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Differentiation through E-Nose and GC-FID data modeling of rosé sparkling wines elaborated via Traditional and Charmat methods.

Raquel Muñoz-CastellsMargherita ModestiJaime Moreno GarcíaMaría Rodríguez-MorenoAlexandro CatiniRosamaria CapuanoCorrado Di NataleAndrea BellincontroJuan Moreno
Published in: Journal of the science of food and agriculture (2023)
Production methods of Rosé sparkling wine affect the final wine aroma profiles due to the differences in terms of volatiles. The PLS-DA of the data obtained with E-nose reveal that distinguishing between Charmat and Traditional methods is possible. Moreover, predictive models using GC-FID analysis and electronic nose highlight the possibility of fast and efficient prediction of volatiles from the electronic nose. This article is protected by copyright. All rights reserved.
Keyphrases
  • electronic health record
  • cell death
  • dna damage
  • gas chromatography mass spectrometry
  • big data
  • gas chromatography
  • single cell
  • deep learning
  • mass spectrometry
  • high resolution
  • liquid chromatography