The authenticity of products labeled as virgin olive oil is of great
importance from commercial and
health aspects. The combination of Fourier transform-Raman
(FT-Raman) spectroscopy with
multivariate procedures has been used for predicting the level of
adulteration in a set of virgin
olive oil samples that were adulterated with soybean, corn, and raw
olive residue (olive pomace)
oils at 1, 5, and 10%, respectively. Six genuine virgin olive oil
samples, differing in their chemical
composition, were selected from a set of 1428 European samples.
The best result in prediction of
adulteration was an adjusted R
2 value of 0.964,
determined by regression on principal components
(PCR), giving 100% correct discrimination between genuine and
adulterated samples and 91.3%
correct classifications at different adulteration levels.
Keywords: Olive oil; adulteration; FT-raman spectroscopy; chemometrics;
authentication
The fluorescence spectroscopy technique has been tested as regards its ability to differentiate between refined hazelnut and olive oils. Classification of these oils based on their excitation-emission fluorescence spectra data (spectral range 300-500 nm of the excitation spectra at lambdaem=655 and spectral range 650-900 of the emission spectra at lambdaex=50 nm) was performed using principal component analysis and artificial neural networks. Both methods provided good discrimination between the refined hazelnut and olive oils. The results have also pointed out the possibilities of a spectrofluorimetric method joined to multivariate analysis, to differentiate refined oils, and even to detect the presence of refined hazelnut oils in refined olive oils at percentages higher than 9%.
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