Tarragon (<i>Artemisia dracunculus</i>) Essential Oil at Optimized Dietary Levels Prompted Growth, Immunity, and Resistance to Enteric Red‐Mouth Disease in the Rainbow Trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
Fingerlings of the rainbow trout, Oncorhynchus mykiss (n = 300, 10.63 ± 0.6 g), were fed tarragon (Artemisia dracunculus) essential oil (TGO) for 2 months to examine its effects on growth properties, immunity, and resistance to Yersinia ruckeri infection. The treatments were control or TG1, TG2 (fed 0.5% TGO), TG3 (1% TGO), and TG4 (2% TGO). According to the results, an improvement was observed in growth parameters in all TGO‐treated groups compared to the control (P < 0.05). The digestive enzyme activities (protease and lipase) were significantly elevated in response to dietary TGO (P < 0.05). The immune system of the fish was enhanced by TGO, as it stimulated the immune parameters in serum (lysozyme, myeloperoxidase (MPO), alternative complement (ACH50), Ig) and mucus (lysozyme, protease, ACH50, Ig) (P < 0.05). The treatments, TG3 and TG4, showed more immune performance in response to TGO (P < 0.05). The fish in TG2 treatment had a higher levels of serum total protein than other groups (P < 0.05). The concentration of triglycerides (TRIG) and cholesterol (CHOL) in serum significantly decreased (P < 0.05) in response to TGO, as the lowest levels were observed in the treatment, TG3. The antioxidant enzymes (superoxide dismutase (SOD) and catalase (CAT)) of serum elevated in TGO‐treated fish, with the maximum values for the TG4 group (P < 0.05). TGO reduced (P < 0.05) alanine aminotransferase (ALT) and alkaline phosphatase (ALP) levels in serum. After bacterial challenge, the TGO‐treated fish showed lower mortality compared to the control, where the lowest mortality was observed in TG4 (P < 0.05). In conclusion, TGO improved growth, immunity, and survival after bacterial challenge in the rainbow trout, with more performance in fish fed 1%–2% TGO.
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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 | 0.000 | 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".