Isolation and identification of a T-2 toxin-producing Fusarium poae strain and studies on its culture conditions
Bibliographic record
Abstract
[Objective] To select and identify an endophytic fungus isolated from wheat head collected from a Kashin-Beck disease area of Qinghai province,and study its influences of culture conditions on the production of T-2 toxin.[Methods] Primary selection of toxin-producing strain was using embryonic bud inhibition and yeast fungistatic tests on all isolated strains.Strain re-selection was carried out by TLC and HPLC assay to check the extract of the strain.Strain 5-5m-1 was identified based on its colonial and microscopic morphological characters and ITS sequencing.The optimization of culture condition for T-2 toxin production was investigated by single factor experiments and orthogonal design method.[Results] The morphological characters of the strain 5-5m-1 were similar to that of Fusarium poae.The ITS sequencing showed that the sequence of strain 5-5m-1 had high similarity to that of the strain F.poae.The optimal culture conditions of the strain to produce T-2 toxin were corn solid medium,alternative illumination with 25 °C during the day and 15 °C at night.[Conclusion] Strain 5-5m-1 was identified as Fusarium poae.Culture conditions have great influence on its ability to produce T-2 toxin.The results will provide important references for further studies on the mechanism of T-2 toxin production and the measure to prevent mycotoxin contamination.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".