Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors.
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/23819 https://doi.org/10.1016/j.foodchem.2018.07.087 |
Resumo: | Wines from different grape varieties, geographical zones, soil types, foliar N application, SO2 addition and oak ageing were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). For this purpose, ICP-MS methodology was optimized. The elements which allowed differentiate wines from studied grape varieties were Sr, Ca, Mg and Mn. Geographical zones were classified according to Sr, Ba, Ni, and Cu. Cs and Pb were the main elements to discriminate the wines from the 3 soil types. Wines from several N foliar doses application were classified by Pb, Ni, Mn and Zn. The content of Cs, Mg, Cu and Pb in wines characterized the SO2 addition. Finally, wines storage in barrels were differentiate by Na and Cs concentration. The discriminant functions classify 100% of the wines, with the exception of grape variety (97.0%) and oak ageing (95.8%). Consequently, ICP-MS can be applied to classified wines according to viticultural and oenological factors. |
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Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors.ICP-MSMulti-element analysisMethos optimizationwine classificationWines from different grape varieties, geographical zones, soil types, foliar N application, SO2 addition and oak ageing were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). For this purpose, ICP-MS methodology was optimized. The elements which allowed differentiate wines from studied grape varieties were Sr, Ca, Mg and Mn. Geographical zones were classified according to Sr, Ba, Ni, and Cu. Cs and Pb were the main elements to discriminate the wines from the 3 soil types. Wines from several N foliar doses application were classified by Pb, Ni, Mn and Zn. The content of Cs, Mg, Cu and Pb in wines characterized the SO2 addition. Finally, wines storage in barrels were differentiate by Na and Cs concentration. The discriminant functions classify 100% of the wines, with the exception of grape variety (97.0%) and oak ageing (95.8%). Consequently, ICP-MS can be applied to classified wines according to viticultural and oenological factors.elsevier2019-01-03T15:42:18Z2019-01-032019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/23819http://hdl.handle.net/10174/23819https://doi.org/10.1016/j.foodchem.2018.07.087engndraquelg@uevora.ptndcmbd@uevora.ptmjbc@uevora.ptnd220Pérez-Álvarez, EvaGarcia, RaquelBarrulas, PedroDias, CristinaCabrita, Maria JoãoGarde-Cerdan, Teresainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:16:00Zoai:dspace.uevora.pt:10174/23819Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:14:28.582134Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
title |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
spellingShingle |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. Pérez-Álvarez, Eva ICP-MS Multi-element analysis Methos optimization wine classification |
title_short |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
title_full |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
title_fullStr |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
title_full_unstemmed |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
title_sort |
Optimization of sample preparation method for multi-element analysis of wines by ICP-MS: Application to classify wines according to several factors. |
author |
Pérez-Álvarez, Eva |
author_facet |
Pérez-Álvarez, Eva Garcia, Raquel Barrulas, Pedro Dias, Cristina Cabrita, Maria João Garde-Cerdan, Teresa |
author_role |
author |
author2 |
Garcia, Raquel Barrulas, Pedro Dias, Cristina Cabrita, Maria João Garde-Cerdan, Teresa |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Pérez-Álvarez, Eva Garcia, Raquel Barrulas, Pedro Dias, Cristina Cabrita, Maria João Garde-Cerdan, Teresa |
dc.subject.por.fl_str_mv |
ICP-MS Multi-element analysis Methos optimization wine classification |
topic |
ICP-MS Multi-element analysis Methos optimization wine classification |
description |
Wines from different grape varieties, geographical zones, soil types, foliar N application, SO2 addition and oak ageing were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). For this purpose, ICP-MS methodology was optimized. The elements which allowed differentiate wines from studied grape varieties were Sr, Ca, Mg and Mn. Geographical zones were classified according to Sr, Ba, Ni, and Cu. Cs and Pb were the main elements to discriminate the wines from the 3 soil types. Wines from several N foliar doses application were classified by Pb, Ni, Mn and Zn. The content of Cs, Mg, Cu and Pb in wines characterized the SO2 addition. Finally, wines storage in barrels were differentiate by Na and Cs concentration. The discriminant functions classify 100% of the wines, with the exception of grape variety (97.0%) and oak ageing (95.8%). Consequently, ICP-MS can be applied to classified wines according to viticultural and oenological factors. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-03T15:42:18Z 2019-01-03 2019-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/23819 http://hdl.handle.net/10174/23819 https://doi.org/10.1016/j.foodchem.2018.07.087 |
url |
http://hdl.handle.net/10174/23819 https://doi.org/10.1016/j.foodchem.2018.07.087 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
nd raquelg@uevora.pt nd cmbd@uevora.pt mjbc@uevora.pt nd 220 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
elsevier |
publisher.none.fl_str_mv |
elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799136626701500416 |