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dc.contributor.authorFemenias, Antoni
dc.contributor.authorLlorens-Serentill, Enric.
dc.contributor.authorRamos Girona, Antonio J.
dc.contributor.authorSanchís Almenar, Vicente
dc.contributor.authorMarín Sillué, Sònia
dc.date.accessioned2022-09-26T10:48:13Z
dc.date.available2022-09-26T10:48:13Z
dc.date.issued2022-07-19
dc.identifier.issn0956-7135
dc.identifier.urihttp://hdl.handle.net/10459.1/83866
dc.description.abstractFusarium is a DON producing filamentous fungi which commonly infects small grain cereals. Near-Infrared Hyperspectral Imaging (HSI-NIR) is considered for its potential to manage this contamination, as it uses spatial recognition, which may be able to deal with the heterogeneity inside the batches for cereal sorting implementation. The focus of this study was the application of HSI-NIR for Fusarium Damaged Kernels (FDK) detection and DON prediction and discrimination of wheat kernels over EU limits. After the HSI scanning of 300 individual grains, the reference values were obtained attributing categories for typical fungal symptoms and analyzing DON from individual grains by HPLC. Several spectral preprocessing methods selected valuable information before model calibration. Externally validated PLS predictions showed RMSEP of 6.65 mg/kg, an R2 of 0.88 and an RPD of 3.21. However, the classification models managed wheat contaminations more appropriately, obtaining discrimination accuracies of 85.8% and 76.9% for fungal symptoms and DON at the EU limit, respectively. These findings suggest that HSI-NIR can be a suitable tool to sort DON contaminated kernels at EU limits.
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).
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
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/
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.relation.isformatofReproducció del document publicat a: https://doi.org/10.1016/j.foodcont.2022.109239
dc.relation.ispartofFood Control, 2022, vol. 142, núm. 109239
dc.rightscc-by (c) Femenias et al., 2022
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectFusarium
dc.subjectFood safety
dc.subjectFungi
dc.subjectPrediction
dc.subjectWheat
dc.titleNear-infrared hyperspectral imaging evaluation of Fusarium damage and DON in single wheat kernels
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2022-09-26T10:48:13Z
dc.identifier.idgrec032625
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.type.versionpublishedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1016/j.foodcont.2022.109239


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cc-by (c) Femenias et al., 2022
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