Supplementary Data
Polyol enhanced dispersive liquid–liquid microextraction coupled by gas chromatography–nitrogen
phosphorous detection for determination of organophosphorous pesticides from aqueous samples,
fruit juices and vegetables
Mir Ali Farajzadeh*a, Mohammad Reza Afshar Mogaddama, Ali Akbar Alizadeh Nabilb
a
Department of Analytical Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran
b
Food and Drug Laboratories, Tabriz University of Medical Sciences, Tabriz, Iran
*Corresponding author: M. A. Farajzadeh
Tel.: +98 411 3393084
Fax: +98 411 3340191
E–mail address: mafarajzadeh@yahoo.com; mafarajzadeh@tabrizu.ac.ir
1
In Fig S1 effect of extraction solvent kind on performance of the presented procedure was evaluated. For
this purpose five different solvents including chloroform, carbon tetrachloride, 1,2–DBE, 1,1,1–TCE and
1,1,2,2–TCE were selected and examined. The results show that 1,1,1–TCE is the suitable extraction
solvent in this study.
16
Dichlorvos
Metrifonate
Dimethoate
Diazinon
Chlorpyrifos methyl
Fenitrothion
Chlorpyrifos
Methidathion
Profenofos
Phosalone
14
ER (%)
12
10
8
6
4
2
0
Chloroform
Carbon
tetrachloride
1,1,1-TCE
1,2-DBE
1,1,2,2-TCE
Fig. S1. Selection of extraction solvent used in the developed method.
Extraction conditions: sample, 50 mL de–ionized water spiked with analytes (25 ng mL–1, each pesticide);
extraction solvent, 1,1,2,2-TCE (132 µL), 1,1,1-TCE (130 µL), chloroform (310 µL), carbon tetrachloride
(270) and 1,2-DBE (120 µL); disperser solvent, DMSO (1.5 mL); centrifuge rate, 4000 rpm; and
centrifuge time, 7 min. The error bars indicate the minimum and maximum of three independent
determinations.
2
In Fig. S2 chemical identity of disperser solvent has been evaluted. The experiments were performed
using different dispersers including methanol, DMSO, DMF, n–propanol, and acetonitrile. To study the
effect of disperser kind, extraction of the analytes was carried out using 1.5 mL of each disperser and 130
µL 1,1,1–TCE (extraction solvent). According to the obtained results, DMF was selected as the most
suitable disperser because of formation of a cloudy state with very fine droplets and having high ERs of
the analytes.
Fig. S2. Effect of the chemical identity of disperser solvent on the efficiency of the method.
Extraction conditions: extraction solvent, 1,1,1-TCE (130 µL). Other conditions are the same as in
Fig. S1.
3
Fig. S3 shows effect the volume of disperser solvent on the extraction efficiency. For this purpose,
different volumes of DMF (0.50, 1.00, 1.50, 1.75, 2.00, and 2.25 mL containing 110, 122, 130, 138, 142,
and 148 µL of 1,1,1–TCE, respectively) were tested. According to the obtained results, ERs initially
increase and then decrease by increasing the volume of DMF. Thus 1.75 mL of DMF was selected as the
optimum volume for the disperser.
Fig. S3. Study of DMF volume.
Extraction conditions: disperser (extraction) solvents volumes, 0.50 (110), 1.00 (122), 1.50 (130), 1.75
(138), 2.0 (142), and 2.25 (148) mL (µL). Other conditions are the same as in Fig. S2.
4
Fig. S4 Shows typical GC-MS chromatogram of tomato sample and presence of phosalone was verified in
it.
Fig. S4 Typical GC–TIC–MS chromatogram of (A) tomato, (B) scan 2794, retention time 27.54 min, (C)
mass spectra of phosalone.
5
Table 1S. Results of assays to check the samples matrices effect for the selected pesticides and concentrations of the detected analytes. Mango, tomato, and onion
juices were diluted with de–ionized water at a ratio of 1:3 before analysis. Analytes’ content of the samples was subtracted.
Mean relative recovery (%) ± standard deviation (n=3)
Analyte
Surface water 1
Surface water 2
Sour cherry
Apple
Peach
Apricot
Mango
Orange
Grape
Tomato
Cucumber
Onion
-1
All samples were spiked with each analyte at a concentration of 0.2 ng mL
Dichlorvos
87 ± 3
91 ± 3
95 ± 4
97 ± 3
96 ± 3
96 ± 3
95 ± 3
92 ± 2
96 ± 4
88 ±3
87 ± 3
92 ± 2
Metrifonate
86 ± 3
90 ± 4
81 ± 1
86± 3
86 ± 3
89 ± 3
88 ± 4
87 ± 4
97 ± 2
89 ± 2
88 ± 4
98 ± 4
Dimethoate
90 ± 2
92 ± 2
78 ± 3
82 ± 2
86 ± 2
80 ± 3
90 ± 3
85 ± 3
82 ± 1
87± 3
88 ± 3
87 ± 4
Diazinon
92 ± 2
93 ± 3
77 ± 1
95 ± 4
89 ± 4
89 ± 3
83 ± 2
87 ± 4
84 ± 5
91 ± 4
89 ± 4
96 ± 3
90 ± 4
89 ± 3
87 ± 3
91 ± 4
79 ± 2
Chlorpyrifos methyl
90 ± 3
92 ± 2
97 ± 3
86 ± 2
84 ± 2
89 ± 3
90 ± 3
97 ± 4
96 ± 2
91 ± 3
98 ± 4
98 ± 3
89 ± 4
87 ± 3
88 ± 3
Fenitrothion
88 ± 3
92 ± 4
86 ± 3
98 ± 4
Chlorpyrifos
93 ± 4
90 ± 2
92 ± 2
92 ± 3
91 ± 3
97 ± 3
88 ± 4
85 ± 4
98 ± 3
92 ± 3
91 ± 4
98 ± 3
86 ± 4
88 ± 3
97 ± 3
98 ± 4
87 ± 3
91 ± 3
Methidathion
97 ± 3
96 ± 2
86 ± 4
87 ± 4
88 ± 4
88 ± 3
Profenofos
90 ± 4
90± 2
88 ± 4
96 ± 3
96 ± 3
88 ± 3
90 ± 2
98 ± 2
87 ± 5
89 ± 2
88 ± 3
96 ± 3
Phosalone
94 ± 2
92 ± 3
88 ± 2
97 ± 3
95 ± 4
87 ± 4
95 ± 3
All samples were spiked with each analyte at a concentration of 10 ng mL-1
88 ± 3
84 ± 4
87 ± 4
95 ± 4
Dichlorvos
91± 2
99 ±2
92 ± 4
96 ± 3
94 ± 5
94 ± 4
98 ± 4
98 ± 1
93 ± 4
87 ± 1
86 ± 2
86 ± 4
Metrifonate
92 ± 3
94 ±6
94 ± 6
97 ± 2
92 ± 3
94 ± 3
95 ± 4
97 ± 5
96 ± 2
89 ± 1
80 ± 3
89 ± 3
Dimethoate
89 ± 4
95 ± 4
95± 3
98 ± 1
94 ± 3
95 ± 4
96 ± 3
95 ± 3
94 ± 1
89 ± 3
79 ± 3
84 ± 2
Diazinon
94 ± 5
94 ± 5
99 ± 5
99 ± 3
95 ± 4
95 ± 3
95 ± 1
98 ± 4
99 ± 2
98 ± 2
78 ± 4
85 ± 4
Chlorpyrifos methyl
93 ± 4
92 ± 3
97 ± 4
98 ± 3
94 ± 5
97 ± 3
94 ± 2
90 ± 2
95 ± 4
89 ± 1
79 ± 1
90 ± 4
Fenitrothion
94 ± 5
94 ± 3
96 ± 5
96 ± 3
99± 1
94 ± 4
95 ± 4
98 ± 4
93 ± 4
88 ± 1
84 ± 2
91 ± 5
Chlorpyrifos
95 ± 4
95 ± 4
95 ± 4
97 ± 2
96 ± 3
95 ± 2
96 ± 2
96 ± 4
98 ± 4
83 ± 4
87 ± 3
89 ± 2
Methidathion
96 ± 5
94 ± 5
99 ± 4
101 ± 3
96 ± 3
96 ± 2
98 ± 4
96 ± 5
96 ± 2
86 ± 2
88 ± 2
91 ± 1
Profenofos
96 ± 4
99± 1
98 ± 3
99 ± 3
98 ± 4
97 ± 2
97± 2
98 ± 5
95 ± 4
84 ± 2
90 ± 2
88 ± 3
Phosalone
97 ± 3
98 ± 4
97 ± 4
98 ± 1
97 ± 3
97 ± 1
96 ± 3
98 ± 3
98 ± 2
79 ± 3
92 ± 4
85 ± 4
88 ± 2
6
Comparison of the developed method with other analytical methodologies
Analytical performance of the developed method for OPPs determination in different samples was
compared with other previously reported analytical methodologies in Table 2S. It is observed that LODs
of the developed method are lower than or comparable with LODs of the other methods. Very high EFs
are achievable by the present method as compared with the others. Also, the proposed method requires an
extraction time shorter than other mentioned methods. By considering these results, the developed method
can be considered as a rapid, sensitive, efficient, reliable, and easy to use technique for the extraction and
highly efficient preconcentration of the selected OPPs from the used samples.
7
Table 2S. Comparison of the presented method with the other approaches used in preconcentration and determination of the target analytes.
LR a)
LOD b)
Extraction time
RSD c)
EF d)
Ref.
Method
Sample
(min)
CME–UABE–GC–MS e)
Honey
300–107
30–470
> 17
2.9–9.5
167
[S1]
USE–HFLPME–GC–NPD f)
Cereal–based baby foods
500–105
10–30
> 240
2.1
56-94
[S2]
LPME–HPLC–DAD g)
Lake and tap water
104–5×106
10000
20
8.4
–
[S3]
SPME–GC–NPD h)
Water sample
100–104
10–200
60
<15
–
[S4]
POE–DLLME–GC–NPD i)
Surface water,
fruit juices and
vegetables
200–105
12–56
<10
3.7–5.9
2799–3066
This method
range (pg mL–1).
Limit of detection (pg mL–1).
c Relative standard deviation.
d Enrichment factor
e
Coacervative microextraction– ultrasound assisted back extraction–gas chromatography–mass spectrometry.
f Ultrasound assisted extraction–hollow fiber liquid phase microextraction–gas chromatography–nitrogen phosphorus detection.
g Liquid–phase microextraction–high performance liquid chromatography–diode array detector.
h Solid phase microextraction–gas chromatography–nitrogen phosphorus detection.
i Polyol enhanced–dispersive liquid–liquid microextraction–gas chromatography–nitrogen phosphorus detection.
a Linear
b
8
Table 3S. Maximum residue limits (MRLs) of OPPs in different matrices (mg kg-1) established by
European Union regulation [5S]. LOQs (µg L-1) obtained by the proposed method are added into
parenthesis.
MRLs
Sour
Analyte
Dichlorvos
Metrifonate
Dimethoate
Diazinon
Chlorpyrifos
methyl
Fenitrothion
Chlorpyrifos
Methidathion
Profenofos
Phosalone
Apple
Peach
Apricot
Mango
Orange
Grape
Tomato
Cucumber
Onion
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
(0.162)
(0.162)
(0.162)
(0.162)
(0.486)
(0.162)
(0.162)
(0.486)
(0.162)
(0.486)
0.05
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
(0.092)
(0.092)
(0.092)
(0.092)
(0.276)
(0.092)
(0.092)
(0.276)
(0.092)
(0.276)
0.05
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
(0.091)
(0.091)
(0.091)
(0.091)
(0.273)
(0.091)
(0.091)
(0.273)
(0.091)
(0.273)
0.05
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.05
(0.044)
(0.044)
(0.044)
(0.044)
(0.132)
(0.044)
(0.044)
(0.132)
(0.044)
(0.132)
0.1
0.5
0.5
0.05
0.05
0.5
0.2
0.5
0.05
0.05
(0.062)
(0.062)
(0.062)
(0.062)
(0.186)
(0.062)
(0.062)
(0.186)
(0.062)
(0.186)
0.05
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.02
(0.063)
(0.063)
(0.063)
(0.063)
(0.189)
(0.063)
(0.063)
(0.189)
(0.063)
(0.189)
0.1
0.5
0.20
0.05
0.05
0.3
0.5
0.5
0.05
0.2
(0.043)
(0.043)
(0.043)
(0.043)
(0.129)
(0.043)
(0.043)
(0.129)
(0.043)
(0.129)
0.1
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.05
(0.131)
(0.131)
(0.131)
(0.131)
(0.393)
(0.131)
(0.131)
(0.393)
(0.131)
(0.393)
0.05
0.01
0.01
0.01
0.2
0.01
0.01
10
0.01
0.01
(0.082)
(0.082)
(0.082)
(0.082)
(0.246)
(0.082)
(0.082)
(0.246)
(0.082)
(0.246)
0.05
0.01
2
2
0.01
0.01
0.01
0.01
0.01
0.02
(0.114)
(0.114)
(0.114)
(0.114)
(0.342)
(0.114)
(0.114)
(0.342)
(0.114)
(0.342)
cherry
9
[1S] Fontana, A.R., Camargob, A.B., Altamirano, J.C., J. Chromatogr. A, 2010, 1217, 6334–6341.
[2S] Gonzalez–Curbelo, M.A., Borges, J.H., Borges–Miquel, T.M., Rodriguez–Delgado, M.A., J.
Chromatogr. A, 2013, 1313, 166–174.
[3S] Liang, P., Guo, L., Liu, Y., Liu, S., Zhang, T., Microchem. J., 2005, 80, 19–23.
[4S] Beltran, J., Lopez, F.J., Cepria, O., Hernandez, F., J. Chromatogr. A, 1998, 808, 257–263.
[5S] http://ec.europa.eu/food/plant/pesticides/eu-pesticides-database (Access date: August/ 4/ 2015)
10