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Determination of multi-class pesticide residue in dietary supplements from grape seed extracts by ultrahigh-performance liquid chromatography coupled to triple quadrupole mass spectrometry a

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Antonio José Nieto-García , Roberto Romero-González & Antonia Garrido Frenich a

Research Group ‘Analytical Chemistry of Contaminants’, Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL), University of Almería, Agrifood Campus of International Excellence, Almería, Spain Accepted author version posted online: 19 Jun 2014.Published online: 14 Jul 2014.

To cite this article: Antonio José Nieto-García, Roberto Romero-González & Antonia Garrido Frenich (2014) Determination of multi-class pesticide residue in dietary supplements from grape seed extracts by ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry, Food Additives & Contaminants: Part A, 31:9, 1550-1561, DOI: 10.1080/19440049.2014.935489 To link to this article: http://dx.doi.org/10.1080/19440049.2014.935489

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Food Additives & Contaminants: Part A, 2014 Vol. 31, No. 9, 1550–1561, http://dx.doi.org/10.1080/19440049.2014.935489

Determination of multi-class pesticide residue in dietary supplements from grape seed extracts by ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry Antonio José Nieto-García, Roberto Romero-González and Antonia Garrido Frenich* Research Group ‘Analytical Chemistry of Contaminants’, Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL), University of Almería, Agrifood Campus of International Excellence, Almería, Spain

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(Received 28 March 2014; accepted 11 June 2014) A new method was developed and validated for the determination of multi-class pesticide residues in nutraceutical products obtained from grape seed extracts. The extraction procedure was based on QuEChERS methodology using ethyl acetate as solvent and a dispersive solid-phase extraction (dSPE) clean-up stage with C18 was included to minimise matrix effects. Pesticides determination was achieved using ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS); total running time was 11 min. Pesticides were quantified using matrixmatched calibration. The developed method was validated in terms of matrix effect, linearity, selectivity, limits of detection and quantification, trueness, repeatability and inter-day precision at three concentration levels (10, 50, 100 µg kg−1). Suitable recovery values were obtained for 76% of analysed pesticides at the lowest concentration (10 µg kg−1). For most of the compounds, relative standard deviation values were lower than 20% and 25% for intra- and inter-day precision, respectively. Finally, 106 pesticides were determined, and the method was applied to seven dietary supplements from grape seed extract, obtaining various positive results for piperonyl butoxide, cyromazine and diniconazole at concentrations ranging from 2.0 to 13.4 µg kg−1. Keywords: dietary supplements; grape seed extract; pesticides; liquid chromatography; mass spectrometry

Introduction The consumption of dietary supplements has considerably increased in the last few years (Bagchi et al. 2004; UBICConsulting 2014), especially those from plants, because in addition to antioxidant, anti-ageing and antibacterial properties (Jayaprakasha et al. 2003) they are reasonably priced for most consumers. Those dietary supplements are called nutraceutical products (Zeisel 1999) and they contain high concentrations of bioactive compounds from a food, presented in a non-food matrix and used to improve human health in doses exceeding those that could be obtained consuming typical food. These products are supposed to provide health benefits and they can be used to prevent and treat several diseases (NW 2014). Research with grape extracts rich in anthocyanins and oligomeric procyanidins (OPC) has shown that these extracts can decrease capillary fragility and permeability (Cuevas Montilla et al. 2011), have anti-inflammatory effects and protect blood vessels from damage caused by high sugar levels in diabetes (Harborne & Williams 2001). Previous studies have shown that grape seed extracts are also an important source of bioactive substances with antioxidant power and free radical scavenger (Bagchi et al. 2000; Jacob et al. 2008). These include anthocyanins

*Corresponding author. Email: [email protected] © 2014 Taylor & Francis

and OPC, tannins and resveratrol. The last compound also has anticancer properties that have been confirmed in studies with mouse (Jang et al. 1997), and it provides protection against atherosclerosis and cardiovascular disease (MC 2014; SFG 2014). Grape seed extract tablets are made from ultraconcentrated juice and dehydrated skin and seed grapes, which implies a higher concentration of active ingredients beneficial to human health. Furthermore, they are free of alcohol and contain high indexes of glycaemic and insulinaemic (Anderson & Waters 2013). However, this concentration step can also lead to a higher concentration of pesticides and other toxic substances, which may have been used during grape cultivation and post-harvest of the raw material (Cabras & Angioni 2000), and LC- and GC-amenable pesticides could be concentrated in the final product (Rose et al. 2009) depending on the manufacturing process. In the United States, the Dietary Supplement Health and Education Act (DSHEA) grants the USFDA the authority to regulate dietary supplements in two important aspects: product labelling and ‘good manufacturing practices’, setting industry standards for maintaining product quality (ANH 2014). On the other side, in the European Union, legislation covers food supplements (European

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Food Additives & Contaminants: Part A Commission 2002) and herbal medicinal products (European Commission 2004), but there is no formal legislation regulating nutraceuticals. For table grapes, European legislation (European Commission 2005) establishes MRLs for pesticide residues ranging from 0.01 to 5 mg kg−1 (EUPD 2014). Despite there not being MRLs set for nutraceutical products obtained from table grapes or derivates, some of the companies in their information booklets mention that quality controls have been carried out, including pesticide residue analysis, as indicated by the Royal Spanish Pharmacopoeia (AEMPS 2014). There are many articles related to the determination of pesticide residues in fresh grapes (Banerjee et al. 2007; Afify et al. 2010; Banerjee et al. 2013) as well as in seeds and skin extracts (Teixeira et al. 2004; Corrales et al. 2010). However there are no relevant studies regarding the presence of pesticide residues in nutraceutical products derived from grapes, which can be considered a more complex and difficult matrix. Nowadays, the reference extraction technique for the determination of pesticides in vegetable matrices as grape is QuEChERS (Lehotay et al. 2007), although other methods as solid liquid extraction using ethyl acetate as the extraction solvent (Afify et al. 2010; Savant et al. 2010) or supercritical fluid extraction (Ghafoor et al. 2012) can also be used. For the analysis of pesticides in fruit and vegetables, LC-MS/MS using a triple quadrupole (QqQ) analyser is probably the most suitable technique due to quantification and identification levels at low concentrations because of high sensitivity as well as short analysis time which can be achieved (Romero-González et al. 2008). However, there are only a few papers (MartínezDomínguez et al. 2014) that deal with the analysis of nutraceuticals by LC or GC (Hayward et al. 2013) assessing the occurrence of mycotoxins in dietary complements from green coffee bean (Vaclavik et al. 2013) or the presence of pesticides in nutraceuticals derived from dried botanical products (saw palmetto, ginkgo biloba or ginseng) (Chen et al. 2012). In the case of grape seed, other analysers such as time of flight (TOF) (Banerjee et al. 2008) have been used, providing acceptable LODs and LOQs, but including fewer pesticides, and they have not been used for the analysis of dietary supplements derived from grape. Due to non-existent studies related to the determination of pesticide residues in nutraceuticals from grape seed, the purpose of this study was the development of a multi-residue analytical method for the determination of pesticide residues in these products using a variation of QuEChERS extraction with ethyl acetate as solvent and performing the analyses by ultra highperformance liquid chromatography (UHPLC) coupled to MS/MS.

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Materials and methods Chemicals and reagents Acetonitrile, methanol, glacial acetic acid, acetone and isopropanol were obtained from J.T. Baker (Deventer, the Netherlands). Primary-secondary amine (PSA) and C18 were acquired from Scharlab (Barcelona, Spain) and Agilent Technologies (Santa Clara, CA, USA), respectively. Formic acid, magnesium sulphate and sodium acetate were obtained from Sigma-Aldrich (Madrid, Spain). All solvents used were HPLC quality. Ultrapure water employed to prepare all aqueous solutions and the mobile phase was obtained by a gradient system Milli-Q water (Millipore, Bedford, MA, USA). A Reax-2 rotary agitator from Heidolph (Schwabach, Germany), a centrifuge Centronic BL-II from J.P. Selecta (Barcelona, Spain) and a vacuum pump from Vacuubrand (Wertheim, Germany) were also utilised. Nylon hydrophilic filters, 0.2 µm pore size, were obtained from Agilent Technologies. Pesticide analytical standards were provided by Dr. Ehrenstorfer GmbH (Augsburg, Germany), with purity higher than 99%. Individual stock standard solutions for each pesticide were prepared by accurately weighing liquid or solid in methanol or acetone (with concentrations between 190 and 900 mg kg−1). An intermediate working standard mixture in methanol containing 2 mg kg−1 of each pesticide was prepared, and was stored under refrigeration at T ≤ 4ºC.

UHPLC-MS/MS analysis The analysis of pesticide residues was performed with LC-MS/MS equipment from Agilent Technologies. This apparatus consists of a high-performance autosampler (G4226A), a binary pump (G4220A), a column compartment thermostat (G1316C) and an autosampler thermostat (G1330B), all coupled to an Agilent triple quadrupole mass spectrometer (6460A) with a Jet Stream ESI ion source (G1958-65138). The LC separation was performed by injecting 5 µl through the autosampler on a Hypersil GOLD aQ (100 mm × 2.1 mm, 1.9 μm particle size) from Thermo Scientific (Waltham, MA, USA) maintained at 30ºC with a flow rate of 0.35 ml min−1. The mobile phase was composed of acetonitrile as the organic phase and an aqueous solution of formic acid (0.01%). The following gradient elution profile was used: the initial conditions (90% aqueous phase) were maintained for 2.5 min and then the organic eluent was increased to 50% in 2.5 min. After that it was linearly increased to 100% during 4.5 min. This composition was kept constant during 2.5 min, before being returned to the initial conditions after 0.5 min, keeping this composition during 1.5 min prior to the next analysis, obtaining a total run

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time of 14 min. Data were collected by dynamic MRM with two mass transitions for each pesticide, selecting the most sensitive for quantification purposes and the second one for confirmation. Ion source parameters were: drying gas temperature at 325ºC and sheath gas temperature at 400°C; drying gas flow at 9 l min−1 and sheath gas flow at 12 l min−1; nebuliser pressure at 25 psi; and capillary voltage was set at 3000 V in positive ion mode.

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Sample extraction Grape seed tablets or capsules were homogenised with a grinder and 2 g were weighed in a 50 ml centrifuge tube. Then, 8 ml of water were added and sample hydrated for 15 min. Then the extraction was carried out by adding 10 ml of ethyl acetate and shaking for 60 min in an overhead shaker. Then 4 g of magnesium sulphate and 1 g of sodium acetate were added and shaken immediately for 1 min in vortex. The sample was centrifuged at 5000 rpm (4136g) for 5 min. Then 1.2 ml of the supernatant were taken to carry out a clean-up step using 50 mg of C18 as sorbent material. This mixture was shaken for 1 min and then centrifuged for 5 min at 5000 rpm (4136g). Finally the extract was filtered through nylon hydrophilic filters with a 0.2 µm pore size for the removal of fine particles and 1 ml was transferred to a vial for UHPLC analysis. Validation parameters Validation parameters were established according to the criteria established in the European SANCO Guideline 2013 (SANCO/12571/2013). The linearity of the method was determined using matrix-matched standard calibration by analysing spiked blank samples of grape seed extracts at five concentration levels (2–50 µg l−1) for all pesticides. Trueness was determined at three concentration levels (10, 50 and 100 µg kg−1) by spiking blank samples. Five replicates were performed for each level. Repeatability was studied at the same concentration levels performing five replicates for each level. Intermediate precision was evaluated by analysing spiked samples at 10, 50 and 100 µg kg−1 in five different days (one replicate per day). LOD and LOQ were calculated analysing blank samples spiked at 0.5, 1, 2, 5 and 10 µg kg−1, and determined as the lowest concentration of the selected compounds that produce chromatographic peak at signal-to-noise ratio (S/N) of 3 and 10 respectively. Nutraceuticals derived from grape seed extract used as spiking blank samples were previously analysed, and no significant signal was obtained for target pesticides.

Results and discussion Initially, 127 LC amenable pesticides, most of them included in the European Union multi-annual control plan (European Commission 2012), were included in this study, and chromatographic and extraction conditions were optimised.

UHPLC–MS/MS optimisation A standard mixture solution was used to develop a method for the evaluation of pesticide residues in nutraceutical products from grape seed extract by UHPLC-MS/MS. For each pesticide the most abundant ion was selected as the precursor ion, setting the minimum fragmentor voltage which provides a constant signal and higher intensity. Next, collision energies were optimised in order to obtain the most sensitive and selective product ions. Thus, for each precursor ion two product ions were selected, using the most sensitive for quantification purposes and the second one for confirmation. Moreover, ion ratios between both product ions were also established. Confirmation was considered unequivocal if the ratio was within the criteria established in SANCO Guideline (SANCO/12571/2013), which were based on relative abundance criteria that are dependent on the relative intensities of the two transitions. Table 1 shows the obtained ion ratios as well as other chromatographic and MS/MS parameters. Dynamic MRM mode was used and cycle time was fixed at 550 ms and dwell time was optimised automatically in a range of 4.2–274.0 ms for the 254 MRM transitions. Using these conditions, enough points per peak were obtained to obtain well-defined peaks and repetitive signals for quantification purposes.

Optimisation of the extraction procedure Several variables were evaluated during the optimisation of the extraction procedure. Bearing in mind that in the last few years the QuEChERS extraction procedure provided suitable results during the extraction of pesticide residues from several matrices, it was selected as a starting point. First the solvent extract was evaluated by studying the recovery at two concentration levels: 10 and 50 µg kg−1 (three replicates of each). In this case, an extraction time of 60 min was used and no clean-up was employed. Two solvents – acetonitrile, which was usually used in the QuEChERS procedure, and ethyl acetate – were studied. It was observed that 51 and 60 compounds, with recoveries between 70% and 120% at 10 and 50 µg kg−1 respectively, were extracted when ethyl acetate was used as an extraction solvent. However, when acetonitrile was checked, only 15 and 64 compounds were extracted at 10 and 50 µg kg−1 respectively. Bearing in mind that the

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Table 1. UHPLC-MS/MS parameters for the analysed pesticides.

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Compound 2,6-Dichlorobenzamide 8-Quinoline Acetamiprid Aldicarb Aldicarb sulfone Aldicarb sulfoxide Azaconazole Azadirachtin Bendiocarb Bioallethrin Bitertanol Butocarboxim Butocarboxim sulfoxide Butoxycarboxim Carbaryl Carbendazim Carbofuran Carbofuran 3-hydroxy Chlorantraniliprole Chloridazon Clofentizine Clothianidin Coumaphos Cyprodinil Cyromazine Demeton-S-methyl Desmetryn Dichlofluanid Diclobutrazol Dicrotophos Diethofencarb Diflubenzuron Diniconazole Diphenylamine Disulfoton sulfone Disulfoton sulfoxide Diuron Dodine Epoxiconazole Ethiofencarb sulfone Ethiofencarb sulfoxide Ethoxyquin Etofenprox Etoxazole Fenazaquin Fenbuconazole Fenhexamid Fenpropidin Fenpropimorph Fenpyroximate Fensulfothion Flonicamid Flubendiamide Flufenoxuron Fluquinconazole Flusilazole Flutolanil Flutriafol Forchlorfenuron

Retention time window (min)

Fragmentor (V)

Precursor ion (m/z)

2.14–2.22 1.61–1.67 2.73–2.77 2.93–2.95 1.55–2.84 1.37–1.40 3.97–3.99 3.57–3.60 3.53–3.56 6.05–6.11 4.89–4.92 2.93–2.95 1.36–1.40 3.54–3.57 3.70–3.74 3.79–3.82 3.54–3.57 2.44–2.48 4.09–4.12 2.36–2.44 5.54–5.57 1.84–1.90 5.45–5.48 2.56–2.76 1.23–1.30 3.35–3.40 3.41–3.51 4.63–4.67 4.77–4.80 2.23–2.41 4.33–4.37 4.79–4.82 5.12–5.14 4.94–4.96 4.19–4.21 3.69–3.72 3.91–3.94 2.88–3.95 4.63–4.67 2.43–2.46 1.77–1.78 4.53–4.66 2.65–2.92 6.43–6.44 7.01–7.05 4.82–4.84 4.56–4.59 5.29–5.60 2.61–2.70 6.47–6.50 3.97–3.99 4.41–4.44 5.06–5.10 6.16–6.19 4.65–4.68 4.83–4.86 4.82–4.85 3.70–3.72 3.76–3.78

90 130 90 90 50 50 90 210 50 90 50 90 90 50 50 90 90 70 90 130 90 50 130 130 130 80 90 50 90 50 50 90 130 120 90 50 120 170 150 50 50 130 90 130 90 130 90 130 130 130 90 130 205 90 90 130 90 90 90

190 146 223 213 223 207 300 743 224 303 338 213 229 223 202 192 222 238 484 222 303 250 363 226 167 253 214 333 328 238 268 311 326 170 307 291 233 228 330 258 242 218 394 360 307 337 302 274 304 422 309 230 705 489 376 316 324 302 248

Product ions (collision energy, eV)a 173 (16);145 (32) 128 (24); 118 (20) 126 (16); 56 (12) 156 (4); 75 (8) 148 (5); 86 (8) 132 (5); 89 (4) 123 (60); 89 (80) 725 (30); 625 (45) 167 (5); 109 (12) 162 (32); 161 (28) 99 (8); 70 (4) 116 (4); 75 (12) 166 (4); 92 (8) 166 (5); 106 (4) 145 (4); 127 (24) 160 (16); 132 (32) 165 (4); 123 (20) 181 (5); 163 (10) 453 (12); 286 (4) 77 (36); 65 (40) 138 (8); 102 (36) 169 (8); 132 (8) 307 (12); 227 (20) 227 (4), 93 (36) 85 (16); 68 (40) 89 (10); 61 (35) 172 (12); 82 (32) 224 (4); 123 (24) 159 (40); 70 (20) 112 (4); 72 (20) 226 (4); 124 (32) 158 (8); 141 (36) 159 (24); 70 (32) 93 (30); 65 (30) 153 (4); 97 (28) 213 (4); 185 (8) 160 (20); 72 (20) 60 (20); 57 (24) 141 (10); 121 (15) 201 (5); 107 (8) 185 (5); 107 (12) 174 (28); 160 (36) 359.2 (4); 177 (8) 141 (28); 113 (64) 161 (12); 57 (24) 125 (28); 70 (16) 97 (20); 55 (44) 147 (28); 117 (60) 147 (28); 117 (64) 366 (8); 138 (28) 173 (20); 140 (40) 203 (12); 174 (16) 531 (45); 174 (35) 158 (16); 141 (52) 349 (25); 307 (20) 247 (12); 165 (24) 262 (12); 242 (20) 123 (24); 70 (12) 129 (12); 93 (36)

Ion ratio (%) 30 21 60 84 83 50 40 9 74 90 70 15 27 6 41 18 65 99 93 65 67 35 55 30 81 91 35 78 9 80 35 42 6 39 54 76 7 71 14 85 74 88 20 34 56 70 92 36 1 10 63 20 54 45 73 91 82 26 40 (continued )

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Table 1. Continued .

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Compound

Retention time window (min)

Fragmentor (V)

Precursor ion (m/z)

1.48–2.96 5.13–5.16 6.22–6.24 5.65–5.78 4.00–4.04 4.42–4.45 4.45–4.47 6.00–6.01 5.04–5.07 4.87–4.91 5.93–5.96 2.86–2.89 1.77–1.78 4.32–4.36 3.44–3.51 4.73–4.76 1.63–1.86 2.56–2.69 3.79–3.82 1.68–1.69 1.67–1.68 4.26–4.29 5.53–5.56 2.89–2.99 5.90–5.95 4.47–4.50 1.57–1.62 1.23–1.31 5.42–5.47 1.61–1.67 6.31–6.33 3.31–3.35 6.64–6.66 5.74–5.87 5.03–5.09 5.85–5.88 4.41–4.44 2.13–2.22 3.80–3.92 3.47–3.50 2.20–2.26 3.73–3.76 3.37–3.40 5.70–5.75 4.89–4.91 2.29–2.34 5.13–5.16 5.66–5.72 3.00–3.36 2.31–2.35

90 90 90 130 90 90 90 138 90 130 130 70 90 50 70 90 50 90 90 90 50 90 130 90 90 50 90 90 90 60 170 130 115 100 90 130 90 130 90 170 90 90 90 50 90 85 90 90 90 50

222 252 353 297 256 321 249 511 330 224 507 275 242 226 163 369 224 271 282 242 247 294 329 300 356 208 189 218 388 146 308 202 273 298 353 334 230 202 253 377 257 241 343 296 314 257 253 346 359 288

Formetanate Furmecyclox Hexythiazox Imazalil Imidacloprid Iprovalicarb Linuron Lufenuron Mecarbam Mepanipyrim Metaflumizone Methiocarb sulfone Methiocarb sulfoxide Methiocarb Methomyl Methoxyfenozide Monocrotophos Nitempyram Ofurace Oxamyl Oxydemeton-methyl Paclobutrazol Pencycuron Phosphamidon Piperonylbutoxide Promecarb Propamocarb Pymetrozine Pyraclostrobin Quinosol Quinoxyfen Simazine Spiromesifen Spiroxamine Tebufenozide Tebufenpyrad Terbuthylazine Thiabendazole Thiacloprid Thiodicarb Thiofanox sulfoxide Thiofanox Thiophanate-methyl Triadimenol Triazophos Trichlorfon Tricresyl phosphate Triflumizole Triflumuron Vamidothion

Product ions (collision energy, eV)a 165 (8); 65 (52) 170 (8); 110 (20) 228 (8); 168 (20) 159 (16); 69.2 (12) 209 (8); 175 (12) 203 (5); 119 (16) 182 (8); 160 (12) 158 (16); 141 (45) 227 (5); 125 (20) 106 (24); 77 (40) 287 (20); 178 (20) 201 (10); 122 (20) 185 (4); 122 (28) 169 (4); 121 (12) 106 (5); 88 (5) 313 (5); 149 (8) 193 (5); 127 (8) 225 (4); 56 (36) 254 (4); 160 (20) 121 (4); 72 (16) 169 (8); 109 (24) 125 (40); 70 (16) 330 (5); 89 (68) 174 (4); 127 (16) 177 (4); 119 (36) 151 (5); 109 (12) 102 (16); 74 (24) 105 (16); 51 (68) 194 (4); 163 (24) 128 (25); 118 (20) 197 (32); 162 (52) 104 (24); 68.2 (32) 255 (10); 295 (10) 144 (16); 100 (32) 203 (4); 133 (15) 147 (28); 145 (24) 174 (8); 68 (40) 175 (24); 131 (36) 126 (16); 73 (68) 113 (8); 64 (12) 200 (5); 137 (10) 184 (4); 57 (20) 311 (4); 151 (20) 133 (8); 77 (80) 162 (12); 119 (36) 221 (5); 109 (10) 171 (8); 110 (16) 278 (4); 73 (8) 156 (8); 139 (32) 146 (4); 58 (40)

Ion ratio (%) 3 44 83 65 91 47 89 61 12 72 69 62 44 67 76 77 85 70 90 14 55 8 15 91 24 78 44 25 95 17 89 72 88 55 24 90 13 61 16 10 55 26 22 45 21 31 46 36 65 60

Note: aQuantifier ions are shown in bold.

number of extracted compounds at low concentrations was higher when ethyl acetate was used, at 50 µg kg−1 the number of extracted compounds is similar, and ethyl acetate was used for further experiments.

Then the effect of the extraction time on the recovery of the target compounds was tested using different extraction times (0, 30, 60 and 120 min). Recovery was calculated using matrix-matched standard calibration and

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Food Additives & Contaminants: Part A

Figure 1.

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Influence of (a) extraction time and (b) clean-up sorbent in the recovery of pesticides. Spiked samples are at 50 µg kg−1.

spiking blank samples at 50 µg kg−1 for all pesticides. Three replicates were used at each extraction time. Figure 1a shows the number of compounds with appropriate recovery (70 < R < 120%) and with recovery values close to 70% (60–70%), when different extraction times were tested. It can be observed that the number of pesticides with suitable recovery increased with extraction time up to 1 h, when 51 pesticides with recoveries between 70% and 120%, and 13 pesticides were extracted with recoveries ranging from 60% to 70%. Moreover, some compounds showed low recoveries at short extraction times, such as carbamates (aldicarb, aldicarb sulfone, aldicarb sulfoxide, ethifencarb sulfone, ethiofencarb sulfoxide, oxamyl, methomyl or thyodicarb) and some organophosphorus pesticides such as monocrotophos, oxydemeton-methyl or trichlorfon. However, note that the number of extracted compounds decreased when a longer extraction time was used. Therefore, 1 h was selected as the optimum extraction time.

Bearing in mind the high amount of co-extractive substances, the effectiveness of a clean-up step was evaluated by using different sorbents as PSA, C18 or a mixture of both sorbents. The selection of these sorbents was performed considering that PSA has shown its effectiveness to remove organic acids, sugars and pigments present in wine and grapes (Oliver 2013), and C18 has been used as a sorbent clean-up to reduce the fat content of the extract and matrix effect (Nguyen et al. 2010). Thus the use of C18 could minimise the content of co-extractive substances by taking into account the fact that grape seed oil is rich in fatty acids, containing about 8% of saturated fat (palmitic acid and stearic acid), 15% of monounsaturated fat (oleic acid) and high levels of polyunsaturated fat, linoleic acid being the major component ranging from 67.6% to 73.2% of the fatty acids present in grape seed oil (Beveridge et al. 2005; Botanical Online 2014). In order to evaluate the effectiveness of the clean-up procedure, blank samples were spiked at 50 µg kg−1 and

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three replicates were used. In the three cases, an aliquot of supernatant (1.2 ml) was transferred into a 2 ml Eppendorf tube containing 50 mg of PSA, 50 mg C18 or 50 mg of a mixture of both sorbents. Figure 1b shows that the worst recovery values were obtained by applying PSA as the sorbent, and some compounds such as carbamates (aldicarb, bendiocarb, butocarboxim, butocarboxim sulfoxide, carbaryl or carbendazim) were not recovered when this sorbent was used. Slightly better results were observed when PSA + C18 (68 compounds with recovery between 70% and 120%) were used. Finally, using C18 as a sorbent, 93 pesticides were recovered. Moreover, the number of pesticides showing a matrix effect was reduced significantly. Thus, the matrix effect was studied by evaluating the analyte signal ratio in the matrix and solvent. If no clean-up step was used, only eight compounds did not present a matrix effect, obtaining the same results when PSA was used during the clean-up step (nine compounds did not present a matrix effect). Only 14 pesticides did not show a matrix effect when a mixture of PSA and C18 was used, and the best results were obtained when C18 was used as a sorbent in cleanup. In this case, 55 compounds without a matrix effect were achieved. Therefore, a clean-up step with C18 was used for further experiments.

Linearity was considered acceptable for all target compounds, obtaining a determination coefficient (R2) higher than 0.98. Trueness was evaluated through recovery studies. Recovery values between 70% and 120% are considered suitable. Table 2 shows the recoveries obtained at each level using the optimised method. It can be observed that 76% of pesticides showed recovery in a range between 70% and 120% at 10 µg kg−1, whereas 92% of the compounds included in this study were recovered at 50 µg kg−1 and 88% of compounds at 100 µg kg−1. Intermediate precision (inter-day precision) and repeatability (intra-day precision) were studied. RSD values were less than 25% and 20% respectively for most of the compounds (Table 2), indicating the suitability of the proposed method. Finally, Table 2 shows the obtained results for LODs and LOQs, which ranged from 0.5 to 10 µg kg−1 and from 1 to 25 µg kg−1 respectively. It is important to highlight that only 11 compounds present LOQs above 10 µg kg−1. These values are quite suitable, bearing in mind that MRLs for pesticides in table grape range from 10 to 5000 µg kg−1 (European Commission 2005). Analysis of samples

Method validation Finally, 106 pesticides, which had recoveries between 60% and 120% during the optimisation process, were considered as suitable for inclusion in the validation procedure. It is important to bear in mind that when ESI is used as an ion source, the matrix effect can affect the ionisation of the target compounds (Romero-González et al. 2011). This was studied by performing calibration curves in both the matrix (nutraceutical from grape seed extract blank) and solvent, both prepared by adding the corresponding amount of intermediate solution with the target compounds at the same concentrations (0, 2, 5, 10, 25 and 50 µg l−1). Therefore, in order to compensate for this effect, a matrix-matched standard calibration was used for quantification purposes. The slope ratios matrix/solvent for each compound were calculated, considering an acceptable signal suppression or enhancement effect if the slope ratio ranged from 0.8 to 1.2, while a value < 0.8 or > 1.2 implies a high matrix effect. It can be indicated that 54 of target pesticides did not show a matrix effect (0.8 < ME< 1.2), whereas 32 pesticides showed significant signal suppression (ME < 0.5), 15 pesticides showed a medium signal suppression (0.5 1.5).

Seven samples of nutraceuticals from grape seed extract were analysed. All samples were acquired from local stores in Almería (Spain), except three of them which were obtained in Veracruz (México). During the analysis of samples, an internal quality control was carried out using matrix-matched calibration, a standard solution of the compounds in solvent and three spiked samples at different levels (10, 50, 100 µg kg−1) in order to assure the reliability of the results. Some pesticide residues were found in three samples. Figure 2 shows a chromatogram of a positive sample for piperonyl butoxide (3.4 µg kg−1) and a chromatogram of a blank sample spiked at 2.0 µg kg−1. In both, quantification and detection ions show the same peaks and keep the ion ratio. This compound is not a plant protection product, and an MRL is not established. However, it is usually used as a synergist, upgrading the toxicity of some insecticides usually employed in grapes such as carbamates, pyrethrins and pyrethroids (Banerjee et al. 2010; Akkad & Schwack 2012). Moreover, diniconazole, fungicide usually applied in grape (Xiong et al. 2002) was also detected in one sample at 13.4 µg kg−1. It can be highlighted that the detected concentration was higher than the MRLs established by the European Union in table grapes (10 µg kg−1). Finally, cyromazine residues were found in another sample at 2 µg kg−1, which was below the MRL set by the European Union (50 µg kg−1).

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Table 2. Validation results of the developed method. Intermediate precision (%)b

Recovery (%)

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Compound 2,6-Dichlorobenzamide 8-Quinoline Acetamiprid Aldicarb Aldicarb sulfone Aldicarb sulfoxide Azaconazole Azadirachtin Bendiocarb Bioallethrin Bitertanol Butocarboxim Butocarboxim sulfoxide Butoxycarboxim Carbaryl Carbendazim Carbofuran Carbofuran 3-hydroxy Chlorantraniliprole Chloridazon Clofentizine Clothianidin Coumaphos Cyprodinil Cyromazine Demeton-S-methyl Desmetryn Dichlofluanid Diclobutrazol Dicrotrophos Diethofencarb Diflubenzuron Diniconazole Diphenylamine Disulfoton sulfone Disulfoton sulfoxide Diuron Dodine Epoxiconazole Ethiofencarb sulfone Ethiofencarb sulfoxide Ethoxyquin Etofenprox Etoxazole Fenazaquin Fenbuconazole Fenhexamid Fenpropidin Fenpropimorph Fenpyroximate Fensulfothion Flonicamid Flufenoxuron Fluquinconazole Flusilazole Flutolanil Flutriafol Forchlorfenuron

−1

10 µg kg 78 101 90 100 173 51 118 89 94 88 114 99 77 115 106 114 101 82 103 103 77 130 146 97 75 110 106 106 119 93 115 95 170 98 106 93 122 59 118 77 75 107 125 106 81 112 126 102 119 95 97 115 107 122 124 116 106 110

(19) (16) (18) (12) (14) (12) (15) (19) (6) (15) (4) (6) (9) (18) (16) (12) (13) (19) (15) (12) (8) (16) (15) (22) (8) (20) (12) (13) (16) (13) (7) (19) (6) (14) (11) (8) (8) (20) (11) (19) (18) (11) (12) (5) (7) (14) (5) (7) (15) (13) (14) (6) (14) (16) (7) (18) (11) (9)

−1

50 µg kg 81 104 83 86 83 45 101 98 83 96 107 74 59 74 90 116 79 78 81 69 93 98 112 96 62 91 80 92 108 99 96 91 110 90 73 77 83 97 97 77 71 93 100 98 84 96 88 87 104 103 78 97 84 114 106 112 90 88

(13) (6) (8) (7) (4) (10) (5) (18) (3) (13) (4) (6) (9) (15) (8) (4) (6) (11) (11) (8) (7) (12) (6) (9) (4) (17) (5) (8) (14) (5) (5) (9) (6) (9) (5) (4) (6) (16) (5) (13) (9) (4) (8) (6) (2) (7) (5) (7) (7) (3) (10) (4) (11) (10) (6) (6) (7) (5)

–1

100 µg kg 106 98 92 82 119 41 98 97 93 77 102 84 68 90 112 120 91 83 95 80 120 75 132 82 77 112 89 106 112 100 111 114 119 104 106 95 100 111 108 83 75 94 146 87 72 114 114 90 91 80 98 104 98 113 114 104 98 93

(3) (5) (9) (6) (5) (3) (4) (11) (3) (13) (5) (6) (3) (7) (3) (1) (3) (10) (9) (1) (6) (11) (6) (7) (7) (5) (3) (9) (9) (3) (2) (2) (3) (6) (3) (1) (3) (5) (5) (11) (3) (1) (9) (4) (2) (2) (2) (4) (6) (1) (2) (1) (5) (4) (3) (7) (5) (3)

−1

10 µg kg 24 20 21 16 20 18 19 25 11 26 8 20 19 25 20 14 22 22 24 20 13 22 16 23 12 17 19 19 12 21 12 24 6 19 13 14 15 25 14 19 21 11 12 24 15 13 12 16 22 20 15 11 25 23 12 24 25 10

−1

50 µg kg 19 16 13 8 14 14 7 22 5 23 5 10 10 14 8 4 6 17 22 20 6 19 14 15 10 11 11 11 10 12 10 10 5 10 5 6 12 20 9 15 15 6 9 20 4 8 6 15 19 15 9 10 21 16 11 16 17 7

−1

100 µg kg 16 4 9 6 4 3 4 9 4 20 5 6 7 11 4 3 4 11 9 6 7 17 14 9 8 5 4 11 7 9 7 4 5 7 4 5 2 19 4 12 14 2 8 5 3 5 4 5 17 3 6 6 20 5 8 8 5 5

LODc LOQd −1 (µg kg ) (µg kg−1) 10.0 0.5 5.0 1.0 10.0 1.0 0.5 2.0 0.5 10.0 2.0 0.5 0.5 2.0 0.5 0.5 1.0 2.0 2.0 10.0 2.0 10.0 1.0 2.0 2.0 10.0 0.5 10.0 0.5 1.0 0.5 5.0 1.0 2.0 1.0 0.5 2.0 5.0 1.0 5.0 1.0 1.0 10.0 2.0 0.5 1.0 0.5 1.0 2.0 0.5 1.0 0.5 1.0 10.0 0.5 0.5 0.5 0.5

25.0 1.0 10.0 2.0 25.0 2.0 1.0 5.0 1.0 25.0 5.0 1.0 1.0 5.0 1.0 1.0 2.0 5.0 5.0 25.0 5.0 25.0 2.0 5.0 5.0 25.0 1.0 25.0 1.0 2.0 1.0 10.0 2.0 5.0 2.0 1.0 5.0 10.0 2.0 10.0 2.0 2.0 25.0 5.0 1.0 2.0 1.0 2.0 5.0 1.0 2.0 1.0 2.0 25.0 1.0 1.0 1.0 1.0 (continued )

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Table 2. Continued . Intermediate precision (%)b

Recovery (%)

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Compound Formetanate Furmecyclox Hexythiazox Imazalil Imidacloprid Iprovalicarb Linuron Lufenuron Mecarbam Mepanipyrim Metaflumizone Methiocarb sulfone Methiocarb sulfoxide Methiocarb Methomyl Methoxyfenozide Monocrotophos Nitempyram Ofurace Oxamyl Oxydemeton-methyl Paclobutrazol Pencycuron Phosphamidon Piperonyl butoxide Promecarb Pymetrozine Quinosol Quinoxyfen Simazine Spiromesifen Spiroxamine Tebufenozide Tebufenpyrad Terbuthylazine Thiabendazole Thiacloprid Thiodicarb Thiofanox sulfoxide Thiofanox Thiophanate-methyl Triadimenol Triazophos Trichlorfon Tricresyl phosphate Triflumizole Triflumuron Vamidothion

−1

10 µg kg 71 130 96 71 110 114 124 108 129 123 71 118 101 108 114 114 85 64 105 93 72 104 130 91 86 119 14 102 99 88 91 87 129 104 107 74 98 117 62 115 91 99 116 99 134 187 100 77

(20) (3) (20) (18) (7) (7) (18) (16) (10) (13) (12) (18) (10) (16) (18) (12) (20) (19) (9) (20) (15) (10) (19) (17) (20) (10) (20) (12) (9) (10) (7) (8) (13) (19) (8) (14) (18) (11) (20) (4) (12) (11) (14) (8) (17) (8) (5) (16)

−1

50 µg kg 107 103 71 73 104 114 97 83 109 109 112 95 76 77 78 112 72 72 82 76 61 98 96 101 105 95 15 107 116 75 99 72 116 104 100 66 77 89 80 96 72 107 104 89 102 102 96 76

(15) (3) (10) (17) (4) (3) (14) (11) (6) (6) (7) (16) (6) (14) (18) (5) (8) (18) (5) (15) (15) (4) (14) (18) (15) (5) (16) (8) (7) (5) (5) (7) (12) (15) (7) (12) (16) (5) (10) (4) (8) (8) (5) (8) (4) (7) (4) (11)

–1

100 µg kg

100 (11) 120 (3) 97 (6) 61 (12) 105 (3) 105 (3) 104 (4) 72 (7) 116 (6) 126 (4) 88 (6) 75 (5) 107 (4) 100 (4) 91 (17) 116 (2) 70 (7) 64 (17) 100 (4) 74 (10) 68(6) 99 (1) 123 (6) 82 (11) 71 (7) 119 (3) 12 (10) 120 (6) 90 (4) 88 (4) 70 (3) 71 (3) 125 (10) 102 (10) 102 (6) 73 (12) 91 (15) 86 (5) 71 (10) 105 (4) 83 (6) 100 (5) 120 (4) 104 (2) 120 (3) 170 (4) 107 (2) 76 (10)

−1

10 µg kg 23 16 23 21 13 16 24 23 15 14 22 20 20 21 25 13 21 22 17 25 18 13 19 18 20 13 25 21 17 18 9 21 14 21 11 20 18 16 20 10 18 20 16 13 7 25 22 19

−1

50 µg kg 23 4 18 17 12 8 13 20 10 8 14 18 7 20 22 11 19 21 7 20 17 10 20 12 15 6 21 15 11 15 6 9 15 18 10 17 16 11 14 5 12 12 4 12 3 19 22 12

−1

100 µg kg 19 3 9 11 3 4 15 10 7 4 8 11 4 11 20 4 13 20 7 9 12 3 11 9 15 3 9 3 5 3 5 7 14 14 6 13 13 3 10 4 7 12 4 4 2 14 20 14

LODc LOQd −1 (µg kg ) (µg kg−1) 10.0 0.5 1.0 1.0 0.5 0.5 5.0 2.0 0.5 0.5 5.0 0.5 0.5 0.5 2.0 0.5 1.0 1.0 1.0 2.0 2.0 10.0 1.0 0.5 0.5 0.5 0.5 0.5 0.5 1.0 0.5 1.0 2.0 1.0 0.5 5.0 2.0 0.5 0.5 0.5 0.5 0.5 0.5 5.0 0.5 0.5 5.0 0.5

25.0 1.0 2.0 2.0 1.0 1.0 10.0 5.0 1.0 1.0 10.0 1.0 1.0 1.0 5.0 1.0 2.0 2.0 2.0 5.0 5.0 25.0 2.0 1.0 1.0 1.0 1.0 1.0 1.0 2.0 1.0 2.0 5.0 2.0 1.0 10.0 5.0 1.0 1.0 1.0 1.0 1.0 1.0 10.0 1.0 1.0 10.0 1.0

Notes: aRSD (%) values are given in parentheses (repeatability) (n = 5). b n = 5. c Limits of detection (LOD). d Limits of quantification (LOQ).

Conclusions A method was developed and optimised for the analysis of pesticides in dietary supplements from grape seed extract by UHPLC-MS/MS. A QuEChERS-based method

was developed using ethyl acetate as an extraction solvent. Because of the complexity of the sample, a cleanup stage using C18 was needed, reducing matrix effects. Suitable validation parameters (linearity, recovery, repeatability, intermediate precision, and LOD and LOQ) were

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Figure 2. (colour online) UHPLC-MS/MS chromatograms obtained for piperonyl butoxide in (a) a real sample (3.5 μg kg−1) and (b) a spiked blank matrix at 2 μg kg−1. Both quantification and confirmation transitions were plotted.

obtained. Because of simplicity and high sample throughput, it is a suitable method for application in routine analysis. The method was applied to seven grape seed extract tablets and three pesticides were found, showing the need to develop methods for pesticide residue analysis in these kinds of matrices, as well as the establishment of specific legislation for this type of product.

Acknowledgements This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER [grant number CTQ2012-34304]. RRG is also grateful for personal funding through the ‘University Research Plan’ (Almeria University) and Cajamar. The authors declare that they have no conflict of interest.

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Determination of multi-class pesticide residue in dietary supplements from grape seed extracts by ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry.

A new method was developed and validated for the determination of multi-class pesticide residues in nutraceutical products obtained from grape seed ex...
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