Sugars’ Quantifications Using a Potentiometric Electronic Tongue with Cross-Selective Sensors: Influence of an Ionic Background

Abstract

Glucose, fructose and sucrose are sugars with known physiological effects, and their consumption has impact on the human health, also having an important effect on food sensory attributes. The analytical methods routinely used for identification and quantification of sugars in foods, like liquid chromatography and visible spectrophotometry have several disadvantages, like longer analysis times, high consumption of chemicals and the need for pretreatments of samples. To overcome these drawbacks, in this work, a potentiometric electronic tongue built with two identical multi-sensor systems of 20 cross-selectivity polymeric sensors, coupled with multivariate calibration with feature selection (a simulated annealing algorithm) was applied to quantify glucose, fructose and sucrose, and the total content of sugars as well. Standard solutions of ternary mixtures of the three sugars were used for multivariate calibration purposes, according to an orthogonal experimental design (multilevel fractional factorial design) with or without ionic background (KCl solution). The quantitative models’ predictive performance was evaluated by cross-validation with K-folds (internal validation) using selected data for training (selected with the K-means algorithm) and by external validation using test data. Overall, satisfactory predictive quantifications were achieved for all sugars and total sugar content based on subsets comprising 16 or 17 sensors. The test data allowed us to compare models’ predictions values and the respective sugar experimental values, showing slopes varying between 0.95 and 1.03, intercept values statistically equal to zero (p-value ≥ 0.05) and determination coefficients equal to or greater than 0.986. No significant differences were found between the predictive performances for the quantification of sugars using synthetic solutions with or without KCl (1 mol L−1), although the adjustment of the ionic background allowed a better homogenization of the solution’s matrix and probably contributed to an enhanced confidence in the analytical work across all of the calibration working range.

Effect of malaxation temperature on the physicochemical and sensory quality of cv. Cobrançosa olive oil and its evaluation using an electronic tongue

“…Higher lipid concentration leads to a more hydrophilic surface and, contrary, higher plasticizer concentration corresponds to a more hydrophobic surface . The capacity and versatility of E-tongues containing lipid sensors to qualitatively or quantitatively assess physicochemical compounds that can be related to different sensory gustatory sensations has been reported in the literature (Arca, Peres, Machado, Bona, & Dias, 2019;Jeong et al, 2020;Oohira & Toko, 1996;Oohira, Toko, Akiyama, Yoshihara, & Yamafuji, 1995;Sharma et al, 2015;Slim et al, 2017;Toko, Hara, Tahara, Yasuura, & Ikezaki, 2014;Veloso et al, 2016;Wu, Miyake, et al, 2020;Yasuura, Shen, Tahara, Yatabe, & Toko, 2015) and recently reviewed by Wu, Tahara, Yatabe, and Toko (2020). In fact, polar compounds (acids, alcohols, aldehydes, esters and phenolic compounds, among others) can be naturally found in olive oils or in other olive products.…”

Improvement strategies of food supply chain through novel food processing technologies during COVID-19 pandemic

“…An E-tongue is a simulation of the human tongue for rapid, and unbiased detection of five basic tastes via taste sensors, including potentiometric sensors, voltametric sensors, and bioelectric sensors ( Jiang et al, 2018 ). Potentiometric E-tongue has been used for oil classification from a single olive cultivar ( Dias et al, 2014 ), honey differentiation ( Escriche et al, 2012 ), beer and wine discrimination ( Nery & Kubota, 2016 ), and sugar quantification in solution ( Arca et al, 2019 ). Similarly, voltametric E-tongue was used to detect the adulteration of sunflower oil in argan oil ( Bougrini et al, 2014 ), to discriminate the honey from different flowers ( Tiwari et al, 2013 ), and to analyze spring water ( Carbó et al, 2017 ).…”

Impact of the Covering Vegetable Oil on the Sensory Profile of Canned Tuna of Katsuwonus pelamis Species and Tuna’s Taste Evaluation Using an Electronic Tongue

“…However, for qualitative and quantitative evaluations, the former present known drawbacks, including the intrinsic subjectivity of human assessment, problems of human fatigue, and the limited daily number of samples that can be assessed [14,15]. Regarding the sensor-based approach, it is known that, for example, potentiometric electronic tongues (E-tongue) with lipid membranes can interact with polar compounds present in the food matrices, through electrostatic/hydrophobic interactions, which are responsible for different sensory attributes, including the basic tastes [16][17][18][19][20][21][22][23][24]. The lipid membrane sensor's sensitivity depends on the concentration of the charged lipids inside the membrane, its selectivity being dependent on the surface hydrophobicity, which in turn depends on the relative composition and type of lipids and plasticizers used [25].…”