New Developments in QuEChERS methodology Michelangelo Anastassiades Bünyamin Tasdelen Ellen Scherbaum Stuttgart Chemical and Veterinary Control Laboratory Slide 1
Outline Introduction, Original QuEChERS Modifications to broaden analyte spectrum Modified QuEChERS Modifications to broaden matrix spectrum Results from method validation Results from EU-PT 6 + 7 Summary Slide 2
Introduction QuEChERS: Quick Easy Cheap Effective Rugged Safe Was first introduced at the EPRW 2002 in Rome and published in 2003 as Fast and Easy Multiresidue Method Employing Acetonitrile Extraction/Partitioning and Dispersive SPE for the Determination of Pesticide Residues in Produce M. Anastassiades, S.J. Lehotay, D. Štajnbaher, F.J. Schenck, J. AOAC Int., 86 (2) 412-431, 2003 Slide 3
Original QuEChERS-Method Weigh 10 g of Sample (50 ml Teflon-Tube) Add 10 ml Acetonitrile Shake Vigorously 1 min Add 4 g MgSO 4 and 1 g NaCl Add ISTD-Solution Shake Vigorously 1 min Shake 30 s and Centrifuge Take Aliquot and Mix with MgSO 4 and PSA GC-MSD and LC-MS Shake Vigorously 30 s and Centrifuge Anastassiades et al. J. AOAC Int. 86 (2) 412-431 Slide 4
Analyte and Matrix Spectrum The original QuEChERS covers a broad analyte spectrum ranging from the unpolar to the very polar end The original method was developed for fruit and vegetables Propamocarb (ph4) Clopyralid (ph5) Acephat Oxamyl Methomyl 2,4-D (ph 5) Cymoxanil (ph5) Acetamiprid Kasugamycin Aldicarb Ofurace Pirimicarb Dichlorvos Iprodion Spinosad Tebufenpyrad Fenpropathrin Etofenprox -2,6-1,8-0,9-0,4 0,1 0,2 0,6 0,8 1,0 1,2 1,4 1,7 2,1 3,0 4,0 5,0 6,0 7,0 Slide 5
Broaden Analyte Spectrum Some pesticides are sensitive to ph Some get ionized at certain ph-values Acids: HX H + + X - Bases: B + H + BH + Ionic form prefers to stay in the waterphase ph-range of agricultural samples: ~2.5 7 Slide 6
Ionizable Compounds - Basic Pesticides Matrix: apple; fortif. level: 0.1 mg/kg; analysis: LC/MS; ESI (+) Propamocarb Imazalil Prochloraz Thiabendazole Carbendazim Fenpropimorph Spiroxamine pka of corresp. acid 9.5 pka of corresp. acid 6.5 pka of corresp. acid 3.8 pka of corresp. acid 4.7 pka of corresp. acid 4.2 pka of corresp. acid 6.9 pka of corresp. acid 7.0 ph 2.9 0 20 40 60 80 100 120 Recovery % Slide 7
Ionizable Compounds - Acidic Pesticides LC-MS/MS, ESI (-), No PSA Cleanup 120 Recovery % 100 80 ph5.5 60 40 20 0 ph 6 ph 5 ph 4 ph 3 Imazethapyr Dicamba MCPA 2,4-D Imazaquin Naphthylacetic acid Fluoxypyr 2,4,5-T Mecoprop Triclopyr 2,4,5-TP 2,4-DP Propyzamid Ioxynil Bentazon Bromoxynil Fluazifop Bromacil 2,4-DB MCPB Imazapyr Clopyralid Picloram Benazolin 4-CPA Lower pka values General Trend Higher pka values Slide 8
ph-labile Compounds Some Pesticides are sensitive to ph and degrade at high or low ph-values In the sample (during processing and storage) Keep low temperatures During sample preparation Work fast, adjust ph In the extract during storage (1 week is common) Keep low temperatures, adjust ph, after dispersive SPE with PSA, ph may reach values exceeding 8 Slide 9
Optimal ph for QuEChERS? Goals: Still good extraction for the most strong acids Still good protection for base-sensitives tolylfluanid, dichlofluanid, captan, folpet, dicofol, pyridate Still good protection for acid-sensitives sulfonylureas, pymetrozine, carbosulfan, dioxacarb... Extraction Extract storage Slide 10
Optimal ph for QuEChERS? ph adjustment before extraction (Buffering) 1) Buffering to ph of ~6, Lehotay et al. with acetate buffer good recovery for pymetrozine Low recoveries for some acidic pesticides PSA cleanup is much less efficient 2) Buffering to ph of 5 to 5.5, citrate buffer, 4 g Magnesium sulphate anhydrous, 1 g Sodium chloride, 1 g Trisodium citrate dihydrate and 0.5 g Disodium hydrogencitrate sesquihydrate Slide 11
Portioning of sorbents and salts Rapid and Easy Slide 12
Optimal ph for QuEChERS? ph adjustment after cleanup Use of formic acid in acetonitrile to achieve a ph of 5 Base-labile compounds are stabilized: tolylfluanid, Tolylfluanid extract stability Rec. % 100 dichlofluanid, 90 7 days 80 captan, 13 days 70 60 folpet, 50 40 dicofol, 30 20 pyridate 5% formic acid: 10 µl/ml 10 0 ph 4 ph 5 ph 6 ph 7 ph 8 ph 9 MeCN Measured ph in extract Slide 13
Sulfonylureas, Carbosulfan acid labile... Rec. in % 120 100 80 60 40 20 0 7 days 13 days Primisulfuron-Methyl ph 4 ph 5 ph 6 ph 7 ph 8 ph 9 MeCN Measured ph of extract If these compounds are included in the target spectrum use an aliquot of the final extract before acidifying Slide 14
Improved cleanup Alox N Supelco, C18 C8-Varian, C8-Amino 50mg C8/SAX, ENVI-18 Polymeric Strata x, PSA Varian Si-PFP, Strata NH2 Strata polym. w. Anion, Waters Wax cc6 Si-Triamine, Si-Diamine H2O Phobic WA-DVB Speedisk, Si-Amine NH2 Amino Speedisk, Si-Dimethylamine C8-Amino25, Strata Screen-A Diamino MN, UP60-50NH2 interchrom 1,2,Amino Bakerbond, Amino SPE J.T.Baker Alox Aldrich, Aminopropyl modif. MN Alumina-B Supelclean, Alox Aldrich acidic DEA Varian, Alox N MN Alumina A Supelclean, Dimethylamino modif. MN LiChrolut Sax, PA Chromabond DPA-6S, PF-AEV interchrom DSC-MCAX, Cation mixed-mode polym. Strata PCA MN, PH Varian... For samples, with a high content of carotinoides or chlorophyll cleanup with PSA is not satisfying... We tested more than 50 SPE sorbents! Slide 15
Improved cleanup GCB, Graphitized Carbon Black, was best in handling and effect Some pesticides have a high affinity towards GCB e.g. hexachlorobenzene, chlorothalonil, thiabendazole Lettuce Extract Anthracene may be used as surrogate QC standard. Recoveries > 70% will indicate that no unacceptable losses of pesticides have occurred. PSA GCB Slide 16
Improved cleanup Dispersive SPE is performed using a combination of PSA and GCB Final extract should remain slightly coloured PSA GCB The cleanup time (shaking) is extended from 30 s to 2 min, Pre-mixtures of MgSO 4 and GCB facilitates weighing Slide 17
Weigh 10 g of Frozen Sample Add 10 ml Acetonitrile Add ISTD-Solution Shake Add 4 g MgSO 4 / 1 g NaCl / Buffered to ph 5-5.5 with Citrate Buffer Shake & Centrifuge Mix an Aliquot with MgSO 4 & PSA/(GCB) Shake & Centrifuge Acidify extract to ph ~5 to protect base-sensitive pesticides Optionally: Add other Analyte Protectants Optionally: Acidic Pesticides LC-MS Optionally: SUs LC-MS QuEChERS Multiresidue Analysis by GC-MS, LC-MS... Slide 18
Broaden matrix spectrum Dry commodities (cereals, dried fruits) Fatty Commodities Slide 19
Broaden matrix spectrum E.g. cereals, dried fruits Dry Commodities require the addition of water prior to extraction to weaken interactions of pesticides with the matrix and to ensure adequate partitioning. Weigh 5 g of sample add 10 ml water... Remove co-extracted fat by freezing out or C18, if necessary... Slide 20
Dry Commodities Sample type Weigh Water Annotation Cereals 5 g 10 g Dried fruits 5 g 7.5 g Add water to comminute, weigh 12.5 g of homogenate Fruit/Vegetables (water >80 %) 10 g - Fruit/Vegetables (water 30-80 %) 10 g X g X = 10 g water amount in 10 g sample Honey 5 g 10 g Spices 2 g 10 g Slide 21
Broaden matrix spectrum Fatty commodities Commodities with a high lipid load, such as avocados or plant oils can be employed. Problems: Highly non-polar pesticides may give recoveries < 70% (e.g. HCB and DDT) Co-extracted lipids have to be removed prior to GC-analysis Slide 22
Removal of co-extracted lipids 5 4 4,20 4,03 3 2 1,48 1,33 1,25 1,23 1,15 1,10 1 Extractives [mg/ml] 0 freezing out PSA raw extract C18/freezing out C18 PSA/freezing out PSA/C18/freezing out PSA/C18 Slide 23
100 75 50 25 0 Slide 24 1g 2g 3g BS138 Hexachlorobenzene p,p' -DDE Dieldrin Endosulfan HCH, gamma- Chlorpyriphos-methyl Carbaryl Chlorpyriphos Fenthion Pirimiphos-methyl Diazinon TPP Trifluralin Deltamethrin Malathion Cypermethrin Recoveries for oil matrix
Recoveries for oil matrix 100 75 50 25 0 Slide 25 1g 2g 3g BS138 Hexachlorobenzene p,p' -DDE Dieldrin Endosulfan HCH, gamma- Chlorpyriphos-methyl Carbaryl Chlorpyriphos Fenthion Pirimiphos-methyl Diazinon TPP Trifluralin Deltamethrin Malathion Cypermethrin PCB 138 or 153 may be used as surrogate QC standards Recoveries > 70% will indicate that no unacceptable losses of pesticides have occurred.
Interlaboratory Validation 3 Validation studies were performed in 2005 and 2006 in Germany Thanks to: Dr. Lutz Alder Berlin, PeterBaumann Dortmund, Dr. Sabine Bracht Münster, Dr. Franz Haslbeck Pfaffenhofen, Dr. Matthias Heinzler Kassel, Dr. Günther Kempe Chemnitz, Labor Specht Hamburg, Dr. Jürgen Lipinski Berlin, Dr. Peter Seulen Kiel, Dr. Magnus Jezussek Erlangen, Dr. Iris Suckrau Oldenburg, Dr. Harald Kubel Potsdam, Anja Bostel Stuttgart, Dr. Norbert Reichert Taunusstein, Dr. Graf Rostock Slide 26
GC-MS and LC-MS/MS Inter-Laboratory Validation Study (GDCh) GC LC (+) Mean recovery, all laboratories, all analytes 101% 100% 105% 102% 100% 100% Apple Lettuce Orange Slide 27 LC (-)
GC-MS and LC-MS/MS Inter-Laboratory Validation Study (GDCh) GC Slide 28 LC (+) LC (-) Mean RSD %, all laboratories, all analytes 3% 4% 8% 9% 5% 3% Apple Lettuce Orange
LC-MS/MS Inter-Laboratory Validation Study (BLAPS-Working Group) Mean recovery, all laboratories, all analytes 97% 97% 98% 98% 96% 98% 95% 97% Cucumber Lemon Wheat Raisins Ethiofencarb was oxidized in cucumber Slide 29 SUs degraded in acidified extract
LC-MS/MS Inter-Laboratory Validation Study (BLAPS-Working Group II) Mean recovery, all laboratories, all analytes 101% 98% 99% 94% 100% 101% 100% 97% Cucumber Lemon Wheat Raisins Oxidation Acids, lost in PSA cleanup Degraded in the standard solution provided Slide 30
EU - Proficiency Test 6 and 7 EU-PT 6, Tomates (mg/kg) Pesticide Acrinathrin Azoxystrobin Bromopropylate Chlorothalonil Diazinon Dimethoate Endosulfan Imazalil Imidacloprid Oxydemeton-me Procymidone Thiabendazole CVUA S QuEChERS 0.2 0.23 0.46 2.2 4.4 0.13 0.31 0.16 0.23 0.24 0.41 0.33 No. 4 Median (n=130) 0.284 0.225 0.490 1.626 3.955 0.132 0.344 0.167 0.232 0.199 0.412 0.330 No. 1 EU-PT 7, Grapes (mg/kg) Pesticide Acetamiprid Carbaryl Cyprodinil Diazinon Dimethoate Fenhexamid Fludioxonil Imidacloprid Iprodione Kresoxim-me Methomyl Monocrotophos Procymidone Pyrimethanil Tetraconazole Thiabendazole CVUA S QuEChERS 0.324 1.68 0.472 0.318 0.144 0.772 0.242 0.598 0.538 0.502 0.153 0.761 1.98 0.148 0.076 0.745 Median (n=128) 0.312 1.62 0.437 0.287 0.139 0.706 0.238 0.549 0.524 0.453 0.167 0.643 1.90 0.149 0.064 0.656 Slide 31
www.quechers.com...the modified QuEChERS method including all presented modifications and a lot of background information is available via the internet, as well as the validation data. www.quechers.com Slide 32
Thank you for your attention!...and the CVUA-Team for their dedicated work and their support! Slide 33