Bioaccumulation of triclosan and triclocarban in plants grown in soils amended with municipal dewatered biosolids
Bibliographic record
Abstract
Biosolids generally contain the microbiocidal agents triclosan (TCS) and triclocarban (TCC) that are persistent during wastewater treatment and sorp to organic material. The present study investigated the concentration of TCS in tissues of radish, carrot, and soybean grown in potted soil amended with biosolids. Highest mean concentrations of TCS in radish, carrot, and soybean root tissue midway through the life cycle were 24.8 ng/g, 49.8 ng/g, and 48.1 ng/g dry weight, respectively; by the conclusion of the test, however, concentrations had declined to 2.1 ng/g, 5.5 ng/g, and 8.4 ng/g dry weight, respectively. Highest mean concentrations of TCS in radish and carrot shoot tissue were 33.7 and 18.3 ng/g dry weight at days 19 and 45, respectively, but had declined to 13.7 ng/g and 5.5 ng/g dry weight at days 34 and 69, respectively. Concentration of TCS in all samples of soybean seeds was below method detection limit (i.e., 2.8 ng/g dry wt). The present study also examined the concentration of TCS and TCC in edible portions of green pepper, carrot, cucumber, tomato, radish, and lettuce plants grown in a field amended with biosolids. Triclosan was detected only in cucumber and radish up to 5.2 ng/g dry weight. Triclocarban was detected in carrot, green pepper, tomato, and cucumber up to 5.7 ng/g dry weight. On the basis of the present study and other studies, we estimate that vegetable consumption represents less than 0.5% of the acceptable daily intake of TCS and TCC. These results demonstrate that, if best management practices for land application of biosolids in Ontario are followed, the concentration of TCS and TCC in edible portions of plants represents a negligible exposure pathway to humans.
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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) | 0.000 | 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".