Utilization of kudzu as a lead phytoremediator and the impact of lead on selected physiological responses
Bibliographic record
Abstract
Schwarzauer-Rockett, K., Al-Hamdani, S. H., Rayburn, J. R. and Mwebi, N. O. 2013. Utilization of kudzu as a lead phytoremediator and the impact of lead on selected physiological responses. Can. J. Plant Sci. 93: 951–959. This study was carried out to evaluate kudzu [Pueraria montana var. lobata (Willd.)] in lead phytoremediation. The impact of lead (PbNO3) concentrations of 100 and 200 mg L−1on plant growth, photosynthetic pigments, photosynthesis, and stomatal conductance were evaluated. Additionally, concentrations of phenolic compounds and anthocyanin were determined. The lead was dissolved in 0.142 g L−1ethylenediaminetetraacetic acid (EDTA) and an EDTA control treatment was added to evaluate the impact of EDTA on the above selected plant responses. Root accumulation of lead was significantly higher than in the shoot. Kudzu growth in response to the presence of lead and EDTA in the Hoagland's solution was similar to that of the EDTA control, except for plants growing at 200 mg L−1, which showed significantly lower root dry weight. Total phenolic compounds increased with the presence of EDTA and lead in the Hoagland's solution. Photosynthetic rate, stomatal conductance, chlorophyll a and chlorophyll b, carotenoids, and anthocyanin were not different (P≤0.05) among the treatments, with the exception that carotenoids were significantly higher in plants growing in the presence of EDTA without lead compared with 200 mg L−1lead concentration. Kudzu accumulated most of the lead in the root and therefore can be considered as a rhizofiltrator. As kudzu was able to accumulate 1.02% (wt/wt) of lead it can be considered a hyper-accumulator.
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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".