Methods and Evaluation of Soybean Genotypes for Resistance to <i>Colletotrichum truncatum</i>
Bibliographic record
Abstract
Anthracnose of soybean (Glycine max) occurs throughout the soybean production areas of the world. There is little information on evaluating inoculation techniques or evaluating soybean germplasm for resistance. The objectives of this study were to develop a reliable inoculation technique for evaluating soybean for resistance to Colletotrichum truncatum and to evaluate soybean genotypes for resistance. Inoculated plants incubated in a dew chamber for 48 or 72 h had higher (P = 0.05) area under disease progress curve (AUDPC) values than when incubated for 24 h. Three experiments evaluated soybean genotypes for resistance to C. truncatum. In the first experiment using 15 soybean genotypes, 'Mandarin' had lower (P = 0.05) AUDPC values than all the other genotypes except for 'Mandarin 507', 'Mandarin (Ottawa)', and 'Boone'. In the second experiment using 28 soybean genotypes, Mandarin 507 had lower (P = 0.05) AUDPC values compared with all other soybean genotypes except 'Early White Eyebrow', 'Mandarin Yowa', Boone, and 'Manchuria'. In the third experiment, Mandarin 507 had lower (P = 0.05) AUDPC values compared with 23 other soybean genotypes except 'Spry', Mandarin, and 'Iroquois'. Plants of Mandarin 507 and 'Williams 82' were inoculated at the vegetative and reproductive growth stages; Mandarin 507 had lower (P = 0.05) AUDPC values compared with Williams 82 for both growth stages evaluated, and Mandarin 507 had less (P = 0.05) pod area covered by lesions compared with the pods of Williams 82. This study provided a descriptive method to inoculate soybean plants with C. truncatum and identified soybean genotypes with resistance to anthracnose.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".