Effects of Light Exposure and Nitrogen Source on the Production of Oil from Freshwater and Marine Water Microalgae
Bibliographic record
Abstract
The biomass yield and oil content of Chlorella saccharophila (freshwater) and Tetraselmis suecica (marine) microalgae were investigated using various nitrogen source (ammonium nitrate, ammonium phosphate, ammonium sulfate and combination of nutrients) at various light durations (9, 16 and 24 h).NaHCO 3 was used as the carbon source.The nitrogen concentration, temperature and pH were maintained at 70 mg/L, 22°C and 8.5, respectively.The results indicated that T. suecica produced higher cell yield compared to the C. saccharophila under all levels of parameters tested.Light exposure of 24 h produced the highest biomass yield.However, the difference in cell yields between light duration of 16 and 24 h was not significant.The combination of nutrients resulted in the highest growth for both species of microalgae.However, high growth did not necessarily result in high oil yield.The oil content was much higher for C. saccharophila than T. suecica.Varying light duration had no direct effect on oil yield.The nutrient type significantly influenced the production of oil.C. saccharophila produced the highest oil yield using ammonium phosphate while T. suecica achieved the highest oil yield using ammonium nitrate.The results indicated that high algal growth does not necessarily result in high oil yield.Both, the generation of new cells and storage of oil require energy.When the cells used energy for generation of new cells they store less oil.Thus, growing C. saccharophila using the combination of nutrients at 16 h light exposure would be the optimal growth conditions for producing oil for biodiesel production.
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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".