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Ripening assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) on tree by SW-NIR reflectance spectroscopy-based calibration models

2022-01Journal article Open Access
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dc.contributor.authorPires, Rosa
dc.contributor.authorGuerra, Rui Manuel Farinha das Neves
dc.contributor.authorCruz, Sandra
dc.contributor.authorAntunes, MDC
dc.contributor.authorBrazio, António
dc.contributor.authorAfonso, Andreia M.
dc.contributor.authorDaniel, Mariana
dc.contributor.authorPanagopoulos, Thomas
dc.contributor.authorGonçalves, Isabel
dc.contributor.authorCavaco, Ana M.
dc.date.accessioned2021-11-15T11:19:49Z
dc.date.available2021-11-15T11:19:49Z
dc.date.issued2022-01
dc.description.abstractThe aim of this study was the non-destructive assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) ripening, based on the prediction of internal quality attributes (IQA) by short-wave near-infrared reflectance spectroscopy (SW-NIRS) calibration models. Spectra from fruit of 50 trees located in two different orchards, were acquired on tree using a customized portable visible near-infrared (vis-NIR) system. Partial least squares (PLS) was used to build the various IQA calibration models. The models were tested through internal validation (IV) and external validation (EV). Generally, the IV results were always superior to those of EV: regarding IV, a high regression coefficient (R2) and low root mean square error of prediction (RMSEP) were achieved, revealing a good predictive performance for juice pH (R2 = 0.80; RMSEP = 0.10; SDR = 2.23), soluble solids content (SSC) (R2 = 0.79; RMSEP = 0.75 %; SDR = 2.27), titratable acidity (TA) (R2 = 0.73; RMSEP = 0.24 % citric acid; SDR = 1.94) and the maturation index (MI) (R2 = 0.80; RMSEP = 1.38; SDR = 2.2). The best EV predictions were obtained for TA (R2 = 0.69; RMSEP = 0.38 % citric acid; SDR = 1.24), and MI (R2 = 0.69; RMSEP = 2.07; SDR = 1.49). Calibration models for glucose, fructose and sucrose showed medium-coarse predictions for both validation strategies. A detailed investigation of MI models was performed, to understand the causes of their poor EV results. In the context of EV, model updating strategies were explored by using some validation samples to improve the calibration model. The methods of bias correction and spiking were tested, showing a clear improvement in the predictions.pt_PT
dc.description.sponsorshipALG-01-0247-FEDER-037303
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.postharvbio.2021.111750pt_PT
dc.identifier.eissn1873-2356
dc.identifier.urihttp://hdl.handle.net/10400.1/17326
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationSmart tools for optimizing management in precision agriculture of citrus orchards
dc.relationCenter for Electronics, Optoelectronics and Telecommunications
dc.relationNot Available
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAlgarve Citruspt_PT
dc.subjectRipeningpt_PT
dc.subjectOptimal harvest datept_PT
dc.subjectModel recalibrationpt_PT
dc.subjectMulti-orchardpt_PT
dc.subjectNon-destructivept_PT
dc.titleRipening assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) on tree by SW-NIR reflectance spectroscopy-based calibration modelspt_PT
dc.title.alternativeAvaliação de amadurecimento de 'Ortanique' (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) em árvore por SW-NIR modelos de calibração baseados em espectroscopiapt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleSmart tools for optimizing management in precision agriculture of citrus orchards
oaire.awardTitleCenter for Electronics, Optoelectronics and Telecommunications
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBPD%2F101634%2F2014/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FMulti%2F00631%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMulti%2F00631%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/DL 57%2F2016/DL 57%2F2016%2FCP1361%2FCT0031/PT
oaire.citation.startPage111750pt_PT
oaire.citation.titlePostharvest Biology and Technologypt_PT
oaire.citation.volume183pt_PT
oaire.fundingStream5876
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamDL 57/2016
person.familyNamePires
person.familyNameGuerra
person.familyNameCruz
person.familyNameAntunes
person.familyNameBrazio
person.familyNameDaniel
person.familyNamePanagopoulos
person.familyNameCavaco Guerra
person.givenNameRosa
person.givenNameRui
person.givenNameSandra P.
person.givenNameMaria Dulce
person.givenNameAntónio
person.givenNameMariana
person.givenNameThomas
person.givenNameAna Margarida
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project.funder.identifierhttp://doi.org/10.13039/501100001871
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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
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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