Production of aroma and flavor‐rich fusel alcohols by cheese whey fermentation using the <i>Kluyveromyces marxianus</i> and <scp><i>Debaryomyces hansenii</i></scp> yeasts in monoculture and co‐culture modes
Bibliographic record
Abstract
Abstract BACKGROUND Whey is one of the main agro‐industrial by‐products generated in the production of cheese. It is a residue with low pH and high content of organic and inorganic compounds, such as lactose, proteins, and minerals that can be used as nutrients in fermentation. The aim of the present study was to produce biomolecules with aroma and flavor properties by whey fermentation using Kluyveromyces marxianus (KM) and Debaryomyces hansenii (DH). RESULTS These yeasts produced and accumulated in the culture broth aroma and flavor compounds, the main ones being ethanol, glycerol, propanoic acid, dihydroxyacetone, methionol, isopentanol, and 2‐phenylethanol (2PE). This last one was retained as the target biomolecule, because of its potential to be commercialized industrially. Both yeasts were able to metabolize L‐phenylalanine (Lphe) to produce 2PE, in monoculture and co‐culture modes. When yeasts were used under monoculture mode, KM produced the highest 2PE concentration 82 ± 28 mg/L under aerobic fermentation, with yield of 0.16 ± 0.08 g2PE/gLphe and a productivity of 0.86 ± 0.18 mg2PE/L*h at a fermentation time of 96 h. Whereas in co‐culture mode the 2PE yield was 0.38 g2PE/gLphe, twice as high as the maximum yield for monocultures. This yield corresponded to a productivity of 1.93 ± 0.02 mg2PE/L*h. CONCLUSION The whey fermentation using KM and DH in co‐culture mode is technically feasible. The KM yeast is apparently dominant and the co‐culture of both yeasts led to increase in the 2PE yield and the productivity. The faster kinetics of KM quickly induced substrate starvation triggering early production and accumulation of 2PE. © 2021 Society of Chemical Industry (SCI).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".