Multivariate statistical analysis and odor taste network to reveal odor taste associations

Date

2020

Authors

Guichard, Elisabeth
Thomas-Gaudin, Thierry
Tromelin, Anne

Director

Publisher

American Chemical Society
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión aceptada / Onetsi den bertsioa

Project identifier

  • European Commission/Horizon 2020 Framework Programme/655545/ openaire
Impacto
No disponible en Scopus

Abstract

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.

Description

Keywords

Odor-taste association, Odor descriptors, Multivariate analysis, Sweetness, Saltiness, Bitterness, Sourness, Partial least square analysis, Multidimensional scaling

Department

Agronomía, Biotecnología y Alimentación / Agronomia, Bioteknologia eta Elikadura

Faculty/School

Degree

Doctorate program

item.page.cita

Guichard, E., Barba, C., Thomas-Danguin, T., & Tromelin, A. (2020). Multivariate statistical analysis and odor–taste network to reveal odor–taste associations. Journal of Agricultural and Food Chemistry, 68(38), 10318-10328. https://doi.org/10.1021/acs.jafc.9b05462

item.page.rights

© 2019 American Chemical Society.

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