratios (0, 10, 20,
30%, 40 and50%) on the basis of steady, dynamic and creep/recovery
rheologicalanalysis. In addition, HPLC-RID analysis followed to
determine thesugar composition of the adulterated honey samples in
order toconrm the rheological test results by nding possible
correlationsbetween sugar composition and rheological parameters of
the adul-terated honey samples.
2. Materials and methods
2.1. Materials
Control (natural) honey samples were collected from a local
marketin stanbul, Turkey. Saccharose and fructose were obtained
fromMerck(Merck, Darmstadt, Germany). The adulterants, namely,
saccharose orfructose syrups, were prepared by slowly adding 150 g
of saccharoseor fructose powder to 100 g of water, followed by
mixing the mixtureswith a magnetic stirrer at a constant speed.
Both syrup types were con-centrated to approximately 75 brix at 60
C. For preparation of adulter-ated honey samples, the prepared
syrups were added to natural honeysamples in relevant
concentrations (0, 10, 20, 30, 40 and 50%, w/w).The adulterated
honey samples were stirred in a temperature-controlled water bath
for 30 min at room temperature. Then, the sam-ples were centrifuged
for 3 min at 2500 rpm to remove impurities andwere stored at room
temperature until the analyses.
2.2. Physicochemical analyses
Color was analyzed by using an automatic colorimeter
(KonicaMinolta,model CM-5,Mississauga, ON, Canada) and theywere
recordedas the values of L, a, and b. L values measure the level
brightness(0100), a red to green (+ = red and = green), and b
yellow to
blue (+ = yellow and = blue). All analyses were carried out
in
-
636 M.T. Yilmaz et al. / Food Research International 64 (2014)
634646(nephelometric turbidity unit). The pH values were measured
with apH meter (WTW-Inolab, Weilheim, Germany) in a solution of 10%
(w/v) honey in distilled water at 25 C. An Aqualab water activity
(aw)meter (Decagon, Pullman, WA) was used for the determination
ofwater activity of the samples at 20 C. The brix values were
determinedusing an automatic refractometer (Reichert AR 700, USA)
at 20 C. Drymatter contents were measured by conventional drying
method as de-scribed (AOAC, 2000). Ash content was determined by
incinerating thesamples at 625 C in a mufe oven (Protherm, Ankara,
Turkey).
2.3. HPLC analysis
The major sugar (fructose, glucose and saccharose) compositions
ofthe samples were determined according to the method described
byJahanbin, Moini, Gohari, Emam-Djomeh, and Masi (2012). For this
pur-pose, 1 g of honey was dissolved in 9 mL of distilled water and
themix-ture was ltered using a 0.45 m syringe lter. The ltrate was
injectedto the HPLC (Agilent 1100, USA) equippedwith a refractive
index detec-tor (RID). An Agilent Zorbax carbohydrate analysis
column (5 m and4.6 mm 150 mm) was used and HPLC conditions were set
as follows:mobile phase, 80% acetone and 20%water; ow rate, 1.4
mL/min; injec-tion volume, 20 L and the column temperature was set
to be 25 C.Sugars were identied according to their retention times
by comparingwith sugar standards. The sugar concentration was
calculated by usingthe calibration curve of each sugar.
2.4. Rheological analysis
Steady shear, dynamic shear and creep and recovery analyses
werecarried out using a stress or strain controlled rheometer
(Anton Paar,MCR 302, Austria) equipped with a peltier system. All
of the experi-ments were performed by a parallel plate conguration
(diameter50 mm, gap 0.5 mm).
2.4.1. Steady shear analysisThe prepared samples were sheared in
the range of 0.1100 s1 at
25 C. A total of 25 data points were recorded at 10 s intervals
duringthe shearing. Each measurement was replicated three times in
two dif-ferent samples (each 1mL). The apparent viscosity was
determined as afunction of shear rate. The ow curves, shear stress
versus shear rate,were plotted by increasing shear rate. Obtained
data were tted to aNewtonian model. The related parameters for this
model werecalculated using the following equation:
n 1
where is the shear stress (Pa),is the shear rate (s1) and is the
vis-cosity of the sample.
2.4.2. Dynamic shear analysisThe amplitude sweep test was
performed at 1 Hz in the strain range
of 0.1100% to determine the linear viscoelastic region (LVR).
Frequen-cy sweep test was performed at 1% strain (determined by
amplitudesweep test) over a frequency range of 0.110Hz at 25 C.
Eachmeasure-ment was repeated three times with three
replications.
The viscoelastic parameters ofG (elastic or storagemodulus)
andG(viscous or loss modulus) are calculated using the following
equations(Steffe, 1996).
G0 G cos 2
triplicate. To measure the turbidity of the samples, a
turbidimeter(HACH, 2100 N, USA) was used and the results were
stated as NTUG G sin 3Complexmodulus,G, was used to characterize
the overall responseof the sample against the sinusoidal strain
(Gunasekaran & Ak, 2000).
G G0 2 G 2 1=2
4
Non-linear regression was applied to the plots of G and G
versusdata and the magnitudes of intercepts K, K and K, and R2 were
com-puted using the following equations (Kang & Yoo, 2008; Yoo
& Rao,1996).
G0 K 0 5
G K 6
G K 7
In order to observe the variation in the steady and dynamic
shear pa-rameters by temperature, a temperature sweep test was
conducted at ashear rate of 50 s1 and 1 Hz, respectively, at
temperature levels rang-ing between 5 and 50 C. Briey, temperature
sweep test was carriedout to determine dependency of the
viscoelastic parameters ontemperature.
2.4.3. Creep and recovery analysisThese tests were conducted at
constant stress (0.1 Pa within the
LVR). Deformation of the viscoelastic materials approaching a
steadystate in the time when the deformation rate remains constant
was thecritical point; after this time, the stress was applied and
then suddenlyremoved and analyzed for recoverable shear. In this
time, the stresswas instantly applied and maintained for 150 s, and
then released toallow sample recovery for a further 150 s. Each
measurement was re-peated three times with three replications.
Creep parameters were obtained from calculating a constant
stress() over time (t) and expressed using the creep compliance (J)
functionas represented by Eq. (8) in terms of shear deformation
():
J t t = 8
where () was the shear deformation.The Burger model, consisting
of Maxwell and KelvinVoigt models
associated with series, is widely used in the food industry to
provide in-formation about the internal structure of a product
(Dolz, Hernandez, &Delegido, 2008). The system deformation per
unit stress, namely com-pliance (J), is a function of time and
calculated using the following equa-tion (Eq. (9)) (Steffe,
1996):
J t 1G0|{z}Elastic
1G1
1 exp tG11
|{z}
Viscoelastic behavior
t0|{z}
Viscous flow
9
where J(t) is the overall compliance at any time t in the creep
phase, G0is the elasticmodulus of theMaxwell unit, 0 is the
viscosity of the liquidlling the dashpot of the Maxwell element (Pa
s), G1 is the shear mod-ulus of the KelvinVoigt unit, and 1 is the
viscosity of the liquid llingthedashpot of theKelvinVoigt element
(Pa s) (Barry, 1983). The valuesG0, G1, 0 and 1 can be used to
understand the internal structure of aproduct (Dolz et al.,
2008).
2.5. Method validation
Different honey sampleswere selected to analyze and test
themeth-od validation parameters. Some samples were marked as
control in
order to compare the results. The following parameters,
namely,
-
Table1
Physicochemicalprop
erties
andsugarcompo
sition
ofsamples.
Samples
Physicalprop
erties
Chem
icalprop
erties
Sugarcompo
sition
La
bTu
rbidity(N
TU)
pHa w
Brix
Dry
matter(%)
Ash
(%)
Fructose
(%)
Glucose
(%)
Saccharose
(%)
Adu
lterants
Saccharose
syrup
92.00
0.14
0.04
0.00
3.80
0.51
90.63
0.15
5.08
0.01
0.759
0.01
75.36
0.62
75.36
0.01
74.72
0.00
Fructose
syrup
95.81
0.00
0.66
0.00
2.17
0.01
23.30
0.10
4.13
0.01
0.661
0.01
74.72
0.13
74.72
0.01
75.36
0.00
Adu
lterated
honeysamples
HASa 0%(con
trolho
ney)
81.99
0.01
8.29
0.01
77.02
0.02
72.70
2.21
4.13
0.01
0.539
0.01
81.69
0.31
85.17
0.18
0.206
0.01
32.47
0.09
29.77
0.42
1.64
0.13
10%
81.33
0.01
6.21
0.01
73.05
0.01
104.0
2.65
4.01
0.01
0.574
0.01
79.77
0.87
84.56
0.41
0.283
0.03
33.34
0.23
32.31
0.25
9.49
0.26
20%
82.70
0.01
4.34
0.01
67.66
0.01
89.37
1.79
3.93
0.05
0.581
0.01
80.33
0.29
84.26
0.43
0.220
0.02
30.42
0.13
28.69
0.06
12.21
0.07
30%
84.66
0.01
2.63
0.01
61.71
0.01
53.07
2.59
3.92
0.08
0.634
0.01
77.69
0.39
83.31
1.04
0.202
0.01
29.45
0.71
27.81
0.42
16.72
0.22
40%
85.81
0.01
1.47
0.01
56.34
0.01
25.70
0.36
3.78
0.01
0.643
0.02
78.26
0.25
83.40
0.58
0.193
0.01
26.45
0.06
24.04
0.22
22.65
0.01
50%
87.32
0.02
0.17
0.02
47.83
0.01
21.80
1.58
3.18
0.01
0.692
0.02
77.55
0.32
82.37
2.24
0.142
0.01
23.13
0.49
21.73
0.27
33.07
0.08
HAFa 0%(con
trolho
ney)
81.99
0.01
8.29
0.01
77.02
0.02
72.70
2.21
4.13
0.01
0.539
0.01
81.69
0.31
85.17
0.18
0.206
0.01
32.47
0.09
29.77
0.42
1.64
0.13
10%
77.11
0.01
5.63
0.01
42.13
0.02
38.30
1.47
3.93
0.02
0.567
0.01
80.66
0.08
83.93
0.22
0.211
0.03
35.71
0.62
28.72
0.56
1.59
0.08
20%
78.06
0.01
4.47
0.02
41.13
0.01
24.10
0.10
3.81
0.04
0.593
0.01
79.85
0.59
82.46
0.19
0.186
0.01
37.54
0.37
25.63
0.32
1.74
0.01
30%
79.87
0.01
3.05
0.02
39.79
0.01
22.37
0.47
3.81
0.05
0.607
0.01
78.41
0.39
82.54
0.39
0.164
0.01
40.55
0.65
22.66
0.33
1.41
0.02
40%
81.09
0.01
1.94
0.02
37.86
0.01
17.70
0.00
3.74
0.02
0.619
0.02
78.46
0.21
81.59
0.19
0.122
0.01
43.16
0.56
19.06
0.48
1.44
0.02
50%
82.73
0.01
0.79
0.01
35.21
0.01
16.53
0.41
3.59
0.01
0.624
0.02
77.63
0.25
84.17
0.12
0.104
0.00
44.44
0.92
15.34
0.44
0.92
0.01
aHASandHAFweretheadulteratedho
neysamples
withsaccharose
andfructose
syrups,respectively.
637M.T. Yilmaz et al. / Food Research International 64 (2014)
634646repeatability, sensitivity and linearity, were used to
validate the analyt-ical methods.
2.6. Statistical analysis
SPSS Statistics (SPSS Statistics 17.0, Armonk, NY, USA) was
usedto conduct ANOVA to show the effect of adulterant levels on
steadyand dynamic shear parameters as well as to perform validation
tests(P b 0.05; 0.01). Bivariate correlations between sugar
compositionand rheology parameters of adulterated honey samples
were analyzedby Pearson's test using Minitab 14.0 software.
Principal componentanalysis (PCA) was performed using XLSTAT
software (XLSTAT, 2008,Addinsoft, New York, NY) to categorize the
honey samples based ontheir sugar composition and rheological
parameters.
3. Results and discussion
3.1. Physicochemical properties
Table 1 shows the physicochemical properties of
adulterants(saccharose and fructose syrups), HAS (adulterated honey
sampleswith saccharose syrup) and HAF (adulterated honey samples
with fruc-tose syrup). As can be seen, the adulterants were
brighter (L values)than the control honey sample, which was
expected since saccharoseand fructose syrups were brighter than
honey and the L value generallyincreasedwith the addition of these
syrups to honey. On the other hand,the control honey samplewas
redder (a values) and yellower (b values)than the adulterants.
Expected resultswere generally observed for the L,a and b values
that were between those values of the adulterants andthe control
honey sample. However, such trends were not observed inthe
turbidity, but these values generally decreased depending on the
ad-dition of the adulterants. In pH values, a consistent trendwas
observed,decreasing linearly with adulterant addition. Expected
results were ob-served in the aw valueswhich increasedwith the
addition of adulterantshaving higher aw values. For brix, dry
matter and ash content values, noclear trend was observed with the
adulterant addition.
3.2. HPLC analysis
Fig. 1 shows the chromatograms of the standard mixture ofsugars
and adulterated honey samples with different levels
ofsaccharose/fructose syrups using an Agilent Zorbax
carbohydrateanalysis column operating with 80% acetone and 20%
water asmobile phase at 25 C. Themethod allowed separation of all
analytesthat could be detected by an RID detector. The internal
standards(fructose, glucose and sucrose) were eluted at 6.32, 7.91
and 14.99 min,respectively, without interfering with the elution of
the other standards.For each compound, a linear regression was
performed and the re-gression equations were y = 0.007x 224.5, y =
0.0069x + 2398.8and y= 0.0072x 534.2 for fructose, glucose and
sucrose standards,respectively. The determination coefcients (R2)
were N0.993, indicat-ing that there was a linear relationship
between the chromatographicresponse areas and the concentrations
for all the compounds. The in-strument detection limit (IDL) for
each compound was measuredbased on the signal to noise ratio of 3
and ranged between 20 and160 mg/L.
Table 1 shows themajor sugar composition of adulterants and
adul-terated honey samples. As can be seen from the table, the HPLC
resultsreected the expected trends in the change of sugar
composition. Thesaccharose content of the control honey sample
increased with the in-crease in added saccharose level and the
saccharose content of HAS lin-early increased as the saccharose
level increased. This was also the casefor the HAF with the
fructose content linearly increased with fructoseaddition.
Regarding the fructose content of HAS and the saccharose con-tent
of HAF, theywere observed to decreasewith increase in
saccharose
or fructose level, respectively. However, it should be also
noted here
-
se)
638 M.T. Yilmaz et al. / Food Research International 64 (2014)
634646Fig. 1. HPLC-RID chromatograms for peaks of standards
(fructose, glucose and saccharothat no clear trend was observed in
the fructose contents of HAS andsaccharose contents of HAF although
these contents were determinedto show a generally decreasing trend.
The possible reason could be at-tributed to the fact that the
saccharose might have been inverted withthe help of acids and
enzymes (Tosun, 2013) naturally present inhoney in the course of
time in both cases, namely HAS and HAF.
3.3. Steady shear properties
Table 2 shows the Newtonianmodel parameters for adulterants
andadulterated honey samples with different levels of saccharose
andfructose. All samples (including control honey) had Newtonian
owbehavior. It is well known that natural honeys exhibit Newtonian
owbehavior (Juszczak & Fortuna, 2006; Karaman, Yilmaz, &
Kayacier,2011; Kumar & Mandal, 2009; Lazaridou, Biliaderis,
Bacandritsos, &Sabatini, 2004; Yoo, 2004). From the table, it
is also clear that saccharoseand fructose syrup addition
signicantly (P b 0.05) decreased theviscosity of the control
(natural) honey sample and viscosity decreased(P b 0.05) as the
levels of these adulterants increased. These resultswere also
evident from those presented in Fig. 2 which shows theshear stress
data as a function of shear rate for adulterants and adulter-ated
honey samples. Shear stress values of all the samples linearly
in-creased with increase in shear rate, indicating that all samples
showedNewtonian ow behavior (Rao & Tattiyakul, 1999; Sikora,
Kowalski,Tomasik, & Sady, 2007; Steffe, 1996). The results in
Fig. 2 also provedthat shear stress values of the adulterated honey
samples decreased asthe level of adulterants, namely, saccharose
and fructose syrups, in-creased, revealing that syrup addition
decreased the viscosity of naturalhoney. This result was expected
since viscosity of saccharose and fruc-tose syrups was found to be
0.297 Pa s and 1.265 Pa s, respectively,which were lower than that
of the control honey sample (6.531 Pa s).These results clearly
suggest that adulteration in natural honey can bedetected by steady
shear rheological analysis.and adulterated honey samples with
different levels of saccharose and fructose syrups.Fig. 3 shows the
temperature sweep test results indicating the effectof temperature
(from 5 C to 50 C) on apparent viscosity at shear rate50 s1 (50)
values of adulterants and adulterated honey sampleswith different
levels of fructose and saccharose syrups. As can be seen,50 values
of all the samples linearly decreased as the temperaturelevel
increased. The thermal energy of the molecules and the
intermo-lecular distances between them increasedwith increasing
temperature,which results in reduction of intermolecular forces;
therefore viscosityof the samples decreases (Arslan, Yener, &
Esin, 2005; Hassan &Hobani, 1998; Holdsworth, 1971). But, it
should be noted here that
Table 2Newtonian model parameters dening ow behavior of
samples.
Samples (Pa s) R2
AdulterantsSaccharose syrup 0.297 0.999Fructose syrup 1.265
0.999
Adulterated honey samples
HAS
0% (control honey) 6.531a 0.99810% 5.650b 0.99620% 3.704c
0.99830% 2.972d 0.99840% 2.239e 0.99850% 2.019f 0.999
HAF
0% (control honey) 6.531a 0.99810% 4.028b 0.99820% 2.462c
1.00030% 2.067d 0.99740% 1.598e 0.99750% 1.085f 0.999
Different lowercase letters show differences (P b 0.05) between
the adulteration levels.HAS and HAF were the adulterated honey
samples with saccharose and fructose syrups,respectively.
-
639M.T. Yilmaz et al. / Food Research International 64 (2014)
634646temperature did not inuence the trend of 50 values to
decrease as theadulterant level increased, suggesting that honey
adulteration can bedetected in honeys within a temperature range
between 5 C and50 C. Furthermore, steady shear analysis showed the
great deviationsof the ow curves from those of control and
adulterated honey sampleswith 10% of saccharose and fructose syrups
(Fig. 3). This result revealedthat it was possible to detect
adulteration in honey even at the 10% levelwithin a temperature
range of 520 C.
3.4. Dynamic shear properties
G (storagemodulus) versus G (loss modulus) values of
adulterantsand adulteratedhoney samples are shown in Fig. 4. As can
be seen theGandG values of all the samples increasedwith frequency.
But, attentionshould be drawn to the fact that the G values showed
non-linear incre-ment while the G values exhibited a linear
increment. This means that,in dynamic rheological characterization,
G values should be taken intoconsideration to reach a conclusion
for viscoelastic properties of adul-terated honey samples. Another
point that should be taken into accountwas that magnitudes of the G
values were remarkably higher thanthose of the G values, indicating
that both adulterants and adulterated
Fig. 2. Shear stress versus shear rate data for adulterants and
adulterated honey samples(Control, natural honey; F, fructose
syrup; S, saccharose syrup).honey samples had viscous nature rather
than elastic. In addition, nocross-point of G and G was observed
along the whole frequencyrange studied. From a structural point of
view, it can be stated that thehoney samples exhibited liquid-like
behavior because G values werehigher than G values.
G, G and G values were subjected to non-linear regression as
afunction of frequency (Eqs. (5), (6) and (7)) to calculate
themagnitudesof intercepts K, K, and K alongwith their R2 values.
Based on the highR2 values (Table 3), it was possible to say that
theNewtonianmodel wassuccessful in modeling the dynamic shear
behavior of adulteratedhoney samples. Table 3 also shows the effect
of adulterants onthe dynamic shear behavior of samples. It is seen
that K and K valueslinearly decreased (P b 0.05) as the adulterant
level increased. This de-crease (P b 0.05) was also the case for
the K values, but it was non-linear. Given that the indices for
complex modulus, K, represent totalresistance to deformation of a
material considered to be elastic solid, itis possible to say that
the control honey had the highest total resistanceto deformation
and this resistance decreased with adulterant addition.These
results suggested that K would potentially be a good indicatorto
detect adulteration at the levels ranging between 10 and 50%.
Detection of honey adulteration is of great concern to the food
indus-try; therefore, numerous techniques have been developed and
appliedso far. Previously, traditional methods were used to detect
impurities,but they are now rarely used because of their poor
specicity(Hudson, 1942; Seoane, Moresco, & Sansn, 2008). For
this purpose, in
Fig. 3. Temperature sweep tests indicating the effect of
temperature on apparent viscosityvalues (50) at a shear rate of 50
s1 of adulterants and adulterated honey samples (Con-trol, natural
honey; F, fructose syrup; S, saccharose syrup).
-
640 M.T. Yilmaz et al. / Food Research International 64 (2014)
634646recent years, many analytical methods and techniques have
been usedto detect honey adulteration. These methods were based on
high per-formance liquid chromatography (HPLC) with mass
spectrometry(MS) (Cheng, Tsai, & Chang, 2006), coupled with
several systems suchas refractive index (RI) detection (Park, Yang,
Kim, & Kim, 2012), pulsedamperometric detection (PAD) (Morales
et al., 2008), evaporative lightscattering detection (ELSD) (Zhou
et al., 2014) and UV detection (Yan &Evenocheck, 2012). Other
chromatographic techniques including gaschromatographymass
spectrometry (GCMS) (Ruiz-Matute et al.,2007) and high-performance
thin layer chromatography (HP-TLC)(Puscas et al., 2013) have been
tested and used in this purpose. Howev-er, some problems have been
faced; for example, the specicity of de-tectors is limited by their
high sensitivity to ambient temperature,pressure and ow-rate
changes, and poor signal-to-noise ratio, whichmight lead to false
results. In our study, detection of adulteration was
Fig. 4. G (storage modulus) and G (loss modulus) values of
adulterants and adulterated honefrequency.not based on any
sensitive detector; so any risk stemming from suchchanges was not
the case, which would enable the analyst to avoidfrom such
problems. Another advantage is that the rheological testsare not
time-consuming, are not expensive and do not require remark-able
analytical skills.
Detection of honey adulteration has also been achieved by
stablecarbon isotopic ratio by mass spectrometry (SCIR) (Cengiz,
Durak, &Ozturk, 2014; inar, Eki, & Cokun, 2014; Guler et
al., 2014; Simsek,Bilsel, & Goren, 2012). However, despite some
potential advantages,some problems have also been reported by
Cengiz et al. (2014) whopointed out the homogeneity problem of the
sample. They also statedthat even if the honey samples could be
ltered to achieve homogeneitybefore analysis by an IRMS system, in
this time, the homogeneity of theextracted protein would be a
common problem. Therefore, this tech-nique will require effective
clean-up procedures in order to obtain a
y samples (Control, natural honey; F, fructose syrup; S,
saccharose syrup) as a function of
-
pure protein extract. The second problem is that the SCIRA
technique istime-consuming, destructive, and expensive and requires
considerableanalytical skills that are hard to meet in routine
monitoring analysis
(Li, Shan, Zhu, Zhang, & Ling, 2012). On the other hand, in
detection ofadulteration based on rheological analysis techniques,
neither anyclean-up procedure nor extension time, expensive systems
and greatanalytical skills are required, which would facilitate and
accelerate thedetection procedure.
In addition, other methods have been developed to detect
honeyadulteration based on thermal analysis (Cordella et al.,
2002), capillaryelectrophoresis (CE) (Khandurina & Guttman,
2005) and nuclear mag-netic resonance (Cotte et al., 2007).
Although it has been demonstratedthat these methods could be used
to assess the adulteration of honey,similar disadvantages as SCIR
would also be the case. Therefore, faster,user-friendly and
cost-effective analytical techniques should be devel-oped to detect
adulteration in honey. In this respect, several other tech-niques
based on spectroscopy have also been recently offered for
fasterdetection of honey adulteration. Among them aremiddle
infrared (MIR)(Gallardo-Velzquez, Osorio-Revilla, Zuiga-de, &
Rivera-Espinoza,2009) and near infrared (NIR) spectroscopy (Chen et
al., 2011; Zhuet al., 2010), high-resolution nuclear magnetic
resonance (HR-NMR)(Bertelli et al., 2010), Raman spectroscopy (Li
et al., 2012) andFourier-transform Raman spectroscopy using
canonical variate analysis(CVA) (Paradkar & Irudayaraj, 2001).
Although the spectroscopicmethods have some advantages with respect
to speed, simplicity andcost-effectiveness, the targeted compounds
to be detected have identi-cal molecular structures, which may
result in unsatisfactory results in
Table 3Newtonian model parameters describing dynamic shear
properties of samples.
Samples G = K() G = K() G = K()
K R2 K R2 K R2
AdulterantsSaccharose syrup 0.026 0.937 1.268 0.999 1.269
0.999Fructose syrup 0.027 0.890 0.291 0.999 0.292 0.999
Adulterated honey samples
HAS
0% (control honey) 0.046b 0.969 6.367a 0.999 6.367a 0.99910%
0.041c 0.962 5.811b 0.999 5.811b 0.99920% 0.039d 0.905 4.397c 0.999
4.397c 0.99930% 0.033e 0.918 3.594d 0.999 3.594d 0.99940% 0.051a
0.941 2.837e 0.999 2.838e 0.99950% 0.003f 0.054 2.234f 0.999 2.234f
0.999
HAF
0% (control honey) 0.046b 0.969 6.367a 0.999 6.367a 0.99910%
0.052a 0.939 4.382b 0.999 4.382b 0.99920% 0.042c 0.967 2.696c 0.999
2.697c 0.99930% 0.028d 0.919 2.039d 0.998 2.039d 0.99840% 0.018e
0.951 1.567e 0.999 1.567e 0.99950% 0.021f 0.958 1.111f 0.999 1.111f
0.999
Different lowercase letters show differences (P b 0.05) between
the adulteration levels.HAS and HAF were the adulterated honey
samples with saccharose and fructose syrups,respectively.
641M.T. Yilmaz et al. / Food Research International 64 (2014)
634646Fig. 5. Compliance values (J(t)) as a function of time for
adulterants and adulterated honeysamples (Control, natural honey;
F, fructose syrup; S, saccharose syrup).terms of reaching clear
decisions (Cengiz et al., 2014). On the otherhand, detection of
adulteration by rheological tests is not directlybased on detection
of molecular structure, which will provide a greatadvantage to an
analyst in case adulteration would be detected inhoney samples
adulteratedwith sugars havingmolecules with
identicalstructures.
Given all the pros and cons of the reported techniques, some
chemo-metric approaches seem to be useful in detection of honey
adulteration(Cai et al., 2013). Therefore, as reported by Bogdanov
and Martin(2002), the chemometric analysis will not be useful for
detection ofadulteration in unioral honeys using routine quality
parameters asthere is a great variation of parameters in polyoral
honeys. Chemomet-ric detection is based on different parameters
such aswater, proline, ashcontent, electrical conductivity, acidity
(free and lactone), pH, HMF, di-astase and sugars. However, these
parameters change depending on thebotanical origin of honeys, which
makes the method practically ques-tionable. In addition, the fact
that some parameters such as HMF,
Table 4Burger model parameters dening creep behavior of
samples.
Samples Burger model parameters
G0 106 (Pa) 0 (Pa s) G1 (Pa) 1 (Pa s) R2
AdulterantsSaccharose syrup 0.7 1.3 0.5 34 0.999Fructose syrup
0.4 0.3 193 5757 0.999
Adulterated honey samples
HAS
0% (control honey) 5 7.0a 19 190 0.99910% 25 6.0b 29 43 106
0.99920% 7 5.0c 26 247 0.99930% 11 4.0d 14 194 0.99940% 7 4.0d 8 73
0.99950% 31 2.0e 30 70 106 0.999
HAF
0% (control honey) 5 7.0a 19 190 0.99910% 0.0003 5.1b 1 56
0.99920% 1 3.0c 2 80 0.99930% 12 2.0d 14 254 0.99940% 0.002 1.6e
212 2234 0.99950% 0.006 1.1f 1152 11,340 0.999
Different lowercase letters show differences (P b 0.05) between
the adulteration levels.HAS and HAF were the adulterated honey
samples with saccharose and fructose syrups,
respectively.
-
diastase and content of individual sugars are storage- and
heat-dependent (Bogdanov & Martin, 2002) should be taken into
account.
In summary, majority of the aforementioned methods showgood
precision, accuracy, and reliability; however, they are
time-consuming, subjective, expensive and component-dependent and
re-quire complicated pretreatments and long experimental steps as
wellas considerable analytical skills. Therefore, it is essential
to developfast, simple and cost-effective analytical methods to
detect and quantifyadulterations in honey. In this respect,
detection of adulteration basedon rheological methods might be a
promising approach in terms ofavoiding such disadvantages and
problems.
3.5. Creep and recovery properties
In this study, creep and recoverymeasurements were conducted
be-cause highly concentrated sucrose solutions like
saccharose/fructose adulterated honey samples showed no consistent
trendwith increasing
adulterant level, which means no clear effect of adulterants on
elastic
terant level on the viscosity represented by the Maxwell dashpot
(0)
y (s
amic shear parametersb Burger model parametersc
K K G0 0 G1 1
.684 0.938 0.938 0.367 0.934 0.071 0.425
.587 0.907 0.907 0.238 0.873 0.179 0.314
.750 0.953 0.953 0.544 0.980 0.041 0.552
.970 0.959 0.959 0.137 0.815 0.675 0.684
.971 0.896 0.896 0.168 0.871 0.798 0.806
.886 0.683 0.683 0.013 0.810 0.824 0.829
dynamic and creep) parameters were signicant.
d G (complex modulus), respectively.lus of KelvinVoigt unit; 1:
viscosity of KelvinVoigt dashpot.s, respectively.
Table 6Results of the PCA analysis using data obtained from
physicochemical and rheologicalanalyses of the samples.
Principal component Eigenvalues Explained variance
For PC Cumulative Variance (%) Cumulative
PC1 11.257 11.257 56.283 56.283PC2 5.002 16.259 25.008 81.291PC3
1.373 17.632 6.864 88.155PC4 1.145 18.777 5.724 93.879PC5 0.513
19.290 2.565 96.444PC6 0.406 19.696 2.031 98.474PC7 0.154 19.850
0.772 99.247PC8 0.066 19.916 0.330 99.576PC9 0.064 19.980 0.320
99.897PC10 0.021 20.001 0.103 100.00
642 M.T. Yilmaz et al. / Food Research International 64 (2014)
634646syrup and honey might be in a metastable state, having a
tendency tocrystallize (Quintas, Brando, Silva, & Cunha, 2006).
Therefore, a colli-sion between the molecules is promoted by
shearing. These results innucleation and subsequent crystal growth
(Hartel, 1993; Shastry &Hartel, 1996), which limit the use of
steady-state ow measurementsconducted to characterize rheological
properties of such solutions. Tobe more precise, a faster
crystallization occurs, leading a change in therheological behavior
due to the increasing shear applied during themeasurements (Quintas
et al., 2006). Therefore, in addition to steadyand dynamic shear
measurements, creep and recovery tests were alsofollowed in this
study to conrm the other rheological test results.
3.5.1. Creep phaseThe creep test results for the values of
compliance J= / as a func-
tion of timewere displayed in Fig. 5where the effects of
adulterant levelon the creep behavior of adulterated honey samples
can be seen in atime interval between 0 and 150 s. The recovery
phase in Fig. 5 corre-sponding to the time interval of 150 t 300 s
will be discussedlater in the recovery phase section. Table 4
indicates the values of G0,G1, 0 and 1 and the related
determination coefcients (R2 values).The R2 values higher than
0.999 in all cases indicated that the tting ofJ = f(t) in the
interval 0 t 150 s could be successfully done basedon the Burger
model (Eq. (9)) for the adulterants and adulteratedhoney samples as
affected by different levels of adulterants.
G0, G1, 0 and 1 values reect the structure of any food system
anddecrease in these values shows its weakened structure; namely a
de-crease in the shear moduli and viscosity of the elements present
in theBurger model. G0, the instantaneous shear modulus, represents
a mea-sure of elastic strength on the bonds making up the
interfacial networkstructure (Lobato-Calleros, Aguirre-Mandujano,
Vernon-Carter, &Snchez-Garca, 2000). As can be seen in Table 4,
G0 values of the
Table 5Pearson correlation coefcients (r) between sugar
composition (HPLC results) and rheolog
Adulterated honey samples Sugar composition Rheology
parameters
Steady shear parametera Dyn
K
HASd Fructose 0.881 0Glucose 0.848 0Saccharose 0.909 0
HAFd Fructose 0.939 0Glucose 0.864 0Saccharose 0.622 0
In bold, correlations between the sugar composition (HPLC
results) and rheology (steady,a : apparent viscosity.b K, K and K:
magnitudes of intercepts for G (storage modulus), G (loss modulus)
anc G0: elastic modulus of Maxwell unit; 0: viscosity of Maxwell
dashpot; G1: shear modud HAS and HAF were the honey samples
adulterated with saccharose and fructose syrup P b 0.05.
b 0.01.Pparameter was clear; namely, adulterant addition could
be revealedby the 0 values which decreased (P b 0.05) as the
adulterant level in-creased (Table 4). In addition, Fig. 5 shows
the variation of the shearcreep and recovery compliance J(t) with
respect to the adulterantlevel, indicating that the adulterated
honey sampleswith higher saccha-rose and fructose syrups exhibited
higher J(t) values during creep andrecovery. It can be said based
on these results that adulterant additioninduced large deformation
in the viscoelastic nature of honey; thus,weakening its internal
structure for the same applied stress. These re-sults suggested
that viscosity represented by the Maxwell dashpot(0) can be a good
indicator of saccharose or fructose adulteration inhoney.
3.5.2. Recovery phaseThe recovery analysis results indicated
that the samples reached the
maximum deformation (JMAX) after 150 s of stress application.
Thestress applied was removed at the time when was equal to 0,
andthen, the compliance values J = f(t) were measured at a duration
of150 s (Yilmaz, Karaman, Cankurt, Kayacier, & Sagdic, 2011).
Fig. 5 alsoindicates the experimental results for the recovery
phase of the adulter-ants and adulterated honey samples in a time
interval between 150 and
teady, dynamic and creep) parameters of adulterated honey
samples.strength on the bonds making up the interfacial network
structure ofhoney. This was also the case for the G1 and 1 values,
exhibiting greatuctuations with adulterant level. These results
revealed that G0, G1,and 1 cannot be clear indicators to understand
if honey would be de-formed by addition of the adulterants and how
the internal structureof adulterated honey would be. In other
words, these creep parameterscould not be used to detect the
potential presence of adulterants, name-ly saccharose and fructose
syrups in honey. However, the effect of adul-
-
643M.T. Yilmaz et al. / Food Research International 64 (2014)
634646300 s with changing adulterant levels. As can be seen in Fig.
5, the adul-terants showed a Newtonian behavior, with a linear
response of strainduring the force application and no recovery was
observed after theforce was removed, which is typical of Newtonian
uids. Consistent re-sults were reported by Quintas et al. (2006)
who observed no recoveryfor an 82.90% sucrose solution. As far as
the adulterated honey sampleswere concerned, similar situation was
the case; namely, no recoverywas observed. Furthermore, this
situation did not change with in-creased level of adulterants;
however, the recovery start point increasedas the adulterant level
increased (Fig. 5). From these results, it can bededuced that the
effect of adulteration was clear, changing the creeprecovery
behavior of natural honey, and easily deforming the honeystructure
that could be immediately detected by creeprecovery analy-sis.
These results would be promising in developing an alternative
ap-proach for detection of such adulterants in honey.
3.6. Correlations between sugar composition and rheology
parameters
Pearson's test was used to analyze correlations between sugar
com-position and rheology parameters of adulterated honey samples.
InTable 5, the analysis results were presented. Signicant (P b
0.05;0.01) negative and positive correlations were found between
sugarcomposition and rheology parameters. These parameters were
(vis-cosity), K, K (magnitudes of intercepts for G and G,
respectively)and 0 (viscosity of Maxwell dashpot), proving that ,
K, K and 0could be indicators for the presence of saccharose or
fructose syrups innatural honey within the studied concentration
levels ranging between10 and 50%.
Fig. 6. Score plots of established PCs (Control, natura3.7. PCA
analysis
PCA was applied to classify the control and adulterated honey
sam-ples based on physicochemical and all of the rheological
results, namelysteady, dynamic and creep/recovery results.
According to the PCA re-sults, four different PCs were established
to explain the total variabilityof physicochemical and rheological
properties of the samples. Table 6shows the Eigen values and
variance value of each PC. As seen, fourPCs were adequate for
explanation of variability due to their Eigenvalue higher than
unity. PC1, PC2, PC3 and PC4 accounted for 56.283%,25.008%, 6.864%
and 5.724% of the total variability, respectively, in thedata set.
In other words, 93.879% of the total variance in the data setcan be
satisfactorily described by these four PCs.
Larrigaudiere,Lentheric, Puy, and Pinto (2004) reported that the
percentage higherthan 70% is considered as sufcient for explanation
of variability; there-fore, in the present study established
PCswere adequate to classify con-trol honey and adulterated honey
samples with respect to theirphysicochemical and rheological
properties.
Score plots of the PCs are presented in Fig. 6 inwhich PC1PC2,
PC1PC3 and PC1PC4 plots are shown. As seen from the gure, the
controlhoney sample and the sample adulterated with 10% fructose
were clus-tered on the bottom right quadrant of the PC1PC2 plot due
to their a,brix, pH and K values, indicating that these were among
the rheologicalparameters which could not be used for detection of
honey adulterationwith 10% concentration of fructose. The other
fructose adulteratedhoney samples were located on the bottom left
quadrant of the PC1PC2 plot, which might have resulted from the
fructose concentrationand G1 value calculated from the creep data.
As seen also in Fig. 6,honey samples adulterated with saccharose
syrups in concentrations
l honey; F, fructose syrup; S, saccharose syrup).
-
sponsible for this clustering. According to the PCA results, it
was seenthat the magnitudes of the K, K, 0 and rheological
parameters
3.8. Method validation
ity
sitiv
trol
31
75
20SD 1.588 1.184 3.366 0.025 0.046 1.303
27
962
bet
644 M.T. Yilmaz et al. / Food Research International 64 (2014)
634646In addition to conrmation of the rheological methods with
HPLC-RID results by Pearson correlation analysis, the methods were
also vali-dated with the following validation parameters.
3.8.1. RepeatabilityThe repeatability of honey samples was
calculated using twelve suc-
cessive measurements and expressed as the percent relative
standardcould be used for detection of adulteration in saccharose
adulteratedhoney samples. Honey samples adulterated with saccharose
in concen-trations of 40% and 50% were clustered on the left
quadrant of the PC1PC2 plot due to their saccharose content and L
and 1 values.of 10%, 20% and 30% were clustered on the top right
quadrant of thePC1PC2 plot. Turbidity and b values, ash and glucose
contents,among the other rheological parameters K, K, 0 and values
are re-
RSD% 0.03 1.20 1.09 0.10 0.45 a (Pa s) Mean 8.331 8.139 8.068
7.318 2.855 8.50
SD 0.253 1.401 1.153 0.865 0.110 0.20RSD% 0.03 0.17 0.14 0.12
0.04 a
JMAX (Pa1) Mean 16.913 14.097 26.491 20.715 45.431 13.2SD 4.687
6.479 10.899 6.814 6.488 1.56RSD% 0.28 0.46 0.41 0.33 0.14 b
adFor each parameter tested and sugar type, different lower case
letters show differencesTable 7Validation of rheological analysis
to detect honey adulteration by repeatability and sensitiv
Parameters tested Repeatability Sen
Control Saccharose Fructose Con
10% 50% 10% 50%
(Pa s) Mean 7.267 6.592 3.645 5.905 2.339 7.25SD 0.176 0.257
0.211 0.263 0.115 0.17RSD% 0.02 0.04 0.06 0.04 0.05 a
G (Pa) Mean 0.369 0.990 5.169 0.246 0.100 0.33SD 0.170 1.184
3.366 0.025 0.047 0.06RSD% 0.46 1.20 0.65 0.10 0.47 a
G (Pa) Mean 52.346 0.990 3.093 0.246 0.102 53.4deviation (RSD%).
The RSD% values were calculated (1) to range be-tween 0.04 and 0.06
for values in 10 and 50% saccharose and fructoseadulteration, (2)
to be 0.10 for G and G values in 10% fructose adulter-ation, (3) to
range between 0.04 and 0.17 for values in 10 and 50%saccharose and
fructose adulteration and (4) to be 0.33 for JMAX valuesin 10%
fructose adulteration (Table 7). Such low RSD% values indicatedthe
repeatability of the rheological parameters in detection of
honeyadulteration at such concentrations. However, the data
obtained forthe and parameters were more repeatable.
3.8.2. Sensitivity (LOD)Limit of detection (LOD) or detection
limit is the lowest concentra-
tion level that can be detected to be statistically different
from a control(99% condence). In this study, ANOVA was performed to
differentiatebetween the sugar concentrations, thus to nd the
lowest concentrationlevel at which the adulteration could be
detected. Table 7 shows theANOVA test results. Based on the ANOVA
test results, saccharose adul-teration could be clearly detected by
parameter at 6% and by G and parameters at 4%. Regarding fructose
adulteration, it could be clearlydetected by , G and parameters at
4%. Thus, the LOD was generallydetermined to be 4%. Based on our
results, these rheological parameterscan detect adulteration ratio
greater than 4%.3.8.3. LinearityIn this study, the rheological
method linearity was based on four
concentration levels between 20% and 50% of sugar adulteration.
Thelinearity was determined by preparing honey samples
adulteratedwith different saccharose and fructose concentrations.
The determina-tion coefcients (R2) and linear regression equations
are presented inFig. 7. For , G and parameters, high determination
coefcients(Fig. 7)were obtained, indicating that therewas exact
linearity betweenthe determined adulteration ratios and these
parameters. However, thiswas not case for the G and JMAX
parameters, as can be seen by their rel-atively low R2 values.
Based on these results, it waspossible to say that ,G and
parameters were appropriate for determining adulteration inhoney
samples.
4. Conclusion
In this study, natural honey was adulterated with different
levels ofsaccharose and fructose syrups at a ratio of 0%, 10%, 20%,
30%, 40% and50% by weight. Steady, dynamic and creep tests were
conducted to de-tect such adulterations at specied ratios. The
rheological analysis testresults revealed that adulteration at
these levels could be clearly detect-
parameters.
ity
Saccharose Control Fructose
2% 4% 6% 8% 2% 4% 6% 8%
6.718 6.596 5.737 5.402 7.253 7.812 6.327 6.520 5.5230.348 0.288
0.479 0.437 0.171 0.241 0.631 0.195 0.699a a b b ab a cd bc d0.365
0.276 0.223 0.247 0.337 0.315 0.282 0.245 0.2580.223 0.137 0.011
0.045 0.065 0.065 0.029 0.085 0.039a a a a a a a a a49.566 45.650
44.670 45.466 53.420 50.778 48.140 42.724 43.5260.857 1.103 1.746
4.353 1.303 3.329 5.391 1.968 1.546ab bc c bc a a ab b b7.889 7.266
7.110 7.236 8.502 8.082 7.662 6.800 6.9270.136 0.176 0.278 0.693
0.207 0.530 0.858 0.313 0.246ab bc c bc a a ab b b22.162 22.384
18.456 16.490 13.296 18.936 13.162 12.548 16.7408.834 2.906 0.800
1.846 1.562 2.703 0.944 0.477 1.814a a ab ab b a b b a
ween the concentrations (P b 0.01).ed by remarkable changes in
the ow, viscoelastic and creep behavior ofnatural honey. Signicant
correlations found between the rheology pa-rameters and sugar
composition of adulterated honey samples sug-gested that these
parameters could be a combination of indicators fordetection of
such adulterations in honey at specied ratios. This wasalso
demonstrated by our validation data which indicated that , Gand
parameters could be used to precisely determine the adultera-tion
status of honey samples, resulting from saccharose/fructose.
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Steady, dynamic and creep rheological analysis as a novel
approach todetect honey adulteration by fructose and saccharose
syrups:Correlations with HPLC-RID results1. Introduction2.
Materials and methods2.1. Materials2.2. Physicochemical
analyses2.3. HPLC analysis2.4. Rheological analysis2.4.1. Steady
shear analysis2.4.2. Dynamic shear analysis2.4.3. Creep and
recovery analysis
2.5. Method validation2.6. Statistical analysis
3. Results and discussion3.1. Physicochemical properties3.2.
HPLC analysis3.3. Steady shear properties3.4. Dynamic shear
properties3.5. Creep and recovery properties3.5.1. Creep
phase3.5.2. Recovery phase
3.6. Correlations between sugar composition and rheology
parameters3.7. PCA analysis3.8. Method validation3.8.1.
Repeatability3.8.2. Sensitivity (LOD)3.8.3. Linearity
4. ConclusionReferences