Omega-3 enriched eggs: The influence of dietary α-linolenic fatty acid source on egg production and composition
Bibliographic record
Abstract
A study was conducted to assess the effect of replacing chia with flaxseed as a source of α-linolenic acid in laying hen feed. Five diets, identified as T0 through T4, containing 0-0, 7-3, 9-5, 11.5-2.5 and 14-0% whole chia seed and whole flaxseed, respectively, were fed to 240 White Shaver laying hens, at 60 wk of age. No difference (P > 0.05) in egg production, egg weight, yolk weight and albumen weight were found among treatments. Total ω-3 acid percentage was higher (P < 0.05) in the yolks from the hens fed the α-linolenic acid-enriched diets, than in those fed the control diet. Of the three treatments that had any combination of chia and flaxseed comprising 14% of the diet, T2 yielded a lower (P < 0.05) ω-3 content in the yolk, than did T3 and T4. A taste panel found no difference (P > 0.05) in flavor or off-flavor among treatments; however, panel preferences were lower for eggs produced by hens fed the highest level of flaxseed (T2). This study showed no advantages to replacing chia with flaxseed to produce ω-3 enriched eggs. Greater availability of flaxseed, however, might make it more attractive in some markets. Key words: Eggs, chia, flaxseed, omega-3 fatty acid
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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 | 0.000 |
| 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".