Effects of Dietary Palm Oil on Production Performance and Serum Parameters of Laying Hens
Bibliographic record
Abstract
Background and Objective: Difficulties in satisfying the energy requirements of birds with cereals, especially maize, have led researchers to investigate the effects of different levels of dietary palm oil on the production performance of laying hens. This study was conducted to investigate the effects of dietary palm oil on the egg production performance and serum parameters of laying hens. Materials and Methods: One hundred eighty 55-week-old Isa Brown laying hens were used in a completely randomized study involving four treatments (groups). Birds in the four groups were fed for 14 weeks with diet 0, 1, 2 or 3. Diet 0 was the basal diet without palm oil, while diets 1, 2 and 3 contained 1, 2 and 3% palm oil obtained by a traditional procedure, respectively. Data were collected on feed intake, egg production, organ weight and biochemical parameters. Results: The results showed that feed intake decreased with an increase in dietary palm oil. Groups D1 (diet 1) and D2 (diet 2) showed high laying rates, low egg weights, low liver weights and a low feed conversion ratio, whereas group D3 (diet 3) had the heaviest eggs and the highest serum total protein concentration. These results might be related to the ability of palm oil to influence feed transit and to improve nutrient digestibility and absorption. Conclusion: Feed containing up to 2% palm oil had a beneficial effect on the egg production performance 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".