Characterize Fatty Acid Composition in Food Quality

The fatty acid composition of foods governs a wide variety of qualities of food, ranging from product shelf life and sensory properties such as texture and taste through to nutrition and the effect on health aspects. It also governs factors such as feeding regimes, animal metabolism, and even genetic origin. Recently, consumer awareness of food products and human health has increased, notably related to fat consumption. Reliable and effective techniques for characterizing and documenting the fatty acid profiles of food products are therefore of great significance in industrial applications, and also for research purposes.

Raman spectroscopy is considered to be a sensitive probe for quantitative and qualitative characterization of fatty acid composition, varying from gross fatty acid features to single fatty acids. Raman spectroscopy also offers multiple sampling possibilities for the analysis of lipid-containing samples at the micro- and macro-scale. Raman spectroscopy is a substitute for conventional techniques for approaching problems such as quality control, adulteration, or advanced study of oils and fats, as it is non-destructive, quick and highly chemically sensitive, .

Characterization of Vegetable Oil Blends

In the food industry, the adulteration of vegetable oils is an immense challenge as low-cost or low-quality oils may replace the costlier ones. Raman spectra of vegetable oils and oil blends are depicted in Figure 1. The clear spectral signature differences between olive oil (a highly mono-unsaturated oil), sunflower oil (a highly polyunsaturated oil), and a mixture of the two are demonstrated in the top figure. The principal component analysis score plot of duplicate Raman spectra of olive oil (O), sunflower oil (S), fish oil (F), and 60–40 blends of all oils (capital letters indicate the most abundant oil) are demonstrated in the bottom figure. This shows the capability of Raman spectroscopy to characterize oils, making it a beneficial tool for the determination of real quality and composition of a given oil blend.

Raman spectral signatures of olive oil (blue), sunflower oil (green), and a blend of the two oils (red).

Principal Component Analysis score plot of duplicate Raman spectra of pure oils and oil blends. Along the first PC, a clear separation according to carbon-carbon unsaturation is visible (increasing from olive oil to fish oil).

Figure 1. Upper: Raman spectral signatures of olive oil (blue), sunflower oil (green), and a blend of the two oils (red). Lower: Principal Component Analysis score plot of duplicate Raman spectra of pure oils and oil blends. Along the first PC, a clear separation according to carbon-carbon unsaturation is visible (increasing from olive oil to fish oil).

Characterization of the Lipid Composition of Bovine Tissue at the Microscale

Employing the high spatial resolution of Raman microscopic systems offers the chance of researching and documenting particular lipid features within cell populations, food products and biological tissues. Figure 2 illustrates the analysis of bovine adipose tissue by focusing on the lipid-rich parts of intact bovine tissue. Specifically interesting are different features related to the configuration of the carbon-carbon double bonds in the Raman spectra of adipose tissue. In this regard, the C=C stretching vibration about 1660 cm-1 is specifically sensitive. For example, in the spectra shown in Figure 2, a clear shoulder on the right side of this band can be observed, which is associated with the trans-configuration of the double bonds. Varying impacts from the protein-matrices could also be seen in the spectra.

Microscopic Raman analysis of bovine adipose tissue. All spectra are obtained with a Raman microscope (785 nm).

Figure 2. Microscopic Raman analysis of bovine adipose tissue. All spectra are obtained with a Raman microscope (785 nm).

The mappings of an area of a sample are executed to observe these local differences on a greater scale. A bovine adipose tissue is analyzed under the Raman microscope over an area of 1.2 mm x 1.2 mm. The distribution of the trans-configuration of the double bond of the fatty acids over the mapped area is depicted in Figure 3.

Raman image of the trans-configuration distribution of a 1200 x 1200 µm bovine adipose tissue sample, using a 785 nm excitation.

Figure 3. Raman image of the trans-configuration distribution of a 1200 x 1200 µm bovine adipose tissue sample, using a 785 nm excitation.

Reproducible Characterization of Adipose Tissue Employing Transmission Raman Spectroscopy

The local differences noticed in adipose tissues are shown in the former example. Composition variation in fatty acids was also established between the different fat layers (inner and outer) of adipose tissues. In this case, the ability to obtain an averaged spectrum of a bulk sample is essential, if global information is needed.

Transmission Raman spectroscopy offers such averaged information: by gathering the Raman transmitted light all over the area, the resulting spectra will be representative of the full sample, without regard to local variations.

Adipose tissues of veal, lamb, and pork chops were evaluated in transmission: several thicknesses and sizes of samples were analyzed without any preparation by transmission Raman spectroscopy.

Transmission Raman spectra of adipose tissues from different species (lamb, pork, veal) using the transmission accessory operating at 785 nm.

Figure 4. Transmission Raman spectra of adipose tissues from different species (lamb, pork, veal) using the transmission accessory operating at 785 nm.

Raman spectra offer multiple indications related to the composition of the samples. For instance, trans-fatty acids can be easily noticed from the spectra: the peak at 1668 cm-1 is directly connected to the trans-configuration of the C=C double bond of fatty acids. The consumption of trans-fats increases the risk of health problems and is hence prone to regulations in various countries.

Similarly, Raman spectra can be employed to obtain quantitative information about the fatty acid profiles.

The score plot in Figure 5 illustrates that it is possible to classify the species according to the Raman signature of their adipose tissues.

Principal component analysis score plot of samples of lamb, pork, and veal adipose tissues.

Figure 5. Principal component analysis score plot of samples of lamb, pork, and veal adipose tissues.

Conclusions and Perspectives

This paves the way for a non-destructive and fast characterization method, which is a substitute for wet chemical techniques which may be tedious, expensive and need sample preparation. This would also enable more systematic control of foodstuffs on a broad range of analyses, providing quick indications about origin, food quality, and potential adulteration of products. The usage of a single instrument offers information on the macroscale (including the transmission option) and on the microscale.

References and Further Reading

  1. Heidi Najbjerg, et al., Monitoring cellular responses upon fatty acid exposure by Fourier transform infrared spectroscopy and Raman spectroscopy, Analyst, 136, 1649–1658, 2011.
  2. Beattie, J. R. et al., 2006, Prediction of Adipose Tissue Composition Using Raman Spectroscopy: Average Properties and Individual Fatty Acids, Lipids, v. 41, n 3, p. 287–294.
  3. Afseth, N. K., et al, 2005, Raman and near-infrared spectroscopy for quantification of fat composition in a complex food model system: Applied Spectroscopy, v. 59, p. 1324–1332.

This information has been sourced, reviewed and adapted from materials provided by HORIBA.

For more information on this source, please visit HORIBA.

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