Isolation and characterization of potentially ochratoxigenic fungi from Costa Rican coffee ( <i>Coffea arabica</i> L.) beans
Bibliographic record
Abstract
Coffee plants and beans are prone to fungal contamination that pose health risks to consumers by producing mycotoxins like ochratoxin A (OTA). Thus, the present study aimed to analyze the mycobiota of Costa Rican coffee beans, focusing on potentially ochratoxigenic species and their in vitro susceptibility patterns to antifungal agents. Fungal isolates were obtained from cherry, green, and roasted coffee beans from Costa Rica; they were identified by morphology, MALDI-TOF technology, and sequencing. The isolation frequency (FR) was 33.10% for all the samples analyzed, 49.51% for the cherry fruits, 37.67% for the green coffee beans, and 17.33% for the roasted beans. The cherry beans were mainly contaminated with Geotrichum klebahni (46.34% FR and 90.91% relative density (RD)), while the green and roasted coffee beans were mainly infected with Aspergillus spp. (22.00% FR and 55.23% RD and 13.83% FR and 77.57% RD, respectively). A total of 46.67% of A. westerdijkiae and 20.00% of A. ochraceus produced fluorescence in YES broth related with ochratoxin production. The isolates of the Aspergillus section Circumdati were susceptible to the azole antifungals. Costa Rican coffee beans could be contaminated with mycotoxigenic fungi during storage.
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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 | 0.000 |
| 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) | 0.000 | 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".