Barba González-Albo, Carmen

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https://academica-e.unavarra.es/handle/2454/48660

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Barba González-Albo

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Carmen

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Agronomía, Biotecnología y Alimentación

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IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain

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0000-0001-6084-9725

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88784

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810384

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Subject: Bitterness ×

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    PublicationOpen Access
    Multivariate statistical analysis and odor taste network to reveal odor taste associations
    (American Chemical Society, 2020) Guichard, Elisabeth; Barba González-Albo, Carmen; Thomas-Gaudin, Thierry; Tromelin, Anne; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura
    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.