MétaCan
Menu
Back to cohort

Splash dispersal of <i>Leptosphaeria maculans</i> pycnidiospores and the spread of blackleg on oilseed rape

2007· article· en· W2040233290 on OpenAlexfundno aff
Renaud Travadon, Lydia Bousset, Sébastien Saint‐Jean, Hortense Brun, Ivan Sache

Bibliographic record

VenuePlant Pathology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaRégion BretagneInstitut National de la Recherche Agronomique
KeywordsLeptosphaeria maculansBiologyBiological dispersalPhomaSplashPopulationBlacklegSporeBotanyBrassicaPhysics

Abstract

fetched live from OpenAlex

The fungus Leptosphaeria maculans causes blackleg (phoma stem canker), one of the most serious diseases of oilseed rape. The role of pycnidiospores produced during asexual reproduction is poorly documented and limits the understanding of the pathogen's population dynamics. The objectives of this study were to assess rain‐splash dispersal of pycnidiospores of L. maculans from phoma leaf spots, and transmission of the disease from oilseed rape stubble carrying pycnidia. The work was conducted in still air with either a drop generator or a rain simulator. The impact of simulated incident drops on phoma leaf spots resulted in the dispersal of L. maculans pycnidiospores within splash droplets. Ninety per cent of the spores were collected within 14 cm of the source and a few were regularly observed up to 40 cm. Pycnidiospores produced on oilseed rape stubble and dispersed by simulated rain infected oilseed rape trap plants in a spatial pattern that matched the spatial dispersal of the pycnidiospores. In the field, rain‐splash dispersal of pycnidiospores could increase the pathogen population and may enhance sexual reproduction by facilitating the mating of initially spatially separated isolates of opposite mating type.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations46
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePlant PathologySame topicPlant Pathogens and Fungal DiseasesFrench-language works237,207