Identification, stress tolerance, and antioxidant activity of lactic acid bacteria isolated from tropically grown fruits and leaves
Bibliographic record
Abstract
From 6 samples of tropically grown fruits and leaves, 10 lactic acid bacteria belonging Leuconostoc, Weissella, and Lactobacillus species were isolated and identified by 16S rRNA gene sequencing and (GTG)5 fingerprinting. Acidification kinetics determined from BHI broth cultures showed genus-related patterns. In particular, Weissella cibaria appeared to act as a potent acidifier. Tolerance of isolates to acid, oxidative, or salt stress was highly variable and strain dependent. Isolate S14 (Leuconostoc pseudomesenteroides) growth was not affected by the presence of 0.05% H2O2, while Lactobacillus spp. isolates (S17 and S29) were the most tolerant to pH 4.5. The growth of 4 isolates, S5 (Leuconostoc mesenteroides), S14 and S10 (Leuconostoc pseudomesenteroides), and S27 (W. cibaria), was not affected by 5% NaCl. Nutritional beneficial properties were examined through measurement of antioxidant activities of short-term fermented pineapple juice, such as LDL oxidation and polyphenol content, and through exopolysaccharide formation from sucrose. Two isolates, S14 and S27, increased the antioxidant capacity of pineapple juice. The robust capacity of W. cibaria and of Leuconostoc pseudomesenteroides for vegetable lactic fermentation aimed to ameliorate food nutritional and functional quality was highlighted.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".