Food Chemistry 190 (2016) 982–989

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Food Chemistry

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Analytical Methods

Development and validation of a modified QuEChERS protocol coupledto LC–MS/MS for simultaneous determination of multi-class antibioticresidues in honey

http://dx.doi.org/10.1016/j.foodchem.2015.06.0480308-8146/� 2015 Elsevier Ltd. All rights reserved.

⇑ Corresponding author at: Analytical Chemistry Department, Faculty of Phar-macy, Cairo University, Cairo 11562, Egypt.

E-mail address: medhat.alghobashy@cu.edu.eg (M.A. Al-Ghobashy).

Amr H. Shendy a, Medhat A. Al-Ghobashy b,c,⇑, Sohair A. Gad Alla a, Hayam M. Lotfy b,d

a Central Laboratory of Residue Analysis of Pesticides and Heavy Metals in Food, Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Giza, Egyptb Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, Cairo, Egyptc Bioanalysis Research Group, Faculty of Pharmacy, Cairo University, Cairo, Egyptd Pharmaceutical Chemistry Department, Faculty of Pharmaceutical Sciences and Pharmaceutical Industries, Future University, Cairo, Egypt

a r t i c l e i n f o

Article history:Received 1 July 2014Received in revised form 8 April 2015Accepted 17 June 2015Available online 18 June 2015

Keywords:LC–MS/MSHoneyVeterinary drug residuesNitrofuranNitroimidazolesRonidazoleDimetridazoleAHDAOZAMOZSEM

a b s t r a c t

LC–MS/MS assay was developed and validated according to EU guidelines for determination of nitrofuranmetabolites and nitroimidazole residues in honey. Crude samples were acid-treated to liberatematrix-bound residues and a modified QuEChERS protocol was employed. Nitrofurantoin, furazolidone,furaltadone and nitrofurazone were determined via analysis of their metabolites AHD, AOZ, AMOZ andSEM, respectively while nitroimidazole residues; ronidazole (RNZ) and dimetridazole (DMZ) were deter-mined directly. For all analytes, neat standard calibration curves, after correction for matrix effect weresuccessfully employed. Decision limit (CCa) and detection capability (CCb) were below the MRPL fornitrofurans (1.00 lg kg�1) and the recommended concentration for nitroimidazole (3.00 lg kg�1), respec-tively. The CCa, CCb, percentage recovery and CV% ranges were 0.12–0.74 lg kg�1, 0.21–1.27 lg kg�1,90.96–104.80% and 2.65–12.58%, respectively. This work is part of the national initiative for establishinga national monitoring program for drug residues in Egyptian honey.

� 2015 Elsevier Ltd. All rights reserved.

1. Introduction formed about 25% of these notifications (Galarini, Saluti,

Illegal use of antibiotics as veterinary drugs is well documentedaround the world, regardless of the socioeconomic status. Thepresence of antibiotic residuals in food products constitutes animportant health risk and is associated with the increased micro-bial resistance to antibiotics (Barganska, Namiesnik, & Slebioda,2011; Butaye, Devriese, & Haesebrouck, 2001; Venable, Haynes, &Cook, 2014). Recently, WHO identified antimicrobial resistance asone of the three greatest threats to global health (WHO:Antimicrobial resistance: global report on surveillance, 2014).Galarini et al. reported that during the last five years �71% of thenotifications issued by the Rapid Alert System for Food and Feed(RASFF Portal), Directorate-General for Health and Consumersinvolved the presence of antimicrobial residues in honey bee prod-ucts. Alerts concerning nitrofurans (NF) and nitroimidazoles (NMZ)

Giusepponi, Rossi, & Moretti, 2015).NF are broad-spectrum antibiotics currently in use either as a

prophylactic measure or for treatment of diseases such as theAmerican foulbrood (Barganska et al., 2011; Cronly et al., 2010).The most commonly used members of the NF are nitrofurantoin,furazolidone, furaltadone and nitrofurazone (Lopez, Feldlaufer,Williams, & Chu, 2007; O’Keeffe et al., 2004). The presence of NFresidues in honey has been previously reported (Barganska et al.,2011; Bottoni & Caroli, 2015; Kaufmann, Butcher, Maden,Walker, & Widmer, 2015; Venable et al., 2014). Due to concernsabout the carcinogenicity and mutagenicity of NF and theirmetabolites, they were banned from use in the EU (1995) andthe United States (2002) (Barganska et al., 2011; Kaufmann et al.,2015). Such zero tolerance compounds were classified under groupA: Prohibited substances, according to the Council Directive96/23/EC and Commission Regulation (EU) 37/2010. Owing to therapid metabolism of NF, recent reports (Barganska et al., 2011;Lopez et al., 2007; Venable et al., 2014) focused on the detectionof NF metabolites;1-aminohydantoin (AHD, metabolite of

Table 1MS/MS transitions and optimal operational conditions used for analysis.

Compound(s) Precursorion m/z

MRMtransitionsm/z

RT DPV

EPV

CEV

EXPV

NP-AHD 249.09 134.00a 6.85 71 10 19 6104.00b 71 10 33 6

NP-AOZ 236.10 134.00a 6.96 41 10 19 6104.00b 41 10 33 6

NP-AMOZ 335.09 291.10a 7.40 66 10 17 16128.00b 66 10 33 6

NP-SEM 209.14 165.90a 7.03 61 10 15 8192.00b 61 10 17 10

RNZ 201.12 140.10a 5.55 26 10 17 855.10b 26 10 35 8

DMZ 142.13 96.10a 6.21 56 10 23 1681.10b 56 10 35 6

RT, retention time (min); DP, declustering potential (volt); EP, entrance potential(volt); CE, collision energy (volt); EXP, exit potential (volt).

a Transitions for quantifier peaks.b Transitions for qualifier peaks.

A.H. Shendy et al. / Food Chemistry 190 (2016) 982–989 983

nitrofurantoin), 3-amino-2-oxazolidinone (AOZ, metabolite offurazolidone), 3-amino-morpholinomethyl-2-oxazolidinone(AMOZ, metabolite of furaltadone) and semicarbazide (SEM,metabolite of nitrofurazone). The chemical structures of parentNF compounds and their metabolites are shown in Fig. S1.

On the other hand, NMZ are antibiotics that are used to combatanaerobic bacterial and parasitic infections (Hernandez-Mesa,Garcia-Campana, & Cruces-Blanco, 2014; Mital, 2009).Nitroimidazoles; most commonly ronidazole (RNZ) and dimetrida-zole (DMZ) have been in use to prevent and control Nosema apis inhives that is one of the most common adult honey bee diseases(Cronly et al., 2010). Both of RNZ and DMZ along with theirhydroxy metabolites are suspected of being genotoxic, carcino-genic and mutagenic (Hernandez-Mesa et al., 2014; Huet et al.,2005). Similar to NFs, NMZ were detected in honey (Bottoni &Caroli, 2015; Galarini et al., 2015; Venable et al., 2014) and areclassified as zero tolerance substances for all food producing spe-cies according to EU Commission Regulation 37/2010 and belongto Group A (Prohibited substances). The chemical structures ofthe most commonly used NMZ are shown in Fig. S1.

With the implementation of the stringent requirements CD2002/657/EC and 2003/181/EC, the development of highly sensi-tive and specific analytical methods for the determination of drugresidues has become a challenging task. The EU has established aharmonized minimum required performance limit (MRPL) for thedetection of NF residues at 1.00 lg kg�1 and a recommended con-centration for NMZ residues of 3.00 lg kg�1 (CRL guidance paper2007). Such ultra-low levels required sophisticated sample prepa-ration and/or analysis techniques. Few methods have beenreported for the analysis of NF and/or NMZ in a variety of matricesincluding honey (Bottoni & Caroli, 2015; Kaufmann et al., 2015;Venable et al., 2014; Xia et al., 2008). A rapid multi-class,multi-residue method for the determination of NMZ in honeyusing LC–MS/MS has been reported (Cronly et al., 2010; Lopezet al., 2007). Recently, LC–MS/MS has also been employed for thedetermining NF metabolites in different matrices (Vass, Hruska,& Franek, 2008). To the best of our knowledge, there are no reportson the simultaneous determination of NF and NMZ in honey.

The aim of this study was to develop and validate a sensitive,simple and multi-class LC–MS/MS analysis protocol for the simul-taneous determination of residues of NF metabolites (AHD, AOZ,AMOZ and SEM) and NMZ (DMZ and RNZ) in honey.Derivatisation of NF metabolites using 2-nitrobenzaldehyde(2-NBA) will be carried out followed by extraction using a modifiedQuEChERS sample preparation technique. The proposed protocolwas validated to the quality criteria of CD 2002/657/EC by measur-ing linearity, accuracy, repeatability, within-laboratory repro-ducibility, decision limit (CCa) and detection capability (CCb).The applicability of the developed protocol for the routine moni-toring of locally produced honey will be investigated, as part ofthe national monitoring program for drug residues in Egyptianhoney. This should help various Egyptian honeybee products topenetrate international markets.

2. Materials and methods

2.1. Chemicals, reagents and standard solutions

Reference standards for AHD, AOZ, AMOZ, SEM, RNZ and DMZwith purity of at least 98% were obtained from Dr. EhrenstorferGmbH (Germany). All other chemicals were of HPLC grade andwere obtained from Sigma–Aldrich (USA). 50 mM2-nitrobenzaldehyde (NBA) solution was prepared by dissolving189 mg of NBA powder into 25 mL methanol in an amber volumet-ric flask. Individual standard stock solutions were prepared byaccurately weighing 10 mg of each standard into a set of 100 mL

amber volumetric flasks. The volume was completed to the markwith methanol: acetonitrile (80:20 v/v) in case of NF metabolitesand methanol in case of NMZ to a final concentration of100.00 lg mL�1. Stock solutions were stored at �20 ± 2 �C awayfrom direct light. Two working standard solutions of the four NFmetabolites (1.00 lg mL�1 and 0.10 lg mL�1) were prepared bydiluting suitable aliquots of each stock solution with methanol.Similarly, two working standard solutions of NMZ standards(1.00 lg mL�1 and 0.10 lg mL�1) were prepared in methanol.Ultra-pure water was obtained using a MilliQ UF-Plus system(Millipore, Germany) with a resistivity of at least 18.2 MO cm at25 �C and TOC below 5 ppb.

2.2. Instrumentation and conditions

Analysis was carried out using an Agilent 1200 HPLC system(Agilent Technologies, USA) connected to an API 4000 QTrap tan-dem mass spectrometer (Applied Biosystems, USA).Chromatographic separations were accomplished using aZORBAX Eclipse XDB C-18 column (4.6 � 150 mm, 5 lm) thatwas obtained from Agilent Technologies (USA). The temperatureof the column compartment and sample tray were maintained at40 �C and 4–8 �C, respectively. A gradient elution at a flow rate of0.3 mL min�1 was employed. The mobile phase composition was:(A) 5 mM ammonium formate buffer in methanol/water (1:9 v/v),pH 3.0 ± 0.05 and (B) methanol. The gradient was optimised inorder to achieve a run time with enough data points for each peakover 14 min: 0.0–6.0 min (60–95% B), 6.0–12.0 min (95% B) and12.0–14.0 min (95–60% B). The injection volume was 25 lL anddetection was achieved using ESI in positive ion mode. Nitrogenwas used as: nebuliser gas, curtain gas, heater gas and collisiongas according to manufacturer’s recommendations. Ion spray volt-age was 5500 V and the temperature source was set at 400 �C.Acquisition was performed in MRM mode in which one MRMwas used for quantification (quantifier peak) and the other wasused for confirmation (qualifier peak). The MS/MS transitions andoptimal operational conditions used for analysis are summarizedin Table 1.

2.3. Sample preparation

2.3.1. DerivatisationOrganic honey samples were obtained from local market and

used as blank samples. Aliquots of 1.00 ± 0.02 g were accuratelyweighed into 50 mL polypropylene centrifuge tubes. Suitable ali-quots of the NF metabolites and NMZ working standard solutions

984 A.H. Shendy et al. / Food Chemistry 190 (2016) 982–989

were added to final concentration of 1.00 lg kg�1 and 3.00 lg kg�1,respectively. Spiked blank samples were vortex mixed for 30 s andleft to stand away from light at room temperature for 10 min.Deionised water (4.0 mL) was added to the samples followed by0.5 mL of 1.0 M HCl and 150 lL NBA reagent solution. Sampleswere vortex mixed until complete homogeneity was obtainedand then incubated at 55 �C in an agitated water bath for 4 h awayfrom light. Neutralisation to pH 7.0 ± 0.5 was carried out using5.0 mL of 0.1 M di-potassium hydrogen phosphate followed by300 lL of 1.0 M NaOH. Throughout this manuscript, nitrophenyl(NP) derivatives of the NF metabolites will be abbreviated asNP-AHD, NP-AOZ, NP-AMOZ and NP-SEM (Fig. S1).

2.3.2. ExtractionA modified QuEChERS protocol (Anastassiades, Lehotay,

Stajnbaher, & Schenck, 2003) using acetonitrile extraction, withoutaddition of primary secondary amine followed by evaporationunder vacuum was employed. NP derivatives of the NF metabolitesand NMZ were extracted using 10.0 mL acetonitrile followed byagitation for 2 min at 700 rpm. The efficiency of extraction was fur-ther enhanced by adding 4 g of MgSO4 and 1 g NaCl followed byagitation for 1 min at the same speed. Samples were then cen-trifuged at 15,000�g for 10 min using a cooling centrifuge. Theorganic layer was carefully transferred into 50 mL flask and evap-orated at 45 �C using a rotatory evaporator. The residue was thenreconstituted into 1.0 mL mobile phase A, sonicated for 1 min thenfiltered through a disposable 0.45 lm PTFE membrane filter into anamber glass vial and injected into LC–MS/MS.

2.4. Calibration and validation

A mixture of NF metabolite standards was derivatised with NBAas described above. The final preparation of NP-derivatives wasthen mixed with NMZ to a final concentration of (1 lg mL�1 each).A serial dilution of the obtained mixture was prepared usingmobile phase A (0.25, 0.50, 1.00, 2.00, 5.00 and 10.00 ng mL�1)and analysed using LC–MSMS as described. The neat standard cal-ibration curves were constructed by plotting concentration(ng mL�1) versus instrument response and correlation coefficientswere estimated. In order to determine the matrix effect; calibra-tion curves were constructed using matrix matched standardsand results were compared to those of the neat calibration curves.

In-house validation with a model-dependent performanceparameters approach was performed according to the criteriaand recommendations of the European Commission Decision(CD) 2002/657/EC implementing the Council Directive 96/23/EC.The ResVal software (EC 2002, ver. 2.0) was used for data analysisand calculations of decision limit (CCa), detection capability (CCb)and measurement uncertainty (MU).

Blank honey samples were fortified at three levels, 0.5, 1.0 and1.5 �MRPL/recommended concentration. The final concentrationsfor NF metabolites were 0.5, 1.0 and 1.5 lg kg�1 while for NMZ theconcentration levels were 1.5, 3.0 and 4.5 lg kg�1. At each level theanalysis was performed on three different days using six repli-cates/day in order to verify the accuracy, repeatability andwithin-laboratory reproducibility. Twenty blank honey samplesfrom different botanical and geographical origins were analysedon the fourth day to distinguish possible interference in identifica-tion and/or quantification of the analytes. Results were expressedas percentage recovery and coefficient of variation (CV%). TheCCa and CCb were obtained through the analysis of one blank sam-ple and five fortified samples at concentration levels (0.5, 1.0, 1.5,2.0 and 5.0 �MRPL/recommended concentration) in accordance toISO 11843. MU was then estimated by combining thewithin-laboratory reproducibility and matrix effect variances inagreement to SANCO/2004/2726-rev 4.

2.5. Application to real samples

One point matrix matched standard at the MRPL/recommendedconcentration and an equivalent neat standard sample were pre-pared and analysed. Results were used to estimate the matrixeffect and correct for minor variability in test results. The opti-mised assay protocol was applied for the analysis of thirty com-mercial honey samples obtained from local market. Naturallyincurred sample, a proficiency testing sample (PT sample) by ourlaboratory for NF metabolites, round 02249 (2015) was tested. Inthe case of the PT sample, results of the proposed assay were com-pared to those obtained using the currently employed assay withmodifications (Verdon, Couedor, & Sanders, 2007). Briefly, derivati-sation was carried out using NBA, ethyl acetate was used forextraction without further cleanup. Collected extracts were evapo-rated under N2 stream at 45 �C and reconstituted inmethanol/1 mM ammonium formate (60/40 v/v) before analysis.

3. Results and discussion

3.1. Instrumentation and conditions

LC separation was optimised for all studied analytes (NP-AHD,NP-AOZ, NP-AMOZ, NP-SEM, RNZ and DMZ). Different mobilephases: 1, 5 and 10 mM ammonium formate in methanol/water(1:9 v/v) with pH 3.0–4.0 were tested using five LC columns of dif-ferent dimensions and from different suppliers; Agilent ZorbaxEclipse XDB C18 (4.6 � 150 mm, 5 lm), Phenomenex Kinetex C18(4.6 � 150 mm, 2.6 lm), Waters Symmetry C18 (4.6 � 150 mm,5 lm), Thermo scientific Hypersil C18 (4.6 � 150 mm, 5 lm) andSun Fire C8 (4.6 � 75 mm, 2.5 lm). The flow rate and gradient wereoptimised as described above in order to obtain separation withenough data points (at least 10–12) for each component in a rela-tively short run time. Efficient separation, symmetric peaks alongwith the highest possible signal intensity was successfullyachieved using the described conditions in a total run time of14 min. The fragmentation conditions and collision energies wereoptimised for each analyte by direct infusion of analyte standardsolutions into the mass spectrometer. For quantification and con-firmation, the protonated parent ions [M+1]+ and two transitionproducts were monitored (Table 1). This yields four identificationpoints, 1 for the precursor ion and 1.5 for each product ion, inagreement with CD 2002/657/EC for confirmatory methods.Moreover, identification and quantification of all analytes wasbased on four criteria: (1) chromatographic retention time stabil-ity, (2) matching of the retention time of analytes in spiked sam-ples and standard solutions, (3) presence of the two relevanttransitions from the analyte molecular peak, a signal to noise ratioof the ionic transitions (S/N > 3) and (4) stability of the ion ratiobetween the quantifier and qualifier peaks in accordance withthe tolerances recommended by CD 2002/657/EC (point 2.3.3.2).The ion ratio for each analyte was regularly monitored throughoutthe study in order to ensure that they were within acceptableranges. The less intense signal (low transition) was used as thequalifier and the most intense one (high transition) was used asthe quantifier (Fig. S2).

3.2. Sample preparation

It has been reported that NF metabolites could bind to proteinsor peptides and might form Schiff’s base adducts with carbohy-drates, aldehydes and/or ketones in honey (Lopez et al., 2007).Moreover, Tolgyesi et al. reported that RNZ might bind to sugarsforming an N-glycoside bond (Tolgyesi et al., 2012). Thus, mild acidtreatment for honey samples prior to analysis was carried out in

A.H. Shendy et al. / Food Chemistry 190 (2016) 982–989 985

order to liberate matrix-bound compounds. Moreover, acidic con-ditions provided a suitable environment for the derivatisationreaction using NBA (Verdon et al., 2007), as will be discussed indetail.

3.2.1. DerivatisationIn order to improve the sensitivity of detection, NF metabolites

are commonly derivatised prior to determination using LC–MS orLC–MS/MS (Chu & Lopez, 2007; Lopez et al., 2007). In this study,spiked honey samples were prepared using all analytes at theMRPL of NF metabolites and recommended concentration forNMZ (CRL guidance paper, 2007), as described above.Derivatisation of NF metabolites using NBA and extraction of NPderivatives using ethyl acetate was carried out in accordance tothe method of Verdon et al. that was previously reported for theanalysis of NF metabolite residues in poultry muscle tissue(Verdon et al., 2007). The effect of duration of incubation step(0.5–4 h) has been investigated at 55 �C in an agitated water bath.Results were calculated relative to a control sample of equivalentconcentration prepared in solvent and corrected for matrix effect(Table S1).

In agreement to previously reported results (Verdon et al.,2007), the reaction between NBA and NF metabolites was completeafter 3 h. Thus, in all determinations NP derivatives were analysedafter incubation at 55 �C for up to 4 h (Table S1). Lack of significantdifference in the percentage recovery of NMZ confirmed their sta-bility under the studied experimental conditions. The derivatisa-tion experiment was also carried out at a higher temperature(80 �C) in order to investigate whether increasing the reaction tem-perature would help reduce the reaction time. Results showed thatat 80 �C, maximum reaction yield for all NF metabolites wasreached within 0.5 h. However, a gradual decrease in the percent-age recovery was noted upon incubation for longer period of time.Results raised a concern about the stability of NP derivatives athigh temperature. Moreover, percentage recovery obtained uponincubation at 80 �C for 0.5 h was not significantly higher than thatobtained at 55 �C for 4 h, for all analytes. Neutralization of the reac-tion mixture was then carried out to pH 7.00 ± 0.05 in order toallow extraction using organic solvents as described.

3.2.2. ExtractionOwing to the complexity of honey matrix, that contains sugars,

enzymes, proteins as well as other minor components such aslipids and waxes, sample clean-up is generally employed.QuEChERS method (Anastassiades et al., 2003; Barganska et al.,2011) has been in use for sample preparation prior to analysis ofmulti-class residues in honey (Wang & Leung, 2012) and veterinarydrugs in honey and milk (Aguilera-Luiz, Vidal, Romero-Gonzalez, &Frenich, 2008). Originally, QuEChERS method involved a singleextraction step, sample clean up via dispersive solid phase extrac-tion using primary secondary amine and direct injection of largeextract volumes (Anastassiades et al., 2003).

In this study, a modified QuEChERS extraction protocol withoutsample clean-up followed by evaporation was optimised andemployed. Initially, the effect of extraction solvent composition;ethyl acetate, acetonitrile, dichloromethane and mixtures of ace-tonitrile – dichloromethane (1:1, 2:1, 3:1 and 4:1 v/v) was investi-gated. Results were evaluated on the basis of extraction efficiencyfor all components, cost and safety of employed solvent. Althoughextraction efficiency was relatively higher in case of acetonitrile –dichloromethane mixtures, acetonitrile was chosen in order toachieve efficient extraction of all studied analytes at approximatelythe same percentage recovery (Fig. 1). In this study, salting out andcomplete phase separation was achieved via addition of 4 g MgSO4

and 1 g NaCl in accordance to previously published protocol(Anastassiades et al., 2003). It should be noted that salting out

was particularly important in the case of extraction of NMZ com-pounds using acetonitrile (Fig. 1). Extracts were then centrifugedat 15,000�g using a cooling centrifuge. This step enabled furthersample clean-up via removal of solidified lipids and waxes in thesample. The resulting acetonitrile extracts were evaporated undervacuum at 45 �C till complete dryness using a rotary evaporator.Residue obtained was then reconstituted with mobile phase Aand analysed directly by LC–MS/MS.

It should be noted that vacuum evaporation resulted in accept-able percentage recovery for all studied analytes that were compa-rable to those obtained using nitrogen stream evaporationtechnique. Evaporation under vacuum was considered superior tothe commonly employed evaporation using nitrogen stream withrespect to both duration of time and cost. Results showing a com-parison between the two techniques relative to an equivalent con-trol sample prepared in solvent are summarized in Table S2.

The obtained results were in agreement to the previouslyreported recovery ranges for NF metabolites and NMZ in honeyat 0.50–2.00 lg kg�1 (Lopez et al., 2007) and at 10.00–100.00 lg kg�1 (Zhou et al., 2007), respectively. Slightly lower per-centage recoveries for NMZ have also been reported when com-pared to the above results (Galarini et al., 2015; Tolgyesi et al.,2012). The optimised sample preparation protocol enabled highpercentage recoveries for NMZ which could be attributed to inte-gration of the effects of both acid hydrolysis and salting out.

3.3. Calibration and quantification

When a multi-residue, multi-class assay is developed, it wouldbe difficult to obtain a radio labelled internal standard for eachcompound. In many cases, a representative internal standard isused in order to overcome cost and availability limitations of inter-nal standards (Nunez, Moyano, & Galceran, 2005). Matrix matchedcalibration; the most commonly adopted approach is used to com-pensate for signal suppression/enhancement experienced duringMS/MS analysis. In the current study, internal standard was notemployed and the quantification was accomplished using a set ofneat standard calibration curves using external standardisationapproach. Results were corrected using one point matrix matchedstandard at the MRPL of NF metabolites (1.00 lg kg�1) and recom-mended concentration of NMZ (3.00 lg kg�1). Assay validation andapplication to spiked honey samples, commercial samples as wellas a PT sample was then carried out in order to verify the applica-bility of this approach.

3.3.1. Linearity and working rangeA mixture of NF metabolite standards was prepared and deriva-

tised as described and NMZ standards were then added. A serialdilution of the standard mixture was prepared (0.25–10.00 ng mL�1) and analysed using the optimised assay conditions.Results were used to construct the neat standard calibration curvesfor the studied compounds. The matrix effect on instrumentresponse was then investigated in order to reveal possible signalsuppression or enhancement as previously recommended(Gosetti, Mazzucco, Zampieri, & Gennaro, 2010). Blank honey sam-ples were extracted and fortified with appropriate aliquots ofNP-derivatives of NF metabolites as well as NMZ (0.25–10.00 ng mL�1). Matrix matched calibration curves were con-structed and regression equation parameters were compared tothose obtained using the neat standard calibration curves(Table 2). Results showed that both curves were linear with accept-able correlation coefficients and random distribution of the resid-uals. Two spiked honey samples were prepared at 2.00 and10.00 lg kg�1 and their concentrations were determined usingboth calibration curves. Acceptable percentage recoveries wereobtained when the matrix matched calibration was employed.

Fig. 1. The effect of extracting solvents on the percentage recoveries of NP-AHD, NP-AOZ, NP-AMOZ, NP-SEM, RNZ and DMZ from honey samples. Error bars of the averagepercentage recovery are indicated.

Table 2Regression equation parameters and differences obtained for both neat standard and matrix matched calibration curves.

Compound(s) Neat standard calibration curves Matrix matched calibration curves Slope difference (%)

Slope Intercept R2 Slope Intercept R2

NP-AHD 19148.72 1058.97 0.999 14296.00 2516.00 0.996 �25NP-AOZ 241928.21 20097.44 0.998 127845.10 9004.10 0.995 �47NP-AMOZ 150331.28 10478.97 1.000 104011.30 4901.03 0.999 �31NP-SEM 10666.46 971.23 0.994 11205.95 477.64 1.000 +5RNZ 88894.36 5200.51 0.999 17272.82 7270.26 0.982 �81DMZ 21390.77 944.62 1.000 13607.18 8609.74 0.984 �36

Linear regression equation, y = ax + b; a, slope; b, intercept; y, response (cps); x, concentration (ng mL�1).

Table 3Statistical analysis for the results of the matrix matched standards determined usingneat standard calibration curves showing the matrix effect.

Compound(s) Descriptive statistical analysis for percentage recoveries(N = 15)

Meanpercentagerecovery

Medianpercentagerecovery

CV% Confidenceinterval (95.0%)

NP-AHD 66.96 68.07 5.02 6.23NP-AOZ 51.85 51.98 2.42 3.00NP-AMOZ 66.56 67.51 4.55 5.65NP-SEM 101.93 102.06 4.25 6.77RNZ 16.00 16.14 1.49 1.85DMZ 63.20 64.67 3.77 4.68

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On the other hand, when the neat standard calibration curves wereused, the percentage recoveries were significantly lower than thoseobtained using the matrix matched calibration curve, as shown inANOVA results (Table S3). Such results along with slope differencesshown in Table 2 indicated significant matrix effect.

3.3.2. Matrix effect and quantificationFor in depth evaluation of the matrix effect, the neat standard

calibration curves and matrix matched calibration curves werecompared. Slope differences calculated for each component indi-cated a significant matrix suppression ranging from �25% up to�81%, as shown in Table 2. Such differences were out of the±10% limit that has been previously suggested (Matuszewski,Constanzer, & Chavez-Eng, 2003) which indicated matrixsuppression.

In order to estimate a correction factor for the matrix effect, aset of extracted blank honey samples were fortified at 0.50, 1.00,1.50, 2.00 and 5.00 �MRPL/recommended concentration of thestudied compounds. Analysis was carried out as described andmean percentage recoveries and CV% were calculated using theneat standard calibration curve for each compound (Table 3).Results indicated a homogenous matrix effect throughout the lin-ear concentration range for each of the studied compounds.

Based on the obtained results, a correction factor was proposedfor each compound at the validation level. For each batch of honeysamples, one point matrix matched standard was prepared at theMRPL/recommended concentration of each compound. Results ofthe one point matrix matched standard were used to estimatethe correction factor for each compound. The following mathemat-ical equation can be then applied for the determination of analyteconcentration in samples after correction for the matrix effect:

Cs ¼ CiVextV f

VevpW

� �CmtxðlabelledÞ

CmtxðfoundÞ

� �

Cs, analyte concentration in sample (lg kg�1)Ci, found analyte concentration determined from calibrationcurve (lg kg�1)Vext, total volume of extraction solvent (mL)Vevp, aliquot volume taken for evaporation (mL)Vf, final volume after reconstitution of evaporated aliquot (mL)W, sample weight (g)Cmtx (labelled), labelled concentration of one point matrixmatched standard (lg kg�1)Cmtx (found), found concentration of one point matrix matchedstandard (lg kg�1)Cmtx (labelled)/Cmtx (found), matrix effect correction factor

A.H. Shendy et al. / Food Chemistry 190 (2016) 982–989 987

In order to verify the applicability of the proposed method ofcalculation, two spiked honey samples (2.00 and 10.00 lg kg�1 ofeach compound) were prepared and analysed as described above.The concentration of each compound was determined using thecorresponding neat standard calibration curve. Results were cor-rected using the proposed one point matrix matched method ofcalculation. Statistical comparison was then carried out to thoseobtained directly from the matrix matched calibration curves,using one-way ANOVA. Significant difference between the resultsobtained using the neat standard calibration curve and the matrixmatched calibration curve confirmed the profound matrix effect as

Fig. 2. Typical chromatograms for NP-AHD, NP-AOZ, NP-AMOZ, NP-SEM, RNZ and DMZcomparison to the corresponding blank samples, fortification level; 1.00 lg kg�1 for NP-

explained above. On the other hand, no significant differencebetween the results corrected for matrix effect and those obtainedusing the conventional matrix matched calibration confirmed theapplicability of our approach. A summary of the results of the sta-tistical analysis are summarized in Table S3.

3.4. Validation procedure

Validation was carried out in accordance with the proceduresoutlined in CD 2002/657/EC covering specificity and recovery(trueness/accuracy), precision (repeatability and

in fortified samples at the respective MRPL/recommended concentration level inAHD, NP-AOZ, NP-AMOZ and NP-SEM and 3.00 lg kg�1 for RNZ and DMZ.

988 A.H. Shendy et al. / Food Chemistry 190 (2016) 982–989

within-laboratory reproducibility), decision limits (CCa), detectioncapability (CCb) and measurement uncertainty (MU). The rugged-ness of the assay was demonstrated on an ongoing basis throughits use for routine analysis of honey samples.

3.4.1. SpecificityA specificity study was conducted in order to verify the absence

of potential interfering compounds at the retention time of thestudied analytes. The assay was applied to twenty blank honeysamples of different origins/matrix composition (viscosity, pig-ment content, pollen grain contents. . .). Representative honeysamples were fortified with all analytes at theMRPL/recommended concentration and analysis was carried outas described. No interfering peaks were detected in the region ofinterest for all analytes as shown in the chromatograms of blankhoney samples (Fig. 2).

3.4.2. Accuracy and precisionThe accuracy and precision (repeatability and within-laboratory

reproducibility) of the assay were measured at 0.5, 1.0 and1.5 �MRPL/recommended concentration for each analyte. Resultsindicated acceptable performance of the assay for all analytes overthe studied validation levels. The percentage recoveries were in therange of 90.96–104.80% with CV% of 1.35–5.10% and 2.65–12.58%for repeatability and within-laboratory reproducibility, respec-tively. These results were in agreement to the requirements ofCD 2002/657/EC regarding the CV% for repeated analysis of spikedor incurred material. Results are summarized in Table 4.

3.4.3. Decision limit and detection capabilityThe CD 2002/657/EC recommended analytical limits: (1) deci-

sion limit (CCa); the critical concentration at risk alpha (also calledthe decision limit) and (2) the detection capability (CCb); the crit-ical concentration at risk beta (also called the detection capability).In this study, CCa and CCb were calculated using the calibrationcurve procedure in accordance with ISO 11843. Blank honey sam-ples were analysed along with fortified samples with the studiedNF metabolites (0.50, 1.00, and 1.50 lg kg�1) and NMZ (1.50,3.00, and 4.50 lg kg�1). Responses were plotted against the addedconcentration, and CCa and CCb were determined. The CCa andCCb for the NF metabolites were 0.12–0.31 lg kg�1 and 0.21–

Table 4Accuracy, precision values, decision limit (CCa), detection capability (CCb) and measuremhoney.

Compound(s) Fortification level(lg kg�1)

Accuracy Repeatability

Percentagerecovery

Mean concentration(lg kg�1)

C

NP-AHD 0.5 95.60 0.49 31.0 96.40 1.00 41.5 97.33 1.50 3

NP-AOZ 0.5 99.80 0.51 21 99.60 1.01 21.5 97.73 1.48 2

NP-AMOZ 0.5 95.00 0.49 11 104.80 1.04 51.5 104.00 1.50 3

NP-SEM 0.5 98.20 0.50 41 95.60 0.99 21.5 100.93 1.50 1

RNZ 1.5 96.20 1.51 33 94.03 2.89 14.5 95.67 4.47 2

DMZ 1.5 93.33 1.51 43 97.00 3.03 14.5 90.96 4.40 5

0.53 lg kg�1 while for NMZ values were 0.53–0.74 lg kg�1 and0.91–1.27 lg kg�1, respectively. The obtained results confirmedthe high sensitivity of the developed assay. The calculated criticalconcentrations for CCa and CCb for the studied analytes are sum-marized in Table 4.

3.4.4. Measurement uncertainty (MU)Measurement uncertainty has not been explicitly mentioned in

CD 2002/657/EC. However, it can be determined correctly by sys-tematically taking into account all relevant influencing factors pos-sibly affecting the measurement results. According toSANCO/2004/2726-rev 4, the within-laboratory reproducibilitycan be regarded as a good estimator for the combined MU of indi-vidual methods. In this work, MU% was calculated for all studiedanalytes (11–21%) as summarized in Table 4.

3.5. Application to commercial honey samples

In order to demonstrate the applicability of the optimised assayprotocol as well as the correction factor calculation, thirty com-mercial honey samples of different botanical origin were obtainedfrom local market. The validated assay protocol was then appliedfor the detection and determination of the studied analytes.Results showed that AHD, AOZ, AMOZ, SEM, RNZ and DMZ werenot present in amounts above the detection capability or decisionlimit of the employed assay. Samples were claimed appropriate forhuman use according to the CRL guidance paper 2007. In all deter-minations, 1 g of honey sample was employed in order to reducethe time and cost of sample preparation and the amounts of theresidual matrix components.

3.6. Application to previously analysed PT sample

Further verification of assay performance and calculationapproach was carried out through analysis of a PT sample (round02249), as part of the Food Analysis Performance AssessmentScheme (FAPAS). An incurred honey claimed to contain NF metabo-lites was analysed as described and results were calculated usingthe proposed calculation method. Matrix-corrected results werecompared to those obtained using the currently adopted methodin our laboratory (Verdon et al., 2007) with modifications

ent uncertainty (MU) obtained for the studied NF metabolites and NMZ residues in

Within-lab reproducibility R2 CCa(lg kg�1)

CCb(lg kg�1)

MU%

V% Mean concentration(lg kg�1)

CV%

.76 0.48 9.83 0.998 0.12 0.21 18

.74 0.96 9.18

.66 1.46 6.45

.24 0.50 2.96 0.994 0.22 0.38 11

.93 1.00 5.16

.66 1.47 4.78

.35 0.48 4.71 0.999 0.2 0.34 21

.10 1.05 8.92

.37 1.56 8.32

.42 0.49 7.27 0.999 0.31 0.53 21

.47 0.96 5.63

.36 1.51 2.65

.74 1.44 5.44 0.999 0.53 0.91 13

.51 2.82 6.81

.83 4.31 5.06

.12 1.40 12.58 0.990 0.74 1.27 17

.81 2.91 7.57

.04 4.09 9.62

A.H. Shendy et al. / Food Chemistry 190 (2016) 982–989 989

described above (Table S4). Results of the optimised assay con-firmed the presence of AMOZ from the NF metabolite family.These results were in agreement to those obtained using the cur-rently adopted method and published in the results report (round02249). The z-score was calculated for the obtained results andwas found within the acceptable range |z| < 2 (Table S4).Satisfactory z-scores indicated the applicability of the proposedassay protocol for the determination of the studied compoundsin honey samples.

4. Conclusion

An accurate and sensitive LC–MS/MS assay was developed andvalidated for the simultaneous determination of six banned antibi-otics from two different classes in honey. Analytes were extractedusing modified QuEChERS protocol, without sample clean-up. Neatstandard calibration curves were successfully employed in con-junction with correction for matrix effect. Assay validation to thequality criteria and requirements of CD 2002/657/EC was carriedout. The applicability of the method for the determination of thestudied compounds was verified using spiked honey samples aswell as PT samples. The assay was deemed suitable for the regula-tory monitoring of NF metabolites and NMZ residues in locally pro-duced honey. This should help develop an efficient nationalmonitoring plan for Egyptian honeybee products.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.foodchem.2015.06.048.

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