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metadata.artigo.dc.title: Temporal dominance of sensations of chocolate bars with different cocoa contents: a multivariate approach to assess TDS profiles
metadata.artigo.dc.creator: Rodrigues, Jéssica Ferreira
Condino, João Paulo Ferreira
Pinheiro, Ana Carla Marques
Nunes, Cleiton Antônio
metadata.artigo.dc.subject: Sensory analysis
Pattern recognition
Parallel factor analysis
Principal component analysis
metadata.artigo.dc.publisher: Elsevier Jan-2016
metadata.artigo.dc.identifier.citation: RODRIGUES, J. F. et al. Temporal dominance of sensations of chocolate bars with different cocoa contents: a multivariate approach to assess TDS profiles. Food Quality and Preference, v. 47, part A, p. 91-96, Jan. 2016.
metadata.artigo.dc.description.abstract: Temporal dominance of sensations (TDS) method is used to investigate the perception of sensory attributes over time after ingesting a food. In this study, we used multivariate approaches for TDS data assessment based on Parallel Factor Analysis (PARAFAC) and Principal Component Analysis. Tests were performed in triplicate with 10 selected panelists who were acquainted with chocolate attributes. Six samples of chocolate containing different cocoa contents (28%, 34%, 41%, 55%, 70%, and 85%) were evaluated for 40 s. PARAFAC was able to compare the entire TDS curves of the products, which allowed discrimination among the chocolates on the basis of TDS profile pattern recognition. In addition, PARAFAC enabled identification of attributes that contributed the most toward product discrimination and assessment of the influence of time. PCA enabled the discrimination of the chocolates on the basis of parameters that summarize TDS curves and the assessment of the influence of the quantitative curve parameters on the discrimination of the samples. The approaches present as complementary tools to assist TDS interpretations and can be used in conjunction with other statistical methods.
metadata.artigo.dc.language: en_US
Appears in Collections:DCA - Artigos publicados em periódicos

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