A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication.

Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H3O+, NO+ and O2+ as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases).

Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics.

High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted.

In-Depth Two-Year Study of Phenolic Profile Variability among Olive Oils from Autochthonous and Mediterranean Varieties in Morocco, as Revealed by a LC-MS Chemometric Profiling Approach.

Olive oil phenolic fraction considerably contributes to the sensory quality and nutritional value of this foodstuff. Herein, the phenolic fraction of 203 olive oil samples extracted from fruits of four autochthonous Moroccan cultivars ("Picholine Marocaine", "Dahbia", "Haouzia" and "Menara"), and nine Mediterranean varieties recently introduced in Morocco ("Arbequina", "Arbosana", "Cornicabra", "Frantoio", "Hojiblanca", "Koroneiki", "Manzanilla", "Picholine de Languedoc" and "Picual"), were explored over two consecutive crop seasons (2012/2013 and 2013/2014) by using liquid chromatography-mass spectrometry. A total of 32 phenolic compounds (and quinic acid), belonging to five chemical classes (secoiridoids, simple phenols, flavonoids, lignans and phenolic acids) were identified and quantified. Phenolic profiling revealed that the determined phenolic compounds showed variety-dependent levels, being, at the same time, significantly affected by the crop season. Moreover, based on the obtained phenolic composition and chemometric linear discriminant analysis, statistical models were obtained allowing a very satisfactory classification and prediction of the varietal origin of the studied oils.

Comprehensive 3-year study of the phenolic profile of Moroccan monovarietal virgin olive oils from the Meknès region.

The phenolic fraction of monovarietal virgin olive oils (VOOs) from the main Moroccan cultivar Picholine marocaine (142 samples from three different subareas of the Meknès region) was studied over three consecutive crop seasons (2011, 2012, and 2013) using a powerful LC-MS methodology. First, LC-ESI-TOF MS was used to get a comprehensive characterization of the phenolic fraction; afterward, LC-ESI-IT MS was utilized for further identification (MS/MS experiments) and quantitation purposes. A total of 28 phenolic compounds (and quinic acid) were determined, revealing the complex profile of Meknès VOO, composed, in order of abundance, by secoiridoids, phenolic alcohols, lignans, flavonoids, and phenolic acids. Tukey's test was applied to ascertain possible significant intraregional and/or interannual variations of the phenolic content of the Meknès VOOs under study. Results showed that the content of phenolic compounds was mainly related to the crop season.

Quality and chemical profiles of monovarietal north Moroccan olive oils from "Picholine Marocaine" cultivar: registration database development and geographical discrimination.

Current knowledge of the quality and composition of Moroccan olive oil is still incomplete and no consistent database compiling its properties is available. This study was carried out to achieve a comprehensive characterisation of north Moroccan olive oils. Thus, 279 olive samples of "Picholine Marocaine" cultivar grown in 7 Moroccan regions were collected, and oils extracted over two consecutive crop seasons (2011 and 2012) and analysed (considering physicochemical quality parameters and purity criteria). Results indicated that all the studied samples showed values fulfilling the established limits set by the International Olive Council (IOC) standards, with the exception of 32 samples that had a linolenic acid content higher than 1%, which is the maximum value fixed by the IOC regulation. Furthermore, the usefulness of the evaluated parameters for tracing the geographical origin of the studied samples was tested by using canonical discriminant analysis. A good rate of correct classification and prediction was achieved.

First comprehensive characterization of volatile profile of north Moroccan olive oils: A geographic discriminant approach.

Herewith we have evaluated the variability of the composition in terms of volatile compounds of monovarietal "Picholine marocaine" olive oils and checked the possible influence of their geographical origin. For this purpose, 92 olive samples were collected during the harvesting period 2012/2013 from 7 north Moroccan regions, and the analysis of the volatile profiles of the obtained oils was performed by using headspace solid-phase microextraction coupled to gas chromatography with flame ionization and mass spectrometry detectors (HS-SPME/GC-FID-MS). A total of 40 volatile compounds belonging to different chemical classes were identified and quantified. Significant differences in the concentration levels of volatile constituents from oils of different geographical origins were found. Furthermore, for testing the ability of the identified volatile compounds for the geographical origin discrimination of the investigated oils, a stepwise linear discriminant analysis (s-LDA) was applied. Results revealed a very satisfactory classification of the studied oils according their geographic origin.

Potential of LC-MS phenolic profiling combined with multivariate analysis as an approach for the determination of the geographical origin of north Moroccan virgin olive oils.

The applicability of two different platforms (LC-ESI-TOF MS and LC-ESI-IT MS) as powerful tools for the characterisation and subsequent quantification of the phenolic compounds present in north Moroccan virgin olive oils was assessed in this study. 156 olives samples of "Picholine Marocaine" cultivar grown in 7 Moroccan regions were collected and olive oils extracted. The phenolic profiles of these olive oils were studied using a resolutive chromatographic method coupled to ESI-TOF MS (for initial characterisation purposes) and coupled to ESI-IT MS (for further identification and quantification). 25 phenolic compounds belonging to different chemical families were identified and quantified. Secoiridoids were the most abundant phenols in all the samples, followed by phenolic alcohols, lignans and flavonoids, respectively. For testing the ability of phenolic profiles for tracing the geographical origin of the investigated oils, multivariate analysis tools were used, getting a good rate of correct classification and prediction by using a cross validation procedure.