Multivariate statistical analysis and odor taste network to reveal odor taste associations
Fecha
2020Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Impacto
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10.1021/acs.jafc.9b05462
Resumen
Odor−taste association has been successfully applied to enhance taste perception in foods with low sugar or lowsalt content. Nevertheless, selecting odor descriptors with a given associated taste remains a challenge. In the aim to look forodors able to enhance some specific taste, we tested different multivariate analyses tofind links between taste descriptors andodor descriptors, starting from a ...
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Odor−taste association has been successfully applied to enhance taste perception in foods with low sugar or lowsalt content. Nevertheless, selecting odor descriptors with a given associated taste remains a challenge. In the aim to look forodors able to enhance some specific taste, we tested different multivariate analyses tofind links between taste descriptors andodor descriptors, starting from a set of data previously obtained using gas chromatography/olfactometry-associated taste: 68odorant zones described with 41 odor descriptors and 4 taste-associated descriptors (sweetness, saltiness, bitterness, andsourness). A partial least square analysis allowed for identification of odors associated with a specific taste. For instance, odorsdescribed as either fruity, sweet, strawberry, candy,floral, or orange are associated with sweetness, while odors described aseither toasted, potato, sulfur, or mushroom are associated with saltiness. A network representation allowed for visualization ofthe links between odor and taste descriptors. As an example, a positive association was found between butter odor and bothsaltiness and sweetness. Our approach provided a visualization tool of the links between odor and taste description and could beused to select odor-active molecules with a potential taste enhancement effect based on their odor descriptors. [--]
Materias
Odor-taste association,
Odor descriptors,
Multivariate analysis,
Sweetness,
Saltiness,
Bitterness,
Sourness,
Partial least square analysis,
Multidimensional scaling
Editor
ACS
Publicado en
Journal of Agricultural and Food Chemistry 2020, 68, 10318-10328
Departamento
Universidad Pública de Navarra. Departamento de Agronomía, Biotecnología y Alimentación /
Nafarroako Unibertsitate Publikoa. Agronomia, Bioteknologia eta Elikadura Saila
Versión del editor
Entidades Financiadoras
Carmen Barba received support from the European Union (EU)in the framework of the Marie Sklodowska-Curie H2020-MSCA-IF-2014-655545.