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RESIDUES AND TRACE ELEMENTS Simultaneous Screening and Target Analytical Approach by Gas Chromatography-Quadrupole-Mass Spectrometry for Pesticide Residues in Fruits and Vegetables MILAGROS MEZCUA and MARIA A. MARTÍNEZ-UROZ University of Almería, Community Reference Laboratory (DG SANCO) for Residues of Pesticides in Fruits and Vegetables, Pesticide Residue Research Group, 04120 La Cañada de San Urbano, Almería, Spain PHILIP L. WYLIE Agilent Technologies, Inc., 285 Centerville Rd, Wilmington, DE 19808-1610 AMADEO R. FERNÁNDEZ-ALBA 1 University of Almería, Community Reference Laboratory (DG SANCO) for Residues of Pesticides in Fruits and Vegetables, Pesticide Residue Research Group, 04120 La Cañada de San Urbano, Almería, Spain A full-scan GC/quadrupole/MS method has been developed to perform large-scale screenings of pesticides and simultaneous quantification of 95 target compounds in a single run of 21 min. The screening method was performed by using a deconvolution of the spectrum of the full-scan data files acquired under a retention time locked method. The identification performance of the screening method was evaluated in eight different food matrixes at three different concentrations. The system was equipped with a programmable temperature vaporizing inlet, allowing 10 mL injections. The LOQ in the full-scan mode and linearity were studied for four different matrixes. Correlation coefficients >0.99 were achieved in all cases, and the LOD was <20 mg/kg for 80% of the studied pesticides. Maintenance of the system was reduced by the use of a QuickSwap device that provided backflush capabilities by reversing column flow immediately after elution of the last compound of interest. The combined screening and target method was used in the analysis of more than 100 food samples, including a carrot sample from the European Proficiency Test FV 10, with good results. T arget analysis methods applied in many laboratories for routine pesticide residue control basically consist of a list of around 100–150 GC- and LC-amenable compounds. The analyte list is selected by using the established priority lists combined with any other relevant information related to agricultural uses in local regions (1, 2). This means that the majority of the low-frequency or misused (nonpriority) compounds typically fall outside of any extensive control. Thus, they are detected purely by chance, based on extra information or analytical work. An example of this is the case of the European Union safety alert generated in 2006 because of the presence of the nonauthorized insecticide isofenphos-methyl found in pepper samples (3, 4). This is becoming more important, given that the pesticides currently authorized in Europe (Annex I, Directive 91/414/EEC; 5) and other developed countries have been reduced to around 50% of the total amount of compounds manufactured. Consequently, in the field of food safety, there is an obvious need for methods offering the rapid and reliable screening of a large number of compounds. From an analytical point of view, this task is difficult to accomplish since it involves extending the scope of the multiresidue methods to cover several hundred chemicals. It is difficult to carry out these approaches cost-effectively due to the time and money required for upgrading methods to incorporate new compounds, and management of the standards and solutions. Extra analytical effort and an overall decrease in laboratory throughput result. Thus, other alternatives should be explored and evaluated. A good alternative is the application of combined analyses based on the target/screening approach. This is done by targeting a group of priority compounds based on their toxicity and/or frequency of detection and, at the same time, carrying out a rapid screening of a much larger number of compounds for identification purposes only (6–9). GC/MS has been used for many years to identify pesticides in food samples. Generally, to efficiently remove interference from coeluting peaks and to ensure sensitivity, selective ion monitoring (SIM) or MS/MS by selection of a precursor ion, as opposed to full scanning (monitoring the whole spectrum), has been used to detect trace levels of pesticides in complex samples (10, 11). However, these methods rely on only a few ions and are not designed to find compounds unless they are on the target list. 1790 MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009 Received September 12, 2008. Accepted by AK March 12, 2009. 1 Corresponding author’s e-mail: [email protected]

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  • RESIDUES AND TRACE ELEMENTS

    Simultaneous Screening and Target Analytical Approach by GasChromatography-Quadrupole-Mass Spectrometry for PesticideResidues in Fruits and Vegetables

    MILAGROS MEZCUA and MARIA A. MARTÍNEZ-UROZUniversity of Almería, Community Reference Laboratory (DG SANCO) for Residues of Pesticides in Fruits andVegetables, Pesticide Residue Research Group, 04120 La Cañada de San Urbano, Almería, SpainPHILIP L. WYLIEAgilent Technologies, Inc., 285 Centerville Rd, Wilmington, DE 19808-1610AMADEO R. FERNÁNDEZ-ALBA1

    University of Almería, Community Reference Laboratory (DG SANCO) for Residues of Pesticides in Fruits andVegetables, Pesticide Residue Research Group, 04120 La Cañada de San Urbano, Almería, Spain

    A full-scan GC/quadrupole/MS method has beendeveloped to perform large-scale screenings ofpesticides and simultaneous quantification of95 target compounds in a single run of 21 min. Thescreening method was performed by using adeconvolution of the spectrum of the full-scan datafiles acquired under a retention time locked method. The identification performance of the screeningmethod was evaluated in eight different foodmatrixes at three different concentrations. Thesystem was equipped with a programmabletemperature vaporizing inlet, allowing 10 mLinjections. The LOQ in the full-scan mode andlinearity were studied for four different matrixes.Correlation coefficients >0.99 were achieved in allcases, and the LOD was

  • MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009 1791

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  • The full-scan mode is a standard feature in all MSdetectors. However, most methods employ it for qualitativeanalysis only. A major advantage of the full-scan mode overthe SIM mode is the simultaneous identification of othereluted compounds that could be of interest. A majordisadvantage is that, generally, the full-scan method is lesssensitive than the SIM method, although new generationequipment yields sufficient sensitivity to meet currentregulations (12). Recently, the use of library searchingmethods for GC/MS has made it possible to search the largeNational Institute of Standards and Technology (NIST)pesticide libraries in minutes (13).

    With retention time locked (RTL)-GC/MS, the detectionselectivity is greatly improved by linking the locked retentiontime to the mass spectral data. This reduces the risk of falsepositives. Nowadays, these methods have been widelydeveloped to analyze multiresidues in fresh vegetables,fruit, and honey (14–16). The automated mass spectraldeconvolution and identification system (AMDIS; 13) ispost-processing software for extracting “purified” mass spectrafrom a one-dimensional gas chromatogram. The AMDIS offers the possibility of identifying compounds by both mass spectraand retention index (or retention time) together.

    This paper reports the development and evaluation of arapid, automated screening method for the detection ofpesticide residues in food using GC/MS. It is based on the useof deconvolution reporting software (DRS) together with adatabase containing mass spectra and locked retention timesfor 927 pesticides and endocrine disruptors (13).Simultaneously with the screening, the method performs anautomatic quantification of 95 target pesticides. The method is RTL, and the analytical column is backflushed by reversingthe column flow at the end of the run in order to minimizemaintenance of the system.

    Experimental

    Chemicals and Reagents

    Pesticide analytical standards were purchased from Dr.Ehrenstorfer (Ausburg, Germany) or Riedel de-Haën (Seelze,Germany). Individual pesticide stock solutions(approximately 500 mg/mL) were prepared in methanol orethyl acetate and were stored at –18°C. HPLC gradeacetonitrile (ACN) and methanol were obtained from Merck(Darmstadt, Germany). Primary-secondary amine (PSA)sorbent material was obtained from Supelco (Bellefonte, PA).

    Sample Treatment

    Fruit, vegetable, and olive oil samples were purchasedfrom different local markets. The extraction procedure usedfor fruit and vegetable samples [the so-called quick, easy,cheap, effective, rugged, and safe (QuEChERS) method,described elsewhere; 17, 18], comprised the following steps:A representative 15 g portion of previously homogenizedsample was weighed in a 200 mL PTFE centrifuge tube. Then15 mL ACN was added, and the tube was shaken vigorouslyfor 1 min. After this, 1.5 g NaCl and 4 g MgSO4 were added,

    MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009 1797

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  • and the shaking process was repeated for 1 min. The extractwas then centrifuged (3700 rpm) for 1 min. A 5 mL amount ofthe supernatant (acetonitrile phase) was then transferred to a15 mL graduated centrifuge tube containing 250 mg PSA and750 mg MgSO4, which was then shaken energetically for 20 s. Following this, the extract was centrifuged again (3700 rpm)for 1 min. Finally, an extract containing the equivalent of 1 gof sample/mL of nearly 100% ACN was obtained.

    Olive oil samples were extracted by matrix solid-phasedispersion, with a preliminary liquid–liquid extraction usingaminopropyl as the sorbent material, with a cleanupperformed in the elution step with Florisil. The completeprocedure was described previously (19).

    GC/MS System

    GC/MS analyses were run on an Agilent 7890 series gaschromatograph (Agilent Technologies, Santa Clara, CA)interfaced to an Agilent 5975 mass selective detector (MSD).Retention time locking, data acquisition, processing, andinstrumental control were performed by the AgilentMSD ChemStation software (E.0200.493 version). Aprogrammable temperature vaporizing (PTV) inlet was usedin the solvent vent mode; an empty 1.8 mm id liner wasplaced in the PTV injector. Analytes were separated in anAgilent HP-5MSi capillary column (5% biphenyl/95%dimethylsiloxane), 15 m ´ 0.25 mm id, 0.25 mm filmthickness. A deactivated fused-silica restrictor (0.171 m ´0.120 mm id, 0.1 mm film thickness) was placed in the transfer

    line, which was connected to the capillary column through aQuickSwap device. The QuickSwap device is a purgedT-connection placed between the end of the GC column andthe entrance to the MSD transfer line. The inlet operatingconditions were injection volume, 10 mL, and injection speed,30 000 mL/min; the temperature program was set at 79°C for0.25 min, programmed to 300°C at 710°C/min, and kept atthis temperature for 2 min. The helium carrier gas flow wasmaintained at a constant pressure of 17.296 psi. As RTLmethod was used, using the locked retention time ofchlorpyriphos methyl divided by 2 (8.297 min) as thereference; this retention time was taken from the AgilentPesticide and Endocrine Disruptor database. The retentiontime database was created with a chromatographic method inwhich the run time was double the run time proposed in thispaper. All of the conditions in the methods were the sameexcept for the column length; the reference method used acolumn length of 30 m length, and the proposed method 15 m.To compare experimental retention times with thoseregistered in the database, division by 2 was required.

    As an example, the retention time of chlorpyriphos methyl(used as the reference) in the original method with a column of 30 m length was 16.594 min, and in the proposed methodusing a column of 15 m was 8.297 min. The oven temperatureprogram was 70°C for 1 min, programmed to 150°C at50°C/min, then to 200°C at 6°C/min, and finally to 280°Cat 16°C/min; it was kept at this temperature for 5 min. Afterthat, a post-run of 5 min was carried out with a temperature of

    1798 MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009

    Figure 1. Extracts of lettuce and pepper injected 3 times with a 2 min backflush and 3 times without backflush.The first and third injections are shown in each case. Without backflushing, the third injection (B) shows carryover,and retention time shifts compared to the first injection (A).

  • 290°C. During the post-run, the column head pressure waslowered to 1 psi and the pressure in the Quick Swap increasedto 60 psi. During this post-run time, the column flow wasreversed in order to backflush high-boiling components fromthe head of the column and out through the split vent of thePTV inlet.

    Electron impact mass spectra in the full-scan mode wereobtained at 70 eV; the monitoring was from m/z 50 to 400. The ion source and quadrupole analyzer temperatures were fixedat 230 and 150°C, respectively.

    Trace ion detection (20) was turned on. This is a filteringalgorithm to smooth peaks. This filtering is an advanced formof averaging used to remove the noise riding on the signal.Trace ion detection provides better S/N values and helpsdeconvolution to confirm target compounds.

    Automatic Screening

    A pesticide mixture containing the compounds listed inTable 1 was spiked into eight different matrix extracts:aubergine, potato, cucumber, banana, tangerine, orange,melon, and olive oil. All compounds were added at threespiking levels: 20, 50, and 100 mg/kg. The spiked extractswere analyzed by GC/MS in the full-scan mode using the RTL method detailed above. DRS (Version A.03.00) was used toidentify the compounds in chromatograms obtained in thefull-scan mode in these matrixes. This software results from amarriage of three different software packages: the AgilentGC/MS ChemStation, the NIST Mass Spectral SearchProgram with the NIST’05 MS Library, and the AutomatedMass Spectral Deconvolution and AMDIS software (Version2.64), also from NIST. The deconvolution parameters inAMDIS were fixed as follows: adjacent peak subtraction, 2;resolution, high; sensitivity, very high; and shaperequirements, medium.

    The used database has the possibility of increasing thenumber of compounds. This feature is very interesting for theuser. The way to include new compounds in the database is byanalyzing a pure standard of the new substance using theproposed RTL method and storing the mass spectrum in thedatabase, along with its locked retention time. This retentiontime must be expressed in seconds because absolute retentiontimes in seconds instead of retention index values areemployed for this method. The AMDIS software allows thesubstitution of retention times expressed in seconds forretention index values. Therefore, retention times obtainedmust be multiplied by 60. The retention times must also bemultiplied by 2, because the original database retention timeswere obtained by analysis in an analytical column of 30 mlength using a method that took exactly twice as long; theretention times obtained for this method are exactly half ofthose stored in the Pesticide and Endocrine Disruptordatabase. The AMDIS retention index calibration fileautomatically converts real retention times obtained in thechromatogram, so they are comparable to those stored inthe database.

    Quantification of Target Compounds

    Table 2 lists the locked retention time (min), the target ion,and the qualifier ions for the 95 pesticides selected forfull-scan quantification. Matrix-matched solutions wereprepared by spiking the selected matrixes (after the extraction) with all of the pesticides at 5, 10, 20, 50, 200, and 500 mg/kg.

    The quantification of target compounds was performed inthe full-scan mode. An automatic method was used to identifyand quantify the samples. For this automatic method, threeions and the retention time were selected for each compound(Table 1).

    MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009 1799

    Figure 2. Mean AMDIS match values obtained after DRS analysis of full-scan chromatograms obtained by RTL GCof aubergine, potato, cucumber, banana, tangerine, orange, melon, and olive oil extracts at three concentrationlevels of 20, 50, and 100 mg/kg.

  • Limit of identification (LOI) values were determined foreach compound; this limit was considered to be the minimumconcentration identified by the DRS software with theselected library.

    The LOI of each compound in each matrix wasinvestigated to ensure the S/N was equal to or higher than 10,and they were used as LOQs. Linearity of the analyticalresponse was evaluated by the injection of a matrix-matchedsolution at six concentrations levels, ranging from the LOI ofeach compound up to 500 mg/kg.

    Results and Discussion

    GC/MS System

    The GC system employed had a QuickSwap device placedbetween the end of the column and the entrance to the MSDtransfer line. A small purge gas flow mixed with the columneffluent and passed through the deactivated fused silicarestrictor inside the transfer line and into the MSD source.This device provided a means of removing or changing thecolumn without needing to cool and vent the massspectrometer; gave protection against unwanted air entrywhen doing routine maintenance on columns and inlets; andoffered a means for backflushing columns to removehigh-boiling components, thus reducing both run times and

    cool-down times, as well as minimizing ghosting from run

    to run.

    Backflush is a means of discarding high-boiling

    compounds from a column after the peaks of interest have

    eluted. It saves analysis time and has the following additional

    benefits: longer column life (due to less high-temperature

    exposure), protection from air and water at high temperatures,

    and less chemical background and contamination of the

    MSD source.

    The advantage of using backflush in the column was

    demonstrated for two different matrixes: lettuce and pepper.

    Six 10 mL injections were made of each extract—three with

    and three without backflushing; the chromatograms obtained

    are shown in Figure 1. Both lettuce and pepper samples

    showed the same results. When analyses were run without

    backflush, the baseline increased, and retention times shifted a

    mean of 5 s after three injections. In Figure 1, the third

    injection (labeled B) shows considerable chromatographic

    deterioration compared to the first injection (labeled A).

    However, when injections were performed with 2 min of

    backflushing at the end of each run, the baseline and retention

    times were stable. As shown by the overlapped

    chromatograms in Figure 1, backflushing eliminated

    carryover and retention time shifts.

    1800 MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009

    Figure 3. Total ion chromatograms in full-scan and SIM modes of a melon extract spiked at 5 mg/kg. The areas ofthe chromatograms where chlorpyriphos-methyl elutes are magnified. The S/N of chlorpyriphos-methyl is shown inthe chromatograms.

  • Automatic Screening

    Matrixes from different categories were chosen to performthis study. Spiked samples of aubergine, potato, cucumber,banana, tangerine, orange, melon, and olive oil at 20, 50, and100 mg/kg were analyzed by the RTL GC/MS method;full-scan spectra were analyzed with DRS. Analysis withDRS provides a report with the following information: theretention time of the identified compound, CAS number,compound name, match quality, and the retention timedifference (in seconds) between the observed peak and thedatabase value, and the match and hit number—all bysearching the deconvoluted spectrum against the entire NISTMass Spectral Library.

    In Table 1, the match values obtained by AMDIS for all ofthe compounds in the selected matrixes at the threeconcentrations are given. In all cases included in Table 1, DRS showed confirmation by NIST and retention time differences(compared to the pesticide database) of less than 5 s.

    This study has been performed to find out about theinfluence of concentration and matrix in the identificationcapabilities of the proposed method. Means of the AMDISmatch values are shown in Figure 2 for all of the selectedpesticides in aubergine, potato, cucumber, banana, tangerine,orange, melon, and olive oil extracts at 20, 50, and 100 mg/kg.A clear relationship is observed between the mean matchvalues for all of the studied matrixes and the pesticideconcentration level. Match values increased when theconcentration was higher. Lower concentrations imply lowerS/Ns, and deconvoluted spectra are affected with ions fromthe matrix.

    The influence of the matrix was also observed (Figure 2);matrixes with high acid content, such as tangerine and orange,usually showed lower match values compared to the rest of the studied matrixes. The extracts of matrixes with high acidcontent probably also contained the largest number of volatilenatural products. They could interfere with the pesticide

    analysis, and the deconvolution process was less effectivethan in other types of matrixes.

    The AMDIS match values were, in general, better than 90.A small group of pesticides (dichlorvos, monocrotophos,dimethoate, metalaxyl, prometryn, fenitrothion, malathion,fenthion, parathion, isocarbophos, thiabendazole,tolylfluanide, methidathion, phenamiphos, buprofecin,iprovalicarb, ofurace, endosulfan sulphate, trifloxystrobin,nuarimol, tebuconazole, iprodione, phosmet, fenpropathrin,phosalone, l-cyhalothrin, pyrazophos, acrinathrin,prochloraz; fenbuconazole, azoxystrobin, and imazalil)showed lower match values (70–90). Taking into accountthese results, the target match value was fixed at ³70.Furthermore, a reduced group of pesticides with specificcommodities at low concentration (20 mg/kg) showed matchvalues lower than 70 (Table 1). Those cases represented 3% of the total determinations performed. In such cases, the NISTmatch value obtained and the retention time difference inAMDIS were ³60 and 5 s, respectively. Therefore, they wereconsidered as possible positive findings, but some additionalparameters should be necessary for confirmation.

    With regard to automatic screening, isofenphos methyl is aspecial case. Although this compound was not included in thecommercial library due to its particular interest (3, 4), it wasintroduced additionally into the commercial database. Itsdetermination was performed following the proceduresdescribed in the Experimental section.

    Analysis of Target Compounds

    Our first option for performing analysis of targetcompounds was to develop an acquisition method in the SIMmode, since the system provides the possibility of acquiringdata in full-scan and SIM modes within the same analysis.Two alternatives were considered: to make a unique methodthat includes the acquisition of 100 compounds in SIM; orto develop two different SIM methods, each including

    MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009 1801

    Figure 4. Distribution of recoveries studied in two matrixes for 95 pesticides using QuEChERS as the extractionprocedure.

  • 50 compounds. When the SIM LOD values of the targetcompound, calculated as the minimal concentration withS/N = 3, were evaluated and compared with the LOI in thefull-scan mode, our expectation was to improve the sensitivity by 10 times when working in SIM compared with full scan.However, the LOD achieved for most of the compounds inboth SIM alternatives (the SIM method with 100 compounds,and the two different methods with 50 compounds each) weresimilar to those in the full-scan mode.

    The proposed method had an analysis time of 22 min. Inorder to perform a SIM method for 50 selected pesticides, itwas necessary to create 13 retention time windows with166 selected ions. Due to the properties of the pesticides, 76%of them eluted between 6 and 15 min.

    Figure 3 shows chromatograms in full-scan and SIMmodels of a melon extract spiked at 5 mg/kg. The areas of thechromatograms where chlorpyriphos-methyl elutes aremagnified. S/N ratio values are very close in SIM(S/N = 11) and full-scan (S/N = 14) chromatograms forchlorpyrifos-methyl, and the same trend was observed for theother compounds (data not shown). The difference in the S/Nvalues in SIM and full-scan chromatograms were in the rangeof ±5. The developed quantification method was performed in full-scan mode.

    LOI was evaluated for all compounds in the eight differentmatrixes. In Table 2, values for four different matrixes areshown, corresponding to the four commodity categories:cucumber (high water content), olive oil (high oil content),potato (high protein or high starch content), and tangerine(high acid content). LOIs lower than 20 mg/kg were achievedfor 70% of the studied pesticides.

    The linearity of the pesticides listed in Table 2 was studiedin aubergine, potato, cucumber, banana, tangerine, orange,melon, and olive oil matrixes from the LOI to 500 mg/kg. Alinear response was obtained for all pesticides in all of theselected matrixes within the studied range, and r2 values >0.99 were obtained in all cases.

    For the recovery study, spiked samples were prepared foreach of the two matrixes selected (tomato and orange) at the100 mg/kg level. The QuEChERS method was carried out5 times on each matrix. The data evaluation was carried out by comparing the peak intensities of the spiked samples to thoseobtained by matrix-matched standard calibration. Extracted“blank” matrixes may have contained some of the investigated pesticides. Therefore, blank correction from the calibrationsamples and also from the spiked samples was necessaryduring the analysis. The distribution of the recoveries isshown in Figure 4. More than 95% of the pesticides under

    1802 MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009

    Table 3. Carrot sample from European Proficiency Test (EUPT) FV 10 analyzed by the RTL method for simultaneousscreening and target compound quantification

    Pesticide Concn, mg/kg, EUPT FV 10Positives found with the proposed

    screening methodQuantification with the proposed

    method, concn, mg/kg

    Acetamiprid 0.419 Yes a

    Boscalid 0.238 Yes a

    Chlorpyriphos-methyl 0.078 Yes 0.076

    Diazinon 0.603 Yes 0.609

    Endosulfan sulfate 0.107 Yes 0.119

    Hexythiazox 0.509 Nob a

    Isofenphos-methyl 0.499 Yes 0.521

    Kresoxim-methyl 0.050 Yes 0.049

    Malathion 0.771 Yes 0.769

    Metamidophos 0.342 Yes 0.342

    Methiocarb 0.043 Yes 0.050

    Methiocarb sulfone 0.065 Nob a

    Methiocarb sulfoxide 0.051 Nob a

    Methomyl 0.739 Yes 0.790

    Oxamyl 0.322 Yes a

    Pendimethalin 0.074 Yes a

    Phosmet 0.236 Yes 0.235

    Quinoxifen 0.298 Yes 0.298

    Triadimenol 0.331 Yes 0.325

    Vinclozolin 1.040 Yes 1.038

    a Not included in the quantification method.b Not included in the database used.

  • MEZCUA ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 92, NO. 6, 2009 1803

    Table 4. Analysis of 117 market-purchased fruit,vegetable, and olive oil samples using the proposedautomatic simultaneous screening and quantificationmethod

    Sample Identified pesticides Concn, mg/kg

    Red_apple_s1 Chloropyriphos 30

    Thiabendazole a

    Imazalil 23

    Diclorvos a

    Green_pepper_s2 —

    Red_pepper_s3 —

    Carrot_s4 —

    Kiwi_s5 Fenhexamid a

    Lettuce_s6 —

    Apple_s7 Thiabendazole a

    Imazalil a

    Apple_s8 Thiabendazole a

    Imazalil a

    Pear_s9 Imazalil a

    Pear_s10 Ethoxyquin a

    Imazalil a

    Pear_s11 Dichlorvos 15

    Ethoxyquin a

    Thiabendazole a

    Imazalil a

    Pepper_s12 —

    Pepper_s13 Cyprodinil 40

    Tomato_s14 —

    Carrot_s15 —

    Kiwi_s35 —

    Strawberry_s36 —

    Carrot_s16 —

    Watermelon_s17 Bifenthrin 28

    Melon_s18 Pirimiphos-methyl 15

    Nectarine_s19 Fenthion a

    Red_pepper_s20 —

    Leek_s21 —

    Tomato_s22 Bifenthrin 12

    Banana_s23 —

    Melon_s24 —

    Apple_s25 —

    Apple_s26 —

    Tomato_s27 Procymidone 83

    Peach_s28 —

    Tangerine_s29 Isoprocarb a

    Peach_s30 —

    Lettuce_s31 —

    Onion_s32 —

    Table 4. (continued)

    Sample Identified pesticides