Development of a selective myclobutanil agar (MBA) medium for the isolation of <i>Fusarium</i> species from asparagus fields
Bibliographic record
Abstract
A new selective myclobutanil agar medium for the detection of Fusarium, species is proposed. Ten media formulations based on various selective agents (pentachloronitrobenzene (PCNB), Rose Bengal, malachite green, sodium hypochlorite, captan, benomyl, chlorotalonil, myclobutanil, thiram, and cupric sulfate) were compared. First, mycelium growth and colony appearance of Alternaria alternata, Aspergillus flavus, Cladosporium cladosporioides, Epicoccum nigrum, Fusarium sp., Fuisarium solani, Fusarium moniliforme, Fusarium oxysporum f.sp. dianthi, Penicillium sp., and Trichoderma viride isolates were compared. Second, the ability of the different media to isolate and enumerate fusaria from asparagus fields was evaluated. The myclobutanil-based medium showed the highest selectivity to Fusarium spp. growth but required a slightly longer incubation time (>5 d) than peptone-pentachloronitrobenzene-based agar (PPA) (< 5 d). PPA allowed a faster fusaria growth but also permited the growth of other moulds. The other media were less selective and did not allow to isolate fusaria or to differenciate them from other growing fungi.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".