Evolution of the Merchantability and the Level of Ochratoxin A of Ivorian Cocoa Beans from Production Areas during the Harvest Season
Bibliographic record
Abstract
This study aims to investigate the evolution, throughout the harvest season, of merchantability criteria and Ochratoxin A (OTA) levels in cocoa beans produced in Cote d'Ivoire. To this end, 567 samples of cocoa beans, collected in 6 production areas during the 2007-2008 season, were analyzed. Merchantability and OTA levels were determined respectively according to the Ivorian Coffee and Cocoa stock exchange standards and the European Community regulation related to the analytical methods for the control of mycotoxins levels in foodstuffs (EC 401/2006). Concerning merchantability, a significant difference at 5% risk was revealed between the values of moisture, graining and grades. As regards OTA levels, the concentrations obtained ranged from 0.41 µg/kg to 1.36 µg/kg of cocoa beans with an average concentration of 0.69 µg/kg. These concentrations are all below the maximum value set at 2 µg/kg by the European Commission. Moldy and/or slaty beans are chiefly answerable for the depreciation of cocoa beans marketability. These results served to devise a map summarizing the quality of Ivorian cocoa beans. Needless to say, this map is just a representation of a situation at a given time, and should therefore contribute to take up decisions relevant to the application of good production and postharvest processing practices in the country’s quest for cocoa beans of prime quality.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".