A data-driven approach to improve coffee drying: Combining environmental sensors and chemical analysis.
The study introduces a methodology that utilizes data-driven approaches to optimize coffee drying operations. This is achieved through the integration of ambient sensor data and chemical analysis. This statement underscores the significance of temperature regulation, humidity levels, and light inten...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0296526&type=printable |