Response of field pea cultivars to chlorothalonil in the control of mycosphaerella blight
Bibliographic record
Abstract
The efficacy of chlorothalonil in controlling mycosphaerella blight in field pea was evaluated from 1998 to 2000 using 10 cultivars representing different leaf types, market classes, seed sizes, plant heights, and maturities. Significant differences ( P < 0.05) were observed among cultivars in disease severity, yield, 1000-seed weight (TSW), and seed infection each year. Cultivar × fungicide treatment interactions for these parameters were not significant in any of the 3 yr. Under both chlorothalonil treated and untreated conditions, Radley was the most resistant, while Carrera and Keoma were equally the most susceptible cultivars. A higher efficacy of chlorothalonil treatments was observed in 1999 when disease severity was greater than in 1998 or 2000. On average, chlorothalonil treatments reduced disease severity significantly in 1999 and 2000, but not in 1998. Overall, the fungicide increased yield by 6.4%, and TSW by 0.9–5.1%, which were significant in 1998 and 1999, but not in 2000. Based on 2-yr assessments of seed infection by Mycosphaerella pinodes, chlorothalonil reduced seed infection by 19.2%, which was significant in 1999, but not in 2000. Chlorothalonil treatments provide a greater benefit in years when disease pressure and yield potential are high. Key words: Field pea, Pisum sativum, mycosphaerella blight, Mycosphaerella pinodes, chlorothalonil
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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 | 0.000 | 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".