Heavy Metal contamination in chicken feeding at wastewater irrigated agricultural farms in peri urban areas of Multan City, Pakistan: A Health Risk Assessment
Bibliographic record
Abstract
The nourishing of domestic chicken is source of livelihood in suburb of all cities and is favorite food of public in urban areas in Pakistan .The study assessed the heavy metal pollution in chicken’s liver and total target health quotient (TTHQ). From six agricultural farms (4 under wastewater, 1 tube-well and 1 under canal water irrigation), liver samples (n=30) were analyzed for cadmium (Cd), chromium (Cr), copper (Cu), manganese (Mn), nickel (Ni) and lead (Pb) by inductivity coupled plasma-optical emission spectrometry (ICP- OES), Perkin Elmer USA. Samples of wastewater/water used for irrigation and soils from respective sites were analyzed for same metals for source apportionment. The mean contents of Cd, Cr, Cu, Mn and Ni in livers were within safe limits prescribed by World Health Organization (WHO) across all sites and that of of Pb exceeded safe limit at wastewater irrigated sites. TTHQ ranged 0.01 to 0.16 < 1.0 across all farms showing non carcinogenic health risk to humans. TTHQ values were 5 to 12 times higher at wastewater irrigated farms than that at tube-well and canal water farms. Multivariate statistical analysis indicated that wastewater used for irrigation and contaminated soils are common sources contributing the heavy metal contamination in livers. Tube-well and canal water irrigated fields are better places for nourishing the domestic chicken than wastewater irrigated fields to safeguard the public health
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".