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dc.contributor.authorMunera, Sandra
dc.contributor.authorRodríguez-Ortega, Alejandro
dc.contributor.authorAleixos, Nuria
dc.contributor.authorCubero, Sergio
dc.contributor.authorGómez-Sanchís, Juan
dc.contributor.authorBlasco, José
dc.date.accessioned2021-09-23T16:22:30Z
dc.date.available2021-09-23T16:22:30Z
dc.date.issued2021es
dc.identifier.citationMunera, S., Rodríguez-Ortega, A., Aleixos, N., Cubero, S., Gómez-Sanchis, J. & Blasco, J. (2021). Detection of Invisible Damages in ‘Rojo Brillante’Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics. Foods, 10(9), 2170.es
dc.identifier.issn2304-8158
dc.identifier.urihttp://hdl.handle.net/20.500.11939/7618
dc.description.abstractThe main cause of flesh browning in ‘Rojo Brillante’ persimmon fruit is mechanical damage caused during harvesting and packing. Innovation and research on nondestructive techniques to detect this phenomenon in the packing lines are necessary because this type of alteration is often only seen when the final consumer peels the fruit. In this work, we have studied the application of hyperspectral imaging in the range of 450–1040 nm to detect mechanical damage without any external symptoms. The fruit was damaged in a controlled manner. Later, images were acquired before and at 0, 1, 2 and 3 days after damage induction. First, the spectral data captured from the images were analysed through an algorithm based on principal component analysis (PCA). The aim was to automatically separate intact and damaged fruit, and to detect the damage in the PC images when present. With this algorithm, 90.0% of intact fruit and 90.8% of damaged fruit were correctly detected. A model based on partial least squares—discriminant analysis (PLS-DA), was later calibrated using the mean spectrum of the pixels detected as damaged, to determine the moment when the fruit was damaged. The model differentiated fruit corresponding correctly to 0, 1, 2 and 3 days after damage induction, achieving a total accuracy of 99.4%.es
dc.language.isoenes
dc.publisherMDPIes
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectFruit qualityes
dc.subjectNondestructivees
dc.subjectChemometricses
dc.titleDetection of Invisible Damages in ‘Rojo Brillante’ Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometricses
dc.typearticlees
dc.authorAddressblasco_josiva@gva.eses
dc.entidadIVIACentro de Agroingenieríaes
dc.identifier.doi10.3390/foods10092170es
dc.identifier.urlhttps://www.mdpi.com/2304-8158/10/9/2170es
dc.journal.issueNumber9es
dc.journal.titleFoodses
dc.journal.volumeNumber10es
dc.page.final2170es
dc.page.initial2170es
dc.relation.projectIDThis work is co-funded by the projects AEI PID2019-107347RR-C31, PID2019-107347RRC32, PID2019-107347RR-C33, IVIA-GVA 51918 and the European Union through the European Regional Development Fund (ERDF) of the Generalitat Valenciana 2014–2020.es
dc.rights.accessRightsopenAccesses
dc.source.typeelectronicoes
dc.subject.agrisN01 Agricultural engineeringes
dc.subject.agrisH20 Plant diseaseses
dc.subject.agrisH50 Miscellaneous plant disorderses
dc.subject.agrisQ01 Food science and technologyes
dc.subject.agrisQ02 Food processing and preservationes
dc.subject.agrovocDiospyros kakies
dc.subject.agrovocBrowninges
dc.subject.agrovocComputer visiones
dc.type.hasVersionpublishedVersiones


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Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España