Effects of cofermentation and sequential inoculation of <i><scp>S</scp>accharomyces bayanus</i> and <i><scp>T</scp>orulaspora delbruckii</i> on durian wine composition
Bibliographic record
Abstract
Summary This work investigated the effects of cofermentation and sequential inoculation of T orulaspora delbrueckii B iodiva and S accharomyces bayanus EC ‐1118 on chemical and volatile components of durian wines. Cofermentation and sequential inoculation resulted in higher production of ethanol (6.2% and 7.7% v/v, respectively) relative to the control (5.3% for S . bayanus and 5.8% for T . delbrueckii ). Further, cofermentation and sequential inoculation produced higher amounts of acetyl esters and higher alcohols especially isoamyl alcohol and 2‐phenylethyl alcohol than monoculture fermentation. Most endogenous sulphur volatiles, especially disulphides that impart a character‐impact durian odour, declined to trace levels, but new ones such as thioesters were formed. Sulphur volatiles in the durian wines fermented by cofermentation and sequential inoculation accounted for 0.03% and 0.05% of total peak area. The study suggests that the use of S . bayanus in conjunction with non‐ S accharomyces such as T . delbrueckii may improve the aromatic intensity and complexity of durian wine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".