Dietary inclusion of mushroom (<i>Flammulina velutipes</i>) stem waste on growth performance and immune responses in growing layer hens
Bibliographic record
Abstract
BACKGROUND: Medicinal mushrooms contain biologically active substances that can be used as an immune-modulating agent in poultry. The present study aimed to investigate the effects of Flammulina velutipes mushroom waste (FVW) on performance, immune response and serum immunity in growing layer hens. RESULTS: No significant differences (P > 0.05) were observed with respect to average daily feed intake, body weight gain and feed conversion ratio among the experimental groups during the entire study period (1-70 days). Antibody titers against Newcastle disease and infectious bronchitis were higher (P < 0.05) in the FVW fed groups than in the control and antibiotic groups. On day 28, serum immunoglobulin (Ig)A and IgG were higher (P < 0.05) in the 6% FVW group than in the control and antibiotic fed groups. On day 70, serum IgA was higher (P < 0.05) in FVW fed groups than in the control group; IgG was higher (P < 0.05) in the FVW groups than in the control and antibiotic groups. However, IgM was higher (P < 0.05) in both the 4% and 6% FVW groups than in the control and antibiotic groups for both experimental periods. Serum cytokine interleukin (IL)-2 and tumor necrosis factor-α concentrations were significantly higher (P < 0.05) in both the 4% and 6% FVW grousp than in the control and antibiotic groups; IL-4 was significantly higher (P < 0.05) in the FVW groups than in the control group; and IL-6 was significantly higher (P < 0.05) in the 6% FVW group than in the control and antibiotic groups. CONCLUSION: FVW at the 6% level can be used as a potential phytogenic feed stuff in growing layer hen rations with respect to improving the immune response without affecting normal weight gain. © 2018 Society of Chemical Industry.
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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".