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Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants
Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants
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Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants
Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants

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Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants
Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants
Journal Article

Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants

2020
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Overview
The perception of aroma mixtures is based on interactions beginning at the peripheral olfactory system, but the process remains poorly understood. The perception of a mixture of ethyl isobutyrate (Et-iB, strawberry-like odor) and ethyl maltol (Et-M, caramel-like odor) was investigated previously in both human and animal studies. In those studies, the binary mixture of Et-iB and Et-M was found to be configurally processed. In humans, the mixture was judged as more typical of a pineapple odor, similar to allyl hexanoate (Al-H, pineapple-like odor), than the odors of the individual components. To explore the key features of this aroma blend, we developed an in silico approach based on molecules having at least one of the odors—strawberry, caramel or pineapple. A dataset of 293 molecules and their related odors was built. We applied the notion of a “social network” to describe the network of the odors. Additionally, we explored the structural properties of the molecules in this dataset. The network of the odors revealed peculiar links between odors, while the structural study emphasized key characteristics of the molecules. The association between “strawberry” and “caramel” notes, as well as the structural diversity of the “strawberry” molecules, were notable. Such elements would be key to identifying potential odors/odorants to form aroma blends.