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Analytical and Bioanalytical Chemistry

, Volume 411, Issue 20, pp 5099–5113 | Cite as

Comparison of electrospray and UniSpray, a novel atmospheric pressure ionization interface, for LC-MS/MS analysis of 81 pesticide residues in food and water matrices

  • Joseph Hubert Yamdeu GalaniEmail author
  • Michael Houbraken
  • Marijn Van Hulle
  • Pieter Spanoghe
Open Access
Research Paper

Abstract

In mass spectrometry, the type and design of ionization source play a key role on the performance of a given instrument. Therefore, it is of paramount importance to evaluate newly developed sources for their suitability to analyze food contaminants like pesticide residues. Here, we carried out a head-to-head comparison of key extraction and analytical performance parameters of an electrospray ionization (ESI) source with a new atmospheric pressure ionization source, UniSpray (US). The two interfaces were evaluated in three matrices of different properties (coffee, apple, and water) to determine if multiresidue analysis of 81 pesticides by QuEChERS extraction and LC-MS/MS analysis could be improved. Depending on the matrix and irrespective of the chemical class, US provided a tremendous gain in signal intensity (22- to 32-fold in peak area, 6- to 7-fold in peak height), a threefold to fourfold increase in signal-to-noise ratio, a mild gain in the range of compounds that can be quantified, and up to twofold improvement of recovery. UniSpray offered comparable linearity and precision of the analyses with ESI, and did not affect the ion ratio. A gain in sensitivity of many compounds was observed with US, but in general, the two ionization interfaces did not show significant difference in LOD and LOQ. UniSpray suffered less signal suppression; the matrix effect was in average 3 to 4 times more pronounced, but showed better values than ESI. With no effect on recovery efficiency, US improved the overall process efficiency 3 to 4 times more than ESI.

Graphical abstract

Keywords

Pesticide residues Electrospray UniSpray Mass spectrometry Matrix effects Process efficiency 

Introduction

To gather surveillance data from the occurrence and background levels of both recognized and newly identified contaminants in foods, low limits of quantification (LOQs) are required, in order to estimate human daily intake for risk assessment [1]. Therefore, to analyze compounds like pesticide residues in foods and beverages, there is a constant need for more precise and accurate methods and instruments. The ability to quantitatively determine trace levels of residues in samples is essential to monitor and preserve consumer’s health in a precise and more effective way. Among the various techniques of analysis of pesticide residues in water and food items, liquid chromatography (LC) coupled by an atmospheric pressure ionization (API) source to tandem mass spectrometric (MS/MS) detection is the technique of choice, because it offers high throughput, selectivity, and sensitivity as well as its suitability for a wide range of compounds in various sample matrices [2, 3, 4]. It has been observed that the type and the design of an ionization source can have a significant influence on the performances of a bioanalytical method like LC-MS/MS [5]. Furthermore, several studies have demonstrated the differences on the ionization of specific classes of compounds and differences effects of the matrix, observed between different sources [6, 7, 8, 9, 10, 11]. It is therefore of high interest for LC-MS/MS pesticide residue analysis, to evaluate the performances of newly introduced ionization sources in order to highlight their benefits and limitations in comparison with the source that is most commonly applied, i.e., electrospray ionization (ESI) [12].

UniSpray (US) ionization or impactor ionization is a novel atmospheric ionization technique developed by Waters Corporation that makes use of a high-velocity spray, created from a grounded nebulizer impacting on a high-voltage target (stainless steel rod), to ionize analytes in a similar fashion to ESI but promotes extra droplet break-up and desolvation via additional Coandă and vortex effects [13]. Comparatively with ESI, US was proven more performant in analysis of various compounds. The US interface showed a fivefold increase in method sensitivity, with an improved signal intensity, linearity, and repeatability on various matrices in comparison with ESI, for the analysis of prostaglandins and thromboxanes [14]. Similarly, for 24 pharmaceutical and biological compounds, US above ESI improved the dynamic range of analytes at lower concentrations and the sensitivity of late eluting compounds [12]. The novel source US generates very similar spectra compared with ESI, predominantly producing protonated or deprotonated species, but improves the intensity of the MS signal by more than twofold on average. The differences in source design between ESI and US have no significant effect on the adduct formation (e.g., proton, sodium, potassium adducts) and up-front fragmentation [6]. However, little is known on the performance of US for routine multiresidue analysis of pesticides in different matrices, as compared with the current largely used ESI.

Despite the numerous advantages of LC-API-MS/MS over other analytical techniques, the quantitative analysis of biological samples is complicated by the presence of matrix components that co-elute with the compound(s) of interest and can interfere with the ionization process in the mass spectrometer, causing ionization suppression or enhancement [15]. This phenomenon, called matrix effect (ME), was first described in 1993 [16] and until today, its mechanism is not fully understood. The ME is defined as the change in the signal intensity of an analyte in a matrix solution compared with the signal intensity in the corresponding solvent [17]. Matrix effects cause a compound’s response to differ when analyzed in a biological matrix, with signal suppression or enhancement effects, and therefore, must be determined and quantified to ensure acceptable quantitative results in pesticide residue analysis. The extent of ME can be influenced by some instrumental parameters such as the ionization source [18] and ionization mode [7]. Differences were observed in ME percentages of US and ESI analysis of pharmaceutical and biological compounds from plasma and bile [12]. These unpredictable effects are a regular problem for API sources [15], so the ME of novel sources must be investigated for analysis of specific compounds like pesticides in various matrices. Besides, the ME is used to describe the analyte ionization efficiency, while the efficiency of separating analyte from the sample is measured by the recovery. The process efficiency (PE) then summarizes the efficiency of sample preparation (extraction recovery) and analyte ionization during LC-MS/MS analysis (ME). Hence, PE is the suitable parameter for assessing the overall performance of an analysis method [2].

Therefore, this study aimed at determining whether multiresidue analysis of pesticides in food and water on the same LC-MS/MS system can be improved with US, comparatively with the commonly used ESI. The selected active ingredients (a.i.) belong to largely used pesticide classes, i.e., insecticides, fungicides, herbicides, nematicides, and acaricides, and are a good representative selection for such study because of their variable hydrophobic character and their different physicochemical properties. Matrices with different analytical challenges, textures, and physicochemical properties, and also largely consumed, including an agricultural dry product (coffee), a fresh product (apple), and water, were selected. Key extraction and analytical performance parameters like signal intensity, signal-to-noise (S/N) ratio, linearity, accuracy, precision, relative abundance (ion ratio), range of a.i., extraction recovery, sensitivity, and ME, as well as process performance parameters like recovery efficiency (RE) and PE were evaluated and compared.

Materials and methods

Reagents

Analytical grade reagents of above 99% purity were used in the experiments. UPLC-grade acetonitrile was procured from VWR Chemicals (Leuven, Belgium), and anhydrous magnesium sulfate, disodium hydrogen sesquihydrate, trisodium citrate dehydrate, sodium chloride, and pesticide a.i. standards were purchased from Sigma-Aldrich (Bornem, Belgium). The 15-ml-d-SPE tubes as well as Sep-Pak cartridge C18 column were obtained from Waters (Milford, MA, USA). Water was produced locally though a Milli-Q purification system.

Sample collection and preparation

Raw coffee beans and apples were purchased in organic shops in Ghent, Belgium. Traces of epoxiconazole, imidacloprid, pyraclostrobine, thiametoxam, and hexythiazox were found in blank coffee samples, as well as pyrimethanil in blank coffee and apple samples. They were used for correction of corresponding signals obtained in spiked samples. Extraction and clean-up were performed using the QuEChERS method commonly used in the multiresidue analysis of food matrices. Approximately 50 g of sample was ground to powder or paste using a household mill equipped with a stainless steel knife (Krups, Fleurus, Belgium). Precisely 2 g of coffee powder or 10 g of apple paste was weighed into a 50-ml Teflon-capped centrifuge tube, 8 ml of Milli-Q water was added in the coffee powder, and then 15 ml of acetonitrile was added to each sample, and the mixture was vigorously shaken for 1 min. A mixture of disodium hydrogen citrate sesquihydrate (0.75 g), trisodium citrate dihydrate (1.5 g), sodium chloride (1.5 g), and anhydrous magnesium sulfate (6 g) was added to the extract into the tube, which was agitated for 3 min at 300 rpm on a shaker (Edmund Bühler, Hechingen, Germany). The tube was centrifuged for 5 min at 10,000 rpm (Eppendorf, Leipzig, Germany) and the supernatant was collected. For clean-up of the coffee extract, 7 ml of the supernatant was pipetted into a 15-ml-d-SPE tube packed with primary secondary amines (PSA) and octadecyl (C18). The content of the tube was then shaken for 1 min, centrifuged for 5 min at 3000 rpm, and the supernatant collected. For LC-MS/MS analysis, 1 ml of the supernatant was diluted 10 times with Milli-Q water, and 2 ml of the diluted solution was sampled into a screw cap autosampler vial for chromatography analysis. For the other sample sets (pre-extraction spiked samples), before the step of addition of 15 ml of acetonitrile, samples were spiked at 0.01 mg/l with each pesticide standard. The spiked samples were left for 1 h at room temperature to allow pesticide absorption into sample before being subjected to the extraction, clean-up process, and analysis as described previously.

For water samples, Sep-Pak cartridges were used for extracting the pesticides spiked in Milli-Q water [19]. Methanol (1 ml) and water (1 ml) were consecutively used to activate the cartridge before loading the sample. One liter of Milli-Q water sample was passed through the cartridge and pesticides were retained on the column. The pesticides were then desorbed with 10 mL of acetonitrile; the extract was diluted 10 times with Milli-Q water and sampled for chromatography analysis. The other water sample sets (pre-extraction spiked samples) were spiked at 0.01 mg/l with each pesticide standard before Sep-Pak cartridge extraction as described previously.

Liquid chromatography tandem mass spectrometry analysis

The protocol from Galani et al. [20] was followed. The equipment consisted of a Waters Acquity UPLC module coupled to a Waters Xevo TQD tandem triple quadrupole mass spectrometer, equipped with ESI or US ion source (Waters, Milford, MA, USA). Separation was carried out through a HSS T3 column (100 mm × 2.1 mm, 1.8 μm) (Waters) maintained at 40 °C. The injection volume was 10 μl; mobile phase A consisted of a 0.1% formic acid solution in water while mobile phase B was acetonitrile with 0.1% formic acid. The flow rate was set at 0.4 ml/min with a run time of 10 min. The separation started with an initial gradient of 98% mobile phase A for 0.25 min, followed by a linear gradient to 98% mobile phase B from 0.25 to 7 min which was maintained for 1 min. Then, a linear gradient was used to 98% mobile phase A and column was reconditioned for 1 min. The analyses were performed with US and ESI consecutively with less than 24-h interval gap between the two interfaces, with the parameters presented in Table 1. The ESI capillary position in relation to the mass spectrometer aperture as well as the US source protrusion of the capillary within the nebulizer tube and the vertical and horizontal position of the probe tip towards the metal rod were optimized for achieving best results. Analyses of pesticides were performed in positive ion mode, except for fludioxonil and 2,4-D, which were analyzed in negative ion mode. The analytes were monitored and quantified using multiple reaction monitoring (MRM). The optimization of the MS/MS conditions, identification of the precursor and product ions, and selection of the cone and collision voltages were performed with direct infusion of their individual standard solutions prepared at 1 mg/ml in acetonitrile/water (10/90). After the optimization of the collision cell energy, two different m/z transitions were selected for each analyte, one for quantification (QIT) and one for confirmation (CIT). The dwell time was calculated automatically. Parameters of acquisition method are summarized in Table 2. MassLynx 4.1 software (Waters, Milford, MA, USA) was used for the LC-MS/MS system control and data acquisition and analysis.
Table 1

Parameters of the UniSpray and electrospray ionization sources

Source

UniSpray

Electrospray

Source temperature (°C)

150

150

Desolvation temperature (°C)

600

600

US rod voltage/ESI capillary voltage (kV)

± 3

± 2

Cone gas flow (l/h)

20

50

Desolvation gas flow (l/h)

1000

1000

Table 2

Parameters of acquisition method of LC-MS/MS analysis of 81 pesticide active ingredients

Sr. no.

Analyte

Retention time (min)

Precursor ion (m/z)

Cone voltage (eV)

Ionization mode

Dwell time (s)

Product ion 1 (m/z)

Collision energy 1 (eV)

Product ion 2 (m/z)

Collision energy 2 (eV)

1

Methomyl

2.40

163

20

+

0.017

88*

10

106

10

2

Methiocarb

4.00

226

22

+

0.015

121

22

169*

10

3

Fenpropimorph

3.44

304.2

50

+

0.015

57.2

30

147.2*

28

4

Tebuthiuron

2.90

229

30

+

0.015

116

16

172*

18

5

Pirimicarb

2.54

239.1

28

+

0.017

72

28

182.1*

15

6

Thiodicarb

3.17

355

20

+

0.015

87.9*

16

107.9

16

7

Prochloraz

4.17

376

16

+

0.015

70.1*

34

307.1

16

8

Trifloxystrobin

5.76

409

28

+

0.073

145

40

186*

16

9

Acetamiprid

2.71

223

34

+

0.015

56.1

15

126*

20

10

Thimetoxam

3.08

292

22

+

0.038

132

22

211.2*

12

11

Difenconazole

5.19

406

40

+

0.015

111.1

60

251.1*

25

12

Pyrimethanil

3.38

200

45

+

0.015

82

24

107*

24

13

Ametryn

3.10

228.1

32

+

0.013

68.1

36

186.1*

18

14

Boscalid

4.37

342.9

35

+

0.013

139.9*

20

307

20

15

Butachlor

6.11

312.2

20

+

0.067

57.3

22

238.2*

12

16

Carbaryl

3.36

202

22

+

0.08

117

28

145*

22

17

Dimethomorph

4.00

388.1

35

+

0.013

165

30

300.9*

20

18

Hexaconazole

4.67

314

16

+

0.013

70.1*

34

159

22

19

Malathion

4.53

331

20

+

0.013

99

24

127*

12

20

Propoxur

3.18

210

15

+

0.013

111*

16

168

10

21

Spinosad A

4.10

732.6

50

+

0.013

98.1

59

142*

31

22

Spinosad D

4.36

746.5

45

+

0.013

98.1

53

142*

31

23

Spiroxamine

3.45

298

32

+

0.013

100

32

144*

20

24

Thiabendazole

2.36

202

45

+

0.013

131

30

175*

25

25

Thifensulfuron-methyl

2.49

388

30

+

0.015

56

40

167*

15

26

Carbofuran

3.20

222.1

28

+

0.012

123*

16

165.1

16

27

Dimethoate

2.66

230.1

18

+

0.012

125

20

199*

10

28

Diuron

3.53

233

28

+

0.012

46.3

14

72.1*

18

29

Ethoprophos

4.29

243.2

26

+

0.012

97

31

131*

20

30

Fenamiphos

4.25

304.1

30

+

0.012

202.1

36

217.1*

24

31

Fenbuconazole

4.63

337

32

+

0.012

70.1*

20

125

36

32

Fludioxonil

4.14

246.8

50

0.013

126*

30

180

28

33

Metalaxyl

3.41

280.1

20

+

0.012

192.1

17

220.1*

13

34

Metsulfuron methyl

3.07

382

22

+

0.02

167*

16

198

22

35

Monocrotophos

2.39

224.1

20

+

0.163

98.1

12

127.1*

16

36

Pendimethalin

6.23

282.2

20

+

0.028

194

18

212.2*

10

37

Pyrazosulfuron-ethyl

4.03

415

22

+

0.012

82.9

45

182*

20

38

Triazophos

4.60

314.1

25

+

0.012

118.9

35

161.9*

18

39

Azoxystrobin

4.19

404

22

+

0.015

329

30

372*

15

40

Bentazon

3.29

241.4

21

+

0.015

107.2

26

199.1*

12

41

Bitertanol

4.69

338.1

15

+

0.015

70.1*

8

99.1

16

42

Cadusafos

5.15

271.1

22

+

0.015

131

22

159*

16

43

Chlorotoluron

6.26

213

20

+

0.03

72*

20

140

30

44

Cymoxanil

2.77

199

17

+

0.015

111

18

128*

8

45

Iprodione

4.63

330

15

+

0.015

244.7*

16

288

15

46

Linuron

4.06

249.1

31

+

0.015

159.9*

18

181.8

16

47

Oxamyl

2.35

237

15

+

0.163

72*

10

90

10

48

Propanil

3.89

217.9

34

+

0.015

127

22

161.9*

16

49

Tebuconazole

4.51

308

40

+

0.015

70.1*

22

125

40

50

Terbutryn

3.48

242.1

34

+

0.015

91

28

186.1*

20

51

Tiofanate-methyl

3.10

343

22

+

0.015

93

46

151*

22

52

Kresoxim-methyl

4.97

314.1

18

+

0.017

116

12

206*

7

53

Carbendazim

2.27

192.1

27

+

0.08

132.1

28

16.1*

18

54

Diazinon

5.16

305

31

+

0.017

96

35

169*

22

55

Imidacloprid

2.63

256.1

34

+

0.038

175.1*

20

209.1

15

56

Imazalil

2.99

297

34

+

0.02

69*

22

159

22

57

Metribuzin

3.12

215

35

+

0.012

89

20

131*

18

58

Profenofos

5.63

372.9

36

+

0.017

127.9

40

302.6*

20

59

Propiconazole

4.78

342

40

+

0.017

69

22

159*

34

60

Pyrachlostrobin

5.32

388.1

25

+

0.017

163

25

193.9*

12

61

Triadimenol

3.94

296.1

15

+

0.017

70.2*

10

99.1

15

62

Terbufos

6.07

289

12

+

0.017

57.2

22

103*

8

63

Thiacloprid

2.89

253

25

+

0.071

90.1

40

126*

20

64

Penconazole

4.66

284

28

+

0.052

70.1*

16

159

34

65

Pirimiphos-methyl

5.13

306.1

30

+

0.052

108.1*

32

164.1

22

66

Tebufenozide

4.94

353.1

13

+

0.052

133

20

297.1*

8

67

Spirodiclofen

6.98

411.1

25

+

0.108

71.2*

13

313

13

68

Cyflufenamid

5.71

413.2

30

+

0.052

203

35

295.1*

15

69

Temephos

6.35

466.8

32

+

0.052

125*

38

418.9

22

70

2,4-D

3.52

160.7

50

0.071

88.9

20

124.9*

18

71

Chlorpyrifos

3.38

349.9

30

+

0.037

97*

32

198

20

72

Cyanazine

3.12

241.1

35

+

0.03

96

25

214

17

73

Terbutylazine

4.10

230

28

+

0.03

96

28

174*

16

74

Propazine

3.97

230.2

34

+

0.03

146.1

24

188.1*

18

75

Atrazine

2.48

174

30

+

0.038

96*

20

103.9

20

76

Simazine

3.10

202

34

+

0.03

96

22

124*

16

77

Isoproturon

3.52

207.3

34

+

0.03

46

16

72*

16

78

Fenoxycarb

4.74

302.1

22

+

0.03

88

20

116.1*

11

79

Epoxiconazole

4.34

330

28

+

0.03

101

50

121*

22

80

Benalaxyl

4.97

326.1

20

+

0.064

91

34

148*

20

81

Hexythiazox

6.31

353

24

+

0.136

168.1

26

228.1*

14

*Transition used for quantification (QIT)

Evaluation of the performance

Eight replicate injections of each sample were performed. To determine the linearity, five different concentrations of the stock solution (0.1, 0.05, 0.01, 0.005, 0.001 mg/l) were prepared by dilution with acetonitrile/water (10/90) to form a calibration curve. The signal intensity (peak area and peak height), S/N ratio, and relative abundance (ion ratio) of the QIT were calculated by the software. The sensitivity was evaluated by determining the limit of detection (LOD) and the limit of quantification (LOQ), which were statistically calculated based on the t99SLLMV method [21], by multiplying the standard deviation of the detected pesticide concentration at 0.01 mg/l from the eight replicates by 2.998 (for LOD) and 10 (for LOQ). The accuracy (percentage extraction recovery, %recovery) was calculated by dividing the recovered concentrations by spiked concentration. Finally, the precision (percentage relative standard deviation, %RSD) was obtained by dividing the standard deviation by the average calculated concentration.

Matrix effect was determined by post-extraction spike matrix comparison [2]. A set of blank samples was spiked after the procedure of pesticide extraction, at 0.01 mg/l and thoroughly mixed. These post-extraction spiked samples were then diluted 10 times and analyzed as previously described. The peak area of the pesticide in solvent (A), the peak area of the pesticide in post-extraction spiked samples (B), and the peak area of the pesticide in pre-extraction spiked samples (C) were used to calculate the matrix effect (ME), recovery efficiency (RE), and process efficiency (PE) as follows [22]:
$$ \mathrm{ME}\ \left(\%\right)=\mathrm{B}/\mathrm{A}\times 100 $$
$$ \mathrm{RE}\ \left(\%\right)=\mathrm{C}/\mathrm{B}\times 100 $$
$$ \mathrm{PE}\ \left(\%\right)=\mathrm{C}/\mathrm{A}\times 100=\left(\mathrm{ME}\times \mathrm{RE}\right)/100 $$

A value of 100% indicates that there is no absolute ME; if the value is above 100%, there is a signal enhancement and there is signal suppression if the value is < 100%.

Statistical analysis

The number of times (fold) US was higher or lower than ESI value was obtained by dividing each US value by its counterpart ESI value. To determine statistically if the US improved the performance of analyses, the means of different parameters were compared between US and ESI using a one-tailed paired Student’s t test; p values less than 0.05, 0.01, and 0.001 were considered significant, highly significant, and very highly significant, respectively. The software SPSS Statistics 19.0 (IBM Corporation, NY, USA) was used.

Results and discussion

Linearity

For the tested concentration range (0.001 to 0.1 mg/l), a very highly significant difference (p = 0.000005) was observed between the values of US and ESI (Electronic Supplementary Material, ESM) but in both cases, the r2 values were very good: they ranged from 0.9976 to 0.9999 with US, and from 0.9983 to 0.9999 with ESI. The significant difference between ESI and US may result from the fact that the r2 values are very close to each other. Similar linearity with r2 values ranging from 0.994 to 0.999 but with no significant difference between US and ESI was previously reported for pharmaceutical compounds [14].

Signal intensity

There was a very highly significant difference in peak areas obtained with the two interfaces in the three matrices (p = 0.0000002, 0.000035, and 0.000001 in apple, coffee, and water, respectively); US allowed a tremendous gain in intensity, up to 22.4 times in apple (spinosad D), 31.6 times in coffee (spinosad D), and 24.5 times in water (kresoxim-methyl). In average, the gain in peak area with US was 6.4-fold in apple, 7.0-fold in coffee, and 7.2-fold in water (Table 3). Similarly, a highly significant increase of peak height was obtained with US (p = 0.0000001, 0.000033, and 0.000002 in apple, coffee, and water, respectively), and peak 21.3 times higher was obtained with spinosad D in apple, 21.1 times higher with spiroxamine in coffee, and 20.3 times higher with kresoxim-methyl in water. In general, US allowed a peak height gain of 6.3-fold in apple, 6.8-fold in coffee, and 6.9-fold in water (see ESM). A general increase in peak area ranging from a factor 1.1 to 15 with an average around 2 was observed with US for analysis of prostaglandins and thromboxanes [14]. Likewise, US showed an intensity gain of a factor 2.2 compared with ESI when analyzing by infusion, a mix of 22 pharmaceutical compounds. The design of the UniSpray source helps to promote droplet break-up and desolvation which has a significant effect on signal intensity [6].
Table 3

Comparison of performance parameters between UniSpray and electrospray sources for analysis of 81 pesticide residues in apple, coffee, and water

 

Peak area

Signal-to-noise ratio

Limit of quantification (mg/kg)

Matrix effect (%)

Process efficiency (%)

Sr. no.

Analyte

US

ESI

Fold

US

ESI

Fold

US

ESI

Fold

US

ESI

Fold

US

ESI

Fold

Apple

1

Methomyl

7385.8

1402.6

5.3

2641.3

634.6

4.2

0.0023

0.0037

1.6

38.1

5.6

6.8

40.9

5.2

7.8

2

Methiocarb

4954.9

2879.1

1.7

1661.4

1377.8

1.2

0.0027

0.0011

0.4

98.1

8.9

11.1

63.3

5.9

10.7

3

Fenpropimorf

63,342.1

5665.3

11.2

3375.3

707.8

4.8

0.0018

0.0019

1.1

634.1

45.4

14.0

59.3

4.8

12.2

4

Tebuthiuron

93,105.1

8790.3

10.6

9246.3

2155.1

4.3

0.0034

0.0025

0.7

113.7

8.9

12.7

77.3

5.8

13.3

5

Pirimicarb

46,063.6

4118.8

11.2

4816.9

708.5

6.8

0.0012

0.0014

1.2

82.7

8.5

9.7

53.4

5.2

10.2

6

Thiodicarb

10,020.5

3430.5

2.9

1749.6

1004.6

1.7

0.0032

0.0021

0.7

101.3

10.0

10.1

56.2

5.7

9.8

7

Prochloraz

4462.3

348.8

12.8

917.4

280.1

3.3

0.0024

0.0023

1.0

90.7

3.7

24.3

49.6

2.3

21.8

8

Trifloxystrobin

18,436.0

9741.4

1.9

3772.6

2109.1

1.8

0.0013

0.0017

1.3

58.9

5.9

10.0

37.3

5.1

7.3

9

Acetamiprid

11,007.4

4581.9

2.4

985.1

811.3

1.2

0.0021

0.0037

1.8

70.0

8.3

8.5

49.2

5.7

8.6

10

Thifensulfuron

5531.9

1962.8

2.8

1286.8

1067.0

1.2

0.0094

0.0079

0.8

111.8

8.2

13.6

92.5

5.7

16.3

11

Difenconazole

12,020.6

1625.0

7.4

991.5

340.5

2.9

0.0030

0.0023

0.8

100.2

5.3

19.0

67.4

4.2

16.0

12

Pyrimethanil

77,256.4

6833.3

11.3

2214.4

723.0

3.1

0.0049

0.0043

0.9

616.3

58.8

10.5

106.2

10.0

10.6

13

Ametryn

89,324.5

9614.6

9.3

6582.8

1482.8

4.4

0.0021

0.0012

0.5

9.6

7.8

1.2

6.0

5.5

1.1

14

Boscalid

6735.0

1496.3

4.5

1134.6

816.9

1.4

0.0049

0.0036

0.7

10.3

6.4

1.6

6.6

4.5

1.4

15

Butachlor

1494.8

594.9

2.5

519.0

289.5

1.8

0.0026

0.0025

1.0

9.0

4.8

1.9

6.3

4.3

1.5

16

Carbaryl

3237.5

830.8

3.9

775.5

245.4

3.2

0.0030

0.0036

1.2

9.1

7.9

1.2

5.4

5.1

1.1

17

Dimethomorph

7545.8

2771.1

2.7

878.3

348.4

2.5

0.0014

0.0027

2.0

11.2

8.9

1.3

5.7

4.9

1.2

18

Hexaconazole

13,795.1

1877.4

7.3

1342.1

665.3

2.0

0.0017

0.0023

1.3

9.4

6.5

1.5

6.0

5.1

1.2

19

Malathion

5152.8

2763.3

1.9

551.0

489.9

1.1

0.0023

0.0024

1.0

9.4

8.4

1.1

4.9

4.7

1.0

20

Propoxur

25,964.1

4711.5

5.5

2409.5

657.3

3.7

0.0018

0.0031

1.7

9.6

8.1

1.2

6.1

5.4

1.1

21

Spinosad A

19,849.1

1132.1

17.5

2821.5

255.0

11.1

0.0153

0.0043

0.3

497.3

19.6

25.4

596.8

16.1

41.0

22

Spinosad D

6631.9

296.0

22.4

5724.3

312.6

18.3

0.0267

0.0113

0.4

451.4

19.9

22.7

607.7

18.2

33.4

23

Spiroxamine

128,712.8

8507.8

15.1

3393.0

499.0

6.8

0.0015

0.0006

0.4

7.6

4.0

1.9

5.7

3.1

1.9

24

Thiabendazole

25,288.5

1441.9

17.5

2594.9

338.8

7.7

0.0005

0.0019

3.7

6.3

4.0

1.6

3.8

2.8

1.4

25

Thiametoxam

1474.5

626.4

2.4

274.5

169.3

1.6

0.0031

0.0029

0.9

5.1

5.1

1.0

4.4

4.2

1.1

26

Carbofuran

33,900.8

6401.8

5.3

2437.8

758.4

3.2

0.0027

0.0023

0.9

11.3

8.4

1.3

7.3

5.6

1.3

27

Dimethoate

11,479.1

2524.8

4.5

2561.3

888.4

2.9

0.0016

0.0019

1.2

8.8

7.4

1.2

6.0

4.8

1.2

28

Diuron

13,937.6

3965.1

3.5

1320.0

497.5

2.7

0.0040

0.0031

0.8

10.7

9.1

1.2

6.4

6.0

1.1

29

Ethoprophos

11,902.1

4205.5

2.8

654.9

525.3

1.2

0.0030

0.0019

0.6

12.2

9.0

1.4

7.4

5.9

1.2

30

Fenamiphos

13,241.5

4096.0

3.2

1613.0

691.9

2.3

0.0015

0.0036

2.4

12.4

9.8

1.3

6.2

5.4

1.1

31

Fenbuconazole

6146.9

1449.5

4.2

3508.0

402.3

8.7

0.0043

0.0075

1.7

9.7

7.3

1.3

6.0

5.6

1.1

32

Fludioxonil

1149.3

77.0

14.9

1188.9

87.4

13.6

0.0039

0.0070

1.8

11.9

7.0

1.7

7.4

5.3

1.4

33

Metalaxyl

46,920.8

10,792.3

4.3

1949.1

640.4

3.0

0.0022

0.0024

1.1

12.3

10.5

1.2

7.2

6.3

1.1

34

Metribuzin

3075.0

266.6

11.5

118.0

28.6

4.1

0.0041

0.0088

2.1

11.1

9.1

1.2

7.1

5.8

1.2

35

Monocrotophos

14,489.8

3131.6

4.6

1925.6

876.4

2.2

0.0010

0.0019

2.0

5.9

6.2

0.9

5.3

4.6

1.2

36

Pendimethalin

258.0

362.3

0.7

39.8

218.5

0.2

0.0017

0.0020

1.2

3.8

2.6

1.5

2.3

2.6

0.9

37

Pyrazosulfuron-ethyl

4733.5

2202.9

2.1

3337.4

448.4

7.4

0.0068

0.0019

0.3

9.1

7.5

1.2

6.6

5.7

1.2

38

Triazophos

32,214.9

9234.3

3.5

1840.5

1782.6

1.0

0.0021

0.0027

1.3

11.0

10.4

1.1

6.8

7.2

0.9

39

Azoxystrobin

35,276.0

10,195.0

3.5

5861.1

1174.6

5.0

0.0019

0.0017

0.9

17.6

13.5

1.3

6.9

5.6

1.2

40

Bentazon

129.6

36.6

3.5

12.3

6.6

1.8

0.0170

0.0050

0.3

7.3

6.1

1.2

4.8

3.9

1.2

41

Bitertanol

2940.1

317.4

9.3

480.1

153.6

3.1

0.0021

0.0071

3.4

8.3

6.9

1.2

5.1

4.9

1.0

42

Cadusafos

12,629.0

3006.6

4.2

1614.9

612.3

2.6

0.0013

0.0025

2.0

10.4

6.7

1.5

6.6

4.5

1.5

43

Chlorpyrifos

171.5

223.4

0.8

60.6

81.8

0.7

0.0046

0.0039

0.8

4.4

2.3

2.0

3.5

2.5

1.4

44

Cymoxanil

1184.0

516.4

2.3

263.3

474.5

0.6

0.0132

0.0060

0.5

13.1

8.7

1.5

8.4

5.3

1.6

45

Iprodione

146.9

34.4

4.3

15.1

28.8

0.5

0.0210

0.0193

0.9

15.4

7.7

2.0

8.9

5.0

1.8

46

Linuron

962.5

541.4

1.8

79.4

201.9

0.4

0.0094

0.0078

0.8

12.4

6.4

1.9

8.2

4.7

1.7

47

Oxamyl

20,751.5

2503.4

8.3

7032.9

1632.5

4.3

0.0016

0.0007

0.4

6.7

7.0

1.0

5.5

5.2

1.1

48

Propanil

890.8

301.0

3.0

65.1

42.3

1.5

0.0105

0.0099

0.9

10.0

7.0

1.4

6.7

4.7

1.4

49

Tebuconazole

18,561.5

2459.8

7.5

899.3

480.1

1.9

0.0036

0.0023

0.6

9.3

7.1

1.3

5.6

5.0

1.1

50

Terbuthryn

119,793.4

12,769.8

9.4

7864.5

1170.0

6.7

0.0010

0.0011

1.1

8.8

6.8

1.3

5.6

4.9

1.1

51

Thiofanate-methyl

1440.3

109.4

13.2

76.4

11.4

6.7

0.0031

0.0279

8.9

12.4

13.1

0.9

3.8

6.2

0.6

52

Kresoxim-methyl

909.5

42.9

21.2

833.3

61.5

13.5

0.0070

0.0059

0.8

7.5

7.0

1.1

4.4

5.3

0.8

53

Carbendazim

42,296.1

3703.0

11.4

4126.0

621.5

6.6

0.0013

0.0024

1.8

9.2

8.3

1.1

5.6

5.1

1.1

54

Diazinon

87,076.9

8830.0

9.9

2348.4

1815.5

1.3

0.0010

0.0013

1.3

9.7

8.1

1.2

5.7

5.2

1.1

55

Imidacloprid

552.8

197.1

2.8

195.6

550.0

0.4

0.0040

0.0058

1.4

6.9

5.3

1.3

4.4

3.6

1.2

56

Imazalil

8718.3

612.1

14.2

303.1

60.4

5.0

0.0002

0.0004

1.7

0.9

0.4

2.2

0.6

0.3

1.7

57

Metsulfuron-methyl

4183.1

1813.9

2.3

546.5

617.5

0.9

0.0002

0.0003

1.3

1.0

0.9

1.1

0.5

0.5

1.0

58

Profenofos

671.3

452.6

1.5

203.0

179.3

1.1

0.0040

0.0022

0.6

4.9

2.2

2.2

3.1

1.7

1.8

59

Propiconazole

6274.9

914.9

6.9

123.6

46.5

2.7

0.0011

0.0040

3.6

8.9

6.6

1.3

5.5

4.6

1.2

60

Pyraclostrobine

26,157.5

6396.9

4.1

2072.5

728.0

2.8

0.0008

0.0012

1.6

7.6

3.9

1.9

4.8

3.4

1.4

61

Triadimenol

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

62

Terbufos

105.9

23.0

4.6

14.1

5.6

2.5

0.0050

0.0074

1.5

5.0

5.4

0.9

2.9

3.6

0.8

63

Thiacloprid

8151.4

5324.6

1.5

1063.1

1119.5

0.9

0.0034

0.0008

0.2

9.0

6.5

1.4

5.8

4.2

1.4

64

Penconazole

17,579.1

2300.1

7.6

2511.4

543.9

4.6

0.0013

0.0022

1.7

9.2

7.9

1.2

5.9

4.9

1.2

65

Pirimiphos-methyl

26,338.0

4964.0

5.3

3442.6

1079.0

3.2

0.0018

0.0016

0.9

9.6

6.3

1.5

6.0

3.8

1.6

66

Tebufenozide

3124.3

775.6

4.0

1616.4

665.8

2.4

0.0068

0.0067

1.0

10.9

10.1

1.1

7.3

6.4

1.1

67

Spirodiclofen

697.5

192.6

3.6

122.6

60.4

2.0

0.0333

0.0034

0.1

26.3

3.5

7.6

15.9

2.0

8.1

68

Cyflufenamid

1382.1

1102.3

1.3

345.9

318.8

1.1

0.0037

0.0022

0.6

12.6

6.6

1.9

7.8

4.0

2.0

69

Temephos

272.6

NQ

NQ

41.1

NQ

NQ

0.0118

NQ

NQ

14.1

NQ

NQ

9.2

NQ

NQ

70

2,4-D

10.9

6.0

1.8

27.9

23.3

1.2

0.0176

0.0078

0.4

5.1

3.5

1.5

7.6

5.8

1.3

71

Chlorotoluron

12,044.6

4175.9

2.9

1304.6

2212.6

0.6

0.0013

0.0011

0.8

9.5

7.4

1.3

6.3

4.8

1.3

72

Cyanazine

13,686.8

1460.0

9.4

2430.6

1154.8

2.1

0.0022

0.0021

0.9

8.2

8.0

1.0

5.5

5.0

1.1

73

Terbuthylazine

63.9

6.9

9.3

53.8

18.0

3.0

0.0180

0.0383

2.1

9.6

5.6

1.7

6.6

3.8

1.7

74

Propazine

10,320.6

2671.6

3.9

1420.5

1503.4

0.9

0.0019

0.0020

1.1

9.9

7.1

1.4

6.4

4.7

1.4

75

Atrazine

3605.0

205.8

17.5

413.6

69.6

5.9

0.0012

0.0032

2.6

6.7

5.8

1.2

4.3

3.9

1.1

76

Simazine

23,559.4

1596.6

14.8

1414.9

272.8

5.2

0.0018

0.0028

1.6

9.1

7.3

1.3

6.0

4.5

1.3

77

Isoproturon

28,866.4

7110.4

4.1

2945.3

1997.3

1.5

0.0010

0.0010

1.0

9.9

8.0

1.2

6.6

5.2

1.3

78

Fenoxycarb

4603.4

2528.9

1.8

1333.1

1551.9

0.9

0.0025

0.0022

0.9

10.1

6.9

1.5

6.7

4.3

1.6

79

Epoxiconazole

21,751.4

3142.0

6.9

1061.4

325.5

3.3

0.0022

0.0023

1.0

9.3

8.4

1.1

6.1

5.2

1.2

80

Benalaxyl

13,774.3

9182.6

1.5

1601.3

1670.8

1.0

0.0016

0.0008

0.5

10.5

7.9

1.3

6.9

5.0

1.4

81

Hexythiazox

1069.6

585.1

1.8

544.1

465.6

1.2

0.0018

0.0008

0.4

11.4

3.0

3.8

7.8

1.9

4.2

Minimum value

10.9

6.0

0.7

12.3

5.6

0.2

0.0002

0.0003

0.1

0.9

0.4

0.92

0.5

0.3

0.6

Maximum value

128,712.8

12,769.7

22.4

9246.3

2212.6

18.3

0.0333

0.0383

8.9

634.1

58.8

25.4

607.7

18.2

41.0

Average value

18,312.1

3039.0

6.4

1799.2

660.0

3.4

0.0047

0.0042

1.3

46.1

8.4

3.7

29.4

5.0

3.9

p value

0.0000002***

0.00000001***

0.283456

0.002046**

0.010766*

Coffee

1

Methomyl

9381.6

831.5

11.3

2432.4

499.5

4.9

0.0033

0.0032

1.0

70.8

4.1

17.1

52.0

3.1

16.7

2

Methiocarb

4193.4

1959.0

2.1

2306.5

652.9

3.5

0.0046

0.0020

0.4

90.2

6.7

13.5

53.6

4.0

13.4

3

Fenpropimorf

22,737.9

1371.1

16.6

1866.9

443.5

4.2

0.0008

0.0011

1.4

53.7

3.7

14.6

21.3

1.2

18.2

4

Tebuthiuron

77,355.5

6965.8

11.1

9033.4

1324.6

6.8

0.0033

0.0021

0.6

106.2

7.4

14.4

64.2

4.6

14.0

5

Pirimicarb

50,219.1

2940.8

17.1

5861.5

745.0

7.9

0.0021

0.0015

0.7

93.1

6.1

15.3

58.2

3.7

15.6

6

Thiodicarb

9075.0

3196.9

2.8

4095.9

1737.5

2.4

0.0030

0.0010

0.3

99.1

9.4

10.5

50.9

5.3

9.5

7

Prochloraz

4408.5

390.0

11.3

935.9

159.1

5.9

0.0027

0.0051

1.9

70.7

3.9

18.0

49.0

2.5

19.2

8

Trifloxystrobin

11,831.0

4101.3

2.9

3023.3

1363.5

2.2

0.0034

0.0006

0.2

31.2

2.7

11.5

24.0

2.1

11.2

9

Acetamiprid

10,674.0

3836.9

2.8

1092.8

1080.0

1.0

0.0026

0.0012

0.5

78.1

7.4

10.5

47.7

4.8

10.0

10

Thifensulfuron

218.8

NQ

NQ

39.6

NQ

NQ

0.0006

NQ

NQ

111.0

NQ

NQ

3.7

NQ

NQ

11

Difenconazole

8405.9

973.6

8.6

1044.0

197.8

5.3

0.0009

0.0017

1.9

62.9

3.6

17.3

47.1

2.5

18.6

12

Pyrimethanil

245,808.8

19,453.4

12.6

7454.3

872.5

8.5

0.0209

0.0096

0.5

312.2

26.4

11.8

337.8

28.4

11.9

13

Ametryn

93,374.5

7002.5

13.3

6577.9

1364.1

4.8

0.0009

0.0026

2.9

10.7

6.3

1.7

6.3

4.0

1.6

14

Boscalid

6047.1

1353.6

4.5

679.6

611.9

1.1

0.0035

0.0037

1.0

10.0

6.1

1.6

5.9

4.1

1.4

15

Butachlor

710.5

216.3

3.3

207.5

110.5

1.9

0.0020

0.0045

2.2

4.2

2.5

1.7

3.0

1.6

1.9

16

Carbaryl

3309.0

601.1

5.5

1351.4

656.0

2.1

0.0021

0.0051

2.4

9.5

5.7

1.7

5.5

3.7

1.5

17

Dimethomorph

7410.9

2175.4

3.4

808.0

395.0

2.0

0.0017

0.0030

1.8

11.6

7.5

1.5

5.6

3.8

1.5

18

Hexaconazole

12,384.3

1241.0

10.0

1442.4

225.5

6.4

0.0025

0.0011

0.4

8.9

5.8

1.6

5.4

3.4

1.6

19

Malathion

5409.6

2340.8

2.3

659.8

614.6

1.1

0.0043

0.0022

0.5

8.8

6.5

1.4

5.2

4.0

1.3

20

Propoxur

27,407.6

3629.1

7.6

2802.5

707.1

4.0

0.0021

0.0021

1.0

10.5

6.3

1.7

6.4

4.1

1.6

21

Spinosad A

878.3

65.0

13.5

581.0

72.9

8.0

0.0017

0.0043

2.5

8.4

1.7

4.8

2.7

0.5

4.9

22

Spinosad D

343.1

10.9

31.6

477.4

16.3

29.4

0.0048

0.0080

1.7

9.0

1.0

8.9

3.4

0.3

10.3

23

Spiroxamine

1156.4

57.9

20.0

44.5

36.6

1.2

0.0001

0.0001

0.7

2.7

1.2

2.2

0.1

0.0

2.5

24

Thiabendazole

8095.9

702.4

11.5

935.8

170.8

5.5

0.0004

0.0010

2.4

2.7

2.6

1.0

1.2

1.4

0.9

25

Thiametoxam

2719.6

734.0

3.7

500.6

276.8

1.8

0.0025

0.0024

1.0

11.7

6.4

1.8

8.2

4.9

1.7

26

Carbofuran

32,023.0

4953.0

6.5

2050.1

767.0

2.7

0.0022

0.0019

0.8

11.3

6.7

1.7

6.9

4.3

1.6

27

Dimethoate

12,521.8

2010.4

6.2

2511.9

1542.9

1.6

0.0020

0.0016

0.8

10.6

6.0

1.8

6.5

3.8

1.7

28

Diuron

14,390.9

3025.4

4.8

1602.8

396.1

4.0

0.0038

0.0018

0.5

11.1

7.2

1.5

6.6

4.6

1.4

29

Ethoprophos

13,182.4

3082.6

4.3

732.4

1122.6

0.7

0.0042

0.0020

0.5

13.3

7.1

1.9

8.2

4.4

1.9

30

Fenamiphos

11,437.1

2331.0

4.9

1761.9

700.3

2.5

0.0031

0.0016

0.5

12.8

7.3

1.8

5.3

3.1

1.7

31

Fenbuconazole

5270.8

921.1

5.7

2833.3

1060.3

2.7

0.0024

0.0033

1.4

8.6

5.7

1.5

5.2

3.6

1.4

32

Fludioxonil

836.3

NQ

NQ

897.0

NQ

NQ

0.0034

NQ

NQ

8.6

4.7

1.8

5.4

NQ

NQ

33

Metalaxyl

48,720.0

8535.3

5.7

3829.9

889.1

4.3

0.0016

0.0031

2.0

12.4

8.1

1.5

7.5

5.0

1.5

34

Metribuzin

2625.8

182.1

14.4

146.0

16.8

8.7

0.0046

0.0067

1.5

9.7

6.5

1.5

6.0

3.9

1.5

35

Monocrotophos

17,231.9

1960.9

8.8

3051.5

658.1

4.6

0.0017

0.0011

0.6

10.9

4.6

2.4

6.3

2.9

2.2

36

Pendimethalin

87.1

82.8

1.1

33.9

56.5

0.6

0.0012

0.0007

0.5

1.1

0.6

2.0

0.8

0.6

1.3

37

Pyrazosulfuron-ethyl

644.8

257.3

2.5

856.9

431.8

2.0

0.0020

0.0011

0.6

10.0

6.8

1.5

0.9

0.7

1.4

38

Triazophos

30,976.8

6338.3

4.9

2761.5

1174.0

2.4

0.0017

0.0022

1.4

10.4

7.7

1.4

6.5

4.9

1.3

39

Azoxystrobin

31,921.4

7957.6

4.0

5294.9

2101.5

2.5

0.0015

0.0017

1.1

11.1

7.5

1.5

6.3

4.4

1.4

40

Bentazon

75.3

NQ

NQ

6.0

NQ

NQ

0.0086

NQ

NQ

7.2

NQ

NQ

2.8

NQ

NQ

41

Bitertanol

2260.5

241.9

9.3

892.0

88.1

10.1

0.0020

0.0060

3.0

6.4

6.3

1.0

3.9

3.7

1.0

42

Cadusafos

10,881.8

2119.0

5.1

1096.3

501.5

2.2

0.0018

0.0013

0.7

9.7

5.4

1.8

5.7

3.2

1.8

43

Chlorpyrifos

61.6

47.5

1.3

18.0

22.8

0.8

0.0035

0.0010

0.3

1.4

0.5

2.6

1.2

0.5

2.4

44

Cymoxanil

801.9

221.8

3.6

129.6

486.1

0.3

0.0074

0.0036

0.5

12.0

5.3

2.2

5.7

2.3

2.5

45

Iprodione

77.9

14.6

5.3

7.4

21.3

0.3

0.0115

0.0081

0.7

10.7

3.5

3.0

4.7

2.1

2.2

46

Linuron

846.3

396.6

2.1

140.0

74.6

1.9

0.0114

0.0038

0.3

11.7

5.6

2.1

7.2

3.4

2.1

47

Oxamyl

5348.0

605.6

8.8

1745.0

169.0

10.3

0.0006

0.0007

1.2

2.4

2.0

1.2

1.4

1.3

1.1

48

Propanil

721.6

214.6

3.4

34.0

168.3

0.2

0.0136

0.0064

0.5

9.6

5.9

1.6

5.5

3.3

1.6

49

Tebuconazole

16,540.5

1918.3

8.6

1362.0

322.6

4.2

0.0027

0.0042

1.5

8.7

6.6

1.3

5.0

3.9

1.3

50

Terbuthryn

97,963.9

8753.1

11.2

6528.8

1541.9

4.2

0.0007

0.0007

1.1

8.1

5.8

1.4

4.6

3.4

1.4

51

Thiofanate-methyl

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

52

Kresoxim-methyl

772.5

NQ

NQ

492.8

NQ

NQ

0.0086

NQ

NQ

7.6

4.4

1.7

3.8

NQ

NQ

53

Carbendazim

49,837.9

3356.6

14.8

8293.3

1392.1

6.0

0.0022

0.0017

0.8

14.1

9.0

1.6

6.6

4.6

1.4

54

Diazinon

78,696.3

6764.3

11.6

3813.9

1021.8

3.7

0.0011

0.0011

1.0

8.2

6.1

1.3

5.2

4.0

1.3

55

Imidacloprid

1256.3

351.6

3.6

291.5

902.0

0.3

0.0057

0.0085

1.5

14.5

8.8

1.7

10.1

6.4

1.6

56

Imazalil

NQ

250.3

NQ

NQ

18.5

NQ

NQ

0.0001

NQ

0.5

0.3

NQ

NQ

0.1

NQ

57

Metsulfuron-methyl

289.6

132.4

2.2

43.4

173.9

0.2

0.0001

0.0001

1.0

1.0

0.9

1.1

0.0

0.0

0.9

58

Profenofos

283.5

145.4

2.0

131.1

128.3

1.0

0.0016

0.0010

0.6

2.2

0.9

2.3

1.3

0.6

2.3

59

Propiconazole

5817.4

688.4

8.5

256.6

27.0

9.5

0.0021

0.0014

0.6

8.9

5.5

1.6

5.1

3.5

1.5

60

Pyraclostrobine

20,258.9

3853.9

5.3

2989.9

681.0

4.4

0.0008

0.0006

0.8

4.9

2.3

2.1

3.7

2.1

1.8

61

Triadimenol

NQ

68.3

NQ

NQ

39.0

NQ

NQ

0.0008

NQ

NQ

5.2

NQ

NQ

0.4

NQ

62

Terbufos

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

63

Thiacloprid

7987.1

5333.4

1.5

678.9

1270.9

0.5

0.0019

0.0013

0.7

9.5

6.6

1.4

5.7

4.2

1.4

64

Penconazole

17,318.0

2069.1

8.4

2570.8

484.3

5.3

0.0015

0.0027

1.8

8.6

7.1

1.2

5.8

4.4

1.3

65

Pirimiphos-methyl

27,371.5

3898.0

7.0

3504.4

693.9

5.1

0.0008

0.0011

1.3

8.7

4.5

1.9

6.3

3.0

2.1

66

Tebufenozide

3091.8

705.0

4.4

703.9

662.9

1.1

0.0077

0.0063

0.8

10.2

9.4

1.1

7.2

5.8

1.2

67

Spirodiclofen

444.3

146.9

3.0

162.6

54.4

3.0

0.0117

0.0035

0.3

16.3

1.4

11.5

10.1

1.5

6.8

68

Cyflufenamid

1260.4

657.6

1.9

224.9

252.6

0.9

0.0043

0.0026

0.6

10.2

3.6

2.9

7.1

2.4

3.0

69

Temephos

284.1

147.5

1.9

45.9

116.5

0.4

0.0055

0.0043

0.8

12.0

1.6

7.3

9.6

1.9

5.2

70

2,4-D

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

71

Chlorotoluron

11,744.5

4432.0

2.6

1315.4

904.5

1.5

0.0018

0.0026

1.4

10.1

8.4

1.2

6.2

5.1

1.2

72

Cyanazine

12,296.1

1806.1

6.8

1835.1

697.1

2.6

0.0014

0.0031

2.3

8.6

9.9

0.9

4.9

6.2

0.8

73

Terbuthylazine

52.5

6.0

8.8

51.3

27.4

1.9

0.0142

0.0478

3.4

8.9

4.1

2.2

5.4

3.3

1.6

74

Propazine

10,182.6

2981.5

3.4

2460.9

896.9

2.7

0.0011

0.0039

3.5

10.0

9.1

1.1

6.3

5.2

1.2

75

Atrazine

2733.5

194.0

14.1

249.4

40.5

6.2

0.0012

0.0040

3.4

5.4

5.6

1.0

3.2

3.6

0.9

76

Simazine

22,475.9

1725.1

13.0

1885.0

459.4

4.1

0.0007

0.0022

3.0

9.1

7.9

1.2

5.7

4.9

1.2

77

Isoproturon

28,025.4

7245.8

3.9

3256.9

1778.0

1.8

0.0025

0.0018

0.7

10.4

7.8

1.3

6.4

5.3

1.2

78

Fenoxycarb

4294.1

1624.6

2.6

2617.5

460.3

5.7

0.0022

0.0025

1.2

8.9

5.3

1.7

6.3

2.7

2.3

79

Epoxiconazole

22,672.9

3536.3

6.4

1487.9

330.9

4.5

0.0009

0.0027

3.1

9.0

8.9

1.0

6.3

5.9

1.1

80

Benalaxyl

12,915.4

8580.8

1.5

1117.5

1033.8

1.1

0.0018

0.0011

0.6

9.3

7.6

1.2

6.5

4.7

1.4

81

Hexythiazox

829.4

187.1

4.4

460.6

369.9

1.2

0.0055

0.0010

0.2

8.7

2.4

3.7

6.1

0.6

10.1

Minimum value

52.5

6.0

1.1

6.0

16.3

0.2

0.0001

0.0001

0.2

0.5

0.3

0.8

0.0

0.0

0.8

Maximum value

245,808.8

19,453.3

31.6

9033.4

2101.5

29.4

0.0209

0.0478

3.5

312.2

26.4

17.9

337.8

28.4

19.2

Average value

17,423.6

2475.7

7.0

1809.5

588.7

3.8

0.0035

0.0033

1.2

22.8

5.6

3.8

15.1

3.6

3.9

p value

0.000035***

0.00000001***

0.489345

0.000365***

0.005053**

Water

1

Methomyl

NQ

147.4

NQ

NQ

185.4

NQ

NQ

0.0007

NQ

NQ

8.1

NQ

NQ

0.6

NQ

2

Methiocarb

7668.6

3697.0

2.1

1894.0

768.4

2.5

0.0016

0.0018

1.1

103.0

8.1

12.8

98.0

7.6

12.9

3

Fenpropimorf

90,251.0

6355.8

14.2

4145.4

901.3

4.6

0.0014

0.0011

0.8

89.1

6.2

14.4

84.5

5.4

15.5

4

Tebuthiuron

158,648.0

11,565.6

13.7

14,357.8

3745.1

3.8

0.0017

0.0035

2.1

138.4

8.4

16.5

131.8

7.6

17.3

5

Pirimicarb

83,389.4

6321.4

13.2

6075.1

1095.0

5.5

0.0018

0.0033

1.9

103.3

8.3

12.5

96.6

8.0

12.0

6

Thiodicarb

12,108.9

4552.9

2.7

1945.1

1394.3

1.4

0.0008

0.0038

4.7

79.0

8.4

9.4

67.9

7.6

8.9

7

Prochloraz

12,539.3

860.4

14.6

1458.0

325.5

4.5

0.0025

0.0019

0.8

146.5

6.3

23.4

139.5

5.6

24.8

8

Trifloxystrobine

27,110.8

14,508.9

1.9

5097.9

1948.9

2.6

0.0015

0.0013

0.9

64.5

8.7

7.4

54.9

7.6

7.2

9

Acetamiprid

9723.4

4072.3

2.4

760.9

936.5

0.8

0.0009

0.0025

2.9

77.9

8.9

8.8

43.5

5.1

8.6

10

Thifensulfuron

3673.8

1104.8

3.3

1101.8

1131.0

1.0

0.0016

0.0021

1.3

110.0

6.2

17.8

61.4

3.2

19.3

11

Difenconazole

26,450.9

2598.1

10.2

1562.0

289.6

5.4

0.0028

0.0012

0.4

156.5

8.1

19.3

148.2

6.8

22.0

12

Pyrimethanil

126,667.0

9740.3

13.0

3932.1

624.8

6.3

0.0067

0.0026

0.4

477.4

41.4

11.5

174.1

14.2

12.2

13

Ametryn

135,517.4

12,982.6

10.4

8574.0

1938.1

4.4

0.0015

0.0016

1.1

10.0

7.8

1.3

9.1

7.4

1.2

14

Boscalid

8977.6

1993.3

4.5

1239.9

1846.4

0.7

0.0035

0.0023

0.7

9.8

6.5

1.5

8.7

6.0

1.4

15

Butachlor

2411.1

881.4

2.7

558.0

209.5

2.7

0.0039

0.0039

1.0

11.4

7.1

1.6

10.1

6.3

1.6

16

Carbaryl

4367.4

984.1

4.4

1941.8

1802.8

1.1

0.0025

0.0032

1.3

9.0

7.3

1.2

7.3

6.0

1.2

17

Dimethomorph

10,645.1

3744.8

2.8

1170.0

529.1

2.2

0.0021

0.0024

1.1

11.1

8.6

1.3

8.0

6.6

1.2

18

Hexaconazole

19,375.0

2103.3

9.2

1988.0

642.5

3.1

0.0022

0.0014

0.6

10.2

7.4

1.4

8.5

5.7

1.5

19

Malathion

8435.0

3978.5

2.1

810.4

573.3

1.4

0.0018

0.0020

1.1

9.1

7.4

1.2

8.1

6.8

1.2

20

Propoxur

30,316.1

5095.0

6.0

3457.0

1043.3

3.3

0.0020

0.0014

0.7

9.5

7.6

1.3

7.1

5.8

1.2

21

Spinosad A

1988.8

131.4

15.1

1219.3

190.8

6.4

0.0012

0.0017

1.5

5.3

1.3

4.0

6.1

1.1

5.5

22

Spinosad D

629.5

37.0

17.0

714.3

73.1

9.8

0.0029

0.0043

1.5

5.6

1.0

5.7

6.3

1.1

5.5

23

Spiroxamine

132,853.1

6827.1

19.5

3508.0

384.1

9.1

0.0013

0.0005

0.4

4.8

2.5

1.9

5.9

2.4

2.4

24

Thiabendazole

37,733.9

2049.9

18.4

2945.3

426.4

6.9

0.0018

0.0014

0.8

9.2

6.6

1.4

5.7

4.0

1.4

25

Thiametoxam

359.0

131.9

2.7

65.5

60.6

1.1

0.0008

0.0003

0.3

9.3

7.0

1.3

1.1

0.9

1.2

26

Carbofuran

43,743.4

6717.3

6.5

3314.5

932.3

3.6

0.0021

0.0014

0.6

10.9

7.3

1.5

9.4

5.8

1.6

27

Dimethoate

2782.9

471.5

5.9

610.4

860.8

0.7

0.0004

0.0003

0.7

10.8

7.1

1.5

1.4

0.9

1.6

28

Diuron

20,123.6

4494.9

4.5

1007.4

440.3

2.3

0.0039

0.0019

0.5

10.4

7.7

1.3

9.2

6.8

1.4

29

Ethoprophos

17,230.8

4685.1

3.7

1419.1

531.3

2.7

0.0033

0.0027

0.8

11.2

7.6

1.5

10.7

6.6

1.6

30

Fenamiphos

21,733.9

6209.1

3.5

3486.4

657.9

5.3

0.0027

0.0026

1.0

11.0

9.3

1.2

10.1

8.2

1.2

31

Fenbuconazole

9781.3

1741.5

5.6

2400.5

509.8

4.7

0.0034

0.0043

1.3

10.4

8.3

1.3

9.6

6.8

1.4

32

Fludioxonil

1825.6

106.3

17.2

907.4

80.8

11.2

0.0044

0.0044

1.0

12.5

7.4

1.7

11.7

7.3

1.6

33

Metalaxyl

66,743.8

13,058.8

5.1

3516.1

1616.4

2.2

0.0014

0.0018

1.2

11.3

8.6

1.3

10.3

7.6

1.3

34

Metribuzin

2690.3

181.9

14.8

178.8

19.9

9.0

0.0026

0.0043

1.7

11.2

8.0

1.4

6.2

3.9

1.6

35

Monocrotophos

4944.0

932.3

5.3

918.1

408.5

2.2

0.0003

0.0003

1.0

9.8

7.9

1.2

1.8

1.4

1.3

36

Pendimethalin

984.1

821.0

1.2

78.3

66.8

1.2

0.0035

0.0018

0.5

10.7

7.9

1.4

8.6

5.9

1.5

37

Pyrazosulfuron-ethyl

6984.3

2835.4

2.5

2100.1

860.8

2.4

0.0036

0.0039

1.1

8.8

6.9

1.3

9.8

7.3

1.3

38

Triazophos

44,538.8

10,791.4

4.1

2922.9

1441.1

2.0

0.0023

0.0017

0.7

10.6

9.6

1.1

9.4

8.4

1.1

39

Azoxystrobin

48,719.4

12,878.8

3.8

5734.6

1387.5

4.1

0.0026

0.0015

0.6

11.1

8.1

1.4

9.5

7.1

1.3

40

Bentazon

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

41

Bitertanol

4531.5

460.1

9.8

694.4

170.0

4.1

0.0023

0.0067

2.9

9.2

8.2

1.1

7.8

7.1

1.1

42

Cadusafos

18,517.9

3857.3

4.8

3121.6

833.1

3.7

0.0014

0.0007

0.5

10.9

6.4

1.7

9.6

5.7

1.7

43

Chlorpyrifos

597.9

457.0

1.3

136.1

187.3

0.7

0.0194

0.0037

0.2

13.8

6.3

2.2

12.1

5.1

2.4

44

Cymoxanil

464.5

151.4

3.1

102.6

414.4

0.2

0.0032

0.0022

0.7

12.2

5.4

2.3

3.3

1.5

2.1

45

Iprodione

197.1

31.4

6.3

20.1

76.1

0.3

0.0122

0.0170

1.4

14.0

5.2

2.7

11.9

4.5

2.6

46

Linuron

2092.1

1013.4

2.1

214.1

320.9

0.7

0.0147

0.0051

0.3

14.8

6.6

2.3

17.7

8.8

2.0

47

Oxamyl

3364.3

324.9

10.4

2642.5

397.8

6.6

0.0002

0.0003

2.0

10.5

8.3

1.3

0.9

0.7

1.3

48

Propanil

1207.8

417.9

2.9

59.8

68.6

0.9

0.0076

0.0053

0.7

11.1

6.7

1.7

9.1

6.5

1.4

49

Tebuconazole

27,349.5

3044.4

9.0

1193.3

397.5

3.0

0.0017

0.0027

1.6

10.1

7.2

1.4

8.3

6.1

1.4

50

Terbuthryn

188,905.8

18,208.0

10.4

9758.9

1836.6

5.3

0.0013

0.0020

1.6

10.1

7.6

1.3

8.8

7.0

1.3

51

Thiofanate-methyl

4214.8

201.9

20.9

198.4

21.0

9.4

0.0048

0.0156

3.2

9.7

9.5

1.0

NQ

11.5

NQ

52

Kresoxim-methyl

1257.6

51.4

24.5

378.6

52.4

7.2

0.0065

0.0062

1.0

6.9

8.4

0.8

6.1

6.3

1.0

53

Carbendazim

35,312.5

2477.9

14.3

2611.3

342.4

7.6

0.0011

0.0011

1.0

10.8

8.2

1.3

4.7

3.4

1.4

54

Diazinon

135,234.5

12,429.6

10.9

5428.8

1895.9

2.9

0.0013

0.0013

1.0

9.7

8.0

1.2

8.9

7.3

1.2

55

Imidacloprid

376.1

117.1

3.2

344.8

349.6

1.0

0.0032

0.0025

0.8

9.3

6.8

1.4

3.0

2.1

1.4

56

Imazalil

12,918.6

805.3

16.0

492.9

91.0

5.4

0.0001

0.0003

2.7

1.0

0.5

1.9

0.9

0.4

2.0

57

Metsulfuron-methyl

2809.0

1177.3

2.4

441.6

755.6

0.6

0.0001

0.0009

6.7

0.8

0.8

1.1

0.3

0.3

1.0

58

Profenofos

1208.9

677.4

1.8

429.4

294.4

1.5

0.0049

0.0015

0.3

5.9

3.0

2.0

5.5

2.6

2.1

59

Propiconazole

9666.4

1219.9

7.9

212.3

39.8

5.3

0.0012

0.0023

2.0

9.4

6.7

1.4

8.4

6.1

1.4

60

Pyraclostrobine

45,027.1

9556.0

4.7

2618.3

1309.1

2.0

0.0014

0.0013

1.0

9.3

5.9

1.6

8.3

5.1

1.6

61

Triadimenol

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

62

Terbufos

233.8

36.1

6.5

38.0

11.1

3.4

0.0040

0.0117

2.9

7.2

6.1

1.2

6.4

5.7

1.1

63

Thiacloprid

7616.6

5542.9

1.4

845.9

1548.0

0.5

0.0013

0.0018

1.3

9.5

7.3

1.3

5.4

4.3

1.2

64

Penconazole

19,505.4

2841.9

6.9

3418.8

680.9

5.0

0.0021

0.0008

0.4

9.6

8.9

1.1

6.6

6.1

1.1

65

Pirimiphos-methyl

30,079.6

7913.1

3.8

4094.1

1251.6

3.3

0.0009

0.0025

2.9

9.5

8.5

1.1

6.9

6.1

1.1

66

Tebufenozide

3121.0

893.4

3.5

1481.0

819.3

1.8

0.0047

0.0044

1.0

10.5

10.0

1.0

7.3

7.4

1.0

67

Spirodiclofen

323.6

465.3

0.7

136.5

145.5

0.9

0.0064

0.0041

0.6

11.4

9.3

1.2

7.4

4.7

1.6

68

Cyflufenamid

2032.8

2319.3

0.9

593.5

426.0

1.4

0.0021

0.0027

1.3

10.7

8.0

1.3

11.5

8.4

1.4

69

Temephos

193.6

362.4

0.5

39.0

120.6

0.3

0.0043

0.0067

1.6

9.1

7.6

1.2

6.5

4.6

1.4

70

2,4-D

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

NQ

71

Chlorotoluron

12,152.1

4278.1

2.8

1384.1

791.9

1.7

0.0010

0.0021

2.2

10.1

7.9

1.3

6.4

4.9

1.3

72

Cyanazine

14,965.8

1488.5

10.1

2005.4

1362.6

1.5

0.0007

0.0022

3.1

9.3

8.0

1.2

6.0

5.1

1.2

73

Terbuthylazine

66.1

7.1

9.3

64.0

19.6

3.3

0.0128

0.0228

1.8

10.0

4.3

2.3

6.8

4.0

1.7

74

Propazine

11,310.1

3010.4

3.8

2191.0

1615.1

1.4

0.0014

0.0018

1.3

10.2

7.9

1.3

7.1

5.3

1.3

75

Atrazine

322.9

17.1

18.9

37.4

22.9

1.6

0.0002

0.0004

2.4

9.4

7.4

1.3

0.4

0.3

1.2

76

Simazine

22,136.5

1551.1

14.3

1782.3

1167.0

1.5

0.0011

0.0016

1.4

10.0

7.9

1.3

5.6

4.4

1.3

77

Isoproturon

31,525.8

7624.1

4.1

2502.9

2227.1

1.1

0.0011

0.0012

1.1

10.7

8.6

1.2

7.2

5.5

1.3

78

Fenoxycarb

4857.0

3199.8

1.5

1739.9

856.4

2.0

0.0009

0.0014

1.6

10.2

8.1

1.3

7.1

5.4

1.3

79

Epoxiconazole

24,311.3

3491.6

7.0

1503.5

267.6

5.6

0.0008

0.0009

1.1

9.7

8.7

1.1

6.8

5.8

1.2

80

Benalaxyl

14,008.5

10,303.6

1.4

1258.5

1288.6

1.0

0.0008

0.0005

0.6

9.8

8.3

1.2

7.0

5.6

1.3

81

Hexythiazox

1052.4

1766.6

0.6

702.9

1934.0

0.4

0.0014

0.0009

0.6

10.7

8.4

1.3

7.7

5.7

1.4

Minimum value

66.1

7.1

0.5

20.1

11.1

0.2

0.0001

0.0003

0.2

0.8

0.5

0.82

0.3

0.3

1.0

Maximum value

188,905.8

18,208.0

24.5

14,357.8

3745.1

11.2

0.0194

0.0228

6.7

477.4

41.4

23.38

174.1

14.2

24.8

Average value

25,191.4

3668.992

7.2

2026.4

760.1

3.3

0.0029

0.0030

1.3

28.4

7.6

3.29

20.7

5.4

3.4

p value

0.000001***

0.0000001***

0.359608

0.001379**

0.000170***

US UniSpray ionization, ESI electrospray ionization, NQ not quantified. *, **, and ***t test is significant, highly significant, and very highly significant, respectively

Signal-to-noise ratio

A very highly significant increase of S/N ratio of US over ESI was obtained in all the three matrices (p = 0.00000001 in apple and in coffee, p = 0.0000001 in water). The highest increase of S/N ratio was 18.3 times in apple with spinosad D, 29.4 times in coffee with spinosad D, and 11.2 times in water with fludioxonil. In average, US increased the S/N ratio more than that of ESI by 3.4-fold in apple, 3.8-fold in coffee, and 3.3-fold in water (Table 3). Lubin et al. [14] have observed similar S/N ratios between US and ESI for four out of the five prostaglandins and thromboxane compounds investigated; a distinct increase of S/N ratio with US was obtained for 11-dehydro-thromboxane B(2) (11-dTXB2).

As a result of this increase in S/N ratio with US, more compounds could be detected and quantified at low level. Table 4 presents the distribution of pesticide active ingredients which could not be recovered from pre-extraction spiked samples by using UniSpray and/or electrospray interfaces. Depending on the matrix, while imazalil, triademinol. and methomyl could only be quantified with ESI, US solely could allow the quantification of temephos, thifensulfuron, fludioxonil, bentazon, and kresoxim-methyl. A gain in the range of compounds that can be quantified just by changing the ionization source is an important benefit, especially when multiple residues have to be analyzed in single run.
Table 4

Distribution of the analytes not quantified in all the spiked samples with UniSpray and electrospray interfaces

Matrix

Analyte

UniSpray

Electrospray

Apple

Triademinol

Temephos

Coffee

Thifensulfuron

Fludioxonil

Bentazon

Thiofanate-methyl

Kresoxim-methyl

Imazalil

Triademinol

Terbufos

2,4-D

Water

Methomyl

Bentazon

Triademinol

2,4-D

Total

15

10

12

Ion ratio

No significant difference was found between US and ESI in all the three matrices (see ESM). This can be justified by the similarities in the ionization mechanism of the two interfaces. With US, molecules of the studied pharmaceutical compounds were ionized in a similar fashion to ESI, predominantly producing protonated or deprotonated species. Adduct formation (e.g., proton and sodium adducts) and in-source fragmentation were shown to be almost identical between the two sources [6]. Additionally, the spectra generated when using US closely resemble those from ESI analyses so, although there is no voltage applied to the capillary tip, it is likely that the eluent contains ions formed from solution phase redox reactions and other physical processes. It is also possible that surface-based effects on the US impactor pin, and additional gas phase phenomena, could further contribute to ion formation [13].

Accuracy (%recovery)

The extraction recovery percentage varied largely among the active ingredients and recovery as high as 342.9% was recorded with spinosad D in apple. Pesticides pyrimethanil, spinosad A, spinosad D, and spirodiclofen showed recoveries above 120% in most of the matrices with the two interfaces, while low recoveries were mostly obtained with metsulfuron-methyl and imazalil. As compared with ESI, recovery obtained with US showed a very highly significant increase (p = 0.0000002, 0.001067, and 0.000002 in apple, coffee, and water, respectively), with up to 8.8-fold increase observed in apple (spirodiclofen), up to 10.6-fold increase obtained in coffee (temephos) and up to 6.3-fold increase recorded in water (monocrotophos). However, in average, the gain in recovery percentage with US was 1.4-fold in apple, 1.9-fold in coffee, and 1.5-fold in water (see ESM). High recoveries of spinosad A and D have been previously observed [20] and may result from the ionization of spinosad from reaction with QuEChERS salts that forms a complex with a strong signal enhancement matrix effect.

Precision (%RSD)

For the great majority of analyses, the %RSD remained below the acceptable 20% [23], except bentazon with US, and terbuthylazine, monocrotophos, terbufos, and temephos with ESI. The difference in %RSD between US and ESI was very highly significant for pesticides analyzed in apple (p = 0.0008) and in water (p = 0.0001), and was highly significant for coffee (p = 0.0012). In general, the two interfaces showed equal precision for pesticide residue analyses in apple, and US was 1.7 times more precise than ESI for analyses in coffee (see ESM). Lubin et al. [14] found that US offers a better precision than ESI, for three out of five prostaglandins and thromboxanes in two matrices, human plasma, and pig colon. The high values of %RSD found indicate that these pesticide chemistries favor high variations among repetitions and therefore require more refinement of the protocol for improving within-laboratory reproducibility.

Sensitivity

For the analyses of 81 pesticides in the three matrices, lower LOQs were obtained with US; it ranged between 0.0001 and 0.0333 mg/kg, while it was between 0.0001 and 0.0478 mg/kg with ESI. However, the overall LOD and LOQ did not significantly vary between the two ionization interfaces (Table 3). For analysis of prostaglandins and thromboxanes, Lubin et al. [14] reported that sensitivity was improved for three out of five compounds measured on the UniSpray source, with an increase up to factor 5, probably due to the high signal intensity resulting in saturation phenomena. In our study, we have observed a non-significant factor 1.2 to 1.3 improvement of sensitivity with US, although a rather tremendous increase of signal intensity was obtained with this novel interface.

In fact, the gain in sensitivity with US was clear for some compounds, with improvement of LOQ as high as 8.9 times with thiofanate-methyl in apple and 6.7 times with metsulfuron-methyl in water (Table 3). This can be explained by the gain in signal intensity but this improvement could not be generalized to the total large number of analytes we screened. This clear gain in signal intensity could however result in better accuracy and precision for lower concentrations of analytes, and thus increase the sensitivity of the method. But, better sensitivity is guaranteed only if selectivity is warranted, and thus depends also on the type of mass spectrometer used (e.g., high-resolution MS, MSn, ion mobility capabilities) and the nature of the sample (background) [6]. Further investigation on a broad set of spiked concentrations is needed to draw clear conclusion on the increase in signal intensity and sensitivity observed with US in multiresidue analysis of large number of pesticides.

Matrix effect

Matrix effect values of 100 ± 20% are considered suitable values and indicate a small ME [24]. With US, a strong signal enhancement was mostly observed in apple, the highest values were recorded with fenpropimorf in apple (634.1%), pyrimethanil in apple (616.3%), spinosad A in apple (497.3%), pyrimethanil in water (477.4%), spinosad D in apple (451.4%), and pyrimethanil in coffee (312.2%); most of the other analyses showed ME values below the lowest suitable 80% value. With ESI however, none of the value was found within the suitable range, the signal suppression was more pronounced, and the highest ME values were obtained with pyrimethanil in apple (58.8%), fenpropimorf in apple (45.4%), and pyrimethanil in water (41.4%); all the other analyses showed ME values below 30%. The difference in matrix effect between the two interfaces was highly significant in apple (p = 0.0020) and water (p = 0.0014), and very highly significant in coffee (p = 0.0004) (Table 3). Similar ME values were found by Chawla et al. [17] who showed that MEs were dependent on the nature of both the commodity and the analyte and observed that most of the pesticides showed signal suppression in tomato, capsicum, and cumin matrixes. They also reported very high MEs of 2360.9 and 1250.8% for quizalofop-p-tefuryl and tebuconazole, respectively.

In the case of chromatography coupled with MS, the predominant cause of ME is the presence of undesired components that co-elute in the chromatographic separation and either compete for access to the surface of the droplets and subsequent ion evaporation, or induce changes in eluent properties that are known to affect the ionization process (such as surface tension, viscosity, and volatility) [17]. For most of the analyses in our study, a high signal suppression was observed, but the ME percentages were better with US, suggesting a milder ME with the new interface. In analyzing five pesticides in six matrices, Lucini et al. [25] also observed that ME occurred as ionic suppression and was found in the range of 5 to 22% depending on the compound. For 19 pharmaceutical and biological compounds tested, a quite similar ME was observed between US and ESI, but depending on the matrix and ionization mode, a small but statistically significant lower percentage of ME could be observed for US in plasma and bile in the positive ion mode, and bile in negative ion mode [12]. The difference with our results can be due to the differences of the chemistry of the compounds tested and of the solvents we used.

Recovery efficiency

The RE varied between 1.9 and 150.0% with US, and between 1.7 and 165.5% with ESI. Irrespective of the matrix, with US, the RE percentage of 21% of the analyses was found between the suitable RE values of 100 ± 20%, while with ESI, 24% of the analyses were suitable. A significant difference was found between the RE of US and ESI in apple (p = 0.023259) and water (p = 0.037114), while in coffee, the two interfaces showed no significant difference. But in average, no difference of RE was found between the two interfaces and in the three matrices (see ESM). Lucini et al. [25] found that REs of five pesticides in six matrices were good and substantially comparable, in the range of 93–96%. The extraction recovery measures the efficiency of the analyte extraction process during sample pre-treatment (QuEChERS extraction), and the RE measures the influence of the analyzing instrument on the recovery. This implies that the two interfaces react similarly irrespective of the analyte extraction; hence, the difference of performance will mostly be based on how the interface deals with ME.

Process efficiency

The values of PE related to quantitative determination of pesticide residues followed the same pattern as ME. The PE was higher with US over ESI in almost all the analyses. A 3.9-fold increase was observed in apple and coffee, while the increase was 3.4-fold in water. The observed increase of PE with US was significant in apple (p = 0.0108), highly significant in coffee (p = 0.0051), and very highly significant in water (p = 0.0002) (Table 3). Lucini et al. [25] found more closer values (74% to 90%) of PE for analysis of five pesticides in six matrices and suggested that the differences in terms of overall PE of each compound can be ascribed to different MEs, rather than to poor recoveries due to ineffective extraction efficiencies of the QuEChERS procedure.

In our study, a tentative correlation of the evaluated performance parameters and chemical class of the active ingredients showed no correlation. Similar results were obtained by [14] who observed no correlation between signal increase and chemical structure or physicochemical data of the pharmaceutical compounds analyzed. Also, no correlation could be found between the different gains obtained with ESI or US and the molecular weight, functional groups, pKa, or logP of the studied pharmaceutical compounds. This implies that complex ionization mechanisms are involved with the UniSpray source [6].

Conclusion

This work reports the first results of pesticide residue analysis with UniSpray, a novel API source for LC-MS, in comparison with ESI, for 81 active ingredients of diverse pesticide classes and physicochemical properties, and in three different matrices, apple, coffee, and water. The new source provided comparable and good linearity; it considerably increased the signal intensity and improved the S/N ratio. No significant effects on precision and ion ratio were found. UniSpray also offered a slight gain in the range of compounds that can be quantified, as well as in the recovery percentage. The US allowed a gain in sensitivity for many compounds, but overall, the LOD and LOQ did not significantly vary between the two ionization interfaces. Signal suppression was less pronounced with US, allowing most of the ME values to be within the acceptable range, while it was more prominent with ESI and none of the value was found within the suitable ME range. The ionization sources did not affect the RE, whereas the PE was higher with US in almost all the analyses. The studied performance parameters varied irrespectively to the chemical class of the active ingredients. For a better understanding of applications and benefits of US over ESI, further analysis of pesticides at different spiked concentrations and deep study of the ionization mechanism should be envisaged.

Notes

Acknowledgments

The great laboratory assistance of Lilian Goeteyn is gratefully acknowledged.

Authors’ contributions

Galani Y.J.H. designed the study, wrote the protocol, collected the samples, carried out lab experiments, performed data analysis, and wrote the first manuscript draft. Houbraken M. participated in study design, protocol writing, lab analysis, and data analysis. Van Hulle M. participated in study design and protocol writing and contributed with laboratory equipment. Spanoghe P. provided lab facilities and supervised the entire study. All authors read, checked, and approved the final manuscript.

Funding information

This work was financially supported by Islamic Development Bank’s (IDB) Merit Scholarship for High Technology programme.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

216_2019_1886_MOESM1_ESM.pdf (710 kb)
ESM 1 (PDF 710 kb)
216_2019_1886_MOESM2_ESM.xlsx (138 kb)
ESM 2 (XLSX 138 kb)

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© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.School of Food Science and NutritionUniversity of LeedsLeedsUK
  2. 2.Department of Plants and Crops, Faculty of Bioscience EngineeringGhent UniversityGhentBelgium
  3. 3.Department of Agriculture and Veterinary MedicineUniversité des MontagnesBangangtéCameroon
  4. 4.Waters NV/SAZellikBelgium

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