Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms.

Claudia Gonzalez ViejoSigfredo FuentesDamir TorricoKate HowellFrank R Dunshea

Published in: Journal of the science of food and agriculture (2017)

The method proposed showed to be a rapid system based on NIR spectroscopy and RoboBEER outputs of foamability that can be used to infer the quality, production method and chemical parameters of beer with minimal laboratory equipment. © 2017 Society of Chemical Industry.

Keyphrases

machine learning
deep learning
artificial intelligence
quality improvement
high resolution
photodynamic therapy
single molecule
fluorescent probe
sensitive detection