Effect of fungicide application technology on seed yield in field pea under variable Mycosphaerella blight pressure
Bibliographic record
Abstract
Mycosphaerella blight, caused by Peyronellaea pinodes (Berk. & A. Bloxam) Aveskamp, Gruyter & Verkley (syn. Mycosphaerella pinodes (Berk. et Blox.) Vesterg.), is a destructive foliar pathogen of field pea that is managed, in large part, through application of foliar fungicide at flowering. The fungicides are usually applied into dense crop canopies, so reaching the lower areas of the canopy where the pathogen is initially most active is a challenge. Field trials were conducted across the Canadian prairies from 2008 to 2011 to assess the efficacy of various nozzle numbers and orientations, droplet sizes, and water volumes for the management of Mycosphaerella blight to increase yield in field pea. Pea plants were assessed for disease severity during flowering and seed yield was measured. In 10 of the 13 trials, double-nozzle configurations provided a 15% reduction in disease severity and up to a 60% increase in yield. In contrast, droplet size and angle of application had no effect on field pea yield. Water volume trials using up to 400 L ha−1 improved fungicide efficacy relative to control treatments, however, volumes above 400 L ha−1 resulted in high-disease severity and lower yield, likely as a result of fungicide run-off due to saturation of the leaf surface. When deciding on effective sprayer techniques for fungicide application, disease pressure, environmental conditions and cultivar characteristics are important to consider.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".