Next Article in Journal
Nanostructured Molecularly Imprinted Polyaniline for Acrylamide Sensing
Previous Article in Journal
The Targeting of Quadruplex Nucleic Acids in Human Cancers
Article Menu
Issue 1 (XoveTIC 2019) cover image

Export Article

Open AccessProceedings

Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning

Faculty of Computer Science, CITIC, University of A Coruna, 15071 Galicia, Spain
*
Author to whom correspondence should be addressed.
Presented at the 2nd XoveTIC Conference, A Coruña, Spain, 5–6 September 2019.
Proceedings 2019, 21(1), 48; https://doi.org/10.3390/proceedings2019021048
Published: 13 August 2019
(This article belongs to the Proceedings of XoveTIC Conference)
PDF [165 KB, uploaded 13 August 2019]

Abstract

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 spectrophotometer, 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.
Keywords: NIR; Electromagnetic spectrum; Neural networks NIR; Electromagnetic spectrum; Neural networks
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Galdo, B.; Rivero, D.; Fernandez-Blanco, E. Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning. Proceedings 2019, 21, 48.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Proceedings EISSN 2504-3900 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top