Low Level of Dietary Organic Trace Elements Improve the Eggshell Strength, Trace Element Utilization, and Intestinal Function in Late-Phase Laying Hens
Bibliographic record
Abstract
This study was conducted to evaluate the effects of organic trace elements (Cu, Fe, Zn, and Mn) on performance, egg quality, trace elements utilization, and intestinal function in late-phase laying hens. A total of 1,080 laying hens (Hy-line brown, 65 weeks old) were randomly assigned to four treatments with six replications of 45 layers each. The basal diet was prepared without adding exogenous trace elements. The control group was fed with a basal diet supplemented with 600 mg/kg of inorganic trace elements. The three treatment groups were fed basal diets supplemented with 300, 450, and 600 mg/kg organic trace elements (OTE300, 450, and 600), respectively. The results showed that there was no significant difference in growth performance among all treatments. However, OTE450 significantly improved the eggshell strength of laying hens ( p < 0.05), but had no significant effects on haugh unit, egg yolk weight, eggshell weight, and eggshell thickness, compared with other groups. Moreover, compared with the control group, OTE450 significantly increased the contents of copper, iron, and zinc in serum ( p < 0.05). Meanwhile, all of the trace elements had a lower deposition in the feces in organic trace elements groups ( p < 0.05). Histological analysis showed that the addition of organic trace elements could significantly improve the villus height and villus concealment ratio ( p < 0.05). In addition, the messenger RNA (mRNA) and protein expressions of divalent metal transporter 1 ( DMT1 ), zinc transporter 1 ( ZnT-1 ), and ferroportin 1 ( FPN1 ) were the highest in the OTE450 group. In conclusion, OTE450 could improve egg quality, intestinal function, and trace element utilization efficiency. Thus, this study provides a theoretical basis for the application of low levels of organic trace elements in 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".