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Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents
Quality control during spirits production and means of authenticating or verifying sources of spirits in the sub-Saharan region of Africa are limited due to lack of resources and the scientific acumen required to develop methodologies for characterizing spirits. However, the increasing needs to prot...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454205/ https://www.ncbi.nlm.nih.gov/pubmed/31008383 http://dx.doi.org/10.1016/j.heliyon.2019.e01417 |
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author | Otim, Eric Oloya Chen, I Ru Otim, Ochan |
author_facet | Otim, Eric Oloya Chen, I Ru Otim, Ochan |
author_sort | Otim, Eric Oloya |
collection | PubMed |
description | Quality control during spirits production and means of authenticating or verifying sources of spirits in the sub-Saharan region of Africa are limited due to lack of resources and the scientific acumen required to develop methodologies for characterizing spirits. However, the increasing needs to protect consumers from negligence, or willful contamination of spirits in this region underscores the urgency with which growth in this area must happen. In this paper, we describe a multivariate statistical framework upon which characterization, identification and authentication of spirits could be developed. The framework exploits the unique chemical fingerprints of spirits with the goal of accomplishing three functions simultaneously: the detection of class differences, the authentication of spirits and the verification of sources. In a test case using the metal contents of 17 Ugandan spirits, this framework shows (i) that a class of unrecorded spirits known locally as Lira-Lira can be singled out from other spirits by their Cu contents, (ii) that localities from where the Lira-Lira spirits were purchased can be resolved to within 8 km by cluster analysis and principal component analysis, (iii) that cluster analysis loadings and scores, placed side-by-side, can pair spirits and their unique discriminating contaminants directly, (iv) that the most important metals for authenticating 13 spirits, source verification and production methods are Al, Sr, Ba, Mn, Zn and Cu (high concentration variability across samples is the qualifying factor), (v) that common sources of contamination can be detected by Pearson correlation analysis (this study finds that Sn/Cd, Pb/Cr, Tl/Cr, Pb/Ni or Cu/Ag as well as the triad Se/As/Ni in the 13 Ugandan spirits are from similar sources), and (vi) that inconsistency in spirits production can be detected with empirical data. Such rudimentary solutions to characterizing spirits have never been offered to the sub-Saharan countries. |
format | Online Article Text |
id | pubmed-6454205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-64542052019-04-19 Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents Otim, Eric Oloya Chen, I Ru Otim, Ochan Heliyon Article Quality control during spirits production and means of authenticating or verifying sources of spirits in the sub-Saharan region of Africa are limited due to lack of resources and the scientific acumen required to develop methodologies for characterizing spirits. However, the increasing needs to protect consumers from negligence, or willful contamination of spirits in this region underscores the urgency with which growth in this area must happen. In this paper, we describe a multivariate statistical framework upon which characterization, identification and authentication of spirits could be developed. The framework exploits the unique chemical fingerprints of spirits with the goal of accomplishing three functions simultaneously: the detection of class differences, the authentication of spirits and the verification of sources. In a test case using the metal contents of 17 Ugandan spirits, this framework shows (i) that a class of unrecorded spirits known locally as Lira-Lira can be singled out from other spirits by their Cu contents, (ii) that localities from where the Lira-Lira spirits were purchased can be resolved to within 8 km by cluster analysis and principal component analysis, (iii) that cluster analysis loadings and scores, placed side-by-side, can pair spirits and their unique discriminating contaminants directly, (iv) that the most important metals for authenticating 13 spirits, source verification and production methods are Al, Sr, Ba, Mn, Zn and Cu (high concentration variability across samples is the qualifying factor), (v) that common sources of contamination can be detected by Pearson correlation analysis (this study finds that Sn/Cd, Pb/Cr, Tl/Cr, Pb/Ni or Cu/Ag as well as the triad Se/As/Ni in the 13 Ugandan spirits are from similar sources), and (vi) that inconsistency in spirits production can be detected with empirical data. Such rudimentary solutions to characterizing spirits have never been offered to the sub-Saharan countries. Elsevier 2019-04-06 /pmc/articles/PMC6454205/ /pubmed/31008383 http://dx.doi.org/10.1016/j.heliyon.2019.e01417 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Otim, Eric Oloya Chen, I Ru Otim, Ochan Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents |
title | Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents |
title_full | Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents |
title_fullStr | Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents |
title_full_unstemmed | Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents |
title_short | Applying multivariate analysis to characterize waragi spirits from Acoli, Uganda, by their metal contents |
title_sort | applying multivariate analysis to characterize waragi spirits from acoli, uganda, by their metal contents |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454205/ https://www.ncbi.nlm.nih.gov/pubmed/31008383 http://dx.doi.org/10.1016/j.heliyon.2019.e01417 |
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