Screening US peanut mini-core accessions for resistance to Sclerotinia blight caused by <i>Sclerotinia sclerotiorum</i>
Bibliographic record
Abstract
Sclerotinia blight is a destructive disease of peanut caused by Sclerotinia sclerotiorum (Lib.) de Bary and Sclerotinia minor Jagger. Crop management practices are routinely used to control Sclerotinia blight, however, development of resistant cultivars together with crop management practices may provide a lasting solution to control the disease in peanut fields. In this study, 95 accessions of United States’ peanut mini-core collection were evaluated using detached leaflet and whole plant inoculation methods under greenhouse conditions. The area of detached leaflet infected was scored using a scale from 0 (no disease) to 4 (76%–100% leaflet area infected). Whole plants were evaluated based on disease severity index (DSI) from 0% (no disease) to 100% (entire plants infected). In the detached leaflet inoculation method, accessions PI-268586, PI-268696, PI-356004, PI-372305, and PI-429420 had the lowest average disease score of 2.7. In the whole plant inoculation method, accessions PI-200441, PI-259658, PI-319770, PI-323268, and PI-337293 had the lowest DSI from 86% to 90%. The two inoculation methods resulted in different set of accessions with the lowest disease level. These results may reflect differences in disease pressure between the two screening methods.
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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 | 0.001 | 0.001 |
| 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".