Characterisation of malolactic conversion by <i>Oenococcus oeni</i> to reduce the acidity of apple juice
Bibliographic record
Abstract
Summary The high concentration of malic acid is responsible for the acidity and sourness in apple juice. Bio‐conversion of malic acid to lactic acid through malolactic conversion (MC) in apple juice using Oenococcus oeni was investigated. When apple juice was inoculated with O. oeni (1 × 10 6 CFU mL −1 ), over 90% of malic acid was converted into lactic acid within 96 h at room temperature. When pH of apple juice was adjusted to 4.1 prior to inoculation, MC was completed within 60 h. MC was enhanced at a higher temperature (30°C) when compared with room temperature. The rate of MC was directly proportional to the number of bacteria added and MC was completed within 24 h at 1 × 10 9 CFU mL −1 initial cell density. MC occurred equally under aerobic and anaerobic conditions. The sensory analysis of partial MC‐applied juice when compared against control revealed potential for use of MC for manufacture of low‐acid apple juice.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".