Population Yields and Vegetable Juice Fermentation of<i>Leuconostoc mesenteroides</i>Cultures Grown Under Free-Cell or Immobilized-Cell Technologies
Bibliographic record
Abstract
Leuconostoc mesenteroides BLAC cultures were produced using classical free-cell fermentation technology and immobilized cell technology (ICT). The ICT process consisted of entrapping the culture into alginate or pectin beads, adding them to a growth medium, and incubating for 14 h to allow growth of the culture inside the beads. Cell populations, survival to freeze-drying and specific acidifying activity (SAA) following inoculation in vegetable juices were examined. In free cell fermentations, 1.3 × 1010 cells/mL were obtained while 1.6 to 2.0 × 1011 cells/g were found in beads. The total cell counts recovered per fermentor were similar in free-cell and ICT systems. In the ICT process, the free-cell level was only of 1% or less. No difference in population yields were noted between alginate and pectin gels. Survival to freeze-drying was between 65 and 80% and was not significantly affected by the prior fermentation process nor the alginate or pectin matrix. A methodology was developed to ascertain the free-cell content of the freeze-dried ICT cultures, and data showed that they contained 97.5% of gel-entrapped cells. Freshly prepared free-cell suspensions had four times higher SAA than comparative free-cell freeze-dried cultures. The dried ICT cultures had lower SAA than free-cell equivalents, but there was no significant effect of the ICT matrix (alginate or pectin) on SAA. The powders of the ICT culture were ground and sieved to obtain particles ranging from 38 μm to 1000 μm in diameter. The smaller the particle, the higher was its SAA. Fermentation of vegetable juices or pastes were carried out with the free and ICT cultures. In the ICT fermentation, the free-cell content of the inoculum represented 2.5% of the total population, but this increased to 88% after the 22 h incubation in vegetable juice. Data are discussed in relationship with potential benefits of ICT cultures in vegetable fermentations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".