Olfactory signature and odorant mixture having the same

Patent metadata

Field	Value
Publication number	US-11062794-B2
Application number	US-201815965930-A
Country	US
Kind code	B2
Filing date	Apr 29, 2018
Priority date	Sep 7, 2011
Publication date	Jul 13, 2021
Grant date	Jul 13, 2021

Abstract

An odorant mixture is disclosed. The odorant mixture comprises N odorant components wherein N equals at least 20. Each odorant component is characterized by a multidimensional vector of attributes. A z score of an average of characteristic distances between vectors corresponding to odorant components in the mixture and vectors corresponding to odorant components in a group of M odorant components but not in the mixture is less than 2.

First claim

What is claimed is:

1. A method of producing an odorant mixture to mask odors, the method comprising:
for each odorant component from a first group of M odorant components, obtaining, by a data processor, a multidimensional vector of attributes characterizing the given odorant component, thereby providing an olfactory space of M multidimensional vectors corresponding to the M odorant components;
selecting, by the data processor, a second group of N odorant components among the M odorant components of the first group, wherein a z-score indicative of a uniformity of distribution of the N odorant components from the second group over the olfactory space is less than 2, and wherein the z-score is calculated as an average of characteristic distances between vectors corresponding to odorant components in the second group and vectors corresponding to odorant components in the first group but not belonging to the second group;
and
mixing said N odorant components to form the odorant mixture.

2. The method according to claim 1 , wherein each characteristic distance is defined as a minimum distance between a vector corresponding to odorant components in the second group and a vector corresponding to an odorant component in the first group but not belonging to the second group.

3. The method according to claim 1 , wherein each of said multidimensional vectors has at least 50 dimensions.

4. The method according to claim 1 , wherein each of said multidimensional vectors has at least 100 dimensions.

5. The method according to claim 1 , wherein each of said multidimensional vectors has at least 1000 dimensions.

6. The method according to claim 1 , wherein N equals at least 30.

7. The method according to claim 1 , wherein N equals at least 40.

8. The method according to claim 1 , wherein N equals at least 50.

9. The method according to claim 1 , wherein M equals at least 100.

10. The method according to claim 1 , wherein M equals at least 1000.

11. The method according to claim 1 , wherein the first group of M odorant components is selected from the odorant components listed in Table A.1 or Table A.2 of Annex 1.

12. The method according to claim 1 , wherein the z-score is calculated with respect to a synthetic database which comprises a plurality of entries, each corresponding to a database odorant mixture defined as being producible from a plurality of odorant components selected from the first group of M odorant components.

13. The method according to claim 12 , further comprising generating said synthetic database.

14. The method according to claim 1 , wherein N equals at least 20.

Assignees

• Yeda Res & Dev

Inventors

• Sobel Noam
• Weiss Tali
• Snitz Kobi
• Yablonka-Barak Adi
• Schneidman Elad
• Khan Rehan Mahmood

Classifications

• G01N33/0001 Primary

  by organoleptic means · CPC title

• G16C20/30

  Prediction of properties of chemical compounds, compositions or mixtures · CPC title

• G16C20/90 Primary

  Programming languages; Computing architectures; Database systems; Data warehousing · CPC title

• G01N33/0004

  Gaseous mixtures, e.g. polluted air · CPC title

• C11B9/02

  Recovery or refining of essential oils from raw materials · CPC title