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Astringency assessment of persimmon by hyperspectral imaging

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Astringency assessment of persimmon by hyperspectral imaging

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dc.contributor.author Munera Picazo, Sandra Maria es_ES
dc.contributor.author Besada Ferreiro, Cristina María es_ES
dc.contributor.author Blasco Ivars, José es_ES
dc.contributor.author Cubero-García, Sergio es_ES
dc.contributor.author Salvador, Alejandra es_ES
dc.contributor.author Talens Oliag, Pau es_ES
dc.contributor.author Aleixos Borrás, María Nuria es_ES
dc.date.accessioned 2018-04-13T04:15:51Z
dc.date.available 2018-04-13T04:15:51Z
dc.date.issued 2017 es_ES
dc.identifier.issn 0925-5214 es_ES
dc.identifier.uri http://hdl.handle.net/10251/100335
dc.description.abstract [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. es_ES
dc.description.sponsorship 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. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation GENERALITAT VALENCIANA/AICO/2015/122 es_ES
dc.relation INST NAC DE INV. Y TECNOL. AGRARIA Y ALIMENT/RTA2012-00062-C04-03 es_ES
dc.relation.ispartof Postharvest Biology and Technology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Diospyros kaki es_ES
dc.subject Fruit internal quality es_ES
dc.subject Soluble tannins es_ES
dc.subject Distribution map es_ES
dc.subject Hyperspectral imaging es_ES
dc.subject Computer vision es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.title Astringency assessment of persimmon by hyperspectral imaging es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.postharvbio.2016.11.006 es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2019-03-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.postharvbio.2016.11.006 es_ES
dc.description.upvformatpinicio 35 es_ES
dc.description.upvformatpfin 41 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 125 es_ES
dc.relation.pasarela S\320366 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria es_ES


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