Digital Assessment and Classification of Wine Faults Using a Low-Cost Electronic Nose, Near-Infrared Spectroscopy and Machine Learning Modelling

The winemaking industry can benefit greatly by implementing digital technologies to avoid guesswork and the development of off-flavors and aromas in the final wines. This research presents results on the implementation of near-infrared spectroscopy (NIR) and a low-cost electronic nose (e-nose) coupl...

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Detalles Bibliográficos
Autores principales: Gonzalez Viejo, Claudia, Fuentes, Sigfredo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955090/
https://www.ncbi.nlm.nih.gov/pubmed/35336472
http://dx.doi.org/10.3390/s22062303

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955090/
https://www.ncbi.nlm.nih.gov/pubmed/35336472
http://dx.doi.org/10.3390/s22062303

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