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Detection of adulterations with different grains in wheat products based on the hyperspectral image technique: The specific cases of flour and bread

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Detection of adulterations with different grains in wheat products based on the hyperspectral image technique: The specific cases of flour and bread

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dc.contributor.author Verdú Amat, Samuel es_ES
dc.contributor.author Vásquez, Francisco es_ES
dc.contributor.author Grau Meló, Raúl es_ES
dc.contributor.author Ivorra Martínez, Eugenio es_ES
dc.contributor.author Sánchez Salmerón, Antonio José es_ES
dc.contributor.author Barat Baviera, José Manuel es_ES
dc.date.accessioned 2017-12-11T10:34:57Z
dc.date.available 2017-12-11T10:34:57Z
dc.date.issued 2016 es_ES
dc.identifier.issn 0956-7135 es_ES
dc.identifier.uri http://hdl.handle.net/10251/92323
dc.description.abstract [EN] The objective of this study was to test the capability of a SW-NIR hyperspectral image technique to detect adulterations in wheat flour and bread with cheap grains, such us sorghum, oats and corn, and to compare the hyperspectral information with the physicochemical alterations in the properties of products. Wheat flour was adulterated at four different degrees (2.5, 5, 7.5 and 10%) with sorghum, oat and corn flours. Flours were prepared and used to make bread. Flours and breads were characterized according to several physicochemical parameters (pasting properties, water activity, mass loss during the baking process and texture profile analysis). Crumbs were extracted from breads and conditioned. Hyperspectral image captures were taken of both flours and conditioned crumbs. The data analysis was based on multivariate statistical process control method (MSPC), where the differentiation of adulterated samples was observed in all cases for both flours and crumbs. Finally, in order to relate the image analysis results and the adulterated sample properties, a correlation significance map was created between the physicochemical properties of samples and the multivariate statistical parameters. The SW-NIR image technique was capable of detecting adulterations in each case and high correlation significances were observed (alpha = 0.01) between wavelengths from specific spectra zones and the physicochemical properties of samples. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Food Control es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Bread es_ES
dc.subject Adulteration es_ES
dc.subject Image analysis es_ES
dc.subject MSPC es_ES
dc.subject Hyperspectral es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.subject.classification TECNOLOGIA DE ALIMENTOS es_ES
dc.title Detection of adulterations with different grains in wheat products based on the hyperspectral image technique: The specific cases of flour and bread es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.foodcont.2015.11.002 es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 0999-01-01 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 de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Verdú Amat, S.; Vásquez, F.; Grau Meló, R.; Ivorra Martínez, E.; Sánchez Salmerón, AJ.; Barat Baviera, JM. (2016). Detection of adulterations with different grains in wheat products based on the hyperspectral image technique: The specific cases of flour and bread. Food Control. 62:373-380. https://doi.org/10.1016/j.foodcont.2015.11.002 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1016/j.foodcont.2015.11.002 es_ES
dc.description.upvformatpinicio 373 es_ES
dc.description.upvformatpfin 380 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 62 es_ES
dc.relation.pasarela S\302278 es_ES


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