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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...
Autores principales: | Calle, José Luis P., Barea-Sepúlveda, Marta, Ruiz-Rodríguez, Ana, Álvarez, José Ángel, Ferreiro-González, Marta, Palma, Miguel |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
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 |
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