Worldwide aflatoxin contamination of agricultural products and foods: From occurrence to control
Bibliographic record
Abstract
Aflatoxins represent a global public health and economic concern as they are responsible for significant adverse health and economic issues affecting consumers and farmers worldwide. Produced by fungal species from the Aspergillus genus, aflatoxins are a toxic, mutagenic, and carcinogenic group of fungal metabolites that routinely contaminate food and agricultural products. Climate and diet are essential factors in the aflatoxin contamination of food and subsequent human exposure process. Countri es with warmer climates and staple foods that are aflatoxin-susceptible shoulder a substantial portion of the global aflatoxins burden. Enactment of regulations, prevention of pre- and postharvest contamination, decontamination, and detoxification have been used to prevent human dietary exposure to aflatoxin. Exploiting their chemical and structural properties, means are devised to detect and quantify aflatoxin presence in foods. Herein, recent developments in several important aspects impacting aflatoxin contamination of the food supply, including: fungal producers of the toxin, occurrence in food, worldwide regulations, detection methods, preventive strategies, and removal and degradation methods were reviewed and presented. In conclusion, aflatoxin continues to be a major food safety problem, especially in developing countries where regulatory limits do not exist or are not adequately enforced. Finally, knowledge gaps and current challenges in each discussed aspect were identified, and new solutions were proposed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".