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Single-cultivar extra virgin olive oil classification using a potentiometric electronic tongue

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Detalhes bibliográficos
Resumo: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.
Autores principais:Dias, L.G.
Outros Autores:Fernandes, Andreia; Veloso, Ana C.A.; Machado, Adélio A.M.; Pereira, J.A.; Peres, António M.
Assunto:Extra virgin olive oil Single olive cultivar Potentiometric electronic tongue Linear discriminant analysis Simulated annealing algorithm
Ano:2014
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo: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.