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dc.contributor.authorFemenias, Antoni
dc.contributor.authorGatius Cortiella, Ferran
dc.contributor.authorRamos Girona, Antonio J.
dc.contributor.authorSanchís Almenar, Vicente
dc.contributor.authorMarín Sillué, Sònia
dc.date.accessioned2020-01-20T11:39:54Z
dc.date.available2020-08-20T22:21:51Z
dc.date.issued2019-08-20
dc.identifier.issn0956-7135
dc.identifier.urihttp://hdl.handle.net/10459.1/67826
dc.description.abstractHyperspectral imaging (HSI) is an emergent, rapid, cost-effective and non-destructive technique in which the spectral data are obtained for each pixel location in a sample's image. The application of this technique to assess mycotoxins and mycotoxigenic fungi in cereals is considered promising to replace time-consuming wet-chem- istry methods and for its potential grain sorting ability, in order to reduce food and feed contamination and the associated toxic effects in human and animals. Fusarium is a plant pathogen and deoxynivalenol (DON)-producer which presents high incidence in cereals such as wheat, maize and barley. The following review encompasses detailed information about the HSI principle and an updated outlook of its applications in the detection and quantification of Fusarium and DON in cereals. Moreover, HSI prediction algorithms for DON quantification are novel approaches which present high complexity owed to the asymptomatic nature of the grain despite of high mycotoxin concentrations. The spatial faculty of this system may be able to overcome the contamination het- erogeneity of the grain for its elimination, enhancing risk management and rising the economic performance. Additionally, HSI is also proposed as a powerful grain sorting instrument due to high accuracies obtained in classification of single kernels according to Fusarium and DON infection. Therefore, an overview of the HSI applications for on-line and massive cereal sorting in grain industry is also presented.
dc.description.sponsorshipThe authors are grateful to the University of Lleida (predoctoral grant), and to the Spanish Ministry of Science, Innovation and Universities (Project AGL2017-87755-R) for funding this work.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relationMINECO/PN2013-2016/AGL2017-87755-R
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1016/j.foodcont.2019.106819
dc.relation.ispartofFood Control, 2020, vol. 108, article number 106819
dc.rightscc-by-nc-nd (c) Elsevier, 2020
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es
dc.subjectHyperspectral imaging
dc.subjectNear infrared
dc.subjectDeoxynivalenol
dc.subjectCereal sorting
dc.titleUse of hyperspectral imaging as a tool for Fusarium and deoxynivalenol risk management in cereals: A review
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2020-01-20T11:39:54Z
dc.identifier.idgrec029401
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1016/j.foodcont.2019.106819


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cc-by-nc-nd (c) Elsevier, 2020
Except where otherwise noted, this item's license is described as cc-by-nc-nd (c) Elsevier, 2020