Effects of Dietary Inclusion of Seaweed, Heat Stress and Genetic Strain on Performance, Plasma Biochemical and Hematological Parameters in Laying Hens
Bibliographic record
Abstract
This study was planned to investigate the effects of seaweed supplementation, genetic strain, heat stress and their interactions on laying hen performances, blood chemistry and hematology. In a short-term trial, laying hens of the two genetic lines Lohman LSL-Lite (White) and Lohman Brown-Lite (Brown) were supplemented with Chondrus crispus (CC) at 3% for 21 days, while a control group was not. In a long-term trial, the same two strains were assigned to control (0%), 3% red seaweed Chondrus crispus (CC) or 0.5% brown seaweed Ascophyllum nodosum (AN)-supplemented diets for 41 weeks, concluding with a four-week control or heat-stress period. The White hens displayed higher egg production and a lower feed/egg ratio. The short-term inclusion of CC significantly reduced the feed intake, weight gain and feed/egg ratio. The long-term seaweed intake affected the plasma albumin and gamma-glutamyl transferase (GGT) (p < 0.05), and there were significant strain-heat stress interactions; heat stress in the Brown birds was associated with reduced protein, globulin and glucose and increased cholesterol and GGT levels and higher heterophil-to-lymphocyte (H/L) ratios (p < 0.05) in response to heat stress (p < 0.05). In conclusion, a long-term seaweed supplementation affected the plasma protein and enzyme profiles, yet had little effect on hen leukocyte counts and the overall performance.
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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) | 0.001 | 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".