The Use of FTIR Spectroscopy and Chemometrics for Rapid Authentication of Extra Virgin Olive Oil

The authenticity of high value edible fats and oils including extra virgin olive oil (EVOO) is an emerging issue, currently. The potential employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis has been exploited for rapid authentication of EVOO from canola oil (Ca‐O). The optimization of two calibration models of partial least square (PLS) and principle component regression was performed in order to quantify the level of Ca‐O in EVOO. The chemometrics of discriminant analysis (DA) was used for making the classification between pure EVOO and EVOO adulterated with Ca‐O. The individual oils and their blends were scanned on good contact with ZnSe crystals in horizontal attenuated total reflectance, as a sampling technique. The wavenumbers of 3,028–2,985 and 1,200–987 cm^?1 were used for quantification and classification of EVOO adulterated with Ca‐O. The results showed that PLS with normal FTIR spectra was well suited for quantitative analysis of Ca‐O with a value of the coefficient of determination (R²) > 0.99. The error, expressed as root mean square error of calibration obtained was relatively low, i.e. 0.108 % (v/v). DA can make the classification between pure EVOO and that adulterated with Ca‐O with one misclassified reported.     

The use of electronic and human nose for monitoring rapeseed oil autoxidation

This work was aimed at assessing the effectiveness of the electronic nose to monitor off‐flavor associated with lipid oxidation as a supplementary tool to human sensory panel assessment. Therefore, correlations between electronic nose and sensory analysis were determined. Also GC analyses and chemical analyses of oil samples were run to characterize the analyzed samples with well‐described parameters. Refined rapeseed oil was subjected to an accelerated storage test for 12 days at 60 °C and to an ambient temperature storage test in which it was stored in retail plastic bottles for up to 6 months. PCA of electronic nose data samples stored at an elevated temperature was related to PCA of sensory analysis, and similarities in sample clustering were observed. For samples stored at room temperature, the human panel showed greater sensitivity than the electronic nose. Prediction models based on PLS of electronic nose data were able to predict the sensory quality changes during storage at elevated and room temperature, ranging from 0.721 to 0.989 and from 0.849 to 0.881 (p <0.05), respectively. PV and p‐AV were well predicted on the basis of both electronic nose (0.989, 0.998 for elevated temperature; 0.907, 0.881 for room temperature) and sensory analysis data (0.973, 0.993 for elevated temperature; 0.939, 0.886 for room temperature). Applicability of the electronic nose technology to verify sensory and rancidity changes during storage showed to be promising in quality control of oils.     

Application of a spectroscopic method to estimate the olive oil oxidative status

A rapid Fourier transformed infrared (FTIR) attenuated total reflectance (ATR) spectroscopic method coupled with partial least squares (PLS), was developed to estimate the oxidation degree of extra virgin olive oil (EVOO). The reference values of EVOO oxidation for the FTIR calibration were obtained by the specific absorptions at 232 and 270 nm, due to the presence of conjugated diene (CD) and conjugated triene (CT) groups, as monitored by the UV spectrophotometric determination. Specific washing procedures were applied to the EVOO to obtain EVOOP and EVOOTP samples, without phenolic compounds and without tocopherols and phenols, respectively. To obtain different oxidation degrees covering wide CD and CT ranges, EVOO, EVOOP, and EVOOTP samples were subjected to a forced oxidation at 60°C for 20 days and aliquots of the oils were daily analyzed. Regression of the FTIR/PLS‐predicted CD and CT of individual oxidized oils EVOO, EVOOP, EVOOTP, and all combined oils (EVOOALL) against UV–Visible reference values demonstrated the good quality of the models in terms of R² and RMSECV values. The results of the study indicated that a strong correlation existed between FTIR and UV–Visible peak intensities. Practical applications: The FTIR‐ATR method coupled with PLS elaboration was developed and applied to predict the oxidation degree of EVOO samples with considerable advantages in terms of simplicity, analysis time, and solvent consumption as compared to the standard method. Moreover, suitable adjustments of the equipment could permit a rapid control at‐line in oil sector.     

Novel,Rapid Identification,and Quantification of Adulterants in Extra Virgin Olive Oil Using Near‐Infrared Spectroscopy and Chemometrics

A new, rapid Fourier transform near infrared (FT‐NIR) spectroscopic procedure is described to screen for the authenticity of extra virgin olive oils (EVOO) and to determine the kind and amount of an adulterant in EVOO. To screen EVOO, a partial least squares (PLS1) calibration model was developed to estimate a newly created FT‐NIR index based mainly on the relative intensities of two unique carbonyl overtone absorptions in the FT‐NIR spectra of EVOO and other mixtures attributed to volatile (5280 cm^?1) and non‐volatile (5180 cm^?1) components. Spectra were also used to predict the fatty acid (FA) composition of EVOO or samples spiked with an adulterant using previously developed PLS1 calibration models. Some adulterated mixtures could be identified provided the FA profile was sufficiently different from those of EVOO. To identify the type and determine the quantity of an adulterant, gravimetric mixtures were prepared by spiking EVOO with different concentrations of each adulterant. Based on FT‐NIR spectra, four PLS1 calibration models were developed for four specific groups of adulterants, each with a characteristic FA composition. Using these different PLS1 calibration models for prediction, plots of predicted vs. gravimetric concentrations of an adulterant in EVOO yielded linear regression functions with four unique sets of slopes, one for each group of adulterants. Four corresponding slope rules were defined that allowed for the determination of the nature and concentration of an adulterant in EVOO products by applying these four calibration models. The standard addition technique was used for confirmation.     

Classification of Turkish Monocultivar (Ayvalık and Memecik cv.) Virgin Olive Oils from North and South Zones of Aegean Region Based on Their Triacyglycerol Profiles

In this study, a total of 22 domestic monocultivar (Ayval?k and Memecik cv.) virgin olive oil samples taken from various locations of the Aegean region, the main olive growing zone of Turkey, during two (2001–2002) crop years were classified and characterized by well‐known chemometric methods (principal component analysis [PCA] and hierarchical cluster analysis [HCA]) on the basis of their triacylglycerol (TAG) components. The analyses of TAG components (LLL and major fractions LOO, OOO, POO, PLO, SOO, and ECN 42–ECN 50) in the oil samples were carried out according to the HPLC method described in a European Union Commission (EUC) regulation. In all analyzed samples the value of trilinolein (LLL), the least abundant TAG, did not exceed the maximum limit of 0.5 % given by the EUC regulation for different olive oil grades. The ranges of abundant TAG, namely LOO, OOO, POO, PLO, and SOO, were 13.30–16.08, 37.27–46.36, 21.39–23.24, 4.93–7.03, and 4.72–6.00 %. The TAG data of Aegean virgin olive oils were similar to those of products from important olive‐oil‐producing Mediterranean countries was determined. Also, the estimation of major fatty acids (FA) was carried out by using a formula based on TAG data. The PCA results showed that some TAG components have an important role in the characterization and geographical classification of 22 monocultivar virgin olive oil. The Aegean virgin olive oil samples were successfully classified and discriminated into two main groups as the North and South (growing) subzones or Ayval?k and Memecik olives (cultivars) according to the HCA results based on experimental TAG data and calculated major FA profile.     

Comparison of fatty acid profiles and mid‐infrared spectral data for classification of olive oils

The composition of olive oils may vary depending on environmental and technological factors. Fatty acid profiles and Fourier‐transform infrared (FT‐IR) spectroscopy data in combination with chemometric methods were used to classify extra‐virgin olive oils according to geographical origin and harvest year. Oils were obtained from 30 different areas of northern and southern parts of the Aegean Region of Turkey for two consecutive harvest years. Fatty acid composition data analyzed with principal component analysis was more successful in distinguishing northern olive oil samples from southern samples compared to spectral data. Both methods have the ability to differentiate olive oil samples with respect to harvest year. Partial least squares (PLS) analysis was also applied to detect a correlation between fatty acid profile and spectral data. Correlation coefficients (R²) of a calibration set for stearic, oleic, linoleic, arachidic and linolenic acids were determined as 0.83, 0.97, 0.97, 0.83 and 0.69, respectively. Fatty acid profiles were very effective in classification of oils with respect to geographic origin and harvest year. On the other hand, FT‐IR spectra in combination with PLS could be a useful and rapid tool for the determination of some of the fatty acids of olive oils.     

电子鼻测定苯系物的方法研究

为考察电子鼻用于苯系物(BTEX)快速检测的可行性,分别采用电子鼻(zNose4200,GC/SAW)和普通气相色谱(GC522,FID)对其进行分析.结果表明:电子鼻的灵敏度均为普通气相色谱的10倍以上,最高可达140倍.此外,精密度和重现性也优于后者,可用于BTEX快速、实时分析,是一种用于分析环境中挥发性和半挥发...     

Developing FT-NIR and PLS1 Methodology for Predicting Adulteration in Representative Varieties/Blends of Extra Virgin Olive Oils

It was previously demonstrated that Fourier transform near infrared (FT‐NIR) spectroscopy and partial least squares (PLS1) were successfully used to assess whether an olive oil was extra virgin, and if adulterated, with which type of vegetable oil and by how much using previously developed PLS1 calibration models. This last prediction required an initial set of four PLS1 calibration models that were based on gravimetrically prepared mixtures of a specific variety of extra virgin olive oil (EVOO) spiked with adulterants. The current study was undertaken after obtaining a range of EVOO varieties grown in different countries. It was found that all the different types of EVOO varieties investigated belonged to four distinct groups, and each required the development of additional sets of specific PLS1 calibration models to ensure that they can be used to predict low concentrations of vegetable oils high in linoleic, oleic, or palmitic acid, and/or refined olive oil. These four distinct sets of PLS1 calibration models were required to cover the range of EVOO varieties with a linoleic acid content from 1.3 to 15.5 % of total fatty acids. An FT‐NIR library was established with 66 EVOO products obtained from California and Europe. The quality and/or purity of EVOO were assessed by determining the FT‐NIR Index, a measure of the volatile content of EVOO. The use of these PLS1 calibration models made it possible to predict the authenticity of EVOO and the identity and quantity of potential adulterant oils in minutes.     

Geographical Differentiation of Greek Extra Virgin Olive Oil from Late-Harvested Koroneiki Cultivar Fruits

Seventy‐four monovarietal olive oil samples belonging to the Koroneiki cultivar were collected from four selected olive oil‐producing regions of Greece (Messinia, Lakonia, Irakleio and Etoloakarnania), during two harvesting periods (2012/2013 and 2013/2014) at the stage of full maturation (maturation index 5–6). Determination of volatile compounds (VC), fatty acid (FA) composition, total phenolic content (TPC) and color parameters was carried out in an effort to classify Koroneiki olive oil samples according to geographical origin, while conventional quality parameters (CQP) were used to characterize the samples. The analytical data were then subjected to statistical analysis using multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA). The results showed a correct classification rate of 79.7% based on VC analysis, 81.1% based on the combination of VC analysis and FA composition, and 87.8% based on the combination of VC analysis and color parameters.     

Protected Designation of Origin Extra Virgin Olive Oils Assessment by Nuclear Magnetic Resonance and Multivariate Statistical Analysis: “Terra di Bari”, an Apulian (Southeast Italy) Case Study

We report a study on the chemical characterization of 102 monovarietal micro‐extracted and genetically characterized extra virgin olive oils (EVOOs) from Coratina, Ogliarola Barese and Cima di Mola cultivar, according to “Terra di Bari” (Apulia, southeast Italy) PDO requirement. Three additional geographical mentions, all belonging to the same Bari district (Bitonto, Castel del Monte and Murgia dei Trulli e delle Grotte), were studied and potential microclimate differences were evaluated. Our results indicate the possibility of distinguishing EVOOs from the same “Terra di Bari” PDO with respect to different cultivars and (to some extent) different subareas. In particular, two cultivars (Ogliarola Barese and Coratina), obtained from the same Bitonto area, and a single cultivar (Coratina), obtained from Bitonto and Castel del Monte subareas, were compared to investigate the micro‐area pedoclimatic effect. Finally, ¹H NMR data were found significant for classification purposes of unknown EVOO samples, the results of which were included in the model space, as they were correctly predicted by the OPLS‐DA obtained by ¹H NMR data. This work aims to classify commercial “Terra di Bari” PDO EVOOs by comparison of the declared cultivar and geographical origin with a reference dataset of genetically characterized micro‐extracted monovarietal oils. In conclusion, the effect of the pedoclimatic micro‐areas of origin on the Coratina cultivar, which is the main component of the “Terra di Bari” PDO, has been studied in order to improve the traceability of the raw material used to produce this valuable food.     

Classification of Turkish Extra Virgin Olive Oils by a SAW Detector Electronic Nose

An electronic nose (e-nose), in combination with chemometrics, has been used to classify the cultivar, harvest year, and geographical origin of economically important Turkish extra virgin olive oils. The aroma fingerprints of the eight different olive oil samples [Memecik (M), Erkence (E), Gemlik (G), Ayvalık (A), Domat (D), Nizip (N), Gemlik–Edremit (GE), Ayvalık–Edremit (AE)] were obtained using an e-nose consisting a surface acoustic wave detector. Data were analyzed by principal component analysis (PCA) and discriminant function analysis (DFA). Classification of cultivars using PCA revealed that A class model was correctly discriminated from N in two harvest years. The DFA classified 100 and 97% of the samples correctly according to the cultivar in the 1st and 2nd harvest years, respectively. Successful separation among the harvest years and geographical origins were obtained. Sensory analyses were performed for determining the differences in the geographical origin of the olive oils and the preferences of the panelists. The panelists could not detect the differences among olive oils from two different regions. The cultivar, harvest year, and geographical origin of extra virgin olive oils could be discriminated successfully by the e-nose.     

Monitoring wastewater BOD using a non‐specific sensor array

An electronic nose incorporating a non‐specific sensor array of 12 conducting polymers was evaluated for its ability to monitor wastewater samples. Sewage samples collected from the inlet works, settlement tank and final effluent outlet over 5 months (January–May) were used to correlate the sensor responses of these samples with their corresponding 5‐day biochemical oxygen demand (BOD) values. Canonical correlation analysis (a linear reduction technique) showed that the relationship between the sensor responses and BOD over the 5 months was non‐linear. However, the separate analyses of subsets of these samples for shorter time periods showed that a linear relationship is apparent for time periods of 4 weeks or less, suggesting a correlation window occurs between the sensor responses and BOD. Preliminary neural network analysis supported these observations and using a three‐layer back‐propagation network showed that it is possible to predict BOD values from electronic nose analysis of a wastewater sample. The findings suggest that electronic nose technology could be used for the non‐invasive monitoring and/or control of a wastewater treatment process. © 1999 Society of Chemical Industry     

Detection of Olive Oil Adulteration Using FT-IR Spectroscopy and PLS with Variable Importance of Projection (VIP) Scores

Determination of adulteration and authenticity of extra virgin olive oil (EVOO) was investigated by means of infrared spectroscopy and chemometric methods. The study was focused on the detection and quantification of extra virgin olive oil adulteration by soybean (SB) and sunflower (SF) oils using FT-IR spectroscopy based on the use of PLS modeling and variable importance of projection (VIP) scores. A PLS model, using orthogonal signal correction and mean centering data pretreatments, and VIP scores variable preselection, was able to predict the concentration of sunflower and soybean oil adulterants in the 1–24 % weight ratio range with relative prediction errors lower than 3 % (w/w), for external validation samples. Moreover, the PLS-DA (discriminant analysis) model using the same preselected wavelengths was able to explain 99.9 % of variance and to predict with 100 % accuracy both classes of adulteration (EVOO–SB and EVOO–SF) in the external validation.     

Determination of Origin of Commercial Flavored Rapeseed Oil by the Pattern of Volatile Compounds Obtained via GC–MS and Flash GC Electronic Nose

Flavored rapeseed oil (FRO) is a typical hot‐pressed oil and is widely consumed in China due to its strong characteristic flavor and intensive color. In this study, volatile profiles of 33 representative commercial rapeseed oils in China are characterized by gas chromatography‐mass spectrometry (GC‐MS) and flash gas chromatography (GC) electronic nose system. 51 volatile compounds are identified and the nitriles (methallyl cyanide and 5‐cyano‐1‐pentene), aldehydes (nonanal, 3‐furaldehyde, and 5‐methyl‐2‐furancarboxaldehyde), alcohols (1,5‐hexadien‐3‐ol, 2‐furanmethanol, and phenylethyl alcohol), and pyrazines (2,5‐dimethyl‐pyrazine and 2,6‐dimethyl‐pyrazine) are the major volatile compounds in FROs. Glucosinolate degradation products account for the highest proportion of these volatiles, which are found to have a positive correlation with the erucic acid content (R² = 0.796, p < 0.01). FRO from Sichuan province in the southwest of China can be characterized by the obvious distinctions in flash GC electronic nose combined with principal component analysis, which indicates that the flash GC electronic nose can be used as a promising method to identify the origins of FRO. Practical Applications: This work is helpful for expanding the knowledge of volatiles of commercial flavored rapeseed oil. The data can also serve as a basis for the quality assessment of hot‐pressed rapeseed oil. Meanwhile, the flash GC electronic nose combined with principal component analysis can be used as a promising method for the classification of flavor rapeseed oil production areas.     

Characterization and Classification of Extra Virgin Olive Oil from Five Less Well-Known Greek Olive Cultivars

The present study comprises the second part of an ongoing study focusing on olive oil from five less well‐known Greek cultivars for three of which there are no data available in the literature regarding their chemical composition. A total of 74 olive oil samples were collected during the harvesting periods 2012–2013 and 2013–2014. Headspace‐solid phase microextraction was applied to determine the olive oil volatile profile. Fifty‐six compounds were identified and semi‐quantified by CG–MS. Furthermore, fatty acid composition, conventional quality parameters and color parameters were determined in an effort to characterize and differentiate olive oils according to cultivar. All samples were characterized as extra virgin olive oils. Data obtained showed significant differences between the cultivars. Multi‐element analysis in combination with chemometrics resulted in a high classification rate of 86.5 % for the combination of volatiles plus color, 89.2 % for the combination of VC plus FA, and 91.9 % for the combination of FA composition plus color plus CQP.     

Identification of Turkish extra virgin olive oils produced in different regions by using NMR (1H and 13C) and IRMS (13C/12C)

Isotope ratio mass spectroscopy (IRMS) and nuclear magnetic resonance (NMR) spectroscopy techniques are two of the analytical methods that are used to characterize food products. The aim of this study is to classify extra virgin olive oil (EVOO) samples collected from different regions of Turkey based on ¹H and ¹³C NMR spectra along with IRMS δ¹³C carbon isotope ratio data by using chemometrics multivariate data analysis methods. A total of 175 EVOO samples were analyzed in 2014/15 and 2015/16 harvest seasons. Multivariate classification and clustering models were used to identify geographical and botanical origins of the EVOOs. IRMS results showed that there was no significant difference in terms of δ¹³C values between the years in terms of harvest year (p > 0.05), only extraction phase and variety were statistically significant factors (p < 0.05). The interactions of the factors showed that the harvest year × variety interaction is important. The outcomes of this research clearly indicated that considering the partial least squares discriminant analysis result with NMR spectra, the percent success of the model in the South Marmara, North Aegean, and South Aegean region samples were 95%, 95.7%, and 96.4% in the model set, respectively. The results showed that by using classification and clustering models, geographic marking and labeling of these oils can be carried out regardless of differences in year and production systems (2 and 3 phase extraction system) according the NMR analysis.     

Chemometric analysis of combined NIR and MIR spectra to characterize French olives

Chemometric treatment of near‐infrared (NIR) and mid‐infrared (MIR) combined spectra was used firstly to predict oil and water contents in fresh olive fruit samples (n = 223) and secondly to classify these samples into five principal French cultivar origins (Aglandau, Cailletier, Olivière, Salonenque, and Tanche). The study was carried out during four crop years (2005/2006 to 2008/2009) to take into account the seasonal variations. The comparison of the results obtained in the combined range (REP = 2.6% for the water content and 3.5% for the oil content) provides an obvious advantage compared to the NIR and MIR techniques used separately. Fresh olive fruit cultivars were satisfactorily classified with the partial least squares‐discriminant analysis (PLS‐DA) method in the combined range. After use of the K‐means clustering on the PLS‐DA scores, all the samples were well classified into their five groups of origin. The use of infrared combined spectra allows a considerable improvement in estimating olive fruit quality (oil and water contents, varietal origins).     

An electronic nose to classify Iberian pig fats with different fatty acid composition

Fatty acid analysis is frequently performed in fat and other raw materials to classify them according to their fatty acid composition, but the need to carry out online determinations has generated a growing interest in more rapid options. This research was done to evaluate the ability of a polymer-sensor based electronic nose to classify Iberian pig fat samples with different fatty acid compositions. Significant correlations were found between individual fatty acids and sensor responses, proving that sensor response data were not fortuitously sorted. Significant correlations also appeared between some sensors and water activity, which was considered during the sample classification. Two supervised pattern recognition techniques were attempted to process the sensor responses: 85.5% of the samples were correctly classified by discriminant analysis, but the percentage increased to 97.8% using a one-hidden layer back-propagation artificial neural network. The electronic nose (specifically, sensor responses analyzed by a neural network) achieved success similar to that obtained using the more usual fatty acid analysis by gas chromatography.     

Evaluation of MALDI-TOF/MS Technology in Olive Oil Adulteration

Adulteration of extra virgin olive oil (EVOO) by addition of other vegetable oils or lower-grade olive oils is a common problem of the oil market worldwide. Therefore, we developed a fast protocol for detection of EVOO adulteration by mass spectrometry fingerprinting of triacylglycerol (TAG) profiles based on MALDI-TOF/MS. For that purpose, EVOO TAG profiles were compared with those of edible sunflower oil and olive oil composed of refined olive oil and virgin olive oils. Adulteration of EVOO was simulated by addition of sunflower and mixture of refined olive oil and virgin olive oils at 1, 10 and 20% w/w. Results of mass spectrometry TAG profiling were compared with routinely assessed K values for identification of adulteration. MALDI-TOF/MS technology coupled with statistical analysis was proven as useful for detection of adulteration in EVOO at a rate down to 1%. In contrast, standard spectrophotometric methods failed to identify minor adulterations. In addition, the ability of MALDI-TOF/MS in detection of adulteration was tested on EVOO samples from different geographical regions. Results demonstrated that MALDI-TOF/MS technology coupled with statistical analysis is able to distinguish adulterated oils from other EVOO.