Effect of Halamphora coffeaeformis supplementation in rice bran biofloc on the growth and survival of black tiger shrimp (Penaeus monodon) postlarvae
Bibliographic record
Abstract
The shrimp aquaculture industry is hindered by disease outbreaks and low survival rates, primarily exacerbated by nutritional deficiencies and environmental stressors. This study examined the effects of Halamphora coffeaeformis -supplemented rice bran biofloc on the growth, nutritional composition, and disease resistance of black tiger shrimp ( Penaeus monodon ) postlarvae (PL). The H. coffeaeformis was added into biofloc at 1 × 10 4 cells mL −1 (BFR4) And 1× 10 5 cells mL −1 (BFR5) for eight weeks and compared with a biofloc-only system as control. Shrimp in BFR5 exhibited improved overall growth ( p = 0.03) with higher final weight (347.54 ± 74.72 mg) and daily weight gain (5.42 ± 1.19 mg day⁻1) compared to other treatments. The shrimp also had the highest lipid content (2.45 ± 0.15% dry weight; p = 0.03) and enriched fatty acid profile, with elevated eicosapentaenoic acid (3.46 ± 1.25% of total fatty acids) and docosahexaenoic acid (0.65 ± 0.37% of total fatty acids) compared to other treatments. After exposure to Vibrio parahaemolyticus , shrimp in BFR4 and BFR5 exhibited significantly higher survival rates (40.74 ± 6.05% And 39.26 ± 2.20%, respectively; p = 0.04) compared to the control (24.93 ± 4.95%) with histological analysis revealing reduced vacuolation and hepatopancreatic necrosis. These findings highlight the potential of H. coffeaeformis -enriched biofloc to improve shrimp growth, nutritional quality, and disease resistance, thereby supporting sustainable aquaculture practices.
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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 | 0.000 | 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) | 0.000 | 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".