Modelling wine astringency from its chemical composition using machine learning algorithms

Modelling wine astringency from its chemical composition using machine learning algorithms

Aims: The present work aims to predict sensory astringency from wine chemical composition using machine learning algorithms. Material and results: Moristel grapes from different vineblocks and at different stages of ripening were collected. Eleven different wines were produced in 75 L tanks in tripl...

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Bibliographic Details
Main Authors: Maria P Sáenz-Navajas, Sara Ferrero-del-Teso, Miguel Romero, Darío Pascual, David Diaz, Vicente Ferreira, Purificación Fernández-Zurbano
Format: Article
Language:English
Published: International Viticulture and Enology Society 2019-08-01
Series:OENO One
Subjects:
wine
astringency
modelling
machine learning
tannin activity
sensory
Online Access:https://oeno-one.eu/article/view/2380

Internet

https://oeno-one.eu/article/view/2380

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