Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes

Autores
Goyeneche, Rosario; Roura, Sara Ines; Di Scala, Karina Cecilia
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The application of principal component and hierarchical cluster analysis as a mathematical tool to select hurdle technologies (physical and chemical) to inhibit polyphenol oxidase (PPO) activity and color stability of minimally sliced radishes was presented. Results of PPO activity and color were reported initially (day zero) and after 4 d of refrigerated storage. Based on the mentioned tools and from the thirteen mono-hurdles technologies that were initially selected, eight hurdles were chosen as the best and combined in pairs. From those hurdles, the following double-hurdles were selected as those capable of retaining the product color: Ascorbic Acid (AA) + Acetic Acid (ACA-05), AA + NaCl-1, ACA-05+NaCl-1, AA + Heat Treatment (TT-501), ACA-05 + Ultrasound (US), Citric Acid (CA) + AA, CA + ACA-05, NaCl-1+US. When comparing the best mono-hurdles (AA, TT-501, NaCl-1) to the best double hurdles, the following hurdles: AA, TT-501, CA + ACA-05, NaCl-1+US, CA + AA and NaCl-1 were chosen as those capable of maintaining the typical color of radish slices with acceptable sensory parameters and enzyme inhibition after 4 d of storage.
Fil: Goyeneche, Rosario. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina. Agencia Nacional de Promoción Científicas y Tecnológica ; Argentina
Fil: Roura, Sara Ines. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina
Fil: Di Scala, Karina Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina
Materia
Hurdle Technology
Minimally Processing
Polyphenoloxidase
Color
Radish
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:11336/34759
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishesGoyeneche, RosarioRoura, Sara InesDi Scala, Karina CeciliaHurdle TechnologyMinimally ProcessingPolyphenoloxidaseColorRadishhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2The application of principal component and hierarchical cluster analysis as a mathematical tool to select hurdle technologies (physical and chemical) to inhibit polyphenol oxidase (PPO) activity and color stability of minimally sliced radishes was presented. Results of PPO activity and color were reported initially (day zero) and after 4 d of refrigerated storage. Based on the mentioned tools and from the thirteen mono-hurdles technologies that were initially selected, eight hurdles were chosen as the best and combined in pairs. From those hurdles, the following double-hurdles were selected as those capable of retaining the product color: Ascorbic Acid (AA) + Acetic Acid (ACA-05), AA + NaCl-1, ACA-05+NaCl-1, AA + Heat Treatment (TT-501), ACA-05 + Ultrasound (US), Citric Acid (CA) + AA, CA + ACA-05, NaCl-1+US. When comparing the best mono-hurdles (AA, TT-501, NaCl-1) to the best double hurdles, the following hurdles: AA, TT-501, CA + ACA-05, NaCl-1+US, CA + AA and NaCl-1 were chosen as those capable of maintaining the typical color of radish slices with acceptable sensory parameters and enzyme inhibition after 4 d of storage.Fil: Goyeneche, Rosario. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina. Agencia Nacional de Promoción Científicas y Tecnológica ; ArgentinaFil: Roura, Sara Ines. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; ArgentinaFil: Di Scala, Karina Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; ArgentinaElsevier Science2014-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/34759Goyeneche, Rosario; Roura, Sara Ines; Di Scala, Karina Cecilia; Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes; Elsevier Science; LWT - Food Science and Technology; 57; 2; 7-2014; 522-5290023-6438CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.lwt.2014.02.022info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S002364381400098Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:16:11Zoai:ri.conicet.gov.ar:11336/34759instacron: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 10:16:11.877CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
title Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
spellingShingle Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
Goyeneche, Rosario
Hurdle Technology
Minimally Processing
Polyphenoloxidase
Color
Radish
title_short Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
title_full Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
title_fullStr Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
title_full_unstemmed Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
title_sort Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes
dc.creator.none.fl_str_mv Goyeneche, Rosario
Roura, Sara Ines
Di Scala, Karina Cecilia
author Goyeneche, Rosario
author_facet Goyeneche, Rosario
Roura, Sara Ines
Di Scala, Karina Cecilia
author_role author
author2 Roura, Sara Ines
Di Scala, Karina Cecilia
author2_role author
author
dc.subject.none.fl_str_mv Hurdle Technology
Minimally Processing
Polyphenoloxidase
Color
Radish
topic Hurdle Technology
Minimally Processing
Polyphenoloxidase
Color
Radish
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The application of principal component and hierarchical cluster analysis as a mathematical tool to select hurdle technologies (physical and chemical) to inhibit polyphenol oxidase (PPO) activity and color stability of minimally sliced radishes was presented. Results of PPO activity and color were reported initially (day zero) and after 4 d of refrigerated storage. Based on the mentioned tools and from the thirteen mono-hurdles technologies that were initially selected, eight hurdles were chosen as the best and combined in pairs. From those hurdles, the following double-hurdles were selected as those capable of retaining the product color: Ascorbic Acid (AA) + Acetic Acid (ACA-05), AA + NaCl-1, ACA-05+NaCl-1, AA + Heat Treatment (TT-501), ACA-05 + Ultrasound (US), Citric Acid (CA) + AA, CA + ACA-05, NaCl-1+US. When comparing the best mono-hurdles (AA, TT-501, NaCl-1) to the best double hurdles, the following hurdles: AA, TT-501, CA + ACA-05, NaCl-1+US, CA + AA and NaCl-1 were chosen as those capable of maintaining the typical color of radish slices with acceptable sensory parameters and enzyme inhibition after 4 d of storage.
Fil: Goyeneche, Rosario. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina. Agencia Nacional de Promoción Científicas y Tecnológica ; Argentina
Fil: Roura, Sara Ines. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina
Fil: Di Scala, Karina Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Inv En Ingeniería En Alimentos; Argentina
description The application of principal component and hierarchical cluster analysis as a mathematical tool to select hurdle technologies (physical and chemical) to inhibit polyphenol oxidase (PPO) activity and color stability of minimally sliced radishes was presented. Results of PPO activity and color were reported initially (day zero) and after 4 d of refrigerated storage. Based on the mentioned tools and from the thirteen mono-hurdles technologies that were initially selected, eight hurdles were chosen as the best and combined in pairs. From those hurdles, the following double-hurdles were selected as those capable of retaining the product color: Ascorbic Acid (AA) + Acetic Acid (ACA-05), AA + NaCl-1, ACA-05+NaCl-1, AA + Heat Treatment (TT-501), ACA-05 + Ultrasound (US), Citric Acid (CA) + AA, CA + ACA-05, NaCl-1+US. When comparing the best mono-hurdles (AA, TT-501, NaCl-1) to the best double hurdles, the following hurdles: AA, TT-501, CA + ACA-05, NaCl-1+US, CA + AA and NaCl-1 were chosen as those capable of maintaining the typical color of radish slices with acceptable sensory parameters and enzyme inhibition after 4 d of storage.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
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/11336/34759
Goyeneche, Rosario; Roura, Sara Ines; Di Scala, Karina Cecilia; Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes; Elsevier Science; LWT - Food Science and Technology; 57; 2; 7-2014; 522-529
0023-6438
CONICET Digital
CONICET
url http://hdl.handle.net/11336/34759
identifier_str_mv Goyeneche, Rosario; Roura, Sara Ines; Di Scala, Karina Cecilia; Principal component and hierarchical cluster analysis to select hurdle technologies for minimal processed radishes; Elsevier Science; LWT - Food Science and Technology; 57; 2; 7-2014; 522-529
0023-6438
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.lwt.2014.02.022
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S002364381400098X
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
application/pdf
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
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score 13.070432

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