Analytical determination of polyphenols in olive oils

The increasing popularity of olive oil is mainly attributed to its high content of oleic acid, which may affect the plasma lipid/lipoprotein profiles, and its richness in phenolic compounds, which act as natural antioxidants and may contribute to the prevention of human disease. An overview of analytical methods for the measurement of polyphenols in olive oil is presented. In principle, the analytical procedure for the determination of individual phenolic compounds in virgin olive oil involves three basic steps: extraction from the oil sample, analytical separation, and quantification. A great number of procedures for the isolation of the polar phenolic fraction of virgin olive oil, utilizing two basic extraction techniques, LLE or SPE, have been included. The reviewed techniques are those based on spectrophotometric methods, as well as analytical separation (gas chromatography (GC), high-performance liquid chromatography (HPLC), and capillary electrophoresis (CE)). Many reports in the literature determine the total amount of phenolic compounds in olive oils by spectrophometric analysis and characterize their phenolic patterns by capillary gas chromatography (CGC) and, mainly, by reverse phase high-performance liquid chromatography (RP-HPLC); however, CE has recently been applied to the analysis of phenolic compound of olive oil and has opened up great expectations, especially because of the higher resolution, reduced sample volume, and analysis duration. CE might represent a good compromise between analysis time and satisfactory characterization for some classes of phenolic compounds of virgin olive oils.     

Classification of olive leaves and pulps according to their cultivar by using protein profiles established by capillary gel electrophoresis

A method to classify olive leaves and pulps according to their cultivar using protein profiles obtained by capillary gel electrophoresis (CGE) has been developed. For this purpose, proteins were extracted using an enzyme-assisted method, which provided higher protein recoveries than other previously described methods. Ten and nine common peaks, for leaf and pulp samples, respectively, were identified in the 12 cultivars studied in this work. In addition, and using linear discriminant analysis of the CGE data, olive leaf and pulp samples belonging to 12 cultivars from different Spanish regions were correctly classified with an excellent resolution among all the categories, which demonstrated that protein profiles were characteristic of each cultivar.

Simple and fast determination of phenolic compounds from different varieties of olive oil by nonaqueous capillary electrophoresis with UV‐visible and fluorescence detection

In this article, we proposed very simple procedures to analyze important phenolic compounds in olive oil samples from different olive varieties. A nonaqueous CE method has been employed. The main phenolic alcohols in virgin olive oil (tyrosol and hydroxytyrosol) and some among the most abundant secoiridoid aglycone derivatives (dialdehydic form of decarboxymethyl elenoic acid linked to hydroxytyrosol, an isomer of oleuropein aglycone and the dialdehydic form of decarboxymethyl elenoic acid linked to tyrosol) were determined by a direct injection into the capillary of the olive oil dissolved in 1‐propanol 1:1 v/v. For the determination of compounds present at lower concentrations, a very simple liquid–liquid extraction method with ethanol has been proposed. The extraction was performed using a relationship 5:1 w/v olive oil/ethanol to achieve the necessary preconcentration of the analytes and the ethanolic extracts were directly injected into the capillary to obtain a very important time reduction. Good recoveries were obtained with both the procedures, using an internal standard. Finally, these procedures were applied to the analysis of these compounds in extra virgin olive oil samples from different varieties of olive.     

Organic Profiles and Pattern Recognition Analysis for Clinical Applications

Efficient gas chromatographic (GC) and capillary electrophoretic (CE) profiling methods were combined with simple pattern recognition methods for the correlation between urinary organic profiles (organic acids,polyamines and nucleosides) and uterine cervical cancer.For the urinary organic acid profiles, free organic acids were recovered by dual solid-phase extraction (SPE) in anion-exchange and normal-phase partition modes after methoximation of keto acids in alkalinized urine samples, followed by conversion to tert.-butyldimethylsilyl derivatives for the direct analysis by dual-capillary column GC.     

Capillary gas chromatography combined with high performance liquid chromatography for the structural analysis of olive oil triacylglycerols

The triacylglycerol composition of olive oil samples has been determined by stereospecific analysis after partial hydrolysis with ethyl magnesium bromide, derivatization, preparative chiral HPLC, transesterification, and GC quantitation of fatty acid methyl esters. The data obtained for position sn-2 were compared with those from capillary GC analysis of monoacyl sn-2-glycerols after enzymatic lipolysis of triacylglycerols. The determination of triacylglycerols collected by silver ion HPLC and quantified (as fatty acid methyl esters) by GC, together with direct GC analysis on a polar column, have then furnished a comprehensive picture of the triacylglycerol content of olive oil.     

Novel combination of non-aqueous capillary electrophoresis and multivariate curve resolution-alternating least squares to determine phenolic acids in virgin olive oil

This paper presents the development of a non-aqueous capillary electrophoresis method coupled to UV detection combined with multivariate curve resolution-alternating least-squares (MCR-ALS) to carry out the resolution and quantitation of a mixture of six phenolic acids in virgin olive oil samples. p-Coumaric, caffeic, ferulic, 3,4-dihydroxyphenylacetic, vanillic and 4-hydroxyphenilacetic acids have been the analytes under study. All of them present different absorption spectra and overlapped time profiles with the olive oil matrix interferences and between them. The modeling strategy involves the building of a single MCR-ALS model composed of matrices augmented in the temporal mode, namely spectra remain invariant while time profiles may change from sample to sample. So MCR-ALS was used to cope with the coeluting interferences, on accounting the second order advantage inherent to this algorithm which, in addition, is able to handle data sets deviating from trilinearity, like the data herein analyzed. The method was firstly applied to resolve standard mixtures of the analytes randomly prepared in 1-propanol and, secondly, in real virgin olive oil samples, getting recovery values near to 100% in all cases. The importance and novelty of this methodology relies on the combination of non-aqueous capillary electrophoresis second-order data and MCR-ALS algorithm which allows performing the resolution of these compounds simplifying the previous sample pretreatment stages.     

Classification of polymer batch variations by dynamic headspace/capillary gas chromatography/multivariate data analysis

Gas chromatographic profiles have been generated from different batches of a polypropylene/polyethylene copolymer. The profiles generated from polymer pellets have been obtained by dynamic headspace/capillary gas chromatography analysis. Initially 10 to 40 peaks were chosen at random from the quantitative reports and transferred to a data table. After appropriate scaling the table has been analyzed by a multivariate statistic program, SIMCA (Soft Independent Modeling of Class Analogy) a pattern recognition technique. The method has been used to differentiate batches according to sensory qualities of the final packaging product and changes in polymer peilet production.     

Electrophoretic identification and quantitation of compounds in the polyphenolic fraction of extra-virgin olive oil

A capillary zone electrophoresis method has been carried out to determine and quantitate some compounds of the polyphenolic fraction of virgin olive oil which have never previously been determined before using capillary electrophoresis, such as elenolic acid, ligstroside aglycon, oleuropein aglycon, and (+)-pinoresinol. The compounds were identified using standards obtained by semipreparative high-performance liquid chromatography (HPLC). A detailed method optimization was performed to separate the phenolic compounds present in olive oil using a methanol-water extract of Picual extra-virgin olive oil, and different extraction systems were compared (C18-solid phase extraction (SPE), Diol-SPE, Sax-SPE and liquid-liquid extraction). The optimized parameters were 30 mM sodium tetraborate buffer (pH 9.3) at 25 kV with 8 s hydrodynamic injection, and the quantitation was carried out by the use of two reference compounds at two different wavelengths.     

Recognition of volatile compounds as markers in geographical discrimination of Spanish extra virgin olive oils by chemometric analysis of non-specific chromatography volatile profiles

Chromatographic profiles obtained by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography (GC) were processed as continuous and non-specific signals through multivariate analysis techniques in order to select and identify the most discriminate volatile marker compounds related to the geographical origin of extra virgin olive oils. The blind analysis of the chromatographic profiles was carried out on several steps including preliminary mathematical treatments, explorative analysis, feature selection and classification. The results obtained through the application of stepwise linear discriminant analysis (SLDA) method revealed a perfect discrimination between the different Spanish geographical regions considered (La Rioja, Andalusia and Catalonia). The assignment success rate was 100% in both classification and prediction by using cross validation procedure. In addition, it must be noted that the proposed strategy was able to verify the geographical origin of the samples involving only a reduced number of discriminate retention times selected by the stepwise procedure. This fact emphasizes the quality of the accurate results obtained and encourages the feasibility of similar procedures in olive oil quality and traceability studies. Finally, volatile compounds corresponding to the predictors retained were identified by gas chromatography-mass spectrometry (GC-MS) for a chemical interpretation of their importance in quality virgin olive oils.     

Co-pyrolysis of olive residue with poly(vinyl chloride) using thermogravimetric analysis

Pyrolytic process has a promising potential for the environmentally friendly upgrading of lignocellulosic materials and plastic waste. The co-pyrolysis of olive residue and poly(vinyl chloride) was investigated under nitrogen atmosphere by dynamic thermogravimetric analysis in the temperature range of 300–975 K. Two main stages of mass loss have been evidenced by TG analysis. The first occurs in the temperature range of 420–684 K, and the second occurs at 631–840 K. This research was focused on the interaction between olive residue and poly(vinyl chloride) during the pyrolysis process. Discrepancies between the experimental and calculated TG/DTG profiles were considered as a measurement of the extent of interactions occurring on co-pyrolysis. It was found that reactivity of olive residue was increased in olive residue/PVC mixture. In addition, a kinetic analysis was performed to fit thermogravimetric data, the mixture is considered as multistage process. A reasonable fit to the experimental data was obtained for all materials and their mixture by isoconversional Friedman method.     

Mass spectrometry fingerprinting coupled to National Institute of Standards and Technology Mass Spectral search algorithm for pattern recognition

A new analytical strategy based on mass spectrometry fingerprinting combined with the NIST-MS search program for pattern recognition is evaluated and validated. A case study dealing with the tracing of the geographical origin of virgin olive oils (VOOs) proves the capabilities of mass spectrometry fingerprinting coupled with NIST-MS search program for classification. The volatile profiles of 220 VOOs from Liguria and other Mediterranean regions were analysed by secondary electrospray ionization-mass spectrometry (SESI-MS). MS spectra of VOOs were classified according to their origin by the freeware NIST-MS search v 2.0. The NIST classification results were compared to well-known pattern recognition techniques, such as linear discriminant analysis (LDA), partial least-squares discriminant analysis (PLS-DA), k-nearest neighbours (kNN), and counter-propagation artificial neural networks (CP-ANN). The NIST-MS search program predicted correctly 96% of the Ligurian VOOs and 92% of the non-Ligurian ones of an external independent data set; outperforming the traditional chemometric techniques (prediction abilities in the external validation achieved by kNN were 88% and 84% for the Ligurian and non-Ligurian categories respectively). This proves that the NIST-MS search software is a useful classification tool.     

Determination of olive oil acidity by CE

In this work, a CE method for the determination of olive oil acidity was proposed. The method was based on an ethanolic extraction (at 60 degrees C) of the oil long-chain free fatty acids (LC-FFAs) components followed by CE determination in pH 6.86 phosphate buffer at 15 mmol/L concentration containing 4 mmol/L sodium dodecylbenzenesulfonate (SDBS), 10 mmol/L polyoxyethylene 23 lauryl ether (Brij 35), 2% v/v 1-octanol and 45% v/v ACN under indirect UV detection at 224 nm. Although this electrolyte promoted baseline separation of myristic acid (C14:0) (internal standard (IS)) and olive oil major components (palmitic acid (C16:0), oleic acid (C18:1c) and linoleic acid (C18:2cc)) in less than 8 min, after a few injections, the electropherogram profiles were severely altered (peak broadening, migration time shifts, etc.) and the current increased substantially. An adsorption study was conducted revealing that the dissolution of the capillary external polyimide coating during the electrophoretic run caused the detrimental effect. After removal of the capillary tip coating, ten consecutive injections could be performed without any disturbances and this simple procedure was, therefore, implemented during quantitative purposes. The reliability of the proposed method was further investigated by the determination of acidity of an extra virgin olive oil sample in comparison to the established methodology (AOCS method Ca 5a-40, alkaline volumetric titration (AVT)). No statistical differences were found within 95% confidence level. A % acidity of 0.39 +/- 0.02 was found for the olive oil sample under consideration.     

常压火焰离子化质谱技术对食用植物油快速分析的初探

建立了常压火焰离子化质谱(Ambient flame ionization mass spectrometry,AFI-MS)快速分析食用植物油(橄榄油、芝麻油、花生油和葵花籽油)的方法。AFI-MS检出食用植物油(橄榄油、芝麻油、花生油和葵花籽油)中的26种甘油三酯和11种甘油二脂。AFI-MS分析显示,不同的食用植物油(橄榄油、芝麻油、花生油和葵花籽油)得到的质谱图轮廓信息不同。通过对不同食用植物油的甘油三酯相对峰强度进行分析,可初步归纳出食用植物油的类型。AFI-MS分析食用植物油的操作简单,普通的打火机就可以作为离子源用于食用植物油的分析。这种便捷的离子化技术可以用于食用植物油的快速分析。     

Capillary Electrophoretic Profiling and Pattern Recognition Analysis of Urinary Nucleosides from Tumor Patients

An efficient capillary electrophoretic (CE) profiling method was combined with pattern recognition method for the correlation between urinary nucleoside profiles and malignant tumors. Nucleosides were extracted from urine specimens by solid-phase extraction in affinity mode using phenyl boronic acid gel.     

Meat species identification by linear discriminant analysis of capillary electrophoresis protein profiles

The objective of this study was to utilize linear discriminant analysis (LDA) in the interpretation of capillary electrophoresis-sodium dodecyl sulfate polymer-filled capillary gel electrophoresis (CE-SDS) meat protein profiles for the identification of meat species. The specific objectives were 1) to collect quantitative data on water-soluble and saline-soluble proteins of different meat species obtained by CE-SDS and 2) to apply LDA on collected CE-SDS protein data for the development of a pattern recognition statistical model useful in the differentiation of meat species. Samples were raw beef top and eye round, boneless fresh pork ham and loin, turkey leg and breast meat, and mechanically deboned turkey meat collected on six different occasions, making a total of 42 samples. Additionally, 14 samples were used as test samples to determine the classification ability of the procedure. Quantitative protein data obtained by CE-SDS was used to generate separate LDA models for either water- or saline-soluble protein extracts. Although a saline solution was a more efficient meat protein-extracting agent, as shown by a higher total protein concentration and a larger number of peaks, water-soluble CE-SDS protein profiles gave more distinctive discrimination among meat species. The correct classification given by LDA on water-soluble protein data was 100% for all meat species, except pork (94%). Conversely, the correct classification on saline-soluble protein data was 88% for beef and mechanically deboned turkey meat, and 94% and 100% for turkey and pork meat, respectively. LDA proved to be a useful pattern recognition procedure in the interpretation of CE-SDS protein profiles for the identification of meat species.     

Pyrolysis of olive residue/low density polyethylene mixture: Part I Thermogravimetric kinetics

This paper demonstrates the thermal pyrolysis of olive residue, low density polyethylene (LDPE) and olive residue/LDPE mixture in an inert atmosphere of N2 using thermogravimetric analysis (TGA). Measurements were carried out in the temperature range 300K~973K at heating rates of 2K/min, 10K/min, 20K/min and 50K/min. Based on the results obtained, three temperature regimes were selected for studying the nonisothermal kinetics of olive residue/LDPE mixture. The first two were dominated by the olive residue pyrolysis, while the third was linked to the LDPE pyrolysis, which occurred at much higher temperatures. Discrepancies between the experimental and calculated TG/DTG profiles were considered as a measurement of the extent of interactions occurring on copyrolysis. The maximum degradation temperatures of each component in the mixture were higher than those the individual components; thus an increase in thermal stability was expected. The kinetic parameters associated with thermal degradation were determined using Friedman isoconversional method.     

Analysis of sterols in vegetable oils using off-line SFC/capillary GC-MS

Summary The analysis of sterols in vegetable oils by off-line SFC followed by capillary GC-MS is described. The fractionation of the sterols from the complex oil matrix is achieved by SFC on aminopropyl silicagel in less than 8 minutes. Injection and collection of the sterol fraction is fully automated and time controlled. The sterols are analysed without derivatisation by capillary GC-MS. Identification is performed by full scan electron ionisation and quantitation is carried out by extracted ion chromatography at m/e 107, with cholesterol as internal standard. The analyses of the sterols from the sunflower oil and two olive oils illustrate the possibilities of the method.     

Electronic nose based on metal oxide semiconductor sensors as a fast alternative for the detection of adulteration of virgin olive oils

An “electronic nose” has been used for the detection of adulterations of virgin olive oil. The system, comprising 12 metal oxide semiconductor sensors, was used to generate a pattern of the volatile compounds present in the samples. Prior to different supervised pattern recognition treatments, feature selection techniques were employed to choose a set of optimally discriminant variables. Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA) and artificial neural networks (ANN) were applied. Excellent results were obtained in the differentiation of adulterated and non-adulterated olive oils and it was even possible to identify the type of oil used in the adulteration. Promising results were also obtained as regards quantification of the percentages of adulteration.     

毛细管电泳-小波神经网络法辅佐诊断乳腺癌的研究

采用毛细管电泳法测定了46个健康人和26个乳腺癌病人尿样中的13种正常核苷和修饰核苷,以小波神经网络作为模式识别工具对健康人和乳腺癌病人的分类作了研究,随机选取的训练集的识别率达到100％,相应的预测集判别率正确性在96％以上,与经典的前向多层神经网络相比,小波神经网络具有更强的信息提取和逼近能力.研究结果还表明,小波神经网络的预测能力强于主成分分析和线性判别分析,毛细管电泳法与小波神经网络的结合有望成为乳腺癌的辅助诊断手段.     

Applications of pattern recognition

This poster illustrates the lecture on Pattern Recognition and gives recently published and unpublished examples, mainly from the laboratory from the first author. The applications concern:

- the determination of metabolic pathways of branched chain fatty acids (by clustering),

- the development of a genetic classification of meteorites (by clustering),

- the classification of cholinergic agents according to their interaction with different receptors (by clustering),

- the structure of a data set consisting of gaschromatographic profiles in samples collected in pollution monitoring stations (by factor analysis and pattern recognition),

- factors determining GLC behaviour of solutes (by factor analysis and multiple regression),

- the classification of olive oils according to geographic origin (by principal components and pattern recognition),

- the diagnosis of thyroid status (by pattern recognition).