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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...

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Detalles Bibliográficos
Autores principales: Otim, Eric Oloya, Chen, I Ru, Otim, Ochan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
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.
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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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