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:mtyilmaz@yildiz.edu.tr (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