100 Pesticides in Fruit and Veg

RAPID COMMUNICATIONS IN MASS SPECTROMETRY

Rapid Commun. Mass Spectrom. 2007; 21: 3869–3882

) DOI: 10.1002/rcm.3268
Published online in Wiley InterScience (www.interscience.wiley.com
Screening and confirmation of 100 pesticides in food

samples by liquid chromatography/tandem mass

spectrometry

Imma Ferrer1*, E. Michael Thurman2 and Jerry A. Zweigenbaum3

1Pesticide Residue Research Group, University of Almeria, Almeria, Spain2Department of Environmental Engineering, University of Colorado, Boulder, CO, USA3Agilent Technologies, Inc., LFS, Wilmington, DE, USA

Received 27 July 2007; Revised 11 September 2007; Accepted 13 September 2007

*CorrespoUniversitE-mail: if

An analytical method for screening, quantitation and confirmation of a group of 100 pesticides in

vegetable and fruit samples was developed using liquid chromatography coupled with tandemmass

spectrometry (LC/MS/MS). The pesticides studied belonged to different chemical families

of herbicides, insecticides and fungicides; some degradation products were included as well. A

thorough optimization was performed for each analyte to achieve individual optimum fragmentor

and collision energy voltages. Two transitions per parent compound were monitored in a single

chromatographic run containing two time segments. A small particle size C18 column (1.8mm) was

used for the chromatographic separation of the mixture, providing very narrow peaks and allowing

an excellent separation of all the analytes in a 30-min period formaximumpeak capacity. Themethod

was validated with blank matrices of green pepper, tomato and orange spiked from 0.1 to 100mg/kg

with the pesticide mix. Quantitation was carried out using matrix-matched standard calibration and

linearity of response over 3 orders of magnitude was demonstrated (r > 0.99). Limits of detection

based on two transitions and ion-ratio requirements ranged between 0.3 and 50mg/kg. In general, the

sensitivity obtained meets the maximum residue levels (MRLs) established by the European Union

regulation for food monitoring programs. The analytical performance of the method was evaluated

for different types of vegetables and fruits, showing little or no matrix effects, and examples of

screening and confirmation of pesticides in these samples are shown here. Copyright # 2007 John

Wiley & Sons, Ltd.

It is well known that the presence of pesticide residues in

food can affect human health. Different organizations have

set stringent regulatory controls on pesticide use in order to

minimize exposure of the general population to pesticide

residues in food. For example, the European Union (EU) has

set newDirectives for pesticides at low levels in vegetables in

order to meet health concerns.1 For fruits and vegetables

intended for production of baby food, a maximum residue

limit (MRL) of 0.01mg/kg is applicable for all pesticides, and

compounds without a stated regulation have the lowest

MRLs at 0.01mg/kg as well.2

The low MRLs have encouraged the development of more

sensitive analytical methods to meet the requirements in

complex samples. Therefore, sensitive and reliable con-

firmatorymethods are required tomonitor pesticide residues

in foods. In this sense, liquid chromatography/tandemmass

spectrometry (LC/MS/MS) with a triple quadrupole in

multiple reaction monitoring (MRM) mode has become, so

far, the most widely used technique for monitoring and

quantitation of pesticides in food, as reported extensively in

ndence to: I. Ferrer, Pesticide Residue Research Group,y of Almeria, Almeria, [email protected]

the literature.3–13 The advantages of tandem mass spectrom-

etry are based on high sensitivity, reduction of sample-

treatment steps and reliable quantitation and confirmation at

the low required concentrations.11 The simplicity of meth-

odologies using the triple quadrupole as a detection

technique together with the low limits of detection achieved,

and the MS/MS capability, makes this technique a valuable

and unique tool for routine monitoring programs established

in regulatory official laboratories. The ease of use is some-

times an essential for these types of regulatory agencies,

which lack the highly skilled personnel required for more

sophisticated techniques.

The recent developments in stationary column phases,

such as the use of smaller particle sizes (1.7 and 1.8mm),11,14

have allowed improved peak resolution and, therefore,

increased sensitivity in chromatographic separations. The

van Deemter equation indicates that, as the particle size

decreases to less than 2.5mm, there is a significant gain in

efficiency and that efficiency does not diminish at increased

flow rates or linear velocities.15 This is especially useful when

Copyright # 2007 John Wiley & Sons, Ltd.

3870 I. Ferrer, E. M. Thurman and J. A. Zweigenbaum

the number of compounds is high since it allows the

separation and detection of all the compounds present in a

complex sample. The only requirement when coupling to

tandem mass spectrometry is to achieve rapid data

acquisition, so the improved resolution is not degraded.11

Currently more than 900 pesticides are used worldwide,

both legally and illegally, on food products and in the treat-

ment of soil and crops. Most of these pesticides have MRLs

for both food and water to protect consumers. The MRL

concentrations have to be monitored as part of the quality

control of food, especially fruits and vegetables; thus,

large-scale multi-residue methods with hundreds of pesti-

cides are needed for quality control. However, the ability to

monitor hundreds of pesticides in a single analysis is a

challenging problem both for chromatography and mass

spectrometry. Herewe evaluate a tandemmass spectrometry

methodology to not only screen but also to quantitate and

confirm 100 pesticides in a single analysis using a

combination of the new 1.8mm LC columns (for maximum

peak resolution) and two time segments with 100 transitions

per segment in order to have both a quantifier ion and

a qualifier ion, which satisfies the EU specifications for

unequivocal identification and confirmation by mass spec-

trometry.16 A validation study was carried out using

matrix-matched samples for quantitation and as alternative

to compensate effects of suppression or enhancement of

signal due to the matrix.

EXPERIMENTAL

Chemicals and reagentsPesticide analytical standards were purchased from both

Sigma (St. Louis, MO, USA) and Dr. Ehrenstorfer (Ausburg,

Germany) by Agilent and kindly supplied to us. Individual

pesticide stock solutions (approximately 1000mg/mL) were

prepared in pure acetonitrile or methanol depending on the

solubility of each individual compound, and stored at�188C.From these stock solutions, working standard solutions

were prepared by dilution with acetonitrile and water.

HPLC-grade acetonitrile and methanol were obtained from

Merck (Darmstadt, Germany). Formic acid was obtained

from Fluka (Buchs, Switzerland). A Milli-Q-Plus ultra-pure

water system from Millipore (Milford, MA, USA) was used

throughout the study to obtain the HPLC-grade water used

during the analyses.

Sample preparationVegetable and fruit samples were obtained from local

markets. ’Blank’ vegetable and fruit extracts were used to

prepare the matrix-matched standards for validation pur-

poses. In this way, two types of vegetables and one fruit

(green peppers, tomatoes and oranges) were extracted using

the QuEChERS method described previously.17,18 The final

vegetable extracts were spiked with the mix of standards at

different concentrations (ranging from 0.1 to 100mg/kg) and

subsequently analyzed by LC/MS/MS. The scope of this

work was simply to develop a method for the screening,

quantitation and confirmation of a large number of pesticides

in vegetable and fruit matrices, not to study the recovery of

this type of compounds from food matrices. This has already


been reported in various studies6,11,12 and, as the response of

every pesticide in the raw sample highly depends on the

recovery obtained, we decided that to spike directly the

matrices and to study the behavior of all the analytes was a

more fair, clear and broad comparison for this specific study.

LC/MS/MS analysesThe separation of the analytes was carried out using an

HPLC system (consisting of vacuum degasser, autosampler

and a binary pump, Agilent Series 1200; Agilent Technol-

ogies, Santa Clara, CA, USA) equipped with a reversed-

phase C18 analytical column of 150mm� 4.6mm and 1.8mm

particle size (Zorbax Eclipse SB-C18). Column temperature

was maintained at 258C. The injected sample volume was

10mL. Mobile phases A and B were acetonitrile and water

with 0.1% formic acid, respectively. The optimized chroma-

tographic method started at an initial mobile phase

composition of 10% A and gradually increased to 98% in

28min, then to 100% A in a further 2min, and finally held at

100% for 1min. The flow rate used was 0.6mL/min. A low

flow rate and a wide diameter column were used in order to

stretch the run time and allow improved separation between

the 100 compounds. A 10-min post-run time was used after

each analysis. This HPLC system was connected to a Agilent

6410 triple quadrupole mass spectrometer (Agilent Tech-

nologies) equipped with an electrospray ionization (ESI)

interface operating in positive ion, using the following

operating parameters: capillary voltage: 4000V; nebulizer

pressure: 40 psig; drying gas: 9 L/min; gas temperature:

3508C; dwell time: 10ms. The data recorded was processed

with the Mass Hunter software.

RESULTS AND DISCUSSION

Optimization of LC/MS/MS conditionsA preliminary study of the optimal MRM conditions for

every compound was carried out by injecting individual

standard solutions (1mg/mL) in acetonitrile/water (50:50).

All the compounds analyzed were detected with the ESI

source in positive ion mode. Full-scan spectra were acquired

first to optimize the collision-induced dissociation (CID)

fragmentation applied at the source via the fragmentor

voltage in order to obtain the maximum sensitivity for the

protonated molecule. Typically, the protonated molecule

was used as a precursor ion, except for one case (aldicarb, for

which a fragment ion had to be selected instead due to the

lack of protonated molecule in the spectrum). Secondly, MS/

MS spectra in product ion mode of operation were acquired

to obtain information on fragment ions. Once the product

ions (two) had been selected for every analyte, an MRM

experiment was carried out to select the optimum collision

energy for every specific transition. Various collision energies

(from 5 to 30 eV) were investigated. The optimum energies

were those ones that gave the best sensitivity for every

transition, and they were selected as optimum ones. An

example of this optimization is shown in Fig. 1 for linuron.

The product ion at m/z 182 was most sensitive at 15 eV and

the ion at m/z 160 was slightly more sensitive at 20 eV. This

process was carried out for all the other analytes studied and

specific information was obtained for each transition. Table 1


DOI: 10.1002/rcm

Figure 1. Example of optimization of the collision energy for linuron.

Screening of 100 pesticides in food samples by LC/MS/MS 3871

summarizes the most relevant MS settings such as fragmen-

tor voltage and collision energies used for each one of the 100

compounds investigated, as well as all the MRM transitions

selected for screening, quantitation and confirmation. These

were the MRM transitions selected in the validation study

with real matrices. The first transition shown was used for

quantitation (calibration curves and reproducibility) and the

second transition was used for confirmatory purposes and to

calculate limits of detection as well.

Chromatographic separation and dwell timeA slow gradient starting with 10% acetonitrile up to 100% in

30min was applied, which was first developed by our

group19 and has proven to be successful for the separation of

pesticide compounds. The use of a small particle size column

leads to very narrow peaks (approx. 5 s), in comparison with

conventional columns of 5mmwith peak widths of 15–20 s.20

The analytical column packed with non-porous 1.8mm

particles enabled elution of sample components in much

narrower, more concentrated, bands, resulting in better

chromatographic resolution and increased peak height. The

typical peak width was 5–10 s at base, thus permitting very

good separation of all compounds in only 30min. The

optimized gradient adequately resolved the geometric

isomers of bromuconazole, difeconazole, dimethomorph

and propiconazole (see Table 1).

Two different time segments were recorded in the

chromatographic run (each one of them containing about

half of the pesticides studied). In this way, a total of 100

transitions were monitored in each segment (50 compounds

per segment with two transitions each). The time segment

change was set up at 20min. Figure 2 shows the


chromatogram corresponding to the analysis of a tomato

sample spiked with the 100 pesticide mix, at a concentration

equivalent to 100 pg on column for all analytes (or 0.01mg/

kg). Extracted ion chromatograms are overlaid for each one

of the target analytes according to their respective MRM

quantifying transition.

In this study, the effect of reduced dwell times on mass

spectral quality and sensitivity was assessed in the devel-

opment of an analytical method for quantitative and

confirmatory purposes as well. Different dwell times were

tested between 5 and 20ms (Fig. 3). When higher dwell times

of 50 and 100ms (results not shown) were used the number

of data points were not enough to define a good chromato-

graphic peak. When the dwell time was between 5 or 10ms

the peak shape improved becoming Gaussian. Usually, a

chromatographic peak needs at least 10 data points to be

Gaussian. If we take into account that a peak is 10 s wide by

default, then a dwell time of 10ms is theoretically needed for

a total of 100 transitions to have an average of 10 data points

in each peak (1 data point per second). For this reason, a

common dwell time of 10ms was chosen for all the

transitions monitored.

MRM ion ratiosConfirmation of positive identifications in real samples

requires the additional second MRM transition and the

evaluation of ion ratios between the two monitored

transitions as compared to a reference standard. The con-

firmation criteria using tandem mass spectrometry cover a

range of maximum permitted tolerances for relative ion

intensity, expressed as a percentage of the intensity of the

most intense transition.21 Figure 4 shows the ion ratios for


DOI: 10.1002/rcm

Table 1. Retention times, MRM transitions and MS operating parameters selected for analysis of the 100 pesticides

Compound RT (min) Fragmentor voltage MRM transition (m/z) Collision energy (eV) LOD� (mg/kg)

Acetamiprid 12.2 80 223> 126 15 0.3223> 56 15

Acetochlor 23.1 120 270> 224 10 0.8270> 148 10

Alachlor 23.1 80 270> 238 10 0.8270> 162 15

Aldicarb 14.3 80 116> 89 5 2116> 70 5

Aldicarb sulfone 7.9 80 223> 76 5 5223> 148 5

Aldicarb sulfoxide 6.1 80 207> 89 5 2207> 132 5

Atrazine 17.5 120 216> 174 15 0.4216> 132 20

Azoxystrobin 21.3 120 404> 372 10 0.3404> 344 15

Benalaxyl 24.4 120 326> 148 10 0.5326> 294 5

Bendiocarb 16.5 80 224> 109 10 1224> 167 5

Bensulfuron-methyl 19 120 411> 149 20 0.4411> 182 15

Bromoxynil 17.9 120 278> 199 30 40278> 223 30

Bromuconazole 21.5þ 22.5 80 376> 159 20 1376> 70 20

Buprofezin 26.6 120 306> 201 10 0.7306> 116 15

Butylate 27.7 120 218> 57 10 5218> 156 10

Carbaryl 17.4 80 202> 145 5 10202> 117 10

Carbendazim 7.1 80 192> 160 15 0.5192> 132 20

Carbetamide 13.9 80 237> 118 10 0.5237> 192 5

Carbofuran 16.6 120 222> 165 10 0.9222> 123 15

Chlorfenvinphos 23.7 120 359> 155 10 2359> 127 15

Chlorotoluron 16.8 120 213> 72 20 0.3213> 140 20

Chlorpyrifos methyl 25.9 80 322> 125 15 10322> 290 15

Cyanazine 15.3 120 241> 214 15 2241> 174 15

Cyproconazole 20.3 120 292> 70 15 0.5292> 125 15

Cyromazine 3.4 120 167> 85 25 10167> 125 20

Deethylatrazine 11.2 120 188> 146 15 1188> 104 20

Deethylterbuthylazine 15.4 120 202> 146 15 0.8202> 110 20

Deisopropylatrazine 8.7 120 174> 96 15 4174> 132 15

Diazinon 25.3 160 305> 169 20 0.3305> 153 20

Dichlorvos 15.4 120 221> 109 15 5221> 145 15

Difeconazole 24.7þ 24.9 160 406> 251 20 0.3406> 337 15

Difenoxuron 18 120 287> 72 20 0.6287> 123 15

Diflubenzuron 22.3 80 311> 158 10 6311> 141 15

Dimethenamide 21.2 120 276> 244 10 0.4

(Continues)

Copyright # 2007 John Wiley & Sons, Ltd. Rapid Commun. Mass Spectrom. 2007; 21: 3869–3882

DOI: 10.1002/rcm


Table 1. (Continued)


276> 168 15Dimethoate 11.8 80 230> 199 5 0.7

230> 171 10Dimethomorph 19.2þ 19.6 120 388> 301 20 0.6

388> 165 25Diuron 17.1 120 233> 72 20 0.8

233> 160 20Ethiofencarb 17.9 80 226> 107 5 0.7

226> 164 5Fenamiphos 20.8 120 304> 217 20 0.6

304> 234 15Fenuron 11.2 120 165> 72 15 1.5

165> 120 15Flufenacet 23.0 80 364> 152 10 0.5

364> 194 5Flufenoxuron 27.6 80 489> 158 10 5

489> 141 15Fluometuron 17.9 120 233> 72 20 1

233> 160 20Fluroxypyr 14.9 80 255> 209 10 10

255> 181 15Hexaflumuron 25.1 120 461> 158 10 7

461> 141 20Hydroxyatrazine 8.1 120 198> 156 15 4

198> 86 20Imazalil 18.5 160 297> 159 20 10

297> 255 20Imazapyr 9.2 160 262> 217 15 0.7

262> 234 15Imazaquin 15.4 160 312> 199 25 0.6

312> 267 20Imidacloprid 11.4 80 256> 175 10 4

256> 209 10Ioxynil 19.6 120 372> 118 30 20

372> 245 30Iprodione 22.6 120 330> 245 10 12

330> 288 10Irgarol 1051 19.2 120 254> 198 15 0.8

254> 156 20Irgarol metabolite 13.6 120 214> 158 15 1.2

214> 110 20Isofenphos 26.4 80 346> 217 20 1

346> 245 10Isoproturon 17.7 120 207> 72 15 1.3

207> 165 15Lenacil 15.5 80 235> 153 10 8

235> 136 15Linuron 20.7 120 249> 160 20 1

249> 182 15Lufenuron 26.8 80 511> 158 10 3

511> 141 20Malathion 22.7 80 331> 99 10 0.8

331> 127 5Mebendazole 14.8 120 296> 264 20 0.6

296> 105 25Metalaxyl 17.7 120 280> 192 15 1

280> 220 10Metamitron 10.6 120 203> 175 15 0.9

203> 104 20Methidathion 20.8 80 303> 85 10 0.7

303> 145 5Methiocarb 20.4 80 226> 121 10 0.8

226> 169 5Methiocarb sulfone 13.2 80 258> 122 5 30

258> 217 10Methomyl 8.6 80 163> 88 5 0.8

163> 106 5

(Continues)


DOI: 10.1002/rcm




Metolachlor 23.2 120 284> 252 10 0.4284> 176 15

Metolcarb 15.3 80 166> 109 5 2166> 91 10

Metribuzin 15.9 120 215> 187 15 1215> 131 20

Molinate 22.2 120 188> 126 10 2188> 83 15

Monuron 14.9 120 199> 72 15 1.5199> 126 15

Nicosulfuron 13.7 120 411> 182 15 0.8411> 213 10

Nitenpyram 11.0 120 271> 225 10 0.7271> 99 15

Oxadixyl 14.9 80 279> 219 10 5279> 102 10

Parathion ethyl 24.6 120 292> 236 10 5292> 264 5

Pendimethalin 28.5 80 282> 212 5 4282> 194 10

Phosmet 21.2 80 318> 160 5 6318> 133 5

Prochloraz 23.2 80 376> 308 10 5376> 266 10

Profenofos 26.6 120 373> 303 15 5373> 345 10

Promecarb 20.9 80 208> 109 10 0.7208> 151 5

Prometon 14.0 120 226> 142 20 2226> 184 20

Prometryn 18.3 120 242> 158 20 0.9242> 200 20

Propachlor 19.1 80 212> 170 10 1212> 152 15

Propanil 19.8 120 218> 127 20 0.8218> 162 15

Propiconazole 23.7þ 24.0 120 342> 159 20 0.7342> 69 20

Prosulfocarb 27.1 120 252> 91 15 0.6252> 128 10

Simazine 14.9 120 202> 132 20 0.7202> 124 20

Spiromesifen 30.1 80 371> 273 5 7371> 255 20

Sulfosulfuron 18.4 120 471> 211 10 0.8471> 261 15

Teflubenzuron 25.6 80 381> 158 10 9381> 141 15

Terbuthylazine 20.5 120 230> 174 15 0.3230> 132 20

Terbutryn 18.6 120 242> 186 15 1242> 71 20

Thiabendazole 7.8 120 202> 175 30 6202> 131 30

Thiacloprid 14.0 120 253> 126 15 2253> 186 10

Thiocyclam 6.3 120 182> 137 10 50182> 73 20

Triazophos 22.9 120 314> 162 20 0.6314> 286 10

Triclocarban 25.2 120 315> 162 15 2315> 128 15

Trifloxystrobin 26.1 120 409> 186 15 0.4409> 206 10

Triflumizole 24.9 80 346> 278 5 3346> 73 10

RT: retention time.�LODs were calculated for all 100 compounds spiked in a green pepper matrix sample.


DOI: 10.1002/rcm


Figure 2. (a) Total ion chromatogram (TIC) corresponding to the analysis of the mix of 100 pesticides in a tomato matrix

(concentration: 0.01mg/kg or 100 pg on-column) using a 1.8mmC18 column. (b) Extracted ion chromatograms for the quantifying

MRM transition of each analyte.


benalaxyl in solvent and in an extract of green pepper spiked

with the pesticide mix at 50mg/kg (500 pg on-column). The

m/z 148 ionwas used for quantitation and them/z 294 ionwas

used as the qualifier ion, with a window set at �25% for an

ion ratio of 45. As shown in Fig. 4, in the two ion profiles

benalaxyl was easily identified in this complex matrix due to

the selectivity of the MRM transitions and instrument

sensitivity. Confirmation of the identity of the pesticides

in real samples is usually based in ion-ratio statistics for

the transitions monitored.22 Table 2 shows the ion ratios

obtained for all the compounds studied in solvent (expected


ratio) and in a green pepper matrix (observed ratio) at

50mg/kg concentration. As can be observed in this table

almost all the compounds can be confirmed in a vegetable

matrix sample by LC/MS/MS at the low-mg/kg level, being

the ion ratios in vegetable matrices within the tolerances

specified in the EU directives.22 The exceptions in the table

(marked with asterisks) are those cases where the analyte

was not sensitive enough (such is the case of bromoxynil,

ioxynil, lufenuron and methiocarb sulfone). In the case of

carbofuran the problem was the presence of an interferent

peak at the same retention time and with the same qualifying


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Figure 3. Effect of dwell time on atrazine.

Figure 4. Ion ratios for benalaxyl in (a) solvent and (b) green pepper matrix. Concentration: 50mg/kg.


ion transition. For prochloraz the problem was the poor

chromatography that this compound experiences in C18

columns due to the basicity of the protonated molecule.

Analytical performance

(a) Quantitation and confirmationQuantitation was performed using calibration with matrix-

matched standards to prevent slight variations in the signal

for some analytes and possible enhancement or suppression

of the signal from vegetable samples as compared to pure


solvent.19 For quantitation and confirmation purposes the

peak areas of both transitions (quantifier and qualifier) were

measured using the automated Mass Hunter quantitation

software. Using this approach, samples can be quantified

automatically by the use of batches, which include the files of

the calibration standards selected. An example is shown in

Fig. 5 for the neonicotinoid pesticide acetamiprid in a green

pepper matrix. As can be observed in this figure, a range of

values (retention times, peak areas and calculated concen-

trations) are obtained aswell as information on ion ratios and

calibration curve data. Values in light blue in the software


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Table 2. LC/MS/MS ion ratios (intensity of qualifying ion/intensity of quantifying ion) for the 100 pesticides spiked into solvent and

in a green pepper matrix sample at 50mg/kg

Compound Expected ratioa Observed ratiob Acceptable limit (%)c

Acetamiprid 35 37 25Acetochlor 47 45 20Alachlor 94 93 20Aldicarb 74 88 20Aldicarb sulfone 77 73 20Aldicarb sulfoxide 50 59 20Atrazine 20 19 25Azoxystrobin 19 19 30Benalaxyl 45 45 25Bendiocarb 50 51 25Bensulfuron-methyl 26 23 25Bromoxynil� 67 44 20Bromuconazole 18 17 30Buprofezin 54 58 20Butylate 5 3 50Carbaryl 6 7 50Carbendazim 6 5 50Carbetamide 35 38 25Carbofuran� 24 78 25Chlorfenvinphos 80 69 20Chlorotoluron 7 6 50Chlorpyrifos methyl 8 11 50Cyanazine 10 10 30Cyproconazole 24 25 25Cyromazine 58 55 20Deethylatrazine 19 18 30Deethylterbuthylazine 6 5 50Deisopropylatrazine 76 72 20Diazinon 55 52 20Dichlorvos 3 4 50Difeconazole 8 9 50Difenoxuron 47 44 25Diflubenzuron 49 53 25Dimethenamide 39 36 25Dimethoate 81 85 20Dimethomorph 42 43 25Diuron 4 4 50Ethiofencarb 7 7 50Fenamiphos 12 11 30Fenuron 2 2 50Flufenacet 51 47 20Flufenoxuron 14 16 30Fluometuron 4 5 50Fluroxypyr 97 90 20Hexaflumuron 70 65 20Hydroxyatrazine 45 44 25Imazalil 14 19 30Imazapyr 20 18 30Imazaquin 58 53 20Imidacloprid 76 69 20Ioxynil� 20 31 30Iprodione 6 5 50Irgarol 1051 5 5 50Irgarol metabolite 3 3 50Isofenphos 32 37 25Isoproturon 8 7 50Lenacil 2 1 50Linuron 76 67 20Lufenuron� 70 41 20Malathion 45 53 25Mebendazole 21 20 25Metalaxyl 63 60 20Metamitron 38 37 25Methidathion 55 51 20Methiocarb 80 79 20

(Continues)


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Compound Expected ratioa Observed ratiob Acceptable limit (%)c

Methiocarb sulfone� 5 0.2 50Methomyl 46 48 25Metolachlor 25 27 25Metolcarb 5 5 50Metribuzin 16 16 30Molinate 41 46 25Monuron 5 4 50Nicosulfuron 15 19 30Nitenpyram 61 58 20Oxadixyl 18 20 30Parathion ethyl 13 12 30Pendimethalin 27 28 25Phosmet 1 0.3 50Prochloraz� 20 38 30Profenofos 12 15 30Promecarb 61 56 20Prometon 39 37 25Prometryn 30 29 25Propachlor 6 7 50Propanil 94 107 20Propiconazole 53 47 20Prosulfocarb 10 8 30Simazine 82 76 20Spiromesifen 93 81 20Sulfosulfuron 75 73 20Teflubenzuron 40 50 25Terbuthylazine 10 9 50Terbutryn 6 6 50Thiabendazole 63 70 20Thiacloprid 4 3 20Thiocyclam 58 49 20Triazophos 3 3 50Triclocarban 89 73 20Trifloxystrobin 15 14 30Triflumizole 55 57 20

a Ratio determined from analysis of standard solutions (n¼ 3).b Ratio determined from analysis of spiked samples of green pepper (n¼ 3).c Reference 22 sets the criteria for the observed ratio as follows: expected ratio >50%, observed ratio should be within �20%; expected ratio>20–50%, observed ratio should be within �20%; expected ratio >10–20%, ratio should be within �30%; expected ratio �10%, ratio should bewithin �50%.�Compounds that exceeded the criteria.


(shown in white here) denote values between the expected

ion-ratio ranges, whereas values in red in the software

(shown in dark grey here) represent outlier values. In this

figure for example the outlier value of 50.1 corresponds to

the ion ratio that exceeded the theoretical value at this

low concentration. The expected ratio should be 35 for

acetamiprid, so the tolerated values (according to the 25%

tolerance) would be between 26.2 and 43.7.

(b) Linearity and limits of detectionLinearity was evaluated by analyzing the standard solutions

at six different concentration levels in the range from 0.1 to

100mg/kg. For the calibration curves only the area of the

quantifying transition was taken into account. As an

example, the calibration curves generated for four com-

pounds are shown in Fig. 6. As can be observed in this figure,

the linearity of the analytical response across the studied

range is excellent, with correlation coefficients higher than

0.998. In general, matrix-matched calibration curves were

linear between the concentrations studied with correlation

coefficients higher than 0.99 for all the matrices tested, with


the exception of those analytes with higher limits of detection

(LODs).

The LODs were estimated from the injection of matrix-

matched solutions at concentration levels corresponding to a

signal-to-noise ratio of about 3 for the quantitation ion and

presence of the confirmatory ion aswell. The results obtained

for all the standards spiked in a green pepper matrix are

included in Table 1. These LODs are higher and more reali-

stic than others reported for only one transition23 since it not

only takes into account the main transition, but also confirms

the compound with the second MRM transition. The best

LODs were obtained for acetamiprid, azoxystrobin, chloroto-

luron, diazinon, difeconazole, and terbuthylazine (0.3mg/kg

or 3pg on-column) and the highest LODs were for bro-

moxynil, ioxynil, methiocarb sulfone and thiocyclam (above

20mg/kg or 200 pg on-column). These are compounds that

do not ionize well under electrospray conditions in positive

ion mode. In some cases (i.e. imazalil, oxadixyl) the shape of

the peak from the separation in the C18 column is also the

cause for the poor LODobtained. In general, the LODs for the

100-pesticide mix met the requirements regarding the MRLs


DOI: 10.1002/rcm

Figure

5.Example

ofautomatedquantitationfortheneonicotinoid

pesticideacetamipridin

greenpeppermatrices(areasandexperimental

concentrationsare

shown).Ionratiosandcalibrationcurveare

shownaswell.


DOI: 10.1002/rcm


Figure

6.Calibrationcurvesforcarbofuran,deethylterbuthylazine,fenuronandparathion-ethylin

orangematrix

usingalinearfitwithno

weightingandnoorigin

treatm

ent.

Copyright # 2007 John Wiley & Sons, Ltd. Rapid Commun. Mass S


pectrom. 2007; 21: 3869–3882

DOI: 10.1002/rcm

Figure 7. MRM extracted chromatograms of a tomato sample for (a) buprofezin and (b) cyproconazole. Ion ratios are included.


imposed by the existing EU regulations which are close

to 10mg/kg.

The precision and repeatability of the method was

assessed using a 0.05mg/kg matrix-matched standard. Peak

area values were obtained for the quantifying ion, yielding a

relative standard deviation of 6% (median RSD) and a mean

RSD of 6.7% (n¼ 5).

(c) Matrix effectsMatrix effects are common in vegetable and fruit samples

due to the presence of natural products in such samples.

Matrix effects typically mean suppression; however, they

also mean matrix interferences that are present in the sample

and, hence, they show up in the detector. These effects can be

acute when using full-scan mass spectrometry techniques

such as the case of time-of-flight mass spectrometry and, in

fact, they have been reported in our previous work.19 When

using tandem mass spectrometric techniques these effects

are further minimized due to the higher selectivity of the two

MRM transitions.6,11 The presence of interfering peaks in the

chromatogram is diminished under these conditions. In this

study the calibration curves in solvent were plotted against

those in matrix and no significative differences in slope were

observed. This demonstrates that the use of LC/MS/MSwith

two MRM transitions is a highly selective technique that

discriminates any interferences present in the matrix. So,

standards in pure solvent could, in principle, be used for

quantitation. However, we prefer the use of matrix-matched

standards for quantitation in order to match as closely as

possible the samples and the standards used for quantitation.

Application to vegetable matricesTo confirm the suitability of the method for analysis of real

samples, several vegetable and fruit samples were analyzed

(green peppers, tomatoes and oranges). Positive findings for

three or more pesticides were obtained for all the samples

analyzed, but always at concentrations below 10mg/kg.

Figure 7 shows the analysis of a tomato sample analyzed by


the methodology described in this work. As can be observed

in the twoMS/MS extracted product ion chromatograms, for

buprofezin and cyproconazole, these two compounds could

be easily identified in these complex matrices due to the

selectivity of the two MRM transitions, thus fulfilling the

regulation limits imposed by the EU directives. Furthermore,

confirmation of these analytes was possible according to

themaximumpermitted tolerances for relative ion intensities

(ion ratios) as shown in this figure.

CONCLUDING REMARKS

A study to evaluate the effectiveness of LC/MS/MS for

screening, quantitation and confirmation of different families

of pesticides in vegetable and fruit samples was carried out.

The methodology developed in this work allowed the

screening of a large-scale number of pesticides, commonly

used in agricultural practices. Two MRM transitions were

monitored for each pesticide and ion-ratio information was

acquired for confirmatory purposes. We have demonstrated

that the sensitivity and selectivity achieved with this

methodology are appropriate for large-scale multi-residue

analysis of pesticides in food samples according to the

requirements imposed by the EU regulations. The potential

of the proposed method was established by analysis of

vegetable and fruit samples showing the presence of several

pesticides in these samples.

AcknowledgementsAnalytical standards, chromatographic columns and sol-

vents were kindly provided by Agilent Inc. All the analytical

work described in this manuscript was carried out by the

authors at the Agilent facilities in Little Falls (Wilmington,

Delaware, USA) in May of 2006. Travel funding from

Almeria to Wilmington was provided by Dr. Jerry Zweigen-

baum. Paul Zavitsanos is thanked for helpful discussions

and support with the instrument and Yanyan Fang for help

in sample preparation.


DOI: 10.1002/rcm


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DOI: 10.1002/rcm

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