Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits

Autores
Cortina, Pablo Ramiro; Santiago, Ana Noemi; Sance, Maria Mirta; Peralta, Iris Edith; Carrari, Fernando Oscar; Asis, Ramón
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The process of tomato (Solanum lycopersicum) breeding has affected negatively the fruit organoleptic properties and this is evident when comparing modern cultivars with heirloom varieties. Flavor of tomato fruit is determined by a complex combination of volatile and nonvolatile metabolites that is not yet understood. Objectives: The aim of this work was to provide an alternative approach to exploring the relationship between tomato odour/taste and volatile organic compounds (VOCs). VOC composition and organoleptic properties of seven Andean tomato landraces along with an edible wild species (Solanum pimpinellifolium) and four commercial varieties were characterized. Six hedonic traits were analyzed by a semitrained sensory panel to describe the organoleptic properties. Ninety-four VOCs were analyzed by headspace solid phase microextraction/gas chromatography–mass spectrometry (HS/SPME/GC–MS). The relationship between sensory data and VOCs was explored using an Artificial Neural Networks model (Kohonen Self Organizing Maps, omeSOM). The results showed a strong preference by panelists for tomatoes of landraces than for commercial varieties and wild species. The predictive analysis by omeSOM showed 15 VOCs significantly associated to the typical and atypical tomato odour and taste. Moreover, omeSOM was used to predict the relationship of VOC ratios with sensory data. A total of 108 VOC ratios out of 8837 VOC ratios were predicted to be contributing to the typical and atypical tomato odour and taste. The metabolic origin of these flavor-associated VOCs and the metabolic point or target for breeding strategies were discussed.
Fil: Cortina, Pablo Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Fil: Santiago, Ana Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Fil: Sance, Maria Mirta. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Peralta, Iris Edith. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina
Fil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Asis, Ramón. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina
Materia
ARTIFICIAL NEURAL NETWORK
GC–MS
SPME
TOMATO FLAVOR
VOC
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:11336/84911
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/84911
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruitsCortina, Pablo RamiroSantiago, Ana NoemiSance, Maria MirtaPeralta, Iris EdithCarrari, Fernando OscarAsis, RamónARTIFICIAL NEURAL NETWORKGC–MSSPMETOMATO FLAVORVOChttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The process of tomato (Solanum lycopersicum) breeding has affected negatively the fruit organoleptic properties and this is evident when comparing modern cultivars with heirloom varieties. Flavor of tomato fruit is determined by a complex combination of volatile and nonvolatile metabolites that is not yet understood. Objectives: The aim of this work was to provide an alternative approach to exploring the relationship between tomato odour/taste and volatile organic compounds (VOCs). VOC composition and organoleptic properties of seven Andean tomato landraces along with an edible wild species (Solanum pimpinellifolium) and four commercial varieties were characterized. Six hedonic traits were analyzed by a semitrained sensory panel to describe the organoleptic properties. Ninety-four VOCs were analyzed by headspace solid phase microextraction/gas chromatography–mass spectrometry (HS/SPME/GC–MS). The relationship between sensory data and VOCs was explored using an Artificial Neural Networks model (Kohonen Self Organizing Maps, omeSOM). The results showed a strong preference by panelists for tomatoes of landraces than for commercial varieties and wild species. The predictive analysis by omeSOM showed 15 VOCs significantly associated to the typical and atypical tomato odour and taste. Moreover, omeSOM was used to predict the relationship of VOC ratios with sensory data. A total of 108 VOC ratios out of 8837 VOC ratios were predicted to be contributing to the typical and atypical tomato odour and taste. The metabolic origin of these flavor-associated VOCs and the metabolic point or target for breeding strategies were discussed.Fil: Cortina, Pablo Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Santiago, Ana Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Sance, Maria Mirta. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Peralta, Iris Edith. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; ArgentinaFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Asis, Ramón. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaSpringer2018-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/84911Cortina, Pablo Ramiro; Santiago, Ana Noemi; Sance, Maria Mirta; Peralta, Iris Edith; Carrari, Fernando Oscar; et al.; Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits; Springer; Metabolomics; 14; 5; 5-20181573-3882CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s11306-018-1355-7info:eu-repo/semantics/altIdentifier/doi/10.1007/s11306-018-1355-7info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:49:46Zoai:ri.conicet.gov.ar:11336/84911instacron: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 09:49:46.838CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
title Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
spellingShingle Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
Cortina, Pablo Ramiro
ARTIFICIAL NEURAL NETWORK
GC–MS
SPME
TOMATO FLAVOR
VOC
title_short Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
title_full Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
title_fullStr Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
title_full_unstemmed Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
title_sort Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits
dc.creator.none.fl_str_mv Cortina, Pablo Ramiro
Santiago, Ana Noemi
Sance, Maria Mirta
Peralta, Iris Edith
Carrari, Fernando Oscar
Asis, Ramón
author Cortina, Pablo Ramiro
author_facet Cortina, Pablo Ramiro
Santiago, Ana Noemi
Sance, Maria Mirta
Peralta, Iris Edith
Carrari, Fernando Oscar
Asis, Ramón
author_role author
author2 Santiago, Ana Noemi
Sance, Maria Mirta
Peralta, Iris Edith
Carrari, Fernando Oscar
Asis, Ramón
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv ARTIFICIAL NEURAL NETWORK
GC–MS
SPME
TOMATO FLAVOR
VOC
topic ARTIFICIAL NEURAL NETWORK
GC–MS
SPME
TOMATO FLAVOR
VOC
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The process of tomato (Solanum lycopersicum) breeding has affected negatively the fruit organoleptic properties and this is evident when comparing modern cultivars with heirloom varieties. Flavor of tomato fruit is determined by a complex combination of volatile and nonvolatile metabolites that is not yet understood. Objectives: The aim of this work was to provide an alternative approach to exploring the relationship between tomato odour/taste and volatile organic compounds (VOCs). VOC composition and organoleptic properties of seven Andean tomato landraces along with an edible wild species (Solanum pimpinellifolium) and four commercial varieties were characterized. Six hedonic traits were analyzed by a semitrained sensory panel to describe the organoleptic properties. Ninety-four VOCs were analyzed by headspace solid phase microextraction/gas chromatography–mass spectrometry (HS/SPME/GC–MS). The relationship between sensory data and VOCs was explored using an Artificial Neural Networks model (Kohonen Self Organizing Maps, omeSOM). The results showed a strong preference by panelists for tomatoes of landraces than for commercial varieties and wild species. The predictive analysis by omeSOM showed 15 VOCs significantly associated to the typical and atypical tomato odour and taste. Moreover, omeSOM was used to predict the relationship of VOC ratios with sensory data. A total of 108 VOC ratios out of 8837 VOC ratios were predicted to be contributing to the typical and atypical tomato odour and taste. The metabolic origin of these flavor-associated VOCs and the metabolic point or target for breeding strategies were discussed.
Fil: Cortina, Pablo Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Fil: Santiago, Ana Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina
Fil: Sance, Maria Mirta. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Peralta, Iris Edith. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina
Fil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Asis, Ramón. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina
description The process of tomato (Solanum lycopersicum) breeding has affected negatively the fruit organoleptic properties and this is evident when comparing modern cultivars with heirloom varieties. Flavor of tomato fruit is determined by a complex combination of volatile and nonvolatile metabolites that is not yet understood. Objectives: The aim of this work was to provide an alternative approach to exploring the relationship between tomato odour/taste and volatile organic compounds (VOCs). VOC composition and organoleptic properties of seven Andean tomato landraces along with an edible wild species (Solanum pimpinellifolium) and four commercial varieties were characterized. Six hedonic traits were analyzed by a semitrained sensory panel to describe the organoleptic properties. Ninety-four VOCs were analyzed by headspace solid phase microextraction/gas chromatography–mass spectrometry (HS/SPME/GC–MS). The relationship between sensory data and VOCs was explored using an Artificial Neural Networks model (Kohonen Self Organizing Maps, omeSOM). The results showed a strong preference by panelists for tomatoes of landraces than for commercial varieties and wild species. The predictive analysis by omeSOM showed 15 VOCs significantly associated to the typical and atypical tomato odour and taste. Moreover, omeSOM was used to predict the relationship of VOC ratios with sensory data. A total of 108 VOC ratios out of 8837 VOC ratios were predicted to be contributing to the typical and atypical tomato odour and taste. The metabolic origin of these flavor-associated VOCs and the metabolic point or target for breeding strategies were discussed.
publishDate 2018
dc.date.none.fl_str_mv 2018-05
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/11336/84911
Cortina, Pablo Ramiro; Santiago, Ana Noemi; Sance, Maria Mirta; Peralta, Iris Edith; Carrari, Fernando Oscar; et al.; Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits; Springer; Metabolomics; 14; 5; 5-2018
1573-3882
CONICET Digital
CONICET
url http://hdl.handle.net/11336/84911
identifier_str_mv Cortina, Pablo Ramiro; Santiago, Ana Noemi; Sance, Maria Mirta; Peralta, Iris Edith; Carrari, Fernando Oscar; et al.; Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits; Springer; Metabolomics; 14; 5; 5-2018
1573-3882
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s11306-018-1355-7
info:eu-repo/semantics/altIdentifier/doi/10.1007/s11306-018-1355-7
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
application/pdf
application/pdf
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
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
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