Honey samples collection region and years of cultivar - UMF2598 S. M. Wabaidur et al. J. Sep. Sci....

J. Sep. Sci. 2015, 38, 2597–2606 2597

Saikh Mohammad Wabaidur1

Yacine Badjah Hadj Ahmed1

Zeid Abdullah Alothman1 ∗Munir Saeed Obbed1

Nasser Mohamed AL-Harbi2Turki Mohammad AL-Turki3

1Advanced Materials ResearchChair, Department of Chemistry,College of Science, King SaudUniversity, Riyadh, Kingdom ofSaudi Arabia

2Regional Analytical SABIC T&I,Saudi Basic IndustriesCorporation, Riyadh, SaudiArabia

3Department of Chemistry,College of Science, King SaudUniversity, Riyadh, Kingdom ofSaudi Arabia

Received April 5, 2015Revised April 29, 2015Accepted April 30, 2015

Research Article

Ultra high performance liquidchromatography with mass spectrometrymethod for the simultaneous determinationof phenolic constituents in honeyfrom various floral sources using multiwalledcarbon nanotubes as extraction sorbents

An ultra high performance liquid chromatography with mass spectrometry method hasbeen developed for the simultaneous separation, identification and determination of 22phenolic constituents in honey from various floral sources from Yemen. Solid-phase extrac-tion was used for extraction of the target phenolic constituents from honey samples, whilemultiwalled carbon nanotubes were used as solid-phase adsorbent. The chromatographicseparation of all phenolic constituents was performed on a BEH C18 column using a lin-ear gradient elution with a binary mobile phase mixture of aqueous 0.1% formic acid andmethanol. The quantitation was carried out in selected ion reaction monitoring acquisitionmode. The total amount of phenolic acids, flavonoids and other phenols in each analyzedhoney was found in the range of 338–3312, 122–5482 and 2.4–1342 �g/100 g of honey,respectively. 4-Hydroxybenzoic acid was found to be the major phenolic acid. The maindetected flavonoid was chrysin, while cinnamic acid was found to be the major other phenolcompound. The regeneration of solid phase adsorbent to be reused and recovery resultsconfirm that the proposed method could be potentially used for the routine analysis ofphenolic constituents in honey extract.

Keywords: Honey / Mass spectrometry / Multiwalled carbon nanotubes / Phenolicconstituents / Ultra high performance liquid chromatographyDOI 10.1002/jssc.201500386

1 Introduction

Honey is a well-known natural food product that possesseshigh nutritional and prophylactic medicinal value. Ancientpeople of many countries used honey as a medicine to treatstomach ulcers and skin wounds. It has shown often appli-cations as a sugar substitute and an ingredient or a natu-ral preservative in many of manufactured foods due to itsunique sweetness, color and flavor. It is rich in many ac-tive compounds such as phenolic acids and flavonoids [1]. Afew papers have reported that flavonoids and phenolic acidsof honey are mainly responsible for its significant antioxi-dant capacity [2–4] and other beneficial effects such as woundhealing [5], skin cells and tissues protection from oxidativedamage [6] and food preservation [7, 8].

Recently, analysis of phenolic constituents has beenregarded as a very promising technique of identifying

Correspondence: Mr. S. M. Wabaidur, Advanced Materials Re-search Chair, Department of Chemistry, College of Science, KingSaud University, Bld 5, P.O. Box 2455, Riyadh, 11451, Saudi ArabiaE-mail: [email protected]: +96614675992

Abbreviation: MWCNTs, multiwalled carbon nanotubes

floral and geographical origins of honeys [9–14]. Hence, itis worth to establish a simple, sensitive and accurate methodto perform extensive honey compositional analysis. Many an-alytical methods have been reported in the literature for theanalysis of phenolic contents in honey [15–18]. Among them,liquid chromatographic techniques for the analysis of organicacids in honey have proven to be very valuable in determin-ing the authenticity of the floral and geographical origin ofhoney [17–20]. UHPLC–MS could be much more beneficialfor analyzing phenolic constituents due to the advantagesof high sensitivity, accurate quantification and low sampleinjection volume. Therefore, this study aims to develop ananalytical method based on UHPLC–MS for simultaneousdetermination of phenolic acids, flavonoids and other phe-nols in Yemeni honeys of various floral sources. The extrac-tion of the phenolic constituents from honey was carriedout using multiwalled carbon nanotubes (MWCNTs) as SPEadsorbent as they have shown unique physicochemical, out-standing recovery and regeneration properties [21–23]. Thedescribed method is simple, precise, reproducible and highly

∗Additional Corresponding author: Z. A. AlothmanE-mail: [email protected]

C© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com

2598 S. M. Wabaidur et al. J. Sep. Sci. 2015, 38, 2597–2606

Table 1. Honey samples collection region and years of cultivar

Sample Species Region (Yemen) Harvest (Year)

1 Ziziphus Spina-christs Hadramout 20082 Ziziphus Spina-christs Hadramout 20113 Ziziphus Spina-christs Hadramout 20104 Ziziphus Spina-christs Hadramout 20095 Ziziphus Spina-christs Hadramout 20096 Ziziphus Spina-christs Hadramout 2009

Monofloral 7 Ziziphus Spina-christs Hadramout 20108 Ziziphus Spina-christs Hadramout 20109 Ziziphus Spina-christs Shabwa 200910 Ziziphus Spina-christs Hadja 201111 Ziziphus Spina-christs Dhamar 201012 Ziziphus Spina-christs Omran 201113 Various species Hadramout 200814 Various species Hadramout 201015 Various species Hadramout 200916 Various species Hadramout 2011

Multifloral 17 Various species Hadramout 201018 Various species Abeen 201019 Wild plants Sanaa 201020 Wild plants Hadja 201021 Wild plants Socotry 201022 Acacia tortilis Hadramout 200923 Acacia tortilis Hadramout 201124 Acacia tortilis Hadramout 201025 Acacia tortilis Hadramout 2010

Cactus 26 Acacia tortilis Hadramout 200927 Acacia ehrenbergiana Hadja 201128 Aloe vera barbadensis Mantuka 201029 Aloe vera barbadensis Abh 2010

sensitive in addition with other advantage that the quanti-tation may be accurately carried out without the use of aninternal standard [24].

2 Materials and methods

2.1 Chemicals and reagents

UHPLC-grade solvents were used during the experiment.The standard phenolic constituents were collected from var-ious chemical companies. Carvacrol, 4-hydroxybenzoic acid,maleic acid, chlorogenic acid, sinapic acid and naringeninwere supplied by Aldrich Chemicals (Milwaukee, WI, USA).Galangin, gallic acid, apigenin, kaempferol, luteolin, caffeicacid, quercetin and p-coumaric acid were purchased fromSigma Chemicals (St Louis, MO, USA). Acetonitrile, aceticacid, ethanol, formic acid, diethylether, methanol, hydrlochlo-ric acid and anhydrous sodium carbonate were suppliedby BDH Chemicals (UK). Naringin, syringic acid, thymol,4-hydroxyphenyl acetic acid, chrysin, myricetin and vanillicacid were obtained from Acros Organics (New Jersey, USA).Potassium acetate was bought from Riedel de Haen (Seelze,Germany) while benzoic acid was supplied by Winlab, cin-namic acid from SAFC, ferulic acid from Fluka (St. Louis,

MO, USA), phenol from Merck (NJ, USA), sodium sulfatefrom Koch-Light Lab. (Haverhill, UK) and MWCNTs fromTimesnano (Chengdu Organic Chemicals, China). Ultrapurewater used for the UHPLC mobile phase and sample prepa-ration was obtained using a Milli-Q water purification instru-ment from Millipore (Bedford, MA, USA).

2.2 Sample collection

The honey to be analyzed was collected from beehives fedeither with monofloral, multifloral species and cactus trees.Mainly, 12 types of monofloral, nine types of multifloral andeight types of cactus honey from various regions of Yemenwere collected in different harvesting seasons. The sampleswere numbered from 1 to 29. All these samples were pre-served at a temperature below 4�C inside the refrigerator. Theyear of harvesting and region of collection of these analyzedhoney samples are listed in Table 1.

2.3 Extraction procedure

SPE procedure was used for the extraction of phenolic con-stituents from honeys. The extractions of these phenolic


J. Sep. Sci. 2015, 38, 2597–2606 Liquid Chromatography 2599

Table 2. The abbreviations, retention times and optimized SIR parameters for the studied phenolic components (dwell time = 0.025 s)

Analyte names Abbreviations Retention time (min) Molecular weight Cone voltage (V) [M–H]+ (m/z)

Maleic acid Mal 1.4 116.07 25 115Gallic acid Gal 2.5 170.12 29 1694-Hydroxybenzoic acid 4Hba 9.1 138.12 32 1374-Hydroxyphenyl acetic acid 4Hpa 10.4 152.15 28 151Caffeic acid Caf 11.3 180.16 37 179Chlorogenic acid Clo 11.8 354.31 33 353Vanillic acid Van 12.1 168.15 35 167Syringic acid Syr 12.9 198.17 25 197p-Coumaric acid Pco 15.5 164.05 24 163Ferulic acid Fer 16.0 194.18 28 193Phenol Phe 16.3 94.11 27 93Benzoic acid Ben 18.1 122.12 30 121Myricetin Myr 19.5 318.23 35 317Naringin Nar 21.1 580.54 31 579Cinnamic acid Cin 23.2 148.17 28 147Quercetin Que 24.0 302.24 24 301Naringenin Narn 25.5 272.26 33 271Kaempferol Kae 26.1 286.23 34 285Luteolin Lut 26.9 286.24 28 285Apigenin Api 32.1 270.24 29 269Galangin Gal 33.0 270.24 34 269Chrysin Chr 33.2 254.24 34 253

Figure 1. The UHPLC–MS chro-matogram of mixture of all standardphenolic constituents.

species were achieved using our previously reported pro-cedure [25]. Shortly the procedure can be explained as fol-lows. 200 g of individual honey was dissolved in three partsusing distilled water (200 mL each) while the pH of the so-lution was maintained at 2 by addition of HCl. Then, 1 g ofMWCNTs was added to this acidified honey solution. MWC-NTs were used as SPE adsorbent for extraction of the targetphenols, since their unique mechanical, physical, chemical,thermal and excellent recovery and regeneration properties

provide exceptionally better sorption ability and high stabilityto the extraction procedure [21–23]. The MWCNTs containingfinal acidified solution was then magnetically stirred for 20–30 min and the extremely large surface area and the uniquetubular structure of MWCNTs [26] allow the adsorption ofhoney phenolics onto them [27]. The vacuum filtration on acellulose nitrate membrane filter (47 mm diameter, 0.45 �mporosity) was carried out to separate the MWCNTs fromhoney samples and the separated MWCNTs were washed



Table 3. Validation parameters of the studied method (UHPLC–MS)

Compound type Samples LOD (�g/mL) LOQ (�g/mL) Correlation coefficient (r2) Precision (RSD%)a)

Inter-day Intra-day

Phenolic acids 4Hba 0.033 0.11 0.9976 1.8 1.94Hpa 0.082 0.27 0.9992 1.9 2.1Caf 0.026 0.086 0.9993 2.1 2.3Clo 0.015 0.051 0.9996 1.7 2.2Fer 0.023 0.075 0.9999 1.9 1.9Gal 0.036 0.12 0.9989 1.8 2.2Pco 0.018 0.058 0.9999 2.1 2.1Syr 0.029 0.1 0.9997 1.9 2.3Van 0.016 0.054 0.9997 1.7 2.1

Flavonoids Api 0.029 0.097 0.9998 1.6 2.1Chr 0.036 0.12 0.9998 1.9 2.1Galn 0.018 0.06 0.9997 2.1 2.5Kae 0.041 0.14 0.9987 1.8 2.1Lut 0.029 0.095 0.9992 1.8 2.5Myr 0.036 0.12 0.9999 2.0 2.1Nar 0.14 0.46 0.9999 2.0 2.5Narn 0.027 0.089 0.9997 1.9 2.0Que 0.029 0.096 0.9994 2.0 2.4

Other phenols Ben 0.037 0.122 0.9996 1.9 2.2Cin 0.034 0.11 0.9991 2.0 2.1Mal 0.4 1.35 0.9996 2.1 2.4Phe 0.037 0.12 0.9999 1.8 2.4

a) RSD (n = 5).

with 100 mL of acidified water of pH 2.0 followed by washingwith 300 mL of Milli-Q water to remove sugars and other po-lar constituents [28]. Then, the phenolic compounds whichwere retained onto the surface of MWCNTs were eluted withmethanol (300 mL) and were concentrated under reducedpressure at around 40�C temperature in a rotary evaporator(Buchi, Model V–850, Switzerland). After that the residuewas mixed with 6 mL of distilled water and extracted withdiethyl ether (5 mL x 3). Then, the extraction solution was re-concentrated by removing diethyl ether using nitrogen flush-ing. Again this concentrated residue was dissolved in 2 mL ofmethanol and filtered with 0.45 �m membrane filter beforeinjection into the UHPLC–MS system.

2.4 Instrumentation

2.4.1 UHPLC

The chromatographic separations of all phenolic compoundswere carried out using Acquity UHPLC BEH C18 column(2.1 mm id, 50, 100 and 150 mm length, 1.7 �m particle size)(Waters

R©, Milford, MA, USA). The column was connected to

an Acquity UHPLC system (WatersR©, Manchester, UK) con-

sisting of an Acquity UHPLC binary solvent manager, sam-ple manager and column heater. A Welch Duo-Seal vacuum

pump (Model No.1400, USA) was used for sample filtration.A shaker (Kjanke & Kunkel Ika Labor Technik Ks501D) wasused for mixing the solutions while a pH meter (Metrohm6.0228.000) was used for pH measurements of the samples.The sample volume injected was 5 �L.

2.4.2 MS

A Quattro Premier triple-quadrupole mass spectrometerfrom Micromass (Manchester, UK) equipped with an ESIsource was used for the detection of analyzed compounds.An Oerlikon rotary pump, model SOGEVAC SV40 BI (Paris,France) was used to provide the primary vacuum to themass spectrometer. MS measurements were performed withelectrospray negative ionization (ESI−) mode. Monitoringconditions were optimized for better peak sensitivity. Theoptimized specific cone voltage was chosen for the formationof parent ions of the target analyte. The MS conditions wereoptimized as follows: capillary voltage 3.0 kV, cone voltagesource temperature 120�C, desolvation temperature 420�C,desolvation and cone gas flows were 800 and 80 L/h, respec-tively. High-purity nitrogen was used as nebulizing and wasproduced by a Peak Scientific NM30LA nitrogen generator(Inchinann, UK). Data acquisition was carried out by MassL-ynx V4.1 software (Micromass, Manchester, UK).



Ta

ble

4.

Det

erm

inat

ion

of

ph

eno

licac

ids

inm

on

ofl

ora

l(sa

mp

le1–

12),

mu

ltifl

ora

l(sa

mp

le13

–21)

and

cact

us

(sam

ple

22–2

9)h

on

eys

±S

D(�

g/1

00g

of

ho

ney

)(n

=3)

(R=

reco

very

rate

s,%

)

Sam

ple

Phen

olic

acid

sTo

tal

Gal(R

)Cl

o(R)

4Hba

(R)

4Hpa

(R)

Caf(R

)Va

n(R)

Syr(R

)Pc

o(R)

Fer(R

)

1nd

(94)

nd(9

6)64

8±

1.1(

98)

84±

0.2(

91)

nd(9

7)34

4±

0.5(

96)

nd(9

9)nd

(96)

nd(9

9)10

76±

0.9

218

8±

1.1(

96)

nd(9

5)14

10±

2.9(

97)

nd(9

6)15

6±

0.9(

96)

nd(9

9)44

4±

0.7(

97)

60±

0.3(

91)

312

±0.

2(96

)25

71±

1.6

333

±0.

5(9

4)nd

(96)

1120

±1.

9(98

)nd

(98)

146

±0.

5(9

3)25

8±

0.5

(96)

204±

0.5

(94)

26±

0.5

(96)

nd(9

3)17

91±

1.1

417

1±

1.2(

97)

nd(9

6)nd

(98)

nd(9

6)14

9±

1.1(

91)

nd(9

7)17

5±

0.1

(96)

22±

0.1(

93)

nd(9

8)51

7±

0.9

524

0±

2.4(

96)

nd(9

6)12

30±

2.5(

99)

nd(9

2)15

4±

1.6(

95)

422

±0.

1(9

5)39

6±

1.9(

98)

nd(9

2)18

0±

0.2

(90)

2618

±1.

96

79±

0.9(

94)

nd(9

3)33

2±

3.1(

99)

nd(9

8)nd

(93)

nd(9

2)nd

(94)

25±

0.2(

R)nd

(96)

436±

1.4

712

7±

1.1(

97)

nd(9

2)79

4±

1.8(

100)

114±

0.8(

95)

nd(9

5)50

±0.

5(95

)nd

(96)

nd(9

5)38

±0.

5(93

)11

24±

0.9

817

3±

1.7(

98)

106

±0.

5(91

)10

40±

1.9(

100)

nd(9

4)37

±0.

4(92

)39

0±1.

4(95

)63

6±

1.9(

98)

07±

0.5(

93)

43±

0.5(

95)

2434

±1.

29

46±

0.2(

94)

nd(9

0)60

0±

1.8(

100)

nd(9

6)77

±0.

6(94

)nd

(94)

122±

0.5(

99)

12±

0.1(

95)

nd(9

2)85

6±

0.9

1031

±0.

3(96

)22

±0.

1(9

5)21

6±

1.4(

96)

nd(9

5)58

±0.

5(93

)nd

(94)

nd(9

2)nd

(92)

12±

0.2

(96)

338

±0.

511

38±

0.5(

97)

31±

0.3(

96)

434

±1.

8(97

)19

9±

0.1

(96)

nd(9

6)24

±1.

1(96

)96

±0.

7(95

)4±

0.1

(96)

nd(9

1)79

2±

0.9

1233

±0.

1(9

6)nd

(96)

464±

1.6(

97)

48±

0.5(

95)

03±

0.8(

95)

nd(9

7)nd

(96)

34±

0.6(

95)

07±

0.1(

95)

589

±0.

613

72±

0.2(

94)

nd(9

0)36

6±

1.8(

100)

60(9

6)17

±0.

6(94

)nd

(94)

nd(9

9)nd

(95)

nd(9

2)51

5±

0.9

1413

7±

0.3(

96)

nd(9

5)27

2±

1.4(

96)

nd(9

5)nd

(93)

nd(9

4)nd

(92)

10±

0.2(

92)

nd(9

6)48

1±

0.5

15nd

(97)

nd(9

6)32

2±

1.8(

97)

nd(9

6)nd

(96)

nd(9

6)nd

(95)

nd(9

6)45

±0.

2(91

)36

7±

0.9

1628

4±

0.5(

96)

149

±0.

5(96

)45

6±

1.6(

97)

nd(9

5)31

±0.

8(95

)nd

(97)

nd(9

6)15

±0.

6(95

)nd

(95)

935±

0.6

1720

4±

0.3(

99)

nd(9

8)52

4±

1.4(

101)

nd(9

4)22

9±

0.5(

98)

nd(9

9)30

6±

0.2(

98)

43±

0.2(

95)

nd(9

8)13

06±

0.5

1848

±0.

5(98

)nd

(95)

448±

1.8(

99)

nd(9

5)nd

(92)

17±

0.3(

96)

nd(9

9)26

±0.

7(96

)nd

(96)

539±

0.9

1925

0±

0.1(

95)

53±

0.6(

95)

1160

±1.

6(95

)26

8±

0.3(

93)

nd(9

1)86

±0.

5(99

)nd

(90)

18±

0.6(

94)

20±

0.1(

91)

1851

±0.

620

312±

0.5(

91)

21±

0.7(

98)

1190

±1.

8(96

)nd

(91)

35±

1.1(

95)

34±

0.5(

97)

326

±0.

3(98

)07

±0.

7(92

)10

6±

0.9(

97)

2030

±0.

921

97±

0.1(

92)

nd(9

1)10

20±

1.6(

97)

nd(9

5)17

±0.

8(92

)nd

(96)

122±

0.3(

92)

12±

0.6(

93)

nd(9

3)12

68±

0.6

2217

3±

1.0(

94)

nd(9

6)31

2±

1.1(

98)

07±

0.2(

91)

05±

0.1(

97)

35±

0.5(

96)

18±

0.3(

99)

nd(9

6)nd

(99)

549±

0.9

2325

8±

1.1(

96)

234

±0.

1(95

)60

8±

2.9(

97)

nd(9

6)nd

(96)

124±

0.1(

99)

94±

0.4(

97)

10±

0.3(

91)

nd(9

6)13

28±

1.6

24nd

(94)

nd(9

6)42

6±

1.9(

98)

348

±0.

2(98

)09

±0.

1(93

)nd

(96)

nd(9

4)55

±0.

1(96

)67

±0.

5(93

)90

4±

1.1

2551

4±

1.2(

97)

100

±1.

0(9

6)15

50±

1.5(

98)

nd(9

6)21

0±

1.1(

91)

248

±0.

6(97

)15

2±

0.1(

96)

nd(9

3)16

7±

0.1

(98)

3312

±0.

926

318±

2.4(

96)

178

±0.

1(96

)67

0±

2.5(

99)

30±

1.0

(92)

31±

1.6(

95)

nd(9

5)15

3±

1.9(

98)

166

±1.

1(92

)nd

(90)

1546

±1.

927

72±

0.9(

94)

218

±0.

2(93

)27

2±

3.1(

99)

186

±0.

5(98

)35

±0.

1(93

)nd

(92)

58±

0.1(

94)

18±

0.2(

98)

nd(9

6)85

9±

1.4

2824

±1.

1(97

)nd

(92)

490±

1.8(

100)

17±

0.8(

95)

nd(9

5)nd

(95)

140±

0.5(

96)

21±

0.2(

95)

nd(9

3)69

2±

0.9

2916

±1.

7(98

)02

±0.

5(91

)55

2±

1.9(

100)

nd(9

4)16

±0.

4(92

)nd

(95)

27±

1.9(

98)

13±

0.5(

93)

nd(9

5)62

6±

1.2

Tota

l39

38±

0.8

1114

±0.

318

896±

1.8

1301

±0.

714

15±

0.9

2032

±1.

534

69±

1.6

604±

0.4

997±

1.0

3425

0±

1.2

Aver

age

151.

4611

1.4

674.

8513

0.1

74.4

716

9.33

204.

0528

.76

90.6

316

35.0

5a)

%b)

11.4

93.

2555

.17

3.79

4.13

5.93

10.1

21.

762.

91

a)To

talp

hen

olic

acid

sav

erag

ed.

b)

Perc

enta

ge

of

each

ind

ivid

ual

ph

eno

licac

idin

the

tota

lph

eno

licac

ids,

nd

isn

ot

det

ecte

d.



Table 5. Determination of flavonoids in monofloral (sample 1–12), multifloral (sample 13–21) and cactus (sample 22–29) honeys ± SD (�g/100 g ofhoney) (n = 3) (R = recovery rates, %)

Sample Flavonoids Total

Nar(R) Myr(R) Lut(R) Que(R) Narn(R) Kae(R) Api(R) Chr(R) Gal(R)

1 nd(92) nd(92) nd(92) 93 ± 1.3(91) nd(91) 10 ± 0.2(96) 03 ± 0.5(95) 51 ± 0.3(90) 10 ± 0.2(91) 167 ± 0.82 117 ± 1.8(92) 45 ± 1.9(92) nd(96) 472 ± 2.6(92) 83 ± 1.6(90) 45 ± 2.5(90) 13 ± 0.5(91) 850 ± 2.9(97) 23 ± 0.6(91) 1646 ± 1.83 25 ± 1.6(93) 41 ± 2.0(90) nd(91) 41 ± 1.5(90) 21 ± 0.5(99) 28 ± 2.1(91) 03 ± 2.6(94) 550 ± 1.6(95) 21 ± 0.6(90) 731 ± 1.34 13 ± 0.8(93) nd(90) nd(93) 27 ± 1.2(94) 67 ± 0.2 (92) 37 ± 2.1(91) 05 ± 1.0(91) 113 ± 2.1(96) 13 ± 1.2 (91) 275 ± 1.35 29 ± 1.2(99) 55 ± 2.1(91) nd(94) 296 ± 2.5(99) 67 ± 1.5 (93) nd (93) 13 ± 1.2(96) 692 ± 1.0(91) 21 ± 0.8(96) 1173 ± 1.76 nd(96) nd(92) nd(92) 06 ± 0.4(90) nd(93) nd(93) nd(95) 252 ± 2.5(95) 13 ± 0.1(92) 272 ± 1.07 22 ± 0.4 (93) 24 ± 1.2(91) nd(96) 39 ± 1.2(95) 31 ± 1.2(99) 21 ± 1.9(92) 11 ± 0.4 (90) 404 ± 2.2(99) 23 ± 0.9(95) 573 ± 1.48 04 ± 0.2(93) 38 ± 1.9(90) nd(91) 126 ± 2.1(96) 95 ± 2.1(99) 35 ± 0.4 (91) 09 ± 0.2(92) 634 ± 2.8(100) 15 ± 1.2(95) 954 ± 1.49 nd (90) 3 ± 0.5(90) nd(97) nd(95) 119 ± 1.5(96) nd(92) nd(93) 712 ± 2.6(100) nd(91) 834 ± 1.610 13 ± 0.1 (96) nd(96) nd(94) 109 ± 2.2(90) nd(90) nd(91) nd(91) 564 ± 2.2(97) nd(92) 686 ± 1.811 nd(98) nd(93) 6nd(93) 186 ± 2.2(99) nd(91) 37 ± 1.5(92) nd(90) 629 ± 2.6(99) nd(91) 852 ± 1.612 09 ± 0.1 (96) nd(92) nd(92) 113 ± 2.0(95) 134 ± 1.5 (90) 42 ± 1.5(92) 03 ± 1.5(96) 536 ± 2.9(98) nd(92) 837 ± 1.713 nd(92) nd(92) nd(92) 63 ± 1.3(91) nd(91) 46 ± 0.2(96) nd(95) nd 13 ± 0.2(91) 122 ± 0.814 nd(96) 15 ± 1.9(92) 15.2 ± 1.8(92) 72 ± 2.6(92) nd(90) 8 ± 2.5(90) 02 ± 0.5(91) 183 ± 2.9(97) nd(91) 279 ± 1.815 nd(93) nd(90) nd(91) 3 ± 1.5(90) 262 ± 0.5(99) nd(91) nd(94) nd nd(90) 275 ± 1.316 31 ± 0.8(93) 43 ± 0.8(90) 14.8 ± 0.9(93) 65 ± 1.2(94) nd(92) 30 ± 2.1(91) 07 ± 1.0(91) 171 ± 2.1(96) nd(91) 275 ± 1.317 99 ± 1.2(99) 77 ± 2.1(91) 12.4 ± 1.5(94) 123 ± 2.5(99) nd(93) 41 ± 1.5(93) 89 ± 1.2(96) nd 81 ± 0.8(96) 347 ± 1.718 46 ± 0.4(96) nd(92) nd(92) nd(90) nd(93) nd(93) 43 ± 0.4(95) 131 ± 2.5(95) 13 ± 0.1(92) 510 ± 1.019 nd(93) 28 ± 1.2(91) nd(96) 25 ± 1.2(95) 452 ± 1.2(99) 25 ± 1.9(92) nd(90) 330 ± 2.2(99) 57 ± 0.9(95) 927 ± 1.420 123 ± 0.2(93) 213 ± 1.9(90) 120 ± 0.1(91) 117 ± 2.1(96) 756 ± 2.1(99) nd(91) 175 ± 0.2(92) 86 ± 2.8(100) 45 ± 1.2(95) 1535 ± 1.421 5 ± 0.5(90) nd(90) 10.0 ± 1.9(97) 37 ± 2.2(95) 103 ± 1.5(96) nd(92) 24 ± 0.2(93) 426 ± 2.6(100) 9 ± 1.5(91) 652 ± 1.622 nd(92) nd(92) nd(92) 13 ± 1.3(91) nd(91) 05 ± 0.2(96) 03 ± 0.3(95) 159 ± 0.5(95) 11 ± 0.2(91) 191 ± 0.823 93 ± 0.9(96) nd(92) nd(92) 226 ± 2.6(92) nd(90) 54 ± 2.5(90) nd(91) 292 ± 2.9(97) nd(91) 663 ± 1.824 nd(93) nd(90) nd(91) 33 ± 1.5(90) nd(99) nd(91) nd(94) 197 ± 0.5(nd 13 ± 0.5(90) 243 ± 1.325 236 ± 0.8(93) 450 ± 0.8(90) nd(93) 1340 ± 1.2(94) 1060 ± 1.5(92) 554 ± 2.1(91) 444 ± 1.0(91) 1140 ± 2.1(96) 258 ± 0.5(91) 5482 ± 1.326 36 ± 1.2(99) 232 ± 2.1(91) nd(94) 248 ± 2.5(99) 422 ± 1.6(93) 43 ± 1.5(93) 25 ± 1.2(96) 494 ± 0.5(97) 230 ± 0.8(96) 1730 ± 1.727 nd(93) nd(94) nd(93) 91 ± 2.2(95) nd(92) nd(94) 6 ± 0.2(92) 272 ± 2.6(99) 39 ± 1.5(94) 408 ± 1.628 nd(94) nd(95) 15.0 ± 1.1(94) nd(91) 172 ± 2.6(97) 73 ± 1.5(95) nd(90) 324 ± 2.9(100) 65 ± 0.8(93) 634 ± 1.729 nd(96) 27 ± 0.8(95) 22.4 ± 1.1(93) 36 ± 2.0(91) nd(93) nd(93) nd(96) 324 ± 2.9(99) 65 ± 0.8(95) 387 ± 1.7Total 901 ± 1.1 1291 ± 1.3 209.8 ± 1.2 4000 ± 2.1 3844 ± 2.5 1134 ± 1.5 878±1.0 10516 ± 1.3 1038 ± 1.1 23660 ± 1.7Average 56.31 92.21 29.91 153.84 256.26 63.09 48.77 404.46 49.42 1154.27c)

%d) 3.81 5.45 0.89 16.90 16.25 4.79 3.71 44.44 4.39

c) Total flavonoids averaged.d) Percentage of each individual flavonoid in the total flavonoids, nd is not detected.

3 Results and discussion

3.1 Optimization of UHPLC conditions

The preliminary separation was carried out on a standardsolution including 22 phenolic compounds. The chromato-graphic conditions such as column, mobile phase compo-sition and flow rate were optimized to achieve the bestseparation of adjacent peaks and to avoid peak tailing. Vari-ous lengths of RP columns were tested such as BEH C18 (5, 10or 15 cm). The best results were obtained with BEH C18 col-umn (2.1 x 150 mm, 1.7 �m particle size). Mobile phasesof different compositions of acetonitrile, methanol and0.1% v/v aqueous formic acid were tested at different flowrates in the range 0.05–1 mL/min in both isocratic and gra-dient elution modes. Column temperature was also checkedfrom 25 to 60�C to see the effect on the separations. The bestseparation was obtained once using linear gradient elutionwith a binary mobile phase mixture of aqueous 0.1% formicacid (A) and methanol (B) with a flow rate in the range 0.3–0.4 mL/min in the shortest analysis time of 33.2 min. Initially,the composition of A was 100% and flow rate 0.3 mL/min for5 min. Composition of A was decreased to 90% between 5

and 15 min. In the third step, the composition of mobilephase remains constant (A/B 90:10) while the flow rate wasgradually increased to 0.4 mL/min till 20 min. In the fourthstep, the composition of A was decreased to 40% till 35 min.The column was heated at a fixed temperature 40�C.

3.2 MS parameters optimizations

Firstly, an optimization process (Quan-optimization) for eachphenolic constituent was performed to optimize the data ac-quisition parameters by direct infusion of each individual tar-get analyte (10 �g/mL) to the ion source of the MS detector.This tuning method was performed to obtain the maximumintensity of the molecular ions peak. The MS conditions wereoptimized in both positive and negative ionization modes toget maximum analyte response. Better and highly abundantanalyte signals were detected under different ion source pa-rameters in negative than in positive ionization mode. There-fore, the optimization was carried out in ESI– mode. Theeffect of ESI–MS parameters such as capillary voltage (2.0–4.5 kV), cone voltage (10–100 V), source temperature (100–140�C), desolvation temperature (200–450�C) and desolvation



Figure 2. The UHPLC–MS chro-matogram of the phenolic com-pounds presents in sample 8.

gas flow (500–800 L/h) were studied. The optimal MS param-eters were as follows: capillary voltage 3.0 kV, extractor 3 V,RF lens 0.3 V, source temperature 120�C, desolvation tem-perature 420�C, desolvation and cone gas flows were 800 and80 L/h, respectively. The quantitation was carried out in se-lected ion reaction (SIR) monitoring mode for each phenolicconstituent. The SIR parameters (precursor ion, [M–H]+ andcone voltage) of the target phenolic constituents including theabbreviation and retention times of each analyte are providedin Table 2.The obtained chromatogram and the resulting re-tention times for each phenolic compounds present in thestandard mixture using the developed UHPLC–MS methodsare shown in Fig. 1. The developed separation method ad-dressed so many significant issues including good resolutionand very sharp and symmetric peak shape without any peaktailing. However, the efficient separation of each analyte isnot necessary in MS detection, although it brings further en-hancement of sensitivity and selectivity to the analysis [29].

3.3 Performance of the proposed method

3.3.1 Calibration and linearity

Construction of calibration curves was performed by using aset of calibration standards of each analyzed compounds ofconcentration 0.01, 0.05, 0.1, 0.5, 1, 5, 10, 50, 100, 200 and250 �g/mL which were prepared in methanol. The linearityof the proposed method was established under the optimizedexperimental conditions by plotting the graph detection sig-nal versus analyte concentration. The least squares methodwas applied to establish the linear regression equation foreach analyte. The calibration curve was found to be linear

over the concentration range of 0.05–200 �g/mL and correla-tion coefficient (r2) was found to be >0.998 (Table 3) for eachregression equation.

3.3.2 LOD and LOQ

The LOD was calculated at S/N = 3:1, while the LOQ wascalculated at S/N = 10:1. These values of the proposedmethod were discretely determined by analyzing three repli-cates of a blank sample (Milli-Q water) spiked with each stan-dard at the lower concentration levels [30]. The LOD andLOQ values were found between 0.015–0.041 �g/mL and0.051–1.35 �g/mL, respectively, for all analyzed components(Table 3).

3.3.3 Accuracy and precision

The intra-day and inter-day precisions of the proposedUHPLC–MS method were established by injecting five repli-cates of the standard mixture (10 �g/mL) on the same day and15 replicates during three consecutive days (five replicates perday), respectively [24]. High values of intra-day and inter-dayprecisions were achieved with RSD values less than 2.3%(Table 3). The lower values of precision with ˂2.3% RSD con-firm the successful applications of the proposed UHPLC–MSmethod for the routine analysis of phenolic acids, flavonoidsand other phenols in various natural samples. The applica-bility of the proposed method was further confirmed by per-forming recovery assay. To obtain the recoveries of all thephenolic compounds, addition of the standards at three dif-ferent concentration levels was made to each honey samplebefore performing the extraction. The average recoveries were



Table 6. Determination of other phenols in monofloral (sample 1–12), multifloral (sample 13–21) and cactus (sample 22–29) honeys ± SD(�g/100 g of honey) (n = 3) (R = recovery rates, %)

Sample Other phenols Total

Mal(R) Phe(R) Ben(R) Cin(R)

1 nd(93) nd(92) 03 ± 0.2(92) 47 ± 0.2(94) 50 ± 0.22 nd(91) nd(90) 06 ± 0.2(93) 1336 ± 1.2(97) 1342 ± 1.03 nd(95) nd(93) nd(90) 306 ± 0.2(94) 306 ± 0.54 nd(90) nd(90) nd(95) 512 ± 0.2(95) 512 ± 0.65 nd(94) nd(91) nd(93) 758 ± 1.3(97) 758 ± 0.86 nd(94) nd(91) nd(91) 224 ± 0.7(94) 224 ± 0.87 nd(96) nd(93) nd(90) 318 ± 0.8(92) 318 ± 0.68 nd(94) 68 ± 0.2(94) nd(96) 926 ± 0.5(94) 994 ± 0.99 nd(94) nd(92) nd(91) 306 ± 0.3(93) 306 ± 0.710 nd(93) nd(90) nd(90) 330 ± 0.4(93) 330 ± 0.211 nd(91) nd(93) 09 ± 0.7(93) 410 ± 0.9(96) 419 ± 0.812 nd(90) nd(91) 07 ± 0.2(93) 328 ± 0.9(96) 335 ± 1.013 nd(94) nd(90) 35.0 ± 0.2(94) 25.6 ± 2.6(94) 60.6 ± 1.314 nd(90) nd(91) 55.0 ± 1.5(95) nd(96) 64.8 ± 1.615 nd(92) nd(92) 17.0 ± 1.3(94) nd(94) 17 ± 1.316 nd(92) nd(91) 33.0 ± 0.1(95) 63.0 ± 2.6(98) 100.8 ± 1.217 nd(91) nd(93) nd(92) 118.0 ± 2.7(98) 136.0 ± 2.118 nd(93) nd(92) 7.0 ± 0.3(92) 47.2 ± 0.9(97) 54.2 ± 0.919 0.4 ± 0.1(91) 0.2 ± 0.2(90) nd(93) 57.0 ± 1.2(97) 64.4 ± 1.220 nd(95) 0.6 ± 0.1(91) 3.0 ± 0.4(93) 113.8 ± 2.8(96) 117.4 ± 1.421 nd(94) nd(93) 5.2 ± 0.1(95) nd(90) 15.2 ± 1.122 nd(96) 0.4 ± 0.1(92) nd(92) 139 ± 1.5(95) 145.2 ± 1.523 nd(95) nd(92) nd(92) 206.0 ± 2.6(99) 212.2 ± 1.624 nd(98) 0.8 ± 0.1(91) 1 ± 0.9(91) 226.0 ± 1.2(100) 227.8 ± 1.625 nd(92) 0.4 ± 0.2(92) nd(92) 670.0 ± 2.8(101) 677.6 ± 1.426 nd(91) 0.2 ± 0.1(91) nd(93) 522.0 ± 1.3(101) 528.6 ± 1.127 0.4 ± 0.2(90) nd(92) 20.6 ± 1.1(95) 142.4 ± 1.5(99) 170.0 ± 1.528 nd(92) nd(91) nd(92) nd(96) 5.0 ± 1.129 nd(90) nd(91) nd(93) nd(92) 2.4 ± 1.6Total 0.8 ± 0.1 9.4 ± 0.1 201.8 ± 0.5 8131 ± 1.1 8493.2 ± 1.5Average 0.4 1.34 15.52 369.59 386.85e)

%f) 0.01 0.11 2.38 95.74

e) Total other phenols averaged.f) Percentage of each individual other phenol in the total other phenols, nd is not detected.

found to be in the range from 90.0 to 101.0% with RSDs be-tween 1.3–1.9% (Tables 4–6).

3.4 Honey sample analysis

The SPE technique in combination with UHPLC–MS wasapplied for the simultaneous determination of phenolic con-stituents in Yemeni monofloral, multifloral and cactus honey.All the extracted samples obtained using SPE technique fromeach variety of honey (10 �L) were injected into the UHPLC–MS instrument and the peaks in the chromatograms obtainedwere identified by comparison of retention times of standardsrecorded in the same conditions [17, 18, 31] and their corre-sponding MS spectra. Figure 2 shows the UHPLC–MS chro-matogram of sample 8. The chromatogram provided wellseparated peaks and no interferences from any other

components were observed since there were no detectablematrix peaks eluted in the retention time of the analyzedcompounds [32].

3.4.1 Analysis of phenolic acids

The results of analyzed samples of monofloral, multifloraland cactus Yemeni honey showed that the averaged contentof total phenolic acids was 1.635 mg/100 g honey, whichis smaller than that found in jujube honey [25]. It was alsoobserved that 4Hba (55.17%) (Table 2 lists all abbreviations)was the main phenolic acid component (18.896 mg/100 ghoney) (Table 4). On the other hand, syringic (10.12%) andgallic (11.49%) were the secondary phenolic acids with theamount 3.469 and 3.938 mg/100 g honey, respectively, inall the analyzed honeys. The amounts of other individualphenolic acids were found in a relatively lower proportion



ranging from 1.76 (Pco acid) to 5.93% (Van acid) of totalphenolic acids (34.250 mg/100 g honey) (Table 4). However,the contents of individual phenolic acids in each analyzedhoney samples were found to be clearly different from eachother and among them Acacia tortilis (sample 25) which wasobtained from cactus has displayed the highest concentrationof 4Hba (1.550 mg/100 g honey). More remarkably, the acid4Hba was detected in all analyzed honey samples except insample 4 (Table 4).

3.4.2 Analysis of flavonoids

The results obtained from UHPLC–MS analysis showed thatchrysin was the main flavonoid component present in most ofthe analyzed samples (Table 5). The experimental results alsoshowed that among the nine investigated flavonoids most ofthem occurred in small amounts except chrysin, quercetinand naringenin. The total amount of flavonoids contentfrom all analyzed honeys was found to be 23.660 mg/100 ghoney, where chrysin was 10.516 mg/100 g honey. In ad-dition, quercetin (4.000 mg/100 g honey) and naringenin(3.844 mg/100 g honey) were the secondary constituents rep-resenting 16.90% and 16.25% of the total flavonoids, respec-tively. The other flavonoid contents were found relatively inlower proportions (0.89–5.45% of the total flavonoids). How-ever, among the honey samples most of them showed acommon flavonoid profile, consisting of chrysin, quercetin,naringenin, kaempferol, apigenin and galangin suggestingthat they could be utilized as characteristic floral markers forYemeni monofloral, multifloral and cactus honeys [28].

3.4.3 Analysis of other phenols

The total other phenol contents from all analyzed hon-eys were found to be 8.493 mg/100 g honey. Among allother phenols cinnamic acid was found in major amount(8.131 mg/100 g honey), which was 95.74% of the total phe-nols (Table 6). The other phenolic constituents such as maleicacid, phenol and benzoic acid were present in the honey sam-ples in a very low proportion with 0.01, 0.11 and 2.38% of totalphenols, respectively. It can be clearly seen from Table 4 thatthe other phenols contents varied from sample to sample,while the concentration of cinnamic acid was found muchhigher than other phenols almost in all honey samples. How-ever, the maximum concentration of cinnamic acid was foundin sample 2 (1.336 mg/100 g honey). In addition, among 29honey samples, benzoic acid and phenol were found in lessthan 50% of samples, while maleic acid was found only intwo samples with almost negligible amount (sample 19 and27) (Table 6). Therefore, from the quantitative results listedin Tables 4–6, it is obvious that there is no clear correlationfound between the geographical source of the honeys andtheir chemical composition since concentration of each phe-nolic constituents varies in a wide range even for samplescollected from the same region.

4 Conclusions

A simple, sensitive and accurate UHPLC–MS method hasbeen developed for the simultaneous separation, identifica-tion and quantitation of nine phenolic acids, nine flavonoidsand four other phenols in Yemeni honey. In total, 29 honeysamples were analyzed. The total phenolic acids, flavonoidsand other phenols contents in each analyzed honeys werefound in the range of 338 (sample 10) to 3312 (sample 25),122 (sample 13) to 5482 (sample 25) and 2.4 (sample 29) to1342 �g/100 g of honey (sample 2), respectively. The amountof 4-hydroxybenzoic acid (18.896 mg/100 g of honey) wasfound in major quantity (55.17% of the total phenolic acids)than other phenolic acids in all analyzed honeys, while it wasnot detected in sample 4. The main detected flavonoid wasfound to be chrysin (10.516 mg/100 g honey) which corre-sponds to 44.44% of the total flavonoids, while cinnamic acid(8.131 mg/100 g honey) was the major other phenols com-pound which was 95.74% of the total phenols compounds.Among all the investigated phenolic constituents, maleic acidwas found only in sample 19 and 27 with almost negligiblequantity of 0.01% of total other phenols. Also from the re-sults a common flavonoid profile corresponding to quercetin,chrysin, kaempferol, apigenin and galangin was establishedin all honey samples. In addition, the quality parameters andresults obtained by the proposed analysis method confirmedthat the proposed UHPLC–MS methodology could be suc-cessfully applied for the analysis of phenolic constituents invarious natural honeys.

The authors extend their appreciation to the Deanship ofScientific Research, College of Science Research Center, King SaudUniversity, Riyadh, Saudi Arabia for supporting this project.

The authors have declared no conflict of interest.

5 References

[1] Pyrzynska, K., Biesaga, M., TrAC Trends Anal. Chem.2009, 28, 893–902.

[2] Khalil, M. I., Sulaiman, S. A., Boukraa, L., OpenNutraceutl. J. 2010, 3, 6–16.

[3] Lachman, J., Hejtmankova, A., Sykora, J., Karban, J.,Orsak, M., Rygerova, B., Czech. J. Food Sci. 2010, 28,412–426.

[4] Lachman, J., Orsak, M., Hejtmankova, A., Kovakova, E.,LWT-Food Sci. Technol. 2010, 43, 52–58.

[5] Bergman, A., Yanai, J., Weiss, J., Bell, D., David, M. P.,Am. J. Surg. 1983, 145, 374–376.

[6] Phan, T. T., Wang, L., See, P., Grayer, R. J., Chan, S. Y.,Lee, S. T., Biol. Pharm. Bull. 2001, 24, 1373–1379.

[7] Cherbuliez, T., Domerego, R., L’apitherapie., Medecinedes Abeilles, Editions Amyris, Brussels 2003.

[8] Cherbuliez, T., Domerego, R., Medicine from the Bees,Apimondia Standing Commission for Apitherapy, Api-mondia, Rome 2001.



[9] Ferreres, F., Blazquez, M. A., Gil, M. I., Thomas-Barberan,F. A., J. Chromatogr. A 1994, 669, 268–274.

[10] Merken, H. M., Beecher, G. R., J. Agri. Food Chem. 2000,48, 577–599.

[11] Kucuk, M., Kolayh, S., Karaoglu, S., Ulusoy, E.,Baltaci, C., Candan, F., Food Chem. 2007, 100, 526–534.

[12] Yao, L., Jiang, Y., Arcy, B. D., Singanusong, R., Datta, N.,Caffin, N., Raymont, K., J. Agri. Food Chem. 2004, 52,210–214.

[13] Cuevas-Glory, L. F., Pino, J. A., Santiago, L. S., Sauri-Duch, E., Food Chem. 2007, 103,1032–1043.

[14] Oddo, L. P., Bogdanov, S., Apidologie 2004, 35, S2–S3.

[15] Ferreres, F., Tomas-Barberan, F. A., Gil, M. I., Tomas-Lorente, F., J. Sci. Food Agri. 1991, 56, 49–56.

[16] Gil, M. I., Ferreres, F., Ortiz, A., Subra, E., Tomas-Barberan, F. A., J. Agri. Food Chem. 1995, 43, 2833–2838.

[17] Martos, I., Ferreres, F., Tomas-Barberan, F. A., J. Agri.Food Chem. 2000, 48, 1498–1502.

[18] Martos, I., Ferreres, F., Yao, L. D., Arcy, B., Caffin, N.,Tomas-Barberan, F. A., J. Agri. Food Chem. 2000, 48,4744–4748.

[19] Andrade, P., Ferreres, F., Amaral, M. T., J. Liq.Chromatogr. Relat. Technol. 1997, 20, 2281–2288.

[20] Andrade, P., Ferreres, F., Gil, M. I., Tomas-Barberan, F. A.,Food Chem. 1997, 60, 79–84.

[21] Valcarcel, M., Cardenas, S., Simonet, B. M., Moliner-Martinez, Y., Lucena, R., TrAC Trends Anal. Chem. 2008,27, 34–43.

[22] Herrera-Herrera, A. V., Gonzalez-Curbelo, M. A.,Hernandez-Borges, J., Rodrıguez-Delgado, M. A., Anal.Chim. Acta 2012, 734, 1–30.

[23] Perez-Lopez, B., Merkoci, A., Microchim. Acta 2012, 179,1–16.

[24] Wabaidur, S. M., Alothman, Z. A., Khan, M. R., Spec-trochim. Acta Part A 2013, 108, 20–25.

[25] Badjah Hadj Ahmed, A. Y., Obbed, M. S., Wabaidur, S. M.,Alothman, Z. A., Al-Shaalan, N. H., J. Agri. Food Chem.2014, 62, 5443–5450.

[26] Cai, Y. Q., Jiang, G. B., Liu, J. F., Zhou, Q. X., Anal. Chim.Acta 2003, 494, 149–156.

[27] Liang P., Liu Y., Guo L., Zeng J., Lu, H., J. Anal. Atom.Spectrom. 2004, 19, 1489–1492.

[28] Yao, L., Datta, N., Tomas-Barberan, F. A., Ferreres, F., Mar-tos, I., Singanusong, R., Food Chem. 2003, 81, 159–168.

[29] Novakova, L., Vildova, A., Mateus, J. P., Goncalves, T.,Solich, P., Talanta 2010, 82, 1271–1280.

[30] Khan, M. R., Alothman, Z. A., Ghafar, A. A., Wabaidur, S.M., J. Sep. Sci. 2013, 36, 572–577.

[31] Martos, I., Cossentini, M., Ferreres, F., Tomas-Barberan,F. A., J. Agri. Food Chem. 1997, 45, 2824–2829.

[32] Alothman, Z. A., Wabaidur, S. M., Khan, M. R., Ghafar,A. A., Habila, M. A., Yacine, B. H. A., J. Sep. Sci. 2012, 35,2892–2896.


Honey samples collection region and years of cultivar - UMF2598 S. M. Wabaidur et al. J. Sep. Sci....

Documents

Transcript of Honey samples collection region and years of cultivar - UMF2598 S. M. Wabaidur et al. J. Sep. Sci....