Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS

Autores
Yener, Sine; Sánchez-López, José A.; Granitto, Pablo Miguel; Cappellin, Luca; Märk, Tilmann D.; Zimmermann, Ralf; Bonn, Günther K.; Yeretzian, Chahan; Biasioli, Franco
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Volatile profiles of 63 black and 38 green teas from different countries were analysed with Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) both for tea leaves and tea infusion. The headspace volatile fingerprints were collected and the tea classes and geographical origins were tracked with pattern recognition techniques. The high mass resolution achieved by ToF mass analyser provided determination of sum formula and tentative identifications of the mass peaks. The results provided successful separation of the black and green teas based on their headspace volatile emissions both from the dry tea leaves and their infusions. The volatile fingerprints were then used to build different classification models for discrimination of black and green teas according to their geographical origins. Two different cross validation methods were applied and their effectiveness for origin discrimination was discussed. The classification models showed a separation of black and green teas according to geographical origins the errors being mostly between neighbouring countries.
Fil: Yener, Sine. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia. Universidad de Innsbruck; Austria
Fil: Sánchez-López, José A.. Universitat Zurich; Suiza. Universität Rostock; Alemania
Fil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Cappellin, Luca. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia
Fil: Märk, Tilmann D.. Universidad de Innsbruck; Austria
Fil: Zimmermann, Ralf. Universität Rostock; Alemania. Technische Universitat Munchen; Alemania
Fil: Bonn, Günther K.. Universidad de Innsbruck; Austria. Austrian Drug Screening Institute; Austria
Fil: Yeretzian, Chahan. Universitat Zurich; Suiza
Fil: Biasioli, Franco. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia
Materia
Geographic Origin Classification
Headspace Volatile Fingerprinting
Tea Aroma
Tea Infusion
Tea Leaf
Volatile Profiling
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/52665
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/52665
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MSYener, SineSánchez-López, José A.Granitto, Pablo MiguelCappellin, LucaMärk, Tilmann D.Zimmermann, RalfBonn, Günther K.Yeretzian, ChahanBiasioli, FrancoGeographic Origin ClassificationHeadspace Volatile FingerprintingTea AromaTea InfusionTea LeafVolatile Profilinghttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Volatile profiles of 63 black and 38 green teas from different countries were analysed with Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) both for tea leaves and tea infusion. The headspace volatile fingerprints were collected and the tea classes and geographical origins were tracked with pattern recognition techniques. The high mass resolution achieved by ToF mass analyser provided determination of sum formula and tentative identifications of the mass peaks. The results provided successful separation of the black and green teas based on their headspace volatile emissions both from the dry tea leaves and their infusions. The volatile fingerprints were then used to build different classification models for discrimination of black and green teas according to their geographical origins. Two different cross validation methods were applied and their effectiveness for origin discrimination was discussed. The classification models showed a separation of black and green teas according to geographical origins the errors being mostly between neighbouring countries.Fil: Yener, Sine. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia. Universidad de Innsbruck; AustriaFil: Sánchez-López, José A.. Universitat Zurich; Suiza. Universität Rostock; AlemaniaFil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Cappellin, Luca. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; ItaliaFil: Märk, Tilmann D.. Universidad de Innsbruck; AustriaFil: Zimmermann, Ralf. Universität Rostock; Alemania. Technische Universitat Munchen; AlemaniaFil: Bonn, Günther K.. Universidad de Innsbruck; Austria. Austrian Drug Screening Institute; AustriaFil: Yeretzian, Chahan. Universitat Zurich; SuizaFil: Biasioli, Franco. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; ItaliaElsevier Science2016-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/52665Yener, Sine; Sánchez-López, José A.; Granitto, Pablo Miguel; Cappellin, Luca; Märk, Tilmann D.; et al.; Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS; Elsevier Science; Talanta; 152; 5-2016; 45-530039-9140CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.talanta.2016.01.050info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0039914016300522info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:23:16Zoai:ri.conicet.gov.ar:11336/52665instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:23:16.559CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
title Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
spellingShingle Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
Yener, Sine
Geographic Origin Classification
Headspace Volatile Fingerprinting
Tea Aroma
Tea Infusion
Tea Leaf
Volatile Profiling
title_short Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
title_full Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
title_fullStr Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
title_full_unstemmed Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
title_sort Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS
dc.creator.none.fl_str_mv Yener, Sine
Sánchez-López, José A.
Granitto, Pablo Miguel
Cappellin, Luca
Märk, Tilmann D.
Zimmermann, Ralf
Bonn, Günther K.
Yeretzian, Chahan
Biasioli, Franco
author Yener, Sine
author_facet Yener, Sine
Sánchez-López, José A.
Granitto, Pablo Miguel
Cappellin, Luca
Märk, Tilmann D.
Zimmermann, Ralf
Bonn, Günther K.
Yeretzian, Chahan
Biasioli, Franco
author_role author
author2 Sánchez-López, José A.
Granitto, Pablo Miguel
Cappellin, Luca
Märk, Tilmann D.
Zimmermann, Ralf
Bonn, Günther K.
Yeretzian, Chahan
Biasioli, Franco
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Geographic Origin Classification
Headspace Volatile Fingerprinting
Tea Aroma
Tea Infusion
Tea Leaf
Volatile Profiling
topic Geographic Origin Classification
Headspace Volatile Fingerprinting
Tea Aroma
Tea Infusion
Tea Leaf
Volatile Profiling
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Volatile profiles of 63 black and 38 green teas from different countries were analysed with Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) both for tea leaves and tea infusion. The headspace volatile fingerprints were collected and the tea classes and geographical origins were tracked with pattern recognition techniques. The high mass resolution achieved by ToF mass analyser provided determination of sum formula and tentative identifications of the mass peaks. The results provided successful separation of the black and green teas based on their headspace volatile emissions both from the dry tea leaves and their infusions. The volatile fingerprints were then used to build different classification models for discrimination of black and green teas according to their geographical origins. Two different cross validation methods were applied and their effectiveness for origin discrimination was discussed. The classification models showed a separation of black and green teas according to geographical origins the errors being mostly between neighbouring countries.
Fil: Yener, Sine. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia. Universidad de Innsbruck; Austria
Fil: Sánchez-López, José A.. Universitat Zurich; Suiza. Universität Rostock; Alemania
Fil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Cappellin, Luca. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia
Fil: Märk, Tilmann D.. Universidad de Innsbruck; Austria
Fil: Zimmermann, Ralf. Universität Rostock; Alemania. Technische Universitat Munchen; Alemania
Fil: Bonn, Günther K.. Universidad de Innsbruck; Austria. Austrian Drug Screening Institute; Austria
Fil: Yeretzian, Chahan. Universitat Zurich; Suiza
Fil: Biasioli, Franco. Instituto Agrario San Michele all'Adige Fondazione Edmund Mach; Italia
description Volatile profiles of 63 black and 38 green teas from different countries were analysed with Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) both for tea leaves and tea infusion. The headspace volatile fingerprints were collected and the tea classes and geographical origins were tracked with pattern recognition techniques. The high mass resolution achieved by ToF mass analyser provided determination of sum formula and tentative identifications of the mass peaks. The results provided successful separation of the black and green teas based on their headspace volatile emissions both from the dry tea leaves and their infusions. The volatile fingerprints were then used to build different classification models for discrimination of black and green teas according to their geographical origins. Two different cross validation methods were applied and their effectiveness for origin discrimination was discussed. The classification models showed a separation of black and green teas according to geographical origins the errors being mostly between neighbouring countries.
publishDate 2016
dc.date.none.fl_str_mv 2016-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/52665
Yener, Sine; Sánchez-López, José A.; Granitto, Pablo Miguel; Cappellin, Luca; Märk, Tilmann D.; et al.; Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS; Elsevier Science; Talanta; 152; 5-2016; 45-53
0039-9140
CONICET Digital
CONICET
url http://hdl.handle.net/11336/52665
identifier_str_mv Yener, Sine; Sánchez-López, José A.; Granitto, Pablo Miguel; Cappellin, Luca; Märk, Tilmann D.; et al.; Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS; Elsevier Science; Talanta; 152; 5-2016; 45-53
0039-9140
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.talanta.2016.01.050
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0039914016300522
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846082640205053952
score 13.22299

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