Anal Bioanal Chem DOI 10.1007/s00216-014-8270-1
NOTE
Pesticide determination in rose petals using dispersive solid-phase extraction followed by gas chromatography-tandem mass spectrometry Oriane Tascone & Marina Shirshikova & Céline Roy & Uwe J. Meierhenrich
Received: 12 September 2014 / Revised: 13 October 2014 / Accepted: 13 October 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Damascena and centifolia roses are cultivated worldwide for their petal extracts that contain key odorant ingredients of perfumes. The analytical identification and quantification of pesticides in rose petals have never been described in the literature. Here, we report on a newly developed method using dispersive solid-phase extraction (d-SPE) cleanup followed by gas chromatography-tandem mass spectrometry for the quantitative determination of multi-residue pesticides in rose petals. Analytes were extracted from the matrix using acetonitrile and a mixture of salts containing magnesium sulfate, sodium citrate, sodium chloride, and sodium sesquihydrate. Samples were cleaned up twice by d-SPE applying primary and secondary amines (PSAs), magnesium sulfate, C18, and graphitized carbon black (GCB). Two fortification levels of 0.05 and 0.5 mg kg−1 were assessed for method validation purposes. The obtained pesticide recoveries were in the range of 70–120 % with a relative standard deviation (RSD) of less than 20 %. The newly developed method was allowed for the quantification of 57 pesticides residues. It was applied to pesticide residue detection in rose petals from an organic field, without treatment, compared to those from a field with classic phytosanitary treatment using fungicide and/or insecticide. We did not detect pesticide residues in rose petals from the organic field. The classically treated samples of roses contained pesticides such as chlorpyriphos and methidathion which are in accordance with the previous application of these pesticides on the roses.
O. Tascone : M. Shirshikova : C. Roy European Research Institute on Natural Ingredients (ERINI), 06130 Grasse, France O. Tascone : U. J. Meierhenrich (*) Institut de Chimie de Nice, UMR 7272 CNRS, University Nice Sophia Antipolis, 06108 Nice, France e-mail: [email protected]
Insecticides were quantified at 0.05 mg kg−1 rose petal maximum. Keywords Dispersive solid-phase extraction . Gas chromatography . Perfume . Pesticides residue analysis . Rose petals . Tandem mass spectrometry
Introduction Extracts of natural raw materials are commonly used in perfume, aroma, and cosmetic industries. The crop production of those is habitually based on monoculture and involves the use of different chemical classes of xenobiotica, including pesticides. Legal regulations for raw materials intended for perfume, aroma, and cosmetic products have become increasingly strict in terms of the allowed residual levels of chemicals used for treatment because of their impact on public health and on the environment. A few studies have been dedicated to the analyses of pesticides in natural extracts and raw materials from which they originate [1, 2]. Extracts of roses in the form of essential oils and absolutes are widely used in perfumes. Despite the low extraction yields with approximately 0.03 and 0.3 %, for rose essential oil and rose concrete, respectively [3], more than 10 tons of concrete and 4 tons of essential oils are produced worldwide each year. Typical rose species are Rosa damascena from Turkey, Bulgaria, and Morocco; Rosa centifolia is cultivated in France only. To define and regulate the agricultural residue levels in rose extracts, it is important to develop an analytical method that is able to systematically determine pesticide contents in rose petals. In a later step, the content of individual pesticides in rose petals will be compared with the pesticide content in intermediate perfume products such as rose absolute and rose concrete.
O. Tascone et al.
The QuEChERS approach and derivatives of this method have recently been applied for the analysis of more than 200 pesticide residues in fruit and vegetable samples [4, 5]. We here describe the development and the application of a method using an extraction and d-SPE purification step to analyze a priority list of 57 multiclass pesticides in rose petals. This method allowed quantifying 57 pesticides. Fifty pesticides, out of them, were quantified in a concentration lower or equal their authorized maximum residue limits. Due to the volatility of the targeted molecules and the sensitivity of the apparatus, GC-MS/MS was employed to quantify the pesticide residues.
Standard solution preparation Individual pesticide standard stock solutions were prepared at approximately 1000 μg mL−1 in toluene and stored at −18 °C. A 100 μg mL−1 working standard mixture of these pesticides in toluene was prepared from the stock solution (mix 1). Two other mixtures of pesticides (mix 2) from CPI International were diluted in toluene at 100 μg mL−1. All these mixtures served as the spiking solution of high concentration and two low concentration spiking solutions of 10 and 1 μg mL−1 were also prepared in toluene. Sample preparation method
Materials and methods Chemicals and materials Acetonitrile (Optima LCMS grade) and acetic acid (HOAc Optima) were purchased from Fisher Scientific (Illkirch, France). Toluene (Chromasolv for HPLC 99.9 % grade) was from Sigma-Aldrich (Saint-Quentin Fallavier, France). A modified QuEChERS method for sample preparation was developed as follows: For the extraction/partitioning step, pouches (DisQuE) containing 1 g sodium citrate, 1 g sodium chloride, 4 g magnesium sulfate, and 0.5 g sodium sesquihydrate were purchased from Waters (Wexford, Ireland). For dispersive solid-phase extraction (d-SPE) cleanup, tubes containing 900 mg MgSO4, 150 mg primary and secondary amines (PSAs), and 150 mg C18 were obtained from Waters (Wexford, Ireland). One hundred fifty micrograms graphitized carbon black (GCB) sorbent purchased from Agilent Technologies (Massy, France) was added to the cleanup tubes. The reconstituted matrix contained phenethyl alcohol from Yinghai (Canghzou, China); citronellol from BASF (Ludwigshafen, Germany); linalool from DSM Nutritional (Heerlen, Netherlands); geranyl acetate, citronellyl acetate, and eugenol from internal preparation; and alkanes (C7–C40), geraniol, and fatty acid esters from Sigma-Aldrich (Saint-Quentin Fallavier, France). Pesticide reference standards (mixture and individual standard) of ≥95 % or higher purity were obtained from CPI International (Santa Rosa, USA) and Dr. Ehrenstorfer GmbH (Augsburg, Germany). Table 1 lists the pesticides investigated by this study. These pesticides are those most often found in natural extract analysis according to previous analyses (unpublished data) or known to be applied in crops. The analytical method was developed on pesticide-spiked rose petals from an organic field. The method was also applied on roses from fields with phytosanitary treatment and on organic flowers.
Rose petals were cut and directly stored in the freezer at −18 °C. The moisture of rose petals was ∼80 %. After freezing, 100 g of the rose petals was ground and homogenized. A subsample of 5.0 g of rose petals was transferred into a 50-mL centrifuge tube and 15 mL acetonitrile were added. The tube was shaken by hand for 1 min and placed in the fridge (4 °C) for 4 h. The contents of a pouch (MgSO4, sodium citrate, NaCl, and sodium sesquihydrate) were added into the tube to remove residual water and to assist the extraction of pesticides from the matrix. The tube was vigorously shaken with a vortex mixer for ∼30 s. Subsequently, the mixture was centrifuged for 10 min at 2630 rcf. Then, 8.0 mL of the supernatant was transferred into a d-SPE cleanup tube containing MgSO4 (900 mg), PSA (150 mg), C18 (150 mg), and GCB (150 mg), and 3 mL toluene was added. The tube was vigorously shaken with a vortex mixer for 1 min. Subsequently, the mixture was centrifuged for 10 min at 2630 rcf. The extract was transferred in a second purification tube which also contained MgSO4, PSA, C18, and GCB and shaken with a vortex mixer. After centrifugation, 4 mL of the resulting solution was evaporated under nitrogen flow at 35 °C. Then, the residue was transferred in a GC vial. The tube was washed with a small amount of toluene. The final volume was adjusted to 1 mL. For the development of the analytical method, samples were spiked before the extraction step at 0.5 mg kg−1. For each trial, a non-spiked sample was prepared to check the pesticide concentration in the blank matrix. To evaluate sample preparation and to validate the quantification method, quality control samples were prepared: Rose petals were spiked at 0.05 and 0.5 mg kg−1 before the extraction step with the mixture of the pesticides under investigation. GC-MS/MS analysis GC-MS/MS analyses were performed on an Agilent 7000 triple-quadrupole mass spectrometer interfaced to an Agilent 7890A gas chromatograph (Massy, France). The GC was equipped with a capillary column HP5-MS (30 m×0.25 mm
Pesticide determination in rose petals Table 1 GC-MS/MS parameters for the determination of 57 pesticide residues in rose petals Time segment
1 2 3 4 5
6 7 8
9
10 11
12 13
14 15
16
17
18
Compound
tR (min)
MRM transition Quantifier
CE (V)
Qualifier 1
CE (V)
Qualifier 2
CE (V)
2-Phenylphenol Phorate 2,4-D Isopropyl ester Lindane Propetamphos Diazinon Phosphamidon Acetochlor Parathion-methyl Chlorpyrifos-methyl Fenitrothion Pirimiphos-methyl Malathion Fenthion
7.78 9.92 10.28 11.11 11.13 11.51 12.87 13.16 13.25 13.28 14.32 14.38 14.73 15.11
170→169 260→75 175→111 181→145 138→110 137→84 127→109 223→132 125→79 286→93 125→79 290→125 127→99 278→109
12 5 12 20 5 10 15 20 5 30 10 25 5 20
170→141 231→175 175→145 219→183 138→64 152→137 127→95 147→132 263→109 286→271 277→260 290→151 173→99 278→169
25 15 17 7 15 5 15 10 15 15 5 25 12 15
170→115 231→129 175→109 181→109 236→166 152→84 264→127 223→147 263→79 286→208 277→109 305→290 173→127 278→125
30 30 25 25 15 20 5 10 30 15 20 10 5 25
Chlorpyrifos Parathion Dichlorobenzophenone
15.21 15.24 15.37
197→169 291→109 139→111
15 15 15
314→258 291→81 139→75
15 25
258→166 291→91
22 25
Chlorfenvinphos Isofenphos Quinalphos Phenthoate Mecarbam Methidathion Endosulfan I Fenamiphos Prothiofos Profenofos p,p′-DDE Fludioxonil Buprofezin Chlorfenapyr
17.00 17.04 17.09 17.16 17.16 17.78 18.28 18.85 19.17 19.30 19.49 19.54 19.99 20.84
267→159 213→121 156→129 274→121 329→159 145→85 241→206 303→154 267→239 337→267 246→176 248→182 190→175 328→247
17 15 15 10 5 5 17 15 10 15 25 15 5 5
323→267 213→185 156→102 274→125 131→86 145→58 195→159 303→288 309→239 337→309 318→248 248→154 190→117 247→200
30 10 5 15 20 10 17 5 10 15 5 30 20 30 30
111→75 267→81 185→121 270→156 273→93
10 30 15 15 10
195→125 303→195 309→281 337→188 318→246 248→127 190→132 247→227
25 7 7 30 30 30 25
Endosulfan II
21.05
195→159
10
195→125
25
241→206
30 10
Chlorobenzilate o,p′-DDT Ethion Triazophos Endosulfan sulfate p,p′-DDT Propargite Iprodione Pyridafenthion Phosmet Bromopropylate Bifenthrin
21.14 21.71 21.86 22.54 23.21 23.49 24.56 25.83 25.94 26.00 26.21 26.59
139→111 235→165 153→97 161→134 387→253 235→165 135→107 314→245 188→82 160→77 183→155 181→165
15 30 15 5 5 30 15 10 10 25 15 30
251→139 237→165 231→175 161→91 387→289 235→199 173→91 187→124 340→199 160→133 183→76 181→153
15 30 15 15 5 17 30 30 10 15 30 15
251→111 235→199 231→129 161→106 387→219 165→164 173→107 314→271 188→91 160→105 340→183 181→141
30 15 30 15 30 20 30 6 20 20 15 30
Fenpropathrin Tetradifon Azinphos-methyl
26.82 27.61 28.14
208→181 159→131 160→77
5 5 17
181→152 354→159 160→132
30 10 5
265→210 227→199 160→104
10 14 7
O. Tascone et al. Table 1 (continued) Time segment
19
20
Compound
Phosalone Cyfluthrin I Cyfluthrin II Cyfluthrin III Cyfluthrin IV Cypermethrin I Cypermethrin II Cypermethrin III Cypermethrin IV Deltamethrin
tR (min)
28.16 33.58 33.89 34.10 34.26 34.48 34.81 35.02 35.15 39.60
MRM transition Quantifier
CE (V)
Qualifier 1
CE (V)
Qualifier 2
CE (V)
182→111 163→91 163→91 163→91 163→91 163→91 163→91 163→91 163→91 253→93
20 15 15 15 15 15 15 15 15 15
182→138 163→127 163→127 163→127 163→127 163→127 163→127 163→127 163→127 181→152
5 5 5 5 5 5 5 5 5 15
182→102 226→206 226→206 226→206 226→206 181→152 181→152 181→152 181→152 253→174
20 15 15 15 15 30 30 30 30 5
i.d.×0.25 μm film thickness) from Agilent Technologies. The carrier gas was helium at a constant flow of 1 mL min−1. The gas chromatograph was equipped with an Agilent 7683 autosampler and a split/splitless injector. The temperature program was the following: initial temperature of 90 °C held for 1 min, 30 °C min−1 ramp to 180 °C, then 3 °C min−1 ramp to 280 °C and held for 5 min. The temperature of the injection port was 280 °C, and a 1-μL volume was injected in pulsed splitless mode. The MS transfer line and ion source temperatures were both set at 280 °C. An electron energy of 70 eV was used for ionization of the analytes. Analyses were performed in multiple reaction monitoring (MRM) mode based on the use of one transition for quantification (quantifier) and two transitions to confirm the compound identity (qualifier). For each analyte, we optimized the transitions and the collision energy (CE). To detect all 57 pesticides, the MRM method was divided into 20 time segments (Fig. 1). Acquisitions and data processing were performed with Mass Hunter software. Table 1 summarizes the optimized MS/MS conditions for the individual analytes and their retention times (tR). Method validation The analytical method was validated according to the singlelaboratory validation approach. The performance of the method was evaluated considering different validation parameters that include linearity, recovery, repeatability, and reproducibility. Five replicates of samples at two spiking levels (0.05 and 0.5 mg kg−1) were extracted and injected. Samples were quantified with external calibration curves. Five calibration levels ranging from 0.01 to 1 μg mL−1 were prepared in the reconstituted matrix containing phenethyl alcohol (0.1 %), geranyl acetate (0.01 %), citronellyl acetate (0.001 %), eugenol (0.001 %), geraniol (0.001 %), citronellol (0.001 %), linalool (0.01 %), alkanes (C7–C40) (10 %), and fatty acid
esters (1 %) diluted in toluene. The calibration standards were distributed among the sample extracts. Five replicates of standards were injected. The precision of the method which was represented by estimation of the variability of measurements was described as the value of relative standard deviation (RSD). Recoveries included in the range 70–120 % with a repeatability RSD ≤20 % allowed to validate accuracy of the method [6].
Results and discussion Development of the reconstituted matrix First, the QuEChERS method was tested as it was described in NF EN 15662. The calibration curves of standards prepared in toluene and the calibration curves of standards prepared in the pesticide-free matrix were used to quantify the pesticide residues. Strong positive matrix effects were observed with the calibration curve prepared in solvent. With matrix calibration, 90 % of the recoveries were within the 70–120 % range. However, the use of matrix extracts to prepare the standard cannot be chosen routinely because rose crop begins in May and finishes in June, so rose petals are not available all year long, especially organic flowers from which the pesticide-free calibration curve is built. An alternative solution was to use the reconstituted matrix for calibration purposes. The components for this mixture were chosen after their identification in blank-extracted petals. Some of these compounds were conventionally found in rose extracts such as absolute or essential oils [7, 8]. Matrix effects were still present but induced less bias as compared to a standard prepared in pure solvent. A standard prepared in the reconstituted matrix was adopted for quantification purpose.
1 7
2
3 10
4
5
6
7 8
9
10
11
15
12
Sample D Standard 0.05 µg.mL -1
13
14
15
16
Phosalone + Azinphos methyl
Sample B Standard 0.01 µg.mL -1 Sample A
18
19 30
Deltamethrin
CypermethrinI, II, III, IV
Cyfluthrin I, II, III, IV
Chlorpyrifos Ethyl, tR : 15.21 min
Tetradifon
Fenpropathrin
Bromopropylate
17 25
20
Pyridaphenthion + Iprodione
Propargite
Triazophos
Phosmet Bifentrhin
Sample F
Endosulfan sulfate p,p’-DDT
Chlorfenapyr
Endosulfan II + Chlorobenzilate + o,p’DDT + Ethion
Buprofezin
Methidathion
Prothiofos + Profenofos +p,p’-DDE + Fludioxonil
Chlorfenvinphos + Isofenphos + Mecarbam + Phenthoate + Quinalphos
Standard 0.1 µg.mL -1
Endosulfan I Fenamiphos
Malathion
Fenthion + Chlropyrifos Ethyl + Parathion + Dichlorobenzophenone
Phosphamidon Acetochlor + Methyl Parathion + Chlorpyifos Methyl
Lindane + Propetamphos Diazinon
Phorate 2,4-D Isopropyl Ester
2-phenylphenol
Fenitrothion + Pirimiphos Methyl
Pesticide determination in rose petals
20 35
40
t (min)
Fig. 1 MRM chromatogram of the 1 μg mL−1 standard as prepared in the reconstituted matrix including the repartition of time segments 1–20. The inset represents the extracted chlorpyrifos signals at three calibration
levels along with samples A, B, D, and F. In samples B, F, and D, chlorpyrifos was quantified at 0.012, 0.033, and 0.055 mg kg−1, respectively
Impact of equilibration time before extraction
sample prepared with the complete QuEChERS method with a sample that was not QuEChERS-purified. The pesticide recoveries were impacted. A positive matrix effect in the non-QuEChERS-purified sample caused an increase of recovery rates above 100 % that overestimated extraction yields. The purification step was thus found to be essential for sample preparation; its improvement, however, was required.
The influence of the equilibration time te before salt addition for extraction was tested. Mixtures of sample and acetonitrile were stored in fridge at 4 °C for te =4 h and 2, 3, and 4 days before the extraction. At te =4 h, the pesticide recovery was improved: about 10 % more analytes were in the 70–120 % tolerance range at te =4 h as compared to te =0 h. Increasing te to 48 h allowed to slightly increase the recoveries for several pesticides, but because of the high increase of the analysis time, these conditions were not retained for routine purposes. Samples at room temperature and samples stored in the fridge at 4 °C were subjected to te =4 h to test the influence of the equilibration temperature Te. The number of analytes with recoveries within 70–120 % was similar between both trials, but when the sample was stored in the fridge, recoveries were closer to 100 %. This is probably due to cooling of the sample before extraction which allowed extracting less matrix. Moreover, the extraction step produced exothermic reactions, so pesticides were potentially degraded by temperature increase.
The influence of GCB on the purification step GCB is known to irreversibly retain planar pesticides [5] and therefore to potentially induce a bias on the pesticide recoveries. To test the GCB impact, one sample was purified without using GCB. The results were compared with those obtained for purification with GCB. Pigments present in the extract were not removed by non-GCB purification. Consequently, recoveries were impacted by this more complex matrix. With GCB, 15 % more analytes possessed recoveries within the 70–120 % range. Addition of toluene for the purification step
Selection of cleanup conditions Influence of the purification step The impact of the purification step was investigated by comparing the pesticide extraction recoveries obtained for a
As mentioned above, GCB adsorbent removes pigment and sterols from the extracts, but it is also known to irreversibly retain pesticides of planar-aromatic structure [5], such as o-phenylphenol, dichlorobenzophenone, and fenamiphos. The addition of a solvent as toluene was tested to desorb planar-
O. Tascone et al.
aromatic pesticides [9, 10]. Toluene was chosen because of its insolubility in water, limiting polar coextractives, its lower volume expansion compared to acetonitrile, and its compatibility with splitless injection [11]. Moreover, toluene provides π-π interaction with planar aromatic pesticides and limits their adsorption by GCB. After transfer of 8 mL of supernatant in the purification tube, 3 mL toluene was added. Recoveries were found to be improved using toluene. To give an example, the fenamiphos recovery increased from 49 % without toluene to 81 % with toluene addition. Influence of the injection order Despite the QuEChERS-type sample preparation, specific molecules that possessed similar properties as compared to the analytes stayed in the extract. To decrease such effects and to provide a compensation for the instrument response,
standards were prepared in the reconstituted matrix and were injected interchangeably with the extracts [12]. By this way, the bias in the quantification was minimized: 90 % of molecules showed recoveries in the 70–120 % range; only 50 % of the analytes show such acceptable recoveries if standards were injected at the beginning of sequence.
Optimization of the purification step A repeated purification and purification with double amounts of adsorbents were investigated. In both cases, samples were quantified with standards prepared in the reconstituted matrix and injected in alternation with the samples. With double cleaning, recoveries were also improved in a way that 95 % of the recoveries were in the range of tolerance against 90 % with a simple purification. Using a double amount of the adsorbents did not, however, improve the result.
Table 2 Maximum residue limit (MRLs), average recovery (%) (n=5), and precision (RSD) for 57 pesticides in rose petals Compound
MRLs (mg kg−1) [15]
Rose Petals Spiked 0.05 mg kg−1
Spiked 0.5 mg kg−1
Average recovery (%)
RSD (%)
Average recovery (%)
RSD (%) 26
2-Phenylphenol
0.1
45
22
66
Phorate
0.05
40
22
61
35
2,4-D Isopropyl ester
0.01
58
13
72
17
Propetamphos
0.01
75
8
80
6
Lindane
1
60
10
70
14
Diazinon
0.05
67
11
80
13
Phosphamidon
0.02
96
5
88
1
Acetochlor
0.01
79
6
80
4
Chlorpyrifos-methyl
0.1
72
8
76
7
Parathion-methyl
0.05
77
6
74
10
Fenitrothion
0.05
82
6
83
11
Pirimiphos-methyl
0.3
78
6
82
8
Malathion
0.02
89
5
86
4
Fenthion
0.05
80
5
82
3
Chlorpyrifos
0.5
78
5
82
5
Parathion
0.1
90
5
80
9
Dichlorobenzophenone
0.1
72
7
95
7
Chlorfenvinphos
0.05
90
5
86
8
Isofenphos
UD
83
7
87
9
Mecarbam
0.1
83
8
83
6
Quinalphos
0.1
84
6
85
9
Phenthoate
UD
83
6
81
6
Methidathion
0.1
89
5
85
7
Endosulfan I
0.1
77
6
79
5
Fenamiphos
0.05
90
4
90
9
Prothiofos
UD
82
4
81
5
Profenofos
0.1
94
3
96
11
Fludioxonil
0.05
87
5
89
5
UD undefined
Pesticide determination in rose petals
using standards that were prepared in the matrix (data not shown). For isopropyl ester and diazinon, the lowest spiked level had recoveries less than 70 %. Their limit of quantification should therefore be increased.
Validation procedure The method validation in terms of linearity, recovery, repeatability, and reproducibility was carried out for the sample matrix in five replicates at two spiking levels, namely 0.05 mg kg−1 (i.e., 0.048 μg mL−1) and 0.5 mg kg−1 (i.e., 0.48 μg mL-1).
Method application on samples of rose petals The above described newly developed method was applied in six rose samples originating from (a) organic fields (sample A) and (b) from classic crop (samples B–F). Pesticides were not detected in organic petals. In classically treated petals, a variety of pesticides was identified (Table 3). The maximum quantity was 0.05 mg kg−1 for chlorpyrifos in samples D and E. Some pesticides such as dichlorobenzene and dichlorobenzophenone were detected (signal/noise >3) in various classically treated samples but not quantified. According to our knowledge, among the detected pesticides, only chlorpyrifos was applied in the classically treated rose fields of samples D–F (Fig. 1). Other pesticides found may originate from neighboring fields (cross-contamination) or field treatments of the previous years. The amounts of identified pesticides in rose petals are in the same order of quantity as those found in food. For example, 0.01–0.07 and 0.02– 0.08 mg kg−1 of chlorpyrifos were found in blackcurrant and in grape, respectively [16, 17].
Linearity tests Five replicates of each standard concentration were GC-MS/ MS analyzed. Linear regression coefficients (R2) were higher than 0.98 for each pesticide. To investigate the linear range, the Fisher test using lack-of-fit of the sum square was employed for all pesticides as described in the literature [13]. Good linearity was found for all molecules at concentration between 0.01 μg mL−1 (i.e., 0.010 mg kg−1) and 1 μg mL−1 (i.e., 1.03 mg kg−1). Accuracy tests Accuracy and bias of the developed method were determined from the measurements of the recoveries using quality control samples [14]. The pesticides were determined with five replicates at two levels (0.05 and 0.5 mg kg−1) in the spiked samples. The results obtained are given in Table 2. Fiftythree pesticides and 55 pesticides on the 57 tested molecules had recoveries between 70 and 120 % with RSD less than 20 % for the first and second spiked level, respectively. The distribution of pesticide recoveries is shown in Table 2. 2-Phenylphenol, phorate, and lindane were not validated for each spike level, probably due to matrix effects: These compounds were well quantified when a calibration was applied
Conclusion The newly developed modified QuEChERS method allowed for the extraction, purification, and quantification of 57 pesticides in spiked rose petals. The addition of acetonitrile and the
Table 3 Pesticides detected and/or quantified in samples of roses originating from an organic field (sample A) and from classically treated crop (samples B–F). Two replicates of samples C–F were prepared Pesticides found in real rose petals (mg kg−1) Sample A
Sample B
Sample C
Replicate 1
Replicate 1
Replicate 1
Sample D Replicate 2
Replicate 1
Sample E Replicate 2
Replicate 1
Sample F Replicate 2
Replicate 1
Replicate 2 –
Acetochlor
–
–
Det
Det
–
–
–
–
–
Pirimiphos-methyl
–
–
Det
Det
–
–
–
–
Det
Det
Chlorpyriphos
–
0.012
Det
Det
0.046
0.055
0.046
0.055
0.033
0.033
Dichlorobenzophenone
–
Det
Det
Det
Det
Det
Det
Det
Det
Det
Methidathion
–
Det
Det
Det
0.012
0.014
0.012
0.014
0.013
0.016
Profenofos
–
Det
–
–
–
–
–
–
–
–
pp′-DDE
–
Det
–
–
–
–
–
–
–
–
Cypermethrin I
–
–
0.014
0.014
–
–
–
–
–
–
Cypermethrin II
–
–
0.014
0.013
–
–
–
–
–
–
Cypermethrin III
–
–
0.016
0.015
–
–
–
–
–
–
Cypermethrin IV
–
–
0.014
0.014
–
–
–
–
–
–
Det detected (S/N >3)
O. Tascone et al.
optimization of the equilibration time prior to extraction proved to provide optimal conditions for the extraction step. Toluene addition, the use of GCB, and double purification significantly improved the purification step by decreasing matrix effects. Ninety-five percent of the pesticide analytes were well quantified with an RSD of less than 20 %. The modified QuEChERS method will be employed for the routine and systematic residue analysis of pesticides in rose petals, which will allow for the perfume industry to control pesticide levels in natural raw materials and to meet criteria of green chemistry and sustainable development. Future analytical investigations will focus on the follow-up of pesticide residues in rose concrete and rose absolute used in perfume industry. Acknowledgments We thank the ‘Association Nationale de la Recherche et de la Technologie’ (ANRT) concerning the CIFRE funding for the Ph.D. thesis of O.T. We acknowledge the financial and scientific support of Waters and International Flavors & Fragrances, LMR Naturals division.
References 1. Tascone O, Roy C, Filippi J-J, Meierhenrich UJ (2014) Use, analysis, and regulation of pesticides in natural extracts, essential oils, concretes, and absolutes. Anal Bioanal Chem 406:971–980 2. Fillâtre Y, Rondeau D, Daguin A, Jadas-Hecart A, Communal P-Y (2013) Multiresidue determination of 256 pesticides in lavandin essential oil by LC/ESI/sSRM: advantages and drawbacks of a sampling method involving evaporation under nitrogen. Anal Bioanal Chem 406:1541–1550 3. Naves YR (1974) Technologie et chimie des parfums naturels: essences concrètes, résinoïdes, huiles, et pommades aux fleurs. Masson, Paris 4. Lehotay SJ, Kok A, Hiemstra M, Bodegraven P (2005) Validation of a fast and easy method for the determination of residues from 229 pesticides in fruits and vegetables using gas and liquid chromatography and mass spectrometric detection. J AOAC Int 88:595–614
5. Lehotay SJ, Mastovska K, Lightfield AR (2005) Use of buffering and other means to improve results of problematic pesticides in a fast and easy method for residue analysis of fruits and vegetables. J AOAC Int 88:615–629 6. Guidance document on analytical quality control and validation procedures for pesticides residues analysis in food and feed (2013) SANCO/12571/2013 7. Aydinli M, Tutaş M (2003) Production of rose absolute from rose concrete. Flavour Fragr J 18:26–31 8. Bayrak A, Akgül A (1994) Volatile oil composition of Turkish rose (Rosa damascena). J Sci Food Agric 64:441–448 9. Limian Zhao JS (2012) Optimizing recoveries of planar pesticides in spinach using toluene and agilent bond elute QuEChERS AOAC kits with graphitized carbon. Agilent Technologies 10. Wong JW, Hennessy MK, Hayward DG, Krynitsky AJ, Cassias I, Schenck FJ (2007) Analysis of organophosphorus pesticides in dried ground ginseng root by capillary gas chromatography-mass spectrometry and-flame photometric detection. J Agric Food Chem 55: 1117–1128 11. Wong JW, Zhang K, Tech K, Hayward DG, Makovi CM, Krynitsky AJ, Schenck FJ, Banerjee K, Dasgupta S, Brown D (2010) Multiresidue pesticide analysis in fresh produce by capillary gas chromatography-mass spectrometry/selective ion monitoring (GCMS/SIM) and-tandem mass spectrometry (GC-MS/MS). J Agric Food Chem 58:5868–5883 12. Walorczyk S (2012) Gas chromatographic–tandem mass spectrometric analysis of pesticides residues in produce using concurrent solvent recondensation-large volume injection. J Chromatogr A 1222:98– 108 13. Max F (2009) Labostat—guide de validation des méthodes d’analyse. Lavoisier, Paris 14. Feinberg M (2001) Validation interne des méthodes d’analyse. Ed. Techniques Ingénieur 15. EU Pesticides database (2014) http://ec.europa.eu/sanco_pesticides/ public/?event=homepage 16. Banerjee K, Mujawar S, Utture SC, Dasgupta S, Adsule PG (2013) Optimization of gas chromatography–single quadrupole mass spectrometry conditions for multiresidue analysis of pesticides in grapes in compliance to EU-MRLs. Food Chem 138:600–607 17. Walorczyk S (2014) Validation and use of a QuEChERS-based gas chromatographic–tandem mass spectrometric method for multiresidue pesticide analysis in blackcurrants including studies of matrix effects and estimation of measurement uncertainty. Talanta 120:106–113
NOTE
Pesticide determination in rose petals using dispersive solid-phase extraction followed by gas chromatography-tandem mass spectrometry Oriane Tascone & Marina Shirshikova & Céline Roy & Uwe J. Meierhenrich
Received: 12 September 2014 / Revised: 13 October 2014 / Accepted: 13 October 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Damascena and centifolia roses are cultivated worldwide for their petal extracts that contain key odorant ingredients of perfumes. The analytical identification and quantification of pesticides in rose petals have never been described in the literature. Here, we report on a newly developed method using dispersive solid-phase extraction (d-SPE) cleanup followed by gas chromatography-tandem mass spectrometry for the quantitative determination of multi-residue pesticides in rose petals. Analytes were extracted from the matrix using acetonitrile and a mixture of salts containing magnesium sulfate, sodium citrate, sodium chloride, and sodium sesquihydrate. Samples were cleaned up twice by d-SPE applying primary and secondary amines (PSAs), magnesium sulfate, C18, and graphitized carbon black (GCB). Two fortification levels of 0.05 and 0.5 mg kg−1 were assessed for method validation purposes. The obtained pesticide recoveries were in the range of 70–120 % with a relative standard deviation (RSD) of less than 20 %. The newly developed method was allowed for the quantification of 57 pesticides residues. It was applied to pesticide residue detection in rose petals from an organic field, without treatment, compared to those from a field with classic phytosanitary treatment using fungicide and/or insecticide. We did not detect pesticide residues in rose petals from the organic field. The classically treated samples of roses contained pesticides such as chlorpyriphos and methidathion which are in accordance with the previous application of these pesticides on the roses.
O. Tascone : M. Shirshikova : C. Roy European Research Institute on Natural Ingredients (ERINI), 06130 Grasse, France O. Tascone : U. J. Meierhenrich (*) Institut de Chimie de Nice, UMR 7272 CNRS, University Nice Sophia Antipolis, 06108 Nice, France e-mail: [email protected]
Insecticides were quantified at 0.05 mg kg−1 rose petal maximum. Keywords Dispersive solid-phase extraction . Gas chromatography . Perfume . Pesticides residue analysis . Rose petals . Tandem mass spectrometry
Introduction Extracts of natural raw materials are commonly used in perfume, aroma, and cosmetic industries. The crop production of those is habitually based on monoculture and involves the use of different chemical classes of xenobiotica, including pesticides. Legal regulations for raw materials intended for perfume, aroma, and cosmetic products have become increasingly strict in terms of the allowed residual levels of chemicals used for treatment because of their impact on public health and on the environment. A few studies have been dedicated to the analyses of pesticides in natural extracts and raw materials from which they originate [1, 2]. Extracts of roses in the form of essential oils and absolutes are widely used in perfumes. Despite the low extraction yields with approximately 0.03 and 0.3 %, for rose essential oil and rose concrete, respectively [3], more than 10 tons of concrete and 4 tons of essential oils are produced worldwide each year. Typical rose species are Rosa damascena from Turkey, Bulgaria, and Morocco; Rosa centifolia is cultivated in France only. To define and regulate the agricultural residue levels in rose extracts, it is important to develop an analytical method that is able to systematically determine pesticide contents in rose petals. In a later step, the content of individual pesticides in rose petals will be compared with the pesticide content in intermediate perfume products such as rose absolute and rose concrete.
O. Tascone et al.
The QuEChERS approach and derivatives of this method have recently been applied for the analysis of more than 200 pesticide residues in fruit and vegetable samples [4, 5]. We here describe the development and the application of a method using an extraction and d-SPE purification step to analyze a priority list of 57 multiclass pesticides in rose petals. This method allowed quantifying 57 pesticides. Fifty pesticides, out of them, were quantified in a concentration lower or equal their authorized maximum residue limits. Due to the volatility of the targeted molecules and the sensitivity of the apparatus, GC-MS/MS was employed to quantify the pesticide residues.
Standard solution preparation Individual pesticide standard stock solutions were prepared at approximately 1000 μg mL−1 in toluene and stored at −18 °C. A 100 μg mL−1 working standard mixture of these pesticides in toluene was prepared from the stock solution (mix 1). Two other mixtures of pesticides (mix 2) from CPI International were diluted in toluene at 100 μg mL−1. All these mixtures served as the spiking solution of high concentration and two low concentration spiking solutions of 10 and 1 μg mL−1 were also prepared in toluene. Sample preparation method
Materials and methods Chemicals and materials Acetonitrile (Optima LCMS grade) and acetic acid (HOAc Optima) were purchased from Fisher Scientific (Illkirch, France). Toluene (Chromasolv for HPLC 99.9 % grade) was from Sigma-Aldrich (Saint-Quentin Fallavier, France). A modified QuEChERS method for sample preparation was developed as follows: For the extraction/partitioning step, pouches (DisQuE) containing 1 g sodium citrate, 1 g sodium chloride, 4 g magnesium sulfate, and 0.5 g sodium sesquihydrate were purchased from Waters (Wexford, Ireland). For dispersive solid-phase extraction (d-SPE) cleanup, tubes containing 900 mg MgSO4, 150 mg primary and secondary amines (PSAs), and 150 mg C18 were obtained from Waters (Wexford, Ireland). One hundred fifty micrograms graphitized carbon black (GCB) sorbent purchased from Agilent Technologies (Massy, France) was added to the cleanup tubes. The reconstituted matrix contained phenethyl alcohol from Yinghai (Canghzou, China); citronellol from BASF (Ludwigshafen, Germany); linalool from DSM Nutritional (Heerlen, Netherlands); geranyl acetate, citronellyl acetate, and eugenol from internal preparation; and alkanes (C7–C40), geraniol, and fatty acid esters from Sigma-Aldrich (Saint-Quentin Fallavier, France). Pesticide reference standards (mixture and individual standard) of ≥95 % or higher purity were obtained from CPI International (Santa Rosa, USA) and Dr. Ehrenstorfer GmbH (Augsburg, Germany). Table 1 lists the pesticides investigated by this study. These pesticides are those most often found in natural extract analysis according to previous analyses (unpublished data) or known to be applied in crops. The analytical method was developed on pesticide-spiked rose petals from an organic field. The method was also applied on roses from fields with phytosanitary treatment and on organic flowers.
Rose petals were cut and directly stored in the freezer at −18 °C. The moisture of rose petals was ∼80 %. After freezing, 100 g of the rose petals was ground and homogenized. A subsample of 5.0 g of rose petals was transferred into a 50-mL centrifuge tube and 15 mL acetonitrile were added. The tube was shaken by hand for 1 min and placed in the fridge (4 °C) for 4 h. The contents of a pouch (MgSO4, sodium citrate, NaCl, and sodium sesquihydrate) were added into the tube to remove residual water and to assist the extraction of pesticides from the matrix. The tube was vigorously shaken with a vortex mixer for ∼30 s. Subsequently, the mixture was centrifuged for 10 min at 2630 rcf. Then, 8.0 mL of the supernatant was transferred into a d-SPE cleanup tube containing MgSO4 (900 mg), PSA (150 mg), C18 (150 mg), and GCB (150 mg), and 3 mL toluene was added. The tube was vigorously shaken with a vortex mixer for 1 min. Subsequently, the mixture was centrifuged for 10 min at 2630 rcf. The extract was transferred in a second purification tube which also contained MgSO4, PSA, C18, and GCB and shaken with a vortex mixer. After centrifugation, 4 mL of the resulting solution was evaporated under nitrogen flow at 35 °C. Then, the residue was transferred in a GC vial. The tube was washed with a small amount of toluene. The final volume was adjusted to 1 mL. For the development of the analytical method, samples were spiked before the extraction step at 0.5 mg kg−1. For each trial, a non-spiked sample was prepared to check the pesticide concentration in the blank matrix. To evaluate sample preparation and to validate the quantification method, quality control samples were prepared: Rose petals were spiked at 0.05 and 0.5 mg kg−1 before the extraction step with the mixture of the pesticides under investigation. GC-MS/MS analysis GC-MS/MS analyses were performed on an Agilent 7000 triple-quadrupole mass spectrometer interfaced to an Agilent 7890A gas chromatograph (Massy, France). The GC was equipped with a capillary column HP5-MS (30 m×0.25 mm
Pesticide determination in rose petals Table 1 GC-MS/MS parameters for the determination of 57 pesticide residues in rose petals Time segment
1 2 3 4 5
6 7 8
9
10 11
12 13
14 15
16
17
18
Compound
tR (min)
MRM transition Quantifier
CE (V)
Qualifier 1
CE (V)
Qualifier 2
CE (V)
2-Phenylphenol Phorate 2,4-D Isopropyl ester Lindane Propetamphos Diazinon Phosphamidon Acetochlor Parathion-methyl Chlorpyrifos-methyl Fenitrothion Pirimiphos-methyl Malathion Fenthion
7.78 9.92 10.28 11.11 11.13 11.51 12.87 13.16 13.25 13.28 14.32 14.38 14.73 15.11
170→169 260→75 175→111 181→145 138→110 137→84 127→109 223→132 125→79 286→93 125→79 290→125 127→99 278→109
12 5 12 20 5 10 15 20 5 30 10 25 5 20
170→141 231→175 175→145 219→183 138→64 152→137 127→95 147→132 263→109 286→271 277→260 290→151 173→99 278→169
25 15 17 7 15 5 15 10 15 15 5 25 12 15
170→115 231→129 175→109 181→109 236→166 152→84 264→127 223→147 263→79 286→208 277→109 305→290 173→127 278→125
30 30 25 25 15 20 5 10 30 15 20 10 5 25
Chlorpyrifos Parathion Dichlorobenzophenone
15.21 15.24 15.37
197→169 291→109 139→111
15 15 15
314→258 291→81 139→75
15 25
258→166 291→91
22 25
Chlorfenvinphos Isofenphos Quinalphos Phenthoate Mecarbam Methidathion Endosulfan I Fenamiphos Prothiofos Profenofos p,p′-DDE Fludioxonil Buprofezin Chlorfenapyr
17.00 17.04 17.09 17.16 17.16 17.78 18.28 18.85 19.17 19.30 19.49 19.54 19.99 20.84
267→159 213→121 156→129 274→121 329→159 145→85 241→206 303→154 267→239 337→267 246→176 248→182 190→175 328→247
17 15 15 10 5 5 17 15 10 15 25 15 5 5
323→267 213→185 156→102 274→125 131→86 145→58 195→159 303→288 309→239 337→309 318→248 248→154 190→117 247→200
30 10 5 15 20 10 17 5 10 15 5 30 20 30 30
111→75 267→81 185→121 270→156 273→93
10 30 15 15 10
195→125 303→195 309→281 337→188 318→246 248→127 190→132 247→227
25 7 7 30 30 30 25
Endosulfan II
21.05
195→159
10
195→125
25
241→206
30 10
Chlorobenzilate o,p′-DDT Ethion Triazophos Endosulfan sulfate p,p′-DDT Propargite Iprodione Pyridafenthion Phosmet Bromopropylate Bifenthrin
21.14 21.71 21.86 22.54 23.21 23.49 24.56 25.83 25.94 26.00 26.21 26.59
139→111 235→165 153→97 161→134 387→253 235→165 135→107 314→245 188→82 160→77 183→155 181→165
15 30 15 5 5 30 15 10 10 25 15 30
251→139 237→165 231→175 161→91 387→289 235→199 173→91 187→124 340→199 160→133 183→76 181→153
15 30 15 15 5 17 30 30 10 15 30 15
251→111 235→199 231→129 161→106 387→219 165→164 173→107 314→271 188→91 160→105 340→183 181→141
30 15 30 15 30 20 30 6 20 20 15 30
Fenpropathrin Tetradifon Azinphos-methyl
26.82 27.61 28.14
208→181 159→131 160→77
5 5 17
181→152 354→159 160→132
30 10 5
265→210 227→199 160→104
10 14 7
O. Tascone et al. Table 1 (continued) Time segment
19
20
Compound
Phosalone Cyfluthrin I Cyfluthrin II Cyfluthrin III Cyfluthrin IV Cypermethrin I Cypermethrin II Cypermethrin III Cypermethrin IV Deltamethrin
tR (min)
28.16 33.58 33.89 34.10 34.26 34.48 34.81 35.02 35.15 39.60
MRM transition Quantifier
CE (V)
Qualifier 1
CE (V)
Qualifier 2
CE (V)
182→111 163→91 163→91 163→91 163→91 163→91 163→91 163→91 163→91 253→93
20 15 15 15 15 15 15 15 15 15
182→138 163→127 163→127 163→127 163→127 163→127 163→127 163→127 163→127 181→152
5 5 5 5 5 5 5 5 5 15
182→102 226→206 226→206 226→206 226→206 181→152 181→152 181→152 181→152 253→174
20 15 15 15 15 30 30 30 30 5
i.d.×0.25 μm film thickness) from Agilent Technologies. The carrier gas was helium at a constant flow of 1 mL min−1. The gas chromatograph was equipped with an Agilent 7683 autosampler and a split/splitless injector. The temperature program was the following: initial temperature of 90 °C held for 1 min, 30 °C min−1 ramp to 180 °C, then 3 °C min−1 ramp to 280 °C and held for 5 min. The temperature of the injection port was 280 °C, and a 1-μL volume was injected in pulsed splitless mode. The MS transfer line and ion source temperatures were both set at 280 °C. An electron energy of 70 eV was used for ionization of the analytes. Analyses were performed in multiple reaction monitoring (MRM) mode based on the use of one transition for quantification (quantifier) and two transitions to confirm the compound identity (qualifier). For each analyte, we optimized the transitions and the collision energy (CE). To detect all 57 pesticides, the MRM method was divided into 20 time segments (Fig. 1). Acquisitions and data processing were performed with Mass Hunter software. Table 1 summarizes the optimized MS/MS conditions for the individual analytes and their retention times (tR). Method validation The analytical method was validated according to the singlelaboratory validation approach. The performance of the method was evaluated considering different validation parameters that include linearity, recovery, repeatability, and reproducibility. Five replicates of samples at two spiking levels (0.05 and 0.5 mg kg−1) were extracted and injected. Samples were quantified with external calibration curves. Five calibration levels ranging from 0.01 to 1 μg mL−1 were prepared in the reconstituted matrix containing phenethyl alcohol (0.1 %), geranyl acetate (0.01 %), citronellyl acetate (0.001 %), eugenol (0.001 %), geraniol (0.001 %), citronellol (0.001 %), linalool (0.01 %), alkanes (C7–C40) (10 %), and fatty acid
esters (1 %) diluted in toluene. The calibration standards were distributed among the sample extracts. Five replicates of standards were injected. The precision of the method which was represented by estimation of the variability of measurements was described as the value of relative standard deviation (RSD). Recoveries included in the range 70–120 % with a repeatability RSD ≤20 % allowed to validate accuracy of the method [6].
Results and discussion Development of the reconstituted matrix First, the QuEChERS method was tested as it was described in NF EN 15662. The calibration curves of standards prepared in toluene and the calibration curves of standards prepared in the pesticide-free matrix were used to quantify the pesticide residues. Strong positive matrix effects were observed with the calibration curve prepared in solvent. With matrix calibration, 90 % of the recoveries were within the 70–120 % range. However, the use of matrix extracts to prepare the standard cannot be chosen routinely because rose crop begins in May and finishes in June, so rose petals are not available all year long, especially organic flowers from which the pesticide-free calibration curve is built. An alternative solution was to use the reconstituted matrix for calibration purposes. The components for this mixture were chosen after their identification in blank-extracted petals. Some of these compounds were conventionally found in rose extracts such as absolute or essential oils [7, 8]. Matrix effects were still present but induced less bias as compared to a standard prepared in pure solvent. A standard prepared in the reconstituted matrix was adopted for quantification purpose.
1 7
2
3 10
4
5
6
7 8
9
10
11
15
12
Sample D Standard 0.05 µg.mL -1
13
14
15
16
Phosalone + Azinphos methyl
Sample B Standard 0.01 µg.mL -1 Sample A
18
19 30
Deltamethrin
CypermethrinI, II, III, IV
Cyfluthrin I, II, III, IV
Chlorpyrifos Ethyl, tR : 15.21 min
Tetradifon
Fenpropathrin
Bromopropylate
17 25
20
Pyridaphenthion + Iprodione
Propargite
Triazophos
Phosmet Bifentrhin
Sample F
Endosulfan sulfate p,p’-DDT
Chlorfenapyr
Endosulfan II + Chlorobenzilate + o,p’DDT + Ethion
Buprofezin
Methidathion
Prothiofos + Profenofos +p,p’-DDE + Fludioxonil
Chlorfenvinphos + Isofenphos + Mecarbam + Phenthoate + Quinalphos
Standard 0.1 µg.mL -1
Endosulfan I Fenamiphos
Malathion
Fenthion + Chlropyrifos Ethyl + Parathion + Dichlorobenzophenone
Phosphamidon Acetochlor + Methyl Parathion + Chlorpyifos Methyl
Lindane + Propetamphos Diazinon
Phorate 2,4-D Isopropyl Ester
2-phenylphenol
Fenitrothion + Pirimiphos Methyl
Pesticide determination in rose petals
20 35
40
t (min)
Fig. 1 MRM chromatogram of the 1 μg mL−1 standard as prepared in the reconstituted matrix including the repartition of time segments 1–20. The inset represents the extracted chlorpyrifos signals at three calibration
levels along with samples A, B, D, and F. In samples B, F, and D, chlorpyrifos was quantified at 0.012, 0.033, and 0.055 mg kg−1, respectively
Impact of equilibration time before extraction
sample prepared with the complete QuEChERS method with a sample that was not QuEChERS-purified. The pesticide recoveries were impacted. A positive matrix effect in the non-QuEChERS-purified sample caused an increase of recovery rates above 100 % that overestimated extraction yields. The purification step was thus found to be essential for sample preparation; its improvement, however, was required.
The influence of the equilibration time te before salt addition for extraction was tested. Mixtures of sample and acetonitrile were stored in fridge at 4 °C for te =4 h and 2, 3, and 4 days before the extraction. At te =4 h, the pesticide recovery was improved: about 10 % more analytes were in the 70–120 % tolerance range at te =4 h as compared to te =0 h. Increasing te to 48 h allowed to slightly increase the recoveries for several pesticides, but because of the high increase of the analysis time, these conditions were not retained for routine purposes. Samples at room temperature and samples stored in the fridge at 4 °C were subjected to te =4 h to test the influence of the equilibration temperature Te. The number of analytes with recoveries within 70–120 % was similar between both trials, but when the sample was stored in the fridge, recoveries were closer to 100 %. This is probably due to cooling of the sample before extraction which allowed extracting less matrix. Moreover, the extraction step produced exothermic reactions, so pesticides were potentially degraded by temperature increase.
The influence of GCB on the purification step GCB is known to irreversibly retain planar pesticides [5] and therefore to potentially induce a bias on the pesticide recoveries. To test the GCB impact, one sample was purified without using GCB. The results were compared with those obtained for purification with GCB. Pigments present in the extract were not removed by non-GCB purification. Consequently, recoveries were impacted by this more complex matrix. With GCB, 15 % more analytes possessed recoveries within the 70–120 % range. Addition of toluene for the purification step
Selection of cleanup conditions Influence of the purification step The impact of the purification step was investigated by comparing the pesticide extraction recoveries obtained for a
As mentioned above, GCB adsorbent removes pigment and sterols from the extracts, but it is also known to irreversibly retain pesticides of planar-aromatic structure [5], such as o-phenylphenol, dichlorobenzophenone, and fenamiphos. The addition of a solvent as toluene was tested to desorb planar-
O. Tascone et al.
aromatic pesticides [9, 10]. Toluene was chosen because of its insolubility in water, limiting polar coextractives, its lower volume expansion compared to acetonitrile, and its compatibility with splitless injection [11]. Moreover, toluene provides π-π interaction with planar aromatic pesticides and limits their adsorption by GCB. After transfer of 8 mL of supernatant in the purification tube, 3 mL toluene was added. Recoveries were found to be improved using toluene. To give an example, the fenamiphos recovery increased from 49 % without toluene to 81 % with toluene addition. Influence of the injection order Despite the QuEChERS-type sample preparation, specific molecules that possessed similar properties as compared to the analytes stayed in the extract. To decrease such effects and to provide a compensation for the instrument response,
standards were prepared in the reconstituted matrix and were injected interchangeably with the extracts [12]. By this way, the bias in the quantification was minimized: 90 % of molecules showed recoveries in the 70–120 % range; only 50 % of the analytes show such acceptable recoveries if standards were injected at the beginning of sequence.
Optimization of the purification step A repeated purification and purification with double amounts of adsorbents were investigated. In both cases, samples were quantified with standards prepared in the reconstituted matrix and injected in alternation with the samples. With double cleaning, recoveries were also improved in a way that 95 % of the recoveries were in the range of tolerance against 90 % with a simple purification. Using a double amount of the adsorbents did not, however, improve the result.
Table 2 Maximum residue limit (MRLs), average recovery (%) (n=5), and precision (RSD) for 57 pesticides in rose petals Compound
MRLs (mg kg−1) [15]
Rose Petals Spiked 0.05 mg kg−1
Spiked 0.5 mg kg−1
Average recovery (%)
RSD (%)
Average recovery (%)
RSD (%) 26
2-Phenylphenol
0.1
45
22
66
Phorate
0.05
40
22
61
35
2,4-D Isopropyl ester
0.01
58
13
72
17
Propetamphos
0.01
75
8
80
6
Lindane
1
60
10
70
14
Diazinon
0.05
67
11
80
13
Phosphamidon
0.02
96
5
88
1
Acetochlor
0.01
79
6
80
4
Chlorpyrifos-methyl
0.1
72
8
76
7
Parathion-methyl
0.05
77
6
74
10
Fenitrothion
0.05
82
6
83
11
Pirimiphos-methyl
0.3
78
6
82
8
Malathion
0.02
89
5
86
4
Fenthion
0.05
80
5
82
3
Chlorpyrifos
0.5
78
5
82
5
Parathion
0.1
90
5
80
9
Dichlorobenzophenone
0.1
72
7
95
7
Chlorfenvinphos
0.05
90
5
86
8
Isofenphos
UD
83
7
87
9
Mecarbam
0.1
83
8
83
6
Quinalphos
0.1
84
6
85
9
Phenthoate
UD
83
6
81
6
Methidathion
0.1
89
5
85
7
Endosulfan I
0.1
77
6
79
5
Fenamiphos
0.05
90
4
90
9
Prothiofos
UD
82
4
81
5
Profenofos
0.1
94
3
96
11
Fludioxonil
0.05
87
5
89
5
UD undefined
Pesticide determination in rose petals
using standards that were prepared in the matrix (data not shown). For isopropyl ester and diazinon, the lowest spiked level had recoveries less than 70 %. Their limit of quantification should therefore be increased.
Validation procedure The method validation in terms of linearity, recovery, repeatability, and reproducibility was carried out for the sample matrix in five replicates at two spiking levels, namely 0.05 mg kg−1 (i.e., 0.048 μg mL−1) and 0.5 mg kg−1 (i.e., 0.48 μg mL-1).
Method application on samples of rose petals The above described newly developed method was applied in six rose samples originating from (a) organic fields (sample A) and (b) from classic crop (samples B–F). Pesticides were not detected in organic petals. In classically treated petals, a variety of pesticides was identified (Table 3). The maximum quantity was 0.05 mg kg−1 for chlorpyrifos in samples D and E. Some pesticides such as dichlorobenzene and dichlorobenzophenone were detected (signal/noise >3) in various classically treated samples but not quantified. According to our knowledge, among the detected pesticides, only chlorpyrifos was applied in the classically treated rose fields of samples D–F (Fig. 1). Other pesticides found may originate from neighboring fields (cross-contamination) or field treatments of the previous years. The amounts of identified pesticides in rose petals are in the same order of quantity as those found in food. For example, 0.01–0.07 and 0.02– 0.08 mg kg−1 of chlorpyrifos were found in blackcurrant and in grape, respectively [16, 17].
Linearity tests Five replicates of each standard concentration were GC-MS/ MS analyzed. Linear regression coefficients (R2) were higher than 0.98 for each pesticide. To investigate the linear range, the Fisher test using lack-of-fit of the sum square was employed for all pesticides as described in the literature [13]. Good linearity was found for all molecules at concentration between 0.01 μg mL−1 (i.e., 0.010 mg kg−1) and 1 μg mL−1 (i.e., 1.03 mg kg−1). Accuracy tests Accuracy and bias of the developed method were determined from the measurements of the recoveries using quality control samples [14]. The pesticides were determined with five replicates at two levels (0.05 and 0.5 mg kg−1) in the spiked samples. The results obtained are given in Table 2. Fiftythree pesticides and 55 pesticides on the 57 tested molecules had recoveries between 70 and 120 % with RSD less than 20 % for the first and second spiked level, respectively. The distribution of pesticide recoveries is shown in Table 2. 2-Phenylphenol, phorate, and lindane were not validated for each spike level, probably due to matrix effects: These compounds were well quantified when a calibration was applied
Conclusion The newly developed modified QuEChERS method allowed for the extraction, purification, and quantification of 57 pesticides in spiked rose petals. The addition of acetonitrile and the
Table 3 Pesticides detected and/or quantified in samples of roses originating from an organic field (sample A) and from classically treated crop (samples B–F). Two replicates of samples C–F were prepared Pesticides found in real rose petals (mg kg−1) Sample A
Sample B
Sample C
Replicate 1
Replicate 1
Replicate 1
Sample D Replicate 2
Replicate 1
Sample E Replicate 2
Replicate 1
Sample F Replicate 2
Replicate 1
Replicate 2 –
Acetochlor
–
–
Det
Det
–
–
–
–
–
Pirimiphos-methyl
–
–
Det
Det
–
–
–
–
Det
Det
Chlorpyriphos
–
0.012
Det
Det
0.046
0.055
0.046
0.055
0.033
0.033
Dichlorobenzophenone
–
Det
Det
Det
Det
Det
Det
Det
Det
Det
Methidathion
–
Det
Det
Det
0.012
0.014
0.012
0.014
0.013
0.016
Profenofos
–
Det
–
–
–
–
–
–
–
–
pp′-DDE
–
Det
–
–
–
–
–
–
–
–
Cypermethrin I
–
–
0.014
0.014
–
–
–
–
–
–
Cypermethrin II
–
–
0.014
0.013
–
–
–
–
–
–
Cypermethrin III
–
–
0.016
0.015
–
–
–
–
–
–
Cypermethrin IV
–
–
0.014
0.014
–
–
–
–
–
–
Det detected (S/N >3)
O. Tascone et al.
optimization of the equilibration time prior to extraction proved to provide optimal conditions for the extraction step. Toluene addition, the use of GCB, and double purification significantly improved the purification step by decreasing matrix effects. Ninety-five percent of the pesticide analytes were well quantified with an RSD of less than 20 %. The modified QuEChERS method will be employed for the routine and systematic residue analysis of pesticides in rose petals, which will allow for the perfume industry to control pesticide levels in natural raw materials and to meet criteria of green chemistry and sustainable development. Future analytical investigations will focus on the follow-up of pesticide residues in rose concrete and rose absolute used in perfume industry. Acknowledgments We thank the ‘Association Nationale de la Recherche et de la Technologie’ (ANRT) concerning the CIFRE funding for the Ph.D. thesis of O.T. We acknowledge the financial and scientific support of Waters and International Flavors & Fragrances, LMR Naturals division.
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