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Rapid Quantitative Determination of Squalene in Shark Liver Oils by Raman and IR Spectroscopy

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Abstract

Squalene is sourced predominantly from shark liver oils and to a lesser extent from plants such as olives. It is used for the production of surfactants, dyes, sunscreen, and cosmetics. The economic value of shark liver oil is directly related to the squalene content, which in turn is highly variable and species-dependent. Presented here is a validated gas chromatography-mass spectrometry analysis method for the quantitation of squalene in shark liver oils, with an accuracy of 99.0 %, precision of 0.23 % (standard deviation), and linearity of >0.999. The method has been used to measure the squalene concentration of 16 commercial shark liver oils. These reference squalene concentrations were related to infrared (IR) and Raman spectra of the same oils using partial least squares regression. The resultant models were suitable for the rapid quantitation of squalene in shark liver oils, with cross-validation r 2 values of >0.98 and root mean square errors of validation of ≤4.3 % w/w. Independent test set validation of these models found mean absolute deviations of the 4.9 and 1.0 % w/w for the IR and Raman models, respectively. Both techniques were more accurate than results obtained by an industrial refractive index analysis method, which is used for rapid, cheap quantitation of squalene in shark liver oils. In particular, the Raman partial least squares regression was suited to quantitative squalene analysis. The intense and highly characteristic Raman bands of squalene made quantitative analysis possible irrespective of the lipid matrix.
Lipids (2016) 51:139–147
DOI 10.1007/s11745-015-4097-6
1 3
METHODS
Rapid Quantitative Determination of Squalene in Shark Liver
Oils by Raman and IR Spectroscopy
David W. Hall1 · Susan N. Marshall1 · Keith C. Gordon2 · Daniel P. Killeen1
Received: 18 September 2015 / Accepted: 8 November 2015 / Published online: 30 November 2015
© AOCS 2015
made quantitative analysis possible irrespective of the lipid
matrix.
Keywords Squalene · Shark liver · Raman · Infrared ·
Partial least squares regression · Gas chromatography ·
Mass spectrometry
Abbreviations
ATR Attenuated total reflectance
CCD Charge coupled device
DAGE Diacylglycerol ether
GC Gas chromatography
HPLC High performance liquid chromatography
ICH International Conference on Harmonization of
Technical Requirements
IR Infrared
MAD Mean absolute deviation
MS Mass spectrometry
MUFA Monounsaturated fatty acids
NIPALS Non-iterative partial least squares
PLS-R Partial least squares regression
PUFA Polyunsaturated fatty acids
RMSEC Root mean squared error of calibration
RMSEV Root mean squared error of validation
SNV Standard normal variate
TAG Triacylglyerol
Introduction
Squalene is a highly unsaturated, unconjugated triterpene
(Fig. 1a), sourced primarily from shark liver oils and to a
lesser extent from plant sources [1]. It is used in the produc-
tion of surfactants, dyes, and sunscreens [2]. It has also been
associated with a range of bioactivities and therapeutic uses
Abstract Squalene is sourced predominantly from shark
liver oils and to a lesser extent from plants such as olives.
It is used for the production of surfactants, dyes, sun-
screen, and cosmetics. The economic value of shark liver
oil is directly related to the squalene content, which in
turn is highly variable and species-dependent. Presented
here is a validated gas chromatography-mass spectrom-
etry analysis method for the quantitation of squalene in
shark liver oils, with an accuracy of 99.0 %, precision of
0.23 % (standard deviation), and linearity of >0.999. The
method has been used to measure the squalene concentra-
tion of 16 commercial shark liver oils. These reference
squalene concentrations were related to infrared (IR) and
Raman spectra of the same oils using partial least squares
regression. The resultant models were suitable for the rapid
quantitation of squalene in shark liver oils, with cross-val-
idation r2 values of >0.98 and root mean square errors of
validation of 4.3 % w/w. Independent test set validation
of these models found mean absolute deviations of the 4.9
and 1.0 % w/w for the IR and Raman models, respectively.
Both techniques were more accurate than results obtained
by an industrial refractive index analysis method, which
is used for rapid, cheap quantitation of squalene in shark
liver oils. In particular, the Raman partial least squares
regression was suited to quantitative squalene analysis. The
intense and highly characteristic Raman bands of squalene
* Daniel P. Killeen
Daniel.killeen@plantandfood.co.nz
1 The New Zealand Institute for Plant and Food Research
Limited, PO Box 5114, Nelson 7010, New Zealand
2 Department of Chemistry, University of Otago, P.O. Box 56,
Dunedin, New Zealand
140 Lipids (2016) 51:139–147
1 3
[3]. Squalene is the main raw material for the production of
its fully saturated analogue squalane, an emollient used by
the cosmetics industry (Fig. 1a) [4]. The squalene concen-
tration of shark liver oil is highly species-dependent, vary-
ing from 0 to 90 % w/w [59]. The low density of squalene
(0.858 g cm3) is believed to aid deep-sea sharks in main-
taining neutral buoyancy [10]. As such, the livers of deep-
sea species tend to have higher squalene concentrations
than those of shark species living at shallower depths [59].
The other major components of shark liver oil are diacyl-
glycerol ethers (DAGE) and triacylglycerols (TAG) [59].
DAGE, like squalene, is believed to function as a buoyancy
aid (density = 0.89 g cm3). The concentration of DAGE in
shark liver oils tends to be negatively correlated to the con-
centrations of squalene in shark species (r2 = 0.83) [5].
The value of shark liver oil is directly related to its
squalene composition, necessitating reliable analytical
methodologies for its measurement [2]. A recent review
summarized squalene analysis methods, which is most
commonly achieved by gas chromatography (GC) and high
performance liquid chromatography (HPLC), with vari-
ous detection methods [1]. While these chromatographic
techniques produce accurate results, the cost of purchas-
ing, operating, and maintaining GC or HPLC systems can
outweigh their benefits. Another analytical method for
squalene analysis is thin layer chromatography with flame
ionization detection (commonly referred to as “Iatroscan”
analysis) [5, 8]. However, this approach is not specific and
cannot discriminate squalene from other hydrocarbons that
may be present in the oil. Historically, quantitative spectro-
photometry with detection at 400 nm has been used to esti-
mate squalene concentrations [11]. That method required
samples to be dried, treated with H2SO4, and developed
[11]. A more recent methodology involved the use of ele-
mental analysis with isotope-ratio mass spectrometry (MS)
detection [12]. In industrial settings, the squalene content
a
bc
Fig. 1 Summary of gas chromatography–mass spectrometry (GC–
MS) analysis method for quantitation of squalene in shark liver
oil. a Retention time range showing the elution times of squalane
(16.0 min) and squalene (17.7 min) with the selective ion monitor
(SIM) responses for m/z = 69.1, 81.1, 57.0 and 71.5, b mass spec-
trum of squalane with highlighted SIM and c mass spectrum of
squalene with highlighted SIM
141Lipids (2016) 51:139–147
1 3
of shark liver oils is sometimes calculated from the oil’s
refractive index [13]. While refractive index is a cheap
and fast analytical method, it suffers from inaccuracy and
temperature sensitivity. Furthermore, refractive index is a
“black-box” methodology, which provides no additional
corroborating evidence relating to oil composition.
The Raman and IR spectra of squalene have recently been
investigated experimentally and assigned using density func-
tional theory calculations [14]. While the IR spectrum con-
tains no unusual or exceptionally characteristic bands, the
Raman spectrum of squalene has an unusually intense band at
1670 cm1, arising from the cumulative intensity of the sym-
metric stretching of the compound’s six double bonds (Fig. 1a)
[14]. A recent review of the Raman spectra of lipids showed
that the C-H stretching region of these compounds (3100–
2700 cm1) is generally far more intense than the vibrational
modes occurring below 1800 cm1 [15]. As such, the squalene
Raman band at 1670 cm1 is unusually intense and, because
the double bonds are tri-substituted, occurs at a higher energy
than double bonds found in MUFA and PUFA [15]. This
potentially makes the band analytically useful. Indeed, recent
reports that use Raman spectroscopy for the analysis of olive
oils have observed this characteristic squalene band, despite
the compound being present at less than 1 % in these oils [16
18]. Therefore, Raman spectroscopy may be suitable for the
selective analysis of squalene in lipid matrixes. It is noted that
the squalene band at 1670 cm1 is much less intense than the
vibrational bands associated with highly conjugated terpenes
derivatives such as β-carotene [19, 20].
This report describes a validated GC-MS method for
accurate and precise quantitation of squalene in shark liver
oils. The method was based on a previously published
report by Lanzon et al. [21]. This method was used to meas-
ure the squalene content of 16 commercial shark liver oils.
The Raman and IR spectra of the same shark liver oils were
related to the GC-MS reference results using partial least
squares regression (PLS-R). The quantitative performance
of the resultant spectroscopic models was appraised by
both cross-validation and test-set validation. Results from
the spectroscopic analyses were compared with results gen-
erated by an industrial refractive index method [13]. These
spectroscopic models were developed as a compromise
between the rapid, but unreliable, refractive index analysis
method and the accurate, but more expensive, gas chroma-
tography analysis method.
Materials and Methods
Chemicals and Standards
Squalene (98 %) and squalane (99 %) were sourced from
Sigma-Aldrich. GC grade hexane and methanol (Merck),
and MilliQ™ (Millipore) grade water were used. Analyti-
cal reagent grade ethanol (96 %), KOH, and Na2SO4 were
sourced from Merck.
Samples
Sixteen shark liver oils, chosen to represent a wide range of
squalene concentrations and diverse oil compositions, were
provided for this study by SeaDragon Marine Oils Ltd®
(New Zealand). Oils were sourced from a variety of shark
species from different global locations. Oils were either
unmodified or had undergone various chemical processing,
e.g. steam stripping, molecular distillation, and bleaching.
The processing methods commonly applied to shark liver
oils have recently been reviewed [1]. A series of valida-
tion standards were prepared by adding accurately weighed
amounts of squalene to school shark (Galeorhinus galeus
L.) oil (Table 1). The school shark oil itself contained only
trace amounts of squalene (<0.1 %). An additional “check”
sample was prepared from squalene and school shark oil
(50.2 % w/w squalene) and analysed periodically through-
out GC-MS analysis runs.
Gas Chromatography‑Mass Spectrometry: Sample
Preparation
An internal standard solution was prepared by dissolv-
ing squalane in hexane (100 mg mL1). Shark liver oil
(100–200 mg) was accurately weighed into a 15-mL plastic
Table 1 Squalene composition of validation standards by gas chromatography-mass spectrometry (GC-MS)
Validation standards
(% squalene)
GC-MS replicate analyses Average
% Recovery (n = 4)
Standard
deviation (n = 4)
Prep. 1 Inj. 1 Prep. 1 Inj. 2 Prep. 2 Inj. 1 Prep. 2 Inj. 2 Average (n = 4)
9.8 9.62 9.64 9.57 9.56 9.6 97.9 0.04
30.3 30.38 30.25 30.66 30.55 30.5 100.5 0.18
49.8 49.8 50.01 49.92 49.64 49.8 100.1 0.16
70.1 69.8 69.69 69.16 69.22 69.5 99.1 0.32
89.9 88.14 87.91 87.085 87.68 87.7 97.6 0.45
Average (n = 5) 99.0 0.23
142 Lipids (2016) 51:139–147
1 3
centrifuge tube and dissolved in 4 mL of hexane and 1 mL
of ISS. One milliliter of a 2 M KOH solution in methanol
was added to the tube. The tube was capped and the contents
mixed for 90 s (vortex mixer) at room temperature to effect
methanolysis of acylglycerides in the oils. After standing
for 10 min, the reaction mixture was centrifuged to achieve
clean phase separation, and the lower methanolic layer
was removed and discarded. The remaining hexane layer
was washed twice with 1:1 ethanol–water (4 mL), with the
lower aqueous layer being removed and discarded between
washes. The washed hexane extract was then removed, dried
with anhydrous Na2SO4 (c. 500 mg), and diluted 1000× for
analysis by GC-MS. This method was based on a previously
published report [21]. Calibration standards were prepared
by substituting accurately measured quantities of squalene
standard (100 mg mL1 in hexane) for shark liver oil sam-
ples. The final squalene concentrations in the calibration
standards were 0, 8, 16, 24, 32, and 40 ppm.
Gas Chromatography‑Mass Spectrometry
GC-MS analysis was performed using a Shimadzu
QP-2010 instrument equipped with a Restek Rxi®-5Sil MS,
30 m × 0.25 mm ID column (5 % dipheny/95 % dimethyl-
polysiloxane). Injections (1 µL, splitless, 300 °C, sampling
time 2 min) were performed using a PAL auto-sampler. The
GC oven temperature was held at 60 °C for 2.5 min, ramped
from 60 to 240 °C (20 °C min1), then from 240 to 280 °C
(5 °C min1), and finally to 300 (20 °C min1), where it was
held for 2 min. The carrier gas was helium, with a column
flow rate of 2 mL min1 maintained using linear velocity
control (total flow 37 mL min1). Detection was facilitated
by electron impact mass spectrometry at 70 eV (ion source
230 °C, transfer line 270 °C). Selective ion monitoring was
performed at m/z = 57.0, 69.1, 71.1, and 81.1 (Fig. 1).
Validation was performed in agreement with the gen-
eral guidelines supplied by The International Conference
on Harmonization of Technical Requirements (ICH) [22].
Squalene recovery (extractability) was determined by ana-
lysing the validation standards and comparing the results
with their known squalene concentrations, listed in Table 1.
This analysis was also used to determine analytical accu-
racy and precision over a range of squalene concentrations.
Intermediate precision was determined by preparing and
analysing shark liver oils in triplicate on three separate days
by two different analysts. Throughout these analyses, the
same “check” sample was periodically analysed to demon-
strate sample stability and method reproducibility.
IR Analysis
IR absorption spectra were acquired in the region of 4000–
400 cm1 using a Bruker ALPHA Fourier transform IR
spectrometer. Oils were presented directly onto the attenu-
ated total reflectance (ATR) diamond accessory and 16
co-added scans were acquired with a spectral resolution of
4 cm1. Spectra consisted of 2514 data points. Three spec-
tral replicates were acquired for each oil sample and spec-
tral backgrounds were acquired at regular 5-min intervals.
Raman Analysis
Raman spectra were acquired using a Senterra Raman
microscope equipped with an Olympus BX microscope
with × 20 objective lens. Raman scattering was generated
using a 785 nm diode laser at 100 mW. Raman spectra were
measured as Stokes-shifted radiation from the laser line
in the range of 3200–90 cm1 with a spectral resolution
of 9–18 cm1, using OPUS 6.5 software. Detection was
facilitated by dispersing Raman-shifted radiation onto a
CCD detector using a grating (1200 grooves mm1). Shark
liver oils (approx. 50 µL) were presented in aluminium div-
ots and analysed in triplicate. Spectra were the average of
100 × 2 s co-additions and consisted of 6221 data points.
Spectral Preprocessing and Multivariate Analysis
Preprocessing and multivariate analysis were performed
using the Unscrambler® v10.3 software. IR spectra under-
went a standard normal variate (SNV) transformation to
compensate for inter-sample absorbance intensity and y-scat-
tering effects. These spectra were subjected to a 15-point,
second order gap derivative to remove baseline features, and
the spectral ranges from 3050 to 2670 and 1800 to 500 cm1
were used to generate the PLS-R model (908 data points).
Raman spectra were subjected to a SNV transforma-
tion to normalize inter-sample spectral intensities and a
25-point, second order gap derivative to remove baseline
features. The combined spectral ranges from 3050 to 2700
and 1800 to 400 cm1 were used to generate PLS-R models
(3503 data points).
PLS regression models were generated using the non-
iterative partial least squares (NIPALS) algorithm. Full,
“leave-one-out” cross-validation was performed on each
model. The IR and Raman models were subsequently used
to predict squalene concentrations in the validation sam-
ples. Analysis of these samples constituted an independent
test set validation of the spectroscopic models.
Refractive Index Analysis
The refractive indices of the shark liver oil sample set and
validation standards were measured using an Atago® PAL-
RI “Pocket” refractometer. The average squalene con-
tent (n = 3) was determined using the method previously
described by Batista and Nunes [13].
143Lipids (2016) 51:139–147
1 3
Results and Discussion
GC‑MS Results and Method Validation
To account for losses throughout the multi-step sam-
ple preparation, a fixed quantity of the squalane ISS was
added to each shark liver oil sample. Squalane was chosen
because it possesses similar physical properties to squalene
(i.e. high boiling point, low polarity, and similar molecu-
lar mass), was chromatographically resolved (Fig. 1a),
and was commercially available. To enhance analytical
sensitivity and selectivity MS detection was performed
using selected ion monitoring. Four ion channels were
monitored: the two most abundant ions in the squalene
mass spectrum at 69.1 and 81.1 (Fig. 1b), and the two
most abundant ions in the mass spectrum of squalane at
57.0 and 71.1 (Fig. 1c). This approach provided excellent
selectivity and allowed detection of squalene at concentra-
tions of approximately 0.4 ppm. The ratio of the squalane
peak area to squalene peak is defined here as the squalene
response, which was related to the squalene concentration
using a six-point calibration curve. Squalene response was
linear (r2 > 0.999) from 0 to 40 ppm and the best-fit line
passed easily through the origin. Taking into account the
preparative dilutions, this range equated to squalene con-
centrations of 0–100 % w/w in undiluted shark liver oils.
To assess the recovery, accuracy, and precision of
the GC-MS analysis method, duplicate preparation and
analysis of the five validation standards was performed.
The average recovery for these samples was 99.0 %
(Table 1). These results also demonstrated the accuracy of
the method, i.e. the closeness of measured values to the
known concentrations. Precision was assessed by meas-
uring the deviation of results from duplicate injections
of duplicate preparations of the five validation samples.
The average standard deviation of the replicate analyses
(n = 4) of the five validation samples was 0.23 % w/w
(Table 1). Reproducibility was demonstrated by repli-
cate analysis of a check sample, which was periodically
analysed throughout the GC-MS analyses. The squalene
concentration of this sample was 50.2 % w/w. The aver-
age result of the GC-MS analysis of this sample was
50.16 ± 0.25 % w/w (n = 13).
Intermediate precision was measured by comparing
results for the squalene composition of the shark liver oil
sample set by “analyst 1 on day 1” with results from inde-
pendent preparations of the same samples by “analyst 2 on
day 2”. The inter-analyst/inter-day analyses were in good
agreement (103.4 %, n = 16) with an average standard devi-
ation of 0.57 % w/w (Table 2). The average squalene content
(n = 3) of these analyses were used as reference data for the
spectroscopic PLS-R models described below (Table 2).
Table 2 Squalene composition of shark liver oil samples by gas chromatography-mass spectrometry (GC-MS)
SD standard deviation
a Average result of two injections
b Analyst 2 result as a % of the average analyst 1’s results (n = 2)
Sample Analyst 1 Analyst 1 Analyst 2 Average (n = 6) Intermediate precisionbSD (n = 6)
Day 1aDay 2aDay 3a
S01 88.2 87.8 85.6 87.2 100.9 1.28
S02 37.9 37.4 38 37.8 99.7 0.46
S03 29.8 29.8 30 29.9 99.8 0.13
S04 77.6 77.8 76.7 77.4 100.4 0.52
S05 0.5 0.5 0.7 0.6 87.7 0.13
S06 6.8 6.9 7.4 7.1 97.5 0.27
S07 54.4 54.3 54.6 54.4 99.8 0.20
S08 3.3 3.3 3.5 3.4 97.9 0.13
S09 8.5 8.7 8.7 8.6 99.5 0.13
S10 97.2 94.6 94.2 95.3 100.6 1.48
S11 97.2 96.7 94.3 96.1 100.9 1.49
S12 83.7 84.2 81.7 83.2 100.9 1.21
S13 83.2 83.1 82.6 82.9 100.2 0.33
S14 67.2 67.2 67.1 67.2 100.0 0.12
S15 17.1 17.0 17.2 17.1 99.7 0.13
S16 6.9 6.8 7.2 7.0 98.3 0.18
Average (n = 16) 99.0 0.51
144 Lipids (2016) 51:139–147
1 3
IR and Raman Spectra of Shark Oils
The IR spectrum of squalene had three intense C–H
stretching bands at 2965, 2913, and 2852 cm1 and four
intense skeletal vibrational modes at 1440, 1376, 1107, and
832 cm1 (Fig. 2a). The low intensity band at 1666 cm1
due to C=C stretching was also of analytical importance.
The IR spectra of a TAG and a shark oil rich in DAGE,
which are the other main constituents of shark liver oils,
are also shown in Fig. 2a. The IR spectra of these glyc-
erol derivatives share many features, including the intense
C-H stretching bands from 3000 to 2800 cm1, the intense
carbonyl stretches (1740 cm1) and strong skeletal
and hydroxyl bending modes at 1468, 1165, 1112, and
720 cm1. The full assignments of the IR spectra of these
and related compounds are comprehensively described
elsewhere [14, 23].
As is the case with most lipids, the Raman spectrum of
squalene was dominated by the C-H stretching region (3000–
2700 cm1) [15]. Therefore, for the purposes of presentation,
the intensity of the spectral region from 1800 to 400 cm1
has been magnified 3× compared to the C–H stretching
region (Fig. 2b). Some less intense, but analytically impor-
tant, bands in the Raman spectrum of squalene occurred at
1440, 1383, 1330, 1283, 1001, 803, and 454 cm1 due to
various skeletal stretching and bending modes. However, the
most distinctive Raman band in the spectrum of squalene
was observed at 1670 cm1 due to the additive intensity of
the symmetric stretching of the six highly polarisable double
bonds in the compound (Fig. 1a) [14]. These tri-substituted
double bonds gave rise to a Raman band at slightly higher
energy than those of di-substituted fatty acid double bonds
[15]. As such, the squalene Raman band at 1670 cm1 could
be used to distinguish squalene double bond stretches from
normal fatty acid double bond stretching 1640–1660 cm1
[15]. While the intensity of this band was high relative to
those of other lipids, it was far less intense than double bond
stretching signals associated with conjugated hydrocarbons
such as β-carotene [15, 19].
The IR and Raman spectra of the other most common
shark liver oil components (DAGE and TAG) are shown in
Fig. 2b [5]. Besides the C–H stretching region, the most
intense Raman bands in the DAGE-rich shark oil were
observed at 1660, 1442, 1305, and 1266 cm1, whereas the
most intense TAG bands were found at 1446, 1298, 1130,
and 1061 cm1 (Fig. 2b). Weak carbonyl stretching vibra-
tions were observed for both TAG and DAGE samples at
1750 cm1. The Raman spectrum of these and related
compounds have recently been reviewed and assigned in
detail [15]. The double bond stretching mode of the DAGE-
rich shark oil is at 1660 cm1. This illustrates the afore-
mentioned distinction between di- and tri-substituted dou-
ble bond stretching vibrational frequencies (Fig. 2b).
Spectroscopic PLS‑R Models
The optimal IR PLS-R model was produced by relat-
ing the GC-MS reference data (Table 2) to the IR spec-
tral ranges from 3050 to 2670 and 1800 to 500 cm1 of
the shark liver oils. The modelled relationship between
the squalene reference concentrations by GC-MS and the
predicted squalene concentrations by IR is summarized in
Fig. 3a. The full, “leave-one-out” cross-validation of this
model had an r2 = 0.986 and a root-mean-square error of
validation (RMSEC) of 4.1 % w/w using three regression
factors (Fig. 3a). The spectral variability responsible for the
PLS-R model is summarized by the PLS regression coef-
ficient (β), which is related to the spectrum of squalene in
a
b
Fig. 2 a Infrared (IR) and b Raman spectra of squalene, triacylgl-
ceride (TAG) and shark oil rich in diacylglyceride ether (DAGE). In
the Raman spectra, the intensity of the region from 1800–400 cm-1 is
scaled ×3 relative to the region from 3050–2700 cm-1
145Lipids (2016) 51:139–147
1 3
Fig. 3b. It is evident that intensity variance of the squalene
IR bands at 1666, 1440, 1376, 1107, and 832 cm1 influ-
ences the PLS-R model. However, the most notable feature
in the IR PLS-R model regression factor is due to the car-
bonyl stretching of the glycerol derivatives at 1750 cm1
(Fig. 3b). This band is inversely loaded to the squalene
bands, which means that, in addition to squalene vibra-
tional bands, the IR model is using the “absence of glycerol
derivatives” to estimate the squalene concentration.
The optimal Raman PLS-R model was produced
from the spectral ranges from 3050 to 2700 and 1800 to
400 cm1. The model had a cross-validation r2 = 0.986,
with a RMSEV of 4.3 % w/w (Fig. 4a). The model con-
sisted of just a single PLS-R factor, which was strongly
influenced by intensity variances at 2913, 1670, 1383,
1330, 1283, 1001, 803, and 454 cm1—all of which are
associated with the Raman spectrum of squalene (Fig. 4b).
The strong influence of the symmetric double bond
a
b
Fig. 3 Summary of infrared (IR) partial least squares regression
(PLS-R) model. a Calibration and cross-validation regression lines
with model performance metrics inset and b the PLS-R model regres-
sion coefficient related to the IR spectrum of squalene from shark
liver oils
a
b
Fig. 4 Summary of Raman partial least squares regression model. a
Calibration and cross-validation regression lines with model perfor-
mance metrics inset and b the model regression coefficient related to
the Raman spectrum of squalene from shark liver oils
146 Lipids (2016) 51:139–147
1 3
stretching band at 1670 cm1 was apparent (Fig. 4b). The
IR and Raman regression factors (β) shown in Figs. 3b and
4b, describe the explained spectral variance of the IR and
Raman PLS-R models, respectively. A visual inspection
of these figures suggests that the regression factor for the
Raman model contained more squalene-specific explained
variance than the regression factor for the IR model.
The validation samples were analysed using both spec-
troscopic PLS-R models and the refractive index method.
These samples were diluted in school shark oil, which con-
tained only trace amounts of squalene and had an oil com-
positon distinct from the shark liver oil sample set. This
provided a means of testing the selectivity of the squalene
analysis methods. The squalene concentration of these
samples by refractive index was highly inaccurate, with a
mean absolute deviation (MAD) of 27.8 % w/w (Table 3).
This was in line with refractive index results for the shark
liver oils sample set, which produced values in the range
of 45 to 112 % w/w (data not shown). While it has been
shown previously that the squalene composition of shark
liver oil can be correlated to refractive index [13], we found
that the squalene content of processed shark liver oil could
not be accurately measured using this approach. This was
in line with results reported by industrial sources, who
found that refractive index was highly unreliable for pre-
dicting the squalene content of processed shark liver oils,
oils with unusual compositions and oils that have had been
artificially enriched with squalene (personal communica-
tion). As such, refractive index analysis of squalene should
be restricted to pure shark oils that have undergone mini-
mal or no chemical processing.
The squalene composition of the validation samples
were also measured using the IR and Raman PLS-R mod-
els. The results of these analyses represent an independent,
test-set validation of the spectroscopic models (Table 3).
The MAD of squalene concentrations in the validation
samples was 4.9 % w/w using the IR model. This was a
large improvement over the refractive index method for
these samples. However, results from the IR model system-
atically over-estimated squalene content (Table 3). This was
probably due to interfering components in the school shark
oil. As mentioned, the IR spectrum of squalene does not
contain any characteristically intense or unusual vibrational
bands, rendering it prone to interference from other lipid
components with similar IR absorption bands. Analysis of
the shark liver oil samples using the Raman PLS-R model
produced more accurate results than results produced by
the IR model. The MAD of squalene concentrations in
the validation samples was 1.0 % w/w using the Raman
model (Table 3). Unlike analysis using the refractive
index method and the IR PLS-R model, the school shark
oil matrix did not interfere with the accuracy of squalene
quantitation by the Raman PLS-R model. As discussed
above, this was probably due to the unusually strong and
characteristic Raman spectral features of squalene, in par-
ticular the band at 1670 cm1. As such, the Raman PLS-R
model for squalene demonstrated better selectivity than
both the refractive index and IR analysis methods. Raman
spectroscopy is, therefore, better suited for the quantitative
analysis of squalene than IR spectroscopy, especially in
variable lipid matrixes. However, both spectroscopic tech-
niques produced more accurate results than the refractive
index methodology.
Conclusions
A validated, quantitative GC-MS analysis method for
squalene in pure and processed shark liver oils has been
described. It has been demonstrated that quantitative anal-
ysis of squalene in shark oils can be performed rapidly
using both IR and Raman spectroscopy in conjunction with
PLS-R. These methods provide a compromise between the
inexpensive, but unreliable, refractive index method and
the highly accurate, but more expensive, chromatographic
analysis methodologies. In particular, Raman spectroscopy
was well suited to the analysis of squalene in shark liver
oils. The strong performance of the Raman model is prob-
ably influenced by the relatively intense alkene stretching
band of squalene, which helps to distinguish it from the
Table 3 Squalene content of
validation standards by infrared
(IR) and Raman partial least
squares regression (PLS-R)
models and refractive index
Validation standards
Squalene
(% w/w)
GC-MS results
Squalene
(% w/w)
IR Raman Refractive index
Squalene
(% w/w)
Error
(% w/w)
Squalene
(% w/w)
Error
(% w/w)
Squalene
(% w/w)
Error
(% w/w)
0 0 1.3 0 0.1 0.0 47.6 47.6
9.8 9.6 10.8 1.2 9.4 0.2 48.7 48.7
30.3 30.5 34.3 3.8 33.3 2.8 64.9 55.3
49.8 49.8 55 5.2 51.3 1.5 78.5 48.0
70.1 69.5 77.9 8.4 69.2 0.3 83.7 33.9
89.9 87.7 98.6 10.9 86.8 0.9 93.2 23.7
Mean absolute deviation (MAD) 4.9 1.0 41.9
147Lipids (2016) 51:139–147
1 3
Raman spectra of most other lipids, including DAGE and
TAG [15]. Based on our results, refractive index analysis
is inappropriate for quantitation of squalene in variable oil
matrixes, including processed shark liver oil samples.
Acknowledgments This research was supported by funding from
the New Zealand Ministry for Business Innovation and Employment
(MBIE) for the programme Export Marine Products (C11X1307)
and the Dodd-Walls Centre. The authors would like to thank Michael
Baird and Mark Gornall of Seadragon Marine Oils Ltd® for providing
shark liver oil samples and information.
Compliance with Ethical Standards
Conflict of interest The authors declare no conflict of interest.
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... The band at 1666 cm À1 was due to CHC stretching (Hall et al., 2016;Chun et al., 2013). The recorded infrared spectrum of compound 1 as squalene was compared was in accordance with Hall et al. (2016) and Chun et al. (2013). ...
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