Prediction of the genetic variety of Spanish extra virgin olive oils using fatty acid and phenolic compound profiles established by direct infusion mass spectrometry

Characteristics of Some Wild Olive Phenotypes (Oleaster) Selected from the Western Mountains of Syria

This study presents the evaluation of some technological and production specifications of 20 selected wild olive (oleaster) phenotypes from Hama Province, western–central Syria. The analyses of oil quantity showed that the olive oil (OO) extracted ranged from 10.43 to 29.3%. The fatty acid composition determined by gas chromatography (m/m%, methyl esters), conforming to commercial standards, showed the percentages of palmitic (ranged 13.2–15.06%), stearic (2.27–4.2%), arachidic (0.42–0.7%), palmitoleic (0.73–1.25%), oleic (64.29–73.17%), linoleic (8.96–16.45%), and linolenic (0.23–1.6%). Our results suggest that, despite being in a harsh environment and lacking agricultural service, two wild olive phenotypes (WA4, WA6) are interesting since their fruits showed high-quality properties (fruit weight 2.16, 3.24 g; flesh 75.83, 86.2, respectively), high content of OO% (29.27, 29.01, respectively), and better fatty acid composition (oleic % 68.45, 66.74, respectively). This enables them to be a very promising introductory feature in olive genetic improvement processes. Thus, both phenotypes were adopted tentatively as inputs, the first for oil purposes and the second for dual purposes (oil and table olives). It will be important to further evaluate these promising phenotypes in terms of their OO minor compounds, as well as their ability to resist biotic and abiotic stresses.

Olive Oil Quality and Authenticity Assessment Aspects Employing FIA-MRMS and LC-Orbitrap MS Metabolomic Approaches

Edible vegetable oils comprise integral components of humans' daily diet during the lifetime. Therefore, they constitute a central part of dietary-exposome, which among other factors regulates human health. In particular, the regular consumption of olive oil (OO) has been largely accepted as a healthy dietary pattern. Responsible for its recognition as a superior edible oil is its exceptional aroma and flavor. Its unique composition is characterized by high levels of monounsaturated fatty acids and the presence of minor constituents with important biological properties, such as the so-called OO polyphenols. Being a high added value product, OO suffers from extensive fraud and adulteration phenomena. However, its great chemical complexity, variability, and the plethora of parameters affecting OO composition hamper significantly the selection of the absolute criteria defining quality and authenticity, and a reliable and robust methodology is still unavailable. In the current study, Flow Injection Analysis-Magnetic Resonance Mass Spectrometry (FIA-MRMS) was investigated under a metabolic profiling concept for the analysis of Greek Extra Virgin Olive Oils (EVOO). More than 200 monovarietal (Koroneiki) EVOO samples were collected from the main Greek OO producing regions and investigated. Both intact oil and the corresponding polyphenols were analyzed in fast analysis time of 2 and 8 min, respectively. In parallel, an LC-Orbitrap MS platform was used to verify the efficiency of the method as well as a tool to increase the identification confidence of the proposed markers. Based on the results, with FIA-MRMS, comparable and improved projection and prediction models were generated in comparison to those of the more established LC-MS methodology. With FIA-MRMS more statistically significant compounds and chemical classes were identified as quality and authenticity markers, associated with specific parameters, i.e. geographical region, cultivation practice, and production procedure. Furthermore, it was possible to monitor both lipophilic and hydrophilic compounds with a single analysis. To our knowledge, this approach is among the few studies in which two FT-MS platforms combining LC and FIA methods were integrated to provide solutions to quality control aspects of OO. Moreover, both lipophilic and hydrophilic components are analyzed together, providing a holistic quality control workflow for OO.

Comparison and Discrimination of Two Major Monocultivar Extra Virgin Olive Oils in the Southern Region of Peloponnese, According to Specific Compositional/Traceability Markers

The qualitative characteristics and chemical parameters were determined for 112 virgin olive oil samples of the two dominant olive cultivars in the southern region of Peloponnese, cv. Koroneiki and cv. Mastoides. As no relevant data exist for this geographical area, yet one of the most important olive-growing regions in Greece, this study aimed to evaluate and evidence the differences on specific chemical characteristics of the oils because of their botanical origin. Olive oils of Koroneiki variety were characterized by a three-fold lower concentration in heptadecanoic and heptadecenoic acid compared to oils of cv. Mastoides. In addition, Mastoides oils exhibited higher β-sitosterol and total sterols concentration and lower Δ-5-avenasterol and total erythodiol content compared to Koroneiki olive oils Analysis of variance and principal component analysis of the GC-analyzed olive oil samples showed substantial compositional differences in the fatty acid and sterolic profile between Koroneiki and Mastoides cultivars. Hence, results demonstrate that the fatty acid and sterolic profile can be used as exceptional compositional marker for olive oil authenticity.

High-resolution mass spectrometry to evaluate the influence of cross-breeding segregating populations on the phenolic profile of virgin olive oils

BACKGROUND

The growing demand for high-quality virgin olive oils (VOOs) has increased the interest in olive breeding programs. Cross-breeding is considered, within these programs, the best strategy to generate new cultivars as an attempt to improve the present cultivars. In this research, the phenolic profile of VOOs from target crosses (Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana) and their corresponding genitors (Arbequina, Arbosana, Koroneiki, Picual and Sikitita) has been evaluated using a targeted metabolomics approach.

RESULTS

The phenolic profiles were obtained by liquid chromatographic-hybrid quadrupole time-of-flight mass spectrometric targeted analysis of 37 phenols or compounds involved in the main pathways for their biosynthesis. Statistical multivariate analysis by principal component analysis was applied to study the influence of genotype on phenol composition. Phenolic compounds with the highest contribution to explain the observed variability associated to genotype were identified through fold change algorithms (cut-off > 2.0) and t-test analysis.

CONCLUSION

A total of nine phenols (viz. quercetin, ligstroside aglycon (p-HPEA-EA), demethyl oleuropein aglycon, oleuropein aglycon (3,4-DHPEA-EA), hydroxypinoresinol, hydroxytyrosol and phenolic acids such as p-coumaric acid, ferulic acid and protocatechuic acid) contributed to explain the observed variability with 99% confidence (P<0.01).

Determination of nonprotein amino acids and betaines in vegetable oils by flow injection triple-quadrupole tandem mass spectrometry: a screening method for the detection of adulterations of olive oils

A novel screening method using an automated flow injection electrospray ionization tandem mass spectrometry system is proposed for the simultaneous determination of five nonprotein amino acids (β-alanine, alloisoleucine, ornithine, citrulline, pyroglutamic acid) and three betaines (glycine betaine, trigonelline, proline betaine) after derivatization with butanolic HCl. MS/MS experiments were carried out in a triple-quadrupole instrument using multiple reaction monitoring mode in <2 min. The proposed method provided high fingerprinting power to identify the presence of five of the studied compounds in different types of vegetable oils (soybean, sunflower, corn, olive) with LODs at parts per billion levels. The method was validated, and different mixtures of extra virgin olive oil with seed oils were analyzed, achieving the typification for the detection of adulterations in extra virgin olive oils up to 2% w/w. The nonprotein amino acid ornithine was confirmed as a marker for adulteration in the olive oils analyzed.

Foodomics: MS-based strategies in modern food science and nutrition

Modern research in food science and nutrition is moving from classical methodologies to advanced analytical strategies in which MS-based techniques play a crucial role. In this context, Foodomics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Applications of Foodomics include the genomic, transcriptomic, proteomic, and/or metabolomic study of foods for compound profiling, authenticity, and/or biomarker-detection related to food quality or safety; the development of new transgenic foods, food contaminants, and whole toxicity studies; new investigations on food bioactivity, food effects on human health, etc. This review work does not intend to provide an exhaustive revision of the many works published so far on food analysis using MS techniques. The aim of the present work is to provide an overview of the different MS-based strategies that have been (or can be) applied in the new field of Foodomics, discussing their advantages and drawbacks. Besides, some ideas about the foreseen development and applications of MS-techniques in this new discipline are also provided.

Comparison between classical and innovative class-modelling techniques for the characterisation of a PDO olive oil

An authentication study of the Italian PDO (protected designation of origin) olive oil Chianti Classico, based on near-infrared and UV-Visible spectroscopy, an artificial nose and an artificial tongue, with a set of samples representative of the whole Chianti Classico production and a considerable number of samples from a close production area (Maremma) was performed. The non-specific signals provided by the four fingerprinting analytical techniques, after a proper pre-processing, were used for building class models for Chianti Classico oils. The outcomes of classical class-modelling techniques like soft independent modelling of class analogy and quadratic discriminant analysis-unequal dispersed classes were compared with those of two techniques recently introduced into Chemometrics: multivariate range modelling and CAIMAN analogues modelling methods.

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

A large number of certified samples (84) of Sicilian olive oils arising from the eight cultivars most represented in Sicily (Biancolilla, Cerasuola, Moresca, Nocellara del Belice, Nocellara Etnea, Oglialora Messinese, Brandofino and Tonda Iblea) have been collected and analyzed by HPLC/MS using an atmospheric pressure chemical ionization (APCI) source. The sample preparation is very simple; in fact, the oil samples are diluted without any chemical derivatization. A following statistical data treatment by general discriminant analysis (GDA) allows the determination of the olive oil cultivar. Furthermore, changes in the composition of glyceridic components of the olive oils lead to easy discrimination between fresh oils and 1-year-old samples.

Traceability markers to the botanical origin in olive oils

This review provides an overview of traceability studies performed to date (April 2009) for olive oils. Special emphasis has been made on the botanical origin because high-quality monovarietal olive oils have been recently introduced on the markets and their quality control requires the development of new and powerful analytical tools as well as new regulations to avoid fraud to consumers. Several parameters with discriminant power have been used for olive oil traceability according to the olive variety used in the production of the oil. They have been considered as traceability markers to the botanical origin and classified, in this work, as compositional and genetical markers.

Classification of extra virgin olive oils produced at La Comunitat Valenciana according to their genetic variety using sterol profiles established by high-performance liquid chromatography with mass spectrometry detection

A method to classify extra virgin olive oils (EVOOs) according to their genetic variety using sterol profiles obtained by high-performance liquid chromatography (HPLC) with mass spectrometry (MS) detection has been developed. Sterol extracts were chromatographed on a dC18 Atlantis column (100x3 mm, 3 microm) with a gradient of acetonitrile/water (0.01% acetic acid) at a flow rate of 1.0 mL min(-1) and positive-ion mode MS detection. Using linear discriminant analysis of the HPLC-MS data (extracted ion chromatograms), EVOO samples belonging to six genetic varieties cultivated at La Comunitat Valenciana, Spain (Arbequina, Borriolenca, Canetera, Farga, Picual, and Serrana), were correctly classified with an excellent resolution among all of the categories.