Astringency assessment of persimmon by hyperspectral imaging

[EN] One of the current challenges of persimmon postharvest research is the development of non-destructive methods that allow determination of the internal properties of the fruit, such as maturity, flesh firmness and astringency. This study evaluates the usefulness of hyperspectral imaging in the 4...

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Autores: Munera Picazo, Sandra Maria, Besada Ferreiro, Cristina María, Blasco Ivars, José, Cubero-García, Sergio, Salvador, Alejandra, Talens Oliag, Pau|||0000-0001-7318-3336, Aleixos Borrás, María Nuria|||0000-0001-6051-3375
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/100335
Acceso en línea:https://riunet.upv.es/handle/10251/100335
Access Level:acceso abierto
Palabra clave:Diospyros kaki
Fruit internal quality
Soluble tannins
Distribution map
Hyperspectral imaging
Computer vision
EXPRESION GRAFICA EN LA INGENIERIA
TECNOLOGIA DE ALIMENTOS
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spelling Astringency assessment of persimmon by hyperspectral imagingMunera Picazo, Sandra MariaBesada Ferreiro, Cristina MaríaBlasco Ivars, JoséCubero-García, SergioSalvador, AlejandraTalens Oliag, Pau|||0000-0001-7318-3336Aleixos Borrás, María Nuria|||0000-0001-6051-3375Diospyros kakiFruit internal qualitySoluble tanninsDistribution mapHyperspectral imagingComputer visionEXPRESION GRAFICA EN LA INGENIERIATECNOLOGIA DE ALIMENTOS[EN] One of the current challenges of persimmon postharvest research is the development of non-destructive methods that allow determination of the internal properties of the fruit, such as maturity, flesh firmness and astringency. This study evaluates the usefulness of hyperspectral imaging in the 460 1020 nm range as a non-destructive tool to achieve these aims in Persimmon cv. Rojo Brillante which is an astringent cultivar. Fruit were harvested at three different stages of commercial maturity and exposed to different treatments of CO2 (95% CO2 20 ºC from 0 to 24 h) in order to obtain fruit with different levels of astringency. Partial Least Square (PLS) based methods were used to classify persimmon fruits by maturity and to predict flesh firmness from the average spectrum of each fruit. The results showed a 97.9% rate of correct maturity classification and an R2P of 0.80 for firmness prediction with only five selected wavelengths. For astringency assessment, as our results showed that the soluble tannins that remain after CO2 treatments are distributed irregularly inside the flesh, a model based on PLS was built using the spectrum of every pixel in the fruit. The model obtained an R2P of 0.91 which allowed the creation of the predicted distribution maps of the tannins in the flesh of the fruit, thereby pointing to hyperspectral systems as a promising technology to assess the effectiveness of the deastringency treatments that are usually applied before commercialising persimmons from astringent cultivars.This work has been partially funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) through projects RTA2012-00062-C04-01, RTA2012-00062-C04-03 and RTA2013-00043-C02 with the support of FEDER funds and by the Conselleria d' Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana, through the project AICO/2015/122. Sandra Munera thanks INIA for the grant FPI-INIA #43 (CPR2014-0082) partially supported by FSE funds.ElsevierDepartamento de Tecnología de AlimentosDepartamento de Ingeniería GráficaInstituto Universitario de Ingeniería de Alimentos (FoodUPV)Escuela Técnica Superior de Ingeniería IndustrialEscuela Técnica Superior de Ingeniería Agronómica y del Medio NaturalGrupo de Investigación e Innovación AlimentariaGeneralitat ValencianaMinisterio de Economía y CompetitividadRepositorio Institucional de la Universitat Politècnica de València Riunet20172017-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/100335reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengGeneralitat Valenciana https://doi.org/10.13039/501100003359 AICO%2F2015%2F122 INCORPORACION DE NUEVAS TECNOLOGIAS OPTICAS NO DESTRUCTIVAS PARA EVALUAR LA CALIDAD Y SEGURIDAD ALIMENTARIA DE FRUTASMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 RTA2012-00062-C04-03 Nuevas técnicas de inspección basadas en visión por computador multiespectral para la estimación de propiedades y determinación automática de la calidad y sanidad de la producción agroalimentaria en líneas de inspección y manipulación (VIS-DACSA)open accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1003352026-06-13T07:49:27Z
dc.title.none.fl_str_mv Astringency assessment of persimmon by hyperspectral imaging
title Astringency assessment of persimmon by hyperspectral imaging
spellingShingle Astringency assessment of persimmon by hyperspectral imaging
Munera Picazo, Sandra Maria
Diospyros kaki
Fruit internal quality
Soluble tannins
Distribution map
Hyperspectral imaging
Computer vision
EXPRESION GRAFICA EN LA INGENIERIA
TECNOLOGIA DE ALIMENTOS
title_short Astringency assessment of persimmon by hyperspectral imaging
title_full Astringency assessment of persimmon by hyperspectral imaging
title_fullStr Astringency assessment of persimmon by hyperspectral imaging
title_full_unstemmed Astringency assessment of persimmon by hyperspectral imaging
title_sort Astringency assessment of persimmon by hyperspectral imaging
dc.creator.none.fl_str_mv Munera Picazo, Sandra Maria
Besada Ferreiro, Cristina María
Blasco Ivars, José
Cubero-García, Sergio
Salvador, Alejandra
Talens Oliag, Pau|||0000-0001-7318-3336
Aleixos Borrás, María Nuria|||0000-0001-6051-3375
author Munera Picazo, Sandra Maria
author_facet Munera Picazo, Sandra Maria
Besada Ferreiro, Cristina María
Blasco Ivars, José
Cubero-García, Sergio
Salvador, Alejandra
Talens Oliag, Pau|||0000-0001-7318-3336
Aleixos Borrás, María Nuria|||0000-0001-6051-3375
author_role author
author2 Besada Ferreiro, Cristina María
Blasco Ivars, José
Cubero-García, Sergio
Salvador, Alejandra
Talens Oliag, Pau|||0000-0001-7318-3336
Aleixos Borrás, María Nuria|||0000-0001-6051-3375
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Tecnología de Alimentos
Departamento de Ingeniería Gráfica
Instituto Universitario de Ingeniería de Alimentos (FoodUPV)
Escuela Técnica Superior de Ingeniería Industrial
Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural
Grupo de Investigación e Innovación Alimentaria
Generalitat Valenciana
Ministerio de Economía y Competitividad
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Diospyros kaki
Fruit internal quality
Soluble tannins
Distribution map
Hyperspectral imaging
Computer vision
EXPRESION GRAFICA EN LA INGENIERIA
TECNOLOGIA DE ALIMENTOS
topic Diospyros kaki
Fruit internal quality
Soluble tannins
Distribution map
Hyperspectral imaging
Computer vision
EXPRESION GRAFICA EN LA INGENIERIA
TECNOLOGIA DE ALIMENTOS
description [EN] One of the current challenges of persimmon postharvest research is the development of non-destructive methods that allow determination of the internal properties of the fruit, such as maturity, flesh firmness and astringency. This study evaluates the usefulness of hyperspectral imaging in the 460 1020 nm range as a non-destructive tool to achieve these aims in Persimmon cv. Rojo Brillante which is an astringent cultivar. Fruit were harvested at three different stages of commercial maturity and exposed to different treatments of CO2 (95% CO2 20 ºC from 0 to 24 h) in order to obtain fruit with different levels of astringency. Partial Least Square (PLS) based methods were used to classify persimmon fruits by maturity and to predict flesh firmness from the average spectrum of each fruit. The results showed a 97.9% rate of correct maturity classification and an R2P of 0.80 for firmness prediction with only five selected wavelengths. For astringency assessment, as our results showed that the soluble tannins that remain after CO2 treatments are distributed irregularly inside the flesh, a model based on PLS was built using the spectrum of every pixel in the fruit. The model obtained an R2P of 0.91 which allowed the creation of the predicted distribution maps of the tannins in the flesh of the fruit, thereby pointing to hyperspectral systems as a promising technology to assess the effectiveness of the deastringency treatments that are usually applied before commercialising persimmons from astringent cultivars.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/100335
url https://riunet.upv.es/handle/10251/100335
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Generalitat Valenciana https://doi.org/10.13039/501100003359 AICO%2F2015%2F122 INCORPORACION DE NUEVAS TECNOLOGIAS OPTICAS NO DESTRUCTIVAS PARA EVALUAR LA CALIDAD Y SEGURIDAD ALIMENTARIA DE FRUTAS
Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 RTA2012-00062-C04-03 Nuevas técnicas de inspección basadas en visión por computador multiespectral para la estimación de propiedades y determinación automática de la calidad y sanidad de la producción agroalimentaria en líneas de inspección y manipulación (VIS-DACSA)
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
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:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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