Effects of Octacosanol Extracted from Rice Bran on the Laying Performance, Egg Quality and Blood Metabolites of Laying Hens
Bibliographic record
Abstract
A 42-d study with 384 Hy-line brown laying hens was conducted to assess the effects of dietary octacosanol supplementation on laying performance, egg quality and blood metabolites of laying hens. Hens were randomly allocated into 4 dietary groups of 8 cages each, which were fed basal diet supplemented with 0 (Control), 9 (OCT9), 18 (OCT18), and 27 (OCT27) mg/kg diet of octacosanol isolated from rice bran, respectively. The experiment was conducted in an environmental controlled house and hens were fed twice daily for ad libitum intake. Laying performance was determined over the 42-d period, and egg quality as well as blood metabolites were estimated on d 21 and d 42. Diets in OCT18 and OCT27 increased (p<0.05) laying rate, egg weight, egg mass, egg albumen height, Haugh unit and eggshell strength on d 42, but decreased (p<0.05) feed conversion rate and levels of total cholesterol, triglyceride and low density lipoprotein cholesterol in the serum as compared to those of Control. Feed intake, yolk color, yolk diameter, eggshell thickness and high density lipoprotein cholesterol were similar (p>0.05) among treatments. Results demonstrate that supplementing 18 to 27 mg/kg diet of rice bran octacosanol can improve laying rate and egg quality and reduce blood lipid of laying hens.
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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".