Performance and Fatty Acid Composition of Adipose Tissue, Breast and Thigh in Broilers Fed Flaxseed: A Review
Bibliographic record
Abstract
Interest on the enrichment of poultry meat with n-3 fatty acids has increased given its important role in human health. Flaxseed is the main sources of n-3 fatty acids, and contains between 45 to 71% of total fatty acids of the oil as α-linolenic acid. This paper reviews the plausibility of n-3 enrichment. Its focus is on the processing of flaxseed and begins by summarizing the benefits of supplementation on broiler performance. The literature on altering the FA deposition in different tissues is then reviewed, and the factors that affect the incorporation of n-3 PUFA into edible tissues of poultry are investigated. Flaxseed supplementation caused a reduction in the abdominal fat pad, and the main fatty acid deposited in the tissue is LNA. The use of fold-change analysis allowed interpreting and determining the variation of results within experiments that do not report data in similar units of measure. The fold change analysis identified three categories of desaturation response to feeding flaxseed to broilers, resulting in different values for EPA and DHA in both breast and thigh tissues: high, medium and low fold-changes. The use of flaxseed oil, whole or ground flaxseed 14 to 21 day before slaughter is recommended to poultry producers as feeding strategies to optimize n-3 enrichment, without compromising animal performance. Enriched DHA deposition could be accomplished feeding whole flaxseed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".