Effect of live algae used as green water on survival, growth, behaviour, ontogeny and bacterial profile of lobster larvae (<i>Homarus americanus</i>Milne Edwards)
Bibliographic record
Abstract
Green water is a technique commonly used in aquaculture, that consists of adding live algae in the water culture and its benefits have been shown for several species. Several hypotheses exist to explain the benefits of green water: increase in nutritional value; action as a probiotic; increase in contrast to reveal preys for larvae; or increase in predator behaviour of larvae. Green water produced with a mix of strains Isochrysis galbana and Chaetoceros muelleri (50:50, cells:cells) applied in four different ways was tested. The survival and the growth of American lobster (Homarus americanus) between stage I and stage IV post-larvae were not affected by the addition of live algae. The lipid classes were not affected by the addition of algae and limited variation was observed in the fatty acids and bacterial profiles. Furthermore, the green water techniques had a limited effect on the behaviour of post-larvae stage IV lobster at releasing. Behaviour was mostly affected by the age of post-larvae. The bacteria Lewinella sp., Leucothrix sp. and Thiothrix sp. appeared to represent a common and core component of Stage IV lobster post-larvae microflora. The results show that the algae do not increase either nutritional value or feed intake of the lobster larvae. Probiotic effect may be more important when larvae are raised in a close system where potential bacterial pathogens could have more chances to colonize the culture. Also, the dark green colour of the larval tank used in this study may have mimicked the effect of green water in the control group. Biochemical results suggest that dietary supplementation with phospholipids and DHA is needed in a lobster hatchery using frozen Artemia and our open formula Dry mix.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".