First Report of Resistance to Benomyl Fungicide in <i>Sclerotinia sclerotiorum</i>
Bibliographic record
Abstract
Benomyl fungicide (Benlate) is used worldwide to control ascomycete pathogens, but resistance has developed in several pathogen populations (1). On the Canadian prairies, benomyl is used to reduce injury caused by Sclerotinia sclerotiorum (Lib.) de Bary on canola (Brassica napus, B. rapa) and alfalfa (Medicago sativa) seed crops. To determine if populations are resistant to benomyl, isolates of S. sclerotiorum collected from 15 fields (12 alfalfa and 3 canola, one isolate per field) in 2000 were grown on potato dextrose agar amended with benomyl at 0, 0.05, 0.5, 5, 50, and 500 mg/liter. Plugs of mycelium from the margin of an actively growing colony were placed in the center of a 10-cm-diameter petri dish containing 15 ml of test medium and incubated on a laboratory bench. Linear growth (mean of maximum width and right angle) of each colony (three replicates each) was measured after 5 to 6 days. The growth of isolates from 13 fields was inhibited by low concentrations of benomyl (EC50 < 8 mg/liter), but two isolates were very resistant (EC50 > 200 mg/liter). Resistant cultures were isolated from infected canola plants in the only two fields in the study in which reduced efficacy of benomyl was suspected. The distribution and importance of benomyl-resistant populations of S. sclerotiorum in the region remains to be determined. Reference: (1) T. R. Pettitt et al. Mycol. Res. 97:1172, 1993.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".