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Determination of the most effective wavelengths for prediction of Fuji Apple starch and total soluble solids properties

2020Journal article Open access
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dc.contributor.authorPourdarbani, Razieh
dc.contributor.authorSabzi, Sajad
dc.contributor.authorJarolmasjed, Sanaz
dc.contributor.authorPanagopoulos, Thomas
dc.date.accessioned2020-12-17T10:26:36Z
dc.date.available2020-12-17T10:26:36Z
dc.date.issued2020
dc.description.abstractProper physical properties and standard chemical properties are among the criteria that consumers use to select fruits. Recently, researchers attempted to develop non-destructive methods for measuring properties, among which the near-infrared (NIR) spectroscopy is of great use. Fuji apples were collected in three di erent growth stages, and then starch and soluble solids were extracted. Spectral data in the range of 800 to 900 nm were used to predict the amount of starch content and 920 to 980 nm to estimate total soluble solids (TSS). Reflectance spectra were pre-processed and the most e ective wavelengths of each property were selected using hybrid artificial neural network-simulated annealing (ANN-SA). Non-destructive estimation of physicochemical properties was conducted using spectral data of the most e ective wavelengths using a hybrid artificial neural network-biogeography-based optimization algorithm (ANN-BBO). The results indicated that the regression coe cient of the best state of training for predicting starch was 0.97 and of TSS was 0.96, while R2 was 0.92 for both. The most e ective wavelengths were 852.58, 855.54, 849.03, 855.83, 853.47, 844.90 nm for starch and 967.86, 966.67, 964.90, 958.40, 957.22, 963.97 nm for TSS.pt_PT
dc.description.sponsorshipFEDER ALG-01-0247-FEDER-037303; AGNETICS funded the APCpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/app10228145pt_PT
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10400.1/14917
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBiogeography-based optimization algorithmpt_PT
dc.subjectFruit propertiespt_PT
dc.subjectNon-destructive methodpt_PT
dc.subjectStarchpt_PT
dc.subjectTotal soluble solidspt_PT
dc.titleDetermination of the most effective wavelengths for prediction of Fuji Apple starch and total soluble solids propertiespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue22pt_PT
oaire.citation.startPage8145pt_PT
oaire.citation.titleApplied Sciencespt_PT
oaire.citation.volume10pt_PT
person.familyNamePanagopoulos
person.givenNameThomas
person.identifierR-000-K9N
person.identifier.ciencia-id411D-5652-57A8
person.identifier.orcid0000-0002-8073-2097
person.identifier.ridA-3048-2012
person.identifier.scopus-author-id9736690000
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication3dfd5be1-8e22-4dda-bd34-f3b1e5f249e2
relation.isAuthorOfPublication.latestForDiscovery3dfd5be1-8e22-4dda-bd34-f3b1e5f249e2

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