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Record W7073553549

Virulence characterization of international collections of the wheat stripe rust pathogen, Puccinia striiformis f. sp. tritici

2013· article· en· W7073553549 on OpenAlexaboutno aff

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsStripe rustVirulencePuccinia striiformisRust (programming language)Race (biology)Pathogenicity
DOInot available

Abstract

fetched live from OpenAlex

Wheat stripe rust (yellow rust [Yr]), caused by Puccinia striiformis f. sp.
\ntritici, is an economically important disease of wheat worldwide. Virulence
\ninformation on P. striiformis f. sp. tritici populations is important to
\nimplement effective disease control with resistant cultivars. In total, 235 P.
\nstriiformis f. sp. tritici isolates from Algeria, Australia, Canada, Chile,
\nChina, Hungary, Kenya, Nepal, Pakistan, Russia, Spain, Turkey, and Uzbekistan
\nwere tested on 20 single Yr-gene lines and the 20 wheat genotypes
\nthat are used to differentiate P. striiformis f. sp. tritici races in the United
\nStates. The 235 isolates were identified as 129 virulence patterns on the
\nsingle-gene lines and 169 virulence patterns on the U.S. differentials.
\nVirulences to YrA, Yr2, Yr6, Yr7, Yr8, Yr9, Yr17, Yr25, YrUkn, Yr28, Yr31,
\nYrExp2, Lemhi (Yr21), Paha (YrPa1, YrPa2, YrPa3), Druchamp (Yr3a,
\nYrD, YrDru), Produra (YrPr1, YrPr2), Stephens (Yr3a, YrS, YrSte), Lee
\n(Yr7, Yr22, Yr23), Fielder (Yr6, Yr20), Tyee (YrTye), Tres (YrTr1, YrTr2),
\nExpress (YrExp1, YrExp2), Clement (Yr9, YrCle), and Compair (Yr8, Yr19)
\nwere detected in all countries. At least 80% of the isolates were virulent on
\nYrA, Yr2, Yr6, Yr7, Yr8, Yr17, YrUkn, Yr31, YrExp2, Yr21, Stephens (Yr3a,
\nYrS, YrSte), Lee (Yr7, Yr22, Yr23), and Fielder (Yr6, Yr20). Virulences to Yr1, Yr9, Yr25, Yr27, Yr28, Heines VII (Yr2, YrHVII), Paha (YrPa1, YrPa2,
\nYrPa3), Druchamp (Yr3a, YrD, YrDru), Produra (YrPr1, YrPr2), Yamhill
\n(Yr2, Yr4a, YrYam), Tyee (YrTye), Tres (YrTr1, YrTr2), Hyak (Yr17, YrTye),
\nExpress (YrExp1, YrExp2), Clement (Yr9, YrCle), and Compair (Yr8, Yr19)
\nwere moderately frequent (>20 to <80%). Virulence to Yr10, Yr24, Yr32,
\nYrSP, and Moro (Yr10, YrMor) was low (≤20%). Virulence to Moro was
\nabsent in Algeria, Australia, Canada, Kenya, Russia, Spain, Turkey, and
\nChina, but 5% of the Chinese isolates were virulent to Yr10. None of the
\nisolates from Algeria, Canada, China, Kenya, Russia, and Spain was
\nvirulent to Yr24; none of the isolates from Algeria, Australia, Canada,
\nNepal, Russia, and Spain was virulent to Yr32; none of the isolates from Australia,
\nCanada, Chile, Hungary, Kenya, Kenya, Nepal, Pakistan, Russia, and
\nSpain was virulent to YrSP; and none of the isolates from any country was
\nvirulent to Yr5 and Yr15. Although the frequencies of virulence factors
\nwere different, most of the P. striiformis f. sp. tritici isolates from these countries
\nshared common virulence factors. The virulences and their frequencies
\nand distributions should be useful in breeding stripe-rust-resistant wheat
\ncultivars and understanding the pathogen migration and evolution.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.004
Open science0.0040.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.202
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2013
Admission routes1
Has abstractyes

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