Risk Assessment of Heavy Metals and Pesticides in Honey From Sicily (Italy)
Bibliographic record
Abstract
Honey, obtained by the honeybee (Apis mellifera) from nectar plants, with different composition according to floral sources, regional and climatic conditions, is widely consumed for its nutritional value and various properties. It could be considered a bio-indicator of environmental pollution to assess the presence of metals, naturally present in soil, and pesticides, widely used in agricultural practices. Actually no specific legislation on honey’s metals and pesticides content exists. The aim of this study was to evaluate the presence of toxic metals (Pb and Cd) and insecticides (organochlorines, organophosphates, pyrethrins and pyrethroids) in carob, chestnut and eucalyptus honey samples from Sicily and carried out a risk assessment to dietary intake of these contaminants. The results obtained showed low residual levels of Pb (0.1709 ± 0.078 mg kg-1) and Cd (0.0153 ± 0.004 mg kg-1) while the concentrations of all pesticides analyzed were under the LOD (< 0.01 mg kg-1). To explain the source of metals contamination in honey, the analytical investigation was conducted also in carob (Ceratonia siliqua L.), chestnut (Castanea sativa) and eucalyptus (Eucalyptus globules Labill.) powders, from which nectar honey is produced, confirming the presence of Pb and Cd concentrations with statistically significant differences (P < 0.05 and P < 0.01) in all three types. The risk assessment, evaluated through the Target Hazard Quotient (THQ) and confirmed also by EFSA Provisional Tolerable Weekly Intake (PTWI), showed that metals daily intake through Sicilian honey consumption is not likely to cause deleterious effect for consumers.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".