Evaluation of pesticide residues and heavy metals in common food tubers from Nigeria
Bibliographic record
Abstract
Pesticide residues and heavy metal content of cassava, yam, cocoyam, potato, water yam and carrot were evaluated by gas chromatography–mass spectrometry and atomic absorption spectroscopy. The detected pesticide residues in the samples were 2,4-dichlorophenoxyacetic acid, glyphosate, hexachlorobenzene (HCB), dichlorobiphenyl, aldrin, endosulfan, profenofos, g-chlordane, carbofuran, biphenyl, heptachlor, lindane and t-Nonachlor. The concentration of HCB ranged between 0.0799 ± 0.06 mg/kg and 0.1596 ± 0.00 mg/kg, which was greater than the permitted maximum limit of 0.5 mg/kg established by the US Environmental Protection Agency. The concentration of aldrin and profenofos detected was lower than the predetermined maximum allowed limits. Endosulfan concentrations in cocoyam (0.2500 mg/kg) and potato (0.3265 mg/kg) were higher than the limits allowed by the Canadian Department of Industrial Research. The heavy metals detected in these samples include cobalt, nickel, lead, manganese, chromium, arsenic and mercury in at least one of the samples evaluated. There was not much difference between the concentration of cobalt in yam (0.036 mg/kg) and the maximum allowed concentration (0.043 mg/kg). Lead was detected in potatoes and carrots but was below detectable concentration in cassava, yam, cocoyam and water yam. Similarly, cocoyam was found to have a significant mercury content (0.658 mg/kg), but mercury content was below detectable concentrations in cassava, yam and water yam.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".