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 Torulaspora delbrueckiiBiodiva and Saccharomyces bayanusEC‐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‐Saccharomyces 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 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 | 0.000 |
| 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 | 0.001 |
| 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".