Feeding vitamins, antioxidants and cod liver oil enriched formulated feed influences the growth, survival and fatty acid composition of <i>Macrobrachium rosenbergii</i> (de Man, 1879) postlarvae
Bibliographic record
Abstract
Effects of feeding Macrobrachium rosenbergii postlarvae with a formulated feed enriched with four different media viz. vitamin E (feed F1), vitamin D (feed F2), cod liver oil (feed F3), astaxanthin (feed F4) on growth, survival and fatty acid composition of the postlarvae were investigated in comparison to the unenriched formulated feed (FC, control feed) using five groups of postlarvae with three replicates for each feed.Results showed that the postlarvae fed with cod liver oil enriched feed (F3) had the highest weight gain (225.72±9.05%), highest specific growth rate (2.95±0.07%), and highest survival (77.14±4.28%) as well as low food conversion ratio (0.87±0.03) compared to the postlarvae fed with the other feeds. The postlarvae fed with astaxanthin (F4) or vitamin E (F1) enriched feed also showed relatively higher percentage weight gain, higher specific growth rate and lower food conversion ratios but the larval survival was better in the group fed with astaxanthin enriched feed. Postlarvae fed with cod liver oil enriched feed contained the highest levels of eicosapentaenoic acid (EPA) (4.45±0.44%) in the body where as the highest levels of docosahexaenoic acid (DHA) and total highly unsaturated fatty acids (HUFA) in the body were observed in the postlarvae fed with astaxanthin enriched feed (F4) and vitamin E enriched feed (F1). The results indicate that the nutritional quality of formulated feed can be increased through enrichment, especially with astaxanthin or cod liver oil which could improve the growth and survival of postlarvae of M. rosenbergii and the postlarval quality in relation to the fatty acid profile in the body. DOI: 10.4038/sljas.v14i0.2200Sri Lanka J. Aquat. Sci. 14 (2009): 59-74
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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) | 0.001 | 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".