Pesticide residues in Brassica vegetables and exposure assessment of consumers

Food Control 25 (2012) 561e575

Contents lists available at SciVerse ScienceDirect

Food Control journal homepage: www.elsevier.com/locate/foodcont

Pesticide residues in Brassica vegetables and exposure assessment of consumers  ski B. qozowicka*, M. Jankowska, P. Kaczyn  skiego 22, Postal code: 15-195 Bialystok, Poland Plant Protection Institute - National Research Institute, Regional Experimental Station, Laboratory of Pesticide Residues, Chełmon

a r t i c l e i n f o

a b s t r a c t

Article history: Received 3 March 2011 Received in revised form 10 October 2011 Accepted 16 November 2011

The presence of pesticide residues in Brassica vegetables (365 samples) produced in north-eastern Poland (2006e2009) was determined and their health risks assessed. The analytical procedure was developed to examine of 130 pesticides of different chemical classes (chloroorganic, phosphoroorganic, carbamates, strobilurines, neonicotinoids, amides, pyrimidines, benzimidazoles, imidazoles and triazoles) in broccoli, Brussels sprouts, cauliflower, head and Chinese cabbage. Pesticides were extracted using matrix solid phase dispersion (MSPD) and analyzed by gas chromatography (GC) with dual detection system: electron capture (ECD) and nitrogenephosphorus (NPD). Linearity (R2
0.997) was good over the concentration range from 2.5 to 0.001 mg/kg for all the pesticides, and instrumental detection limits ranged from 0.001 to 0.01 mg/kg. Mean recoveries for vegetables spiked at three fortification levels (0.001e2.5 mg/kg) ranged from 70.07 to 118.90%. Relative standard deviations ranged from 0.15 to 8.58%, except: dicofol, pyridaben (acaricides), dichloran (fungicide), isofenphos, triasophos (insecticides) where mean recoveries were above 120% (122.2e127%) and also dichlofluanid, tecnazene (fungicides), dichlobenil (herbicide), endosulfan-sulfate, phorate, phosmet (insecticides) with mean recoveries below 70% (42.83e69.1%). The method used to monitor pesticide residues in vegetables. Fifteen different pesticides (insecticides mainly) were detected in 118 samples (32%), while multiple pesticides (more than one pesticide residue) in about 4% samples. Chlorpyrifos and cypermethrin were the most commonly detected pesticides. Chlorpyrifos was present in 27.4% items and ranged from 0.005 to 1.51 mg/kg, while cypermethrin were detected in 3.3% samples and ranged from 0.02 to 0.19 mg/kg. Thirty-three (9%) samples exceeded the maximum residue levels (MRLs). The dietary intake of residues of some pesticides can pose acute hazards. Data obtained were then used for estimating the potential health risks associated with the exposures to these pesticides. The estimated daily intakes (EDIs) ranged from 0.005% of the ADI (acceptable daily intake) for fenhexamid to 4.454% of the ADI for diazinon. Combine cumulative exposure for chlorpyrifos detected on Brassica were 0.777% of ADI. The results show that occurrence of pesticide residues in Brassica vegetables from this region could not be considered a serious public health problem. Nevertheless, an investigation into continuous monitoring and tighter regulation of pesticide residues in vegetables is recommended. Ó 2011 Elsevier Ltd. All rights reserved.

Keywords: Brassica vegetable Matrix solid phase dispersion Gas chromatography Risk assessment Acceptable daily intake Acute reference dose

1. Introduction The Brassicaceae ( ¼ Cruciferae) family consists of a wide range of vegetables that originated in Europe and China. This important plant group includes broccoli (Brassica oleracea L. var. italica), cauliflower (Brassica oleracea L. var. botrytis), cabbage (Brassica oleracea L. var. capitata), Brussels sprouts (Brassica oleracea L. var. gemmifera), oilseed rape (Brassica napus L.), kohlrabi (Brassica oleracea L. var. gangylodes), turnip (Brassica rapa pekinesis) and some specialized crops.

* Corresponding author. Fax: þ48 85 675 34 19. E-mail addresses: [email protected], (B. qozowicka).

[email protected]

0956-7135/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodcont.2011.11.017

In recent years, the area on which Brassica vegetables in Poland are planted is growing. Now some 400,000 ha of head cabbage, 5000 ha of cauliflower, 3000 ha of broccoli, 5000 ha of Chinese cabbage and 750,000 ha of rapeseed (Robak & Gidelska, 2009) are grown. During its growth process, the vegetables are damaged by many insects such as Delia brassicae, Phyllotreta spp. Ceutorhynchus spp.,Thrips tabaci, Brevicoryne brassicae, Contarinia nasturrii, Agrotinae (Altieri and Gliessman, 1983). Different pesticides (insecticides, fungicides, and herbicides) are applied to control insects and diseases of the Brassica. Organophosphate and pyrethroid pesticides are the most extensively used on the Polish market. Pesticide residues on vegetables constitute a possible risk to consumers, and have been a human health concern. If the chemical is used as recommended on the label of the product, any residues that do occur should not exceed the maximum residue levels (MRLs). Residues

562

B. Łozowicka et al. / Food Control 25 (2012) 561e575

detected in excess of the MRL rarely constitute residues of toxological concern (Winter, 1992). A good diet, which includes a high percentage of fruits and vegetables, has been shown to be an important factor in reducing the risk of diseases such as gastrointestinal and breast cancers (Verhoeven, Goldbohm, Van Poppel, Verhagen, & Van den Brandt, 1996). The consumption of Brassica vegetables may be important in cancer prevention, since they are rich in sulfur-containing glycosides called glucosinolates (Fahey, Zalcmann, & Talalay, 2001). Some of the glucosinolates are precursors for anti-cancer compounds (e.g., glucoraphanin as precursor for sulphoraphane (4-methylsulphinylbutylisothiocyanate)), whereas others are precursors for anti-nutritional or toxic compounds (e.g., progotrin as precursor for the growth retarding compound goitrin). Due to the different content of active compounds those matrices for the determination of pesticide residues are very complicated. Several analytical procedures have been developed for the determination of pesticide residues in vegetables. Development of the multiresidue method (MRM) is difficult, due to the fact that compounds are characterized by different polarity, solubility and volatility (Hajslova & Zrostlikova, 2003; Lehotay, Mastovska, & Lightfield, 2005). Based on the chemical classes of pesticides (e.g., chloroorganic, phosphoroorganic), several methods using gas chromatography (GC) with selective and sensitive detectors, such as electron capture detector (ECD) (Ismail, Ali, & Habiba, 1993), nitrogenephosphorus detector (NPD) (Fenoll, Hellin, Martinez, Miguel, & Flores, 2007) and flame photometric detector (FPD) for separation of individual compounds have been proposed. Several extraction procedures have been developed i.e., homogenization (Ishimitsu et al., 2002; Mol, van Dam, & Steijger, 2003), dispersing extraction (Ueno, Oshima, Saito, & Matsumoto, 2003, Ueno et al., 2004), solidphase microextraction (Anastassiades, Lehotay, Stajnbaher, & Schenck, 2003; Berrada, Font, & Molto, 2004), microwave-assisted extraction and supercritical fluid extraction (Kaihara, Yoshii, Tsumura, Ishimitsu, & Tonogai, 2002). Many of the published methods (Diez, Traag, Zommer, Marinero, & Atienza, 2006; Gelsomino, Petrovicowa, Tiburtini, Magnani, & Felici, 1997; Hernando, Aguera, Fernandez-Alba, Piedra, & Contreras, 2001) for pesticide determination in food commodities seem to be complicated and very time consuming, usually requiring a large volume of solvent or expensive and highly specialized equipment. This paper describes a simple and effective procedure for isolation and extraction using a modified matrix solid phase dispersion (MSPD) sample preparation method and GC-ECD/NPD for the simultaneous quantification of 130 pesticides (64 insecticides, 44 fungicides, 15 herbicides and 7 acaricides) in Brassica, below their respective MRLs. Good knowledge of pesticide concentration is necessary to properly assess human exposure. ADI (acceptable daily intake) and ARfD (acute reference dose) are measures for the chronic and acute toxicity of a pesticide. These parameters are usually based on animal studies in which the highest dose (mg/kg body weight) of the chemical is established at which no effects can be observed (the NOAEL). A safety factor of 100 is usually applied to obtain the ADI or the ARfD (in case of human studies a factor 10 is usually applied). The ADI is based on chronic or acute toxicity studies, the ARfD on acute studies only. These toxicological parameters are supposed to protect all consumer groups including infants and children (Guidelines WHO, 1997; Hamilton et al., 1997). The information concerning residue intakes are combined with databases of residues found for the purpose of the estimation of both long-term and short-term intake residue of pesticides through the diet. The estimated intake residue in the diet is then set against accepted safe levels (ADI and ARfD). In the present work a method of analysis for the simultaneous determination of 130 pesticides: chloroorganic, phosphoroorganic,

carbamates, strobilurines, neonicotinoids, amides, pyrimidines, benzimidazoles, imidazoles and triazoles was developed and validated using a matrix solid phase dispersion technique and a GC multi method with EC-, NP-detection for residue determination and confirmation. In addition, attention was given to evaluate the potential health risks associated with the exposures to detected pesticide residues in the Brassica vegetables. 2. Material and methods 2.1. Samples and reagents Pesticide-free vegetable samples were used as blank to spike for the validation process. All reagents used were analytical grade. Acetone, n-hexane, diethyl ether and toluene for pesticide residue analysis were provided by J.T. Baker (Deventer, Holland). Florisil (60e100 mesh) was supplied by J.T. Baker (Deventer, Holland) and sodium sulfate anhydrous from Fluka (Seelze-Hannover, Germany). Silica gel was obtained from Merck (Darmstadt, Germany). All sorbents were activated at 600  C. 2.2. Standards Pesticides were obtained from the Dr. Ehrenstorfer Laboratory (Germany) and are listed in Table 1. Pesticide standard stock solutions (purity for all standards > 95%) of various concentrations were prepared in acetone and stored at 4  C. Standard working solutions were prepared by dissolving appropriate amounts of stock solution with a mixture hexane/acetone (9:1). 2.3. Sample preparation A representative portion of the sample was chopped up and blended. 2.0 g of a homogenized sample was put in a mortar with 4.0 g of the solid support e florisil and was manually mixed together using a pestle, to produce a homogeneous mixture. The mixed material was transferred to the glass column (1.5 cm i.d.  40 cm length) containing a piece of glass wool, anhydrous sodium sulfate (5.0 g) and silica gel (2.5 g). The analytes were eluted using 15 mL of a mixture of hexane/acetone (8:2) and 15 mL of a mixture of diethyl ether/acetone (8:2). The extract was dried by evaporation at a temperature of about 40  C. Further purification was done by a gravity chromatography column (only in the case of broccoli samples) with 4.0 g of silica gel conditioned with 10 mL of a mixture hexane/acetone (8:2). The pesticide residues were eluted and 10 mL fractions were collected: A: hexane/ acetone (8:2); B: acetone/toluene (2:1) and C: acetone/toluene (3:1). The eluate was collected in a conical evaporating flask. The eluate was concentrated in a vacuum rotary evaporator to approximately 1 mL at 40  C (ca. 30 min). Then the eluate was diluted to 2 mL volume of a mixture of hexane/acetone (9:1). One mL of the final solution was put into a GC vessel and placed to the rack of the autosampler. 2.4. Instrumentation and chromatographic conditions GC analysis was performed with an Agilent (Waldbronn, Germany) model 7890 A gas chromatograph equipped with ECD and NPD with a non-polar column HP-5 ((5%-Phenyl)-methylpolysiloxane; 30 m  0.32 mm and film thickness 0.50 mm) and Chemstation chromatography manager data acquisition and processing system (HewlettePackard, version A.10.2). For confirmation of residues a mid-polarity column: HP-35 ((35%Phenyl)-methylpolysiloxane; 30 m  0.32 mm and film thickness 0.50 mm) was used. The operating conditions were as follows: for

B. Łozowicka et al. / Food Control 25 (2012) 561e575

563

Table 1 Parameters of validation MRM for 130 pesticides. Pesticide group

Pesticide

R2

1st fort. level (mg/kg)

Mean recovery  RSD (%)

A

Acrinathrin Dicofol Ethion Fenazaquin Hexythiazox Pyridaben Tebufenpyrad Azoxystrobin Benalaxyl Bitertanol Boscalid Bromuconazole Bupirimate Captan Chlorothalonil Cyprodinil Cyproconazole Dichlofluanid Dichloran Difenoconazole Dimethomorph Diphenylamine Epoxiconazole Fenarimol Fenbuconazole Fenhexamid Fenpropimorph Fluquinconazole Fludioxonil Flusilazole Folpet Hexaconazole Imazalil Iprodione Kresoxim-methyl Metalaxyl Penconazole Pyrimethanil Procymidone Propiconazole Quinoxyfen Quintozene Tebuconazole Tecnazene tetraconazole Tolclofos-methyl Tolylfluanid Triadimefon Triadimenol Trifloxystrobin Vinclozolin Atrazine Chlorpropham Dichlobenil Lenacil Metribuzin Myclobutanyl Napropamide Nitrofen Pendimethalin Propham Prometrine Propachlor Propyzamide Simazine Trifluralin

0.99980 0.99903 0.99990 0.99919 0.99856 0.99968 0.99959 0.99970 0.99828 0.99996 0.99795 0.99987 0.99993 0.99960 0.99852 0.99978 0.99994 0.99972 0.99673 0.99995 0.99982 0.99865 0.99964 0.99995 0.99769 0.99711 1.00000 0.99998 0.99958 0.99995 0.99894 0.99922 0.99984 1.00000 0.99975 0.99839 0.99997 0.99968 0.99963 0.99995 0.99847 0.99697 0.99991 0.99958 0.99997 0.99962 0.99975 0.99975 0.99923 0.99989 0.99723 0.99990 0.99922 0.99847 0.99924 0.99906 0.99975 0.99993 0.99993 0.99997 0.99966 0.99998 0.99998 0.99950 0.99995 0.99986

0.020 0.010 0.010 0.030 0.050 0.020 0.010 0.020 0.030 0.020 0.005 0.010 0.010 0.010 0.005 0.010 0.010 0.010 0.010 0.050 0.030 0.010 0.010 0.010 0.010 0.005 0.020 0.010 0.010 0.010 0.010 0.010 0.010 0.020 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.005 0.010 0.005 0.010 0.010 0.010 0.010 0.050 0.010 0.010 0.010 0.010 0.010 0.020 0.010 0.010 0.020 0.005 0.010 0.020 0.005 0.010 0.020 0.010 0.010

95.52 122.20 101.94 103.50 94.06 122.63 101.92 95.10 94.25 99.70 102.57 95.93 114.50 75.98 89.47 103.87 70.97 54.60 126.97 98.07 95.80 103.47 102.54 95.17 103.03 101.42 105.43 106.00 82.43 104.68 70.10 104.87 72.83 104.93 106.73 104.77 98.87 94.57 101.30 104.83 83.77 101.03 76.50 64.43 78.83 106.57 76.73 94.87 113.86 102.57 91.70 98.78 95.16 85.10 101.18 96.78 103.43 100.44 96.64 97.85 96.27 103.00 98.68 118.03 100.03 98.67

F

H

                                                                 

3.52 3.92 0.55 2.18 3.89 3.15 0.27 3.31 2.34 3.34 2.15 8.58 0.36 2.43 6.06 1.19 2.61 2.07 3.04 1.67 1.12 3.17 3.30 0.96 2.63 0.88 1.27 1.47 6.00 1.62 1.44 1.50 0.83 4.62 3.35 1.72 2.44 1.19 0.62 3.78 3.57 3.56 2.57 2.16 3.78 1.79 2.47 3.79 1.15 1.90 6.24 0.56 1.51 3.33 2.20 1.36 1.36 0.26 2.74 1.72 2.13 0.96 0.80 4.60 2.35 2.40

2nd fort. level (mg/kg)

Mean recovery  RSD (%)

0.200 0.100 0.100 0.300 0.500 0.200 0.100 0.200 0.300 0.200 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.500 0.300 0.100 0.100 0.100 0.100 0.100 0.200 0.100 0.100 0.100 0.100 0.100 0.100 0.200 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.050 0.100 0.050 0.100 0.100 0.100 0.100 0.500 0.100 0.100 0.100 0.100 0.100 0.200 0.100 0.100 0.200 0.050 0.100 0.200 0.050 0.100 0.200 0.100 0.100

80.03 97.70 96.43 106.93 83.73 105.27 108.79 88.83 90.63 95.67 105.10 108.00 114.57 73.70 98.70 104.83 87.53 57.10 98.80 87.13 92.37 94.57 107.37 95.17 97.27 102.95 94.79 94.00 98.10 77.40 95.30 107.10 74.07 106.07 106.42 96.23 109.60 106.50 100.23 107.93 98.10 93.07 87.53 67.43 94.70 106.63 70.77 87.80 94.83 99.87 116.30 104.17 113.33 65.57 118.90 106.83 93.73 105.33 96.53 104.70 94.00 95.43 97.17 94.31 98.37 98.44

                                                                 

2.37 5.55 4.29 3.16 1.75 2.05 0.80 3.45 5.46 2.63 2.86 2.67 2.46 3.30 1.23 2.07 2.56 1.08 1.21 5.58 6.65 2.80 3.66 0.15 1.59 2.57 3.17 4.47 2.59 2.60 2.95 1.45 2.48 3.50 3.15 1.78 2.72 2.50 0.67 2.80 1.97 1.79 2.49 3.29 2.57 2.99 3.06 15.87 2.78 4.86 5.03 4.15 5.16 3.25 5.84 3.01 0.31 4.08 2.90 3.05 0.44 2.45 0.75 1.72 0.72 1.14

3rd fort. level (mg/kg)

Mean recovery  RSD (%)

2.000 0.500 0.500 1.500 2.500 1.000 0.500 1.000 1.500 1.000 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 2.500 1.500 0.500 0.500 0.500 0.500 0.500 1.000 0.500 0.500 0.500 0.500 0.500 0.500 1.000 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.250 0.500 0.250 0.500 0.500 0.500 0.500 2.500 0.500 0.500 0.500 0.500 0.500 1.000 0.500 0.500 1.000 0.250 0.500 1.000 0.250 0.500 1.000 0.500 0.500

78.97 90.53 77.30 77.53 75.53 98.86 89.43 92.30 87.00 86.90 107.57 92.33 93.60 95.53 93.57 91.90 78.20 55.33 73.67 103.10 91.91 85.80 96.13 109.33 89.67 94.27 79.80 88.20 107.30 95.43 87.30 89.47 73.73 93.43 96.97 85.43 95.63 89.43 105.77 96.63 78.07 98.07 94.57 98.53 94.70 105.67 74.83 107.80 95.20 101.15 85.37 95.00 93.70 53.67 113.03 94.77 97.67 93.77 96.77 97.11 82.40 91.33 89.40 94.30 97.53 115.63

                                                                 

1.95 5.41 4.10 2.21 3.86 2.96 2.80 3.10 3.65 2.02 1.86 5.34 0.44 2.57 3.39 3.04 2.33 1.15 2.20 1.42 2.95 3.50 2.97 4.88 2.47 3.95 1.47 2.82 1.75 4.06 4.13 2.49 1.15 0.64 3.77 7.02 3.29 2.40 2.66 0.23 2.87 0.15 2.21 3.05 3.31 2.80 3.22 2.29 1.32 1.26 3.90 3.27 2.45 2.36 1.40 2.50 1.01 2.65 0.64 3.12 6.32 5.29 2.54 3.50 0.40 2.06

LOQ (mg/kg)

LOD (mg/kg)

0.010 0.002 0.002 0.010 0.020 0.020 0.010 0.010 0.020 0.010 0.010 0.010 0.005 0.010 0.005 0.010 0.010 0.005 0.002 0.010 0.030 0.010 0.010 0.010 0.010 0.010 0.020 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.005 0.005 0.010 0.010 0.010 0.005 0.010 0.005 0.005 0.005 0.008 0.010 0.020 0.005 0.005 0.005 0.010 0.010 0.020 0.005 0.010 0.020 0.003 0.010 0.020 0.005 0.010 0.010 0.005 0.010

0.005 0.001 0.001 0.005 0.010 0.010 0.004 0.002 0.010 0.006 0.002 0.004 0.004 0.005 0.001 0.005 0.004 0.004 0.001 0.006 0.020 0.005 0.005 0.004 0.004 0.005 0.010 0.005 0.005 0.005 0.005 0.005 0.008 0.005 0.005 0.005 0.004 0.004 0.005 0.005 0.008 0.002 0.005 0.003 0.004 0.002 0.005 0.005 0.010 0.003 0.003 0.002 0.005 0.008 0.010 0.003 0.005 0.010 0.001 0.005 0.010 0.004 0.005 0.005 0.003 0.005

(continued on next page)

B. Łozowicka et al. / Food Control 25 (2012) 561e575

564 Table 1 (continued ) Pesticide group

Pesticide

R2

1st fort. level (mg/kg)

Mean recovery  RSD (%)

I

Acetamiprid Aldrine Azinphos-ethyl Azinphos-methyl Bifenthrin Bromopropylate Buprofezin Carbaryl Carbofuran Chlorfenvinphos Chlorpyrifos Chlorpyrifos-methyl Cyfluthrin b-Cyfluthrin g-Cyhalothrin a-Cypermethrin Cypermethrin p.p0 -DDD p.p0 -DDE o.p0 -DDT p.p0 -DDT Deltamethrin Diazinon Dichlorphos Dieldrin Dimethoate a-Endosulfan b-Endosulfan Endosulfan-sulfate Endrin Esfenvalerate Ethoprophos Fenitrothion Fenpropathrin Fenvalerate Fipronil Formothion HCB a-HCH b-HCH g-HCH (lindane) Heptachlor Heptachlor-epoxide Heptenophos Indoxacarb Isofenphos Malathion Mecarbam Methoxychlor (DMDT) Methidathion Parathion-ethyl Parathion-methyl Permethrin Phorate Phosmet Phosalone Pirimiphos-methyl Pirimicarb Propoxur Pyriproxyfen Quinalphos Tetradifon Triazophos Zeta-cypermethrin

0.99740 0.99900 0.99990 0.99956 0.99783 0.99864 0.99990 0.99956 0.99858 0.99970 0.99994 0.99994 0.99952 0.99811 0.99991 0.99930 0.99969 0.99989 0.99989 0.99976 0.99726 0.99934 0.99990 0.99892 0.99984 0.99997 0.99894 0.99930 0.99992 0.99984 0.99910 0.99969 0.99995 0.99967 0.99920 0.99983 0.99840 0.99745 0.99894 0.99283 0.99940 0.99971 0.99750 0.99999 0.99953 0.99991 0.99991 0.99997 0.99807 0.99997 1.00000 1.00000 0.99794 0.99990 0.99923 0.99997 0.99998 0.99994 0.99991 1.00000 0.99995 0.99932 0.99963 0.99771

0.010 0.005 0.010 0.010 0.010 0.010 0.010 0.050 0.020 0.010 0.005 0.005 0.010 0.010 0.010 0.010 0.030 0.006 0.004 0.006 0.007 0.010 0.010 0.010 0.003 0.005 0.005 0.005 0.010 0.004 0.010 0.005 0.008 0.006 0.020 0.004 0.005 0.003 0.005 0.010 0.003 0.002 0.003 0.010 0.020 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.040 0.010 0.010 0.010 0.010 0.010 0.010 0.030 0.010 0.010 0.010 0.020

80.57 95.36 106.53 97.07 98.23 89.40 100.23 94.30 114.73 108.86 102.53 109.40 90.20 81.97 104.33 97.59 101.15 103.57 96.81 91.94 85.45 98.60 115.80 82.39 75.71 97.56 56.77 89.63 55.67 95.57 83.73 108.05 104.90 95.40 107.87 77.50 81.07 98.49 96.27 104.72 99.18 99.75 91.07 101.32 104.50 93.23 97.50 108.87 91.09 105.53 106.29 96.90 94.83 70.07 50.31 95.17 108.37 96.44 94.87 97.83 110.68 97.53 105.00 100.97

                                                               

2.41 1.02 8.10 3.76 3.71 3.59 6.88 4.60 6.25 2.35 5.54 0.17 3.77 2.90 1.35 6.46 0.67 0.84 2.69 0.38 4.49 0.72 0.20 5.97 1.34 4.12 2.50 2.15 4.48 3.10 2.10 2.52 1.97 3.26 0.72 1.73 4.51 2.44 1.65 3.15 4.63 4.21 2.66 3.43 0.92 5.42 2.13 0.50 1.75 3.30 3.93 0.87 0.40 6.86 2.57 4.01 1.35 1.89 2.05 2.48 3.74 1.12 2.59 2.48

2nd fort. level (mg/kg)

Mean recovery  RSD (%)

0.100 0.050 0.100 0.100 0.100 0.100 0.100 0.500 0.200 0.100 0.050 0.050 0.100 0.100 0.100 0.100 0.300 0.060 0.040 0.060 0.070 0.100 0.100 0.100 0.300 0.050 0.050 0.050 0.100 0.040 0.200 0.050 0.080 0.060 0.200 0.040 0.050 0.300 0.050 0.100 0.300 0.020 0.300 0.100 0.200 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.040 0.100 0.100 0.100 0.100 0.100 0.100 0.300 0.100 0.100 0.100 0.200

97.07 94.33 100.63 98.77 100.46 89.57 99.83 101.20 103.20 105.57 103.13 107.83 94.80 97.50 93.47 104.07 107.46 92.80 78.07 93.73 93.10 97.43 87.61 86.14 95.73 107.97 93.10 107.27 106.62 92.77 91.87 74.67 95.07 99.00 92.95 96.53 98.57 91.20 94.80 94.57 91.73 97.47 88.90 75.87 113.93 112.23 106.77 96.71 102.79 105.27 96.62 108.07 108.53 65.37 55.03 103.77 90.03 106.87 106.17 106.53 98.40 98.37 123.50 101.70

                                                               

1.00 2.80 2.48 4.29 2.51 3.16 3.94 1.68 0.66 2.31 4.54 3.96 1.31 0.89 4.52 0.23 3.30 2.52 0.90 3.11 3.61 1.62 2.54 3.09 1.36 1.96 6.27 1.35 0.87 2.61 4.91 5.46 2.60 4.53 2.04 3.59 3.36 3.97 3.83 4.46 5.17 1.27 3.40 1.15 0.32 4.52 2.01 1.34 1.61 3.31 5.48 0.86 2.38 4.95 3.97 4.03 2.27 2.94 3.87 0.85 2.51 1.66 2.07 1.51

3rd fort. level (mg/kg)

Mean recovery  RSD (%)

0.500 0.250 0.500 0.500 0.500 0.500 0.500 2.500 1.000 0.500 0.250 0.250 0.500 0.500 0.500 0.500 1.500 0.300 0.200 0.300 0.350 0.500 0.500 0.500 1.500 0.250 0.250 0.250 0.500 0.200 1.000 0.250 0.400 0.300 1.000 0.200 0.250 1.500 0.250 0.500 1.500 0.100 1.500 0.500 1.000 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.200 0.500 0.500 0.500 0.500 0.500 0.500 1.500 0.500 0.500 0.500 1.000

105.77 85.23 92.20 106.30 106.63 90.33 105.00 78.60 107.67 103.93 101.50 96.17 79.63 102.67 97.11 103.67 105.33 103.53 95.30 95.47 93.65 104.63 92.30 78.20 103.33 95.60 90.93 83.93 51.83 84.87 88.77 89.10 98.93 97.28 92.47 98.57 105.50 85.07 90.90 78.97 90.77 92.93 95.90 86.68 76.27 123.07 96.47 92.40 82.83 91.75 94.67 115.13 90.13 66.23 42.83 93.73 95.05 88.41 92.47 85.43 75.90 98.43 104.43 96.97

R2 e correlation coefficient; a e alpha, b e beta, g e gamma, l e lambda Bolded e detected pesticide, fort. e fortification, A e acaricides (7), F e fungicides (44), H e herbicides (15), I e Insecticides (64).

                                                               

3.45 8.76 1.05 5.14 1.36 3.15 1.04 3.15 1.68 1.53 3.86 6.52 2.48 1.96 1.74 2.90 2.78 0.64 2.86 2.22 1.92 2.42 3.12 6.46 2.80 3.47 4.15 2.16 1.16 2.23 2.44 5.04 1.62 1.52 2.65 5.37 2.79 4.67 3.38 4.61 3.59 0.59 2.19 5.09 2.91 6.70 0.58 2.15 0.58 1.09 3.56 0.61 3.20 4.00 2.47 2.20 3.06 1.67 2.50 4.06 3.65 0.76 2.17 2.32

LOQ (mg/kg)

LOD (mg/kg)

0.010 0.003 0.005 0.005 0.010 0.005 0.005 0.030 0.020 0.010 0.005 0.005 0.010 0.010 0.010 0.005 0.010 0.006 0.004 0.006 0.007 0.010 0.005 0.010 0.003 0.005 0.005 0.005 0.010 0.004 0.020 0.005 0.008 0.006 0.020 0.004 0.005 0.003 0.005 0.010 0.001 0.002 0.003 0.010 0.020 0.005 0.010 0.005 0.010 0.005 0.005 0.005 0.020 0.005 0.010 0.005 0.005 0.005 0.010 0.020 0.010 0.005 0.005 0.010

0.008 0.001 0.004 0.004 0.005 0.003 0.004 0.010 0.010 0.005 0.001 0.002 0.008 0.008 0.005 0.003 0.005 0.003 0.002 0.003 0.003 0.002 0.002 0.008 0.001 0.001 0.003 0.003 0.005 0.002 0.003 0.003 0.005 0.005 0.010 0.002 0.002 0.001 0.003 0.005 0.001 0.001 0.001 0.005 0.005 0.002 0.002 0.003 0.005 0.003 0.003 0.003 0.010 0.003 0.005 0.003 0.002 0.002 0.005 0.010 0.005 0.003 0.003 0.005

B. Łozowicka et al. / Food Control 25 (2012) 561e575

detectors e injector temperature: 210  C; carrier gas: helium at a flow-rate of 3.0 mL/min; detector temperature: 300  C (ECD and NPD); make up gas: nitrogen at a flow-rate of 57 mL/min (ECD) and 8 mL/min (NPD), hydrogen 3.0 mL/min, air 60 mL/min; for oven e initial temperature: 120  C increase to 190  C at 16  C/min, then to 230  C at 8  C/min and finally to 285  C at 18  C/min and hold 10 min (ECD and NPD). The volume of final sample extract injected at 210  C in splitless mode (purge off time 2 min) was 2 mL. Total time of analysis: 20.43 min.

565

2.5.3. LOQ and LOD The limit of quantification (LOQ) was defined as the lowest concentration of the analyte that could be quantified with acceptable precision and accuracy. The limit of detection (LOD) was defined as the lowest concentration of the analyte in a sample which could be detected but not necessarily quantified. The LOQ and LOD were evaluated as the signal-to-noise ratios (S/N) of 10:1 and 3:1 for the pesticide, respectively. 2.6. Risk assessment

2.5. Method of validation All validation procedures were performed using broccoli extracts from samples with no pesticides. In this study broccoli was selected as a representative commodity for the validation of the method in determination of pesticide residue because of difficulty of matrix with high sulfur and wax content. 2.5.1. Preparation of calibration standards Calibration curves were obtained from matrix-matching calibration solutions. The lowest concentration level in the calibration curve was established as a practical determination limit. Calibration standards were prepared by addition respective spiking solutions to a blank matrix of the broccoli, to produce a final concentration of 1st range 0.001e0.05 mg/kg, 2nd range 0.1e0.5 mg/kg and 3rd range 0.5e2.5 mg/kg. 2.5.2. Recovery studies Recovery data was obtained at three range concentrations in the matrix, each day using blank vegetable samples (broccoli) in accordance with European Commission (EC) guidelines (Document Sanco, 2007). Blank samples (2.0 g) after homogenization were spiked by addition of appropriate volumes of pesticide standard mixture in solution: hexane/acetone (9:1) and were left for 1 h (equilibration times) and then prepared according to the procedure described above. Method accuracy and precision were evaluated by performing recovery studies. The precision was expressed as the relative standard deviation (RSD). Accuracy can be measured by analyzing samples with known concentration and comparing the measured values with the true values.

For preliminary assessment of consumer’s exposure to pesticide residues in Brassica samples, the estimated daily intakes (EDIs) expressed as percentages of the ADI and ARfD were calculated according to the following equation: EDI (mg/kg body weight (b.w.)/ day) ¼ broccoli consumption (g/kg b.w./day)  residue (mg/kg). The study included 130 compounds in 365 samples of Brassica vegetables from north-eastern Poland. Results under LOD of analytical methods used for intake calculations were taken as LOD values. Values of ADI and ARfD are elaborated by Joint FAO/WHO Meeting on Pesticide Residues (JMPR) and the European Food Safety Authority (EFSA) of the European Union (EU) (EFSA, 2008a) or the Federal Institute for Risk Assessment (BfR), Germany (Grenzwerte, 2006). For the estimation of consumer residue intake (qozowicka, 2009) a new model from the Pesticides Safety Directorate (PSD, 2006) were used. 3. Results 3.1. Matrix solid phase dispersion The analytical procedure of isolation, extraction and purification of pesticide residues in Brassica vegetables by MSPD shows Fig. 1. To extract pesticides of different polarity (Table 1) from Brassica vegetables the proposed MRM has been used. Kadenczki, Arpad, and Gardi (1992) have developed MSPD technique using activated florisil at 600  C as dispersing sorbent and a mixture of dichloromethane/acetone to elution of analytes from fruits and vegetables. This method was not applied in this study but it was a basis for a number of modifications. The procedure was optimized using

Fig. 1. Steps in isolation, extraction and purification of pesticide residues in Brassica vegetables by MSPD.

B. Łozowicka et al. / Food Control 25 (2012) 561e575

566

a recovery study to investigate the effect of four variables: nature of dispersing phase (florisil activated, no activated, silica gel, alumina oxide), nature of clean up adsorbent (florisil, silica gel, activated carbon and alumina oxide), ratio matrix/sorbent, selectivity of the extraction process using solvents, their mixtures, different volumes. In conclusion, 2 g sample was blended with 4 g inorganic normal phase e activated florisil as supporting material. Among all the tested solvents, mixture of hexane/acetone (8:2) and diethyl ether/acetone (8:2) appeared to be optimal, and used only in small volume of 15 mL. The simultaneously extraction and purification step using the glass column with of anhydrous sodium sulfate (2.0 g) and an additional layer of cleaning material such as 4.0 g activated silica gel represented the best compromise for all analyte. Among the Brassica, only in the case of broccoli, additional purification step were necessary. It was due to the presence of volatile organosulphur compounds and non-volatile macromolecular compounds (e.g., waxes), which are the cause of reduction of working time capillary columns in GC (Fig. 2). 3.2. Gas chromatographic determination The final analyses were carried out by gas chromatograph with dual detection system. Table 1 summarizes the pesticides studied. All pesticides were satisfactorily separated, obtaining high

sensitivity and selectivity. The absence of co-extracted compounds was confirmed by blank sample analysis. The developed MRM provides extracts without interferences during GC. Identification of analytes was carried out by comparing retention times of peaks in a sample to retention times for standards; quantification was based on the height peak of the sample extract with the height of pesticide standard solution in the matrix (0.005 min for positive confirmation). Fig. 3 shows representative chromatograms of selected standard mixtures of forty pesticides prepared in the matrix. Among them 15 were determinated only on the ECD, 10 on the NPD and 15 were determinated on both detectors simultaneously. From the 130 active substances over 60% were determined using the dual EC- and NP-detection system. 3.3. Method validation 3.3.1. Specificity The ability of the analytical method to determine a particular analyte, metabolites or known additives was investigated. Lack of interference was demonstrated by the analysis of the concentrated blank formulations and concentrated sample extracts. The use of a second capillary column with a different polarity also confirmed interference-free separation. The following parameters were determined during the validation of the analytical method: linear range, LOD, LOQ, accuracy, precision, and matrix effects.

Fig. 2. Typical chromatograms of blank broccoli sample before (A, C) and after clean-up (B, D) e ECD (A, B) and NPD (C, D).

B. Łozowicka et al. / Food Control 25 (2012) 561e575

567

Fig. 3. Chromatogram of the selected standard mixture of 40 pesticides e ECD (A) and NPD (B) (concentration mg/kg): 1. dichlobenil (0.1); 2. propachlor (0.2); 3. dimethoate (0.1); 4. propyzamide (0.1); 5. diazinon (0.1); 6. chlorothalonil (0.1); 7. chlorpyrifos-methyl (0.1); 8. fenitrothion (0.1); 9. malathion (0.1); 10. chloropyrifos (0.1); 11. tetraconazole (0.1); 12. pendimethalin (0.2); 13. mecarbam (0.1); 14. methidathion (0.1); 15. myclobutanyl (0.2); 16. iprodione (0.5); 17. trifloxystrobin (0.1); 18. fenhexamid (0.4); 19. bifenthrin (0.1); 20. tetradifon (0.1); 21. l-cyhalothrin (isomers) (0.2); 22. fenarimol (0.1); 23. azinphos-ethyl (0.1); 24. pyridaben (0.4); 25. b-cyfluthrin (isomers) (0.3); 26. cypermethrin (isomers) (0.4); 27. esfenvalerate (isomers) (0.4); 28. deltamethrin (isomers) (0.3); 29. indoxacarb (0.2); 30. azoxystrobin (0.4); 31. heptenophos (0.1); 32. chlorpropham (0.5); 33. pirimicarb (0.1); 34. metalaxyl (0.5); 35. cyprodinil (0.2); 36. napropamide (0.2); 37. fludioxonil (0.2); 38. cyproconazole (0.3); 39. tebuconazole (0.1); 40. fenazaquin (0.3).

3.3.2. Linearity Linearity was evaluated by the calculation of a five-point linear plot with three replicates, based on linear regression and squared correlation coefficient (R2), which should be above 0.9900. Pesticides had a linear range from 0.001 to 2.5 mg/kg. The results are summarized in Table 1. 3.3.3. Matrix effect The response of the detectors to certain pesticides may be affected by the presence of co-extractives from the sample. These matrix-effects may be observed as an increase or decrease in response, compared with those produced by solvent solutions of the analyte. The effect of the matrix can be variable and unpredictable in the occurrence of measurable effects. The matrix effect on the detectors (ECD and NPD) response for the studied pesticides and matrices was evaluated in the present work. To determine if there is a different response between matrix-matched standards and standards in solvent, matrix-matched standards were used.

expressed as the repeatability (ten replicates) of the recovery determinations at the studied spiked levels and RSDs for all compounds have been defined (20%). These results indicate that the recoveries and accuracy of pesticides were good. Consequently, the pesticides were satisfactorily determined using this method. 3.3.5. LOD and LOQ The LOD values of individual pesticides were calculated based on the noise level in the chromatograms at S/N of 3:1 and are shown in Table 1. These values were lower than the MRLs (ranged from 0.001 mg/kg for chlorpyrifos in broccoli). The GC-ECD/NPD chromatograms of blank broccoli sample, standards, and spiked vegetable are presented in Figs. 2e4, respectively. The LOQs of the proposed method were calculated by considering a value 10 times that of the background noise. For most compounds the values obtained are lower than their respective MRLs (Table 1). The LOQs ranged from 0.001 to 0.03 mg/kg. 3.4. Application to vegetable samples

3.3.4. Recovery and repeatability To assess the performance of an analytical method, several criteria have to be considered. The pesticide recoveries should be in the range 70e120% with relative standard deviations (RSDs) < 20% (Document Sanco, 2007). In this study recovery experiments for 130 pesticides at three spiking levels between 0.001 and 2.5 mg/kg for a period of five days were performed. Each pesticide was fortified at its LOQ level, at the MRLs level or at 10 times the LOQ level and at a third intermediate level. The recoveries obtained for the most pesticides were satisfactory and ranged from 70% to 120% with the exception of dichlofluanid, dichlobenil, endosulfan-sulfate, phorate, phosmet, tecnazene (40e70%) and dichloran, dicofol, isofenphos, pyridaben, triasophos (120e130%) with RSDs of 0.15e8.76 %. Table 1 presents the recoveries along with RSDs obtained by a matrixstandard calibration in broccoli spiked at three concentration levels. However, a range of 60e140% may be use in routine multiresidue analysis (Document Sanco, 2007). A variable influence of matrix on the calculated recoveries was observed, depending on the physicochemical properties of each pesticide and its concentration in the sample. The accuracy and precision of the method via recovery experiments with fortified samples was tested. Method precision

Broccolis (206, 56.4% total), Brussels sprouts (2), cauliflowers (97), Chinese cabbages (6) and head cabbages (54) from different farms in north-eastern Poland were sampled and analyzed following the method described above. Pesticide residue levels were compared to national Polish (Reg., 2004; Reg., 2007) (for samples from the 2006e2007 year) and European MRLs (Commission Reg., 2008) (samples from the 2008e2009 year). Chromatogram of real broccoli sample presents Fig. 5. During the four-year testing period, 68% (247 samples) of vegetable were found free of residues, 32% (118 from 365 samples) contained residues, of which 23% (85) had residues below MRLs and 9% (33) above MRLs (Fig. 6.). Chlorpyrifos (MRL ¼ 0.05 mg/kg) in 28, boscalid (0.01 mg/kg) in 3, chlorothalonil (0.01 mg/kg) in 2, dimethoate (0.02 mg/kg) in 2 broccoli samples and also chlorothalonil in 1 Chinese cabbage were detected above MRLs. During this period, 28% (102) of samples with one residue and 4% (16) with two or three residues were detected (Fig. 6.). There were 15 pesticides detected: 4 fungicides e azoxystrobin, boscalid, chlorothalonil and pyrimethanil, 7 e insecticides pyrethroids e alphacypermethrin, cypermethrin, lambda-cyhalothrin, indoxacarb,

568

B. Łozowicka et al. / Food Control 25 (2012) 561e575

Fig. 4. Chromatogram of spiked broccoli sample e ECD (A) and NPD (B) (retention time e tR (min)): 1. dichlobenil (3.647 (A)); 2. propachlor (5.491 (A); 5.492 (B)); 3. dimethoate (6.474 (A); 6.479 (B)); 4. propyzamide (6.921 (A)); 5. diazinon (7.032 (A); 7.035 (B)); 6. chlorothalonil (7.373 (A)); 7. chlorpyrifos-methyl (7.988 (A); 7.992 (B)); 8. fenitrothion (8.496 (A); 8.500 (B)); 9. malathion (8.653 (A); 8.661 (B)); 10. chloropyrifos (8.912 (A); 8.917 (B)); 11. tetraconazole (9.031 (A)); 12. pendimethalin (9.559 (A); 9.51 (B)); 13. mecarbam (9.712 (A); 9.717 (B)); 14. methidathion (10.058 (A); 10.062 (B)); 15. myclobutanyl (10.747 (A); 10.749 (B)); 16. iprodione (11.252 (A)); 17. trifloxystrobin (11.736 (A)); 18. fenhexamid (11.838 (A)); 19. bifenthrin (12.452 (A)); 20. tetradifon (12.854 min (A)); 21. l-cyhalothrin (isomers) (13.031, 13.187 (A)); 22. fenarimol (13.423 (A); 13.424 (B)); 23. azinphos-ethyl (13.526 (A); 13.529 (B)); 24. pyridaben (14.055 (A); 14.058 (B)); 25. b-cyfluthrin (14.472, 14.563, 14.699 (A)); 26. cypermethrin (sum of isomers) (14.850, 14.961, 15.072 (A)); 27. esfenvalerate (sum of isomers) (16.162, 16.483 (A)); 28. deltamethrin (17.057, 17.442 (A)); 29. indoxacarb (17.290 (A)); 30. azoxystrobin (17.991 (A); 17.993 (B)); 31. heptenophos (5.183 (B)); 32. chlorpropham (5.744 (B)); 33. pirimicarb (7.526 (B)); 34. metalaxyl (8.200 (B)); 35. cyprodinil (9.425 (B)); 36. napropamide (10.4581 (B)); 37. fludioxonil (10.587 (B)); 38. cyproconazole (11.013 (B)); 39. tebuconazole (12.008 (B)); 40. fenazaquin (12.686 (B)).

fenvalerate, esfenvalerate and bifenthrin, 4 insecticides phosphoroorganic e chlorpyrifos, diazinon, dimethoate and fenitrothion (Fig. 7). The most commonly detected compound was chlorpyrifos which occurred in 27.4% (100) of the analyzed samples. The residues were found in 110 samples of broccolis (54% of total), 1 Brussels sprout (50%), 5 cauliflowers (5%), 1 Chinese cabbage (16.6%) and 1 head cabbage (1.8%). The ranges of concentration pesticide of the analyzed samples are presented in Table 2. Fig. 7 illustrates the frequency of all detected active substances. 3.5. The co-occurrence of pesticide residues The co-occurrence of pesticide residues is listed in detail in Table 3. Residues of two or three pesticides were found in 16 (4.4%)

analyzed vegetables samples. 13 (3.6%) samples of the commodities studied contained two residues of pesticides and 3 (0.8%) samples were contaminated with three pesticide residues. The most often found combination in multiresidue samples were chlorpyrifos (I) with cypermethrin (I) 10 of 16 multiresidue samples (62.5%) (6 samples with two residues and 3 samples with three residues in broccoli and also 1 sample with two residues in head cabbage). Chlorpyrifos was detected at concentrations ranging from 0.005 to 1.51 mg/kg (MRL ¼ 0.05 mg/kg) in 93 broccoli samples, 0.88 mg/kg (MRL ¼ 1.00 mg/kg) in head cabbage and 0.02 mg/kg (MRL ¼ 0.50 mg/kg) in Chinese cabbage sample. Cypermethrin was found at concentrations ranging from 0.02 to 0.19 mg/kg (MRL ¼ 2.0 mg/kg and MRL ¼ 0.5 mg/kg) in 11 broccoli samples and 0.17 mg/kg in head cabbage (MRL ¼ 0.5 mg/kg). One sample of Chinese cabbage was contaminated with two pesticide residues

Fig. 5. Chromatograms of the real broccoli sample e ECD (A) and NPD (B) chlorpyrifos 0.04 mg/kg (tR ¼ 8.914 min (A); 8.919 min (B)) and cypermethrin (isomers) 0.07 mg/kg (tR ¼ 14.852; 14.963, 15.077 min (A)).

B. Łozowicka et al. / Food Control 25 (2012) 561e575

569

Fig. 6. Occurrence of pesticide residues and multiresidue samples of Brassica vegetables sampled in 2006e2009.

chlorpyrifos (I) and chlorothalonil (F). In 10 multiresidue samples concentration of chlorpyrifos was above MRL. 3.6. Risk assessment Based on the results of analytical studies of pesticide residues in Brassica samples from 2006 to 2009, a list of pesticide active substances potentially harmful to health was established (Tables 4 and 5). Chronic exposure assessment was carried out for the British (76 kg b.w) and Polish general population (71 kg b.w.) with the highest (97.5 percentile) and mean intake. Assessment of chronic risk was conducted for broccoli, cabbage, cauliflower and Chinese cabbage for three groups of pesticides divided depends of action mode (PPDB, 2011). I. Insecticide, the same action mode A. Cholinesterase inhibitor organophosphate insecticide Chlorpyrifos e (example products using this active: Alpha Chlorpyrifos, Ballad, Cyren, Dursban WG, Equity, Govern, Parapet), non-systemic with contact and stomach action, acetylcholinesterase (AChE) inhibitor, nervous system cholinesterase inhibitor (irreversible). Diazinon e Excluded from Annex 1 EC Directive 91/414 (1991), (Diazol 60EC, Knox-Out, DZN, Basin), non-systemic with respiratory, contact and stomach action, acetylcholinesterase (AChE) inhibitor, nervous system cholinesterase inhibitor (irreversible).

Dimethoate e (Dimethoate 40, Danadim, Danadim Progress) systemic with contact and stomach action, acetylcholinesterase (AChE) inhibitor. Fenitrothion e Excluded from Annex 1 EC Directive 91/414 (1991), (IPM 400, Fenitrocap, Fenifos, Niton), non-systemic, broad spectrum with contact and stomach action, acetylcholinesterase (AChE) inhibitor. B. Sodium channel modulator, synthetic pyrethroid Alpha-cypermethrin e (Antec, Contest, Fedona, Littac, Tenopa), non-systemic with contact and stomach action, sodium channel modulator. Bifenthrin e Pending (Re-submitted) EC Directive 91/414 (1991), (Gala 10 EC, Gyro, Starion Flo, Talstar Flo, Brigade, Talstar 8 SC), contact and stomach action with some residual effect, sodium channel modulator. Cypermethrin e (Permasect C), non-systemic with contact and stomach action, nervous system, sodium channel modulator. Esfenvalerate e (Sumi-Alpha, Hounddog, Sven, Asana), contact and stomach action, sodium channel modulator. Fenvalerate e Excluded from Annex 1 EC Directive 91/414 (1991), (Fenvalerate 20% EC) non-systemic with contact and stomach action, sodium channel modulator. Indoxacarb e (Provaunt, Steward, Avaunt), contact and stomach action, voltage-dependent sodium channel blocker. Lambda-cyhalothrin e (Dovetail, Hallmark, Seal Z, Warrior, Jackpot 2), non-systemic, contact and stomach action, some

0,3

pyrimethanil

0,8

lambda-cyhalothrin

0,8

indoxacarb fenvalerate

0,3

fenitrothion

0,3

fenhexamide

0,3

esfenvalerate

0,3 0,8

dimethoate

0,3

diazinon cypermethrin

3,3

chlorpyrifos

27,4

chlorothalonil

0,8

bifenthrin

0,3

boscalid

1,1

azoxystrobin

0,3

alpha-cypermethrin

0,3

0

5

10

15

20

% of samples with residues Fig. 7. Frequency of occurrence residues in Brassica vegetables in 2006e2009.

25

30

B. Łozowicka et al. / Food Control 25 (2012) 561e575

570

repellant properties, synthetic pyrethroid, nervous system sodium channel modulator. II. Fungicide with various mode of action: Azoxystrobin e strobilurin, (Amistar, Amistar Opti, Amistar Pro, Olympus, Priori Xtra, Quadris, Abound, Ortiva), systemic translaminar and protectant action having additional curative and eradicant properties, respiration inhibitor (QoL fungicide). Boscalid e carboxamide, (Filan, Signum, Splice, Tracker, Venture, Emerald, Bosco WG), protectant, foliar absorption, translocates, inhibits spore germination and germ tude elongation. Chlorothalonil e chloronitrile, (Alto Elite, Amistar Opti, Bravo 500, Cherokee, Credo, Folio, Joules, Merlin, Midas, Repuls), non-systemic, broad-spectrum, foliar action with some protectant properties, acts by preventing spore germination and zoospore motility. Pyrimethanil e anilinopyrimidine, (Scala, Walabi), protective action with some curative properties.

Table 2 Pesticide residues in Brassica vegetables in 2006e2009 (number of detections). Active substance Number of samples With With residues residues > MRL

With residues

MRL Concentration [mg/kg] range [mg/kg]

Broccoli N ¼ 206

a-Cypermethrin

1 Azoxystrobin 1 Bifenthrin 1 Boscalid 4 Chlorpyrifos 93 Chlorothalonil 2 Cypermethrin 11 Diazinon 1 Dimethoate 3 Esfenvalerate 1 Fenitrothion 1 Fenvalerate 1 Indoxycarb 3 l-Cyhalothrin 3 Pyrimethanil 1 Total 127 Brussels sprouts N ¼ 2 Chlorpyrifos 1 Total 1 Head cabbage N ¼ 54 Chlorpyrifos 1 Cypermethrin 1 Total 2 Cauliflower N ¼ 97 Chlorpyrifos 4 Fenhexamide 1 Total 5 Chinese cabbage N ¼ 6 Chlorpyrifos 1 Chlorothalonil 1 Total 2 Total 137

e e e 3 28 2 e e 2 e e e e e e 35

1 1 1 1 65 e 11 1 1 1 1 1 3 3 1 92

0.5 0.5 0.2 0.01 0.05 0.01 0.5 0.02 0.02 0.04 0.5 0.04 0.3 0.1 0.5

0.04 0.05 0.03 0.02e0.20 0.005e1.51 0.012e0.28 0.02e0.19 0.012 0.01e0.05 0.02 0.035 0.02 0.05e0.08 0.02 0.02

0 0

1 1

0.05

0.005

e e e

1 1 2

1 0.5

0.88 0.17

e e e

4 1 5

0.05 0.1

0.005e0.016 0.03

e 1 1 36

1 e 1 101

0.5 0.01

0.02 0.06

Table 4 shows the results of estimation of chronic dietary exposure to pesticide from Brassica vegetables for the two groups: British adults and Polish general population. Both the average (mean) and highest consumption level (97.5 percentile) were used. Cumulative chronic dietary exposure to acetylcholinesterase (AChE) inhibiting of pesticides and sodium channel modulators pesticide group were evaluated. The cumulative assessment of organophosphorous insecticides (I.A) in broccoli samples were higher than of pyrethroid compounds (I.B), but in all cases were below than 6.1 %ADI. The potential chronic dietary exposure for British adults at 97.5% consumption, British adults and Polish general population at mean consumption level were: I.A e 6.081; 0.512; 0.067 %ADI and I.B e 1.669; 0.145; 0.0184 %ADI, respectively. The long-term consumer exposure to individual pesticide residues (e.g., diazinon) does not exceed the % of the ADI (4.454 %ADI for British adults at 97.5 percentile and 0.375, 0.049 %ADI for British

Table 3 The co-occurrence of pesticide residues in Brassica vegetables. Commodity

Broccoli

Head cabbage Chinese cabbage

Active substance

Chlorpyrifos (I) Cypermethrin (I) Chlorpyrifos (I) a-Cypermethrin (I) Chlorpyrifos (I) l-Cyhalothrin (I) Chlorpyrifos (I) Azoxystrobin (F) Dimethoate (I) l-Cyhalothrin (I) Chlorpyrifos (I) Cypermethrin (I) Dimethoate (I) Chlorpyrifos (I) Cypermethrin (I) Bifenthrin (I) Chlorpyrifos (I) Cypermethrin (I) Esfenvalerate (I) Chlorpyrifos (I) Cypermethrin (I) Chlorpyrifos (I) Chlorotalonil (F)

Number of samples

Number of samples With residues < MRL

With residues > MRL

6

1 6 1 2 1 1 0 1 1 1 0 1 0 0 1 1 0 1 1 1 1 1 0

5 0 1 0 0 0 1 0 0 0 1 0 1 1 0 0 1 0 0 0 0 0 1

2 1 1 1 1

1

1

1 1

Bold represents the active substance with concentration exceeding MRL.

Concentration range [mg/kg]

0.04 0.07 0.005 0.02 0.05 0.02 0.08 0.04 0.01 0.02 0.19 0.03 0.05 1.51 0.19 0.03 0.15 0.02 0.02 0.88 0.17 0.02 0.06

0.08 0.04

0.22 0.06

0.29 0.02 0.16 0.05

MRL [mg/kg]

0.16 0.03

0.30 0.06

0.05 2.00; 0.50 0.05 0.50 0.05 0.10 0.05 0.50 0.02 0.10 0.05 0.50 0.02 0.05 0.50 0.20 0.05 0.50 0.02 1.00 0.50 0.50 0.01

B. Łozowicka et al. / Food Control 25 (2012) 561e575

571

Table 4 Estimation of chronic dietary exposure to pesticide for Brassica vegetables in 2006e2009. Active substance

Average residues level (mg/kg)

Acceptable daily intake (ADI) (mg/kg b.w.)

British adults (76 kg) (97.5 percentile) ng/kg b.w.

Broccoli Consumption (g/person/day) Group I.A Chlorpyrifos Diazinon Dimethoate Fenitrothion Total Group I.B a-cypermethrin Bifenthrin Cypermethrin Esfenvalerate Fenvalerate Indoxacarb l-cyhalothrin Total Group II. Azoxystrobin Boscalid Chlorothalonil Pyrimethanil Total Brussels sprouts Consumption (g/person/day) Chloropyrifos Total Head cabbage Consumption (g/person/day) Chloropyrifos Cypermethrin Total Cauliflower Consumption (g/person/day) Chloropyrifos Fenhexamid Total Chinese cabbage Consumption (g/person/day) Chloropyrifos Chlorothalonil Total

British adults (76 kg) (mean) %ADI

ng/kg b.w.

46

Polish general population (71 kg) (mean) %ADI

1.8

ng/kg b.w.

%ADI

0.2

0.04005 0.01 0.01024 0.0201

0.01 0.0002 0.001 0.005

35.7 8.9 9.1 17.9

0.357 4.454 0.912 0.358 6.081

3 0.8 0.8 1.5

0.03 0.375 0.077 0.03 0.512

0.4 0.1 0.1 0.2

0.004 0.049 0.01 0.004 0.067

0.02015 0.03 0.02155 0.02 0.02 0.0502 0.02

0.015 0.015 0.05 0.02 0.0125 0.006 0.005

17.9 26.7 19.2 17.8 17.8 44.7 17.8

0.12 0.178 0.038 0.089 0.143 0.745 0.356 1.669

1.5 2.3 1.6 1.5 1.5 3.8 1.5

0.01 0.015 0.003 0.008 0.012 0.063 0.03 0.145

0.2 0.3 0.2 0.2 0.2 0.5 0.2

0.001 0.002 0.0004 0.001 0.002 0.008 0.004 0.0184

0.04 0.01126 0.01105 0.01005

0.2 0.04 0.015 0.17

35.6 10 9.8 9

0.018 0.025 0.066 0.005 0.114

3 0.8 0.8 0.8

0.002 0.002 0.006 0.0004 0.0104

0.4 0.1 0.1 0.1

0.0002 0.0003 0.001 0.0001 0.0016

0.0075

0.01

4.6 4.5

0.0261 0.0326

0.01 0.05

82 28.2 35.2

0.00531 0.01021

0.01 0.2

80.3 5.6 10.8

0.0075 0.0183

0.01 0.015

37.8 3.7 9.1

and Polish consumers at mean consumption level). It is noted that the use of diazinon is no longer permitted in the European Union. The total risk for chlorpyrifos occurring in all analyzed commodities yields 0.777% ADI for adults with the high consumption level (0.357% ADI in broccoli; 0.045% ADI in Brussels sprouts, 0.282% ADI in cabbage, 0.056% ADI in cauliflower and 0.037% ADI in Chinese cabbage). Short-term exposure for the two groups: adults (76 kg b.w.) and toddlers (15.5 kg b.w.) based on the highest consumption at 97.5

1.8 0.2

0.045 0.045

0.018 0.018

5.5 1.9 2.4

0.282 0.07 0.35

0.019 0.005 0.02

4.8 0.3 0.6

0.056 0.005 0.061

0.003 0.0003 0.004

0.1 0.01 0.02

0.037 0.061 0.1

0.0001 0.0002 0.0003

0.2 0.02

25.9 9.5 11.9

6.5 0.5 0.9

1.4 0.1 0.4

0.0002 0.0002

0.095 0.024 0.12

0.005 0.0005 0.0055

0.001 0.002 0.004

percentile and highest concentrations of pesticides residues detected in broccoli and Chinese cabbage are presented in Table 5. Chlorpyrifos detected at the highest concentration (HR) 1.51 mg/ kg in broccoli (ARfD is 0.1 mg/kg b.w.) has shown the maximum exposure for toddlers (32% of the ARfD), while for adults does not exceed 20% of ARfD allowed value. The highest detected level of boscalid (HR 0.20 mg/kg; ARfD 0.04 mg/kg b.w.) and dimethoate in broccoli (HR 0.05 mg/kg; ARfD 0.01 mg/kg b.w.) in an intake were at 10.7% and 10.5% of the ARfD for children, 6.6% and 6.4% for adults,

Table 5 Estimation of acute dietary exposure of pesticides based on their highest residues in Brassica vegetables in 2006e2009. Active substance

Boscalid Chloropyrifos Chlorothalonil Dimethoate Chlorothalonil

Commodity

Broccoli Broccoli Broccoli Broccoli Chinese cabbage

HR [mg/kg]

0.20 1.51 0.28 0.05 0.06

ARfD [mg/kg b.w.]

0.04 0.1 0.6 0.01 0.65

v

5 5 5 5 5

U [kg]

0.68 0.68 0.68 0.68 0.54

Consumptiona [g/person/day]

Intake Toddlers [14.5 kg]

Adults [76 kg]

toddlers

adults

mg/kg b.w.

% ARfD

mg/kg b.w.

% ARfD

24.8 24.8 24.8 24.8 n.d.

67.7 67.7 67.7 67.7 37.8

4.27 31.61 5.86 1.05 e

10.7 31.6 1.0 10.5 e

2.62 19.42 3.60 0.64 0.93

6.6 19.4 0.6 6.4 0.2

HR e the highest residue level, ARfD e Acute Reference Dose, v e variability factor, U e the weight of first commodity unit, b.w. e body weight, n.d. e no data. a Full portion consumption data (97.5 percentile).

572

B. Łozowicka et al. / Food Control 25 (2012) 561e575

respectively. An acute exposure to chlorothalonil occurred in broccoli (HR 0.28 mg/kg; ARfD 0.6 mg/kg b.w.) and Chinese cabbage (HR 0.06 mg/kg; ARfD 0.65 mg/kg b.w.) for adults were 0.6% and 0.2% of the ARfD, respectively and for toddlers only in broccoli 1.0% of the ARfD. 4. Discussion 4.1. Analytical method Conventional sample preparation methods involve several steps leading to the possibility of loss or contamination during sample preparation. Regulatory authorities provide assurance that any pesticide remaining in or on the food is within safe limits through monitoring programmes of random sampling and analysis of raw and processed food on the market. Although during the past years, many new solventless extraction techniques have emerged such as supercritical fluid extraction (SFE) (Nerin, Battle, & Cacho, 1998; Valverde-Garcia, FernandezAlba, Contreras, & Aguera, 1996), solid-phase microextraction (SPME) (Diaz, Vazquez, Ventura, & Galceran, 2004; Hu, Hennion, Urruty, & Montury, 1999), solid-phase extraction (SPE) (Colume, Cardenas, Gallego, & Valance, 2001; Gonzalez-Rodriguez, RialOtero, Cancho-Grande, & Simal-Gandara, 2008; Rodriguez, Pico, Font, & Manes, 2002) and matrix solid phase dispersion (MSPD) (Albero, Sanchez-Brunete, & Tadeo, 2003). Many conventional methods for the extraction of pesticide residues in vegetables using solvent partitioning (Luke, Froberg, & Masumoto, 1975; Wang et al., 2009; Zamora, Pozo, Lopez, & Hernandez, 2004) has been still used. Liquideliquid extraction using organic solvents such as ethyl acetate (Aguera, Contreras, Crespo, & Fernandez-Alba, 2002; Hernando et al., 2001), acetone (Aguera, Piedra, Hernando, Fernandez-Alba, & Contreras, 2000), 2propanol, petroleum ether, dichloromethane, n-hexane and acetonitrile (Valverde-Garcia, Gonzales-Pradas, Aguilera-Del Real, & Urena-Amate, 1993) are also preferred. MSPD has been shown to be a good alternative to liquideliquid extraction because it easy and fast to perform and in general, MSPD avoids the use of large amounts of solvents and the occurrence of troublesome emulsions. Literature describes use MSPD for the isolation of individual pesticides or groups of pesticides in fruit or vegetables. MSPD has been used to extract ninety-five different pesticides (Domotrova, Matisova, Kirchner, & de Zeeuw, 2005), azoxystrobin and trifloxystrobin (Giza & Sztwiertnia, 2003) from apples and beans (Lopes & Dorea, 2003), carbofuran from maize (Yang & Chengguang, 1994), urea derivatives (Valenzuela, Pico, & Font, 2000), organophosphate insecticides (Torres, Pico, Rosa, & Manes, 1997), carbamates from fruits and vegetables (Fernandez, Pico, & Manes, 2000), fourteen fungicides (Blasco, Pico, Manes, & Font, 2002), fungicides from fruits and vegetables (Morzycka, 2002) and pesticides from different groups from fruit and vegetables (Kristenson et al., 2001). Modified by our group MSPD method was used to determine the presence of pesticide residues in real samples of Brassica vegetables. This techniques combines sample homogenization, extraction and clean-up steps. The sample was dispersed over a surface of florisil. The mechanism occurring by blending the sample with this inorganic normal phase material is not the same proposed for silica bonded phase sorbents. This material does not dissolve the sample matrix but only adsorb the organic molecules and mechanical disruption of the cells sufficiently permits the pesticide migration to the sorbent surface. Selection of eluents to be used for recovery of pesticides with retention of matrix compounds is function of analyte polarity. To improve the recovery for pesticide florisil, silica gel and anhydrous sodium sulfate had to be activated before use.

Usually, elutes may be taken directly for instrumental analysis (Barker, 2007) however, a purification step of the Brassica extracts was required to the decrease the high volatile sulfur organic content and remove co-eluating matrix components of the broccoli samples. Chromatogram of blank broccoli extracts contained no interfering peaks presents Fig. 2. Determination by GC usually with mass spectrometric detector (Blasco et al., 2002; Fernandez, Arrebola, Garrido Frenich, & Martinez Vidal, 2006; Fillion, Sauve, & Selwyn, 2000; Lehotay, de Kok, Hiemstra, & van Bodegraven, 2005; Shuling, Xiaodong, & Chongjiu, 2007; Tanaka, Hori, Asada, Oikawa, & Kawata, 2007; Wang, Xu, Pan, Jiang, & Liu, 2007; Zrostlikova, Hajslova, & Cajka, 2003) have been published in the last decade. From among the cited reports, only a few (Domotrova et al., 2005; Giza & Sztwiertnia, 2003) describe the use of the MSPD technique and gas chromatography with dual detection system EC and NP. When we use GC as separation analytical technique, anhydrous sodium sulfate was added to the glass column for the purpose of water retention. Less polar solvent or mixtures were used for desorption to improve recoveries. To be sure about the quality of results when the proposed method is applied to routine analyses, various internal criteria have been established. The first one is blank extract that eliminates the contamination in the extraction and clean-up processes, instrument or chemicals used. One blank sample was processed in each set of experiments. The second one is to check the extraction efficiency. Recoveries at the second concentration level (0.1e0.5 mg/kg) will be accepted if the majority of recoveries are within 70e120% range. The third Laboratory regularly takes a part in proficiency testing schemes organized by the Food Analysis Performance Assessment Scheme (FAPAS; Central Science Laboratory in York) and the European Commission (at the beginning by the University of Uppsala and then by the University of Almeria). 4.2. Risk assessment In this paper we estimated pesticide intakes using the average detected pesticide residue levels and compared with estimated using high and mean consumption diets to determine long-term health risks to British adults and Polish general population (Szponar, Sekula, Rychlik, O1tarzewski, & Figurska, 2003). Longterm intakes were also compared to the full ADI. Overall results from pesticide residues assessment performed in Brassica samples indicate a no zero risk by pointing positive detections of pesticide residues in the 30% of samples from north-eastern Poland cultivations. In order to take account of the maximum risk of consumer’s exposure in Brassica samples, the estimated daily intake (EDI) residues was calculated using the means of detected pesticides according to the guideline of World Health Organization (Guidelines WHO, 1997). As can be seen in Table 4, when calculation based on mean consumption level consumer’s exposure to individual pesticides did not exceed the ADI certainly. In the case of group of organophosphorus pesticides a cumulative risk should be considered, because these compounds may have a common mechanism of acetylcholinesterase inhibition. Nevertheless %ADI of acetylcholinesterase inhibitors estimated for the adults were far below one (ranged from 0.067 to 0.512 %ADI) that may probably constitute a risk. Furthermore, a cumulative risk for sodium channel modulator compounds was calculated and these ranged from 0.018 to 0.145 % ADI. Although, results show a negligible risk associated with the exposure via broccoli consumption, a special precaution should be taken with the possible aggregate exposure to these chemicals from multiple sources of nutrition and domestic use of pesticides. Chronic dietary exposure calculated for British adults at high consumption level was 10 times higher than for British adults and 100 times for Polish general population at mean consumption level.

B. Łozowicka et al. / Food Control 25 (2012) 561e575

Acute exposure (short-term) was calculated only for compounds exceeding the MRLs for the broccoli and Chinese cabbage commodities. MRLs are often mistaken for toxicological safety limits and all violations of an ARfD should be notified to the RASFF (Rapid Alert System for Food and Feed) system operating in EU since 1979. To evaluate whether an observed violation of an MRL can lead to a risk to the consumer, it is necessary to estimate the actual risk to the most critical consumer group. Generally, children from 1.5 to 6 years of age are considered as the most vulnerable group, because they tend to eat a large number of single units of one food commodity in one day. Therefore in the deterministic exposure approach used in several European countries, a high percentile of consumption (e.g., 97.5) by these children is used. European Union takes actions with risk management connected with food safety threats from pesticide residues for protecting European consumers every year. For example, in 2008 for 35 pesticide/commodity combinations a potential consumer risk could not be excluded (EFSA, 2008b). Ludwicki and Kostka (2008) indicate that in Poland, among 148 samples 17 cases of fruit and vegetable crops were noted in RASFF system in the years 2003e2007. The highest potential exceedances of the toxicological reference value was indicated for e.g., lettuce containing procymidone showing the highest excess of acute reference dose (1211% of the ARfD), mushrooms with carbendazim (160% of the ARfD) and lettuce with diazinon (127% of the ARfD). Consumption these products may adversely affect human health. In our work the assessment was based on worst-case scenarios: the consumption data for consumers who eat a large portion size of the food were combined with the highest residue found in Brassica from agricultural north-eastern Poland in 2006e2009. It seems that these critical cases of consumption have no reasonable possibility of occurring. In order to accommodate for a possible non-homogeneous distribution of residues in an analyzed food, a variability factor “5” was introduced. Assuming that through a coincidence these events did occur (high food consumption, high residue concentration and non-homogeneous residue distribution in a lot), potential consumer risk could not be excluded for five pesticide/commodity combinations: boscalid/broccoli, chlorpyrifos/broccoli, chlorothalonil/broccoli, dimethoate/broccoli and chlorothalonil/Chinese cabbage. One of these critical combinations chlorpyrifos/broccoli, where chlorpyrifos had the highest concentration (1.51 mg/kg), resulted in an intake that is at 31.6% of the ARfD value for toddlers consuming 24.8 mg/kg b.w./ day and 19.4% of the ARfD for adults consuming three times bigger portion (67.7 mg/kg b.w./day), when using EFSA high consumption diets (EFSA, 2006). In this paper described case of chlorpyrifos in broccoli shows 30 times exceedance of the MRL (0.05 mg/kg). Chlorpyrifos MRL (0.05 mg/kg) was established in such a way that even 30 times its exceedance does not constitute a serious threat to human health. Additionally, 28 times and 20 times MRL exceedances for chlorothalonil and boscalid in broccoli were observed. Combinations boscalid/broccoli (HR 0.20 mg/kg) and dimethoate/broccoli (0.05 mg/kg) showed similar values % of the ARfD despite of different concentrations of these compounds. Obtained values depend on the toxicological parameter ARfD of each pesticide. Boscalid (fungicide) has a higher value of ARfD (0.04 mg/kg b.w.) than organophosphorus insecticide dimethoate (0.01 mg/kg b.w.). For the most critical group (toddlers) for all combinations % of the ARfD was three times higher than for adults. However, in all investigated cases values did not exceed the safe level of 100% ARfD. However, the critical intake events identified in the acute risk assessment calculations were considered very unlikely to occur, taking into account the frequency of critical residues and the frequency of extreme consumption events. For five of the pesticide/ commodity combinations for which critical intake situation could

573

not be excluded, risk management activities have already been put into effect, by withdrawing authorizations or by lowering the MRLs. It should be emphasized that dietary pesticide intakes estimated in this study considered only exposures from vegetables and did not include other food products such as grains, dairy, fish, and meats. As such, estimates are not considered as total dietary exposure to the pesticides, nor do we consider drinking water, residential, or occupational exposures. Therefore, it is an underestimation of the total exposure of pesticides studied. Although the dietary intakes estimated from all pesticide level detected in vegetables do not represent a health risk to local consumers, the intake estimated from the highest pesticide residues level is low and did not exceed the short-term health standards. 4.3. Application to vegetable samples The proposed method was applied to the routine analysis of 365 real vegetable samples of different matrices (broccoli, Brussels sprouts, cauliflower, head and Chinese cabbage). The results showed that the 32% of the analyzed samples gave positive results (higher than LOQ). Nine % of them overcame the levels established by both the European legislation (MRL) and Polish legislation (MRL). The most frequently and the highest concentration pesticide found was chlorpyrifos. Traces of other compounds (diazinon, dimethoate, fenitrothion, azoxystrobin, boscalid, bifenthrin, chlorothalonil, fenhexamid, pyrimethanil, a-cypermethrin, cypermethrin, esfenvalerate, fenvalerate, indoxacarb, l-cyhalothrin) were detected. Chlorpyrifos is an organophosphorus insecticide with a broadspectrum activity and plant protection products with this substance registered for application on more than 40 different commodities. Cholinesterase inhibition is the mode of action of chlorpyrifos and is the cause of potential toxicity in humans (Oliver, Bolles, & Shurdut, 2000). In vegetable samples collected from farmer’s fields, higher chlorpyrifos residue exceeding MRLs values was observed (28 samples). Farmers are mostly unaware of safe use of pesticides. They have a tendency to over-dose with pesticides to produce a high quality fruit and vegetables (Yen, Bekele, & Kalloo, 1999). Nurelle D 505, combination of two active substances: chlorpyrifos (phosphorothioate group of organophosphorus pesticides) and cypermethrin (synthetic pyrethroid) is a very often-used insecticide in Poland. Chlorpyrifos plus cypermethrin affects both the axonic and synaptic transmission of the nerve impulses in the nervous system of insects. Pesticide residues were compared according to Polish and EU regulations (Commission Reg., 2008; Reg., 2004, 2007; Status, 2008). The year 2008 was important in the harmonization of pesticide MRLs legislation at the European level. National MRLs for about 250 active substances existed in Poland before September 1, 2008. Regulation (EC) No 396/2005 was harmonized MRLs for all active substances used in plant protection products. For example, in 2006 and 2007 year Polish MRL for cypermethrin was 2 mg/kg, after September 1, 2008 reduced to 0.5 mg/kg. 5. Conclusion A rapid, reliable, time and resource saving analytical method is reported for the measurement of a wide range of 130 different pesticides used in agriculture. The multiresidue analytical procedure developed in this study was based on matrix solid phase dispersion using activated florisil and extraction with purification step using activated silica gel and anhydrous sodium sulfate. Extracts were analyzed without other purification by GC-ECD/NPD except for broccoli. For broccoli adsorption chromatography column were used. Modified MSPD method showed satisfactory

574

B. Łozowicka et al. / Food Control 25 (2012) 561e575

validation parameters such as accuracy, precision, recovery, lower detection limits and selectivity. The results obtained indicate that the methodologies developed could be a successful alternative for laboratories where new extractions techniques (SPE cartridges, SFE and SPME) and expensive apparatus are unavailable. The proposed method was adapted for routine application in monitoring studies and surveys. Monitoring results pointed that consumers could be exposed to more than one pesticide (4% of samples) especially when it comes to insecticides. The most frequently detected residue in vegetable samples is the organophosphate insecticide chlorpyrifos, one of most commonly used insecticide locally and, likely, commonly used in other countries. Notably, some residue levels of chlorpyrifos largely exceed the MRLs given by Polish and European government. The highest residue level was found in broccoli e chlorpyrifos 1.51 mg/kg. The performed risk assessment showed that pesticide residues detected in Brassica vegetables will not constitute a risk for any consumer groups studied. Results suggest that chronic exposure to pesticide residue from broccoli may, in fact, be significantly higher for 15 pesticides for which quantifiable residues were detected. The highest detected chlorpyrifos level would have resulted in an intake of 19.4% for toddlers and 31.6% for adults of the ARfD. It should be emphasized that dietary pesticide exposures estimated in this study considered only exposures from Brassica, and did not include other food products such as fruit, other vegetables, grains, dairy, fish and meats. As such, these exposure estimates are not considered to be estimates of total dietary exposure to pesticides nor do they consider drinking water, residential, or occupational exposures. References Aguera, A., Piedra, L., Hernando, M. D., Fernandez-Alba, A. R., & Contreras, M. (2000). Splitless large-volume GC-MS injection for the analysis of organophosphorus and organochlorine pesticides in vegetables using a miniaturised ethyl acetate extraction. Analyst, 125, 1397e1402. Aguera, A., Contreras, M., Crespo, J., & Fernandez-Alba, A. R. (2002). Multiresidue method for the analysis of multiclass pesticides in agricultural products by gas chromatography-tandem mass spectrometry. Analyst, 127, 347e354. Albero, B., Sanchez-Brunete, C., & Tadeo, J. L. (2003). Determination of endosulfan isomers and endosulfan sulfate in tomato juice by matrix solid-phase dispersion and gas chromatography. Journal of Chromatography A, 1007, 137e143. Altieri, M. A., & Gliessman, S. R. (1983). Effects of plant diversity on the density and herbivory of the flea beetle, Phyllotreta cruciferae Goez, in California collard (Brassica oleracea) cropping systems. Crop Protection, 2, 497e501. Anastassiades, M., Lehotay, S. J., Stajnbaher, D., & Schenck, F. J. (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 the Association of Official Agricultural Chemists International, 86, 412e431. Barker, S. A. (2007). Matrix solid phase dispersion (MSPD). Journal of Biochemical and Biophysical Methods, 70, 151e162. Berrada, H., Font, G., & Molto, J. C. (2004). Application of solid-phase microextraction for determining phenylurea herbicides and their homologous anilines from vegetables. Journal of Chromatography A, 1042, 9e14. Blasco, C., Pico, Y., Manes, J., & Font, G. (2002). Determination of fungicide residues in fruits and vegetables by liquid chromatographyeatmospheric pressure chemical ionization mass spectrometry. Journal of Chromatography A, 947, 227e235. Colume, A., Cardenas, S., Gallego, M., & Valance, M. (2001). Semiautomatic multiresidue gas chromatographic method for the screening of vegetables for 25 organochlorine and pyrethroid pesticides. Analytica Chimica Acta, 436, 153e162. Commission Regulation (EC) No 839/2008 of 30 August 2008 amending Regulation (EC) No 396/2005 of the European Parliament and of the Council as regards Annexes II, III and IV on maximum residue levels of pesticides in or on certain products. Council Directive 91/414/EEC of 15 July 1991 concerning the placing of plant protection products on the market (with following changes). Diaz, A., Vazquez, L., Ventura, F., & Galceran, M. T. (2004). Estimation of measurement uncertainty for the determination of nonylphenol in water using solid-phase extraction and solid-phase microextraction procedures. Analytica Chimica Acta, 506, 71e80. Diez, C., Traag, W. A., Zommer, P., Marinero, P., & Atienza, J. (2006). Comparison of an acetonitrile extraction/partitioning and “dispersive solid-phase extraction” method with classical multi-residue methods for the extraction of herbicide residues in barley samples. Journal of Chromatography A, 1131, 11e23.

Document N SANCO/2007/3131 31/October/2007. Method validation and quality control procedures for pesticides residues analysis in food and feed. Domotrova, M., Matisova, E., Kirchner, M., & de Zeeuw, J. (2005). MSPD combined with fast GC for ultratrace analysis of pesticide residues in non-fatty food. Acta Chimica Slovenica, 52, 422e428. EFSA. (2006). Calculation model. Acute and chronic consumer exposure REV1. http:// www.efsa.europa.eu/en/efsajournal/pub/32r.htm (03.10.2011). EFSA. (2008a). Report on the toxicological reference values for the active substances in plant protection products. Web report nr 1, July 2008. EFSA. (2008b). 2008 Annual report on pesticide residues according to Article 32 of Regulation (EC) No 396/2005. http://www.efsa.europa.eu/en/efsajournal/pub/ 1646.htm (07.10.2011). Fahey, J. W., Zalcmann, A. T., & Talalay, P. (2001). The chemical diversity and distribution of glucosinolates and isothiocyanates among plants. Phytochemistry, 56, 5e51. Fenoll, J., Hellin, P., Martinez, C. M., Miguel, M., & Flores, P. (2007). Multiresidue method for analysis of pesticides in pepper and tomato by gas chromatography with nitrogenephosphorus detection. Food Chemistry, 105, 711e719. Fernandez, J. L., Arrebola, F. J., Garrido Frenich, A., & Martinez Vidal, J. L. (2006). Evaluation of different sample treatments for determining pesticide residues in fat vegetable matrices like avocado by low-pressure gas chromatographyetandem mass spectrometry. Journal of Chromatography A, 1111, 97e105. Fernandez, M., Pico, Y., & Manes, J. (2000). Determination of carbamate residues in fruits and vegetables by matrix solid-phase dispersion and liquid chromatography-mass spectrometry. Journal of Chromatography A, 71, 43e56. Fillion, J., Sauve, F., & Selwyn, J. (2000). Multiresidue method for the determination of residues of 251 pesticides in fruits and vegetables by gas chromatography/ mass spectrometry and liquid chromatography with fluorescence detection. Journal of the Association of Official Analytical Chemists, 83, 698e713. Gelsomino, A., Petrovicowa, B., Tiburtini, S., Magnani, E., & Felici, M. (1997). Multiresidue analysis of pesticides in fruits and vegetables by gel permeation chromatography followed by gas chromatography with electron-capture and mass spectrometric detection. Journal of Chromatography A, 782, 105e122. Giza, I., & Sztwiertnia, U. (2003). Gas chromatographic determination of azoxystrobin and trifloxystrobin residues in apples. Acta Chromatographica, 13, 226e229. Gonzalez-Rodriguez, R. M., Rial-Otero, R., Cancho-Grande, B., & Simal-Gandara, J. (2008). Occurrence of fungicide and insecticide residues in trade samples of leafy vegetables. Food Chemistry, 107, 1342e1347. Grenzwerte für die gesundheitliche. (2006). Bewertung von Pflanzenschutzmittelrückständen. Aktualisierte Information Nr. 003/2008 des BfR vom 4. Januar 2006. . Guidelines for predicting dietary intake of pesticide residues (revised)1997. World Health Organization (WHO). Hajslova, J., & Zrostlikova, J. (2003). Matrix effects in (ultra)trace analysis of pesticide residues in food and biotic matrices. Journal of Chromatography A, 1000, 181e197. Hamilton, D. J., Holland, P. T., Ohlin, B., Murray, W. J., Ambrus, A., Baptista De, G. C., et al. (1997). Optimum use of available residue data in the estimation of dietary intake of pesticides. Pure and Applied Chemistry, 69, 1373e1410. Hernando, M. D., Aguera, A., Fernandez-Alba, A. R., Piedra, L., & Contreras, M. (2001). Gas chromatographic determination of pesticides in vegetable samples by sequential positive and negative chemical ionization and tandem mass spectrometric fragmentation using an ion trap analyzer. Analyst, 126, 46e51. Hu, R. W., Hennion, B., Urruty, L., & Montury, M. (1999). Solid phase microextraction of pesticide residues from strawberries. Food Additives & Contaminants, 16, 111e116. Ishimitsu, S., Kaihara, A., Yoshii, K., Tsumura, Y., Nakamura, Y., & Tonogai, Y. (2002). Simultaneous determination of azimsulfuron, flazasulfuron and halosulfuron methyl in grains, seeds, vegetables and fruits by HPLC. Journal of Health Sciences, 48, 335e340. Ismail, S. M. M., Ali, H. M., & Habiba, R. A. (1993). GCeECD and GCeMS analyses of prophenofos residues and its biochemical effects in tomatoes and tomato products. Journal of Agricultural and Food Chemistry, 41, 610e615. Kadenczki, L., Arpad, Z., & Gardi, I. (1992). Column extraction of residues of several pesticides from fruits and vegetables. A simple multiresidue analysis method. Journal of the Association of Official Analytical Chemists, 75, 53e61. Kaihara, A., Yoshii, K., Tsumura, Y., Ishimitsu, S., & Tonogai, Y. (2002). Multi-residue analysis of 18 pesticides in fresh fruits, vegetables and rice by supercritical fluid extraction and liquid chromatography-electrospray ionization mass spectrometry. Journal of Health Sciences, 8, 173e178. Kristenson, E. M., Haverkate, E. G., Slooten, C. J., Ramos, L., Vreuls, R. J., & Brinkman, U. A. (2001). Miniaturized automated matrix solid-phase dispersion extraction of pesticides in fruit followed by gas chromatographicemass spectrometric analysis. Journal of Chromatography A, 917, 277e286. Lehotay, S. J., Mastovska, K., & Lightfield, A. R. (2005). Use of buffering and other means to improve results of problematic pesticides in fast and easy method for residue analysis of fruits and vegetables. Journal of the Association of Official Agricultural Chemists International, 88, 615e629. Lehotay, S. J., de Kok, A., Hiemstra, M., & van Bodegraven, P. (2005). Validation of a fast and easy method for the determination of residues from 229 pesticides in fruits and vegetables using gas and liquid chromatography and mass spectrometric detection. Journal of the Association of Official Agricultural Chemists International, 88, 595e614. Lopes, W. G., & Dorea, H. S. (2003). Determination of pesticides in beans by matrix solid-phase dispersion (MSPD). Pesticides, 13, 73e82.

B. Łozowicka et al. / Food Control 25 (2012) 561e575 _ Ludwicki, J. K., & Kostka, G. (2008). Przekroczenia najwyzszych dopuszczalnych _ sci zg1aszane do oceny ryzyka poziomów pozosta1osci pestycydów w zywno zgodnie z procedurami RASFF w Polsce. Roczniki PZH, 59, 389e396. Luke, M. A., Froberg, J. E., & Masumoto, H. T. (1975). Extraction and cleanup of organochlorine, organophosphate, organonitrogen, hydrocarbon pesticides in produce for determination by gas chromatography. Journal of the Association of Official Analytical Chemists, 58, 1020e1026. qozowicka, B. (2009). Risk and threat for health consumers by pesticide residues from Polish north east crops. Ecological Chemistry and Engineering A, 16, 1327e1337. Mol, H. G. J., van Dam, R. C. J., & Steijger, O. M. (2003). Determination of polar organophosphorus pesticides in vegetables and fruits using liquid chromatography with tandem mass spectrometry: selection of extraction solvent. Journal of Chromatography A, 1015, 119e127. Morzycka, B. (2002). Multiresidue matrix solid-phase dispersion method for the determination of fungicides in fruits and vegetables. Analytical Chemistry, 46, 571e583. Nerin, C., Battle, R., & Cacho, J. (1998). Determination of pesticides in high-watercontent samples by off-line supercritical fluid extractionegas chromatographyeelectron-capture detection. Journal of Chromatography A, 795, 117e124. Oliver, G. R., Bolles, H. G., & Shurdut, B. A. (2000). Chlorpyrifos: probabilistic assessment of exposure and risk. Neurotoxicology, 21, 203e208. PPDB. (2011). Pesticide Properties DataBase. A to Z list of pesticide active ingredients. http://sitem.herts.ac.uk/aeru/footprint/en/ (03.10.2011). PSD. (2006). New intake calculation models for consumer intake assessments. http:// www.detergents.gov.uk/approvals.asp?id¼1687 (22.02.2011). Regulation of the Minister of Heath of 16.04.2004 on the maximum residue levels of chemical pesticides, which may be present in foodstuffs or on their surface. Journal of Laws No. 85, item. 801 as amended. Regulation of the Minister of Heath of 16.05.2007 on the maximum residue levels of chemical pesticides, which may be present in plant foods or on their surface. Journal of Laws No. 119, item. 817 as follows changes. Robak, J., & Gidelska, A. (2009). Epidemiology and new possibility of control of Plasmodiophora brassicae causal agent of clubroot of cruciferous crops in Poland. Progress in Plant Protection, 49, 268e274. Rodriguez, R., Pico, Y., Font, G., & Manes, J. (2002). Analysis of thiabendazole and procymidone in fruits and vegetables by capillary electrophoresiseelectrospray mass spectrometry. Journal of Chromatography A, 949, 359e366. Shuling, S., Xiaodong, M., & Chongjiu, L. (2007). Multi-residue determination method of pesticides in leek by gel permeation and solid phase extraction followed by gas chromatography with mass spectrometric detector. Food Control, 18, 448e453. Status of active substances under EU review. (2008). European food safety authority. http://ec.europa.eu/food/plant/protection/evaluation/index_en.print. htm (21.02.2011). Szponar, L., Sekula, W., Rychlik, E., O1tarzewski, M., & Figurska, K. (2003). Project Report TCP/POL/8921(A). The household food consumption and anthropometric survey in Poland, vol. 4 (pp. 1183e1186). The National Food and Nutrition Institute.

575

Tanaka, T., Hori, T., Asada, T., Oikawa, K., & Kawata, K. (2007). Simple one-step extraction and cleanup by pressurised liquid extraction for gas chromatographic-mass spectrometric determination of pesticides in green leafy vegetables. Journal of Chromatography A, 1175, 181e186. Torres, C. M., Pico, Y., Rosa, M., & Manes, J. (1997). Evaluation of organophosphorus pesticide residues in citrus fruits from the Valencian Community (Spain). Journal of the Association of Official Analytical Chemists, 80, 1122e1128. Ueno, E., Oshima, H., Saito, I., & Matsumoto, H. (2003). Simple one-step extraction and cleanup by pressurized liquid extraction for gas chromatographicemass spectrometric determination of pesticides in green leafy vegetables. Journal of the Association of Official Agricultural Chemists International, 86, 1241e1251. Ueno, E., Oshima, H., Saito, I., Matsumoto, H., Yoshimura, Y., & Nakazawa, H. (2004). Multiresidue analysis of pesticides in agricultural products by GCeECD after GPC and graphitized carbon column cleanup. Journal of the Association of Official Agricultural Chemists International, 87, 1003e1015. Valenzuela, A. I., Pico, Y., & Font, G. (2000). Liquid chromatography/atmospheric pressure chemical ionization-mass spectrometric analysis of benzoylurea insecticides in citrus fruits. Rapid Communications in Mass Spectrometry, 14, 572e577. Valverde-Garcia, A., Gonzales-Pradas, E., Aguilera-Del Real, A., & Urena-Amate, M. D. (1993). Determination and degradation study of chlorothalonil residues in cucumbers, peppers and cherry tomatoes. Analytica Chimica Acta, 276, 15e23. Valverde-Garcia, A., Fernandez-Alba, A. R., Contreras, M., & Aguera, A. (1996). Supercritical fluid extraction of pesticides from vegetables using anhydrous magnesium sulfate for sample preparation. Journal of Agricultural and Food Chemistry, 44, 1780e1784. Verhoeven, D. T. H., Goldbohm, R. A., Van Poppel, G., Verhagen, H., & Van den Brandt, P. A. (1996). Epidemiological studies on Brassica vegetables and cancer risk. Cancer Epidemiology, Biomarkers & Prevention, 5, 733e748. Wang, S., Xu, Y., Pan, C., Jiang, S., & Liu, F. (2007). Application of matrix solid-phase dispersion and LC-MS of fungicide residue analysis in fruits and vegetables. Analytical and Bioanalytical Chemistry, 387, 673e685. Wang, S., Yang, S., Ren, L., Qian, Ch., Liu, F., & Jiang, S. (2009). Determination of organophosphorus pesticides in leeks (Allium porrum L.) by GC-FPD. Chromatographia, 69, 79e84. Winter, C. K. (1992). Pesticide tolerances and their relevance as safety standards. Regulatory Toxicology and Pharmacology, 15, 137e150. Yang, R., & Chengguang, F. (1994). Matrix solid-phase dispersion and high performance liquid chromatographic determination of trace carbofuran in corn. Fenxi Ceshi Xuebao, 13, 72e75. Yen, I. C., Bekele, I., & Kalloo, C. (1999). Use patterns and residue levels of organophosphate pesticides on vegetables in Trinidad, West Indies. Journal of the Association of Official Agricultural Chemists International, 82, 991e995. Zamora, T., Pozo, O. J., Lopez, F. J., & Hernandez, F. (2004). Determination of triadimorph and other fungicide residues in fruit samples by liquid chromatographyeelectrospray tandem mass spectrometry. Journal of Chromatography A, 1045, 137e143. Zrostlikova, J., Hajslova, J., & Cajka, T. (2003). Evaluation of two-dimensional gas chromatographyetime-of-flight mass spectrometry for the determination of multiple pesticide residues in fruit. Journal of Chromatography A, 1019, 173e186.