Bioavailability comparison between herbal methionine and DL-methionine on growth performance and immunocompetence basis in broiler chickens
Bibliographic record
Abstract
BACKGROUND:Herbal methionine can be compared relative toDl-methionine with evaluation of bioavailability of this source ofmethionine. OBJECTIVES: An experiment was carried out todetermine the relative bioefficacy of herbal methionine (H-Met)®relative to DL-methionine (DL-Met) on performance criteria andimmunocompetence of Met sources in male broilers. Atotal of 160male broilers were fed a Met-deficient basal diet or the basal dietsupplemented with three or four concentrations of each Metsources. METHODS: Multiexponential and multilinear regressionswere used to determined bioavailability of herbal methionine (HMet)®relative to DL-Met on performance and immunocompetenceof broilers. RESULTS: Body weight gain and feed intake of thebroilers fed H-Met or DL Met improved in the experiment,regardless of Met sources, relative to those broilers that were fed thebasal diet. Immunocompetence of broilers were not significant at 28day of age (p>0.05), whereas the broilers were significantlyaffected by the additional levels of Met sources at 42 day of age.CONCLUSIONS: The bioefficacy estimates for H-Met® relative toDL-Met on a product basis were 55% for weight gain, 71% for feedintake, 78% for feed conversion ratio, 70% for dilution 1-choloro 2-3-dinitrobenzene (DNCB), 67% for sheep red blood cell (SRBC),and 68% for phytohemagglutinine (PHA-P). The relativeeffectiveness of H-Met® compared to that of DL-Met is 68% onaverage across performance criteria and all immune criteria tested.H-Met®can be supplemented as a new and natural source of Met forthe poultry 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) | 0.000 | 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".