Rapid Detection and Quantification of Adulterants in Fruit Juices Using Machine Learning Tools and Spectroscopy Data

Fruit juice production is one of the most important sectors in the beverage industry, and its adulteration by adding cheaper juices is very common. This study presents a methodology based on the combination of machine learning models and near-infrared spectroscopy for the detection and quantificatio...

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Detalles Bibliográficos
Autores principales: Calle, José Luis P., Barea-Sepúlveda, Marta, Ruiz-Rodríguez, Ana, Álvarez, José Ángel, Ferreiro-González, Marta, Palma, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145498/
https://www.ncbi.nlm.nih.gov/pubmed/35632260
http://dx.doi.org/10.3390/s22103852

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145498/
https://www.ncbi.nlm.nih.gov/pubmed/35632260
http://dx.doi.org/10.3390/s22103852

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