Cluster Analysis Applied to the Exploratory Analysis of Commercial Spanish Olive Oils by Means of Excitation−Emission Fluorescence Spectroscopy

Abstract

Olive oil fluorescence is related to oil composition. Here it is shown that the natural clustering of different types of commercial Spanish olive oils depends on their fluorescence excitation-emission matrices (EEMs). Fifty-six commercial samples of olive oil (29 virgin olive oils, 20 pure olive oils, and 7 olive-pomace oils) were used. The clustering method was hierarchical agglomerative clustering using the Euclidean distance as a similarity measure and the average linkage. Two spectral ranges were considered (which either contained the fluorescence peak of the chlorophylls or did not), and various methods for preprocessing the fluorescence spectra were compared. The oils were clearly distinguished using the unfolded EEMs measured between lambda(ex) = 300-400 nm and lambda(em) = 400-600 nm. The optimal preprocessing was normalization of the unfolded spectra followed by column autoscaling. Also shown are the advantages of using second-order data (EEMs) instead of first-order data (a single fluorescence spectrum) for each sample.

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

“…Therefore, the information obtained is more objective. In addition, CA can reduce dimensionality while retaining the required information [16]. Figure 5 shows a dendogram that illustrates the stages of linkage.…”

Determination of the cultivar and aging of Sicilian olive oils using HPLC‐MS and linear discriminant analysis

“…[18,19] Further, a statistical elaboration of raw data provides more detailed information on the characteristics of the oil samples not otherwise achievable. Currently, in literature, there are a number of studies in which principal component analysis (PCA) [20,21] or cluster analysis (CA) [22] or linear discriminant analysis (LDA) [20,21,23] are carried out.…”

Chemometrical and molecular methods in olive oil analysis: A review

“…In olive OO research, the method has been used together with PCA in order to analyze fluorescence spectroscopy data of OO by Guimet, Boqué, and Ferré () in a form called “parallel factor analysis” (PARAFAC). The authors analyzed two types of oils (28 EVOOs and 1 VOO, and 20 pomace OO) using unfold‐PCA (it involves computing principal component of a matrix obtained after unfolding a three‐way original array) and PARAFAC.…”

“…HCA with Euclidean distances used a measure was applied by Guimet et al () on 56 OOs (29 VOOs, 20 pure OOs, and 7 pomace OOs). The oils were described on their fluorescence excitation−emission matrices (EEMs) data.…”