Prevalence of Aflatoxins in Selected Dry Fruits, Impact of Storage Conditions on Contamination Levels and Associated Health Risks on Pakistani Consumers
Bibliographic record
Abstract
Dry fruits and nuts are nutritious foods with several health-promoting properties. However, they are prone to contamination with aflatoxins at all stages of production and storage. The present study aimed to determine the natural occurrence of aflatoxin B1 (AFB1), aflatoxin B2 (AFB2), aflatoxin G1 (AFG1), aflatoxin G2 (AFG2), and total aflatoxins (AFT) in dates, pistachios, and walnuts collected from four districts of South Punjab (Pakistan), and to assess the associated health risks as estimated by dietary exposure and the Margin of Exposure (MoE) determinations. The contents of AFB1 and AFT in these food products were monitored during storage under three different conditions (open-air, hermetically closed jars, and refrigeration at 4 °C) to determine the most efficient conditions in preventing aflatoxin accumulation. HPLC-fluorescence analysis of 60 samples of these products for aflatoxin contamination showed that 52 (86.7%) samples were contaminated at different levels, with a maximum of 24.2 ng/g. The overall (all samples) mean concentrations of AFB1, AFB2, AFG1, AFG2, and AFT were 3.39 ± 2.96, 1.39 ± 1.68, 1.63 ± 1.48. 1.12 ± 1.23, and 7.54 ± 6.68, respectively. The Estimated Daily Intake (EDI) and MoE of aflatoxins through the consumption of the products ranged from 0.06 ng/kg bw/day to 2.0 ng/kg bw/day and from 84.84 to 2857.13, respectively, indicating that consumers are at high health risk. Significant differences were recorded between aflatoxin levels in the samples stored under different storage conditions, with storage under refrigeration (4 °C) being the most effective in controlling aflatoxin accumulation, although storage in closed jars was also efficient and offers a more flexible alternative to retailers. The findings of the study urge official authorities of Pakistan to implement appropriate regulatory and control measures and surveillance program to alleviate the potential public health risks associated with the consumption of dry fruits and nuts in the scope of their increased consumption.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".