Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning
- Brais Galdo 1
- Daniel Rivero 1
- Enrique Fernandez-Blanco 1
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1
Universidade da Coruña
info
- Alberto Alvarellos González (ed. lit.)
- José Joaquim de Moura Ramos (ed. lit.)
- Beatriz Botana Barreiro (ed. lit.)
- Javier Pereira Loureiro (ed. lit.)
- Manuel F. González Penedo (ed. lit.)
Editorial: MDPI
ISBN: 978-3-03921-444-0, 978-3-03921-443-3
Año de publicación: 2019
Congreso: XoveTIC (2. 2019. A Coruña)
Tipo: Aportación congreso
Resumen
It is a fact that, non-destructive measurement technologies have gain a lot of attention over the years. Among those technologies, NIR technology is the one which allows the analysis of electromagnetic spectrum looking for carbon-link interactions. This technology analyzes the electromagnetic spectrum in the band between 700 nm and 2500 nm, a band very close to the visible spectrum. Traditionally, the devices used to measure are utterly expensive and enormously bulky. That is why this project was focused on a portable spectrophotometer to make measures. This device is smaller and cheaper than the common pectrophotometer, although at the cost of a lower resolution. In this work, that device in combination with the use of machine learning was used to detect if a beer contains alcohol or it can be labeled as non-alcoholic drink.