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Non-destructive follow-up of ‘Jintao’ kiwifruit ripening through VIS-NIR spectroscopy – individual vs. average calibration model’s predictions

2022Journal article Open access
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dc.contributor.authorAfonso, Andreia M.
dc.contributor.authorAntunes, Maria Dulce
dc.contributor.authorCruz, Sandra
dc.contributor.authorCavaco, A. M.
dc.contributor.authorGuerra, Rui Manuel Farinha das Neves
dc.date.accessioned2022-11-02T14:26:41Z
dc.date.available2022-11-02T14:26:41Z
dc.date.issued2022
dc.description.abstractVisible/near infrared spectroscopy (Vis-NIRS) was used to monitor the yellow-fleshed kiwifruit (Actinidia chinensis Planch 'Jintao') ripening on two selected orchards along 13 weeks, from pre-harvest to the late harvest. Calibration models for several Internal Quality Attibutes (IQA) were built from the spectral data of 375 individual kiwifruit. The analyzed IQA were L*, a* and b* from the CIELAB color space, hue angle, chroma, firmness, dry matter (DM), soluble solids content (SSC), juice pH and titratable acidity (TA). Different pre-processing methods were tested for the construction of PLS calibration models. SSC and Hue were the best performing models with a correlation coefficient of 0.81 and 0.88, and root mean square error of prediction (RMSEP) of 1.27% and 1.95 degrees, respectively. The interpretation of the models in terms of the known absorption bands and the impact of signal to noise ratio (SNR) in them is discussed. The calibration models were used to perform average predictions of the IQA on orchard subareas, for each day of the experiment. These average predictions were compared with the IQA's average reference values on the same subareas and days. The model's metrics improved significantly through the averaging procedure, with RMSEP = 0.26-0.36% and R-2 = 0.99 for SSC; and RMSEP = 0.42 degrees - 0.56 degrees and R-2 = 1 for Hue. Since orchard management is done essentially through averages and not individual values, this result reinforces the applicability of the NIR technology for follow-up of fruit ripening in the tree.pt_PT
dc.description.sponsorshipALG-01-0247-FEDER-037303; ALG-01-0247-FEDER-033652
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.postharvbio.2022.111895pt_PT
dc.identifier.issn0925-5214
dc.identifier.urihttp://hdl.handle.net/10400.1/18468
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationNon-invasive monitoring of kiwifruit ripening
dc.relationCenter for Electronics, Optoelectronics and Telecommunications
dc.relationCenter for Electronics, Optoelectronics and Telecommunications
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectNoninvasivept_PT
dc.subjectInternal qualitypt_PT
dc.subjectOptimal harvest datept_PT
dc.subjectSignal-to-noise ratiopt_PT
dc.subjectFlesh colorpt_PT
dc.subjectSoluble solids contentpt_PT
dc.titleNon-destructive follow-up of ‘Jintao’ kiwifruit ripening through VIS-NIR spectroscopy – individual vs. average calibration model’s predictionspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleNon-invasive monitoring of kiwifruit ripening
oaire.awardTitleCenter for Electronics, Optoelectronics and Telecommunications
oaire.awardTitleCenter for Electronics, Optoelectronics and Telecommunications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/OE/SFRH%2FBD%2F131462%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00631%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00631%2F2020/PT
oaire.citation.startPage111895pt_PT
oaire.citation.titlePostharvest Biology and Technologypt_PT
oaire.citation.volume188pt_PT
oaire.fundingStreamOE
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameGuedes da Silva Afonso
person.familyNameAntunes
person.familyNameCruz
person.familyNameCavaco Guerra
person.familyNameGuerra
person.givenNameAndreia Melissa
person.givenNameMaria Dulce
person.givenNameSandra P.
person.givenNameAna Margarida
person.givenNameRui
person.identifier177556
person.identifier2123697
person.identifierC-1285-2012
person.identifier.ciencia-id4712-0B78-4A48
person.identifier.ciencia-idC11B-9B05-217E
person.identifier.ciencia-id1513-2781-23A3
person.identifier.ciencia-idC91E-B434-E327
person.identifier.ciencia-id3D16-5067-D6BB
person.identifier.orcid0000-0002-8913-6136
person.identifier.orcid0000-0001-5909-3684
person.identifier.orcid0000-0003-2708-5991
person.identifier.orcid0000-0002-8642-5792
person.identifier.ridA-4683-2012
person.identifier.ridIXN-8734-2023
person.identifier.scopus-author-id7102645075
person.identifier.scopus-author-id57214582876
person.identifier.scopus-author-id6602899707
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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