Effects of feeding extruded flaxseed on layer performance, total tract nutrient digestibility, and fatty acid concentrations of egg yolk, plasma and liver
Bibliographic record
Abstract
A study was conducted to determine the effects of graded levels of extruded flaxseed (EF) on laying hen performance, apparent total tract nutrient retention (ATTNR) and fatty acid concentrations of egg yolk, blood plasma and liver. Seventy-two White Leghorn layers (58 weeks old; three per cage) were randomly assigned to one of four dietary treatments: 0 (control), 3, 6 and 9% of EF-supplemented diets for 8 weeks. Results showed that feed intake, egg production, feed conversion ratio and egg weight were not affected by treatments. The ATTNR of dry matter (p = .001) and gross energy (p = .014) was lower for layers fed 9% EF than those fed the control diet, while ATTNR of organic matter (p = .001) and nitrogen-corrected apparent metabolizable energy (p = .003) were lower for birds fed 6% and 9% EF compared with those fed the control diet. Relative to the control diet, feeding EF increased (p < .001) egg yolk, plasma and liver n-3 polyunsaturated fatty acid (PUFA) concentrations. Birds fed 6% EF produced eggs > 300 mg of n-3 PUFA after two weeks of feeding, while the highest of n-3 PUFA concentrations were achieved for birds fed 9% EF. It was concluded that feeding EF up to 9% of the diet had no adverse effects on layer performance and increased n-3 PUFA concentrations in blood plasma, liver and egg yolk. However, moderate to high levels of EF (i.e., 6% and 9% of the diet) reduced nutrient ATTNR and nitrogen-corrected apparent metabolizable energy. Omega-3-enriched eggs can be achieved by feeding layers EF at 6% of the diet.
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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".