Mycotoxins in botanicals and dried fruits: A review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Botanicals are used in many countries for medicinal and general health-promoting purposes. Numerous natural occurrences of mycotoxins in botanicals and dried fruits have been reported. Aflatoxins or ochratoxin A (OTA) have been found in botanicals such as ginseng, ginger, liquorice, turmeric, and kava-kava in the USA, Spain, Argentina, India, and some other countries, while fumonisins have been found in medicinal wild plants in South Africa and in herbal tea and medicinal plants in Turkey. Zearalenone was identified in ginseng root. Dried fruits can be contaminated with aflatoxins, OTA, kojic acid, and, occasionally, with patulin or zearalenone. One main area of concern is aflatoxins in dried figs; bright greenish yellow fluorescence under ultraviolet light is associated with aflatoxin contamination. OTA in dried vine fruits (raisins, sultanas, and currants) is another concern. There are also reports of aflatoxins in raisins and OTA in dried figs, apricots, dried plums (prunes), dates, and quince. Maximum permitted levels in the European Union include 4 microg kg(-1) for total aflatoxins in dried fruit intended for direct consumption and 10 microg kg(-1) for OTA in dried vine fruit. This review discusses the occurrence of mycotoxins in botanicals and dried fruits and analytical issues such as sampling, sample preparation, and methods for analysis. Fungal contamination of these products, the influence of sorting, storage, and processing, and prevention are also considered.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it