Development of selective media for the isolation and enumeration of <i>Alternaria</i> species from soil and plant debris
Bibliographic record
Abstract
A new semi-selective medium, acidified weak potato-dextrose agar (AWPDA) with Mertect (active ingredient: thiabendazole), was developed for the isolation and enumeration of Alternaria species from samples of soil and plant debris. The medium was selected based on growth inhibition tests against Alternaria and several other commonly encountered saprobic fungi utilizing three antifungal agents, Botran (active ingredient: dichloran), Bayleton (active ingredient: triadimefon), and Mertect, and two basal media, acidified potato-dextrose agar (APDA) and AWPDA. Botran inhibited growth of Rhizopus stolonifer moderately, but had little effect on Cladosporium cladosporoides, Fusarium oxysporum, Penicillium chrysogenum, or Trichoderma harzianum. Bayleton inhibited growth of R. stolonifer and C. cladosporoides severely, and inhibited growth of F. oxysporum, P. chrysogenum, and T. harzianum moderately. Mertect inhibited growth of C. cladosporoides, F. oxysporum, P. chrysogenum, and T. harzianum completely, but had little or moderate effect on R. stolonifer. All three antifungal agents inhibited growth of Alternaria species slightly or moderately. The combination of Bayleton and Mertect inhibited growth of all fungi severely. A comparison of recovery rates of Alternaria from soil and plant debris samples on AWPDA with Mertect and weak potato-dextrose agar (WPDA) revealed that Alternaria spp. accounted for 63.6%-81.0% of recovered fungal isolates on AWPDA with Mertect as compared to 0.6%-2.7% of recovered isolates on WPDA. The AWPDA medium with Mertect exhibited superior selective growth of Alternaria species from samples of soil and plant debris, and will be useful in studies where the recovery and enumeration of Alternaria species is necessary.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".