Evaluation of host resistance and fungicide application as tools for the management of root rot of field pea caused by Aphanomyces euteiches
Bibliographic record
Abstract
Aphanomyces root rot (ARR) of field pea (Pisum sativum), caused by Aphanomyces euteiches, can cause severe root damage, wilting, and large yield losses under wet soil conditions. To identify ways to manage this disease, the effect of A. euteiches inoculum density on field pea was studied under greenhouse and field conditions in 2015 and 2016. Increases in inoculum density reduced seedling emergence, root nodulation, and plant vigor, and resulted in increased root rot severity in both field and greenhouse tests. Seed treatments with the fungicides Apron Advance (thiabendazole + fludioxonil + metalaxyl) + Vibrance (difenoconazole + metalaxyl-M + sedaxane), INTEGO Solo (ethaboxam), BAS 516F (boscalid + pyraclostrobin), BAS 720F (metalaxyl + pyraclostrobin + fluxapyroxad), and BAS 516F + BAS 720F (3:1) were evaluated for their efficacy against ARR. All seed treatments except Apron Advance + Vibrance reduced root rot severity under controlled conditions. BAS 516F, BAS 720F and INTEGO Solo improved plant vigor and all treatments reduced seedling blight to varying degrees under greenhouse conditions, but not in the field. A collection of 22 pea genotypes was evaluated for resistance to root rot in field plot experiments. Line 00–2067 showed the least severe root rot symptoms, whereas ‘Spring D’ showed the lowest reduction in yield. The results suggest that there may be an opportunity to combine partial host resistance and fungicidal seed treatments to adequately manage ARR of field pea.
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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".