Phytoextraction of Heavy Metals by Various Vegetable Crops Cultivated on Different Textured Soils Irrigated with City Wastewater
Why this work is in the frame
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Bibliographic record
Abstract
A challenging task in urban or suburban agriculture is the sustainability of soil health when utilizing city wastewater, or its dilutes, for growing crops. A two-year field experiment was conducted to evaluate the comparative vegetable transfer factors (VTF) for four effluent-irrigated vegetable crops (brinjal, spinach, cauliflower, and lettuce) grown on six study sites (1 acre each), equally divided into two soil textures (sandy loam and clay loam). Comparisons of the VTF factors showed spinach was a significant and the best phytoextractant, having the highest heavy metal values (Zn = 20.2, Cu = 12.3, Fe = 17.1, Mn = 30.3, Cd = 6.1, Cr = 7.6, Ni = 9.2, and Pb = 6.9), followed by cauliflower and brinjal, while lettuce extracted the lowest heavy metal contents (VTF: lettuce: Zn = 8.9, Cu = 4.2, Fe = 9.6, Mn = 6.6, Cd = 4.7, Cr = 2.9, Ni = 5.5, and Pb = 2.5) in response to the main (site and vegetable) or interactive (site * vegetable) effects. We suggest that, while vegetables irrigated with sewage water may extract toxic heavy metals and remediate soil, seriously hazardous/toxic contents in the vegetables may be a significant source of soil and environmental pollution.
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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 | 0.000 | 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 it