A front-face fluorescence method has been used to obtain an excitation-emission matrix (EEM) of various Italian mono-cultivar, and mix-cultivar, extra virgin olive oils without any laborious sample preparation. These EEM use excitations from 230 to 360 nm and emissions from 260 to 390 nm to explore potential fingerprint characteristics that could be used for cultivar and geographical origin authentication. To simplify these complex spectral datasets, the variable reduction was undertaken using total absolute principal component coefficients. It has been found that at least 3 excitation wavelengths are necessary to obtain 5 variables which could explain more than 95% of the sample variance with 4 principal components. The 5 selected wavelength pairs (Ex./Em. 300/315; 300/340; 280/300; 280/320; and 265/330 nm) are recommended as a sensitive fingerprint of the EVOOs. Of the subsequent models explored based on this fingerprint, a non-parametric fine k-NN classifier was found to best classify the cultivar and geographical origins of the EVOOs. This result demonstrates that multiple excitation fluorescence techniques can be used for authentication of EVOO cultivars and geographical origins.

Cultivar and geographical origin authentication of Italian extra virgin olive oil using front-face fluorescence spectroscopy and chemometrics

Perone C.;Giametta F.
Ultimo
2021-01-01

Abstract

A front-face fluorescence method has been used to obtain an excitation-emission matrix (EEM) of various Italian mono-cultivar, and mix-cultivar, extra virgin olive oils without any laborious sample preparation. These EEM use excitations from 230 to 360 nm and emissions from 260 to 390 nm to explore potential fingerprint characteristics that could be used for cultivar and geographical origin authentication. To simplify these complex spectral datasets, the variable reduction was undertaken using total absolute principal component coefficients. It has been found that at least 3 excitation wavelengths are necessary to obtain 5 variables which could explain more than 95% of the sample variance with 4 principal components. The 5 selected wavelength pairs (Ex./Em. 300/315; 300/340; 280/300; 280/320; and 265/330 nm) are recommended as a sensitive fingerprint of the EVOOs. Of the subsequent models explored based on this fingerprint, a non-parametric fine k-NN classifier was found to best classify the cultivar and geographical origins of the EVOOs. This result demonstrates that multiple excitation fluorescence techniques can be used for authentication of EVOO cultivars and geographical origins.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/97147
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