Insights into garlic (Allium Sativum)’s nutrigenomics-associated fly-repellent potency in cattle
Bibliographic record
Abstract
Despite effective control of flies using synthetic pesticides, fly resistance and environmental contamination have led to the inadequacy of this strategy. The use of integrated pest management approaches has since been advocated in contemporary research to sustainably control fly populations. Recent studies have found garlic (Allium Sativum) and its derivative bioactive compounds to possess insect-repellent attributes among other key health and production enhancing properties. This highlights the potential of garlic as a botanical pesticide to control flies in cattle. Moreover, the ability of cattle to naturally repel flies is influenced by animal genetic predisposition. The dietary garlic supplementation and gene interaction in disease resistance could also be an influential factor in repelling flies in cattle. Transcriptomics has emerged as a valuable tool in animal breeding and genetics which allows identification of trait-associated genes and understanding of complex interactions between dietary nutrients and animal genome expression. This paper explores the nutrigenomic effects of garlic supplementation on cattle and its contribution towards fly repellence efficacy in cattle. It was concluded that garlic supplementation in cattle diets could offer a sustainable approach to managing fly infestations in cattle farming. These findings underscore the importance of further research to validate these assertions and optimise the use of garlic to control flies in cattle under different production systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".