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An AI-powered Electronic Nose System with Fingerprint Extraction for Aroma Recognition of Coffee Beans
- Source :
- Micromachines, Vol 13, Iss 8, p 1313 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- 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 coffee origin, in this study we have developed an e-nose system to discriminate the aroma of freshly roasted coffee in different production regions. In the case study, we employed the e-nose system to experiment with various machine learning models for recognizing several collected coffee beans such as coffees from Yirgacheffe and Kona. Additionally, our contribution also includes the development of a method to create an aromatic digital fingerprint of a specific coffee bean to identify its origin. The experimental results show that the developed e-nose system achieves good recognition performance for coffee aroma recognition. The extracted digital fingerprints have great potential to be stored in an extensible coffee aroma database similar to a comprehensive library of specific coffee bean aroma characteristics, for traceability and reconfirmation of their origin.
Details
- Language :
- English
- ISSN :
- 2072666X
- Volume :
- 13
- Issue :
- 8
- Database :
- Directory of Open Access Journals
- Journal :
- Micromachines
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9c7a23c4559949d6bc705002470b1edc
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/mi13081313