| Title |
Rapid Quantitative Determination of Squalene in Shark Liver Oils by Raman and IR Spectroscopy
|
|---|---|
| Published in |
Lipids, November 2015
|
| DOI | 10.1007/s11745-015-4097-6 |
| Pubmed ID | |
| Authors |
David W. Hall, Susan N. Marshall, Keith C. Gordon, Daniel P. Killeen |
| 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Austria | 1 | 1% |
| Unknown | 66 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 18% |
| Researcher | 10 | 15% |
| Student > Master | 7 | 10% |
| Student > Bachelor | 5 | 7% |
| Student > Doctoral Student | 3 | 4% |
| Other | 13 | 19% |
| Unknown | 18 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 17 | 25% |
| Agricultural and Biological Sciences | 14 | 21% |
| Engineering | 3 | 4% |
| Environmental Science | 2 | 3% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Other | 7 | 10% |
| Unknown | 23 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2016.
All research outputs
#20,300,248
of 22,837,982 outputs
Outputs from Lipids
#1,773
of 1,904 outputs
Outputs of similar age
#324,791
of 387,533 outputs
Outputs of similar age from Lipids
#22
of 27 outputs
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