Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/41657

TitleElectronic tongue: a versatile tool for mineral and fruit-flavored waters recognition
Author(s)Dias, Luís G.
Alberto, Zelda
Veloso, Ana C. A.
Peres, António M.
KeywordsNatural mineral waters
Fruit-flavored waters
Water quality parameters
Electronic tongue
Discriminant analysis
Multiple linear regression models
Issue dateJun-2016
PublisherSpringer Verlag
JournalJournal of Food Measurement and Characterization
CitationDias, Luís G.; Alberto, Zelda; Veloso, Ana C. A.; Peres, António M., Electronic tongue: a versatile tool for mineral and fruit-flavored waters recognition. Journal of Food Measurement and Characterization, 10(2), 264-273, 2016
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/41657
DOI10.1007/s11694-015-9303-y
ISSN2193-4126
e-ISSN2193-4134
Publisher versionhttp://www.springer.com/food+science/journal/11694
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

Files in This Item:
File Description SizeFormat 
document_29685_1.pdf618,64 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID