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PLS-R Calibration models for wine spirit volatile phenols pre-diction by near infrared spectroscopy

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dc.contributor.authorAnjos, O.
dc.contributor.authorCaldeira, I.
dc.contributor.authorFernandes, T.A.
dc.contributor.authorPedro, S.I.
dc.contributor.authorVitória, C.
dc.contributor.authorOliveira-Alves, S.
dc.contributor.authorCatarino, S.
dc.contributor.authorCanas, S.
dc.date.accessioned2022-02-03T10:23:41Z
dc.date.available2022-02-03T10:23:41Z
dc.date.issued2022
dc.description.abstractNear-infrared spectroscopic (NIR) technique was used, for the first time, to predict volatile phenols content, namely guaiacol, 4-methyl-guaiacol, eugenol, syringol, 4-methyl-syringol and 4- allyl-syringol, of aged wine spirits (AWS). This study aimed to develop calibration models for the volatile phenol’s quantification in AWS, by NIR, faster and without sample preparation. Partial least square regression (PLS-R) models were developed with NIR spectra in the near-IR region (12,500–4000 cm􀀀1) and those obtained from GC-FID quantification after liquid-liquid extraction. In the PLS-R developed method, cross-validation with 50% of the samples along a validation test set with 50% of the remaining samples. The final calibration was performed with 100% of the data. PLS-R models with a good accuracy were obtained for guaiacol (r2 = 96.34; RPD = 5.23), 4-methyl-guaiacol (r2 = 96.1; RPD = 5.07), eugenol (r2 = 96.06; RPD = 5.04), syringol (r2 = 97.32; RPD = 6.11), 4-methylsyringol (r2 = 95.79; RPD = 4.88) and 4-allyl-syringol (r2 = 95.97; RPD = 4.98). These results reveal that NIR is a valuable technique for the quality control of wine spirits and to predict the volatile phenols content, which contributes to the sensory quality of the spirit beveragespt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAnjos, O.; Caldeira, I.; Fernandes, T.A.; Pedro, S.I.; Vitória, C.; Oliveira-Alves, S.; Catarino, S.; Canas, S. PLS-R Calibration Models forWine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy. Sensors 2022, 22, 286pt_PT
dc.identifier.doihttps://doi.org/10.3390/s22010286pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/23368
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationPOCI-01-0145-FEDER-027819pt_PT
dc.relationForest Research Centre
dc.relationNot Available
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectNIRpt_PT
dc.subjectcalibration modelspt_PT
dc.subjectPLS-Rpt_PT
dc.subjectvolatile phenolspt_PT
dc.subjectaged wine spiritpt_PT
dc.titlePLS-R Calibration models for wine spirit volatile phenols pre-diction by near infrared spectroscopypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleForest Research Centre
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FOCE-ETA%2F27819%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00239%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/DL 57%2F2016/DL 57%2F2016%2FCP1382%2FCT0025/PT
oaire.citation.titleSensorspt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamDL 57/2016
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
relation.isProjectOfPublication627882e1-519b-44d6-b886-3b92ca218701
relation.isProjectOfPublication56bd0ae9-f8da-4344-b9a2-f633d4f68b89
relation.isProjectOfPublicationcd7df150-192b-4f82-825f-7895ad9ae890
relation.isProjectOfPublication.latestForDiscovery627882e1-519b-44d6-b886-3b92ca218701

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