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1.
The potential of a headspace device coupled to multi-capillary column-ion mobility spectrometry has been studied as a screening
system to differentiate virgin olive oils (“lampante,” “virgin,” and “extra virgin” olive oil). The last two types are virgin olive oil samples of very similar characteristics,
which were very difficult to distinguish with the existing analytical method. The procedure involves the direct introduction
of the virgin olive oil sample into a vial, headspace generation, and automatic injection of the volatiles into a gas chromatograph-ion
mobility spectrometer. The data obtained after the analysis by duplicate of 98 samples of three different categories of virgin
olive oils, were preprocessed and submitted to a detailed chemometric treatment to classify the virgin olive oil samples according
to their sensory quality. The same virgin olive oil samples were also analyzed by an expert’s panel to establish their category
and use these data as reference values to check the potential of this new screening system. This comparison confirms the potential
of the results presented here. The model was able to classify 97% of virgin olive oil samples in their corresponding group.
Finally, the chemometric method was validated obtaining a percentage of prediction of 87%. These results provide promising
perspectives for the use of ion mobility spectrometry to differentiate virgin olive oil samples according to their quality
instead of using the classical analytical procedure. 相似文献
2.
M. Angiuli C. Ferrari L. Lepori E. Matteoli G. Salvetti E. Tombari A. Banti N. Minnaja 《Journal of Thermal Analysis and Calorimetry》2006,84(1):105-112
Extra Virgin olive oils
(7 samples) originating from different areas of Tuscany, defective olive oils
(5 samples), commercial edible seed oils (4 samples) and two commercial samples
of olive oil (one declared ‘extra virgin olive oil’ and one ‘olive
oil’) were studied by different calorimetric techniques: high sensitivity
isothermal, differential scanning, and modulated scanning calorimetry. The
temperature interval (–60) – (+30)°C was explored for monitoring: i) the main features of the liquid↔solid phase
transitions, ii) the nucleation and growth
rate of the polymorphous crystalline phases of the triacylglicerols, and iii) the melting process. This investigation was
planned for verifying the utility and effectiveness of calorimetry for screening
quality and origin of olive oil. To this end, the main calorimetric operation
modes have been applied, the experimental results reported and their utility
for developing an effective and reliable screening protocol discussed. 相似文献
3.
Panagiotis Diamantakos Kostas Ioannidis Christos Papanikolaou Annia Tsolakou Aimilia Rigakou Eleni Melliou Prokopios Magiatis 《Molecules (Basel, Switzerland)》2021,26(4)
In the last few years, a new term, “High-phenolic olive oil”, has appeared in scientific literature and in the market. However, there is no available definition of that term regarding the concentration limits of the phenolic ingredients of olive oil. For this purpose, we performed a large-scale screening and statistical evaluation of 5764 olive oil samples from Greece coming from >30 varieties for an eleven-year period with precisely measured phenolic content by qNMR. Although there is a large variation among the different cultivars, the mean concentration of total phenolic content was 483 mg/kg. The maximum concentration recorded in Greece reached 4003 mg/kg. We also observed a statistically significant correlation of the phenolic content with the harvest period and we also identified varieties affording olive oils with higher phenolic content. In addition, we performed a study of phenolic content loss during usual storage and we found an average loss of 46% in 12 months. We propose that the term high-phenolic should be used for olive oils with phenolic content > 500 mg/kg that will be able to retain the health claim limit (250 mg/kg) for at least 12 months after bottling. The term exceptionally high phenolic olive oil should be used for olive oil with phenolic content > 1200 mg/kg (top 5%). 相似文献
4.
de la Mata-Espinosa P Bosque-Sendra JM Bro R Cuadros-Rodríguez L 《Analytical and bioanalytical chemistry》2011,399(6):2083-2092
This work presents a method for an efficient differentiation of olive oil and several types of vegetable oils using chemometric
tools. Triacylglycerides (TAGs) profiles of 126 samples of different categories and varieties of olive oils, and types of
edible oils, including corn, sunflower, peanut, soybean, rapeseed, canola, seed, sesame, grape seed, and some mixed oils,
have been analyzed. High-performance liquid chromatography coupled to a charged aerosol detector was used to characterize
TAGs. The complete chromatograms were evaluated by PCA, PLS-DA, and MCR in combination with suitable preprocessing. The chromatographic
data show two clusters; one for olive oil samples and another for the non-olive oils. Commercial oil blends are located between
the groups, depending on the concentration of olive oil in the sample. As a result, a good classification among olive oils
and non-olive oils and a chemical justification of such classification was achieved. 相似文献
5.
The freshness of virgin olive oils (VOO) from typical cultivars of Garda regions was evaluated by attenuated total reflectance (ATR) and Fourier transform infrared (FTIR) spectroscopy, in combination with multivariate analysis. The olive oil freshness decreased during storage mainly because of oxidation processes. In this research, 91 virgin olive oils were packaged in glass bottles and stored either in the light or in the dark at room temperature for different periods. The oils were analysed, before and after storage, using both chemical methods and spectroscopic technique.Classification strategies investigated were partial least square discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and soft independent modelling of class analogy (SIMCA).The results show that ATR-MIR spectroscopy is an interesting technique compared with traditional chemical index in classifying olive oil samples stored in different conditions. In fact, the FTIR PCA results allowed a better discrimination among fresh and oxidized oils, than samples separation obtained by PCA applied to chemical data. Moreover, the results obtained by the different classification techniques (PLS-DA, LDA, SIMCA) evidenced the ability of FTIR spectra to evaluate the olive oil freshness. FTIR spectroscopy results are in agreement with classical methods. The spectroscopic technique could be applied for the prediction of VOOs freshness giving information related to chemical modifications. The great advantages of this technique, compared to chemical analysis, are related to rapidity, non-destructive characteristics and low cost per sample. In conclusion, ATR-MIR represents a reliable, cheap and fast classification tool able to assess the freshness of virgin olive oils. 相似文献
6.
Vasil Simeonov Costel Sarbu Desire-Luc Massart Stefan Tsakovski 《Mikrochimica acta》2001,137(3-4):243-248
A data set (48×19) consisting of Danube river water analytical data collected at Galati site, Romania, during a four-year
period has been treated by principal components analysis (PCA). The PCA indicated that seven latent factors (“hardness”, “biochemical”,
“waste inlets”, “turbidity”, “acidity”, “soil extracts” and “organic wastes”) are responsible for the data structure and explain
over 80 % of the total variance of the system. Its complexity is further proved by the application of multiple linear regression
analysis on the absolute principal components scores (APCS) where the contribution of each natural or anthropogenic sources
in the factor formation is shown. The apportioning makes clear that each variable participates to a different extent to each
source and, in this way, no pure natural or pure anthropogenic influence could be determined. No specific seasonality for
the variables in consideration is found.
Received January 24, 2001. Revision July 6, 2001. 相似文献
7.
Kuligowski J Carrión D Quintás G Garrigues S de la Guardia M 《Analytical and bioanalytical chemistry》2011,399(3):1305-1314
The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect
of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS)
regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of
deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized
triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least
squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification.
Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation
of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation
testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness
of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on
the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples
from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected
calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w). 相似文献
8.
Thomas Spanos Vasil Simeonov John Stratis Xatzixristou Xristina 《Mikrochimica acta》2003,141(1-2):35-40
This study deals with the application of chemometric approaches (cluster analysis and principal components analysis) to a
potable water monitoring demonstrated on a data set from the region of Kavala, Greece, being analysed according to the standard
instructions and directives of the European Union. It is shown that the data classification by cluster analysis and data structure
modeling by principal components analysis reveals similar results, namely four different patterns of water source sites are
identified depending on the geographical site location (near to Nestos river, near to Strimon river, elevated sites and near-to-coast
sites). Three latent factors, explaining over 85% of the total variance, are responsible for the data structure as follows:
“water acidity (anthropogenic)”, “water hardness (natural)” and the “marine factor”. Their importance for the different sites
is related to the site location. Finally, it is recommended to involve the environmetric data treatment as a substantial standard
procedure in assessment of the quality of water intended for human consumption.
Received October 18, 2001; accepted June 24, 2002 相似文献
9.
Multivariate statistical assessment of polluted soils 总被引:9,自引:0,他引:9
Vasil Simeonov Juergen Einax Stafan Tsakovski Joerg Kraft 《Central European Journal of Chemistry》2005,3(1):1-9
This study deals with the application of several multivariate statistical methods (cluster analysis, principal components
analysis, multiple regression on absolute principal components scores) for assessment of soil pollution by heavy metals. The
sampling was performed in a heavily polluted region and the chemometric analysis revealed four latent factors, which describe
84.5 % of the total variance of the system, responsible for the data structure. These factors, whose identity was proved also
by cluster analysis, were conditionally named “ore specific”, “metal industrial”, “cement industrial”, and “steel production”
factors. Further, the contribution of each identified factor to the total pollution of the soil by each metal pollutant in
consideration was determined. 相似文献
10.
Marta Bevilacqua Remo BucciAndrea D. Magrì Antonio L. MagrìFederico Marini 《Analytica chimica acta》2012
In this paper, the potential of coupling mid- and near-infrared spectroscopic fingerprinting techniques and chemometric classification methods for the traceability of extra virgin olive oil samples from the PDO Sabina was investigated. To this purpose, two different pattern recognition algorithm representative of the discriminant (PLS-DA) and modeling (SIMCA) approach to classification were employed. Results obtained after processing the spectroscopic data by PLS-DA evidenced a rather high classification accuracy, NIR providing better predictions than MIR (as evaluated both in cross-validation and on an external test set). SIMCA confirmed these results and showed how the category models for the class Sabina can be rather sensitive and highly specific. Lastly, as samples from two harvesting years (2009 and 2010) were investigated, it was possible to evidence that the different production year can have a relevant effect on the spectroscopic fingerprint. Notwithstanding this, it was still possible to build models that are transferable from one year to another with good accuracy. 相似文献
11.
Saliu F Modugno F Orlandi M Colombini MP 《Analytical and bioanalytical chemistry》2011,401(6):1785-1800
The lipid fractions of residues from historical pharmaceutical ointments were analysed by reversed-phase liquid chromatography
coupled with atmospheric pressure chemical ionization and mass spectrometer detection. The residues were contained in a series
of historical apothecary jars, dating from the eighteenth century and conserved at the “Aboca Museum” in Sansepolcro (Arezzo,
Italy) and at the pharmacy of the “Real Cartuja de Valldemossa” in Palma de Majorca (Spain). The analytical protocol was set
up using a comparative study based on the evaluation of triacylglycerol (TAG) compositions in raw natural lipid materials
and in laboratory-reproduced ointments. These ointments were prepared following pharmaceutical recipes reported in historical
treatises and used as reference materials. The reference materials were also subjected to stress treatments in order to evaluate
the modification occurring in the TAG profiles as an effect of ageing. TAGs were successfully detected in the reproduced formulations
even in mixtures of up to ten ingredients and after harsh degradative treatments, and also in real historical samples. No
particular interferences were detected from other non-lipid ingredients of the formulations. The TAG compositions detected
in the historical ointments indicated a predominant use of olive oil and pig adipose material as lipid ingredients. The detection
of a high level of tristearine and myristyl-palmitoyl-stearyl glycerol in two of the samples suggested the presence of a fatty
material of a different origin (maybe a ruminant). On the basis of the positional isomer ratio, sn-PPO/sn-POP, it was possible to hypothesize an exclusive use of pig fat in one sample. We also evaluated the application of principal
component analysis of TAG profiles as an approach for the multivariate statistical comparison of the reference and historical
ointments. 相似文献
12.
For olive oil production a metal hammer-decanter olive processing line was compared to a traditional metal hammer-press line, a discontinuous method which, if properly used, yields high-quality virgin olive oils. Galega, Carrasquenha and Cobrançosa olives (traditional Portuguese varieties) were studied. The analysis of the aroma compounds was performed after headspace-solid phase micro extraction. The analytical results obtained after comprehensive gas chromatography in tandem with time of flight mass spectrometry (GC × GC/ToFMS) for these three different olive oil varieties, from a single year harvest and processed with two different extraction technologies, were compared using statistical image treatment, by means of ImageJ software, for fingerprint recognitions and compared with principal component analysis when the area data of each chromatographic spot of the contour plots were considered. The differences used to classify the olive oils studied under different groups after principal component analysis were observed independently of the treatment used (peak areas or the sum of the pixels counts). When the individual peak areas were considered, more then 75.7% of the total variance is explained by the first two principal components while in the case where the data were subjected to image treatment 84.0% of the total variance is explained by the first two principal components. In both cases the first and second principal components present eigenvalues higher then 1.0. Fingerprint image monitoring of the aroma compounds of the olive oil allowed a rapid differentiation of the three varieties studied as well as the extraction methods used. The volatile compounds responsible for their characterization were tentatively identified in a bi-dimensional polar/non-polar column set in the GC × GC/Tof-MS apparatus. This methodology allowed the reduction of the number of compounds needed for matrices characterization, preserving the efficiency of the discrimination, when compared with the traditional methods where the identification of all peaks is needed. 相似文献
13.
Pavlina Simeonova Costel Sarbu Thomas Spanos Vasil Simeonov Stefan Tsakovski 《Central European Journal of Chemistry》2006,4(1):68-80
The present paper deals with the application of classical and fuzzy principal components analysis to a large data set from
coastal sediment analysis. Altogether 126 sampling sites from the Atlantic Coast of the USA are considered and at each site
16 chemical parameters are measured. It is found that four latent factors are responsible for the data structure (“natural”,
“anthropogenic”, “bioorganic”, and “organic anthropogenic”). Additionally, estimating the scatter plots for factor scores
revealed the similarity between the sampling sites. Geographical and urban factors are found to contribute to the sediment
chemical composition. It is shown that the use of fuzzy PCA helps for better data interpretation especially in case of outliers. 相似文献
14.
Aleksander Astel Grażyna Głosińska Tadeusz Sobczyński Leonard Boszke Vasil Simeonov Jerzy Siepak 《Central European Journal of Chemistry》2006,4(3):543-564
The sustainable development rule implementation is tested by the application of chemometrics in the field of environmental
pollution. A data set consisting of Cd, Pb, Cr, Zn, Cu, Mn, Ni, and Fe content in bottom sediment samples collected in the
Odra River (Germany/Poland) is treated using cluster analysis (CA), principal component analysis (PCA), and source apportionment
techniques. Cluster analysis clearly shows that pollution on the German bank is higher than on the Polish bank. Two latent
factors extracted by PCA explain over 88 % of the total variance of the system, allowing identification of the dominant “semi-natural”
and “anthropogenic” pollution sources in the river ecosystem. The complexity of the system is proved by MLR analysis of the
absolute principal component scores (APCS). The apportioning clearly shows that Cd, Pb, Cr, Zn and Cu participate in an “anthropogenic”
source profile, whereas Fe and Mn are “semi-natural”. Multiple regression analysis indicates that for particular elements
not described by the model, the amounts vary from 4.2 % (Mn) to 13.1 % (Cr). The element Ni participates to some extent to
each source and, in this way, is neither pure “semi-natural” nor pure “anthropogenic”. Apportioning indicates that the whole
heavy metal pollution in the investigated river reach is 12510.45 mg·kg−1. The contribution of pollutants originating from “anthropogenic sources” is 9.04 % and from “semi-natural” sources is 86.53
%. 相似文献
15.
Th. Spanos V. Simeonov S. Tsakovski D. Thiokas 《Central European Journal of Chemistry》2004,2(2):402-416
The present paper deals with chemometric interpretation of soil analysis data collected from 31 sampling sites in the region
of Kavala and Drama, Northern Greece. The determination of 16 different chemical and physicochemical characteristics is principally
needed for prognosis of the land treatment and fertilizing. The study carried out indicates that the application of multivariate
statistical approaches could reveal new and specific information about sampling sites. It has been found that they could be
divided into four general patterns: pattern 1 contains dominantly inorganic and alkaline soil samples from semi-mountainous
regions in close proximity to the seacoast; pattern 2 indicates the same soil sample type and regional location as pattern
1 but is far from the coastal line; pattern 3 includes samples from sites from the plains with organic and alkaline soils
with close proximity to the coast; pattern 4 resembles pattern 3 as soil type but involves samples from sites far from the
shore. Further, six latent factors were identified, conditionally named “structural”, “acidic”, “nutritional”, “salt”, “microcomponents”
and “organic”. Finally, an apportioning procedure was carried out to find the source contributions in the measured analytical
values. In this way the routine estimation of the soil quality could be improved. 相似文献
16.
Paolo Oliveri M. Antonietta Baldo Salvatore Daniele Michele Forina 《Analytical and bioanalytical chemistry》2009,395(4):1135-1143
In this paper, we propose a novel strategy to perform cyclic voltammetric measurements with a platinum microelectrode directly
in edible oil samples. The microelectrode was employed as an electronic tongue that, along with the application of chemometrics
to the current–potential responses, proved useful for discriminating oils on the basis of their quality and geographical origin.
The method proposed here is based on the use of suitable room temperature ionic liquids, added to oils as supporting electrolytes
to provide conductivity to the low-polarity samples. The entire voltammograms, recorded directly on the oil/RTIL mixtures,
were processed via principal component analysis and a classification technique (K nearest neighbors), to extract information on samples characteristics. Data processing showed that oils having different
nature (i.e. maize and olive) or geographical origin (i.e. olive oils coming from different regions) can be distinguished. 相似文献
17.
In this study, the potential of high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (HPLC–QTOFMS) for metabolomic profiling of red wine samples was examined. Fifty one wines representing three varieties (Cabernet Sauvignon, Merlot, and Pinot Noir) of various geographical origins were sourced from the European and US retail market. To find compounds detected in analyzed samples, an automated compound (feature) extraction algorithm was employed for processing background subtracted single MS data. Stepwise reduction of the data dimensionality was followed by principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) which were employed to explore the structure of the data and construct classification models. The validated PLS-DA model based on data recorded in positive ionization mode enabled correct classification of 96% of samples. Determination of molecular formula and tentative identification of marker compound was carried out using accurate mass measurement of full single MS spectra. Additional information was obtained by correlating the fragments obtained by MS/MS accurate mass spectra using the QTOF with collision induced dissociation (CID) of precursor ions. 相似文献
18.
I. Stanimirova S. Tsakovski V. Simeonov 《Fresenius' Journal of Analytical Chemistry》1999,365(6):489-493
Multivariate statistical analysis of sediment data (information matrix 123 × 16) from the Gulf of Mexico, USA shows that
the data structure is defined by four latent factors conditionally called “inorganic natural”, “inorganic anthropogenic”,
“bioorganic” and “organic anthropogenic” explaining 39.24%, 23.17%, 10.77% and 10.67% of the total variance of the data system,
respectively. The receptor model obtained by the application of the PCR approach makes it possible to apportion the contribution
of each chemical component for the latent factor formation. A separation of the contribution of each chemical parameter is
achieved within the frames of “natural” and “anthropogenic” origin of the respective heavy metal or organic matter to the
sediment formation process. This is a new approach as compared to the traditional “one dimensional” search with a limited
number of preliminary selected tracer components. The model suggested divides natural from anthropogenic influences and allows
in this way each participant in the sediment formation process to be used as marker of either natural or anthropogenic effects.
Received: 20 March 1999 / Revised: 1 June 1999 / Accepted: 3 June 1999 相似文献
19.
Synchronous fluorescence spectroscopy for quantitative determination of virgin olive oil adulteration with sunflower oil 总被引:2,自引:0,他引:2
Adulteration of extra virgin olive oil with sunflower oil is a major issue for the olive oil industry. In this paper, the
potential of total synchronous fluorescence (TSyF) spectra to differentiate virgin olive oil from sunflower oil and synchronous
fluorescence (SyF) spectra combined with multivariate analysis to assess the adulteration of virgin olive oil are demonstrated.
TSyF spectra were acquired by varying the excitation wavelength in the region 270–720 nm and the wavelength interval (Δλ) in the region from 20 to 120 nm. TSyF contour plots for sunflower, in contrast to virgin olive oil, show a fluorescence
region in the excitation wavelength range 325–385 nm. Fifteen different virgin olive oil samples were adulterated with sunflower
oil at varying levels (0.5–95%) resulting in one hundred and thirty six mixtures. The partial least-squares regression model
was used for quantification of the adulteration using wavelength intervals of 20 and 80 nm. This technique is useful for detection
of sunflower oil in virgin olive oil at levels down to 3.4% (w/v) in just two and a half minutes using an 80-nm wavelength
interval. 相似文献
20.
Multivariate statistical analysis of sediment data (information matrix 123 × 16) from the Gulf of Mexico, USA shows that
the data structure is defined by four latent factors conditionally called “inorganic natural”, “inorganic anthropogenic”,
“bioorganic” and “organic anthropogenic” explaining 39.24%, 23.17%, 10.77% and 10.67% of the total variance of the data system,
respectively. The receptor model obtained by the application of the PCR approach makes it possible to apportion the contribution
of each chemical component for the latent factor formation. A separation of the contribution of each chemical parameter is
achieved within the frames of “natural” and “anthropogenic” origin of the respective heavy metal or organic matter to the
sediment formation process. This is a new approach as compared to the traditional “one dimensional” search with a limited
number of preliminary selected tracer components. The model suggested divides natural from anthropogenic influences and allows
in this way each participant in the sediment formation process to be used as marker of either natural or anthropogenic effects.
Received: 20 March 1999 / Revised: 1 June 1999 / Accepted: 3 June 1999 相似文献