3D printed e-tongue

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICONowadays, one of the biggest issues addressed to electronic sensor fabrication is the build-up of efficient electrodes as an alternative way to the expensive, complex and multistage processes required by traditional techniques. Printed electronics arises as an interesting alternative to fulfill this task due to the simplicity and speed to stamp electrodes on various surfaces. Within this context, the Fused Deposition Modeling 3D printing is an emerging, cost-effective and alternative technology to fabricate complex structures that potentiates several fields with more creative ideas and new materials for a rapid prototyping of devices. We show here the fabrication of interdigitated electrodes using a standard home-made CoreXY 3D printer using transparent and graphene-based PLA filaments. Macro 3D printed electrodes were easily assembled within 6 min with outstanding reproducibility. The electrodes were also functionalized with different nanostructured thin films via dip-coating Layer-by-Layer technique to develop a 3D printed e-tongue setup. As a proof of concept, the printed e-tongue was applied to soil analysis. A control soil sample was enriched with several macro-nutrients to the plants (N, P, K, S, Mg, and Ca) and the discrimination was done by electrical impedance spectroscopy of water solution of the soil samples. The data was analyzed by Principal Component Analysis and the 3D printed sensor distinguished clearly all enriched samples despite the complexity of the soil chemical composition. The 3D printed e-tongue successfully used in soil analysis encourages further investments in developing new sensory tools for precision agriculture and other fields exploiting the simplicity and flexibility offered by the 3D printing techniques.618FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO2014/03691-72015/14836-92015/21616-52017/06985-0sem informaçãosem informaçãoSem informaçã

Improved Classification of Orthosiphon stamineus by Data Fusion of Electronic Nose and Tongue Sensors

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together

A novel strategy for rapid identification of the fruits of Illicium verum and Illicium anisatum using electronic nose and tongue technology

Purpose: To develop an effective and rapid strategy for the identification of fruits of I. verum and I. anisatum based on their odor and taste.Methods: Electronic nose (E-nose) and electronic tongue (E-tongue) technology was used to identify the fruits of I. verum (FIV) and I. anisatum (FIA). Samples of FIA, FIV, and FIA : FIV mixtures in different proportions (1 : 3, 1 : 1, and 3 : 1) were prepared to evaluate the identification abilities of E-nose and Etongue methods. Samples were powdered and sifted through a standard sieve (aperture size 355 ± 13 μm) for E-nose analysis. Each sample was refluxed with water for 1 h before E-tongue analysis. The acquired data were analyzed by principal component analysis (PCA) and discriminant factor analysis (DFA).Results: Based on the signals acquired by E-nose and E-tongue analyses, a total of 90 data points each were used for PCA. The three principal component values for E-nose analysis were PC1 = 93.89 %, PC2 = 6.08 %, and PC3 = 0.03 %, and those for E-tongue analysis were PC1 = 98.72 %, PC2 = 0.68 %, and PC3 = 0.57 %. The sample data were significantly divided into two groups representing FIV and FIA. Furthermore, E-nose and E-tongue assessments combined with PCA and DFA analyses effectively identified FIV, FIA and their mixtures.Conclusion: The use of E-nose and E-tongue technology is an effective and rapid strategy to identify the fruits of I. verum and I. anisatum and their mixtures. This strategy may also offer an effective method for detection of adulterants.Keywords: Illicium verum, Illicium anisatum, Discrimination, Electronic nose, Electronic tongue, Safety, Principal component analysis, Discriminant factor analysi

Optimization and validation of the protocol used to analyze the taste of traditional Chinese medicines using an electronic tongue

Tools to define the active ingredients and flavors of Traditional Chinese Medicines (TCMs) are limited by long analysis times, complex sample preparation and a lack of multiplexed analysis. The aim of the present study was to optimize and validate an electronic tongue (E‑tongue) methodology to analyze the bitterness of TCMs. To test the protocol, 35 different TCM concoctions were measured using an E‑tongue, and seven replicate measurements of each sample were taken to evaluate reproducibility and precision. E‑tongue sensor information was identified and classified using analysis approaches including least squares support vector machine (LS‑SVM), support vector machine (SVM), discriminant analysis (DA) and partial least squares (PLS). A benefit of this analytical protocol was that the analysis of a single sample took \u3c15 min for all seven sensors. The results identified that the LS‑SVM approach provided the best bitterness classification accuracy (binary classification accuracy, 100%; ternary classification accuracy, 89.66%). The E‑tongue protocol developed showed good reproducibility and high precision within a 6 h measurement cycle. To the best of our knowledge, this is the first study of an E‑tongue being applied to assay the bitterness of TCMs. This approach could be applied in the classification of the taste of TCMs, and serve important roles in other fields, including foods and beverages

Insight into the sensing mechanism of an impedance based electronic tongue for honey botanic origin discrimination

Animpedance based electronictongue was developed and used to discriminate honey of different botanic origin. The e-tongue presented here is based on the small-signal frequency response of the electrical double-layer established between the honey solution and an array of four different sensing units composed by gold, carbon, indium-tin-oxide, and doped silicon. The ability of the e-tongue to discriminate honey of different floral origins was demonstrated by distinguishing honey from Bupleurum and Lavandula pollen prevalence. The honey fingerprint obtained with the e-tongue was validated by parallel melissopalenogical analysis and physico-chemical methods. It is demonstrated that the e-tongue is very sensitive to changes on the honey electrical conductivity. Small differences in electrical conductivity are introduced by the presence of ionisable organic acids and mineral salts. Moreover, we propose that the sensitivity of the tongue to changes in electrical conductivity can be explored to probe other complex liquid substances.We gratefully acknowledge financial support from the Portuguese Foundation for Science and Technology (FCT), the Instituto de Telecomunicações (UID/Multi/04326/2013), the Centro para os recursos biologicos e alimentos mediterranicos (UID/BIA/04325/2013) and the Centro de Estudos Florestais (UID/AGR/00239/2013).info:eu-repo/semantics/publishedVersio

Discrimination of Xihulongjing tea grade using an electronic tongue

Five grades of Xihulongjing tea (grade: AAA, AA, A, B and C, from the same region and processed with the same processing method) were discriminated using -Astree II electronic tongue (e-tongue) coupled with pattern recognition methods including principal component analysis (PCA), canonical discriminant analysis (CDA) and back-propagation neural networks (BPNN). Results of PCA and CDA showed that the grades of the samples were discriminated with the exception of a few overlap samples between grade AA and grade A. The discrimination of accuracy of the training sample set and the predicted sample set was 95.7 and 97.5%, respectively, by the analysis of BPNN. 92.9% of all the crossvalidated training sample set and 100% of the predicted sample set were exactly grouped by CDA. The sensory evaluation of the samples was consistent with the evaluation based on the e-tongue. Theresults show that the e-tongue is a potential tool to identify the tea quality

Keeping track of phaeodactylum tricornutum (Bacillariophyta) culture contamination by potentiometric e-tongue

The large-scale cultivation of microalgae provides a wide spectrum of marketable bioproducts, profitably used in many fields, from the preparation of functional health products and feed supplement in aquaculture and animal husbandry to biofuels and green chemistry agents. The commercially successful algal biomass production requires effective strategies to maintain the process at desired productivity and stability levels. Hence, the development of effective early warning methods to timely indicate remedial actions and to undertake countermeasures is extremely important to avoid culture collapse and consequent economic losses. With the aim to develop an early warning method of algal contamination, the potentiometric E-tongue was applied to record the variations in the culture environments, over the whole growth process, of two unialgal cultures, Phaeodactylum tricornutum and a microalgal contaminant, along with those of their mixed culture. The E-tongue system ability to distinguish the cultures and to predict their growth stage, through the application of multivariate data analysis, was shown. A PLS regression method applied to the E-tongue output data allowed a good prediction of culture growth time, expressed as growth days, with R-2 values in a range from 0.913 to 0.960 and RMSEP of 1.97-2.38 days. Moreover, the SIMCA and PLS-DA techniques were useful for cultures contamination monitoring. The constructed PLS-DA model properly discriminated 67% of cultures through the analysis of their growth media, i.e., environments, thus proving the potential of the E-tongue system for a real time monitoring of contamination in microalgal intensive cultivation

A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria

Microorganism assessment plays a key role in food quality and safety control but conventional techniques are costly and/or time consuming. Alternatively, electronic tongues (E-tongues) can fulfill this critical task. Thus, a potentiometric lab-made E-tongue (40 lipid sensor membranes) was used to differentiate four common food contamination bacteria, including two Gram positive (Enterococcus faecalis, Staphylococcus aureus) and two Gram negative (Escherichia coli, Pseudomonas aeruginosa). Principal component analysis and a linear discriminant analysis-simulated annealing algorithm (LDA-SA) showed that the potentiometric signal profiles acquired during the analysis of aqueous solutions containing known amounts of each studied bacteria allowed a satisfactory differentiation of the four bacterial strains. An E-tongue-LDA-SA model (12 non-redundant sensors) correctly classified 98 ± 5% of the samples (repeated K-fold-CV), the satisfactory performance of which can be attributed to the capability of the lipid membranes to establish electrostatic interactions/hydrogen bonds with hydroxyl, amine and/or carbonyl groups, which are comprised in the bacteria outer membranes. Furthermore, multiple linear regression models, based on selected subsets of E-tongue sensors (1215 sensors), also allowed quantifying the bacteria contents in aqueous solutions (0.993 ± 0.011 R2 0.998 ± 0.005, for repeated K-fold-CV). In conclusion, the E-tongue could be of great value as a preliminary food quality and safety diagnosis tool.Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020) and to CEB (UIDB/04469/2020), as well as to the BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. Ítala M.G. Marx also acknowledges the Ph.D. research grant (SFRH/BD/137283/2018) provided by FCT.info:eu-repo/semantics/publishedVersio

Standard Analytical Methods, Sensory Evaluation, NIRS and Electronic Tongue for Sensing Taste Attributes of Different Melon Varieties

Grafting by vegetables is a practice with many benefits, but also with some unknown influences on the chemical composition of the fruits. Our goal was to assess the effects of grafting and storage on the extracted juice of four orange-fleshed Cantaloupe type (Celestial, Donatello, Centro, Jannet) melons and two green-fleshed Galia types (Aikido, London), using sensory profile analysis and analytical instruments: An electronic tongue (E-tongue) and near-infrared spectroscopy (NIRS). Both instruments are known for rapid qualitative and quantitative food analysis. Linear discriminant analysis (LDA) was used to classify melons according to their varieties and storage conditions. Partial least square regression (PLSR) was used to predict sensory and standard analytical parameters. Celestial variety had the highest intensity for sensory attributes in Cantaloupe variety. Both green and orange-fleshed melons were discriminated and predicted in LDA with high accuracies (100%) using the E-tongue and NIRS. Galia and Cantaloupe inter-varietal classification with the E-tongue was 89.9% and 82.33%, respectively. NIRS inter-varietal classification was 100% with Celestial variety being the most discriminated as with the sensory results. Both instruments, classified different storage conditions of melons (grafted and self-rooted) with high accuracies. PLSR showed high accuracy for some standard analytical parameters, where significant differences were found comparing different varieties in ANOVA

Electrochemical taste sensor for unmasking extra-virgin olive oils adulterated with rancid or winey-vinegary olive oils

Olive oils may be commercially classified, in a decrease order of quality and economic value, as extra-virgin (EVOO), virgin (VOO) or lampante (LOO) olive oils, being quite prone to frauds. Thus legal protection regulations have been approved by the European Union Commission [1,2], being required the fulfilment of several physicochemical and sensory thresholds [3,4]. Unfortunately, the mixture of expensive olive oils with low quality oils aiming fraudulent economic revenue is still a common practice difficult to detect. In this work, a potentiometric electronic tongue (E-tongue) was used to detect adulteration of an EVOO with different added levels (2.5%, 5%, 10%, 20% and 40%; v/v) of an LOO with an intense sensory defect (rancid or wineyvinegary). Previously, similar electrochemical devices, also comprising lipid polymeric sensor membranes, showed to be able to give qualitative and/or quantitative responses towards basic taste sensations (acid, bitter, salty, sweet, and umami), positive sensory attributes (bitter, fruity, green and pungency) or defects (e.g., butyric, musty, putrid, winey-vinegary and zapateria) [5-8]. The E-tongue coupled with linear discriminant technique (based on the signal profiles of 19 or 20 E-tongue sensors, chosen using a simulated annealing meta-heuristic variable selection algorithm, for rancid and wineyvinegary adulterations, respectively) allowed to semi-quantitatively distinguish olive oils with different adulteration levels (repeated K-fold crossvalidation predictive correct classifications of 84±10% and 94±8% for rancid and winey-vinegary adulterations, respectively). The preliminary results showed the practical potential of the E-tongue as a taste device for the successful detection of EVOOs adulterated with LOO containing organoleptic defects.This work was financially supported by POCI- 01–0145-FEDER-006984–Associate Laboratory LSRE-LCM, Project UID/QUI/00616/2013 –CQVR, Project UID/BIO/04469/2013 – CEB and Project UID/AGR/00690/2013 –CIMO all funded by FEDER, through COMPETE2020, and by national funds through. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant SFRH/BD/104038/2014.info:eu-repo/semantics/publishedVersio