Application of HR-LC-MS in screening methods for pesticides in cereals Anne Kruse Lykkeberg, Mette Erecius Poulsen Almeria, 12 June 2014.
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Application of HR-LC-MS in screening methods for pesticides in cereals
Anne Kruse Lykkeberg, Mette Erecius PoulsenAlmeria, 12 June 2014
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
No selection
QTOF-analysis – MS scan
No collision
• Used to determine retention time
National Food Institute, Technical University of Denmark
Selection of single mass
QTOF-analysis – Targeted MS/MS
Collision
10, 20 and 40 V
• Obtaining compound spectra for Library• Spectra of daughter ions from the single
ion isolated in the quadropole
National Food Institute, Technical University of Denmark
No selection
QTOF-analysis – All ion MS
Collision
10, 20 and 40 V
• MS scan with collision energy• Screening samples• Spectra of daughter ions of all compounds
eluting on a certain time point
National Food Institute, Technical University of Denmark
Spectra – MSscan incl. collision
0V
10V
20V
40V
Ofurace, [M+H]+
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
Standard mixtures
50-100 pesticidesMixtures
Avoiding isomers in the mixtures
Isomers
2-6 mixtures togetherValidation
National Food Institute, Technical University of Denmark
Spectra of isomers in Agilents libraryLibrary spectrum
m/z
30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 200 205 210 215 220 225 230 235 240 245 250
Ab
un
dan
ce
0
10
20
30
40
50
60
70
80
90
100
110
142.07234100.00 184.1192996.84
226.1662467.74
86.0348915.20100.0505412.10
68.024324.7957.044724.62 152.118231.62
Library spectrum
m/z
30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 200 205 210 215 220 225 230 235 240 245 250
Ab
un
dan
ce
0
10
20
30
40
50
60
70
80
90
100
110
170.10364100.00
226.166246.72114.066185.83 142.072345.31100.050543.8275.055293.1185.076032.24 128.081832.1057.069881.58
Library spectrum
m/z
30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 200 205 210 215 220 225 230 235 240 245 250
Ab
un
dan
ce
0
10
20
30
40
50
60
70
80
90
100
110
170.10364100.00
226.1662441.95
100.0505410.48114.066189.97 142.072349.5875.055294.9686.034894.38 128.081834.1257.069882.73
N
N
N
NHNH CH3
CH3
CH3
CH3
OCH3
N
N
N
NHNH CH3
CH3
CH3
OCH3
CH3
N
N
N
NHNH
CH3
CH3
OCH3
CH3
Prometon
Terbumeton
Secbumeton
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
Validation• My alternative validation plan• 20-25 samples – spiked at 0.1 mg/kg• 10-20 blank samples
Spiked – 0.1 mg/kg
Blank
Rice 5 5Oat 5 5Barley 5 5Wheat 5 5Rye 5 5
National Food Institute, Technical University of Denmark
Dilution of spiked samples
Spiked rye is diluted with Blank rye …
Matrix is the sameRecovery is assumed to be the same at the different concentration levels
Rye 0.1 mg/kg Blank
0.10 mg/kg 1000 µl -
0.02 mg/kg 200 µl 800 µl
0.01 mg/kg 100 µl 900 µl
Blank - 1000 µl
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
Comparison of areas in spiked samples with blank
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
Virtual computers for data-analysisChallenges• The Agilent software demands Windows Professional 64 bit
– english version• Back up of all laboratory computer on LAB-domain• Laboratory domain, with no access from personal
computers
Solution• Virtual computers from Citrix
– On the Laboratory domain– Windows Professional 64 bit– Access to all data – back up early in the morning– Few licenses are necessary– Access from all computers with internet
National Food Institute, Technical University of Denmark
Disposition
Analysis at the instrument
Standard mixtures
Validation plan
Validation
Virtual computers – for data treatment
Sample preparation of cereals – QuEChERS
National Food Institute, Technical University of Denmark
FVII cocktail IV – project• Aim is to develop a cereal-method to analyze many
analytes in one method.
• Analytes:– Pesticides (The pesticides most present in cereal – in practice
the standard mixtures which we use for our quantitative methods).
– Mycotoxins: Most important mycotoxins in cereals.
National Food Institute, Technical University of Denmark
Method development - QuEChERS
• Water• AcetonitrileExtraction
• Magnesium sulphate• NaCl, Citrate buffer
Phase separation
• 1 h at -80 ºC• Centrifugation
Freeze out step
• PSA • Magnesium sulphatePSA clean up
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 18 200
200
400
600
800
1000
1200
1400
1600
Positive mode
Pos blank 1
Retention time
m/z
Extraction
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 18 200
200
400
600
800
1000
1200
Positive mode
Pos blank 1Pos blank 2
Retention time
m/z
Phase separation
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 18 200
200
400
600
800
1000
1200
Positive mode
Pos blank 1Pos blank 2Pos blank 3
Retention time
m/z
Freeze out step
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 18 200
200
400
600
800
1000
1200
1400
1600
Positive mode
Pos blank 1Pos blank 2Pos blank 3Pos blank 4
Retention time
m/z
PSA clean up
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 18 200
200
400
600
800
1000
1200
1400
1600
Positive mode
Pos blank 1Pos blank 2Pos blank 3Pos blank 4MycotoxinsPesticides
Retention time
m/z
Analytes
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 180
100
200
300
400
500
600
700
800
Negative mode
Neg blank 1
Retention time
m/z
Extraction
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 180
100
200
300
400
500
600
700
800
Negative mode
Neg blank 1Neg blank 2
Retention time
m/z
Phase separation
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 180
2
4
6
8
10
12
Negative mode
Neg blank 1Neg blank 2Neg blank 3
Retention time
m/z
Freeze out step
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 180
100
200
300
400
500
600
700
Negative mode
Neg blank 1Neg blank 2Neg blank 3Neg blank 4
Retention time
m/z
PSA clean up
National Food Institute, Technical University of Denmark
0 2 4 6 8 10 12 14 16 180
100
200
300
400
500
600
700
800
Negative mode
Neg blank 1Neg blank 2Neg blank 3Neg blank 4MycotoxinsPesticides
Retention time
m/z
Analytes
National Food Institute, Technical University of Denmark
TIC af blank i positiv mode
7x10
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
3
3.2
3.4
3.6
3.8
4
4.2
4.4
4.6
4.8
5
5.2
5.4+ESI TIC Scan pos_Blank4.d
2
Counts vs. Acquisition Time (min)1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.5 17 17.5 18
National Food Institute, Technical University of Denmark
TIC af blank i positiv mode
7x10
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
3
3.2
3.4
3.6
3.8
4
4.2
4.4
4.6
4.8
5
5.2
5.4+ESI TIC Scan pos_Blank4.d
Counts vs. Acquisition Time (min)6.6 6.8 7 7.2 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 12 12.2 12.4 12.6 12.8
National Food Institute, Technical University of Denmark
TIC af blank i negativ mode
7x10
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
2.2
2.3
2.4
2.5
2.6-ESI TIC Scan neg_Blank4.d
1 1 2 2
Counts vs. Acquisition Time (min)0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5
National Food Institute, Technical University of Denmark
TIC af blank i negativ mode
7x10
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
2.2
2.3
2.4
2.5
2.6-ESI TIC Scan neg_Blank4.d
Counts vs. Acquisition Time (min)6 6.2 6.4 6.6 6.8 7 7.2 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8 10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 12 12.2 12.4 12.6 12.8 13
National Food Institute, Technical University of Denmark
Matrix effect & recovery – Mycophenol acid• Mycophenol acid• 6.63 min• Mass: 320.1260
Recovery Matrix effect
PSA 7 106
Freeze out 114 153
Phase separation 105 149
Extraction 123 159
National Food Institute, Technical University of Denmark
Matrix effect & recovery – Fumonisin B2• Fumonisin B2• 5.07 min • Mass: 705.3936
Recovery Matrix effect
PSA 6 111
Freeze out 36 151
Phase separation 73 166
Extraction 76 153
National Food Institute, Technical University of Denmark
Matrix effect & recovery – Roquefortin C• Roquefortin C• 5.15 min • Mass: 389.1852
Recovery Matrix effect
PSA 92 75
Freeze out 92 41
Phase separation 101 38
Extraction 153 31
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