AIMC Topic: Humulus

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Gas-phase volatilomic approaches for quality control of brewing hops based on simultaneous GC-MS-IMS and machine learning.

Analytical and bioanalytical chemistry Aug 4, 2020
For the first time, a prototype HS-GC-MS-IMS dual-detection system is presented for the analysis of volatile organic compounds (VOCs) in fields of quality control of brewing hop. With a soft ionization and drift time-based ion separation in IMS and a...
Machine Learning Reproducibility of Results Principal Component Analysis Gas Chromatography-Mass Spectrometry Quality Control Fermentation Volatile Organic Compounds Solid Phase Microextraction Ion Mobility Spectrometry Humulus
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Assessment of Beer Quality Based on a Robotic Pourer, Computer Vision, and Machine Learning Algorithms Using Commercial Beers.

Journal of food science Mar 30, 2018
UNLABELLED: Sensory attributes of beer are directly linked to perceived foam-related parameters and beer color. The aim of this study was to develop an objective predictive model using machine learning modeling to assess the intensity levels of senso...
Neural Networks, Computer Machine Learning Computers Color Taste Food Technology Yeasts Food Handling Smell Viscosity Food Quality Beer Humulus
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