Changes in Quality Attributes Related to Browning during Storage of Litchi Juice Fermented by Lactobacillus
Bibliographic record
Abstract
Litchi juice fermented by Lactobacillus casei was heated (95°C, 1 min) and stored in a dark place at 25°C. Changes in quality attributes (color, 5-hydroxymethylfurfural (5-HMF) phenolic compounds, antioxidant capacity, sugars, free amino acids, and others) related to browning in fermented litchi juice were investigated during the six months of storage. Noticeable visual changes due to browning were observed during storage of fermented litchi juice, especially in the upper part of the juice bottle, and the value of color difference (△E) increased to 7.12±0.04 after six months of storage. The 5-HMF content increased with the increase in storage time, which rose from 0 to 2.31±0.16 mg/L after six months of storage. Five soluble phenolic compounds (rutin, narcissoside, quercetin, kaempferol-rutinose-rhamnoside, and isorhamnetin-rutinose-rhamnoside) were identified in fermented litchi juice, none of which showed a significant decrease (P>0.05), whereas a tendency for total phenolic content to decrease was observed during storage of fermented litchi juice. Adding 0.3 g/L of sodium sulfite can inhibit the browning reaction in fermented litchi juice and decrease the formation of 5-HMF as well as the loss of total phenolics.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".