1. automotive and vehicles
2. vehicle brands
3. peugeot

Using Deconvolution to
Improve GC/MS
Detection and
Quantitation
E-Seminar, October 19th, 2010
2 pm, EST (11 am PST)
Chinkai (Kai) Meng, Ph.D.
Senior Applications Chemist
Wilmington, Delaware USA
chin_meng@agilent.com
Outline
• Introduction
• Deconvolution - Find Trace Compounds in Complex Matrices
• Deconvolution - Quantitation
• Summary
E-seminar, October 2010
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Introduction
• Instrument sensitivity (e.g., signal-to-noise ratio) is usually
determined by the amount of sample injected and the responses
from the detector. We will discuss sensitivity from a different view.
• In a multi-residue analysis, the data reviewing process is also very
important in confirming the hits found by the software and reviewing
the integration/quantitation for accuracy.
• Deconvolution has been proven to be a powerful data processing
tool in finding trace compounds in complex matrices. In this study,
results from Deconvolution (AMDIS) is closely looked at and
compared to the results from ChemStation. The goal is to
determine if Deconvolution can provide better results (sensitivity)
than the routine ChemStation data processing.
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What is Deconvolution?
Deconvolution is a process (tool) to extract ions from a complex
full-scan total ion chromatogram (TIC), even with the target
compound signal at trace level. The software used for this
technique is AMDIS (Automated Mass spectral Deconvolution
and Identification System) developed by NIST (National Institute
of Standards and Technology).
Magic Eye
3-D movie
Information is there, you just need the right tool to see it.
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GC/MSD Deconvolution – What it can do.
From here…
GC/MSD in Scan Mode
Deconvolution Reporting Software
Quant on Deconvoluted Peaks
…to here in 2 - 3 min
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Extracted Ion Chromatograms of a Pear Extract
Ion 41
Ion 42
Ion 43
Ion 55
Ion 56
Ion 57
Ion 98
Ion 99
Ion 116
Ion 131
Ion 154
Ion 248
10
15
20
25
30
35
40
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How Does Deconvolution Work?
Eliminate Ions that Do Not Fit the Criteria
160 shape
50
same shape and
17
same retention
0
28
time
0 185 shape & early retention
75time
late retention
time
310
early retention
time
Deconvolution
Spectrum at dotted line
50
75
17 18
160 5
28
0
0
31
0
Two criteria:
1. Same RT
2. Same peak shape
Spectrum at dotted line (a component)
50
17
0
28
0
These
deconvoluted ions
are group together
50
17
0
28
0
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More than
370 peaks
found
TIC of
Spinach
Extract
5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00
Deconvolution
Components
Search RTL Pesticide Library for hits
Page 8
E-seminar, October 2010
Comparison of Raw,
Deconvoluted and Library
Spectra
Scan at 10.776 min
Deconvoluted/extracted
spectrum
A component in the
scan above.
Library spectrum
Fenbuconazole
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Sample and Instruments
• Spinach extract prepared using QuEChERS protocol
• 35 pesticides spiked into spinach extract at 50 ppb (pg/uL)
each
• 7890 GC, Multimode Inlet (MMI), 2-µL cold splitless injection
• 7693 Automatic Liquid Sampler (ALS)
• 5975 MSD in full-scan mode (45 - 550 amu)
Acknowledgement
The author would like to thank Dr. Jon Wong
(FDA-CFSAN, College Park, Maryland) for
graciously providing samples for this study.
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Typical TIC of Spinach Extracts
(in Toluene, 35 pesticides spiked at 50 ppb)
3.8e+07
3.4e+07
3e+07
2.6e+07
2.2e+07
1.8e+07
1.4e+07
1e+07
6000000
2000000
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
TIC: Grp1_spinach_50ppb_cold_SL_ramp3_1.D\data.ms
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MSD ChemStation “Edit Compound” Screen
This screen shows the quantitation
database for locating and then
confirming a compound.
In ChemStation, the target
compound identification is based
on 4 ions and three ion ratios.
However, the target compound
identification in AMDIS was based
on the full spectral library match
which is more dependable.
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AMIDS “Identification” Settings
The minimum match
factor was set to 30
and the retention time
window was limited to
±30 seconds to qualify
the hits from the
retention-time library
search.
Typical RT window is
±10-15 seconds.
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AMIDS “Deconvolution” Settings (1 of 2)
Assumed component width in scans.
Increase this if all peaks are wider.
Masses listed here will not be used as
models but can still be included in a
component.
A closely eluting large ion will be
subtracted to allow more models to be
considered. None yields the fastest
processing, two the slowest.
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AMIDS “Deconvolution” Settings (2 of 2)
Higher resolution will separate closer
eluting peaks finding more
components – runs slower
Higher sensitivity will find smaller,
noisier components but maybe more
false positives – runs slower
Higher requires that EICs have exactly
the same shape – fewer components
found and more “uncertain” peaks may
be present.
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Comparison of Match Factors with AMDIS Settings
100
Adjacent peak subtraction (1 or 2) and Sensitivity (VH or H)
90
80
70
60
50
1 H VH M
40
2 H VH M
1HHM
2HHM
30
20
10
0
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Resolution = H, Sensitivity = H, Peak Shape = M
Chlorpyrifos Methyl
Net = 94
Methyl Parathion
Net = 92
25 standards mixture
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Resolution = M, Sensitivity = H, Peak Shape = M
Chlorpyrifos Methyl
Net = 89
Methyl Parathion
Net = 37
25 standards mixture
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Comparison of Number of Compounds Found with
Various AMDIS Settings (Spinach Extract, MF = 30)
Changing Resolution only
M 31
H
M
35
Changing Sensitivity
only
H
35 VH
M
H
H
33 H
H
H
M
Changing Shape Requirement only
H
M 33
M
H
H
L 32
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35 Targets @ 50 ppb in Spinach
ChemStation Results
120
AMDIS Results
110
100
88
80
83
72
73
60
49
40
20
11
35
17
6
12
20
35
35
19
35
0
50%
Relative
30%
Relative
50%
Absolute
30%
1 H VH M
2 H VH M
Absolute
ChemStation Settings
False Positive
1HH M
AMDIS Settings
2HH M
Actual Targets Found
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35 Targets @ 50 ppb in Spinach
ChemStation Results
120
AMDIS Results
110
100
88
80
83
72
73
60
49
40
20
11
35
17
6
12
20
35
35
19
35
0
50%
Relative
30%
Relative
50%
Absolute
30%
1 H VH M
2 H VH M
Absolute
ChemStation Settings
False Positive
1HH M
AMDIS Settings
2HH M
Actual Targets Found
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Deconvolution (AMDIS) Helps to Find all Compounds
in a Complex Matrix.
Will Deconvolution Help in Quantitation?
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Deconvolution Advantage – no baseline drift, noise-free,
easier to integrate for more reliable quantitation results
Ion 123
Ion 171
Ion 128
Ion 143
AMDIS
14000
12000
|
10000
|
8000
|
14.079
14.078
6000
|
4000
|
2000
|
0
13.60
13.70
13.80
13.90
14.00
14.10
14.20
14.30
Deconvolution shows
a flat baseline
Deconvolution is fully integrated in MSD ChemStation.
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Deconvolution Advantage – finds the correct peak
3500
Ion 147
Ion 76
Ion 104
Ion 103
AMDIS
3000
2500
2000
|
3.873
4.067
|
|
1500
|
1000
|
500
0
|
3.50
|
3.60
3.70
3.80
Depending on the ion-ratio
criteria (relative or absolute),
peaks might be incorrectly
identified by ChemStation.
3.90
4.00
4.10
(79) Phthalimide
4.069min (+0.079) 0.07
response 62142
Ion
Exp% Act%
147.00
100
100
76.00
60.50
48.95
104.00
57.30
14.64
103.00
28.80
35.45
4.20
AMDIS: 0.04
AMDIS: 36450
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ChemStation could not discriminate co-eluting signals,
Deconvolution isolates the target signal from the matrix
12.482
50000
|
40000
|
30000
|
20000
|
10000
| 12.303
0
|
11.70
Ion 175
Ion 177
Ion 258
Ion 260
AMDIS
|
|
11.90
12.10
12.30
Zoom in
7000
12.50
12.70
A factor of 150x !
12.482
6000
5000
4000
3000
12.303
2000
1000
0
||
11.70
|
|
11.90
12.10
12.30
12.50
12.70
(604) Oxadiazon
12.486min (+0.277) 9.89
response 8806390
Ion
Exp% Act%
175.00
100
100
177.00
64.50
73.85
258.00
53.10
0.96#
260.00
35.20
6.05
AMDIS: 0.06
AMDIS: 55432
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Summary
• Deconvolution (AMDIS) finds more target compounds than
ChemStation does with fewer false positives in a complex
matrix. (Improved sensitivity?) This minimizes the time an
analyst must spend reviewing results.
• Deconvolution provides a cleaned peak to be integrated
properly for more reliable results. (Improved sensitivity?)
Using Deconvolution to Improve
GC/MS Detection and Quantitation
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References
• Christopher P. Sandy, “A Blind Study of Pesticide Residues in Spiked and Unspiked Fruit
Extracts Using Deconvolution Reporting Software”Agilent Technologies publication, 59891654EN, October 2006
• M. Anastassiades, S. J. Lehotay, D. Stajnbaher, and F. J. Schenck, “Fast and Easy
Multiresidue Method Employing Acetonitrile Extraction/Partitioning and ‘Dispersive SolidPhase Extraction’ for the Determination of Pesticide Residues in Produce,” 2003, J. AOAC Int,
86:412–431
• S. J. Lehotay, K. Maštovská, and A.R. Lightfield, “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,” 2005, J. AOAC Int, 88:615–629
• Philip L. Wylie, “Screening for 926 Pesticides and Endocrine Disruptors by GC/MS with
Deconvolution Reporting Software and a New Pesticide Library,” Agilent Technologies
publication, 5989-5076EN, April 2006
• Chin-Kai Meng and Mike Szelewski, “Replacing Multiple 50-Minute GC and GC-MS/SIM
Analyses with One 15-Minute Full-Scan GC-MS Analysis for Nontargeted Pesticides
Screening and >10x Productivity Gain” Agilent Technologies publication, 5989-7670EN,
December 2007
• Chin-Kai Meng and Mike Szelewski , “Can Deconvolution Improve GC/MS Detectability?”,
Agilent Technologies publication, 5990-5052EN, January 2010.
E-seminar, October 2010
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