Partial replacement of fish oil by flaxseed oil in Atlantic halibut (Hippoglossus hippoglossus L.) diets: effects on growth, nutritional and sensory quality
Bibliographic record
Abstract
Three isonitrogenous (520 g protein kg−1 DM) and isoenergetic (25 MJ kg−1 DM) diets containing increasing levels of flaxseed oil (FxO; 0%, 40% and 70% of total added oil) at the expense of fish oil (FO) were tested for 33 weeks in groups of 61 individually PIT-tagged halibut (initial weight, 849 ± 99 g). Effects on fish growth performance, fillet nutritional and sensory quality were determined. Specific growth rate (0.2% day−1), feed conversion ratio (1.2–1.3) and nitrogen and energy retention were not affected by dietary treatments. Dietary fatty acid composition was reflected in fatty acid profiles of halibut muscle, liver and heart. Muscle of fish fed FxO diets contained higher 18:2n-6 and 18:3n-3 concentrations whereas 20:5n-3 and 22:6n-3 levels were significantly reduced. However, increasing FO replacement induced preferential retention of 22:6n-3 especially in heart, and a trend for 20:5n-3 conservation in heart and muscle was observed. FO replacement did not affect colour, texture and the characteristic fish odour and flavour of cooked fillets. By selectively retaining long-chain polyunsaturated fatty acids halibut can adapt to a lower dietary supply without adverse effects on growth, feed conversion ratio, survival, and fillet nutritional and sensory quality.
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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) | 0.001 | 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".