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A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers
In the present study a single screen-printed carbon electrode (SPCE) and chemometric techniques were utilized for forensic differentiation of Brazilian American lager beers. To differentiate Brazilian beers at the manufacturer and brand level, the classification techniques: soft independent modeling...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980006/ https://www.ncbi.nlm.nih.gov/pubmed/35379877 http://dx.doi.org/10.1038/s41598-022-09632-9 |
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author | Mutz, Yhan S. do Rosario, Denes Silva, Luiz R. G. Galvan, Diego Janegitz, Bruno C. de Q. Ferreira, Rafael Conte-Junior, Carlos A. |
author_facet | Mutz, Yhan S. do Rosario, Denes Silva, Luiz R. G. Galvan, Diego Janegitz, Bruno C. de Q. Ferreira, Rafael Conte-Junior, Carlos A. |
author_sort | Mutz, Yhan S. |
collection | PubMed |
description | In the present study a single screen-printed carbon electrode (SPCE) and chemometric techniques were utilized for forensic differentiation of Brazilian American lager beers. To differentiate Brazilian beers at the manufacturer and brand level, the classification techniques: soft independent modeling of class analogy (SIMCA), partial least squares regression discriminant analysis (PLS-DA), and support vector machines discriminant analysis (SVM-DA) were tested. PLS-DA model presented an inconclusive assignment ratio of 20%. On the other hand, SIMCA models had a 0 inconclusive rate but an sensitivity close to 85%. While the non-linear technique (SVM-DA) showed an accuracy of 98%, with 95% sensitivity and 98% specificity. The SPCE-SVM-DA technique was then used to distinguish at brand level two highly frauded beers. The SPCE coupled with SVM-DA performed with an accuracy of 97% for the classification of both brands. Therefore, the proposed electrochemicalsensor configuration has been deemed an appropriate tool for discrimination of American lager beers according to their producer and brands. |
format | Online Article Text |
id | pubmed-8980006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89800062022-04-06 A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers Mutz, Yhan S. do Rosario, Denes Silva, Luiz R. G. Galvan, Diego Janegitz, Bruno C. de Q. Ferreira, Rafael Conte-Junior, Carlos A. Sci Rep Article In the present study a single screen-printed carbon electrode (SPCE) and chemometric techniques were utilized for forensic differentiation of Brazilian American lager beers. To differentiate Brazilian beers at the manufacturer and brand level, the classification techniques: soft independent modeling of class analogy (SIMCA), partial least squares regression discriminant analysis (PLS-DA), and support vector machines discriminant analysis (SVM-DA) were tested. PLS-DA model presented an inconclusive assignment ratio of 20%. On the other hand, SIMCA models had a 0 inconclusive rate but an sensitivity close to 85%. While the non-linear technique (SVM-DA) showed an accuracy of 98%, with 95% sensitivity and 98% specificity. The SPCE-SVM-DA technique was then used to distinguish at brand level two highly frauded beers. The SPCE coupled with SVM-DA performed with an accuracy of 97% for the classification of both brands. Therefore, the proposed electrochemicalsensor configuration has been deemed an appropriate tool for discrimination of American lager beers according to their producer and brands. Nature Publishing Group UK 2022-04-04 /pmc/articles/PMC8980006/ /pubmed/35379877 http://dx.doi.org/10.1038/s41598-022-09632-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Mutz, Yhan S. do Rosario, Denes Silva, Luiz R. G. Galvan, Diego Janegitz, Bruno C. de Q. Ferreira, Rafael Conte-Junior, Carlos A. A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers |
title | A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers |
title_full | A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers |
title_fullStr | A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers |
title_full_unstemmed | A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers |
title_short | A single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of Brazilian beers |
title_sort | single screen-printed electrode in tandem with chemometric tools for the forensic differentiation of brazilian beers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980006/ https://www.ncbi.nlm.nih.gov/pubmed/35379877 http://dx.doi.org/10.1038/s41598-022-09632-9 |
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