Modified biochar amended phytostabilization of selenium in contaminated soil under cold climate in northern Québec (Canada)
Bibliographic record
Abstract
The strategy of combining phytostabilization and biochar amendment was suggested as an alternative for selenium (Se) bioremediation in contaminated soils. The current study aimed to test the performance of activated biochar as an amendment for the phytostabilization of selenium in soil by Phleum sp. For this, Phleum sp. had been grown in Se-contaminated soil mixed with activated biochar which was produced by the pyrolysis of wood residues and the activation of biochar at 900°C in presence of superheated steam. Results showed that Se immobilization in soil was enhanced by the addition of activated biochar owing to its improved physicochemical structure compared to non-modified biochar. In parallel, activated biochar contributed to the improvement of soil fertility by increasing pH and organic matter. The bioaccumulation factor (BAF) of Se in absence of activated biochar and biochar amendment was 8.7, which suggests the suitability of Phleum plant species as Se secondary accumulator species to be further used in a Nordic context. Se plant uptake was positively correlated to Se level in soil, pH, redox potential, organic matter, cations, metals (Al, Cr, Fe, Mn, Co, Pb) and anions (Cl, SO 4 ). However, Se bioavailability for plant uptake was reduced due to Se immobilization in soil by activated biochar which reduced the translocation of Se from soil to plant and then its bioaccumulation in plant. Thus, combination of activated biochar and Phleum Se-accumulator plant was validated as an efficient solution for Se remediation in contaminated soil which could be applied at large scale under cold climates.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".