An Improved Global Method for the Quantitation

An Improved Global Method for the
Quantitation and Characterization of Lipids by
High Performance Liquid Chromatography and
Corona Charged Aerosol Detection
Marc Plante, Bruce Bailey, and Ian N. Acworth
Thermo Fisher Scientific, Chelmsford, MA, USA
Thermo Fisher Scientific, Chelmsford, MA, USA
Overview
Purpose: To develop an improved global HPLC method for the high-resolution
characterization and quantitation of a variety of lipids from different lipid classes.
Method: A ternary gradient HPLC method, using the Thermo Scientific™
Accucore™ C18 HPLC column, and the Thermo Scientific™ Corona™ ultra RS™
charged aerosol detector is outlined.
Results: The global method was evaluated for selectivity, calibration, sensitivity, and
precision. Five different lipid classes were analyzed demonstrating the selectivity of the
method, and calibration curves over four orders of magnitude were created. For
examples, two oil samples were analyzed.
Introduction
Methods
Standard and Sample Preparation
Stock standards were generally prep
methanol/chloroform (1:1). More chl
compounds (large paraffins).
Samples were dissolved at 10 mg/m
or methanol/tetrahydrofuran (1:1), de
10,000 g for 3 minutes to clarify.
Liquid Chromatography
HPLC System:
Lipids constitute a wide variety of compounds and for convenience can be classified
based on their chemical structure (e.g., fatty acids, triglycerides, waxes, steroids,
phospholipids etc). Lipids play numerous important roles including biological
(e.g., for fuel storage, insulation, and membrane structure), industrial (e.g., lubricants
and fuels), and cooking. One of the most common methods used to measure lipids
is gas chromatography, with many of the lipids requiring derivatization prior to
separation and detection. Another approach uses high performance liquid
chromatography (HPLC), but their lack of a chromophore leaves lipids unresponsive
to detection by the most common HPLC detector, ultraviolet absorbance. HPLC also
can be used with universal detectors, such as evaporative light scattering (ELS), but
lack of sensitivity, poor linearity, and a narrow dynamic range are often too limiting.
The previous version of this method lacked resolution of triglycerides, which is now
improved using the method presented here.
To overcome the poor resolution of triglycerides lipids were separated on an
Accucore C18, a solid core column, using a ternary gradient and then measured using
a Corona ultra RS charged aerosol detector. This approach was capable of resolving
and detecting numerous classes of lipids (esters, all acylglycerols, fatty alcohols and
acids, and paraffins) in a single analysis with only simple dilution as a sample
pretreatment.
Thermo Sci
pump, WPS
oven
HPLC Column:
Accucore C
Column Temperature:
40 °C
Mobile Phase A:
Methanol/w
Mobile Phase B:
Tetrahydrof
Mobile Phase C:
Acetone/ac
Flow Rate:
1.0–1.5 mL
Injection Volume:
2–10 µL
Detector:
Corona ultra
Nebulizer Temperature: 15 °C
Filter:
3
Data Rate:
10 Hz
Power Function:
1.00
Flow Gradient:
Time (min)
Flow
(mL
-10
1
0
1
20
1
35
1
60
1
65
1
The Corona ultra RS detector provides the most sensitive and most uniform response
factors of all universal HPLC detectors. As shown in the system schematic in Figure 1,
it uses nebulization to form droplets that are then dried to particles. Particles are
charged and measured using an electrometer. This mechanism enables detection
at single-digit nanogram on-column. Since the mobile phase requirements for the
charged aerosol detector are similar to those for mass spectrometry (MS), the same
separation methods can be used with MS for peak identification.
Data Analysis
All HPLC chromatograms were obtai
Dionex™ Chromeleon™ Chromatog
A complete lipid composition of samples can now be generated using a single HPLC
method. The method was used to characterize complex oil samples, such as algal oil
and emu oil.
Results
FIGURE 1. Schematic and functioning of charged aerosol detection
1
10
3
2
8
4
6
5
7
9
1.
2.
3.
4.
5.
6.
7.
Liquid eluent enters from HPLC system
Pneumatic nebulization occurs
Small droplets enter drying tube
Large droplets exit to drain
Dried particles enter mixing chamber
Gas stream passes over corona needle
Charged gas collides with particles and
charge is transferred
8. High mobility species are removed
9. Charge is measured by a highly sensitive
electrometer
10. Signal transferred to chromatographic
software
Calibrations
Calibration curves were generated u
analyzed in triplicate. The data were
on inverted axes (amount on the y-ax
correlations for second-order polynom
quadratic fits were performed for am
(ng o.c.) for paraffins, fatty alcohols,
of linear fits was provided using the f
are used to internally correct for the
Chromatograms of these four classe
were resolved within their group as w
demonstrating the specificity of the m
Fitted, quadratic calibration curves fo
calibration curves for the fatty acids,
is shown in Figure 4. The spread of a
of differences in analyte volatility. Sin
particles passing through the detecto
is produced, and therefore less respo
The results of the quadratic calibratio
time, limit of quantitation (LOQ) base
calibration over the entire dynamic ra
calibration.
2 An Improved Global Method for the Quantitation and Characterization of Lipids by High Performance Liquid Chromatography and Corona Charged Aerosol Detection
entific, Chelmsford, MA, USA
or selectivity, calibration, sensitivity, and
nalyzed demonstrating the selectivity of the
ers of magnitude were created. For
s and for convenience can be classified
acids, triglycerides, waxes, steroids,
portant roles including biological
ane structure), industrial (e.g., lubricants
mmon methods used to measure lipids
ds requiring derivatization prior to
uses high performance liquid
chromophore leaves lipids unresponsive
ector, ultraviolet absorbance. HPLC also
s evaporative light scattering (ELS), but
w dynamic range are often too limiting.
esolution of triglycerides, which is now
des lipids were separated on an
ternary gradient and then measured using
This approach was capable of resolving
ters, all acylglycerols, fatty alcohols and
only simple dilution as a sample
most sensitive and most uniform response
hown in the system schematic in Figure 1,
then dried to particles. Particles are
er. This mechanism enables detection
he mobile phase requirements for the
e for mass spectrometry (MS), the same
r peak identification.
now be generated using a single HPLC
ze complex oil samples, such as algal oil
of charged aerosol detection
9
1.
2.
3.
4.
5.
6.
7.
Liquid eluent enters from HPLC system
Pneumatic nebulization occurs
Small droplets enter drying tube
Large droplets exit to drain
Dried particles enter mixing chamber
Gas stream passes over corona needle
Charged gas collides with particles and
charge is transferred
8. High mobility species are removed
9. Charge is measured by a highly sensitive
electrometer
10. Signal transferred to chromatographic
software
Samples were dissolved at 10 mg/mL concentration in either methanol/chloroform (1:1)
or methanol/tetrahydrofuran (1:1), depending on solubility. Samples were centrifuged at
10,000 g for 3 minutes to clarify.
185
pA
175
75
HPLC System:
25
Flow Rate
(mL/min)
%A
%B
%C
-10
1.0
90
10
0
0
1.0
90
10
0
20
1.5
15
85
0
35
1.5
2
78
20
60
1.5
2
3
95
65
1.0
90
10
0
22
11 12
100
50
Time (min)
20
125
Liquid Chromatography
Thermo Scientific™ Dionex™ UltiMate™ 3000 DGP-3600RS
pump, WPS-3000RS autosampler, and TCC-3000RS column
oven
HPLC Column:
Accucore C18, 2.6 µm, 3.0 × 150 mm
Column Temperature:
40 °C
Mobile Phase A:
Methanol/water/acetic acid (600:400:4)
Mobile Phase B:
Tetrahydrofuran/acetonitrile (50:950)
Mobile Phase C:
Acetone/acetonitrile (900:100)
Flow Rate:
1.0–1.5 mL/min
Injection Volume:
2–10 µL
Detector:
Corona ultra RS
Nebulizer Temperature: 15 °C
Filter:
3
Data Rate:
10 Hz
Power Function:
1.00
Flow Gradient:
21
150
15 16
14
0
17
10 19
18
9
13
-25
2
8
1
-50
-75
-85
0.0
5.0
10.0
15.0
20.0
25.0
30.0
FIGURE 3. Second-order polynomial f
injected in triplicate
12000
10000
Amount on Column (ng)
using the Thermo Scientific™
rmo Scientific™ Corona™ ultra RS™
Standard and Sample Preparations
Stock standards were generally prepared at a concentration of 10 mg/mL in
methanol/chloroform (1:1). More chloroform was used (up to 1:3) for more hydrophobic
compounds (large paraffins).
Data Analysis
All HPLC chromatograms were obtained and compiled using Thermo Scientific™
Dionex™ Chromeleon™ Chromatography Data System software, 7.1 SR 1.
8000
6000
4000
2000
0
Results
0
20
40
60
Peak Area (pA
Calibrations
Calibration curves were generated using standard solutions (prepared as above), and
analyzed in triplicate. The data were fit to second-order polynomials using data plotted
on inverted axes (amount on the y-axis, peak area on the x-axis), as it provides for better
correlations for second-order polynomial fits on Corona detector data. Calibrations using
quadratic fits were performed for amounts ranging from 10 to 10,000 ng on column
(ng o.c.) for paraffins, fatty alcohols, fatty acids, esters, and acylglycerides. An example
of linear fits was provided using the fatty acids with different power function values, which
are used to internally correct for the curvature of the charged aerosol response curves.
Chromatograms of these four classes of lipids are shown in Figure 2. All of the analytes
were resolved within their group as well as between analytes in different groups,
demonstrating the specificity of the method.
Fitted, quadratic calibration curves for seven paraffins are shown in Figure 3, and linear
calibration curves for the fatty acids, each with its indicated power function value (PFV),
is shown in Figure 4. The spread of analyte response seen in these figures is the result
of differences in analyte volatility. Since the Corona detector responds to mass of analyte
particles passing through the detector, the more volatile an analyte, the less particle mass
is produced, and therefore less response.
The results of the quadratic calibrations are provided in Table 1, including analyte retention
time, limit of quantitation (LOQ) based on a signal-to-noise ratio of 10.0, precision of
calibration over the entire dynamic range, and the correlation coefficient for each analyte
calibration.
FIGURE 4. Linear calibration plots for
using power function values (PFV).
5
4.5
4
3.5
Peak Area (pA*min)
PLC method for the high-resolution
of lipids from different lipid classes.
FIGURE 2. Overlays of HPLC-Corona
fatty alcohols, fatty acids, and esters,
Methods
3
2.5
2
1.5
1
0.5
0
0
1000
2000
3000
Thermo Scientific Poster Note • PN70533_e 03/13S 3
4000
Amount on Col
FIGURE 2. Overlays of HPLC-Corona detector chromatograms of paraffins,
fatty alcohols, fatty acids, and esters, at 2500 ng o.c.
s
pared at a concentration of 10 mg/mL in
loroform was used (up to 1:3) for more hydrophobic
185
pA
175
20
125
L concentration in either methanol/chloroform (1:1)
epending on solubility. Samples were centrifuged at
11 12
100
75
15 16
50
ientific™ Dionex™ UltiMate™ 3000 DGP-3600RS
S-3000RS autosampler, and TCC-3000RS column
C18, 2.6 µm, 3.0 × 150 mm
17
10 19
25
14
0
18
9
4
6
7
2
8
1
-50
-75
-85
0.0
5
3
13
-25
water/acetic acid (600:400:4)
uran/acetonitrile (50:950)
etonitrile (900:100)
/min
22
Compound
Peaks
12.Eicosanol
13.Lauricacid
14.Myristicacid
15.Palmiticacid
16.Oleicacid
17.Steariccid
a
18.Methyldodecanoate
19.Ethylhexadecanoate
20.Methyloctadecanoate
21.Ethylnonadecanoate
22.Methylhexacosonate
1.Octadecane
2.Eicosane
3.Docosane
4.Tetracosane
5.Hexacosane
6.Octacosane
7.Triacontane
8.Dodecanol
9.Tetradecanol
10.Hexadecanol
11.Octadecanol
21
150
TABLE 1. Calibration data for five
min
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
55.0
60.0
65.0
FIGURE 3. Second-order polynomial fits for paraffins, from 10 to 10,000 ng o.c.,
injected in triplicate
a RS
12000
%A
%B
%C
1.0
90
10
0
1.0
90
10
0
1.5
15
85
0
1.5
2
78
20
1.5
2
3
95
1.0
90
10
0
10000
Amount on Column (ng)
w Rate
L/min)
1. Octadecane
2. Eicosane
3. Docosane
4. Tetracosane
5. Hexacosane
6. Octacosane
7. Triacontane
8. Dodecanol
9. Tetradecanol
10. Hexadecanol
11. Octadecanol
12. Eicosanol
13. Lauric acid
14. Myristic acid
15. Palmitic acid
16. Oleic acid
17. Stearic acid
18. Methyl dodecanoate
19. Ethyl hexadecanoate
20. Methyl octadecanoate
21. Ethyl nonadecanoate
22. Methyl hexacosonate
Monostearin
1,3-Distearin
Tristearin
2
3
3
3
4
4
4
1
1
1
1
2
1
1
1
1
1
1
2
2
2
1
3
5
Sample Results
8000
Octadecane
Eicosane
Docosane
6000
Tetracosane
Hexacosane
4000
Samples of algal oil and emu oil wer
analyzed. Algal oil, an important sou
proved to be a complex sample, as
overlay of stearylglycerols shows th
method provides high resolution thro
chromatogram, the triglyceride regio
Octacosane
Triacontane
ined and compiled using Thermo Scientific™
raphy Data System software, 7.1 SR 1.
Ret
Tim
2000
FIGURE 5. HPLC-Corona detector
methanol/chloroform (1:1) and the
250
pA
225
0
0
20
40
60
80
100
120
140
200
Peak Area (pA*min)
175
es of lipids are shown in Figure 2. All of the analytes
well as between analytes in different groups,
method.
or seven paraffins are shown in Figure 3, and linear
each with its indicated power function value (PFV),
analyte response seen in these figures is the result
nce the Corona detector responds to mass of analyte
or, the more volatile an analyte, the less particle mass
onse.
ons are provided in Table 1, including analyte retention
ed on a signal-to-noise ratio of 10.0, precision of
ange, and the correlation coefficient for each analyte
FIGURE 4. Linear calibration plots for free fatty acids, from 10 – 5000 ng o.c.,
using power function values (PFV).
150
Di
125
100
5
75
4.5
PFV 1.75, r2=0.9989
4
25
PFV 1.75, r2=0.9992
PFV 1.45, r2=0.9969
3
0
Lauric
PFV 1.75, r2=0.9989
2.5
Myristic
Linolenic
Palmitic
2
Oleic
PFV 1.05, r2=0.9990
1.5
Stearic
1
0.5
0
0
1000
2000
3000
4000
Amount on Column (ng)
5000
6000
7000
Monostearin
50
PFV 1.65, r2=0.9972
3.5
Peak Area (pA*min)
using standard solutions (prepared as above), and
fit to second-order polynomials using data plotted
xis, peak area on the x-axis), as it provides for better
mial fits on Corona detector data. Calibrations using
mounts ranging from 10 to 10,000 ng on column
fatty acids, esters, and acylglycerides. An example
fatty acids with different power function values, which
curvature of the charged aerosol response curves.
8000
-20
0.0
5.0
10.0
15.0
20.0
25.0
Emu oil, with a number of purported
(TAG). A sample of AEA-certified (Am
analyzed, and the chromatogram is
integrated and compared against em
The triglycerides are grouped togeth
ECN is the value calculated by 2Cthe number of double bonds in a TA
lower amounts of TAG (ECN 50) are
detector response of this experimen
larger than at higher amounts (provi
4 An Improved Global Method for the Quantitation and Characterization of Lipids by High Performance Liquid Chromatography and Corona Charged Aerosol Detection
etector chromatograms of paraffins,
t 2500 ng o.c.
TABLE 1. Calibration data for five lipid classes by quadratic fits using inverted axes
Compound
Peaks
12.Eicosanol
13.Lauricacid
14.Myristicacid
15.Palmiticacid
16.Oleicacid
17.Steariccid
a
18.Methyldodecanoate
19.Ethylhexadecanoate
20.Methyloctadecanoate
21.Ethylnonadecanoate
22.Methylhexacosonate
1.Octadecane
2.Eicosane
3.Docosane
4.Tetracosane
5.Hexacosane
6.Octacosane
7.Triacontane
8.Dodecanol
9.Tetradecanol
10.Hexadecanol
11.Octadecanol
4
5
3
6
7
min
35.0
40.0
45.0
50.0
55.0
60.0
65.0
s for paraffins, from 10 to 10,000 ng o.c.,
1. Octadecane
2. Eicosane
3. Docosane
4. Tetracosane
5. Hexacosane
6. Octacosane
7. Triacontane
8. Dodecanol
9. Tetradecanol
10. Hexadecanol
11. Octadecanol
12. Eicosanol
13. Lauric acid
14. Myristic acid
15. Palmitic acid
16. Oleic acid
17. Stearic acid
18. Methyl dodecanoate
19. Ethyl hexadecanoate
20. Methyl octadecanoate
21. Ethyl nonadecanoate
22. Methyl hexacosonate
Monostearin
1,3-Distearin
Tristearin
Retention
Time (min)
LOQ
(ng o.c.)
Calibration
RSD (%)*
28.05
31.34
34.56
37.56
40.49
43.27
45.88
11.07
14.10
16.80
19.17
21.32
6.99
10.15
13.09
13.38
15.73
17.22
18.66
20.66
25.62
28.48
14.42
32.85
50.60
225
80
33
25
20
20
20
1515
35
10
2
2
190
10
5
3
1
300
40
10
4
4
20
20
18
1.75
1.99
1.90
2.66
2.91
2.55
2.78
3.37
5.90
5.49
7.21
8.73
4.94
2.52
2.08
1.65
2.79
1.98
6.03
4.11
3.29
2.87
2.03
5.33
2.35
Quadratic
Correlation
Coeff. (r2)
0.9998
0.9998
0.9999
0.9997
0.9997
0.9998
0.9997
0.9996
0.9990
0.9990
0.9979
0.9967
0.9984
0.9997
0.9998
0.9999
0.9997
0.9998
0.9985
0.9994
0.9996
0.9997
0.9998
0.9998
0.9995
Sample Results
Octadecane
Eicosane
Docosane
Tetracosane
Hexacosane
Samples of algal oil and emu oil were prepared and 5 µL aliquots were injected and
analyzed. Algal oil, an important source of a variety of lipids and other compounds,
proved to be a complex sample, as the shown in the chromatogram in Figure 5. An
overlay of stearylglycerols shows the position of highly retained acylglycerols. The
method provides high resolution throughout the chromatogram. As can be seen in this
chromatogram, the triglyceride region is also highly resolved.
Octacosane
Triacontane
FIGURE 5. HPLC-Corona detector chromatogram of algal oil (blue), 10 mg/mL in
methanol/chloroform (1:1) and the stearylglycerols standards (black)
250
pA
Triglycerides
225
100
0
120
140
min)
175
n (ng)
150
75
0
Lauric
r2=0.9989
Myristic
Linolenic
Palmitic
Oleic
PFV 1.05, r2=0.9990
5000
6000
7000
Tristearin
25
PFV 1.75, r2=0.9992
PFV 1.45, r2=0.9969
PFV 1.75,
1,3-Distearin
Monostearin
50
PFV 1.65, r2=0.9972
Stearic
8000
-20
220
pA
200
175
150
125
100
75
50
25
0
-20
0.0
5.0
10.0
15.0
20.0
2
TABLE 2. Nonlinear, relative experiment
specifications for triacylglycerols
Equivalent
Carbon
Number
(ECN)
TAGs
Spec
Am
(M
Rang
ECN-42
LLL, OLLn, PLLn
0.1-
ECN-44
OLL, PLL
4.0-1
ECN-46
OOL, POL, SLL
15.6-4
ECN-48
OOO, POO,
PPO, SOL
33.2-6
ECN-50
POS
3.4
Conclusions
Diglycerides
125
100
PFV 1.75, r2=0.9989
FIGURE 6. Chromatogram of 5 µL injecti
tetrahydrofuran (1:1), with equivalent ca
L = linoleic, Ln = linolenic, P = palmitic, S =
200
ee fatty acids, from 10 – 5000 ng o.c.,
With the determination of appropriate powe
increase analyte separation, and with comp
is capable of highly sensitive and fast chara
analytes.
min
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
55.0
60.0
65.0
Emu oil, with a number of purported health benefits, consists largely of triglycerides
(TAG). A sample of AEA-certified (American Emu Association) emu oil was prepared and
analyzed, and the chromatogram is shown in Figure 6. Relative peak area amounts were
integrated and compared against emu oil product specifications, as presented in Table 2.
The triglycerides are grouped together and labeled by equivalent carbon number, ECN.
ECN is the value calculated by 2C-2n, where C is the number of carbon atoms, and n is
the number of double bonds in a TAG. The results are consistent with expectations. The
lower amounts of TAG (ECN 50) are overestimates, which is attributable to the non-linear
detector response of this experiment. At lower amounts of analyte, the response factor is
larger than at higher amounts (providing more peak area per amount of analyte).
• A general, universal method for the simult
including paraffins, fatty acids, alcohol, es
• Sensitivity is dependent on the normal bo
a general limit for detectability by charged
• Sensitivity for the majority of analytes was
• A complex lipid sample, algal oil, demonst
entire range of compounds present in this
quantitative possibilities of the method, ev
• The power function can be used to create
References
1. Emushop.com. http://www.emushop.com
content of emu oil by AOCS HPLC meth
© 2013 Thermo Fisher Scientific Inc. All rights
Thermo Fisher Scientific Inc. and its subsidiari
use of these products in any manners that mig
Thermo Scientific Poster Note • PN70533_e 03/13S 5
ses by quadratic fits using inverted axes
LOQ
(ng o.c.)
Calibration
RSD (%)*
225
80
33
25
20
20
20
1515
35
10
2
2
190
10
5
3
1
300
40
10
4
4
20
20
18
1.75
1.99
1.90
2.66
2.91
2.55
2.78
3.37
5.90
5.49
7.21
8.73
4.94
2.52
2.08
1.65
2.79
1.98
6.03
4.11
3.29
2.87
2.03
5.33
2.35
Quadratic
Correlation
Coeff. (r2)
0.9998
0.9998
0.9999
0.9997
0.9997
0.9998
0.9997
0.9996
0.9990
0.9990
0.9979
0.9967
0.9984
0.9997
0.9998
0.9999
0.9997
0.9998
0.9985
0.9994
0.9996
0.9997
0.9998
0.9998
0.9995
d and 5 µL aliquots were injected and
ariety of lipids and other compounds,
in the chromatogram in Figure 5. An
of highly retained acylglycerols. The
e chromatogram. As can be seen in this
highly resolved.
ogram of algal oil (blue), 10 mg/mL in
lycerols standards (black)
Triglycerides
With the determination of appropriate power function values, changing the gradient to
increase analyte separation, and with comparable standards for this analysis, the method
is capable of highly sensitive and fast characterizations and quantitation of specific
analytes.
FIGURE 6. Chromatogram of 5 µL injection of emu oil, 10 mg/mL in methanol/
tetrahydrofuran (1:1), with equivalent carbon numbers (ECN) for triglycerides
220
pA
ECN 48
200
175
POS
ECN 46
150
ECN 50
POS
125
100
ECN 44
75
50
ECN 52
25
0
-20
min
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
50.0
55.0
TABLE 2. Nonlinear, relative experimental results for emu oil against product
specifications for triacylglycerols
Equivalent
Carbon
Number
(ECN)
TAGs
Specification
Amount1
(Mass-%)
Range, Mean
Experimental
Amount Found
(Area-%)
Recovery
at Mean
(%)
ECN-42
LLL, OLLn, PLLn
0.1-2.5, 1.0
--
--
ECN-44
OLL, PLL
4.0-16.0, 10.0
10.3
103
ECN-46
OOL, POL, SLL
15.6-40.8, 28.2
29.1
103
ECN-48
OOO, POO,
PPO, SOL
33.2-63.2, 48.2
41.9
ECN-50
POS
3.4-8.2, 5.8
8.1
86.9
283
L = linoleic, Ln = linolenic, P = palmitic, S = stearic, O = oleic
Conclusions
1,3-Distearin
Tristearin
min
35.0
40.0
45.0
50.0
55.0
60.0
65.0
nefits, consists largely of triglycerides
mu Association) emu oil was prepared and
Figure 6. Relative peak area amounts were
uct specifications, as presented in Table 2.
beled by equivalent carbon number, ECN.
C is the number of carbon atoms, and n is
sults are consistent with expectations. The
mates, which is attributable to the non-linear
amounts of analyte, the response factor is
peak area per amount of analyte).
• A general, universal method for the simultaneous analysis of different classes of lipids,
including paraffins, fatty acids, alcohol, esters, and acylglycerols is presented.
• Sensitivity is dependent on the normal boiling points of the analytes, with 300 ºC being
a general limit for detectability by charged aerosol detection.
• Sensitivity for the majority of analytes was found to be between 2 and 20 ng o.c.
• A complex lipid sample, algal oil, demonstrated the resolution of the method over the
entire range of compounds present in this sample. Emu oil demonstrated the
quantitative possibilities of the method, even without standards.
• The power function can be used to create linear calibration curves when required.
References
1. Emushop.com. http://www.emushop.com/specs.html, specifications of triacylglycerol
content of emu oil by AOCS HPLC method Ce 5b-89 (last accessed 12 Feb 2013)
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6 An Improved Global Method for the Quantitation and Characterization of Lipids by High Performance Liquid Chromatography and Corona Charged Aerosol Detection
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