Essential fatty acid content of eggs and performance of Layer Hens fed with different levels of full-fat flaxseed
Bibliographic record
Abstract
An examination of the earlier studies in the USA and Canada demonstrate that flax seeds are good source of omega 3 fatty acids. This experiment studies the effect of providing laying hens, with various levels of roasted and unroasted locally produced flax seeds. A key components of this experiment involved attentively observing the laying hens performance, and determining the fatty acids content of the eggs produced. Five levels of flax seeds 0, 5, 10, 15 and 20 dry weight %, roasted or unroasted, were fed to 200 pullets in 5 replicates (4 birds/cage). The results indicated that feeding 5 or 10% roasted flax seed supported good egg production. Birds fed higher levels of unroasted flax seed had the lowest feed consumption. Livability, egg weight, yolk color and specific gravity values were not significantly affected by feeding flax seeds. Feeding 15% unroasted flax seeds maintained higher omega-3 levels: that is docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA) and alpha-linolenic acid (C18:3n3) levels in egg, whereas feeding 5 or 15 weight % unroasted flax seeds resulted in the highest level of linoleic acid (C18:2n6) in the egg. Roasting the seeds did not improve the omega-3 content of the egg. Feeding flax, regardless of heat treatment, marginally increased the amount of cholesterol. The saturate palmitic acid (C16:0) was lower at 15% flax inclusion. We conclude that 10% flax seed added to feed supports good egg production. However, 15% inclusion of unroasted flax may relatively lower the egg production rate but would support an excellent profile of omega 3 fatty acids in the egg. Key words: Docosahexaenoic acid, eicosapentaenoic acid, docosapentaenoic acid, α-linolenic acid, production, flax seeds.
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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".