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Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images

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Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images

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Ivorra Martínez, E.; Sánchez Salmerón, AJ.; Verdú Amat, S.; Barat Baviera, JM.; Grau Meló, R. (2016). Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images. Journal of Food Engineering. 178:110-116. doi:10.1016/j.jfoodeng.2016.01.008

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/82187

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Title: Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments
Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny
Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural
Issued date:
Abstract:
Ready-to-eat foods that does not receive a heat treatment before being consumed can be at risk of foodborne hazards and spoilage, so it would be of great interest to have a method for monitoring their safety. This work ...[+]
Subjects: Hyperspectral imaging , Tissue segmentation , SW-NIR , Fish shelf life , Smoked salmon , SVM
Copyrigths: Reserva de todos los derechos
Source:
Journal of Food Engineering. (issn: 0260-8774 ) (eissn: 1873-5770 )
DOI: 10.1016/j.jfoodeng.2016.01.008
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.jfoodeng.2016.01.008
Thanks:
This work has been partially funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA - Spanish National Institute for Agriculture and Food Research and Technology) through ...[+]
Type: Artículo

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