Luehea divaricata Martius et Zuccarini Is a Sensitive Species to Aluminum, Not Presenting Phytoremediation Potential
Bibliographic record
Abstract
The aim of this work was to evaluate the effect of different concentrations of aluminum (Al) on physiological and biochemical parameters of Luehea divaricata seedlings grown in a hydroponic system under greenhouse conditions to verify the possible tolerance to Al or phytoremediation potential of this species. Seeds of Luehea divaricata were placed to germinate in commercial substrate and after 30 days the seedlings were transferred to a hydroponic system with a complete nutrient solution, pH at 4.5±0.1, with daily adjustment. After 20 days of acclimatization, homogenous plants were selected and transferred to a new nutrient solution (without phosphorus (P) and pH at 4.5±0.1) with different concentrations of Al: 0, 25, 50, 75 and 100 mg L-1, each treatment being composed of 10 replicates of one plant each. The experiment was conducted in a completely randomized design. After seven days of exposure to the treatments, plants were collected for physiological and biochemical analyzes. Aluminum promoted a significant reduction in fresh and dry weight of roots, stems and leaves; in plant height; leaf number; leaf area; and pigment content. On the other hand, Al promoted an increase in lipid peroxidation and guaiacol peroxidase enzyme activity. Therefore, the presence of Al in the growth medium, for the studied conditions, altered significantly both physiological and biochemical parameters in Luehea divaricata seedlings, presenting a sensitive behavior to this element. Due to these characteristics, the studied species does not show phytoremediation potential.
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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".