Discrimination of Olive Oil by Cultivar, Geographical Origin and Quality Using Potentiometric Electronic Tongue Fingerprints

Souayah, Fatma; Rodrigues, Nuno; Veloso, Ana C. A.; Dias, Luís G.; Pereira, José Alberto; Oueslati, Souheib; Peres, António M.

doi:10.1007/s11746-017-3051-6

Cited by 30 publications

(22 citation statements)

References 37 publications

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“…Harzalli et al Computers and Electronics in Agriculture 144 (2018) 222-231 the potentiometric E-tongue capability to detect adulterated EVOO due to the intentionally addition of different percentages of LOO-R or LOO-WV, was evaluated using linear discriminant analysis (LDA) coupled with the meta-heuristic simulated annealing (SA) variable selection algorithm (Bertsimas and Tsitsiklis, 1992;Kirkpatrick et al, 1983;Cadima et al, 2004). The electrochemical-chemometric strategy followed was similar to previous works of the research team Rodrigues et al, 2016;Veloso et al, 2016Veloso et al, , 2018Marx et al, 2017aMarx et al, , 2017bMarx et al, , 2017cSlim et al, 2017;Souayah et al, 2017). The signal profiles generated during the electrochemical analysis of the hydro-ethanolic extracts of non-adulterated and intentionally-adulterated olive oils were subjected to a linear discriminant analysis (LDA) in combination with a meta-heuristic simulated annealing (SA) algorithm, in order to establish predictive E-tongue-LDA-SA models capable of classifying olive oil according to their adulteration level.…”

Section: Discussionmentioning

confidence: 99%

“…The literature survey clearly point out the limited number of works reporting the successful use of E-noses (Oliveros et al, 2002;Jeleń, 2008, 2010;Lerma-García et al, 2010;Santonico et al, 2015) to detect olive oil adulteration with other vegetable oils or lower quality olive oils (possessing or not common sensory defects), as well as the scarce use of voltammetric E-tongues (Apetrei and Apetrei, 2014;Santonico et al, 2015). Recently, the use of a pontentiometric E-tongue device comprising cross-sensitivity lipid polymeric membranes, has demonstrated to be a practical and helpful taste sensor tool for olive oil analysis (Dias et al, 2014Veloso et al, 2016Veloso et al, , 2018Slim et al, 2017;Souayah et al, 2017). It was previously reported by Marx et al (2017b) and Slim et al (2017) the capability of this type of E-tongue to provide quantitative potentiometric responses towards aldehydes, alcohols and esters compounds that mimic positive olive oil sensory attributes namely, 4-hydroxy-3-methoxybenzaldehyde (vanilla sensation), hexyl acetate (sweet, green, grassy, fruity or apple sensations), (Z)-hex-3-en-1-ol (green leaves or banana sensations), (E)-hex-2-enal (green, almonds or apple sensations), (Z)-hex-3-enyl acetate (fruity or green leaves sensations), citric and tartaric acids (acid sensation), caffeine and quinine (bitter sensations) and sodium or potassium chloride (salty sensation).…”

Section: Introductionmentioning

confidence: 99%

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A taste sensor device for unmasking admixing of rancid or winey-vinegary olive oil to extra virgin olive oil

Harzalli

Rodrigues

Veloso

et al. 2018

Computers and Electronics in Agriculture

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A B S T R A C TElectrochemical sensor devices have gathered great attention in food analysis namely for olive oil evaluation. The adulteration of extra-virgin olive oil with lower-grade olive oil is a common worldwide fraudulent practice, which detection is a challenging task. The potentiometric fingerprints recorded by lipid polymeric sensor membranes of an electronic tongue, together with linear discriminant analysis and simulated annealing metaheuristic algorithm, enabled the detection of extra-virgin olive oil adulterated with olive oil for which an intense sensory defect could be perceived, specifically rancid or winey-vinegary negative sensations. The homemade designed taste device allowed the identification of admixing of extra-virgin olive oil with more than 2.5% or 5% of rancid or winey-vinegary olive oil, respectively. Predictive mean sensitivities of 84 ± 4% or 92 ± 4% and specificities of 79 ± 6% or 93 ± 3% were obtained for rancid or winey-vinegary adulterations, respectively, regarding an internal-validation procedure based on a repeated K-fold cross-validation variant (4 folds × 10 repeats, ensuring that the dataset was forty times randomly split into 4 folds, leaving 25% of the data for validation purposes). This performance was satisfactory since, according to the legal physicochemical and sensory analysis, the intentionally adulterated olive oil with percentages of 2.5-10%, could still be commercialized as virgin olive oil. It could also be concluded that at a 5% significance level, the trained panelists could not distinguish extra-virgin olive oil samples from those adulterated with 2.5% of rancid olive oil or up to 5% of winey-vinegary olive oil. Thus, the electronic tongue proposed in this study can be foreseen as a practical and powerful tool to detect this kind of worldwide common fraudulent practice of high quality olive oil.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A taste sensor device for unmasking admixing of rancid or winey-vinegary olive oil to extra virgin olive oil

Harzalli

Rodrigues

Veloso

et al. 2018

Computers and Electronics in Agriculture

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“…These models had the most representative and non-collinear sub-sets of sensor signal profiles that were selected, in each case, by applying the simulated annealing (SA) meta-heuristic algorithm. This algorithm has proven to be a powerful variable selection algorithm, for both qualitative Dias et al, 2014;Slim et al, 2017;Souayah et al, 2017;Veloso et al, 2018Veloso et al, , 2016 and quantitative ) evaluation of olive oil using potentiometric taste sensor devices. The quality criterions involved the maximization of the coefficient of determination (R 2 ) and the minimization of the root-mean-square error (RMSE) for the lowest number of sensors with non-collinear potentiometric signals responses, based on the results achieved for the leave-one-out (LOO) cross-validation (CV) procedure (Cadima, Cerdeira, & Minhoto, 2004;Cadima, Cerdeira, Silva, & Minhoto, 2012;Cortez, 2014).…”

Section: Discussionmentioning

confidence: 99%

Application of a potentiometric electronic tongue for assessing phenolic and volatile profiles of Arbequina extra virgin olive oils

Borges

Peres

Dias

et al. 2018

LWT

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A B S T R A C TThe capability of determining the phenolic and volatile profiles of olive oils is of major relevance since these compounds are known to greatly influence the gustatory and olfactory positive attributes of olive oils. An electronic tongue with multiple linear regression models was used to evaluate both profiles based on olive oils potentiometric data generated during a single assay. The proposed electronic tongue-chemometric procedure enabled the quantification of flavonoids, phenolic acids and phenol alcohols of Arbequina extra-virgin olive oils with a similar accuracy of UPLC-MS (0.93 ± 0.03 ≤ R 2 ≤ 0.98 ± 0.08 for the repeated K-fold cross-validation procedure). Also, it was verified that the potentiometric device should not be applied to evaluate volatile compounds in solution (0.80 ± 0.14 ≤ R 2 ≤ 0.94 ± 0.05 for the repeated K-fold cross-validation procedure),showing a lower accuracy than HS-SPME-GS-MS. The overall satisfactory results showed that electronic tongue could be used as a practical sensing instrument to generate a chemical profile of the compounds known to influence the positive sensory attributes of olive oils.

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“…Therefore, the search for methods which enable to verify geographical origin and authenticity of olive oils has been the object of numerous studies in the past few years. Different targeted and non‐targeted approaches as well as different analytical techniques in combination with multivariate data analysis were applied for this purpose: While some studies focused on the analysis of specific compounds like sterols, carotinoids, tocopherols, isotope ratios, volatiles, and phenolic compounds, other studies used the so called “chemical fingerprints” of olive oils analyzed by gas and liquid chromatography, mass spectrometry, spectroscopic techniques (NMR, NIR, MIR, and Raman fluorescence) or potentiometric electronic nose . The combination of the determination of phenolic compounds, sterols or other minor compounds with fatty acid (FA) patterns is also proposed .…”

Section: Introductionmentioning

confidence: 99%

A Systematic Chemometric Approach to Identify the Geographical Origin of Olive Oils

Gertz¹,

Gertz²,

Matthäus

et al. 2019

Euro J Lipid Sci & Tech

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The verification of the geographical origin of olive oils by analytical techniques is still a challenge. The goal of this work is to explore the application and accuracy of different chemometric tools combined with near infrared spectroscopy (NIR) based analytical methods in the field of geographical authenticity of olive oils. As olive oils associated with different geographical origins are mainly characterized by different fatty acid (FA) and triacylglycerol (TAG) compositions, NIR methods for the fast and reliable determination of these parameters are developed. Next, these NIR methods are used to characterize a comprehensive set of olive oils (n > 5000) derived from 19 different countries. This set of data is used to build a statistical workflow, which allows the determination of the geographical origin of unknown olive oil samples. First of all, the untreated data set is pretreated by k‐means clustering and the selection of the relevant analytical variables by principal component analysis (PCA) and linear discriminant analysis (LDA) and min/max normalization of all parameters. Subsequently, classification is performed with a reduced sample set of the 200 most similar samples identified by k‐nearest neighbor tool (kNN). For classification purpose kNN, LDA, naïve Bayes classifier, and logit regression are applied. Practical Applications: The established statistical workflow can be used to verify the geographical origin of olive oils. The application and usage of up to four different statistical models for classification purpose results in a superior probability of the predicted origin in comparison to the application of only one single statistical classification test. As standardized methods are used as reference methods for building the NIR methods, the FA and TAG composition and the iodine value can be either determined by the standard methods or by the described NIR method. The presented statistical approach will help to build up a system for the verification of the geographical origin of olive oils.

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Discrimination of Olive Oil by Cultivar, Geographical Origin and Quality Using Potentiometric Electronic Tongue Fingerprints

Cited by 30 publications

References 37 publications

A taste sensor device for unmasking admixing of rancid or winey-vinegary olive oil to extra virgin olive oil

A taste sensor device for unmasking admixing of rancid or winey-vinegary olive oil to extra virgin olive oil

Application of a potentiometric electronic tongue for assessing phenolic and volatile profiles of Arbequina extra virgin olive oils

A Systematic Chemometric Approach to Identify the Geographical Origin of Olive Oils

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