Evidence of heavy metal in soil, irrigation water and vegetable cultivated in peri‑urban area of Yaoundé-Cameroon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it