Fermentation technologies for the production of exopolysaccharide- synthesizing Lactobacillus rhamnosus concentrated cultures
Bibliographic record
Abstract
The exopolysaccharide (EPS)-producing cultures such as Lactobacillus rhamnosus RW-9595M present a challenge for the culture producers because the high viscosity of the fermented growth medium makes it difficult to recover the cells by centrifugation or filtration. This study examined four approaches to reduce viscosity of the medium while producing high cell densities: incubation temperature, extended incubation in the stationary growth phase, production in alginate gel beads and fed-batch fermentation technology. Automated spectrophotometry (AS) was used to study the effects of temperature, pH and lactate level on growth of the strain. In AS assays, there was no significant difference in final maximal biomass production at temperatures ranging between 34°C to 44°C, but lower yields were noted at 46°C. A pH below 6.0 and a lactate concentration higher than 4% almost completely prevented growth. Under batch fermentation conditions, the viscosity of the medium obtained at 37°C was two fold higher than for 44°C. For cultures produced at 37°C, centrifugation at 10000 g during 5 min did not allow complete recovery of cells, in contrast to cultures grown at 44°C. An extended period of incubation (5 hrs) in the stationary growth phase did not reduce the final viscosity of the growth medium. For similar biomass levels, the glucose-based fed-batch fermentation allowed a 40% reduction in viscosity of the fermented medium in comparison to traditional batch cultures. High-density cell populations (3 x 1010 CFU/g) were obtained when L. rhamnosus RW-9595M was grown in alginate beads. However, overall biomass yields in the immobilized cell bioreactor were half of those obtained in free-cell fermentations. Therefore three methods of producing concentrated EPS-producing cultures are proposed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".