doi: 10.14720/aas.2018.111.2.13 Original research article / izvirni znanstveni članek Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries Helena BAŠA ČESNIK1 * Received February 12, 2018; accepted September 23, 2018. Delo je prispelo 12. februarja 2018, sprejeto 23. septembra 2018. ABSTRACT Gas chromatography coupled with mass spectrometry was used for the introduction and validation of the multiresidual method for determining of plant protection product residues in strawberries. During the validation procedure, limits of quantification were set and the method was checked for its recovery, linearity, repeatability, reproducibility and measurement uncertainty. An interlaboratory comparison was also performed to check the accuracy of the method. The method was proven to be fit for purpose. Afterwards 19 strawberry samples were analysed for the presence of plant protection product residues using the validated method. In the strawberries 5 active substances, all fungicides, were found: chlorothalonil, cyprodinil, fludioxonil, metalaxyl+metalaxyl-M and pyrimethanil. Residues of these active substances were in range 0.01 - 0.44 mg/kg. No cases exceeding the maximum residue levels were measured. Key words: pesticide residues; GC-MS; strawberries; plant protection product residues; multiresidual method IZVLEČEK VALIDACIJA MULTIREZIDUALNE GC-MS METODE ZA DOLOČEVANJE OSTANKOV FITOFARMACEVTSKIH SREDSTEV V JAGODAH Plinsko kromatografijo sklopljeno z masno spektrometrijo smo uporabili za vpeljavo in validacijo multirezidualne metode za določanje ostankov fitofarmacevtskih sredstev v jagodah. Med validacijo smo postavili meje kvantitativne določitve metode in preverili izkoristek, linearnost, ponovljivost, obnovljivost in merilno negotovost metode. Sodelovali smo tudi v medlaboratorijski primerjavi, da smo preverili točnost metode. Za metodo se je izkazalo, da ustreza namenu. Nato smo z validirano metodo ugotavljali prisotnost ostankov fitofarmacevtskih sredstev v 19 vzorcih jagod. V njih smo določili 5 aktivnih spojin: klorotalonil, ciprodinil, fludioksonil, meatalaksil + metalaksil-M in pirimetanil. Ostanki teh aktivnih snovi so se gibali v območju 0,01 -0,44 mg/kg. Preseganja maksimalnih dovoljenih količin ostankov nismo izmerili. Ključne besede: ostanki pesticidov; GC-MS; jagode; ostanki fitofarmacevtskih sredstev; multirezidualna metoda 1 INTRODUCTION Fruit is an important part of our diet for its nutrition and health properties. To prevent the destruction of food crops by agricultural pests and to improve plant quality, plant protection products (PPPs) must be used in fruit production. While monitoring the PPP residues in fruit, vegetables and cereals, we noticed (Basa Cesnik et al., 2009) that fruit contains the highest number of active compounds. Farmers need to protect fruit against rot, mould and insects, otherwise the fruit would not grow. Strawberries are mainly attacked by the diseases Botrytis cinerea (Persoon), Colletotrichum acutatum (J.H. Simmonds), Oidium fragariae (Harz) and Mycospharella fragariae ((Tul.) Lindau) and by the pests Steneotarsonemus fragariae (Banks, 1901), Anthonomus rubi (Herbst, 1795), and Tetranychus urticae (C. L. Koch, 1836; (Sojka et al., 2015). Therefore, the use of PPPs during strawberry growth is inevitable. Unfortunately, PPP residues can have a negative impact on consumer health when they exceed the Maximum Residue Levels (MRLs). Therefore, the monitoring of PPP residues is necessary. For proper monitoring, efficient analytical methods are required, which enable analysis of large number of active substances and their residues at the same time. 1 Agricultural Institute of Slovenia, Hacquetova ulica 17, SI-1000 Ljubljana, Slovenia, PhD, Corresponding author: helena.basa@kis.si Acta agriculturae Slovenica, 111 - 2, september 2018 str. 393 - 405 Helena BASA CESNIK For determining the PPP residues in strawberries, a number of analytical methods were published. The first step in the methods is usually performed by liquidliquid extraction, with three main solvents being used: ethylacetate (Berrada et al., 2006; Ferrer et al., 2005), acetonitrile -also known as the QuEChERS method (Bakirci et al., 2014; Lehotay et al., 2007) or acetone (Jardim et al., 2012; Stan, 2000). Our laboratory used acetone because of its high volatility and miscibility with the water present in strawberry matrices. For the better extraction of active substance residues, we added dichloromethane and petroleum ether to the acetone. In this way, a wide range of active substances from medium polar (e.g. diazinon and dimethoate) to nonpolar (e.g. chlorpyrifos and cyhalothrin-lambda) were extracted. The extraction of PPP residues from the strawberry matrix is complicated because of its acidity. Therefore, in our laboratory, pH adjustment was used for better extraction efficiency, similar to the in QuEChERS method. CH3COONa and acetic acid were added to the strawberry matrix, which enhanced the extraction efficiency of pH sensitive active compounds (e.g. pirimicarb and pyrimethanil). For determining active substance residues, chromatography is usually used. Gas chromatographs (GC), used for non-polar to medium polar and volatile compounds, can be connected to a flame ionisation detector (FID), electron capture detector (ECD), nitrogen phosphor detector (NPD), flame photometric detector (FPD) or mass spectrometer (MS). In our laboratory, an MS was used as this is the only system that enables unequivocal qualitative and quantitative detection of active substance residues based on chromatographic retention time and mass spectra. The purpose of this paper is to present the introduced, modified (pH adjustment) and then validated gas chromatography-mass spectrometry (GC-MS) method, which enables the qualitative and quantitative determination of a wide range of active compounds in strawberries and their residues in one chromatographic run. Statistical analyses for the obtained data were used: for linearity using the F test, for accuracy by checking recoveries and cooperation in interlaboratory comparisons, for precision according to ISO 5725 standard and for measurement uncertainty by multiplying the standard deviation by Student's t factor for 9 degrees of freedom and a 95% confidence level. Finally, method implementation in practice was performed. 2 MATERIALS AND METHODS 2.1 Materials Chemicals: Acetone (Merck), dichloromethane (Merck), ethyl acetate (Merck), cyclohexane (Merck) and petroleum ether (Merck) with p.a. grade and GC grade were used as solvents in our experiment. Similarly, only active substances (dr. Ehrenstorfer, Pestanal) with the highest available purity on the market (a minimum of 95 %) were used. Preparation of the solutions: Stock solutions in a mixture of ethyl acetate and cyclohexane in a ratio of 1 to 1 of the individual active substances were prepared in 25 ml volumetric flasks with concentrations of 625 |g pesticide ml-1. From 53 stock solutions, two mixed solutions of all 53 active substances were prepared in 500 ml volumetric flasks: one at a concentration of 5 |g ml-1 and the other at the limit of quantification (LOQ) of the active substances. All the solutions used to determine the linearity and LOQs were prepared from the 5 | g ml-1 mixed solution with proper dilutions. For other validation parameters, both mixed solutions (5 | g ml-1 concentration and the concentration at LOQ) were used. For standard solutions, solvents of GC grade were used. 2.2 Procedure To 20 g of homogenised blank matrix (milled strawberries, which contain no PPP residues) or homogenised sample, 2 g of anhydrous CH3COONa was added. Afterwards 40 ml of acetone p.a. and 0.4 ml 100 % acetic acid were added. The mixture was homogenised for 2 minutes with mixer (Ultra-turrax T 25, Ika-Werke). Then 80 ml mixture of petroleum ether p.a. and dichloromethane p.a. at a ratio of 1:1 was added and mixed for another 2 minutes with a mixer. This mixture was filtered into the separatory funnel, containing 3 g of NaCl. The vessel was rinsed with 80 ml of a mixture of petroleum ether p.a. and dichloromethane p.a. at a ratio of 1:1 (v/v). The solvent was added to the separatory funnel, which was shaken for 1 minute. The upper organic phase was filtered through 15 g anhydrous Na2SO4 in 500 ml Soxhlet flask. The lower water phase was re-extracted twice using the same procedure. Solvents were evaporated to approximately 2 ml on a rotavapor and dried with a nitrogen flow. 8 ml of a mixture of cyclohexane p.a. and ethyl acetate p.a. at a ratio 1:1 (v/v) were added to dry extract. After filtration through a 0.2 |im pore size filter, 5 ml of the extract was cleaned using a gel permeation 3 90 Acta agriculturae Slovenica, 111 - 2, September 2018 Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries chromatograph, containing a column filled with bio-beds SX3. The flow of the mobile phase (ethyl acetate p.a. and cyclohexane p.a., v/v = 1:1) through the GPC column was 5 ml min-1. The 90-200 ml of the eluate was collected into a Soxhlet flask, evaporated to approximately 2 ml on a rotavapor and dried with a nitrogen flow. To the dry eluate, 2 ml of the mixture of ethyl acetate p.a. and cyclohexane p.a. at a ratio of 1:1 (v/v) was added in case of sample preparation. In the case of the matrix match standards, 2 ml of the working solutions with proper concentrations were added. 2.3 Determination Table 1: Chromatographic conditions of the GC (HP 6890)-MS (HP 5973) system: Liner: HP 5181-3316 Temperature of injector: 250 °C Injection type: Pulsed Splitless Precolumn: 2 m * 0,25 mm Column: HP 5 MS, 30 m * 0.25 mm, 0.25 ^m film Temperature gradient of column: 55 °C 2 min 55 °C - 130 °C 25 °C/min 130 °C 1 min 130 °C - 180 °C 5 °C/min 180 °C 30 min 180 °C - 230 °C 20 °C/min 230 °C 16 min 230 °C - 250 °C 20 °C/min 250 °C 13 min 250 °C - 280 °C 20 °C/min 280 °C 20 min Temperature of ion source: 230 °C Temperature of connector: 280 °C Temperature of detector: 150 °C Carrier gas: Helium 6.0, 1.2 ml/min constant flow Volume of injection: 1 |l Table 2: Detection (selective ion monitoring): active substance T, Q1, Q2, Q3 (m/z) aldrin 263, 265, 261 azinphos-methyl 160, 132, 105 azoxystrobin 344, 388, 345 bifenthrin 181, 165, 166 bromopropylate 183, 341, 185 bupirimate 273, 316, 208 captan 79, 107, 119, 149 chlorothalonil 266, 264, 268 chlorpropham 213, 127, 154 chlorpyriphos 314, 316, 197 chlorpyriphos-methyl 286, 288, 125 cyhalotrin-X 181, 197, 208 cypermethrin (four isomers) 181, 163, 165 cyprodinil 224, 225, 210 DDT (5 isomers) DDD-o,p: 235, 237, 165 DDD-p,p and DDT-o,p: 235, 237, 165 DDE-p,p: 318, 246, 248 DDT-p,p: 235, 237, 165 Acta agriculturae Slovenica, 111 - 2, september 2018 Helena BASA CESNIK active substance T, Q1, Q2, Q3 (m/z) deltamethrin 181, 251, 255 diazinon 179, 304, 199 dichlofluanid 226, 123, 167 dimethoate 87, 229, 143 diphenylamine 169, 167, 168 endrin 263, 261, 265 fenitrothion 277, 260, 109 fenthion 278, 279, 280 fludioxonil 248, 154, 127 folpet 260, 262, 130 HCH-alpha 219, 181, 183 heptachlor 272, 274, 270 heptenophos 124, 215, 250 iprodione 314, 316, 187 kresoxim-methyl 116, 206, 131 lindane 183, 219, 181 mecarbam 131, 159, 329 metalaxyl+metalaxyl-M 249, 206 , 234 methidathion 145, 85, 125 myclobutanil 179, 288, 150 parathion 291, 292, 235 penconazole 248, 159, 161 permethrin (2 isomers) 183, 163, 165 phosalone 182, 367, 121 pirimicarb 166, 238, 167 pirimipho s -methyl 290, 305, 276 propyzamide 173, 175, 145 pyridaphenthion 199, 340, 188 pyrimethanil 198, 199, 200 quinalphos 146, 298, 157 spiroxamine (2 isomers) 100, 126, 198 tolclofos-methyl 265, 267, 250 tolylfluanid 238, 137, 240 triadimefon 208, 210, 181 triadimenol (2 isomers) 112, 168, 128 triazophos 161, 162, 285 trifloxystrobin 116, 222, 186 vinclozolin 285, 124, 187 2.4 Sampling Strawberry samples were randomly taken in May and June 2007 directly in the field after the expiration of pre-harvest interval. Samples originated from 6 production areas in Slovenia: Celje, Kranj, Ljubljana, Maribor, Murska Sobota and Novo mesto. 3 90 Acta agriculturae Slovenica, 111 - 2, September 2018 Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries 3 RESULTS AND DISCUSSION The previous protocol for the determination of PPP residues in fruit and vegetables was published before (Basa Cesnik et al., 2006). The disadvantage of this procedure was, that when it was used for strawberries, some active substances were not extracted at all. Recoveries of previous procedure were compared to recoveries of new procedure (the one that includes pH adjustment) for two parallel samples of blank strawberries (strawberries that contained no PPP residues) spiked at level 0.2 mg kg-1. The new procedure differs from old procedure only in step where the anhydrous CH3COONa and the 100 % acetic acid are added to the sample. pH adjustment enabled extraction of bupimirate, pirimicarb, pyrimethanil and spiroxamine, where recoveries were 0 without pH adjustment. Table 3: Linearity 3.1 Linearity and limits of quantification Linearity was verified using the matrix match standards (five repetitions for one concentration level, three to seven concentration levels for the calibration curve). The linearity and range were determined by linear regression using the F test. The linear model is fit and remains linear throughout the range presented in Table 1. The limits of quantification (LOQs) were estimated from chromatograms of the matrix match standards. LOQs were chosen at S/N = 10. The LOQ is the lowest value of the linearity range for particular active substance presented in Table 3. active substance linearity range (mg kg"1) R2 active substance linearity range (mg kg-1) R2 aldrin 0.005-0.2 0.997 heptenophos 0.01-0.2 0.997 azinpho s-methyl 0.01-0.2 0.989 iprodione 0.01-0.2 0.995 azoxystrobin 0.04-0.2 0.985 kresoxim-methyl 0.02-0.2 0.995 bifenthrin 0.01-0.2 0.997 lindane 0.01-0.2 0.997 bromopropylate 0.01-0.2 0.997 mecarbam 0.04-0.2 0.995 bupirimate 0.02-0.2 0.995 metalaxyl+metalaxyl-M 0.01-0.2 0.998 captan 0.1-0.2 0.994 methidathion 0.01-0.2 0.995 chlorothalonil 0.01-0.2 0.995 myclobutanil 0.05-0.2 0.996 chlorpropham 0.01-0.2 0.997 parathion 0.03-1.0 0.992 chlorpyriphos 0.01-0.2 0.997 penconazole 0.01-0.2 0.996 chlorpyripho s-methyl 0.02-0.2 0.997 permethrin 0.02-0.2 0.994 cyhalotrin-lambda 0.01-0.5 0.977 phosalone 0.01-0.2 0.993 cypermethrin 0.03-0.2 0.991 pirimicarb 0.01-0.2 0.997 cyprodinil 0.01-0.2 0.996 pirimipho s-methyl 0.01-0.2 0.998 DDT 0.05-1.0 0.997 propyzamide 0.01-0.2 0.997 deltamethrin 0.03-0.2 0.989 pyridaphenthion 0.01-1.0 0.991 diazinon 0.01-0.2 0.998 pyrimethanil 0.01-0.2 0.997 dichlofluanid 0.01-0.2 0.997 quinalphos 0.01-0.2 0.996 Acta agriculturae Slovenica, 111 - 2, september 2018 Helena BASA CESNIK active substance linearity range (mg kg-1) R2 active substance linearity range (mg kg-1) R2 dimethoate 0.01-0.2 0.995 spiroxamine 0.02-1.0 0.993 diphenylamine 0.01-0.2 0.996 tolclofos-methyl 0.01-0.2 0.997 endrin 0.01-0.2 0.996 tolylfluanid 0.01-0.2 0.996 fenitrothion 0.01-1.0 0.991 triadimefon 0.02-0.2 0.997 fenthion 0.005-0.2 0.996 triadimenol 0.02-0.2 0.994 fludioxonil 0.01-0.2 0.992 triazophos 0.01-0.2 0.992 folpet 0.02-1.0 0.988 trifloxystrobin 0.03-0.2 0.996 HCH-alpha 0.005-0.2 0.997 vinclozolin 0.01-0.2 0.997 heptachlor 0.005-0.2 0.998 3.2 Accuracy Accuracy was verified by checking the recoveries. Ten extracts of spiked blank strawberry homogenate (milled strawberries that contained no PPP residues) were prepared for each spiking level in the shortest period possible. Each extract was injected twice. The average of the recoveries was calculated. According to the requirements for the method validation procedures (Document N° SANTE/11945/2015), acceptable mean recoveries are those within the range of 70-120 %, with an associated repeatability RSDr < 20 %. Our recoveries of the spiking level at LOQ ranged from 96.6 % to 105.4 % with RSDr < 15 %, except for HCH-alpha were the RSDr was 23 %. At spiking level 0.2 mg kg-1, Table 4: Recoveries for spiked strawberry blank matrix recoveries ranged from 96.8 % to 99.9 % with RSDr < 13 %. According to the guidelines for single-laboratory validation (Alder et al., 2000), the acceptable mean recoveries: - at level > 0.1 mg kg-1 < 1 mg kg-1 are within the range 70-110 %, with an associated repeatability RSDr < 15 %, - at level > 0.01 mg kg-1 < 0.1 mg kg-1 are within the range 70-120 %, with an associated repeatability RSDr < 20 % and - at level > 0.001 mg kg-1 < 0.01 mg kg-1 are within the range 60-120 %, with an associated repeatability RSDr < 30 %. These requirements were achieved for all 53 active compounds. The results are given in Table 4. active substance spiking level (mg kg-1) recovery (%) RSD (%) spiking level (mg kg-1) recovery (%) RSD (%) aldrin 0.005 99.1 6.8 0.2 97.7 7.8 azinphos-methyl 0.01 98.9 11.4 0.2 99.9 12.2 azoxystrobin 0.04 98.8 14.5 0.2 99.8 12.2 bifenthrin 0.01 101.0 12.1 0.2 97.7 9.2 bromopropylate 0.01 101.3 13.8 0.2 97.6 9.3 bupirimate 0.02 103.2 13.6 0.2 97.5 9.6 captan 0.1 101.5 9.9 0.2 97.4 9.4 chlorothalonil 0.01 96.6 9.3 0.2 97.8 9.2 chlorpropham 0.01 100.6 8.6 0.2 97.6 8.2 chlorpyriphos 0.01 102.6 12.4 0.2 97.1 8.0 chlorpyriphos-methyl 0.02 102.1 9.6 0.2 97.5 7.8 cyhalotrin-lambda 0.01 99.8 8.4 0.2 97.3 10.6 lOT 3 90 Acta agriculturae Slovenica, 111 - 2, September 2018 Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries active substance spiking level (mg kg-1) recovery (%) RSD (%) spiking level (mg kg-1) recovery (%) RSD (%) cypermethrin 0.03 97.3 6.9 0.2 98.8 12.5 cyprodinil 0.01 103.1 12.1 0.2 97.5 9.3 DDT 0.05 101.6 9.8 1.0 97.4 9.1 deltamethrin 0.03 99.9 10.4 0.2 98.9 12.4 diazinon 0.01 104.2 12.0 0.2 97.8 7.4 dichlofluanid 0.01 100.1 8.8 0.2 97.4 8.1 dimethoate 0.01 102.7 10.9 0.2 97.9 8.9 diphenylamine 0.01 99.5 7.3 0.2 98.0 7.5 endrin 0.01 97.9 9.2 0.2 97.5 8.7 fenitrothion 0.01 100.1 8.3 0.2 97.0 10.2 fenthion 0.005 101.8 13.9 0.2 97.4 8.3 fludioxonil 0.01 99.3 11.8 0.2 99.3 11.3 folpet 0.02 101.7 11.2 0.2 97.6 10.7 HCH-alpha 0.005 100.9 23.0 0.2 97.8 7.5 heptachlor 0.005 99.8 7.0 0.2 97.9 7.5 heptenophos 0.01 101.2 8.4 0.2 97.9 7.9 iprodione 0.01 99.1 11.6 0.2 98.2 10.3 kresoxim-methyl 0.02 103.3 12.2 0.2 97.5 9.6 lindane 0.01 99.4 8.4 0.2 97.9 7.4 mecarbam 0.04 103.1 11.0 0.2 97.7 8.8 metalaxyl+metalaxyl-M 0.01 103.2 11.1 0.2 97.6 8.1 methidathion 0.01 103.5 12.0 0.2 98.0 9.8 myclobutanil 0.05 104.5 14.6 0.2 97.8 9.7 parathion 0.03 98.3 7.7 0.2 96.8 10.1 penconazole 0.01 104.9 10.2 0.2 97.7 9.1 permethrin 0.02 100.3 12.6 0.2 98.0 11.3 phosalone 0.01 101.3 11.5 0.2 98.1 10.9 pirimicarb 0.01 101.5 10.8 0.2 97.8 8.0 pirimipho s -methyl 0.01 103.6 12.1 0.2 97.9 8.2 propyzamide 0.01 102.1 9.0 0.2 97.4 8.4 pyridaphenthion 0.01 103.6 10.7 0.2 97.8 11.0 pyrimethanil 0.01 100.8 9.4 0.2 97.6 8.2 quinalphos 0.01 104.5 13.7 0.2 97.3 9.3 spiroxamine 0.03 102.2 10.9 0.2 97.4 8.1 tolclofos-methyl 0.01 101.6 8.3 0.2 97.8 7.8 tolylfluanid 0.01 100.1 9.7 0.2 97.2 8.7 triadimefon 0.02 101.5 10.6 0.2 97.3 8.8 triadimenol 0.02 105.4 10.6 0.2 97.6 9.9 triazophos 0.01 102.1 12.4 0.2 97.6 11.5 trifloxystrobin 0.03 102.9 13.4 0.2 97.8 9.9 vinclozolin 0.01 100.3 8.6 0.2 97.5 8.6 Acta agriculturae Slovenica, 111 - 2, september 2018 Helena BASA CESNIK Table 5: Interlaboratory comparison results (in mg kg-1) (BIPEA, 2015) active substance reference tolerance maximum minimum our result z azoxystrobin 0.053 0.027 0.080 0.026 0.056 0.22 bifenthrin 0.022 0.011 0.033 0.011 0.018 -0.73 cyhalotrin-lambda 0.064 0.032 0.096 0.032 0.062 -0.13 deltamethrin 0.166 0.076 0.242 0.090 0.164 -0.05 diphenylamine 0.129 0.062 0.191 0.067 0.112 -0.55 dimethoate 0.066 0.033 0.099 0.033 0.061 -0.3 fenitrothion 0.044 0.022 0.066 0.022 0.050 0.55 phosalone 0.163 0.075 0.238 0.088 0.158 -0.13 kresoxim-methyl 0.023 0.012 0.035 0.011 0.020 -0.5 lindane 0.146 0.068 0.214 0.078 0.140 -0.18 metalaxyl+metalaxyl-M 0.036 0.018 0.054 0.018 0.028 -0.89 myclobutanil 0.032 0.016 0.048 0.016 0.031 -0.13 pirimicarb 0.169 0.078 0.247 0.091 0.152 -0.44 Accuracy was also checked with participation in a proficiency testing scheme organised by BIPEA (Bureau interprofessionnel d'études analytiques). All the results were within the required range (-2 > z < 2). The results are presented in Table 3. 3.3 Precision For the determination of precision (ISO 5725), i.e. repeatability and reproducibility, the extracts of spiked blank strawberry matrix were analysed at two concentration levels. Within the 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 repeatability of the level and the standard deviation of reproducibility of the level were both calculated. The results are given in Table 6. 3 90 Acta agriculturae Slovenica, 111 - 2, September 2018 Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries Table 6: Standard deviation of repeatability (sr) and reproducibility (sR) of the method active substance spiking level (mg kg-1) means of the levels (mg kg-1) sr (mg kg-1) sr (mg kg-1) spiking level (mg kg-1) means of the levels (mg kg-1) sr (mg kg-1) sr (mg kg-1) aldrin 0.005 0.0050 0.0002 0.0003 0.2 0.19 0.01 0.01 azinphos-methyl 0.01 0.010 0.001 0.001 0.2 0.19 0.02 0.02 azoxystrobin 0.04 0.038 0.005 0.006 0.2 0.19 0.02 0.02 bifenthrin 0.01 0.0098 0.0007 0.0008 0.2 0.19 0.01 0.01 bromopropylate 0.01 0.0097 0.0009 0.0009 0.2 0.19 0.01 0.01 bupirimate 0.02 0.020 0.001 0.001 0.2 0.19 0.01 0.01 captan 0.1 0.10 0.02 0.02 0.2 0.19 0.01 0.02 chlorothalonil 0.01 0.0099 0.0007 0.0007 0.2 0.19 0.01 0.01 chlorpropham 0.01 0.0098 0.0005 0.0006 0.2 0.19 0.01 0.01 chlorpyriphos 0.01 0.0098 0.0005 0.0007 0.2 0.19 0.01 0.01 chlorpyriphos -methyl 0.02 0.020 0.001 0.001 0.2 0.19 0.01 0.01 cyhalotrin-lambda 0.01 0.0095 0.0007 0.0009 0.2 0.19 0.01 0.01 cypermethrin 0.03 0.029 0.003 0.003 0.2 0.19 0.01 0.01 cyprodinil 0.01 0.0098 0.0006 0.0007 0.2 0.19 0.01 0.01 DDT 0.05 0.050 0.003 0.004 1.0 0.95 0.05 0.06 deltamethrin 0.03 0.029 0.003 0.003 0.2 0.19 0.02 0.02 diazinon 0.01 0.0098 0.0005 0.0006 0.2 0.19 0.01 0.01 dichlofluanid 0.01 0.0096 0.0006 0.0009 0.2 0.19 0.01 0.01 dimethoate 0.01 0.0097 0.0007 0.0008 0.2 0.19 0.01 0.01 diphenylamine 0.01 0.0099 0.0004 0.0005 0.2 0.19 0.01 0.01 endrin 0.01 0.0100 0.0006 0.0006 0.2 0.19 0.01 0.01 fenitrothion 0.01 0.0098 0.0007 0.0008 0.2 0.19 0.01 0.01 fenthion 0.005 0.0049 0.0003 0.0004 0.2 0.19 0.01 0.01 fludioxonil 0.01 0.010 0.001 0.001 0.2 0.19 0.01 0.02 folpet 0.02 0.020 0.004 0.004 0.2 0.19 0.01 0.02 HCH-alpha 0.005 0.0049 0.0002 0.0002 0.2 0.19 0.01 0.01 heptachlor 0.005 0.0050 0.0003 0.0003 0.2 0.19 0.01 0.01 Acta agriculturae Slovenica, 111 - 2, september 2018 385 Helena BASA CESNIK active substance spiking level (mg kg-1) means of the levels (mg kg-1) sr (mg kg-1) sr (mg kg-1) spiking level (mg kg-1) means of the levels (mg kg-1) sr (mg kg-1) sr (mg kg-1) heptenophos 0.01 0.0098 0.0004 0.0006 0.2 0.19 0.01 0.01 iprodione 0.01 0.0097 0.0009 0.0011 0.2 0.19 0.01 0.01 kresoxim-methyl 0.02 0.020 0.001 0.001 0.2 0.19 0.01 0.01 lindane 0.01 0.0100 0.0005 0.0005 0.2 0.19 0.01 0.01 mecarbam 0.04 0.039 0.003 0.003 0.2 0.19 0.01 0.01 metalaxyl+metalaxyl-M 0.01 0.0098 0.0004 0.0004 0.2 0.19 0.01 0.01 methidathion 0.01 0.0098 0.0009 0.0009 0.2 0.19 0.01 0.01 myclobutanil 0.05 0.049 0.004 0.004 0.2 0.19 0.01 0.01 parathion 0.03 0.029 0.002 0.002 0.2 0.19 0.01 0.01 penconazole 0.01 0.0097 0.0006 0.0007 0.2 0.19 0.01 0.01 permethrin 0.02 0.020 0.002 0.002 0.2 0.19 0.01 0.01 phosalone 0.01 0.0097 0.0009 0.0011 0.2 0.19 0.01 0.01 pirimicarb 0.01 0.0099 0.0006 0.0006 0.2 0.19 0.01 0.01 pirimiphos -methyl 0.01 0.0098 0.0005 0.0006 0.2 0.19 0.01 0.01 propyzamide 0.01 0.0098 0.0005 0.0005 0.2 0.19 0.01 0.01 pyridaphenthion 0.01 0.010 0.001 0.001 0.2 0.19 0.01 0.01 pyrimethanil 0.01 0.0098 0.0006 0.0006 0.2 0.19 0.01 0.01 quinalphos 0.01 0.0098 0.0007 0.0009 0.2 0.19 0.01 0.01 spiroxamine 0.03 0.0296 0.001 0.002 0.2 0.19 0.01 0.01 tolclofos-methyl 0.01 0.0099 0.0005 0.0005 0.2 0.19 0.01 0.01 tolylfluanid 0.01 0.010 0.001 0.001 0.2 0.19 0.01 0.01 triadimefon 0.02 0.020 0.001 0.001 0.2 0.19 0.01 0.01 triadimenol 0.02 0.0195 0.002 0.002 0.2 0.19 0.01 0.01 triazophos 0.01 0.0097 0.0008 0.0009 0.2 0.19 0.01 0.01 trifloxystrobin 0.03 0.029 0.002 0.003 0.2 0.19 0.01 0.01 vinclozolin 0.01 0.0099 0.0006 0.0006 0.2 0.19 0.01 0.01 386 Acta agriculturae Slovenica, 111 - 2, September 2018 Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries 3.4 Uncertainty of repeatability and uncertainty of reproducibility Uncertainty of repeatability and uncertainty of reproducibility were calculated by multiplying the standard deviation of repeatability and the standard deviation of reproducibility by Student's t factor for 9 degrees of freedom and a 95% confidence level (t95;9 = 2.262). Ur = t95; 9 x sr ; UR = t95; 9 x sR The results are presented in Table 7. The measurement uncertainty for PPP residues is set in the Official Gazette of the Republic of Slovenia (Republic of Slovenia, 2007). Its value is 50 %. With validation, analysts must prove that their measurement uncertainty is below or equal to the official measurement uncertainty. 3.5 Sample analysis The method was checked in practice. 19 strawberry samples were analysed for the presence of all 53 validated active substances. 10 samples, which represent 52.6 % of all the analysed samples contained no residues. 5 active substances, all fungicides, were found: chlorothalonil, cyprodinil, fludioxonil, metalaxyl+metalaxyl-M and pyrimethanil. Other active substances were below the LOQ. The most frequently measured was cyprodinil, which was found in 8 samples, representing 42.1 % of all the analysed samples. The reason is probably that this substance is included in the PPP Switch 62.5 WG, which is the mixture of fungicides cyprodinil and fludioxonil used for strawberries and sold in Slovenia. 9 samples, which represent 47.4 % of all the analysed samples contained PPP residues in the range 0.01 - 0.44 mg/kg. Multiple residues (2 or more active substances) were found in 5 samples, representing 26.3 % of all the analysed samples. None of the substances exceeded the valid MRL. Therefore, the conclusion was drawn that farmers were using PPPs according to good agriculture practice described on the labels of the PPPs. Also, these strawberries presented no risk to consumers. The results are presented in Table 8. Comparing our results with the literature we observed that PPP residues in strawberries in Slovenia are mainly comparable to observations of other authors. Jardim et al. (2012) found pesticide residues in Brazilia in 76.3 % of strawberry samples; 71.6 % of them had multiple residues and 13.5 % of them were exceeding the MRL. In Slovenia, the amount of positive samples was about 29 % lower, the amount of multiple residues was about 45 % lower and no MRL exceedances were observed. On the other hand Poulsen et al. (2017) reported that in Denmark, 37 % of the analysed samples contained multiple residues, which is approximately 11 % higher than in Slovenia. In strawberry samples in Poland, Szpyrka et al. (2015) found cypermethrin, deltamethrin and trifloxystrobin among the active substances that we both analysed. On the other hand, again in strawberry samples in Poland, Sójka et al. (2015) found the fungicides cyprodinil (mean content 0.16 mg kg-1), fludioxonil (mean content 0.115 mg kg-1) and pyrimethanil (mean content 0.056 mg kg-1), as well as the insecticide chlorpyrifos (mean content 0.012 mg kg-1) among the active substances that we both analysed. The mean contents of cyprodinil and fludioxonil were comparable to ours, while the content of pyrimethanil was slightly lower. Chlorpyriphos was not found in our research. In protected strawberries Allen et al. (2015) found cyprodinil (mean content 0.062 mg kg-1) and iprodione (mean content 0.055 mg kg-1) among the active substances that we both analysed. The cyprodinil mean content was in the range of contents that we measured, while iprodione was not found in our research. Acta agriculturae Slovenica, 111 - 2, september 2018 Helena BASA CESNIK Table 7: Uncertainty of repeatability (Ur) and reproducibility (UR) of the method active substance spiking level (mg kg-1) Ur (mg kg-1) Ur (%) Ur (mg kg-1) Ur (%) spiking level (mg kg-1) Ur (mg kg-1) Ur (%) Ur (mg kg-1) Ur (%) aldrin 0.005 0.0006 12.0 0.0006 12.0 0.2 0.02 10.0 0.02 10.0 azinphos-methyl 0.01 0.003 30.0 0.003 30.0 0.2 0.04 20.0 0.05 25.0 azoxystrobin 0.04 0.01 25.0 0.01 25.0 0.2 0.04 20.0 0.04 20.0 bifenthrin 0.01 0.002 20.0 0.002 20.0 0.2 0.02 10.0 0.03 15.0 bromopropylate 0.01 0.002 20.0 0.002 20.0 0.2 0.02 10.0 0.03 15.0 bupirimate 0.02 0.003 15.0 0.003 15.0 0.2 0.03 15.0 0.03 15.0 captan 0.1 0.04 40.0 0.04 40.0 0.2 0.04 20.0 0.1 50.0 chlorothalonil 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 chlorpropham 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.02 10.0 chlorpyriphos 0.01 0.001 10.0 0.002 20.0 0.2 0.02 10.0 0.02 10.0 chlorpyriphos-methyl 0.02 0.003 15.0 0.003 15.0 0.2 0.02 10.0 0.03 15.0 cyhalotrin-lambda 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 cypermethrin 0.03 0.007 23.3 0.007 23.3 0.2 0.03 15.0 0.03 15.0 cyprodinil 0.01 0.001 10.0 0.002 20.0 0.2 0.02 10.0 0.03 15.0 DDT 0.05 0.007 14.0 0.008 16.0 1.0 0.12 12.0 0.14 14.0 deltamethrin 0.03 0.006 20.0 0.006 20.0 0.2 0.04 20.0 0.04 20.0 diazinon 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.02 10.0 dichlofluanid 0.01 0.001 10.0 0.002 20.0 0.2 0.03 15.0 0.02 10.0 dimethoate 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 diphenylamine 0.01 0.0009 9.0 0.0011 11.0 0.2 0.02 10.0 0.02 10.0 endrin 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.03 15.0 fenitrothion 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 fenthion 0.005 0.0007 14.0 0.0008 16.0 0.2 0.02 10.0 0.02 10.0 fludioxonil 0.01 0.002 20.0 0.003 30.0 0.2 0.03 15.0 0.04 20.0 folpet 0.02 0.009 45.0 0.009 45.0 0.2 0.03 15.0 0.03 15.0 HCH-alpha 0.005 0.0005 10.0 0.0005 10.0 0.2 0.02 10.0 0.02 10.0 heptachlor 0.005 0.0006 12.0 0.0006 12.0 0.2 0.02 10.0 0.02 10.0 386 Acta agriculturae Slovenica, 111 - 2, September 2018 Validation of the multiresidual GC-MS method for determining plant protection product residues in strawberries active substance spiking level (mg kg-1) Ur (mg kg-1) Ur (%) Ur (mg kg-1) Ur (%) spiking level (mg kg-1) Ur (mg kg-1) Ur (%) Ur (mg kg-1) Ur (%) heptenophos 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.03 15.0 iprodione 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 kresoxim-methyl 0.02 0.003 15.0 0.003 15.0 0.2 0.03 15.0 0.03 15.0 lindane 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.02 10.0 mecarbam 0.04 0.007 17.5 0.007 17.5 0.2 0.02 10.0 0.03 15.0 metalaxyl+metalaxyl-M 0.01 0.0009 9.0 0.0010 10.0 0.2 0.02 10.0 0.03 15.0 methidathion 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 myclobutanil 0.05 0.009 18.0 0.009 18.0 0.2 0.02 10.0 0.03 15.0 parathion 0.03 0.005 16.7 0.005 16.7 0.2 0.03 15.0 0.03 15.0 penconazole 0.01 0.001 10.0 0.002 20.0 0.2 0.02 10.0 0.03 15.0 permethrin 0.02 0.004 20.0 0.005 25.0 0.2 0.03 15.0 0.03 15.0 phosalone 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 pirimicarb 0.01 0.001 10.0 0.001 10.0 0.2 0.03 15.0 0.03 15.0 pirimipho s -methyl 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.02 10.0 propyzamide 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.03 15.0 pyridaphenthion 0.01 0.002 20.0 0.003 30.0 0.2 0.03 15.0 0.03 15.0 pyrimethanil 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.03 15.0 quinalphos 0.01 0.002 20.0 0.002 20.0 0.2 0.02 10.0 0.02 10.0 spiroxamine 0.03 0.003 10.0 0.004 13.3 0.2 0.02 10.0 0.02 10.0 tolclofos-methyl 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.02 10.0 tolylfluanid 0.01 0.002 20.0 0.002 20.0 0.2 0.02 10.0 0.03 15.0 triadimefon 0.02 0.003 15.0 0.003 15.0 0.2 0.02 10.0 0.03 15.0 triadimenol 0.02 0.003 15.0 0.004 20.0 0.2 0.02 10.0 0.03 15.0 triazophos 0.01 0.002 20.0 0.002 20.0 0.2 0.03 15.0 0.03 15.0 trifloxystrobin 0.03 0.005 16.7 0.006 20.0 0.2 0.03 15.0 0.03 15.0 vinclozolin 0.01 0.001 10.0 0.001 10.0 0.2 0.02 10.0 0.02 10.0 Acta agriculturae Slovenica, 111 - 2, september 2018 Helena BASA CESNIK Table 8: Contents of active substances found in 19 strawberry samples chlorothalonil (mg kg-1) cyprodinil (mg kg-1) fludioxonil (mg kg-1) metalaxyl+metalaxyl-M (mg kg-1) pyrimethanil (mg kg-1) MRL (mg kg-1) 4.0 5.0 4.0 0.6 5.0 sample no. 1 - - - - - 2 - - - - - 3 - 0.04 - - - 4 - 0.04 - - - 5 - - - - - 6 - - - - - 7 - - - - - 8 0.01 - - - - 9 - - - - - 10 - 0.02 - - - 11 0.10 0.02 - - - 12 - - - - - 13 - 0.24 0.17 - 0.13 14 0.06 0.02 - - - 15 - - - - - 16 - 0.24 - 0.02 - 17 0.02 0.08 - - 0.44 18 - - - - - 19 - - - - - - means