Pathogenicity of Pythium species causing seed rot and damping-off in soybean under controlled conditions
Bibliographic record
Abstract
Pythium species cause seed rot (SR) and damping-off (DO) in soybean worldwide. In a previous study, a number of Pythium species were isolated from infected soybean plants across Ontario and Quebec, but their comparative pathogenicities to soybean were not examined. In the present research, 24 isolates from eight Pythium spp. were evaluated for their pathogenicity in causing soybean SR and DO in a greenhouse environment. The effect of temperature on the ability of these isolates to cause SR was also studied. There were significant differences among the eight Pythium spp. for both SR and DO. When tested at 25°C, Pythium ultimum was the most pathogenic species, causing 97.0% SR and 46.4% DO, on average, in the two soybean cultivars used. Pythium aphanidermatum was the second most pathogenic species, resulting in 88.5% SR and 41.8% DO. The two species resulted in significantly greater SR and DO than the other six species tested and were considered highly pathogenic. Of the two cultivars used in these trials, ‘Beechwood’ was significantly more susceptible than ‘Nattawa’ to both SR and DO. Temperature had a significant influence on SR caused by Pythium spp. At all four temperatures tested (4°C, 12°C, 20°C and 28°C), P. ultimum was highly pathogenic, while P. arrenomanes, P. coloratum and P. dissotocum were the least pathogenic. The interactions between temperature and Pythium spp. were more pronounced for P. aphanidermatum, which showed an increased percentage of SR with an increase in temperature, and for P. irregulare, P. macrosporum and P. sylvaticum, which showed a decreased percentage of SR with an increase in temperature.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".