Assessment of macadamia kernel quality defects by means of near infrared spectroscopy (NIRS) and nuclear magnetic resonance (NMR)

dc.contributor.authorCarvalho, Lívia Cirino de [UNESP]
dc.contributor.authorMorais, Camilo de Lelis Medeiros de
dc.contributor.authorLima, Kássio Michell Gomes de
dc.contributor.authorTeixeira, Gustavo Henrique de Almeida [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionSchool of Pharmacy and Biomedical Sciences
dc.contributor.institutionQuímica Biológica e Quimiometria
dc.date.accessioned2019-10-06T16:36:39Z
dc.date.available2019-10-06T16:36:39Z
dc.date.issued2019-12-01
dc.description.abstractMacadamia kernels are visually sorted based on the presence of quality defects by specialized labors. However, this process is not as accurate as non-destructive methods such as near infrared spectroscopy (NIRS) and nuclear magnetic resonance (NMR). Thus, NIRS and NMR in combination with chemometrics have become established non-destructive method for rapid assessment of quality parameters in the food and agricultural sectors. Therefore, the quality of macadamia kernel was assessed by NIRS and NMR using chemometric tools such as PCA-LDA and GA-LDA to evaluate external kernel defects. Macadamia kernels were classified as: 1 = good, marketable kernels without defects; 2 = kernels with discoloration; 3 = immature kernels; 4 = kernels affected by mold; and 5 = kernels with insect damage. Using NIRS, the GA-LDA resulted in an accuracy and specificity of 97.8% and 100%, respectively, to classify good kernels. On the other hand, PCA-LDA technique resulting in an accuracy higher than 68% and specificity of 97.2% to classify immature kernels. For NMR, PCA-LDA resulted in an accuracy higher than 83% and GA-LDA resulted in an accuracy of 100%, both to classify kernels with insect damage. NIRS and NMR spectroscopy can be successfully used to classify unshelled macadamia kernels based on the defects. However, NIRS out-performed NMR based on the higher accuracy results.en
dc.description.affiliationUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Farmacêuticas (FCFAR) Departamento de Alimentos e Nutrição Campus de Araraquara, Rodovia Araraquara-Jaú, km 1 – CP 502, São Paulo
dc.description.affiliationUniversity of Central Lancashire School of Pharmacy and Biomedical Sciences
dc.description.affiliationUniversidade Federal do Rio Grande do Norte (UFRN) Instituto de Química Química Biológica e Quimiometria, Avenida Senador Salgado Filho, n° 3000, Bairro de Lagoa Nova
dc.description.affiliationUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Agrárias e Veterinárias (FCAV) Campus de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/n, São Paulo
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Farmacêuticas (FCFAR) Departamento de Alimentos e Nutrição Campus de Araraquara, Rodovia Araraquara-Jaú, km 1 – CP 502, São Paulo
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Agrárias e Veterinárias (FCAV) Campus de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/n, São Paulo
dc.identifierhttp://dx.doi.org/10.1016/j.foodcont.2019.06.021
dc.identifier.citationFood Control, v. 106.
dc.identifier.doi10.1016/j.foodcont.2019.06.021
dc.identifier.issn0956-7135
dc.identifier.scopus2-s2.0-85067804634
dc.identifier.urihttp://hdl.handle.net/11449/189311
dc.language.isoeng
dc.relation.ispartofFood Control
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectChemometrics
dc.subjectGA-LDA
dc.subjectMacadamia integrifolia maiden & betche
dc.subjectPCA-LDA
dc.subjectTD–NMR
dc.titleAssessment of macadamia kernel quality defects by means of near infrared spectroscopy (NIRS) and nuclear magnetic resonance (NMR)en
dc.typeArtigo

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