Descriptor Fingerprints and Their Application to Red Wine Clustering and Discrimination

I.P. Bangov; M. Moskovkina; B.P. Stojanov

doi:10.1515/asn-2017-0005

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Descriptor Fingerprints and Their Application to Red Wine Clustering and Discrimination

Acta Scientifica Naturalis

Volume 4 (2017): Issue 1 (March 2017)

By: I.P. Bangov, M. Moskovkina and B.P. Stojanov

Open Access

|Feb 2017

Abstract

The investigation was performed to test the potentials of the fingerprint clustering algorithm for a set of 1599 red wines in relation to some wine properties, comprised in the notion “wine quality”. We have obtained a distribution of the wines into different clusters as a result. Each cluster was composed of wine-objects with similar values of laboratory parameters and with a wine quality certificate. A correlation between the. quality of wines (a sensory taste factor) and the phisicochemical descriptors (laboratory analytical test results data) was observed and analyzed.

References

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Articles in this issue

DOI: https://doi.org/10.1515/asn-2017-0005 | Journal eISSN: 2603-347X | Journal ISSN: 2367-5144

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Language: English

Page range: 29 - 33

Submitted on: Oct 30, 2016

Accepted on: Jan 11, 2017

Published on: Feb 9, 2017

Published by: Konstantin Preslavski University of Shumen

In partnership with: Paradigm Publishing Services

Publication frequency: 3 issues per year

Keywords:

similarity search,

descriptor fingerprints,

Related subjects:

Life sciences, other,

Physics,

Physics, other

© 2017 I.P. Bangov, M. Moskovkina, B.P. Stojanov, published by Konstantin Preslavski University of Shumen
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 4 (2017): Issue 1 (March 2017)