Trace element contents and essential oil yields from wild thyme plant (Thymus serpyllum L.) grown at different natural variable environments, Jordan
Bibliographic record
Abstract
The yields of essential oils and concentrations of some heavy metals (Fe, Cu, Ni, Cd, Co, Pb and Cr) were determined in the wild thyme plant (Thymus serpyllum L.) grown at different environments in Jordan. The samples were collected from various natural climatic regions located northern (Jeresh) and southern (Al-Karak, Al-Shouback and Aqaba) regions of Jordan. Our results showed a wide variation of essential oil contents among wild thyme plants grown at different natural variable environments, Jordan. They were 5.6 and 5.4% in Aqaba and Al-Karak regions, respectively, and 3.3 and 2.5% in Jerash and Al-Shouback, respectively. The results showed different heavy metal concentrations in all investigated samples. The highest mean levels of copper (10.40 mg/kg) were recorded at the southern regions of Al-Karak and Al-Shouback but they were within the range of permissible limit for medicinal plants. The average concentrations of lead in T. serpyllum were 1.45, 0.05, and 0.79, 1.26 mg/kg, in samples collected from Jerash, Al-Karak, Al-Shouback and Aqaba, respectively. The lead concentrations were below recommended levels by WHO. The iron content showed a great variation between the different plant samples that can be attributed to the place of growth, concentrations varying from 15.31 to 205.80 mg/kg. Cadmium concentration was below the guidelines toxic levels in samples collected from Jerash and Al-Karak, however, it was not detected in Aqaba and Al-Shouback. The essential oil and heavy metal contents in T. serpyllum are mainly affected by variable natural climatic conditions. Moreover, the current study showed that T. serpyllum species grown in Jordan are characterized by low heavy metal contents and can safely be used for pharmaceutical and edible purposes without any hazardous effect on human health.
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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) | 0.000 | 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 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".