Characterization of wild and ancient olive trees for its valorization”

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Discrimination of olive oil by cultivar, geographical origin and quality using potentiometric electronic tongue fingerprints

Publication . Souayah, Fatma; Rodrigues, Nuno; Veloso, Ana C.A.; Dias, L.G.; Pereira, J.A.; Oueslati, Souheib; Peres, António M.

Legal regulations are set for protecting claims regarding olive oil geographical denomination. When meteorological or agroecological factors similarly affect different regions, the origin identification is a challenging task. This study demonstrated the use of a potentiometric electronic tongue coupled with linear discriminant analysis to discriminate the geographical origin of monovarietal Tunisian olive oil produced from local cv Chemlali (Kairouan, Sidi Bouzid or Sfax regions) and cv Sahli (Kairouan, Mahdia or Sousse regions). The potentiometric fingerprints of 12 or eight lipid sensors (for Chemlali and Sahli, respectively), selected using a simulated annealing meta-heuristic algorithm, allowed the 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.

2017Journal article

Open access

Perception of olive oils sensory defects using a potentiometric taste device

Publication . Veloso, Ana C.A.; Silva, Lucas M.; Rodrigues, Nuno; Rebello, Ligia P.G.; Dias, L.G.; Pereira, J.A.; Peres, António M.

The 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 intra- and 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 (P-value = 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.

2018Journal article

Open access

Quantification of table olives' acid, bitter and salty tastes using potentiometric electronic tongue fingerprints

Publication . Marx, Ítala; Rodrigues, Nuno; Dias, L.G.; Veloso, Ana C.A.; Pereira, J.A.; Drunkler, Deisy A.; Peres, António M.

The intensities of the gustatory attributes of table olives is one of the sensory set of parameters evaluated by trained sensory panels accordingly to the recommendations of the International Olive Council. However this is an expensive and time-consuming process that only allows the evaluation of a limited number of samples per day. So, an electronic tongue coupled with multivariate statistical tools, is proposed for assessing the median intensities of acid, bitter and salty tastes perceived in table olives. The results showed that the device, coupled with linear discriminant analysis, could be used as a taste sensor, allowing classifying aqueous standard solutions according to the three basic tastes (repeated K-fold cross-validation: 98% ± 3% of correct classifications) based on the electrochemical signals of 5 sensors. It was demonstrated that the taste sensor with multiple linear regression models, enabled quantifying the median intensities of the three basic tastes (repeated K-fold cross-validation: R2 0.96 ± 0.04) perceived in table olives by a trained sensory panel, based on the potentiometric fingerprints (21e25 signal profiles) of aqueous olive pastes and brines. The overall satisfactory results showed the electronic tongue potential to assess the intensities of gustatory attributes of table olives, formerly only achievable by sensory panels.

2017Journal article

Open access

Characterization of commercial Tunisian monovarietal olive oils produced from autochthonous olive cultivars

Publication . Slim, Souihli; Rodrigues, Nuno; Veloso, Ana C.A.; Dias, L.G.; Cruz, Rebeca; Casal, Susana; Oueslati, Souheib; Pereira, J.A.; Peres, António M.

Tunisian commercial monovarietal olive oils, produced from two predominant autochthonous olive cultivars (cvs Chétoui and Oueslati) and another less investigated olive cultivar (cv Sahli) were studied. Chemical and sensory data have shown that most olive oils should be classified as lampante olive oil, pointing out the need of improving producing and/or storage conditions. Sahli olive oils showed the lowest total phenols content (157±48 mg/kg), oxidative stability (6.5±2.1 h), DPPH scavenging activity (68%±14) and monounsaturated fatty acids content (63.1%±3.1). These olive oils had the highest saturated and polyunsaturated fatty acids contents (19.9%±2.4 and 16.9%±1.4) as well as total tocopherols levels (222±49 mg/kg). Finally, the information of 12 selected parameters (total phenols, oxidative stability, nine fatty acids and γ-tocopherol), allowed establishing a linear discriminant model that correctly classified olive oils according to the olive cultivar with predictive rates of 90%±8. Heptadecenoic, behenic and eicosenoic acids were the three fatty acids identified as the most relevant chemical markers of Sahli olive oils.

2018Journal article

Open access

Sensory classification of table olives using an electronic tongue: analysis of aqueous pastes and brines

Publication . Marx, Ítala; Rodrigues, Nuno; Dias, L.G.; Veloso, Ana C.A.; Pereira, J.A.; Drunkler, Deisy A.; Peres, António M.

Table olives are highly appreciated and consumed worldwide. Different aspects are used for trade category classification being the sensory assessment of negative defects present in the olives and brines one of the most important. The trade category quality classification must follow the International Olive Council directives, requiring the organoleptic assessment of defects by a trained sensory panel. However, the training process is a hard, complex and sometimes subjective task, being the low number of samples that can be evaluated per day a major drawback considering the real needs of the olive industry. In this context, the development of electronic tongues as taste sensors for defects' sensory evaluation is of utmost relevance. So, an electronic tongue was used for table olives classification according to the presence and intensity of negative defects. Linear discrimination models were established based on sub-sets of sensor signals selected by a simulated annealing algorithm. The predictive potential of the novel approach was first demonstrated for standard solutions of chemical compounds that mimic butyric, putrid and zapateria defects (≥93% for cross-validation procedures). Then its applicability was verified; using reference table olives/brine solutions samples identified with a single intense negative attribute, namely butyric, musty, putrid, zapateria or winey-vinegary defects (≥93% cross-validation procedures). Finally, the E-tongue coupled with the same chemometric approach was applied to classify table olive samples according to the trade commercial categories (extra, 1(st) choice, 2(nd) choice and unsuitable for consumption) and an additional quality category (extra free of defects), established based on sensory analysis data. Despite the heterogeneity of the samples studied and number of different sensory defects perceived, the predictive linear discriminant model established showed sensitivities greater than 86%. So, the overall performance achieved showed that the electrochemical device could be used as a taste sensor for table olives organoleptic trade successful classification, allowing a preliminary quality assessment, which could facilitate, in the future, the complex task of sensory panelists.

2017Journal article

Open access