Multivariate calibration applied to ESI mass spectrometry data: a tool to quantify adulteration in extra virgin olive oil with inexpensive edible oils

Alves, J. O.; Sena, Marcelo M.; Augusti, Rodinei

doi:10.1039/c4ay00967c

Cited by 13 publications

(4 citation statements)

References 38 publications

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“…In this method, the determination of latent variables (factors or components) is carried out under the criterion of as high as possible covariance between the response variables and the explanatory variables, yielding a regression model. In such an approach, large and continuous datasets containing abundant multicollinearities (mass spectra) can be handled . Reduction of data dimensionality is performed by eliminating explanatory variables of low covariance and by selecting a suitable number of components; cross‐validation is applied to set the final regression model which minimizes the error of an analyte's concentration prediction.…”

Section: Resultsmentioning

confidence: 99%

“…Partial least squares (PLS2) is a typical tool available for multivariate analysis, especially useful when relatively few samples with a large containing abundant multicollinearities (mass spectra) can be handled. 36,37 Reduction of data dimensionality is performed by eliminating explanatory variables of low covariance and by selecting a suitable number of components; cross-validation is applied to set the final regression model which minimizes the error of an analyte's concentration prediction. Using the mass spectra dataset, the explanatory variables correspond to m/z values and there is no need for the identification nor for the assignation of individual ionic species.…”

Section: Partial Least Squares Regression (Pls2)mentioning

confidence: 99%

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Determination of copper and lead in tequila by conventional matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry and partial least squares regression

Garcia

Wróbel

Barrientos

et al. 2018

Rapid Comm Mass Spectrometry

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Rationale Quantification of small molecules by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOFMS) is challenging yet attractive, due to micro‐scale procedural simplicity, high throughput and lack of memory effects. Since these features are important while analyzing trace elements in quality control schemes, MALDI‐TOFMS was used for the determination of copper (Cu) and lead (Pb) in tequila with quantification carried out by partial least squares regression (PLS2) and by univariate calibration (UC). Methods In the proposed procedure, Bi(III) was added as internal standard (IS), diethyldithiocarbamate complexes were formed (pH 7.4) and extracted into chloroform; after solvent evaporation and re‐constitution in acetonitrile, the sample was co‐crystallized with α‐cyano‐4‐hydroxycinnamic acid on a steel target. From the acquired mass spectra, UC was performed using IS‐normalized signals of the monoisotopic ions of analytes, and the m/z range 350–513 was used for PLS2. Accuracy was tested by recovery experiments and by inductively coupled plasma (ICP)‐MS analysis. Results When compared with direct analyte signal measurements, application of IS yielded enhanced analytical performance using either UC or PLS2; the method quantification limits were: 11.1 μg L−1, 23.4 μg L−1 for Cu and 89.8 μg L−1, 97.1 μg L−1 for Pb, respectively. In tequila, MALDI‐TOFMS and ICP‐MS provided consistent results for Cu (165–2599 μg L−1); Pb was not detected in any sample by MALDI‐TOFMS, yet recoveries obtained after standard addition were indicative of acceptable accuracy (400 μg L−1 Pb added; recoveries: 91.2–108% for UC and 98.8–120% for PLS2). Conclusions New experimental evidence has been provided supporting the inclusion of trace metals quantification within a range of MALDI‐TOFMS applications. Slightly better results were obtained for UC as compared with PLS2 yet both methods can be recommended for testing the compliance of Cu and Pb levels with Official Mexican Norm. Of note, while using PLS2, there is no need for signal integration nor for IS normalization.

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Section: Resultsmentioning

confidence: 99%

Section: Partial Least Squares Regression (Pls2)mentioning

confidence: 99%

Determination of copper and lead in tequila by conventional matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry and partial least squares regression

Garcia

Wróbel

Barrientos

et al. 2018

Rapid Comm Mass Spectrometry

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“…Aer specic extraction and enrichment of phospholipids combined the MS method, a 1% contamination level of HO was found in EVOO. Another example was introduced by Alves et al, 28 in which PLS and electrospray ionization mass spectrometry (ESI-MS) data were combined to determine the adulteration of EVOO with four adulterant oils (SoO, CoO, SuO, and CaO). Each model was built with 40 adulterated samples (from 0.5 to 20.0% w/w), which were prepared using commercial oils.…”

Section: Chromatography (-Mass Spectrometry) Methodsmentioning

confidence: 99%

Advanced detection methods for traceability of origin and authenticity of olive oils

Zhang

et al. 2015

Anal. Methods

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The adulteration of olive oils based on advanced sensors has attracted high interest owing to its health benefits in the prevention and treatment of certain pathologies. Concerning its health and commercial aspects, lower grade oil blending and other illegal additives in virgin olive oil can negatively affect the nutritive value of olive oil. This review focuses on the advances in the sensing and identification of adulteration of olive oil. Optical sensing, chromatography (usually coupled with mass spectrometry), and nuclear magnetic resonance are discussed in detail. Other methods including a DNA-based method, dielectric spectroscopy, differential scanning calorimetry, thermogravimetric analysis and electronic nose among others, are overviewed as well.

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“…Prates et al (2010) combined multivariate calibration and ESI-MS to quantify the biodiesel content of a soybean/tallow blends with diesel. Alves et al (2014) applied PLS in spectra obtained by ESI-MS to determine adulteration of extra virgin olive oil with four adulterant oils (soybean, corn, sunflower, and rapeseed).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Kinematic Viscosity and Density of Biodiesel Using Electrospray Ionization Mass Spectrometry by Multivariate Statistical Models

Leal

Sarmanho²,

Leal³

et al. 2016

Energy Fuels

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By Brazilian law, biodiesel has to satisfy certain quality requirements and measurements established by standardized procedures, as is the case for kinematic viscosity and density. In this respect, information on the profile of methyl esters in biodiesel is very important because they are directly related to both these parameters. The objective of this study was to determine the profile of methyl esters present in a biodiesel sample by electrospray ionization mass spectrometry and evaluate its reliability in predicting their kinematic viscosity and density. Two multivariate statistical models were used for this purpose, the multiple multivariate linear regression (MMLR) and the partial least square regression (PLSR). The input variables used in the models were the relative intensities of the main methyl ester peaks, and the models were compared by their predictive behavior. Samples were randomly divided into two parts: 87% in the training or calibration set, used for the estimation of MMLR and PLSR models, and the remaining 13% in the test or validation set, which was used to evaluate the predictive power of each model that was estimated. Although the root mean squared error and R 2 for the MMLR model were slightly better than those of the PLSR model (R 2 PLSR = 0.9232 and R 2 MMLR = 0.9908 for kinematic viscosity and R 2 PLSR = 0.8721 and R 2 MMLR = 0.9415 for density), both showed a similarity with respect to predicted values for the training and validation sets, and thus for the performance statistics, attesting to the quality of these models in predicting kinematic viscosity and density. Furthermore, the prediction of kinematic viscosity showed better performance compared to the density.

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Multivariate calibration applied to ESI mass spectrometry data: a tool to quantify adulteration in extra virgin olive oil with inexpensive edible oils

Abstract: A fast method of multivariate calibration applied to ESI-MS data for quantification of adulteration of EVOO with cheaper edible oils.

Cited by 13 publications

References 38 publications

Determination of copper and lead in tequila by conventional matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry and partial least squares regression

Determination of copper and lead in tequila by conventional matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry and partial least squares regression

Advanced detection methods for traceability of origin and authenticity of olive oils

Prediction of Kinematic Viscosity and Density of Biodiesel Using Electrospray Ionization Mass Spectrometry by Multivariate Statistical Models

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