Daily feeding frequency affects feed intake and body weight management of growing layers
Bibliographic record
Abstract
The objective of this study was to investigate the effect of feeding behavior on feed intake and body weight in growing layers and the underlying mechanisms, thereby providing a scientific foundation for optimal feeding practices in growing layers' management. A total of 144 Hy-line brown growing layers of 10 wk old and similar body weight, were divided into 3 treatment groups with different feeding frequency and equal cumulative daily feeding amount: the once-a-day feeding group (F1) was fed at 9:00 am every day, with feeding amount of 150 g/layer; the twice-a-day feeding group (F2) were fed at 9:00 am and 13:00 pm every day, with each feeding amount of 75 g/layer; the 4 times-a-day feeding group (F4) were fed at 9:00 am, 11:00 am, 13:00 pm, and 15:00 pm every day, with each feeding amount of 37.5 g/layer. Pre-experiment lasted for 1 wk and formal experiment lasted for 8 wk. The results indicated that the daily feed intake and body weight were decreased (P < 0.05) while feed conversion ratio was not affected (P > 0.05) as daily feeding times increased. The glandular stomach proportion was significantly increased in twice-a-day feeding group, while liver proportion and ileum length were significantly increased in 4 times-feeding group (P < 0.05). Additionally, 4 times-feeding daily resulted in a significant elevation of blood glucose levels, which may have suppressed feed intake (P < 0.05). In 4 times-feeding group, the plasma triglyceride levels increased as feeding times, accompanied by a notable up-regulation in the mRNA level of appetite-suppressing gene, hypothalamic pro-opiomelanocortin (POMC) and glandular stomach ghrelin. This modulation effectively suppressed the subsequent feed intake and body weight. Therefore, 4 times feeding daily is recommended in growing layers' management, because it reduced the feed cost without affecting the feed conversion efficiency.
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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 | 0.001 |
| 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".