TY  - GEN 
AU  - Pérez Calle, José Luis
AU  - Barea Sepúlveda, Marta
AU  - Ruiz Rodríguez, Ana
AU  - Álvarez Saura, José Ángel
AU  - Palma Lovillo, Miguel
A4  - Química Analítica
A4  - Química Física
PY  - 2022
SN  - 1424-8220
UR  - http://hdl.handle.net/10498/27242
AB  - 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...
LA  - eng
PB  - MDPI
KW  - near-infrared spectroscopy
KW  - adulteration
KW  - fruits juices
KW  - machine learning
KW  - regression
KW  - classification
TI  - Rapid Detection and Quantification of Adulterants in Fruit Juices Using Machine Learning Tools and Spectroscopy Data
DO  - 10.3390/s22103852
ER  -