Baseline and non-baseline sensitivity of<i>Magnaporthe oryzae</i>isolates from perennial ryegrass to azoxystrobin in the northeastern United States
Bibliographic record
Abstract
Gray leaf spot, caused by Magnaporthe oryzae, is chiefly managed by the application of fungicides. Among several systemic fungicides, azoxystrobin has been effectively used to control the disease; however, the development of resistance in M. oryzae to azoxystrobin has been reported in some regions of the United States. The sensitivity level to azoxystrobin of pathogen isolates from perennial ryegrass turf has not been documented in a comprehensive manner in the northeastern United States. This survey was conducted to evaluate the sensitivity to azoxystrobin of 135 isolates of M. oryzae collected between 1995 and 2004 from golf courses primarily in the northeastern United States. Media components, incubation time, and temperature were optimized for a modified in vitro spore germination assay to determine the sensitivity of the isolates. The EC50 value of 111 baseline isolates ranged from 0.001 to 0.083 µg/mL (mean 0.039 µg/mL) and 21 non-baseline isolates from Pennsylvania (PA) ranged from 0.007 to 0.066 µg/mL (mean 0.029 µg/mL). No significant difference in sensitivity (P ≤ 0.05) was observed between baseline and PA non-baseline isolates. DNA sequence analysis of the cytochrome b gene (CYTB) showed that no mutation had occurred among PA non-baseline isolates. The study established azoxystrobin baseline sensitivity for M. oryzae in the northeastern United States and indicated that because of limited use of QoI (quinone outside inhibitor) fungicides and the practice of using fungicide rotations and mixtures for gray leaf spot control, a shift in sensitivity to azoxystrobin has not yet occurred in the PA non-baseline isolates.
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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".