252 Efficiency of Utilization of Methionine for Weight Gain in Weaning Pigs is not Affected by Methionine Source: A Meta-Analysis
Bibliographic record
Abstract
Abstract Methionine is an essential dietary amino acid that can be supplied in different chemical forms: DL-methionine, L-methionine, and OH-methionine. It has been hypothesized that L-methionine might be used with greater efficacy for average daily gain (ADG) in weaning pigs due to their decreased enzymatic capacity to convert the other methionine forms. This study aimed to compare DL-methionine, L-methionine, and OH-methionine efficiency of utilization for ADG in weaned pigs through meta-analysis.The systematic review resulted in 2,167 papers screened for the title and abstract, with 24 papers meeting the inclusion criteria. The ADG was regressed as a function of the standardized ileal digestible (SID) methionine intake (Meti). The study was used as a random intercept, and regressions were weighted by the square root of the number of observations. Non-linear models were used to determine the Meti requirements. The average Meti requirement for pigs of 5 to 25 kg body weight (BW) was 2.09 g/d. The slopes of linear mixed-effects regression models were compared for the different methionine sources. Average initial BW was 7.99 (DL-methionine), 8.82 (L-methionine), and 7.06 kg (OH-methionine). Meti was 1.5 g/d for all sources whereas SID cysteine intake was 1.90, 2.23, and 1.93 g/d, for DL-methionine, L-methionine, and OH-methionine, respectively . Increase in Meti below the estimated requirement linearly increased ADG (ADG = 107 + 138 × Meti; P < 0.01). No difference between the slopes of methionine sources was observed, rejecting the hypothesis that L-methionine is used with greater efficiency in weaned pigs. Pigs receiving DL-methionine, L-methionine, and OH-methionine presented an estimated ADG of 319, 317, and 311 (SE = 19, 25 and, 26, respectively) g/d, respectively. In conclusion, methionine efficiency of utilization for ADG in post-weaned pigs is not affected by methionine sources.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.065 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".