Acta agriculturae Slovenica, 120/2, 1–9, Ljubljana 2024 doi:10.14720/aas.2024.120.2.17017 Original research article / izvirni znanstveni članek Gas chromatography-tandem mass spectrometry multiresidual method for determination of pesticide residues in honey Helena BAŠA ČESNIK 1, 2, Veronika KMECL 1 Received December 14, 2023; accepted April 19, 2024. Delo je prispelo 12. decembra 2023, sprejeto 19. aprila 2024. 1 Agricultural Institute of Slovenia, Ljubljana, Slovenia 2 Corresponding author, e-mail: helena.basa@kis.si Gas chromatography-tandem mass spectrometry multiresid- ual method for determination of pesticide residues in honey Abstract: In our laboratory we introduced and validated a new analytical method for determination of environmental pesticide residues in honey. The extraction was conducted us- ing acetone, petroleum ether and dichlorometane. The deter- mination was conducted using gas chromatography coupled with tandem mass spectrometry. Practical usage of method was analyses of 31 samples of Slovenian honey. 33 active substances (pesticides) were sought. The insecticide cypermethrin was the only active substance found in three samples. The active sub- stances sought were not found in 90.3 % of the samples anal- ysed. The risk assessment showed that no unacceptable risk is expected for consumers. The results were compared with those from the literature. We revealed that honey from Slovenia con- tained a lower portion of positive samples per active substance sought as in Italy, comparable as in Estonia and Spain, compa- rable to higher as in Poland and higher as in Egypt. Key words: honey, GC-MS/MS, pesticide residues, mul- tiresidual method Multirezidualna metoda za določanje ostankov fitofarma- cevtskih sredstev v medu s plinsko kromatografijo sklopljeno s tandemsko masno spektrometrijo Izvleček: V našem laboratoriju smo uvedli in validirali novo analizno metodo za določanje ostankov fitofarmacevt- skih sredstev iz okolja v medu. Ekstrakcijo smo izvedli z ace- tonom, petroletrom in diklorometanom, določitev pa s plinsko kromatografijo sklopljeno s tandemsko masno spektrometrijo. Praktična uporaba metode je bila analiza 31 vzorcev slovenske- ga medu. Določali smo 33 aktivnih spojin (pesticidov). Edina najdena aktivna snov je bil insekticid cipermetrin v treh vzor- cih. Iskanih aktivnih snovi nismo določili v 90,3 % analiziranih vzorcev. Ocena tveganja je pokazala, da ni pričakovati nespre- jemljivega tveganja za potrošnika. Rezultate smo primerjali z li- teraturnimi podatki. Odkrili smo, da je slovenski med vseboval manjši delež pozitivnih vzorcev na aktivno snov kot v Italiji, primerljiv kot v Estoniji in Španiji, primerljiv do večji kot na Poljskem in večji kot v Egiptu. Ključne besede: med, GC-MS/MS, ostanki fitofarmace- vtskih sredstev, multirezidualna metoda Acta agriculturae Slovenica, 120/2 – 20242 H. BAŠA ČESNIK and V. KMECL 1 INTRODUCTION Honey is produced from nectar collected by bees, which gets broken down into simple sugars stored in- side the honeycomb. Therefore, honey is mainly com- posed of carbohydrates (approx. 80 %): glucose, fructose, sucrose and maltose, and water (approx. 20 %). It also contains minor compounds such as vitamins, minerals, amino acids, proteins and aroma compounds (Geană at al., 2020, Kahraman et al., 2010). Nutritional properties and therapeutic applications of honey are reason for its frequent use. Honey bees can fly within a radius of 4.8 km in all directions from their apiary (Eckert, 1933). On their way they can come into contact with pesticide residues when they collect nectar and pollen on plants treated with plant protection products (PPPs) (Colin et al., 2004) and/or on the ground, in water, in the air, on melliferous in-field weeds and off-field plants where PPPs were carried by the drift after treatment (Bonmatin at al., 2015, Krupke et al., 2012, SANTE, 2023, Ward et al., 2022). Bees carry pesti- cide residues into the hive, from where they eventually end up in honey (Zhou et al., 2018). Technical guidelines for determining the magni- tude of pesticide residues in honey and setting Maximum Residue Levels in honey (SANTE/11956/2016 rev. 9) en- tered into force on 1 January 2020. With the introduc- tion of this guideline, during PPPs authorisation of uses on plants with melliferous capacity, experiments are re- quired to determine residues in honey. Therefore, moni- toring of PPP residues in honey is recommended. For extraction procedures of analytical methods for determination of PPP residues in honey nowadays mainly use modified Quick Easy Cheap Effective Rugged and Safe method also called QuEChERS method, where acetonitrile is used (Gawel et al., 2019, Karise et al., 2017, Shendy et al., 2016). In some laboratories extraction is performed with ethyl acetate (Panseri et al., 2014) or the mixture of ethyl acetate and cyclohexane (Brugnerotto et al., 2023). In our laboratory a mixture of acetone, di- chloromethane and petroleum ether was used, to achieve the extraction of very polar (for instance, flonicamid) to non-polar (for instance, cyhalothrin-lambda) pesticides at the same time (Baša Česnik et al., 2019). Besides, when extracting materials containing high amount of sugar with acetone, no double layered extract is obtained like with acetonitrile (Luke et al., 1975). Determination of pesticide residues is nowadays usually performed using gas chromatography coupled with mass spectrometry (GC-MS) (Brugnerotto et al., 2023, Karise et al., 2017, Mukiibi et al., 2021), gas chro- matography coupled with tandem mass spectrometry (GC-MS/MS) (Gawel et al., 2019, Lazarus et al., 2021, Panseri et al., 2014, Shendy et al., 2016, Sun et al., 2022) and/or liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) (Gawel et al., 2019, Ka- rise et al., 2017, Liu et al., 2022). The most sensitive is tandem mass spectrometry, which was also used by our laboratory. Numerous authors have analysed pesticide residues in honey with GC-MS/MS. Gawel et al. (2019) analysed 53 active substances in honey from Poland. Panseri et al. (2014) tested honey samples from Italy for 28 active sub- stances. Shendy et al. (2016) introduced a method for de- termining 200 active substances in honey samples from Egypt. Wang et al. (2022) used a method for determining 203 active substances in China honey. In our study up to 24 of active substances sought in literature studies were introduced. 97.0 % of active substances selected in this paper are authorised for use in Slovenia. The rest were authorised in previous years. Of those selected, 57.6 % were fungicides, 21.2 % were acaricides and/or insecti- cides and 21.2 % were herbicides. Our paper is presenting a new GC-MS/MS multire- sidual method for determination of 33 active substances (pesticides) in honey. The old extraction procedure using acetone, dichlorometane and petroleum ether was used, but new active substances were introduced and validated with the new, more sensitive instrument. Method was used in practice. 31 honey samples, collected from Slove- nian beekeepers, were analysed. Results were compared with literature data and consumer risk assessment was calculated. 2 MATERIALS AND METHODS 2.1 MATERIALS 2.1.1 Chemicals The certified pesticide standards were obtained from Dr. Ehrenstorfer (Augsburg, Germany). For ex- traction procedure acetone - p.a. grade, dichlorome- tane – p.a. grade and petroleum ether – p.a. grade, were obtained from J.T.Baker (Deventer, Netherlands). Also acetone HPLC-grade, which was used for preparation of standards, was obtained from J.T.Baker (Deventer, Netherlands). All other chemicals used were supplied by Sigma-Aldrich (Steinheim, Germany). The water used was MilliQ deionised water. 2.1.2 Preparation of the solutions Stock solutions of individual active substances were Acta agriculturae Slovenica, 120/2 – 2024 3 Gas chromatography-tandem mass spectrometry multiresidual method for determination of pesticide residues in honey prepared in acetone. Concentration of each active sub- stance was 625 mg ml-1. From 33 stock solutions, three mixed solutions of all 33 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 Extraction procedure was conducted with acetone, petroleum ether and dichlorometane. We used the same extraction procedure as the one for determination of chlorfenvinphos, coumaphos and thymol, described by Baša Česnik at al. (2019). The only difference was that the final dry extract was dissolved in acetone HPLC-grade. 2.3 DETERMINATION The samples were analysed using a gas chromato- graph (Agilent Technologies 8890, Shanghai, China) coupled with tandem mass spectrometer (Agilent Tech- nologies 7010B, Santa Clara, USA), equipped with a Ger- stel 20PRE0795 multipurpose sampler (Gerstel, Sursee, Switzerland) and a HP-5 MS UI column (Agilent Tech- nologies, 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 qualitative and quantitative determination, the MRM transitions were used presented in Table 1. For each ac- tive substance two to four transitions were scaned. For calibration matrix match standards were used. 2.4 VALIDATION OF METHODS 2.4.1 LOQ and linearity The linearity was tested with matrix match stand- ards. F test was used to check linearity and determine linearity range. Each calibration curve had three to seven concentration levels with two repetitions at each level. Estimation of LOQs was conducted using matrix match standards. S/N ratio had to be at least 10. 2.4.2 Precision Blank honey was purchased in store. It was analysed on presence of pesticide residues sought. After proving that it does not contain pesticides of our choice, it was spiked in two parallel samples at LOQ within the peri- od of 10 days. For the determination of precision (ISO 5725), i.e. repeatability and reproducibility, the standard deviation of the repeatability of the level and the standard deviation of reproducibility of the level were both calcu- lated from results obtained. 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 PPP residues should be 50 %, as proposed in SANTE/11312/2021. The method is fit for purpose when during validation it is proven that measurement uncertainty is ≤ 50 %. 2.4.4 Accuracy The accuracy was verified by checking the recov- eries. We used recoveries obtained during test for pre- cision. 20 results for each active substance (pesticide) were averaged and RSD was calculated. According to the requirements for method validation procedures (SANTE/11312/2021), acceptable mean recoveries are those within the range of 70 % to 120 %, with an associ- ated repeatability of RSDr ≤ 20 %. The guidelines for single-laboratory validation (Al- der et al. 2000) require mean recoveries at level > 0.001 mg kg-1 and ≤ 0.01 mg kg-1 from 60 % to 120 %, with an associated repeatability RSDr ≤ 30 %. 2.5 CONSUMER RISK ASSESSMENT Long-term exposure was calculated using the EFSA PRIMo model revision 3.1. Chronic consumer exposure was expressed in % of the Acceptable Daily Intake (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. Acute consumer exposure Acta agriculturae Slovenica, 120/2 – 20244 H. BAŠA ČESNIK and V. KMECL Table 1: Active substances sought, their activity type, MRM transitions, dwell time and collision energy Active substance Activity typea MRM transitions (Q1, Q2, Q3)b Dwell (ms) CE (V)c 8-hydroxyquinoline F 145->117.1, 145->89, 117->90 77.5 10, 40, 10 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 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 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 20, 30, 40 metazachlor H 209->132.1, 209->117.1, 133->131.7 14 20, 40, 20 myclobutanil F 179->125, 179->90, 179->63 8.6 10, 40, 40 napropamide H 271->72, 128->100.1, 128->72.1 17.7 20, 10, 10 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 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 trifloxystrobin F 222->162.1, 222->130, 131->116 11.1 10, 10, 20 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, 120/2 – 2024 5 Gas chromatography-tandem mass spectrometry multiresidual method for determination of pesticide residues in honey was expressed in % of the Acute Reference Dose (ARfD). The acceptable limit for short-term exposure is 100 % of the ARfD. 2.6 SAMPLING 31 honey samples were collected from Slovenian beekeepers from 11 statistical regions in Slovenia in 2023. The sampling distribution is presented in Table 2. 3 RESULTS AND DISCUSSION 3.1 VALIDATION OF METHOD 3.1.1 LOQ and linearity The linear model is valid for all active substances presented in Table 3. Linearity was proven in the range of 0.005 mg kg-1 to 0.02 mg kg-1 for pendimethalin, in the range of 0.005 mg kg-1 to 0.04 mg kg-1 for 8-hydroxyqui- noline and prosulfocarb, in the range of 0.005 mg kg-1 to 0.05 mg kg-1 for flonicamid and in the range of 0.005 mg kg-1 to 0.03 mg kg-1 for all other active substances. R2 ranged from 0.987 to 1.000. Results are presented in Table 3. 3.1.2 Accuracy The recoveries at LOQs for the active substances scanned with GC-MS/MS are in the range of 92.8 % to 98.9 %, with RSDs of 6.0 % to 11.3 %. The results are pre- sented in Table 3. All recoveries and RSDs are within the re- quired ranges from the literature (Alder et al., 2000; SANTE/11813/2017). 3.1.3 Uncertainty of repeatability and uncertainty of reproducibility The uncertainty of repeatability and uncertainty of reproducibility were determined at concentrations equal to the LOQs. Uncertainty of repeatability ranged from 0.0004 mg kg-1 to 0.0009 mg kg-1, which is 7.6 % to 18.3 % of LOQ. Uncertainty of reproducibility ranged from 0.0007 mg kg-1 to 0.0013 mg kg-1, which is 13.3 % to 25.2 % of LOQ. The results are presented in Table 3. 3.2 SURVEY OF PESTICIDE RESIDUES IN HONEY SAMPLES Of the 31 honey samples analysed, only 3 contained one active substance: cypermethrin in concentrations 0.006 (honey poured in 2022, Osrednja Slovenija), 0.015 (honey poured in 2023, Koroška) and 0.048 mg kg-1 (honey poured in 2023, Koroška). This means that in 90.3 % of all samples analysed, were free of pesticides sought. In Slovenia, cypermethrin is authorised as insecticide for seed treatment of cereals (formulation ES, Emulsion for seed treatment), and for use on soil at planting of mel- liferous crops like oilseed rape, pumpkin and aubergines and on non-melliferous crops like onion, garlic, head cab- bage, horseradish, chinese cabbage, carrot, potatoes, kale, tomatoes, parsnips, parsley, beetroots, radishes, sugar beet, shallots, tobacco, celery and grass (formulation GR, Granule). Cypermethrin is a non-systemic and cannot be translocated in plants. But granules of PPPs contain 10 % dust (SANTE, 2023). Dust from treated seeds and/ or granules of PPPs can be deposited on melliferous in- field weeds and off-field plants like clover or dandelion (Bonmatin at al., 2015, SANTE, 2023). The consequence is that residues of all active substances used in the field near the hive can be present in honey up to 0.05 mg kg-1, which is MRL for cypermethrin in honey. Value of 0.05 mg kg-1 is calculated as a default value for all active sub- Table 2: Sampling distribution according to statistical regions of Slovenian honey samples collected in 2023 Region  No of samples Pouring in 2022 Pouring in 2023 sum Goriška 5 0 5 Jugovzhodna Slovenija 1 1 2 Koroška 1 3 4 Obalno Kraška 1 0 1 Osrednja Slovenija 3 2 5 Podravska 5 1 6 Pomurska 1 1 2 Posavska 0 1 1 Primorsko- Notranjska 1 0 1 Savinjska 3 0 3 Zasavska 1 0 1 sum 22 9 31 Acta agriculturae Slovenica, 120/2 – 20246 H. BAŠA ČESNIK and V. KMECL Table 3: Validation parameters for honey Active substance Linearity range (mg kg-1) R2 LOQ (mg kg-1) Recovery (%) RSDa (%) Ur b (mg kg-1) Ur c (%) UR d (mg kg-1) UR e (%) 8-hydroxyquinoline 0.005-0.04 0.995 0.005 95.5 8.2 0.0007 13.8 0.0009 17.9 benthiavalicarb- isopropyl 0.005-0.03 0.999 0.005 97.3 7.4 0.0004 7.6 0.0008 16.6 boscalid 0.005-0.03 0.997 0.005 95.1 7.4 0.0006 11.4 0.0008 16.2 clomazone 0.005-0.03 0.999 0.005 96.3 7.3 0.0005 10.9 0.0008 16.2 cypermethrin 0.005-0.03 0.997 0.005 93.3 11.0 0.0009 18.3 0.0012 23.4 cyprodinil 0.005-0.03 0.999 0.005 95.0 6.1 0.0005 10.8 0.0007 13.3 deltamethrin 0.005-0.03 0.997 0.005 92.8 9.8 0.0008 16.5 0.0010 20.8 fenhexamid 0.005-0.03 0.999 0.005 96.4 11.2 0.0005 9.8 0.0012 24.9 flonicamid 0.005-0.05 0.987 0.005 98.3 7.0 0.0006 11.9 0.0008 15.7 fluazifop-p-butyl 0.005-0.03 0.999 0.005 96.9 8.6 0.0008 15.6 0.0009 18.9 fludioxonil 0.005-0.03 0.998 0.005 95.7 8.0 0.0007 13.3 0.0009 17.5 flufenacet 0.005-0.03 0.999 0.005 96.5 7.6 0.0006 12.5 0.0008 16.8 fluopicolide 0.005-0.03 0.998 0.005 97.0 7.6 0.0007 13.2 0.0008 16.9 fluopyram 0.005-0.03 0.999 0.005 97.3 6.4 0.0004 8.5 0.0007 14.2 flutolanil 0.005-0.03 0.999 0.005 95.6 8.2 0.0007 14.9 0.0009 17.9 iprovalicarb 0.005-0.03 0.999 0.005 96.1 8.1 0.0008 15.9 0.0009 17.8 kresoxim-methyl 0.005-0.03 0.999 0.005 97.0 7.4 0.0006 11.5 0.0008 16.4 lambda-cyhalothrin 0.005-0.03 0.999 0.005 98.7 7.8 0.0009 18.0 0.0009 18.0 metazachlor 0.005-0.03 0.999 0.005 96.2 6.8 0.0005 9.7 0.0007 15.0 myclobutanil 0.005-0.03 0.998 0.005 97.1 7.0 0.0005 10.8 0.0008 15.7 napropamide 0.005-0.03 0.999 0.005 95.9 6.0 0.0007 14.0 0.0007 14.0 penconazole 0.005-0.03 1.000 0.005 96.8 8.0 0.0006 11.3 0.0009 17.8 pendimethalin 0.005-0.02 1.000 0.005 93.7 7.3 0.0007 13.8 0.0008 15.6 pirimicarb 0.005-0.03 0.997 0.005 96.7 8.0 0.0007 13.7 0.0009 17.6 proquinazid 0.005-0.03 0.999 0.005 96.4 7.0 0.0005 10.5 0.0008 15.6 prosulfocarb 0.005-0.04 1.000 0.005 93.7 8.1 0.0008 15.7 0.0009 17.2 pyraclostrobin 0.005-0.03 0.993 0.005 96.9 11.3 0.0006 12.7 0.0013 25.2 pyrimethanil 0.005-0.03 1.000 0.005 95.1 7.7 0.0007 13.8 0.0008 16.8 tebuconazole 0.005-0.03 0.999 0.005 96.7 8.5 0.0007 14.1 0.0009 18.9 tebufenpyrad 0.005-0.03 0.998 0.005 95.9 7.2 0.0004 8.7 0.0008 15.9 tefluthrin 0.005-0.03 0.999 0.005 95.9 6.8 0.0005 9.9 0.0008 15.0 tetraconazole 0.005-0.03 0.999 0.005 94.1 8.7 0.0006 11.4 0.0009 18.9 trifloxystrobin 0.005-0.03 0.998 0.005 97.7 10.2 0.0008 15.5 0.0011 22.9 a RSD was obtained during recovery analyses b,c Ur = uncertainty of repeatability d,e UR = uncertainty of reproducibility Acta agriculturae Slovenica, 120/2 – 2024 7 Gas chromatography-tandem mass spectrometry multiresidual method for determination of pesticide residues in honey stances and presumes that the lowest ARfD is 1.5 x 10-4 mg (kg bw)-1 d-1 (for active substance carbofuran) and the highest portion of consumed honey is 3.58 g (kg bw)-1 (children consumption) (SANTE/11956/2016, rev. 9), meaning that residue of 0.05 mg kg-1 does not present acute risk for consumer. When residues are < 0.05 mg kg-1 it is not suspected that violation of PPPs happened. We do not have data about exact location of hives where Slovenian honey with cypermethrin residues was pro- duced. Cypermethrin was probably found in Slovenian honey as a consequence of its use in vicinity of agricul- tural fields with melliferous off-field plants. We assume that in-field weeds were not present at application of PPPs and cereal seeds, containing cypermethrin, on soil. Farmers probably removed in-field weeds before sowing/ planting. Therefore it is recommended that before PPPs are used, off-field plants near hives are mowed, to prevent presence of pesticide residues in honey. A consumer risk assessment was performed using the EFSA PRIMo model rev. 3.1, which includes 36 na- tional diets from EU countries. Slovenia did not create its own model, therefore EU model was used. The same model is also used during authorisation of PPPs in Slo- venia and EU. For chronic exposure ADI of 0.005 mg (kg bw)-1 d-1 and Supervised Trial Median Residue (STMR) of 0.015 mg kg-1 were used. The calculations of chronic ex- posure showed that the highest was observed in the Ger- man diet for children. It represented 0.03 % of ADI. For acute exposure ARfD of 0.005 mg (kg bw)-1 d-1 and the Highest Residue (HR) of 0.048 mg kg-1 were used. The calculations of acute exposure showed that the highest was observed for children. It represented 3 % of ARfD. Based on these calculations, the conclusion was that the analysed honey samples do not represent unacceptable risk for consumers. Our results were compared with the results from other scientific papers. Cypermethrin was not found in literature by our knowledge. Panseri et al. (2014), Malhat et al. (2015) and Juan-Borrás et al. (2016) did not meas- ure presence of cypermethrin in Italy, Egypt and Spain. Cypermethrin was measured only by Gawel et al. (2019), but was not found in honey samples from Poland. The reason is probably that PPPs containing cypermethrin were not used in vicinity of locations of Polish hives. Other active substances (pesticides) analysed in our lab- oratory, namely boscalid, lambda-cyhalothrin, tebucona- zole, tetraconazole and trifloxystrobin, were not found in Slovenian honey, but were found in samples analysed in Egypt, Estonia, Italy, Poland and Spain. Literature data for these active substances are presented in Table 4. 4 CONCLUSIONS A method for determining pesticide residues origi- nating from the environment in honey was introduced and validated by our laboratory. The limit of quantifica- tion was 0.005 mg kg-1 for all active substances. The cali- bration curves gave a linear response with R2 0.987 to 1.000. The recoveries ranged from 92.8 % to 98.7 % with RSDs from 6.0 % to 11.3 %. The measurement uncer- tainty of repeatability ranged from 7.6 to 18.3 % and the measurement uncertainty of reproducibility from 13.3 to 25.2 %. The method was found to be fit for purpose for analysing 33 active substances and for determination of possible MRL exceedances. In practice method was tested by analysing 31 hon- ey samples gathered from Slovenian beekeepers, all from conventional production. A total of 33 active substances were sought, but only the insecticide cypermethrin was found in three of these samples, below valid MRL. In 90.3 % of the samples analysed, the active substances sought were not found. A risk assessment revealed that the ana- lysed Slovenian honey samples are safe for consumers. Table 4: Literature data for active substances analysed by our laboratory, but not found in Slovenian honey samples Active substance Max content (mg kg -1) Ratio of positive samples (%) Country of origin  Reference  boscalid not reported 27.8 Italy Panseri et al., 2014 boscalid 0.005 5 Poland Gawel et al., 2019 cyhalothrin 0.0073 6.0 Egypt Malhat et al., 2015 tebuconazole 0.012 10 Poland Gawel et al., 2019 tebuconazole 0.005 9.1 Estonia Karise et al., 2017 tebuconazole 0.004 9.1 Spain Juan-Borrás et al., 2016 tetraconazole 0.005 3 Poland Gawel et al., 2019 trifloxystrobin not reported 20.8 Italy Panseri et al., 2014 Acta agriculturae Slovenica, 120/2 – 20248 H. BAŠA ČESNIK and V. KMECL 5 ACKNOWLEDGEMENTS The authors expresses thanks to Janja Debevc for her help with the preparation of the extracts. For finan- cial support we express our thanks to the Ministry of the Republic of Slovenia for Agriculture, 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 Slove- nian Research Agency (research core funding No. P4- 0133). 6 REFERENCES Alder L., Hill A., Holland P.T., Lantos J., Lee S.M., MacNeil 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, Princi- ples and practices of method validation (ed.: A. Fajgelj, A. Ambrus). The Royal Society of Chemistry, pp. 179 – 252. https://doi.org/10.1039/9781847551757-00179 Baša Česnik H., Kmecl V., Velikonja Bolta Š. (2019). Pesticide and veterinary drug residues in honey - validation of meth- ods and a survey of organic and conventional honeys from Slovenia. Food Additives & Contaminants. 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