Quality Assessment of Red Wine Grapes through NIR Spectroscopy
Red wine grapes require a constant follow-up through analytical chemistry to assure the greatest wine quality. Wet chemical procedures are time-consuming and produce residues that are hard to eliminate. NIR (near infrared radiation) spectroscopy has been referred as an accurate, rapid, and cost-effi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/12/3/637 |
| _version_ | 1797447364447830016 |
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| author | Maria Inês Rouxinol Maria Rosário Martins Gabriela Carneiro Murta João Mota Barroso Ana Elisa Rato |
| author_facet | Maria Inês Rouxinol Maria Rosário Martins Gabriela Carneiro Murta João Mota Barroso Ana Elisa Rato |
| author_sort | Maria Inês Rouxinol |
| collection | DOAJ |
| description | Red wine grapes require a constant follow-up through analytical chemistry to assure the greatest wine quality. Wet chemical procedures are time-consuming and produce residues that are hard to eliminate. NIR (near infrared radiation) spectroscopy has been referred as an accurate, rapid, and cost-efficient technique to evaluate quality in many fruit species, both in field and in industry. The main objective of this study was to develop predictive models using NIR spectroscopy to quantify important quality attributes in wine grapes. Soluble solids content (SSC), titratable acidity (TA), total phenolic content, total flavonoids, total anthocyanins, and total tannins were quantified in four red wine grape varieties, ‘Aragonês’, ‘Trincadeira’, ‘Touriga Nacional’, and ‘Syrah’. Samples were collected during 2017 and 2018 along véraison. Prediction models were developed using a near-infrared portable device (Brimrose, Luminar 5030), and spectra were collected from entire grapes under near field conditions. Models were built using a partial least square regression (PLSR) algorithm and SSC, TA, total anthocyanins, and total tannins exhibited a determination coefficient of 0.89, 0.90, 0.87, and 0.88, respectively. The Residual Prediction Deviation (<i>RPD</i>) values of these models were higher than 2.3. The prediction models for SSC, TA, total anthocyanins, and total tannins have considerable potential to quantify these attributes in wine grapes. Total flavonoids and total phenolic content were predicted with a slightly lower capacity, with R<sup>2</sup> = 0.72 and 0.71, respectively, and both with a RPD of 1.6, indicating a very low to borderline potential for quantitative predictions in flavonoids and phenols models. |
| first_indexed | 2024-03-09T13:54:58Z |
| format | Article |
| id | doaj.art-5f25b92ea7644e5b9219f086c7b2e56e |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-09T13:54:58Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-5f25b92ea7644e5b9219f086c7b2e56e2023-11-30T20:44:24ZengMDPI AGAgronomy2073-43952022-03-0112363710.3390/agronomy12030637Quality Assessment of Red Wine Grapes through NIR SpectroscopyMaria Inês Rouxinol0Maria Rosário Martins1Gabriela Carneiro Murta2João Mota Barroso3Ana Elisa Rato4MED—Mediterranean Institute for Agriculture, Environment and Development, IIFA—Institute for Advanced Studies and Research, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-554 Evora, PortugalHERCULES Laboratory, Departamento de Ciências Médicas e da Saúde, Escola de Saúde e Desenvolvimento Humano, Universidade de Évora, Rua Romão Ramalho 59, 7000-671 Evora, PortugalMED—Mediterranean Institute for Agriculture, Environment and Development, IIFA—Institute for Advanced Studies and Research, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-554 Evora, PortugalDepartamento de Fitotecnia, Escola de Ciências e Tecnologia, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-554 Evora, PortugalDepartamento de Fitotecnia, Escola de Ciências e Tecnologia, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-554 Evora, PortugalRed wine grapes require a constant follow-up through analytical chemistry to assure the greatest wine quality. Wet chemical procedures are time-consuming and produce residues that are hard to eliminate. NIR (near infrared radiation) spectroscopy has been referred as an accurate, rapid, and cost-efficient technique to evaluate quality in many fruit species, both in field and in industry. The main objective of this study was to develop predictive models using NIR spectroscopy to quantify important quality attributes in wine grapes. Soluble solids content (SSC), titratable acidity (TA), total phenolic content, total flavonoids, total anthocyanins, and total tannins were quantified in four red wine grape varieties, ‘Aragonês’, ‘Trincadeira’, ‘Touriga Nacional’, and ‘Syrah’. Samples were collected during 2017 and 2018 along véraison. Prediction models were developed using a near-infrared portable device (Brimrose, Luminar 5030), and spectra were collected from entire grapes under near field conditions. Models were built using a partial least square regression (PLSR) algorithm and SSC, TA, total anthocyanins, and total tannins exhibited a determination coefficient of 0.89, 0.90, 0.87, and 0.88, respectively. The Residual Prediction Deviation (<i>RPD</i>) values of these models were higher than 2.3. The prediction models for SSC, TA, total anthocyanins, and total tannins have considerable potential to quantify these attributes in wine grapes. Total flavonoids and total phenolic content were predicted with a slightly lower capacity, with R<sup>2</sup> = 0.72 and 0.71, respectively, and both with a RPD of 1.6, indicating a very low to borderline potential for quantitative predictions in flavonoids and phenols models.https://www.mdpi.com/2073-4395/12/3/637NIR-spectroscopyphenolicflavonoidsanthocyaninstanninsSSC |
| spellingShingle | Maria Inês Rouxinol Maria Rosário Martins Gabriela Carneiro Murta João Mota Barroso Ana Elisa Rato Quality Assessment of Red Wine Grapes through NIR Spectroscopy Agronomy NIR-spectroscopy phenolic flavonoids anthocyanins tannins SSC |
| title | Quality Assessment of Red Wine Grapes through NIR Spectroscopy |
| title_full | Quality Assessment of Red Wine Grapes through NIR Spectroscopy |
| title_fullStr | Quality Assessment of Red Wine Grapes through NIR Spectroscopy |
| title_full_unstemmed | Quality Assessment of Red Wine Grapes through NIR Spectroscopy |
| title_short | Quality Assessment of Red Wine Grapes through NIR Spectroscopy |
| title_sort | quality assessment of red wine grapes through nir spectroscopy |
| topic | NIR-spectroscopy phenolic flavonoids anthocyanins tannins SSC |
| url | https://www.mdpi.com/2073-4395/12/3/637 |
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