Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/46970
DC FieldValueLanguage
dc.contributor.authorMoscetti, Robertoit
dc.contributor.authorBerhe, Daniel Hagosit
dc.contributor.authorAgrimi, Mariagraziait
dc.contributor.authorHaff, Ron P.it
dc.contributor.authorLiang, Peishihit
dc.contributor.authorFerri, Serenait
dc.contributor.authorMonarca, Daniloit
dc.contributor.authorMassantini, Riccardoit
dc.date.accessioned2022-02-28T13:39:03Z-
dc.date.available2022-02-28T13:39:03Z-
dc.date.issued2021it
dc.identifier.issn0260-8774it
dc.identifier.urihttp://hdl.handle.net/2067/46970-
dc.description.abstractNIR spectroscopy and physical properties derived from image analysis were evaluated as potential features for the classification of seed kernels from two pine nut species (P. pinea L. and P. sibirica Du Tour) using Partial Least Squares Discriminant Analysis (PLS-DA). Model performances were evaluated in terms of specificity, sensitivity and accuracy. Data pre-treatments were essential for achieving excellent performances (accuracy rate > 95%) in all tests. The interval PLS-DA highlighted that the most important features for (1) the NIR method were the absorption bands at 1640–1658, 1720–1738 and 1880–1998 nm, while for (2) the image analysis were kernel eccentricity, kernel major axis length, kernel lightness (L*) and kernel perimeter. The results demonstrate potential of both techniques for discriminating the two pine nut species.it
dc.language.isoengit
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titlePine nut species recognition using NIR spectroscopy and image analysisit
dc.typearticle*
dc.identifier.doi10.1016/j.jfoodeng.2020.110357it
dc.identifier.scopus2-s2.0-85091341416it
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85091341416it
dc.relation.journalJOURNAL OF FOOD ENGINEERINGit
dc.relation.firstpage110357it
dc.relation.volume292it
dc.subject.scientificsectorAGR09; AGR15it
dc.description.numberofauthors8it
dc.contributor.countryUSAit
dc.type.miur262*
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairetypearticle-
item.cerifentitytypePublications-
crisitem.journal.journalissn0260-8774-
crisitem.journal.anceE091846-
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