Skip to main navigation Skip to search Skip to main content

Llengües (bio)electròniques aplicades a l'anàlisi i caracterització de begudes

Student thesis: Doctoral thesis

Abstract

Over the last years, there has been an increasing demand of new analytical methods_x000D_ with the high sensitivity and selectivity, and fast response needed to meet new_x000D_ challenges in environmental monitoring, food safety and public health. In this fashion,_x000D_ industry is increasingly focused on fast-response and low-cost methods, as those based_x000D_ on chemical sensors, that may be used for screening or detecting any adulteration or_x000D_ contamination of the products, either during or after its production, or to assess they_x000D_ guarantee quality control standards._x000D_ In this sense, classical research lines in the field of chemical sensors have focused_x000D_ on the development of ever more selective devices towards a particular species, and_x000D_ sensitive to lower concentrations at the same time. Unfortunately, there are few_x000D_ optimally operating chemical sensors that function without any interference or matrix_x000D_ effect in the required conditions when dealing with real samples analysis. Precisely, the_x000D_ difficulty to obtain sensors with appropriate selectivity and sensitivity for a given_x000D_ analyte has led to the appearance of new strategies such as electronic tongues in order to_x000D_ tackle these problems._x000D_ These analytical systems are inspired by the sensory ability of taste in mammals,_x000D_ where a few receptors can respond to a large variety of substances. This principle is_x000D_ coupled with complex data treatment analogous to the applied in the brain, which_x000D_ allows to quantify or to classify a large amount of substances. These biomimetic_x000D_ systems, opposed to conventional approaches, are directed towards the combination of_x000D_ low selectivity sensors array response (or cross response features) in order to obtain_x000D_ some added value in the generation of analytical information._x000D_ One of the recent advances in the design of electronic tongues has been the_x000D_ incorporation of biosensors, in order to tackle new application fields or to improve_x000D_ existing ones. These bioelectronic tongues, as they have been named, are only_x000D_ distinguished from conventional ones in the incorporation of one or several biosensors_x000D_ into the sensor array, normally sharing the same transduction principle to facilitate_x000D_ compatibility._x000D_ In this context, the work presented herein aims to demonstrate the applicability of_x000D_ these systems towards the analysis and characterization of beverages, specifically_x000D_ towards wine and alcoholic beverages, either for the extraction of qualitative_x000D_ information and its classification or the quantification of analytical parameters of interest, responding in both cases to the needs of each sector. Concretely, its application_x000D_ towards cava wine, brandy, beer and wine has been studied; the most important sectors_x000D_ in terms of alcoholic beverages in our country._x000D_ Additionally, given the importance that phenolic compounds have achieved in the_x000D_ recent years due to its antioxidant activity, with huge health benefits, the quantification_x000D_ of these compounds has been addressed from both points of view: its global content and_x000D_ the individual discrimination; tackling it using either a classical electronic tongue and a_x000D_ bioelectronic tongue, comparing the benefits of the incorporation of biosensors in the_x000D_ e-tongue array._x000D_ Lastly, given the difficulties derived in the treatment of the data generated with such_x000D_ systems, specially in the case of voltammetric sensors, much attention has been paid to_x000D_ the development and application of novel processing strategies in order to reduce its_x000D_ complexity and improve the obtained results; besides comparing the different proposed_x000D_ strategies between each other.
Date of Award15 Mar 2013
Original languageUndefined/Unknown
SupervisorFrancisco Cespedes Mulero (Director) & Manel del Valle (Director)

Cite this

'