Optimisation of Growth of Raphidocelis subcapitata Immobilised for Biofuel Production: Influence of Alginate and CaCl2 Concentrations on Growth
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it