Isolation of <i>Burkholderia cepacia</i> JB12 from lead- and cadmium-contaminated soil and its potential in promoting phytoremediation with tall fescue and red clover
Bibliographic record
Abstract
Phytoremediation combined with suitable microorganisms and biodegradable chelating agents can be a means of reclaiming lands contaminated by toxic heavy metals. We investigated the ability of a lead- and cadmium-resistant bacterial strain (JB12) and the biodegradable chelator ethylenediamine-N,N'-disuccinic acid (EDDS) to improve absorption of these metals from soil by tall fescue and red clover. Strain JB12 was isolated from contaminated soil samples, analysed for lead and cadmium resistance, and identified as Burkholderia cepacia. Tall fescue and red clover were grown in pots to which we added JB12, (S,S)-EDDS, combined JB12 and EDDS, or water only. Compared with untreated plants, the biomass of plants treated with JB12 was significantly increased. Concentrations of lead and cadmium in JB12-treated plants increased significantly, with few exceptions. Plants treated with EDDS responded variably, but in those treated with combined EDDS and JB12, heavy metal concentrations increased significantly in tall fescue and in the aboveground parts of red clover. We conclude that JB12 is resistant to lead and cadmium. Its application to the soil improved the net uptake of these heavy metals by experimental plants. The potential for viable phytoremediation of lead- and cadmium-polluted soils with tall fescue and red clover combined with JB12 was further enhanced by the addition of EDDS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".