Cargando…
An AI-powered Electronic Nose System with Fingerprint Extraction for Aroma Recognition of Coffee Beans
Aroma and taste have long been considered important indicators of quality coffee. Specialty coffee, that is, coffee from a single estate, farm, or village in a coffee-growing region, in particular, has a unique aroma that reflects the coffee-producing region. In order to enable the traceability of c...
Autores principales: | Lee, Chung-Hong, Chen, I-Te, Yang, Hsin-Chang, Chen, Yenming J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414376/ https://www.ncbi.nlm.nih.gov/pubmed/36014234 http://dx.doi.org/10.3390/mi13081313 |
Ejemplares similares
-
Improving the Performance of an Electronic Nose by Wine Aroma Training to Distinguish between Drip Coffee and Canned Coffee
por: Fujioka, Kouki, et al.
Publicado: (2014) -
Prediction of coffee aroma from single roasted coffee beans by hyperspectral imaging
por: Caporaso, Nicola, et al.
Publicado: (2022) -
Impact of agro-forestry systems on the aroma generation of coffee beans
por: Xu, Su, et al.
Publicado: (2022) -
Modifying Robusta coffee aroma by green bean chemical pre-treatment
por: Liu, Chujiao, et al.
Publicado: (2019) -
Integrating a Low-Cost Electronic Nose and Machine Learning Modelling to Assess Coffee Aroma Profile and Intensity
por: Gonzalez Viejo, Claudia, et al.
Publicado: (2021)