Characteristics of Resistance to <i>Puccinia coronata</i> f. sp. <i>avenae</i> in <i>Avena fatua</i>
Bibliographic record
Abstract
Crown rust, caused by Puccinia coronata f. sp. avenae, is the most widespread and harmful fungal disease of oat. The best defense against the pathogen is use of cultivars with genetic resistance, which is effective, economic, and an environmentally friendly alternative to chemical control. However, the continuous evolution of the pathogen can rapidly overcome major gene resistance, creating an urgent need to identify new sources. Wild oat accessions have already proven to be valuable donors of many resistance genes, but the weed species Avena fatua remains underexploited. Its abundance across multiple environments and the frequent occurrence of herbicide-resistant populations demonstrate its ready ability to adapt to biotic and abiotic stresses; yet, surprisingly, there are no extensive studies which describe crown rust resistance occurrence in gene bank stocks of A. fatua. In this study, 204 accessions of A. fatua maintained in the collections of the United States Department of Agriculture (USDA) and Polish National Centre for Plant Genetic Resources were evaluated at the seedling stage for crown rust reaction using host-pathogen tests with five highly diverse and virulent races of P. coronata. Of tested genotypes, 85% showed a heterogeneous infection pattern, while 61% were susceptible or moderately susceptible to all races. Of the 79 resistant A. fatua accessions, seedling resistance to at least two P. coronata isolates was recognized within 19 accessions, with 13 displaying a homogeneously resistant phenotype to one or two races. Accessions showing multiple single seedling resistance to three or four isolates were observed. Based on the seedling reaction to isolates used in the study, 18 infection profiles (IP) were determined. Using UPGMA clustering, resistant accessions were divided into six main clusters encompassing samples with similar IPs. Twelve of 18 patterns allowed us to postulate the likely presence of novel crown rust resistance genes, whose origin was predominantly from Kenya or Egypt. Future work will clarify the genetic basis of the resistances observed here, as well as confirm their potential utility in breeding resistant oat cultivars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".