Evaluation of <i>Claviceps purpurea</i> isolates on wheat reveals complex virulence and host susceptibility relationships
Bibliographic record
Abstract
Ergot of cereals, caused by Claviceps purpurea, results in yield loss and downgrading of infested grain because of toxic alkaloids in the sclerotia. Resistant wheat genotypes are known, but their effectiveness against different C. purpurea isolates over geographic regions has not been studied. The objective of this study was to examine the pathogenic variability among isolates of C. purpurea on wheat lines differing in resistance. Under controlled environmental conditions, 41 single spore isolates of C. purpurea were obtained from Canadian and UK collections and inoculated onto a set of wheat genotypes composed of durum wheat lines ‘Melita’, ‘Kyle’ and 9260B-173A, and hexaploid spring wheat lines ‘Cadillac’, ‘Vista’, ‘Kenya Farmer’, ‘Lee’ and HY630. Honeydew production and weight of sclerotia produced per spike were assessed. There were significant differences among the wheat genotypes for overall reactions to the pathogen isolates, and among pathogen isolates for geographic origin and host origin. Twenty virulence phenotypes were identified using the honeydew production data, and 23 virulence phenotypes identified using the sclerotial weight data from the 41 isolates. The existence of different virulence phenotypes indicates that variability in virulence exists in populations of C. purpurea, and knowledge of virulence phenotypes is necessary to effectively breed for resistant commercial lines.
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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) | 0.000 | 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".