Lead and Zinc tolerance and accumulation in metallicolous and non-metallicolous populations of <i>Peganum harmala L</i> : potential use in phytostabilization
Bibliographic record
Abstract
Peganum harmala L., commonly known as Harmal, is an aromatic and medicinal plant that grows in North Africa. P harmala is a pseudometallophyte that occur both in heavy metals contaminated and non contaminated soils . In order to identify the best adapted and suitable populations within P. harmala species, a comprehensive analysis and evaluation of the morphological, physiological, and biochemical responses to lead (Pb) and zinc (Zn) were performed in three metallicolous populations (MP) and a non-metallicolous one (NMP). In Zaida, Mibladen, and Aouli Morrocan sites, P. harmala growing soils show a low organic matter content, high Pb and Zn concentrations, and a pollution index higher than 1, indicating a significant contamination level. The effects of Pb and Zn on growth, physiological, antioxidant enzyme activities, and Pb/Zn accumulation capacity were compared between a NMP and three MP of P. harmala. Plants were grown in hydroponic culture with 100 µM of ZnSO4 or 100 µM of Pb(NO3)2 for 15 days. Our results show that Pb and Zn significantly decreased the aboveground biomass in the NMP, MP-Mibladen, and MP-Aouli compared to MP-Zaida. Pb and Zn decreased significantly the root biomass in the NMP compared to the MP. There is no significant difference in chlorophyll a and b contents between NMP and MP. Under Pb exposure, anthocyanin content is shown to be significantly higher in MP-Zaida than in other populations. In contrast, there is no difference between NMP and MP under Zn stress. Proline content as well as the catalase, peroxidase, and ascorbate peroxidase activities was significantly higher in NMP than in MP under Pb and Zn exposure. In particular, lower proline content, and antioxidant activities were observed in MP-Zaida under the Pb and Zn exposure. Pb and Zn accumulations were significantly higher in the NMP than in the MP, both in roots and aboveground parts, showing that the NMP plants accumulated highly but tolerated less compared to the MP. In the present study, the MP-Zaida accumulated less Pb and Zn in their tissues and tolerated more than the other populations, suggesting this population as a good candidate for a phytostabilization strategy.
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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".