Use of 13 C nuclear magnetic resonance distortionless enhancement by polarization transfer pulse sequence and multivariate analysis to discriminate olive oil cultivars

Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers’ awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers’ interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

Chemometric Discrimination of the Varietal Origin of Extra Virgin Olive Oils: Usefulness of 13C Distortionless Enhancement by Polarization Transfer Pulse Sequence and 1H Nuclear Magnetic Resonance Data and Effectiveness of Fusion with Mid-Infrared Spectroscopy Data

The label authentication of monovarietal extra virgin olives is of great relevance from a socio-economical point of view. This work aims to gain insights into the prediction of the varietal origin of extra virgin olive oil (EVOO) samples obtained from single olive cultivars, French cultivars Olivière, Salonenque, and Tanche and Portuguese cultivars Blanqueta, Carrasquenha, and Galega Vulgar, collected in 2016-2017 and 2017-2018 harvest seasons. To pursue this study, spectroscopic approaches based on one-dimensional nuclear magnetic resonance (1D NMR) spectroscopy, namely, ¹H and ¹³C NMR distortionless enhancement by polarization transfer (DEPT) 45 pulse sequence, and Fourier transform mid-infrared spectroscopy (FT-MIR) are used in combination with partial least square discriminant analysis (PLS1-DA). The results obtained by PLS1-DA models using ¹H and ¹³C NMR DEPT 45 data are compared to those of PLS1-DA models using MIR data. The application of a control chart method allows for the optimization of the interpretation of the PLS1-DA results, and an efficient two-step strategy is proposed to improve the discrimination of the six studied cultivars. Then, NMR and MIR data are combined by either a mid- or high-level data fusion approach to further improve the discrimination. The models are also tested on samples from other cultivars to check their ability to reject varieties that were not considered in the calibration process.

Hybrid Filaments from Saccaharina lattisima Biomass: Engineering of Alginate Properties with Maleic Anhydride Grafted Linseed Oil

Linseed oil was graft modified with maleic anhydride and introduced into alginate by co-extrusion, producing alginate hybrid filaments. A straightforward grafting of maleic anhydride onto the oil backbone produced the modified oil. Additional esterification with n-dodecanol was also investigated. The structures of the modified oils were verified with 2D-NMR. The modified oil was mixed with alginate and extruded into CaCl2, forming thin filaments with diameters in the 130-260 μm range. The impact of oil integration into the alginate filaments was assessed, with special emphasis on stress-at-break, and compared to values predicted by an empirical model relating the "stress to alginate concentration" ratio to prevailing conditions during filament drawing. Analogous alginate filaments were prepared with hydrochloric-, oxalic- and phytic acid calcium salts for comparison with alginate-oil hybrids to reveal the induced impact, with respect to the composition and charge, on the tensile performance.

Seeking a Fast Screening Method of the Varietal Origin of Olive Oil: The Usefulness of an NMR-Based Approach

This work encompasses the use of 1D multinuclear NMR spectroscopy, namely, ¹H NMR and ¹³C NMR DEPT 45, combined with a multivariate statistical analysis to characterize olive oils produced from nine different varieties: Galega Vulgar, Cobrançosa, Cordovil de Serpa, Blanqueta, Madural, Verdeal Alentejana, Arbequina, Picual and Carrasquenha. Thus, the suitability of an NMR-based spectroscopic tool to discriminate olive oils according to their varietal origin is addressed. The results obtained show that the model based on ¹³C NMR DEPT 45 data has a stronger performance than the model based on ¹H NMR data, proving to be promising in the discrimination of the olive oils under study based on their varietal origin, being particularly relevant for olive oils of the Galega Vulgar variety.

Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

¹H NMR and Multivariate Analysis for Geographic Characterization of Commercial Extra Virgin Olive Oil: A Possible Correlation with Climate Data

¹H Nuclear Magnetic Resonance (NMR) spectroscopy coupled with multivariate analysis has been applied in order to investigate metabolomic profiles of more than 200 extravirgin olive oils (EVOOs) collected in a period of over four years (2009-2012) from different geographic areas. In particular, commercially blended EVOO samples originating from different Italian regions (Tuscany, Sicily and Apulia), as well as European (Spain and Portugal) and non-European (Tunisia, Turkey, Chile and Australia) countries. Multivariate statistical analysis (Principal Component Analisys (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA)) applied on the NMR data revealed the existence of marked differences between Italian (in particular from Tuscany, Sicily and Apulia regions) and foreign (in particular Tunisian) EVOO samples. A possible correlation with available climate data has been also investigated. These results aim to develop a powerful NMR-based tool able to protect Italian olive oil productions.

Nuclear magnetic resonance and chemometrics to assess geographical origin and quality of traditional food products

In this globalization era, the opening of the markets has put at almost everybody's disposal a wide variety of foods, allowing everybody to taste food flavors and aromas from different nations. Notwithstanding this opportunity, countries try to preserve their markets by developing protection policies. A few countries have adopted different denominations to label their "typical food" products in order to give them additional value. Besides, the term "typical food" is widely thought of as something anchored to the local traditions, with geographical meaning and made with typical raw materials. Then a "typical food" starts to be considered "traditional" when it is made following specific and old recipes. As a matter of fact, these products acquire particular organoleptic characteristics that are not reproducible when produced in different places. In this review, NMR studies coupled to multivariate statistical analysis are presented with the aim of determining geographical origin and key quality characteristics.

A novel approach to the rapid assignment of (13)C NMR spectra of major components of vegetable oils such as avocado, mango kernel and macadamia nut oils

Assignment of (13)C nuclear magnetic resonance (NMR) spectra of major fatty acid components of South African produced vegetable oils was attempted using a method in which the vegetable oil was spiked with a standard triacylglycerol. This proved to be inadequate and therefore a new rapid and potentially generic graphical linear correlation method is proposed for assignment of the (13)C NMR spectra of major fatty acid components of apricot kernel, avocado pear, grapeseed, macadamia nut, mango kernel and marula vegetable oils. In this graphical correlation method, chemical shifts of fatty acids present in a known standard triacylglycerol is plotted against the corresponding chemical shifts of fatty acids present in the vegetable oils. This new approach (under carefully defined conditions and concentrations) was found especially useful for spectrally crowded regions where significant peak overlap occurs and was validated with the well-known (13)C NMR spectrum of olive oil which has been extensively reported in the literature. In this way, a full assignment of the (13)C{1H} NMR spectra of the vegetable oils, as well as tripalmitolein was readily achieved and the resonances belonging to the palmitoleic acid component of the triacylglycerols in the case of macadamia nut and avocado pear oil resonances were also assigned for the first time in the (13)C NMR spectra of these oils.

Use of different artificial neural networks to resolve binary blends of monocultivar Italian olive oils

The problem of authenticating extra virgin olive oil varieties is particularly important from the standpoint of quality control. After having shown in our previous works the possibility of discriminating oils from a single variety using chemometrics, in this study a combination of two different neural networks architectures was employed for the resolution of simulated binary blends of oils from different cultivars. In particular, a Kohonen self-organizing map was used to select the samples to include in the training, test and validation sets, needed to operate the successive calibration stage, which has been carried out by means of several multilayer feed-forward neural networks. The optimal model resulted in a validation Q2 in the range 0.91-0.96 (10 data sets), corresponding to an average prediction error of about 5-7.5%, which appeared significantly better than in the case of random or Kennard-Stone selection.

Implementation of Physicochemical and Sensory Analysis in Conjunction with Multivariate analysis towards Assessing Olive Oil Authentication/Adulteration

The authenticity of products labeled as olive oils, and in particular as virgin olive oils, stands for a very important issue both in terms of its health and commercial aspects. In view of the continuously increasing interest in virgin olive oil therapeutic properties, the traditional methods of characterization and physical and sensory analysis were further enriched with more advanced and sophisticated methods such as HPLC-MS, HPLC-GC/C/IRMS, RPLC-GC, DEPT, and CSIA among others. The results of both traditional and "novel" methods were treated both by means of classical multivariate analysis (cluster, principal component, correspondence, canonical, and discriminant) and artificial intelligence methods showing that nowadays the adulteration of virgin olive oil with seed oil is detectable at very low percentages, sometimes even at less than 1%. Furthermore, the detection of geographical origin of olive oil is equally feasible and much more accurate in countries like Italy and Spain where databases of physical/chemical properties exist. However, this geographical origin classification can also be accomplished in the absence of such databases provided that an adequate number of oil samples are used and the parameters studied have "discriminating power."

13C nuclear magnetic resonance spectroscopy to determine olive oil grades

13C nuclear magnetic resonance spectroscopy was used in a first attempt to differentiate olive oil samples by grades. High resolution 13C NMR Distortionless Enhancement by Polarization Transfer (DEPT) spectra of 137 olive oil samples from the four grades, extra virgin olive oils, olive oils, olive pomace oils and lampante olive oils, were measured. The data relative to the resonance intensities (variables) of the unsaturated carbons of oleate (C-9 and C-10) and linoleate (L-9, L-10 and L-12) chains attached at the 1,3- and 2-positions of triacylglycerols were analyzed by linear discriminant analysis. The 1,3- and 2- carbons of the glycerol moiety of triacylglycerols along with the C-2, C-16 and C-18 resonance intensities of saturated, oleate and linoleate chains were also analyzed by linear discriminant analysis. The three discriminanting functions, which were calculated by using a stepwise variable selection algorithm, classified in the true group by cross-validation procedure, respectively, 76.9, 70.0, 94.4 and 100% of the extra virgin, olive oil, olive pomace oil and lampante olive oil grades.

Use of flow injection atmospheric pressure photoionization quadrupole time-of-flight mass spectrometry for fast olive oil fingerprinting

The recently introduced technique of an atmospheric pressure photoionization (APPI) source coupled to quadrupole time-of-flight mass spectrometry (QqTOFMS) has been applied to fast olive oil fingerprinting on the basis of the accurate mass measurements obtained with this instrumentation. The key compounds can be characterized as [M+H]+ (produced by proton transfer) or as [M]+* (by charge transfer) ions in the mass spectra. [M+H]+ ions, however, show higher abundance, especially for triacylglycerols. Other ions present in APPI-MS are the acylium ion [RiCO]+ and [RiCO-H2O]+. This latter ion is absent in the electrospray ionization (ESI)-MS spectra, and this represents valuable complementary information. Several critical parameters in the APPI source were optimized such as LC eluent composition, ion spray voltage and, especially, declustering potential. APPI-QqTOFMS allows easy discrimination among different edible oils: olive, extra virgin olive, olive-pomace, hazelnut, sunflower, corn and several mixed oils, with high throughput (approximately 1 min per sample). Cluster analysis was applied to obtain the best experimental conditions for oil discrimination on the basis of declustering potential. Principal components analyses of these APPI-MS spectra show that the approach can be used for studies of olive oil adulteration with other oils, even in the case of hazelnut oil that exhibits a high chemical similarity with olive oil.

Rapid quantitative assessment of the adulteration of virgin olive oils with hazelnut oils using Raman spectroscopy and chemometrics

The authentication of extra virgin olive oil and its adulteration with lower-priced oils are serious problems in the olive oil industry. In addition to the obvious effect on producer profits, adulteration can also cause severe health and safety problems. A number of techniques, including chromatographic and spectroscopic methods, have recently been employed to assess the purity of olive oils. In this study Raman spectroscopy together with multivariate and evolutionary computational-based methods have been employed to assess the ability of Raman spectroscopy to discriminate between chemically very closely related oils. Additionally, the levels of hazelnut oils used to adulterate extra virgin olive oil were successfully quantified using partial least squares and genetic programming.

Determination of geographical origin of olive oils using 13C nuclear magnetic resonance spectroscopy. I - Classification of olive oils of the Puglia region with denomination of protected origin

13C nuclear magnetic resonance spectroscopy was used to classify olive oils from the three production areas of the Puglia region labeled with the "denomination of protected origin" (DPO) Terra di Bari, Colline di Brindisi, and Dauno. High resolution (13)C spectra of 173 olive oil samples were measured, and the intensity data of triacylglycerol resonances were processed by using linear discriminant analysis, which was carried out stepwise for variable selection. The olive oil samples from the DPOs Colline di Brindisi and Terra di Bari were 90% correctly classified, whereas only 74% of "Dauno" DPO oils were classified in the true group. The performance of the discriminant model was verified by applying the cross-validation procedure based on the "leave one out" formalism. The discriminant model was evaluated against a blind test set of olive oils from the three DPO areas. All the oils used for the purpose were correctly assigned to their respective groups, with the exception of the Dauno oil samples based on the Coratina cv. They were misclassified as Terra di Bari oils because of a common monovarietal composition.

Triacylglycerol and fatty acid compositions of French virgin olive oils. Characterization by chemometrics

There is no data concerning the fatty acid and triacylglycerol composition of French virgin olive oil. Thus, these compositions were determined using 564 samples coming from four olive harvests (1998-1999 to 2000-2001). Among these 564 samples, 372 came from the four main French cultivars (Aglandau, Cailletier, Picholine, and Salonenque) and from both of the oldest French protected designations of origin: "Nyons" (cv. Tanche) and "Vallée des Baux". The fatty acid compositions took the different isomeric monounsaturated fatty acids (C16:1 and C18:1) into account. The eicosenoic acid is gondoic acid (20:1n-9) and was determined by dimethyl disulfide adduct using GC/MS. The use of propionitrile as a mobile phase for the HPLC analysis of the triacylglycerols led to better resolutions between triacylglycerols than those resolutions obtained with the mix of solvents recommended by the normalized method (acetone/acetonitrile). Of the samples, 88 had a 9-heptadecenoic acid level (17:1n-8) higher than 0.3% and 33 had a linolenic acid level higher than 0.9%, which are maximal values accepted by the International Olive Oil Council and the European Union. A linear discriminant analysis was carried out on 372 samples with the SAS system and particularly with STEPISC and CANDISC procedures. Variables (n = 37) representing the different fatty acids, the sum of saturated, monounsaturated, and polyunsaturated fatty acids, squalene, and triacylglycerols were used, thus allowing us to classify samples into six groups defined with 100% of well classified samples. These results constitute an original data bank that can be used to identify the origin of virgin olive oils.

Using simple 13C NMR linewidth and relaxation measurements to make detailed chemical shift assignments in triacylglycerols and related compounds

Two simple experiments measuring the 13C linewidths nu(1/2) and spin-lattice relaxation times T(1) of each of the signals in the spectrum of trilinolein indicate that the nu(1/2) and T(1) values are consistent with the different degrees of motional freedom expected for the various 13C nuclei. However, for each chain, the nu(1/2) and T(1) measurements indicate a small reversal in mobility at C-10 relative to C-9 before motional freedom again steadily increases on each chain starting at C-11. The T(1) experiment allows unambiguous assignments of the C-8 signal and C-14 signal, which differ by only 0.010 ppm. Measurements of 13C nu(1/2) and T(1) values on tripalmitin provide secure assignments for the C-5 and C-6 signals, for which conflicting assignments have been reported. The T(1) measurements also show that among the tightly clustered C-8 through C-12 signals, the C-11 signals are the most downfield, while the C-12 signals are the most upfield, again contrary to a previous report. Similar measurements of 13C nu(1/2) and T(1) values on other triacylglycerols or related compounds may prove equally useful in making chemical shift assignments and detecting any discontinuities in motional freedom along a chain. The benefits and possible limitations of ultrahigh field NMR for studying triacylglycerols and related compounds are discussed.

(13)C NMR characterization of triacylglycerols of Moringa oleifera seed oil: an "oleic-vaccenic acid" oil

The composition of acyl chains and their positions in the triacylglycerols of the oil extracted from seeds of Moringa oleifera were studied by (13)C NMR spectroscopy. The unsaturated chains of M. oleifera seed oil were found to comprise only mono-unsaturated fatty acids and, in particular, two omega-9 mono-unsaturated acids, (cis-9-octadecenoic (oleic acid) and cis-11-eicosenoic acids) and one omega-7 mono-unsaturated acid (cis-11-octadecenoic acid (vaccenic acid)). The mono-unsaturated fatty acids were detected as separated resonances in the spectral regions where the carbonyl and olefinic carbons resonate according to the 1,3- and 2-positions on the glycerol backbone. The unambiguous detection of vaccenic acid was also achieved through the resonance of the omega-3 carbon. The (13)C NMR methodology enabled the simultaneous detection of oleate, vaccenate, and eicosenoate chains according to their positions on the glycerol backbone (1,3- and 2-positions) through the carboxyl, olefinic, and methylene envelope carbons of the triacylglycerol acyl chains.

Chemical authentication of extra virgin olive oil varieties by supervised chemometric procedures

This work has focused on discriminating extra virgin olive oils from Sabina (Lazio, Italy) by olive fruit variety (cultivar). A set of oils from five of the most widespread cultivars (Carboncella, Frantoio, Leccino, Moraiolo, and Pendolino) in this geographical area was analyzed for chemical composition using only the Official Analytical Methods, recognized for the quality control and commercial classification of this product. The obtained data set was converted into a computer-compatible format, and principal component analysis (PCA) and a method based on the Fisher F ratio were used to reduce the number of variables without a significant loss of chemical information. Then, to differentiate these samples, two supervised chemometric procedures were applied to process the experimental data: linear discriminant analysis (LDA) and artificial neural network (ANN) using the back-propagation algorithm. It was found that both of these techniques were able to generalize and correctly predict all of the samples in the test set. However, these results were obtained using 10 variables for LDA and 6 (the major fatty acid percentages, determined by a single gas chromatogram) for ANN, which, in this case, appears to provide a better prediction ability and a simpler chemical analysis. Finally, it is pointed out that, to achieve the correct authentication of all samples, the selected training set must be representative of the whole data set.