A review on the potential use of eubiotics in non-chicken poultry species
Bibliographic record
Abstract
As the demand for poultry products increases, safe nutritional measures should be implemented to ensure successful diversification of the poultry industry with non-chicken poultry (NCP) species such as quail, turkey, ostrich, waterfowls, and guinea fowls. Thus, this review focuses on the current and future utility of eubiotics in NCP species by outlining the challenges and potential benefits that are associated with their utilization. Eubiotics are a group of feed additives, including probiotics, prebiotics, synbiotics, organic acids, and essential oils, that are safe and exhibit antimicrobial and immunomodulatory activities, prudent in an era where multi-drug antimicrobial resistance poses a grave threat to human health. Using eubiotics, separately or in combination, in NCP diets could enhance gut health, immune responses, growth performance, and product quality. However, their mechanisms of action are not fully understood, and their synergistic effects are not clearly outlined especially for NCP species. Moreover, inconsistent results have been reported, possibly due to various sources, application methods, production systems, bird types, and variations in rearing sites (macro- and micro-climatic conditions). We postulate that their extensive adoption in diets of NCP species could, in the future, deliver safe, efficient, and sustainable poultry production systems. We conclude that correct application methods, optimal dosages, and understanding of their synergistic actions could ensure alternative poultry systems that would contribute significantly to global food safety and nutrition security.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".