Sensory intensity assessment of olive oils using an electronic tongue

Abstract

a b s t r a c tOlive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14 7 2 to 257 6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

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

“…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.…”

“…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).…”

Perception of olive oils sensory defects using a potentiometric taste device

“…Recently, this same research team demonstrated the feasibility of fusing an E-nose (based on headspace mass spectrometry), an E-tongue (based on mid-infrared spectroscopy) and an E-eye (based on UV-Vis spectrophotometry) to discriminate EVOO, VOO and LOO, to detect the main off-flavors (fusty, musty, rancid and winey-vinegary) of olive oils and to predict the intensity scores of the main sensory attributes of olive oils evaluated by a human taste panel [5,6]. The capability of a potentiometric E-tongue with cross-sensitivity and non specific lipid polymeric membranes to correctly classify olive oils according to the sensory intensity perception levels (i.e., intense, medium and light) of positive attributes (fruity, bitter and pungency) has been shown by our research team [13]. A similar electrochemical device was also used to classify table olives according to the sensory quality category based on the intensity of the defect predominantly perceived (DPP), to differentiate organoleptic negative attributes that may be perceived in table olives, using standard solutions and real samples as well as to quantify the intensity of the DPP in table olive and respective brine solutions as well as to evaluate table olives' gustatory attributes (e.g., acid, bitter and salty sensations) [22][23][24].…”

“…In each assay, 10.00 g of olive oil were mixed to 100 mL of hydro-ethanolic solution during 5-10 min under strong agitation, using a vortex stirrer (LBX V05 series, lbx instruments), with a constant speed of approximately 500 rpm. This process allowed the extraction of polar compounds, which are responsible for sensory attributes of olive oils [10,13,25,26]. The mixture was left at ambient temperature during 60 min, after which, 40.0 mL of the supernatant solution was carefully removed and immediately analyzed with the Etongue.…”

“…Several approaches have been proposed as alternatives to human sensory panels to evaluate the quality of olive oil (positive and/ or negative attributes), namely those based on the individual or fused application of electronic noses, tongues and/or eyes (E-nose, E-tongue and/or E-eye), based on different analytical procedures and principles [5,6,[10][11][12][13]. Qualitative and/or quantitative E-tongue based approaches have been successfully reported for olive oils physicochemical and positive sensory sensations assessment [10,[13][14][15][16][17][18][19][20][21]. In which concerns the evaluation of negative sensory attributes, Borràs et al [4] proposed partial least squares discriminant classification models, based on mid-infrared spectra, to differentiate EVOOs (defect absent) from lower quality olive oils (defect present).…”