Evidence of heavy metal in soil, irrigation water and vegetable cultivated in peri‑urban area of Yaoundé-Cameroon
Bibliographic record
Abstract
Environmental pollution from anthropogenic activities is of global concern. The levels of heavy metal contamination were evaluated in the soil and irrigation water, and their transferability to the cultivated plant was appraised in the locality of Nkolbisson, Yaoundé-Cameroun. The levels of Zn, Cu, Cd, Ni, Pb, Cr, and Mn contamination were evaluated to determine the current status, possible source(s), bio-accumulation in food crops, the suitability of the water for irrigation purposes, and hence the probable health risk. The analysis of soils, waters, and crops (Corchorus olitorius and Lactuca sativa) samples has shown high levels of heavy metal contamination. Cd, Ni, and Cr concentrations in water samples (0.98, 2.230, and 2.635 mg/l) were above the threshold set by FAO for irrigation water. In agricultural soils, only the level of Mn (1013.090 mg/kg) contained in soil samples was above the European Union (EU) and the Canadian Council of Ministers for Environment (CCME) thresholds of toxicity. Except for Pb (0.361; 0.394 and 0.043; 0.041 mg/kg DM) and Mn (113.457; 123.341 and 173.667; 180.321 mg/kg DM), the concentration of heavy metals analysed in plant samples were above the standard values in the edible parts. Market gardening in this city presents risks due to the presence of heavy metals in soils and irrigation waters. Thus, market gardeners must be taking appropriate measures to avoid crop contamination. The bioconcentration and translocation factors have shown that Lactuca sativa can be used for phytoextraction of Zn, Cu and Cd whereas Corchorus olitorius can be used for phytomobilization of the same elements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".