The Biological Activity of Monarda didyma L. Essential Oil and Its Effect as a Diet Supplement in Mice and Broiler Chicken
Bibliographic record
Abstract
The use of growth-promoting antibiotics in livestock faces increasing scrutiny and opposition due to concerns about the increased occurrence of antibiotic-resistant bacteria. Alternative solutions are being sought, and plants of Lamiaceae may provide an alternative to synthetic antibiotics in animal nutrition. In this study, we extracted essential oil from Monarda didyma, a member of the Lamiaceae family. We examined the chemical composition of the essential oil and then evaluated the antibacterial, antioxidant, and anti-inflammatory activities of M. didyma essential oil and its main compounds in vitro. We then evaluated the effectiveness of M. didyma essential oil in regard to growth performance, feed efficiency, and mortality in both mice and broilers. Carvacrol (49.03%) was the dominant compound in the essential oil extracts. M. didyma essential oil demonstrated antibacterial properties against Escherichia coli (MIC = 87 µg·mL−1), Staphylococcus aureus (MIC = 47 µg·mL−1), and Clostridium perfringens (MIC = 35 µg·mL−1). Supplementing the diet of mice with essential oil at a concentration of 0.1% significantly increased body weight (+5.4%) and feed efficiency (+18.85%). In broilers, M. didyma essential oil significantly improved body weight gain (2.64%). Our results suggest that adding M. didyma essential oil to the diet of broilers offers a potential substitute for antibiotic growth promoters.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".