Genetic diversity of <i> <scp>P</scp> uccinia striiformis </i> from cereals in <scp>A</scp> lberta, <scp>C</scp> anada
Bibliographic record
Abstract
Stripe rust of wheat caused by P uccinia striiformis f. sp. tritici has recently become a production problem on wheat in A lberta, C anada, and stripe rust of barley caused by P . striiformis f. sp. hordei occurs regularly. A total of 261 isolates of P . striiformis were collected from wheat, barley, H ordeum jubatum and triticale plants in A lberta, C anada from 2007 to 2012, and compared to isolates from other provinces and the USA . The genetic diversity of the pathogen was assessed using 11 simple sequence repeat ( SSR ) markers and by examining a length polymorphism in the ribosomal DNA ( rDNA ) intergenic spacer 1 ( IGS 1) region. A total of 28 SSR genotypes were detected within Alberta. The 13 genotypes common on wheat ( P . striiformis f. sp. tritici ) were distinct from the 15 genotypes common on barley ( P . striiformis f. sp. hordei ). Four SSR genotypes, two within each forma specialis, represented 85% of the isolates recovered. Genotypic diversity was low, population genetic analysis indicated a clonal structure, and the genotypes were widely dispersed. In both formae speciales, the dominant genotype varied between years. The second most common P . striiformis f. sp. hordei genotype was found to be more closely related to older P . striiformis f. sp. tritici genotypes from the USA than to other P . striiformis f. sp. hordei genotypes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 teacher head, 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".