PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.2/12975 |
Resumo: | Near-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-methyl-syringol (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 beverages. |
id |
RCAP_5dc48614374bd9c34d2f10e1a83cd009 |
---|---|
oai_identifier_str |
oai:repositorioaberto.uab.pt:10400.2/12975 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopyNIRCalibration modelsPLS-RVolatile phenolsAged wine spiritODS::09:Indústria, Inovação e InfraestruturasODS::12:Produção e Consumo SustentáveisNear-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-methyl-syringol (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 beverages.The authors thank “Centro de Biotecnologia de plantas” for the equipment availability and Vitor de Freitas as the Scientific Consultant of the Project PO-CI-01-0145-FEDER-027819. This research was funded by National Funds through FCT—Foundation for Science and Technology under the Project POCI-01-0145-FEDER-027819 (PTDC/OCE-ETA/27819/2017). This work is also funded by National Funds through FCT—Foundation for Science and Technology under the Projects UIDB/00239/2020 [CEF], UIDB/05183/2020 [MED]; UIDB/00100/2020, UIDP/00100/2020 [CQE]; UID/AGR/04129/2020, DL 57/2016/CP1382/CT0025 [LEAF].MDPIRepositório AbertoAnjos, OféliaCaldeira, IldaFernandes, TiagoPedro, SoraiaVitória, CláudiaAlves, Sheila Cristina OliveiraCatarino, SofiaCanas, Sara2023-01-04T11:18:32Z2021-12-312021-12-31T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.2/12975eng10.3390/s22010286info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-03T01:47:46Zoai:repositorioaberto.uab.pt:10400.2/12975Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:51:52.733425Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
title |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
spellingShingle |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy Anjos, Ofélia NIR Calibration models PLS-R Volatile phenols Aged wine spirit ODS::09:Indústria, Inovação e Infraestruturas ODS::12:Produção e Consumo Sustentáveis |
title_short |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
title_full |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
title_fullStr |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
title_full_unstemmed |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
title_sort |
PLS-R calibration models for wine spirit volatile phenols prediction by near-infrared spectroscopy |
author |
Anjos, Ofélia |
author_facet |
Anjos, Ofélia Caldeira, Ilda Fernandes, Tiago Pedro, Soraia Vitória, Cláudia Alves, Sheila Cristina Oliveira Catarino, Sofia Canas, Sara |
author_role |
author |
author2 |
Caldeira, Ilda Fernandes, Tiago Pedro, Soraia Vitória, Cláudia Alves, Sheila Cristina Oliveira Catarino, Sofia Canas, Sara |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Aberto |
dc.contributor.author.fl_str_mv |
Anjos, Ofélia Caldeira, Ilda Fernandes, Tiago Pedro, Soraia Vitória, Cláudia Alves, Sheila Cristina Oliveira Catarino, Sofia Canas, Sara |
dc.subject.por.fl_str_mv |
NIR Calibration models PLS-R Volatile phenols Aged wine spirit ODS::09:Indústria, Inovação e Infraestruturas ODS::12:Produção e Consumo Sustentáveis |
topic |
NIR Calibration models PLS-R Volatile phenols Aged wine spirit ODS::09:Indústria, Inovação e Infraestruturas ODS::12:Produção e Consumo Sustentáveis |
description |
Near-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-methyl-syringol (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 beverages. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-31 2021-12-31T00:00:00Z 2023-01-04T11:18:32Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.2/12975 |
url |
http://hdl.handle.net/10400.2/12975 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.3390/s22010286 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799135110834946048 |