Guanidinoacetic acid supplementation: A narrative review of its metabolism and effects in swine and poultry
Bibliographic record
Abstract
Guanidinoacetic acid (GAA) is an amino acid derivative and precursor for creatine which plays a significant role in energy metabolism. However, because of creatine’s instability during the manufacturing process and cost, GAA has been explored as an effective alternative to creatine supplements. GAA has been tested as a potential feed additive to enhance energy utilization and growth performance in the poultry and swine industries. Moreover, GAA has been combined with methionine to improve growth outcomes and may also act as an arginine-sparing agent in birds. The safety of the GAA supplements for animals, consumers, and the environment and its efficacy in numerous livestock species have been proven. This narrative review discusses the scientific evidence regarding the metabolism and effects of GAA supplementation in swine and poultry, identifying the knowledge gaps and future directions for further research on GAA supplementation. A systematic search of the literature identified published research findings related to GAA supplementation in swine and poultry and their findings are summarized in this narrative review to confirm the impacts of GAA supplementation on growth performance, reproductive performance, and meat quality in swine and poultry. Amongst its many demonstrated benefits, GAA is effective at improving body creatine concentration, growth parameters, feed conversion ratio, and performance of animals. Although GAA exerts many non-creatine roles, including the stimulation of insulin secretion, neuromodulation, and vasodilation, further research may require in-depth elaboration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".