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a b s t r a c tAn electronic tongue with 36 cross-sensibility sensors was built allowing a successful recognition of the five basic taste standards, showing high sensibility to acid, salty and umami taste substances and lower performance to bitter and sweet tastes. The taste recognition capability was afterwards tested in the detection of goat milk adulteration with bovine milk, which is a problem for the dairy industry. This new methodology is an alternative to the classical analytical methods used to detect caprine milk adulterations with bovine milk, being a simpler, faster and economical procedure. The different signal profiles recorded by the e-tongue device together with linear discriminant analysis allowed the implementation of a model that could distinguish between raw skim milk groups (goat, cow and goat/cow) with an overall sensibility and specificity of 97% and 93%, respectively. Furthermore, cross-validation showed that the model was able to correct classify unknown milk samples with a sensibility and specificity of 87% and 70%, respectively. Additionally, the model robustness was confirmed since it correctly or incorrectly classified milk samples with, respectively, higher and lower probabilities than those that could be expected by chance.

a b s t r a c tLabel 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 paper presents a new semi-quantitative metric, Green Star (GS), for evaluation of the global greenness of chemical reactions used in teaching laboratories. Its purpose is to help choose the more acceptable reactions for implementing Green Chemistry (GC) and to identify suitable modifications of protocols to improve the greenness of the chemistry practiced by students. GS considers globally, in principle, all the Twelve Principles of GC. The metric consists in the evaluation of the greenness of the reaction for each principle by pre-defined criteria, followed by graphical representation of the results in an Excel radar chart Á the fuller the chart, the higher degree of greenness. To illustrate the construction and the scope of the metric, a case study is presented Á the iron(II) oxalate dihydrate synthesis performed under several sets of conditions to pursue the implementation of greenness.

Abstract. An electronic tongue system was developed based on 20 all-solid-state potentiometric sensors and chemometric data processing, with polymeric membranes applied on solid conducting silver-epoxy supports and a Ag=AgCl reference electrode. The sensor array was applied to 52 commercial honey samples obtained randomly from different regions of Portugal. These samples were analysed independently for their pollen profiles by biological techniques and the data collected with the tongue were evaluated for discrimination of the samples with multivariate statistical methods (principal component analysis and linear discriminant analysis), to investigate whether the device may provide an analytical alternative for classification of honey samples with respect to pollen type, a task which is time consuming and requires skilled labour when performed by biological techniques. It was found that the tongue has a reasonable efficiency for classification of honey samples of the most common three types (with Erica, Echium and Lavandula as predominant pollens). With linear discriminant analysis, the honey samples yielded about 84% classification accuracy and 72% for crossed validation. In this study, the honey samples correctly classified for the different types of the dominant pollen were: 53% for Lavandula, 83% for Erica and 78% for Echium pollen.Keywords: Honey; pollen; electronic tongue; multivariate analysis Multi-sensor arrays that provide global information on complex samples have deserved much interest recently. Instead of measuring specific parameters, these devices acquire global information which, after treatment by appropriate chemometric methods, can be used for multicomponent classification analysis, taste evaluation, etc. Electrochemical sensor arrays or electronic tongues built with non-specific, low-selectivity, chemical sensors with high stability and cross sensitivity to different species in solution, are suitable for analysing complex liquid samples [1]. Electronic tongues or taste sensors based on different electrochemical principles, such as potentiometry [2][3][4][5][6] or voltammetry [7,8], have been described. Several array types have been tested for potentiometric devices, namely chalcogenide glass sensors [3][4][5], lipid=poly-meric membranes [2,6] and ion selective membranes [9]. The signal profiles generated by such devices vary with the characteristics of different samples and upon data treatment with multivariate statistical methods for pattern recognition (identification, classification

A procedure for teaching green chemistry through laboratory experiments is presented in which students are challenged to use the 12 principles of green chemistry to review and modify synthesis protocols to improve greenness. A global metric, green star, is used in parallel with green chemistry mass metrics to evaluate the improvement in greenness. The methodology is exemplified with the search for the greenest metal−acetylacetonate synthesis experiment commonly included in the teaching laboratory literature. Green star responds holistically to a large number of features that have to be considered when the greenness of a process is under discussion because it involves an assessment of all the relevant twelve principles of green chemistry in a systemic way. The advocated procedure allows students to become familiar with both the 12 principles and green chemistry mass metrics and to gain experience in changing synthetic chemistry to improve its greenness.

a b s t r a c tColour and floral origin are key parameters that may influence the honey market. Monofloral light honey 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 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.

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