Effect of dietary folic acid supplementation on egg folate content and the performance and folate status of two strains of laying hens
Bibliographic record
Abstract
Enrichment of eggs with folate is possible when dietary folic acid levels are increased. However, development of optimal strategies for the production of folate-enriched eggs requires knowledge as to differences due to strain of bird and a greater understanding of the factors limiting egg folate deposition. To this end, a study was designed to determine the response of two leghorn strains that differ in production performance. Hyline W36 and W98 hens (n = 6 per diet) received a barley-based ration containing 0, 2, 4, 8, 16, 32, 64, or 128 mg/kg of crystalline folic acid for 21 d. Response criteria included production parameters, measures of blood folate status, and egg folate content. Significant (P < 0.05) main effects of folate supplementation were observed for egg folate content and plasma folate, which increased, and homocysteine concentrations, which decreased with supplementation; performance, however, was not affected. The Hyline W98 strain had significantly (P < 0.05) higher total egg and yolk weights and feed consumption when compared with the W36. Significant (P < 0.05) ration x strain interactions were observed for egg and yolk weight, egg folate content, and plasma homocysteine. The higher egg mass producing strain, Hyline W98, benefited from increased folic acid through a reduction in plasma homocysteine concentrations, suggesting that this strain has a higher requirement for folate than the W36 strain. Overall, egg folate content is maximized when crystalline folic acid is supplemented to the diet at 2 mg/kg or higher. Higher levels of egg folate are not achieved due to the saturation of the precursor pool for egg folate deposition.
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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 | 0.001 |
| 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 | 0.001 | 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".