Rumen-protected methionine for dairy and beef cattle: current perspectives on methionine role, supplementation strategies, metabolism, health, and performance
Bibliographic record
Abstract
Protein utilization by ruminants has unique characteristics due to the fractioning into ruminal degraded and undegraded portions. Because of these peculiarities, the amino acid (AA) profile that reaches the intestines for absorption differs from the known dietary protein sources. Among the essential AAs, methionine (Met) is the most limiting nutrient, especially in dairy cattle diets. Moreover, Met contributes to several biological processes, such as protein synthesis, epigenetic regulation, nuclear function, cellular redox potential, phospholipid homeostasis, among others. Hence, given these factors, there are considerable efforts to investigate the efficacy of this AA by employing technologies aimed at shielding it from rumen degradation in both dairy and beef cattle. In light of this, it is valuable to consolidate the findings available in the scientific literature regarding the performance, reproduction, fetal development, and health-related outcomes of rumen-protected methionine (RPM). This approach aims to offer a thorough and unbiased perspective concerning the potential outcomes achievable through the application of this technology. For instance, such insights can serve as a robust foundation for decision-making regarding the implementation of this technology in practical operations. Therefore, this literature review aims to: (1) explore Met metabolism and its importance as a precursor of methyl donors; (2) provide information on the existing methods for protecting Met in the rumen; and (3) compile research findings concerning the potential impacts of Met supplementation on milk production and composition, body weight gain, reproductive outcomes, immune function, and fetal development in both dairy and beef cattle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".