Comparison of pesticides levels in grape skin and in the whole grape by a new liquid chromatographic multiresidue methodology

Analytica Chimica Acta 513 (2004) 333–340

Comparison of pesticides levels in grape skin and in the whole grape by a new liquid chromatographic multiresidue methodology Maria Joana Teixeira a , Ana Aguiar b , Carlos M.M. Afonso c , Arminda Alves a , Margarida M.S.M. Bastos a,∗ a

LEPÆ—Departamento de Engenharia Qu´ımica, Faculdade de Engenharia da Universidade do Porto, Porto, Portugal b CECA-ICETA—Faculdade de Ciˆ encias da Universidade do Porto, Porto, Portugal c CEQOFFLIP—Faculdade de Farmácia da Universidade do Porto, Porto, Portugal Received 11 July 2003; accepted 20 November 2003 Available online 20 January 2004

Abstract The increasing interest in the study of pesticides in grapes is justified from an enological point of view, since some pesticides can interfere with fermentative microflora used in wine production, as well as, with the consumer’ safety. Considering that washing grapes before consumption is the standard procedure, the study of the effect of washing on the residue concentration is required to assess real consumer exposure. In this work, pesticide mobility in grapes was studied, by comparing their residual concentration in the skin with that of the whole grape. The efficiency of water washing to remove pesticides from grape skins was also evaluated. One variety of grapes from the Northern region of Portugal, Trajadura, sampled at two maturation periods of the 2001 crop, were analysed by a new validated methodology involving liquid chromatography with diode array detection. It was concluded that, although there were no significant differences between some pesticide levels found in the whole grape (skin and pulp) and in the grape skin, pyrimethanil was preferably found in the pulp, while metalaxyl was detected in the skin but not in the whole grape. The removal of pesticides from grapes by washing did not exceed 70% (procymidone). Never the less, it was concluded that consumer intake of the pesticides from grapes studied in this work should be significantly decreased as a result of water washing of the grapes. The concentration levels found for the pesticide residues were below both the Portuguese and the FAO Maximum Residue Levels (MRLs), thus causing no problems in terms of food safety. © 2003 Elsevier B.V. All rights reserved. Keywords: Integrated pest management; Pesticide residues; Grapevine; HPLC-DAD

1. Introduction Grapevines are normally subject to fungi (Botrytis cinerea, Plasmopora viticola and Uncinula necator) or insects attacks (such as Lobesia botrana). For both, fungicides and insecticides are applied for crop protection purposes. In Portugal, about 25% of the total vine area (63000 ha of vineyards), are treated according to the Integrated Pest Management practices, meaning that the pesticides consumption is minimised in an ecological approach [1]. Although the mobility of pesticides from grape to wine is generally reduced [2] due to the winemaking process (crush-

∗

Corresponding author. Tel.: +351-225081648; fax: +351-225081449. E-mail address: [email protected] (M.M.S.M. Bastos).

0003-2670/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.aca.2003.11.077

ing, pressing, stabilisation, etc.), there is a need for rapid and reliable analytical techniques to control their residual levels in grapes, in order to verify their compliance with the Maximum Residue Levels (MRLs) [3,4]. The different modes of action of the phytosanitary products applied to vine may explain the different localisations and concentrations of their residue in the grape. While systemic pesticides are expected to be found in the pulp, the contact ones may be preferably located in the grape skin. Adjuvants, commonly used in commercial formulations, also have fundamental importance in pesticide penetration in grape tissues. As far as is known, no published data reports the levels found in the grape skin and the penetration of the pesticide in the grape. In previous work an analytical method to detect mainly fungicides and some insecticides in grape skin was validated [5].

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Pesticide residues are normally determined in the whole grapes, after appropriate solvent extraction or other similar techniques [6–11]. Following grape extraction, the chromatographic analysis may be performed by several instrumental techniques, depending on the family of the analytes, the need for low detection limits and the available instrumental resources [12]. However, if pesticides are thermolabile and thus destroyed in the injection port (as is flufenoxuron), liquid chromatographic techniques are advisable [5,13,14]. In this paper, a new analytical methodology to analyse 14 fungicides and insecticides mostly used in grapevines, accepted by Integrated Pest Management procedures [15] it is reported, employing liquid chromatography with diode array detection (LC-DAD). Validation parameters were obtained according to the European Norm ISO 17025 and global uncertainty associated to the analytical result was estimated (as described by Eurachem [16]). Furthermore, in order to inspect the pesticides’ fate after application, a comparative study between their levels in the whole grape and in the grape skin was achieved in this work. Additionally because the residual pesticide levels may be altered by water rinsing conditions [17], a comparative study before and after the washing procedure was performed. Table grapes have an important contribution in the human diet, so grape consumption may be one of the sources of pesticides residues intake. Data of the concentration level of pesticide residues in grapes are essential for the calculation of the theoretical maximum intake. Considering that washing grapes before consumption is the standard procedure, data about the effect of washing on the residue concentration is required to assess real consumer exposure.

2. Material and methods 2.1. Reagents and standards Thirteen fungicides (azoxystrobin, cymoxanil, fenhexamid, flusilazole, folpet, metalaxyl, ofurace, oxadixyl, procymidone, pyrimethanyl, tebuconazol, trifloxystrobin and vinclozolin) and one insecticide (phosalone) were used. Pesticide analytical standards were purchased from Riedel-de Häen (Buchs, Switzerland) and were >99% pure. Acetonitrile, methanol and dichloromethane were HPLC grade. These solvents were obtained from Riedel-de Häen. Stock standard solutions were prepared in acetonitrile and stored at −5 ◦ C in dark glass vials. Working standards solutions, with the concentrations mentioned in Table 1, were prepared daily in methanol–water (55:45, v/v) from individual stock solutions. The water was deionised and bidistilled. 2.2. Sampling procedure Grapes of the Trajadura variety were collected on two farms of the Northern Region of Portugal, where Vinho Verde is produced.

The grapes were collected in two maturation periods (half maturation—August; harvest date—September), in 2001. Sampling was performed according to rules usually accepted in this kind of study: (i) grapes collected were in the phenological stage, representative of the vineyard; (ii) the grapes were not affected by pests or abiotic factors. The grapes were transported to the laboratory in thermally conditioned bags and immediately frozen at −20 ◦ C. 2.3. LC apparatus and operation Chromatographic analyses were performed with a Merck Hitachi (Tokyo) system equipped with a L-7100 pump (Merck Hitachi), a Rheodyne injector (Rohnert Park, USA) Model 7725 (100 ␮l loop) and a diode array detector L-7450 A (Merck Hitachi). Data were acquired and processed using proper software (HSM D-7000, version 3.1). A reverse phase analytical column Macherey-Nagel (Duren, Germany) endcapped Superspher C18 , 250 mm × 4 mm i.d., 4 ␮m particle size, and Merck (Darmstadt, Germany) a guard column LiChrospher RP-18, 4 mm × 4 mm i.d. were used. The column temperature was 20 ◦ C. The separation of the selected pesticides was made by gradient elution. The mobile phase was methanol–water, at a flow-rate of 0.7 ml−1 min, with a composition gradient of methanol–water increasing from 55 to 90% (v/v) methanol over 22 min, then an increase to 100% of methanol over 7 min, and finally decreasing to 55% methanol over 5 min, giving a total run time of 34 min. The optimum detection wavelength was 207 nm. 2.4. Sample preparation The grapes were defrosted for 3 h and 100 or 25 g of intact berries was weighed, depending on the method to be used, for pesticides in grape skin (method 1) or pesticides in the whole grape (method 2), respectively. 2.5. Washing procedure Water 200 ml was added to a 600 ml beaker containing 100 g of whole grapes with the pedicel. The beaker was kept in the dark for 10 min. After water removal, the grapes were extracted differently according to the required analysis of grape skin (method 1) or whole grape (method 2). 2.6. Solvent extraction of pesticides in grape skin (method 1) Methanol (100 ml) was added to a 600 ml beaker containing 100 g of whole grapes with the pedicel. The beaker was kept in the dark for 5 min. The methanol solution obtained was filtered through glass wool (Riedel-de Häen). The filtrate was concentrated almost to dryness by rotary vacuum evaporation and the residue was redissolved in 25 ml of water–methanol (88:12, v/v). This solution was filtered through a VariDisk sterile nylon membrane filter of 45 ␮m

Table 1 Validation parameters and relative global uncertainty of the analytical methodologies

Cymoxanil Oxadixyl Ofurace Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin Tebuconazole Phosalone Trifloxystrobin a b c d

Linearity range (␮g ml−1 )

LODa (␮g ml−1 )

1.89–19.70 1.45–20.06 4.67–16.92 1.60–12.00 1.11–4.95 2.28–9.97 1.98–17.96 1.35–8.04 1.17–5.08 1.56–7.41 0.51–4.93 3.05–16.99 0.20–5.02 0.40–3.95

1.886 1.451 4.667 1.604 1.105 2.280 1.980 1.346 1.173 1.564 0.510 3.047 0.198 0.389

Method 1: grape skin (␮g ml−1 )

Method 2: whole grape

of working C standard solution

Precisionb

Recoveryc

(R.S.D.%)

(%)

9.85 10.03 8.46 6.00 2.48 4.99 8.98 4.02 2.54 3.70 2.47 8.50 2.51 1.98

0.71 13.37 14.90 16.25 17.69 15.06 6.73 24.37 19.37 35.31 5.76 1.05 15.12 17.63

86.89 108.86 91.64 121.70 89.85 82.65 87.19 57.85 82.53 91.79 62.69 67.15 31.73 48.60

LOD: limit of detection from the calibration graph. Precision: expressed by repeatability assays of six grape samples. Recovery: calculated from six grape samples spiked with working standard solution. U: estimated relative global uncertainty.

Precisionb (R.S.D.%)

Recoveryc (%)

(R.S.D.%)

C (␮g ml−1 ) of working standard solution

Ud (R.S.D.%)

23.1 21.4 27.3 26.4 26.3 27.7 24.0 36.0 26.5 27.2 31.7 29.0 58.9 43.8

14.78 15.04 15.01 7.47 3.71 7.48 13.47 4.44 3.81 5.55 3.70 12.75 14.88 2.96

42.15 32.15 8.17 19.74 20.08 5.41 28.72 9.62 3.44 12.93 15.78 21.19 26.44 10.80

40.98 28.10 99.76 71.63 114.40 86.12 37.42 52.26 62.12 34.52 43.06 62.39 40.93 20.16

49.5 67.1 21.6 29.2 20.3 23.6 53.0 37.3 31.5 54.6 44.7 32.5 40.5 88.7

Ud

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Pesticides

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pore size (Varian, Walnut Creek, CA), prior to solid phase extraction (SPE).

extracts obtained were evaporated to dryness by rotary vacuum evaporation, the residue was redissolved in 500 ␮l of methanol–water (55:45 v/v) and 100 ␮l were injected in the chromatograph.

2.7. Solvent extraction of pesticides in the homogenised whole grape (method 2)

2.9. Quantification

Methanol 25 ml was added to a 400 ml beaker containing 25 g of whole grapes. The grapes were homogenised with a blender for 2 min and transferred to a 250 ml Beckman centrifuge polypropylene tube (Beckman, Palo Alto, CA), then centrifuged in a AvantiTM Centrifuge J-25 (Beckman) (15 min, 10,000 rpm, 10 ◦ C). The liquid phase was filtered through a VariDisk sterile nylon membrane filter of 45 ␮m pore size (Varian) and added to water to complete a volume of 300 ml.

Pesticides were quantified by external standard calibration. The efficiency of the extraction was used to correct the final results, when needed. 3. Results and discussion In order to proceed to the comparison of the pesticide levels found in the grape skin or in the whole grape, two analytical methodologies were implemented, validated and used. Based on EN ISO 17025 criteria, the scope (range of analytes and sample matrix), specificity (interferences), limit of detection (LOD), the accuracy (by recovery from spiked samples), precision (repeatability of replicate analyses) and global uncertainty (according to the Eurachem-CITAC Guide [16]) were calculated.

2.8. Solid-phase extraction of the pesticides After solvent extraction by methods 1 or 2, a clean-up and pre-concentration step was utilised. Supelclean SPE cartridges (Supelco, Bellefonte, PA) containing 500 mg of C8 sorbent were used. The C8 cartridge was preconditioned with 6 ml of methanol and 6 ml of water. Then the prepared sample (25 ml—method 1; 300 ml—method 2) was percolated through the cartridge at Ca. 1 ml−1 min under negative pressure (−20 × 103 Pa). After the enrichment step, the cartridge was rinsed with 12 ml of water to clean-up the extract. Water was removed from the cartridge by passing dry air through it for about 60 min. Pesticides were eluted first with 5 ml of dichloromethane and after with 5 ml of methanol (method 1) or 15 ml of dichloromethane (method 2). The

9

Under the operational conditions detailed in Section 2, the chromatographic separation achieved is satisfactory (Fig. 1), with a 34 min run. Chromatograms for injected samples proved to be lacking in interferent peaks that co-eluted with the pesticides studied (Fig. 2).

N-Meth 0

100

14

3

60

8

15

1,0 40

Solvent (%)

6

80 17

7

4

1

Intensity (AU)

1,5

13

10 11

12

Sens 20

16

5

2,0

3.1. Validation of the analytical methodologies

2

0,5 20

0,0

0 0

5

10

15

20

25

30

Retention Time (min) Fig. 1. Chromatogram of the pesticide standard solution with an average concentration of 6.83 ␮g ml−1 (1, phthalimide; 2, cymoxanil; 3, oxadixyl; 4, ofurace; 5, metalaxyl; 6, azoxystrobin; 7, pyrimethanil; 8, folpet; 9, fenhexamid; 10, procymidone; 11, flusilazole; 12, vinclozolin; 13, tebuconazole; 14, phosalone; 15, trifloxystrobin; 16, flufenoxuron; 17, pyridaben).

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100

N-Meth 0 Sens 20

80

Intensity (AU)

1,0 0,8

60 17

0,6

40 12

0,4

20

8

5

3

0,2

Solvent (%)

1,2

0,0 -0,2

0 0

5

10

15

20

25

30

Retention Time (min) Fig. 2. Chromatogram of a sample of grape skin extract (Trajadura—19/09/01; 3, oxadixyl; 5, metalaxyl; 8, folpet; 9, fenhexamid; 12, vinclozolin; 17, pyridaben).

For calibration, linearity of the detector response (Table 1) ranged from 1 to 20 mg l−1 , on average, with correlation coefficients between 0.966 (metalaxyl) and 1.000 (phosalone). The repeatability of peak areas was also good, with relative standard deviation (R.S.D.) values ranging between 1.3% for folpet and 6.9% for pyrimethanil. Table 2 summarises the statistical parameters obtained when carrying out the linear regression and repeatability of peak areas for each of the pesticides. The analytical method proved to be sensitive enough to analyse the expected very small amounts of pesticide residues present in grape skin. LODs were 1.7 mg l−1 on average, representing 10.3 ␮g pesticide/kg of grapes (method 1) and 30.8 ␮g pesticide/kg of grapes (method 2), which is far below the legislated maximum residue levels (Table 6).

To evaluate accuracy, grape samples were spiked with a volume of working standard solution (500 ␮l—method 1; 250 ␮l—method 2) and processed according to the procedure described above. Recovery assays were replicated six times. Average recovery was 79.4±27.7% for method 1 and was 56.7 ± 27.8% for method 2. A lack of information about the global uncertainty, associated with sample results obtained by different analytical method, is common in the literature, making a reliable comparison between those methods difficult. A simple way to overcome the impossibility of making such comparisons, caused either by the absence of reference materials or by difficulties in finding available interlaboratory studies in specific areas, is through the estimation of the global uncertainty, following to Eurachem guide rules [16]. This

Table 2 Linearity [peak area = bC + a] and repeatability [R.S.D. (%), n = 4] of peak areas Pesticide

RT (min)

r

a ± (95%) CIa

b ± (95%) CIa

Cymoxanil Oxadixyl Ofurace Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin Tebuconazole Phosalone Trifloxystrobin

5.93 6.97 8.87 12.42 14.63 16.78 17.77 18.36 19.07 20.01 20.67 21.58 23.10 24.04

0.998 0.990 0.977 0.966 0.985 0.984 0.993 0.991 0.992 0.993 0.995 0.999 1.000 0.996

−48550 −656578 −472982 −889180 −300784 −247799 −486319 −658697 −298330 −328099 −453950 −199627 −228641 −87524

116060 378996 369483 641139 845536 521283 363428 986433 1013375 609169 1259091 270333 1031577 959725

a

± ± ± ± ± ± ± ± ± ± ± ± ± ±

90598 727753 929402 1409148 504485 640948 513741 504485 440125 513741 435234 143828 109940 231487

± ± ± ± ± ± ± ± ± ± ± ± ± ±

4645 30729 46412 99554 86299 54435 24172 86299 74348 24172 74962 7149 18558 49607

R.S.D. (%) 2.30 3.23 2.79 3.44 6.11 6.94 1.29 2.31 3.34 4.10 4.62 3.99 2.27 4.21

CI, confidence interval; RT, retention time; R.S.D. (%), relative standard deviation; C, concentration in ␮g ml−1 ; r, correlation coefficient (n = 6).

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Table 3 Contributions of the individual uncertainties of the standards (U1), calibration graph (U2), precision (U3) and accuracy (U4) to the relative global uncertainty of method 1 (U), according to the Eurachem/CITAC Guide [16]. Pesticide

U1

U2

U3

U4

U

Cymoxanil Oxadixyl Ofurace Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin Tebuconazole Phosalone Trifloxystrobin

0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008

0.056 0.103 0.160 0.198 0.131 0.133 0.085 0.098 0.093 0.089 0.075 0.040 0.023 0.066

0.157 0.172 0.131 0.033 0.081 0.082 0.022 0.042 0.117 0.039 0.014 0.053 0.064 0.087

0.224 0.180 0.213 0.161 0.217 0.235 0.223 0.332 0.235 0.212 0.307 0.287 0.585 0.392

0.231 0.214 0.273 0.264 0.263 0.277 0.240 0.360 0.265 0.272 0.317 0.290 0.589 0.404

calculation accounts for the most significant sources of uncertainty that are thought to affect the final result. In the present work, the greatest contributions to uncertainty were attributed to: preparation of standards (U1), the calibration graph (U2), precision (U3) and accuracy (U4). Expressing each term as a R.S.D. (Tables 3 and 4), it is concluded that the accuracy (as shown by recoveries from spiked samples) is the dominant source of global uncertainty in this study. This probably arises from the extraction procedures. The global uncertainty for method 1 was 30.7 ± 39.4% and for method 2 was 42.4 ± 19.2%. 3.2. The efficiency of the washing procedure In order to study the washing efficiency, similar experimental conditions, to those used before grape consumption were applied [17].

Table 4 Contributions of the individual uncertainties of the standards (U1), calibration curve (U2), precision (U3) and accuracy (U4) to the relative global uncertainty of method 2 (U), according to Eurachem/CITAC Guide [16] Pesticide

U1

U2

U3

U4

U

Cymoxanil Oxadixyl Ofurace Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin Tebuconazole Phosalone Trifloxystrobin

0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008

0.038 0.069 0.090 0.159 0.087 0.088 0.056 0.088 0.062 0.059 0.050 0.027 0.019 0.044

0.157 0.172 0.131 0.033 0.081 0.082 0.042 0.117 0.039 0.014 0.053 0.064 0.108 0.090

1.107 0.461 0.655 0.196 0.270 0.171 0.252 0.502 0.366 0.310 0.541 0.439 0.461 0.392

0.493 0.671 0.218 0.324 0.209 0.244 0.518 0.378 0.316 0.547 0.447 0.322 0.402 0.887

Table 5 Washing efficiency (%) of the pesticides in grape samples Pesticide

Cymoxanil Oxadixyl Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin Pyridaben

Solubility in watera (mg l−1 ) (20–25 ◦ C)

1 Log Kow (pH ≈ 7)

890 3400 8400 6.0 121 0.8 14 45 54 2.6 0.012

0.67 0.65 1.75 2.50 2.84 3.11 3.51 3.14 3.74 3.00 6.37

Washing efficiency (%) 22 August 2001

19 September 2001

33.30 46.88b – – 54.83 (2.61) – 69.72 (18.61)b – –

– (13.45) 40.95 – – 43.17 64.54 – – (29.00) (18.70)

( ): Values in parenthesis are referred to washing efficiencies below the estimated relative global uncertainty and therefore results may not be significant. a Data extracted from [18]. b Washing efficiency was calculated with the MDC value.

Results for the washing efficiency (calculated as the ratio between the concentration of the pesticide after and before the washing step) are very variable (Table 5). As was probably expected, the removal of pesticides by washing did not exceed 70% (procymidone). Several factors should be considered in the analysis of the washing efficiency, such as the estimated relative global uncertainty associated with the results, the variety of the grapes and the physicochemical properties of the compounds (solubility, octanol/water partition coefficient and hydrolysis). In Table 5, a decrease of the pesticide concentration by washing which was within the uncertainty associated with the result, is identified by brackets. This means that the measurement errors preclude drawing any conclusion about this data. Grapes from the same sample were used to evaluate the pesticides’ concentrations before and after washing, but differences may appear for each individual grape, due, for example, to its exposure to pesticide application in the vineyard, sun exposure, water feed in the plant and others. This is a non-quantifiable effect that was tried to be avoided by mixing the grapes. After analyzing the data obtained, it is suggested that the actual intake of the pesticides studied in this work by the consumer, is somewhat decreased if water washing procedures are used. 3.3. Mobility study of the pesticides in grapes After phytosanitary treatment, most pesticides deposit on leaves and fruits. Detection frequency and the detected quantity of the studied pesticides depend, among other factors, on the relationship between application date and sampling date, as well as on the applied concentration and chemical properties of the compounds. The most applied pesticide in the vineyard was cymoxanil and as expected, was the

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Table 6 Comparison between the pesticide residues found in grape skin (after and before washing) and the whole grape Pesticide

MDC (␮g/kg of grapes) Method 1

Cymoxanil Oxadixyl Ofurace Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin Tebuconazole Phosalone Trifloxystrobin

10.85 7.00 25.46 8.52 6.15 13.79 11.37 11.63 7.11 8.52 4.11 22.68 3.12 4.12

C (␮g/kg of grapes) Trajadura (August 2001) Method 2

46.03 51.63 46.78 22.39 9.66 26.47 52.91 25.76 18.88 45.31 11.84 48.84 4.84 19.30

C (␮g/kg of grapes) Trajadura (September 2001)

Whole grape

Grape skin Before washing

After washing

415.09 298.98 n.a. n.a. 26.40 283.16 n.d. n.a. 184.11 n.d. n.a. n.a. n.a. n.a.

18.26 13.17 n.a. n.a. n.d. 14.28 14.94 n.a. 17.24 10.47 n.a. n.a. n.a. n.a.

12.18 n.d. n.a. n.a. n.d. 6.45 14.55 n.a. 5.22 n.d. n.a. n.a. n.a. n.a.

MRL on grapes (␮g/kg of grapes)

Whole grape

Grape skin Before washing

After washing

305.10 334.46 n.a. n.d. n.a. n.a. n.d. 223.07 n.a. n.a. 62.43 n.a. n.a. n.a.

n.d. 17.69 n.a. 17.02 n.a. n.a. 24.09 42.24 n.a. n.a. 5.38 n.a. n.a. n.a.

n.d. 15.31 n.a. 10.05 n.a. n.a. 13.69 14.98 n.a. n.a. 3.82 n.a. n.a. n.a.

Portugal

FAO

100 1000 200 1000 2000 5000 10000 w 5000 500 5000 2000 1000 w

w w w 1000 w w 2000 w 5000 500 5000 w w w

MDC: minimum detectable concentration in the sample; MRL: maximum residue level; w: no MRL; n.d.: not detected; n.a.: not applied in vineyards. Table 7 Comparison of the pesticide levels found in the grape skin and in the whole grape Pesticide

Cymoxanil Oxadixyl Metalaxyl Azoxystrobin Pyrimethanil Folpet Fenhexamid Procymidone Flusilazole Vinclozolin

Action mode

Systemic Systemic Systemic Systemic Contact Contact Contact Systemic Systemic Contact

Trajadura (August 2001)

Trajadura (September 2001)

Date of last application

Whole grape

Grape skin

% in grape skin

Date of last application

Whole grape

Grape skin

% in grape skin

19 July 2001 17 May 2001 n.a. 11 June 2001 20 August 2001 18 August 2001 n.a. 28 August 2001 19 July 2001 n.a.

415.09 298.98 n.a. 26.4 283.16 n.d. n.a. 184.11 n.d. n.a.

18.26 13.17 n.a. n.d. 14.28 14.94 n.a. 17.24 10.47 n.a.

4.40 4.40 n.a. 0.00 5.04 –

27 July 2001 29 May 2001 15 June 2001 n.a. n.a. 16 June 2001 29 August 2001 n.a. n.a. 8 August 2001

305.10 334.46 n.d. n.a. n.a. n.d. 223.07 n.a. n.a. 62.43

n.d. 17.69 17.02 n.a. n.a. 24.09 42.24 n.a. n.a. 5.38

0.00 5.29 – – – – 18.94 – – 8.62

most frequently detected one. Table 6 clearly shows those situations when the pesticide was not applied to vine (n.a.) or, when applied, not detected (n.d.). All the pesticide levels found in grapes were considerably below the maximum residue level (MRL) set for grapes, except for cymoxanil, but the results should be analysed with regarding to the uncertainty of the methodology. Pesticides can be adsorbed by grape skin or penetrate the epicuticular wax and subsequently the cuticle layer [2]. Lipophilicity and concentration of the active ingredient are the driving forces in this transfer, but adjuvants in commercial formulation and grape skin constitution may also interfere. The mobility of pesticides in grapes is difficult to discuss, because other factors rather than pesticides actuation mode, such as the time gap between application and sampling, may interfere. Systemic pesticides as oxadixyl were preferably found in the pulp, while contact ones such as folpet were

9.36 – –

detected in the skin but not in the whole grape (Table 7). So a correlation between each pesticide’s mode of action and its preferential localisation—skin or pulp—could be found in all cases except for fenhexamid, pyrimethanil and vinclozolin. The unexpected high level of these contact fungicides in the whole grape can be explained by the existence of micro-fissures in skin due to pest or abiotic damages, which is normal in grapes during the maturation period, allowing the penetration of pesticide into the grape.

4. Conclusions Two analytical methods were implemented, validated and used with the Objective of comparing the pesticide levels found in the grape skin and in the whole grape. Polar compounds, as ofurace, metalaxyl, azoxystrobin, pyrimethanil and miclobutanil, are more suitably determined by method

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2, while cymoxanil and oxadyxil may be prone to matrix interferences, thus requiring special attention and additional confirmation procedures. The main validation parameters of the two analytical methodologies, to analyse for pesticides in grape skin and in the whole grape, were obtained and compared: the total run time of an analysis is 34 min; the average LOD is 1.7 mg l−1 , which corresponds to 10.3 mg kg−1 (method 1) or 30.8 mg kg−1 (method 2), which is acceptable taking into account the MRLs for grapes; the average recovery was 79.4 ± 27.7% for method 1 and 56.7 ± 27.8% for method 2; the global uncertainty for method 1 was, on average, 30.7 ± 39.4% and for method 2 was 42.4 ± 19.2%. The removal of pesticides by water washing did not exceed 70% (procymidone). Consumer intake of the pesticides studied in this work from grapes should be significantly lowered due to the decrease in pesticide residues concentration by water washing. The mobility of pesticides in grapes is difficult to discuss, because other factors rather than the pesticides actuation mode, such as time gap between application and sampling may also have an effect. Systemic pesticides such as oxadixyl were preferably found in the pulp, while contact pesticides such as folpet were detected in the skin but not in the whole grape. The concentration level (± the uncertainty of the result) found for the pesticide residues was below both the Portuguese and the FAO MRLs, thus causing no problems in terms of food consumption.

Acknowledgements This work has been supported by FCT: Project POCTI/ 1999/AGR/34591. The authors also acknowledge the agronomic data and facilities to harvest grapes provided by EVAG-CVRVV.

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