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PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy
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 ph...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749750/ https://www.ncbi.nlm.nih.gov/pubmed/35009831 http://dx.doi.org/10.3390/s22010286 |
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author | Anjos, Ofélia Caldeira, Ilda Fernandes, Tiago A. Pedro, Soraia Inês Vitória, Cláudia Oliveira-Alves, Sheila Catarino, Sofia Canas, Sara |
author_facet | Anjos, Ofélia Caldeira, Ilda Fernandes, Tiago A. Pedro, Soraia Inês Vitória, Cláudia Oliveira-Alves, Sheila Catarino, Sofia Canas, Sara |
author_sort | Anjos, Ofélia |
collection | PubMed |
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 (r(2) = 96.34; RPD = 5.23), 4-methyl-guaiacol (r(2) = 96.1; RPD = 5.07), eugenol (r(2) = 96.06; RPD = 5.04), syringol (r(2) = 97.32; RPD = 6.11), 4-methyl-syringol (r(2) = 95.79; RPD = 4.88) and 4-allyl-syringol (r(2) = 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. |
format | Online Article Text |
id | pubmed-8749750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87497502022-01-12 PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy Anjos, Ofélia Caldeira, Ilda Fernandes, Tiago A. Pedro, Soraia Inês Vitória, Cláudia Oliveira-Alves, Sheila Catarino, Sofia Canas, Sara Sensors (Basel) Article 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 (r(2) = 96.34; RPD = 5.23), 4-methyl-guaiacol (r(2) = 96.1; RPD = 5.07), eugenol (r(2) = 96.06; RPD = 5.04), syringol (r(2) = 97.32; RPD = 6.11), 4-methyl-syringol (r(2) = 95.79; RPD = 4.88) and 4-allyl-syringol (r(2) = 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. MDPI 2021-12-31 /pmc/articles/PMC8749750/ /pubmed/35009831 http://dx.doi.org/10.3390/s22010286 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Anjos, Ofélia Caldeira, Ilda Fernandes, Tiago A. Pedro, Soraia Inês Vitória, Cláudia Oliveira-Alves, Sheila Catarino, Sofia Canas, Sara 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 |
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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749750/ https://www.ncbi.nlm.nih.gov/pubmed/35009831 http://dx.doi.org/10.3390/s22010286 |
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