Lipid analysis by vibrational spectroscopy

Voort, F.R. van de; Sedman, Jacqueline; Russin, Ted A.

doi:10.1002/1438-9312(200112)103:12<815::aid-ejlt1111815>3.3.co;2-g

Cited by 31 publications

(43 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FTIR is also a promising analytical tool for quantitative analysis of analytes because, following Beer's law, the peak intensities (absorbances) of the IR spectrum are directly proportional to concentration. In addition, FTIR has been utilized for the characterization and differentiation of fats and oils because the peak intensities and the exact frequencies at which the maximum absorbance of peaks appear, differ according to the nature and composition of the sample [5].…”

Section: Introductionmentioning

confidence: 90%

“…Comprehensive examination of the FTIR spectra of evaluated fats and oils allowed the identification of certain peaks or peak ratios that help in the characterization, differentiation, and classification of lard and other edible fats and oils [5]. The peak intensities of lard and other fat and oils at certain frequencies are listed in Table 2.…”

Section: Fatty Acid Composition and Ftir Spectramentioning

confidence: 99%

See 1 more Smart Citation

Differentiation of Lard From Other Edible Fats and Oils by Means of Fourier Transform Infrared Spectroscopy and Chemometrics

Man

Rohman

Mansor

2010

J Americ Oil Chem Soc

View full text Add to dashboard Cite

Fourier transform infrared (FTIR) spectra at mid infrared regions (4,000-650 cm -1 ) of lard and 16 edible fats and oils were compared and differentiated. The chemometrics of principal component analysis and cluster analysis (CA) was used for such differentiation using FTIR spectra intensities of evaluated fats and oils. With PCA, an ''eigenvalue'' of about 90% was achieved using four principal components (PCs) of variables (FTIR spectra absorbances at the selected frequency regions). PC1 accounted for 44.1% of the variation, while PC2 described 30.2% of the variation. The main frequency regions that influence the separation of lard from other evaluated fats and oils based on PC1 are 2,852.8 followed by 2,922 and 1,464.7 cm -1 . Furthermore, CA can classify lard into its group based on Euclidean distance.

show abstract

Section: Introductionmentioning

confidence: 90%

Section: Fatty Acid Composition and Ftir Spectramentioning

confidence: 99%

Differentiation of Lard From Other Edible Fats and Oils by Means of Fourier Transform Infrared Spectroscopy and Chemometrics

Man

Rohman

Mansor

2010

J Americ Oil Chem Soc

View full text Add to dashboard Cite

show abstract

“…Raman scattering is based on the rate of change of the molecular polarizability or configuration of electron distribution in the molecule as vibrational transitions occurring mainly in the electronic ground state take place within the molecule. [20] The major advantages of Raman spectroscopy are that it requires no sample preparation, it is a rapid and nondestructive tool, and, when combined with a fiber-optic sampling station, it can make such a system ideally suited for online industrial processing, since the direct contact with the sample is not necessarily required to obtain spectra; both excitation and collection of signal light can be performed, e.g., through windows of a production vessel. As a matter of fact, in recent research works, extensive effort has been spent on the authentication of virgin olive oil [21,22] and edible oils [23,24] by FT-Raman spectroscopy with NIR excitation.…”

Section: Introductionmentioning

confidence: 99%

Visible Raman spectroscopy for the discrimination of olive oils from different vegetable oils and the detection of adulteration

El-Abassy

Donfack

Materny

2009

J Raman Spectroscopy

156

View full text Add to dashboard Cite

We have investigated the potential of Raman spectroscopy with excitation in the visible spectral range (VIS Raman) as a tool for the classification of different vegetable oils and the quantification of adulteration of virgin olive oil as an example. For the classification, principal component analysis (PCA) was applied, where 96% of the spectral variation was characterized by the first two components. A significant similarity between sunflower oil and extra-virgin olive oil was found using this approach. Therefore, sunflower oil is a potential candidate for adulteration in most commercially available olive oils. Beside the classification of the different vegetable oils, we have successfully applied Raman spectroscopy in combination with partial least-squares (PLS) regression analysis for very fast monitoring of adulteration of extra-virgin olive oil with sunflower oil. Different mixtures of extra-virgin olive oil with three different sunflower oil types were prepared between 5 and 100% (v/v) in 5% increments of sunflower oil. While in the present context the adulteration usually refers to the addition of reasonable amounts of the adulterant (given the similarity with the basic product), we show that the technique proposed can also be used for trace analysis of the adulterant. Without using techniques like surface-enhanced Raman scattering (SERS), a quantitative detection limit down to 500 ppm (0.05%) could be achieved, a limit irrelevant for adulteration in commercial terms but significant for trace analysis. The qualitative detection limit even was at considerably lower concentration values. Based on PCA, a clear discrimination between pure extra-virgin olive oil and olive oil adulterated with sunflower oil was achieved. The adulterant content was successfully determined using PLS regression with a high correlation coefficient and small root mean-square error for both prediction and validation.

show abstract

“…The advantages of the Fourier-transform include the improvement in the signal-to-noise ratio, a significant reduction in the scan time, higher energy throughout, superior spectral resolution, wavelength accuracy, and ease of sample handling aspects (Sivakesava & Irudayaraj, 2000). In fact, Fourier-transform infrared (FTIR) represents an important tool used for quality control and monitoring process in the food industry due to the cost effectiveness, improved performance and ease of use compared to other methods (Guillé n & Cabo, 2000;Innawong, Mallikarjunan, Irudayaraj, & Marcy, 2004;Van de Voort, Sedman, & Russin, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…MIR and NIR have been used in authentication procedures, in order to assess if a product strictly conforms to description provided by its label and complies with legislation (Hourant et al, 2000;Reid et al, 2005;Vlachos et al, 2006). In the field of oil analysis, MIR has been effectively used to determine -cis and -trans content, iodine value, saponification number, peroxide value, anisidine value, free fatty acid content of oil and fat samples (Innawong et al, 2004;Van de Voort et al, 2001). Innawong et al (2004) used attenuated total reflectance MIR to discriminate between good, marginal and unacceptable frying oils based on rancidity.…”

Section: Introductionmentioning

confidence: 99%