Compensation for matrix effects in gas chromatography–tandem mass spectrometry using a single point standard addition

Journal of Chromatography A, 1216 (2009) 4798–4808

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Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma

Compensation for matrix effects in gas chromatography–tandem mass spectrometry using a single point standard addition Antonia Garrido Frenich ∗ , José Luis Martínez Vidal, José Luis Fernández Moreno, R. Romero-González Research group “Analytical Chemistry of Contaminants”, Department of Analytical Chemistry, University of Almería, 04120 Almería, Spain

a r t i c l e

i n f o

Article history: Received 23 October 2008 Received in revised form 31 March 2009 Accepted 8 April 2009 Available online 15 April 2009 Keywords: Standard addition calibration Matrix effect Pesticide Gas chromatography Tandem mass spectrometry Triple quadrupole analyser

a b s t r a c t One of the major problems in quantitative analysis of pesticide residues in food samples by gas chromatography–tandem mass spectrometry (GC–MS/MS) is the enhancement or the suppression, of the target analyte signals in matrix extracts. Potentially positive samples, which had previously been identified by a rapid screening method, were quantified using standard addition to compensate matrix effects. As example we performed a systematic study on the application of the standard addition calibration (SAC) method for the determination of 12 pesticides (acephate, bromopropylate, chlorpyrifos, cypermethrin, diazinon, etrimfos, heptenophos, iprodione, methamidophos, procymidone, tetradifon, and triadimefon) in two matrices (cucumber and orange) in the range of initial concentrations of 10–200 ␮g kg−1 . The influence of some factors, such as the minimum number of standard additions used (single, two, three or four points calibration), as well as the known amount of analyte added to the sample, is evaluated in order to obtain reliable results. Accurate quantification is achieved when a single point SAC at 200 ␮g kg−1 was used, obtaining for all the cases recoveries between 70 and 120%. The proposed analytical approach only needs two injections per sample (blank and spiked extracted sample) to determine the final concentration of pesticide in positive samples. © 2009 Elsevier B.V. All rights reserved.

1. Introduction Gas chromatography (GC) is one of the most used analytical techniques for determining multiclass pesticides in one single run in vegetables. The most used detectors in GC, electron capture detector (ECD), nitrogen–phosphorus detector (NPD), flame photometric detector (FPD) or mass spectrometry (MS), even in the tandem (MS/MS) mode, are prone to detect coextracted matrix components that may lead to an enhancement of the chromatographic signal [1,2] or to a diminishment of the response of the target analyte [3] in relation to the signal in pure solvent. Matrix-induced response enhancement was correctly explained by Erney et al. [4,5] and Gillespie et al. [6]. They propose that coextracted matrix components compete with the target pesticides to access to the active site of the GC system (inlet and column), and also protect them from the decomposition in the hot injector. Matrix-induced response diminishment occurs when non-volatile coextracted matrix components, accumulated into the gas chromatographic system, help to the generation of new active sites. In both cases, the obtained signals from a standard solution in pure solvent and in blank extracts (matrix standards) may be significantly different, so matrix effects must be taken into account to obtain quantitatively accurate results.

∗ Corresponding author. E-mail address: [email protected] (A. Garrido Frenich). 0021-9673/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2009.04.018

Several approaches have been proposed to reduce matrix effects during the determination of pesticides in food commodities. The most obvious strategy is the reduction of the amount of matrix components entering the gas chromatographic system, for instance by application of sample extract clean-up steps [1,5–10]. Most routine laboratories tend to avoid these clean-up procedures because they are time consuming, they can increase the risk of analyte losses or sample contamination, and in consequence the uncertainty of the results can be higher. Other ideal approach to eliminate the matrix enhancement would be the use of inert surfaces in the GC system, but current materials still contain active sites. The use of different injection techniques, such as pulsed splitless, on-column or programmed temperature vaporizer (PTV), sometimes with a plug of carbofrit inserted in the glass liner, can diminish matrix effect but not eliminate it [2,10–14]. Likewise, dirty sample injection (DSI), also named direct sample introduction [15,16], or its commercially automated form called difficult matrix introduction (DMI) [17,18], have been also tested with the purpose of avoiding that the nonvolatile compounds enter in the chromatographic system, but the total elimination of sample components is not possible. An alternative strategy to reduce matrix effects is their compensation using appropriate calibration methods. In this sense the approaches can be classified in two groups: those based on the use of calibration standards in pure solvent, and those based on the use of standards in matrix. The current compensation methods that belong to the first group include the use of: (i) correction

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factors and (ii) analyte protectants. The use of correction factors compensates matrix effects by the transformation of the results for each vegetable matrix after quantitation with a calibration curve prepared in pure solvent [19,20]. A drawback of the correction factors is its dependence of the stability of the chromatographic system, so they should be periodically estimated, which is a time consuming approach. On the contrary, the addition of appropriate additives to the standards in pure solvent and samples is a promising approach to avoid matrix effects by blocking active sites in the injector [18,21–24], although its robustness in routine analysis should be tested. On the other hand, the main compensation approaches based on the use of calibration standards in matrix imply the use of: (i) isotopically labelled standards, (ii) matrix matched standards and (iii) standard addition method. Currently, only a reduced number of isotopically certified pesticide standards is available, and they are expensive [7]. In contrast, matrix matched standards are often used [10,12,13,25–27], in spite of their disadvantages including the laborious preparation of the standards in matrix and the availability of an appropriate blank matrix (ideally the same as the sample). This last aspect can be overcome in routine analysis laboratories by the selection of a representative matrix for calibration purposes [28,29]. In this sense, guidance SANCO [30] on residue analytical method classifies the foods of plant origin in four groups: high water, acid or fat content and the last group is formed by cereals and other dry crops. Finally, standard addition is a cheap and useful approach when there is no blank matrix to carry out the calibration. Standard addition calibration (SAC) introduces known amounts of analyte(s) into aliquots of sample extracts containing the target compound(s), so any coextracted impurity is accounted in the calibration, bearing in mind that the volume of standard added must be small enough to avoid dilution of sample extracts [31]. Using this methodology, the unknown concentration initially present in the sample is calculated by extrapolation. It is worthwhile to point out that the more important aspect of standard addition is that calibration is always carried out in the sample matrix. Obviously it is time consuming for standard preparation [32], although this disadvantage can be overcome if the method is used for quantification of potentially positive samples, previously identified by a screening method [33,34]. In fact, accurate quantification of pesticides is only required when the amount detected is expected to exceed the maximum allowable residue level. Despite all these features, only very few researchers have reported the application of the SAC for the quantification of pesticides by GC–MS [26,34–36], and no systematic studies on the application of this methodology in pesticide residues analysis in food commodities by GC–MS/MS have been carried out so far. This study considers the application of the SAC for the quantification of 12 pesticide residues in two matrices, cucumber and orange, representatives of crops with high water and acid content respectively, analysed by GC–MS/MS. Samples had been previously analysed using a screening method [34]. In this paper, different factors such as the number of sample standard additions used and the known amounts of analyte added to the sample have been evaluated in order to obtain reliable results but minimizing experimental work. 2. Experimental 2.1. Standards and reagents Acephate, bromopropylate, chlorpyrifos, cypermethrin, diazinon, etrimfos, heptenophos, iprodione, methamidophos, procymidone, tetradifon, triadimefon and the Internal Standard (IS), caffeine, were supplied from Dr. Ehrenstorfer GmbH (Augsburg, Germany). Pesticide-quality solvents (cyclohexane, acetone and

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ethyl acetate) and anhydrous sodium sulphate (instrumental analysis quality) were supplied by Panreac (Barcelona, Spain). Stock standard solutions of individual compounds (with concentrations between 400 and 550 ␮g mL−1 ) were prepared by exact weighing of the powder and dissolution in 100 mL of acetone, which were then stored in a freezer (−30 ◦ C). A multicompound working standard solution (2 ␮g mL−1 concentration of each compound) was prepared by appropriate dilutions of the stock solutions with acetone and stored under refrigeration (4 ◦ C). 2.2. Sample preparation Blank cucumber and orange samples were bought in organic greengrocers in Almeria (Spain). 2 kg mass of vegetable or fruit sample were chopped and initially homogenized by using a kitchen blender Braun MX32 (Barcelona, Spain). An aliquot of 15 g was exactly weighed, using an analytical balance AB204-S from Mettler Toledo (Greifensee, Switzerland), into a 100 mL glass flask, and 50 mL of ethyl acetate and 10 g of anhydrous sodium sulphate were added. The mixture was homogenized using a Polytron® benchtop homogenizer (Kinematica AG, Luzern, Switzerland) at 20,000 rpm for 2 min. The extract was filtered through a porous plate funnel to a spherical flask. Evaporation of the solvent to a small volume (1–2 mL) was done in a rotary evaporator R-114 (Büchi, Flawil, Switzerland) at 40 ◦ C of bath temperature, and then the extract was taken to nearly dryness under a soft nitrogen stream. The residue was re-dissolved in 5 mL of a cyclohexane solution containing 0.5 ␮g mL−1 of caffeine used as IS. Aliquots of 1 mL of this solution were added to a 2 mL volumetric flask. The final 2 mL volume was made up with cyclohexane. Aliquots (10 ␮L) of this extract were injected into the GC–MS/MS system. 2.3. Instrumental analysis GC–MS analysis was performed with a Varian 3800 gas chromatograph with electronic flow control (EFC) and fitted with a Varian 1200 L triple quadrupole mass spectrometer. Samples were injected with a Combi Pal (CTC Analytics AG, Zwingen, Switzerland) using a 100 ␮L syringe, into an SPI/1079 split/splitless programmed temperature injector operated in the large volume injection technique. The glass liner was equipped with a plug of carbofrit (Restek, Bellefonte, PA, USA). The injector temperature program started at 70 ◦ C (hold for 0.5 min) and then was increased with a rate of 100 ◦ C min−1 until 310 ◦ C (hold for 10 min). The injector split ratio was initially set at 20:1. Splitless mode was switched on at 0.5 min until 3.5 min. At 3.5 min, the split ratio was 100:1 and at 10 min, 20:1. At the beginning of the injection, column temperature was set at 70 ◦ C (hold for 3.5 min), later the temperature was increased until 180 ◦ C at a 50 ◦ C min−1 rate and then until 300 ◦ C (hold 10 min) at a rate of 25 ◦ C min−1 . A cryogenic cooling with CO2 was applied when the injector temperature was 170 ◦ C in order to reach the initial injector temperature as fast as possible before continuing with the next injection. A fused silica untreated capillary column 2 m × 0.25 mm i.d. from Supelco (Bellefonte, PA, USA) was used as guard column connected to a Factor Four Capillary Column VF5ms analytical column (30 × 0.25 mm i.d. × 0.25 ␮m film thickness) from Varian Instruments (Sunnyvale, CA, USA). The triple quadrupole mass spectrometer (QqQ) was operated in the selected reaction monitoring (SRM) mode. The temperatures of the transfer line, manifold and ionization source were set at 280, 40 and 250 ◦ C, respectively. The analysis was performed with a filament-multiplier delay of 4.5 min in order to prevent instrument damage. The electron multiplier voltage was set at 1600 V (+200 V offset above the auto-tuning process). The scan time was 0.35 s. Mass peak widths set in the first and third quadrupole were of 1.5 and 2.0 m/z, respectively.

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Table 1 Concentrations used in the standard addition study. Level

Initial concentration (␮g kg−1 )

Approach 1: added concentration (␮g kg−1 )

Approach 2: added concentration (␮g kg−1 )

A

10 10 10 10

20 30 40 50

20 50 100 200

B

20 20 20 20

40 60 80 100

20 50 100 200

C

50 50 50 50

100 150 200 250

20 50 100 200

D

100 100 100 100

200 300 400 500

20 50 100 200

E

200 200 200 200

400 600 800 1000

20 50 100 200

2.4. Standard addition calibration Two sets of experiments were performed to study the SAC in two matrices, cucumber and orange, in the range of 10–200 ␮g kg−1 of initial concentration of pesticide in the sample. The sample preparation was done in the same way as described before. After extraction, 1 mL aliquots of the spiked blank sample were transferred to separate 2 mL volumetric flask, and different volumes of the standard multicompound solution of the target analytes were added in the concentration range between 10 and 1000 ␮g kg−1 . In the first set (approach 1), the sample extracts were spiked with concentrations that were multiple (2, 3, 4 and 5 times) of the initial concentration (10, 20, 50, 100 and 200 ␮g kg−1 ) in the sample (see Table 1 for more details). In the second set (approach 2), the sample extract were spiked with concentrations multiple of the lowest maximum residue level (MRL) (10 ␮g kg−1 ) established in the selected matrices (Table 1).

2.5. Long-term stability study The analytical response of the GC equipped with a PTV injector and a carbofrit plug was studied when successive injections where performed in matrix-matched standard solutions. Blank samples of cucumber and orange were extracted as described above. Matrix-

matched and external calibrations were prepared from 10 to 200 ␮g kg−1 . After GC maintenance (replacing the glass insert with carbofrit and the retention gap), a sequence of 300 injections of matrix-matched standard solution in cucumber extracts were analysed. External and matrix-matched calibration in cucumber and orange extracts were injected at the beginning of the sequence, and after 50, 150, and 300 successive injections. Long-term stability of the analytical signal was studied for those pesticides which presented the largest matrix-induced chromatographic response enhancement. The application of the SAC was also evaluated for the quantification of spiked cucumber sample at 50 ␮g kg−1 after 50, 150 and 300 injections.

2.6. Analysis of samples Samples were extracted as described in Section 2.2, and 10 ␮L aliquots of these extracts were injected into the GC–MS/MS system and analysed with a screening method [34]. The method monitors only one MS/MS transition of the compounds previously identified by its retention time (Table 2). Furthermore, a conservative cutoff around 7 ␮g kg−1 (30% below the lowest MRL) has been established, corresponding to relative peak area of the analyte to IS (Table 2). Samples that do not fulfil these requirements were classified as negative, and the rest were considered as potentially positives. These

Table 2 Retention times, MS/MS parameters and relative area of the pesticides at the conservative cutoff value (7 ␮g kg−1 ), in cucumber and orange. Pesticide

Retention time (min)

Parent ion, m/z

Product ions, m/z (collision energy, V)

Acephate Bromopropylate Chlorpyrifos Cypermethrin Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

7.87 15.80 11.70 18.30 10.10 10.37 8.62 15.61 6.86 12.66 16.35 11.91

136 341 314 163 179 292 215 314 141 283 227 208

42 (10), 94 (20), 136a (5) 155 (40), 185a (20) 258a (20), 286 (10) 91a (20), 127 (10) 121a (30), 137 (20) 152 (20), 181a (10) 200 (5), 89a (15) 271 (10), 245a (10), 162 (20) 95a (10), 79 (15), 64 (20) 96a (10), 255 (10) 164 (30), 199a (20) 111a (20), 181 (10)

a

Screening transition.

Relative area at the conservative cutoff value Cucumber

Orange

0.0364 0.0215 0.0230 0.0083 0.0119 0.0037 0.0008 0.0003 0.0032 0.0066 0.0029 0.0132

0.0406 0.0285 0.0278 0.0073 0.0183 0.0041 0.0016 0.0003 0.0030 0.0091 0.0046 0.0095

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last samples were reanalysed to confirm the results obtained by the screening method (monitoring two or three MS/MS transitions by compound (Table 2), and quantified by the SAC. For this purpose, 200 ␮g kg−1 of the pesticide(s) previously confirmed, were added to a new aliquot of the sample extract. 3. Results and discussion Although the extraction procedure has already been validated [37], it was observed the presence of matrix effects that provokes the presence of systematic errors during the measurement step. In order to avoid the presence of these errors, the applicability of SAC was evaluated in this paper, bearing in mind the reduced number of available isotopically labelled standards, and the differences in the matrix effect within a given matrix when matrix-matched calibration was applied. For that purpose, the analytes were added after sample treatment, in order to correct the matrix effect occurring in the GC–MS system. Furthermore, for the evaluation of standard addition methodology two several matrices (cucumber and orange), with high water and acid content were selected, taking into account that they are very common in the Southeast of Spain. 3.1. Preliminary studies Routine laboratories of pesticide residues in foods usually have to analyse several types of sample extracts, which belong to different classes of representative matrices [32], in the same injection sequence. In this situation, if matrix-matched calibration is used for quantification purposes a calibration per representative matrix should be carried out, increasing the total analysis time, and therefore decreasing sample throughput, which is one of the most important factors to be considered when an analytical method is applied in routine analysis. Besides, this method can also leads to inaccuracy results because the final value can be dependent on the sample matrix, and the use of a representative matrix or even a

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blank sample from the same matrix is not easy. In addition, routine laboratories only need an accurate quantification for the pesticides presenting in the sample at concentration higher than the established MRLs. All these drawbacks can be overcome applying the SAC to quantify only potentially positive samples, which are previously analysed by a screening approach. For this study, the selected pesticides belong to different classes, such as, organophosphorous (acephate, chlorpyrifos, diazinon, etrimfos, heptenophos and methamidophos), dicarboximides (iprodione and procymidone), pyrethroids (cypermethrin), benzilates (bromopropylate), organochlorines (tetradifon) and triazoles (triadimefon). These pesticides have been previously reported to present matrix-induced chromatographic response enhancement and, therefore an overestimation of the recovery rates exceeding the 100% value takes place when they are determined in vegetable samples [2]. Most of the studied pesticides are mainly organophosphorous, since they present a polar group, which makes them prone to be retained in the active sites of the injection port [11]. The application of the SAC requires a linear response of the pesticides, at least in a narrow range. The linearity was studied in the range 10–1000 ␮g kg−1 , being the lower calibration range more interesting because it is close to MRLs for the assayed pesticides. The first calibration level was always equal to the minimum MRL (10 ␮g kg−1 ) set for the analysed pesticides. Fig. 1 shows the calibration curves for the target pesticides obtained by least-squares regression, using relative peak area (analyte/IS) as analytical response when external and matrix-matched standard solutions in cucumber and orange extracts are injected in the GC system. The determination coefficients were always higher than 0.96, except for methamidophos and heptenophos, with values of 0.90 and 0.94 for the external calibration, respectively and test for linearity was based on the analysis of the residual variance from a regression into parts due to “lack of fit” and “pure error”. Furthermore, solvent and matrix blanks were not significantly different from zero. In consequence, the influence of the intercept in the linear model was negligible.

Fig. 1. Calibration curves for the target pesticides in orange, cucumber and solvent, in the range 10–1000 ␮g kg−1 .

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Fig. 2. Evolution of the slope of the calibration curves for iprodione, methamidophos and iprodione in cucumber and orange extracts after 50, 150 and 300 injections into the GC system. Error bars indicate the standard deviation (n = 3).

On the other hand, the plots show that the analytical response is increased when matrix-matched calibration is used, and additionally, orange standards always presented a larger signal enhancement. These extracts contain higher amounts of matrix components than cucumber ones, which are prone to be retained in the active sites of the glass liner as well as the acidity of the orange can act as protectant during extraction process and GC analysis [38]. Methamidophos, heptenophos, acephate and iprodione were pesticides which showed greater matrix effect. Bromopropylate, etrimphos, tetradifon and triadimefon were as well affected, but to a lesser extent. Chlorpyrifos, cypermethrin, diazinon and procymidone presented a special behaviour. The analytical response was only affected when matrix-matched standard solutions in orange extracts were analysed (signal enhancement), whereas matrixmatched standard solutions in cucumber extracts showed similar response to the external standard solutions. 3.2. Stability of matrix effect It is well known that the matrix-induced response enhancement is mainly caused by matrix participation in the transfer of pesticides from vaporizing injectors to the head of column. The co-injected matrix compounds are mainly retained in the injector port and in the first part of the column, but they can also be transferred to the ion source to a lesser extent. Initially, matrix molecules are retained in the active sites of the walls of the injector and the retention gap, leading to an increase in the number of analyte molecules reaching the column as well as the analytical response. However, the successive accumulation of non-volatile compounds increases the number of active sites. This provokes a gradual decrease in the analyte response, and in the analytical resolution, so the linearity could be changed and the sensitivity should be decreased within a long sequence. These effects depend on the type of matrix and analyte, as well as on the concentration level, and they should be evaluated during routine analysis. For this purpose, a long sequence of blank cucumber injections was run. External and matrix-matched calibrations (n = 3, for each concentration level) in cucumber and orange extracts were initially injected (just after GC maintenance), and after 50, 150 and 300 of successive injections of blank cucumber. Fig. 2 shows the evolution of the slope value for methamidophos, iprodione and heptenophos, which were the pesticides with most enhanced analytical response when matrix-matched calibration was used. It can be observed that for the selected compounds, sensitivity (slope) was reduced when the number of injections increased. However, for iprodione, matrix effect (matrix–solvent slope ratio) was maintained up to 150 injections, and after that, it was reduced. On the other hand, the matrix effect for methamidophos was maintained up to 50 injections, and after that, the matrix–solvent slope ratio increased and it was kept constant to the end of the sequence. Finally, heptenophos showed a higher matrix enhancement in orange extracts, decreasing gradually, although for cucumber, it was constant through the

assayed sequence, indicating that matrix effect was kept constant. Furthermore, the analytical response was decreasing and after 300 injections, it was reduced considerably, and the first calibration point (10 ␮g kg−1 ) was not properly detected, so the sequence should be stopped and a GC maintenance should be done. In general, the rest of the compounds showed a common behaviour. Both, the matrix effect and the analytical response were increased up to 50 injections, and afterwards, a gradual decrease was registered up to the end of the sequence, except for heptenophos in orange, where matrix effect decreased from initial to 150 injections. The robustness of the SAC methodology was also evaluated during the injected sequence. A spiked cucumber sample at 50 ␮g kg−1 was quantified by means of the SAC when 200 ␮g kg−1 of the multicompound standard solution were added to the sample extract after 50, 150 and 300 of successive injections. Accurate results were obtained during the complete sequence for all the pesticides with recovery rates in the range 73–114%. 3.3. Standard addition calibration studies When the SAC methodology was applied for quantification purposes, two main parameters must be optimised: concentration and number of the added levels. These factors were evaluated using two approaches, according to Section 2. When the first approach was used, the added concentration was multiple of the sample one (2, 3, 4 and 5 times the sample concentration). However, when the second approach was applied, fixed concentration levels were added to the sample (20, 50, 100 and 200 ␮g kg−1 ), bearing in mind that the added concentration was multiple of the lowest MRL (10 ␮g kg−1 ). Both approaches were studied selecting one, two, three and four points for the calibration procedure, apart from the zero level, which is always necessary when SAC is used. Furthermore, the influence of the added concentration and number of levels were studied in two matrices, cucumber and orange, at different initial concentrations in the sample (10, 20, 50, 100 and 200 ␮g kg−1 ). In order to assure the reliability of the obtained results it has been checked that the calibration function was linear in the concentration range evaluated and the blank signal was null in that concentration range [39]. For the quantification process, when one-point calibration was used, the sample amount is obtained using Csample = Cadded ×

Ssample Ssample+added − Ssample

(1)

where Csample is the initial concentration in the sample, Cadded is the added concentration to the sample, Ssample is the signal of the sample, and Ssample+added is the signal which corresponds to the sample with the added concentration. If more than one point was used for calibration purposes, conventional least square regression was applied bearing in mind that at least three points were used (zero level plus the two added concentrations). In both approaches, three aliquots of spiked samples were analysed and an average value and relative standard deviation (RSD)

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Table 3 Estimated recoveries (in %) in cucumber (and orange) using approach 1. Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

20a

30a

40a

50a

20 + 30a

20 + 30 + 40a

20 + 30 + 40 + 50a

107 (87) 84 (91) 102 (118) 88 (85) 81 (98) 77 (85) 110 (87) 87 (98) 106 (94) 88 (92) 85 (108) 97 (105)

115 (90) 83 (86) 99 (110) 86 (83) 80 (89) 77 (82) 115 (89) 84 (86) 99 (88) 86 (88) 79 (101) 93 (101)

120 (85) 85 (88) 102 (110) 90 (86) 83 (93) 83 (84) 120 (87) 94 (98) 106 (87) 91 (90) 78 (110) 99 (104)

104 (87) 81 (95) 102 (120) 86 (89) 78 (102) 73 (86) 109 (88) 80 (102) 103 (96) 86 (96) 82 (112) 95 (107)

111 (94) 76 (93) 96 (116) 80 (90) 73 (94) 70 (81) 112 (94) 70 (86) 89 (87) 80 (94) 70 (106) 87 (103)

124 (87) 80 (94) 100 (115) 86 (95) 78 (99) 80 (84) 123 (92) 78 (101) 96 (81) 86 (96) 51 (120) 95 (108)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

10

119 (85) 92 (79) 103 (105) 94 (77) 89 (84) 87 (83) 119 (83) 110 (87) 117 (90) 95 (81) 93 (96) 103 (98)

Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

40a

60a

80a

100a

40 + 60a

40 + 60 + 80a

40 + 60 + 80 + 100a

136 (93) 97 (93) 119 (98) 106 (97) 105 (99) 106 (97) 117 (90) 99 (90) 117 (82) 103 (96) 91 (101) 114 (105)

120 (93) 90 (88) 110 (90) 97 (92) 96 (95) 95 (92) 110 (90) 91 (87) 108 (82) 95 (94) 83 (96) 101 (99)

107 (89) 82 (86) 107 (92) 91 (91) 90 (93) 94 (92) 110 (87) 91 (85) 108 (79) 91 (91) 75 (94) 98 (99)

136 (92) 97 (92) 120 (98) 106 (95) 106 (99) 106 (97) 116 (88) 99 (89) 117 (84) 104 (96) 90 (101) 114 (105)

125 (92) 86 (83) 112 (85) 92 (87) 92 (92) 89 (90) 108 (86) 84 (82) 106 (84) 91 (91) 75 (92) 95 (96)

119 (85) 66 (75) 100 (83) 77 (82) 77 (85) 80 (86) 103 (81) 80 (76) 102 (79) 79 (83) 53 (85) 83 (92)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

20

134 (94) 97 (97) 114 (98) 106 (100) 102 (100) 106 (96) 120 (94) 100 (94) 113 (79) 102 (99) 94 (103) 110 (104)

Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

100a

150a

200a

250a

100 + 150a

100 + 150 + 200a

100 + 150 + 200 + 250a

104 (91) 80 (107) 96 (104) 84 (102) 84 (112) 93 (96) 98 (88) 89 (105) 102 (107) 88 (101) 91 (107) 91 (104)

109 (86) 96 (100) 110 (93) 98 (96) 99 (103) 98 (90) 108 (89) 94 (102) 106 (108) 97 (94) 103 (105) 99 (96)

105 (95) 92 (97) 105 (97) 94 (101) 95 (107) 96 (102) 103 (94) 90 (105) 108 (120) 93 (97) 98 (106) 93 (103)

103 (89) 78 (108) 93 (104) 82 (102) 81 (110) 91 (94) 95 (86) 88 (105) 99 (107) 85 (100) 90 (105) 88 (103)

113 (78) 105 (99) 112 (88) 101 (91) 101 (101) 95 (82) 106 (86) 95 (98) 113 (107) 97 (89) 108 (99) 99 (87)

104 (91) 110 (90) 113 (88) 102 (97) 104 (102) 93 (99) 103 (97) 90 (102) 108 (128) 94 (90) 107 (99) 93 (94)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

50

110 (98) 84 (101) 103 (103) 92 (102) 94 (108) 102 (102) 109 (93) 93 (107) 113 (108) 95 (102) 95 (114) 98 (111)

Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

200a

300a

400a

500a

200 + 300a

200 + 300 + 400a

200 + 300 + 400 + 500a

104 (97) 97 (98) 107 (95) 99 (98) 99 (98) 101 (95) 103 (99) 90 (95) 107 (120) 96 (92) 102 (96) 98 (97)

92 (98) 85 (103) 95 (98) 87 (98) 88 (101) 93 (92) 90 (95) 83 (93) 100 (123) 87 (94) 92 (96) 89 (98)

98 (101) 85 (106) 98 (101) 89 (104) 90 (106) 96 (96) 93 (99) 86 (99) 105 (122) 90 (98) 94 (101) 93 (100)

105 (95) 97 (96) 108 (92) 99 (95) 100 (95) 102 (92) 104 (98) 91 (92) 108 (116) 97 (89) 103 (95) 99 (94)

87 (94) 78 (100) 91 (93) 80 (92) 81 (96) 90 (84) 84 (90) 80 (87) 98 (120) 83 (90) 89 (92) 85 (93)

91 (99) 71 (107) 90 (98) 78 (102) 79 (105) 91 (88) 81 (93) 81 (96) 103 (119) 83 (98) 87 (100) 87 (96)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

100

101 (104) 96 (106) 102 (106) 97 (109) 97 (109) 98 (105) 100 (104) 88 (102) 103 (109) 93 (100) 97 (103) 94 (106)

Pesticide

Initial concentrationa

One-point calibration

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon a

200

Added concentration (␮g kg−1 ).

Two-point calibration

Three-point calibration

Four-point calibration

400a

600a

800a

1000a

400 + 600a

400 + 600 + 800a

400 + 600 + 800 + 1000a

98 (101) 100 (90) 108 (88) 101 (96) 103 (95) 100 (97) 96 (102) 94 (98) 110 (117) 99 (93) 104 (98) 99 (94)

91 (102) 92 (92) 102 (90) 94 (94) 96 (93) 93 (100) 91 (104) 87 (100) 101 (104) 95 (95) 99 (101) 94 (97)

82 (89) 85 (79) 94 (80) 86 (80) 88 (77) 85 (84) 81 (86) 79 (88) 92 (90) 88 (83) 91 (87) 87 (85)

80 (89) 84 (79) 93 (81) 85 (79) 88 (74) 84 (82) 80 (84) 78 (89) 93 (82) 87 (82) 89 (88) 85 (86)

88 (102) 89 (92) 100 (90) 92 (93) 94 (92) 90 (101) 89 (104) 85 (101) 98 (101) 93 (95) 98 (102) 92 (98)

71 (81) 76 (71) 86 (73) 76 (70) 78 (65) 75 (74) 70 (76) 70 (82) 81 (75) 81 (76) 83 (79) 78 (80)

62 (74) 69 (63) 79 (69) 68 (58) 73 (50) 69 (63) 61 (63) 60 (77) 76 (53) 73 (68) 74 (74) 71 (74)

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A. Garrido Frenich et al. / J. Chromatogr. A 1216 (2009) 4798–4808

Table 4 Estimated recoveries (in %) in cucumber (and orange) using approach 2. Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

20a

50a

100a

200a

20 + 50a

20 + 50 + 100a

20 + 50 + 100 + 200a

120 (85) 86 (88) 102 (110) 90 (86) 83 (93) 83 (84) 120 (87) 94 (98) 106 (87) 91 (90) 78 (111) 99 (104)

108 (89) 81 (83) 103 (110) 86 (83) 80 (92) 80 (84) 119 (88) 92 (95) 108 (91) 88 (88) 75 (110) 96 (105)

105 (82) 74 (86) 94 (103) 78 (84) 72 (91) 74 (78) 108 (82) 76 (88) 97 (91) 77 (83) 71 (104) 85 (95)

104 (80) 88 (76) 101 (96) 92 (78) 85 (88) 86 (76) 120 (86) 105 (96) 110 (93) 93 (83) 86 (94) 102 (97)

116 (84) 82 (86) 105 (98) 88 (87) 87 (96) 82 (86) 115 (91) 108 (94) 107 (86) 96 (91) 82 (103) 97 (99)

116 (79) 78 (79) 98 (83) 82 (79) 75 (85) 79 (81) 102 (84) 99 (87) 96 (88) 83 (86) 76 (98) 89 (89)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

10

119 (85) 92 (79) 104 (105) 94 (77) 89 (84) 87 (83) 119 (83) 114 (87) 117 (90) 95 (81) 93 (96) 103 (98)

Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

20a

50a

100a

200a

20 + 50a

20 + 50 + 100a

20 + 50 + 100 + 200a

129 (95) 99 (90) 118 (95) 107 (95) 106 (98) 104 (96) 110 (91) 98 (88) 117 (77) 104 (96) 100 (97) 111 (101)

107 (99) 82 (86) 107 (92) 91 (91) 90 (93) 94 (92) 110 (87) 91 (85) 108 (79) 91 (91) 75 (94) 98 (99)

109 (89) 87 (98) 110 (94) 95 (96) 94 (100) 94 (87) 109 (90) 85 (84) 107 (92) 91 (92) 71 (96) 96 (96)

126 (94) 100 (84) 118 (91) 108 (93) 109 (93) 106 (94) 110 (90) 101 (85) 116 (74) 106 (93) 125 (97) 110 (98)

118 (83) 70 (76) 98 (85) 79 (85) 78 (84) 87 (86) 110 (82) 89 (79) 102 (78) 82 (82) 97 (91) 87 (94)

114 (82) 78 (109) 104 (90) 85 (97) 85 (104) 86 (72) 116 (91) 70 (75) 97 (118) 78 (85) 100 (95) 81 (87)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

20

124 (97) 96 (103) 119 (104) 105 (102) 102 (109) 99 (100) 109 (94) 91 (93) 117 (84) 99 (105) 126 (98) 111 (107)

Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

20a

50a

100a

200a

20 + 50a

20 + 50 + 100a

20 + 50 + 100 + 200a

107 (87) 92 (88) 107 (88) 95 (91) 96 (99) 95 (97) 104 (87) 100 (106) 108 (98) 97 (95) 78 (106) 97 (98)

110 (98) 84 (101) 103 (103) 92 (102) 94 (108) 102 (102) 109 (93) 93 (107) 110 (108) 95 (102) 73 (114) 98 (111)

109 (86) 96 (100) 110 (93) 98 (96) 99 (103) 98 (90) 108 (89) 94 (102) 106 (108) 97 (94) 70 (105) 99 (96)

105 (88) 89 (88) 104 (87) 90 (90) 91 (98) 92 (95) 105 (87) 99 (104) 104 (100) 93 (94) 97 (104) 93 (97)

108 (103) 76 (108) 99 (108) 87 (106) 88 (109) 100 (102) 110 (96) 85 (105) 109 (115) 90 (104) 88 (115) 93 (114)

113 (84) 97 (107) 109 (94) 97 (96) 97 (104) 95 (83) 110 (90) 88 (96) 112 (115) 93 (91) 102 (91) 97 (92)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

50

117 (86) 114 (86) 124 (93) 120 (95) 124 (106) 116 (106) 100 (84) 130 (120) 139 (88) 121 (98) 87 (116) 122 (103)

Pesticide

Initial concentrationa

One-point calibration

Two-point calibration

Three-point calibration

Four-point calibration

20a

50a

100a

200a

20 + 50a

20 + 50 + 100a

20 + 50 + 100 + 200a

109 (120) 80 (128) 97 (132) 93 (123) 94(119) 113 (111) 111 (107) 86 (105) 114 (122) 95 (113) 70 (121) 100 (128)

99 (100) 78 (128) 88 (121) 83 (114) 81 (120) 94 (98) 93 (95) 85 (101) 95 (105) 85 (106) 65 (104) 89 (109)

101 (104) 96 (106) 102 (106) 97 (109) 97 (109) 98 (105) 100 (104) 88 (102) 103 (109) 93 (100) 71 (103) 94 (106)

107 (126) 82 (124) 108 (130) 96 (121) 97 (120) 116 (113) 113 (110) 84 (108) 116 (126) 98 (118) 90 (126) 102 (132)

96 (103) 80 (117) 89 (123) 83 (118) 81 (126) 131 (97) 91 (96) 82 (104) 93 (120) 85 (111) 87 (106) 89 (110)

98 (106) 106 (105) 106 (102) 101 (108) 101 (110) 122 (106) 99 (106) 87 (103) 102 (124) 94 (100) 101 (102) 93 (103)

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon

100

120 (81) 65 (85) 82 (107) 77 (95) 77 (88) 91 (96) 96 (85) 103 (88) 103 (84) 80 (84) 63 (90) 87 (100)

Pesticide

Initial concentrationa

One-point calibration

Acephate Bromopropylate Cypermethrin Chlorpyrifos Diazinon Etrimfos Heptenophos Iprodione Methamidophos Procymidone Tetradifon Triadimefon a

200

Added concentration (␮g kg−1 ).

Two-point calibration

Three-point calibration

Four-point calibration

20a

50a

100a

200a

20 + 50a

20 + 50 + 100a

20 + 50 + 100 + 200a

126 (67) 125 (70) 123 (56) 132 (73) 126 (67) 116 (62) 130 (126) 126 (61) 137 (129) 114 (61) 126 (77) 128 (57)

120 (79) 117 (80) 114 (70) 124 (78) 123 (78) 122 (77) 119 (103) 122 (89) 130 (102) 112 (77) 114 (95) 119 (75)

103 (110) 109 (81) 110 (86) 119 (97) 115 (92) 106 (116) 114 (118) 99 (101) 116 (138) 110 (91) 101 (100) 105 (99)

103 (110) 107 (78) 108 (78) 101 (85) 106 (83) 104 (94) 103 (105) 101 (91) 107 (110) 109 (83) 93 (91) 110 (88)

129 (81) 122 (81) 120 (72) 128 (79) 123 (79) 115 (79) 127 (101) 121 (93) 132 (100) 124 (80) 120 (97) 126 (77)

100 (117) 115 (82) 116 (92) 119 (101) 116 (96) 105 (124) 108 (116) 97 (109) 121 (127) 108 (97) 112 (103) 113 (107)

102 (103) 112 (79) 115 (83) 109 (88) 112 (85) 106 (102) 106 (103) 98 (95) 112 (116) 106 (87) 111 (92) 105 (94)

A. Garrido Frenich et al. / J. Chromatogr. A 1216 (2009) 4798–4808

4805

Table 5 ANOVA study of the standard addition methodology. Factor Approach Sig

Acephate

No (0.09)

Bromopropylate

Yes (0.01)

Cypermethrin

No (0.27)

Chlorpyrifos

Yes (0.02)

Diazinon

Yes (0.04)

Etrimfos

Yes (0.01)

Heptenophos

Yes (0.00)

Iprodione

Yes (0.01)

Methamidophos

Yes (0.03)

Procymidone

Yes (0.04)

Tetradifon

No (0.05)

Triadimefon

Yes (0.04)

a b

Matrixa

Calibration

b

Mean value 1

96.3

2

101.6

1

87.5

2

95.5

1

97.5

2

100.6

1

88.8

2

95.2

1

90.0

2

96.4

1

87.6

2

95.6

1

93.4

2

101.8

1

88.1

2

93.9

1

98.6

2

106.0

1

89.3

2

93.4

1

91.4

2

96.8

1

93.4

2

98.3

b

Sig

No (0.66)

No (0.79)

No (0.37)

No (0.38)

No (0.46)

No (0.38)

No (0.40)

Yes (0.03)

No (0.82)

Yes (0.04)

Yes (0.04)

Yes (0.02)

Mean value

Sigb

1-point 2-points 3-points 4-points

98.4 102.1 98.7 96.7

1-point 2-points 3-points 4-points

92.0 94.0 89.8 90.6

No (0.75)

1-point 2-points 3-points 4-points

99.2 102.7 98.2 96.0

Yes (0.01)

1-point 2-points 3-points 4-points

92.4 95.7 90.6 89.4

No (0.80)

1-point 2-points 3-points 4-points

93.7 97.0 91.7 90.5

No (0.12)

1-point 2-points 3-points 4-points

91.5 95.2 91.5 88.2

No (0.30)

1-point 2-points 3-points 4-points

97.8 101.3 96.4 95.2

Yes (0.00)

1-point 2-points 3-points 4-points

91.3 96.4 89.3 87.0

Yes (0.01)

1-point 2-points 3-points 4-points

102.0 105.0 100.9 101.2

No (0.28)

1-point 2-points 3-points 4-points

91.5 96.1 90.9 87.7

No (0.97)

1-point 2-points 3-points 4-points

90.4 100.7 93.9 91.4

Yes (0.00)

1-point 2-points 3-points 4-points

96.3 101.5 95.3 91.2

No (0.25)

Yes (0.00)

Mean value C

102.6

O

90.0

C

91.0

O

92.0

C

103.0

O

95.0

C

91.7

O

92.4

C

90.8

O

95.6

C

93.1

O

90.2

C

103.5

O

91.8

C

88.2

O

93.8

C

104.2

O

100.4

C

91.5

O

91.6

C

88.6

O

99.6

C

94.8

O

97.3

C: cucumber; O: orange. Sig: significant (p < 0.05). p-Values are given in parentheses.

were calculated (RSD values were always lower than 15%). The obtained results, expressed as recovery rate (%) values, using both approaches are shown in Table 3 (approach 1) and Table 4 (approach 2). The values obtained should be within the range 70–120% for validation purposes [30]. A preliminary view of the results indicates that when approach 1 is used (Table 3), acceptable recoveries are obtained using onepoint SAC in both matrices for all compounds, except for acephate in two cases in cucumber, and methamidophos in two cases in orange (recoveries higher than 120%). Also, good recoveries are obtained if the quantification is carried out using two or three calibration points, except in two cases for the acephate pesticide in cucum-

ber matrix. In general, the use of a four-point standard addition originated poorer recoveries, probably due to the great weight of the biggest addition level in the slope of the straight line. This behaviour is more evident at the highest tested concentration level (200 ␮g kg−1 ), whereas recoveries ranged from 61 to 79% in cucumber and from 50 to 77% in orange. When the second strategy is used (Table 4), it can be observed that if 100 or 200 ␮g kg−1 were added, accurate results were obtained for all range of initial concentrations. In general the use of multi-point calibration provides good results when concentrations of 10, 20 and 50 ␮g kg−1 should be estimated. However, the multiple standard addition calibration provided variable results when

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Table 6 ANOVA results when one-point standard addition is evaluated using approach 2. Added concentration a

Matrix −1

Con (␮g kg

Acephate

No (p = 0.663)

20 50 100 200

102.2 105.1 102.3 99.8

Yes (p = 0.001)

Bromopropylate

No (p = 0.875)

20 50 100 200

91.5 94.8 91.3 92.8

No (p = 0.959)

Cypermethrin

No (p = 0.959)

20 50 100 200

101.7 103.3 102.3 99.8

No (p = 0.064)

No (p = 0.914)

20 50 100 200

97.0 98.2 95.8 93.9

Diazinon

No (p = 0.963)

20 50 100 200

97.2 98.9 96.5 95.4

No (p = 0.869)

Etrimfos

No (p = 0.738)

20 50 100 200

95.6 98.2 96.8 92.2

No (p = 0.166)

Heptenophos

No (p = 0.812)

20 50 100 200

102.6 104.0 102.6 99.8

Yes (p = 0.001)

Iprodione

No (p = 0.291)

20 50 100 200

101.3 98.6 94.9 91.1

No (p = 0.330)

Methamidophos

No (p = 0.732)

20 50 100 200

108.8 106.1 105.8 103.0

Yes (p = 0.001)

Procymidone

No (p = 0.819)

20 50 100 200

93.8 97.0 94.7 93.8

No (p = 0.145)

Tetradifon

No (p = 0.405)

20 50 100 200

97.2 97.0 91.1 87.5

Yes (p = 0.002)

Triadimefon

No (p = 0.692)

20 50 100 200

101.6 103.2 100.9 96.5

No (p = 0.386)

Chlorpyrifos

a

)

Mean value

Siga

Sig

No (p = 0.242)

Mean value Cucumber

112.2

Orange

92.5

Cucumber

93.0

Orange

92.2

Cucumber

106.2

Orange

97.3

Cucumber

98.9

Orange

93.6

Cucumber

97.4

Orange

96.6

Cucumber

98.5

Orange

92.9

Cucumber

109.6

Orange

94.9

Cucumber

98.4

Orange

94.6

Cucumber

112.2

Orange

99.6

Cucumber

97.2

Orange

91.5

Cucumber

85.0

Orange

101.4

Cucumber

102.3

Orange

98.8

Sig: Significant (p < 0.05). p-Values are given in parentheses.

high concentration levels were quantified. Despite these variable results, some remarks can be made for certain unfavorable cases. For cucumber matrix, the single addition of a low concentration (20 and 50 ␮g kg−1 ) to a high concentration level (200 ␮g kg−1 ) led to higher recovery rates, because of an underestimation of the analytical response and overestimation of the results. This fact also took place when two and three-point calibration were used. Nevertheless, the four-point calibration compensates this effect (overestimation recovery) and more adequate results were obtained. The same situation was observed for orange matrix. When 50 ␮g kg−1 were added to a 100 ␮g kg−1 sample, higher recovery rates were obtained when using a single, two- or three-point addition, but the effect was corrected when the four-point calibration was utilised.

In order to study the reliability of the calibration process an evaluation of the experimental data was made by an ANOVA study, selecting the type of matrix (cucumber and orange), type of calibration (one, two, three and four points) and approach (same concentration or same ratio) as factors. The significant effects are shown in Table 5, where it can be observed that approach is the most frequently significant factor (p < 0.05). When the mean recovery values were compared, approach 2 provided recovery values closer to 100% than approach 1 for bromopropylate, chlorpyrifos, diazinon, etrimfos, heptenophos, iprodione, procymidone and triadimefon, whereas approach 1 provided better results only for heptenophos and methamidophos. Furthermore the type of matrix is also a significant factor for some pesticides (acephate, cypermethrin, heptenophos, iprodione and tetradifon). Finally, the type of

A. Garrido Frenich et al. / J. Chromatogr. A 1216 (2009) 4798–4808

4807

Table 7 Screening results and quantitative values obtained (␮g kg−1 ) in the analysis of cucumber (C) and orange (O) samples by the proposed single standard addition of 200 (␮g kg−1 ) and matrix matched calibration. Pesticide

Area (pesticide/IS)

Screening result

Quantitative results Single standard addition

Procymidone Iprodione

Matrix matched calibration

C1

C2

O1

O2

C1

C2

O1

O2

C1

C2

O1

O2

C1

– –

0.1043 –

– 0.0024

– –

N N

NN N

N NN

N N

– –

89 –

– 41

– –

– –

C2 94 –

O1

O2

– 38

– –

N, negative sample; NN, non-negative sample.

calibration was only significant for iprodione, procymidone, tetradifon and triadimefon, whereas for the rest of the assayed pesticides this factor was not statistically significant. Bearing in mind that the use of one point could increase sample throughput and good recoveries were obtained (Table 5), the best concentration added to the sample was studied by a new ANOVA. In this sense, approach 2 was selected (better results were obtained in the previous study) and several concentrations were added to the sample (20, 50, 100 and 200 ␮g kg−1 ). Recoveries were estimated using only one point during the quantification step. The statistical study (Table 6) revealed that added concentration is not significant (p > 0.05) for all the selected pesticides, although the type of matrix was significant for some pesticides (acephate, heptenophos, methamidophos and tetradifon), despite mean recoveries were always between 70 and 120%. Taking into account the obtained results it can be indicated that one point calibration can be used in order to obtain reliable results when standard addition methodology is applied. In relation to the added concentration, no significant differences were detected when the added concentration range from 20 to 200 ␮g kg−1 . However, it can be observed that if lower concentrations were added higher recoveries were obtained when high concentration levels must be detected (see Table 4), although recoveries close to 100% are obtained if 100 or 200 ␮g kg−1 were added. Although this methodology (one single point calibration) increases sample throughput during routine analysis, one drawback is related to the uncertainty of the results, because if fewer points are used during the calibration, the contribution of this step to the combined uncertainty will be more important. 3.4. Application to the analysis of vegetable samples In order to test the feasibility of the proposed approach for routine quantification of pesticide residues in real samples, four samples of vegetables (two cucumbers and two oranges) were analysed for the target compounds. Besides, the obtained results were compared with the values obtained when matrix-matched calibration was used. All samples came from LAB laboratory located in Almería, accredited by UNE-EN-ISO/IEC 17025 for pesticide residue analysis, where they were previously analysed by GC–MS/MS and quantified with matrix matched standards. First, the target pesticides were searched in the appropriate retention time, being procymidone and iprodione respectively identified in cucumber and orange. The rest of the target pesticides were not found in the analysed samples. The obtained relative areas to the IS for the identified pesticides are shown in Table 7. After screening, potentially positive samples were confirmed taking into account the presence of two MS/MS transitions by compound (Table 1). Following this, positive samples were quantified by the SAC using one-point addition. Therefore, 200 ␮g kg−1 of procymidone and iprodione were added to an aliquot of each positive sample. The estimated concentrations are summarized in Table 7. The obtained results using matrix-matched calibration were compared to those obtained with SAC (spiking with 200 ␮g kg−1 ). In

general, differences lower than 10% were obtained, providing the reliability of the proposed methodology. 4. Conclusions It can be concluded that the SAC can serve as a very practical approach to overcome the matrix effects for the GC–MS/MS analysis of pesticides in food commodities. The use of one-point calibration, adding 100 or 200 ␮g kg−1 , can provide accurate determination of samples with initial concentrations ranged from 10 to 200 ␮g kg−1 . Although SAC requires more sample runs than a standard calibration curve approach, it remains an efficient technique for routine monitoring laboratories of pesticide residues that have to analyse different types of sample extracts daily, avoiding the use of different matrix matched calibrations. In this way, the sample throughput can increase considering if one-point calibration is used, reducing analysis time. In addition, this approach eliminates any bias associated with the use of a representative matrix for calibration, because both quantification and calibration are always performed on the same sample. The effectiveness of this approach for routine analysis was evaluated by its application to real samples that had previously been quantified by matrix matched calibration. The excellent agreement between the results demonstrates the applicability of the SAC to routine analysis. Finally, GC maintenance should be carried out after 300 injections, due to the loss of the sensitivity in the analytical responses, in order to detect low concentration levels. Acknowledgements The authors gratefully acknowledge the Consejería de Innovación Ciencia y Empresa de la Junta de Andalucía (P05-FQM-0202) for the financial support. We thank the three anonymous referees for their valuable comments. References [1] J. Hajslova, K. Holadová, V. Kocourek, J. Poustka, M. Godula, P. Cuhra, M. Kempny, J. Chromatogr. A 800 (1998) 283. [2] J. Hajslova, J. Zrostlíková, J. Chromatogr. A 1000 (2003) 181. [3] E. Soboleva, N. Rathor, A. Mageto, A. Ambrus, in: A. Fajgelj, A. Ambrus (Eds.), Principles Practices of Method Validation, Royal Society of Chemistry, Cambridge, U.K., 2000, p. 138. [4] D.R. Erney, A.M. Gillespie, D.M. Gilvydis, C.F. Poole, J. Chromatogr. 638 (1993) 57. [5] D.R. Erney, T.M. Pawlowski, C.F. Poole, J. High Resolut. Chromatogr. 120 (1997) 375. [6] A.M. Gillespie, S.L. Daly, D.M. Gilvydis, F. Schneider, S.M. Walters, J. AOAC Int. 78 (1995) 431. [7] E. Ueno, H. Oshima, I. Saito, H. Matsumoto, Y. Yoshimura, H. Nakazawa, J. AOAC Int. 87 (2004) 103. [8] T. Schmeck, B. Wenclawiak, Chromatographia 62 (2005) 159. [9] W.G. Zhang, X.G. Chu, H.X. Cai, J. An, C.J. Li, Rapid Commun. Mass Spectrom. 20 (2006) 609. [10] J.L. Fernandez Moreno, F.J. Arrebola Liebanas, A. Garrido Frenich, J.L. Martinez Vidal, J. Chromatogr. A 1111 (2006) 97. [11] J. Zrostlíková, J. Hajslova, M. Godula, K. Mastovska, J. Chromatogr. A 937 (2001) 73.

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