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dc.contributor.authorMunera, Sandra
dc.contributor.authorBesada, Cristina
dc.contributor.authorAleixos, Nuria
dc.contributor.authorTalens, Pau
dc.contributor.authorSalvador, Alejandra
dc.contributor.authorSun, Da-Wen
dc.contributor.authorCubero, Sergio
dc.contributor.authorBlasco, José
dc.date.accessioned2017-08-04T12:33:54Z
dc.date.available2017-08-04T12:33:54Z
dc.date.issued2017es
dc.identifier.citationMunera S, Besada C, Aleixos N, Talens P, Salvador A, Sun, D-W, Cubero C, Blasco J (2017) Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging. LWT - Food Science and Technology, 77C, 241-248.es
dc.identifier.urihttp://hdl.handle.net/20.500.11939/5726
dc.description.abstractThe internal quality of intact persimmon cv. ‘Rojo Brillante’ was assessed trough visible and near infrared hyperspectral imaging. Fruits at three stages of commercial maturity were exposed to different treatments with CO2 to obtain fruit with different ripeness and level of astringency (soluble tannin content). Spectral and spatial information were used for building classification models to predict ripeness and astringency trough multivariate analysis techniques like linear and quadratic discriminant analysis (LDA and QDA) and support vector machine (SVM). Additionally, flesh firmness was predicted by partial least square regression (PLSR). The full spectrum was used to determine the internal properties and later principal component analysis (PCA) was used to select optimal wavelengths (580, 680 and 1050 nm). The correct classification was above 92% for the three classifiers in the case of ripeness and 95% for QDA in the case of astringency. A value of R2 = 0.80 and a ratio of prediction deviation (RPD) of 1.86 were obtained with the selected wavelengths for the prediction of firmness which demonstrated the potential of hyperspectral imaging as a non-destructive tool in the assessment of the firmness, ripeness state and astringency level of ‘Rojo Brillante’ persimmon.es
dc.language.isoenes
dc.publisherElsevieres
dc.subjectDiospyros kaki, internal fruit quality, soluble tannins, astringency, classification, computer vision.es
dc.titleNon-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaginges
dc.typearticlees
dc.entidadIVIACentro de Agroingenieríaes
dc.identifier.doi10.1016/j.lwt.2016.11.063.es
dc.identifier.urlhttp://www.sciencedirect.com/science/article/pii/S0023643816307344es
dc.journal.issueNumber1es
dc.journal.titleLWT - Food Science and Technologyes
dc.journal.volumeNumber77Ces
dc.page.final248es
dc.page.initial241es
dc.relation.projectIDNon-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaginges
dc.subject.agrisJ11 Handling, transport, storage and protection of plant productses
dc.subject.agrovocDiospyros kakies
dc.subject.agrovocFood qualityes
dc.subject.agrovocImage analysises


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