Optimisation of Growth of Raphidocelis subcapitata Immobilised for Biofuel Production: Influence of Alginate and CaCl2 Concentrations on Growth
Bibliographic record
Abstract
The growth of the green microalga Raphidocelis subcapitata in sodium alginate beads was studied. The beads were generated by the extrusion technique, which was followed by gelling in a Ca2+ solution. The alginate concentrations studied were 1%, 1.5% and 2% (w/v), while the concentrations of CaCl2 were 0.2%, 0.5% and 1% (w/v). The growth monitoring of the cells in the beads was performed by dissolving the gel in a sodium phosphate buffer and reading the optical density at 685 nm using a spectrophotometer. The results clearly showed that alginate and divalent Ca2+ ions do not contribute directly to the growth of microalgae but play a decisive role in preserving the integrity of the beads and protecting them from shrinkage. Furthermore, they have an important role in the transfer of nutrients, light and CO2 in the beads. The highest growth (3.92 × 106 ± 0.39 cells/bead) was obtained with the concentrations of alginate being 1.5% and CaCl2 being 0.2%. However, the beads began to shrink and this resulted in the cells being released into the culture medium after the 8th day. Of all the combinations studied, the combination of 2% alginate and 1% CaCl2 was the best because it ensured the stability of the beads during the 10 days of culture and resulted in a low concentration of free cells detected in the culture medium. These concentrations were determined as the optimal conditions for the immobilization of microalgae and will be used in the following work.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".