Machine learning modeling for optimizing fermentation process of Dendrobium officinale with improved antioxidant property and metabolic changes
Yuhang Yi, Chenghao Lv, Hongbin Lan, Abdulaziz Nuhu Jibril, Yibo Luo, Jun Fang, Si Qin · 2026
Read Machine learning modeling for optimizing fermentation process of Dendrobium officinale with improved antioxidant property and metabolic changes by Yuhang Yi, Chenghao Lv, Hongbin Lan, Abdulaziz Nuhu Jibril, Yibo Luo, Jun Fang, Si Qin (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13571729.txt.
Description
Yuhang Yi and co-authors tune a fermentation that boosts the antioxidant power of a medicinal orchid. The plant, Dendrobium officinale, is both food and medicine in China. Lactic bacteria fermentation can free its helpful compounds and add new ones. Nine learning models were raced against a classic surface method to find the best brew settings.
One boosting model won with near-perfect fit scores over the classic method. The tuned brew raised radical-scavenging power without harming cell life in dish tests. Chemical reads showed deep reshaping of the plant's molecule mix. Thirty-one flavonoids rose, and rich phenolic acids grew in step. Alkaloid paths also shifted in marked ways under the bacteria.
Catalog record
| CREATOR | Yuhang Yi, Chenghao Lv, Hongbin Lan, Abdulaziz Nuhu Jibril, Yibo Luo, Jun Fang, Si Qin |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 55 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |