Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra

The Harbertson-Adams phenolic parameter assay is a well- known method to measure a panel of phenolic compounds in red wines. However, the multistep analyses required by the method fail at producing results on multiple parameters rapidly. In the present article, we analyze the bene ts of applying a...

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Autores principales: Catania, Aníbal, Catania, Carlos, Sari, Santiago, Fanzone, Martín
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2020
Materias:
Ciencias Informáticas
Phenolic components
Wine making
Statistical learning
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/115420
http://49jaiio.sadio.org.ar/pdfs/cai/CAI_14.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-115420
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Phenolic components
Wine making
Statistical learning
spellingShingle Ciencias Informáticas
Phenolic components
Wine making
Statistical learning
Catania, Aníbal
Catania, Carlos
Sari, Santiago
Fanzone, Martín
Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra
topic_facet Ciencias Informáticas
Phenolic components
Wine making
Statistical learning
description The Harbertson-Adams phenolic parameter assay is a well- known method to measure a panel of phenolic compounds in red wines. However, the multistep analyses required by the method fail at producing results on multiple parameters rapidly. In the present article, we analyze the bene ts of applying a statistical model based on Principal Component Analysis (PCA) and a statistical learning technique denoted as Support Vector Regression Machines (SVR) for correlating sample spectra data to the Harbertson-Adams assay, on each of the phenolics components. The resulting model showed a high correlation between the measured and predicted values for each of the phenolic parameters despite the multicollinearity and high dimensions of the dataset.
format Objeto de conferencia
Objeto de conferencia
author Catania, Aníbal
Catania, Carlos
Sari, Santiago
Fanzone, Martín
author_facet Catania, Aníbal
Catania, Carlos
Sari, Santiago
Fanzone, Martín
author_sort Catania, Aníbal
title Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra
title_short Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra
title_full Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra
title_fullStr Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra
title_full_unstemmed Predicting Harbertson-Adams Assay Phenolic Parameters In Red Wines Using Visible Spectra
title_sort predicting harbertson-adams assay phenolic parameters in red wines using visible spectra
publishDate 2020
url http://sedici.unlp.edu.ar/handle/10915/115420
http://49jaiio.sadio.org.ar/pdfs/cai/CAI_14.pdf
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AT sarisantiago predictingharbertsonadamsassayphenolicparametersinredwinesusingvisiblespectra
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bdutipo_str Repositorios
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