Producing of extra virgin olive oils (EVOOs) containing pleasant sensory notes depends on fruits quality and production process and is strongly associated with their classification that is based on ...aroma and sensory taste. Consolidated as an efficient method, the direct headspace solid phase microextraction technique (HS‐SPME) was utilized to characterize the volatile organic compounds (VOCs) profile, which contributes to the aroma of olive oils from southwestern (Serra da Mantiqueira region) and southern (Campanha Gaúcha region) Brazil. In this work, the relationship between the VOCs and sensory characteristics has been established; 19 EVOO samples (12 from Campanha Gaúcha and 7 from Serra da Mantiqueira) were studied. Indeed, the main volatile compounds were analyzed and grouped by their classification as well stood up with the trained sensorial panel perceptions. Relevant correlation between artichoke notes and ripe EVOO and between herbaceous notes and green EVOO was found. Additional correlations were observed for C5 and C6 VOCs with green and fruit/floral notes. The results denote the high quality among the samples and imply that besides the genetic factor, ripe or green classification influenced the volatile composition.
Practical Application
As the Brazilian olive oil production is increasing, knowing about different sensory characteristics and its correlation with the volatile compounds of extra virgin olive oil represents a good tool to improve the quality. Moreover, the application of direct SPME method was possible evidence in the differentiation of ripe and green olive oils, beyond the production region and in consonance with its sensory notes and characteristics.
•Olive oil phenolic compounds profiling using LC–ESI–TOF MS and GC–APCI–TOF MS.•PCA facilitated visualisation of natural clustering of studied oils.•Reliable PLS-DA models for varietal discrimination ...of studied oils were established.•Potential varietal markers were identified.
Over the last decades, the phenolic compounds from virgin olive oil (VOO) have become the subject of intensive research because of their biological activities and their influence on some of the most relevant attributes of this interesting matrix. Developing metabolic profiling approaches to determine them in monovarietal virgin olive oils could help to gain a deeper insight into olive oil phenolic compounds composition as well as to promote their use for botanical origin tracing purposes. To this end, two approaches were comparatively investigated (LC–ESI–TOF MS and GC–APCI–TOF MS) to evaluate their capacity to properly classify 25 olive oil samples belonging to five different varieties (Arbequina, Cornicabra, Hojiblanca, Frantoio and Picual), using the entire chromatographic phenolic profiles combined to chemometrics (principal component analysis (PCA) and partial least square-discriminant analysis (PLS–DA)). The application of PCA to LC–MS and GC–MS data showed the natural clustering of the samples, seeing that 2 varieties were dominating the models (Arbequina and Frantoio), suppressing any possible discrimination among the other cultivars. Afterwards, PLS–DA was used to build four different efficient predictive models for varietal classification of the samples under study. The varietal markers pointed out by each platform were compared. In general, with the exception of one GC–MS model, all exhibited proper quality parameters. The models constructed by using the LC–MS data demonstrated superior classification ability.
Within olive oils, extra virgin olive oil is the highest quality and, in consequence, the most expensive one. Because of that, it is common that some merchants attempt to take economic advantage by ...mixing it up with other less expensive oils, like olive oil or olive pomace oil. In consequence, the characterization and authentication of extra virgin olive oils is a subject of great interest, both for industry and consumers. This paper reports the potential of front-face total fluorescence spectroscopy combined with second-order chemometric methods for the detection of extra virgin olive oils adulteration with other olive oils. Excitation-emission matrices (EEMs) of extra virgin olive oils and extra virgin olive oils adulterated with olive oils or with olive pomace oils were recorded using front-face fluorescence spectroscopy. The full information content in these fluorescence images was analyzed with the aid of unsupervised parallel factor analysis (PARAFAC), PARAFAC supervised by linear discriminant analysis (LDA-PARAFAC), and discriminant unfolded partial least-squares (DA-UPLS). The discriminant ability of LDA-PARAFAC was studied through the tridimensional plots of the canonical vectors, defining a surface separating the established categories. For DA-UPLS, the discriminant ability was established through the bidimensional plots of predicted values of calibration and validation samples, in order to assign each sample to a given class. The models demonstrated the possibility of detecting adulterations of extra virgin olive oils with percentages of around 15% and 3% of olive and olive pomace oils, respectively. Also, UPLS regression was used to quantify the adulteration level of extra virgin olive oils with olive oils or with olive pomace oils.
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•Front-face autofluorescence of olive oils combined with LDA-PARAFAC and DA-UPLS.•LDA-PARAFAC discriminates between non and adulterated extra virgin olive oils.•Discrimination is satisfactory for adulterations higher than 16% with olive oils.•With olive pomace oils, discrimination is possible for levels higher than 3%.•UPLS allows to quantify the grade of adulteration.
Olea europaea, meaning “European olive,” is a small tree belonging to the family Oleaceae, occurring in the Mediterranean Basin. Olive oil is an essential component of a balanced diet because of its ...nutritional value. Among micronutrients, phenolic compounds did show important beneficial effects for human health. The majority of the research studies on the phenol content are carried out by liquid chromatography combined to photodiode array and/or mass spectrometry detection; however, because of matrix complexity, one‐dimensional liquid chromatography cannot be sometimes sufficient to obtain rewarding separations, requiring more advanced analytical techniques. In this work, comprehensive two‐dimensional liquid chromatography, incorporating RP‐Amide and C18 stationary phases, in the first and second dimension, respectively, both under reversed phase conditions, was investigated for the determination of the phenolic fraction in extra virgin olive oil samples. As far as detection is concerned, triple quadrupole mass spectrometry was employed under multi reaction monitoring mode offering superior selectivity and sensitivity. The reduction of matrix effects, when using comprehensive two‐dimensional liquid chromatography with respect to conventional one‐dimensional liquid chromatography, was assessed by comparing the slopes of calibration curves built from standard solutions and spiked olive oil samples.
A voltammetric electronic tongue (E-tongue) is “a multisensor system, which consists of a number of low-selective sensors and uses advanced mathematical procedures for signal processing based on ...pattern recognition and/or data multivariate analysis such as artificial neural networks (ANNs), principal component analysis (PCA), among others”. Thus, E-tongues in combination with chemometrics tools result in more accurate and selective analytical methods.
In this work, we report results of a simple and reliable electroanalytical method to determine butyl hydroxyanisole (BHA), butyl hydroxytoluene (BHT) and propyl gallate (PG) in edible olive oils (EOO). Therefore, the square wave voltammetry (SWV) was used on platinum and carbon fiber disk ultramicroelectrodes (E-tongue configuration) combined with chemometrics tools to perform these studies.
On the other hand, two data fusion strategies were used in order to combine electrochemical data obtained for each working electrode in the E-tongue: low-level data fusion (LLDF) and mid-level data fusion (MLDF). In addition, to reduce the dimensionality of the dataset in MLDF, the discrete wavelet transform (DWT) was used.
Finally, to assert the predictive capability of the method for BHA, BHT, and PG determination in real samples, a recovery study for the antioxidants in EOO samples was performed, demonstrating the analytical accuracy of the proposed method. Moreover, from the comparison between the proposed electrochemical method with the AOAC reference method and others found in the literature in terms of the quality of the model (REP %) and the percent recovery assays (%) in different samples, our results were better than other reported previously for the simultaneous determination of BHA, BHT, and PG in real samples. Moreover, the percent recovery assays obtained with the proposed electrochemical method were in good agreement with those obtained by the chromatographic method.
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•E-Tongues were used for the determination of BHA, BHT and PG in EOO samples.•Square wave voltammetry was used to perform the development of the method.•Mid-level data fusion (MLDF) to reduce the dimensionality of the dataset was used.•The method is very suitable to determine BHA, BHT and PG in EOO samples.
In this paper, an approach for the detection of extra-virgin olive oil (EVOO) free-acidity, based on combination of voltammetric profiles (Voltammetry) and Partial Least Squares (PLS) multivariate ...regression, is described. Voltammetric measurements are performed with a 12.5 μm radius platinum microdisk, directly in the oil samples mixed with 0.5 M of the room temperature ionic liquid (RTIL) tri-hexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide, which acted as a supporting electrolyte, and allows achieving a suitable conductivity in the matrices. Multivariate regression is performed directly on full voltammetric responses recorded over a properly chosen negative potential range and scan rate, where essentially all free fatty acids, characterizing EVOOs, can be reproducibly reduced. PLS regression models are built by employing Italian EVOO samples training sets at different acidity levels (over the range 0.2% w/w - 1.5% w/w; (% w/w) represents mass percentage) and optimized by choosing the optimal complexity, in terms of number of latent variables (LVs). The free-acidity prediction is made through a multivariate model, constructed by using standards of known acidity (determined by the official volumetric titration method) and validated on an external sample set. To show the validity of the proposed method, the PLS/Voltammetry predictions of the free-acidity of a series of commercially available Italian EVOOs, ranging from 0.2 to 0.41 %w/w, are obtained and the values compared with those determined by the official titration approach. Differences found between the two methods are within 5% RSD.
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•Voltammetry and chemometrics allow predicting free acidity of extra-virgin olive oils.•Direct voltammetry is performed in oils samples mixed with an ionic liquid.•Fatty acids of the oils samples produce voltammetric waves.•Partial least squares regression is applied to whole voltammetric profiles.•Acidity found by the PLS/voltammetry and the official method agrees satisfactorily.
Olive oil is an important product in the Mediterranean diet, due to its health benefits and sensorial characteristics.
is the most cultivated variety in Morocco. The present research aims to evaluate ...the phenolic compounds, vitamin E and fatty acids of commercial
virgin olive oils (VOOs) from five different North Moroccan provinces (Chefchaouen, Taounate, Errachidia, Beni Mellal and Taza), using HPLC-photodiode array (PDA)/electrospray ionization (ESI)-MS, normal phase (NP)-HPLC/ fluorescence detector (FLD) and GC-flame ionization detector (FID)/MS, respectively. The obtained results showed an average content of 130.0 mg kg
of secoiridoids (oleuropein aglycone, 10-hydroxy-oleuropein aglycone and ligstroside aglycone, oleocanthal and oleacein), 108.1 mg kg
of phenolic alcohols (tyrosol and hydroxytyrosol), 34.7 mg kg
of phenolic acids (caffeic acid, ferulic acid and elenolic acid), and 8.24 mg kg
of flavonoids (luteolin, luteolin glucoside, apigenin). With regard to vitamin E, α-tocopherol was the most abundant vitamin E (57.9 mg kg
), followed by α-tocotrienol (2.5 mg kg
), γ-tocopherol (4.5 mg kg
) and β-tocopherol (1.9 mg kg
), while δ-tocopherol was not detected. Moreover, 14 fatty acids were found and, among them, oleic acid (76.1%), linoleic acid (8.1%) palmitic acid (8.7%) and stearic acid (2.5%) were the major fatty acids detected. Finally, heat map and principal component analysis allowed us to classify the studied provinces in terms of VOO chemical composition: Chefchaouen (tyrosol and hydroxytyrosol), Taounate (oleuropein aglycone), Errachidia (ferulic acid,
-3 and
-6), Beni Mellal (oleocanthal) and Taza (luteolin and oleic acid).
•HPLC fingerprinting approach with the use of chemometric pattern recognition tools.•Fingerprints of phenolic compounds were monitored using dual detection (DAD and FLD).•Data fusion applied to HPLC ...(DAD and FLD) matrices.•Best combinations (LC data+statistical tool) for varietal authentication indicated.
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.
A new approach to the geographical characterisation of virgin olive oils (VOOs) based on the
1H NMR fingerprint of the unsaponifiable matter is presented. The
1H NMR spectra of the unsaponifiable ...fraction of virgin olive oils from Spain, Italy, Greece, Tunisia, Turkey, and Syria were analysed by several pattern recognition techniques (LDA, PLS-DA, SIMCA, and CART). PLS-DA (PLS-1 approach) obtained the best classification results for all classes. Moreover,
1H NMR spectra of the bulk oil, and its corresponding unsaponifiable fraction, as well as the subfractions of the unsaponifiable fraction (alcohol, sterol, hydrocarbon, and tocopherol fractions) were studied in the search for the markers that multivariate techniques revealed to be related to the geographical origin of olive oils. Additionally, a preliminary study regarding
1H NMR data of the bulk oil and the corresponding unsaponifiable fraction of VOOs suggested that these spectral data contained complementary information for the geographical characterisation of VOOs.
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