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Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling
The variability in grape ripening is associated with the fact that each grape berry undergoes its own biochemical processes. Traditional viticulture manages this by averaging the physicochemical values of hundreds of grapes to make decisions. However, to obtain accurate results it is necessary to ev...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001218/ https://www.ncbi.nlm.nih.gov/pubmed/36900479 http://dx.doi.org/10.3390/foods12050962 |
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author | Schorn-García, Daniel Giussani, Barbara García-Casas, María Jesús Rico, Daniel Martin-Diana, Ana Belén Aceña, Laura Busto, Olga Boqué, Ricard Mestres, Montserrat |
author_facet | Schorn-García, Daniel Giussani, Barbara García-Casas, María Jesús Rico, Daniel Martin-Diana, Ana Belén Aceña, Laura Busto, Olga Boqué, Ricard Mestres, Montserrat |
author_sort | Schorn-García, Daniel |
collection | PubMed |
description | The variability in grape ripening is associated with the fact that each grape berry undergoes its own biochemical processes. Traditional viticulture manages this by averaging the physicochemical values of hundreds of grapes to make decisions. However, to obtain accurate results it is necessary to evaluate the different sources of variability, so exhaustive sampling is essential. In this article, the factors “grape maturity over time” and “position of the grape” (both in the grapevine and in the bunch/cluster) were considered and studied by analyzing the grapes with a portable ATR-FTIR instrument and evaluating the spectra obtained with ANOVA–simultaneous component analysis (ASCA). Ripeness over time was the main factor affecting the characteristics of the grapes. Position in the vine and in the bunch (in that order) were also significantly important, and their effect on the grapes evolves over time. In addition, it was also possible to predict basic oenological parameters (TSS and pH with errors of 0.3 °Brix and 0.7, respectively). Finally, a quality control chart was built based on the spectra obtained in the optimal state of ripening, which could be used to decide which grapes are suitable for harvest. |
format | Online Article Text |
id | pubmed-10001218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100012182023-03-11 Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling Schorn-García, Daniel Giussani, Barbara García-Casas, María Jesús Rico, Daniel Martin-Diana, Ana Belén Aceña, Laura Busto, Olga Boqué, Ricard Mestres, Montserrat Foods Article The variability in grape ripening is associated with the fact that each grape berry undergoes its own biochemical processes. Traditional viticulture manages this by averaging the physicochemical values of hundreds of grapes to make decisions. However, to obtain accurate results it is necessary to evaluate the different sources of variability, so exhaustive sampling is essential. In this article, the factors “grape maturity over time” and “position of the grape” (both in the grapevine and in the bunch/cluster) were considered and studied by analyzing the grapes with a portable ATR-FTIR instrument and evaluating the spectra obtained with ANOVA–simultaneous component analysis (ASCA). Ripeness over time was the main factor affecting the characteristics of the grapes. Position in the vine and in the bunch (in that order) were also significantly important, and their effect on the grapes evolves over time. In addition, it was also possible to predict basic oenological parameters (TSS and pH with errors of 0.3 °Brix and 0.7, respectively). Finally, a quality control chart was built based on the spectra obtained in the optimal state of ripening, which could be used to decide which grapes are suitable for harvest. MDPI 2023-02-24 /pmc/articles/PMC10001218/ /pubmed/36900479 http://dx.doi.org/10.3390/foods12050962 Text en © 2023 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 Schorn-García, Daniel Giussani, Barbara García-Casas, María Jesús Rico, Daniel Martin-Diana, Ana Belén Aceña, Laura Busto, Olga Boqué, Ricard Mestres, Montserrat Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling |
title | Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling |
title_full | Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling |
title_fullStr | Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling |
title_full_unstemmed | Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling |
title_short | Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling |
title_sort | assessment of variability sources in grape ripening parameters by using ftir and multivariate modelling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001218/ https://www.ncbi.nlm.nih.gov/pubmed/36900479 http://dx.doi.org/10.3390/foods12050962 |
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