Simultaneous effect of nitrate (NO3-) concentration, carbon dioxide (CO2) supply and nitrogen limitation on biomass, lipids, carbohydrates and proteins accumulation in Nannochloropsis oculata
Bibliographic record
Abstract
Biodiesel from microalgae is a promising technology. Nutrient limitation and the addition of CO2 are two strategies to increase lipid content in microalgae. There are two different types of nitrogen limitation, progressive and abrupt limitation. In this work, the simultaneous effect of initial nitrate concentration, addition of CO2, and nitrogen limitation on biomass, lipid, protein and carbohydrates accumulation were analyzed. An experimental design was established in which initial nitrogen concentration, culture time and CO2 aeration as independent numerical variables with three levels were considered. Nitrogen limitation was taken into account as a categorical independent variable. For the experimental design, all the experiments were performed with progressive nitrogen limitation. The dependent response variables were biomass, lipid production, carbohydrates and proteins. Subsequently, comparison of both types of limitation i.e. progressive and abrupt limitation, was performed. Nitrogen limitation in a progressive mode exerted a greater effect on lipid accumulation. Culture time, nitrogen limitation and the interaction of initial nitrate concentration with nitrogen limitation had higher influences on lipids and biomass production. The highest lipid production and productivity were at 582 mgL-1 (49.7 % lipid, dry weight basis) and 41.5 mgL-1d-1, respectively; under the following conditions: 250 mgL-1 of initial nitrate concentration, CO2 supply of 4% (v/v), 12 d of culturing and 2 d in state of nitrogen starvation induced by progressive limitation. This work presents a novel way to perform simultaneous analysis of the effect of the initial concentration of nitrate, nitrogen limitation, and CO2 supply on growth and lipid production of Nannochloropsis oculata, with the aim to produce potential biofuels feedstock.
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How this classification was reachedexpand
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".