Predicting and improving complex beer flavor through machine learning
Abstract The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models th...
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| Główni autorzy: | , , , , , , , , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Nature Portfolio
2024-03-01
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| Seria: | Nature Communications |
| Dostęp online: | https://doi.org/10.1038/s41467-024-46346-0 |
| Etykiety: |
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