Effects of ginger root (Zingiber officinale) on laying performance and antioxidant status of laying hens and on dietary oxidation stability
Bibliographic record
Abstract
To investigate the effects of ginger root (Zingiber officinale) on laying performance and antioxidant status of laying hens and on dietary oxidation stability, 675 Hy-Line brown laying hens at 27 wk of age were randomly allocated to 5 treatments with 5 replicates in a complete randomized design. Laying hens were fed corn-soybean meal based diets and supplemented with 0, 5, 10, 15, or 20 g of ginger powder/kg of diet for 10 wk. The ADFI, laying rate, average egg weight, egg mass, and feed conversion of each replicate were measured weekly. Blood samples from 10 laying hens and 15 egg samples/treatment were obtained on d 35 and 70 of the experiment to determine the serum or egg yolk antioxidant enzymatic activities. Three separate batches of each treatment diet were also made at the beginning of the experiment and stored at 20°C. Subsamples were taken at 10-d intervals to determine the dietary oxidation stability over a 60-d period. All laying hens had similar ADFI, laying rate, average egg weight, and feed conversion. However, laying hens supplemented with ginger powder had higher (P = 0.024) egg mass than the control group. Supplementation of ginger powder increased (P < 0.05) the serum and egg yolk antioxidant enzymatic activities of laying hens on d 35 and 70. Increasing ginger powder from 0 to 20 g/kg of diet linearly increased (P < 0.05) the peroxide value but linearly reduced (P < 0.05) the acid value of lipid extracted from stored diets for the first 30 d, but not for the second 30 d. Dietary supplementation of ginger powder improved laying performance and serum and egg yolk antioxidant status and enhanced dietary oxidation stability in a dose-dependent manner. The optimum supplementation rate of ginger powder in the diet of laying hens appeared to be between 10 and 15 g/kg of 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".