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The impact of the covering vegetable oil (sunflower oil, refined olive oil and extra virgin olive oil, EVOO) on the physicochemical and sensory profiles of canned tuna (Katsuwonus pelamis species) was evaluated, using analytical techniques and a sensory panel. The results showed that canned tuna covered with EVOO possesses a higher content of total phenols and an enhanced antioxidant capacity. This covering medium also increased the appreciated redness-yellowness color of the canned tuna, which showed a higher chromatic and intense color. Olfactory and kinesthetic sensations were significantly dependent on the type of oil used as covering medium. Tuna succulence and adhesiveness were promoted by the use of EVOO, which also contributed to decreasing the tuna-related aroma sensations. The tuna sensory data could be successfully used to identify the type of vegetable oil used. Moreover, a potentiometric electronic tongue allowed discriminating between the canned tuna samples according to the vegetable oil used (mean sensitivity of 96 ± 8%; repeated K-fold cross-validation) and the fruity intensity of the EVOO (mean sensitivity of 100%; repeated K-fold cross-validation). Thus, the taste sensor device could be a practical tool to verify the authenticity of the declared covering medium in canned tuna and to perceive the differences in consumers' taste., This research was funded by the Foundation for Science and Technology (FCT, Portugal) through the national funds FCT/MCTES to CIMO (UIDB/00690/2020) and to CEB (UIDB/04469/2020) units, to the Associate Laboratory SusTEC (LA/P/0007/2020), as well as by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte to BioTecNorte operation (NORTE-01-0145-FEDER-000004). Nuno Rodrigues thanks the National funding by FCT- Foundation for Science and Technology, P.I., through the Institutional scientific employment program-contract., info:eu-repo/semantics/publishedVersion

Oils from cv. Arbequina were industrially extracted together with olive leaves of cv. Arbequina or Santulhana (1%, w/w), and their olfactory and volatile profiles were compared to those extracted without leaves addition (control). The leaves incorporation resulted in green fruity oils with fresh herbs and cabbage olfactory notes, while control oils showed a ripe fruity sensation with banana, apple, and dry hay grass notes. In all oils, total volatile contents varied from 57.5 to 65.5mg/kg (internal standard equivalents), being aldehydes followed by esters, hydrocarbons, and alcohols the most abundant classes. No differences in the number of volatiles were observed. The incorporation of cv. Arbequina or Santulhana leaves significantly reduced the total content of alcohols and esters (minus 3756% and 1013%, respectively). Contrary, cv. Arbequina leaves did not influence the total content of aldehydes or hydrocarbons, while cv. Santulhana leaves promoted a significant increase (plus 49 and 10%, respectively). Thus, a leaf-cultivar dependency was observed, tentatively attributed to enzymatic differences related to the lipoxygenase pathway. Olfactory or volatile profiles allowed the successful unsupervised differentiation of the three types of studied cv. Arbequina oils. Finally, a lab-made electronic nose was applied to allow the nondestructive discrimination of cv. Arbequina oils extracted with or without the incorporation of olive leaves (100% and 99±5% of correct classifications for leave-one-out and repeated K-fold cross-validation variants), being a practical tool for ensuring the label correctness if future commercialization is envisaged. Moreover, this finding also strengthened that olive oils extracted with or without olive leaves incorporation possessed quite different olfactory patterns, which also depended on the cultivar of the olive leaves., The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020), CEB (UIDB/04469/2020), REQUIMTE-LAQV (UIDB/ 50006/2020) units, and the Associate Laboratories for Green Chemistry-LAQV (UIDB/50006/2020) and SusTEC (LA/P/0007/2020), as well as to BioTecNorte operation (NORTE01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. ´Itala M.G. Marx also acknowledges the PhD research grant (SFRH/BD/137283/2018) provided by FCT. Nuno Rodrigues likes to thank national funding by FCT—Foundation for Science and Technology, P.I., through the institutional scientific employment program contract., info:eu-repo/semantics/publishedVersion

Serra da Estrela is a Portuguese traditional cheese produced with raw ewes milk from Churra Mondegueira and Bordaleira autochthonous breeds and the wild thistle flower (Cynara cardunculus L.), which benefits from the status of Protected Designation of Origin. Cheese chemical composition, namely the fatty acids profile, depends on milk composition and on manufacturing practices. Thus, the identification of possible chemical biomarkers capable of classifying Serra da Estrela cheeses according to the dairy manufacturing plant, geographical origin or production date would be of utmost relevance for producers and consumers. A typical fatty acids profile, including 23 saturated and unsaturated fatty acids, was identified for the studied cheeses, being butyric, caproic, caprilic, capric, lauric, miristic, palmitic, stearic, oleic, linoleic and its trans-isomer and -linolenic acids the most abundant ones (relative mean abundances ranging from 1.4%±0.5% to 23.9%±1.9%). Linear discriminant models were established based on the most discriminative fatty acids (namely, caproic, caprilic, undecanoic, lauric, pentadecanoic, palmitic, palmitoleic, heptadecanoic, oleic, linoleic trans-isomer, heneicosanoic and arachidonic acids) that included less abundant fatty acids, which were selected using the simulated annealing algorithm. The established models enabled assessing cheeses origin (models based on 1012 fatty acids) and/or production date (model based on 20 fatty acids) with predictive sensitivities of 7188%. Therefore, fatty acids profiles coupled with chemometric techniques, could be foreseen as a fingerprint of cheeses genuineness, enhancing the consumers confidence when purchasing this high-value cheese, This work was financially supported by Associate Laboratory LSRE-LCM - UID/EQU/50020/2019, strategic funding UID/BIO/04469/2019-CEB and BioTecNorte operation (NORTE01-0145-FEDER-000004), and strategic project PEst-OE/AGR/ UI0690/2014–CIMO funded by—funded by national funds through FCT/MCTES (PIDDAC). The authors would also like to acknowledge the funding provided by the approved Project, with reference 02/ SAICT/ 2016/23290, entitled Characterization and Valorization of QSE PDO and its ability for health promotion (QCLASSE), financed by FCT., info:eu-repo/semantics/publishedVersion

Phenolic compounds contribute to the bioactive properties of olive oil. However, olive oils can only support a health claim concerning the protection against oxidative stress depending on the polyphenolic concentration, requiring effective measures during extraction to preserve/enhance their concentrations. The effect of the malaxation temperature (22, 28 and 34 °C) on the phenolic profile was studied for industrially extracted cv. Cobrançosa oils. Higher malaxation temperatures decreased the contents of the majority of the chromatographically detected compounds (P, The authors are grateful to the Foundation for Science andTechnology (FCT, Portugal) forfinancial support by national fundsFCT/MCTES to CIMO (UIDB/00690/2020), to CEB (UIDB/04469/2020), to REQUIMTE-LAQV (UIDB/50006/2020) and to BioTecNorteoperation (NORTE‐01‐0145‐FEDER‐000004) funded by the EuropeanRegional Development Fund under the scope of Norte2020‐Programa Operacional Regional do Norte. Ítala Marx acknowledges the Ph.D.research grant (SFRH/BD/137283/2018) provided by FCT. NunoRodrigues thanks the National funding by FCT- Foundation for Scienceand Technology, P.I., through the institutional scientific employment program-contract., info:eu-repo/semantics/publishedVersion

Electronic tongues include any electrochemical nonspecific multisensor device with global selectivity, aiming mimicking the human tongue taste capability. Electronic tongues have been widely and successfully applied as taste sensors in food and pharmaceutical areas showing huge potential as a complementary analytical tool for routine sensory analysis. In comparison with trained human panelists, the electronic tongue shows several advantages namely no detection fatigue, the possibility of analyzing toxic substances and performing objective analysis, while minimizing the risk of human subjectivity. This chapter aims to compile and discuss the main research advances reported in the last decade regarding the electronic tongues’ applications as taste sensors, being focused on the operating principles and types of devices. Thus, the main advantages and limitations of these fast, accurate, bioinspired potentiometric, voltammetric, and/or amperometric green sensor-based tools will be addressed, aiming to make an overview of the recent and future challenges toward industrial and commercial applications. The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020), to CEB (UIDB/04469/2020), to REQUIMTE-LAQV (UID/QUI/50006/2020) units and to BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. I´tala M.G. Marx also acknowledges FCT for the PhD grant (reference number SFRH/BD/137283/2018). info:eu-repo/semantics/publishedVersion

This study shows the potential application of a potentiometric electronic tongue coupled with a lab-made DataLogger device for the classification of dairy products according to the type of milk used in their production, i.e., natural, fermented and UHT milk. The electronic tongue device merged a commercial pH electrode and 15 lipid/polymeric membranes, which were obtained by a drop-by-drop technique. The potentiometric signal profiles gathered from the 16 sensors, during the analysis of the 11 dairy products (with ten replicate samples), together with principal component analysis showed that dairy samples could be naturally grouped according to the three types of milk evaluated. To further investigate and verify this capability, a linear discriminant analysis together with a simulated annealing variable selection algorithm was also applied to the electrochemical data, which were randomly split into two datasets, one used for model training and internal-validation using a repeated K-fold cross-validation procedure (with 64\% of the data); and the other for external validation purposes (containing the remaining 36\% of the data). The multivariate supervised strategy used allowed establishing a classification model, based on the potentiometric information of four sensor lipid membranes, which enabled achieving a successful discrimination rate of 100\\% for both internal- and external-validation processes. The demonstrated versatility of the built electronic tongue for discriminating dairy products according to the type of milk used in their production combined with its simplicity, low-cost and fast time analysis may envisage a possible future application in dairy industry., This study was funded in part by the Ministry of Research, Technology and Higher Education, the Republic of Indonesia, Project 001/SP2H/LT/DRPM/IV/2017. The authors also thank the Directorate General of Islamic Education and Instituto Politécnico de Bragança, Portugal, for their support throughout the completion of this work. This work was financially supported by Project POCI01–0145-FEDER-006984 – Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013 – CEB and strategic project PEst-OE/ AGR/UI0690/2014 – CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal., info:eu-repo/semantics/publishedVersion

Table olives are prone to the appearance of sensory defects that decrease their quality and in some cases result in olives unsuitable for consumption. The evaluation of the type and intensity of the sensory negative attributes of table olives is recommended by the International Olive Council, although not being legally required for commercialization. However, the accomplishment of this task requires the training and implementation of sensory panels according to strict directives, turning out in a time-consuming and expensive procedure that involves a degree of subjectivity. In this work, an electronic tongue is proposed as a taste sensor device for evaluating the intensity of sensory defects of table olives. The potentiometric signal profiles gathered allowed establishing multiple linear regression models, based on the most informative subsets of signals (from 24 to 29 recorded during the analysis of olive aqueous pastes and brine solutions) selected using a simulated annealing meta-heuristic algorithm. The models enabled the prediction of the median intensities (R2 ≥ 0.942 and RMSE ≤ 0.356, for leave-one-out or repeated K-fold cross-validation procedures) of butyric, musty, putrid, winey-vinegary, and zapateria negative sensations being, in general, the predicted intensities within the range of intensities perceived by the sensory panel. Indeed, based on the predicted mean intensities of the sensory defects, the electrochemical-chemometric approach developed could correctly classify 86.4% of the table olive samples according to their trade category based on a sensory panel evaluation and following the International Olive Council regulations (i.e., extra, 1st choice, 2nd choice, and olives that may not be sold as table olives). So, the satisfactory overall predictions achieved demonstrate that the electronic tongue could be a complementary tool for assessing table olive defects, reducing the effort of trained panelists and minimizing the risk of subjective evaluations., This work was financially supported by Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRE-LCM, by Project UID/QUI/00616/2013 —CQ-VR, and UID/AGR/00690/ 2013—CIMO, all funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through Fundação para a Ciência e a Tecnologia (FCT), Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN, and FSE for the Ph.D. Grant (SFRH/BD/104038/2014)., info:eu-repo/semantics/publishedVersion

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&rsquo, 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&rsquo, 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 &ge, 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&minus, 1), although the adjustment of the ionic background allowed a better homogenization of the solution&rsquo, s matrix and probably contributed to an enhanced confidence in the analytical work across all of the calibration working range.

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/publishedVersion

An electronic nose, comprising nine metal oxide sensors, has been built aiming to classify olive oils according to the fruity intensity commercial grade (ripely fruity or light, medium and intense greenly fruity), following European regulated complementary terminology. The lab-made sensor device was capable to differentiate standard aqueous solutions (acetic acid, cis-3-hexenyl, cis-3-hexen-1-ol, hexanal, 1-hexenol and nonanal) that mimicked positive sensations (e.g., fatty, floral, fruit, grass, green and green leaves attributes) and negative attributes (e.g., sour and vinegary defects), as well as to semi-quantitatively classify them according to the concentration ranges (0.05 to 2.25 mg/kg). For that, unsupervised (principal component analysis) and supervised (linear discriminant analysis: sensitivity of 92% for leave-one-out cross validation) classification multivariate models were established based on nine or six gas sensors, respectively. It was also showed that the built E-nose allowed differentiating/discriminating (sensitivity of 81% for leave-one-out cross validation) extra virgin olive oils according to the perceived intensity of fruitiness as ripely fruity, light, medium or intense greenly fruity. In conclusion, the gas sensor device could be used as a practical preliminary non-destructive tool for guaranteeing the correctness of olive oil fruitiness intensity labelling., The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/ MCTES to CIMO (UIDB/00690/2020), to CEB (UIDB/04469/2020) and to BioTecNorte operation (NORTE-01-0145-FEDER-000004) and Project “GreenHealth - Digital strategies in biological assets to improve wellbeing and promote green health” (Norte-01-0145-FEDER-000042) funded by the European Regional Development Fund (ERDF) under the scope of Regional Operational Program North 2020. ´Itala Marx acknowledges the Ph.D. research grant (SFRH/BD/137283/2018) provided by FCT. Nuno Rodrigues thanks the National funding by FCTFoundation for Science and Technology, P.I., through the Institutional Scientific Employment Program-contract., info:eu-repo/semantics/publishedVersion

The effect of thermal sterilization processes on the physicochemical parameters and sensory characteristics of Californian-style black olives, from Hojiblanca and Manzanilla Cacereña brine solutions, were evaluated. Two-way ANOVA showed that Hojiblanca olives had a lower phenols content and defect intensity and that increasing the sterilization period resulted in a decrease in total phenols and an increase of the cooked defect. The impact of thermal sterilization was further evaluated using a potentiometric electronic tongue, which was capable of discriminating the different sterilization treatments (repeated K-fold cross-validation sensitivity: 89.0?±?15.0% to 97.0?±?6.0%). Moreover, multiple regressions allowed the prediction of phenols (R2???0.95?±?0.03) and the intensity of the defect (R2???0.95?±?0.04). These results point out the feasibility of the electronic tongue as an analytical tool for monitoring the effects of thermal sterilization treatments. Furthermore, the satisfactory results obtained for the brine solutions may foresee a practical non-destructive method for indirect quality assessment of table olives., Consejería de Educación y Empleo of the Junta de Extremadura to work with a scholarship at the Polytechnic Institute of Bragança for 4 months (Resolución de 18 de julio de 2019, DOE de 25 de julio de 2019, no 143) (Expedient number A28). Nuno Rodrigues thanks to National funding by FCT- Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract. The authors are also grateful to the Foundation for Science and Technology (FCT, Portugal) and FEDER, under Programme PT2020, for the financial support of CIMO (UID/AGR/00690/2019) and of CEB (UID/BIO/04469/2019) and to BioTecNorte operation (NORTE-01-0145-FEDER-000004), info:eu-repo/semantics/publishedVersion

Oleaster (Olea europaea var. sylvestris), or the wild olive tree, has great interest as a source of genetic material for olive breeding programs. Nevertheless, information about its oil composition is scarce. In the present work, the characterization of oleaster fruit morphology and oil chemical composition from three different tree populations in Northeastern Portugal (Moncorvo, Alij&oacute, and Vila Nova de Foz C&ocirc, a) was performed. The three studied populations presented some morphological differences in the fruits, but similar oil chemical composition. Oleic acid (68.9&ndash, 70.6%) was the most abundant fatty acid. High variability was observed in total tocopherol content, ranging between 263 and 503 mg/kg. Additionally, high amounts of total sterols were found, from 1742 to 2198 mg/kg of oil. A rich composition in phenols was found with 14 phenolic compounds identified. The evaluated parameters for oleander oils allowed discriminating the oils according to the geographical origin and were consistent with those commonly found in olive oil, showing that they are particularly rich in antioxidants and can be exploited in breeding programs to increase the amounts of bioactive compounds in cultivated oils.

Mycotoxins are a group of secondary metabolites produced by different species of filamentous fungi and pose serious threats to food safety due to their serious human and animal health impacts such as carcinogenic, teratogenic and hepatotoxic effects. Conventional methods for the detection of mycotoxins include gas chromatography and high-performance liquid chromatography coupled with mass spectrometry or other detectors (fluorescence or UV detection), thin layer chromatography and enzyme-linked immunosorbent assay. These techniques are generally straightforward and yield reliable results; however, they are time-consuming, require extensive preparation steps, use large-scale instruments, and consume large amounts of hazardous chemical reagents. Rapid detection of mycotoxins is becoming an increasingly important challenge for the food industry in order to effectively enforce regulations and ensure the safety of food and feed. In this sense, several studies have been done with the aim of developing strategies to detect mycotoxins using sensing devices that have high sensitivity and specificity, fast analysis, low cost and portability. The latter include the use of microarray chips, multiplex lateral flow, Surface Plasmon Resonance, Surface Enhanced Raman Scattering and biosensors using nanoparticles. In this perspective, thin film sensors have recently emerged as a good candidate technique to meet such requirements. This review summarizes the application and challenges of thin film sensor devices for detection of mycotoxins in food matrices., This work was funded by Project POCI-01–0145-FEDER-006984 - Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013 - CEB and strategic project PEst-OE/AGR/UI0690/2014 - CIMO all funded by European Regional Development Fund (ERDF) through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia I.P. Andréia O. Santos also acknowledges the research grant provided by the Associate Laboratory LSRE-LCM under the Projects UID/EQU/50020/2013 and POCI-01-0145-FEDER-006984. Andreia Vaz acknowledges the research grant provided by the Portuguese Foundation for Science and Technology (FCT), reference number SFRH/BD/129775/2017. The APC was kindly waived by MDPI., info:eu-repo/semantics/publishedVersion

An electronic nose (E-nose), comprising eight metal oxide semiconductor (MOS) gas sensors and a moisture-temperature sensor, was used for classifying three quality grades of superior java cocoa beans, namely fine cocoa dark bean < 20%, fine cocoa dark bean > 60%, and bulk cocoa bean that is a harder task compared to the discrimination of high versus low-quality cocoa beans. The E-nose signals were pre-processed using the maximum value method. The capability for discriminating the quality grade of the cocoa beans was checked by applying multivariate statistical tools, namely, linear discriminant analysis (LDA), support vector machine (SVM) and artificial neural networks (ANN). For this, the experimental dataset was split into two subsets, one for training (i.e., establishing the classification models) and the other for external-validation purposes. Furthermore, hyperparameter optimization and K-fold cross-validation variant were implemented during the model training procedure to select the best classification models and to avoid over-fitting issues. The best predictive classification performance was obtained with the E-nose-MLP-ANN procedure, which allowed 99% of correct classifications (overall accuracy) for the training dataset and 95% of correct classifications (overall accuracy) for the external-validation dataset. The satisfactory results clearly demonstrated that the E-nose could be applied as a quality control tool in the cocoa industry, requiring minimum and simple sample preparation. © Intelligent Network and Systems Society., The authors thank the Directorate of Research and Community Service, Ministry of Research, Technology and Higher Education, the Republic of Indonesia for providing research grants of PTUPT 2019 (Contract No. 2688/UN1.DITLIT/DITLIT/LT/2019). The authors also like to acknowledge the financial support given by Associate Laboratory LSRE-LCM-UID/EQU/50020/2019, strategic funding UID/BIO/04469/2019-CEB, BioTecNorte operation (NORTE-01-0145-FEDER-000004) and strategic project PEst-OE/AGR/UI0690/2014 – CIMO, all funded by national funds through FCT/MCTES (PIDDAC)., info:eu-repo/semantics/publishedVersion

Olive oil is highly appreciated due to its nutritional and organoleptic characteristics. However, a huge compositional variation is observed between olive oils, requiring the use of diverse analytical techniques for its classification including titration, spectrophotometry and chromatography, as well as sensory analysis. Chemical analysis is usually time-consuming, expensive and require skilled technicians, while the sensorial ones are dependent upon individual subjective evaluations, even if performed by trained panellists. This work evaluated and demonstrated the feasibility of using a potentiometric electronic tongue, comprising non-specific lipid polymeric and cross-sensitive sensor membranes, coupled with chemometric tools based on different sub-sets of sensors (from 11 to 14 sensors), to predict key quality parameters of olive oils based on single-run assays. The multivariate linear models established for 23 centenarian olive trees from different cultivars allowed predicting peroxide value, oxidative stability, total phenols and tocopherols contents, CIELAB scale parameters (L*, a* and b* values), as well as 11 gustatory-retronasal positive attributes (green, sweet, bitter, pungent, tomato and tomato leaves, apple, banana, cabbage, fresh herbs and dry fruits) with satisfactory accuracy (0.90±0.07 R2 0.98±0.02 for the repeated K-fold-CV procedure, which ensured that 25% of the data was used for internal-validation purposes). The electronic tongue device had an accuracy statistically similar to that achieved with standard analytical techniques, pointing out the versatility of the device for the fast and simultaneous chemical and sensory analysis of olive oil., Project POCI-01-0145-FEDER-006984 – Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013 – CEB, Project UID/QUI/50006/2013 - REQUIMTE-LAQV and strategic project PEst-OE/AGR/UI0690/2014 – CIMO all funded by European Regional Development Fund (ERDF) through COMPETE2020 – Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT – Fundação para a Ciência e a Tecnologia I.P., info:eu-repo/semantics/publishedVersion

Honey-rich composition in biologically active compounds makes honey a food products highly appreciated due to the nutritional and healthy properties. Food-manufacturing is very prone to different types of adulterations and fraudulent labelling making it urgent to establish accurate, fast and cost-effective analytical techniques for honey assessment. In addition to the classical techniques (e.g., physicochemical analysis, microscopy, chromatography, immunoassay, DNA metabarcoding, spectroscopy), electrochemical based-sensor devices have arisen as reliable and green techniques for food analysis including honey evaluation, allowing in-situ and on-line assessment, being a user-friendly procedure not requiring high technical expertise. In this work, the use of electronic tongues, also known as taste sensor devices, for honey authenticity and assessment is reviewed. Also, the versatility of electronic tongues to qualitative (e.g., botanical and/or geographical origin assessment as well as detection of adulteration) and quantitative (e.g., assessment of adulterants levels, determination of flavonoids levels or antibiotics and insecticides residues, flavonoids) honey analysis is shown. The review is mainly focused on the research outputs reported during the last decade aiming to demonstrate the potentialities of potentiometric and voltammetric multi-sensor devices, pointing out their main advantages and present and future challenges for becoming a practical quality analytical tool at industrial and commercial levels., (undefined), This work was financially supported by Project POCI-01-0145-FEDER-006984-Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013-CEB and strategic project PEst-OE/AGR/UI0690/2014-CIMO all funded by FEDER-Fundo Europeu de Desenvolvimento Regional through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT-Fundação para a Ciência e a Tecnologia, Portugal., info:eu-repo/semantics/publishedVersion

Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation., This work was co-financed by FCT/MEC and FEDER under Programme PT2020 (Project UID/EQU/50020/2013); and under the strategic funding of UID/BIO/04469/2013 unit.

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination., This work was co-financed by FCT/MEC and FEDER under Program PT2020 (Project UID/EQU/50020/2013); by Fundacao para a Ciencia e Tecnologia under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC-Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal.

The identification of more than three perfumes is difficult and no analytical tool can completely replace the human olfactory system for fragrance classification. Indeed, no analytical system can mimic the human fragrance perception, being the recognition of perfume aroma patterns by conventional or sensor-based analytical tools a challenging task. For the perfume sector, the possibility of applying fast, cost-effective and green analytical devices for perfume analysis would represent a huge economic revenue. Since the perfume aroma pattern will depend on the composition of the liquid phase and on the diffusion properties of their volatile components, this work aimed to apply a potentiometric electronic tongue, comprising non-specific cross-sensitive lipid polymeric membranes, combined with chemometric techniques, as a novel perfume classifier. The multisensors device allowed establishing perfumes unique fingerprints, which were successfully used to discriminate men from women perfumes, to identify the perfume aroma family (Citric-Aromatic, Floral, Floral-Fruity, Floral-Oriental, Floral-Woody, Woody-Oriental and Woody-Spicy) and, assessing the perfume storage time-period (? 9 months; 924 months; and, ? 24 months). The established linear discriminant models were based on single-run potentiometric profiles gathered by sub-sets of sensors selected using the simulated annealing algorithm, which enabled achieving correct classification rates of 93100% (for leave-one-out cross-validation procedure). The satisfactory performance of the electronic tongue demonstrates the versatility of the proposed approach as a practical perfume preliminary classifier sensor device, which industrial application may be foreseen in a near future, contributing to a green-sustained economic growth of the perfume industry., This work was funded by Associate Laboratory LSRE-LCM - UID/EQU/50020/2019, strategic funding UID/BIO/04469/2019 - CEB and BioTecNorte operation (NORTE-01-0145-FEDER-000004), Project UID/QUI/50006/2019 - REQUIMTE-LAQV and strategic project PEst-OE/AGR/UI0690/2014 – CIMO, all funded by FCT/MCTES through national funds. Ítala G. Marx also acknowledges the Ph.D. research grant (SFRH/BD/137283/2018) provided by FCT., info:eu-repo/semantics/publishedVersion

An electronic nose (E-nose), comprising eight metal oxide semiconductor (MOS) gas sensors, was used in situ for real-time classification of black tea according to its quality level. Principal component analysis (PCA) coupled with signal preprocessing techniques (i.e., time set value preprocessing, F1, area under curve preprocessing, F2, and maximum value preprocessing, F3), allowed grouping the samples from seven brands according to the quality level. The E-nose performance was further checked using multivariate supervised statistical methods, namely, the linear and quadratic discriminant analysis, support vector machine together with linear or radial kernels (SVM-linear and SVM-radial, respectively). For this purpose, the experimental dataset was split into two subsets, one used for model training and internal validation using a repeated K-fold cross-validation procedure (containing the samples collected during the first three days of tea production), and the other, for external validation purpose (i.e., test dataset, containing the samples collected during the 4th and 5th production days). The results pointed out that the E-nose-SVM-linear model together with the F3 signal preprocessing method was the most accurate, allowing 100% of correct predictive classifications (external-validation data subset) of the samples according to their quality levels. So, the E-nose-chemometric approach could be foreseen has a practical and feasible classification tool for assessing the black tea quality level, even when applied in-situ, at the harsh industrial environment, requiring a minimum and simple sample preparation. The proposed approach is a cost-effective and fast, green procedure that could be implemented in the near future by the tea industry.

Olive oil phenolic compounds are receiving increased attention due to its influence on sensory characteristics and to scientific evidences of positive health effects. In this work, 28 ancient olive trees were selected and, during four consecutive seasons (2014–2017), oils were extracted and their phenolic fraction characterized. Hydroxytyrosol and tyrosol secoiridoids were the predominant groups, with contents between 32 and 496 mg of tyrosol equivalents/kg. Based on principal component analysis it could be concluded that the individual phenolic contents enabled the unsupervised grouping of olive oils by crop year. Furthermore, linear discriminant analysis allowed achieving sensitivities greater than 90%. It was shown that some specimens consistently allowed obtaining oils with high phenolic contents (≥500 mg tyrosol equivalents/kg). The identification of centenarian specimens for breeding based on their potential to produce oils with high levels of healthy compounds is of utmost interest, contributing to preserve the genetic heritage. This work was financially supported by Strategic Project PEst-OE/ AGR/UI0690/2014 (CIMO), Project UID/QUI/50006/2013 (REQUIMTE-LAQV); and Project POCI-01-0145-FEDER-006984 (Associate Laboratory LSRE-LCM); all funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through Fundação para a Ciência e a Tecnologia (FCT), Portugal. This work was also supported by PRODER project OliveOld – Identificação e caraterização de oliveiras centenárias para obtenção de produtos diferenciados” n° 53988. Nuno Rodrigues thanks FCT, POPHQREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014). info:eu-repo/semantics/publishedVersion

Supplementary data to this article can be found online at https://doi.org/10.1016/j.microc.2020.105034., The demand for organic foods has increased worldwide, in particular due to the association with healthier, more nutritious and tasty products, being a clear trend on sweet peppers consumption. Thus, this study aimed to evaluate the effects of agronomic production mode (conventional and organic) and maturation stage (associated to green, turning and red colours) on the chemical-sensory attributes of peppers grown in open field. It was found that organic peppers had a better visual/tactile aspect (greater firmness and more intense colours) but lower chemical quality (lower titratable acidity and total soluble solids). On the other hand, red peppers (higher maturation stage) had lower visual-tactile quality but higher chemical quality. From sensory analysis, conventional peppers had better overall aspect, colour intensity-homogeneity and brightness. Then again, the maturation stage of peppers mostly influenced the sensory visual attributes, being turning colour peppers the less appreciated, although organic red peppers were less succulent and had a lower global quality. Even so, the chemical-sensory parameters could be used to discriminate peppers taking into account the agronomic production mode and the maturation stage/colour (79±12% of correct classifications for the repeated K-fold cross-validation procedure). However, a trained sensory panel is required, which can be a major drawback considering their scarcity. This limitation was successfully overcome by using a potentiometric electronic tongue, which allowed discriminating the peppers with a higher predictive sensitivity (85±9%), showing that this device could be used as an accurate taste sensor for the qualitative analysis of sweet peppers., The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) and FEDER under Program PT2020 for financial support to CIMO (UIDB/00690/2020) and to CEB (UIDB/04469/2020) units and to BioTecNorte operation (NORTE‐01‐0145‐FEDER‐000004) funded by the European Regional Development Fund under the scope of Norte2020 ‐ Programa Operacional Regional do Norte. Nuno Rodrigues thanks to National funding by FCT- Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract., info:eu-repo/semantics/publishedVersion

The industrial process of freezing chestnuts generates 5560% of by-products. This study aimed to valorise these low-value by-products by producing high-value chestnut flour. Two flour production processes were evaluated, using raw (RCF) and cooked (CCF10, CCF30, CCF50) chestnut by-products during 10, 30 and 50 min. The highest production yield was obtained for RCF (43.6±1.0%) followed by CCF10 (38.0±1.0%). Regarding flour composition, CCF50 presented the smaller protein, fat, fibre and ash contents (P0.05). The CCF10 flour also presented the smallest particle size. The highest peroxide index was found in CCF50 penalizing its acceptance by consumers due to the evidence of rancidity, emphasizing that long time-periods of cooking must be avoided. Finally, up to 129 days of storage, under no temperature or lighting controlled conditions, all chestnut flours showed to be stable overtime., Part of this work was supported by the program CENTRO2020, under the code 02/SAICT/2016, financed by the Portuguese Government and FEDER. Project nº 023631: SoSValor-Sustainable solutions for the valorisation of plant natural products and industrial waste, and by PRODER-Inovação na cadeia de produção da castanha: competitividade e sustentabilidade—Medida 4.1, Cooperação para a Inovação, Ref.ª 53590. This work was also supported by Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013 — CEB and strategic project PEst-OE/ AGR/UI0690/2014—CIMO, all funded by FEDER through COMPETE2020—POCI and by Portuguese funds through FCT., info:eu-repo/semantics/publishedVersion

Olive oil has unique organoleptic attributes and its consumption is associated with nutritional and health benefits, which are mainly related to its rich composition in phenolic and volatile compounds. The use of olive oil in heat-induced cooking leads to deep reduction of phenolic and volatile concentrations and to changes of the sensory profiles. This work confirmed that oven and microwave heating significantly reduced total phenolic contents (value < 0.0001, one-way ANOVA), more pronounced in the latter, together with a significant reduction of the intensity of fruity, sweet, bitter, pungent, and green attributes (value < 0.0001, Kruskal-Wallis test), particularly for fruity and green sensations. Besides, bitter, fruity, green, and pungent intensities showed a linear dependency with the total phenolic contents (-Pearson 0.9694). Finally, the potentiometric electronic tongue together with linear discriminant analysis-simulated annealing algorithm allowed satisfactory discrimination (sensitivities of %, for repeated -fold cross-validation) of olive oils subjected to intense microwave heating (510min, 160205°C) from those processed under usual cooking conditions (oven heating during 1560min or microwave heating during 1.53min, 72165°C). This could be due to the different responses of the electronic tongue towards olive oils with diverse phenolic and sensory profiles., This work was financially supported by Associate Laboratory LSRE-LCM, Project POCI-01-0145-FEDER-006984;CQ-VR, Project UID/QUI/00616/2013; CEB, Project UID/BIO/04469/2013; REQUIMTE-LAQV, Project UID/QUI/50006/2013; and CIMO, Strategic Project PEst-OE/AGR/UI0690/2014, all funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through Fundação para a Ciência e a Tecnologia (FCT), Portugal. Nuno Rodrigues acknowledges FCT, POPH-QREN, and FSE for the Ph.D. Grant (SFRH/ BD/104038/2014)., info:eu-repo/semantics/publishedVersion

Electrochemical 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 meta-heuristic 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 2.510%, 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., This work was financially supported by Project POCI-01–0145FEDER-006984 – Associate Laboratory LSRE-LCM, Project UID/QUI/ 00616/2013 – CQ-VR, Project UID/BIO/04469/2013 – CEB and strategic project PEst-OE/AGR/UI0690/2014 – CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014). Souheib Oueslati is also grateful for the support of the Tunisian Ministry of Agriculture., info:eu-repo/semantics/publishedVersion

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., This work was financially supported by Project POCI-01–0145FEDER-006984 – Associate Laboratory LSRE-LCM, Project UID/QUI/ 00616/2013 – CQ-VR, and UID/AGR/00690/2013 – CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT Fundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/ 104038/2014)., info:eu-repo/semantics/publishedVersion

Electrochemical bioinspired sensor devices combined with chemometric tools have experienced great advances in the last years, being extensively used for food qualitative and quantitative evaluation, namely for olive oil analysis. Olive oil plays a key role in the Mediterranean diet, possessing unique and recognized nutritional and health properties as well as highly appreciated organoleptic characteristics. These positive attributes are mainly due to olive oil richness in bioactive compounds such as phenolic compounds. In addition, these compounds enhance their overall sensory quality, being mainly responsible for the usual olive oil pungency and bitterness. This review aims to compile and discuss the main research advances reported in the literature regarding the use of electrochemical sensor based-devices for assessing bioactive compounds in olive oil. The main advantages and limitations of these fast, accurate, bioinspired voltammetric, potentiometric and/or amperometric sensor green-approaches will be addressed, aiming to establish the future challenges for becoming a practical quality analytical tool for industrial and commercial applications., This research was funded by Project POCI-01–0145-FEDER-006984–Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013–CEB, Project UID/QUI/50006/2013–REQUIMTE-LAQV and strategic project PEst-OE/AGR/UI0690/2014–CIMO all funded by European Regional Development Fund (ERDF) through COMPETE2020–Programa Operacional Competitividade e Internacionalização (POCI)–and by national funds through FCT–Fundação para a Ciência e a Tecnologia I.P. Ítala G. Marx also acknowledges the research grant provided by Project UID/EQU/50020/2013 and POCI-01-0145-FEDER-006984. The APC was kindly waived by MDPI., info:eu-repo/semantics/publishedVersion

A DNA aptamer with affinity and specificity for human osteopontin (OPN), a potential breast cancer biomarker, was selected using the SELEX process, considering its homology rate and the stability of its secondary structures. This aptamer exhibited a satisfactory affinity towards OPN, showing dissociation constants lower than 2.5 nM. It was further used to develop a simple, label-free electrochemical aptasensor against OPN. The aptasensor showed good sensitivity towards OPN in standard solutions, being the square wave voltammetry (SWV), compared to the cyclic voltammetry, the most sensitive technique with detection and quantification limits of 1.4 ± 0.4 nM and 4.2 ± 1.1 nM, respectively. It showed good reproducibility and acceptable selectivity, exhibiting low signal interferences from other proteins, as thrombin, with 2.610 times lower current signals-off than for OPN. The aptasensor also successfully detected OPN in spiked synthetic human plasma. Using SWV, detection and quantification limits (1.3 ± 0.1 and 3.9 ± 0.4 nM) within the OPN plasma levels reported for patients with breast cancer (0.44.5 nM) or with metastatic or recurrent breast cancer (0.98.4 nM) were found. Moreover, preliminary assays, using a sample of human plasma, showed that the aptasensor and the standard ELISA method quantified similar OPN levels (2.2 ± 0.7 and 1.7 ± 0.1 nM, respectively). Thus, our aptasensor coupled with SWV represents a promising alternative for the detection of relevant breast cancer biomarkers., The authors acknowledge the financial support from the Strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), and from project BioTecNorte (project number NORTE-01-0145-FEDER-000004). This work was also financially supported by Project POCI-01–0145-FEDER-006984 – Associate Laboratory LSRE-LCM and by Project UID/QUI/00616/2013 – CQ-VR both funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal. S. Meirinho also acknowledges the research grant provided by Project UID/EQU/50020/2013., info:eu-repo/semantics/publishedVersion

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 (2125 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., This work was financially supported by Project POCI-01–0145-FEDER-006984 – Associate Laboratory LSRE-LCM and by Project UID/QUI/00616/2013 – CQ-VR both funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).

The development of bioinspired sensors has emerged and grown in recent decades, given their broad and exciting applications to pharmaceutical formulations, medical diagnosis and health care. These sensor-based technologies, owing to their function and to the elements involved in their design, potentially generate fast, selective, sensitive, safe and green analysis solutions. Their applications have evolved into mainly two fields. The first comprises sensor array systems like the electronic tongues (E-tongues), which are innovative (bio)sensing devices that, combined with chemometric tools, provide highly specialized responses, enabling the discrimination of thousands of possible targets. The second line of action involves the application of biosensors, namely aptasensors, which are highly specific against a target biomarker. In this chapter, the concept, design and application of electrochemical sensor approaches, such as E-tongues and aptasensors, for (bio)sensing applications, will be discussed and the main trends in medical and pharmaceutical applications will be highlighted. info:eu-repo/semantics/publishedVersion

Physicochemical quality parameters, olfactory and gustatoryretronasal positive sensations of extra-virgin olive oils vary during storage leading to a decrease in the overall quality. Olive oil quality decline may prevent the compliance of olive oil quality with labeling and significantly reduce shelf life, resulting in important economic losses and negatively condition the consumer confidence. The feasibility of applying an electronic tongue to assess olive oils usual commercial light storage conditions and storage time was evaluated and compared with the discrimination potential of physicochemical or positive olfactory/gustatory sensorial parameters. Linear discriminant models, based on subsets of 58 electronic tongue sensor signals, selected by the meta-heuristic simulated annealing variable selection algorithm, allowed the correct classification of olive oils according to the light exposition conditions and/or storage time (sensitivities and specificities for leave-one-out cross-validation: 8296 %). The predictive performance of the E-tongue approach was further evaluated using an external independent dataset selected using the KennardStone algorithm and, in general, better classification rates (sensitivities and specificities for external dataset: 67100 %) were obtained compared to those achieved using physicochemical or sensorial data. So, the work carried out is a proof-of-principle that the proposed electrochemical device could be a practical and versatile tool for, in a single and fast electrochemical assay, successfully discriminate olive oils with different storage times and/or exposed to different light conditions., The authors acknowledge the financial support from the strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRELCM funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia and under the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014)., info:eu-repo/semantics/publishedVersion

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 wineyvinegary 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, 1st choice, 2nd 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., This work was financially supported by Project POCI-01–0145FEDER-006984 – Associate Laboratory LSRE-LCM and by Project UID/QUI/00616/2013 – CQ-VR both funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).

Olive oil commercialization has a great impact on the economy of several countries, namely Tunisia, being prone to frauds. Therefore, it is important to establish analytical techniques to ensure labeling correctness concerning olive oil quality and olive cultivar. Traditional analytical techniques are quite expensive, time consuming and hardly applied in situ, considering the harsh environments of the olive industry. In this work, the feasibility of applying a potentiometric electronic tongue with cross-sensitivity lipid membranes to discriminate Tunisian olive oils according to their quality level (i.e., extra virgin, virgin or lampante olive oils) or autochthonous olive cultivar (i.e., cv Chétoui and cv Shali) was evaluated for the first time. Linear discrimination analysis coupled with the simulated annealing variable selection algorithm showed that the signal profiles of olive oils hydroethanolic extracts allowed olive oils discrimination according to physicochemical quality level (classification model based on 25 signals enabling 84 ± 9% correct classifications for repeated K-fold cross-validation), and olive cultivar (classification model based on 20 signals with an average sensitivity of 94 ± 6% for repeated K-fold cross-validation), regardless of the geographical origin and olive variety or the olive quality, respectively. The results confirmed, for the first time, the potential discrimination of the electronic tongue, attributed to the observed quantitative response (sensitivities ranging from 66.6 to +57.7 mV/decade) of the E-tongue multi-sensors towards standard solutions of polar compounds (aldehydes, esters and alcohols) usually found in olive oils and that are related to their sensory positive attributes like green and fruity., This work was financially supported by Project POCI-01–0145-FEDER-006984–Associate Laboratory LSRE-LCM and by Project UID/QUI/00616/2013–CQ-VR both funded by FEDER—Fundo Europeu de Desenvolvimento Regional through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCTFundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/ BD/104038/2014)., info:eu-repo/semantics/publishedVersion

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., This work was financially supported by Project POCI-01–0145-FEDER-006984 - Associate Laboratory LSRE-LCM, Project UID/QUI/00616/2013 - CQ-VR, and UID/AGR/00690/2013 - CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI) - and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/ BD/104038/2014). Souheib Oueslati is also grateful for the support of the Tunisian Ministry of Agriculture., info:eu-repo/semantics/publishedVersion

Olive 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±2 to 25±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., This study was supported by Fundação para a Ciência e a Tecnologia (FCT),Portugal and the European Community fund FEDER, under the Program PT2020 (Project UID/EQU/50020/2013); under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC – Experimentation network and transfer for development of agricultural and agroindustrial sectors between Spain and Portugal.

The commercialization of safe foods is a main concern and should be ensured throughout the entire food supply chain. So, fast, sensitive, and reliable analytical methods are needed to identify food-related specific hazards, ensuring consumers' protection and avoiding health problems. This chapter is focused on the emerging (bio)sensors to detect the heat-stable allergen gliadin in gluten-free foods. A brief overview concerning gliadin and its relation to celiac disease is provided. Several works related to the development of biosensors for gliadin detection are presented. Moreover, the use of electronic tongues to detect gliadin or gluten is reviewed and further investigated in an attempt to explain the possible detection mechanism based on gliadin-lipid membranes interactions. The challenges, concerns, and potential application of these (bio)sensors are discussed. Finally, some future perspectives are included regarding the applicability of electronic tongue within this research field. This work was supported by Fundação para a Ciência e a Tecnologia (FCT) and the European Community fund FEDER, through Program COMPETE, under the scope of the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462); under the Strategic funding of UID/BIO/04469/2013 unit; and under the Program PT2020 (Project UID/EQU/50020/2013). info:eu-repo/semantics/publishedVersion

"Available online 4 July 2016", Monitoring olive oils oxidative stability and quality parameters (free acidity, peroxide values, K232 and K270 extinction coefficients) is needed to guarantee that, during storage, their levels remain within the legal thresholds enabling their commercialization as high-value extra-virgin olive oils. Physicochemical levels are assessed using time-consuming routine analytical reference techniques. In this work, the feasibility of a novel approach that merges an electronic tongue and chemometric tools, for monitoring extra-virgin olive oils' quality along one year of storage at dark or exposed to light is discussed. The results confirmed that physicochemical parameters varied with the storage lighting conditions and more significantly with time. Also, multiple linear regression models, using sub-sets of 2228 sensors selected with a meta-heuristic simulated annealing algorithm, allow evaluating the storage time-evolution of olive oils peroxide values, extinction coefficients and oxidative stabilities with satisfactory accuracy (R2 0.98 and 0.96, for leave-one-out and repeated K-fold cross-validation procedures, respectively). The capability of monitoring, in a single electrochemical assay, legal required quality parameters of olive oils, decreases considerable the analysis time and cost, allowing checking the compliance of extra-virgin olive oil quality with labeling. So, the use of electronic tongues for extra-virgin olive oil shelf-life assessment could be envisaged., This work was co-financed by Project POCI-01-0145-FEDER- 006984 e Associated Laboratory LSRE-LCM funded by FEDER funds through COMPETE2020 - Programa Operacional Competitividade e Internacionalizaçao (POCI), by national funds through FCT - Fundação para a Ciencia e a Tecnologia; and by the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPHQREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).

This chapter is focused on the application of electrochemical techniques (e.g., sensors and biosensors), as the predominant methodology, to the quantification of individual or total phenolic compounds, either in standard solutions or in real matrices (e.g., plants, fruits and beverages) and their capability for assessing antioxidant activity/capacity. Specially, the potential application to evaluate antioxidant capacity of bee-hives products (e.g., propolis, honey) is addressed. Finally, the voltammetric behavior of Portuguese monofloral honeys is discussed for the first time, taking into account the expected effects of honey color and floral origin. Also, a possible relation with the expected antioxidant capacity of honeys is discussed, considering their floral origin. Works describing the use of electrochemical detection imbibed on liquid chromatographic or capillary electrophoretic configurations among other analytical methods will not be focused in this review, although their undoubtedly potentials and proved applications., This work was supported by Fundação para a Ciência e a Tecnologia (FCT) and the European Community fund FEDER, under the Program PT2020 (Project UID/EQU/50020/2013) and by the strategic funding of UID/BIO/04469/2013 unit.

Natural mineral waters (still), effervescent natural mineral waters (sparkling) and aromatized waters with fruit-flavors (still or sparkling) are an emerging market. In this work, the capability of a potentiometric electronic tongue, comprised with lipid polymeric membranes, to quantitatively estimate routinely quality physicochemical parameters (pH and conductivity) as well as to qualitatively classify water samples according to the type of water was evaluated. The study showed that a linear discriminant model, based on 21 sensors selected by the simulated annealing algorithm, could correctly classify 100 % of the water samples (leave-one out cross-validation). This potential was further demonstrated by applying a repeated K-fold cross-validation (guaranteeing that at least 15 % of independent samples were only used for internal-validation) for which 96 % of correct classifications were attained. The satisfactory recognition performance of the E-tongue could be attributed to the pH, conductivity, sugars and organic acids contents of the studied waters, which turned out in significant differences of sweetness perception indexes and total acid flavor. Moreover, the E-tongue combined with multivariate linear regression models, based on sub-sets of sensors selected by the simulated annealing algorithm, could accurately estimate waters pH (25 sensors: R 2 equal to 0.99 and 0.97 for leave-one-out or repeated K-folds cross-validation) and conductivity (23 sensors: R 2 equal to 0.997 and 0.99 for leave-one-out or repeated K-folds cross-validation). So, the overall satisfactory results achieved, allow envisaging a potential future application of electronic tongue devices for bottled water analysis and classification., This study was supported by Fundação para a Ciência e Tecnologia (FCT) and the European Community fund FEDER, under the Program PT2020 (Project UID/EQU/50020/2013) and under the strategic funding of UID/BIO/04469/2013 unit.

"Available online 24 May 2016", An electrochemical aptasensor is a compact analytical device where the bioreceptor (aptamer) is coupled to a transducer surface to convert a biological interaction into a measurable signal (current) that can be easily processed, recorded and displayed. Since the discovery of the Systematic Evolution of Ligands by Enrichment (SELEX) methodology, the selection of aptamers and their application as bioreceptors has become a promising tool in the design of electrochemical aptasensors. Aptamers present several advantages that highlight their usefulness as bioreceptors such as chemical stability, cost effectiveness and ease of modification towards detection and immobilization at different transducer surfaces. In this review, a special emphasis is given to the potential use of electrochemical aptasensors for the detection of protein disease biomarkers using voltammetry techniques. Methods for the immobilization of aptamers onto electrode surfaces are discussed, as well as different electrochemical strategies that can be used for the design of aptasensors., The authors acknowledge the financial support from the Strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145- FEDER-006984 – Associate Laboratory LSRE-LCM funded by FEDER funds through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia and project ref. RECI/BBB-EBI/ 0179/2012 (project number FCOMP-01-0124-FEDER-027462) and S. Meirinhos's doctoral grant (ref SFRH/BD/65021/2009) funded by Fundação para a Ciência e a Tecnologia.

Colour and floral origin are key parameters that may influence the honey market. Monofloral light honeys are more demanded by consumers, mainly due to their flavour, being more valuable for producers due to their higher price when compared to darker honey. The latter usually have a high anti-oxidant content that increases their healthy potential. This work showed that it is possible to correctly classify monofloral honey with a high variability in floral origin with a potentiometric electronic tongue after making a preliminary selection of honey according to their colours: white, amber and dark honey. The results showed that the device had a very satisfactory sensitivity towards floral origin (Castanea sp., Echium sp., Erica sp., Lavandula sp., Prunus sp. and Rubus sp.), allowing a leave-one-out cross validation correct classification of 100%. Therefore, the E-tongue shows potential to be used at analytical laboratory level for honey samples classification according to market and quality parameters,as a practical tool for ensuring monofloral honey authenticity.

Overconsumption of sugar-sweetened beverages may increase the risk of health problems and so, the evaluation of their glycemic load and fructose-intolerance level is essential since it may allow establishing possible relations between physiologic effects of sugar-rich beverages and health. In this work, an electronic tongue was used to accurately classify beverages according to glycemic load (low, medium or high load) as well to their adequacy for people suffering from fructose malabsorption syndrome (tolerable or not): 100% of correct classifications (leave-one-out cross-validation) using linear discriminant models based on potentiomentric signals selected by a meta-heuristic simulated annealing algorithm. These results may be partially explained by the electronic tongue’s capability to mimic the human sweetness perception and total acid flavor of beverages, which can be related with glycemic load and fructose-intolerance index. Finally, the E-tongue was also applied to quantify, accurately, healthy and sensory indexes using multiple linear regression models (leave-one-out cross-validation: Radj > 0.99) in the following dynamic ranges: 4.7 < glycemic load ≤ 30; 0.4 < fructose intolerance index ≤ 1.5; 32 < sweetness perception < 155; 1.3 < total acid flavor, g L−1 < 8.3; and, 5.8 < well-balanced flavor ≤ 74. So, the proposed electronic tongue could be used as a practical, fast, low-cost and green tool for beverage’s healthy and sensory evaluation., This work was partially co-financed by FCT and FEDER under Program COMPETE (Project PEst-C/EQB/LA0020/2013); by the Strategic Project PEst-OE/EQB/LA0023/2013 and by the project ref. RECI/BBB-EBI/0179/2012 (project number FCOMP-01-0124-FEDER-027462) funded by Fundacao para a Ciencia e a Tecnologia.

In this work, the main organic acids (citric, malic and ascorbic acids) and sugars (glucose, fructose and sucrose) present in commercial fruit beverages (fruit carbonated soft-drinks, fruit nectars and fruit juices) were determined. A novel size exclusion high performance liquid chromatography isocratic green method, with ultraviolet and refractive index detectors coupled in series, was developed. This methodology enabled the simultaneous quantification of sugars and organic acids without any sample pre-treatment, even when peak interferences occurred. The method was in-house validated, showing a good linearity (R > 0.999), adequate detection and quantification limits (20 and 280 mg L−1, respectively), satisfactory instrumental and method precisions (relative standard deviations lower than 6%) and acceptable method accuracy (relative error lower than 5%). Sugars and organic acids profiles were used to calculate dose-over-threshold values, aiming to evaluate their individual sensory impact on beverage global taste perception. The results demonstrated that sucrose, fructose, ascorbic acid, citric acid and malic acid have the greater individual sensory impact in the overall taste of a specific beverage. Furthermore, although organic acids were present in lower concentrations than sugars, their taste influence was significant and, in some cases, higher than the sugars’ contribution towards the global sensory perception. FCT (Fundação para a Ciência e a Tecnologia) and FEDER (Fundo Europeu de Desenvolvimento Regional) under Program COMPETE (Programa Operacional Factores de Competitividade) (Project PEst-C/EQB/LA0020/2013); by the Strategic Project PEst-OE/EQB/LA0023/2013 and by Project Reference RECI/BBB-EBI/0179/2012 (Project Number FCOMP-01-0124-FEDER-027462)

Label authentication of monovarietal extra virgin olive oils is of great importance. A novel approach based on a potentiometric electronic tongue is proposed to classify oils obtained from single olive cultivars (Portuguese cvs. Cobrançosa, Madural, Verdeal Transmontana; Spanish cvs. Arbequina, Hojiblanca, Picual). A meta-heuristic simulated annealing algorithm was applied to select the most informative sets of sensors to establish predictive linear discriminant models. Olive oils were correctly classified according to olive cultivar (sensitivities greater than 97%) and each Spanish olive oil was satisfactorily discriminated from the Portuguese ones with the exception of cv. Arbequina (sensitivities from 61% to 98%). Also, the discriminant ability was related to the polar compounds contents of olive oils and so, indirectly, with organoleptic properties like bitterness, astringency or pungency. Therefore the proposed E-tongue can be foreseen as a useful auxiliary tool for trained sensory panels for the classification of monovarietal extra virgin olive oils., This work was co-financed by FCT and FEDER under Program COMPETE (Project PEst-C/EQB/LA0020/2013).

Chloroanisoles, namely 2,4,6-trichloroanisole, are pointed out as the primary responsible of the development of musty off-flavours in bottled wine, due to their migration from cork stoppers, which results in huge economical losses for wine industry. A prevention step is the detection of these compounds in cork planks before stoppers are produced. Mass spectrometry gas chromatography is the reference method used although it is far beyond economical possibilities of the majority of cork stoppers producers. In this work, a portable cyclic voltammetry approach was used to detect 2,4,6-trichloroanisole extracted from natural cork planks to the aqueous phase during the cork boiling industrial treatment process. Analyses were carried out under ambient conditions, in less than 15 min with a low use of solvent and without any sample pre-treatment. The proposed technique had detection (0.31±0.01 ng/L) and quantification (0.95±0.05 ng/L) limits lower than the human threshold detection level. For blank solutions, without 2,4,6-trichloroanisole addition, a concentration in the order of the quantification limit was estimated (1.0±0.2 ng/L), which confirms the satisfactory performance of the proposed methodology. For aqueous samples from the industrial cork planks boiling procedure, intra-day repeatabilities were lower than 3%, respectively. Also, 2,4,6-trichloroanisole contents in the aqueous samples determined by this novel approach were in good agreement with those obtained by GC-MS (correlation coefficient equal to 0.98), confirming the satisfactory accuracy of the proposed methodology. So, since this novel approach is a fast, low-cost, portable and user-friendly method, it can be an alternative and helpful tool for in-situ industrial applications, allowing accurate detection of releasable 2,4,6-trichloroanisole in an earlier phase of cork stoppers production, which may allow implementing more effective cork treatments to reduce or avoid future 2,4,6-trichloroanisole contaminations of wine., This work was partially supported by project PEst-C/EQB/LA0020/2011, financed by FEDER through COMPETE - Programa Operacional Factores de Competitividade and by FCT - Fundacao para a Ciencia e a Tecnologia (Portugal).

The electrochemical reduction of 2,4,6-trichloroanisole (TCA), which is a chlorinated arene with electron-donating substituents, was evaluated by cyclic voltammetry (CV). TCA is a major concern for the winery industry since it is related with cork taint, a wine defect. The results obtained in this work showed that CV could be used to detect and quantify TCA in preparative standard solutions. Linear relationships could be set between the current amplitude and TCA concentration (R > 0.999), being the detection (LOD) and quantification (LOQ) limits of 0.8 and 2.0 ppm, respectively. Although, these preliminary limits are higher than the human sensory threshold (around 5 ppt in wine), the simplicity and low-cost of the methodology confer this study a possible role in the development of more efficient, less expensive processes for TCA detection in the industry., info:eu-repo/semantics/publishedVersion

Lactic proteins are complex biomolecules, possessing different molecular weights (from 19 kDa up to 66 kDa), which can be used as biomarkers for detecting food adulterations. This study reports for the first time the evaluation of two potentiometric sensor arrays, one electronic tongue (ET) using only cross-sensitivity chemical sensors and a hybrid-ET containing ionic-selective and cross-sensitivity chemical sensors. Although both devices could detect and distinguish soluble and insoluble lactic proteins, namely bovine serum albumin and three main casein fractions (alpha-, beta- and kappa-), the inclusion of ionic-selective sensors increased the device performance (100% of correct leave-oneout cross-validation classification for hybrid-ET against 94% for the ET) and reduced the number of sensors needed (5 for the hybrid-ET instead of 9 sensors used by the ET device). Finally, the results showed that with the hybrid-ET a second-order polynomial equation could be derived relating the measured potential of the aqueous solution and the logarithmic of the total casein concentration, with satisfactory determination coefficients (R 2 >0.99).

Enzymatic synthesis of fructose fatty acide sterwasper formed inorganic solventmedia, using apurified lipase from Candida antartica B immobilizedinacrylicresin. Response sur face methodology with a central composit erotatable design based on five levels was implemented to optimize three experimental operating conditions (temperature, agitation and reaction time). A statistical significant cubic model was established. Temperature andre action time were found to bethe most significant parameters. The optimum operational conditions for maximizing the synthesis of fructos e esters were 57.18C, 100rpm and 37.8h. The model was validated in the identified optimal condition stocheck its adequacy and accuracy, and an experimental esterification percentage of 88.4% ( 0.3%) was obtained. These results showed that animprovement of the enzymatic synthesis of fructose esters was obtained under the optimized conditions, The authors acknowledge the AlBan Programme (European Union Programme of High Level Scholarships for Latin America) for financial support of N. Lopes through the research grant E07D401544BR. Also, the authors acknowledge the Department of Chemistry from University of Minho (Portugal) for running the infrared spectroscopy analysis.

An all-solid-state potentiometric electronic tongue with 36 polymeric membranes has been used for the first time to detect gliadins, which are primarily responsible for gluten intolerance in people suffering from celiac disease. A linear discriminant model, based on the signals of 11 polymeric membranes, selected from the 36 above using a stepwise procedure, was used to semi-quantitatively classify samples of a “Gluten-free” foodstuff (baby milked flour), previously contaminated with known amounts of gliadins (50 mg/kg), as “Gluten-free”, “Low-Gluten content” or “Gluten-containing”. For this food matrix, the device had sensitivity towards gliadins of 1–2 mg/kg and overall sensitivity and specificity of 77% and 78%, respectively. Moreover, the device never identified an ethanolic extract containing gliadins as “Gluten-free”. Finally, the system also allowed distinguishing “Gluten-free” and “Gluten-containing” foodstuffs (15 foods, including breads, flours, baby milked flours, cookies and breakfast cereals) with an overall sensitivity and specificity greater than 83%, using the signals of only 4 selected polymeric membranes (selected using a stepwise procedure). Since only one “Gluten-containing” foodstuff was misclassified as “Gluten-free”, the device could be used as a preliminary tool for quality control of foods for celiac patients., Financial support received from FCT, Lisbon, under the research project PPCDT/QUI/58076/2004, is gratefully acknowledged.

Olive mill wastewaters (OMW) are a potential source of biophenols, but they have a complex composition with many unknown phenolics. The analysis of purified methanol extracts from two Portuguese OMW by electrospray mass spectrometry in the negative mode showed [M-H]- ions at m/z 539 and m/z 523, corresponding respectively to oleuropein and ligstroside isomers which contain the glucose unit linked to its aromatic moiety. Also, the fragmentation pathway of the [M-H]- ions at m/z 863, 685 and 847 indicated the presence of a diglucoside derivative of the oleuropein isomer and of mono- and diglucosides of the ligstroside isomer, respectively. Moreover, the two OMW samples contained an elenoic derivative of the ion at m/z 685 and a degradation product (m/z 453) of the [M-H]- ion at m/z 523. Future studies focusing on the abundance of these compounds on OMW, as well as their bioactivities, will determine their possible industrial exploitation. This work was supported by Fundaçao para Ciência e Tecnologia (FCT), project Biotechnological valorization of olive mill wastewaters (OMWalor) - PTDC/AMB/69379/ 2006