Omega‐3 long‐chain polyunsaturated fatty acids in Atlantic salmon: Functions, requirements, sources, de novo biosynthesis and selective breeding strategies
Bibliographic record
Abstract
Abstract The aquaculture industry is a substantial user of wild‐sourced fish oil to supply omega‐3 (n‐3) long‐chain polyunsaturated fatty acids (LC‐PUFAs) in fish diets, which are required by many economically important farmed fish species, particularly Atlantic salmon ( Salmo salar L.). Fish oil is commonly replaced with plant‐based oils as more environmentally and economically sustainable substitutes due to concerns regarding over‐fishing of wild stocks and increasing demand. One potential strategy to meet the physiological requirement for n‐3 LC‐PUFA is to improve n‐3 LC‐PUFA biosynthesis in salmon through selective breeding and strain enhancement. The objective of this review is to discuss strategies to supply sufficient levels of n‐3 LC‐PUFA to Atlantic salmon through the diet and de novo biosynthesis through selective breeding and salmon strain enhancement. This review provides an overview on the functions of n‐3 LC‐PUFA in Atlantic salmon, dietary requirements, source and supply of n‐3 LC‐PUFA in aquaculture feeds, and biosynthesis of n‐3 LC‐PUFA in fish. Several relevant studies have revealed the genetic influences on n‐3 LC‐PUFA biosynthesis and storage in Atlantic salmon. The results of the present review show that selective breeding of high n‐3 PUFA‐producing Atlantic salmon could be an effective strategy to improve the amount of EPA and DHA stored in tissues and reduce reliance on dietary sources of n‐3 LC‐PUFA such as fish oil.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".