Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing

Due to its physical, chemical, and structural properties, oakwood is widely used in the production of barrels for wine ageing. When in contact with the wine, oak continuously releases aromatic compounds such as lignin, tannin, and cellulose to the liquid. Due to the release process, oak loses its ch...

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Main Authors: Tatevik Chalyan, Indy Magnus, Maria Konstantaki, Stavros Pissadakis, Zacharias Diamantakis, Hugo Thienpont, Heidi Ottevaere
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Biosensors
Subjects:
Online Access:https://www.mdpi.com/2079-6374/12/4/227
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author Tatevik Chalyan
Indy Magnus
Maria Konstantaki
Stavros Pissadakis
Zacharias Diamantakis
Hugo Thienpont
Heidi Ottevaere
author_facet Tatevik Chalyan
Indy Magnus
Maria Konstantaki
Stavros Pissadakis
Zacharias Diamantakis
Hugo Thienpont
Heidi Ottevaere
author_sort Tatevik Chalyan
collection DOAJ
description Due to its physical, chemical, and structural properties, oakwood is widely used in the production of barrels for wine ageing. When in contact with the wine, oak continuously releases aromatic compounds such as lignin, tannin, and cellulose to the liquid. Due to the release process, oak loses its characteristic aromatic compounds in time; hence, the flavour that it gives to the enclosed wine decreases for repeated wine refills and a barrel replacement is required. Currently, the estimation of the maximum number of refills is empirical and its underestimation or overestimation can impose unnecessary costs and impair the quality of the wine. Therefore, there is a clear need to quantify the presence of the aforementioned aromatic compounds in an oak barrel prior to a refill. This work constitutes a study to examine noninvasive optical biosensing techniques for the characterization of an oak barrel used in wine ageing, towards the development of a model to unveil its lifespan without inducing structural damage. Spectroscopic diagnostic techniques, such as reflectance, fluorescence, and Raman scattering measurements are employed to assess the change in the chemical composition of the oakwood barrel (tannin and lignin presence) and its dependence on repeated refills. To our knowledge, this is the first time that we present a benchmarking study of oak barrel ageing characteristics through spectroscopic methods for the wine industry. The spectroscopic data are processed using standard chemometric techniques, such as Linear Discriminant Analysis and Partial Least Squares Discriminant Analysis. Results of a study of fresh, one-time-used, and two-times-used oak barrel samples demonstrate that reflectance spectroscopy can be a valuable tool for the characterization of oak barrels. Moreover, reflectance spectroscopy has demonstrated the most accurate classification performance. The highest accuracy has been obtained by a Partial Least Squares Discriminant Analysis model that has been able to classify all the oakwood samples from the barrels with >99% accuracy. These preliminary results pave a way for the application of cost-effective and non-invasive biosensing techniques based on reflectance spectroscopy for oak barrels assessment.
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spelling doaj.art-5558e31a88ec49138e03dc54e50c0e972023-12-01T00:58:12ZengMDPI AGBiosensors2079-63742022-04-0112422710.3390/bios12040227Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine AgeingTatevik Chalyan0Indy Magnus1Maria Konstantaki2Stavros Pissadakis3Zacharias Diamantakis4Hugo Thienpont5Heidi Ottevaere6Brussels Photonics (B-PHOT), Department of Applied Physics and Photonics, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, BelgiumBrussels Photonics (B-PHOT), Department of Applied Physics and Photonics, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, BelgiumInstitute of Electronic Structure and Laser (IESL), Foundation for Research and Technology-Hellas (FORTH), 70013 Heraklion, GreeceInstitute of Electronic Structure and Laser (IESL), Foundation for Research and Technology-Hellas (FORTH), 70013 Heraklion, GreeceWinemakers’ Association of the Department of Heraklion—Wines of Crete, Archimidous 1 & Ikarou St., 71601 Heraklion, GreeceBrussels Photonics (B-PHOT), Department of Applied Physics and Photonics, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, BelgiumBrussels Photonics (B-PHOT), Department of Applied Physics and Photonics, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, BelgiumDue to its physical, chemical, and structural properties, oakwood is widely used in the production of barrels for wine ageing. When in contact with the wine, oak continuously releases aromatic compounds such as lignin, tannin, and cellulose to the liquid. Due to the release process, oak loses its characteristic aromatic compounds in time; hence, the flavour that it gives to the enclosed wine decreases for repeated wine refills and a barrel replacement is required. Currently, the estimation of the maximum number of refills is empirical and its underestimation or overestimation can impose unnecessary costs and impair the quality of the wine. Therefore, there is a clear need to quantify the presence of the aforementioned aromatic compounds in an oak barrel prior to a refill. This work constitutes a study to examine noninvasive optical biosensing techniques for the characterization of an oak barrel used in wine ageing, towards the development of a model to unveil its lifespan without inducing structural damage. Spectroscopic diagnostic techniques, such as reflectance, fluorescence, and Raman scattering measurements are employed to assess the change in the chemical composition of the oakwood barrel (tannin and lignin presence) and its dependence on repeated refills. To our knowledge, this is the first time that we present a benchmarking study of oak barrel ageing characteristics through spectroscopic methods for the wine industry. The spectroscopic data are processed using standard chemometric techniques, such as Linear Discriminant Analysis and Partial Least Squares Discriminant Analysis. Results of a study of fresh, one-time-used, and two-times-used oak barrel samples demonstrate that reflectance spectroscopy can be a valuable tool for the characterization of oak barrels. Moreover, reflectance spectroscopy has demonstrated the most accurate classification performance. The highest accuracy has been obtained by a Partial Least Squares Discriminant Analysis model that has been able to classify all the oakwood samples from the barrels with >99% accuracy. These preliminary results pave a way for the application of cost-effective and non-invasive biosensing techniques based on reflectance spectroscopy for oak barrels assessment.https://www.mdpi.com/2079-6374/12/4/227wine ageingoak barrellignintanninRaman spectroscopyfluorescence spectroscopy
spellingShingle Tatevik Chalyan
Indy Magnus
Maria Konstantaki
Stavros Pissadakis
Zacharias Diamantakis
Hugo Thienpont
Heidi Ottevaere
Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
Biosensors
wine ageing
oak barrel
lignin
tannin
Raman spectroscopy
fluorescence spectroscopy
title Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
title_full Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
title_fullStr Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
title_full_unstemmed Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
title_short Benchmarking Spectroscopic Techniques Combined with Machine Learning to Study Oak Barrels for Wine Ageing
title_sort benchmarking spectroscopic techniques combined with machine learning to study oak barrels for wine ageing
topic wine ageing
oak barrel
lignin
tannin
Raman spectroscopy
fluorescence spectroscopy
url https://www.mdpi.com/2079-6374/12/4/227
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