Quantification of the total lipids in three aquaculture microalgae using BODIPY™ 505/515 stain and flow cytometry
Bibliographic record
Abstract
Abstract Microalgae are essential food sources for fish and shellfish aquaculture and contain abundant lipids with diverse fatty acid profiles. Quantification of total lipids in microalgae could assist commercial microalgal culture operations, harvest, and management in hatchery farms. Currently, reported protocols for lipid quantification are mainly for biofuel microalgal species. This study aimed to develop effective methodologies for total lipid quantification in three aquaculture microalgae using lipid‐specific probe BODIPY™ 505/515 and flow cytometry. The objectives were to determine the effects of (1) staining concentration and time; (2) microalgal concentration; and (3) microalgal age. For Tisochrysis lutea , Chaetoceros muelleri , and Tetraselmis suecica , the optimal staining concentrations and times were 2.0 μg/mL for 0.5–30 min, 2.5 μg/mL for 5–30 min, and 1.5 μg/mL for 5–30 min, and the suitable algal concentrations were 5 × 10 5–6 , 5 × 10 4–6 , and 1 × 10 4–6 cells/mL. The total lipid accumulation in all three microalgae was contrary to the cell growth— low at the exponential growth stage and high at the stationary stage (beyond day 9). Overall, the methodologies developed in this study could be used to quantify total lipids in microalgae rapidly and accurately and require a small sample biomass (about 1 mL directly from algal culture). To produce microalgae with high total lipid accumulation, the best time to harvest may be at the stationary stage but not at the exponential growth stage. This study provided a better understanding of the lipid accumulation dynamics in the three aquaculture microalgae.
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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 | 0.001 | 0.000 |
| 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".