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Record W2833153201 · doi:10.23986/afsci.69116

Ramularia collo-cygni: a new pathogen spreading in barley fields in Estonia

2018· article· en· W2833153201 on OpenAlexfundno aff
Andres Mäe, Pille Sooväli, Lee Põllumaa

Bibliographic record

VenueAgricultural and Food Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersMinistry of Rural Affairs
KeywordsBiologyCultivarPathogenTemperate climateConidiumPoaceaeLeaf spotFungusGrowing seasonCropGenotypeAgronomyBotanyMicrobiologyGene

Abstract

fetched live from OpenAlex

Ramularia leaf spot (RLS) caused by the fungus Ramularia collo-cygni (Rcc) is affecting barley fields throughout temperate regions worldwide. The first finding of RLS in Estonia was reported on spring barley in 2012 and since then the area of RLS infection has been widening in Estonia. This work has been carried out to monitor the natural infection of Rcc in two winter barley cultivars and to follow artificial fungal infection by a PCR-based assay. Using our approach, we could detect presence of the fungal pathogen in barley leaves before the appearance of disease symptoms at early growth stages. Response of two tested cultivars to Rcc infection in the field conditions was different, showing genotype-environment interaction in the development and spreading of Rcc. In harvested grain samples at the end of growing season no Rcc infection was detected. The role of external inoculum, Rcc conidia transmitted from various grasses (Poaceae) growing next to crop fields, is discussed. These results provide further insight into the epidemiology of Rcc.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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