Hyperspectral imaging for the classification of individual cereal kernels according to fungal and mycotoxins contamination: A review

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dc.contributor.authorFemenias, Antoni
dc.contributor.authorGatius, Ferran
dc.contributor.authorRamos Girona, Antonio J.
dc.contributor.authorTeixido Orries, Irene
dc.contributor.authorMarín Sillué, Sònia
dc.date.accessioned2022-05-13T08:30:27Z
dc.date.available2022-05-13T08:30:27Z
dc.date.issued2022
dc.description.abstractOne of the most common concerns in the cereal industry is the presence of fungi and their associated mycotoxins. Hyperspectral Imaging (HSI) has been proposed recently as one of the most potent tools to manage fungal associated contamination. The introduction of a spatial dimension to the spectral analysis allows the selection of the specific regions of the sample for further screening. Single kernel analysis would enable the discrimination of the highly contaminated kernels to establish a mitigation strategy, overcoming the contamination heterogeneity of cereal batches. This document is a detailed review of the HSI recently published studies that aimed to discriminate fungi and mycotoxin contaminated single cereal kernels. The most relevant findings showed that fungal infection and mycotoxins levels discrimination accuracies were above 90% and 80%, respectively. The results indicate that NIR-HSI is suitable for the detection of fungal-related contamination in single kernels and it has potential to be applied at food industry stages.ca_ES
dc.description.sponsorshipThis work was supported by Project AGL2017-87755-R funded by MCIN/ AEI /10.13039/501100011033/ FEDER ?Una manera de hacer Europa? and project PID2020-114836RB-I00 funded by MCIN/ AEI /10.13039/501100011033. The authors are grateful to the University of Lleida (predoctoral grant).ca_ES
dc.identifier.doihttps://doi.org/10.1016/j.foodres.2022.111102
dc.identifier.idgrec032530
dc.identifier.issn0963-9969
dc.identifier.urihttp://hdl.handle.net/10459.1/83276
dc.language.isoengca_ES
dc.publisherElsevierca_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114836RB-I00/ES/ESTRATEGIAS DE MITIGACION DE LA CONTAMINACION POR DEOXINIVALENOL Y FUMONISINAS EN ALIMENTOS A BASE DE MAIZ Y AVENA/
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2017-87755-R/ES/TECNICAS DE SELECCION Y PROCESADO DE CEREALES, Y SU IMPACTO EN LA CONTAMINACION POR DEOXINIVALENOL EN ALIMENTOS INFANTILES/Sa
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.1016/j.foodres.2022.111102ca_ES
dc.relation.ispartofFood Research International, 2022, vol. 155, núm. 111102, p. 1-12ca_ES
dc.rightscc-by (c) Femenias et. al., 2022ca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectCereal sortingca_ES
dc.subjectMycotoxinsca_ES
dc.subjectFungal infectionsca_ES
dc.subjectHyperspectral imagingca_ES
dc.subjectSingle-kernel analysisca_ES
dc.subject.otherFongs fitopatògensca_ES
dc.subject.otherFongs en l'agriculturaca_ES
dc.titleHyperspectral imaging for the classification of individual cereal kernels according to fungal and mycotoxins contamination: A reviewca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_ES
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