Analysis of cocoa products for ochratoxin A and aflatoxins
Bibliographic record
Abstract
Eighty-five samples of cocoa products sampled in Canada were analysed for ochratoxin A (OTA) and aflatoxins in 2011-2012. Inclusion of the aflatoxins in this survey required additional method development. Chocolate was extracted with methanol-water plus NaCl, while for cocoa two successive extractions with methanol and methanol-water were made. Extracts were cleaned on an AflaOchra immunoaffinity column (IAC). Determination was by reversed phase high performance liquid chromatography (HPLC). Detection of the aflatoxins was with a post-column photochemical reactor and of OTA by fluorescence detection. Mean limits of quantification (LOQ) of chocolate and cocoa powders were 0.16 ng/g (OTA) and 0.07 ng/g (aflatoxin B1), respectively. Survey results showed that the incidences of OTA above the LOQ in natural cocoa were 15/15 (mean 1.17 ng/g), 20/21 for alkalized cocoa (mean 1.06 ng/g), 9/9 for baking chocolate (mean 0.49 ng/g), 20/20 for dark chocolate (mean 0.39 ng/g), 7/10 for milk chocolate (mean 0.19 ng/g), 5/5 for cocoa liquor (mean 0.43 ng/g), and 0/5 for cocoa butter. These results confirm our previous work with OTA. In the same samples, incidences of aflatoxin B1 above the LOQ were 14/15 for natural cocoa (mean 0.86 ng/g), 20/21 for alkalized cocoa (mean 0.37 ng/g), 7/9 for baking chocolate (mean 0.22 ng/g), 16/20 for dark chocolate (mean 0.19 ng/g), 7/10 for milk chocolate (mean 0.09 ng/g), 4/5 for cocoa liquor (mean 0.43 ng/g), and 0/5 for cocoa butter. Both aflatoxins and OTA were confirmed by HPLC-MS/MS when OTA or aflatoxin levels found were above 2 ng/g in cocoa.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".