A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools

Silva

et al. 2018

Talanta

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A B S T R A C TThe capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intraand inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (Pvalue = 0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils' sensory defect (P-value = 0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75 ± 3% and specificity of 73 ± 4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92 ± 3% of the olive oils as virgin or lampante, being an average specificity of 93 ± 3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils' defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage.

Section: E-tongue Devicementioning

confidence: 99%

Perception of olive oils sensory defects using a potentiometric taste device

Silva

et al. 2018

Talanta

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“…1) included two homemade print-screen potentiometric arrays covered with an acrylic resin (PLASTIK 70) for ensuring a waterproof surface. As previously described (Dias et al, 2015;Veloso et al, 2018), each polyvinyl chloride (PVC) board (3 cm × 12 cm) had 20 wells (3.6 mm of diameter and 0.3 mm of thickness), where 20 cross-sensitivity lipid polymeric membranes were applied, using a drop-by-drop technique. The polymeric membranes had different combinations of 4 lipid additives (∼3%: octadecylamine, oleyl alcohol, methyltrioctylammonium chloride or oleic acid), 5 plasticizers (∼32%: bis(1-butylpentyl) adipate, dibutyl sebacate, 2-nitrophenyl-octylether, tris(2-ethylhexyl)phosphate or dioctyl phenylphosphonate) and PVC (∼65%), which were used as chemical sensors (Fluka, minimum purity ≥97%).…”

Section: E-tongue Device and Set-upmentioning

confidence: 99%

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

Harzalli

Computers and Electronics in Agriculture

et al. 2018

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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.

“…The E-tongue device was designed and constructed as previously described [22,23]. The device comprised two homemade print-screen potentiometric arrays (3 cm × 12 cm visible PVC sheet plus 5 cm due to the RS232 plug; Fig.…”

Section: E-tongue Device and Set-upmentioning

confidence: 99%

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

Souayah

et al. 2017

J Americ Oil Chem Soc

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correct prediction (repeated K-fold cross-validation) of the geographic production region with sensitivities of 92 ± 7% (Chemlali) and 97 ± 8% (Sahli). It was also confirmed the electronic tongue capability to classify Tunisian olive oil according to olive cultivar or quality grade. The results indicated the possible use of potentiometric fingerprints as a promising innovative strategy for olive oil analysis allowing assessing geographical origin, olive cultivar and quality grade, which are key factors determining olive oil price and consumers' preference.