Acta agriculturae Slovenica, 120/4, 1–14, Ljubljana 2024
doi:10.14720/aas.2024.120.4.16468 Original research article / izvirni znanstveni članek
Pesticide residues in vegetables-validation of the gas chromatography-tan-
dem mass spectrometry multiresidual method and a survey of vegetables 
on Slovenian market
Helena BAŠA ČESNIK 1,  2, Špela VELIKONJA BOLTA1
Received October 30, 2023; accepted October 07, 2024.
Delo je prispelo 30. oktober 2024, sprejeto 07. oktober 2024
1 Agricultural Institute of Slovenia, Hacquetova ulica 17, SI-1000 Ljubljana, Slovenia, PhD
2 Corresponding author: helena.basa@kis.si
Pesticide residues in vegetables-validation of the gas chroma-
tography-tandem mass spectrometry multiresidual method 
and a survey of vegetables on Slovenian market
Abstract: An analytical method for determining pesti-
cide residues in vegetables was introduced and validated. The 
extraction was conducted using acetone, dichloromethane and 
petroleum ether, to enable extraction of active substances with 
a wide range of polarity. Determination was conducted using 
gas chromatography coupled with tandem mass spectrometry. 
Method is according to extraction efficiency and determination 
sensitivity comparable to other methods for determination of 
pesticide residues such as QuEChERS. The method was applied 
in practice. A total of 35 active substances (pesticides) were 
sought in 50 vegetable samples gathered from Slovenian stores. 
The active substances sought were not determined in 86.0 % 
of the samples analysed. Among positive samples in carrot 
boscalid and fluopyram were found. 21.4 % of carrot samples 
were positive. In lamb`s lettuce boscalid and fludioxonil were 
determined. 50 % of lamb`s lettuce  samples were positive. In 
pepper boscalid, fluopyram and pyraclostrobin were found. 
16.7 % of pepper samples were positive. In tomato flonicamid, 
fluopyram and tebuconazole were determined. 11.1 % of toma-
to samples were positive. The results were compared with those 
from the literature and the outcome was that vegetables from 
Slovenia contained boscalid, fluopyram, pyraclostrobin and te-
buconazole, which were found also in China, Italy and Turkey.
Key words: vegetables. GC-MS/MS, pesticide residues. 
multiresidual method
Ostanki fitofarmacevtskih sredstev v zelenjavi - validacija 
multirezidualne metode s plinsko kromatografijo sklopljeno 
s tandemsko masno spektrometrijo in preiskava zelenjave na 
trgu v Sloveniji
Izvleček: Uvedli in validirali smo analizno metodo 
za določanje ostankov fitofarmacevtskih sredstev v zelen-
javi. Ekstrakcijo smo izvedli z acetonom, diklormetanom in 
petroletrom, ter s tem omogočili ekstrakcijo aktivnih snovi s 
širokim razponom polarnosti. Določitev smo izvedli s plinsko 
kromatografijo sklopljeno s tandemsko masno spektrometrijo. 
Metoda je glede na učinkovitost ekstrakcije in občutljivost pri 
določitvi, primerljiva z drugimi metodami za določevanje os-
tankov fitofarmacevtskih sredstev kot je QuEChERS metoda. 
Metodo smo uporabili v praksi. V 50 vzorcih zelenjave iz slov-
enskih trgovskih polic smo določali skupno 35 aktivnih spojin 
(pesticidov). Iskanih aktivnih snovi nismo določili v 86,0 % 
analiziranih vzorcev. Med pozitivnimi vzorci smo v korenju 
našli boskalid in fluopiram. 21,4 % vzorcev korenja je bilo 
pozitivnih. V motovilcu smo določili boskalid in fludioksonil. 
50 % vzorcev motovilca je bilo pozitivnih. V papriki smo našli 
boskalid, fluopiram in piraklostrobin. 16,7 % vzorcev paprike 
je bilo pozitivnih. V paradižniku smo določili flonikamid, 
fluopiram in tebukonazol. 11,1 % vzorcev paradižnika je bilo 
pozitivnih. Rezultate smo primerjali z literaturnimi podatki 
in ugotovili, da je zelenjava v Sloveniji vsebovala boskalid, 
fluopiram, piraklostrobin in tebukonazol, ki so jih določili 
tudi na Kitajskem, v Italiji in Turčiji.
Ključne besede: zelenjava, GC-MS/MS, ostanki fito-
farmacevtskih sredstev, multirezidualna metoda
Acta agriculturae Slovenica, 120/4 – 20242
H. BAŠA ČESNIK et al.
1 INTRODUCTION
Vegetable is important source of nutrients, vitamins 
and fibers and is consumed daily by human popula-
tion. To produce it in quantities large enough for whole 
population, farmers have to use plant protection prod-
ucts (PPPs) to protect it against numerous diseases and 
insects attacking vegetables. But demanding consumers 
require not only healthy but also safe food. Therefore it 
is important to monitor PPPs residues in food products 
on the market.
Numerous analytical methods have been developed 
to analyse PPPs residues in food. In the past there were 
three main routes for extraction procedure: acetone (Díez 
et al., 2006, Pizzutti et al., 2009), ethyl acetate (Sharif et al., 
2006) and acetonitrile (Anastassiades et al., 2003, Leho-
tay and Maštovska, 2005, Lehotay, 2007). Nowadays most 
of laboratories use Quick Easy Cheap Effective Rugged 
and Safe method also called QuEChERS method, where 
acetonitrile is used (Calderon et al., 2022, Ngabirano and 
Birungi, 2022, Sahyoun et al., 2022, Tankiewicz and Berg, 
2022). The advantage of this method is, that it is less time 
consuming and needs lower volumes of organic solvent. 
In our laboratory we are using method with acetone, to 
which dichloromethane and petroleum ether were added 
so that active substances of wide range of polarity can be 
extracted (Baša Česnik and Gregorčič, 2003, Baša Česnik 
et al., 2006) from very polar (for instance, flonicamid) to 
non-polar (for instance, cyhalothrin-lambda). In this pa-
per we present simplified extraction procedure with the 
same three solvents, which is similarly as the QuEChERS 
method less time consuming and needs lower volumes of 
organic solvents as previous one. 
Determination of PPPs residues is nowadays usually 
performed using gas chromatography coupled with mass 
spectrometry (GC-MS) (Knežević and Serdar, 2009, San-
tarelli et al., 2018), gas chromatography coupled with 
tandem mass spectrometry (GC-MS/MS) (Calderon et 
al., 2022, Ngabirano and Birungi, 2022, Sahyoun et al., 
2022, Tankiewicz and Berg, 2022) and/or liquid chroma-
tography coupled with tandem mass spectrometry (LC-
MS/MS) (Balkan and Yilmaz, 2022, Qin et al., 2021). The 
most sensitive is tandem mass spectrometry, which was 
also used in our laboratory. 
Numerous authors have analysed pesticide residues 
in vegetables with GC-MS/MS. Calderon et al. (2022) 
analysed 22 active substances in vegetables from Chile 
and Mexico. Ngabirano and Birungi (2022) analysed 1 
active substance in vegetables from Uganda. Sahyoun 
et al. (2022) tested vegetable samples from France and 
Lebanon for 14 active substances.  Tankiewicz and Berg 
(2022) introduced a method for determining 31 active 
substances in Polish vegetables. Up to 11 of active sub-
stances sought in these studies were introduced in our 
study as well. Our selection of active substances was 
based on both, those authorised for use in Slovenia (94.3 
%) and those not authorised for use in Slovenia, but au-
thorised in previous years (5.7 %), the latter to cover mis-
use of PPPs Of those selected, 57.2 % were fungicides, 
25.7 % were acaricides and/or insecticides and 17.1 % 
were herbicides. 
The purpose of this paper is to present the multire-
sidual GC-MS/MS method introduced for identifying 
35 active substances in vegetables using acetone, dichlo-
romethane and petroleum ether as the extraction solvent. 
The validation parameters for lettuce, potato and tomato 
are summarised, as well as the practical use of the meth-
od on 50 samples of vegetables gathered from Slovenian 
stores. The most problematic were carrot, where boscalid 
and fluopyram were found, lamb`s lettuce where bos-
calid and fludioxonil were determined, pepper where 
boscalid, fluopyram and tebuconazole were found and 
tomato where flonicamid, fluopyram and tebuconazole 
were determined. Concentrations of active substances 
were in range 0.005–0.060 mg kg-1. All concentrations 
were below valid Maximum Residue Levels (MRLs). The 
contents of pesticide residues were compared with those 
from the literature. Finally, a risk assessment for consum-
ers was conducted.
2 MATERIALS AND METHODS
2.1 MATERIALS
2.1.1 Chemicals
The certified standards were supplied by Dr. Ehren-
storfer (Augsburg, Germany). The acetone - p.a. grade, 
dichloromethane – p.a. grade, petroleum ether – p.a. 
grade (used for the extraction procedure) and acetone 
Acta agriculturae Slovenica, 120/4 – 2024 3
Pesticide residues in vegetables - validation of the gas chromatography-tandem mass spectrometry ... vegetables on Slovenian market
HPLC-grade (used for preparation of standards) were 
supplied by J.T.Baker (Deventer, Netherlands). All other 
chemicals used were supplied by Sigma-Aldrich (Stein-
heim, Germany). The water used was MilliQ deionised 
water. 
2.1.2 Preparation of the solutions
Stock solutions in acetone of individual active sub-
stances were prepared with the concentrations of 625 mg 
Active substance Activity typea MRM transitions (Q1, Q2, Q3, Q4)b Dwell (ms) CE (V)c
azoxystrobin F 344→329.1, 344→171.9, 344→155.8 40 10, 40, 40
benthiavalicarb-isopropyl F 181→180, 181→126.9, 181→83.1 20.3, 17.6 20, 40, 40
boscalid F 140→112, 140→76 45.7 10, 30
clomazone H 204→107, 125→99 87.2 20, 20
cyflufenamid F 412→118.1, 412→89.9, 118→90.1, 118→63 8.2, 8.6 30, 40, 10, 40
cypermethrin A, I 181→152.1, 181→126.9, 181→76.9 24.2, 19.7, 19.1, 22.1 30, 40, 40
cyprodinil F 225→223.7, 224→208.1 17.3 20, 20
deltamethrin I 253→171.9, 253→93.1, 253→77 26.9 10, 20, 40
fenhexamid F 301→176.9, 301→97, 301→54.8 13.5 10, 10, 40
flonicamid I 174→146, 174→126, 174→69 77.6 10, 20, 40
fluazifop-p-butyl H 383→282.1, 254→146 8.2 10, 20
fludioxonil F 248→182.1, 248→154.1, 248→127.1 9.7 10, 20, 30
flufenacet H 151→136.1, 151→95.1 30.2 10, 30
fluopicolide F 347→172, 209→182, 173→145 14.5 30, 20, 10
fluopyram F 173→145, 173→95.1 15.3 20, 30
flutolanil F 172.8→145, 172.8→95, 172.8→75 12.6 15, 35, 55
indoxacarb I 264→176, 264→147.9, 264→112.9 23.7 10, 30, 40
iprovalicarb F 158→98, 158→72.1, 158→55.1 8.6, 8.1 10, 10, 20
kresoxim-methyl F 206→131.1, 206→116.1 12.7 10, 10
lambda-cyhalothrin I 181→152.1, 181→127.1, 181→77.1 18.6, 17.6 20, 30, 40
metazachlor H 209→132.1, 209→117.1, 133→131.7 14 20, 40, 20
metrafenone F 408→393, 393→378, 379→364 29.9 10, 10, 10
myclobutanil F 179→125, 179→90, 179→63 8.6 10, 40, 40
penconazole F 248→206.1, 248→192.1, 248→157.1 12.7 10, 10, 30
pendimethalin H 252→191.1, 252→162.1, 252→106.1 12.2 10, 10, 40
pirimicarb I 238→166.1, 166→96.1 33.4 10, 10
proquinazid F 288→245, 288→217, 272→216 13.5 10, 30, 20
prosulfocarb H 251→128.1, 162→91.1, 162→65 32.5 10, 10, 40
pyraclostrobin F 164→132.1, 164→104, 132→104 34.1 10, 30, 10
pyrimethanil F 198→183.1, 198→118 63.4 20, 40
pyriproxyfen I 226→186.1, 226→77.1 21.1 10, 40
tebuconazole F 250→153, 250→125, 250→70 10.2 10, 30, 10
tebufenpyrad A 335→319.9, 333→318.2, 333→276.1 21.3 10, 10, 10
tefluthrin I 177→137, 177→127, 177→87.1 36.6 20, 20, 40
tetraconazole F 336→218.1, 336→164 24.7 20, 30
Table 1: The active substances sought, their activity type, MRM transitions, dwell time and collision energy 
a A = acaricide, I = insecticide, F = fungicide, H = herbicide
b Q = qualifier ion, bold qualifier was used for integration
c CE = collision energy
Acta agriculturae Slovenica, 120/4 – 20244
H. BAŠA ČESNIK et al.
2.4 VALIDATION OF METHODS
Method was validated on three representatives of 
vegetables: lettuce, which contains a lot of chlorophyll, 
potato, which contains a lot of starch and tomato which 
is acidic matrix.
2.4.1 LOQ and linearity
The linearity was verified using the matrix match 
standards (two repetitions for one concentration level, 
four to eight concentration levels for the calibration 
curve). The linearity and range were determined by lin-
ear regression, using the F test. 
LOQs were estimated from the chromatograms of 
matrix match standards. LOQs were chosen at a mini-
mum of S/N = 10. 
2.4.2 Precision
Blank lettuce, potato and tomato were bought in 
store and analysed to prove that they contain no pesti-
cide residues. For the determination of precision (ISO 
5725), i.e. repeatability and reproducibility, the extracts 
of spiked blank lettuce, potato and tomato were analysed 
at LOQ. Within a period of 10 days, two parallel extracts 
were prepared each day for each concentration level. 
Each one was injected once. Then the standard deviation 
of the repeatability of the level and the standard deviation 
of reproducibility of the level were both calculated. 
2.4.3 Uncertainty of repeatability and uncertainty of 
reproducibility
The uncertainty of repeatability and the uncer-
tainty of reproducibility were calculated by multiplying 
the standard deviation of repeatability and the standard 
deviation of reproducibility by the Student’s t factor, for 
nine degrees of freedom and a 95 % confidence level (t95;9 
= 2.262). 
Ur = t95; 9 x sr ; UR = t95; 9 x sR
The measurement uncertainty for PPPs residues 
should be 50 %, as proposed in SANTE/11312/2021. 
When validating, analysts must prove that their meas-
urement uncertainty is below or equal to the proposed 
measurement uncertainty. 
pesticide ml-1. From 35 stock solutions, three mixed so-
lutions of all 35 active substances were prepared with a 
concentration of 5 mg ml-1, 1 mg ml-1 and 0.1 mg ml-1.
2.2 EXTRACTION PROCEDURE
To 20 g of sample in the beaker, 30 ml of acetone : 
dichloromethane : petroleum ether = 1 (v) : 2 (v) : 2 (v) 
was added. The mixture was homogenised for 2 minutes 
with a mixer. 10 g of anhydrous Na2SO4 was added. The 
mixture was homogenised for 2 minutes with a mixer. 
The whole content was filtered through filter paper black 
ribbon, which contained 20 g of anhydrous Na2SO4, into 
a 500 ml Soxhlet flask. Matrix was returned to the same 
beaker, 30 ml of acetone: dichloromethane: petroleum 
ether = 1 (v): 2 (v): 2 (v) was added,  mixture was homog-
enised for 2 minutes with a mixer and afterwards filtered 
through the same filter paper as previously. Last step was 
repeated twice. Then solvent solution in Soxhlet flask was 
evaporated to approximately 2 ml on a rotavapor and 
dried with nitrogen flow. The dry eluate was dissolved in 
2 ml of acetone for HPLC using ultrasound in order to 
prepare a sample. Extract was filtered with 0.2 mm pore 
size filter. 
2.3 DETERMINATION
The samples were analysed using a gas chromato-
graph (Agilent Technologies 8890, Shanghai, China) cou-
pled with tandem mass spectrometer (Agilent Technolo-
gies 7010B, Santa Clara, USA ), equipped with a Gerstel 
20PRE0795 multipurpose sampler (Gerstel, Sursee, Swit-
zerland) and a HP-5 MS UI column (Agilent Technolo-
gies, 30 m, 0.25 mm i.d., 0.25 μm film thickness) with a 
constant flow of helium at 1.2 ml min-1. The GC oven was 
programmed as follows: 55 °C for 2 min, from 55 °C to 
100 °C at 20 °C min-1, from 100 °C to 280 °C at 4 °C min-1, 
held at 280 °C for 19.75 min. The temperature of the ion 
source was 230 °C, the auxiliary temperature was 280 °C 
and the quadrupoles temperature was 150 °C. For quali-
tative and quantitative determination, the MRM transi-
tions were used. For each active substance two to four 
transitions, presented in Table 1, were used. The calibra-
tion was performed to matrix match standards.
Acta agriculturae Slovenica, 120/4 – 2024 5
Pesticide residues in vegetables - validation of the gas chromatography-tandem mass spectrometry ... vegetables on Slovenian market
No. of sample Crop Type of production Origin State of crop Sample mass (kg)
1 brussels sprouts conventional Netherlands fresh 1.1
2 carrot conventional Slovenia frozen 0.9
3 carrot conventional Slovenia frozen 0.9
4 carrot conventional Slovenia fresh 1.3
5 carrot conventional Austria processed 1.2
6 carrot conventional Slovenia processed 2
7 carrot organic Italy fresh 1
8 carrot organic Italy fresh 1
9 carrot conventional Slovenia fresh 1
10 carrot conventional Slovenia fresh 1.1
11 carrot conventional Slovenia fresh 1.2
12 carrot conventional Slovenia fresh 2.5
13 carrot conventional Slovenia fresh 2.5
14 carrot conventional Slovenia fresh 2.5
15 carrot organic Italy fresh 2
16 cauliflower conventional unknown frozen 1
17 cauliflower conventional Netherlands fresh 1.7
18 cauliflower organic Italy fresh 1
19 cauliflower conventional Croatia fresh 1.8
20 kale conventional Croatia fresh 1.2
21 lamb’s lettuce conventional Italy fresh 0.5
22 lamb’s lettuce organic Italy fresh 0.5
23 lamb’s lettuce conventional Italy fresh 0.5
24 lamb’s lettuce conventional Croatia fresh 0.5
25 lettuce conventional Slovenia fresh 1
26 lettuce conventional Slovenia fresh 1
27 pepper organic Italy fresh 1.6
28 pepper organic Italy fresh 1.2
29 pepper organic Italy fresh 1.8
30 pepper conventional Macedonia fresh 1.3
31 pepper conventional Poland fresh 1.5
32 pepper conventional Italy fresh 1.2
33 spinach organic Italy frozen 1.2
34 spinach conventional Slovenia frozen 0.9
35 spinach organic Italy fresh 0.5
36 spinach conventional Croatia fresh 0.5
37 spinach organic Italy fresh 1
38 tomato organic Italy processed 1
39 tomato conventional Italy processed 1
40 tomato conventional Italy processed 1
41 tomato conventional Croatia fresh 1.5
42 tomato conventional Slovenia fresh 1.1
43 tomato conventional Croatia fresh 1.2
44 tomato conventional Croatia fresh 1
45 tomato conventional Croatia fresh 1.1
46 tomato organic Italy fresh 1
47 zucchini conventional Italy fresh 1.3
48 zucchini organic Italy fresh 1
49 zucchini conventional Croatia fresh 1.5
50 zucchini organic Italy fresh 1
Table 2: Vegetable samples collected from stores in Slovenia in 2023 .
Acta agriculturae Slovenica, 120/4 – 20246
H. BAŠA ČESNIK et al.
2.4.4 Accuracy
The accuracy was verified by checking the recover-
ies. The average of the recoveries from the tests for preci-
sion (10 days, 2 parallel samples each day) was calculat-
ed. According to the requirements for method validation 
procedures (SANTE/11312/2021), acceptable mean re-
coveries are those within the range of 70 % to 120 %, with 
an associated repeatability of RSDr ≤ 20 %. 
According to the guidelines for single-laboratory 
validation (Alder et al. 2000), acceptable mean recoveries 
at level > 0.001 mg kg-1 ≤ 0.01 mg kg-1 are those within 
the range of 60 % to 120 %, with an associated repeat-
ability RSDr ≤ 30 %.
2.5 CONSUMER RISK ASSESSMENT
Long-term exposure was calculated using the EFSA 
PRIMo model revision 3.1 (EFSA, 2024). Input values 
were supervised trial median residues (STMRs) and Ac-
ceptable Daily Intakes (ADIs). Chronic consumer expo-
sure was expressed in % of the ADI. The acceptable limit 
for long-term exposure is 100 % of the ADI. 
Short-term exposure was calculated using the EFSA 
PRIMo model revision 3.1. Input values were the high-
est residues (HRs) and Acute Reference Doses (ARfDs). 
Where ARfDs were not allocated, ADIs were used in-
stead. Acute consumer exposure was expressed in % of 
the ARfD. The acceptable limit for short-term exposure 
is 100 % of the ARfD.
2.6 SAMPLING
A total of 50 vegetable samples were collected in 
September 2023 on Slovenian market. The sampling dis-
tribution is presented in Table 2. Processed carrot was 
cooked carrot in salt solution and processed tomato was 
tomato paste.
3 RESULTS AND DISCUSSION
3.1 COMPARISON OF PREVIOUS AND PRESENT 
EXTRACTION METHOD WITH ACETONE, 
DICHLOROMETHANE AND PETROLEU-
METHER
In our previous method (Baša Česnik and Gregorčič, 
2003, Baša Česnik et al., 2006) separation of water and 
organic phase was conducted in separatory funnels, 
which is time consuming and physically demanding. In 
present method this phase is no longer required. Water is 
eliminated by adding anhydrous Na2SO4 directly to the 
mixture of matrix and solvents.
Also, in previous method (Baša Česnik and 
Gregorčič, 2003, Baša Česnik et al., 2006) 74 ml of ac-
etone p.a., 148 ml of dichloromethane p.a. and 148 ml 
of petroleum ether p.a. were used per sample. In pre-
sent method only 18 ml of acetone p.a., 36 ml of dichlo-
romethane p.a. and 36 ml of petroleum ether p.a. were 
used per sample. Therefore approximately 4-times lower 
amounts of solvents were used.
3.2 VALIDATION OF METHOD
3.2.1 LOQ and linearity
The linear model is valid for all active substances 
presented in Tables 3-5. Linearity was proven in the 
range of 0.005 mg kg-1 to 0.04 mg kg-1 for all active sub-
stances for lettuce, potato and tomato. R2 ranged from 
0.953 to 0.999 for lettuce, from 0.970 to 0.999 for potato 
and from 0.960 to 0.997 for tomato. Results are presented 
in Tables 3-5.
3.2.2 Accuracy
The results for the recoveries are given in Tables 3-5. 
The recoveries at LOQs for the active substances scanned 
with GC-MS/MS are in the range of 73.4 % to 94.3 %, 
with RSDs of 11.7 % to 17.8 % for lettuce, 75.0 % to 89.0 
%, with RSDs of 8.6 % to 18.3 % for potato and 81.8 % to 
100.9 %, with RSDs of 9.6 % to 16.7 % for tomato.
All recoveries and RSDs are within the re-
quired ranges from the literature (Alder et al., 2000; 
SANTE/11813/2017).
3.2.3 Uncertainty of repeatability and uncertainty of 
reproducibility
Acta agriculturae Slovenica, 120/4 – 2024 7
Pesticide residues in vegetables - validation of the gas chromatography-tandem mass spectrometry ... vegetables on Slovenian market
Active substance
Linearity range 
(mg kg-1) R2
LOQ 
(mg 
kg-1)
Recovery 
(%) RSD (%)a Ur (mg kg
-1)b Ur (%)
c UR (mg kg
-1)d UR (%)
e
azoxystrobin 0.005-0.04 0.985 0.005 80.6 12.3 0.0008 15.9 0.0011 22.7
benthiavalicarb-isopro-
pyl
0.005-0.04 0.995 0.005 84.6 16.1 0.0007 14.3 0.0016 31.5
boscalid 0.005-0.04 0.984 0.005 77.1 16.3 0.0010 19.8 0.0014 28.8
clomazone 0.005-0.04 0.953 0.005 88.7 16.7 0.0014 27.1 0.0017 33.9
cyflufenamid 0.005-0.04 0.983 0.005 81.0 13.0 0.0006 12.2 0.0012 24.2
cypermethrin 0.005-0.04 0.994 0.005 78.8 16.2 0.0009 17.5 0.0015 29.4
cyprodinil 0.005-0.04 0.999 0.005 86.5 12.2 0.0006 11.8 0.0012 24.5
deltamethrin 0.005-0.04 0.988 0.005 74.0 17.0 0.0009 18.3 0.0014 28.9
fenhexamid 0.005-0.04 0.995 0.005 84.2 14.3 0.0008 15.9 0.0014 27.7
flonicamid 0.005-0.04 0.993 0.005 93.3 12.5 0.0007 13.1 0.0013 27.0
fluazifop-p-butyl 0.005-0.04 0.995 0.005 82.7 13.1 0.0005 10.9 0.0013 25.1
fludioxonil 0.005-0.04 0.972 0.005 80.8 17.1 0.0008 15.5 0.0016 31.9
flufenacet 0.005-0.04 0.991 0.005 83.4 12.9 0.0010 20.5 0.0012 24.6
fluopicolide 0.005-0.04 0.987 0.005 85.5 13.2 0.0007 13.9 0.0013 26.1
fluopyram 0.005-0.04 0.993 0.005 89.2 11.7 0.0006 12.2 0.0012 24.1
flutolanil 0.005-0.04 0.994 0.005 89.2 11.9 0.0006 12.2 0.0012 24.6
indoxacarb 0.005-0.04 0.980 0.005 73.4 16.9 0.0008 15.1 0.0014 28.6
iprovalicarb 0.005-0.04 0.997 0.005 86.3 13.6 0.0007 13.5 0.0014 27.0
kresoxim-methyl 0.005-0.04 0.990 0.005 82.7 12.0 0.0005 10.7 0.0012 23.0
lambda-cyhalothrin 0.005-0.04 0.991 0.005 82.5 14.1 0.0007 13.8 0.0013 26.9
metazachlor 0.005-0.04 0.980 0.005 85.9 12.5 0.0008 15.6 0.0012 24.6
metrafenone 0.005-0.04 0.982 0.005 79.8 14.1 0.0007 14.7 0.0013 25.9
myclobutanil 0.005-0.04 0.989 0.005 84.5 12.9 0.0006 12.6 0.0013 25.2
penconazole 0.005-0.04 0.999 0.005 89.2 12.4 0.0006 12.9 0.0013 25.4
pendimethalin 0.005-0.04 0.997 0.005 81.1 13.7 0.0007 14.4 0.0013 25.6
pirimicarb 0.005-0.04 0.994 0.005 94.3 12.6 0.0007 13.8 0.0014 27.5
proquinazid 0.005-0.04 0.998 0.005 81.2 13.3 0.0006 12.1 0.0012 25.0
prosulfocarb 0.005-0.04 0.994 0.005 87.4 12.3 0.0006 12.1 0.0012 24.8
pyraclostrobin 0.005-0.04 0.986 0.005 73.5 17.8 0.0009 17.8 0.0015 30.2
pyrimethanil 0.005-0.04 0.988 0.005 91.9 12.4 0.0007 13.5 0.0013 26.4
pyriproxyfen 0.005-0.04 0.995 0.005 80.5 13.7 0.0006 12.4 0.0013 25.4
tebuconazole 0.005-0.04 0.996 0.005 85.0 14.0 0.0007 14.8 0.0014 27.4
tebufenpyrad 0.005-0.04 0.987 0.005 81.1 14.0 0.0007 13.5 0.0013 26.2
tefluthrin 0.005-0.04 0.996 0.005 89.7 12.3 0.0007 13.2 0.0013 25.4
tetraconazole 0.005-0.04 0.998 0.005 89.4 12.1 0.0007 13.2 0.0013 25.0
Table 3: Validation parameters for lettuce
a RSD was obtained during recovery analyses
b,c  Ur = uncertainty of repeatability
d,e  UR = uncertainty of reproducibility
Acta agriculturae Slovenica, 120/4 – 20248
H. BAŠA ČESNIK et al.
a RSD was obtained during recovery analyses
b,c  Ur = uncertainty of repeatability
d,e  UR = uncertainty of reproducibility
Active substance
Linearity range 
(mg kg-1) R2
LOQ (mg 
kg-1)
Recovery 
(%)
RSD 
(%)a
Ur (mg 
kg-1)b Ur (%)
c UR (mg kg
-1)d UR (%)
e
azoxystrobin 0.005-0.04 0.981 0.005 87.9 16.9 0.0009 17.7 0.0017 34.2
benthiavalicarb-isopropyl 0.005-0.04 0.981 0.005 86.4 11.7 0.0007 14.6 0.0012 23.3
boscalid 0.005-0.04 0.984 0.005 86.3 12.4 0.0007 13.9 0.0012 24.8
clomazone 0.005-0.04 0.988 0.005 88.5 14.9 0.0009 18.0 0.0015 30.4
cyflufenamid 0.005-0.04 0.990 0.005 79.2 10.6 0.0006 12.6 0.0010 19.3
cypermethrin 0.005-0.04 0.988 0.005 75.0 17.2 0.0009 17.1 0.0015 29.7
cyprodinil 0.005-0.04 0.997 0.005 82.2 9.3 0.0006 13.0 0.0009 17.4
deltamethrin 0.005-0.04 0.976 0.005 78.1 16.4 0.0009 18.0 0.0015 29.4
fenhexamid 0.005-0.04 0.987 0.005 85.7 12.2 0.0008 16.0 0.0012 24.0
flonicamid 0.005-0.04 0.991 0.005 81.2 9.1 0.0007 14.0 0.0008 16.9
fluazifop-p-butyl 0.005-0.04 0.994 0.005 78.7 11.8 0.0007 13.6 0.0011 21.4
fludioxonil 0.005-0.04 0.980 0.005 82.0 12.2 0.0008 16.4 0.0011 22.9
flufenacet 0.005-0.04 0.992 0.005 82.7 9.3 0.0007 13.2 0.0009 17.5
fluopicolide 0.005-0.04 0.970 0.005 83.6 9.2 0.0007 13.4 0.0009 17.6
fluopyram 0.005-0.04 0.991 0.005 82.6 10.1 0.0006 12.2 0.0010 19.1
flutolanil 0.005-0.04 0.995 0.005 81.5 10.8 0.0006 12.5 0.0010 20.3
indoxacarb 0.005-0.04 0.974 0.005 85.6 18.3 0.0009 18.7 0.0018 36.2
iprovalicarb 0.005-0.04 0.991 0.005 84.4 10.2 0.0006 12.2 0.0010 19.8
kresoxim-methyl 0.005-0.04 0.990 0.005 81.5 9.9 0.0006 12.3 0.0009 18.5
lambda-cyhalothrin 0.005-0.04 0.984 0.005 77.2 13.1 0.0007 14.7 0.0012 23.3
metazachlor 0.005-0.04 0.995 0.005 83.2 9.4 0.0007 13.2 0.0009 17.9
metrafenone 0.005-0.04 0.980 0.005 83.1 12.3 0.0007 14.9 0.0012 23.4
myclobutanil 0.005-0.04 0.988 0.005 83.2 9.7 0.0006 12.9 0.0009 18.5
penconazole 0.005-0.04 0.991 0.005 82.5 9.6 0.0007 13.6 0.0009 18.2
pendimethalin 0.005-0.04 0.992 0.005 75.0 10.9 0.0006 12.4 0.0009 18.7
pirimicarb 0.005-0.04 0.997 0.005 82.1 9.7 0.0007 14.5 0.0009 18.1
proquinazid 0.005-0.04 0.987 0.005 80.9 10.3 0.0007 13.2 0.0010 19.2
prosulfocarb 0.005-0.04 0.996 0.005 79.9 9.2 0.0006 12.8 0.0008 16.8
pyraclostrobin 0.005-0.04 0.977 0.005 89.0 17.7 0.0009 18.4 0.0018 36.4
pyrimethanil 0.005-0.04 0.995 0.005 82.5 8.6 0.0006 12.9 0.0008 16.2
pyriproxyfen 0.005-0.04 0.980 0.005 81.5 11.6 0.0007 14.2 0.0011 21.7
tebuconazole 0.005-0.04 0.984 0.005 84.6 10.2 0.0007 13.9 0.0010 19.9
tebufenpyrad 0.005-0.04 0.980 0.005 81.8 11.4 0.0007 14.2 0.0011 21.4
tefluthrin 0.005-0.04 0.999 0.005 75.0 9.3 0.0006 13.0 0.0008 16.0
tetraconazole 0.005-0.04 0.991 0.005 82.4 10.3 0.0007 14.3 0.0010 19.5
Table 4: Validation parameters for potato
Acta agriculturae Slovenica, 120/4 – 2024 9
Pesticide residues in vegetables - validation of the gas chromatography-tandem mass spectrometry ... vegetables on Slovenian market
Active substance
Linearity range 
(mg kg-1) R2
LOQ (mg 
kg-1)
Recovery 
(%)
RSD 
(%)a
Ur (mg 
kg-1)b Ur (%)
c UR (mg kg
-1)d UR (%)
e
azoxystrobin 0.005-0.04 0.960 0.005 97.1 16.0 0.0009 19.0 0.0018 35.8
benthiavalicarb-isopropyl 0.005-0.04 0.965 0.005 88.7 12.5 0.0010 19.5 0.0013 25.3
boscalid 0.005-0.04 0.963 0.005 90.3 11.2 0.0006 11.7 0.0012 23.4
clomazone 0.005-0.04 0.997 0.005 89.3 16.2 0.0011 21.1 0.0017 33.2
cyflufenamid 0.005-0.04 0.996 0.005 84.1 11.8 0.0009 18.0 0.0011 22.8
cypermethrin 0.005-0.04 0.981 0.005 91.8 14.6 0.0012 23.3 0.0015 30.7
cyprodinil 0.005-0.04 0.995 0.005 84.1 12.6 0.0010 19.6 0.0012 24.2
deltamethrin 0.005-0.04 0.970 0.005 95.1 14.5 0.0008 15.2 0.0016 31.8
fenhexamid 0.005-0.04 0.986 0.005 90.2 12.9 0.0011 22.4 0.0013 26.5
flonicamid 0.005-0.04 0.995 0.005 86.4 13.6 0.0011 22.5 0.0013 26.9
fluazifop-p-butyl 0.005-0.04 0.995 0.005 83.4 12.3 0.0010 20.1 0.0012 23.3
fludioxonil 0.005-0.04 0.991 0.005 87.3 15.2 0.0010 20.1 0.0015 30.6
flufenacet 0.005-0.04 0.996 0.005 89.3 13.7 0.0011 22.2 0.0014 28.0
fluopicolide 0.005-0.04 0.990 0.005 84.7 10.5 0.0009 18.0 0.0010 20.2
fluopyram 0.005-0.04 0.996 0.005 84.4 12.7 0.0010 20.4 0.0012 24.4
flutolanil 0.005-0.04 0.996 0.005 85.1 12.4 0.0010 19.2 0.0012 24.2
indoxacarb 0.005-0.04 0.972 0.005 97.6 15.5 0.0009 17.4 0.0017 34.9
iprovalicarb 0.005-0.04 0.994 0.005 85.4 12.6 0.0010 20.8 0.0012 24.6
kresoxim-methyl 0.005-0.04 0.996 0.005 84.0 12.2 0.0010 19.1 0.0012 23.3
lambda-cyhalothrin 0.005-0.04 0.973 0.005 83.3 11.1 0.0009 17.9 0.0011 21.0
metazachlor 0.005-0.04 0.996 0.005 87.0 13.0 0.0009 18.5 0.0013 26.0
metrafenone 0.005-0.04 0.970 0.005 85.1 10.3 0.0009 17.8 0.0010 19.9
myclobutanil 0.005-0.04 0.994 0.005 84.4 11.2 0.0009 18.3 0.0011 21.6
penconazole 0.005-0.04 0.996 0.005 84.9 12.3 0.0010 19.4 0.0012 23.8
pendimethalin 0.005-0.04 0.993 0.005 83.6 13.5 0.0010 20.3 0.0013 25.9
pirimicarb 0.005-0.04 0.995 0.005 85.7 13.6 0.0011 22.7 0.0013 26.5
proquinazid 0.005-0.04 0.981 0.005 81.8 11.5 0.0009 17.9 0.0011 21.4
prosulfocarb 0.005-0.04 0.996 0.005 84.8 13.6 0.0011 21.6 0.0013 26.2
pyraclostrobin 0.005-0.04 0.977 0.005 100.9 16.7 0.0009 17.1 0.0020 39.0
pyrimethanil 0.005-0.04 0.997 0.005 85.2 13.0 0.0011 21.2 0.0013 25.3
pyriproxyfen 0.005-0.04 0.975 0.005 83.5 9.6 0.0009 17.3 0.0009 18.2
tebuconazole 0.005-0.04 0.981 0.005 85.2 10.2 0.0009 17.6 0.0010 19.8
tebufenpyrad 0.005-0.04 0.980 0.005 84.1 9.8 0.0008 16.3 0.0009 18.7
tefluthrin 0.005-0.04 0.997 0.005 84.8 13.5 0.0011 21.6 0.0013 26.1
tetraconazole 0.005-0.04 0.996 0.005 85.1 12.8 0.0010 19.3 0.0012 25.0
Table 5: Validation parameters for tomato
a RSD was obtained during recovery analyses
b,c  Ur = uncertainty of repeatability
d,e  UR = uncertainty of reproducibility
Acta agriculturae Slovenica, 120/4 – 202410
H. BAŠA ČESNIK et al.
no of sample / active substance boscalid flonicamid fludioxonil fluopyram pyraclostrobin tebuconazole
CARROT
MRL 2     0.4    
sample no. 4 0.018 - - - - -
sample no. 9 0.006 - - 0.006 - -
sample no. 10 0.005 - - 0.009 - -
LAMB`S LETTUCE
MRL 50   20      
sample no. 21 - - 0.011 - - -
sample no. 23 0.005 - - - - -
PEPPER
MRL 3     2 0.5  
sample no. 32 0.060 - - 0.008 0.027 -
TOMATO
MRL   0.5   0.5   0.9
sample no. 44 - 0.024 - 0.009 - 0.009
Table 6: Concentrations and MRLs (mg kg-1) (EC, 2005) of pesticide residues found in 50 vegetable samples
Table 7: Input values for chronic and acute risk assessment
boscalid carrot lamb`s lettuce pepper
ADI = 0.04 mg kg-1 bw/d STMR (mg kg-1) HR (mg kg-1) STMR (mg kg-1) HR (mg kg-1) STMR (mg kg-1) HR (mg kg-1)
ARfD =  not applicable 0.006 0.018 0.005 0.005 0.06 0.06
flonicamid tomato        
ADI = 0.025 mg kg-1 bw/d STMR (mg kg-1) HR (mg kg-1)        
ARfD =  0.025 mg kg-1 bw 0.024 0.024        
fludioxonil lamb`s lettuce        
ADI = 0.37 mg kg-1 bw/d STMR (mg kg-1) HR (mg kg-1)        
ARfD =  not applicable 0.011 0.011        
fluopyram carrot pepper tomato
ADI = 0.012 mg kg-1 bw/d STMR (mg kg-1) HR (mg kg-1) STMR (mg kg-1) HR (mg kg-1) STMR (mg kg-1) HR (mg kg-1)
ARfD =  0.5 mg kg-1 bw 0.008 0.009 0.008 0.008 0.009 0.009
pyraclostrobin pepper        
ADI = 0.03 mg kg-1 bw/d STMR (mg kg-1) HR (mg kg-1)        
ARfD =  0.03 mg kg-1 bw 0.027 0.027        
tebuconazole tomato        
ADI = 0.03 mg kg-1 bw/d STMR (mg kg-1) HR (mg kg-1)        
ARfD =  0.03 mg kg-1 bw 0.009 0.009        
ADI = Acceptable daily intake
ARfD = Acute reference dose
HR = Highest residue
STMR = Supervised trial median residue
Acta agriculturae Slovenica, 120/4 – 2024 11
Pesticide residues in vegetables - validation of the gas chromatography-tandem mass spectrometry ... vegetables on Slovenian market
The uncertainty of repeatability and uncertainty of 
reproducibility were determined at contents equal to the 
LOQs. The results are presented in Tables 3-5. Uncertain-
ty of repeatability ranged for lettuce, potato and tomato 
from 0.0005 mg kg-1 to 0.0014 mg kg-1, which is 10.7 % 
to 27.1 % of LOQ, from 0.0006 mg kg-1 to 0.0009 mg kg-1, 
which is 12.2 % to 18.7 % of LOQ and from 0.0006 mg 
kg-1 to 0.0012 mg kg-1, which is 11.7 % to 23.3 % of LOQ, 
respectively.  Uncertainty of reproducibility ranged for 
lettuce, potato and tomato from 0.0011 mg kg-1 to 0.0017 
mg kg-1, which is 22.7 % to 33.9 % of LOQ, from 0.0008 
mg kg-1 to 0.0018 mg kg-1, which is 16.0 % to 36.4 % of 
LOQ and from 0.0009 mg kg-1 to 0.0020 mg kg-1, which is 
18.2 % to 39.0 % of LOQ, respectively.
3.3 SURVEY OF PESTICIDE RESIDUES IN VEG-
ETABLE SAMPLES
In 50 vegetable samples gathered from stores in 
Slovenia, 35 active substances were sought. Only 14 % 
of samples analysed contained pesticide residues. 6 ac-
tive substances were determined at LOQ (0.005 mg kg-1) 
and up to 0.06 mg kg-1 in carrot, lamb`s lettuce, pepper 
and tomato. Brussels sprouts, cauliflower, kale, lettuce, 
potato, spinach and zucchini contained no pesticide 
residues. Concentrations of all active substances found, 
were below MRLs. 28 % of samples was of Slovene origin. 
21.4 % of samples of Slovene origin and 11.4 % of sam-
ples of foreign origin contained pesticide residues. One 
active substance found is insecticide (flonicamid), the 
rest 5 are fungicides. Organically produced commodi-
ties contained no pesticide residues. 2 active substances 
(boscalid and fluopiram) were determined in fresh car-
rot of Slovenian origin. Both of them are authorised for 
use on carrot in Slovenia. 2 active substances (boscalid 
and fludioxonil) were determined in fresh lamb`s lettuce 
of Italian origin. 3 active substances (boscalid, fluopiram 
and pyraclostrobin) were determined in fresh pepper of 
Italian origin. 3 active substances (flonicamid, fluopyram 
and tebuconazole) were determined in fresh tomato of 
Croatian origin. Results are presented in Table 6.
A consumer risk assessment was performed using 
the EFSA PRIMo model rev. 3.1, in which 36 national di-
ets from EU countries are included. This model was used 
since Slovenia has not created a model of its own. The 
same model is used in the process of registration of PPPs 
in Slovenia. Input values for chronic (STMRs) and acute 
risk assessment (HRs) are presented in Table 7. Where 
ARfD was not allocated, ADI value was used instead. 
Results of risk assessment are presented in Table 9. The 
highest chronic exposure was < 1% and the highest acute 
exposure < 10%. Based on these calculations, the conclu-
sion was that the analysed vegetable samples are of no 
cause for concern for consumers.
Our results were compared with the results from 
other scientific papers. Santarelli et al. (2018) found in 
raw green vegetables marketed in Italy boscalid in 22.67 
% of samples, cyprodinil in 6.00 % of samples, deltame-
thrin in 3.33 % of samples, fludioxonil in 2.33 % of sam-
ples, azoxystrobin, lambda-cyhalothrin and fenhexamid 
each in 1.33 % of samples, and fluopicolide in 0.33 % 
of samples. In comparison to our study, boscalid was 
found in 10 % of vegetable samples, fluopyram in 8 % 
of samples, flonicamid, fludioxonil, pyraclostrobin and 
tebuconazole each in 2 % of samples. In these two stud-
ies considering the same active substances sought, only 
boscalid and fludioxonil were found in both of them.
Fluopyram was found in the Turkey lettuce up to 
a concentration of 0.03 mg kg-1 by Balkan and Yilmaz 
(2022). Balkan and Yilmaz (2022) also reported that py-
raclostrobin was found in Turkey lettuce and spinach at a 
maximum concentration of 0.24 and 0.01 mg kg-1, respec-
tively. Qin et al. (2021) wrote that tebuconazole was found 
in 14.63 % of the China vegetable samples analysed, with 
a maximum concentration of 0.36 mg kg-1. Tebuconazole 
was also found by Balkan and Yilmaz (2022) in Turkey 
lettuce at a maximum concentration of 0.01 mg kg-1. In 
Slovenia, fluopyram, pyraclostrobin and tebuconazole 
were found up to concentration 0.009, 0.027 and 0.009 
mg kg-1, respectively. Maximum concentrations found in 
active substance % ADI % ARfD
boscalid 0.1 9.0
flonicamid 0.1 6.0
fludioxonil 0.0003 0.01
fluopyram 0.3 0.1
pyraclostrobin 0.1 5.0
tebuconazole 0.1 2.0
Table 8: Input values for chronic and acute risk assessment
Acta agriculturae Slovenica, 120/4 – 202412
H. BAŠA ČESNIK et al.
Slovenia are lower than maximum concentrations from 
literature.
Other active substances analysed in our laboratory, 
namely cypermethrin, deltamethrin, kresoxim-methyl, 
metrafenone, pyrimethanil and lambda-cyhalothrin were 
not detected in Slovenian vegetables, but were found in 
samples originating from Chile, China, France, Lebanon, 
Marocco, Mexico, Turkey and Uganda. Concentrations 
and/or ratio of positive samples are reported in Table 9.
4 CONCLUSIONS
In our research, a method for determining pesticide 
residues in vegetables was introduced and validated. The 
limit of quantification was 0.005 mg kg-1 for all active 
substances. The calibration curves gave a linear response 
with R2 0.953 to 0.999. The recoveries ranged from 73.4 
% to 100.9 % with RSDs from 8.6 % to 18.3 %. The meas-
urement uncertainty of repeatability ranged from 10.7 to 
active substance commodity
max content 
(mg kg -1)
ratio of positive 
samples (%) country of origin reference
cypermethrin cucumber 1.5 not reported Lebanon Sahyoun et al., 2022
cypermethrin cauliflower 0.0034 not reported Uganda Ngabirano e tal., 2022
cypermethrin tomato 0.0034 not reported Uganda Ngabirano e tal., 2022
cypermethrin lettuce 0.166 50 Chile Calderon et al., 2022
cypermethrin tomato 0.064 40 Chile Calderon et al., 2022
cypermethrin spinach 0.454 33.3 Mexico Calderon et al., 2022
cypermethrin tomato 0.061 12.5 Mexico Calderon et al., 2022
cypermethrin lettuce 0.2 not reported Turkey Balkan and Yilmaz, 2022
deltamethrin lettuce 0.11 not reported Turkey Balkan and Yilmaz, 2022
kresoxim-methyl tomato 0.0004 not reported France Sahyoun et al., 2022
kresoxim-methyl lettuce 1.43 not reported Turkey Balkan and Yilmaz, 2022
metrafenone lettuce 3.49 not reported Turkey Balkan and Yilmaz, 2022
pyrimethanil vegetables 0.53 6.5 China Qin et al., 2021
pyrimethanil lettuce 0.27 not reported Turkey Balkan and Yilmaz, 2022
l-cyhalothrin cucumber 0.002 not reported Lebanon Sahyoun et al., 2022
l-cyhalothrin pepper 0.0015 not reported Marocco Sahyoun et al., 2022
l-cyhalothrin lettuce 0.028 12.5 Mexico Calderon et al., 2022
l-cyhalothrin spinach 0.043 12.5 Mexico Calderon et al., 2022
Table 9: Literature results for active substances sought, but not found in our laboratory
27.1 % and the measurement uncertainty of reproduc-
ibility from 16.0 to 39.0 %. The method was found to be 
fit for purpose of measuring possible breaches of MRL 
for 35 active substances.
The method was used to analyse 50 vegetable sam-
ples gathered from Slovenian stores from organic and 
conventional production. A total of 35 active substances 
were sought, but only the insecticide flonicamid and fun-
gicides boscalid, fludioxonil, fluopyram, pyraclostrobin 
and tebuconazole were found in 7 of these samples (14.0 
%). In 86.0 % of the samples analysed, the active sub-
stances sought were not determined. A risk assessment 
revealed that the Slovenian vegetable samples are no 
cause for concern for consumers.
In national monitoring program, for analyses of 
pesticide residues in vegetables, requirement is to ana-
lyse 1 sample per matrix from organic production. De-
spite the fact that we did not detect a violation in either 
conventional or organic vegetables, we recommend in-
creasing the number of taken ecological samples in the 
Acta agriculturae Slovenica, 120/4 – 2024 13
Pesticide residues in vegetables - validation of the gas chromatography-tandem mass spectrometry ... vegetables on Slovenian market
national monitoring program from 1 sample per matrix 
to approximately 30 % of taken samples per matrix.
5 ACKNOWLEDGEMENTS
The authors expresses thanks to Dominika Jerebič 
and Janja Debevc for their help with the preparation of 
the extracts. For financial support we express our thanks 
to the Ministry of the Republic of Slovenia for Agricul-
ture, Forestry and Food (MAFF), Administration of the 
Republic of Slovenia for Food Safety, Veterinary and 
Plant Protection (AFSVPP). We also acknowledge the 
financial support of the Slovenian Research Agency (re-
search core funding No. P4-0133).
6 REFERENCES
Alder L., Hill A., Holland P.T., Lantos J., Lee S.M., Mac-
Neil J.D., O'Rangers J., van Zoonen P., Ambrus A. 
(2000). Guidelines for single-laboratory validation of 
analytical methods for trace-level concentrations of 
organic chemicals, Principles and practices of method 
validation (ed.: A. Fajgelj, A. Ambrus). The Royal So-
ciety of Chemistry, pp. 179 – 252.
Anastassiades M., Lehotay S. J., Štajnbaher D., Schenck F. 
J. (2003). Fast and easy multiresidue method employ-
ing acetonitrile extraction/partitioning and »disper-
sive solid-phase extraction« for the determination of 
pesticide residues in produce. Journal of AOAC Inter-
national, 86, 412-431. DOI: 10.1093/jaoac/86.2.412.
Balkan T. and Yilmaz Ö. (2022). Method validation, resi-
due and risk assessment of 260 pesticides in some 
leafy vegetables using liquid chromatography cou-
pled to tandem mass spectrometry. Food Chem-
istry, 384, 132516-132537. DOI: 10.1016/j.food-
chem.2022.132516.
Baša Česnik H., Gregorčič A. (2003). Multirezidualna 
analizna metoda za določevanje ostankov pesticidov 
v sadju in zelenjavi. Zbornik Biotehniške fakultete, 
Zootehnika, 82, 167-180.
Baša Česnik H., Gregorčič A., Velikonja Bolta Š., Kmecl 
V. (2006).Monitoring of pesticide residues in ap-
ples, lettuce and potato of the Slovene origin, 2001-
04. Food Additives and Contaminants, 23, 164-173. 
DOI:10.1080/02652030500401199.
Calderon R., García-Hernández J., Palma P., Leyva-Mo-
rales J.B., Zambrano-Soria M., Bastidas-Bastidas P.J., 
Godoy M. (2022). Assessment of pesticide residues in 
vegetables commonly consumed in Chile and Mex-
ico: Potential impacts for public health. Journal of 
Food Composition and Analysis, 108, 104420-104430. 
DOI: 10.1016/j.jfca.2022.104420.
Díez C., Traag W.A., Zommer P., Marinero P., Atienza 
J. (2006). Comparison of an acetonitrile extraction/
partitioning and“dispersive solid-phase extraction” 
method with classical multi-residue methods for the 
extraction of herbicide residues in barley samples. 
Journal of Chromatography A, 1131, 11-23. DOI: 
10.1016/j.chroma.2006.07.046.
EC (2005). Regulation (EC) NO 396/2005 of the Euro-
pean parliament and of the Council of 23 February 
2005 on maximum residue levels of pesticides in 
or on food and feed of plant and animal origin and 
amending Council Directive 91/414/EEC.
EFSA (2024), Pesticide evaluation, Tools, https://www.
efsa.europa.eu/en/applications/pesticides/tools, 
7.10.2024.
ISO 5725. (1994). Accuracy (trueness and precision) of meas-
urement methods and results - Part2: Basic method for the 
determination of repeatability and reproducibility of a stand-
ard measurement method, pp. 1-42.
Knežević Z. and Serdar M. (2009). Screening of fresh fruit and 
vegetables for pesticide residues on Croatian market. Food 
Control, 20, 419-422. DOI:10.1016/j.foodcont.2008.07.014.
Lehotay S. J. and Maštovska K. (2005). Evaluation of two fast 
and easy methods for pesticide residue analysis in fatty 
food matrixes. Journal of AOAC International, 88, 630-638. 
DOI:10.1093/jaoac/88.2.630.
Lehotay S. J. (2007). Determination of pesticide residues in 
foods by acetonitrile extraction and partitioning with mag-
nesium sulfate: collaborative study. Journal of AOAC Inter-
national, 90, 485-520. DOI:10.1093/jaoac/90.2.485.
Ngabirano H. and Birungi G. (2022). Pesticide residues in 
vegetables produced in rural south-western Uganda. 
Food Chemistry, 370, 130972-130983. DOI: 10.1016/j.
foodchem.2021.130972.
Pizzutti I.R., de Kok A., Hiemstra M., Wickert C., Prestes 
O.D. (2009). Method validation and comparison of 
acetonitrile and acetone extraction for the analysis of 
169 pesticides in soya grain by liquid chromatogra-
phy–tandem mass spectrometry. Journal of Chroma-
tography A, 1216, 4539-4552. DOI:10.1016/j.chro-
ma.2009.03.064.
Qin G., Chen Y., He F., Yang B., Zou K., Shen N., Zuo 
B., Liu R., Zhang W., Li Y. (2021). Risk assessment of 
fungicide pesticide residues in vegetables and fruits 
in  the mid-western region of China. Journal of Food 
Composition and Analysis, 95, 103663-103670. DOI: 
10.1016/j.jfca.2020.103663.
Santarelli G.A., Migliorati G.,  Pomilio F., Marfoglia C., 
Centorame P., D'Agostino A., D'Aurelio R., Scarpone 
N.B., Di Simone F., Aprea G., Iannetti L. (2018). As-
sessment of pesticide residues and microbial con-
tamination in raw leafy green vegetables marketed in 
Acta agriculturae Slovenica, 120/4 – 202414
H. BAŠA ČESNIK et al.
Italy. Food Control, 85, 350-358. DOI: 10.1016/j.food-
cont.2017.09.035.
Sahyoun W., Net S., Baroudi M., Ouddane B. (2022). 
Monitoring of pesticides residues in fruits and veg-
etables: Method optimization and application. Food 
Bioscience, 50, 102175-102187. DOI: 10.1016/j.
fbio.2022.102175.
SANTE/11312/2021. Analytical quality control and 
method validation procedures for pesticide residues 
analysis In food and feed.  Sante 11312/2021. DG 
SANTE, European Comission, 2021.
Sharif Z., Che Man Y.B., Hamid N.S.A., Keat C.C. (2006). 
Determination of organochlorine and pyrethroid 
pesticides in fruit and vegetables using solid phase 
extraction clean-up cartridges. Journal of Chroma-
tography A, 1127, 254-261. DOI: doi:10.1016/j.chro-
ma.2006.06.007.
Tankiewicz M. and Berg A. (2022). Improvement of the 
QuEChERS method coupled with GC–MS/MS for 
the determination of pesticide residues in fresh fruit 
and vegetables. Microchemical Journal, 181, 107794-
107806. DOI:10.1016/j.microc.2022.107794.