Seed Treatment with Phosphonate (AG3) Suppresses Pythium Damping-off of Cucumber Seedlings
Bibliographic record
Abstract
A formulation of phosphonate (AG3) was tested as a seed treatment for the control of Pythium damping-off of cucumber (Cucumis sativus L.) plants under controlled environment and field conditions. Cucumber seed were treated by soaking for 10 min in phosphonate solution. They were then planted into peat-based mix or sandy-loam soil mixed with Pythium aphanidermatum or P. ultimum inoculum or into muck soil naturally infested with P. irregulare, P. ultimum, and other Pythium spp. Under growth-room conditions, phosphonate seed treatment provided more than 80% control of damping-off in all infested substrates tested. Effective disease control was obtained even when treated seed were stored for 5 weeks and up to 18 months prior to planting. In microplots containing naturally infested muck soil, phosphonate seed treatment decreased the percentage of diseased cucumber plants and increased total fresh weights compared with untreated seed and phosphonate post-planting drench. In field-plot tests 6 weeks after planting treated seed in Pythium-infested muck soil, cucumber stands were 63% compared with 18% in the control, which had no phosphonate exposure, and 53% in the post-planting drench. Tests for potential phytotoxicity in the greenhouse showed that radish and bok choy germination was reduced by phosphonate treatment but corn, cucumber, soybean, sugar beet, tomato, and wheat were not affected. Phosphonate seed treatment is a cost-effective way of protecting cucumber plants from Pythium damping-off.
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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".