Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods

Autores
Garcia Oliveira, Paula; Chamorro, Franklin; Simal Gandara, Jesus; Prieto, Miguel A.; Cassani, Lucía Victoria
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This study aimed to optimize phenolic compound extraction from Arnica montana (AM) L. flowers,comparing heat- and ultrasound-assisted extraction (HAE and UAE) through a multivariateapproach. Critical parameters, including time, temperature or ultrasonic power, and ethanol concentration, were evaluated through a circumscribed central composite design. Unsupervised multivariate analysis of LC-MS/MS data identified key extraction conditions influencing the phenolicprofile. Response surface methodology (RSM) determined optimal levels of enhancing yield andtotal phenolic content. Among the 24 identified phenolic compounds, dicaffeoylquinic acid wasthe most abundant. Ethanol concentration proved crucial in extracting specific phenolic compounds, supported by multivariate and RSM analyses. Optimal HAE conditions outperformedUAE, resulting in a 26% increase in phenolic compounds. Utilizing extraction cycles under theseconditions, especially two cycles for HAE and three for UAE, surpassed traditional Soxhlet extraction, indicating potential industrial applications for AM flower extracts with improved efficiency and resource utilization compared to conventional methods.
Fil: Garcia Oliveira, Paula. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Chamorro, Franklin. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Simal Gandara, Jesus. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Prieto, Miguel A.. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Cassani, Lucía Victoria. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; Argentina
Materia
BIOACTIVE COMPOUNDS
CHEMOMETRIC ANALYSIS
OPTIMIZATION
EFFICIENT PROCESSES
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:11336/265187
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methodsGarcia Oliveira, PaulaChamorro, FranklinSimal Gandara, JesusPrieto, Miguel A.Cassani, Lucía VictoriaBIOACTIVE COMPOUNDSCHEMOMETRIC ANALYSISOPTIMIZATIONEFFICIENT PROCESSEShttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2This study aimed to optimize phenolic compound extraction from Arnica montana (AM) L. flowers,comparing heat- and ultrasound-assisted extraction (HAE and UAE) through a multivariateapproach. Critical parameters, including time, temperature or ultrasonic power, and ethanol concentration, were evaluated through a circumscribed central composite design. Unsupervised multivariate analysis of LC-MS/MS data identified key extraction conditions influencing the phenolicprofile. Response surface methodology (RSM) determined optimal levels of enhancing yield andtotal phenolic content. Among the 24 identified phenolic compounds, dicaffeoylquinic acid wasthe most abundant. Ethanol concentration proved crucial in extracting specific phenolic compounds, supported by multivariate and RSM analyses. Optimal HAE conditions outperformedUAE, resulting in a 26% increase in phenolic compounds. Utilizing extraction cycles under theseconditions, especially two cycles for HAE and three for UAE, surpassed traditional Soxhlet extraction, indicating potential industrial applications for AM flower extracts with improved efficiency and resource utilization compared to conventional methods.Fil: Garcia Oliveira, Paula. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; EspañaFil: Chamorro, Franklin. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; EspañaFil: Simal Gandara, Jesus. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; EspañaFil: Prieto, Miguel A.. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; EspañaFil: Cassani, Lucía Victoria. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; ArgentinaElsevier2024-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/265187Garcia Oliveira, Paula; Chamorro, Franklin; Simal Gandara, Jesus; Prieto, Miguel A.; Cassani, Lucía Victoria; Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods; Elsevier; Sustainable Chemistry and Pharmacy; 41; 10-2024; 1-172352-5541CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S2352554124002973info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scp.2024.101722info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:20:51Zoai:ri.conicet.gov.ar:11336/265187instacron: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:34982025-09-29 10:20:51.757CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
title Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
spellingShingle Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
Garcia Oliveira, Paula
BIOACTIVE COMPOUNDS
CHEMOMETRIC ANALYSIS
OPTIMIZATION
EFFICIENT PROCESSES
title_short Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
title_full Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
title_fullStr Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
title_full_unstemmed Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
title_sort Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods
dc.creator.none.fl_str_mv Garcia Oliveira, Paula
Chamorro, Franklin
Simal Gandara, Jesus
Prieto, Miguel A.
Cassani, Lucía Victoria
author Garcia Oliveira, Paula
author_facet Garcia Oliveira, Paula
Chamorro, Franklin
Simal Gandara, Jesus
Prieto, Miguel A.
Cassani, Lucía Victoria
author_role author
author2 Chamorro, Franklin
Simal Gandara, Jesus
Prieto, Miguel A.
Cassani, Lucía Victoria
author2_role author
author
author
author
dc.subject.none.fl_str_mv BIOACTIVE COMPOUNDS
CHEMOMETRIC ANALYSIS
OPTIMIZATION
EFFICIENT PROCESSES
topic BIOACTIVE COMPOUNDS
CHEMOMETRIC ANALYSIS
OPTIMIZATION
EFFICIENT PROCESSES
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This study aimed to optimize phenolic compound extraction from Arnica montana (AM) L. flowers,comparing heat- and ultrasound-assisted extraction (HAE and UAE) through a multivariateapproach. Critical parameters, including time, temperature or ultrasonic power, and ethanol concentration, were evaluated through a circumscribed central composite design. Unsupervised multivariate analysis of LC-MS/MS data identified key extraction conditions influencing the phenolicprofile. Response surface methodology (RSM) determined optimal levels of enhancing yield andtotal phenolic content. Among the 24 identified phenolic compounds, dicaffeoylquinic acid wasthe most abundant. Ethanol concentration proved crucial in extracting specific phenolic compounds, supported by multivariate and RSM analyses. Optimal HAE conditions outperformedUAE, resulting in a 26% increase in phenolic compounds. Utilizing extraction cycles under theseconditions, especially two cycles for HAE and three for UAE, surpassed traditional Soxhlet extraction, indicating potential industrial applications for AM flower extracts with improved efficiency and resource utilization compared to conventional methods.
Fil: Garcia Oliveira, Paula. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Chamorro, Franklin. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Simal Gandara, Jesus. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Prieto, Miguel A.. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España
Fil: Cassani, Lucía Victoria. Universidad de Vigo. Facultad de Ciencias de Ourense. Departamento de Química Analitica y Alimentaria; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; Argentina
description This study aimed to optimize phenolic compound extraction from Arnica montana (AM) L. flowers,comparing heat- and ultrasound-assisted extraction (HAE and UAE) through a multivariateapproach. Critical parameters, including time, temperature or ultrasonic power, and ethanol concentration, were evaluated through a circumscribed central composite design. Unsupervised multivariate analysis of LC-MS/MS data identified key extraction conditions influencing the phenolicprofile. Response surface methodology (RSM) determined optimal levels of enhancing yield andtotal phenolic content. Among the 24 identified phenolic compounds, dicaffeoylquinic acid wasthe most abundant. Ethanol concentration proved crucial in extracting specific phenolic compounds, supported by multivariate and RSM analyses. Optimal HAE conditions outperformedUAE, resulting in a 26% increase in phenolic compounds. Utilizing extraction cycles under theseconditions, especially two cycles for HAE and three for UAE, surpassed traditional Soxhlet extraction, indicating potential industrial applications for AM flower extracts with improved efficiency and resource utilization compared to conventional methods.
publishDate 2024
dc.date.none.fl_str_mv 2024-10
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/11336/265187
Garcia Oliveira, Paula; Chamorro, Franklin; Simal Gandara, Jesus; Prieto, Miguel A.; Cassani, Lucía Victoria; Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods; Elsevier; Sustainable Chemistry and Pharmacy; 41; 10-2024; 1-17
2352-5541
CONICET Digital
CONICET
url http://hdl.handle.net/11336/265187
identifier_str_mv Garcia Oliveira, Paula; Chamorro, Franklin; Simal Gandara, Jesus; Prieto, Miguel A.; Cassani, Lucía Victoria; Improving phenolic compound extraction from Arnica montana flowers through multivariate optimization of heat and ultrasound-assisted methods; Elsevier; Sustainable Chemistry and Pharmacy; 41; 10-2024; 1-17
2352-5541
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S2352554124002973
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scp.2024.101722
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
publisher.none.fl_str_mv Elsevier
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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score 13.070432

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