Diagnosing ACCase Inhibitor– Cyhalofop-butyl Resistance in <i>Echinochloa crus-galli </i>at Various Growth Stages
Bibliographic record
Abstract
Cyhalofop-butyl-resistant Echinochloa crus-galli (L.) Beauv. has become wide-spread, so rapid diagnosis of herbicide resistance in E. crus-galli at various growth stages is crucial for timely and effective management of herbicide resistant E. crus-galli throughout the season. This study was thus conducted to diagnose cyhalofop-butyl resistance in E. crus-galli at various stages of growth using rapid diagnostic test methods. Growth pouch, trimmed seedling, and stem node tests were conducted on E. crus-galli at seed germination, juvenile, and heading stages, respectively, and the diagnostic results were then compared with the conventional whole plant test. All rapid diagnostic tests discriminated resistant and susceptible biotypes on the basis of R/S ratios (the ratio of GR50 values of resistant and susceptible biotypes) within 7 d after herbicide treatment. The statistical agreement in R/S ratios between the rapid diagnostic tests (R/S ratios, 2.0–4.8) and the whole plant test (R/S ratio, 3.6) demonstrated that the rapid diagnostic tests could be reliably applied to diagnose cyhalofop-butyl resistance in E. crus-galli at various stages of growth with significant time and cost savings compared with conventional whole plant tests. In addition, the presented diagnostic results coupled with discrimination of herbicide-resistant weeds in previous studies suggest that the rapid diagnostic tests are capable of detecting herbicide resistance regardless of herbicide in many different weed species.
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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 | 0.000 | 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".