Food Research International 54 (2013) 293–301
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A survey of the occurrence of ochratoxin A in Madeira wines based on a modified QuEChERS extraction procedure combined with liquid chromatography–triple quadrupole tandem mass spectrometry Paulo J. Fernandes a,b, Nelson Barros a, José S. Câmara b,c,⁎ a b c
Laboratório Regional de Veterinária e Segurança Alimentar, Caminho das Quebradas de Baixo, 79, 9000-254 Funchal, Portugal CQM – Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, Funchal, Portugal Centro de Ciências Exactas e da Engenharia da Universidade da Madeira, Campus Universitário da Penteada, 9000-390 Funchal, Portugal
a r t i c l e
i n f o
Article history: Received 22 March 2013 Accepted 4 July 2013 Keywords: Ochratoxin A Wine QuEChERS LC–ESI-MS/MS
a b s t r a c t Over the past years, to ensure food safety, the European Union (EU) has adopted specific legislation concerning the control of mycotoxins residue levels in different kinds of food. In this study, a fast, selective and sensitive reversed-phased liquid chromatography with tandem mass spectrometry (LC–MS/MS) methodology was developed and validated for quantification of ochratoxin A (OTA) in Madeira wines. Sample extraction and purification were performed with a modified QuEChERS-based (quick, easy, cheap, effective, rugged, and safe) procedure. Firstly, the homogenized samples are extracted and partitioned using an organic solvent and salt solution. Then, the supernatant is further extracted and cleaned using a dispersive solid phase extraction (dSPE) technique. Finally clear wine extracts were concentrated under vacuum to near dryness and taken up into initial mobile phase. Careful optimization of the LC–MS/MS parameters was achieved in order to attain a fast separation with the best sensitivity. The detection was carried out on a triple–quadrupole tandem mass spectrometer (MS/MS) by electrospray ionization in positive ion mode (ESI+) with multiple reaction monitoring (MRM). MS/MS conditions were optimized in order to increase selectivity, selecting the corresponding product ions (precursor-to-fragment m/z 404 → 239; m/z 404 → m/z 358) for quantification and identification. The performance of the method was assessed and compared to the European Commission (EC) Regulations, by studying the selectivity and specificity, limit of detection (LOD), limit of quantification (LOQ), linear dynamic range, matrix effect, accuracy, precision, robustness/ruggedness and uncertainty. The validation was performed by analyzing recovery samples at four different spiked concentrations, 0.5, 1.0, 5.0 and 10.0 μg/kg, with four replicates (n = 4) at each concentration. Recoveries ranged from 87.2% to 102.6%, with relative standard deviations below 9% in all cases. The intra-day precision and inter-day precision, expressed as relative standard deviation, were lower than 7% and 14%, respectively. Matrix effects were observed by comparing the slope of matrix-matched standard calibration with that of solvent. Good linearity was achieved at the concentration levels of 0.50–22.5 μg/L. The LOQ and LOD, 0.4 and 0.1 μg/kg, respectively, at the signal-to-noise ratio (S/N) of 10 and 3, were lower than the concentration usually permitted by legislation in wines. The method was successfully applied to evaluate the occurrence of OTA in 30 Madeira wine samples. None of the analyzed samples exceeded the maximum permissible limit for wines (2.0 μg/kg) set by the EC, which confirms that the risk of OTA occurrence in Madeira wines is, as expected, is very low. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Several foods, such as wheat, maize, rice, grapes and wines can be infested by filamentous and microscopic fungi which, under appropriate circumstances, can produce a wide range of secondary metabolites — mycotoxins (Almeida, Martins, Santos, Costa, & Bernardo, 2011; Bennett & Klich, 2003; Freitas-Silva & Venâncio, 2011; Khayoon, Saad,
⁎ Corresponding author at: CQM, Centro de Química da Madeira, Campus Universitário da Penteada, Funchal, Portugal. Tel.: +351 291705112; fax: +351 291705149. E-mail address:
[email protected] (J.S. Câmara). 0963-9969/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodres.2013.07.020
Lee, & Salleh, 2012; Soriano & Dragacci, 2004). Their presence depends on several factors, such as: fungal strain, climate and geographical conditions, cultivation technique and foodstuff conservation (Brera, Soriano, Debegnach, & Miraglia, 2004; Pena, Cerejo, Silva, & Lino, 2010). In tropical and subtropical areas, fungi are produced mainly by A s p e r g i l l u s species (Aspergillus ochraceus, Aspergillus sulphureus, Aspergillus sclerotinum, Aspergillus niger, and Aspergillus carbonarius), while in colder regions, Penicillium species (Penicillium verrucosum, Penicillium purpurascens, and Penicillium commune), are the most responsible for its biosynthesis (Gupta, 2007). Their occurrence in agricultural commodities has been long recognized as a potential hazard for both human and animal health since, some of them, can have carcinogenic,
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mutagenic and teratogenic effects (Creppy, 2002; Hussein & Brasel, 2001; IARC, 1993; Pfohl-Leszkowicz & Manderville, 2007). Among mycotoxins, ochratoxin A (OTA), chemically known as N-{[(3R)-5-chloro-8-hydroxy-3-methyl-1-oxo-7-isochromanyl]carbonyl}-3-phenyl-L-alanine (Fig. 1), has been the subject of special concern due to its diffusion and toxicological importance. OTA occurs in a number of food commodities both of plant and animal origin, being cereals and cereal products as the main sources (Duarte, Pena, & Lino, 2010; Kabak, 2009; Paíga et al., 2012), followed by wine and wine grape products, including raisins (Aksoy, Eltem, Meyvaci, Altindisli, & Karabat, 2007; Mikulíková, Beláková, Benešová, & Svoboda, 2012). In addition to its potential mutagenic and carcinogenic effects, there have been reports in literature on its nephrotoxicity, hepatotoxicity, immunotoxicity and neurotoxicity (Zöllner & Mayer-Helm, 2006). According to Turner, Subrahmanyam, and Piletsky (2009), OTA toxicity appears to be related to its ability to inhibit protein synthesis by competing with phenylalanine in the reaction catalyzed by phenylalanyl-tRNA synthetase and other systems requiring this amino acid. The International Agency for Research on Cancer (IARC) has classified it under Group 2B as a possible carcinogenic compound to humans (IARC, 1993). Due to these findings many countries have implemented regulations on OTA in food and feed to protect human and animal health as well as the economic interest of producers and traders. To ensure an efficient protection of public health, and in order to enable an effective enforcement, the EC has set limits on OTA levels in food, typically between 1 and 10 μg/kg depending on the type and quality of the foodstuff. For wines with an ethanol content lower than 14% (v/v) a maximum allowable limit (MAL) of 2.0 (μg/kg) was established (Commission Regulation (EC) No. 1881/2006). However, this limit does not apply to liquor or dessert wines with more than 15% of ethanol content. It is well known that the OTA occurrence and concentration in wines are highly affected by climatic conditions, namely high temperatures and humidity levels (Orduña, 2010; Paterson & Lima, 2011; Russell, Paterson, & Lima, 2010; Tirado, Clarke, Jaykus, McQuatters-Gollop, & Frank, 2010). Madeira island's specific climatic conditions, characterized by relatively high humidity ranging from 52% (mildly humid) to 84% (humid) and moderate temperatures, generally between 15 °C and 26 °C, over the year, makes the island a potential geographic region for OTA biosynthesis. As Madeira wine is the principal exportation product of the island, and therefore plays an important role in the economy of the Island, it is important to assure a continuous monitoring and control in order to guarantee the compliance of regulations, the product quality and consumer food safety (Rodríguez-Carrasco, Font, Mañes, & Berrada, 2012). Monitoring, control, risk assessment, and prevention of contaminants in food and in feed are important issues associated with public health, agricultural production, food processing, and trade. Food safety and feed safety, as well as carryover of contaminants into animal tissue, are of major public concern nowadays, especially when considering the dynamics and challenges in a global economy. Analytical methods for the identification and determination of mycotoxins need to be sensitive, selective, and robust to provide
Fig. 1. Chemical structure of OTA (N-{[(3R)-5-chloro-8-hydroxy-3-methyl-1-oxo7-isochromanyl]-carbonyl}-3-phenyl-L-alanine).
accurate data especially for monitoring, risk assessment, quality control, and research. For extraction and clean-up procedures, different approaches have been proposed (Turner et al., 2009; Zheng, Richard, & Binder, 2006). Enzyme linked immunosorbent assay (ELISA) (Barna-Vetro et al., 1996; Chu, 1992), stable isotope dilution assay (SIDA) (Lindenmeier, Schieberle, & Rychlik, 2011), supercritical fluid extraction (SFE) (Engelhardt & Hass, 1993; Young & Games, 1992), solid phase extraction (SPE) (Hernandez, Valme, Duran, Guillen, & Barroso, 2006), solid phase microextraction (SPME) (Vatinno, Vuckovic, Zambonin, & Pawliszyn, 2008), and molecular imprinted polymers (MIPs) (Maier, Buttinger, Welhartizki, Gavioli, & Lindner, 2004; Yu & Lai, 2010), have been widely employed to achieve extraction of OTA and other mycotoxins from different matrices. Recent studies showed that QuEChERS extraction procedure, initially proposed for pesticide analysis (Anastassiades, Lehotay, Stajnbaher, & Schenk, 2003), has been successfully used for the extraction of a broad range of analytes in food besides pesticides. Such studies include quantification of low molecular weight polyphenols in vegetables (Silva, Nathaly Haesen, & Câmara, 2012), polycyclic aromatic hydrocarbons (PAHs) in fish (Ramalhosa, Paíga, Morais, Delerue-Matos, & Oliveira, 2009), acrylamide in food (Mastovska & Lehotay, 2006), pesticide residues in food matrices (Wilkowska & Biziuk, 2011), carbamate residues in milk (Keegan et al., 2009), mycotoxins in cereal products (Cunha & Fernandes, 2010; Vaclavik, Zachariasova, Hrbek, & Hajslova, 2010; Zachariasova et al., 2010) as well as in other matrices besides foods (Stubbings & Bigwood, 2009). Currently, chromatographic techniques based on high pressure liquid chromatography (HPLC) with UV/Vis and fluorescence detection (Eskola, Kokkonen, & Rizzo, 2002; Visconti, Pascale, & Centonze, 1999), and HPLC coupled to mass spectrometry (LC–MS) (Richard, Plattner, May, & Liska, 1999) or tandem MS (HPLC– MS/MS) (Jorgensen, 1998; Lau, Scott, Lewis, & Kanhere, 2000; Milicevic, Juric, Stefanovic, Veskovic-Moracanin, & Jankovic, 2009) are used for the identification and determination of mycotoxins in food and feed, due to its higher sensitivity, selectivity and accurate identification. The purpose of this work was to develop a confirmative method which is sensitive, reliable, cost-effective, rapid and adaptable to a routine work for the surveillance of OTA in wines, based on QuEChERS extraction combined with LC–ESI-MS/MS analysis for detection, quantification and reliable identification of the target mycotoxin. The procedure is based on the extraction of OTA with a mixture of acetonitrile and acetic acid (99:1), followed by the removal of interfering substances from the extract by dSPE before LC– ESI-MS/MS analysis. The performance of the methodology was evaluated in terms of linearity, LOD, LOQ, precision and accuracy. An additional goal was to evaluate the occurrence of OTA in different types of Madeira wines. 2. Materials and methods 2.1. Chemicals and reagents Solvents were LC–MS grade and OTA was analytical standard grade. The OTA standard from A. ochraceus, with a purity N 98%, and acetonitrile (Fisher Scientific) was obtained from J.M.G. Santos (Odivelas, Portugal), toluene (Fisher Scientific), glacial acetic acid (Fluka), sulfuric acid (Merck), and acetonitrile (Fisher Scientific) were obtained from J.M.G. Santos (Odivelas, Portugal). Methanol (Sigma-Aldrich), ammonium acetate (Sigma-Aldrich), magnesium sulphate anydrous (thin powder) (Fluka), sodium chloride (Fischer Scientific), sodium citrate tribasic dihydrate (Sigma-Aldrich) and sodium citrate dibasic sesquihydrate (Fluka) were obtained from LaborSpirit (Setúbal, Portugal). Ultrapure water (18.2 MΩ/cm, Milli-Q Plus system, Millipore Bedford, MA, USA) was used throughout the work. All chromatographic solvents were filtered through a 0.20 μm Grace membrane nylon filter (Ø 47 mm, Bannockburn, IL, USA) under vacuum and degassed for 15 min in an ultrasonic bath (StarSonic 90 Liarre, Casalfiumanese, Italy).
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All solution and sample extracts were filtered through a Waters syringe filter, PTFE, 0.20 μm, from Via Athena (Ø25 mm, Lisbon, Portugal). For homogenization a Heidolph Reax Top vortex mixer (Schwabach Germany) was used. 2.2. OTA standard solution The OTA standard stock solution was prepared by dissolving the pure standard in 1 mL toluene:acetic acid (99:1, v/v), obtaining a 100 μg/mL solution. The intermediate solutions were prepared at 1 and 10 μg/mL in toluene:acetic acid (99:1). All standards were stored at −20 ºC. Amber glassware was used to prevent light deterioration of the mycotoxin. The actual concentration of the OTA (ρOTA in μg/mL) was calculated using an UV–Vis spectrometer, according to the following equation ρOTA ¼ A max
M 100 kδ
ð1Þ
where, Amax is wavelength at the maximum of the absorbance curve (333 nm); M is molecular weight of OTA (M = 403 g/mol); k is molar absorption coefficient for OTA in mixture I (544 m2/mol); and δ is the length of cell in cm. OTA working solution was prepared at 0.1 μg/mL in mobile phase. Calibration curve standard solutions were prepared in mobile phase at five concentrations ranging from 0.5 to 22.5 μg/L. 2.3. Wine samples Thirty different Madeira wines were analyzed for this study. Seventeen of these wines, from 2010 vintage, were made from Tinta Negra Boal, Malvazia, Sercial and Verdelho grapes. These wines present an ethanol content within 12.5% and 14% (v/v). Thirteen samples, provided by Instituto do Vinho, do Bordado e do Artesanato da Madeira were analyzed without knowing the grape variety and vintage year. 2.4. QuEChERS extraction and clean-up QuEChERS procedure involves two steps: the first one is an extraction step based on partitioning via salting-out extraction involving the equilibrium between an aqueous and an organic layer, and the second one is a dispersive SPE (DSPE) step that involves further clean-up using combinations of MgSO4 and different sorbents, to remove interfering substances. QuEChERS mixture was prepared by weighing anhydrous magnesium sulphate (tin powder), sodium chloride, sodium citrate tribasic dihydrate and sodium citrate dibasic sesquihydrate in a proportion of 4:1:1:0.5. All reagents were well mixed so as to achieve a visually homogeneous mixture. A volume of 4 mL of wine was transferred to 50 mL centrifuge tubes, with screw caps, followed by 4 mL of acetonitrile:acetic acid (99:1 v/v), and 2.6 g of QuEChERS mixture. The mixture is shaken by vortex (Heidolph Reax Top) for 10 s and centrifuged (Selecta Meditronic BL-S) at 1489 g, for 5 min. Afterwards, an aliquot (1 mL) from the upper part of the extract (acetonitrile phase) was transferred into different 2 mL PTFE dSPE clean-up tubes containing, in each tube, 150 mg MgSO4 and 50 mg of different sorbents: primary and secondary amine (PSA), C18, florisil, alumina and silica, and subjected to clean-up by dSPE. This procedure is of crucial importance to maximize the sensitivity of OTA and to minimize the presence of interfering compounds in the extract. The mixture was shaken in a vortex and centrifuged for 2 min at 1489 g. Then, 700 mL aliquot of the extract was evaporated under a gentle stream of nitrogen to near dryness and the residue was taken up with 150 mL of initial mobile phase and stored at −20 ºC until analysis (24 to 48 h at maximum). All the samples and standard extracts were filtered through a 0.22 μm Millipore PTFE filter membrane prior to LC–MS/MS analysis.
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2.5. Method validation Method validation for OTA quantification in wines involved the assessment of the selectivity and specificity, linearity, determination of LOD and LOQ, precision (expressed as relative standard deviation — RSD), accuracy (as recovery percentage), matrix effect (expressed as signal suppression/enhancement — SSE%), robustness/ruggedness (tested with a one-way ANOVA test) and uncertainty estimation. The performance characteristics were established with spiked wine (sample #3). The selectivity of the method was investigated by checking the peak purity of OTA using a compliance technique (LC–ESI-MS/MS), with the ESI source operating in positive mode. The specificity was assessed by analysis of different wine samples (#3, #5 and #7) and checking for possible interferences in the region of interest where the target product ion was expected to elute. Linearity and linear range were evaluated through the coefficient of correlation of a calibration curve constructed by plotting OTA peak area versus OTA concentration of standard solutions injected in quadruplicate at five levels of concentration ranging from 0.5 to 22.5 μg/L, and the respective residuals inspected. The calibration curve was fitted by linear least-square regression and the value obtained for the correlation coefficient (0.996) shows that the method is linear in the range of studied concentrations. This calibration curve was also used to calculate the matrix effect for OTA in wine extract through the quotient between the slope of the standard in the solvent and those obtained by spiking Madeira wine sample #3 extracts. A value of 100% indicated that there was no matrix effect. There was matrix enhancement if the value was higher than 100% and signal suppression if the value was lower than 100%. The LOD and the LOQ were calculated by three different approaches: 1) by using the variability of peak area, injecting the analyte several times at the lowest calibration level (LCL) (approach I); 2) by the calibration curve using the residual standard deviation of linear function (Sy/x) (approach II); and 3) by the concentration at which the quantifier transition presented a signal-to-noise (S/N) ratio greater than 3 and 10, respectively (approach III). The precision of the whole method was evaluated in terms of repeatability (intra-day precision) and intermediate precision (inter-day precision). Repeatability was assessed by the application of the whole procedure on the same day, by the same analyst (experimental replicates). Intermediate precision was evaluated with a similar procedure, by analyzing wine samples on different days. The results were expressed as the relative standard deviation (%RSD). The method accuracy was evaluated through a recovery test at four concentrations in triplicate. Samples were fortified before the extraction step at levels corresponding to 0.5, 1.0, 5.0 and 10 μg/kg. The robustness/ruggedness was calculated by comparing recoveries of the same sample, at different conditions of pH and analyzing differences by one-way ANOVA. 2.6. Uncertainty measurement Measurement uncertainty (Silva, Santos, & Camões, 2006) was performed by combining independent contributions that affect the final result according to the following equation uy ′ ¼u ¼ y
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi r 2 2 2 2ffi u′ precision þ u′ Recovery þ u′ Cp þ u′ m 2 þ u′ Evap
ð2Þ
where: u′precision is relative uncertainty associated to the precision of the method; u′Recovery is relative uncertainty associated to the precision of the method; u′Cp is relative uncertainty associated to the concentration of standard solution;
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u′m u′Evap
is relative uncertainty associated to the mass of subsample; and is relative uncertainty associated to the evaporation of standard solution.
The expanded relative uncertainty (U′) for the method, was calculated by multiplying relative combined uncertainty by a coverage factor of two (k = 2) which corresponds, to a Student-t distribution (two-tailed) for n-1 degrees of freedom with a confidence level of 95%. ′
′
U ¼2u
ð3Þ
The calculated uncertainty was compared to the fitness-for-purpose approach, established by Commission Regulation (EC) No. 401/2006, laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs, to evaluate the acceptability of methods used. According to this regulation, the maximum standard uncertainty may be calculated using the following equation: Uf ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðLOD=2Þ2 þ ðα CÞ2
ð4Þ
where: Uf LOD α C
is the maximum standard uncertainty (μg/kg); is the limit of detection of the method (μg/kg); is a constant, depending on the C value [5]. For C ≤ 50 μg/kg′ α = 0.2; and is the concentration of interest (μg/kg).
2.7. LC–ESI-MS/MS conditions Liquid chromatography was performed on a Waters Alliance 2695 system consisting of a quaternary, low-pressure mixing pump, on-line vacuum degasser, autosampler and column compartment. Separation of OTA was achieved on a silica-based reversed-phase C18 Atlantis T3 (150 mm × 2.1 mm, 5 μm) analytical narrow bore column, kept at 30 °C. A binary mobile phase with a gradient program was used, combining solvent A (water:methanol (9:1) with 5 mM ammonium acetate) and solvent B (water:methanol (1:9) with 5 mM ammonium acetate) as follows: 100% A (0 min); and 0% A (15–20 min). The flow rate of the mobile phase was set to 0.3 mL/min and the injection volume of both standard solutions and sample extracts was 20 μL. The system was reequilibrated with the initial composition for 5 min, prior to next injection. Mass spectrometry was performed on a Micromass Quattro Micro triple-quadrupole equipped with an electrospray ionization (ESI) source, operating in the positive ion mode. Data acquisition, data processing and instrument control were performed through Microsoft Windows-NT (v 4.1)-based MassLynx software. The mass spectra were acquired over the mass range 50 to 1000 m/z. The ionization source working conditions were as follows: source temperature, 140 °C; capillary voltage, 2.9 kV; cone gas flow rate, 80 L/h; desolvation gas flow rate 650 L/h; desolvation temperature, 350 °C; cone voltage was operating at 30 V; and collision energy was set at 19 eV. Nitrogen (N99% purity) and
argon (99% purity) were used as nebulizing and collision (product ion scan, MS/MS) gasses, respectively. Flow injection of OTA was used to optimize the multiple reaction monitoring (MRM) conditions. A dwell time of at least 25 ms was applied to each MRM transition. The most abundant MRM transition (404 N 239; [MOTA + H-C9 H11O2N]+) was used for quantification while the other transition (404 N 358; [MOTA + H-HCOOH]+) was used for confirmation. The criteria applied to confirm the identity of OTA were: (1) the signal for each of the two specific MRM transitions of the analyte had to be identical in the sample and in the standard; (2) the peak ratio of the confirmation transition against quantification; and (3) the relative retention time of the analyte in both, sample and standard solution, should be as maximum difference of 0.1 min. 3. Results and discussion Various clean-up sorbents for the determination of OTA by LC–MS/ MS in wine were tested and compared to the extract without clean-up. In all assays 50 mg of different sorbents was used. All sorbents provided flat baselines that were free from most impurity peaks, and quite repeatable results. However, the best results were obtained using silica as clean-up sorbent (Table 1S; Supplementary material). A preliminary study was performed in order to optimize the LC condition to achieve good resolution in a short chromatographic run. The choice of water–methanol as mobile phase was mainly determined by the lower operational pressure on the column. The optimization of MRM conditions for OTA was carried out by infusing a standard solution at a concentration level of 22.5 μg/mL, in positive ESI ionization mode, with the objective of obtaining the protonated molecule and selecting those transitions with higher molecular weight in order to avoid the disruptive effects of the matrix, as much as possible. All tuning data acquired automatically through the software were manually examined to ensure proper selection of product ions and collision energy. The MS conditions were first optimized in quadrupole 1 (Q1), which transmits only an ion of m/z. After collision induced dissociation (CID) studies, the conditions were adjusted for the third quadrupole (Q3) to provide optimal signals from the daughter ions. The precursor and product ions, quantifier and qualifier, collision energies and cone voltages, as well as the dwell time for OTA are listed in Table 1. The identification procedure for OTA in wines was carried out using the retention time and two transitions: m/z 404 → 239 and m/z 404 → 358 (Fig. 1S, Supplementary material), being the most intense transition (404 → 239) used as quantifier while the other one was used as qualifier peak for the confirmatory analysis (Fig. 1S). Transitions selected from precursor ion [M + H]+, by direct infusion on mass spectrometer, (404 N 239 and 404 N 358) were consistent with transitions selected in similar works and showed suitable selectivity and specificity. In addition to the dominant protonated molecule at m/z 404 are low-abundance fragment ions resulting from the loss of water ([M + H-H2O]+ at m/z 386), loss of formic acid ([M + H-HCOOH]+ at m/z 358) and loss of phenylalanine ([M + H-Phe]+ at m/z 239) (Fig. 2). Proposed fragmentation pathways for OTA are presented in Fig. 3. At high collision energies (e.g. 30 eV), the fragment ion of [M + H]+ from OTA showed additional fragments at m/z 221
Table 1 Monitored ions and MS/MS parameters for OTA analysis. RTa (min.)
Molecular weight
Mode
Percursor ion
MRMb transitions Transition 1
15.30 a b c
403
RT — retention time, in minutes. MRM — multiple reaction monitored. Coll — collision energy.
ESI+
[M + H]+ [M + H]+
Dwell time (ms)
Cone (V)
Coll.c (eV)
Delay (s)
25 25
31 31
19 19
0.01 0.02
Transition 2
404.1 N 239.1 404.1 N 358.1
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Fig. 2. (A) Characteristic transitions viewed in MRM mode, specific daughter ions produced by collision-induced dissociation of [M + H]+ ions of OTA transitions; and (B) MS2 spectra of OTA. The labeled signals of OTA, m/z 239 [M + H-Phe]+ and m/z 358 [M + H-HCOOH]+, were used for quantitative and qualitative analysis, respectively.
([M + H-Phe-H2O]+), 341 ([M + H-HCOOH-NH3]+), and 166 ([M + H-Phe]+). For our quantitative analyses, the two most abundant fragments from the [M + H]+ ions of the OTA, were monitored in the MRM mode. 3.1. Method validation To demonstrate the compliance of the method to the EC requirements, their performance was fully evaluated. 3.1.1. Selectivity and specificity The selectivity and specificity were demonstrated by recognizing the peak of OTA at concentrations of 0.5, 2 and 5 μg/L in a matrix of wine (#3, #5 and #7), in the presence of several mycotoxins (aflatoxins B1, B2, G1, G2, M1, fumonisin B1, T-2 toxin, HT-2, deoxinilvalenol, zearalenone, patulin and nivalenol) (Fig. 4). There are no interferences that resulted from the presence of these mycotoxins, or from the matrix. Specificity was demonstrated by the correlation between peak areas and concentration of OTA, showing that chosen transitions are specific for OTA.
3.1.2. Determination of LOD and LOQ Method sensitivity was determined by LODs and LOQs, calculated by three different approaches. Table 2 presents the obtained results, which can be achieved satisfactorily for the first and third approach. The second approach, using the curve data and using the residual standard deviation (Sy/x) is frequently affected by the heteroscedasticity of the curve which overestimates LOD and LOQ determinations. The three approaches show inter-day variations and involve the participation of the analyst on the integration of peaks. Signal-to-noise (S/ N) approach was chosen as the best method since the calculation is more independent of the activity of the analyst and more realistic. The LOQ obtained (0.4 μg/kg) is lower than the maximum limits established by Commission Regulation (EC) No. 401/2006 showing the suitability of the developed method for the determination of trace amounts of OTA in these types of samples. 3.1.3. Linearity and concentration range Correlation between the response and the amount of analyte was verified by plotting signal intensity against the analyte concentration. Calibration curve, prepared with solvent standards, five levels from 0.5 to 22.5 μg/L, in quadruplicate, showed good linearity (Pearson
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Fig. 3. ESI-MS/MS fragmentation pathways proposed for OTA. Adapted from Lau et al. (2000) and Flamini, Vedova, De Rosso, and Panighel (2007).
coefficient = 0.996 and residuals randomly distributed around the x-axis) (Fig. 5(A)). The use of the weighted function (1 / x) is recommended to calculate percent residuals for curves when some heteroscedasticity is present (Fig. 5(B)). The weighted function (1 / x) shows percent residuals less than 20% along the range tested (Fig. 5(C)). 3.1.4. Matrix effect The matrix effect was evaluated by comparing the slopes in solvent-matched solutions to the slopes in matrix-matched solutions and calculating the signal suppression/enhancement (SSE%) by the following equation, which compares the slopes obtained. SSEð% Þ ¼
slopeðspiked
extractÞ
slopeðspiked
solventÞ
100
5
The obtained results are shown in Table 2. Any significant matrix-induced chromatographic response enhancement effects are observed for OTA determination in wine (SSE% = 106.5%) (Table 2). 3.1.5. Recovery and precision Recovery experiments for the whole procedure were carried out by spiking blank wine samples with OTA, at concentrations of 0.5, 1,
5 and 10 μg/kg, in quadruplicate, by using matrix matched calibrations, in order to correct any potential matrix induced signal suppression/ enhancement (SSE). Satisfactory results were found for most of the recoveries, with individual values ranging from 87.2 to 102.6%, which are according to recoveries accepted by Commission Regulation (EC) No. 401/2006 (50–120% for concentrations until 1 μg/kg and 70–110% for concentrations from 1 to 10 mg/kg). The RSD achieved for the different spiking levels were all lower than 14%. The obtained results, summarized in Table 2, accomplish the target values established by Commission Regulation (EC) No. 401/2006 (RSDr maximum of 40% for concentration until 1 μg/kg and 20% for concentrations from 1 to 10 mg/kg). The RSDR achieved also accomplished the target values established by same EC regulation (RSDR maximum of 60% for concentrations until 1 μg/kg and 30% for concentrations from 1 to 10 mg/kg).
3.1.6. Robustness/ruggedness Robustness was assessed by testing the resistance of the method by changing the pH of matrix prior the extraction. Formic acid and sodium hydroxide were used to adjust the pH to 3 and 9, respectively. The obtained results (Supplementary Table 2S), treated by one-way
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Total Area
A
4500 4000 3500 3000 2500 2000 1500 1000 500 0 0
299
y = 179323x + 43,15 R² = 0,9987
y = 168347x + 44,033 R² =0,9958
0,005
0,01
0,015
0,02
Solvent Wine
0,025
µg/mL
Absolute residuals
B 2.0E+02 1.0E+02 0.0E+00 0.000 -1.0E+02
0.005
0.010
0.015
0.020
0.025
0.020
0.025
-2.0E+02 -3.0E+02
µg/mL
Percent residuals
C
Fig. 4. Product ion mass chromatograms of wine sample (#3) spiked with OTA at different levels, in the presence of other mycotoxins.
Table 2 Figures of merit of the QuEChERS/LC–ESI-MS/MS method, accuracy, precision, matrix effect results and LOD and LOQ values determined by three different approaches (I, II and III). Parameter of validation
Results
Selectivity Linear range (μg/L) Linearity (r) Precision RSDintra-day (%, n = 5) Level 1 (0.5 μg/kg) Level 2 (1.0 μg/kg) Level 3 (5.0 μg/kg) Level 4 (10 μg/kg) RSDinter-day (%, n = 25) Level 1 (0.5 μg/kg) Level 2 (1.0 μg/kg) Level 3 (5.0 μg/kg) Level 4 (10 μg/kg) Mean recovery (%) Level 1 (0.5 μg/kg) Level 2 (1.0 μg/kg) Level 3 (5.0 μg/kg) Level 4 (10 μg/kg) SSEb (%) Limits of detection Ic — 3 × S IIc — 3 × (Sy/x / m) IIIc — S/Ns (3:1) Limits of quantification Ic — 10 × S IIc — 10 × (Sy/x / m) IIIc — S/Ns (10:1)
Selective (LC–ESI-MS/MS) 0.5–22.5 0.996
a b c
15.0 % 10.0 % 5.0 % 0.0 % 0.000 -5.0 %
0.005
0.010
0.015
-10.0 % -15.0 %
µg/mL Fig. 5. (A) OTA calibration curve used for quantification of OTA in wine samples (all calibration points were obtained by three independent sample injections); (B) distribution of absolute residuals; (C) distribution of residuals, by using weighted regression 1 / x.
ANOVA, do not show significant differences between the groups (p N 0.05, null hypothesis is rejected).
6.6 6.5 5.3 4.2
Target Target Target Target
value: value: value: value:
≤40 ≤20 ≤20 ≤20
13.5 12.0 7.2 5.2
Target Target Target Target
value: value: value: value:
≤60 ≤30 ≤30 ≤30
88.7 ± 6.53a 87.2 ± 4.32a 98.7 ± 8.50a 102.6 ± 2.90a 106 ± 7.41 μg/mL (extract) 0.0014 0.0022 0.0001
Target Target Target Target
range; range; range; range;
50–120 70–110 70–110 70–110
0.0046 0.0074 0.0004
4.6 7.4 0.4
μg/kg (sample) 1.4 2.2 0.1
Mean ± SD (standard deviation) (n = 4). Matrix effect expressed as signal suppression/enhancement. LOD and LOQ values determined by three different approaches I, II and III.
3.1.7. Uncertainty Despite the fact that measurement uncertainty cannot be attributed to the method and only to the results knowledge about it is essential for comparing measurements with legal limits. Therefore, method validation should include the estimation of measurement uncertainty, which should incorporate the effects resulting from its normal use. The considered sources for quantifying uncertainty were accuracy, precision, subsample weight, preparation of standard solution (including the impact of spectrophotometer and volumetric steps) and evaporation of standard solution along time, as illustrated in Supplementary Fig. 2S(A). The accuracy component reflects the mean recovery of the method. Precision component combines the effect of several sources, as preparation of diluted standards (volumes used and transferred, calibration curves, equipment specifications, and matrix effects, among others) (Supplementary Fig. 2S(B)) which are not independent, reducing the overall effort involved. The component “Others” includes sources of uncertainty that are constant along time. Relative standard uncertainty for the different components, was calculated and combined, according to the differential approach and their contribution for overall uncertainty is shown in Supplementary Fig. 2S(B).
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Results obtained by differential approach, using Eq. (2): U′ = 2 × 0.186 = 0.37, were considered similar to the ones obtained with the fitting-for-purpose approach: qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Uf ¼ ð0:1=2Þ2 þ ð0:2 2Þ2 ¼ 0:40 which represents 0.40 μg/kg/2 μg/kg = 0.2 or 20% of the concentration of interest. Relative expanded uncertainty (U′) will be 2 × 0.2 = 0.40 or 40%. Therefore the R results obtained should be presented as R ± U′R. 3.2. Quantification of OTA in wine samples The proposed QuEChERS method for OTA extraction followed by LC– ESI-MS/MS was employed in the analysis of real wine samples in order to show its applicability. Representative chromatograms of OTA standard solutions, at concentrations of 0.5, 2 and 4 μg/kg, and wines are presented in Supplementary Fig. 3S(A) and S(B), respectively. All the samples were screened in positive mode with full scan MS (Q1). The results of the occurrence of OTA in all of the investigated wines are summarized in Table 3. None of the 30 samples analyzed showed OTA at or above the used lowest calibration level (LCL) (0.5 μg/kg). OTA was not detected in 28 (93.3%) of the 30 analyzed samples, whereas in 2 of the 30 investigated wine samples, the OTA levels present an average content of 0.42 ± 6.31 μg/kg, a value among LOD (0.4 μg/kg) and LCL (0.5 μg/kg). The repeatability, expressed as the relative standard deviation (n = 3), ranged between 1.2% and 7.4%, with a mean value of 6.31%. The detected OTA content in all the analyzed samples was under the maximum allowable limit set by the EC (2 μg/kg). Table 3 Occurrence of OTA (μg/kg) in Madeira wine samples investigated. Wine samples
OTA concentration (μg/kg)
#1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14 #15 #16 #17 #18 #19 #20 #21 #22 #23 #24 #25 #26 #27 #28 #29 #30 % Positive samples Mean (μg/kg)
NDa bLOQb ND ND ND ND ND bLOQ ND ND bLOQ ND ND bLOQ bLOQ ND ND ND bLOQ bLOQ ND bLCLc (0.41d ± 6.1e) ND ND bLOQ ND ND bLOQ ND bLCL (0.45 ± 7.4) 6.67 (2/30) 0.42c±6.31
a b c d e
ND — not detected. bLOQ — lower than method quantification limit (0.4 μg/kg). bLCL — lower than the lowest calibration level (0.5 μg/kg). Concentration among LCL and LOQ. Relative standard deviation (RSD, %).
4. Conclusions This paper describes an inexpensive and effective procedure for quantification of OTA in wine samples based on a slightly modified QuEChERS extraction procedure followed by LC–ESI-MS/MS. Satisfactory validation parameters, including selectivity/specificity, linearity, recovery, precision, LODs and LOQs, and robustness/ruggedness, were obtained. The recoveries obtained ranged from 87.2% (at 1.0 μg/kg) to 102.6% (at 10.0 μg/kg). The limit of quantification of the method (0.4 μg/kg) was, at least, 5 fold lower than the maximum legal OTA concentration in wines, with precision lower than 14%. The calculated uncertainty was smaller than the maximum standard uncertainty defined by the EC regulation, and therefore the method can be used for reliable OTA monitoring purposes. Moreover, the method has the potential to be used with other matrices assuring compliance with maximum permitted levels and for carrying out survey work and research. The chromatographic method was optimized to screen other mycotoxins with retention times between 7.8 min (as DON) and ZEN (17.6 min). Despite the fact that it is possible to achieve minor retention times for OTA, laboratory batches of samples can include other kinds of samples to analyze other mycotoxins so the chromatographic method remains constant in order to preserve the identity and type of samples analyzed. Finally, this optimized procedure was applied to 30 samples of Madeira wines and none of the samples exceeded the legal European limit of 2 μg/kg. These results confirm that the method is adequate for the purpose intended showing a high probability that the OTA content in wine was below 2 μg/kg. In fact, considering all 30 samples as a lot, on the basis of a binomial probability distribution and using Eq. (6), n
1−p ¼ ð1−iÞ
ð6Þ
where p is the probability; and i is the incidence of non-compliant samples in the lot (both expressed as fractions, and n the number of samples). For p = 0.95 and n = 30, i becomes 0.10. The analysis of 30 samples would detect at least one infraction if the incidence of non-compliant samples was more than 10%. The advantages of the proposed analytical procedure in addition to the low LOQs attained could be applied in surveillance programs and regular monitoring of OTA in wine, wine-based products and other foodstuffs. Supplementary data to this article can be found online at http:// dx.doi.org/10.1016/j.foodres.2013.07.020. Acknowledgments This work is supported by the Fundação para a Ciência e a Tecnologia (FCT) through the Strategic Plan PEst-OE/QUI/UI0674/2011, and the Portuguese Mass Spectrometry Network — RNEM 2013. The authors are grateful to Engª Ângela Nascimento from IVBAM — Instituto do Vinho, do Bordado e do Artesanato da Madeira, for providing wine samples. References Aksoy, U., Eltem, R., Meyvaci, K. B., Altindisli, A., & Karabat, S. (2007). Five-year survey of ochratoxin A in processed sultanas from Turkey. Food Additives and Contaminants, 24(3), 292–296. Almeida, I., Martins, H. M., Santos, S., Costa, J. M., & Bernardo, F. (2011). Co-occurrence of mycotoxins in swine feed produced in Portugal. Mycotoxin Research, 27, 177–181. Anastassiades, M., Lehotay, S., Stajnbaher, D., & Schenk, F. (2003). Fast and easy multiresidue method employing acetonitrile extraction/partitioning and “dispersive solid-phase extraction” for the determination of pesticide residues in produce. Journal of AOAC International, 86, 412–431. Barna-Vetro, I., Solti, L., Teren, J., Gyongyosi, A., Szabo, E., & Wolfling, A. (1996). Sensitive ELISA test for determination of ochratoxin A. Journal of Agricultural and Food Chemistry, 44(12), 4071–4074. Bennett, J. W., & Klich, M. (2003). Mycotoxins. Clinical Microbiology Reviews, 16(3), 497–516. Brera, C., Soriano, C. M., Debegnach, F., & Miraglia, M. (2004). Exposure assessment to ochratoxin A from the consumption of Italian and Hungarian wines. Microchemical Journal, 79(1–2), 109–113.
P.J. Fernandes et al. / Food Research International 54 (2013) 293–301 Chu, F. S. (1992). Handbook of applied mycology. In D. Bhatnagar, E. B. Lillehoj, & D. K. Arora (Eds.), Mycotoxins in Ecological Systems (pp. 87). New York: Marcel Dekker. Commission Regulation (EC) No. 401/2006 laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs. Official Journal of the European Union, L 70. (2006)., 12. Commission Regulation (EC) No. 1881/2006 setting maximum levels for certain contaminants in foodstuffs. Official Journal of the European Communities, L364. (2006)., 5 (20.12.2006). Creppy, E. E. (2002). Update of survey, regulation and toxic effects of mycotoxins in Europe. Toxicological Letters, 127(1–3), 19–28. Cunha, S. C., & Fernandes, J. O. (2010). Development and validation of a method based on a QuEChERS procedure and heart-cutting GC–MS for determination of five mycotoxins in cereal products. Journal of Separation Science, 33, 600. Duarte, S. C., Pena, A., & Lino, C. M. (2010). A review on ochratoxin A occurrence and effects of processing of cereal and cereal derived food products. Food Microbiology, 27(2), 187–198. Engelhardt, H., & Hass, P. (1993). Possibilities and limitations of SFE in the extraction of aflatoxin B1 from food matrices. Journal of Chromatographic Science, 31, 13–19. Eskola, M., Kokkonen, M., & Rizzo, A. (2002). Application of manual and automated systems for purification of ochratoxin A and zearalenone in cereals with immunoaffinity columns. Journal of Agricultural and Food Chemistry, 50(1), 41–47. Flamini, R., Vedova, A. D., De Rosso, M., & Panighel, A. (2007). A new sensitive and selective method for analysis of ochratoxin A in grape and wine by direct liquid chromatography/surface-activated chemical ionization tandem mass spectrometry. Rapid Communications in Mass Spectrometry, 21, 3737–3742. Freitas-Silva, O., & Venâncio, A. (2011). Brazil nuts: Benefits and risks associated with contamination by fungi and mycotoxins. Food Research International, 44(5), 1434–1440. Gupta, R. C. (2007). Veterinary toxicology, basic and clinical principles. Oxford, United Kingdom: Elsevier, Academic Press. Hernandez, M. A., Valme, G. M., Duran, E., Guillen, D., & Barroso, C. G. (2006). Validation of two analytical methods for the determination of ochratoxin A by reversed-phased high-performance liquid chromatography coupled to fluorescence detection in musts and sweet wines from Andalusia. Analytica Chimica Acta, 566, 117–121. Hussein, H. S., & Brasel, J. M. (2001). Toxicity, metabolism, and impact of mycotoxins on humans and animals. Toxicology, 167, 101. IARC (International Agency for Research on Cancer) (1993). IARC monographs on the evaluation of the carcinogenic risks to humans. Some naturally occurring substances: Food items and constituents, heterocyclic aromatic amines and mycotoxins, Vol. 56, Lyon, France: International Agency for Research on Cancer. Jorgensen, K. (1998). Survey of pork, poultry, coffee, beer and pulses for ochratoxin A. Food Additives and Contaminants, 15, 550–554. Kabak, B. (2009). Ochratoxin A in cereal-derived products in Turkey: Occurrence and exposure assessment. Food and Chemical Toxicology, 47, 348–352. Keegan, J., Whelan, M., Danaher, M., Crooks, S., Sayers, R., & Anastasio, A. (2009). Benzimidazole carbamate residues in milk: Detection by surface plasmon resonancebiosensor, using a modified QuEChERS (quick, easy, cheap, effective, rugged and safe) method for extraction. Analytica Chimica Acta, 654, 111–119. Khayoon, W. S., Saad, B., Lee, T. P., & Salleh, B. (2012). High performance liquid chromatographic determination of aflatoxins in chili, peanut and rice using silica based monolithic column. Food Chemistry, 133, 489–496. Lau, B. P. -Y., Scott, P. M., Lewis, D. A., & Kanhere, S. R. (2000). Quantitative determination of ochratoxin A by liquid chromatography/electrospray tandem mass spectrometry. Journal of Mass Spectrometry, 35, 23–32. Lindenmeier, M., Schieberle, P., & Rychlik, M. (2011). Determination of ochratoxin A in food: Comparison of a stable isotope dilution assay, liquid chromatographyfluorescence detection and an enzyme-linked immunosorbent assay. Anaytical and Bioanalytical Chemistry, 27, 115–121. Maier, N. M., Buttinger, G., Welhartizki, S., Gavioli, E., & Lindner, W. (2004). Molecularly imprinted polymer-assisted sample clean-up of ochratoxin A from red wine: Merits and limitations. Journal of Chromatography B, 804, 103–111. Mastovska, K., & Lehotay, S. J. (2006). Rapid sample preparation method for LC–MS/MS or GC–MS analysis of acrylamide in various food matrices. Journal of Agricultural and Food Chemistry, 54, 7001–7008. Mikulíková, R., Beláková, S., Benešová, K., & Svoboda, Z. (2012). Study of ochratoxin A content in South Moravian and foreign wines by the UPLC method with fluorescence detection. Food Chemistry, 133, 55–59.
301
Milicevic, D. R., Juric, V. B., Stefanovic, S. M., Veskovic-Moracanin, S. M., & Jankovic, S. D. (2009). Evaluation and validation of two different chromatographic methods (HPLC and LC–MS/MS) for the determination and confirmation of ochratoxin A in pig tissues. Journal of Environmental Science and Health. Part. B, 44, 781–787. Orduña, R. M. (2010). Climate change associated effects on grape and wine quality and production. Food Research International, 43(7), 1844–1855. Paíga, P., Morais, S., Oliva-Teles, T., Correia, M., Delerue-Matos, C., Duarte, S. C., et al. (2012). Extraction of ochratoxin A in bread samples by the QuEChERS methodology. Food Chemistry, 135, 2522–2528. Paterson, R. R. M., & Lima, N. (2011). Further mycotoxin effects from climate change. Food Research International, 44(9), 2555–2566. Pena, A., Cerejo, F., Silva, L. J. G., & Lino, C. M. (2010). Ochratoxin A survey in Portuguese wine by LC–FD with direct injection. Talanta, 82(4), 1556–1561. Pfohl-Leszkowicz, A., & Manderville, R. A. (2007). Ochratoxin A: An overview on toxicity and carcinogenicity in animals and humans. Review. Molecular Nutrition & Food Research, 51, 61–69. Ramalhosa, M. J., Paíga, P., Morais, S., Delerue-Matos, C., & Oliveira, M. B. (2009). Analysis of polycyclic aromatic hydrocarbons in fish: Evaluation of a quick, easy, cheap, effective, rugged, and safe extraction method. Journal of Separation Science, 32, 3529–3538. Richard, J. L., Plattner, R. D., May, J., & Liska, S. L. (1999). The occurrence of ochratoxin A in dust collected from a problem household. Mycopathologia, 146, 99–103. Rodríguez-Carrasco, Y., Font, G., Mañes, J., & Berrada, H. (2012). Determination of mycotoxins in bee pollen by gas chromatography-tandem mass spectrometry. Journal of Agricultural and Food Chemistry, 61(8), 1999–2005. Russell, R., Paterson, M., & Lima, N. (2010). How will climate change affect mycotoxins in food? Food Research International, 43(7), 1902–1914. Silva, C. L., Nathaly Haesen, N., & Câmara, J. S. (2012). A new and improved strategy combining a dispersive-solid phase extraction-based multiclass method with ultra high pressure liquid chromatography for analysis of low molecular weight polyphenols in vegetables. Journal of Chromatography. A, 1260, 154–163. Silva, R., Santos, J., & Camões, M. F. (2006). A new terminology for the approaches to the quantification of the measurement uncertainty. Accreditation and Quality Assurance, 10, 664–671. Soriano, J. M., & Dragacci, S. (2004). Occurrence of fumonisins in foods. Food Research International, 37(10), 985–1000. Stubbings, G., & Bigwood, T. (2009). The development and validation of a multiclass liquid chromatography tandem mass spectrometry (LC–MS/MS) procedure for the determination of veterinary drug residues in animal tissue using a QuEChERS (quick, easy, cheap, effective, rugged and safe) approach. Analytica Chimica Acta, 637, 68–78. Tirado, M. C., Clarke, R., Jaykus, L. A., McQuatters-Gollop, A., & Frank, J. M. (2010). Climate change and food safety: A review. Food Research International, 43(7), 1745–1765. Turner, N. W., Subrahmanyam, S., & Piletsky, S. A. (2009). Analytical methods for determination of mycotoxins: A review. Analytica Chimica Acta, 632, 168–180. Vaclavik, L., Zachariasova, M., Hrbek, V., & Hajslova, J. (2010). Analysis of multiple mycotoxins in cereals under ambient conditions using direct analysis in real time (DART) ionization coupled to high resolution mass spectrometry. Talanta, 82, 1950. Vatinno, R., Vuckovic, D., Zambonin, C. G., & Pawliszyn, J. (2008). Automated high-throughput method using solid-phase microextraction–liquid chromatography–tandem mass spectrometry for the determination of ochratoxin A in human urine. Journal of Chromatography. A, 1201, 215–221. Visconti, A., Pascale, M., & Centonze, G. (1999). Determination of ochratoxin A in wine by means of immunoaffinity column clean-up and high performance liquid chromatography. Journal of Chromatography A, 864, 89–101. Wilkowska, A., & Biziuk, M. (2011). Determination of pesticide residues in food matrices using the QuEChERS methodology. Review. Food Chemistry, 125, 803–812. Young, J. C., & Games, D. E. (1992). Supercritical fluid chromatography of Fusarium mycotoxins. Journal of Chromatography. A, 627(1–2), 247–254. Yu, J. C. C., & Lai, E. P. C. (2010). Molecularly imprinted polymers for ochratoxin A extraction and analysis. Toxins, 2(6), 1536–1553. Zachariasova, M., Lacina, O., Malachova, A., Kostelanska, M., Poustka, J., Godula, M., et al. (2010). Novel approaches in analysis of Fusarium mycotoxins in cereals employing ultra performance liquid chromatography coupled with high resolution mass spectrometry. Analytica Chimica Acta, 662, 51. Zheng, M. Z., Richard, J. L., & Binder, J. (2006). A review of rapid methods for the analysis of mycotoxins. Mycopathologia, 161, 261–273. Zöllner, P., & Mayer-Helm, B. (2006). Trace mycotoxin analysis in complex biological and food matrices by liquid chromatography–atmospheric pressure ionization mass spectrometry. Journal of Chromatography. A, 1136(2), 123–169.