Bioaccumulation of Fluoride in Plants and Its Microbially Assisted Remediation: A Review of Biological Processes and Technological Performance
Bibliographic record
Abstract
Fluoride is widely found in soil–water systems due to anthropogenic and geogenic activities that affect millions worldwide. Fluoride ingestion results in chronic and acute toxicity, including skeletal and dental fluorosis, neurological damage, and bone softening in humans. Therefore, this review paper summarizes biological processes for fluoride remediation, i.e., bioaccumulation in plants and microbially assisted systems. Bioremediation approaches for fluoride removal have recently gained prominence in removing fluoride ions. Plants are vulnerable to fluoride accumulation in soil, and their growth and development can be negatively affected, even with low fluoride content in the soil. The microbial bioremediation processes involve bioaccumulation, biotransformation, and biosorption. Bacterial, fungal, and algal biomass are ecologically efficient bioremediators. Most bioremediation techniques are laboratory-scale based on contaminated solutions; however, treatment of fluoride-contaminated wastewater at an industrial scale is yet to be investigated. Therefore, this review recommends the practical applicability and sustainability of microbial bioremediation of fluoride in different environments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".