Talanta 131 (2015) 185–191
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Dispersive liquid–liquid microextraction for the determination of flavonoid aglycone compounds in honey using liquid chromatography with diode array detection and time-of-flight mass spectrometry Natalia Campillo, Pilar Viñas, Gema Férez-Melgarejo, Manuel Hernández-Córdoba n Department of Analytical Chemistry, Faculty of Chemistry, Regional Campus of International Excellence Campus Mare Nostrum, University of Murcia, E-30100 Murcia, Spain
art ic l e i nf o
a b s t r a c t
Article history: Received 6 June 2014 Received in revised form 23 July 2014 Accepted 27 July 2014 Available online 12 August 2014
A rapid approach for the determination of eight flavonoid aglycone compounds, baicalein, hesperitin, fisetin, naringenin, chrysin, myricetin, quercetin and kaempferol, in honey samples and related products has been optimized and validated. The enriched extracts obtained by dispersive liquid–liquid microextraction (DLLME) were analyzed by liquid chromatography with diode array detection coupled to electrospray ionization and time-of-flight mass spectrometry (LC–DAD–ESI–ToFMS). For DLLME, using acetonitrile and chloroform as disperser and extractant solvents, respectively, a Taguchi experimental method was applied to find the optimal combination of following six factors: disperser and extractant solvent volumes, sodium chloride concentration, pH of the aqueous phase, honey mass and centrifugation time. The sedimented organic phase obtained after centrifugation was evaporated, reconstituted in acetonitrile and submitted to LC. The matrix effect was evaluated, and it was concluded that sample quantification can be carried out against aqueous external standards when using DAD and by matrixmatched calibration in the case of ToFMS. Detection limits in the ranges of 0.4–4 and 0.01–0.5 ng g 1 were obtained for DAD and ToFMS, respectively. Satisfactory recovery values between 80 and 111% were obtained for three spiked samples. Honeys and related products were analyzed and flavonoids were found within a wide range. & 2014 Elsevier B.V. All rights reserved.
Keywords: Honey Flavonoids Dispersive liquid–liquid microextraction (DLLME) Liquid chromatography (LC) Diode array detection (DAD) Time-of-flight mass spectrometry (ToFMS)
1. Introduction The growing interest in functional foods has changed the way in which nutrition is regarded. Functional foods may be natural or be obtained by adding nutrients to foods and drinks to cover dietetic recommendations and to solve deficiencies in a specific nutrient [1,2]. Honey, which was initially used because of its sweetening power, is now widely consumed because of its other important properties, which, together with those of propolis and royal jelly, have led all of them to be considered as natural functional foods [3]. The antioxidant, antibacterial, antiviral, anti-inflammatory, antithrombotic and anti-allergic capacities of honey, propolis and royal jelly are attributed to many factors such as their pH, sugar content, hydrogen peroxide levels and phenolic compounds content, most of which are present as flavonoids [3]. The beneficial effects of flavonoids for human health are due to their hydrogen-donating
n
Corresponding author. Fax: þ 34 868 887682. E-mail address: [email protected] (M. Hernández-Córdoba).
http://dx.doi.org/10.1016/j.talanta.2014.07.083 0039-9140/& 2014 Elsevier B.V. All rights reserved.
antioxidant activity and their capacity to complex the divalent transition metal cations involved in processes forming radicals. Flavonoids have two aromatic rings enclosing a heterocyclic sixmembered ring with oxygen. Modifications of this central C-ring divide flavonoids into different classes: flavones, flavonols, flavanones, isoflavonoids, anthocyanins, flavanols, chalconoids, dihydrochalcones and aurones. The most widespread flavonoids are flavonols and flavanols [4]. The relation between the phenolic compound composition of honey and its botanical and geographical origin has been the object of many studies [5], especially since labeling of the botanical origin is legally protected. The analysis of flavonoids in honey and related products has been reviewed previously [6–8]. The literature shows a very reduced number of gas chromatographic (GC) methods for these determinations because of the low volatility of flavonoid compounds, which makes it necessary to include a derivatization reaction [9–12], although some analyses have been carried out without this step [13]. Capillary electrophoresis (CE) [14] has also been proposed, although by far the most widely used technique for flavonoid quantification in honey and related products is liquid
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chromatography (LC) coupled to UV/visible [15–28], electrochemical [29], mass spectrometry (MS) detectors [30–33] or combination of two detection systems [34–41], where in many cases MS is used only for identification purposes [34–36,41]. The complexity of honey samples, which are rich in polar compounds such as sugars and in minor concentration proteins, means that sample treatment prior to LC analysis is necessary. The literature mentions different sample preparation methods, one being the widely applied method based on that described by Ferreres et al. [42], which combines filtration through the non-ionic polymeric resin Amberlite XAD-2 to remove polar compounds and extraction with ethyl ether as an additional clean-up to totally remove interferents [14–18,22– 26,33,37]. Polymeric reversed-phase sorbents have also been used to isolate flavonoids from honey samples [19,21,32,34–36,38,39] in procedures that are straightforward because the liquid–liquid extraction step after filtration through Amberlite is omitted. Liquid–liquid extraction has been used by other authors as the only clean-up stage [20,31]. Very simple honey sample treatments involving dissolution in aqueous medium and filtration to remove solid particles without eliminating sugars and proteins, have been proposed with different detectors for LC [27,29,30]. In recent years, miniaturized preconcentration methodologies, in keeping with the principles of green analytical chemistry, have revolutionized many sample treatment steps in several aspects. Thus, liquid-phase microextraction techniques (LPME) have become an interesting alternative to traditional sample treatment methods, because they are faster, cheaper and more environmental friendly [43]. Dispersive liquid–liquid microextraction (DLLME) has been used for the preconcentration of a wide number of compounds from different samples including foods [44]. Only two bibliographic references have been found dealing with polyphenol determination in honey samples using DLLME to preconcentrate quercetin [27] and phenolic acids and flavonoids [41]. Both of the above mentioned references use DAD coupled to LC for quantitation purposes. The present work deals with the quantification of eight aglycone flavonoids, two flavones (baicalein and chrysin), two flavanones (hesperetin and naringenin) and four flavonols (fisetin, myricetin, quercetin and kaempferol), in honey and related products using DLLME combined with LC–DAD–ESI–ToFMS.
2. Experimental 2.1. Chemicals and reagents Analytical-reagent grade ethanol, methanol, acetonitrile (ACN), dichloromethane, chloroform, carbon tetrachloride, 1,2-dichloroethane, 1,1,2,2-tetrachloroethane, tetrachloroethylene, 1-octanol, 1-undecanol, 1-dodecanol, toluene, hexane, isooctane, 2-octanone and 2-undecanone were obtained from Sigma (St. Louis, MO, USA). Deionized water was obtained from a Milli-Q water purification system (Millipore, Bedford, MA, USA). Sodium chloride, sodium acetate, formic acid (98%) and concentrated acetic acid were obtained from Fluka (Buchs, Switzerland). Baicalein (5,6,7-trihydroxyflavone, C15H10O5, 98%), naringenin (4ʹ,5,7-trihydroxyflavanone, C15H12H5, Z 95%), myricetin (3,3ʹ,4ʹ,5,5ʹ,7-hexahydroxyflavone, C15H10O8, Z96%) and kaempferol (3,4ʹ,5,7-tetrahydroxyflavone, C15H10O6, 97%) were supplied by Sigma. Hesperetin (3ʹ,5,7-trihydroxy-4ʹ-methoxyflavanone, C16H14O6, Z98%), fisetin (3,3ʹ,4ʹ,7-tetrahydroxyflavone, C15H10O6, Z98%), chrysin (5,7-dihydroxyflavone, C15H10O4, Z98%) and quercetin (3,3ʹ,4ʹ,5,6-pentahydroxyflavone, C15H10O7, 98%) were provided by Fluka. Standard stock solutions of each compound at 500 mg L 1 were prepared in methanol and stored in darkness at 4 1C. Working standard mixture solutions were prepared daily by diluting the stock solutions with pure water.
2.2. Instrumentation The LC system consisted of an Agilent G1312A (Agilent, Waldbronn, Germany) pump operating at a flow-rate of 0.8 mL min 1. The solvents were degassed using an on-line membrane system (Agilent G1379B). The column was maintained at ambient temperature in a thermostated compartment (Agilent G1316A). Separation was performed on a Discovery HS PEG column (Supelco, Bellefonte, PA, USA) (150 mm 4.6 mm, 5 mm), while injection (20 mL) was performed using an autosampler (Agilent G1367A). Autosampler vials of 2 mL capacity provided with 250 mL microinserts with polymeric feet were used. The mobile phase used consisted of a gradient program: 5 min linear from 30:70 to 33:67 ACN/formic acid (0.1% v/v), then a linear gradient from 33% to 45% ACN in 10 min, with this mobile phase being maintained for 3 min. The LC system was first coupled to a diode array multiple wavelength detector (Agilent 1100 G1315C) operating at 280 and 370 nm. The time-of-flight mass spectrometry device (Agilent G6220A) was equipped with an electrospray ionization (ESI) source. Data were collected in negative mode by scanning a m/z 100–1000 range using the following operation parameters: capillary voltage, 2500 V; nebulizer gas pressure, 60 psi; drying gas flow, 12 L min 1; drying gas temperature, 350 1C; fragmentor voltage, 180 V; skimmer voltage, 65 V; octapole RF, 250 V. Applied Biosystems/MDS-SCIEX Analyst QS software (Frankfurt, Germany) was used for data processing. Accurate mass measurements of each peak from the total ion chromatograms were obtained by means of an automated calibrant delivery system, to provide mass correction. The ToF mass spectrometer carried out the internal mass calibration automatically, using a dual-nebulizer electrospray source with an automated calibrant delivery system, which introduces the flow from the outlet of the chromatograph, together with small amounts (about 5 mL min 1) of a calibrating solution, ES–TOF tuning mix reference (Agilent). Ten reference masses were used between 112.985587 and 966.000725 m/z. Mass Hunter software, version B-02-00, was used for autocalibrating and continuously recording the results of internal reference masses and the raw data. Analyses were carried out using the extracted ion chromatogram of the deprotonated molecule of each analyte. The exact theoretical masses based on the formula were calculated using the molecular weight calculator tools of Mass Hunter software, these data being shown in Table 1. The accurate mass spectrum of the analytes was obtained by subtracting the background of the extracted ion chromatogram. The accurate mass of the deprotonated molecule was used for both quantitation and confirmation purposes. The peak areas were used as analytical signals for quantitation. An EBA 20 (Hettich, Tuttlingen, Germany) centrifuge was used for collecting the sedimented phases obtained from the DLLME process.
Table 1 Mass spectral data of the analytes obtained by DLLME–LC–ESI–ToFMS. Compound
Elemental composition
Theoretical mass (m/z)
Calculated mass (m/z)
Error (ppm)
DLa (ng g 1)
Baicalein Hesperetin Fisetin Naringenin Chrysin Myricetin Quercetin Kaempferol
C15H10O5 C16H14O6 C15H10O6 C15H12O5 C15H10O4 C15H10O8 C15H10O7 C15H10O6
270.0528 302.0790 286.0477 272.0685 254.0579 318.0376 302.0427 286.0477
270.0523 302.0795 286.0478 272.0689 254.0586 318.0376 302.0427 286.0478
1.89 1.44 0.28 1.39 2.68 0.49 0.24 0.28
0.06 0.08 0.40 0.09 0.05 0.91 0.22 0.13
a
Calculated for a signal-to-noise ratio of 3.
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2.3. Samples and analytical procedure A total of eight honey samples were obtained from different suppliers. The samples had been marketed as lavender, orange blossom, rosemary, heather, eucalyptus, chesnut, thyme and flowers, but no verification of the floral origin was made. Three samples of commercial liquid propolis (one of them blended with orange juice: propolis 3) and one of royal jelly were also analyzed. One gram of honey was dissolved in 10 mL of acetate buffer solution (0.01 M, pH 3) and placed in a 15 mL screw-cap glass centrifuge tube with conical bottom. Next, a mixture containing 1.5 mL of acetonitrile (disperser solvent) and 150 mL of chloroform (extractant solvent) was rapidly injected into the aqueous mixture by means of a syringe. A cloudy solution, resulting from the dispersion of the fine organic droplets in the aqueous solution, was formed. After a few seconds of extraction, the mixture was centrifuged for 1 min at 3400 rpm, and the dispersed chloroform droplets settled at the bottom of the conical tube. The sedimented phase (volumes in the 110–125 mL range, depending on the sample) was collected by means of a microsyringe and evaporated to dryness using a mild nitrogen stream. The residue was reconstituted in the minimum volume of acetonitrile necessary to inject by means of the autosampler (50 mL) and a 20 mL aliquot was injected in the LC system. Recovery experiments were carried out using honey sample masses of about 20 g spiked with a standard mixture of the flavonoids at concentration levels roughly corresponding to 10and 100-fold the quantification limit obtained for the LC–DAD of each compound. The samples were left to equilibrate at room temperature for at least 30 min before proceeding with the optimized procedure, which was applied to 1 g aliquots of samples. The fortification procedure was applied to three different honey samples at two concentration levels, and three replicates were analyzed in each case.
3. Results and discussion 3.1. Liquid chromatographic separation Reversed phase chromatography was used. Preliminary experiments were carried out using a Tracer Spherisorb C18 ODS2 column and different mixtures (ACN:water and ACN:formic acid) as the mobile phase in the both isocratic and gradient modes. Nevertheless, no efficient separation of the analytes was achieved. The optimal separation conditions were established by injecting 20 μL of an aqueous standard solution containing the analytes at a concentration level of 1 mg mL 1, into the Discovery HS PEG column. The mobile phase was initially composed of 30:70 ACN:1% (v/v) formic acid. The concentration of ACN was then linearly increased to 33% in 5 min and then to 45% in 10 min, a mobile phase composition that was maintained for 3 min. All the analytes eluted during the second linear gradient, except for kaempferol, which eluted while the ACN percentage was maintained at 45%. Different experiments were carried out in order to eliminate the first linear gradient, but lower resolution was always obtained for the analytes. Several formic acid concentrations in the 0.1–1% (v/v) range were assayed and no significant differences were observed in the retention times and chromatographic peak shape; therefore, a concentration of 0.1% was adopted for the acid. Despite assaying different ramps of between 33% and 45% of ACN, hesperetin and fisetin coeluted. Nevertheless, this was not a problem because these compounds were monitored at very different wavelengths in the DAD system and with different values of [M–H] in the ToFMS. The mobile phase flow rate was 0.8 mL min-1, and the elution order and the retention times for the analytes were (1) baicalein (tR ¼8.97 min); (2) hesperetin (tR ¼9.97 min); (3) fisetin (tR ¼ 10.07 min); (4)
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naringenin (tR ¼ 11.61 min); (5) chrysin (tR ¼12.46 min); (6) myricetin (tR ¼12.87 min); (7) quercetin (tR ¼14.52 min) and (8) kaempferol (tR ¼16.02 min). Separation factors (α) in the 1.1–1.2 range and resolution (Rs) between 1.45 and 2.51 were obtained for those analytes monitored at 280 nm (baicalein, hesperetin, naringenin and chrysin), and in the 1.1–1.3 and 2.1–4.8 for those detected at 370 nm (fisetin, myricetin, quercetin and kaempferol). The exact mass measurements and mass errors obtained in the ToFMS for molecular ions are shown in Table 1. 3.2. Optimization of the DLLME conditions The first step in the DLLME optimization procedure was to select the most appropriate disperser and extractant solvents. For this purpose, 1 g of a spiked honey (at 1 mg g 1 concentration level for all compounds) was dissolved in 10 mL of water and 150 mL of different organic solvents were assayed using 1 mL of ACN as disperser solvent. Lower extraction efficiencies were attained for solvents of lower density than water (1-undecanol, 1-dodecanol, 1-octanol, 2-octanone, 2-undecanone, toluene, hexane and isooctane) than those obtained with organic solvents denser than water. Carbon tetrachloride, tetrachloroethane, chloroform, tetrachloroethylene, 1,2-dichloroethane and dichloromethane were the extractants assayed. Dichloromethane was discarded because no settled phase was obtained owing to its high water solubility. Tetrachloroethylene was also discarded because of the long time required to evaporate the sedimented phase and carbon tetrachloride because no preconcentration of the analytes was attained. As shown in Fig. 1, chloroform extracted all the analytes with higher efficiency than 1,2-dichloroethane and tetrachloroethane, and so it was selected as extractant solvent. The main parameter considered for the selection of the disperser solvent was its miscibility in the extraction solvent and the aqueous phase. ACN, methanol and ethanol have this property, and were tested in this study using 1.0 mL of each solvent and 150 mL of chloroform as the extractant solvent. ACN provided the best discernible settled phase and so was selected; moreover, it was in close consonance with the mobile phase. The Taguchi experimental method, an orthogonal array design, was applied to study the possible influence on DLLME of six factors (each at three levels) which might influence the dispersion, extraction and collection efficiency namely, organic extractant
Fig. 1. Selection of extractant solvent for DLLME. Aqueous phase volume, 10 mL; organic solvent volume, 150 mL; and disperser solvent, 1 mL ACN.
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volume, disperser solvent volume, honey sample mass, centrifugation time, pH and sodium chloride concentration of the aqueous phase. For this purpose, 10 mL of an aqueous solution containing different masses, in the 0.5–1.5 g range, of a fortified honey at concentration levels of 1 mg g 1, was used. The volumes of the extractant and disperser solvents were varied between 50–150 mL and 0.5–1.5 mL, respectively. The effect of ionic strength was studied with NaCl concentrations between 0% and 5% m/v and the pH of the aqueous solution between 3 and 6. Centrifugation times, applied to disrupt the dispersion of the organic droplets, of 1, 3 and 5 min at 3400 rpm were studied. In all cases, the sedimented phase was evaporated and the residue reconstituted in 50 mL of ACN. When the honey mass was increased from 0.5 to 1.0 g, the mean response increased and then was practically constant with a 1.5 g sample mass, so a sample mass of 1.0 g was selected. The highest extraction efficiencies were obtained with 1.5 mL of ACN and 150 mL of chloroform. Varying the pH between 3 and 6 with 0.01 M buffer solutions showed that optimal results were obtained at pH 3, which was selected. Extraction efficiency was higher for all the analytes in the absence of salt and, thus, its addition to the extraction solution was discarded. The centrifugation time necessary to disrupt the cloudy solution was not seen to be a significant factor for extraction efficiency, and so 1 min was adopted for this step at the maximum speed supported by the centrifugal tubes used. A statistical analysis of variance (ANOVA) test was performed to discriminate which parameters significantly affected extraction efficiency (Table 2). From the calculated variance ratios, F, it was deduced that only one factor considered in the experimental design was statistically significant, at a 95% confidence level (in all cases the calculated F was greater than the critical value). This variable was the extractant volume. The contribution of the residual error to the signal variability indicates the goodness of the experimental design used. It is noteworthy that the application of the ANOVA test showed that the disperser volume was not a variable of statistically significant effect on the DLLME extraction efficiency, nevertheless its contribution of the residual error to the signal is not negligible.
characteristics are shown in Table 3. The repeatability was calculated using the relative standard deviation for ten successive analyses of heather honey fortified at a concentration level of 300 ng g 1 for all compounds (Table 3) and values lower than 11% were obtained. Fig. 2 shows the DLLME combined with LC–DAD elution profiles obtained in the analysis of a standard solution mixture. In contrast, a matrix effect was detected when LC–ESI–ToFMS was used, aqueous standard calibration providing higher slopes for all the analytes than standard additions. Nevertheless, the application of a one-way ANOVA test to the slopes obtained for the different matrices pointed to the absence of significant differences at 95% confidence level, p values varying in the 0.05–0.808 range depending on the compound (Table 4). Therefore, a matrix-matched calibration method Table 3 Analytical characteristics of the DLLME combined with the LC–DAD method. Compound
λ (nm)
Slopea (mL ng 1)
Correlation coefficient
DLb (ng mL 1)
RSDc (%)
Baicalein Hesperetin Fisetin Naringenin Chrysin Myricetin Quercetin Kaempferol
280 280 370 280 280 370 370 370
3.50 7 0.10 3.107 0.08 0.357 0.02 2.83 7 0.11 4.84 7 0.18 0.447 0.03 1.42 7 0.06 2.81 7 0.10
0.9958 0.9951 0.9963 0.9984 0.9970 0.9959 0.9984 0.9978
0.4 0.5 3.9 0.8 0.4 4.1 1.3 0.7
5.1 6.2 11 7.3 4.9 11 8.3 6.0
(4) (5) (39) (8) (4) (41) (13) (7)
Values in brackets are ng g 1. a b c
Mean value7 standard deviation (n¼ 5). Calculated for S/N ¼3. Calculated at a concentration level of 300 ng g 1 for each compound (n¼ 10).
3.3. Analytical characteristics of the method To study the relevance of any matrix effect, an ANOVA test was used to compare the slopes of aqueous standards calibration graphs and those obtained when the standard additions method was applied to three different honey samples (eucalyptus, thyme and orange blossom). The absence of a matrix effect when using LC–DAD confirmed as the “p” values were higher than 0.05 for the eight analytes in the three samples. Consequently, quantification of the samples by DLLME combined with LC–DAD was carried out against external aqueous standards; the corresponding analytical Table 2 Results of the analysis of variance for mean response. Variation source Sample mass Dispersant volume Extractant volume pH Ionic strength Centrifugation time Error Total
Degrees of freedom
Sum of squares
Mean of squares
F
2 2
30,773 217,756
15,386 108,878
0.32 0.733 3.7 2.25 0.142 26.4
2
510,370
255,185
5.27 0.020 61.9
2 2 2
54,481 4717 6437
27,240 2358 3219
0.56 0.582 0.05 0.953 0.07 0.936
14 26
677,814 48,415 1,502,348
P
Contribution (%)
6.6 0.6 0.8
Fig. 2. Elution profiles obtained for an aqueous standard solution using the DLLME combined with LC–DAD optimized procedure. The concentrations of the compounds were (1) Baicalein, 15 ng mL 1; (2) hesperetin, 20 ng mL 1; (3) fisetin, 150 ng mL 1; (4) naringenin 20 ng mL 1; (5) chrysin, 10 ng mL 1; (6) myricetin, 60 ng mL 1; (7) quercetin, 40 ng mL 1 and (8) kaempferol, 20 ng mL 1.
N. Campillo et al. / Talanta 131 (2015) 185–191
was adopted for quantification by LC–ESI–ToFMS. The comparison of the standard deviations of the different slopes for each compound did not show significant differences (F values of 0.366–2.92). The regression coefficients obtained under the selected conditions showed a directly proportional relationship between the amount of analyte extracted and the corresponding peak area, being in all cases higher than 0.997. Detection limits (DLs) and quantification limits (QLs) were calculated on the basis of three and ten times the signal-to-noise ratios, respectively. The data obtained for DLs appear in Table 4, while QLs in the 0.035–1.6 ng g 1 range were obtained. When comparing the DLs obtained using DAD and ESI–ToFMS, an increase in sensitivity of between 4.5 and 10 was observed in favor of ToF, depending on the compound. When the DLs obtained by DLLME combined with LC– DAD were compared with previously reported data, an identical value was obtained for quercetin [27], and lower values for hesperetin, quercetin, chrysin, myricetin and kaempferol than those obtained by Campone et al. [41], considering the higher injection volume and the reconstitution of the DLLME organic extract in a lower volume in the procedure presented here. The slopes obtained by aqueous calibration using DLLME–LC–DAD– ESI–ToFMS were compared with those obtained in the absence of a preconcentration step, pointing to an increase in sensitivity of between 10 (for fisetin and myricetin) and 80-fold for chrysin.
showed the highest content for fisetin, naringenin, chrysin and kaempferol, while hesperetin was found at higher concentration in the orange blossom honey. Recovery studies were carried out in order to verify the accuracy of the proposed method by fortifying three samples (heather honey, propolis 2 and royal jelly) in triplicate at two concentration levels in the range 15–1000 ng g 1, depending on the compound. The results obtained appear in Table 6. Recovery values ranged between 80% and 111%, with an average recovery7standard deviation (n¼ 144) of 9777. There were no differences in the RSD values between the different samples, RSD ranging between 5% and 14%. Table 6 Recovery studies. Compound
Spiking level (ng g 1)
Concentration founda (ng g 1) Heather honey
Propolis 2
Royal jelly
Baicalein
15 150
137 1 1557 17
12 7 2 141 7 12
629 743 754 767
Hesperetin
15 150
787 7 205 7 15
81 7 8 199 7 21
18 72 165 715
100 1000
203 7 26 986 7 81
127 7 16 936 7 84
263 731 1094 7121
Naringenin
25 250
217 3 2677 24
109 7 9 308 7 27
60 77 316 728
Chrysin
15 150
606 7 58 748 7 81
271 7 14 431 7 38
69 77 201 719
Fisetin
3.4. Analysis of samples and validation of the method The optimized procedure was applied to eight different honeys, three propolis samples and one royal jelly. Table 5 shows the results obtained using the DLLME combined with LC–ESI–ToFMS, which are similar to those obtained with DAD as detection system. Myricetin was not found in any of the samples above its detection limit (0.9 ng g 1), whereas baicalein was found in four of the twelve samples analyzed at concentration levels ranging from 33 to 622 ng g 1. Of note is the observation that the unique analyte found in lavender honey sample was chrysin. Of the different honeys analyzed, rosemary honey
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Myricetin
100 1000
1037 13 956 7 128
94 7 11 930 7 98
88 712 1056 7129
Quercetin
50 500
707 8 532 7 47
160 7 12 628 7 53
241 725 679 755
Kaempferol
25 250
1537 14 4107 39
355 7 37 603 7 48
298 727 518 737
a
Mean 7 standard deviation (n¼ 3).
Table 4 Slopesa of standard additions calibration graphs by DLLME combined with LC–ToFMS (mL ng 1). Sample
Baicalein
Hesperetin
Fisetin
Naringenin
Chrysin
Myricetin
Quercetin
Kaempferol
Aqueous Eucalyptus honey Heather honey Thyme honey Propolis 1 Royal jelly
38,9007 1230 32,780 7 1860 31,6807 1790 30,340 7 2000 33,0007 1650 31,0607 1600
59,0107 2410 59,460 7 5130 63,0007 4930 62,820 7 5260 62,540 7 4390 61,840 7 5910
6504 7202 5260 7412 6100 7566 5658 7430 5246 7460 5313 7621
165,0007 6300 50,220 7 4940 51,1607 5500 55,630 7 5900 49,880 7 4250 50,4407 2660
395,000 711,100 267,100 712800 253,100 713200 283,700 717400 256,800 715400 270,500 719300
5320 7234 4440 7421 4569 7398 4381 7459 4254 7439 4621 7489
45,030 7 2200 33,3007 2860 34,7307 3020 30,2107 2540 31,7607 2920 35,020 7 3510
132,7007 6580 104,3007 7520 107,2007 8070 102,9007 7070 108,4007 9080 105,4007 8780
a
Mean 7 standard deviation (n ¼5).
Table 5 Flavonoids contenta in the analyzed samples (ng g 1). Sample
Baicalein
Hesperetin
Fisetin
Naringenin
Chrysin
Quercetin
Kaempferol
Honey lavender Orange blossom Rosemary Heather Eucalyptus Chesnut Thyme Flowers Royal jelly Propolis 1 Propolis 2 Propolis 3
ND ND ND ND ND 2147 15 ND 337 4 622 748 ND ND 2667 23
ND 620 7 35 827 6 66 7 3 657 4 307 3 327 3 35 74 2.0 70.3 466 7 23 617 5 207 715
ND 4757 32 1650 7 66 116 710 4177 22 997 12 73 710 292 7 11 149 7 15 8677 70 477 5 7147 36
ND 237 2 49 7 9 ND ND 147 2 167 1 357 4 417 3 257 3 757 3 127 1
2147 20 630 7 14 8137 34 6197 25 425 7 31 284 7 25 205 7 11 1257 12 657 5 846 7 58 2677 19 637 4
ND 727 7 1267 11 137 1 13507 55 11087 60 206 7 10 1327 13 205 7 14 1885 7 83 1017 8 4747 29
ND 7147 36 3806 7 100 143 7 6 241 7 13 455 7 22 1017 11 9017 15 294 7 15 498 7 20 3397 17 607 3
ND means not detected. a
Mean 7 standard deviation (n¼ 3).
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the standards, non-spiked and spiked samples analyzed. The mass error was calculated by using the theoretical mass values provided in Table 1 as reference, which were given by the ToF software. The errors obtained for all the standards and spiked and non-spiked samples were between 1.88 and 2.8 ppm. These values were, in all cases, lower than the accepted accuracy threshold of 5 ppm necessary to confirm elemental compositions. Fig. 3 shows the DLLME combined with LC–ESI–ToFMS extracted ion chromatograms (EICs) obtained for the flowers honey sample fortified at 200 ng g 1.
4. Conclusion The simple extraction and preconcentration of the analytes from honey using a low volume of organic solvent and the environmentally friendly miniaturized technique DLLME allows quantification at low levels to be carried out. Eight flavonoid aglycones can be separated by LC, dual detection with DAD and ToFMS being appropriate for the final measurement. Accurate mass measurements, concordance in retention times and UV spectra provide unequivocal identification of the individual analytes.
Acknowledgments The authors acknowledge to Comunidad Autónoma de la Región de Murcia (CARM, Fundación Séneca, Project 15217/PI/10) and the Spanish MEC (CTQ2012-34722) for financial support. G. Férez-Melgarejo acknowledges a fellowship financed by CARM. References
Fig. 3. Extracted ion chromatograms by DLLME combined with LC–ESI–ToFMS for flowers honey sample fortified at 200 ng g 1 for all compounds. (1) Baicalein, (2) hesperetin, (3) fisetin, (4) naringenin, (5) chrysin, (6) myricetin, (7) quercetin and (8) kaempferol.
The flavonoid compounds were identified according to their retention times, the UV spectra and molecular weights compared with commercial standards. Accurate masses were obtained for all
[1] K. Brandt, L.P. Christensen, J. Hansen-Moller, S.L. Hansen, J. Haraldsdottir, L. Jespersen, S. Purup, A. Kharazmi, V. Barkholt, H. Frokiaer, M. Kobaek-Larse, Trends Food Sci. Technol. 15 (2004) 384–393. [2] C. Sánchez-Moreno, L. Plaza, B. de Ancos, P. Cano, J. Sci. Food Agric. 83 (2003) 430–439. [3] M. Viuda-Martos, Y. Ruiz-Navajas, J. Fernández-López, J.A. Pérez-Álvarez, J. Food Sci. 73 (2008) R117–R124. [4] P. Viñas, N. Campillo, Gas chromatography–mass spectrometry analysis of polyphenols in foods, in: R.R. Watson, V.R. Preedy, S. Zibadi (Eds.), Polyphenols Human Health and Disease, Elsevier, London, 2014. [5] V. Kaskoniene, P.R. Venskutonis, Comp. Rev. Food Sci. Food Saf. 9 (2010) 620–634. [6] H.M. Merken, G.R. Beecher, J. Agric. Food Chem. 48 (2000) 577–599. [7] A.M. Gómez-Caravaca, M. Gómez-Romero, D. Arráez-Román, A. SeguraCarretero, A. Fernández-Gutiérrez, J. Pharm. Biomed. Anal. 41 (2006) 1220–1234. [8] K. Pyrzynska, M. Biesaga, Trends Anal. Chem. 28 (2009) 893–902. [9] A. Uzel, K. Sorkun, O. Oncag, D. Cogulu, O. Gencay, B. Salih, Microbiol. Res. 160 (2005) 189–195. [10] M. Campo Fernández, O. Cuesta-Rubio, A. Rosado Pérez, R. Montes De Oca Porto, I. Márquez Hernández, A. Lisa Piccinelli, L. Rastrelli, J. Agric. Food Chem. 56 (2008) 9927–9932. [11] V.A. Isidorov, A.G. Isidorova, L. Sczczepaniak, U. Czyzewska, Food Chem. 115 (2009) 1056–1063. [12] N. Kalogeropoulos, S.J. Konteles, E. Troullidou, I. Mourtzinos, V.T. Karathanos, Food Chem. 116 (2009) 452–461. [13] W. Maciejewicz, M. Daniewski, K. Bal, W. Markowski, Chromatographia 53 (2001) 343–346. [14] D. Arráez-Román, A.M. Gómez-Caravaca, M. Gómez-Romero, A. SeguraCarretero, A. Fernández-Gutiérrez, J. Pharm. Biomed. Anal. 41 (2006) 1648–1656. [15] I. Martos, F. Ferreres, L.H. Yao, B. D´Arcy, N. Caffin, F.A. Tomás-Barberán, J. Agric. Food Chem. 48 (2000) 4744–4748. [16] L.H. Yao, Y.M. Jiang, B. D´Arcy, R.T. Singanusong, N. Datta, N. Caffin, K. Raymont, J. Agric. Food Chem. 52 (2004) 210–214. [17] L. Estevinho, A.P. Pereira, L. Moreira, L.G. Dias, E. Pereira, Food Chem. Toxicol. 46 (2008) 3774–3779. [18] M.O. Iurlina, A.I. Saiz, R. Fritz, G.D. Manrique, Food Chem. 115 (2009) 1141–1149. [19] E. Pichichero, L. Canuti, A. Canini, J. Sci. Food Agric. 89 (2009) 609–616. [20] M.R. Hadjmohammadi, S. Nazari, K. Kamel, Chromatographia 69 (2009) 1291–1297.
N. Campillo et al. / Talanta 131 (2015) 185–191
[21] R. Socha, L. Juszczak, S. Pietrzyk, T. Fortuna, Food Chem. 113 (2009) 568–574. [22] I. Escriche, M. Kadar, M. Juan-Borras, E. Domenech, Food Res. Int. 44 (2011) 1504–1513. [23] M.I. Isla, A. Craig, R. Ordoñez, C. Zampini, J. Sayago, E. Bedascarrasbure, A. Álvarez, V. Salomon, L. Maldonado, LWT—Food Sci. Technol. 9 (2011) 1922–1930. [24] O. Escuredo, L.R. Silva, P. Valentao, M.C. Seijo, P.B. Andrade, Food Chem. 130 (2012) 671–678. [25] A. Cavazza, C. Corradini, M. Musci, P. Salvadeo, J. Sci. Food Agric 93 (2013) 1169–1175. [26] I. Escriche, M. Kadar, M. Juan-Borras, E. Domenech, Food Chem. 142 (2014) 135–143. [27] E. Ranjbari, P. Biparva, M.R. Hadjmohammadi, Talanta 89 (2012) 117–123. [28] A. Perna, I. Intaglietta, A. Simonetti, E. Gambacorta, Int. Food Sci. Technol. 48 (2013) 1899–1908. [29] Y. Liang, W. Cao, W.J. Chen, X.H. Xiao, J.B. Zheng, Food Chem. 114 (2009) 1537–1541. [30] M. Biesaga, K. Pyrzynska, J. Chromatogr. A 1216 (2009) 6620–6626. [31] A. Ciric, H. Prosen, M. Jelikic-Stankov, P. Durdevic, Talanta 99 (2012) 780–790. [32] S. Keckes, U. Gasic, T.C. Velickovic, D. Milojkovic-Opsenica, M. Natic, Z. Tesic, Food Chem. 138 (2013) 32–40. [33] I. Sergiel, P. Pohl, M. Biesaga, Food Chem. 145 (2014) 404–408. [34] N. Gheldof, X.H. Wang, N.J. Engeseth, J. Agric. Food Chem. 50 (2002) 5870–5877.
191
[35] K. Petrus, H. Schwartz, G. Sontag, Anal. Bioanal. Chem. 400 (2011) 2555–2563. [36] A. Michalkiewicz, M. Biesaga, K. Pyrzynska, J. Chromatogr. A 1187 (2008) 18–24. [37] P. Truchado, E. Tourn, L.M. Gallez, D.A. Moreno, F. Ferreres, F.A. TomásBarberán, J. Agric. Food Chem. 58 (2010) 12678–12685. [38] J.M. Álvarez-Suárez, A.M. González-Paramas, C. Santos-Buelga, M. Battino, J. Agric. Food Chem. 58 (2010) 9817–9824. [39] J. Bertoncelj, T. Polak, U. Kropf, M. Korosec, T. Golob, Food Chem. 127 (2011) 296–302. [40] J.H. Zhou, L.H. Yao, Y. Li, L.Z. Chen, L.M. Wu, J. Zhao, Food Chem. 145 (2014) 941–949. [41] L. Campone, A.L. Piccinelli, I. Pagano, S. Carabetta, R. Di Sanzo, M. Russo, L. Rastrelli, J. Chromatogr. A 1334 (2014) 9–15. [42] F. Ferreres, F.A. Tomás-Barberán, C. Soler, C. García Viguera, A. Ortiz, F. Tomás Lorente, Apidologie 25 (1994) 21–30. [43] L. Ramos, J. Chromatogr. A 1221 (2012) 84–98. [44] P. Viñas, N. Campillo, I. López-García, M. Hernández-Córdoba, Anal. Bioanal. Chem. 406 (2014) 2067–2099.
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Dispersive liquid–liquid microextraction for the determination of flavonoid aglycone compounds in honey using liquid chromatography with diode array detection and time-of-flight mass spectrometry Natalia Campillo, Pilar Viñas, Gema Férez-Melgarejo, Manuel Hernández-Córdoba n Department of Analytical Chemistry, Faculty of Chemistry, Regional Campus of International Excellence Campus Mare Nostrum, University of Murcia, E-30100 Murcia, Spain
art ic l e i nf o
a b s t r a c t
Article history: Received 6 June 2014 Received in revised form 23 July 2014 Accepted 27 July 2014 Available online 12 August 2014
A rapid approach for the determination of eight flavonoid aglycone compounds, baicalein, hesperitin, fisetin, naringenin, chrysin, myricetin, quercetin and kaempferol, in honey samples and related products has been optimized and validated. The enriched extracts obtained by dispersive liquid–liquid microextraction (DLLME) were analyzed by liquid chromatography with diode array detection coupled to electrospray ionization and time-of-flight mass spectrometry (LC–DAD–ESI–ToFMS). For DLLME, using acetonitrile and chloroform as disperser and extractant solvents, respectively, a Taguchi experimental method was applied to find the optimal combination of following six factors: disperser and extractant solvent volumes, sodium chloride concentration, pH of the aqueous phase, honey mass and centrifugation time. The sedimented organic phase obtained after centrifugation was evaporated, reconstituted in acetonitrile and submitted to LC. The matrix effect was evaluated, and it was concluded that sample quantification can be carried out against aqueous external standards when using DAD and by matrixmatched calibration in the case of ToFMS. Detection limits in the ranges of 0.4–4 and 0.01–0.5 ng g 1 were obtained for DAD and ToFMS, respectively. Satisfactory recovery values between 80 and 111% were obtained for three spiked samples. Honeys and related products were analyzed and flavonoids were found within a wide range. & 2014 Elsevier B.V. All rights reserved.
Keywords: Honey Flavonoids Dispersive liquid–liquid microextraction (DLLME) Liquid chromatography (LC) Diode array detection (DAD) Time-of-flight mass spectrometry (ToFMS)
1. Introduction The growing interest in functional foods has changed the way in which nutrition is regarded. Functional foods may be natural or be obtained by adding nutrients to foods and drinks to cover dietetic recommendations and to solve deficiencies in a specific nutrient [1,2]. Honey, which was initially used because of its sweetening power, is now widely consumed because of its other important properties, which, together with those of propolis and royal jelly, have led all of them to be considered as natural functional foods [3]. The antioxidant, antibacterial, antiviral, anti-inflammatory, antithrombotic and anti-allergic capacities of honey, propolis and royal jelly are attributed to many factors such as their pH, sugar content, hydrogen peroxide levels and phenolic compounds content, most of which are present as flavonoids [3]. The beneficial effects of flavonoids for human health are due to their hydrogen-donating
n
Corresponding author. Fax: þ 34 868 887682. E-mail address: [email protected] (M. Hernández-Córdoba).
http://dx.doi.org/10.1016/j.talanta.2014.07.083 0039-9140/& 2014 Elsevier B.V. All rights reserved.
antioxidant activity and their capacity to complex the divalent transition metal cations involved in processes forming radicals. Flavonoids have two aromatic rings enclosing a heterocyclic sixmembered ring with oxygen. Modifications of this central C-ring divide flavonoids into different classes: flavones, flavonols, flavanones, isoflavonoids, anthocyanins, flavanols, chalconoids, dihydrochalcones and aurones. The most widespread flavonoids are flavonols and flavanols [4]. The relation between the phenolic compound composition of honey and its botanical and geographical origin has been the object of many studies [5], especially since labeling of the botanical origin is legally protected. The analysis of flavonoids in honey and related products has been reviewed previously [6–8]. The literature shows a very reduced number of gas chromatographic (GC) methods for these determinations because of the low volatility of flavonoid compounds, which makes it necessary to include a derivatization reaction [9–12], although some analyses have been carried out without this step [13]. Capillary electrophoresis (CE) [14] has also been proposed, although by far the most widely used technique for flavonoid quantification in honey and related products is liquid
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chromatography (LC) coupled to UV/visible [15–28], electrochemical [29], mass spectrometry (MS) detectors [30–33] or combination of two detection systems [34–41], where in many cases MS is used only for identification purposes [34–36,41]. The complexity of honey samples, which are rich in polar compounds such as sugars and in minor concentration proteins, means that sample treatment prior to LC analysis is necessary. The literature mentions different sample preparation methods, one being the widely applied method based on that described by Ferreres et al. [42], which combines filtration through the non-ionic polymeric resin Amberlite XAD-2 to remove polar compounds and extraction with ethyl ether as an additional clean-up to totally remove interferents [14–18,22– 26,33,37]. Polymeric reversed-phase sorbents have also been used to isolate flavonoids from honey samples [19,21,32,34–36,38,39] in procedures that are straightforward because the liquid–liquid extraction step after filtration through Amberlite is omitted. Liquid–liquid extraction has been used by other authors as the only clean-up stage [20,31]. Very simple honey sample treatments involving dissolution in aqueous medium and filtration to remove solid particles without eliminating sugars and proteins, have been proposed with different detectors for LC [27,29,30]. In recent years, miniaturized preconcentration methodologies, in keeping with the principles of green analytical chemistry, have revolutionized many sample treatment steps in several aspects. Thus, liquid-phase microextraction techniques (LPME) have become an interesting alternative to traditional sample treatment methods, because they are faster, cheaper and more environmental friendly [43]. Dispersive liquid–liquid microextraction (DLLME) has been used for the preconcentration of a wide number of compounds from different samples including foods [44]. Only two bibliographic references have been found dealing with polyphenol determination in honey samples using DLLME to preconcentrate quercetin [27] and phenolic acids and flavonoids [41]. Both of the above mentioned references use DAD coupled to LC for quantitation purposes. The present work deals with the quantification of eight aglycone flavonoids, two flavones (baicalein and chrysin), two flavanones (hesperetin and naringenin) and four flavonols (fisetin, myricetin, quercetin and kaempferol), in honey and related products using DLLME combined with LC–DAD–ESI–ToFMS.
2. Experimental 2.1. Chemicals and reagents Analytical-reagent grade ethanol, methanol, acetonitrile (ACN), dichloromethane, chloroform, carbon tetrachloride, 1,2-dichloroethane, 1,1,2,2-tetrachloroethane, tetrachloroethylene, 1-octanol, 1-undecanol, 1-dodecanol, toluene, hexane, isooctane, 2-octanone and 2-undecanone were obtained from Sigma (St. Louis, MO, USA). Deionized water was obtained from a Milli-Q water purification system (Millipore, Bedford, MA, USA). Sodium chloride, sodium acetate, formic acid (98%) and concentrated acetic acid were obtained from Fluka (Buchs, Switzerland). Baicalein (5,6,7-trihydroxyflavone, C15H10O5, 98%), naringenin (4ʹ,5,7-trihydroxyflavanone, C15H12H5, Z 95%), myricetin (3,3ʹ,4ʹ,5,5ʹ,7-hexahydroxyflavone, C15H10O8, Z96%) and kaempferol (3,4ʹ,5,7-tetrahydroxyflavone, C15H10O6, 97%) were supplied by Sigma. Hesperetin (3ʹ,5,7-trihydroxy-4ʹ-methoxyflavanone, C16H14O6, Z98%), fisetin (3,3ʹ,4ʹ,7-tetrahydroxyflavone, C15H10O6, Z98%), chrysin (5,7-dihydroxyflavone, C15H10O4, Z98%) and quercetin (3,3ʹ,4ʹ,5,6-pentahydroxyflavone, C15H10O7, 98%) were provided by Fluka. Standard stock solutions of each compound at 500 mg L 1 were prepared in methanol and stored in darkness at 4 1C. Working standard mixture solutions were prepared daily by diluting the stock solutions with pure water.
2.2. Instrumentation The LC system consisted of an Agilent G1312A (Agilent, Waldbronn, Germany) pump operating at a flow-rate of 0.8 mL min 1. The solvents were degassed using an on-line membrane system (Agilent G1379B). The column was maintained at ambient temperature in a thermostated compartment (Agilent G1316A). Separation was performed on a Discovery HS PEG column (Supelco, Bellefonte, PA, USA) (150 mm 4.6 mm, 5 mm), while injection (20 mL) was performed using an autosampler (Agilent G1367A). Autosampler vials of 2 mL capacity provided with 250 mL microinserts with polymeric feet were used. The mobile phase used consisted of a gradient program: 5 min linear from 30:70 to 33:67 ACN/formic acid (0.1% v/v), then a linear gradient from 33% to 45% ACN in 10 min, with this mobile phase being maintained for 3 min. The LC system was first coupled to a diode array multiple wavelength detector (Agilent 1100 G1315C) operating at 280 and 370 nm. The time-of-flight mass spectrometry device (Agilent G6220A) was equipped with an electrospray ionization (ESI) source. Data were collected in negative mode by scanning a m/z 100–1000 range using the following operation parameters: capillary voltage, 2500 V; nebulizer gas pressure, 60 psi; drying gas flow, 12 L min 1; drying gas temperature, 350 1C; fragmentor voltage, 180 V; skimmer voltage, 65 V; octapole RF, 250 V. Applied Biosystems/MDS-SCIEX Analyst QS software (Frankfurt, Germany) was used for data processing. Accurate mass measurements of each peak from the total ion chromatograms were obtained by means of an automated calibrant delivery system, to provide mass correction. The ToF mass spectrometer carried out the internal mass calibration automatically, using a dual-nebulizer electrospray source with an automated calibrant delivery system, which introduces the flow from the outlet of the chromatograph, together with small amounts (about 5 mL min 1) of a calibrating solution, ES–TOF tuning mix reference (Agilent). Ten reference masses were used between 112.985587 and 966.000725 m/z. Mass Hunter software, version B-02-00, was used for autocalibrating and continuously recording the results of internal reference masses and the raw data. Analyses were carried out using the extracted ion chromatogram of the deprotonated molecule of each analyte. The exact theoretical masses based on the formula were calculated using the molecular weight calculator tools of Mass Hunter software, these data being shown in Table 1. The accurate mass spectrum of the analytes was obtained by subtracting the background of the extracted ion chromatogram. The accurate mass of the deprotonated molecule was used for both quantitation and confirmation purposes. The peak areas were used as analytical signals for quantitation. An EBA 20 (Hettich, Tuttlingen, Germany) centrifuge was used for collecting the sedimented phases obtained from the DLLME process.
Table 1 Mass spectral data of the analytes obtained by DLLME–LC–ESI–ToFMS. Compound
Elemental composition
Theoretical mass (m/z)
Calculated mass (m/z)
Error (ppm)
DLa (ng g 1)
Baicalein Hesperetin Fisetin Naringenin Chrysin Myricetin Quercetin Kaempferol
C15H10O5 C16H14O6 C15H10O6 C15H12O5 C15H10O4 C15H10O8 C15H10O7 C15H10O6
270.0528 302.0790 286.0477 272.0685 254.0579 318.0376 302.0427 286.0477
270.0523 302.0795 286.0478 272.0689 254.0586 318.0376 302.0427 286.0478
1.89 1.44 0.28 1.39 2.68 0.49 0.24 0.28
0.06 0.08 0.40 0.09 0.05 0.91 0.22 0.13
a
Calculated for a signal-to-noise ratio of 3.
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2.3. Samples and analytical procedure A total of eight honey samples were obtained from different suppliers. The samples had been marketed as lavender, orange blossom, rosemary, heather, eucalyptus, chesnut, thyme and flowers, but no verification of the floral origin was made. Three samples of commercial liquid propolis (one of them blended with orange juice: propolis 3) and one of royal jelly were also analyzed. One gram of honey was dissolved in 10 mL of acetate buffer solution (0.01 M, pH 3) and placed in a 15 mL screw-cap glass centrifuge tube with conical bottom. Next, a mixture containing 1.5 mL of acetonitrile (disperser solvent) and 150 mL of chloroform (extractant solvent) was rapidly injected into the aqueous mixture by means of a syringe. A cloudy solution, resulting from the dispersion of the fine organic droplets in the aqueous solution, was formed. After a few seconds of extraction, the mixture was centrifuged for 1 min at 3400 rpm, and the dispersed chloroform droplets settled at the bottom of the conical tube. The sedimented phase (volumes in the 110–125 mL range, depending on the sample) was collected by means of a microsyringe and evaporated to dryness using a mild nitrogen stream. The residue was reconstituted in the minimum volume of acetonitrile necessary to inject by means of the autosampler (50 mL) and a 20 mL aliquot was injected in the LC system. Recovery experiments were carried out using honey sample masses of about 20 g spiked with a standard mixture of the flavonoids at concentration levels roughly corresponding to 10and 100-fold the quantification limit obtained for the LC–DAD of each compound. The samples were left to equilibrate at room temperature for at least 30 min before proceeding with the optimized procedure, which was applied to 1 g aliquots of samples. The fortification procedure was applied to three different honey samples at two concentration levels, and three replicates were analyzed in each case.
3. Results and discussion 3.1. Liquid chromatographic separation Reversed phase chromatography was used. Preliminary experiments were carried out using a Tracer Spherisorb C18 ODS2 column and different mixtures (ACN:water and ACN:formic acid) as the mobile phase in the both isocratic and gradient modes. Nevertheless, no efficient separation of the analytes was achieved. The optimal separation conditions were established by injecting 20 μL of an aqueous standard solution containing the analytes at a concentration level of 1 mg mL 1, into the Discovery HS PEG column. The mobile phase was initially composed of 30:70 ACN:1% (v/v) formic acid. The concentration of ACN was then linearly increased to 33% in 5 min and then to 45% in 10 min, a mobile phase composition that was maintained for 3 min. All the analytes eluted during the second linear gradient, except for kaempferol, which eluted while the ACN percentage was maintained at 45%. Different experiments were carried out in order to eliminate the first linear gradient, but lower resolution was always obtained for the analytes. Several formic acid concentrations in the 0.1–1% (v/v) range were assayed and no significant differences were observed in the retention times and chromatographic peak shape; therefore, a concentration of 0.1% was adopted for the acid. Despite assaying different ramps of between 33% and 45% of ACN, hesperetin and fisetin coeluted. Nevertheless, this was not a problem because these compounds were monitored at very different wavelengths in the DAD system and with different values of [M–H] in the ToFMS. The mobile phase flow rate was 0.8 mL min-1, and the elution order and the retention times for the analytes were (1) baicalein (tR ¼8.97 min); (2) hesperetin (tR ¼9.97 min); (3) fisetin (tR ¼ 10.07 min); (4)
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naringenin (tR ¼ 11.61 min); (5) chrysin (tR ¼12.46 min); (6) myricetin (tR ¼12.87 min); (7) quercetin (tR ¼14.52 min) and (8) kaempferol (tR ¼16.02 min). Separation factors (α) in the 1.1–1.2 range and resolution (Rs) between 1.45 and 2.51 were obtained for those analytes monitored at 280 nm (baicalein, hesperetin, naringenin and chrysin), and in the 1.1–1.3 and 2.1–4.8 for those detected at 370 nm (fisetin, myricetin, quercetin and kaempferol). The exact mass measurements and mass errors obtained in the ToFMS for molecular ions are shown in Table 1. 3.2. Optimization of the DLLME conditions The first step in the DLLME optimization procedure was to select the most appropriate disperser and extractant solvents. For this purpose, 1 g of a spiked honey (at 1 mg g 1 concentration level for all compounds) was dissolved in 10 mL of water and 150 mL of different organic solvents were assayed using 1 mL of ACN as disperser solvent. Lower extraction efficiencies were attained for solvents of lower density than water (1-undecanol, 1-dodecanol, 1-octanol, 2-octanone, 2-undecanone, toluene, hexane and isooctane) than those obtained with organic solvents denser than water. Carbon tetrachloride, tetrachloroethane, chloroform, tetrachloroethylene, 1,2-dichloroethane and dichloromethane were the extractants assayed. Dichloromethane was discarded because no settled phase was obtained owing to its high water solubility. Tetrachloroethylene was also discarded because of the long time required to evaporate the sedimented phase and carbon tetrachloride because no preconcentration of the analytes was attained. As shown in Fig. 1, chloroform extracted all the analytes with higher efficiency than 1,2-dichloroethane and tetrachloroethane, and so it was selected as extractant solvent. The main parameter considered for the selection of the disperser solvent was its miscibility in the extraction solvent and the aqueous phase. ACN, methanol and ethanol have this property, and were tested in this study using 1.0 mL of each solvent and 150 mL of chloroform as the extractant solvent. ACN provided the best discernible settled phase and so was selected; moreover, it was in close consonance with the mobile phase. The Taguchi experimental method, an orthogonal array design, was applied to study the possible influence on DLLME of six factors (each at three levels) which might influence the dispersion, extraction and collection efficiency namely, organic extractant
Fig. 1. Selection of extractant solvent for DLLME. Aqueous phase volume, 10 mL; organic solvent volume, 150 mL; and disperser solvent, 1 mL ACN.
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volume, disperser solvent volume, honey sample mass, centrifugation time, pH and sodium chloride concentration of the aqueous phase. For this purpose, 10 mL of an aqueous solution containing different masses, in the 0.5–1.5 g range, of a fortified honey at concentration levels of 1 mg g 1, was used. The volumes of the extractant and disperser solvents were varied between 50–150 mL and 0.5–1.5 mL, respectively. The effect of ionic strength was studied with NaCl concentrations between 0% and 5% m/v and the pH of the aqueous solution between 3 and 6. Centrifugation times, applied to disrupt the dispersion of the organic droplets, of 1, 3 and 5 min at 3400 rpm were studied. In all cases, the sedimented phase was evaporated and the residue reconstituted in 50 mL of ACN. When the honey mass was increased from 0.5 to 1.0 g, the mean response increased and then was practically constant with a 1.5 g sample mass, so a sample mass of 1.0 g was selected. The highest extraction efficiencies were obtained with 1.5 mL of ACN and 150 mL of chloroform. Varying the pH between 3 and 6 with 0.01 M buffer solutions showed that optimal results were obtained at pH 3, which was selected. Extraction efficiency was higher for all the analytes in the absence of salt and, thus, its addition to the extraction solution was discarded. The centrifugation time necessary to disrupt the cloudy solution was not seen to be a significant factor for extraction efficiency, and so 1 min was adopted for this step at the maximum speed supported by the centrifugal tubes used. A statistical analysis of variance (ANOVA) test was performed to discriminate which parameters significantly affected extraction efficiency (Table 2). From the calculated variance ratios, F, it was deduced that only one factor considered in the experimental design was statistically significant, at a 95% confidence level (in all cases the calculated F was greater than the critical value). This variable was the extractant volume. The contribution of the residual error to the signal variability indicates the goodness of the experimental design used. It is noteworthy that the application of the ANOVA test showed that the disperser volume was not a variable of statistically significant effect on the DLLME extraction efficiency, nevertheless its contribution of the residual error to the signal is not negligible.
characteristics are shown in Table 3. The repeatability was calculated using the relative standard deviation for ten successive analyses of heather honey fortified at a concentration level of 300 ng g 1 for all compounds (Table 3) and values lower than 11% were obtained. Fig. 2 shows the DLLME combined with LC–DAD elution profiles obtained in the analysis of a standard solution mixture. In contrast, a matrix effect was detected when LC–ESI–ToFMS was used, aqueous standard calibration providing higher slopes for all the analytes than standard additions. Nevertheless, the application of a one-way ANOVA test to the slopes obtained for the different matrices pointed to the absence of significant differences at 95% confidence level, p values varying in the 0.05–0.808 range depending on the compound (Table 4). Therefore, a matrix-matched calibration method Table 3 Analytical characteristics of the DLLME combined with the LC–DAD method. Compound
λ (nm)
Slopea (mL ng 1)
Correlation coefficient
DLb (ng mL 1)
RSDc (%)
Baicalein Hesperetin Fisetin Naringenin Chrysin Myricetin Quercetin Kaempferol
280 280 370 280 280 370 370 370
3.50 7 0.10 3.107 0.08 0.357 0.02 2.83 7 0.11 4.84 7 0.18 0.447 0.03 1.42 7 0.06 2.81 7 0.10
0.9958 0.9951 0.9963 0.9984 0.9970 0.9959 0.9984 0.9978
0.4 0.5 3.9 0.8 0.4 4.1 1.3 0.7
5.1 6.2 11 7.3 4.9 11 8.3 6.0
(4) (5) (39) (8) (4) (41) (13) (7)
Values in brackets are ng g 1. a b c
Mean value7 standard deviation (n¼ 5). Calculated for S/N ¼3. Calculated at a concentration level of 300 ng g 1 for each compound (n¼ 10).
3.3. Analytical characteristics of the method To study the relevance of any matrix effect, an ANOVA test was used to compare the slopes of aqueous standards calibration graphs and those obtained when the standard additions method was applied to three different honey samples (eucalyptus, thyme and orange blossom). The absence of a matrix effect when using LC–DAD confirmed as the “p” values were higher than 0.05 for the eight analytes in the three samples. Consequently, quantification of the samples by DLLME combined with LC–DAD was carried out against external aqueous standards; the corresponding analytical Table 2 Results of the analysis of variance for mean response. Variation source Sample mass Dispersant volume Extractant volume pH Ionic strength Centrifugation time Error Total
Degrees of freedom
Sum of squares
Mean of squares
F
2 2
30,773 217,756
15,386 108,878
0.32 0.733 3.7 2.25 0.142 26.4
2
510,370
255,185
5.27 0.020 61.9
2 2 2
54,481 4717 6437
27,240 2358 3219
0.56 0.582 0.05 0.953 0.07 0.936
14 26
677,814 48,415 1,502,348
P
Contribution (%)
6.6 0.6 0.8
Fig. 2. Elution profiles obtained for an aqueous standard solution using the DLLME combined with LC–DAD optimized procedure. The concentrations of the compounds were (1) Baicalein, 15 ng mL 1; (2) hesperetin, 20 ng mL 1; (3) fisetin, 150 ng mL 1; (4) naringenin 20 ng mL 1; (5) chrysin, 10 ng mL 1; (6) myricetin, 60 ng mL 1; (7) quercetin, 40 ng mL 1 and (8) kaempferol, 20 ng mL 1.
N. Campillo et al. / Talanta 131 (2015) 185–191
was adopted for quantification by LC–ESI–ToFMS. The comparison of the standard deviations of the different slopes for each compound did not show significant differences (F values of 0.366–2.92). The regression coefficients obtained under the selected conditions showed a directly proportional relationship between the amount of analyte extracted and the corresponding peak area, being in all cases higher than 0.997. Detection limits (DLs) and quantification limits (QLs) were calculated on the basis of three and ten times the signal-to-noise ratios, respectively. The data obtained for DLs appear in Table 4, while QLs in the 0.035–1.6 ng g 1 range were obtained. When comparing the DLs obtained using DAD and ESI–ToFMS, an increase in sensitivity of between 4.5 and 10 was observed in favor of ToF, depending on the compound. When the DLs obtained by DLLME combined with LC– DAD were compared with previously reported data, an identical value was obtained for quercetin [27], and lower values for hesperetin, quercetin, chrysin, myricetin and kaempferol than those obtained by Campone et al. [41], considering the higher injection volume and the reconstitution of the DLLME organic extract in a lower volume in the procedure presented here. The slopes obtained by aqueous calibration using DLLME–LC–DAD– ESI–ToFMS were compared with those obtained in the absence of a preconcentration step, pointing to an increase in sensitivity of between 10 (for fisetin and myricetin) and 80-fold for chrysin.
showed the highest content for fisetin, naringenin, chrysin and kaempferol, while hesperetin was found at higher concentration in the orange blossom honey. Recovery studies were carried out in order to verify the accuracy of the proposed method by fortifying three samples (heather honey, propolis 2 and royal jelly) in triplicate at two concentration levels in the range 15–1000 ng g 1, depending on the compound. The results obtained appear in Table 6. Recovery values ranged between 80% and 111%, with an average recovery7standard deviation (n¼ 144) of 9777. There were no differences in the RSD values between the different samples, RSD ranging between 5% and 14%. Table 6 Recovery studies. Compound
Spiking level (ng g 1)
Concentration founda (ng g 1) Heather honey
Propolis 2
Royal jelly
Baicalein
15 150
137 1 1557 17
12 7 2 141 7 12
629 743 754 767
Hesperetin
15 150
787 7 205 7 15
81 7 8 199 7 21
18 72 165 715
100 1000
203 7 26 986 7 81
127 7 16 936 7 84
263 731 1094 7121
Naringenin
25 250
217 3 2677 24
109 7 9 308 7 27
60 77 316 728
Chrysin
15 150
606 7 58 748 7 81
271 7 14 431 7 38
69 77 201 719
Fisetin
3.4. Analysis of samples and validation of the method The optimized procedure was applied to eight different honeys, three propolis samples and one royal jelly. Table 5 shows the results obtained using the DLLME combined with LC–ESI–ToFMS, which are similar to those obtained with DAD as detection system. Myricetin was not found in any of the samples above its detection limit (0.9 ng g 1), whereas baicalein was found in four of the twelve samples analyzed at concentration levels ranging from 33 to 622 ng g 1. Of note is the observation that the unique analyte found in lavender honey sample was chrysin. Of the different honeys analyzed, rosemary honey
189
Myricetin
100 1000
1037 13 956 7 128
94 7 11 930 7 98
88 712 1056 7129
Quercetin
50 500
707 8 532 7 47
160 7 12 628 7 53
241 725 679 755
Kaempferol
25 250
1537 14 4107 39
355 7 37 603 7 48
298 727 518 737
a
Mean 7 standard deviation (n¼ 3).
Table 4 Slopesa of standard additions calibration graphs by DLLME combined with LC–ToFMS (mL ng 1). Sample
Baicalein
Hesperetin
Fisetin
Naringenin
Chrysin
Myricetin
Quercetin
Kaempferol
Aqueous Eucalyptus honey Heather honey Thyme honey Propolis 1 Royal jelly
38,9007 1230 32,780 7 1860 31,6807 1790 30,340 7 2000 33,0007 1650 31,0607 1600
59,0107 2410 59,460 7 5130 63,0007 4930 62,820 7 5260 62,540 7 4390 61,840 7 5910
6504 7202 5260 7412 6100 7566 5658 7430 5246 7460 5313 7621
165,0007 6300 50,220 7 4940 51,1607 5500 55,630 7 5900 49,880 7 4250 50,4407 2660
395,000 711,100 267,100 712800 253,100 713200 283,700 717400 256,800 715400 270,500 719300
5320 7234 4440 7421 4569 7398 4381 7459 4254 7439 4621 7489
45,030 7 2200 33,3007 2860 34,7307 3020 30,2107 2540 31,7607 2920 35,020 7 3510
132,7007 6580 104,3007 7520 107,2007 8070 102,9007 7070 108,4007 9080 105,4007 8780
a
Mean 7 standard deviation (n ¼5).
Table 5 Flavonoids contenta in the analyzed samples (ng g 1). Sample
Baicalein
Hesperetin
Fisetin
Naringenin
Chrysin
Quercetin
Kaempferol
Honey lavender Orange blossom Rosemary Heather Eucalyptus Chesnut Thyme Flowers Royal jelly Propolis 1 Propolis 2 Propolis 3
ND ND ND ND ND 2147 15 ND 337 4 622 748 ND ND 2667 23
ND 620 7 35 827 6 66 7 3 657 4 307 3 327 3 35 74 2.0 70.3 466 7 23 617 5 207 715
ND 4757 32 1650 7 66 116 710 4177 22 997 12 73 710 292 7 11 149 7 15 8677 70 477 5 7147 36
ND 237 2 49 7 9 ND ND 147 2 167 1 357 4 417 3 257 3 757 3 127 1
2147 20 630 7 14 8137 34 6197 25 425 7 31 284 7 25 205 7 11 1257 12 657 5 846 7 58 2677 19 637 4
ND 727 7 1267 11 137 1 13507 55 11087 60 206 7 10 1327 13 205 7 14 1885 7 83 1017 8 4747 29
ND 7147 36 3806 7 100 143 7 6 241 7 13 455 7 22 1017 11 9017 15 294 7 15 498 7 20 3397 17 607 3
ND means not detected. a
Mean 7 standard deviation (n¼ 3).
190
N. Campillo et al. / Talanta 131 (2015) 185–191
the standards, non-spiked and spiked samples analyzed. The mass error was calculated by using the theoretical mass values provided in Table 1 as reference, which were given by the ToF software. The errors obtained for all the standards and spiked and non-spiked samples were between 1.88 and 2.8 ppm. These values were, in all cases, lower than the accepted accuracy threshold of 5 ppm necessary to confirm elemental compositions. Fig. 3 shows the DLLME combined with LC–ESI–ToFMS extracted ion chromatograms (EICs) obtained for the flowers honey sample fortified at 200 ng g 1.
4. Conclusion The simple extraction and preconcentration of the analytes from honey using a low volume of organic solvent and the environmentally friendly miniaturized technique DLLME allows quantification at low levels to be carried out. Eight flavonoid aglycones can be separated by LC, dual detection with DAD and ToFMS being appropriate for the final measurement. Accurate mass measurements, concordance in retention times and UV spectra provide unequivocal identification of the individual analytes.
Acknowledgments The authors acknowledge to Comunidad Autónoma de la Región de Murcia (CARM, Fundación Séneca, Project 15217/PI/10) and the Spanish MEC (CTQ2012-34722) for financial support. G. Férez-Melgarejo acknowledges a fellowship financed by CARM. References
Fig. 3. Extracted ion chromatograms by DLLME combined with LC–ESI–ToFMS for flowers honey sample fortified at 200 ng g 1 for all compounds. (1) Baicalein, (2) hesperetin, (3) fisetin, (4) naringenin, (5) chrysin, (6) myricetin, (7) quercetin and (8) kaempferol.
The flavonoid compounds were identified according to their retention times, the UV spectra and molecular weights compared with commercial standards. Accurate masses were obtained for all
[1] K. Brandt, L.P. Christensen, J. Hansen-Moller, S.L. Hansen, J. Haraldsdottir, L. Jespersen, S. Purup, A. Kharazmi, V. Barkholt, H. Frokiaer, M. Kobaek-Larse, Trends Food Sci. Technol. 15 (2004) 384–393. [2] C. Sánchez-Moreno, L. Plaza, B. de Ancos, P. Cano, J. Sci. Food Agric. 83 (2003) 430–439. [3] M. Viuda-Martos, Y. Ruiz-Navajas, J. Fernández-López, J.A. Pérez-Álvarez, J. Food Sci. 73 (2008) R117–R124. [4] P. Viñas, N. Campillo, Gas chromatography–mass spectrometry analysis of polyphenols in foods, in: R.R. Watson, V.R. Preedy, S. Zibadi (Eds.), Polyphenols Human Health and Disease, Elsevier, London, 2014. [5] V. Kaskoniene, P.R. Venskutonis, Comp. Rev. Food Sci. Food Saf. 9 (2010) 620–634. [6] H.M. Merken, G.R. Beecher, J. Agric. Food Chem. 48 (2000) 577–599. [7] A.M. Gómez-Caravaca, M. Gómez-Romero, D. Arráez-Román, A. SeguraCarretero, A. Fernández-Gutiérrez, J. Pharm. Biomed. Anal. 41 (2006) 1220–1234. [8] K. Pyrzynska, M. Biesaga, Trends Anal. Chem. 28 (2009) 893–902. [9] A. Uzel, K. Sorkun, O. Oncag, D. Cogulu, O. Gencay, B. Salih, Microbiol. Res. 160 (2005) 189–195. [10] M. Campo Fernández, O. Cuesta-Rubio, A. Rosado Pérez, R. Montes De Oca Porto, I. Márquez Hernández, A. Lisa Piccinelli, L. Rastrelli, J. Agric. Food Chem. 56 (2008) 9927–9932. [11] V.A. Isidorov, A.G. Isidorova, L. Sczczepaniak, U. Czyzewska, Food Chem. 115 (2009) 1056–1063. [12] N. Kalogeropoulos, S.J. Konteles, E. Troullidou, I. Mourtzinos, V.T. Karathanos, Food Chem. 116 (2009) 452–461. [13] W. Maciejewicz, M. Daniewski, K. Bal, W. Markowski, Chromatographia 53 (2001) 343–346. [14] D. Arráez-Román, A.M. Gómez-Caravaca, M. Gómez-Romero, A. SeguraCarretero, A. Fernández-Gutiérrez, J. Pharm. Biomed. Anal. 41 (2006) 1648–1656. [15] I. Martos, F. Ferreres, L.H. Yao, B. D´Arcy, N. Caffin, F.A. Tomás-Barberán, J. Agric. Food Chem. 48 (2000) 4744–4748. [16] L.H. Yao, Y.M. Jiang, B. D´Arcy, R.T. Singanusong, N. Datta, N. Caffin, K. Raymont, J. Agric. Food Chem. 52 (2004) 210–214. [17] L. Estevinho, A.P. Pereira, L. Moreira, L.G. Dias, E. Pereira, Food Chem. Toxicol. 46 (2008) 3774–3779. [18] M.O. Iurlina, A.I. Saiz, R. Fritz, G.D. Manrique, Food Chem. 115 (2009) 1141–1149. [19] E. Pichichero, L. Canuti, A. Canini, J. Sci. Food Agric. 89 (2009) 609–616. [20] M.R. Hadjmohammadi, S. Nazari, K. Kamel, Chromatographia 69 (2009) 1291–1297.
N. Campillo et al. / Talanta 131 (2015) 185–191
[21] R. Socha, L. Juszczak, S. Pietrzyk, T. Fortuna, Food Chem. 113 (2009) 568–574. [22] I. Escriche, M. Kadar, M. Juan-Borras, E. Domenech, Food Res. Int. 44 (2011) 1504–1513. [23] M.I. Isla, A. Craig, R. Ordoñez, C. Zampini, J. Sayago, E. Bedascarrasbure, A. Álvarez, V. Salomon, L. Maldonado, LWT—Food Sci. Technol. 9 (2011) 1922–1930. [24] O. Escuredo, L.R. Silva, P. Valentao, M.C. Seijo, P.B. Andrade, Food Chem. 130 (2012) 671–678. [25] A. Cavazza, C. Corradini, M. Musci, P. Salvadeo, J. Sci. Food Agric 93 (2013) 1169–1175. [26] I. Escriche, M. Kadar, M. Juan-Borras, E. Domenech, Food Chem. 142 (2014) 135–143. [27] E. Ranjbari, P. Biparva, M.R. Hadjmohammadi, Talanta 89 (2012) 117–123. [28] A. Perna, I. Intaglietta, A. Simonetti, E. Gambacorta, Int. Food Sci. Technol. 48 (2013) 1899–1908. [29] Y. Liang, W. Cao, W.J. Chen, X.H. Xiao, J.B. Zheng, Food Chem. 114 (2009) 1537–1541. [30] M. Biesaga, K. Pyrzynska, J. Chromatogr. A 1216 (2009) 6620–6626. [31] A. Ciric, H. Prosen, M. Jelikic-Stankov, P. Durdevic, Talanta 99 (2012) 780–790. [32] S. Keckes, U. Gasic, T.C. Velickovic, D. Milojkovic-Opsenica, M. Natic, Z. Tesic, Food Chem. 138 (2013) 32–40. [33] I. Sergiel, P. Pohl, M. Biesaga, Food Chem. 145 (2014) 404–408. [34] N. Gheldof, X.H. Wang, N.J. Engeseth, J. Agric. Food Chem. 50 (2002) 5870–5877.
191
[35] K. Petrus, H. Schwartz, G. Sontag, Anal. Bioanal. Chem. 400 (2011) 2555–2563. [36] A. Michalkiewicz, M. Biesaga, K. Pyrzynska, J. Chromatogr. A 1187 (2008) 18–24. [37] P. Truchado, E. Tourn, L.M. Gallez, D.A. Moreno, F. Ferreres, F.A. TomásBarberán, J. Agric. Food Chem. 58 (2010) 12678–12685. [38] J.M. Álvarez-Suárez, A.M. González-Paramas, C. Santos-Buelga, M. Battino, J. Agric. Food Chem. 58 (2010) 9817–9824. [39] J. Bertoncelj, T. Polak, U. Kropf, M. Korosec, T. Golob, Food Chem. 127 (2011) 296–302. [40] J.H. Zhou, L.H. Yao, Y. Li, L.Z. Chen, L.M. Wu, J. Zhao, Food Chem. 145 (2014) 941–949. [41] L. Campone, A.L. Piccinelli, I. Pagano, S. Carabetta, R. Di Sanzo, M. Russo, L. Rastrelli, J. Chromatogr. A 1334 (2014) 9–15. [42] F. Ferreres, F.A. Tomás-Barberán, C. Soler, C. García Viguera, A. Ortiz, F. Tomás Lorente, Apidologie 25 (1994) 21–30. [43] L. Ramos, J. Chromatogr. A 1221 (2012) 84–98. [44] P. Viñas, N. Campillo, I. López-García, M. Hernández-Córdoba, Anal. Bioanal. Chem. 406 (2014) 2067–2099.
