On data analysis in PTR-TOF-MS: From raw spectra to data mining

Autores
Cappellin, Luca; Biasioli, Franco; Granitto, Pablo Miguel; Schuhfried, Erna; Soukoulis, Christos; Costa, Fabrizio; Märk, Tilmann D.; Gasperi, Flavia
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Recently the coupling of proton transfer reaction ionization with a time-of-flight mass analyser (PTRTOF-MS) has been proposed to realise a volatile organic compound (VOC) detector that overcomes the limitations in terms of time and mass resolution of the previous instrument based on a quadrupole mass analysers (PTR-Quad-MS). This opens new horizons for research and allows for new applications in fields where the rapid and sensitive monitoring and quantification of volatile organic compounds (VOCs) is crucial as, for instance, environmental sciences, food sciences and medicine. In particular, if coupled with appropriate data mining methods, it can provide a fast MS-nose system with rich analytical information. The main, perhaps even the only, drawback of this new technique in comparison to its precursor is related to the increased size and complexity of the data sets obtained. It appears that this is the main limitation to its full use and widespread application. Here we present and discuss a complete computer-based strategy for the data analysis of PTR-TOF-MS data from basic mass spectra handling, to the application of up-to date data mining methods. As a case study we apply the whole procedure to the classification of apple cultivars and clones, which was based on the distinctive profiles of volatile organic compound emissions.
Fil: Cappellin, Luca. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia. Universidad de Innsbruck; Austria
Fil: Biasioli, Franco. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Fil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina. Universidad Nacional de Rosario; Argentina
Fil: Schuhfried, Erna. Universidad de Innsbruck; Austria
Fil: Soukoulis, Christos. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Fil: Costa, Fabrizio. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Fil: Märk, Tilmann D.. Universidad de Innsbruck; Austria
Fil: Gasperi, Flavia. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Materia
Proton Transfer Reaction Mass Spectrometry
Time of Flight
Data Analysis
Data Mining
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/15168
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling On data analysis in PTR-TOF-MS: From raw spectra to data miningCappellin, LucaBiasioli, FrancoGranitto, Pablo MiguelSchuhfried, ErnaSoukoulis, ChristosCosta, FabrizioMärk, Tilmann D.Gasperi, FlaviaProton Transfer Reaction Mass SpectrometryTime of FlightData AnalysisData Mininghttps://purl.org/becyt/ford/4.4https://purl.org/becyt/ford/4Recently the coupling of proton transfer reaction ionization with a time-of-flight mass analyser (PTRTOF-MS) has been proposed to realise a volatile organic compound (VOC) detector that overcomes the limitations in terms of time and mass resolution of the previous instrument based on a quadrupole mass analysers (PTR-Quad-MS). This opens new horizons for research and allows for new applications in fields where the rapid and sensitive monitoring and quantification of volatile organic compounds (VOCs) is crucial as, for instance, environmental sciences, food sciences and medicine. In particular, if coupled with appropriate data mining methods, it can provide a fast MS-nose system with rich analytical information. The main, perhaps even the only, drawback of this new technique in comparison to its precursor is related to the increased size and complexity of the data sets obtained. It appears that this is the main limitation to its full use and widespread application. Here we present and discuss a complete computer-based strategy for the data analysis of PTR-TOF-MS data from basic mass spectra handling, to the application of up-to date data mining methods. As a case study we apply the whole procedure to the classification of apple cultivars and clones, which was based on the distinctive profiles of volatile organic compound emissions.Fil: Cappellin, Luca. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia. Universidad de Innsbruck; AustriaFil: Biasioli, Franco. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; ItaliaFil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina. Universidad Nacional de Rosario; ArgentinaFil: Schuhfried, Erna. Universidad de Innsbruck; AustriaFil: Soukoulis, Christos. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; ItaliaFil: Costa, Fabrizio. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; ItaliaFil: Märk, Tilmann D.. Universidad de Innsbruck; AustriaFil: Gasperi, Flavia. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; ItaliaElsevier Science2011-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/15168Cappellin, Luca; Biasioli, Franco; Granitto, Pablo Miguel; Schuhfried, Erna; Soukoulis, Christos; et al.; On data analysis in PTR-TOF-MS: From raw spectra to data mining; Elsevier Science; Sensors And Actuators B: Chemical; 155; 1; 7-2011; 183-1900925-4005enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.snb.2010.11.044info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0925400510009135info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:12:02Zoai:ri.conicet.gov.ar:11336/15168instacron: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:34982025-09-03 10:12:02.654CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On data analysis in PTR-TOF-MS: From raw spectra to data mining
title On data analysis in PTR-TOF-MS: From raw spectra to data mining
spellingShingle On data analysis in PTR-TOF-MS: From raw spectra to data mining
Cappellin, Luca
Proton Transfer Reaction Mass Spectrometry
Time of Flight
Data Analysis
Data Mining
title_short On data analysis in PTR-TOF-MS: From raw spectra to data mining
title_full On data analysis in PTR-TOF-MS: From raw spectra to data mining
title_fullStr On data analysis in PTR-TOF-MS: From raw spectra to data mining
title_full_unstemmed On data analysis in PTR-TOF-MS: From raw spectra to data mining
title_sort On data analysis in PTR-TOF-MS: From raw spectra to data mining
dc.creator.none.fl_str_mv Cappellin, Luca
Biasioli, Franco
Granitto, Pablo Miguel
Schuhfried, Erna
Soukoulis, Christos
Costa, Fabrizio
Märk, Tilmann D.
Gasperi, Flavia
author Cappellin, Luca
author_facet Cappellin, Luca
Biasioli, Franco
Granitto, Pablo Miguel
Schuhfried, Erna
Soukoulis, Christos
Costa, Fabrizio
Märk, Tilmann D.
Gasperi, Flavia
author_role author
author2 Biasioli, Franco
Granitto, Pablo Miguel
Schuhfried, Erna
Soukoulis, Christos
Costa, Fabrizio
Märk, Tilmann D.
Gasperi, Flavia
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Proton Transfer Reaction Mass Spectrometry
Time of Flight
Data Analysis
Data Mining
topic Proton Transfer Reaction Mass Spectrometry
Time of Flight
Data Analysis
Data Mining
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.4
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Recently the coupling of proton transfer reaction ionization with a time-of-flight mass analyser (PTRTOF-MS) has been proposed to realise a volatile organic compound (VOC) detector that overcomes the limitations in terms of time and mass resolution of the previous instrument based on a quadrupole mass analysers (PTR-Quad-MS). This opens new horizons for research and allows for new applications in fields where the rapid and sensitive monitoring and quantification of volatile organic compounds (VOCs) is crucial as, for instance, environmental sciences, food sciences and medicine. In particular, if coupled with appropriate data mining methods, it can provide a fast MS-nose system with rich analytical information. The main, perhaps even the only, drawback of this new technique in comparison to its precursor is related to the increased size and complexity of the data sets obtained. It appears that this is the main limitation to its full use and widespread application. Here we present and discuss a complete computer-based strategy for the data analysis of PTR-TOF-MS data from basic mass spectra handling, to the application of up-to date data mining methods. As a case study we apply the whole procedure to the classification of apple cultivars and clones, which was based on the distinctive profiles of volatile organic compound emissions.
Fil: Cappellin, Luca. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia. Universidad de Innsbruck; Austria
Fil: Biasioli, Franco. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Fil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina. Universidad Nacional de Rosario; Argentina
Fil: Schuhfried, Erna. Universidad de Innsbruck; Austria
Fil: Soukoulis, Christos. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Fil: Costa, Fabrizio. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
Fil: Märk, Tilmann D.. Universidad de Innsbruck; Austria
Fil: Gasperi, Flavia. Instituto Agrario San Michele All'adige Fondazione Edmund Mach; Italia
description Recently the coupling of proton transfer reaction ionization with a time-of-flight mass analyser (PTRTOF-MS) has been proposed to realise a volatile organic compound (VOC) detector that overcomes the limitations in terms of time and mass resolution of the previous instrument based on a quadrupole mass analysers (PTR-Quad-MS). This opens new horizons for research and allows for new applications in fields where the rapid and sensitive monitoring and quantification of volatile organic compounds (VOCs) is crucial as, for instance, environmental sciences, food sciences and medicine. In particular, if coupled with appropriate data mining methods, it can provide a fast MS-nose system with rich analytical information. The main, perhaps even the only, drawback of this new technique in comparison to its precursor is related to the increased size and complexity of the data sets obtained. It appears that this is the main limitation to its full use and widespread application. Here we present and discuss a complete computer-based strategy for the data analysis of PTR-TOF-MS data from basic mass spectra handling, to the application of up-to date data mining methods. As a case study we apply the whole procedure to the classification of apple cultivars and clones, which was based on the distinctive profiles of volatile organic compound emissions.
publishDate 2011
dc.date.none.fl_str_mv 2011-07
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/11336/15168
Cappellin, Luca; Biasioli, Franco; Granitto, Pablo Miguel; Schuhfried, Erna; Soukoulis, Christos; et al.; On data analysis in PTR-TOF-MS: From raw spectra to data mining; Elsevier Science; Sensors And Actuators B: Chemical; 155; 1; 7-2011; 183-190
0925-4005
url http://hdl.handle.net/11336/15168
identifier_str_mv Cappellin, Luca; Biasioli, Franco; Granitto, Pablo Miguel; Schuhfried, Erna; Soukoulis, Christos; et al.; On data analysis in PTR-TOF-MS: From raw spectra to data mining; Elsevier Science; Sensors And Actuators B: Chemical; 155; 1; 7-2011; 183-190
0925-4005
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.snb.2010.11.044
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0925400510009135
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/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_ 1842270182665355264
score 13.13397

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