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Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data
The international seafood trade is based on food safety, quality, sustainability, and traceability. Mussels are bio-accumulative sessile organisms that need regular control to guarantee their safe consumption. However, no well-established and validated methods exist to trace mussel origin, even if s...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125296/ https://www.ncbi.nlm.nih.gov/pubmed/33946469 http://dx.doi.org/10.3390/molecules26092634 |
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author | Forleo, Tiziana Zappi, Alessandro Melucci, Dora Ciriaci, Martina Griffoni, Francesco Bacchiocchi, Simone Siracusa, Melania Tavoloni, Tamara Piersanti, Arianna |
author_facet | Forleo, Tiziana Zappi, Alessandro Melucci, Dora Ciriaci, Martina Griffoni, Francesco Bacchiocchi, Simone Siracusa, Melania Tavoloni, Tamara Piersanti, Arianna |
author_sort | Forleo, Tiziana |
collection | PubMed |
description | The international seafood trade is based on food safety, quality, sustainability, and traceability. Mussels are bio-accumulative sessile organisms that need regular control to guarantee their safe consumption. However, no well-established and validated methods exist to trace mussel origin, even if several attempts have been made over the years. Recently, an inorganic multi-elemental fingerprint coupled to multivariate statistics has increasingly been applied in food quality control. The mussel shell can be an excellent reservoir of foreign inorganic chemical species, allowing recording long-term environmental changes. The present work investigates the multi-elemental composition of mussel shells, including Al, Cu, Cr, Zn, Mn, Cd, Co, U, Ba, Ni, Pb, Mg, Sr, and Ca, determined by inductively-coupled plasma mass-spectrometry in Mytilus galloprovincialis collected along the Central Adriatic Coast (Marche Region, Italy) at 25 different sampling sites (18 farms and 7 natural banks) located in seven areas. The experimental data, coupled with chemometric approaches (principal components analysis and linear discriminant analysis), were used to create a statistical model able to discriminate samples as a function of their production site. The LDA model is suitable for achieving a correct assignment of >90% of individuals sampled to their respective harvesting locations and for being applied to counteract fraud. |
format | Online Article Text |
id | pubmed-8125296 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81252962021-05-17 Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data Forleo, Tiziana Zappi, Alessandro Melucci, Dora Ciriaci, Martina Griffoni, Francesco Bacchiocchi, Simone Siracusa, Melania Tavoloni, Tamara Piersanti, Arianna Molecules Article The international seafood trade is based on food safety, quality, sustainability, and traceability. Mussels are bio-accumulative sessile organisms that need regular control to guarantee their safe consumption. However, no well-established and validated methods exist to trace mussel origin, even if several attempts have been made over the years. Recently, an inorganic multi-elemental fingerprint coupled to multivariate statistics has increasingly been applied in food quality control. The mussel shell can be an excellent reservoir of foreign inorganic chemical species, allowing recording long-term environmental changes. The present work investigates the multi-elemental composition of mussel shells, including Al, Cu, Cr, Zn, Mn, Cd, Co, U, Ba, Ni, Pb, Mg, Sr, and Ca, determined by inductively-coupled plasma mass-spectrometry in Mytilus galloprovincialis collected along the Central Adriatic Coast (Marche Region, Italy) at 25 different sampling sites (18 farms and 7 natural banks) located in seven areas. The experimental data, coupled with chemometric approaches (principal components analysis and linear discriminant analysis), were used to create a statistical model able to discriminate samples as a function of their production site. The LDA model is suitable for achieving a correct assignment of >90% of individuals sampled to their respective harvesting locations and for being applied to counteract fraud. MDPI 2021-04-30 /pmc/articles/PMC8125296/ /pubmed/33946469 http://dx.doi.org/10.3390/molecules26092634 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Forleo, Tiziana Zappi, Alessandro Melucci, Dora Ciriaci, Martina Griffoni, Francesco Bacchiocchi, Simone Siracusa, Melania Tavoloni, Tamara Piersanti, Arianna Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data |
title | Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data |
title_full | Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data |
title_fullStr | Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data |
title_full_unstemmed | Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data |
title_short | Inorganic Elements in Mytilus galloprovincialis Shells: Geographic Traceability by Multivariate Analysis of ICP-MS Data |
title_sort | inorganic elements in mytilus galloprovincialis shells: geographic traceability by multivariate analysis of icp-ms data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125296/ https://www.ncbi.nlm.nih.gov/pubmed/33946469 http://dx.doi.org/10.3390/molecules26092634 |
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